Linear regression in astronomy. I

Science.gov (United States)

Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh

1990-01-01

Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.

Correlation between unstimulated salivary flow, pH and streptococcus mutans, analysed with real time PCR, in caries-free and caries-active children.

Science.gov (United States)

Abbate, G M; Borghi, D; Passi, A; Levrini, L

2014-03-01

Evaluate the correlations between unstimulated salivary flow, pH and level of S. mutans, analysed through real time PCR, in caries-free and caries-active children. Thirty healthy children were divided into 2 groups: test group (DMFT/dmft ≥ 3 and at least 1 active caries lesion) and control group (DMFT/dmft=0). Un-stimulated saliva was collected, pH was measured and S. mutans and total bacterial amount were evaluated with real-time PCR analysis. Unstimulated salivary flow in the test group was significantly lower (p = 0.0269) compared to group control. The level of S. mutans was higher in the test group (p = 0.176), and an inverse correlation was recorded between total bacterial amount and un-stimulated salivary flow (p = 0.063). In the control group a positive relationship was found between total bacterial amount and S. mutans (p = 0.045) and an inverse correlation between pH and S. mutans (p = 0.088). A t-test and a linear regression analysis were performed. A higher salivary flow and an increased salivary pH seem to represent protective factors against caries in children, while high levels of S. mutans are correlated with caries active lesions. Caries risk assessment should be performed considering all parameters involved in the development of the disease.

Relationship between parental locus of control and caries experience in preschool children - cross-sectional survey.

Science.gov (United States)

Lencová, Erika; Pikhart, Hynek; Broukal, Zdenek; Tsakos, Georgios

2008-06-12

Due to high prevalence and serious impacts, childhood caries represents a public health issue. Behavioural risk factors such as locus of health control have been implicated in the development of the disease; however their association with childhood caries has not been thoroughly studied. The aim of this cross-sectional survey was to assess the relationship between parental locus of health control and caries experience and untreated caries of their preschool children in a representative sample in Czech Republic, adjusting for relevant sociodemographic characteristics. A representative sample of 285 preschool children and their parents was recruited. Study data included children's dental status recorded in nurseries and parental questionnaires with 13 attitudinal items regarding locus of control (LoC) in caries prevention. The association between parental locus of control and children's caries experience and level of untreated caries was analysed using logistic regression, adjusting for the effect of key sociodemographic variables. There was a statistically highly significant linear trend between increased parental LoC and higher probability of the children to be free from untreated caries, independent from the effect of sociodemographic variables of children and parents. A similar highly statistically significant trend, although not entirely linear, and independent from sociodemographic variables was observed with respect to the chance of the children to be free from caries experience with increasing strength of parental LoC. After full adjustment, children in the strongest parental LoC quintile were 2.81 (1.23-6.42, pcontrol of both untreated caries and caries experience in their preschool children and highlight that a more internal LoC within the family is advantageous in the prevention of dental caries.

Use of probabilistic weights to enhance linear regression myoelectric control.

Science.gov (United States)

Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

2015-12-01

Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts' law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p linear regression control. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

Linear regression crash prediction models : issues and proposed solutions.

Science.gov (United States)

2010-05-01

The paper develops a linear regression model approach that can be applied to : crash data to predict vehicle crashes. The proposed approach involves novice data aggregation : to satisfy linear regression assumptions; namely error structure normality ...

Biostatistics Series Module 6: Correlation and Linear Regression.

Science.gov (United States)

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Linear regression and the normality assumption.

Science.gov (United States)

Schmidt, Amand F; Finan, Chris

2017-12-16

Researchers often perform arbitrary outcome transformations to fulfill the normality assumption of a linear regression model. This commentary explains and illustrates that in large data settings, such transformations are often unnecessary, and worse may bias model estimates. Linear regression assumptions are illustrated using simulated data and an empirical example on the relation between time since type 2 diabetes diagnosis and glycated hemoglobin levels. Simulation results were evaluated on coverage; i.e., the number of times the 95% confidence interval included the true slope coefficient. Although outcome transformations bias point estimates, violations of the normality assumption in linear regression analyses do not. The normality assumption is necessary to unbiasedly estimate standard errors, and hence confidence intervals and P-values. However, in large sample sizes (e.g., where the number of observations per variable is >10) violations of this normality assumption often do not noticeably impact results. Contrary to this, assumptions on, the parametric model, absence of extreme observations, homoscedasticity, and independency of the errors, remain influential even in large sample size settings. Given that modern healthcare research typically includes thousands of subjects focusing on the normality assumption is often unnecessary, does not guarantee valid results, and worse may bias estimates due to the practice of outcome transformations. Copyright © 2017 Elsevier Inc. All rights reserved.

Controlling attribute effect in linear regression

KAUST Repository

Calders, Toon; Karim, Asim A.; Kamiran, Faisal; Ali, Wasif Mohammad; Zhang, Xiangliang

2013-01-01

In data mining we often have to learn from biased data, because, for instance, data comes from different batches or there was a gender or racial bias in the collection of social data. In some applications it may be necessary to explicitly control this bias in the models we learn from the data. This paper is the first to study learning linear regression models under constraints that control the biasing effect of a given attribute such as gender or batch number. We show how propensity modeling can be used for factoring out the part of the bias that can be justified by externally provided explanatory attributes. Then we analytically derive linear models that minimize squared error while controlling the bias by imposing constraints on the mean outcome or residuals of the models. Experiments with discrimination-aware crime prediction and batch effect normalization tasks show that the proposed techniques are successful in controlling attribute effects in linear regression models. © 2013 IEEE.

Controlling attribute effect in linear regression

KAUST Repository

Calders, Toon

2013-12-01

In data mining we often have to learn from biased data, because, for instance, data comes from different batches or there was a gender or racial bias in the collection of social data. In some applications it may be necessary to explicitly control this bias in the models we learn from the data. This paper is the first to study learning linear regression models under constraints that control the biasing effect of a given attribute such as gender or batch number. We show how propensity modeling can be used for factoring out the part of the bias that can be justified by externally provided explanatory attributes. Then we analytically derive linear models that minimize squared error while controlling the bias by imposing constraints on the mean outcome or residuals of the models. Experiments with discrimination-aware crime prediction and batch effect normalization tasks show that the proposed techniques are successful in controlling attribute effects in linear regression models. © 2013 IEEE.

Return-Volatility Relationship: Insights from Linear and Non-Linear Quantile Regression

NARCIS (Netherlands)

D.E. Allen (David); A.K. Singh (Abhay); R.J. Powell (Robert); M.J. McAleer (Michael); J. Taylor (James); L. Thomas (Lyn)

2013-01-01

textabstractThe purpose of this paper is to examine the asymmetric relationship between price and implied volatility and the associated extreme quantile dependence using linear and non linear quantile regression approach. Our goal in this paper is to demonstrate that the relationship between the

Determination of regression laws: Linear and nonlinear

International Nuclear Information System (INIS)

Onishchenko, A.M.

1994-01-01

A detailed mathematical determination of regression laws is presented in the article. Particular emphasis is place on determining the laws of X j on X l to account for source nuclei decay and detector errors in nuclear physics instrumentation. Both linear and nonlinear relations are presented. Linearization of 19 functions is tabulated, including graph, relation, variable substitution, obtained linear function, and remarks. 6 refs., 1 tab

Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.

Science.gov (United States)

Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

2016-04-01

The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control)-an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees. Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts' law task and was compared to performance of eight subjects using parallel dual-site control. An offline analysis also evaluated how different types of training data affected prediction accuracy of linear regression control. The two control systems demonstrated similar overall performance; however, the linear regression method demonstrated improved performance for targets requiring use of all three DOFs, whereas parallel dual-site control demonstrated improved performance for targets that required use of only one DOF. Subjects using linear regression control could more easily activate multiple DOFs simultaneously, but often experienced unintended movements when trying to isolate individual DOFs. Offline analyses also suggested that the method used to train linear regression systems may influence controllability. Linear regression myoelectric control using intramuscular EMG provided an alternative to parallel dual-site control for 3-DOF simultaneous control at the wrist and hand. The two methods demonstrated different strengths in controllability, highlighting the tradeoff between providing simultaneous control and the ability to isolate individual DOFs when desired.

Augmenting Data with Published Results in Bayesian Linear Regression

Science.gov (United States)

de Leeuw, Christiaan; Klugkist, Irene

2012-01-01

In most research, linear regression analyses are performed without taking into account published results (i.e., reported summary statistics) of similar previous studies. Although the prior density in Bayesian linear regression could accommodate such prior knowledge, formal models for doing so are absent from the literature. The goal of this…

Extending the linear model with R generalized linear, mixed effects and nonparametric regression models

CERN Document Server

Faraway, Julian J

2005-01-01

Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway''s critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author''s treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. All of the ...

Dental caries experience, rather than toothbrushing, influences the incidence of dental caries in young Japanese adults.

Science.gov (United States)

Sonoda, C; Ebisawa, M; Nakashima, H; Sakurai, Y

2017-06-01

A dose-response relationship between toothbrushing frequency and the incidence of dental caries has not been confirmed. Furthermore, no longitudinal study about this relationship has considered dental caries experience at baseline, which is an important factor influencing the frequency of future caries. To elucidate the association between the incidence of dental caries and toothbrushing frequency after adjusting for dental caries experience at baseline in a Japanese population. The 92 recruits of the Japan Maritime Self-Defense Force in Kure, Japan, in 2011 were followed up for 3 years. They underwent oral examination at the annual checkups and answered questions about toothbrushing frequency. The multiple logistic regression analysis was used to analyze the incidence of dental caries and to identify independent effects of toothbrushing frequency and dental caries experience at baseline. Furthermore, the relative importance of the incidence of dental caries was investigated among other independent variables using the partial adjusted R² score. Logistic regression analysis showed that toothbrushing frequency alone did not influence the increment in decayed, missing, and filled teeth (DMFT). However, DMFT at baseline alone was associated with the increment in DMFT (crude odds ratio, OR, 1.20, 95% confidence interval, CI, 1.08,1.33). In the fully adjusted model, only DMFT at baseline was associated with the increment in DMFT (adjusted OR 1.23, 95%CI 1.09,1.38). After three years, the incidence of dental caries in young adult Japanese males was influenced by DMFT at baseline, rather than toothbrushing frequency. Copyright© 2017 Dennis Barber Ltd.

Dental Caries Level and Sugar Consumption in 12-Year-Old Children from Poland.

Science.gov (United States)

Olczak-Kowalczyk, Dorota; Turska, Anna; Gozdowski, Dariusz; Kaczmarek, Urszula

2016-01-01

The frequent and high consumption of sugar products, particularly sucrose, is one of the causative factors of dental caries. Meta-analyses assessing the relationship between sugar intake and dental caries revealed that a restricted sugar intake to less than 10% of the daily energy intake results in substantial health benefits. Sugar consumption in Poland is 2-fold higher than recommended by the WHO. As change in dietary habits is slow, knowledge of whether a gradual reduction of sugar consumption influences beneficially the dental condition is important. Assessment of the relationship between caries experience and sugar consumption in 12-year-old children. The data obtained from the Statistical Agricultural Yearbooks of the Central Statistical Office in Poland regarding the average yearly sugar intake by a person in the years 1995-2013, and caries prevalence (frequency and DMFT) resulting from the national epidemiological studies of the 12-year-old children conducted by the Ministry of Health in those years were analyzed. The data was analyzed by linear regression. Regression function parameters and coefficients of determination were assessed for a possible link between sugar consumption and dental caries frequency and severity was expressed as DMFT value. The mean yearly sugar intake by a statistical Pole ranged from 43.6 kg (2002) to 35.3 kg (2006). Despite a slight trend to lower the sugar consumption, its mean intake in 1995 and 2013 was the same (41.9 kg). Caries frequency and DMFT decreased in 2012 compared to 1995 from 90.5% to 79.6% and from 4.3 to 3.53 kg in 2012, respectively. The increased sugar intake by 1 kg/year caused the increase of caries frequency by 1% and DMFT value by 0.2. Even a relatively low decrease in sugar consumption can exert some beneficial influence on the dental condition in adolescents, particularly upon the severity of caries.

Use of probabilistic weights to enhance linear regression myoelectric control

Science.gov (United States)

Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

2015-12-01

Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

Does dental caries affect dental development in children and adolescents?

Science.gov (United States)

Dhamo, Brunilda; Elezi, Besiana; Kragt, Lea; Wolvius, Eppo B; Ongkosuwito, Edwin M

2018-01-01

Although a link between dietary changes, caries, and dental development has been observed, the literature provides little insight about this relationship. The aim of our study was to investigate the association between dental caries and dental development in a clinical sample of Albanian children and adolescents. In total, 118 children and adolescents, born between 1995 and 2004 and aged 6–15 years, were included. Dental caries in the deciduous dentition was assessed using the Decayed, Filled Teeth (dft) index and dental caries in the permanent dentition was assessed using the Decayed, Missing, Filled Teeth (DMFT) index. Dental development during the permanent dentition was determined using the Demirjian method. Linear and ordinal regression models were applied to analyze the associations of dental caries with dental age and developmental stages of each left mandibular tooth. Dental caries in the deciduous dentition, estimated as a median dft of 2.0 (90% range, 0.0–9.1), was significantly associated with lower dental age (β = -0.21; 90% CI: -0.29, -0.12) and with delayed development of the canine, both premolars, and the second molar. Untreated dental caries (dt) was associated with lower dental age (β = -0.19; 90% CI: -0.28, -0.10). Dental caries in the permanent dentition, estimated as a median DMFT of 1.0 (90% range, 0.0–8.0), was not significantly associated with dental age (β = 0.05; 90% CI: -0.04, 0.14). However, the DMFT was associated with the advanced stages of development of both premolars and the second molar. The untreated dental caries in the deciduous dentition delays the development of permanent teeth. PMID:29659350

Korean Version of Child Perceptions Questionnaire and Dental Caries among Korean Children

Science.gov (United States)

Shin, Hye-Sun; Han, Dong-Hun; Shin, Myung-Seop; Lee, Hyun-Jin; Kim, Mi-Sun; Kim, Hyun-Duck

2015-01-01

Although dental caries has been a major oral health problem for children, the association between dental caries and oral health related quality of life has been still controversial. This study aims to evaluate the association between the Korean version of the Child Perceptions Questionnaire (K-CPQ) and dental caries among Korean children. Eight hundred one school children aged 8 to 14 years participated in this study. After the K-CPQ was validated we performed an association study. The K-CPQ was self-reported. Dental caries were evaluated by dentists using the World Health Organization Index. Correlation analyses (intraclass correlation coefficient, Cronbach’s alpha and Pearson’s correlation coefficient [r]) and linear regression models (partial r) including age, gender and type of school were applied. Untreated deciduous dental caries was associated with the K-CPQ8-10 overall score (partial r = 0.15, P caries (FT) was associated with the K-CPQ11-14 overall domain (partial r = 0.14, P = 0.002) as well as with the oral symptoms domain (partial r = 0.16, P = 0.001). This association was highlighted among public school children. Our data indicate that K-CPQ was independently associated with dental caries. The K-CPQ could be a practical tool to evaluate the subjective oral health among Korean children aged 8 to 14. PMID:25675410

Finite Algorithms for Robust Linear Regression

DEFF Research Database (Denmark)

Madsen, Kaj; Nielsen, Hans Bruun

1990-01-01

The Huber M-estimator for robust linear regression is analyzed. Newton type methods for solution of the problem are defined and analyzed, and finite convergence is proved. Numerical experiments with a large number of test problems demonstrate efficiency and indicate that this kind of approach may...

Direction of Effects in Multiple Linear Regression Models.

Science.gov (United States)

Wiedermann, Wolfgang; von Eye, Alexander

2015-01-01

Previous studies analyzed asymmetric properties of the Pearson correlation coefficient using higher than second order moments. These asymmetric properties can be used to determine the direction of dependence in a linear regression setting (i.e., establish which of two variables is more likely to be on the outcome side) within the framework of cross-sectional observational data. Extant approaches are restricted to the bivariate regression case. The present contribution extends the direction of dependence methodology to a multiple linear regression setting by analyzing distributional properties of residuals of competing multiple regression models. It is shown that, under certain conditions, the third central moments of estimated regression residuals can be used to decide upon direction of effects. In addition, three different approaches for statistical inference are discussed: a combined D'Agostino normality test, a skewness difference test, and a bootstrap difference test. Type I error and power of the procedures are assessed using Monte Carlo simulations, and an empirical example is provided for illustrative purposes. In the discussion, issues concerning the quality of psychological data, possible extensions of the proposed methods to the fourth central moment of regression residuals, and potential applications are addressed.

Simple and multiple linear regression: sample size considerations.

Science.gov (United States)

Hanley, James A

2016-11-01

The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright © 2016 Elsevier Inc. All rights reserved.

Who Will Win?: Predicting the Presidential Election Using Linear Regression

Science.gov (United States)

Lamb, John H.

2007-01-01

This article outlines a linear regression activity that engages learners, uses technology, and fosters cooperation. Students generated least-squares linear regression equations using TI-83 Plus[TM] graphing calculators, Microsoft[C] Excel, and paper-and-pencil calculations using derived normal equations to predict the 2004 presidential election.…

Quantum algorithm for linear regression

Science.gov (United States)

Wang, Guoming

2017-07-01

We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.

Comparison of Linear and Non-linear Regression Analysis to Determine Pulmonary Pressure in Hyperthyroidism.

Science.gov (United States)

Scarneciu, Camelia C; Sangeorzan, Livia; Rus, Horatiu; Scarneciu, Vlad D; Varciu, Mihai S; Andreescu, Oana; Scarneciu, Ioan

2017-01-01

This study aimed at assessing the incidence of pulmonary hypertension (PH) at newly diagnosed hyperthyroid patients and at finding a simple model showing the complex functional relation between pulmonary hypertension in hyperthyroidism and the factors causing it. The 53 hyperthyroid patients (H-group) were evaluated mainly by using an echocardiographical method and compared with 35 euthyroid (E-group) and 25 healthy people (C-group). In order to identify the factors causing pulmonary hypertension the statistical method of comparing the values of arithmetical means is used. The functional relation between the two random variables (PAPs and each of the factors determining it within our research study) can be expressed by linear or non-linear function. By applying the linear regression method described by a first-degree equation the line of regression (linear model) has been determined; by applying the non-linear regression method described by a second degree equation, a parabola-type curve of regression (non-linear or polynomial model) has been determined. We made the comparison and the validation of these two models by calculating the determination coefficient (criterion 1), the comparison of residuals (criterion 2), application of AIC criterion (criterion 3) and use of F-test (criterion 4). From the H-group, 47% have pulmonary hypertension completely reversible when obtaining euthyroidism. The factors causing pulmonary hypertension were identified: previously known- level of free thyroxin, pulmonary vascular resistance, cardiac output; new factors identified in this study- pretreatment period, age, systolic blood pressure. According to the four criteria and to the clinical judgment, we consider that the polynomial model (graphically parabola- type) is better than the linear one. The better model showing the functional relation between the pulmonary hypertension in hyperthyroidism and the factors identified in this study is given by a polynomial equation of second

A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design.

Science.gov (United States)

Meaney, Christopher; Moineddin, Rahim

2014-01-24

In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar results were observed if the

A test for the parameters of multiple linear regression models ...

African Journals Online (AJOL)

A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...

Caries risk assessment in chilean adolescents and adults and its association with caries experience

Directory of Open Access Journals (Sweden)

Rodrigo Andrés Giacaman

2013-02-01

Full Text Available Cariogram is a computer program that uses an algorithm to assess caries risk. Although the use of Cariogram has recently increased, little information is available regarding its effectiveness in adults. This study aimed to determine whether caries risk from Cariogram relates to caries experience in adults. One hundred and eighty Cariogram files were completed from patients aged ten to fifty-six years (mean: 23.28 years. Seven factors from the software were included from patient records to complete the Cariogram: caries experience, diet (content and frequency, stimulated salivary flow, hygiene index, related diseases and fluoride usage. The percentages of "chances of avoiding new lesions" (caries risk were obtained from Cariogram, and the subjects were classified into five risk groups. Results were compared for each variable with ANOVA, and a correlation between caries and Cariogram variables was calculated by Pearson's correlation coefficient. A multivariate regression model was also used. Only three patients were classified as low risk, and none were classified as very low risk. Thus, only the four upper quintiles were considered for the analysis, and the lower quintile was not considered in the study. Neither DMFT nor the number of lesions were significantly different among the Cariogram's risk categories (p > 0.05. Only diet content was significantly correlated with caries experience (p = 0.006. Caries lesions failed to correlate with any Cariogram variable (p > 0.05. Age, not sex or caries risk scores, showed a strong and positive association with DMFT (p < 0.01. Caries risk from Cariogram appears to be unrelated with caries experience or caries lesions in a high-caries adult population.

Testing hypotheses for differences between linear regression lines

Science.gov (United States)

Stanley J. Zarnoch

2009-01-01

Five hypotheses are identified for testing differences between simple linear regression lines. The distinctions between these hypotheses are based on a priori assumptions and illustrated with full and reduced models. The contrast approach is presented as an easy and complete method for testing for overall differences between the regressions and for making pairwise...

Multiple Linear Regression: A Realistic Reflector.

Science.gov (United States)

Nutt, A. T.; Batsell, R. R.

Examples of the use of Multiple Linear Regression (MLR) techniques are presented. This is done to show how MLR aids data processing and decision-making by providing the decision-maker with freedom in phrasing questions and by accurately reflecting the data on hand. A brief overview of the rationale underlying MLR is given, some basic definitions…

Identification of Influential Points in a Linear Regression Model

Directory of Open Access Journals (Sweden)

Jan Grosz

2011-03-01

Full Text Available The article deals with the detection and identification of influential points in the linear regression model. Three methods of detection of outliers and leverage points are described. These procedures can also be used for one-sample (independentdatasets. This paper briefly describes theoretical aspects of several robust methods as well. Robust statistics is a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. A simulation model of the simple linear regression is presented.

Linear regression and sensitivity analysis in nuclear reactor design

International Nuclear Information System (INIS)

Kumar, Akansha; Tsvetkov, Pavel V.; McClarren, Ryan G.

2015-01-01

Highlights: • Presented a benchmark for the applicability of linear regression to complex systems. • Applied linear regression to a nuclear reactor power system. • Performed neutronics, thermal–hydraulics, and energy conversion using Brayton’s cycle for the design of a GCFBR. • Performed detailed sensitivity analysis to a set of parameters in a nuclear reactor power system. • Modeled and developed reactor design using MCNP, regression using R, and thermal–hydraulics in Java. - Abstract: The paper presents a general strategy applicable for sensitivity analysis (SA), and uncertainity quantification analysis (UA) of parameters related to a nuclear reactor design. This work also validates the use of linear regression (LR) for predictive analysis in a nuclear reactor design. The analysis helps to determine the parameters on which a LR model can be fit for predictive analysis. For those parameters, a regression surface is created based on trial data and predictions are made using this surface. A general strategy of SA to determine and identify the influential parameters those affect the operation of the reactor is mentioned. Identification of design parameters and validation of linearity assumption for the application of LR of reactor design based on a set of tests is performed. The testing methods used to determine the behavior of the parameters can be used as a general strategy for UA, and SA of nuclear reactor models, and thermal hydraulics calculations. A design of a gas cooled fast breeder reactor (GCFBR), with thermal–hydraulics, and energy transfer has been used for the demonstration of this method. MCNP6 is used to simulate the GCFBR design, and perform the necessary criticality calculations. Java is used to build and run input samples, and to extract data from the output files of MCNP6, and R is used to perform regression analysis and other multivariate variance, and analysis of the collinearity of data

SPLINE LINEAR REGRESSION USED FOR EVALUATING FINANCIAL ASSETS 1

Directory of Open Access Journals (Sweden)

Liviu GEAMBAŞU

2010-12-01

Full Text Available One of the most important preoccupations of financial markets participants was and still is the problem of determining more precise the trend of financial assets prices. For solving this problem there were written many scientific papers and were developed many mathematical and statistical models in order to better determine the financial assets price trend. If until recently the simple linear models were largely used due to their facile utilization, the financial crises that affected the world economy starting with 2008 highlight the necessity of adapting the mathematical models to variation of economy. A simple to use model but adapted to economic life realities is the spline linear regression. This type of regression keeps the continuity of regression function, but split the studied data in intervals with homogenous characteristics. The characteristics of each interval are highlighted and also the evolution of market over all the intervals, resulting reduced standard errors. The first objective of the article is the theoretical presentation of the spline linear regression, also referring to scientific national and international papers related to this subject. The second objective is applying the theoretical model to data from the Bucharest Stock Exchange

The microcomputer scientific software series 2: general linear model--regression.

Science.gov (United States)

Harold M. Rauscher

1983-01-01

The general linear model regression (GLMR) program provides the microcomputer user with a sophisticated regression analysis capability. The output provides a regression ANOVA table, estimators of the regression model coefficients, their confidence intervals, confidence intervals around the predicted Y-values, residuals for plotting, a check for multicollinearity, a...

Using the Ridge Regression Procedures to Estimate the Multiple Linear Regression Coefficients

Science.gov (United States)

Gorgees, HazimMansoor; Mahdi, FatimahAssim

2018-05-01

This article concerns with comparing the performance of different types of ordinary ridge regression estimators that have been already proposed to estimate the regression parameters when the near exact linear relationships among the explanatory variables is presented. For this situations we employ the data obtained from tagi gas filling company during the period (2008-2010). The main result we reached is that the method based on the condition number performs better than other methods since it has smaller mean square error (MSE) than the other stated methods.

Dental caries clusters among adolescents.

Science.gov (United States)

Warren, John J; Van Buren, John M; Levy, Steven M; Marshall, Teresa A; Cavanaugh, Joseph E; Curtis, Alexandra M; Kolker, Justine L; Weber-Gasparoni, Karin

2017-12-01

There have been very few longitudinal studies of dental caries in adolescents, and little study of the caries risk factors in this age group. The purpose of this study was to describe different caries trajectories and associated risk factors among members of the Iowa Fluoride Study (IFS) cohort. The IFS recruited a birth cohort from 1992 to 1995, and has gathered dietary, fluoride and behavioural data at least twice yearly since recruitment. Examinations for dental caries were completed when participants were ages 5, 9, 13 and 17 years. For this study, only participants with decayed and filled surface (DFS) caries data at ages 9, 13 and 17 were included (N=396). The individual DFS counts at age 13 and the DFS increment from 13 to 17 were used to identify distinct caries trajectories using Ward's hierarchical clustering algorithm. A number of multinomial logistic regression models were developed to predict trajectory membership, using longitudinal dietary, fluoride and demographic/behavioural data from 9 to 17 years. Model selection was based on the akaike information criterion (AIC). Several different trajectory schemes were considered, and a three-trajectory scheme-no DFS at age 17 (n=142), low DFS (n=145) and high DFS (n=109)-was chosen to balance sample sizes and interpretability. The model selection process resulted in use of an arithmetic average for dietary variables across the period from 9 to 17 years. The multinomial logistic regression model with the best fit included the variables maternal education level, 100% juice consumption, brushing frequency and sex. Other favoured models also included water and milk consumption and home water fluoride concentration. The high caries cluster was most consistently associated with lower maternal education level, lower 100% juice consumption, lower brushing frequency and being female. The use of a clustering algorithm and use of Akaike's Information Criterion (AIC) to determine the best representation of the data

Stochastic development regression on non-linear manifolds

DEFF Research Database (Denmark)

Kühnel, Line; Sommer, Stefan Horst

2017-01-01

We introduce a regression model for data on non-linear manifolds. The model describes the relation between a set of manifold valued observations, such as shapes of anatomical objects, and Euclidean explanatory variables. The approach is based on stochastic development of Euclidean diffusion...... processes to the manifold. Defining the data distribution as the transition distribution of the mapped stochastic process, parameters of the model, the non-linear analogue of design matrix and intercept, are found via maximum likelihood. The model is intrinsically related to the geometry encoded...

Comparison between Linear and Nonlinear Regression in a Laboratory Heat Transfer Experiment

Science.gov (United States)

Gonçalves, Carine Messias; Schwaab, Marcio; Pinto, José Carlos

2013-01-01

In order to interpret laboratory experimental data, undergraduate students are used to perform linear regression through linearized versions of nonlinear models. However, the use of linearized models can lead to statistically biased parameter estimates. Even so, it is not an easy task to introduce nonlinear regression and show for the students…

Linear regression methods a ccording to objective functions

OpenAIRE

Yasemin Sisman; Sebahattin Bektas

2012-01-01

The aim of the study is to explain the parameter estimation methods and the regression analysis. The simple linear regressionmethods grouped according to the objective function are introduced. The numerical solution is achieved for the simple linear regressionmethods according to objective function of Least Squares and theLeast Absolute Value adjustment methods. The success of the appliedmethods is analyzed using their objective function values.

Estimating monotonic rates from biological data using local linear regression.

Science.gov (United States)

Olito, Colin; White, Craig R; Marshall, Dustin J; Barneche, Diego R

2017-03-01

Accessing many fundamental questions in biology begins with empirical estimation of simple monotonic rates of underlying biological processes. Across a variety of disciplines, ranging from physiology to biogeochemistry, these rates are routinely estimated from non-linear and noisy time series data using linear regression and ad hoc manual truncation of non-linearities. Here, we introduce the R package LoLinR, a flexible toolkit to implement local linear regression techniques to objectively and reproducibly estimate monotonic biological rates from non-linear time series data, and demonstrate possible applications using metabolic rate data. LoLinR provides methods to easily and reliably estimate monotonic rates from time series data in a way that is statistically robust, facilitates reproducible research and is applicable to a wide variety of research disciplines in the biological sciences. © 2017. Published by The Company of Biologists Ltd.

Boosted regression trees, multivariate adaptive regression splines and their two-step combinations with multiple linear regression or partial least squares to predict blood-brain barrier passage: a case study.

Science.gov (United States)

Deconinck, E; Zhang, M H; Petitet, F; Dubus, E; Ijjaali, I; Coomans, D; Vander Heyden, Y

2008-02-18

The use of some unconventional non-linear modeling techniques, i.e. classification and regression trees and multivariate adaptive regression splines-based methods, was explored to model the blood-brain barrier (BBB) passage of drugs and drug-like molecules. The data set contains BBB passage values for 299 structural and pharmacological diverse drugs, originating from a structured knowledge-based database. Models were built using boosted regression trees (BRT) and multivariate adaptive regression splines (MARS), as well as their respective combinations with stepwise multiple linear regression (MLR) and partial least squares (PLS) regression in two-step approaches. The best models were obtained using combinations of MARS with either stepwise MLR or PLS. It could be concluded that the use of combinations of a linear with a non-linear modeling technique results in some improved properties compared to the individual linear and non-linear models and that, when the use of such a combination is appropriate, combinations using MARS as non-linear technique should be preferred over those with BRT, due to some serious drawbacks of the BRT approaches.

Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

Science.gov (United States)

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-12-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

Dental Caries Status, Socio-Economic, Behavioral and Biological Variables among 12-Year-Old Palestinian School Children.

Science.gov (United States)

Sgan-Cohen, H D; Bajali, M; Eskander, L; Steinberg, D; Zini, A

2015-01-01

There are currently inadequate data regarding the prevalence of dental caries and its associated variables, among Palestinian children. To determine the current prevalence of dental caries and related variables, among Palestinian children in East Jerusalem. A stratified sample of 286 East Jerusalem Palestinian children was selected, employing randomly chosen sixth grade clusters from three pre-selected socio-economic school groups. Dental caries was recorded according to WHO recommendations. Salivary flow, pH, buffer capacity and microbial parameters, were recorded according to previously employed methodologies. The mean level of caries experience, by DMFT, was 1.98 ± 2.05. This level was higher than those found among Israeli children, but lower than several other Middle Eastern countries. In uni-variate analysis, significant associations were revealed between caries and school categories, which indicated lower, middle and higher socio-economic position(SEP), mothers' employment, home densities, dental visits, tooth brushing, Streptococci mutans (SM), Lactobacilli (LB), and saliva pH. According to a linear logistic regression model, children learning in lower SEP schools, with higher SM levels and more acidic saliva, had a higher chance of experiencing dental caries. These findings should be considered in the planning of services and dental health care programs for Palestinian children.

Privacy-Preserving Distributed Linear Regression on High-Dimensional Data

Directory of Open Access Journals (Sweden)

Gascón Adrià

2017-10-01

Full Text Available We propose privacy-preserving protocols for computing linear regression models, in the setting where the training dataset is vertically distributed among several parties. Our main contribution is a hybrid multi-party computation protocol that combines Yao’s garbled circuits with tailored protocols for computing inner products. Like many machine learning tasks, building a linear regression model involves solving a system of linear equations. We conduct a comprehensive evaluation and comparison of different techniques for securely performing this task, including a new Conjugate Gradient Descent (CGD algorithm. This algorithm is suitable for secure computation because it uses an efficient fixed-point representation of real numbers while maintaining accuracy and convergence rates comparable to what can be obtained with a classical solution using floating point numbers. Our technique improves on Nikolaenko et al.’s method for privacy-preserving ridge regression (S&P 2013, and can be used as a building block in other analyses. We implement a complete system and demonstrate that our approach is highly scalable, solving data analysis problems with one million records and one hundred features in less than one hour of total running time.

A comparison of random forest regression and multiple linear regression for prediction in neuroscience.

Science.gov (United States)

Smith, Paul F; Ganesh, Siva; Liu, Ping

2013-10-30

Regression is a common statistical tool for prediction in neuroscience. However, linear regression is by far the most common form of regression used, with regression trees receiving comparatively little attention. In this study, the results of conventional multiple linear regression (MLR) were compared with those of random forest regression (RFR), in the prediction of the concentrations of 9 neurochemicals in the vestibular nucleus complex and cerebellum that are part of the l-arginine biochemical pathway (agmatine, putrescine, spermidine, spermine, l-arginine, l-ornithine, l-citrulline, glutamate and γ-aminobutyric acid (GABA)). The R(2) values for the MLRs were higher than the proportion of variance explained values for the RFRs: 6/9 of them were ≥ 0.70 compared to 4/9 for RFRs. Even the variables that had the lowest R(2) values for the MLRs, e.g. ornithine (0.50) and glutamate (0.61), had much lower proportion of variance explained values for the RFRs (0.27 and 0.49, respectively). The RSE values for the MLRs were lower than those for the RFRs in all but two cases. In general, MLRs seemed to be superior to the RFRs in terms of predictive value and error. In the case of this data set, MLR appeared to be superior to RFR in terms of its explanatory value and error. This result suggests that MLR may have advantages over RFR for prediction in neuroscience with this kind of data set, but that RFR can still have good predictive value in some cases. Copyright © 2013 Elsevier B.V. All rights reserved.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

Science.gov (United States)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

Science.gov (United States)

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

Analysis of γ spectra in airborne radioactivity measurements using multiple linear regressions

International Nuclear Information System (INIS)

Bao Min; Shi Quanlin; Zhang Jiamei

2004-01-01

This paper describes the net peak counts calculating of nuclide 137 Cs at 662 keV of γ spectra in airborne radioactivity measurements using multiple linear regressions. Mathematic model is founded by analyzing every factor that has contribution to Cs peak counts in spectra, and multiple linear regression function is established. Calculating process adopts stepwise regression, and the indistinctive factors are eliminated by F check. The regression results and its uncertainty are calculated using Least Square Estimation, then the Cs peak net counts and its uncertainty can be gotten. The analysis results for experimental spectrum are displayed. The influence of energy shift and energy resolution on the analyzing result is discussed. In comparison with the stripping spectra method, multiple linear regression method needn't stripping radios, and the calculating result has relation with the counts in Cs peak only, and the calculating uncertainty is reduced. (authors)

Higher body mass index associated with severe early childhood caries.

Science.gov (United States)

Davidson, Katherine; Schroth, Robert J; Levi, Jeremy A; Yaffe, Aaron B; Mittermuller, Betty-Anne; Sellers, Elizabeth A C

2016-08-20

Severe Early Childhood Caries (S-ECC) is an aggressive form of tooth decay in preschool children affecting quality of life and nutritional status. The purpose was to determine whether there is an association between Body Mass Index (BMI) and S-ECC. Children with S-ECC were recruited on the day of their slated dental surgery under general anesthesia. Age-matched, caries-free controls were recruited from the community. All children were participating in a larger study on nutrition and S-ECC. Analysis was restricted to children ≥ 24 months of age. Parents completed a questionnaire and heights and weights were recorded. BMI scores and age and gender adjusted BMI z-scores and percentiles were calculated. A p-value ≤ 0.05 was significant. Two hundred thirty-five children were included (141 with S-ECC and 94 caries-free). The mean age was 43.3 ± 12.8 months and 50.2 % were male. Overall, 34.4 % of participants were overweight or obese. Significantly more children with S-ECC were classified as overweight or obese when compared to caries-free children (p = 0.038) and had significantly higher mean BMI z-scores than caries-free children (0.78 ± 1.26 vs. 0.22 ± 1.36, p = 0.002). Those with S-ECC also had significantly higher BMI percentiles (69.0 % ± 29.2 vs. 56.8 % ± 31.7, p = 0.003). Multiple linear regression analyses revealed that BMI z-scores were significantly and independently associated with S-ECC and annual household income as were BMI percentiles. Children with S-ECC in our sample had significantly higher BMI z-scores than caries-free peers.

Social and environmental inequities in dental caries among indigenous population in Brazil: evidence from 2000 to 2007.

Science.gov (United States)

Alves Filho, Pedro; Santos, Ricardo Ventura; Vettore, Mario Vianna

2013-09-01

This ecological study investigated the association between social and environmental inequities and dental caries among indigenous people in Brazil. Dental caries data were gathered from articles identified from electronic databases for the period between 2000 and 2007. Independent variables were obtained from the census of Health Information System for Sanitation Indigenous Populations. Multiple linear regression analysis was conducted to test the association between social and environmental characteristics and dental caries (DMFT index) according to the age group. Results were analyzed for 48 indigenous peoples from 19 selected studies. The occurrence of dental caries in particular age groups was inversely associated with the location of villages outside the Amazon region (12, 15 - 19, and 20 - 34 years), availability of electricity (15 - 19 and 20 - 34 years) and proportion of households covered with straw/thatch (20 - 34 years). The presence of schools was statistically associated with higher DMFT averages (15 - 19 and 20 - 34 years). It can be concluded that aspects of location and existing infrastructure in indigenous communities, which are linked to the availability of oral health services, are associated with the occurrence of dental caries in indigenous populations in Brazil.

Experience of Early Childhood Caries May Positively Correlate with Psychomotor Development.

Science.gov (United States)

Liang, Chen-Yi; Liu, Yen-Chun; Shieh, Tien-Yu; Lin, Jia-Rong; Tseng, Yi-Chun; Teng, Andy Yen-Tung

2015-01-01

To examine the as yet unknown relationship between dental caries and the child's psychomotor development. A cross-sectional study was designed by screening the kindergartens from urban areas of two cities in southern Taiwan. Besides the personal, demographic and dietary information, the common measures for caries (dmft) and the amended comprehensive scales (CCDI) for psychomotor development were used to assess their relationship(s). A power analysis showed that 334 subjects would be required. One-way ANOVA vs multiple linear regression analysis were used to compare the differences of variables between gender, age and dmft scales, vs the relationship among all variables tested, respectively. A total of 433 children completed the study. The results demonstrated that there was a positive relationship between higher (i.e. dmft≥4 and 5) but not lower or extremely high caries experience and aspects of psychomotor development (i.e. personal-social and expressive language) in children aged 4 to 6 years. The present results are important for paediatric dentists, as they suggest a positive correlation between caries experience (dmft 3 to 6) and psychomotor development in pre-school children and that such a correlation may occur more significantly as an attribute of the most affected teeth (incisors and molars) during the critical stage of personal-social and expressive language development (speech-communication).

Multivariate Linear Regression and CART Regression Analysis of TBM Performance at Abu Hamour Phase-I Tunnel

Science.gov (United States)

Jakubowski, J.; Stypulkowski, J. B.; Bernardeau, F. G.

2017-12-01

The first phase of the Abu Hamour drainage and storm tunnel was completed in early 2017. The 9.5 km long, 3.7 m diameter tunnel was excavated with two Earth Pressure Balance (EPB) Tunnel Boring Machines from Herrenknecht. TBM operation processes were monitored and recorded by Data Acquisition and Evaluation System. The authors coupled collected TBM drive data with available information on rock mass properties, cleansed, completed with secondary variables and aggregated by weeks and shifts. Correlations and descriptive statistics charts were examined. Multivariate Linear Regression and CART regression tree models linking TBM penetration rate (PR), penetration per revolution (PPR) and field penetration index (FPI) with TBM operational and geotechnical characteristics were performed for the conditions of the weak/soft rock of Doha. Both regression methods are interpretable and the data were screened with different computational approaches allowing enriched insight. The primary goal of the analysis was to investigate empirical relations between multiple explanatory and responding variables, to search for best subsets of explanatory variables and to evaluate the strength of linear and non-linear relations. For each of the penetration indices, a predictive model coupling both regression methods was built and validated. The resultant models appeared to be stronger than constituent ones and indicated an opportunity for more accurate and robust TBM performance predictions.

Exploring the relation between body mass index, diet, and dental caries among 6-12-year-old children.

Science.gov (United States)

Elangovan, A; Mungara, J; Joseph, E

2012-01-01

Childhood overweight and obesity are becoming a major public health concern all over the world. Change in lifestyles and economic growth have led to sedentary lifestyle and altered dietary patterns. There are conflicting reports in the literature regarding the association between body mass index (BMI) and dental caries from various parts of the world. The aim of the present study was to determine if there is an association between BMI-for-age and dental caries in children and to find out the role of diet with respect to BMI-for-age and dental caries. Demographics and anthropometric measurements were obtained for 600 children and BMI-for-age was calculated. Clinical examination for dental caries was carried out following WHO criteria. A diet recording sheet was prepared and children/parents were asked to record the dietary intake for 3 days. Data obtained were statistically analyzed using Chi-square, analysis of variance (ANOVA), and multiple linear regression. After excluding improperly filled diet recording sheets, 510 children were included in the study. Caries prevalence was more in obese children than in other BMI groups. Caries scores increased as BMI-for-age increased, though this was not statistically significant. Consumption of fatty foods and snacks was more with obese children compared to other groups. A correlation was found between caries and snacks. Dental caries scores showed no relationship between BMI-for-age in children. Both snacks and fatty food items were consumed more by obese children, which seeks attention.

Antipsychotic medications and dental caries in newly diagnosed schizophrenia: A nationwide cohort study.

Science.gov (United States)

Hu, Kai-Fang; Chou, Yu-Hsiang; Wen, Yen-Hsia; Hsieh, Kun-Pin; Tsai, Jui-Hsiu; Yang, Pinchen; Yang, Yi-Hsin; Lin, Chun-Hung Richard

2016-11-30

We investigated the association between antipsychotic medications and the risk of dental caries in patients with schizophrenia. We enroled a nationwide cohort of patients with newly diagnosed schizophrenia within 1 year of dental caries development. Exposure to antipsychotics and other medications was categorised according to their type and duration, and the association between exposure and dental caries was assessed through logistic regressions. Of the 3610 patients with newly diagnosed schizophrenia, 2149 (59.5%) exhibited an incidence of treated dental caries. Logistic regression analysis identified a younger age, female sex, high income, a 2-year history of dental caries, and exposure to first-generation antipsychotics, and antihypertensives as independent risk factors for treated dental caries in patients with schizophrenia. Hyposalivation, the adverse effect of first-generation antipsychotics and antihypertensives, was associated with an increased risk of treated dental caries. However, hypersalivation from first-generation antipsychotics for dental caries was associated with a protective factor. These findings suggest that clinicians should pay attention to the aforementioned risk factors for dental caries in patients with schizophrenia, particularly while prescribing first-generation antipsychotics and antihypertensives to such patients. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

OPLS statistical model versus linear regression to assess sonographic predictors of stroke prognosis.

Science.gov (United States)

Vajargah, Kianoush Fathi; Sadeghi-Bazargani, Homayoun; Mehdizadeh-Esfanjani, Robab; Savadi-Oskouei, Daryoush; Farhoudi, Mehdi

2012-01-01

The objective of the present study was to assess the comparable applicability of orthogonal projections to latent structures (OPLS) statistical model vs traditional linear regression in order to investigate the role of trans cranial doppler (TCD) sonography in predicting ischemic stroke prognosis. The study was conducted on 116 ischemic stroke patients admitted to a specialty neurology ward. The Unified Neurological Stroke Scale was used once for clinical evaluation on the first week of admission and again six months later. All data was primarily analyzed using simple linear regression and later considered for multivariate analysis using PLS/OPLS models through the SIMCA P+12 statistical software package. The linear regression analysis results used for the identification of TCD predictors of stroke prognosis were confirmed through the OPLS modeling technique. Moreover, in comparison to linear regression, the OPLS model appeared to have higher sensitivity in detecting the predictors of ischemic stroke prognosis and detected several more predictors. Applying the OPLS model made it possible to use both single TCD measures/indicators and arbitrarily dichotomized measures of TCD single vessel involvement as well as the overall TCD result. In conclusion, the authors recommend PLS/OPLS methods as complementary rather than alternative to the available classical regression models such as linear regression.

Generalised Partially Linear Regression with Misclassified Data and an Application to Labour Market Transitions

DEFF Research Database (Denmark)

Dlugosz, Stephan; Mammen, Enno; Wilke, Ralf

We consider the semiparametric generalised linear regression model which has mainstream empirical models such as the (partially) linear mean regression, logistic and multinomial regression as special cases. As an extension to related literature we allow a misclassified covariate to be interacted...

Neutrosophic Correlation and Simple Linear Regression

Directory of Open Access Journals (Sweden)

A. A. Salama

2014-09-01

Full Text Available Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. The fundamental concepts of neutrosophic set, introduced by Smarandache. Recently, Salama et al., introduced the concept of correlation coefficient of neutrosophic data. In this paper, we introduce and study the concepts of correlation and correlation coefficient of neutrosophic data in probability spaces and study some of their properties. Also, we introduce and study the neutrosophic simple linear regression model. Possible applications to data processing are touched upon.

Comparison of Classical Linear Regression and Orthogonal Regression According to the Sum of Squares Perpendicular Distances

OpenAIRE

KELEŞ, Taliha; ALTUN, Murat

2016-01-01

Regression analysis is a statistical technique for investigating and modeling the relationship between variables. The purpose of this study was the trivial presentation of the equation for orthogonal regression (OR) and the comparison of classical linear regression (CLR) and OR techniques with respect to the sum of squared perpendicular distances. For that purpose, the analyses were shown by an example. It was found that the sum of squared perpendicular distances of OR is smaller. Thus, it wa...

Single image super-resolution using locally adaptive multiple linear regression.

Science.gov (United States)

Yu, Soohwan; Kang, Wonseok; Ko, Seungyong; Paik, Joonki

2015-12-01

This paper presents a regularized superresolution (SR) reconstruction method using locally adaptive multiple linear regression to overcome the limitation of spatial resolution of digital images. In order to make the SR problem better-posed, the proposed method incorporates the locally adaptive multiple linear regression into the regularization process as a local prior. The local regularization prior assumes that the target high-resolution (HR) pixel is generated by a linear combination of similar pixels in differently scaled patches and optimum weight parameters. In addition, we adapt a modified version of the nonlocal means filter as a smoothness prior to utilize the patch redundancy. Experimental results show that the proposed algorithm better restores HR images than existing state-of-the-art methods in the sense of the most objective measures in the literature.

Teaching the Concept of Breakdown Point in Simple Linear Regression.

Science.gov (United States)

Chan, Wai-Sum

2001-01-01

Most introductory textbooks on simple linear regression analysis mention the fact that extreme data points have a great influence on ordinary least-squares regression estimation; however, not many textbooks provide a rigorous mathematical explanation of this phenomenon. Suggests a way to fill this gap by teaching students the concept of breakdown…

High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

Science.gov (United States)

Laurens, L M L; Wolfrum, E J

2013-12-18

One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

Establishment of regression dependences. Linear and nonlinear dependences

International Nuclear Information System (INIS)

Onishchenko, A.M.

1994-01-01

The main problems of determination of linear and 19 types of nonlinear regression dependences are completely discussed. It is taken into consideration that total dispersions are the sum of measurement dispersions and parameter variation dispersions themselves. Approaches to all dispersions determination are described. It is shown that the least square fit gives inconsistent estimation for industrial objects and processes. The correction methods by taking into account comparable measurement errors for both variable give an opportunity to obtain consistent estimation for the regression equation parameters. The condition of the correction technique application expediency is given. The technique for determination of nonlinear regression dependences taking into account the dependence form and comparable errors of both variables is described. 6 refs., 1 tab

Evaluation of severity of dental caries in primary teeth among children 5-7 years-old in Tehran in 2016

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Hossein Hessari

2017-02-01

Full Text Available Background and Aims: This study aimed to assess the severity of tooth decay and related factors in children 5-7 years old, in 2016, in Tehran. Materials and Methods: A descriptive and cross-sectional study was performed on 572 children aged 5-7 years old (300 girls and 272 boys in public schools in Tehran, Iran. Severity of dental caries (number of decayed, missing, filled surfaces recorded for C, D and E teeth according to WHO criteria. Data analysis was performed by Backward Linear Regression Analyses using SPSS 20 (P≤0.05. Results: Assessment of dental caries severity according to the number of decayed surfaces showed generally higher figures in upper jaw. The order of average severity of carious teeth was C, E and D from low to high in both jaws. According to the results of Linear Regression Analysis, severity of dental caries was more than other children in boys (OR=1.83, 95%CI: 0.81-2.8, those visited dentist due to dental problems associated with pain (OR=1.17, 95%CI: 0.73-1.6, and those without fluoride therapy (OR=1.64, 95%CI: 0.58-2.6 in C, D and E teeth. Conclusion: Flow the results, it was concluded that gender, level of mother's education, type of snack consumption, start age of tooth brushing, reason for dental visit and fluoride therapy affected severity of tooth decay.

The number of subjects per variable required in linear regression analyses.

Science.gov (United States)

Austin, Peter C; Steyerberg, Ewout W

2015-06-01

To determine the number of independent variables that can be included in a linear regression model. We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R(2) of the fitted model. A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, the standard errors of the regression coefficients were accurately estimated and estimated confidence intervals had approximately the advertised coverage rates. A much higher number of SPV were necessary to minimize bias in estimating the model R(2), although adjusted R(2) estimates behaved well. The bias in estimating the model R(2) statistic was inversely proportional to the magnitude of the proportion of variation explained by the population regression model. Linear regression models require only two SPV for adequate estimation of regression coefficients, standard errors, and confidence intervals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Caries-risk profiles in Italian adults using computer caries assessment system and ICDAS

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Giovanna CARTA

2015-01-01

Full Text Available The aim of this study was to examine the correlation among socio-behavioral factors, caries status and caries risk, calculated through Cariogram, in an adult population. Four hundred eighty subjects (mean age 40.73, SE ± 0.33 randomly selected from the municipal electoral registry consented to participate in the survey. Subjects were examined, and the International Caries Detection Assessment System (ICDAS index was registered. A highly structured questionnaire was submitted to investigate (1 personal data (i.e., age, gender, educational level, job categorization, (2 life-style behavior (i.e., smoking and dietary habits, and (3 oral health behavior (i.e., tooth brushing, use of fluoride and dental check-up frequency. An evaluation of the mutans streptococci concentration in saliva was also performed. Information on caries-related factors was entered into the Cariogram in order to generate an individual caries risk profile for each subject. Multinomial logistic regression was performed using Cariogram levels as the dependent variable. The possible correlated variables were analyzed using the principal component analysis (PCA. Considering ICDAS scores, 5.62% of the sample had at least an initial decay (ICDAS = 1-2, whereas 40.83% of the sample presented at least one moderate decay (ICDAS = 3-4 and 17.08% a severe decay (ICDAS = 5-6. Decay at ICDAS levels 5-6 and more than 5 missing teeth were statistically associated with Cariogram scores (OR = 2.36, 95%CI = 1.83–3.03 and OR = 1.43, 95%CI = 1.13–1.82, respectively. The results suggest that the Cariogram model was able to identify caries-related factors in an adult population. A direct association among the risk categories from Cariogram, the caries status and some socio-behavioral variables was verified.

Topical silver diamine fluoride for dental caries arrest in preschool children: A randomized controlled trial and microbiological analysis of caries associated microbes and resistance gene expression.

Science.gov (United States)

Milgrom, Peter; Horst, Jeremy A; Ludwig, Sharity; Rothen, Marilynn; Chaffee, Benjamin W; Lyalina, Svetlana; Pollard, Katherine S; DeRisi, Joseph L; Mancl, Lloyd

2018-01-01

The Stopping Cavities Trial investigated effectiveness and safety of 38% silver diamine fluoride in arresting caries lesions. The study was a double-blind randomized placebo-controlled superiority trial with 2 parallel groups. The sites were Oregon preschools. Sixty-six preschool children with ≥1 lesion were enrolled. Silver diamine fluoride (38%) or placebo (blue-tinted water), applied topically to the lesion. The primary endpoint was caries arrest (lesion inactivity, Nyvad criteria) 14-21days post intervention. Dental plaque was collected from all children, and microbial composition was assessed by RNA sequencing from 2 lesions and 1 unaffected surface before treatment and at follow-up for 3 children from each group. Average proportion of arrested caries lesions in the silver diamine fluoride group was higher (0.72; 95% CI; 0.55, 0.84) than in the placebo group (0.05; 95% CI; 0.00, 0.16). Confirmatory analysis using generalized estimating equation log-linear regression, based on the number of arrested lesions and accounting for the number of treated surfaces and length of follow-up, indicates the risk of arrested caries was significantly higher in the treatment group (relative risk, 17.3; 95% CI: 4.3 to 69.4). No harms were observed. RNA sequencing analysis identified no consistent changes in relative abundance of caries-associated microbes, nor emergence of antibiotic or metal resistance gene expression. Topical 38% silver diamine fluoride is effective and safe in arresting cavities in preschool children. The treatment is applicable to primary care practice and may reduce the burden of untreated tooth decay in the population. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

How Robust Is Linear Regression with Dummy Variables?

Science.gov (United States)

Blankmeyer, Eric

2006-01-01

Researchers in education and the social sciences make extensive use of linear regression models in which the dependent variable is continuous-valued while the explanatory variables are a combination of continuous-valued regressors and dummy variables. The dummies partition the sample into groups, some of which may contain only a few observations.…

Health promotion and dental caries.

Science.gov (United States)

Maltz, Marisa; Jardim, Juliana Jobim; Alves, Luana Severo

2010-01-01

The central idea of the Brazilian health system is to prevent the establishment of disease or detect it as early as possible. Prevention and treatment of dental caries are related to behavioral factors, including dietary and oral hygiene habits, which are related to many chronic diseases. Dental health promotion therefore should be fully integrated into broadly based health-promoting strategies and actions such as food and health policies, and general hygiene (including oral hygiene), among others. For decades, a linear relationship between sugar consumption and caries has been observed. Recent data has indicated that this relationship is not as strong as it used to be before the widespread use of fluoride. However, diet is still a key factor acting in the carious process. Oral hygiene is a major aspect when it comes to caries, since dental biofilm is its etiological factor. Oral hygiene procedures are effective in controlling dental caries, especially if plaque removal is performed adequately and associated with fluoride. An alternative to a more efficient biofilm control in occlusal areas is the use of dental sealants, which are only indicated for caries-active individuals. If a cavity is formed as a consequence of the metabolic activity of the biofilm, a restorative material or a sealant can be placed to block access of the biofilm to the oral environment in order to prevent caries progress. The prevention of dental caries based on common risk-factor strategies (diet and hygiene) should be supplemented by more disease-specific policies such as rational use of fluoride, and evidence-based dental health care.

Health promotion and dental caries

Directory of Open Access Journals (Sweden)

Marisa Maltz

2010-01-01

Full Text Available The central idea of the Brazilian health system is to prevent the establishment of disease or detect it as early as possible. Prevention and treatment of dental caries are related to behavioral factors, including dietary and oral hygiene habits, which are related to many chronic diseases. Dental health promotion therefore should be fully integrated into broadly based health-promoting strategies and actions such as food and health policies, and general hygiene (including oral hygiene, among others. For decades, a linear relationship between sugar consumption and caries has been observed. Recent data has indicated that this relationship is not as strong as it used to be before the widespread use of fluoride. However, diet is still a key factor acting in the carious process. Oral hygiene is a major aspect when it comes to caries, since dental biofilm is its etiological factor. Oral hygiene procedures are effective in controlling dental caries, especially if plaque removal is performed adequately and associated with fluoride. An alternative to a more efficient biofilm control in occlusal areas is the use of dental sealants, which are only indicated for caries-active individuals. If a cavity is formed as a consequence of the metabolic activity of the biofilm, a restorative material or a sealant can be placed to block access of the biofilm to the oral environment in order to prevent caries progress. The prevention of dental caries based on common risk-factor strategies (diet and hygiene should be supplemented by more disease-specific policies such as rational use of fluoride, and evidence-based dental health care.

Common pitfalls in statistical analysis: Linear regression analysis

Directory of Open Access Journals (Sweden)

Rakesh Aggarwal

2017-01-01

Full Text Available In a previous article in this series, we explained correlation analysis which describes the strength of relationship between two continuous variables. In this article, we deal with linear regression analysis which predicts the value of one continuous variable from another. We also discuss the assumptions and pitfalls associated with this analysis.

Social inequalities and dental caries in six-year-old children from the Netherlands.

Science.gov (United States)

van der Tas, Justin T; Kragt, Lea; Elfrink, Marlies E C; Bertens, Loes C M; Jaddoe, Vincent W V; Moll, Henriëtte A; Ongkosuwito, Edwin M; Wolvius, Eppo B

2017-07-01

The purpose of our study was to investigate the association of different socioeconomic and sociodemographic factors with dental caries in six-year-old children. Furthermore, we applied a district based approach to explore the distribution of dental caries among districts of low and high socioeconomic position (SEP). In our cross-sectional study 5189 six-year-olds were included. This study was embedded in a prospective population-based birth cohort study in Rotterdam, the Netherlands, the Generation R Study. Parental education level, parental employment status, net household income, single parenting, and teenage pregnancy were considered as indicators for SEP. Dental caries was scored on intraoral photographs by using the decayed, missing, and filled teeth (dmft) index. We compared children without caries (dmft=0) to children with mild caries (dmft=1-3) or severe caries (dmft >3). Multinomial logistic regression analyses and binary logistic regression analyses were performed to study the association between SEP and caries, and between district and caries, respectively. Only maternal education level remained significantly associated with mild caries after adjusting for all other SEP-indicators. Paternal educational level, parental employment status, and household income additionally served as independent indicators of SEP in children with severe caries. Furthermore, living in more disadvantaged districts was significantly associated with higher odds of dental caries. Dental caries is more prevalent among six-year-old children with a low SEP, which is also visible at the district level. Maternal educational level is the most important indicator of SEP in the association with caries. Our results should raise concerns about the existing social inequalities in dental caries and should encourage development of dental caries prevention strategies. New knowledge about the distribution of oral health inequalities between districts should be used to target the right audience

Dental caries increments and related factors in children with type 1 diabetes mellitus.

Science.gov (United States)

Siudikiene, J; Machiulskiene, V; Nyvad, B; Tenovuo, J; Nedzelskiene, I

2008-01-01

The aim of this study was to analyse possible associations between caries increments and selected caries determinants in children with type 1 diabetes mellitus and their age- and sex-matched non-diabetic controls, over 2 years. A total of 63 (10-15 years old) diabetic and non-diabetic pairs were examined for dental caries, oral hygiene and salivary factors. Salivary flow rates, buffer effect, concentrations of mutans streptococci, lactobacilli, yeasts, total IgA and IgG, protein, albumin, amylase and glucose were analysed. Means of 2-year decayed/missing/filled surface (DMFS) increments were similar in diabetics and their controls. Over the study period, both unstimulated and stimulated salivary flow rates remained significantly lower in diabetic children compared to controls. No differences were observed in the counts of lactobacilli, mutans streptococci or yeast growth during follow-up, whereas salivary IgA, protein and glucose concentrations were higher in diabetics than in controls throughout the 2-year period. Multivariable linear regression analysis showed that children with higher 2-year DMFS increments were older at baseline and had higher salivary glucose concentrations than children with lower 2-year DMFS increments. Likewise, higher 2-year DMFS increments in diabetics versus controls were associated with greater increments in salivary glucose concentrations in diabetics. Higher increments in active caries lesions in diabetics versus controls were associated with greater increments of dental plaque and greater increments of salivary albumin. Our results suggest that, in addition to dental plaque as a common caries risk factor, diabetes-induced changes in salivary glucose and albumin concentrations are indicative of caries development among diabetics. Copyright 2008 S. Karger AG, Basel.

Tightness of M-estimators for multiple linear regression in time series

DEFF Research Database (Denmark)

Johansen, Søren; Nielsen, Bent

We show tightness of a general M-estimator for multiple linear regression in time series. The positive criterion function for the M-estimator is assumed lower semi-continuous and sufficiently large for large argument: Particular cases are the Huber-skip and quantile regression. Tightness requires...

Exploring the determinants of secular decreases in dental caries among Korean children.

Science.gov (United States)

Lee, Hye-Ju; Han, Dong-Hun

2015-08-01

The aim of this study was to determine the contributions of sealant and water fluoridation to the time trends in dental caries from 2003 to 2010. Data were from three waves of the Korean National Oral Health Surveys between 2003 and 2010, including a total of 23 059 children (11 889 boys and 11 170 girls) aged 8, 10, and 12 years. The impacts of sealant and water fluoridation on dental caries were obtained by logistic regression for each age group of children. The contributions of sealant and water fluoridation to the time trends in the prevalence of dental caries were examined by a series of logistic regression models, and changes in the adjusted odds ratios for each survey year were also calculated. Over the past 7 years, the prevalence of dental caries decreased dramatically. Although sealant had a significant impact on dental caries in each survey year, remarkable decreases in dental caries from 2003 to 2010 were not explained by the secular changes in the dental sealant or water fluoridation factor. We observed important population declines in dental caries in Korea in children aged 8-12 years; however, the likely causes for these secular trends remain to be determined. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

BRGLM, Interactive Linear Regression Analysis by Least Square Fit

International Nuclear Information System (INIS)

Ringland, J.T.; Bohrer, R.E.; Sherman, M.E.

1985-01-01

1 - Description of program or function: BRGLM is an interactive program written to fit general linear regression models by least squares and to provide a variety of statistical diagnostic information about the fit. Stepwise and all-subsets regression can be carried out also. There are facilities for interactive data management (e.g. setting missing value flags, data transformations) and tools for constructing design matrices for the more commonly-used models such as factorials, cubic Splines, and auto-regressions. 2 - Method of solution: The least squares computations are based on the orthogonal (QR) decomposition of the design matrix obtained using the modified Gram-Schmidt algorithm. 3 - Restrictions on the complexity of the problem: The current release of BRGLM allows maxima of 1000 observations, 99 variables, and 3000 words of main memory workspace. For a problem with N observations and P variables, the number of words of main memory storage required is MAX(N*(P+6), N*P+P*P+3*N, and 3*P*P+6*N). Any linear model may be fit although the in-memory workspace will have to be increased for larger problems

The Dietary Approaches to Stop Hypertension Diet and New and Recurrent Root Caries Events in Men.

Science.gov (United States)

Kaye, Elizabeth K; Heaton, Brenda; Sohn, Woosung; Rich, Sharron E; Spiro, Avron; Garcia, Raul I

2015-09-01

To examine the effect of overall dietary quality on number of teeth with new or recurrent root caries events during follow-up (root caries increment). Prospective study with dental examinations approximately every 3 years over 20 years. Veterans Affairs Dental Longitudinal Study in greater Boston, Massachusetts, area. Men aged 47 to 90 (N = 533). A single calibrated examiner assessed root caries and restorations, calculus, probing pocket depth, and attachment loss on each tooth at each examination. The adjusted root caries increment (root-ADJCI) was computed from new and recurrent root caries events on teeth with recession of 2 mm or more. Dietary information was obtained from food frequency questionnaires. An adherence score was computed by comparing consumption frequency of 10 food groups (fruits, vegetables, total dairy, low-fat dairy, meat, total grains, high-fiber grains, legumes, fats, sweets) from the Dietary Approaches to Stop Hypertension (DASH) diet guidelines. Mean root-ADJCIs were compared according to DASH adherence score quartile using generalized linear negative binomial regression models, controlling for age, number of teeth at risk of root caries, time at risk of root caries, calculus, presence of removable denture, history of dental prophylaxis, body mass index, and smoking status. Men with DASH adherence scores in the highest quartile had a 30% lower mean root-ADJCI (1.86 teeth) than those in the lowest quartile (2.68 teeth) (P = .03). Root-ADJCI was lower with greater adherence to recommendations for vegetables and total grains and greater with greater sugar-sweetened carbonated beverage consumption. Root caries incidence rate did not vary significantly between quartiles. A higher-quality diet may reduce root caries risk in older men. © 2015, Copyright the Authors Journal compilation © 2015, The American Geriatrics Society.

Association between the number of early carious lesions and diet in children with a high prevalence of caries.

Science.gov (United States)

Llena, C; Leyda, A; Forner, L; Garcet, S

2015-03-01

An investigation was conducted in a population of paediatric patients with a high risk of caries in order to assess the association between caries history (CH) and the number of early carious lesions (ECLs) and the frequency and timing of cariogenic food and beverage intake, sugar-containing medication, the frequency and efficacy of tooth brushing, and the use of topical fluorides. Study design: descriptive study. One hundred children aged 6-15 years with≥ ECL of a permanent tooth and not enrolled in any dental health educational or preventive programme were selected. For diagnosis it was used an explorer according to the ICDAS II criteria. The participants completed a closed-list questionnaire on the frequency and timing of cariogenic food intake. There was a nonsignificant tendency to present more ECLs and a greater CH among patients who consumed cariogenic foods and beverages. A significant relationship (pcariogenic beverages and the number of ECL or CH. Using the number of ECLs as dependent variable, regular fluoridated rinses (p=0.003), frequent sugar-containing medication (p=0.007), and cariogenic beverage consumption (p=0.024) were identified as explanatory parameters in the linear regression model. The Student t-test was used to compare ECL and CH with dietetic factors, fluoridated rinses, sugar- containing medicines, and the frequency and efficacy of tooth brushing. Linear regression analysis correlated the number of ECLs to the mentioned explanatory variables. The frequent consumption of sugary beverages and medications, and failure to regularly use fluoridated rinses, were positively correlated to an increased number of ECLs in patients with a high prevalence of caries.

Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling.

Science.gov (United States)

Kawashima, Issaku; Kumano, Hiroaki

2017-01-01

Mind-wandering (MW), task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological variables. However, these models are not applicable in general situations. Moreover, they output only binary classification. The current study suggests that the combination of electroencephalogram (EEG) variables and non-linear regression modeling can be a good indicator of MW intensity. We recorded EEGs of 50 subjects during the performance of a Sustained Attention to Response Task, including a thought sampling probe that inquired the focus of attention. We calculated the power and coherence value and prepared 35 patterns of variable combinations and applied Support Vector machine Regression (SVR) to them. Finally, we chose four SVR models: two of them non-linear models and the others linear models; two of the four models are composed of a limited number of electrodes to satisfy model usefulness. Examination using the held-out data indicated that all models had robust predictive precision and provided significantly better estimations than a linear regression model using single electrode EEG variables. Furthermore, in limited electrode condition, non-linear SVR model showed significantly better precision than linear SVR model. The method proposed in this study helps investigations into MW in various little-examined situations. Further, by measuring MW with a high temporal resolution EEG, unclear aspects of MW, such as time series variation, are expected to be revealed. Furthermore, our suggestion that a few electrodes can also predict MW contributes to the development of neuro-feedback studies.

Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling

Directory of Open Access Journals (Sweden)

Issaku Kawashima

2017-07-01

Full Text Available Mind-wandering (MW, task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological variables. However, these models are not applicable in general situations. Moreover, they output only binary classification. The current study suggests that the combination of electroencephalogram (EEG variables and non-linear regression modeling can be a good indicator of MW intensity. We recorded EEGs of 50 subjects during the performance of a Sustained Attention to Response Task, including a thought sampling probe that inquired the focus of attention. We calculated the power and coherence value and prepared 35 patterns of variable combinations and applied Support Vector machine Regression (SVR to them. Finally, we chose four SVR models: two of them non-linear models and the others linear models; two of the four models are composed of a limited number of electrodes to satisfy model usefulness. Examination using the held-out data indicated that all models had robust predictive precision and provided significantly better estimations than a linear regression model using single electrode EEG variables. Furthermore, in limited electrode condition, non-linear SVR model showed significantly better precision than linear SVR model. The method proposed in this study helps investigations into MW in various little-examined situations. Further, by measuring MW with a high temporal resolution EEG, unclear aspects of MW, such as time series variation, are expected to be revealed. Furthermore, our suggestion that a few electrodes can also predict MW contributes to the development of neuro-feedback studies.

Caries experience and use of dental services in rural and urban adults and older adults from central Chile.

Science.gov (United States)

Quinteros, Maria E; Cáceres, Dante D; Soto, Alex; Mariño, Rodrigo J; Giacaman, Rodrigo A

2014-10-01

To determine whether there is a relationship between the use of dental services and caries experience in adults and older adults from central Chile. A sample of 453 adults, 35-44 years of age, and 438 older adults, 65-74 years of age, was interviewed and examined using World Health Organisation (WHO) methods. Sociodemographic variables were also registered. Caries experience was assessed using the Decayed, Missing and Filled teeth (DMFT) index. Multiple linear regression models were used to determine whether there was an association between the independent variables and caries experience. Caries prevalence was 99.6% for adults [DMFT score = 14.89 (±6.16)] and 99.8% for older adults [DMFT score = 25.68 (±6.49)]. Less than half of the population - 41.7% of adults and 31.5% of older adults - received dental care. Regardless of the age group, there were no differences in the DMFT score between those who received and those who did not receive attention (P > 0.05). When the DMFT findings were analysed in greater detail, people who received dental care and urban participants had more fillings (P dental damage from caries. Although rurality and use of services do not seem to affect caries experience, they are associated with differences in fillings and missing teeth. © 2014 FDI World Dental Federation.

Stochastic development regression on non-linear manifolds

DEFF Research Database (Denmark)

Kühnel, Line; Sommer, Stefan Horst

2017-01-01

We introduce a regression model for data on non-linear manifolds. The model describes the relation between a set of manifold valued observations, such as shapes of anatomical objects, and Euclidean explanatory variables. The approach is based on stochastic development of Euclidean diffusion...... processes to the manifold. Defining the data distribution as the transition distribution of the mapped stochastic process, parameters of the model, the non-linear analogue of design matrix and intercept, are found via maximum likelihood. The model is intrinsically related to the geometry encoded...... in the connection of the manifold. We propose an estimation procedure which applies the Laplace approximation of the likelihood function. A simulation study of the performance of the model is performed and the model is applied to a real dataset of Corpus Callosum shapes....

EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression.

Science.gov (United States)

Lian, Yao; Ge, Meng; Pan, Xian-Ming

2014-12-19

B-cell epitopes have been studied extensively due to their immunological applications, such as peptide-based vaccine development, antibody production, and disease diagnosis and therapy. Despite several decades of research, the accurate prediction of linear B-cell epitopes has remained a challenging task. In this work, based on the antigen's primary sequence information, a novel linear B-cell epitope prediction model was developed using the multiple linear regression (MLR). A 10-fold cross-validation test on a large non-redundant dataset was performed to evaluate the performance of our model. To alleviate the problem caused by the noise of negative dataset, 300 experiments utilizing 300 sub-datasets were performed. We achieved overall sensitivity of 81.8%, precision of 64.1% and area under the receiver operating characteristic curve (AUC) of 0.728. We have presented a reliable method for the identification of linear B cell epitope using antigen's primary sequence information. Moreover, a web server EPMLR has been developed for linear B-cell epitope prediction: http://www.bioinfo.tsinghua.edu.cn/epitope/EPMLR/ .

The number of subjects per variable required in linear regression analyses

NARCIS (Netherlands)

P.C. Austin (Peter); E.W. Steyerberg (Ewout)

2015-01-01

textabstractObjectives To determine the number of independent variables that can be included in a linear regression model. Study Design and Setting We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression

Distributed Monitoring of the R2 Statistic for Linear Regression

Data.gov (United States)

National Aeronautics and Space Administration — The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and...

Treating experimental data of inverse kinetic method by unitary linear regression analysis

International Nuclear Information System (INIS)

Zhao Yusen; Chen Xiaoliang

2009-01-01

The theory of treating experimental data of inverse kinetic method by unitary linear regression analysis was described. Not only the reactivity, but also the effective neutron source intensity could be calculated by this method. Computer code was compiled base on the inverse kinetic method and unitary linear regression analysis. The data of zero power facility BFS-1 in Russia were processed and the results were compared. The results show that the reactivity and the effective neutron source intensity can be obtained correctly by treating experimental data of inverse kinetic method using unitary linear regression analysis and the precision of reactivity measurement is improved. The central element efficiency can be calculated by using the reactivity. The result also shows that the effect to reactivity measurement caused by external neutron source should be considered when the reactor power is low and the intensity of external neutron source is strong. (authors)

An improved multiple linear regression and data analysis computer program package

Science.gov (United States)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

SCHOOL DIETARY HABITS AND INCIDENCE OF DENTAL CARIES.

Science.gov (United States)

Monteagudo, Celia; Téllez, Francisco; Heras-González, Leticia; Ibañez-Peinado, Diana; Mariscal-Arcas, Miguel; Olea-Serrano, Fatima

2015-07-01

healthy dietary habits are considered to improve oral health and tooth quality. Caries treatment comprises tooth restoration with dental composites and sealants, almost all (> 90%) of which contain bisphenol A (BPA). Study hypotheses were: a) breakfast and oral hygiene habits are important factors in dental caries development; and b) dental caries treatment with epoxy-resins entails a risk of oral exposure to monomers migrating from the polymeric material. We evaluated caries in the teeth of a Spanish school population and determined the percentage treated with dental composites. to relate consumption of breakfast components and oral hygiene habits to dental caries and determine the presence of sealants/composites as potential sources of BPA exposure. subjects: 582 schoolchildren from Granada city (Southern Spain) aged 7 yrs; mean (SD) of 7.55 (0.64) yrs. caries was detected in 21.7% of their teeth. Mean breakfast quality index (BQI) score, based on nutritional questionnaires, was 5.18 (1.29). Breakfast with foods rich in simple sugars representing > 5% of total daily energy was consumed by 24% of the population and was significantly associated with caries frequency in binary logistic regression analysis. Biscuit consumption was reported by 35.8% and significantly associated with caries frequency. Breakfast intake of bakery products/ cereals and of dairy products showed a significant inverse association with caries frequency. No significant relationship was observed between caries and BQI score or oral hygiene factors. further research is required to elucidate the role of diet in caries and the associated risk of exposure to estrogenic xenobiotics such as BPA. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

On macroeconomic values investigation using fuzzy linear regression analysis

Directory of Open Access Journals (Sweden)

Richard Pospíšil

2017-06-01

Full Text Available The theoretical background for abstract formalization of the vague phenomenon of complex systems is the fuzzy set theory. In the paper, vague data is defined as specialized fuzzy sets - fuzzy numbers and there is described a fuzzy linear regression model as a fuzzy function with fuzzy numbers as vague parameters. To identify the fuzzy coefficients of the model, the genetic algorithm is used. The linear approximation of the vague function together with its possibility area is analytically and graphically expressed. A suitable application is performed in the tasks of the time series fuzzy regression analysis. The time-trend and seasonal cycles including their possibility areas are calculated and expressed. The examples are presented from the economy field, namely the time-development of unemployment, agricultural production and construction respectively between 2009 and 2011 in the Czech Republic. The results are shown in the form of the fuzzy regression models of variables of time series. For the period 2009-2011, the analysis assumptions about seasonal behaviour of variables and the relationship between them were confirmed; in 2010, the system behaved fuzzier and the relationships between the variables were vaguer, that has a lot of causes, from the different elasticity of demand, through state interventions to globalization and transnational impacts.

Fuzzy Linear Regression for the Time Series Data which is Fuzzified with SMRGT Method

Directory of Open Access Journals (Sweden)

Seçil YALAZ

2016-10-01

Full Text Available Our work on regression and classification provides a new contribution to the analysis of time series used in many areas for years. Owing to the fact that convergence could not obtained with the methods used in autocorrelation fixing process faced with time series regression application, success is not met or fall into obligation of changing the models’ degree. Changing the models’ degree may not be desirable in every situation. In our study, recommended for these situations, time series data was fuzzified by using the simple membership function and fuzzy rule generation technique (SMRGT and to estimate future an equation has created by applying fuzzy least square regression (FLSR method which is a simple linear regression method to this data. Although SMRGT has success in determining the flow discharge in open channels and can be used confidently for flow discharge modeling in open canals, as well as in pipe flow with some modifications, there is no clue about that this technique is successful in fuzzy linear regression modeling. Therefore, in order to address the luck of such a modeling, a new hybrid model has been described within this study. In conclusion, to demonstrate our methods’ efficiency, classical linear regression for time series data and linear regression for fuzzy time series data were applied to two different data sets, and these two approaches performances were compared by using different measures.

Dental caries experience among indigenous children and adolescents.

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Gonçalves, Érica M; Cavalcanti, Laysa C; Firmino, Ramon T; Ribeiro, Gustavo L; Granville-Garcia, Ana F; Menezes, Valdenice A

2015-06-01

Investigations into the oral health status of indigenous populations are scarce. The aim of this study was to evaluate caries experience and associated factors among 342 indigenous children and adolescents aged 5-15 years of the Xukuru community in the municipality of Pesqueira, Brazil. A cross-sectional census study was carried out using the criteria of the World Health Organization to determine caries experience. Examinations were performed by two calibrated dentists and a questionnaire was administered to parents/caregivers addressing socio-demographic data, diet and oral hygiene habits. Logistic regression analysis were performed, with dmft and DMFT as the dependent variables (P Caries experience (dmft/DMFT) was high in both the primary and permanent dentition (75.6% and 62.9%, respectively). Mean dmft and DMFT indices were 3.11 and 2.21, respectively. Caries experience in the primary dentition was associated with children residing in villages far from urban areas (P = 0.016), while caries in the permanent dentition was associated with older children (P caries experience, which was associated with age and group of villages. Public policies are needed to improve the oral health status of this population.

Oral Hygiene Behaviors and Caries Experience in Northwest PRECEDENT Patients

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Rothen, Marilynn; Cunha-Cruz, Joana; Zhou, Lingmei; Mancl, Lloyd; Jones, Jackie S.; Berg, Joel

2014-01-01

Objectives To investigate the association between oral hygiene behaviors (toothbrushing, water rinsing after brushing, interproximal cleaning, and adjunctive use of fluoride products) and recent caries (past 24 months) in a random sample of patients in Northwest PRECEDENT practices. Methods Practitioner-members of Northwest PRECEDENT dental Practice-based Research Network (PBRN) conducted a longitudinal study on caries risk assessment. At baseline patients completed a questionnaire on oral self-care, snacking, health, and socio-demographics. A dental exam recorded readily-visible heavy plaque and DMFT; chart review captured new caries and treatments in the previous 24 months. Bivariate and multiple GEE log-linear regression models stratified by age groups were used to relate oral hygiene behaviors to the primary outcome of mean dental caries in the past 24 months on data from 1400 patients in 63 practices. The primary exposure of interest was fluoride toothbrushing frequency. Results Fluoride toothbrushing once per day or more by patients 9-17 was significantly associated with a 50% lower mean caries rate compared to fluoride toothbrushing less than once per day, after adjustment for age, gender, race, education, income, between-meal carbohydrate snacks, sugar-added beverages, alcohol consumption, smoking, BMI, exercise, stimulated salivary pH, number of teeth, and all other oral hygiene behaviors captured [Rate Ratio (RR)=0.5; 95% confidence interval (CI)=0.3-0.8]. After adjustment, for patients 18-64 fluoride toothbrushing two or more times per day was significantly associated with a 40% lower recent mean caries rate (RR=0.6; 95%CI=0.4-0.9); in patients 65+, twice a day or more fluoride toothbrushing was not associated with lower caries rates (RR=1.1; 95%CI=0.7-1.8). Of the other oral hygiene variables, after adjustment, patients 18-64 who rinsed with water after brushing had a 40% lower mean caries rate compared to no rinsing (RR=0.6; 95%CI=0.4-0.9) and the

Alzheimer's Disease Detection by Pseudo Zernike Moment and Linear Regression Classification.

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Wang, Shui-Hua; Du, Sidan; Zhang, Yin; Phillips, Preetha; Wu, Le-Nan; Chen, Xian-Qing; Zhang, Yu-Dong

2017-01-01

This study presents an improved method based on "Gorji et al. Neuroscience. 2015" by introducing a relatively new classifier-linear regression classification. Our method selects one axial slice from 3D brain image, and employed pseudo Zernike moment with maximum order of 15 to extract 256 features from each image. Finally, linear regression classification was harnessed as the classifier. The proposed approach obtains an accuracy of 97.51%, a sensitivity of 96.71%, and a specificity of 97.73%. Our method performs better than Gorji's approach and five other state-of-the-art approaches. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Is obesity associated to dental caries in Brazilian schoolchildren?

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Fernández, María Raquel; Goettems, Marília Leão; Demarco, Flávio Fernando; Corrêa, Marcos Britto

2017-11-06

This cross-sectional study aimed to determine the association between dental caries and weight status, and between dental caries and physical activity in Brazilian schoolchildren aged 8 to 12 years. A multi-stage sample of children enrolled in 20 private and public schools in 2010 in Pelotas, Southern Brazil, were invited to participate in the study. Socioeconomic data were collected from parents, and data regarding children characteristics were collected from children using a questionnaire and anthropometric measures. The Body Mass Index was obtained, and children were classified as overweight/obese considering age and sex. Dental examinations were performed to assess the presence of gingival inflammation, dental caries prevalence (DMFT≥1) and dental caries experience (mean DMFT). Multivariate Poisson Regression was used to assess factors associated with dental caries prevalence and experience. A total of 1,210 children were included in the study. Dental caries prevalence was 32.4% (95% CI 29.7-35.2), while the mean DMFT was 0.64 (± SD 1.00). Children who practiced less than 300 minutes per week of physical activity and overweigh/obese children had lower prevalence of dental caries, while children with obesity or overweight presented lower dental caries experience. Obesity/overweight and physical activity level presented an inverse relationship with dental caries. Longitudinal studies investigating the complexity of this relationship are required.

Transmission of linear regression patterns between time series: from relationship in time series to complex networks.

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Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

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Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

2016-01-01

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19

Regression of non-linear coupling of noise in LIGO detectors

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Da Silva Costa, C. F.; Billman, C.; Effler, A.; Klimenko, S.; Cheng, H.-P.

2018-03-01

In 2015, after their upgrade, the advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) detectors started acquiring data. The effort to improve their sensitivity has never stopped since then. The goal to achieve design sensitivity is challenging. Environmental and instrumental noise couple to the detector output with different, linear and non-linear, coupling mechanisms. The noise regression method we use is based on the Wiener–Kolmogorov filter, which uses witness channels to make noise predictions. We present here how this method helped to determine complex non-linear noise couplings in the output mode cleaner and in the mirror suspension system of the LIGO detector.

Dental caries status and its associated factors in pregnant women, Shiraz, Iran, 2014

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Soheila Shaghaghian

2017-07-01

Full Text Available BACKGROUND AND AIM: Dental caries is a common problem in pregnant women which has negative impacts on their quality of life. The aim of this study was to evaluate pregnant women’s dental caries status and its associated risk factors in Shiraz, Iran, in 2014. METHODS: In this cross-sectional study, we selected 423 pregnant women attending Shiraz governmental health centers for routine obstetric examinations by randomized cluster sampling. The women's dental caries status was assessed using decayed, missed, and filled tooth (DMFT index. The women’s demographic characteristics and their oral hygiene habits were evaluated using a valid and reliable questionnaire. The relationship between women's DMFT index and their demographic and oral hygiene characteristics was evaluated using Pearson correlation, analysis of variance, independent sample t-tests, and multiple linear regression models. RESULTS: The mean DMFT index was 5.8 ± 3.6. We found lower scores of DMFT index in women who were younger (P < 0.001, brushed their teeth more (P = 0.014, and used home preventive measures such as mouthwash (P = 0.003 and toothpick (P = 0.006. CONCLUSION: Dental caries status of the pregnant women was unacceptably lower than optimal. Interventions focusing on holding educational programs and taking office-based preventive measures for pregnant women or women who intend to be pregnant are recommended. The interventions are more necessary for older pregnant women and those who use fewer home preventive measures.

Detection method of proximal caries using line profile in digital intra-oral radiography

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Choi, Yong Suk; Kim, Gyu Tae; Hwang, Eui Hwan; Lee, Min Ja; Choi, Sam Jin; Park, Hun Kuk [Department of Oral and Maxillofacial Radiology, School of Dentistry and Institute of Oral Biology, Kyung Hee University, Seoul (Korea, Republic of); Park, Jeong Hoon [Department of Biomedical Engineering, College of Medicine, Kyung Hee University, Seoul (Korea, Republic of)

2009-12-15

The purpose of this study was to investigate how to detect proximal caries using line profile and validate linear measurements of proximal caries lesions by basic digital manipulation of radiographic images. The X-ray images of control group (15) and caries teeth (15) from patients were used. For each image, the line profile at the proximal caries-susceptible zone was calculated. To evaluate the contrast as a function of line profile to detect proximal caries, a difference coefficient (D) that indicates the relative difference between caries and sound dentin or intact enamel was measured. Mean values of D were 0.0354 {+-} 0.0155 in non-caries and 0.2632 {+-} 0.0982 in caries (p<0.001). The mean values of caries group were higher than non-caries group and there was correlation between proximal dental caries and D. It is demonstrated that the mean value of D from caries group was higher than that of control group. From the result, values of D possess great potentiality as a new detection parameter for proximal dental caries.

Detection method of proximal caries using line profile in digital intra-oral radiography

International Nuclear Information System (INIS)

Choi, Yong Suk; Kim, Gyu Tae; Hwang, Eui Hwan; Lee, Min Ja; Choi, Sam Jin; Park, Hun Kuk; Park, Jeong Hoon

2009-01-01

The purpose of this study was to investigate how to detect proximal caries using line profile and validate linear measurements of proximal caries lesions by basic digital manipulation of radiographic images. The X-ray images of control group (15) and caries teeth (15) from patients were used. For each image, the line profile at the proximal caries-susceptible zone was calculated. To evaluate the contrast as a function of line profile to detect proximal caries, a difference coefficient (D) that indicates the relative difference between caries and sound dentin or intact enamel was measured. Mean values of D were 0.0354 ± 0.0155 in non-caries and 0.2632 ± 0.0982 in caries (p<0.001). The mean values of caries group were higher than non-caries group and there was correlation between proximal dental caries and D. It is demonstrated that the mean value of D from caries group was higher than that of control group. From the result, values of D possess great potentiality as a new detection parameter for proximal dental caries.

The Role of Genetic Factors in the Outbreak Mechanism of Dental Caries.

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Shimomura-Kuroki, Junko; Nashida, Tomoko; Miyagawa, Yukio; Sekimoto, Tsuneo

The aim of the present study was to investigate the relationships between cariogenic bacterial infection and single nucleotide polymorphisms (SNPs) in candidate genes associated with dental caries, and to explore the factors related to caries in children. Children aged 3 to 11 years were selected. Detection of cariogenic bacteria (Streptococcus mutans, Streptococcus oralis, Streptococcus sobrinus and Lactobacillus) from the plaque of each patient, and SNP analyses of five candidate genes (MBL2, TAS2R38, GLUT2, MMP13 and CA6) were performed using DNA isolated from buccal mucosal cells. The dental caries experience in primary and permanent teeth was determined using the decayed, missing and filled teeth (DMFT) index, and the effects of the observed factors on the DMFT value were analyzed by multiple regression analysis. The results of the multiple regression analysis showed that the DMFT value significantly increased in the presence of S. mutans or S. sobrinus (p caries.

Fitting program for linear regressions according to Mahon (1996)

Energy Technology Data Exchange (ETDEWEB)

2018-01-09

This program takes the users' Input data and fits a linear regression to it using the prescription presented by Mahon (1996). Compared to the commonly used York fit, this method has the correct prescription for measurement error propagation. This software should facilitate the proper fitting of measurements with a simple Interface.

School-Based Caries Prevention, Tooth Decay, and the Community Environment.

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Ruff, R R; Niederman, R

2018-04-01

The school and community context can contribute to inequity in child oral health. Whether the school and community affect the effectiveness of school-based caries prevention is unknown. The association between the school and community environment and dental caries, as well as their moderating effects with school-based caries prevention, was assessed using multilevel mixed-effects regression. Data were derived from a 6-y prospective cohort study of children participating in a school-based caries prevention program. For the school and community, living in a dental-shortage area and the proportion of children receiving free or reduced lunch were significantly related to an increased risk of dental caries at baseline. Caries prevention was associated with a significant per-visit decrease in the risk of untreated caries, but the rate of total caries experience increased over time. Caries prevention was more effective in children who had prior dental care at baseline and in schools with a higher proportion of low socioeconomic status students. There was significant variation across schools in the baseline prevalence of dental caries and the effect of prevention over time, although effects were modest. The school and community environment have a direct impact on oral health and moderate the association between school-based caries prevention and dental caries. Knowledge Transfer Statement: School-based caries prevention can be an effective means to reduce oral health inequity by embedding dental care within schools. However, the socioeconomic makeup of schools and characteristics of the surrounding community can affect the impact of school-based care.

Comparison of l₁-Norm SVR and Sparse Coding Algorithms for Linear Regression.

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Zhang, Qingtian; Hu, Xiaolin; Zhang, Bo

2015-08-01

Support vector regression (SVR) is a popular function estimation technique based on Vapnik's concept of support vector machine. Among many variants, the l1-norm SVR is known to be good at selecting useful features when the features are redundant. Sparse coding (SC) is a technique widely used in many areas and a number of efficient algorithms are available. Both l1-norm SVR and SC can be used for linear regression. In this brief, the close connection between the l1-norm SVR and SC is revealed and some typical algorithms are compared for linear regression. The results show that the SC algorithms outperform the Newton linear programming algorithm, an efficient l1-norm SVR algorithm, in efficiency. The algorithms are then used to design the radial basis function (RBF) neural networks. Experiments on some benchmark data sets demonstrate the high efficiency of the SC algorithms. In particular, one of the SC algorithms, the orthogonal matching pursuit is two orders of magnitude faster than a well-known RBF network designing algorithm, the orthogonal least squares algorithm.

A SOCIOLOGICAL ANALYSIS OF THE CHILDBEARING COEFFICIENT IN THE ALTAI REGION BASED ON METHOD OF FUZZY LINEAR REGRESSION

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Sergei Vladimirovich Varaksin

2017-06-01

Full Text Available Purpose. Construction of a mathematical model of the dynamics of childbearing change in the Altai region in 2000–2016, analysis of the dynamics of changes in birth rates for multiple age categories of women of childbearing age. Methodology. A auxiliary analysis element is the construction of linear mathematical models of the dynamics of childbearing by using fuzzy linear regression method based on fuzzy numbers. Fuzzy linear regression is considered as an alternative to standard statistical linear regression for short time series and unknown distribution law. The parameters of fuzzy linear and standard statistical regressions for childbearing time series were defined with using the built in language MatLab algorithm. Method of fuzzy linear regression is not used in sociological researches yet. Results. There are made the conclusions about the socio-demographic changes in society, the high efficiency of the demographic policy of the leadership of the region and the country, and the applicability of the method of fuzzy linear regression for sociological analysis.

A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach.

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Weichenthal, Scott; Ryswyk, Keith Van; Goldstein, Alon; Bagg, Scott; Shekkarizfard, Maryam; Hatzopoulou, Marianne

2016-04-01

Existing evidence suggests that ambient ultrafine particles (UFPs) (regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

A primer for biomedical scientists on how to execute model II linear regression analysis.

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Ludbrook, John

2012-04-01

1. There are two very different ways of executing linear regression analysis. One is Model I, when the x-values are fixed by the experimenter. The other is Model II, in which the x-values are free to vary and are subject to error. 2. I have received numerous complaints from biomedical scientists that they have great difficulty in executing Model II linear regression analysis. This may explain the results of a Google Scholar search, which showed that the authors of articles in journals of physiology, pharmacology and biochemistry rarely use Model II regression analysis. 3. I repeat my previous arguments in favour of using least products linear regression analysis for Model II regressions. I review three methods for executing ordinary least products (OLP) and weighted least products (WLP) regression analysis: (i) scientific calculator and/or computer spreadsheet; (ii) specific purpose computer programs; and (iii) general purpose computer programs. 4. Using a scientific calculator and/or computer spreadsheet, it is easy to obtain correct values for OLP slope and intercept, but the corresponding 95% confidence intervals (CI) are inaccurate. 5. Using specific purpose computer programs, the freeware computer program smatr gives the correct OLP regression coefficients and obtains 95% CI by bootstrapping. In addition, smatr can be used to compare the slopes of OLP lines. 6. When using general purpose computer programs, I recommend the commercial programs systat and Statistica for those who regularly undertake linear regression analysis and I give step-by-step instructions in the Supplementary Information as to how to use loss functions. © 2011 The Author. Clinical and Experimental Pharmacology and Physiology. © 2011 Blackwell Publishing Asia Pty Ltd.

Is congenital malformation a risk factor for caries development in Swedish adolescents?

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Julihn, Annika; Jansson, Pelle; Regnstrand, Tobias; Modéer, Thomas

2013-11-01

The aim of this study was to investigate whether various forms of congenital malformations are risk factors for approximal caries development in Swedish adolescents. This longitudinal register-based cohort study included all adolescents (n = 18 142) of 13 years of age who resided in the county of Stockholm, Sweden, in 2000. The cohort was followed until individuals were 19 years of age. Dental caries (decayed, missing and filled teeth/surfaces (DMFT/S)) were collected from the Public Health Care Administration in Stockholm. Data concerning pre- and perinatal factors and parental socio-demographic determinants were collected from Swedish National Registers. In a logistic regression analysis, neither congenital malformation nor any sub-group of congenital malformation registered at birth were significantly associated with an enhanced risk of approximal caries increment in adolescents between 13-19 years of age. The final multivariate logistic regression model, adjusted for possible maternal and family socio-demographic confounders, showed that congenital malformation of the 'circulatory system' was significantly associated with a decreased risk of approximal caries increment, between 13-19 years of age (OR = 0.33; 95% CI = 0.12-0.88). Congenital malformation should not be considered as a risk factor for approximal caries development in Swedish adolescents today. Noticeably, adolescents with congenital heart diseases exhibited less risk of developing approximal caries, which was probably related to prevention programs allocated to these children in Sweden.

Longitudinal associations between children’s dental caries and risk factors

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Chankanka, Oitip; Cavanaugh, Joseph E.; Levy, Steven M.; Marshall, Teresa A.; Warren, John J; Broffitt, Barbara; Kolker, Justine L.

2015-01-01

Dental caries is a common disease in children of all ages. It is desirable to know whether children with primary, mixed and permanent dentitions share risk factors for cavitated and non-cavitated caries. Objective To assess the longitudinal associations between caries outcomes and modifiable risk factors. Methods One hundred and fifty-six children in the Iowa Fluoride Study met inclusion criteria of three dental examinations and caries-related risk factor assessments preceding each examination. Surface-specific counts of new non-cavitated caries and cavitated caries at the primary (Exam 1: age 5), mixed (Exam 2: age 9) and permanent (Exam 3: age 13) dentition examinations were outcome variables. Explanatory variables were caries-related factors, including averaged beverage exposure frequencies, toothbrushing frequencies, and composite water fluoride levels collected from 3–5, 6–8, and 11–13 years, dentition category, socioeconomic status and gender. Generalized linear mixed models (GLMMs) were used to explore the relationships between new non-cavitated or cavitated caries and caries-related variables. Results Greater frequency of 100% juice exposure was significantly associated with fewer non-cavitated and cavitated caries surfaces. Greater toothbrushing frequency and high SES were significantly associated with fewer new non-cavitated caries. Children had significantly more new cavitated caries surfaces at the mixed dentition examination than at the primary and permanent dentition examinations. Conclusions There were common caries-related factors for more new non-cavitated caries across the three exams, including less frequent 100% juice exposure, lower toothbrushing frequency and lower socioeconomic status. Less frequent 100% juice exposures might be associated with higher exposures to several other cariogenic beverages. PMID:22320287

Dental caries

DEFF Research Database (Denmark)

Pitts, Nigel B; Zero, Domenick T; Marsh, Phil D

2017-01-01

Dental caries is a biofilm-mediated, sugar-driven, multifactorial, dynamic disease that results in the phasic demineralization and remineralization of dental hard tissues. Caries can occur throughout life, both in primary and permanent dentitions, and can damage the tooth crown and, in later life......, exposed root surfaces. The balance between pathological and protective factors influences the initiation and progression of caries. This interplay between factors underpins the classification of individuals and groups into caries risk categories, allowing an increasingly tailored approach to care. Dental...... caries is an unevenly distributed, preventable disease with considerable economic and quality-of-life burdens. The daily use of fluoride toothpaste is seen as the main reason for the overall decline of caries worldwide over recent decades. This Primer aims to provide a global overview of caries...

Linear regression analysis: part 14 of a series on evaluation of scientific publications.

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Schneider, Astrid; Hommel, Gerhard; Blettner, Maria

2010-11-01

Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the results should be interpreted. The reader should then be able to judge whether the method has been used correctly and interpret the results appropriately. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls, which are discussed here in detail. The reader is made aware of common errors of interpretation through practical examples. Both the opportunities for applying linear regression analysis and its limitations are presented.

Linear Regression on Sparse Features for Single-Channel Speech Separation

DEFF Research Database (Denmark)

Schmidt, Mikkel N.; Olsson, Rasmus Kongsgaard

2007-01-01

In this work we address the problem of separating multiple speakers from a single microphone recording. We formulate a linear regression model for estimating each speaker based on features derived from the mixture. The employed feature representation is a sparse, non-negative encoding of the speech...... mixture in terms of pre-learned speaker-dependent dictionaries. Previous work has shown that this feature representation by itself provides some degree of separation. We show that the performance is significantly improved when regression analysis is performed on the sparse, non-negative features, both...

Dental caries risk indicators in early childhood and their association with caries polarization in adolescence: a cross-sectional study.

Science.gov (United States)

Zemaitiene, Migle; Grigalauskiene, Ruta; Andruskeviciene, Vilija; Matulaitiene, Zivile Kristina; Zubiene, Jurate; Narbutaite, Julija; Slabsinskiene, Egle

2016-07-02

Based on the hypothesis that biological and social risks accumulate during life, it is important to identify possible dental caries risk indicators from the life course of early childhood and assess their association with caries polarization in adolescence. A cross-sectional design was applied to the study, and a multistage cluster sampling method used to draw a representative sample of 1063 18-year-old Lithuanian adolescents. The dental examinations were performed according to the methodology for oral status evaluation recommended by the World Health Organization. Parents of the participating adolescents completed a self-administered questionnaire about their children's life course during early childhood. The interdependence of characteristics was evaluated by chi-square (χ (2)) and Student's (t) criteria. A multivariate logistic regression model with the Significant Caries (SiC) index as an outcome was performed. The mean scores for the number of decayed, missing, and filled teeth (DMFT) and decayed teeth (DT) in the SiC positive group were higher than the corresponding values in the SiC negative group (6.14 [SD, 2.30] and 1.67 [SD, 2.02] vs 1.28 [SD, 1.11] and 0.34 [SD, 0.69], p caries risk indicators were identified that were independently associated with a SiC positive outcome: gender(OR = 1.32 [95 % CI: 1.01-1.73]), earlier eruption of the first primary tooth(OR = 1.43 [95 % CI: 1.03-1.97]), and past caries experience in the primary dentition (OR = 1.62 [95 % CI:1.22-2.14]). These study findings provide reliable evidence that gender, earlier eruption of the first primary tooth, and past caries experience in the primary dentition should be considered to be dental caries risk indicators and may have an adverse effect on caries polarization in adolescence.

The Relationship between Economic Growth and Money Laundering – a Linear Regression Model

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Daniel Rece

2009-09-01

Full Text Available This study provides an overview of the relationship between economic growth and money laundering modeled by a least squares function. The report analyzes statistically data collected from USA, Russia, Romania and other eleven European countries, rendering a linear regression model. The study illustrates that 23.7% of the total variance in the regressand (level of money laundering is “explained” by the linear regression model. In our opinion, this model will provide critical auxiliary judgment and decision support for anti-money laundering service systems.

Inverse estimation of multiple muscle activations based on linear logistic regression.

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Sekiya, Masashi; Tsuji, Toshiaki

2017-07-01

This study deals with a technology to estimate the muscle activity from the movement data using a statistical model. A linear regression (LR) model and artificial neural networks (ANN) have been known as statistical models for such use. Although ANN has a high estimation capability, it is often in the clinical application that the lack of data amount leads to performance deterioration. On the other hand, the LR model has a limitation in generalization performance. We therefore propose a muscle activity estimation method to improve the generalization performance through the use of linear logistic regression model. The proposed method was compared with the LR model and ANN in the verification experiment with 7 participants. As a result, the proposed method showed better generalization performance than the conventional methods in various tasks.

Defectos del esmalte, caries en dentición primaria, fuentes de fluoruro y su relación con caries en dientes permanentes Enamel defects, caries in primary dentition and fluoride sources: relationship with caries in permanent teeth

Directory of Open Access Journals (Sweden)

Ana Alicia Vallejos-Sánchez

2007-06-01

in 4 elementary schools in Campeche, Mexico through the use of a questionnaire for the mothers and an oral examination in the children. The dependent variable was the prevalence of caries in permanent dentition. Results: The mean number of decay, missing or filling teeth in primary dentition (dmft and in permanent dentition (DMFT was 2.48 (2.82 (deft > 0 = 58.9% and 0.40 (0.98 (DMFT > 0 = 18.2%, respectively. The significant caries index (SiC, which is calculated in deciduous dentition, was 5.85 for 6 year-olds. Multivariate logistic regression adjusted for variables related to fluoride exposure revealed that older age (OR = 2.99, a deft of > 0 (OR = 5.46, and lower maternal educational level (OR = 1.57 were significantly associated with a higher number of dental caries in permanent teeth. An interaction between sex and enamel defects was also found. Conclusions: The number of dental caries in both primary and permanent dentitions was relatively smaller than that found in prior studies performed in Mexican populations. The results confirm that the presence of caries in primary dentition is strongly associated with caries in permanent dentition. No significant relationship was found between fluoride exposure and dental caries in permanent dentition.

Data Transformations for Inference with Linear Regression: Clarifications and Recommendations

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Pek, Jolynn; Wong, Octavia; Wong, C. M.

2017-01-01

Data transformations have been promoted as a popular and easy-to-implement remedy to address the assumption of normally distributed errors (in the population) in linear regression. However, the application of data transformations introduces non-ignorable complexities which should be fully appreciated before their implementation. This paper adds to…

Low sugar nutrition policies and dental caries: A study of primary schools in South Auckland.

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Thornley, Simon; Marshall, Roger; Reynolds, Gary; Koopu, Pauline; Sundborn, Gerhard; Schofield, Grant

2017-05-01

The study assessed whether a healthy food policy implemented in one school, Yendarra Primary, situated in a socio-economically deprived area of South Auckland, had improved student oral health by comparing dental caries levels with students of similar schools in the same region with no such policy. Records of caries of the primary and adult teeth were obtained between 2007 and 2014 for children attending Yendarra, and were compared to those of eight other public schools in the area, with a similar demographic profile. Children were selected between the ages of 8 and 11 years. Linear regression models were used to estimate the strength of association between attending Yendarra school and dental caries. During the study period, 3813 records were obtained of children who attended dental examinations and the schools of interest. In a linear model, mean number of carious primary and adult teeth were 0.37 lower (95% confidence interval: 0.09-0.65) in Yendarra school children, compared to those in other schools, after adjustment for confounders. Pacific students had higher numbers of carious teeth (adjusted β coefficient: 0.25; 95% confidence interval: 0.03-0.46) than Māori. This nutrition policy, implemented in a school in the poorest region of South Auckland, which restricted sugary food and drink availability, was associated with a marked positive effect on the oral health of students, compared to students in surrounding schools. We recommend that such policies are a useful means of improving child oral health. © 2017 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Alpins and thibos vectorial astigmatism analyses: proposal of a linear regression model between methods

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Giuliano de Oliveira Freitas

2013-10-01

Full Text Available PURPOSE: To determine linear regression models between Alpins descriptive indices and Thibos astigmatic power vectors (APV, assessing the validity and strength of such correlations. METHODS: This case series prospectively assessed 62 eyes of 31 consecutive cataract patients with preoperative corneal astigmatism between 0.75 and 2.50 diopters in both eyes. Patients were randomly assorted among two phacoemulsification groups: one assigned to receive AcrySof®Toric intraocular lens (IOL in both eyes and another assigned to have AcrySof Natural IOL associated with limbal relaxing incisions, also in both eyes. All patients were reevaluated postoperatively at 6 months, when refractive astigmatism analysis was performed using both Alpins and Thibos methods. The ratio between Thibos postoperative APV and preoperative APV (APVratio and its linear regression to Alpins percentage of success of astigmatic surgery, percentage of astigmatism corrected and percentage of astigmatism reduction at the intended axis were assessed. RESULTS: Significant negative correlation between the ratio of post- and preoperative Thibos APVratio and Alpins percentage of success (%Success was found (Spearman's ρ=-0.93; linear regression is given by the following equation: %Success = (-APVratio + 1.00x100. CONCLUSION: The linear regression we found between APVratio and %Success permits a validated mathematical inference concerning the overall success of astigmatic surgery.

On the null distribution of Bayes factors in linear regression

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We show that under the null, the 2 log (Bayes factor) is asymptotically distributed as a weighted sum of chi-squared random variables with a shifted mean. This claim holds for Bayesian multi-linear regression with a family of conjugate priors, namely, the normal-inverse-gamma prior, the g-prior, and...

Implementing fuzzy polynomial interpolation (FPI and fuzzy linear regression (LFR

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Maria Cristina Floreno

1996-05-01

Full Text Available This paper presents some preliminary results arising within a general framework concerning the development of software tools for fuzzy arithmetic. The program is in a preliminary stage. What has been already implemented consists of a set of routines for elementary operations, optimized functions evaluation, interpolation and regression. Some of these have been applied to real problems.This paper describes a prototype of a library in C++ for polynomial interpolation of fuzzifying functions, a set of routines in FORTRAN for fuzzy linear regression and a program with graphical user interface allowing the use of such routines.

Application of range-test in multiple linear regression analysis in ...

African Journals Online (AJOL)

Application of range-test in multiple linear regression analysis in the presence of outliers is studied in this paper. First, the plot of the explanatory variables (i.e. Administration, Social/Commercial, Economic services and Transfer) on the dependent variable (i.e. GDP) was done to identify the statistical trend over the years.

Evaluation of linear regression techniques for atmospheric applications: the importance of appropriate weighting

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C. Wu

2018-03-01

Full Text Available Linear regression techniques are widely used in atmospheric science, but they are often improperly applied due to lack of consideration or inappropriate handling of measurement uncertainty. In this work, numerical experiments are performed to evaluate the performance of five linear regression techniques, significantly extending previous works by Chu and Saylor. The five techniques are ordinary least squares (OLS, Deming regression (DR, orthogonal distance regression (ODR, weighted ODR (WODR, and York regression (YR. We first introduce a new data generation scheme that employs the Mersenne twister (MT pseudorandom number generator. The numerical simulations are also improved by (a refining the parameterization of nonlinear measurement uncertainties, (b inclusion of a linear measurement uncertainty, and (c inclusion of WODR for comparison. Results show that DR, WODR and YR produce an accurate slope, but the intercept by WODR and YR is overestimated and the degree of bias is more pronounced with a low R2 XY dataset. The importance of a properly weighting parameter λ in DR is investigated by sensitivity tests, and it is found that an improper λ in DR can lead to a bias in both the slope and intercept estimation. Because the λ calculation depends on the actual form of the measurement error, it is essential to determine the exact form of measurement error in the XY data during the measurement stage. If a priori error in one of the variables is unknown, or the measurement error described cannot be trusted, DR, WODR and YR can provide the least biases in slope and intercept among all tested regression techniques. For these reasons, DR, WODR and YR are recommended for atmospheric studies when both X and Y data have measurement errors. An Igor Pro-based program (Scatter Plot was developed to facilitate the implementation of error-in-variables regressions.

Evaluation of linear regression techniques for atmospheric applications: the importance of appropriate weighting

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Wu, Cheng; Zhen Yu, Jian

2018-03-01

Linear regression techniques are widely used in atmospheric science, but they are often improperly applied due to lack of consideration or inappropriate handling of measurement uncertainty. In this work, numerical experiments are performed to evaluate the performance of five linear regression techniques, significantly extending previous works by Chu and Saylor. The five techniques are ordinary least squares (OLS), Deming regression (DR), orthogonal distance regression (ODR), weighted ODR (WODR), and York regression (YR). We first introduce a new data generation scheme that employs the Mersenne twister (MT) pseudorandom number generator. The numerical simulations are also improved by (a) refining the parameterization of nonlinear measurement uncertainties, (b) inclusion of a linear measurement uncertainty, and (c) inclusion of WODR for comparison. Results show that DR, WODR and YR produce an accurate slope, but the intercept by WODR and YR is overestimated and the degree of bias is more pronounced with a low R2 XY dataset. The importance of a properly weighting parameter λ in DR is investigated by sensitivity tests, and it is found that an improper λ in DR can lead to a bias in both the slope and intercept estimation. Because the λ calculation depends on the actual form of the measurement error, it is essential to determine the exact form of measurement error in the XY data during the measurement stage. If a priori error in one of the variables is unknown, or the measurement error described cannot be trusted, DR, WODR and YR can provide the least biases in slope and intercept among all tested regression techniques. For these reasons, DR, WODR and YR are recommended for atmospheric studies when both X and Y data have measurement errors. An Igor Pro-based program (Scatter Plot) was developed to facilitate the implementation of error-in-variables regressions.

Research on the multiple linear regression in non-invasive blood glucose measurement.

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Zhu, Jianming; Chen, Zhencheng

2015-01-01

A non-invasive blood glucose measurement sensor and the data process algorithm based on the metabolic energy conservation (MEC) method are presented in this paper. The physiological parameters of human fingertip can be measured by various sensing modalities, and blood glucose value can be evaluated with the physiological parameters by the multiple linear regression analysis. Five methods such as enter, remove, forward, backward and stepwise in multiple linear regression were compared, and the backward method had the best performance. The best correlation coefficient was 0.876 with the standard error of the estimate 0.534, and the significance was 0.012 (sig. regression equation was valid. The Clarke error grid analysis was performed to compare the MEC method with the hexokinase method, using 200 data points. The correlation coefficient R was 0.867 and all of the points were located in Zone A and Zone B, which shows the MEC method provides a feasible and valid way for non-invasive blood glucose measurement.

The Predisposing Factors between Dental Caries and Deviations from Normal Weight.

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Chopra, Amandeep; Rao, Nanak Chand; Gupta, Nidhi; Vashisth, Shelja; Lakhanpal, Manav

2015-04-01

Dental caries and deviations from normal weight are two conditions which share several broadly predisposing factors. So it's important to understand any relationship between dental state and body weight if either is to be managed appropriately. The study was done to find out the correlation between body mass index (BMI), diet, and dental caries among 12-15-year-old schoolgoing children in Panchkula District. A multistage sample of 12-15-year-old school children (n = 810) in Panchkula district, Haryana was considered. Child demographic details and diet history for 5 days was recorded. Data regarding dental caries status was collected using World Health Organization (1997) format. BMI was calculated and categorized according to the World Health Organization classification system for BMI. The data were subjected to statistical analysis using chi-square test and binomial regression developed using the Statistical Package for Social Sciences (SPSS) 20.0. The mean Decayed Missing Filled Teeth (DMFT) score was found to be 1.72 with decayed, missing, and filled teeth to be 1.22, 0.04, and 0.44, respectively. When the sample was assessed based on type of diet, it was found that vegetarians had higher mean DMFT (1.72) as compared to children having mixed diet. Overweight children had highest DMFT (3.21) which was followed by underweight (2.31) and obese children (2.23). Binomial regression revealed that females were 1.293 times at risk of developing caries as compared to males. Fair and poor Simplified-Oral Hygiene Index (OHI-S) showed 3.920 and 4.297 times risk of developing caries as compared to good oral hygiene, respectively. Upper high socioeconomic status (SES) is at most risk of developing caries. Underweight, overweight, and obese are at 2.7, 2.5, and 3 times risk of developing caries as compared to children with normal BMI, respectively. Dental caries and deviations from normal weight are two conditions which share several broadly predisposing factors such as diet

Estimating Loess Plateau Average Annual Precipitation with Multiple Linear Regression Kriging and Geographically Weighted Regression Kriging

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Qiutong Jin

2016-06-01

Full Text Available Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK and geographically weighted regression Kriging (GWRK methods were employed using precipitation data from the period 1980–2010 from 435 meteorological stations. The predictors in regression Kriging were selected by stepwise regression analysis from many auxiliary environmental factors, such as elevation (DEM, normalized difference vegetation index (NDVI, solar radiation, slope, and aspect. All predictor distribution maps had a 500 m spatial resolution. Validation precipitation data from 130 hydrometeorological stations were used to assess the prediction accuracies of the MLRK and GWRK approaches. Results showed that both prediction maps with a 500 m spatial resolution interpolated by MLRK and GWRK had a high accuracy and captured detailed spatial distribution data; however, MLRK produced a lower prediction error and a higher variance explanation than GWRK, although the differences were small, in contrast to conclusions from similar studies.

Estimate of DMFT index using teeth most affected by dental caries in twelve-year-old children.

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Pereira, Stela Márcia; Tagliaferro, Elaine Pereira da Silva; Cortellazzi, Karine Laura; Ambrosano, Gláucia Maria Bovi; Mialhe, Fábio Luiz; Meneghim, Marcelo de Castro; Pereira, Antonio Carlos

2009-02-01

The objective of the study was to develop regression models to describe the epidemiological profile of dental caries in 12-year-old children in an area of low prevalence of caries. Two distinct random probabilistic samples of schoolchildren (n=1,763) attending public and private schools in Piracicaba, Southeastern Brazil, were studied. Regression models were estimated as a function of the most affected teeth using data collected in 2005 and were validated using a 2001 database. The mean (SD) DMFT index was 1.7 (2.08) in 2001 and the regression equations estimated a DMFT index of 1.67 (1.98), which corresponds to 98.2% of the DMFT index in 2001. The study provided detailed data on the caries profile in 12-year-old children by using an updated analytical approach. Regression models can be an accurate and feasible method that can provide valuable information for the planning and evaluation of oral health services.

Unstimulated Saliva-Related Caries Risk Factors in Individuals with Cystic Fibrosis: A Cross-Sectional Analysis of Unstimulated Salivary Flow, pH, and Buffering Capacity.

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Alkhateeb, Alaa A; Mancl, Lloyd A; Presland, Richard B; Rothen, Marilynn L; Chi, Donald L

2017-01-01

Salivary flow rate, pH, and buffering capacity are associated with dental caries, but studies from the cystic fibrosis (CF) literature are inconclusive regarding these salivary factors and caries. The aim of this study was to evaluate these factors and their associations with dental caries in individuals with CF. Unstimulated whole saliva was collected from individuals aged 6-20 years at Seattle Children's Hospital CF Clinic, USA (n = 83). Salivary flow rate was measured in milliliters per minute. Salivary pH was assessed using a laboratory pH meter. Buffering capacity was assessed by titration with HCl. The outcome measure was caries prevalence, defined as the number of decayed, missing, or filled primary and permanent tooth surfaces. Spearman's rank correlation coefficient and the t test were used to test for bivariate associations. Multiple variable linear regression models were used to (1) run confounder-adjusted analyses and (2) assess for potential interactions. There was no significant association between salivary flow rate or buffering capacity and caries prevalence. There was a significant negative association between salivary pH and caries prevalence, but this association was no longer significant after adjusting for age. There was no significant interaction between salivary flow rate and buffering capacity or between antibiotic use and the 3 salivary factors. Our results indicate that unstimulated salivary factors are not associated with dental caries prevalence in individuals with CF. Future studies should investigate other potential saliva-related caries risk factors in individuals with CF such as cariogenic bacteria levels, salivary host defense peptide levels, and medication use. © 2016 S. Karger AG, Basel.

Caries experience among children with type 1 diabetes in Kuwait.

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Akpata, Enosakhare Samuel; Alomari, Qasem; Mojiminiyi, Olusequn A; Al-Sanae, Hala

2012-01-01

The purpose of this study was to determine the association among type 1 diabetes mellitus (DM), caries experience, and salivary glucose in 12- to 15-year-olds in Kuwait. A cross-sectional design was chosen involving 53 DM patients and 53 nondiabetic controls, group-matched by age and sex to the experimental group. The DM patients comprised 2 groups: (1) 14 controlled DM children (glycated haemoglobin, HbA1c=8). The children's caries experience, at the precavitation and cavitation diagnostic threshold, was measured. In addition, their frequency of sugar consumption, plaque index, salivary flow rate, buffering capacity, as well as mutans streptococci, lactobacilli, and yeast counts were recorded. The DM children had significantly higher caries experience both at precavitation and cavitation diagnostic thresholds, than the control group. Multiple logistic regression analysis showed age, frequency of sugar consumption, and resting salivary flow rate to be significantly associated with high caries experience among the diabetic children. Caries experience was significantly higher in children with type 1 diabetes than in nondiabetic controls.

Investigation of linear regression of EPR dosimetric signal of the man tooth enamel

International Nuclear Information System (INIS)

Pivovarov, S.P.; Rukhin, A.B.; Zhakparov, R.K.; Vasilevskaya, L.A.

2001-01-01

The experimental relations of the EPR radiation signal in samples of man tooth enamel of three donors of different age up to doses 1350 Gy are examined. To all of them the linear regression is applicable. The considerable errors leading to apparent non-linearity are eliminated most. (author)

Inequalities of caries experience in Nevada youth expressed by DMFT index vs. Significant Caries Index (SiC) over time.

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Ditmyer, Marcia; Dounis, Georgia; Mobley, Connie; Schwarz, Eli

2011-04-05

With the increasingly polarized distribution of dental caries among children and adolescents, the usual DMFT measure has become a less meaningful population descriptor. To re-focus on identifying the high caries prevalence group the Significant Caries Index (SiC) was created. The aims of this study were to analyze the prevalence and severity of dental caries in Nevada youth over a period of eight years and to compare its expression by means of DMFT and SiC; analyze the caries trends in the population and their underlying factors, and determine whether Nevada youth were at risk for significantly high levels of dental caries. Retrospective data was analyzed from a series of sequential, standardized oral health surveys across eight years (2001/2002-2008/2009) that included over 62,000 examinations of adolescents 13-19 years of age, attending public/private Nevada schools. Mean Decayed-Missing-Filled Teeth index (DMFT) and Significant Caries Index (SiC) were subsequently computed for each academic year. Descriptive statistics were reported for analysis of comparative DMFT and SiC scores in relation to age, gender, racial background, and residence in a fluoridated/non-fluoridated community. Logistic regression analysis was used to analyze the differential impact of the variables on the probability of being in the high caries prevalence group. Comparison of students' mean DMFT to National (NHANES) data confirmed that dental caries remains a common chronic disease among Nevada youth, presenting higher prevalence rates and greater mean scores than the national averages. Downward trends were found across all demographics compared between survey years 1 and 6 with the exception of survey year 3. An upward trend began in survey year six. Over time, the younger group displayed an increasing proportion of caries free individuals while a decreasing proportion was found among older examinees. As expected, the mean SiC score was significantly higher than DMFT scores within each

Linear regression metamodeling as a tool to summarize and present simulation model results.

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Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M

2013-10-01

Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

Optimal choice of basis functions in the linear regression analysis

International Nuclear Information System (INIS)

Khotinskij, A.M.

1988-01-01

Problem of optimal choice of basis functions in the linear regression analysis is investigated. Step algorithm with estimation of its efficiency, which holds true at finite number of measurements, is suggested. Conditions, providing the probability of correct choice close to 1 are formulated. Application of the step algorithm to analysis of decay curves is substantiated. 8 refs

LINEAR REGRESSION MODEL ESTİMATİON FOR RIGHT CENSORED DATA

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Ersin Yılmaz

2016-05-01

Full Text Available In this study, firstly we will define a right censored data. If we say shortly right-censored data is censoring values that above the exact line. This may be related with scaling device. And then  we will use response variable acquainted from right-censored explanatory variables. Then the linear regression model will be estimated. For censored data’s existence, Kaplan-Meier weights will be used for  the estimation of the model. With the weights regression model  will be consistent and unbiased with that.   And also there is a method for the censored data that is a semi parametric regression and this method also give  useful results  for censored data too. This study also might be useful for the health studies because of the censored data used in medical issues generally.

Caries in patients with non-insulin-dependent diabetes mellitus.

Science.gov (United States)

Collin, H L; Uusitupa, M; Niskanen, L; Koivisto, A M; Markkanen, H; Meurman, J H

1998-06-01

The purpose of this study was to investigate the prevalence and risk factors of dental caries in patients with non-insulin-dependent diabetes mellitus and to determine whether these factors are associated with metabolic control and vascular complications of the disease. Both the occurrence of caries, acidogenic oral bacteria, and yeasts and salivary flow were studied in 25 patients with non-insulin-dependent diabetes mellitus whose diagnosis had been set 13 to 14 years earlier and in whom the metabolic evolution of the disease was well established. The patients' glycemic control was determined by means of analysis of the blood hemoglobin A1C concentration at the time of dental examination. The control group consisted of 40 nondiabetic subjects in the same age group. Decayed, missing, and filled teeth indices and numbers of surfaces with caries, filled surfaces, and root caries were determined by means of clinical dental caries examination. Stimulated salivary flow was measured, and levels of Streptococcus mutans, lactobacilli, and yeasts were analyzed. The median hemoglobin A1C concentration of the patients was 8.6%, which indicates poor metabolic control of diabetes. No association was found between the metabolic control of disease and dental caries. The occurrence of dental caries was not increased in the patients with non-insulin-dependent diabetes mellitus in comparison with the control subjects. The counts of acidogenic microbes and yeasts did not differ statistically significantly between the groups. There was no association of caries with the prevalence of coronary artery disease or hypertension in either the patients or the control subjects. In a stepwise logistic regression model, a salivary flow of at least 0.8 ml/min was related to the occurrence of dental caries in patients with non-insulin-dependent diabetes mellitus, whereas negligence with respect to dental care was the most important risk predictor in the control group. Our results showed no effect

Incidence of dental caries in primary dentition and risk factors: a longitudinal study.

Science.gov (United States)

Corrêa-Faria, Patrícia; Paixão-Gonçalves, Suzane; Paiva, Saul Martins; Pordeus, Isabela Almeida

2016-05-20

The objectives of this prospective, longitudinal, population-based study were to estimate the incidence of dental caries in the primary dentition, identify risk factors and determine the proportion of children receiving dental treatment, through a two-year follow up. The first dental exam was conducted with 381 children aged one to five years, at health centers during immunization campaigns; 184 of them had dental caries and 197 had no caries experience. The second exam was carried out two years later at a nursery or at home with the same individuals who participated in the first exam. The diagnosis of dental caries was performed using the dmft criteria. Parents were interviewed regarding socioeconomic indicators. Descriptive, bivariate and adjusted Poisson regression analyses were performed. Among the 381 children, 234 were reexamined after two years (non-exposed: 139; exposed: 95). The overall incidence of dental caries was 46.6%. The greatest incidence of dental caries was found in the group of children with previous caries experience (61.1%). Among the children without dental caries in the first exam, 36.7% exhibited caries in the second exam. The majority of children (72.6%) received no treatment for carious lesions in the two-year interval between examinations. Children with previous dental caries (RR: 1.52, 95%CI: 1.12-2.05) had a greater risk of developing new lesions, compared with the children without previous dental caries. The incidence of dental caries was high and most of children's caries were untreated. Previous caries experience is a risk factor for developing new carious lesions in children.

Improving sub-pixel imperviousness change prediction by ensembling heterogeneous non-linear regression models

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Drzewiecki Wojciech

2016-12-01

Full Text Available In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques.

Association between developmental defects of enamel and dental caries: A systematic review and meta-analysis.

Science.gov (United States)

Vargas-Ferreira, F; Salas, M M S; Nascimento, G G; Tarquinio, S B C; Faggion, C M; Peres, M A; Thomson, W M; Demarco, F F

2015-06-01

Dental caries is the main problem oral health and it is not well established in the literature if the enamel defects are a risk factor for its development. Studies have reported a potential association between developmental defects enamel (DDE) and dental caries occurrence. We investigated the association between DDE and caries in permanent dentition of children and teenagers. A systematic review was carried out using four databases (Pubmed, Web of Science, Embase, and Science Direct), which were searched from their earliest records until December 31, 2014. Population-based studies assessing differences in dental caries experience according to the presence of enamel defects (and their types) were included. PRISMA guidelines for reporting systematic reviews were followed. Meta-analysis was performed to assess the pooled effect, and meta-regression was carried out to identify heterogeneity sources. From the 2558 initially identified papers, nine studies fulfilled all inclusion criteria after checking the titles, abstracts, references, and complete reading. Seven of them were included in the meta-analysis with random model. A positive association between enamel defects and dental caries was identified; meta-analysis showed that individuals with DDE had higher pooled odds of having dental caries experience [OR 2.21 (95% CI 1.3; 3.54)]. Meta-regression analysis demonstrated that adjustment for sociodemographic factors, countries' socioeconomic status, and bias (quality of studies) explained the high heterogeneity observed. A higher chance of dental caries should be expected among individuals with enamel defects. Copyright © 2015 Elsevier Ltd. All rights reserved.

Non-operative anti-caries agents and dental caries increment among adults at high caries risk: a retrospective cohort study

OpenAIRE

Chaffee, Benjamin W.; Cheng, Jing; Featherstone, John DB

2015-01-01

Background Consensus guidelines support non-operative preventives for dental caries management; yet, their use in practice is far from universal. The purpose of this study was to evaluate the effectiveness of non-operative anti-caries agents in caries prevention among high caries risk adults at a university clinic where risk-based caries management is emphasized. Methods This retrospective observational study drew data from the electronic patient records of non-edentulous adult patients deeme...

Weighted functional linear regression models for gene-based association analysis.

Science.gov (United States)

Belonogova, Nadezhda M; Svishcheva, Gulnara R; Wilson, James F; Campbell, Harry; Axenovich, Tatiana I

2018-01-01

Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with P models. Moreover, we found an association between diastolic blood pressure and the VMP1 gene (P = 8.18×10-6), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had P = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at https://cran.r-project.org/web/packages/FREGAT/index.html.

Distributed Monitoring of the R(sup 2) Statistic for Linear Regression

Science.gov (United States)

Bhaduri, Kanishka; Das, Kamalika; Giannella, Chris R.

2011-01-01

The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and one or more dependent target variables. This problem becomes challenging for large scale data in a distributed computing environment when only a subset of instances is available at individual nodes and the local data changes frequently. Data centralization and periodic model recomputation can add high overhead to tasks like anomaly detection in such dynamic settings. Therefore, the goal is to develop techniques for monitoring and updating the model over the union of all nodes data in a communication-efficient fashion. Correctness guarantees on such techniques are also often highly desirable, especially in safety-critical application scenarios. In this paper we develop DReMo a distributed algorithm with very low resource overhead, for monitoring the quality of a regression model in terms of its coefficient of determination (R2 statistic). When the nodes collectively determine that R2 has dropped below a fixed threshold, the linear regression model is recomputed via a network-wide convergecast and the updated model is broadcast back to all nodes. We show empirically, using both synthetic and real data, that our proposed method is highly communication-efficient and scalable, and also provide theoretical guarantees on correctness.

Inequality in dental caries distribution at noncavitated and cavitated thresholds in preschool children.

Science.gov (United States)

Piovesan, Chaiana; Tomazoni, Fernanda; Del Fabro, Joana; Buzzati, Bruna Cássia Schmidt; Mendes, Fausto Medeiros; Antunes, José Leopoldo Ferreira; Ardenghi, Thiago Machado

2014-01-01

To evaluate the inequality in dental caries distribution according to different thresholds assessed using the International Caries Detection and Assessment System (ICDAS) and to investigate the associations of socioeconomic factors with caries lesions at both noncavitated and cavitated thresholds. Study subjects were recruited in Santa Maria, Brazil, during the National Day of Children's Vaccination, and 639 children aged 12-59 months were included. Fifteen calibrated examiners performed the examinations using ICDAS criteria. Inequality in dental caries distribution was measured using the Gini coefficient, and the Significant Caries Index was calculated for several thresholds of ICDAS. Poisson regression analysis was used to assess the associations of socioeconomic factors with the highest caries scores. The inequality in the distribution of dental caries was lower when precavitated caries were included; the Gini coefficient decreased from 0.77 to 0.60 when noncavitated caries lesions were included in the analyses. Moreover, the inequalities were higher in the younger than in the older children for all thresholds. Socioeconomic factors were significantly (P < 0.001) associated with caries when an ICDAS score of 3 was considered as the cut-off point. Children whose mothers did not complete primary education (P < 0.001) and those with low household income (P < 0.001) were more likely to have increased dental caries. Caries lesions were more equally distributed when noncavitated lesions were included in the dental survey. Socioeconomic factors are found to be associated with the inequalities in caries distribution in this age group. © 2013 American Association of Public Health Dentistry.

Genomic prediction based on data from three layer lines using non-linear regression models

NARCIS (Netherlands)

Huang, H.; Windig, J.J.; Vereijken, A.; Calus, M.P.L.

2014-01-01

Background - Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. Methods - In an attempt to alleviate

How different do visuo-tactile criteria assess caries lesions activity status on occlusal surfaces?

DEFF Research Database (Denmark)

Floriano, I; Bonini, G C; Matos, R

2015-01-01

the International Caries Detection and Assessment System with an additional criteria--Lesion Activity Assessment (ICDAS + LAA), and a reference examiner classified lesions regarding plaque stagnation, colour, lustre, cavities, depth and texture. Logistic regressions were used to test associations. For analyses, we...... lesions present lustre. CONCLUSION: Most clinical signs associated with active caries lesions were similar, but texture and severity tend to have a greater importance when using ICDAS + LAA for distinguishing caries activity status. Attention should be given to differences due to texture and lustre when...

A method for fitting regression splines with varying polynomial order in the linear mixed model.

Science.gov (United States)

Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W

2006-02-15

The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

Computer software for linear and nonlinear regression in organic NMR

International Nuclear Information System (INIS)

Canto, Eduardo Leite do; Rittner, Roberto

1991-01-01

Calculation involving two variable linear regressions, require specific procedures generally not familiar to chemist. For attending the necessity of fast and efficient handling of NMR data, a self explained and Pc portable software has been developed, which allows user to produce and use diskette recorded tables, containing chemical shift or any other substituent physical-chemical measurements and constants (σ T , σ o R , E s , ...)

Do clinical and translational science graduate students understand linear regression? Development and early validation of the REGRESS quiz.

Science.gov (United States)

Enders, Felicity

2013-12-01

Although regression is widely used for reading and publishing in the medical literature, no instruments were previously available to assess students' understanding. The goal of this study was to design and assess such an instrument for graduate students in Clinical and Translational Science and Public Health. A 27-item REsearch on Global Regression Expectations in StatisticS (REGRESS) quiz was developed through an iterative process. Consenting students taking a course on linear regression in a Clinical and Translational Science program completed the quiz pre- and postcourse. Student results were compared to practicing statisticians with a master's or doctoral degree in statistics or a closely related field. Fifty-two students responded precourse, 59 postcourse , and 22 practicing statisticians completed the quiz. The mean (SD) score was 9.3 (4.3) for students precourse and 19.0 (3.5) postcourse (P REGRESS quiz was internally reliable (Cronbach's alpha 0.89). The initial validation is quite promising with statistically significant and meaningful differences across time and study populations. Further work is needed to validate the quiz across multiple institutions. © 2013 Wiley Periodicals, Inc.

Dental caries and weight among children in Nuuk, Greenland, at school entry.

Science.gov (United States)

Madsen, Signe Sloth; Wetterstrand, Vicky Jenny Rebecka; Pedersen, Michael Lynge

2017-01-01

To explore the possible association between weight class and prevalence of caries among children born 2005-2007, living in Nuuk, Greenland, at time of school entry. A cross-sectional register study based on data from electronic medical records(EMR) and oral health data from public health and dental care facilities. Data from routine examinations of children at time of primary school entry, including height and weight, were obtained from the EMRs. Dental charts recording oral health and caries were collected from public dental healthcare service. The prevalence of caries was calculated as the proportion of included children with dft score (decayed and/or filled non-permanent teeth) ≥1. 55%(373/681) had relevant data recorded in EMRs and dental charts, and could be included in the study. The prevalence of dental caries was 57.1%(213/373). The prevalence of caries increased with higher weight class,but no statistically significant trend was observed(p=0.063). Increasing prevalence of caries with increasing weight class was observed in this study. A linear trend could not be confirmed statistically. The high prevalence of caries and overweight indicate the need for continued focus on preventative initiatives and monitoring. A combined strategy targeting both caries and overweight may be considered.

Total Breast-Feeding Duration and Dental Caries in Healthy Urban Children.

Science.gov (United States)

Wong, Peter D; Birken, Catherine S; Parkin, Patricia C; Venu, Isvarya; Chen, Yang; Schroth, Robert J; Maguire, Jonathon L

2017-04-01

To determine if there is an association between longer breast-feeding duration and dental caries in healthy urban children. We conducted a cross-sectional study of urban children aged 1 to 6 years recruited through The Applied Research Group for Kids (TARGet Kids!) practice-based research network between September 2011 and August 2013. The main outcome measure was parental report of dental caries. The adjusted predicted probability of dental caries was 7%, 8%, 11%, and 16% with total duration of breast-feeding duration of 12, 18, 24, and 36 months, respectively. In the adjusted logistic regression analyses, relative to breast-feeding 0 to 5 months, the odds of dental caries with total breast-feeding duration >24 months was 2.75 (95% confidence interval 1.61-4.72). Among healthy urban children, longer breast-feeding duration was associated with higher odds of dental caries. These findings support heightened awareness and enhanced anticipatory guidance for preventive dental care, particularly among children who breast-feed beyond 2 years of age. Copyright © 2016 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Association between obesity and dental caries in a group of preschool children in Mexico.

Science.gov (United States)

Vázquez-Nava, Francisco; Vázquez-Rodríguez, Eliza Mireya; Saldívar-González, Atenógenes Humberto; Lin-Ochoa, Dolores; Martinez-Perales, Gerardo Manuel; Joffre-Velázquez, Víctor Manuel

2010-01-01

The aim of this study was to determine the association between obesity and caries by utilizing the data of a cohort of preschool children aged 4-5 years. Data were obtained from a cohort of 1,160 children. Dental caries detection was performed according to the World Health Organization criteria. The caries index was measured as the number of decayed (d), extracted (e), and filled (f) teeth (t) (deft), or surfaces (defs). The body mass index (BMI) in units of kg/m2 was determined, and children were categorized according to age- and gender-specific criteria as normal weight (5th-85th percentile), at-risk overweight (> or = 85th- or = 95th percentile). Odds ratios were determined for at-risk overweight and overweight children using logistic regression. The prevalence of dental caries was 17.9 percent. A slightly higher percentage of dental caries was found in boys (19.6 percent) than in girls (16.4 percent). From the total sample, the mean BMI was 17.10 +/- 3.83. Approximately 53.7 percent of children were classified as normal weight, 14.2 percent as at-risk overweight, and 32.1 percent as overweight. At-risk overweight children were higher among girls (17.1 percent) than among boys (11.3 percent). When adjusted for covariates, the logistic regression model showed that there was a significant association between at-risk overweight children (P Obesity appears to be associated with dental caries in the primary dentition of preschool Mexican children.

Non-operative anti-caries agents and dental caries increment among adults at high caries risk: a retrospective cohort study.

Science.gov (United States)

Chaffee, Benjamin W; Cheng, Jing; Featherstone, John D B

2015-09-24

Consensus guidelines support non-operative preventives for dental caries management; yet, their use in practice is far from universal. The purpose of this study was to evaluate the effectiveness of non-operative anti-caries agents in caries prevention among high caries risk adults at a university clinic where risk-based caries management is emphasized. This retrospective observational study drew data from the electronic patient records of non-edentulous adult patients deemed to be at high risk for dental caries during baseline oral evaluations that were completed between July 1, 2007 and December 31, 2012 at a dental university in the United States. We calculated and compared adjusted mean estimates for the number of new decayed or restored teeth (DFT increment) from baseline to the next completed oral evaluation (N = 2,724 patients with follow-up) across three categories of delivery of non-operative anti-caries agents (e.g., high-concentration fluoride toothpaste, chlorhexidine rinse, xylitol products): never, at a single appointment, or at ≥2 appointments ≥4 weeks apart. Estimates were adjusted for patient and provider characteristics, baseline dental status, losses-to-follow-up, and follow-up time. Approximately half the patients did not receive any form of non-operative anti-caries agent. Most that received anti-caries agents were given more than one type of product in combination. One-time delivery of anti-caries agents was associated with a similar DFT increment as receiving no such therapy (difference in increment: -0.04; 95% CI: -0.28, 0.21). However, repeated, spaced delivery of anti-caries agents was associated with approximately one decayed or restored tooth prevented over 18 months for every three patients treated (difference in increment: -0.35; 95% CI: -0.65, -0.08). These results lend evidence that repeatedly receiving anti-caries agents can reduce tooth decay among high-risk patients engaged in regular dental care.

Power properties of invariant tests for spatial autocorrelation in linear regression

NARCIS (Netherlands)

Martellosio, F.

2006-01-01

Many popular tests for residual spatial autocorrelation in the context of the linear regression model belong to the class of invariant tests. This paper derives a number of exact properties of the power function of such tests. In particular, we extend the work of Krämer (2005, Journal of Statistical

Predicting recovery of cognitive function soon after stroke: differential modeling of logarithmic and linear regression.

Science.gov (United States)

Suzuki, Makoto; Sugimura, Yuko; Yamada, Sumio; Omori, Yoshitsugu; Miyamoto, Masaaki; Yamamoto, Jun-ichi

2013-01-01

Cognitive disorders in the acute stage of stroke are common and are important independent predictors of adverse outcome in the long term. Despite the impact of cognitive disorders on both patients and their families, it is still difficult to predict the extent or duration of cognitive impairments. The objective of the present study was, therefore, to provide data on predicting the recovery of cognitive function soon after stroke by differential modeling with logarithmic and linear regression. This study included two rounds of data collection comprising 57 stroke patients enrolled in the first round for the purpose of identifying the time course of cognitive recovery in the early-phase group data, and 43 stroke patients in the second round for the purpose of ensuring that the correlation of the early-phase group data applied to the prediction of each individual's degree of cognitive recovery. In the first round, Mini-Mental State Examination (MMSE) scores were assessed 3 times during hospitalization, and the scores were regressed on the logarithm and linear of time. In the second round, calculations of MMSE scores were made for the first two scoring times after admission to tailor the structures of logarithmic and linear regression formulae to fit an individual's degree of functional recovery. The time course of early-phase recovery for cognitive functions resembled both logarithmic and linear functions. However, MMSE scores sampled at two baseline points based on logarithmic regression modeling could estimate prediction of cognitive recovery more accurately than could linear regression modeling (logarithmic modeling, R(2) = 0.676, PLogarithmic modeling based on MMSE scores could accurately predict the recovery of cognitive function soon after the occurrence of stroke. This logarithmic modeling with mathematical procedures is simple enough to be adopted in daily clinical practice.

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.

Science.gov (United States)

Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-04-01

To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.

truncSP: An R Package for Estimation of Semi-Parametric Truncated Linear Regression Models

Directory of Open Access Journals (Sweden)

Maria Karlsson

2014-05-01

Full Text Available Problems with truncated data occur in many areas, complicating estimation and inference. Regarding linear regression models, the ordinary least squares estimator is inconsistent and biased for these types of data and is therefore unsuitable for use. Alternative estimators, designed for the estimation of truncated regression models, have been developed. This paper presents the R package truncSP. The package contains functions for the estimation of semi-parametric truncated linear regression models using three different estimators: the symmetrically trimmed least squares, quadratic mode, and left truncated estimators, all of which have been shown to have good asymptotic and ?nite sample properties. The package also provides functions for the analysis of the estimated models. Data from the environmental sciences are used to illustrate the functions in the package.

COLOR IMAGE RETRIEVAL BASED ON FEATURE FUSION THROUGH MULTIPLE LINEAR REGRESSION ANALYSIS

Directory of Open Access Journals (Sweden)

K. Seetharaman

2015-08-01

Full Text Available This paper proposes a novel technique based on feature fusion using multiple linear regression analysis, and the least-square estimation method is employed to estimate the parameters. The given input query image is segmented into various regions according to the structure of the image. The color and texture features are extracted on each region of the query image, and the features are fused together using the multiple linear regression model. The estimated parameters of the model, which is modeled based on the features, are formed as a vector called a feature vector. The Canberra distance measure is adopted to compare the feature vectors of the query and target images. The F-measure is applied to evaluate the performance of the proposed technique. The obtained results expose that the proposed technique is comparable to the other existing techniques.

Assessment of dental caries predictors in 6-year-old school children - results from 5-year retrospective cohort study

Directory of Open Access Journals (Sweden)

Masood Mohd

2012-11-01

Full Text Available Abstract Background This was a retrospective cohort study undertaken to assess the rate and pattern of dental caries development in 6-year-old school children followed-up for a period of 5 years, and to identify baseline risk factors that were associated with 5 years caries experience in Malaysian children. Methods This 5-years retrospective cohort study comprised primary school children initially aged 6 years in 2004. Caries experience of each child was recorded annually using World Health Organization criteria. The rates of dental caries were recorded in prevalence and incidence density of carious lesions from baseline to final examination. Risk assessment was done to assess relative risk for caries after 5 years in children with baseline caries status. Simple and multiple logistic regression analysis were performed to identify significant independent risk factors for caries. Results The sample consisted of 1830 school children. All components of DMFT showed significant differences between baseline and final examination. Filled teeth (FT component of the DMFT showed the greatest increases. Results revealed the initial baseline caries level in permanent dentition was a strong predictor for future caries after 5 years (RR=3.78, 95% CI=3.48-4.10, P0.001. Logistic regression analysis showed significant association between caries occurrence and residence (urban/rural (OR=1.80, Pp observed from baseline and after 5 years was 5.80 persons/100 person-year of observation. The rate of new caries-affected tooth (IDt in the period from baseline and after 5-years was 0.76 teeth/100 teeth-year of observation. Conclusion The majority of 12-year-old school children (70% were caries-free and most of the caries were concentrated in only a small proportion (30% of them. We found that the presence of caries in permanent teeth at the age of 6 years was a strong predictor of future caries development in this population. The strong evidence of early permanent teeth

Maternal Depression Increases Childhood Dental Caries: A Cohort Study in Brazil.

Science.gov (United States)

Dos Santos Pinto, Gabriela; de Ávila Quevedo, Luciana; Britto Correa, Marcos; Sousa Azevedo, Marina; Leão Goettems, Marília; Tavares Pinheiro, Ricardo; Demarco, Flávio Fernando

2017-01-01

To investigate the relationship between maternal depression and childhood caries in a cohort of adolescent mothers. This cross-sectional study nested in a cohort evaluated a sample of 538 mother/child dyads. When the children were 24-36 months of age, data regarding oral health from children and mothers were collected by clinical dental examination. A mother's major depressive disorder was assessed by using the Mini International Neuropsychiatric Interview (MINI [Plus]), at the current moment. Independent variables were obtained by using questionnaires. The outcome on dental caries experience was dichotomized by using 2 cut points: dmfs ≥1 and dmfs ≥3. Poisson regression analysis, using a hierarchical approach, was applied to assess the association between major depressive disorder in mothers with and those without caries experience and the outcome. The prevalence of dental caries in children was 15.1% (n = 82). The mean dmfs index was 1.12 (SD = 3.72). The prevalence of major depressive disorder was 32.6% (n = 168). An interaction between caries status and depressive disorder was found, and after adjusted analysis, children from mothers with major depressive disorder with negative caries experience presented a higher caries prevalence (prevalence ratio 4.00, 95% confidence interval 1.29-12.41). Our findings suggest that maternal psychiatric disorders could have a negative impact on children's oral health. © 2016 S. Karger AG, Basel.

Analysis of interactive fixed effects dynamic linear panel regression with measurement error

OpenAIRE

Nayoung Lee; Hyungsik Roger Moon; Martin Weidner

2011-01-01

This paper studies a simple dynamic panel linear regression model with interactive fixed effects in which the variable of interest is measured with error. To estimate the dynamic coefficient, we consider the least-squares minimum distance (LS-MD) estimation method.

Multicollinearity in applied economics research and the Bayesian linear regression

OpenAIRE

EISENSTAT, Eric

2016-01-01

This article revises the popular issue of collinearity amongst explanatory variables in the context of a multiple linear regression analysis, particularly in empirical studies within social science related fields. Some important interpretations and explanations are highlighted from the econometrics literature with respect to the effects of multicollinearity on statistical inference, as well as the general shortcomings of the once fervent search for methods intended to detect and mitigate thes...

Robust best linear estimation for regression analysis using surrogate and instrumental variables.

Science.gov (United States)

Wang, C Y

2012-04-01

We investigate methods for regression analysis when covariates are measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies the classical measurement error model, but it may not have repeated measurements. In addition to the surrogate variables that are available among the subjects in the calibration sample, we assume that there is an instrumental variable (IV) that is available for all study subjects. An IV is correlated with the unobserved true exposure variable and hence can be useful in the estimation of the regression coefficients. We propose a robust best linear estimator that uses all the available data, which is the most efficient among a class of consistent estimators. The proposed estimator is shown to be consistent and asymptotically normal under very weak distributional assumptions. For Poisson or linear regression, the proposed estimator is consistent even if the measurement error from the surrogate or IV is heteroscedastic. Finite-sample performance of the proposed estimator is examined and compared with other estimators via intensive simulation studies. The proposed method and other methods are applied to a bladder cancer case-control study.

Risk indicators and risk predictors of dental caries in schoolchildren

Directory of Open Access Journals (Sweden)

Elaine Pereira da Silva Tagliaferro

2008-12-01

Full Text Available The purpose of this study was to identify risk indicators of high caries level at baseline (HCLB based on cross-sectional data and predictors of high caries increment (HCI based on a 7-year-follow-up examination in 6-8-year-old schoolchildren. Two hundred and six schoolchildren were examined in 1997 and in 2004 by the same two calibrated dentists, in Piracicaba, Brazil. At baseline, dental caries, presence of sealants, fluorosis, and oral hygiene status were recorded. The children's parents completed a questionnaire concerning socioeconomic level, fluoride use, dental service utilization, dietary and oral hygiene habits. HCLB and HCI were defined considering the upper quartile of the total caries experience distribution (dmfs+DMFS and caries increment distribution, respectively. Logistic regression models were adjusted estimating the Odds Ratio (OR, 95% confidence intervals and p-values. Having white spot lesions (OR=5.25 was found to be a risk indicator of HCLB. Schoolchildren with dental fluorosis (OR=0.17 or those who brushed the teeth more than two times a day (OR=0.37 presented less probability of HCLB. The predictors of HCI were: dmfs>0 (OR=2.68 and mothers' educational level up to 8 years of schooling (OR=2.87. Clinical and socioeconomic variables were found to be risk indicators and/or predictors of dental caries in schoolchildren.

Proximal caries detection using digital subtraction radiography in the artificial caries activity model

Energy Technology Data Exchange (ETDEWEB)

Park, Jong Hoon; Lee, Gi Ja; Choi, Sam Jin; Park, Young Ho; Kim, Kyung Soo; Jin, Hyun Seok; Hong, Kyung Won; Oh, Berm Seok; Park, Hun Kuk [Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Seoul (Korea, Republic of); Choi, Yong Suk; Hwang, Eui Hwan [Department of Oral and Maxillofacial Radiology, Institute of Oral Biology, School of Dentistry, Kyung Hee University, Seoul (Korea, Republic of)

2009-03-15

The purpose of the experiment was to evaluating the diagnostic ability of dental caries detection using digital subtraction in the artificial caries activity model. Digital radiographs of five teeth with 8 proximal surfaces were obtained by CCD sensor (Kodak RVG 6100 using a size no.2). The digital radiographic images and subtraction images from artificial proximal caries were examined and interpreted. In this study, we proposed novel caries detection method which could diagnose the dental proximal caries from single digital radiographic image. In artificial caries activity model, the range of lesional depth was 572-1,374 {mu}m and the range of lesional area was 36.95-138.52 mm{sup 2}. The lesional depth and the area were significantly increased with demineralization time (p<0.001). Furthermore, the proximal caries detection using digital subtraction radiography showed high detection rate compared to the proximal caries examination using simple digital radiograph. The results demonstrated that the digital subtraction radiography from single radiographic image of artificial caries was highly efficient in the detection of dental caries compared to the data from simple digital radiograph.

Proximal caries detection using digital subtraction radiography in the artificial caries activity model

International Nuclear Information System (INIS)

Park, Jong Hoon; Lee, Gi Ja; Choi, Sam Jin; Park, Young Ho; Kim, Kyung Soo; Jin, Hyun Seok; Hong, Kyung Won; Oh, Berm Seok; Park, Hun Kuk; Choi, Yong Suk; Hwang, Eui Hwan

2009-01-01

The purpose of the experiment was to evaluating the diagnostic ability of dental caries detection using digital subtraction in the artificial caries activity model. Digital radiographs of five teeth with 8 proximal surfaces were obtained by CCD sensor (Kodak RVG 6100 using a size no.2). The digital radiographic images and subtraction images from artificial proximal caries were examined and interpreted. In this study, we proposed novel caries detection method which could diagnose the dental proximal caries from single digital radiographic image. In artificial caries activity model, the range of lesional depth was 572-1,374 μm and the range of lesional area was 36.95-138.52 mm 2 . The lesional depth and the area were significantly increased with demineralization time (p<0.001). Furthermore, the proximal caries detection using digital subtraction radiography showed high detection rate compared to the proximal caries examination using simple digital radiograph. The results demonstrated that the digital subtraction radiography from single radiographic image of artificial caries was highly efficient in the detection of dental caries compared to the data from simple digital radiograph.

Parental psychosocial factors and childhood caries prevention: Data from an American Indian population.

Science.gov (United States)

Albino, Judith; Tiwari, Tamanna; Henderson, William G; Thomas, Jacob F; Braun, Patricia A; Batliner, Terrence S

2018-04-10

The objective of this study was to examine the association among psychological and social variables reported by American Indian parents/caregivers of preschool children and changes in their Oral Health Knowledge and Behaviors related to care of their children's teeth. We also investigated the relationship of these factors with progression of caries, as reflected by changes in their children's dmfs. The data used for this study were collected at baseline in a clinical trial of an oral health promotion intervention comprising behavioural and clinical interventions for caries prevention delivered by tribal members on a large Southwestern American Indian reservation. Linear regression analyses were performed for changes (baseline to Year 1) in dmfs, Oral Health Knowledge and Oral Health Behavior scores, with baseline psychosocial measures, taken individually, as the independent variables. Parents' attitudes and beliefs were associated with increases in their Oral Health Knowledge and Behavior and also with the progression of caries for their children. When all participants were considered together, increases in children's dmfs were smaller when the caregiver had higher Internal Oral Health Locus of Control (e = -1.33, P = .004), higher Health Literacy (e = -1.55, P Health Belief Model. For parents in the Intervention group, higher scores on Locus of Control, reflecting beliefs that chance, or other people determine their children's oral health, were associated with larger increases in Oral Health Knowledge (e = 1.73, P = .04) and Behaviors (e = 4.00, P = .005). Prevention of early childhood caries in American Indian children has proved to be especially challenging. Some of the measures identified in this report may suggest promising directions to prevention through approaches that build on competencies and skills to be learned and used within a context more broadly focused on parenting and management of health and family challenges. © 2018 John Wiley & Sons A

Relative Importance for Linear Regression in R: The Package relaimpo

Directory of Open Access Journals (Sweden)

Ulrike Gromping

2006-09-01

Full Text Available Relative importance is a topic that has seen a lot of interest in recent years, particularly in applied work. The R package relaimpo implements six different metrics for assessing relative importance of regressors in the linear model, two of which are recommended - averaging over orderings of regressors and a newly proposed metric (Feldman 2005 called pmvd. Apart from delivering the metrics themselves, relaimpo also provides (exploratory bootstrap confidence intervals. This paper offers a brief tutorial introduction to the package. The methods and relaimpo’s functionality are illustrated using the data set swiss that is generally available in R. The paper targets readers who have a basic understanding of multiple linear regression. For the background of more advanced aspects, references are provided.

Factors Associated with Dental Caries in Primary Dentition in a Non-Fluoridated Rural Community of New South Wales, Australia.

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Arora, Amit; Manohar, Narendar; John, James Rufus

2017-11-23

Dental caries persists as one of the most prevalent chronic diseases among children worldwide. This study aims to determine factors that influence dental caries in primary dentition among primary school children residing in the rural non-fluoridated community of Lithgow, New South Wales, Australia. A total of 495 children aged 5-10 years old from all the six primary schools in Lithgow were approached to participate in a cross-sectional survey prior to implementation of water fluoridation in 2014. Following parental consent, children were clinically examined for caries in their primary teeth, and parents were requested to complete a questionnaire on previous fluoride exposure, diet and relevant socio-demographic characteristics that influence oral health. Multiple logistic regression analysis was employed to examine the independent risk factors of primary dentition caries. Overall, 51 percent of children had dental caries in one or more teeth. In the multiple logistic regression analysis, child's age (Adjusted Odd's Ratio (AOR) = 1.30, 95% CI: 1.14-1.49) and mother's extraction history (AOR = 2.05, 95% CI: 1.40-3.00) were significantly associated with caries experience in the child's primary teeth. In addition, each serve of chocolate consumption was associated with 52 percent higher odds (AOR = 1.52, 95% CI: 1.19-1.93) of primary dentition caries.

The relationship between maternal smoking during pregnancy and parental-reported experience of dental caries in Indigenous Australian children.

Science.gov (United States)

Claudia, C; Ju, X; Mejia, G; Jamieson, L

2016-12-01

This study aimed to test the association between maternal smoking during pregnancy and parental-reported experience of dental caries in Indigenous Australian children. Data were from the Longitudinal Study of Indigenous Children (LSIC); a population-based cohort study in Australia. Participants were 1,687 Indigenous Australian children aged 5 or less. Biological, social and behavioural variables were tested using log-linear modelling with binomial regression to determine the association with parental-reported experience of dental caries. Markov Chain Monte Carlo methods were used for multiple imputation of missing data. Overall 25.8% of Indigenous Australian children had dental caries as reported by a carer. In the multivariable model, increased prevalence of parental-reported caries was significantly associated with low maternal education levels (RR=1.60, 95%CI 1.17,2.20) and high sugar consumption (RR= 1.60, 95%CI 1.26,2.02). In the group of children whose mothers smoked tobacco during pregnancy, the association with parent-reported dental caries approached the threshold of significance, but was not significantly associated with caries status in children (RR=1.19, 95%CI 0.99,1.43). After multiple imputation, the most significant association was evident in children of the least educated mothers (RR=1.57, 95%CI 1.25,1.95), breastfeeding more than 12 months (RR=1.26, 95%CI 1.01,1.56), sweet intake more than 30% (RR=1.42, 95%CI 1.15,1.74) and 20-30% (RR=1.29 95%CI 1.04,1.59) and residing in outer regional (RR=1.56, 95%CI 1.19,2.05) or inner regional locations (RR=1.50, 95%CI 1.19,1.88). Mothers' tobacco smoking status showed a weak association with parent-reported dental decay (RR=1.42, 95%CI 1.20,1.68). This study suggests there is a weak association between maternal smoking during pregnancy and prevalence of parentally-reported dental caries in Indigenous Australian children. Copyright© 2016 Dennis Barber Ltd

Dental Caries Experience in Texan Children with Cleft Lip and Palate.

Science.gov (United States)

Sunderji, Sabrina; Acharya, Bhavini; Flaitz, Catherine; Chiquet, Brett

2017-09-15

The purpose of this study was to assess the caries experience in the primary dentition of children born with cleft lip and palate (CLP). A retrospective chart review was conducted on subjects between two and six years old recruited from a university-based pediatric dentistry residency clinic. The number of dental visits and professional fluoride applications, the plaque index and treatment modality, and the presence/location of caries, white spot lesions, and enamel hypoplastic lesions were compared between CLP patients and healthy age- and gender-matched controls. Descriptive statistics, Student's t test, Mann-Whitney U test, and regression analysis were completed. A total of 183 charts were reviewed. Compared to healthy children, CLP children had increases in number of dental visits (P0.05). Children with cleft lip and palate are at a greater risk of enamel hypoplasia and dental caries. No significant caries experience difference was found between unilateral or bilateral CLP cases.

Inequalities of caries experience in Nevada youth expressed by DMFT index vs. Significant Caries Index (SiC over time

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Mobley Connie

2011-04-01

Full Text Available Abstract Background With the increasingly polarized distribution of dental caries among children and adolescents, the usual DMFT measure has become a less meaningful population descriptor. To re-focus on identifying the high caries prevalence group the Significant Caries Index (SiC was created. The aims of this study were to analyze the prevalence and severity of dental caries in Nevada youth over a period of eight years and to compare its expression by means of DMFT and SiC; analyze the caries trends in the population and their underlying factors, and determine whether Nevada youth were at risk for significantly high levels of dental caries. Methods Retrospective data was analyzed from a series of sequential, standardized oral health surveys across eight years (2001/2002-2008/2009 that included over 62,000 examinations of adolescents 13-19 years of age, attending public/private Nevada schools. Mean Decayed-Missing-Filled Teeth index (DMFT and Significant Caries Index (SiC were subsequently computed for each academic year. Descriptive statistics were reported for analysis of comparative DMFT and SiC scores in relation to age, gender, racial background, and residence in a fluoridated/non-fluoridated community. Logistic regression analysis was used to analyze the differential impact of the variables on the probability of being in the high caries prevalence group. Results Comparison of students' mean DMFT to National (NHANES data confirmed that dental caries remains a common chronic disease among Nevada youth, presenting higher prevalence rates and greater mean scores than the national averages. Downward trends were found across all demographics compared between survey years 1 and 6 with the exception of survey year 3. An upward trend began in survey year six. Over time, the younger group displayed an increasing proportion of cariesfree individuals while a decreasing proportion was found among older examinees. As expected, the mean SiC score was

Recursive and non-linear logistic regression: moving on from the original EuroSCORE and EuroSCORE II methodologies.

Science.gov (United States)

Poullis, Michael

2014-11-01

EuroSCORE II, despite improving on the original EuroSCORE system, has not solved all the calibration and predictability issues. Recursive, non-linear and mixed recursive and non-linear regression analysis were assessed with regard to sensitivity, specificity and predictability of the original EuroSCORE and EuroSCORE II systems. The original logistic EuroSCORE, EuroSCORE II and recursive, non-linear and mixed recursive and non-linear regression analyses of these risk models were assessed via receiver operator characteristic curves (ROC) and Hosmer-Lemeshow statistic analysis with regard to the accuracy of predicting in-hospital mortality. Analysis was performed for isolated coronary artery bypass grafts (CABGs) (n = 2913), aortic valve replacement (AVR) (n = 814), mitral valve surgery (n = 340), combined AVR and CABG (n = 517), aortic (n = 350), miscellaneous cases (n = 642), and combinations of the above cases (n = 5576). The original EuroSCORE had an ROC below 0.7 for isolated AVR and combined AVR and CABG. None of the methods described increased the ROC above 0.7. The EuroSCORE II risk model had an ROC below 0.7 for isolated AVR only. Recursive regression, non-linear regression, and mixed recursive and non-linear regression all increased the ROC above 0.7 for isolated AVR. The original EuroSCORE had a Hosmer-Lemeshow statistic that was above 0.05 for all patients and the subgroups analysed. All of the techniques markedly increased the Hosmer-Lemeshow statistic. The EuroSCORE II risk model had a Hosmer-Lemeshow statistic that was significant for all patients (P linear regression failed to improve on the original Hosmer-Lemeshow statistic. The mixed recursive and non-linear regression using the EuroSCORE II risk model was the only model that produced an ROC of 0.7 or above for all patients and procedures and had a Hosmer-Lemeshow statistic that was highly non-significant. The original EuroSCORE and the EuroSCORE II risk models do not have adequate ROC and Hosmer

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

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Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

Linear and support vector regressions based on geometrical correlation of data

Directory of Open Access Journals (Sweden)

Kaijun Wang

2007-10-01

Full Text Available Linear regression (LR and support vector regression (SVR are widely used in data analysis. Geometrical correlation learning (GcLearn was proposed recently to improve the predictive ability of LR and SVR through mining and using correlations between data of a variable (inner correlation. This paper theoretically analyzes prediction performance of the GcLearn method and proves that GcLearn LR and SVR will have better prediction performance than traditional LR and SVR for prediction tasks when good inner correlations are obtained and predictions by traditional LR and SVR are far away from their neighbor training data under inner correlation. This gives the applicable condition of GcLearn method.

Regularized Label Relaxation Linear Regression.

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Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung; Fang, Bingwu

2018-04-01

Linear regression (LR) and some of its variants have been widely used for classification problems. Most of these methods assume that during the learning phase, the training samples can be exactly transformed into a strict binary label matrix, which has too little freedom to fit the labels adequately. To address this problem, in this paper, we propose a novel regularized label relaxation LR method, which has the following notable characteristics. First, the proposed method relaxes the strict binary label matrix into a slack variable matrix by introducing a nonnegative label relaxation matrix into LR, which provides more freedom to fit the labels and simultaneously enlarges the margins between different classes as much as possible. Second, the proposed method constructs the class compactness graph based on manifold learning and uses it as the regularization item to avoid the problem of overfitting. The class compactness graph is used to ensure that the samples sharing the same labels can be kept close after they are transformed. Two different algorithms, which are, respectively, based on -norm and -norm loss functions are devised. These two algorithms have compact closed-form solutions in each iteration so that they are easily implemented. Extensive experiments show that these two algorithms outperform the state-of-the-art algorithms in terms of the classification accuracy and running time.

Evaluation of accuracy of linear regression models in predicting urban stormwater discharge characteristics.

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Madarang, Krish J; Kang, Joo-Hyon

2014-06-01

Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days (ADD), have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency's Storm Water Management Model (SWMM). The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid (TSS) discharge loads and event mean concentrations (EMC) were extracted. From these data, linear regression models were developed. R(2) and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data. Copyright © 2014 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Improving sub-pixel imperviousness change prediction by ensembling heterogeneous non-linear regression models

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Drzewiecki, Wojciech

2016-12-01

In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels) was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques. The results proved that in case of sub-pixel evaluation the most accurate prediction of change may not necessarily be based on the most accurate individual assessments. When single methods are considered, based on obtained results Cubist algorithm may be advised for Landsat based mapping of imperviousness for single dates. However, Random Forest may be endorsed when the most reliable evaluation of imperviousness change is the primary goal. It gave lower accuracies for individual assessments, but better prediction of change due to more correlated errors of individual predictions. Heterogeneous model ensembles performed for individual time points assessments at least as well as the best individual models. In case of imperviousness change assessment the ensembles always outperformed single model approaches. It means that it is possible to improve the accuracy of sub-pixel imperviousness change assessment using ensembles of heterogeneous non-linear regression models.

Modeling Pan Evaporation for Kuwait by Multiple Linear Regression

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Almedeij, Jaber

2012-01-01

Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as functions of available meteorological data of temperature, relative humidity, and wind speed. The data used here for the modeling are daily measurements of substantial continuity coverage, within a period of 17 years between January 1993 and December 2009, which can be considered representative of the desert climate of the urban zone of the country. Multiple linear regression technique is used with a procedure of variable selection for fitting the best model forms. The correlations of evaporation with temperature and relative humidity are also transformed in order to linearize the existing curvilinear patterns of the data by using power and exponential functions, respectively. The evaporation models suggested with the best variable combinations were shown to produce results that are in a reasonable agreement with observation values. PMID:23226984

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression.

Science.gov (United States)

Yu, Xu; Lin, Jun-Yu; Jiang, Feng; Du, Jun-Wei; Han, Ji-Zhong

2018-01-01

Cross-domain collaborative filtering (CDCF) solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR). We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR) model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.

Effectiveness of water fluoridation in the prevention of dental caries across adult age groups.

Science.gov (United States)

Do, Loc; Ha, Diep; Peres, Marco A; Skinner, John; Byun, Roy; Spencer, A John

2017-06-01

Lifetime access to fluoridated water (FW) is associated with lower caries experience. However, assessing this association in adults is likely affected by age. Cohort stratification and categorization of per cent lifetime access to fluoridated water (% LAFW) within cohorts are current approaches to this assessment. These approaches require an examination of the % LAFW and caries experience variation within and across age groups and their association to inform future analyses. This secondary analysis aimed to examine the age group variation in % LAFW and caries experience; and the association of % LAFW with caries within and across age groups of adults. A secondary analysis was undertaken using the Australian National Survey of Adult Oral Health 2004-2006 data on 4090 persons aged 15-91 years randomly sampled by a stratified, multistage probability method. Study participants underwent an interview, an oral examination by trained and standardized dentists to determine decayed, missing or filled tooth surfaces (DMFS) and a mailed self-complete questionnaire which collected residential history to calculate % LAFW. Variations in % LAFW and DMFS across age groups (15-34; 35-44; 45-54; 55+) were examined. Multivariable regression log-link models were generated for DMFS score within each age group. The age groups varied in values and distribution of % LAFW. Caries experience was strongly associated with age. % LAFW was significantly associated with DMFS score in the two younger age groups, but not in the others. Multivariable regression models showed that the highest % LAFW quartile had significantly lower DMFS count than the lowest quartile in the two younger age groups (mean ratios: 0.67 and 0.78, respectively), controlling for other covariates. Access to FW was associated with caries experience in Australian adults. The magnitude of associations varied between age groups, dependent on the natural history of caries and its measurement by DMFS. © 2017 John Wiley & Sons A

Estimate the contribution of incubation parameters influence egg hatchability using multiple linear regression analysis.

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Khalil, Mohamed H; Shebl, Mostafa K; Kosba, Mohamed A; El-Sabrout, Karim; Zaki, Nesma

2016-08-01

This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens' eggs. Five parameters were studied (fertility, early and late embryonic mortalities, shape index, egg weight, and egg weight loss) on four strains, namely Fayoumi, Alexandria, Matrouh, and Montazah. Multiple linear regression was performed on the studied parameters to determine the most influencing one on hatchability. The results showed significant differences in commercial and scientific hatchability among strains. Alexandria strain has the highest significant commercial hatchability (80.70%). Regarding the studied strains, highly significant differences in hatching chick weight among strains were observed. Using multiple linear regression analysis, fertility made the greatest percent contribution (71.31%) to hatchability, and the lowest percent contributions were made by shape index and egg weight loss. A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens.

User's Guide to the Weighted-Multiple-Linear Regression Program (WREG version 1.0)

Science.gov (United States)

Eng, Ken; Chen, Yin-Yu; Kiang, Julie.E.

2009-01-01

Streamflow is not measured at every location in a stream network. Yet hydrologists, State and local agencies, and the general public still seek to know streamflow characteristics, such as mean annual flow or flood flows with different exceedance probabilities, at ungaged basins. The goals of this guide are to introduce and familiarize the user with the weighted multiple-linear regression (WREG) program, and to also provide the theoretical background for program features. The program is intended to be used to develop a regional estimation equation for streamflow characteristics that can be applied at an ungaged basin, or to improve the corresponding estimate at continuous-record streamflow gages with short records. The regional estimation equation results from a multiple-linear regression that relates the observable basin characteristics, such as drainage area, to streamflow characteristics.

Linear Regression Analysis

CERN Document Server

Seber, George A F

2012-01-01

Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.* More than 200 problems throughout the book plus outline solutions for the exercises.* This revision has been extensively class-tested.

Introduction to statistical modelling 2: categorical variables and interactions in linear regression.

Science.gov (United States)

Lunt, Mark

2015-07-01

In the first article in this series we explored the use of linear regression to predict an outcome variable from a number of predictive factors. It assumed that the predictive factors were measured on an interval scale. However, this article shows how categorical variables can also be included in a linear regression model, enabling predictions to be made separately for different groups and allowing for testing the hypothesis that the outcome differs between groups. The use of interaction terms to measure whether the effect of a particular predictor variable differs between groups is also explained. An alternative approach to testing the difference between groups of the effect of a given predictor, which consists of measuring the effect in each group separately and seeing whether the statistical significance differs between the groups, is shown to be misleading. © The Author 2013. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Caries risk assessment

DEFF Research Database (Denmark)

Mejàre, I; Axelsson, S; Dahlén, G

2014-01-01

OBJECTIVE: To assess the ability of multivariate models and single factors to correctly identify future caries development in pre-school children and schoolchildren/adolescents. STUDY DESIGN: A systematic literature search for relevant papers was conducted with pre-determined inclusion criteria...... predictors, baseline caries experience had moderate/good accuracy in pre-school children and limited accuracy in schoolchildren/adolescents. The period of highest risk for caries incidence in permanent teeth was the first few years after tooth eruption. In general, the quality of evidence was limited....... CONCLUSIONS: Multivariate models and baseline caries prevalence performed better in pre-school children than in schoolchildren/adolescents. Baseline caries prevalence was the most accurate single predictor in all age groups. The heterogeneity of populations, models, outcome criteria, measures and reporting...

Restorative treatment thresholds for occlusal primary caries among dentists in the dental practice-based research network

DEFF Research Database (Denmark)

Gordan, Valeria V; Bader, James D; Garvan, Cynthia W

2010-01-01

: The investigators surveyed dentists enrolled in a dental practice-based research network who reported performing at least some restorative dentistry. In the survey, dentists were asked to indicate whether they would intervene surgically in a series of cases involving occlusal caries. Each case presentation included...... a photograph of an occlusal surface displaying typical characteristics of caries penetration and a written description of a patient at a specific level of risk of developing caries. Using logistic regression, the authors analyzed associations between surgical treatment with dentists' and practices......' characteristics and patients' caries risk levels. RESULTS: A total of 517 DPBRN practitioner-investigators responded to the questionnaire. Sixty-three percent of the respondents (326 of 517) indicated that in patients at low risk of developing caries, they would surgically restore teeth with lesions located...

A note on the use of multiple linear regression in molecular ecology.

Science.gov (United States)

Frasier, Timothy R

2016-03-01

Multiple linear regression analyses (also often referred to as generalized linear models--GLMs, or generalized linear mixed models--GLMMs) are widely used in the analysis of data in molecular ecology, often to assess the relative effects of genetic characteristics on individual fitness or traits, or how environmental characteristics influence patterns of genetic differentiation. However, the coefficients resulting from multiple regression analyses are sometimes misinterpreted, which can lead to incorrect interpretations and conclusions within individual studies, and can propagate to wider-spread errors in the general understanding of a topic. The primary issue revolves around the interpretation of coefficients for independent variables when interaction terms are also included in the analyses. In this scenario, the coefficients associated with each independent variable are often interpreted as the independent effect of each predictor variable on the predicted variable. However, this interpretation is incorrect. The correct interpretation is that these coefficients represent the effect of each predictor variable on the predicted variable when all other predictor variables are zero. This difference may sound subtle, but the ramifications cannot be overstated. Here, my goals are to raise awareness of this issue, to demonstrate and emphasize the problems that can result and to provide alternative approaches for obtaining the desired information. © 2015 John Wiley & Sons Ltd.

An evaluation of bias in propensity score-adjusted non-linear regression models.

Science.gov (United States)

Wan, Fei; Mitra, Nandita

2018-03-01

Propensity score methods are commonly used to adjust for observed confounding when estimating the conditional treatment effect in observational studies. One popular method, covariate adjustment of the propensity score in a regression model, has been empirically shown to be biased in non-linear models. However, no compelling underlying theoretical reason has been presented. We propose a new framework to investigate bias and consistency of propensity score-adjusted treatment effects in non-linear models that uses a simple geometric approach to forge a link between the consistency of the propensity score estimator and the collapsibility of non-linear models. Under this framework, we demonstrate that adjustment of the propensity score in an outcome model results in the decomposition of observed covariates into the propensity score and a remainder term. Omission of this remainder term from a non-collapsible regression model leads to biased estimates of the conditional odds ratio and conditional hazard ratio, but not for the conditional rate ratio. We further show, via simulation studies, that the bias in these propensity score-adjusted estimators increases with larger treatment effect size, larger covariate effects, and increasing dissimilarity between the coefficients of the covariates in the treatment model versus the outcome model.

Dental enamel defects, caries experience and oral health-related quality of life: a cohort study.

Science.gov (United States)

Arrow, P

2017-06-01

The impact of enamel defects of the first permanent molars on caries experience and child oral health-related quality of life was evaluated in a cohort study. Children who participated in a study of enamel defects of the first permanent molars 8 years earlier were invited for a follow-up assessment. Consenting children completed the Child Perception Questionnaire and the faces Modified Child Dental Anxiety Scale, and were examined by two calibrated examiners. ANOVA, Kruskal-Wallis, negative binomial and logistic regression were used for data analyses. One hundred and eleven children returned a completed questionnaire and 91 were clinically examined. Negative binomial regression found that oral health impacts were associated with gender (boys, risk ratio (RR) = 0.73, P = 0.03) and decayed, missing or filled permanent teeth (DMFT) (RR = 1.1, P = 0.04). The mean DMFT of children were sound (0.9, standard deviation (SD) = 1.4), diffuse defects (0.8, SD = 1.7), demarcated defects (1.5, SD = 1.4) and pit defects (1.3, SD = 2.3) (Kruskal-Wallis, P = 0.05). Logistic regression of first permanent molar caries found higher odds of caries experience with baseline primary tooth caries experience (odds ratio (OR) = 1.5, P = 0.01), the number of teeth affected by enamel defects (OR = 1.9, P = 0.05) and lower odds with the presence of diffuse enamel defects (OR = 0.1, P = 0.04). The presence of diffuse enamel defects was associated with lower odds of caries experience. © 2016 Australian Dental Association.

Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling

Directory of Open Access Journals (Sweden)

Eric R. Edelman

2017-06-01

Full Text Available For efficient utilization of operating rooms (ORs, accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT. We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT. TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related

Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling.

Science.gov (United States)

Edelman, Eric R; van Kuijk, Sander M J; Hamaekers, Ankie E W; de Korte, Marcel J M; van Merode, Godefridus G; Buhre, Wolfgang F F A

2017-01-01

For efficient utilization of operating rooms (ORs), accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT) per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT) and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA) physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT). We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT). TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related benefits.

Root caries, root surface restorations and lifestyle factors in adult Danes

DEFF Research Database (Denmark)

Christensen, Lisa Bøge; Bardow, Allan; Ekstrand, Kim

2015-01-01

, tobacco use and oral hygiene routines were collected from 4369 adults aged 21-89 who took part in a survey covering 13 municipalities across Denmark. Uni- and multivariate logistic regression analyses were applied to analyse the relationship between the independent lifestyle variables and active caries...... consumption, as well as wearing dentures, were significantly associated with the occurrence of untreated caries and restored root surface lesions, especially in persons over 45. Thus, such lifestyle factors should be taken into consideration, identifying persons with a need of preventive dental services...

Predicting Fuel Ignition Quality Using 1H NMR Spectroscopy and Multiple Linear Regression

KAUST Repository

Abdul Jameel, Abdul Gani; Naser, Nimal; Emwas, Abdul-Hamid M.; Dooley, Stephen; Sarathy, Mani

2016-01-01

An improved model for the prediction of ignition quality of hydrocarbon fuels has been developed using 1H nuclear magnetic resonance (NMR) spectroscopy and multiple linear regression (MLR) modeling. Cetane number (CN) and derived cetane number (DCN

Factors Associated with Dental Caries in Primary Dentition in a Non-Fluoridated Rural Community of New South Wales, Australia

Directory of Open Access Journals (Sweden)

Amit Arora

2017-11-01

Full Text Available Dental caries persists as one of the most prevalent chronic diseases among children worldwide. This study aims to determine factors that influence dental caries in primary dentition among primary school children residing in the rural non-fluoridated community of Lithgow, New South Wales, Australia. A total of 495 children aged 5–10 years old from all the six primary schools in Lithgow were approached to participate in a cross-sectional survey prior to implementation of water fluoridation in 2014. Following parental consent, children were clinically examined for caries in their primary teeth, and parents were requested to complete a questionnaire on previous fluoride exposure, diet and relevant socio-demographic characteristics that influence oral health. Multiple logistic regression analysis was employed to examine the independent risk factors of primary dentition caries. Overall, 51 percent of children had dental caries in one or more teeth. In the multiple logistic regression analysis, child’s age (Adjusted Odd’s Ratio (AOR = 1.30, 95% CI: 1.14–1.49 and mother’s extraction history (AOR = 2.05, 95% CI: 1.40–3.00 were significantly associated with caries experience in the child’s primary teeth. In addition, each serve of chocolate consumption was associated with 52 percent higher odds (AOR = 1.52, 95% CI: 1.19–1.93 of primary dentition caries.

Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression.

Science.gov (United States)

Song, Chao; Kwan, Mei-Po; Zhu, Jiping

2017-04-08

An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale.

Predicting recycling behaviour: Comparison of a linear regression model and a fuzzy logic model.

Science.gov (United States)

Vesely, Stepan; Klöckner, Christian A; Dohnal, Mirko

2016-03-01

In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique. Copyright © 2015 Elsevier Ltd. All rights reserved.

Risk factors for caries-free time: longitudinal study in early childhood

Directory of Open Access Journals (Sweden)

Maria Beatriz Barreto de Sousa Cabral

2017-12-01

Full Text Available ABSTRACT OBJECTIVE To estimate time in days from the beginning of follow-up up to the development of dental caries in children under 30 months and to assess risk factors potentially affecting the development of the disease. METHODS The study population of the cohort study were children attending public, private, and charitable day care centers in Salvador, Northeastern Brazil, followed up for fourteen months. We used the multivariate Cox regression to estimate risk and Kaplan-Meier method to estimate the caries-free time. RESULTS Of the 495 children studied, 112 developed caries (22.6%. Mean caries-free time was 248.6 (SD = 96.2 days. The comparasion of curves by age group (> 24 months and children attending public day care showed more caries in a shorter period (p < 0.00. The following variables were important risk factors for increased rate of caries: district of origin (HR = 1.88, 95%CI 1.27–2.77, category of day care (HR = 3.88, 95%CI 2.04–7.38, age (HR = 1.77, 95%CI 1.15–2.74, bottle-feeding before sleep time after the age of 12 months (HR = 1.62, 95%CI 1.04–2.51, presence of active white spots (HR = 2.70, 95%CI 1.07–6.80, and living in non-masonry house (HR = 1.68, 95%CI 1.02–2.76. The highest hazard ratio (HR = 4.60, 95%CI 2.80–7.42 was found for previous caries experience. CONCLUSIONS Social variables were considered as of high risk for the development of dental caries.

Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

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Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

2006-01-01

Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression

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Xu Yu

2018-01-01

Full Text Available Cross-domain collaborative filtering (CDCF solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR. We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.

Carbon 13 nuclear magnetic resonance chemical shifts empiric calculations of polymers by multi linear regression and molecular modeling

International Nuclear Information System (INIS)

Da Silva Pinto, P.S.; Eustache, R.P.; Audenaert, M.; Bernassau, J.M.

1996-01-01

This work deals with carbon 13 nuclear magnetic resonance chemical shifts empiric calculations by multi linear regression and molecular modeling. The multi linear regression is indeed one way to obtain an equation able to describe the behaviour of the chemical shift for some molecules which are in the data base (rigid molecules with carbons). The methodology consists of structures describer parameters definition which can be bound to carbon 13 chemical shift known for these molecules. Then, the linear regression is used to determine the equation significant parameters. This one can be extrapolated to molecules which presents some resemblances with those of the data base. (O.L.). 20 refs., 4 figs., 1 tab

SOME STATISTICAL ISSUES RELATED TO MULTIPLE LINEAR REGRESSION MODELING OF BEACH BACTERIA CONCENTRATIONS

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As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...

Multiple regression technique for Pth degree polynominals with and without linear cross products

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Davis, J. W.

1973-01-01

A multiple regression technique was developed by which the nonlinear behavior of specified independent variables can be related to a given dependent variable. The polynomial expression can be of Pth degree and can incorporate N independent variables. Two cases are treated such that mathematical models can be studied both with and without linear cross products. The resulting surface fits can be used to summarize trends for a given phenomenon and provide a mathematical relationship for subsequent analysis. To implement this technique, separate computer programs were developed for the case without linear cross products and for the case incorporating such cross products which evaluate the various constants in the model regression equation. In addition, the significance of the estimated regression equation is considered and the standard deviation, the F statistic, the maximum absolute percent error, and the average of the absolute values of the percent of error evaluated. The computer programs and their manner of utilization are described. Sample problems are included to illustrate the use and capability of the technique which show the output formats and typical plots comparing computer results to each set of input data.

Improvement of Storm Forecasts Using Gridded Bayesian Linear Regression for Northeast United States

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Yang, J.; Astitha, M.; Schwartz, C. S.

2017-12-01

Bayesian linear regression (BLR) is a post-processing technique in which regression coefficients are derived and used to correct raw forecasts based on pairs of observation-model values. This study presents the development and application of a gridded Bayesian linear regression (GBLR) as a new post-processing technique to improve numerical weather prediction (NWP) of rain and wind storm forecasts over northeast United States. Ten controlled variables produced from ten ensemble members of the National Center for Atmospheric Research (NCAR) real-time prediction system are used for a GBLR model. In the GBLR framework, leave-one-storm-out cross-validation is utilized to study the performances of the post-processing technique in a database composed of 92 storms. To estimate the regression coefficients of the GBLR, optimization procedures that minimize the systematic and random error of predicted atmospheric variables (wind speed, precipitation, etc.) are implemented for the modeled-observed pairs of training storms. The regression coefficients calculated for meteorological stations of the National Weather Service are interpolated back to the model domain. An analysis of forecast improvements based on error reductions during the storms will demonstrate the value of GBLR approach. This presentation will also illustrate how the variances are optimized for the training partition in GBLR and discuss the verification strategy for grid points where no observations are available. The new post-processing technique is successful in improving wind speed and precipitation storm forecasts using past event-based data and has the potential to be implemented in real-time.

[Comparison of application of Cochran-Armitage trend test and linear regression analysis for rate trend analysis in epidemiology study].

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Wang, D Z; Wang, C; Shen, C F; Zhang, Y; Zhang, H; Song, G D; Xue, X D; Xu, Z L; Zhang, S; Jiang, G H

2017-05-10

We described the time trend of acute myocardial infarction (AMI) from 1999 to 2013 in Tianjin incidence rate with Cochran-Armitage trend (CAT) test and linear regression analysis, and the results were compared. Based on actual population, CAT test had much stronger statistical power than linear regression analysis for both overall incidence trend and age specific incidence trend (Cochran-Armitage trend P valuelinear regression P value). The statistical power of CAT test decreased, while the result of linear regression analysis remained the same when population size was reduced by 100 times and AMI incidence rate remained unchanged. The two statistical methods have their advantages and disadvantages. It is necessary to choose statistical method according the fitting degree of data, or comprehensively analyze the results of two methods.

Evaluation of pH, buffering capacity, viscosity and flow rate levels of saliva in caries-free, minimal caries and nursing caries children: An in vivo study

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Dwitha Animireddy

2014-01-01

Full Text Available Background and Aim: The present study was undertaken to evaluate the pH, buffering capacity, viscosity and flow rate of saliva in caries free, minimal caries and nursing caries children and to evaluate the relationship of these on the caries activity of children. Materials and Methods: A total of 75 school children of age group between 4 and 12 years were selected and divided into three equal groups: Group I, Group II and Group III, consisting of 25 subjects each. Group I included caries-free subjects, Group II included subjects with minimal caries and Group III included subjects with nursing caries. Saliva samples were collected from all subjects and were estimated for flow rate, pH, buffering capacity and viscosity. Results: There was a significant decrease in the mean salivary flow rate, salivary ph and salivary buffer capacity and a significant increase in the salivary viscosity among caries-free subjects, subjects with minimal caries and subjects with nursing caries. Conclusion: The physicochemical properties of saliva, such as salivary flow rate, pH, buffering capacity and viscosity, has a relation with caries activity in children and act as markers of caries activity.

Dental avoidance behaviour in parent and child as risk indicators for caries in 5-year-old children.

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Wigen, Tove I; Skaret, Erik; Wang, Nina J

2009-11-01

The aim of this study was to explore associations between avoidance behaviour and dental anxiety in both parents and children and caries experience in 5-year-old children. It was hypothesised that parents' dental avoidance behaviour and dental anxiety were related to dental caries in 5-year-old children. Data were collected from dental records and by clinical and radiographic examination of 523 children. The parents completed a questionnaire regarding education, national background, dental anxiety, dental attendance, and behaviour management problems. Bivariate and multivariate logistic regression was conducted. Children having one or more missed dental appointments (OR = 4.7), child behaviour management problems (OR = 3.3), child dental anxiety (OR = 3.1), and parents avoiding dental care (OR = 2.1) were bivariately associated with caries experience at the age of 5 years. In multivariate logistic regression, having one or more missed dental appointments (OR = 4.0) and child behaviour management problems (OR = 2.4) were indicators for dental caries in 5-year-old children, when controlling for parents education and national origin. Parents that avoid bringing their child to scheduled dental appointments and previous experiences of behaviour management problems for the child indicated risk for dental caries in 5-year-old children.

Food expenditures, cariogenic dietary practices and childhood dental caries in southern Brazil.

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Feldens, C A; Rodrigues, P H; Rauber, F; Chaffee, B W; Vitolo, M R

2013-01-01

Family expenditures on food for children may represent an important barrier to the adoption of healthy feeding practices in populations of low socioeconomic status. The aim of this study was to explore the relationship between cariogenic feeding practices, expenditures on food for children and dental caries. This cross-sectional study included 329 four-year-old children from São Leopoldo in southern Brazil. Cariogenic dietary practices were assessed at 4 years of age using two 24-hour recalls conducted with the children's mothers. Expenditures on food for children were estimated based on all reported food items and the respective amounts ingested. Early childhood caries and severe early childhood caries were assessed by clinical examination at 4 years of age. Cariogenic dietary habits were not associated with lower food expenditures. On the contrary, in multivariable regression analysis, the intake of chocolate (p = 0.007), soft drinks (p = 0.027) and a higher number of meals and snacks per day (p food for children. No statistically significant differences were observed in food expenditures or in the proportion of household income spent on feeding children between caries-free children, those with early childhood caries and those with severe early childhood caries. In conclusion, keeping children free of dental caries does not necessarily increase food expenditures or the proportion of household income spent on feeding children in low-socioeconomic status populations. Some cariogenic dietary practices were associated with greater expenditures on child feeding. Copyright © 2013 S. Karger AG, Basel.

USE OF THE SIMPLE LINEAR REGRESSION MODEL IN MACRO-ECONOMICAL ANALYSES

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Constantin ANGHELACHE

2011-10-01

Full Text Available The article presents the fundamental aspects of the linear regression, as a toolbox which can be used in macroeconomic analyses. The article describes the estimation of the parameters, the statistical tests used, the homoscesasticity and heteroskedasticity. The use of econometrics instrument in macroeconomics is an important factor that guarantees the quality of the models, analyses, results and possible interpretation that can be drawn at this level.

Association between quantitative measures obtained using fluorescence-based methods and activity status of occlusal caries lesions in primary molars.

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Novaes, Tatiane Fernandes; Reyes, Alessandra; Matos, Ronilza; Antunes-Pontes, Laura Regina; Marques, Renata Pereira de Samuel; Braga, Mariana Minatel; Diniz, Michele Baffi; Mendes, Fausto Medeiros

2017-05-01

Fluorescence-based methods (FBM) can add objectiveness to diagnosis strategy for caries. Few studies, however, have focused on the evaluation of caries activity. To evaluate the association between quantitative measures obtained with FBM, clinical parameters acquired from the patients, caries detection, and assessment of activity status in occlusal surfaces of primary molars. Six hundred and six teeth from 113 children (4-14 years) were evaluated. The presence of a biofilm, caries experience, and the number of active lesions were recorded. The teeth were assessed using FBM: DIAGNOdent pen (Lfpen) and Quantitative light-induced fluorescence (QLF). As reference standard, all teeth were evaluated using the ICDAS (International Caries Detection and Assessment System) associated with clinical activity assessments. Multilevel regressions compared the FBM values and evaluated the association between the FBM measures and clinical variables related to the caries activity. The measures from the FBM were higher in cavitated lesions. Only, ∆F values distinguished active and inactive lesions. The LFpen measures were higher in active lesions, at the cavitated threshold (56.95 ± 29.60). Following regression analyses, only the presence of visible biofilm on occlusal surfaces (adjusted prevalence ratio = 1.43) and ∆R values of the teeth (adjusted prevalence ratio = 1.02) were associated with caries activity. Some quantitative measures from FBM parameters are associated with caries activity evaluation, which is similar to the clinical evaluation of the presence of visible biofilm. © 2016 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Optical quantification of caries-like lesions in vitro by use of a fluorescent dye

International Nuclear Information System (INIS)

Van de Rijke, J.W.; Ten Bosch, J.J.

1990-01-01

An experimental method was developed for measurement of the fluorescence intensity of a dye that was introduced into caries-like lesions in vitro. A distinct pattern of change of fluorescence intensity with time appeared, displaying a plateau value and a peak value for each measurement. Both plateau and peak values showed a linear correlation with calcium loss, as measured with longitudinal microradiography. The correlation coefficients were r = 0.87 for plateau values and r = 0.89 for peak values. The difference in scattering by dry and wet caries lesions was also measured with the same equipment, which showed a linear correlation with calcium loss of r = -0.53

Child oral health-related quality of life (COHQoL), enamel defects of the first permanent molars and caries experience among children in Western Australia.

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Arrow, P

2013-09-01

Published reports suggest that children with enamel defects, especially where enamel is missing or breaking down, experience considerable discomfort and are generally more fearful of dental treatment. However, children's oral health-related quality of life in relation to enamel defects has not been reported. The aim of this study was to examine the association between oral health-related quality of life among children (COHQoL) with enamel defects of the first permanent molars and deciduous caries experience. Children attending pre-primary schools in metropolitan Perth, Western Australia, were recruited and classified for enamel defects using the modified Developmental Defects of Enamel index. Caries experience of deciduous molars and canines was also recorded. Parents completed a child oral health-related quality of life questionnaire. Data were analysed using Kruskal-Wallis, Spearman's rank correlation, chi-square, multiple linear regression and ordered logistic regression to test the factors for their influence on the COHQoL. From the 550 children assessed (mean age 7.2 years) 522 COHQoL questionnaires were returned. Mean COHQoL score was 8.9 (sd 8.8). Bivariate tests showed no association of COHQoL with enamel defect status of the first permanent molars. COHQoL was associated with dmft (mean dmft 1.96, sd 2.62). Higher caries experience children had poorer reported oral health-related quality of life. The presence of enamel defects in the first permanent molars did not affect the children's oral health-related quality of life.

Dentists’ practice patterns regarding caries prevention: results from a dental practice-based research network

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Yokoyama, Yoko; Kakudate, Naoki; Sumida, Futoshi; Matsumoto, Yuki; Gilbert, Gregg H; Gordan, Valeria V

2013-01-01

Objective The purposes of this study were to (1) quantify dentists' practice patterns regarding caries prevention and (2) test the hypothesis that certain dentists' characteristics are associated with these practice patterns. Design The study used a cross-sectional study design consisting of a questionnaire survey. Participants The study queried dentists who worked in outpatient dental practices who were affiliated with the Dental Practice-Based Research Network Japan, which seeks to engage dentists in investigating research questions and sharing experiences and expertise (n=282). Measurement Dentists were asked about their practice patterns regarding caries preventive dentistry. Background data on patients, practice and dentist were also collected. Results 38% of dentists (n=72) provided individualised caries prevention to more than 50% of their patients. Overall, 10% of the time in daily practice was spent on caries preventive dentistry. Dentists who provided individualised caries prevention to more than 50% of their patients spent significantly more time on preventive care and less time on removable prosthetics treatment, compared to dentists who did not provide individualised caries prevention. Additionally, they provided oral hygiene instruction, patient education, fluoride recommendations, intraoral photographs taken and diet counselling to their patients significantly more often than dentists who did not provide individualised caries prevention. Multiple logistic regression analysis suggested that the percentage of patients interested in caries prevention and the percentage of patients who received hygiene instruction, were both associated with the percentage of patients who receive individualised caries prevention. Conclusions We identified substantial variation in dentists' practice patterns regarding preventive dentistry. Individualised caries prevention was significantly related to provision of other preventive services and to having a higher percentage

Dental Caries (Tooth Decay)

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... Materials Contact Us Home Research Data & Statistics Dental Caries (Tooth Decay) Dental caries (tooth decay) remains the most prevalent chronic disease ... adults, even though it is largely preventable. Although caries has significantly decreased for most Americans over the ...

Dental Caries (Tooth Decay)

Science.gov (United States)

... Contact Us Home Research Data & Statistics Share Dental Caries (Tooth Decay) Dental caries (tooth decay) remains the most prevalent chronic disease ... adults, even though it is largely preventable. Although caries has significantly decreased for most Americans over the ...

PRIMARY CARIES: AN OVERVIEW

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Gaurav Solanki

2012-01-01

Full Text Available Primary caries is an initial lesions produced by direct extension from an external surface. Dental caries is called as tooth decay or a cavity is a disease in which bacterial processes changes carbohydrate to acid which than dematerializes the hard tooth structure like enamel, dentin and cementum. Streptococcus mutans and Lactobacillus are the bacteria responsible for the dental caries by acid production. This article throws light on the dental caries disease, its sign and symptoms, treatment and prevention of it. A review of some patents on dental caries is also provided that summarizes the recent technical advancements taken place in this area.

Single camera multi-view anthropometric measurement of human height and mid-upper arm circumference using linear regression.

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Liu, Yingying; Sowmya, Arcot; Khamis, Heba

2018-01-01

Manually measured anthropometric quantities are used in many applications including human malnutrition assessment. Training is required to collect anthropometric measurements manually, which is not ideal in resource-constrained environments. Photogrammetric methods have been gaining attention in recent years, due to the availability and affordability of digital cameras. The primary goal is to demonstrate that height and mid-upper arm circumference (MUAC)-indicators of malnutrition-can be accurately estimated by applying linear regression to distance measurements from photographs of participants taken from five views, and determine the optimal view combinations. A secondary goal is to observe the effect on estimate error of two approaches which reduce complexity of the setup, computational requirements and the expertise required of the observer. Thirty-one participants (11 female, 20 male; 18-37 years) were photographed from five views. Distances were computed using both camera calibration and reference object techniques from manually annotated photos. To estimate height, linear regression was applied to the distances between the top of the participants head and the floor, as well as the height of a bounding box enclosing the participant's silhouette which eliminates the need to identify the floor. To estimate MUAC, linear regression was applied to the mid-upper arm width. Estimates were computed for all view combinations and performance was compared to other photogrammetric methods from the literature-linear distance method for height, and shape models for MUAC. The mean absolute difference (MAD) between the linear regression estimates and manual measurements were smaller compared to other methods. For the optimal view combinations (smallest MAD), the technical error of measurement and coefficient of reliability also indicate the linear regression methods are more reliable. The optimal view combination was the front and side views. When estimating height by linear

Robust linear registration of CT images using random regression forests

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Konukoglu, Ender; Criminisi, Antonio; Pathak, Sayan; Robertson, Duncan; White, Steve; Haynor, David; Siddiqui, Khan

2011-03-01

Global linear registration is a necessary first step for many different tasks in medical image analysis. Comparing longitudinal studies1, cross-modality fusion2, and many other applications depend heavily on the success of the automatic registration. The robustness and efficiency of this step is crucial as it affects all subsequent operations. Most common techniques cast the linear registration problem as the minimization of a global energy function based on the image intensities. Although these algorithms have proved useful, their robustness in fully automated scenarios is still an open question. In fact, the optimization step often gets caught in local minima yielding unsatisfactory results. Recent algorithms constrain the space of registration parameters by exploiting implicit or explicit organ segmentations, thus increasing robustness4,5. In this work we propose a novel robust algorithm for automatic global linear image registration. Our method uses random regression forests to estimate posterior probability distributions for the locations of anatomical structures - represented as axis aligned bounding boxes6. These posterior distributions are later integrated in a global linear registration algorithm. The biggest advantage of our algorithm is that it does not require pre-defined segmentations or regions. Yet it yields robust registration results. We compare the robustness of our algorithm with that of the state of the art Elastix toolbox7. Validation is performed via 1464 pair-wise registrations in a database of very diverse 3D CT images. We show that our method decreases the "failure" rate of the global linear registration from 12.5% (Elastix) to only 1.9%.

Using the fuzzy linear regression method to benchmark the energy efficiency of commercial buildings

International Nuclear Information System (INIS)

Chung, William

2012-01-01

Highlights: ► Fuzzy linear regression method is used for developing benchmarking systems. ► The systems can be used to benchmark energy efficiency of commercial buildings. ► The resulting benchmarking model can be used by public users. ► The resulting benchmarking model can capture the fuzzy nature of input–output data. -- Abstract: Benchmarking systems from a sample of reference buildings need to be developed to conduct benchmarking processes for the energy efficiency of commercial buildings. However, not all benchmarking systems can be adopted by public users (i.e., other non-reference building owners) because of the different methods in developing such systems. An approach for benchmarking the energy efficiency of commercial buildings using statistical regression analysis to normalize other factors, such as management performance, was developed in a previous work. However, the field data given by experts can be regarded as a distribution of possibility. Thus, the previous work may not be adequate to handle such fuzzy input–output data. Consequently, a number of fuzzy structures cannot be fully captured by statistical regression analysis. This present paper proposes the use of fuzzy linear regression analysis to develop a benchmarking process, the resulting model of which can be used by public users. An illustrative example is given as well.

Evaluation of non-microbial salivary caries activity parameters and salivary biochemical indicators in predicting dental caries

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A Kaur

2012-01-01

Full Text Available Aim: The aim of the present study was the evaluation of non-microbial salivary caries activity parameters and salivary biochemical indicators in predicting dental caries. Materials and Methods: The present study was carried out on 60 children, aged 4-6 years, selected from the schools of Panchkula district, Haryana, on the basis of their caries status. Level of hydration, flow rate, pH, buffering capacity, relative viscosity, calcium, phosphorus and alkaline phosphatase levels in caries-free and caries-active children were evaluated. Results: Results showed that 90% of subjects in the caries-free group and 30% of subjects in the caries-active group had normal level of hydration value of less than 60 s and the difference was found to be statistically very highly significant. Normal flow rate of stimulated saliva was found in 90% of the subjects in caries-free group and 33.3% subjects in the caries active group and difference was found to be statistically very highly significant. Adequate salivary pH was found in 100% subjects in caries-free group and 30% in caries-active group and the difference was statistically very highly significant. Conclusion: To conclude, within limitations of this study, it became clear that normal level of hydration and higher values for flow rate, pH, buffering capacity of saliva lead to good oral health and a reduced caries occurrence. Increased salivary viscosity plays a role in increasing caries incidence. Salivary biochemical indicators like calcium, phosphorus and alkaline phosphatase also play their respective role in determining caries susceptibility of an individual. These salivary parameters can be used as diagnostic tool for caries risk assessment.

[Preventive dentistry 5. Secondary caries].

NARCIS (Netherlands)

Hollanders, A.C.C.; Kuper, N.K.; Opdam, N.J.M.; Huysmans, M.C.D.N.J.M.

2017-01-01

Secondary caries is reported as one of the most important reasons for replacing restorations. The patient's general caries risk plays an important role in the development of secondary caries. The connection, at the patient level, between various factors, the risk of caries and restoration factors,

Early Childhood Caries

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Yumiko Kawashita

2011-01-01

Full Text Available Dental caries is one of the most common childhood diseases, and people continue to be susceptible to it throughout their lives. Although dental caries can be arrested and potentially even reversed in its early stages, it is often not self-limiting and progresses without proper care until the tooth is destroyed. Early childhood caries (ECC is often complicated by inappropriate feeding practices and heavy infection with mutans streptococci. Such children should be targeted with a professional preventive program that includes oral hygiene instructions for mothers or caregivers, along with fluoride and diet counseling. However, these strategies alone are not sufficient to prevent dental caries in high-risk children; prevention of ECC also requires addressing the socioeconomic factors that face many families in which ECC is endemic. The aim of this paper is to systematically review information about ECC and to describe why many children are suffering from dental caries.

Least median of squares and iteratively re-weighted least squares as robust linear regression methods for fluorimetric determination of α-lipoic acid in capsules in ideal and non-ideal cases of linearity.

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Korany, Mohamed A; Gazy, Azza A; Khamis, Essam F; Ragab, Marwa A A; Kamal, Miranda F

2018-03-26

This study outlines two robust regression approaches, namely least median of squares (LMS) and iteratively re-weighted least squares (IRLS) to investigate their application in instrument analysis of nutraceuticals (that is, fluorescence quenching of merbromin reagent upon lipoic acid addition). These robust regression methods were used to calculate calibration data from the fluorescence quenching reaction (∆F and F-ratio) under ideal or non-ideal linearity conditions. For each condition, data were treated using three regression fittings: Ordinary Least Squares (OLS), LMS and IRLS. Assessment of linearity, limits of detection (LOD) and quantitation (LOQ), accuracy and precision were carefully studied for each condition. LMS and IRLS regression line fittings showed significant improvement in correlation coefficients and all regression parameters for both methods and both conditions. In the ideal linearity condition, the intercept and slope changed insignificantly, but a dramatic change was observed for the non-ideal condition and linearity intercept. Under both linearity conditions, LOD and LOQ values after the robust regression line fitting of data were lower than those obtained before data treatment. The results obtained after statistical treatment indicated that the linearity ranges for drug determination could be expanded to lower limits of quantitation by enhancing the regression equation parameters after data treatment. Analysis results for lipoic acid in capsules, using both fluorimetric methods, treated by parametric OLS and after treatment by robust LMS and IRLS were compared for both linearity conditions. Copyright © 2018 John Wiley & Sons, Ltd.

Caries-related factors and bacterial composition of supragingival plaques in caries free and caries active Algerian adults

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Amina Hoceini

2016-08-01

Conclusions: This study confirms the association of some aciduric bacteria with caries formation, and a direct association of sugar intake and cultural level with dental caries. Furthermore, oral hygiene practices minimize the prevalence of tooth decay.

Piecewise linear regression techniques to analyze the timing of head coach dismissals in Dutch soccer clubs

NARCIS (Netherlands)

Schryver, T. de; Eisinga, R.

2010-01-01

The key question in research on dismissals of head coaches in sports clubs is not whether they should happen but when they will happen. This paper applies piecewise linear regression to advance our understanding of the timing of head coach dismissals. Essentially, the regression sacrifices degrees

Dental caries is negatively correlated with body mass index among 7-9 years old children in Guangzhou, China.

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Liang, Jing-Jing; Zhang, Zhe-Qing; Chen, Ya-Jun; Mai, Jin-Cheng; Ma, Jun; Yang, Wen-Han; Jing, Jin

2016-07-26

Evidence linking caries in primary dentition and children's anthropometric measures is contradictory. We aimed to evaluate the prevalence of primary dental caries and its relationship with body mass index (BMI) among 7-9 years old school children in urban Guangzhou, China. This cross-sectional study enrolled 32,461 pupils (14,778 girls and 17,683 boys) aged 7-9 years from 65 elementary schools in Guangzhou. Dental caries was detected according to criteria recommended by the World Health Organization (WHO). The total mean decayed, missing or filled teeth (dmft) of primary dentition were assessed. Weight and height were measured and BMI was calculated. Children were classified into underweight, normal weight, overweight and obesity groups by BMI based on Chinese criteria. Z-score of BMI-for-age (BAZ) was calculated by WHO standardized procedure. Multivariable odds ratios (ORs) and 95 % confidence intervals (CIs) were calculated using logistic regression. Restricted cubic spline regression was applied to evaluate the shape of the relationship between BAZ and primary dental caries. The prevalence of primary dental caries was 30.7 % in total sample. Regarding dmft values, the mean ± standard deviation (SD) in the combined sample were 1.03 ± 2.05 in boys and 0.93 ± 1.92 in girls. Both indices decreased by age. Compared with normal BMI group, children in overweight and obesity groups have 27 % (OR = 0.73, 95 % CI: 0.66-0.81, P caries after adjustment for age and gender, respectively. Although in general, increased BAZ was associated with decreased risk of dental caries, full-range BAZ was associated with dental caries in an A-shaped manner with a zenith at around -1.4. Higher BMI was associated with lower odds of caries; overweight and obese children were more likely to be primary dental caries free among 7-9 years in Guangzhou, China.

An Introduction to Graphical and Mathematical Methods for Detecting Heteroscedasticity in Linear Regression.

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Thompson, Russel L.

Homoscedasticity is an important assumption of linear regression. This paper explains what it is and why it is important to the researcher. Graphical and mathematical methods for testing the homoscedasticity assumption are demonstrated. Sources of homoscedasticity and types of homoscedasticity are discussed, and methods for correction are…

Diet and Dental Caries: The Pivotal Role of Free Sugars Reemphasized.

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Sheiham, A; James, W P T

2015-10-01

The importance of sugars as a cause of caries is underemphasized and not prominent in preventive strategies. This is despite overwhelming evidence of its unique role in causing a worldwide caries epidemic. Why this neglect? One reason is that researchers mistakenly consider caries to be a multifactorial disease; they also concentrate mainly on mitigating factors, particularly fluoride. However, this is to misunderstand that the only cause of caries is dietary sugars. These provide a substrate for cariogenic oral bacteria to flourish and to generate enamel-demineralizing acids. Modifying factors such as fluoride and dental hygiene would not be needed if we tackled the single cause--sugars. In this article, we demonstrate the sensitivity of cariogenesis to even very low sugars intakes. Quantitative analyses show a log-linear dose-response relationship between the sucrose or its monosaccharide intakes and the progressive lifelong development of caries. This results in a substantial dental health burden throughout life. Processed starches have cariogenic potential when accompanying sucrose, but human studies do not provide unequivocal data of their cariogenicity. The long-standing failure to identify the need for drastic national reductions in sugars intakes reflects scientific confusion partly induced by pressure from major industrial sugar interests. © International & American Associations for Dental Research 2015.

Error analysis of dimensionless scaling experiments with multiple points using linear regression

International Nuclear Information System (INIS)

Guercan, Oe.D.; Vermare, L.; Hennequin, P.; Bourdelle, C.

2010-01-01

A general method of error estimation in the case of multiple point dimensionless scaling experiments, using linear regression and standard error propagation, is proposed. The method reduces to the previous result of Cordey (2009 Nucl. Fusion 49 052001) in the case of a two-point scan. On the other hand, if the points follow a linear trend, it explains how the estimated error decreases as more points are added to the scan. Based on the analytical expression that is derived, it is argued that for a low number of points, adding points to the ends of the scanned range, rather than the middle, results in a smaller error estimate. (letter)

Caries assessment: establishing mathematical link of clinical and benchtop method

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Amaechi, Bennett T.

2009-02-01

It is well established that the development of new technologies for early detection and quantitative monitoring of dental caries at its early stage could provide health and economic benefits ranging from timely preventive interventions to reduction of the time required for clinical trials of anti-caries agents. However, the new technologies currently used in clinical setting cannot assess and monitor caries using the actual mineral concentration within the lesion, while a laboratory-based microcomputed tomography (MCT) has been shown to possess this capability. Thus we envision the establishment of mathematical equations relating the measurements of each of the clinical technologies to that of MCT will enable the mineral concentration of lesions detected and assessed in clinical practice to be extrapolated from the equation, and this will facilitate preventitive care in dentistry to lower treatment cost. We utilize MCT and the two prominent clinical caries assessment devices (Quantitative Light-induced Fluorescence [QLF] and Diagnodent) to longitudinally monitor the development of caries in a continuous flow mixed-organisms biofilm model (artificial mouth), and then used the collected data to establish mathematical equation relating the measurements of each of the clinical technologies to that of MCT. A linear correlation was observed between the measurements of MicroCT and that of QLF and Diagnodent. Thus mineral density in a carious lesion detected and measured using QLF or Diagnodent can be extrapolated using the developed equation. This highlights the usefulness of MCT for monitoring the progress of an early caries being treated with therapeutic agents in clinical practice or trials.

Comparison of two-concentration with multi-concentration linear regressions: Retrospective data analysis of multiple regulated LC-MS bioanalytical projects.

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Musuku, Adrien; Tan, Aimin; Awaiye, Kayode; Trabelsi, Fethi

2013-09-01

Linear calibration is usually performed using eight to ten calibration concentration levels in regulated LC-MS bioanalysis because a minimum of six are specified in regulatory guidelines. However, we have previously reported that two-concentration linear calibration is as reliable as or even better than using multiple concentrations. The purpose of this research is to compare two-concentration with multiple-concentration linear calibration through retrospective data analysis of multiple bioanalytical projects that were conducted in an independent regulated bioanalytical laboratory. A total of 12 bioanalytical projects were randomly selected: two validations and two studies for each of the three most commonly used types of sample extraction methods (protein precipitation, liquid-liquid extraction, solid-phase extraction). When the existing data were retrospectively linearly regressed using only the lowest and the highest concentration levels, no extra batch failure/QC rejection was observed and the differences in accuracy and precision between the original multi-concentration regression and the new two-concentration linear regression are negligible. Specifically, the differences in overall mean apparent bias (square root of mean individual bias squares) are within the ranges of -0.3% to 0.7% and 0.1-0.7% for the validations and studies, respectively. The differences in mean QC concentrations are within the ranges of -0.6% to 1.8% and -0.8% to 2.5% for the validations and studies, respectively. The differences in %CV are within the ranges of -0.7% to 0.9% and -0.3% to 0.6% for the validations and studies, respectively. The average differences in study sample concentrations are within the range of -0.8% to 2.3%. With two-concentration linear regression, an average of 13% of time and cost could have been saved for each batch together with 53% of saving in the lead-in for each project (the preparation of working standard solutions, spiking, and aliquoting). Furthermore

A comparative evaluation of Oratest with the microbiological method of assessing caries activity in children

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Sundaram, Meenakshi; Nayak, Ullal Anand; Ramalingam, Krishnakumar; Reddy, Venugopal; Rao, Arun Prasad; Mathian, Mahesh

2013-01-01

Aims: The aim of this study is to find out whether Oratest can be used as a diagnostic tool in assessing the caries activity by evaluating its relationship to the existing caries status and the salivary streptococcus mutans level. Materials and Methods: The study sample consists of 90 students divided into two groups. Group I (test group) and Group II (control group) consisting of 30 children for control group and 60 children for test group. The sampling of unstimulated saliva for the estimation of streptococcus mutans was done as per the method suggested by Kohler and Bratthall. The plates were then incubated. Rough surface colonies were identified as streptococcus mutans on a pre-determined area of the tip (approximately 1.5 cm2) were counted for each side of spatula pressed against mitis salivarius bacitracin agar using digital colony counter. The results were expressed in colony forming units (CFU). Oratest was carried out in the same patients after the collection of salivary sample for the microbiological method to evaluate the relationship between the two tests. Statistical Analysis Used: The tests used were ANOVA, Pearson Chi-square test, Pearson′s correlation analysis, Mann-Whitney U test and Student′s independent t-test. Results: In the control group and test group, when the streptococcus mutans count (CFU) and Oratest time (minutes) were correlated using Pearson′s correlation analysis, the streptococcus mutans counts was found to be in a statistically significant negative linear relationship with the Oratest time. When the caries status of the children, participated in the test group were correlated with mutans count (CFU) and Oratest time, caries status were found to be in a statistically significant positive linear relationship with streptococcus mutans count and in a significant negative linear relationship with Oratest time. Conclusions: The test proved to be a simple, inexpensive and rapid technique for assessing caries activity since a

Evaluation of a multiple linear regression model and SARIMA model in forecasting heat demand for district heating system

International Nuclear Information System (INIS)

Fang, Tingting; Lahdelma, Risto

2016-01-01

Highlights: • Social factor is considered for the linear regression models besides weather file. • Simultaneously optimize all the coefficients for linear regression models. • SARIMA combined with linear regression is used to forecast the heat demand. • The accuracy for both linear regression and time series models are evaluated. - Abstract: Forecasting heat demand is necessary for production and operation planning of district heating (DH) systems. In this study we first propose a simple regression model where the hourly outdoor temperature and wind speed forecast the heat demand. Weekly rhythm of heat consumption as a social component is added to the model to significantly improve the accuracy. The other type of model is the seasonal autoregressive integrated moving average (SARIMA) model with exogenous variables as a combination to take weather factors, and the historical heat consumption data as depending variables. One outstanding advantage of the model is that it peruses the high accuracy for both long-term and short-term forecast by considering both exogenous factors and time series. The forecasting performance of both linear regression models and time series model are evaluated based on real-life heat demand data for the city of Espoo in Finland by out-of-sample tests for the last 20 full weeks of the year. The results indicate that the proposed linear regression model (T168h) using 168-h demand pattern with midweek holidays classified as Saturdays or Sundays gives the highest accuracy and strong robustness among all the tested models based on the tested forecasting horizon and corresponding data. Considering the parsimony of the input, the ease of use and the high accuracy, the proposed T168h model is the best in practice. The heat demand forecasting model can also be developed for individual buildings if automated meter reading customer measurements are available. This would allow forecasting the heat demand based on more accurate heat consumption

Convergence diagnostics for Eigenvalue problems with linear regression model

International Nuclear Information System (INIS)

Shi, Bo; Petrovic, Bojan

2011-01-01

Although the Monte Carlo method has been extensively used for criticality/Eigenvalue problems, a reliable, robust, and efficient convergence diagnostics method is still desired. Most methods are based on integral parameters (multiplication factor, entropy) and either condense the local distribution information into a single value (e.g., entropy) or even disregard it. We propose to employ the detailed cycle-by-cycle local flux evolution obtained by using mesh tally mechanism to assess the source and flux convergence. By applying a linear regression model to each individual mesh in a mesh tally for convergence diagnostics, a global convergence criterion can be obtained. We exemplify this method on two problems and obtain promising diagnostics results. (author)

Regressão linear geograficamente ponderada em ambiente SIG

Directory of Open Access Journals (Sweden)

Luís Eduardo Ximenes Carvalho

2009-10-01

Full Text Available

Este artigo aborda considerações teóricas e resultados da implementação em ambiente SIG de um modelo confirmatório de estatística espacial — regressão linear geograficamente ponderada (RGP — não disponível em ambiente livre. Os aspectos teóricos deste modelo local de regressão espacial foram amplamente discutidos em virtude da escassa bibliografia existente. O modelo RGP foi implementado na linguagem de programação GISDK do SIG-T TransCAD, utilizando compreensivamente as ferramentas de manipulação, tratamento georreferenciado dos dados e rotinas de análise espacial disponibilizadas em plataformas SIG. Ao final, espera-se ter desenvolvido, ainda que de maneira parcial, uma importante ferramenta que contribuirá para a compreensão e refinamento da modelagem de fenômenos geográficos tão amplamente analisados em estudos de Planejamento de Transportes.

Is income inequality related to childhood dental caries in rich countries?

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Bernabé, Eduardo; Hobdell, Martin H

2010-02-01

The aim of this study was to assess the correlates of income and income inequality with dental caries in a sample of all countries, as well as in rich countries alone. In this ecological study, the authors analyzed national data on income, income inequality and dental caries from 48 countries. Of them, 22 were rich countries (according to World Bank criteria). The authors determined income by gross national income (GNI) per capita (formerly known as gross national product) and income inequality by the Gini coefficient (a measure of income inequality on a scale between 0 and 1). They assessed dental caries according to the decayed, missing, filled teeth (dmft) index in 5- to 6-year-old children. The authors used Pearson and partial correlation coefficients to examine the linear associations of income and income inequality with dental caries. GNI per capita, but not the Gini coefficient, was inversely correlated with the dmft index in the 48 countries. However, the results showed an opposite pattern when analyses were restricted to rich countries (that is, the dmft index was significantly correlated with the Gini coefficient but not with GNI per capita). These findings support the income inequality hypothesis that beyond a certain level of national income, the relationship between income and the population's health is weak. Income inequality was correlated more strongly with dental caries than was income in rich countries. Among rich countries, income inequality is a stronger determinant of childhood dental caries than is absolute income.

Association between dental caries experience and sense of coherence among adolescents and mothers.

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Lage, Carolina Freitas; Fulgencio, Livia Bonfim; Corrêa-Faria, Patricia; Serra-Negra, Junia Maria; Paiva, Saul Martins; Pordeus, Isabela Almeida

2017-09-01

Sense of coherence (SOC) is associated with oral health. Investigate associations between dental caries experience and SOC among mothers and adolescents. A cross-sectional study was conducted with 1195 adolescents and their mothers. Data were collected through a questionnaire, the short version of the SOC and oral clinical examinations. The data were statistically analyzed using bivariate analysis, Poisson regression models with robust variance, and Spearman's correlation coefficient. The prevalence of dental caries experience was 41.8%. A moderate correlation was found between the SOC of mothers and adolescents (r = 0.563; P caries experience in the adolescents. The prevalence of dental caries experience was higher among adolescents with visible plaque (Model 1-PR: 1.77; 95% CI: 1.53-2.04; Model 2-PR: 1.59; 95% CI: 1.37-1.84) and those whose families were in a lower economic class (Model 1-PR: 1.56; 95% CI: 1.35-1.80; Model 2-PR: 1.57; 95% CI: 1.36-1.81). Dental caries in adolescents was associated with social determinants evaluated through the sense of coherence. © 2016 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Rampant Caries

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Guzman-Armstrong, Sandra

2005-01-01

Although dental caries in the pediatric and adolescent population has consistently declined in the United States, it is still the most common childhood disease. Dental problems are the number one reason for missing school next to the common cold. Dental caries are an infectious, communicable disease resulting in destruction of tooth structure by…

Effect of different frequencies of preventive maintenance treatment on dental caries: five-year observations in general dentistry patients.

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Rosén, Birgitta; Olavi, Göran; Birkhed, Dowen; Edvardsson, Stig; Egelberg, Jan

2004-10-01

A long-term study in adults at a public dental clinic in Sweden was initiated to evaluate the relative effectiveness of prophylactic treatments on the progression of dental caries and periodontal discase. With treatments scheduled every 3rd, 6th, 12th or 18th month, this report presents results on caries for the 3-month, 6-month and 18-month groups, and evaluates the impact of various caries-related risk factors. Caries increment over approximately 5 years was determined by adding clinical and radiographic findings of manifest primary and secondary caries during the study. Overall caries activity among all 105 participating individuals was low to moderate. No significant differences for caries on any of the various tooth surfaces or for total caries were observed among the three groups. Multiple regression analysis with 5-year caries increment as dependent variable showed that the following factors had a statistically significant association with caries increment: percentage filled surfaces at baseline examination, dietary score, plaque score, and number of mutans streptococci and lactobacilli in saliva. Non-significant factors included number of preventive treatments provided during the 5-year interval. The results of this long-term trial suggest that preventive treatments as often as every 3 6 months may not be justified in the case of patients with low to moderate caries activity.

Prevalence of enamel defects and association with dental caries in preschool children.

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Massignan, C; Ximenes, M; da Silva Pereira, C; Dias, L; Bolan, M; Cardoso, M

2016-12-01

This was to evaluate the prevalence of the developmental defects of enamel (DDE) in primary teeth and its association with dental caries. A cross-sectional study with a randomised representative sample was carried out with 1101 children aged 2-5 years enrolled in public preschools (50% prevalence of DDE in primary teeth, a standard error of 3%, and a confidence level of 95%). Three calibrated dentists (K > 0.62) performed clinical examination. Data collected were: sex, age, DDE (Modified DDE Index) and dental caries (WHO). Descriptive analysis, Chi-square test and multinomial logistic regression were applied for data analysis. Among children, 565 (51.3%) were boys; mean age was 3.7 (±0.9 years). The prevalence of enamel defect was 39.1%; the prevalence of diffuse opacities, demarcated opacities and enamel hypoplasia was 25.3, 19.1 and 6.1%, respectively. The prevalence of dental caries was 31.0%, with mean def-t 1.14 (±2.44). Primary teeth with enamel hypoplasia had three times the odds of having dental caries than those with absence of enamel defects (OR = 3.10; 95% CI: 1.91, 5.01). The presence of enamel defects was moderate and associated with dental caries.

Diet and caries-associated bacteria in severe early childhood caries.

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Palmer, C A; Kent, R; Loo, C Y; Hughes, C V; Stutius, E; Pradhan, N; Dahlan, M; Kanasi, E; Arevalo Vasquez, S S; Tanner, A C R

2010-11-01

Frequent consumption of cariogenic foods and bacterial infection are risk factors for early childhood caries (ECC). This study hypothesized that a short diet survey focused on frequency of foods, categorized by putative cariogenicity, would differentiate severe ECC (S-ECC) from caries-free children. Children's diets were obtained by survey and plaque bacteria detected by PCR from 72 S-ECC and 38 caries-free children. S-ECC children had higher scores for between-meal juice (p cariogenicity (p cariogenicity scores. Food frequency, putative cariogenicity, and S. mutans were associated with S-ECC individually and in combination.

Enhancement of Visual Field Predictions with Pointwise Exponential Regression (PER) and Pointwise Linear Regression (PLR).

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Morales, Esteban; de Leon, John Mark S; Abdollahi, Niloufar; Yu, Fei; Nouri-Mahdavi, Kouros; Caprioli, Joseph

2016-03-01

The study was conducted to evaluate threshold smoothing algorithms to enhance prediction of the rates of visual field (VF) worsening in glaucoma. We studied 798 patients with primary open-angle glaucoma and 6 or more years of follow-up who underwent 8 or more VF examinations. Thresholds at each VF location for the first 4 years or first half of the follow-up time (whichever was greater) were smoothed with clusters defined by the nearest neighbor (NN), Garway-Heath, Glaucoma Hemifield Test (GHT), and weighting by the correlation of rates at all other VF locations. Thresholds were regressed with a pointwise exponential regression (PER) model and a pointwise linear regression (PLR) model. Smaller root mean square error (RMSE) values of the differences between the observed and the predicted thresholds at last two follow-ups indicated better model predictions. The mean (SD) follow-up times for the smoothing and prediction phase were 5.3 (1.5) and 10.5 (3.9) years. The mean RMSE values for the PER and PLR models were unsmoothed data, 6.09 and 6.55; NN, 3.40 and 3.42; Garway-Heath, 3.47 and 3.48; GHT, 3.57 and 3.74; and correlation of rates, 3.59 and 3.64. Smoothed VF data predicted better than unsmoothed data. Nearest neighbor provided the best predictions; PER also predicted consistently more accurately than PLR. Smoothing algorithms should be used when forecasting VF results with PER or PLR. The application of smoothing algorithms on VF data can improve forecasting in VF points to assist in treatment decisions.

Knowledge and beliefs concerning early childhood caries from mothers of children ages zero to 12 months.

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Azevedo, Marina Sousa; Romano, Ana Regina; Dos Santos, Iná da Silva; Cenci, Maximiliano Sergio

2014-01-01

This study's purpose was to assess mothers' knowledge and beliefs about early childhood caries (ECC) etiology and prevention. This cross-sectional study targeted mothers (N=277) of zero- to 12-month-olds visiting 12 public health care centers in Pelotas, Rio Grande do Sul, Brazil. Information on causes of and recommendations to prevent ECC, as well as socioeconomic and demographic variables, was collected. Chi-square, univariate, and multiple logistic regression analyses were performed (Pinfluence caries in their children. None reported the role of micro-organisms and lack of fluoride in the caries etiology. These findings highlight the importance of providing preventive orientation to the mothers regarding early childhood caries. Information on age of first dental visit should be emphasized, especially among mothers with more than one child and low-income families.

DD Genotype of ACE I/D Polymorphism Might Confer Protection against Dental Caries in Polish Children.

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Olszowski, Tomasz; Adler, Grażyna; Janiszewska-Olszowska, Joanna; Safranow, Krzysztof; Chlubek, Dariusz

2015-01-01

The aim of the study was to examine the frequencies of the genotypes and alleles of ACE insertion/deletion (I/D) polymorphism and their association with dental caries in a sample of Polish children. The study subjects were 120 children with dental caries experience (cases) and 41 caries-free individuals (controls). The genotyping was performed using polymerase chain reaction. The genotype distributions of ACE I/D polymorphism were not statistically different between carious and control children. However, we found a borderline overrepresentation of the II + ID genotypes versus the DD genotype in the carious compared to the control group (69.2% and 51.2%, respectively, p = 0.057). Logistic regression analysis adjusted for age and sex revealed that I allele carriage was a significant predictor of dental caries susceptibility (OR = 2.14, 95% CI = 1.02-4.49, p = 0.041). In conclusion, the DD genotype of ACE I/D polymorphism might be protective against dental caries in Polish children. © 2015 S. Karger AG, Basel.

Time until first dental caries for young children first seen in Federally Qualified Health Centers: a retrospective cohort study.

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Kuthy, Raymond A; Jones, Michael; Kavand, Golnaz; Momany, Elizabeth; Askelson, Natoshia; Chi, Donald; Wehby, George; Damiano, Peter

2014-08-01

The study assessed the time until first dental caries for young children seen at five Federally Qualified Health Centers (FQHC) in Iowa and the relationship with the frequency and gaps (in months) of dental episodes, the number of topical fluoride treatments, and the number of dentists caring for the subject. Forty children were randomly selected at each FQHC (n = 200). All children were continuously enrolled in the Medicaid program and had their first dental visit prior to age 6. Dental chart findings, claims data for the child and family, and birth certificate information were merged into one dataset. Dental visits were followed for a minimum of 36 months, including dental visits external to the FQHCs. Using time until first caries as the dependent variable, the data were subject to left, interval, and right censoring and were analyzed via Weibull regression. Slightly more than half of the 200 children experienced caries. Regression analysis indicated that the hazard of first dental caries increased by approximately 2% with each additional month that transpired between preventive recall examinations. In addition, children with older siblings who had a dental visit at the same center during the previous year prior to the subject's first visit were more likely to have a longer time until first dental caries. Timing of dental care episodes was associated with caries experience in young children from low income families. Dental professionals should focus on regularity of dental care to prevent or delay caries experience in young children. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Time until first dental caries for young children first seen in Federally Qualified Health Centers: a retrospective cohort study

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Kuthy, RA; Jones, M; Kavand, G; Momany, E; Askelson, N; Chi, D; Wehby, G; Damiano, P

2014-01-01

Objective The study assessed the time until first dental caries for young children seen at 5 Federally Qualified Health Centers (FQHC) in Iowa and the relationship with the frequency and gaps (in months) of dental episodes, the number of topical fluoride treatments, and the number of dentists caring for the subject. Methods Forty children were randomly selected at each FQHC (n=200). All children were continuously enrolled in the Medicaid program and had their first dental visit prior to age 6. Dental chart findings, claims data for the child and family, and birth certificate information were merged into one dataset. Dental visits were followed for a minimum of 36 months, including dental visits external to the FQHCs. Using time until first caries as the dependent variable, the data were subject to left, interval, and right censoring and were analyzed via Weibull regression. Results Slightly more than half of the 200 children experienced caries. Regression analysis indicated that the hazard rate of first dental caries increased by approximately 2% with each additional month that transpired between preventive recall examinations. In addition, children with older siblings who had a dental visit at the same center during the previous year prior to the subject’s first visit were more likely to have a longer time until first dental caries. Conclusions Timing of dental care episodes was associated with caries experience in young children from low income families. Dental professionals should focus on regularity of dental care in order to prevent or delay caries experience in young children. PMID:24483730

Dental Caries and Associated Factors in Children Aged 2-4 Years Old in Mbeya City, Tanzania

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Mwakayoka, Hery; Masalu, Joyce Rose; Namakuka Kikwilu, Emil

2017-01-01

Statement of the Problem: Dental caries in infants and young children is prevalent worldwide; its magnitude and associated factors vary between communities because of cultural and social economic differences. No such information was available for pre-school children in Mbeya city. Purpose: To determine dental caries status and associated factors in 2 to 4-year-old children in Mbeya city. Materials and Method: A cross sectional study was conducted among 525 children aged 2-4 years and their parents/caregivers. Caries was assessed using caries assessment spectrum and treatment index, oral hygiene by visual inspection for visible plaque on index teeth, and dietary and oral hygiene habits by a questionnaire. Kappa statistics was used to test reliability of study instruments, χ2-test and logistic regression was employed for studying associations. Results: Caries free children for dmft1, dmft2 and dmft3 were 79.8%, 83.8% and 94.7% and caries experience was 0.49 (1.23), 0.4 (1.14) and 0.10 (0.53) respectively. Older age [(OR =2.722 (1.617-4.582) p=caries. Prolonged breastfeeding for more than 1 year and breastfeeding at night had no association with dental caries. Conclusion: The prevalence of dental caries was very low. Older age and frequent consumption of factory made sugary foods at age 1-2 years were associated with higher odds of developing dental caries. Prolonged breasfeeding and breastfeeding at night had no association with dental caries. Prevention of dental caries should be instituted as soon as primary teeth start erupting, especially through discouraging consumption of factory made sugary foods/snacks. PMID:28620634

Epidemiology of dental caries among adolescents in Tamil Nadu, India.

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Veerasamy, Arthi; Kirk, Ray; Gage, Jeffrey

2016-06-01

Economic and dietary changes in the Indian state of Tamil Nadu have led to compromised oral health status of the adolescent population. Adequate epidemiological data are not available to address the prevention or treatment needs in this region of India. The aim of this study was to measure the prevalence and severity of dental caries among adolescents of Tamil Nadu, a southern state of India. The study sample included 974 adolescent school students (12-15 years of age) from both rural and urban areas of Tamil Nadu, India. The decayed, missing and filled teeth (DMFT) index of these students was measured using the World Health Organization oral health survey method, in a quantitative cross-sectional study. The oral health survey indicated that the prevalence of dental caries among adolescents in rural and urban areas of Tamil Nadu was 61.4%, with an average DMFT score of 2.03. Multiple regression analyses indicated factors such as gender, mother's education, type of school and caste as significant predictors of dental caries. Female gender, Scheduled Caste and Tribes attending public schools in rural areas were identified as the more vulnerable populations to be affected by dental caries. Oral health policies should be targeted to these adolescent populations in the Tamil Nadu region. © 2016 FDI World Dental Federation.

[Multiple linear regression analysis of X-ray measurement and WOMAC scores of knee osteoarthritis].

Science.gov (United States)

Ma, Yu-Feng; Wang, Qing-Fu; Chen, Zhao-Jun; Du, Chun-Lin; Li, Jun-Hai; Huang, Hu; Shi, Zong-Ting; Yin, Yue-Shan; Zhang, Lei; A-Di, Li-Jiang; Dong, Shi-Yu; Wu, Ji

2012-05-01

To perform Multiple Linear Regression analysis of X-ray measurement and WOMAC scores of knee osteoarthritis, and to analyze their relationship with clinical and biomechanical concepts. From March 2011 to July 2011, 140 patients (250 knees) were reviewed, including 132 knees in the left and 118 knees in the right; ranging in age from 40 to 71 years, with an average of 54.68 years. The MB-RULER measurement software was applied to measure femoral angle, tibial angle, femorotibial angle, joint gap angle from antero-posterir and lateral position of X-rays. The WOMAC scores were also collected. Then multiple regression equations was applied for the linear regression analysis of correlation between the X-ray measurement and WOMAC scores. There was statistical significance in the regression equation of AP X-rays value and WOMAC scores (Pregression equation of lateral X-ray value and WOMAC scores (P>0.05). 1) X-ray measurement of knee joint can reflect the WOMAC scores to a certain extent. 2) It is necessary to measure the X-ray mechanical axis of knee, which is important for diagnosis and treatment of osteoarthritis. 3) The correlation between tibial angle,joint gap angle on antero-posterior X-ray and WOMAC scores is significant, which can be used to assess the functional recovery of patients before and after treatment.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

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Choi, Jae-Seok; Kim, Munchurl

2017-03-01

Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower

Association between body mass index and dental caries among special care female children in Makkah City.

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Ashour, Nisreen Adnan; Ashour, Amal Adnan; Basha, Sakeena

2018-01-01

Dental caries and obesity are multifactorial diseases with diet being a common contributory factor. The main purpose of the present study was to investigate the association between dental caries and obesity among special care female school children in Makkah City, Saudi Arabia. Analytical cross-sectional study. Special schools in Makkah City. Schools were chosen by lottery and female children were ran.domly selected. Dental caries detection was performed according to the World Health Organization criteria. The medical evaluation assessed the body mass index (BMI). With appropriate sample weighting, relationships between dmft/DMFT (decayed, missing, filled teeth for deciduous and permanent dentition) and obesity were assessed using multilevel logistic regression. In 275 special care children, the prevalence of dental caries was 56.7 percent. The mean dmft and DMFT scores for the entire study population were 3.9 (4.8) and 3.2 (4.1), respectively. Forty percent of children were mentally retarded, 22.2% presented with deafness, blindness or both, 18.9% presented with Down syndrome and 14.9% were autistic. From the total sample, the mean BMI was 20.2 (2.8). When adjusted for covariates, the logistic regression model showed strong association between caries and obesity (adjusted odds ratio=2.9; 95% CI=1.2-4.9). This study demonstrated a significant association between caries frequency and overweight/obesity in special care school children. Since the data was cross-sectional, causal relationships cannot be established and the observed association could be due to other unexplored factors. Because of cultural and ethical consideration, including segregation of gender in Saudi Arabia, only female children were included in the present study, which limited the findings.

Using the classical linear regression model in analysis of the dependences of conveyor belt life

Directory of Open Access Journals (Sweden)

Miriam Andrejiová

2013-12-01

Full Text Available The paper deals with the classical linear regression model of the dependence of conveyor belt life on some selected parameters: thickness of paint layer, width and length of the belt, conveyor speed and quantity of transported material. The first part of the article is about regression model design, point and interval estimation of parameters, verification of statistical significance of the model, and about the parameters of the proposed regression model. The second part of the article deals with identification of influential and extreme values that can have an impact on estimation of regression model parameters. The third part focuses on assumptions of the classical regression model, i.e. on verification of independence assumptions, normality and homoscedasticity of residuals.

Early Childhood Dental Caries, Mouth Pain, and Malnutrition in the Ecuadorian Amazon Region.

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So, Marvin; Ellenikiotis, Yianni A; Husby, Hannah M; Paz, Cecilia Leonor; Seymour, Brittany; Sokal-Gutierrez, Karen

2017-05-22

Malnutrition and dental caries in early childhood remain persistent and intertwined global health challenges, particularly for indigenous and geographically-remote populations. To examine the prevalence and associations between early childhood dental caries, parent-reported mouth pain and malnutrition in the Amazonian region of Ecuador, we conducted a cross-sectional study of the oral health and nutrition status of 1407 children from birth through age 6 in the "Alli Kiru" program (2011-2013). We used multivariate regression analysis to examine relationships between severe caries, parent-reported mouth pain measures, and nutritional status. The prevalence of dental caries was 65.4%, with 44.7% of children having deep or severe caries, and 33.8% reporting mouth pain. The number of decayed, missing and filled teeth (dmft) increased dramatically with age. Malnutrition was prevalent, with 35.9% of children stunted, 1.1% wasted, 7.4% underweight, and 6.8% overweight. As mouth pain increased in frequency, odds for severe caries increased. For each unit increase in mouth pain frequency interfering with sleeping, children had increased odds for being underweight (Adjusted Odds Ratio (AOR): 1.27; 95% CI: 1.02-1.54) and decreased odds for being overweight (AOR: 0.76; 95% CI: 0.58-0.97). This relationship was most pronounced among 3-6 year-olds. Early childhood caries, mouth pain and malnutrition were prevalent in this sample of young children. Parent-reported mouth pain was associated with severe caries, and mouth pain interfering with sleeping was predictive of poor nutritional status. We demonstrate the utility of a parsimonious parent-reported measure of mouth pain to predict young children's risk for severe early childhood caries and malnutrition, which has implications for community health interventions.

Caries prevalence and fluoride use in low SES children in Clermont-Ferrand (France).

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Tubert-Jeannin, S; Riordan, P J; Manevy, R; Lecuyer, M M; Pegon-Machat, E

2009-03-01

To evaluate the association between dental caries experience and preventive behaviours of children residing in a deprived area in Clermont-Ferrand (France). All 4-5 yr-olds attending nine schools in deprived areas of the city were invited to participate and 81% (n=282) consented and were examined. Dental caries was recorded at the dentine threshold. Parents completed a questionnaire concerning family demographics and the child's use of fluoride. Non-parametric tests and logistic regression assessed the relative importance of SES and fluoride variables on dental status (dt>1). Fifty four (19%) of the examined children were living in families with an immigrant background, 33% were fully covered by the national health insurance programme for deprived families. Caries experience was high; mean dft was 1.94 (3.31) and 30% of the children had >1 carious teeth. Thirty percent of the families reported using fluoridated salt. Tooth brushing once daily was reported for 39% and twice daily for 26%. Parents declared supervising tooth brushing for 60%. Two thirds of the children, according to their parents, used fluoride supplement between birth and two years. Supervised tooth brushing was significantly correlated with lower mean dt scores. Systemic fluoride use was poorly related to dental caries Immigrant background, family size, type of health insurance and mother's unemployment were significantly correlated with caries prevalence. In multivariate analysis, immigrant status, supervised tooth brushing and parental knowledge about fluoride in toothpastes were significant caries predictors. The majority of low SES children did not practice effective caries prevention; few reported twice daily brushing with fluoride toothpaste. Caries experience was very high and much was untreated. Immigrant status, supervised tooth brushing and parental knowledge about fluoride in toothpastes were significant caries predictors.

Diabetes enhances dental caries and apical periodontitis in caries-susceptible WBN/KobSlc rats.

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Kodama, Yasushi; Matsuura, Masahiro; Sano, Tomoya; Nakahara, Yutaka; Ozaki, Kiyokazu; Narama, Isao; Matsuura, Tetsuro

2011-02-01

Many epidemiologic studies have suggested that diabetes may be an important risk factor for periodontal disease. To determine whether diabetes induces or enhances periodontal disease or dental caries, dental tissue from diabetic male and nondiabetic female WBN/KobSlc rats and male and female age-matched nondiabetic F344 rats was analyzed morphologically and morphometrically for these 2 types of lesions. Soft X-ray examination revealed that the incidence and severity of both molar caries and alveolar bone resorption were much higher in male WBN/KobSlc rats with chronic diabetes than in nondiabetic female rats of the same strain. Histopathologic examination showed that dental caries progressed from acute to subacute inflammation due to bacterial infections and necrosis in the pulp when the caries penetrated the dentin. In the most advanced stage of dental caries, inflammatory changes caused root abscess and subsequent apical periodontitis, with the formation of granulation tissue around the dental root. Inflammatory changes resulted in resorption of alveolar bone and correlated well with the severity of molar caries. Our results suggest that diabetic conditions enhance dental caries in WBN/KobSlc rats and that periodontal lesions may result from the apical periodontitis that is secondary to dental caries.

Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

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Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

2008-01-01

This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

Prevalence and Correlates of Dental Caries in an Elderly Population in Northeast China

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Liu, Lu; Zhang, Ying; Wu, Wei; Cheng, Min; Li, Yan; Cheng, Ruibo

2013-01-01

Objectives The present study aimed to investigate the prevalence and correlates of dental caries in elderly population in northeast China. Methods A community-based, cross-sectional study among 2376 elderly subjects (age: 65–74 years) from nine urban areas and nine rural areas in three provinces of northeast China was conducted using multistage stratified random sampling per the World Health Organization oral health survey methodology. Decayed-missing-filled teeth (DMFT) and decayed-filled teeth (DFT) indices were used to evaluate the prevalence of dental caries. Face-to-face questionnaire survey on oral health was performed in a randomly selected subset (n = 1197). T test and chi square test were employed to compare groups for continuous and categorical variables, respectively. Multivariate logistic regression was used to estimate odds ratios (ORs) and corresponding confidence intervals (CIs). Results 67.5% of elderly subjects reported dental caries (average DFT = 2.68±3.40), and the prevalence was higher in urban areas (Pcaries accounted for 2.08% with a rate higher in urban areas (Pdental insurance (OR 2.050; 95% CI 1.120–3.754) with dental caries. Conclusions The prevalence of dental caries in the elderly population in northeast China is high. The elderly from urban areas who smoke and who do not have a dental insurance are at a higher risk to develop dental caries. PMID:24260129

Can prevention eliminate caries?

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O'Mullane, D

1995-07-01

There are four main factors involved in the carious process: at-risk tooth structure, plaque flora, fermentable carbohydrates, and time. Based on our knowledge of the carious process, four main preventive strategies have been developed over the years, namely, fluorides, fissure sealing, dietary choice, and plaque control. Fluorides are having a major impact on smooth-surface caries; hence, strategies combining fluorides and fissure sealing are very effective. However, use of fissure sealing is still problematic. Changing dietary practices with a view to reducing dental caries seems to be having little impact on a global scale. Plaque control, as practiced routinely by the majority of people, is not sufficient to result in caries reductions. Deprivation and poverty are strongly associated with high caries levels. Although the preventive strategies currently available are likely to result in lower caries levels for many, for logistical reasons and because of factors associated with deprivation and poverty, caries is likely to remain a major public health problem in most communities for the foreseeable future.

Dental caries, periodontal disease, and cardiac arrhythmias in community-dwelling older persons aged 80 and older: is there a link?

DEFF Research Database (Denmark)

Holm-Pedersen, Poul; Avlund, Kirsten; Morse, Douglas E

2005-01-01

lesions had 2.8 times higher odds (95% confidence interval=1.1-7.0) of arrhythmia than persons without active coronal caries, but there was no greater risk for persons with three or more coronal caries lesions. There was no association between periodontal disease and arrhythmia. CONCLUSION: The findings......OBJECTIVES: To examine whether caries or periodontitis is associated with cardiac arrhythmias in community-dwelling people aged 80 and older. SETTING: Urban, community-based population in Stockholm, Sweden. DESIGN: Cross-sectional. PARTICIPANTS: Eligible persons were identified through...... by a physician or the Stockholm Inpatient Register. Active root caries, active coronal caries, and periodontitis were assessed using previously defined National Institute of Dental and Craniofacial Research diagnostic criteria. RESULTS: The primary finding of the multivariate logistic regression analysis...

Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models.

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Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei

2014-01-01

The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

Disparities in untreated caries among children and adults in the U.S., 2011-2014.

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Gupta, Niodita; Vujicic, Marko; Yarbrough, Cassandra; Harrison, Brittany

2018-03-06

The Affordable Care Act of 2010 increased dental coverage for children in the United States, (U.S.) but not for adults. Few studies in current scholarship make use of up-to-date, nationally representative data to examine oral health disparities in the U.S. The purpose of this study is to use nationally representative data to determine the prevalence of untreated caries among children and adults of different socioeconomic and racial/ethnic groups and to examine the factors associated with untreated caries among children and adults. This study used the 2011-2014 National Health and Nutrition Examination Survey (NHANES) demographic, oral health questionnaire, and oral health dentition examination data (n = 7008 for children; n = 9673 for adults). Participants that had a standardized oral health examination and at least one natural primary or permanent tooth considering 28 tooth spaces were included in this study. Our main outcome measure was untreated coronal caries defined as decay on the crown or enamel surface of a tooth that had not been treated or filled. Population estimates were calculated to determine the prevalence of untreated caries among children and adults in the United States. Frequencies and Pearson's chi-square tests were used to compare those with and without untreated caries. Multivariate logistic regression models were used to evaluate the factors associated with untreated caries. We conducted analyses among children and adults separately. From 2011 to 2014, 12.4 million children and 57.6 million adults in the United States had untreated caries. Age, family income level, recent dental visit, and financial and non-financial barriers were significantly associated with untreated caries in both children and adults. Race/ethnicity, gender and education level were also significantly associated with untreated caries among adults. The odds of untreated caries associated with financial barriers were 2.06 for children and 2.84 for adults while the

Maternal identification of dental caries lesions in their children aged 1-3 years.

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Fernandes, I B; Sá-Pinto, A C; Silva Marques, L; Ramos-Jorge, J; Ramos-Jorge, M L

2017-06-01

To analyse the maternal identification of different stages of dental caries in children aged 1-3 years. A cross-sectional study was conducted with 274 children and their mothers. The mothers answered a questionnaire on the occurrence of dental caries in their children and completed questions addressing their demographic/socio-economic status. The oral examination of the children was performed using the International Caries Detection and Assessment System. Descriptive, Chi square test and Poisson regression statistical analyses were performed. The prevalence of initial and established/severe dental caries lesions by age were: 1 year (23.2 and 24.2%), 2 years (17.9 and 55.7%) and 3 years (23.3 and 60.3%) respectively. Significant associations between clinical examinations and the mothers' reports were observed among children aged 1 year old who had initial stage caries lesions (p = 0.006) and in children aged 1, 2 and 3 years old who had established/severe stage caries lesions (p dental caries both at initial (PR 4.01, 95% CI 1.35-11.94) and established/severe stages (PR 9.14, 95% CI 2.49-33.56) in children aged 1 year old. In children aged 2 and 3 years, this identification was more evident in the established/severe stage (2 years, PR 2.98, 95% CI 1.42-6.26; 3 years, PR 2.75, 95% CI 1.09-6.93). Mothers of children aged 1 year old identified dental caries at initial and established/severe stages. Mothers of children aged 2 and 3 years identified dental caries only at established/severe stages.

Revitalising Silver Nitrate for Caries Management

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Sherry Shiqian Gao

2018-01-01

Full Text Available Silver nitrate has been adopted for medical use as a disinfectant for eye disease and burned wounds. In dentistry, it is an active ingredient of Howe’s solution used to prevent and arrest dental caries. While medical use of silver nitrate as a disinfectant became subsidiary with the discovery of antibiotics, its use in caries treatment also diminished with the use of fluoride in caries prevention. Since then, fluoride agents, particularly sodium fluoride, have gained popularity in caries prevention. However, caries is an infection caused by cariogenic bacteria, which demineralise enamel and dentine. Caries can progress and cause pulpal infection, but its progression can be halted through remineralisation. Sodium fluoride promotes remineralisation and silver nitrate has a profound antimicrobial effect. Hence, silver nitrate solution has been reintroduced for use with sodium fluoride varnish to arrest caries as a medical model strategy of caries management. Although the treatment permanently stains caries lesions black, this treatment protocol is simple, painless, non-invasive, and low-cost. It is well accepted by many clinicians and patients and therefore appears to be a promising strategy for caries control, particularly for young children, the elderly, and patients with severe caries risk or special needs.

Factors associated with dental caries in the primary dentition of children with cerebral palsy

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Luana Leal Roberto

2012-10-01

Full Text Available The aim of this study was to investigate factors associated with caries experience in the primary dentition of one- to five-year-old children with cerebral palsy. A total of 266 dental records were examined, and caries experience was measured by dmft. The following variables were also analyzed: gender, oral hygiene, history of gastroesophageal reflux, use of medications for gastroesophageal reflux, gingival status, sugar intake and reports of polyuria, excessive thirst and xerostomia. For analysis purposes, the individuals were categorized as those with and without caries experience and subcategorized into the following age groups: one year; two to three years; and four to five years. After bivariate analysis, variables with a p-value < 0.25 were selected for incorporation into the Poisson regression models. Considering the limitations of the protocol, the level of oral hygiene perceived on the first appointment was the only factor associated with caries experience among two-to-fiveyear-old children with cerebral palsy.

Sugar Alcohols, Caries Incidence, and Remineralization of Caries Lesions: A Literature Review

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Kauko K. Mäkinen

2010-01-01

Full Text Available Remineralization of minor enamel defects is a normal physiological process that is well known to clinicians and researchers in dentistry and oral biology. This process can be facilitated by various dietary and oral hygiene procedures and may also concern dentin caries lesions. Dental caries is reversible if detected and treated sufficiently early. Habitual use of xylitol, a sugar alcohol of the pentitol type, can be associated with significant reduction in caries incidence and with tooth remineralization. Other dietary polyols that can remarkably lower the incidence of caries include erythritol which is a tetritol-type alditol. Based on known molecular parameters of simple dietary alditols, it is conceivable to predict that their efficacy in caries prevention will follow the homologous series, that is, that the number of OH-groups present in the alditol molecule will determine the efficacy as follows: erythritol≥xylitol>sorbitol. The possible difference between erythritol and xylitol must be confirmed in future clinical trials.

A Feature-Free 30-Disease Pathological Brain Detection System by Linear Regression Classifier.

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Chen, Yi; Shao, Ying; Yan, Jie; Yuan, Ti-Fei; Qu, Yanwen; Lee, Elizabeth; Wang, Shuihua

2017-01-01

Alzheimer's disease patients are increasing rapidly every year. Scholars tend to use computer vision methods to develop automatic diagnosis system. (Background) In 2015, Gorji et al. proposed a novel method using pseudo Zernike moment. They tested four classifiers: learning vector quantization neural network, pattern recognition neural network trained by Levenberg-Marquardt, by resilient backpropagation, and by scaled conjugate gradient. This study presents an improved method by introducing a relatively new classifier-linear regression classification. Our method selects one axial slice from 3D brain image, and employed pseudo Zernike moment with maximum order of 15 to extract 256 features from each image. Finally, linear regression classification was harnessed as the classifier. The proposed approach obtains an accuracy of 97.51%, a sensitivity of 96.71%, and a specificity of 97.73%. Our method performs better than Gorji's approach and five other state-of-the-art approaches. Therefore, it can be used to detect Alzheimer's disease. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Does caries risk assessment predict the incidence of caries for special needs patients requiring general anesthesia?

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Chang, Juhea; Kim, Hae-Young

2014-11-01

The aim of this study was to correlate the caries-related variables of special needs patients to the incidence of new caries. Data for socio-demographic information and dental and general health status were obtained from 110 patients treated under general anesthesia because of their insufficient co-operation. The Cariogram program was used for risk assessment and other caries-related variables were also analyzed. Within a defined follow-up period (16.3 ± 9.5 months), 64 patients received dental examinations to assess newly developed caries. At baseline, the mean (SD) values of the DMFT (decayed, missing and filled teeth) and DT (decayed teeth) for the total patients were 9.2 (6.5) and 5.8 (5.3), respectively. During the follow-up period, new caries occurred in 48.4% of the patients and the mean value (SD) of the increased DMFT (iDMFT) was 2.1 (4.2). The patients with a higher increment of caries (iDMFT ≥3) showed significantly different caries risk profiles compared to the other patients (iDMFT dentistry. Past caries experience and inadequate oral hygiene maintenance were largely related to caries development in special needs patients.

MULTIPLE LINEAR REGRESSION ANALYSIS FOR PREDICTION OF BOILER LOSSES AND BOILER EFFICIENCY

OpenAIRE

Chayalakshmi C.L

2018-01-01

MULTIPLE LINEAR REGRESSION ANALYSIS FOR PREDICTION OF BOILER LOSSES AND BOILER EFFICIENCY ABSTRACT Calculation of boiler efficiency is essential if its parameters need to be controlled for either maintaining or enhancing its efficiency. But determination of boiler efficiency using conventional method is time consuming and very expensive. Hence, it is not recommended to find boiler efficiency frequently. The work presented in this paper deals with establishing the statistical mo...

Bivariate least squares linear regression: Towards a unified analytic formalism. I. Functional models

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Caimmi, R.

2011-08-01

Concerning bivariate least squares linear regression, the classical approach pursued for functional models in earlier attempts ( York, 1966, 1969) is reviewed using a new formalism in terms of deviation (matrix) traces which, for unweighted data, reduce to usual quantities leaving aside an unessential (but dimensional) multiplicative factor. Within the framework of classical error models, the dependent variable relates to the independent variable according to the usual additive model. The classes of linear models considered are regression lines in the general case of correlated errors in X and in Y for weighted data, and in the opposite limiting situations of (i) uncorrelated errors in X and in Y, and (ii) completely correlated errors in X and in Y. The special case of (C) generalized orthogonal regression is considered in detail together with well known subcases, namely: (Y) errors in X negligible (ideally null) with respect to errors in Y; (X) errors in Y negligible (ideally null) with respect to errors in X; (O) genuine orthogonal regression; (R) reduced major-axis regression. In the limit of unweighted data, the results determined for functional models are compared with their counterparts related to extreme structural models i.e. the instrumental scatter is negligible (ideally null) with respect to the intrinsic scatter ( Isobe et al., 1990; Feigelson and Babu, 1992). While regression line slope and intercept estimators for functional and structural models necessarily coincide, the contrary holds for related variance estimators even if the residuals obey a Gaussian distribution, with the exception of Y models. An example of astronomical application is considered, concerning the [O/H]-[Fe/H] empirical relations deduced from five samples related to different stars and/or different methods of oxygen abundance determination. For selected samples and assigned methods, different regression models yield consistent results within the errors (∓ σ) for both

Improving sensitivity of linear regression-based cell type-specific differential expression deconvolution with per-gene vs. global significance threshold.

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Glass, Edmund R; Dozmorov, Mikhail G

2016-10-06

The goal of many human disease-oriented studies is to detect molecular mechanisms different between healthy controls and patients. Yet, commonly used gene expression measurements from blood samples suffer from variability of cell composition. This variability hinders the detection of differentially expressed genes and is often ignored. Combined with cell counts, heterogeneous gene expression may provide deeper insights into the gene expression differences on the cell type-specific level. Published computational methods use linear regression to estimate cell type-specific differential expression, and a global cutoff to judge significance, such as False Discovery Rate (FDR). Yet, they do not consider many artifacts hidden in high-dimensional gene expression data that may negatively affect linear regression. In this paper we quantify the parameter space affecting the performance of linear regression (sensitivity of cell type-specific differential expression detection) on a per-gene basis. We evaluated the effect of sample sizes, cell type-specific proportion variability, and mean squared error on sensitivity of cell type-specific differential expression detection using linear regression. Each parameter affected variability of cell type-specific expression estimates and, subsequently, the sensitivity of differential expression detection. We provide the R package, LRCDE, which performs linear regression-based cell type-specific differential expression (deconvolution) detection on a gene-by-gene basis. Accounting for variability around cell type-specific gene expression estimates, it computes per-gene t-statistics of differential detection, p-values, t-statistic-based sensitivity, group-specific mean squared error, and several gene-specific diagnostic metrics. The sensitivity of linear regression-based cell type-specific differential expression detection differed for each gene as a function of mean squared error, per group sample sizes, and variability of the proportions

Determinant Factors of Untreated Dental Caries and Lesion Activity in Preschool Children Using ICDAS.

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Tássia Cristina de Almeida Pinto-Sarmento

Full Text Available The aim of the present study was to investigate determinant factors associated with the presence of dental caries and lesion activity in preschool children. A population-based, cross-sectional study was carried out with 843 children of aged three to five years enrolled at public and private preschools in the city of Campina Grande, Brazil. A questionnaire addressing socio-demographic data and oral health care was self-administered by parents/caregivers. Three dentists previously calibrated examined the children for the diagnosis of dental caries and lesion activity using the International Caries Detection and Assessment System (ICDAS. Nutritional status was evaluated based on the body mass index. Logistic regression analysis for complex samples was performed (α = 5%. The prevalence of dental caries was 66.3%. Among the children with caries, 88.0% had active lesions. Dental caries was more prevalent in girls (OR = 1.53, 95%CI: 1.05-2.23, in children from families with a monthly household income ≤US$312.50 (OR = 2.38, 95%CI: 1.65-3.43 and those whose mothers had up to eight years of schooling (OR = 1.55, 95%CI: 1.07-2.23. Lesion activity was significantly associated with mother's schooling ≤ 8 years (OR = 2.15, 95%CI: 1.15-4.00. The prevalence rates of dental caries and lesion activity were high and mainly associated with a lower socioeconomic status and mother's schooling.

[Prevalence of dental caries among 12-year old schoolchildren in the Dakar region].

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Benoist, F Leye; Bane, K; Aidara, A W; Ndiaye, D; Chouker, Y; Kane, A W

2014-06-01

Oral diseases are considered as major public health problem. Dental caries restricts the school activities and are the dominant cause of dental morbidity. The aims of this survey were to determine prevalence of dental caries among pupils of Dakar and to study their food habits and oral hygiene. A descriptive transversal study was conducted from February 15th to May 07th, 2011 with respect of WHO directives (protocol of 1997) readjusted to Senegalese context. Our results showed a prevalence of 41.8%; a mean DMF index of 0.644; a proportion of teeth decayed of 65%, 32.2% for missing teeth and 2.7% of filled teeth. The multivariate logistic regression analysis showed that snacking, consumption of sweetened drinks far from meals and brushing teeth before the meals were significantly linked to the presence of dental caries. These results showed that the state of oral health and the prevention level of dental caries among these children were not so good. A new orientation of oral health policy based on messages regarding the main etiologic factors is imperative.

Sociodemographic Variation of Caries Risk Factors in Toddlers and Caregivers

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G. J. Eckert

2010-01-01

Full Text Available Objectives. Dental caries is the most common chronic childhood disease, with numerous identified risk factors. Risk factor differences could indicate the need to target caregiver/patient education/preventive care intervention strategies based on population and/or individual characteristics. The purpose of this study was to evaluate caries risk factors differences by race/ethnicity, income, and education. Methods. We enrolled 396 caregiver-toddler pairs and administered a 105-item questionnaire addressing demographics, access to care, oral bacteria transmission, caregiver's/toddler's dental and medical health practices, caregiver's dental beliefs, and caregiver's/toddler's snacking/drinking habits. Logistic regressions and ANOVAs were used to evaluate the associations of questionnaire responses with caregiver's race/ethnicity, income, and education. Results. Caregivers self-identified as Non-Hispanic African-American (44%, Non-Hispanic White (36%, Hispanic (19%, and “other” (1%. Differences related to race/ethnicity, income, and education were found in all risk factor categories. Conclusions. Planning of caregiver/patient education/preventive care intervention strategies should be undertaken with these caries risk factor differences kept in mind.

Prevalence, risk surfaces and inter-municipality variations in caries experience in Danish children and adolescents in 2012

DEFF Research Database (Denmark)

Nørrisgaard, Pia Elisabeth; Qvist, Vibeke; Ekstrand, Kim

2016-01-01

prevalence by def-s = 0/DMF-S = 0. Inter-municipality variations were illustrated. Multivariate regression analyses were applied to assess the influence of fluoride concentration in drinking water, proportion of immigrants and personal income on the inter-municipality variation in mean def-s/DMF-S. Results......-municipality variation in caries experience. Materials and methods Data was collected in the public Child Dental Health Service. In total, 5636 caries registrations on 3-, 9-, 15- and 18-year-olds were collected in 35 of the 98 Danish municipalities. Caries experience was expressed by mean def-s/DMF-S and caries...... Only 4.6% of 3-year-olds had def-s (mean = 0.25), compared to 44.9% of 9-year-olds (mean = 3.07), primarily located occlusally and interproximally on the primary molars. Mean DMF-S for the 9-, 15- and 18-year-olds were 0.27, 1.97 and 4.40, respectively. Caries were primarily located occlusally...

On the Relationship Between Confidence Sets and Exchangeable Weights in Multiple Linear Regression.

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Pek, Jolynn; Chalmers, R Philip; Monette, Georges

2016-01-01

When statistical models are employed to provide a parsimonious description of empirical relationships, the extent to which strong conclusions can be drawn rests on quantifying the uncertainty in parameter estimates. In multiple linear regression (MLR), regression weights carry two kinds of uncertainty represented by confidence sets (CSs) and exchangeable weights (EWs). Confidence sets quantify uncertainty in estimation whereas the set of EWs quantify uncertainty in the substantive interpretation of regression weights. As CSs and EWs share certain commonalities, we clarify the relationship between these two kinds of uncertainty about regression weights. We introduce a general framework describing how CSs and the set of EWs for regression weights are estimated from the likelihood-based and Wald-type approach, and establish the analytical relationship between CSs and sets of EWs. With empirical examples on posttraumatic growth of caregivers (Cadell et al., 2014; Schneider, Steele, Cadell & Hemsworth, 2011) and on graduate grade point average (Kuncel, Hezlett & Ones, 2001), we illustrate the usefulness of CSs and EWs for drawing strong scientific conclusions. We discuss the importance of considering both CSs and EWs as part of the scientific process, and provide an Online Appendix with R code for estimating Wald-type CSs and EWs for k regression weights.

Significance tests to determine the direction of effects in linear regression models.

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Wiedermann, Wolfgang; Hagmann, Michael; von Eye, Alexander

2015-02-01

Previous studies have discussed asymmetric interpretations of the Pearson correlation coefficient and have shown that higher moments can be used to decide on the direction of dependence in the bivariate linear regression setting. The current study extends this approach by illustrating that the third moment of regression residuals may also be used to derive conclusions concerning the direction of effects. Assuming non-normally distributed variables, it is shown that the distribution of residuals of the correctly specified regression model (e.g., Y is regressed on X) is more symmetric than the distribution of residuals of the competing model (i.e., X is regressed on Y). Based on this result, 4 one-sample tests are discussed which can be used to decide which variable is more likely to be the response and which one is more likely to be the explanatory variable. A fifth significance test is proposed based on the differences of skewness estimates, which leads to a more direct test of a hypothesis that is compatible with direction of dependence. A Monte Carlo simulation study was performed to examine the behaviour of the procedures under various degrees of associations, sample sizes, and distributional properties of the underlying population. An empirical example is given which illustrates the application of the tests in practice. © 2014 The British Psychological Society.

Multiple linear regression analysis

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Edwards, T. R.

1980-01-01

Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

Contemporary operative caries management: consensus recommendations on minimally invasive caries removal

NARCIS (Netherlands)

Banerjee, A.; Frencken, J.E.F.M.; Schwendicke, F.; Innes, N.P.

2017-01-01

The International Caries Consensus Collaboration (ICCC) presented recommendations on terminology, on carious tissue removal and on managing cavitated carious lesions. It identified 'dental caries' as the name of the disease that dentists should manage, and the importance of controlling the activity

Dynamic Optimization for IPS2 Resource Allocation Based on Improved Fuzzy Multiple Linear Regression

Directory of Open Access Journals (Sweden)

Maokuan Zheng

2017-01-01

Full Text Available The study mainly focuses on resource allocation optimization for industrial product-service systems (IPS2. The development of IPS2 leads to sustainable economy by introducing cooperative mechanisms apart from commodity transaction. The randomness and fluctuation of service requests from customers lead to the volatility of IPS2 resource utilization ratio. Three basic rules for resource allocation optimization are put forward to improve system operation efficiency and cut unnecessary costs. An approach based on fuzzy multiple linear regression (FMLR is developed, which integrates the strength and concision of multiple linear regression in data fitting and factor analysis and the merit of fuzzy theory in dealing with uncertain or vague problems, which helps reduce those costs caused by unnecessary resource transfer. The iteration mechanism is introduced in the FMLR algorithm to improve forecasting accuracy. A case study of human resource allocation optimization in construction machinery industry is implemented to test and verify the proposed model.

A Linear Regression Model for Global Solar Radiation on Horizontal Surfaces at Warri, Nigeria

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Michael S. Okundamiya

2013-10-01

Full Text Available The growing anxiety on the negative effects of fossil fuels on the environment and the global emission reduction targets call for a more extensive use of renewable energy alternatives. Efficient solar energy utilization is an essential solution to the high atmospheric pollution caused by fossil fuel combustion. Global solar radiation (GSR data, which are useful for the design and evaluation of solar energy conversion system, are not measured at the forty-five meteorological stations in Nigeria. The dearth of the measured solar radiation data calls for accurate estimation. This study proposed a temperature-based linear regression, for predicting the monthly average daily GSR on horizontal surfaces, at Warri (latitude 5.020N and longitude 7.880E an oil city located in the south-south geopolitical zone, in Nigeria. The proposed model is analyzed based on five statistical indicators (coefficient of correlation, coefficient of determination, mean bias error, root mean square error, and t-statistic, and compared with the existing sunshine-based model for the same study. The results indicate that the proposed temperature-based linear regression model could replace the existing sunshine-based model for generating global solar radiation data. Keywords: air temperature; empirical model; global solar radiation; regression analysis; renewable energy; Warri

Caries detection in dental radiographs

International Nuclear Information System (INIS)

Dunn, S.M.

1987-01-01

Caries, or the decay of teeth are difficult to automatically detect in dental radiographs because of the small area of the image that is occupied by the decay. Images of dental radiographs has distinct regions of homogeneous gray levels, and therefore naturally lead to a segmentation based automatic caries detection algorithm. This paper describes a method for caries detection based on a multiclass, area independent thresholding and segmenting scheme. This multiclass thresholding algorithm is an extension of the uniform error threshold, an area independent, distribution free thresholding method used for images of only two classes of objects. The authors first consider the problem of caries detection and the image features that characterize the presence of caries. Next, the uniform error threshold is reviewed, and the general multiclass uniform error threshold algorithm is presented. This algorithm is used to automatically detect caries in dental radiographs

Partitioning of late gestation energy expenditure in ewes using indirect calorimetry and a linear regression approach

DEFF Research Database (Denmark)

Kiani, Alishir; Chwalibog, André; Nielsen, Mette O

2007-01-01

Late gestation energy expenditure (EE(gest)) originates from energy expenditure (EE) of development of conceptus (EE(conceptus)) and EE of homeorhetic adaptation of metabolism (EE(homeorhetic)). Even though EE(gest) is relatively easy to quantify, its partitioning is problematic. In the present...... study metabolizable energy (ME) intake ranges for twin-bearing ewes were 220-440, 350- 700, 350-900 kJ per metabolic body weight (W0.75) at week seven, five, two pre-partum respectively. Indirect calorimetry and a linear regression approach were used to quantify EE(gest) and then partition to EE......(conceptus) and EE(homeorhetic). Energy expenditure of basal metabolism of the non-gravid tissues (EE(bmng)), derived from the intercept of the linear regression equation of retained energy [kJ/W0.75] and ME intake [kJ/W(0.75)], was 298 [kJ/ W0.75]. Values of the intercepts of the regression equations at week seven...

Current possibilities in occlusal caries management

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Hrvoje Jurić

2013-11-01

Full Text Available Dental caries is a multifactorial disease that affects most populations throughout the world and it is still the primary cause of oral pain and tooth loss. The occlusal surfaces of posterior teeth are the most vulnerable sites for dental caries due to their anatomy. Therefore, the aim of the following article is to summarize current knowledge on occlusal caries development and the possibilities of its prevention. Although the overall caries rate today has fallen for populations in industrialized countries, the rate of occlusal surface caries has not decreased. This may be explained with fact that topically applied fluorides and their mode of action prevent caries better on smooth than on occlusal surfaces. As we know, tooth decay of first permanent molars causes a great deal of different short and long term difficulties for patients. Therefore, there is a continuous need for implementation of programs for caries prevention in permanent teeth. Nowadays, we like to treat our patients by minimally invasive methods. A very important step in our effective preventive treatment is sealing pits and fissures as a cornerstone of occlusal caries management. Reliable assessment of caries activity is also very important for defining treatment needs and plans. A very important decision, which should be made during occlusal caries management, is the selection of restorative material according to the treatment plan. Conclusion. Current possibilities in occlusal caries prevention and management are very effective. Therefore, dentists today do not have any excuse for avoiding the philosophy of Minimally Invasive Dentistry, especially when we talk about caries management of occlusal surfaces in permanent molars.

Suppression Situations in Multiple Linear Regression

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Shieh, Gwowen

2006-01-01

This article proposes alternative expressions for the two most prevailing definitions of suppression without resorting to the standardized regression modeling. The formulation provides a simple basis for the examination of their relationship. For the two-predictor regression, the author demonstrates that the previous results in the literature are…

Hyperactive Children are at Risk of Dental Caries -An Analytical Study

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C Jeevika

2013-01-01

Full Text Available Background: Attention-deficit/hyperactivity disorder (ADHD is well recognized in western countries, but there were no much reports of ADHD from India. Aim: To determine the relationship of ADHD with dental caries. Materials & Method : A cross-sectional analytical study was carried out among 120 children aged around 8-15 years who were randomly selected from normal and special schools located in Chennai city. The children were categorized as ADHD according to the criteria of Diagnostic and Statistical Manual of Mental Disorders (DSM-IV.The questionnaire was given to parents and teachers. It included details of DSM- IV criteria, age, sex, demographic details, past dental history, hours diet chart and any medication taken previously. The oral hygiene status was assessed using Oral Hygiene index simplified (OHI-S and the caries experience was recorded using DMFT index. Categorical data were compared by the Chi-square test. The odds ratio (OR was calculated with logistic regression. A multivariate analysis was carried out to adjust for gender, dental caries status of primary and permanent teeth. Results : Males are more in ADHD group when compared to females. Oral Hygiene Status of ADHD group was significantly better than control group. ADHD children were 3.1 times more odds of getting dental caries than children in the control group.

Prevalence and correlates of dental caries in an elderly population in northeast China.

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Liu, Lu; Zhang, Ying; Wu, Wei; Cheng, Min; Li, Yan; Cheng, Ruibo

2013-01-01

The present study aimed to investigate the prevalence and correlates of dental caries in elderly population in northeast China. A community-based, cross-sectional study among 2376 elderly subjects (age: 65-74 years) from nine urban areas and nine rural areas in three provinces of northeast China was conducted using multistage stratified random sampling per the World Health Organization oral health survey methodology. Decayed-missing-filled teeth (DMFT) and decayed-filled teeth (DFT) indices were used to evaluate the prevalence of dental caries. Face-to-face questionnaire survey on oral health was performed in a randomly selected subset (n = 1197). T test and chi square test were employed to compare groups for continuous and categorical variables, respectively. Multivariate logistic regression was used to estimate odds ratios (ORs) and corresponding confidence intervals (CIs). 67.5% of elderly subjects reported dental caries (average DFT = 2.68±3.40), and the prevalence was higher in urban areas (Ppopulation in urban areas (OR 1.713; 95% CI 1.337-2.195), smoking (OR 1.779; 95% CI 1.384-2.288), and individuals without dental insurance (OR 2.050; 95% CI 1.120-3.754) with dental caries. The prevalence of dental caries in the elderly population in northeast China is high. The elderly from urban areas who smoke and who do not have a dental insurance are at a higher risk to develop dental caries.

Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

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Ng, Kar Yong; Awang, Norhashidah

2018-01-06

Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

Bayesian linear regression : different conjugate models and their (in)sensitivity to prior-data conflict

NARCIS (Netherlands)

Walter, G.M.; Augustin, Th.; Kneib, Thomas; Tutz, Gerhard

2010-01-01

The paper is concerned with Bayesian analysis under prior-data conflict, i.e. the situation when observed data are rather unexpected under the prior (and the sample size is not large enough to eliminate the influence of the prior). Two approaches for Bayesian linear regression modeling based on

A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

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Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…

Social support and social network as intermediary social determinants of dental caries in adolescents.

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Fontanini, Humberto; Marshman, Zoe; Vettore, Mario

2015-04-01

The aim of this study was to investigate the association between intermediary social determinants, namely social support and social network with dental caries in adolescents. An adapted version of the WHO social determinants of health conceptual framework was used to organize structural and intermediary social determinants of dental caries into six blocks including perceived social support and number of social networks. A cross-sectional study was conducted with a representative sample of 542 students between 12 and 14 years of age in public schools located in the city of Dourados, Brazil in 2012. The outcome variables were caries experience (DMFT ≥ 1) and current dental caries (component D of DMFT ≥ 1) recorded by a calibrated dentist. Individual interviews were performed to collect data on perceived social support and numbers of social networks from family and friends and covariates. Multivariate Poisson regressions using hierarchical models were conducted. The prevalence of adolescents with caries experience and current dental caries was 55.2% and 32.1%, respectively. Adolescents with low numbers of social networks and low levels of social support from family (PR 1.47; 95% CI = 1.01-2.14) were more likely to have DMFT ≥ 1. Current dental caries was associated with low numbers of social networks and low levels of social support from family (PR 2.26; 95% CI = 1.15-4.44). Social support and social network were influential psychosocial factors to dental caries in adolescents. This finding requires confirmation in other countries but potentially has implications for programmes to promote oral health. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

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MCKissick, Burnell T. (Technical Monitor); Plassman, Gerald E.; Mall, Gerald H.; Quagliano, John R.

2005-01-01

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

The effect of propolis honey candy on Streptococcus mutans prevalence in caries and caries-free subjects

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Soekanto, Sri Angky; Bachtiar, Endang W.; Jiwanakusuma, Pramodanti; Gladea, Zahara; Sahlan, Muhamad

2018-02-01

This study was to evaluate the effect of Propolis Honey candy on Streptococcus mutans prevalence in caries and caries-free subject. The subject of this research was caries and caries-free subjects. The Streptococcus mutans colony was counted in saliva samples before and after a 7-day period of consuming Propolis Honey candy, Honey candy, and "X" candy. The Streptococcus mutans was proliferated in a TYS20B gelatin medium for 48 hours. The number of Streptococcus mutans colonies was expressed in CFU/ml. Compared with the pre-treatment group, the number of Streptococcus mutans colonies in the treatment group tends to show a statistically significant reduction (pcaries-free subject. In caries subject, the result of Propolis honey candy were also lower (2.2×107 CFU/ml) than before (5.8×109 CFU/ml). The study showed a decrease in the number of Streptococcus mutans colonies from caries and caries-free subjects after propolis honey candy consumption.

The relationship between neighborhood empowerment and dental caries experience: a multilevel study in adolescents and adults

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Bianca Marques Santiago

2014-01-01

Full Text Available OBJECTIVE: To investigate the relationship of contextual social capital (neighborhood empowerment and individual social capital (social support and social network with dental caries experience in adolescents and adults. METHODS: A population-based multilevel study was conducted involving 573 subjects, 15-19 and 35-44 years of age, from 30 census tracts in three cities of Paraíba, Brazil. A two-stage cluster sampling was used considering census tracts and households as sampling units. Caries experience was assessed using the DMFT index (decayed, missing and filled teeth and participants were divided into two groups according to the median of the DMFT index in low and high caries experience. Demographic, socioeconomic, behaviors, use of dental services and social capital measures were collected through interviews. Neighborhood empowerment was obtained from the mean scores of the residents in each census tract. Multilevel multivariate logistic regression was used to test the relationship between neighborhood empowerment and caries experience. RESULTS: High caries experience was inversely associated with neighborhood empowerment (OR = 0.58; 95%CI 0.33 - 0.99. Individual social capital was not associated with caries experience. Other associated factors with caries experience were age (OR = 1.15; 95%CI 1.12 - 1.18 and being a female (OR = 1.72; 95%CI 1.08 - 2.73. CONCLUSION: The association between neighborhood empowerment and caries experience suggests that the perception of features of the place of residence should be taken into account in actions of oral health promotion.

Validation of Visual Caries Activity Assessment

DEFF Research Database (Denmark)

Guedes, R S; Piovesan, C; Ardenghi, T M

2014-01-01

We evaluated the predictive and construct validity of a caries activity assessment system associated with the International Caries Detection and Assessment System (ICDAS) in primary teeth. A total of 469 children were reexamined: participants of a caries survey performed 2 yr before (follow-up rate...... of 73.4%). At baseline, children (12-59 mo old) were examined with the ICDAS and a caries activity assessment system. The predictive validity was assessed by evaluating the risk of active caries lesion progression to more severe conditions in the follow-up, compared with inactive lesions. We also...... assessed if children with a higher number of active caries lesions were more likely to develop new lesions (construct validity). Noncavitated active caries lesions at occlusal surfaces presented higher risk of progression than inactive ones. Children with a higher number of active lesions and with higher...

Dental caries among children visiting a mobile dental clinic in South Central Kentucky: a pooled cross-sectional study.

Science.gov (United States)

Dawkins, Erika; Michimi, Akihiko; Ellis-Griffith, Gregory; Peterson, Tina; Carter, Daniel; English, Gary

2013-05-02

Dental caries is one of the most common chronic childhood diseases affecting a large portion of children in the United States. The prevalence of childhood dental caries in Kentucky is among the highest in the nation. The purposes of this study are to (1) compare sociodemographic differences between caries and no caries groups and (2) investigate factors associated with untreated dental caries among children who visited a mobile dental clinic in South Central Kentucky. Study subjects were children aged 6 to 15 years who participated in the school-based dental sealant program through the mobile dental clinic operated by the Institute for Rural Health at Western Kentucky University between September 2006 and May 2011 (n = 2,453). Descriptive statistics were calculated for sociodemographic factors (age, gender, race/ethnicity, insurance status, and urban versus rural residential location) and caries status. We used chi-square tests to compare sociodemographic differences of children stratified by caries and no caries status as well as three levels of caries severity. We developed a logistic regression model to investigate factors associated with untreated dental caries while controlling for sociodemographic characteristics. The proportion of children having untreated dental caries was 49.7% and the mean number of untreated dental caries was 2.0. The proportion of untreated dental caries was higher in older children, children with no insurance and living in rural residential locations, and caries severity was also higher in these groups. Odds ratio indicated that older ages, not having private insurance (having only public, government-sponsored insurance or no insurance at all) and rural residential location were associated with having untreated dental caries after controlling for sociodemographic characteristics of children. Untreated dental caries was more likely to be present in older children living in rural areas without insurance. Health interventionists may use

Body mass index and dental caries in children and adolescents: a systematic review of literature published 2004 to 2011

Science.gov (United States)

2012-01-01

The objective The authors undertook an updated systematic review of the relationship between body mass index and dental caries in children and adolescents. Method The authors searched Medline, ISI, Cochrane, Scopus, Global Health and CINAHL databases and conducted lateral searches from reference lists for papers published from 2004 to 2011, inclusive. All empirical papers that tested associations between body mass index and dental caries in child and adolescent populations (aged 0 to 18 years) were included. Results Dental caries is associated with both high and low body mass index. Conclusion A non-linear association between body mass index and dental caries may account for inconsistent findings in previous research. We recommend future research investigate the nature of the association between body mass index and dental caries in samples that include a full range of body mass index scores, and explore how factors such as socioeconomic status mediate the association between body mass index and dental caries. PMID:23171603

Sealing properties of a self-etching primer system to normal caries-affected and caries-infected dentin.

Science.gov (United States)

Lee, Kwang-Won; Son, H-H; Yoshiyama, Masatoshi; Tay, Franklin R; Carvalho, Ricardo M; Pashley, David H

2003-09-01

To compare the ability of an experimental antibacterial self-etching primer adhesive system to seal exposure sites in normal, caries-affected and caries-infected human dentin. 30 extracted human third molars were used within 1 month of extraction. 10 intact normal teeth comprised the normal group. 20 teeth with occlusal caries that radiographically extended halfway to the pulp were excavated using caries-detector solution (CDS) and a #4 round carbide bur in a slowspeed handpiece. Half of those teeth were fully excavated free of CDS-stained material without exposing the pulp, and were designated as the caries-affected dentin group. The remaining 10 teeth were excavated as close to the pulp as possible without obtaining an exposure, but whose dentin continued to stain red with CDS; this group was designated as the caries-infected dentin group. The remaining dentin thickness in all of the specimens in the other two groups was then reduced to the same extent as the caries-infected group. Direct exposures of the pulp chamber were made with a 1/4 round bur in the normal dentin or a 25 gauge needle in the other two groups. After measuring the fluid flow through the exposure, the sites were then sealed with an experimental antibacterial fluoride-containing self-etching primer adhesive systems (ABF). Fluid conductance was remeasured every week for 16 weeks. The fluid conductance through the exposure fell 99% in all groups following resin sealing. The seals of normal and caries-affected dentin remained relatively stable over the 16 weeks, while the seals of caries-infected dentin gradually deteriorated, reaching significance at 8 weeks. TEM examination revealed very thin (ca. 0.5 mm) hybrid layers in normal dentin, 3-4 microm thick hybrid layers in caries-affected dentin and 40 microm thick hybrid layers in caries-infected dentin. The tubules of caries-infected dentin were enlarged and filled with bacteria. Resin tags passed around these bacteria in the top 20-40 microm

Impact of Oral Health Behaviors on Dental Caries in Children with Intellectual Disabilities in Guangzhou, China

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Zifeng Liu

2014-10-01

Full Text Available Dental care is consistently reported as one of the primary medical needs of children with disabilities (IDC. The aim of the present study was to explore the influence of oral health behaviors on the caries experience in children with intellectual disabilities in Guangzhou, China. A cross-sectional study was carried out in 477 intellectually disabled children, 12 to 17 years old, who were randomly selected from special educational schools in Guangzhou. A self-administered parental questionnaire was used to collect data on socio-demographic characteristics and oral health behavior variables, and 450 valid questionnaires were returned. Multiple regression analysis was used to examine the factors associated with dental caries. The average age of those in the sample was 14.6 years (SD = 1.3, 68.4% of whom were male, and the caries prevalence rate was 53.5% (DMFT = 1.5 ± 2.0. The factors significantly affecting the development of dental caries in IDC included gender, the presence or absence of cerebral palsy, and the frequency of dental visits and toothbrushing. In conclusion, the presence of cerebral palsy contributed to an increase risk of caries experience in intellectually disabled children, while toothbrushing more than twice a day and routine dental visits were caries-protective factors. Oral health promotion action may lead to a reduction in dental caries levels in IDC.

Comparing Regression Coefficients between Nested Linear Models for Clustered Data with Generalized Estimating Equations

Science.gov (United States)

Yan, Jun; Aseltine, Robert H., Jr.; Harel, Ofer

2013-01-01

Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The statistical problem is whether the coefficients associated with a given set of covariates change significantly when other covariates are added into…

Using the Coefficient of Determination "R"[superscript 2] to Test the Significance of Multiple Linear Regression

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Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.

2013-01-01

This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)

Healthcare Expenditures Associated with Depression Among Individuals with Osteoarthritis: Post-Regression Linear Decomposition Approach.

Science.gov (United States)

Agarwal, Parul; Sambamoorthi, Usha

2015-12-01

Depression is common among individuals with osteoarthritis and leads to increased healthcare burden. The objective of this study was to examine excess total healthcare expenditures associated with depression among individuals with osteoarthritis in the US. Adults with self-reported osteoarthritis (n = 1881) were identified using data from the 2010 Medical Expenditure Panel Survey (MEPS). Among those with osteoarthritis, chi-square tests and ordinary least square regressions (OLS) were used to examine differences in healthcare expenditures between those with and without depression. Post-regression linear decomposition technique was used to estimate the relative contribution of different constructs of the Anderson's behavioral model, i.e., predisposing, enabling, need, personal healthcare practices, and external environment factors, to the excess expenditures associated with depression among individuals with osteoarthritis. All analysis accounted for the complex survey design of MEPS. Depression coexisted among 20.6 % of adults with osteoarthritis. The average total healthcare expenditures were $13,684 among adults with depression compared to $9284 among those without depression. Multivariable OLS regression revealed that adults with depression had 38.8 % higher healthcare expenditures (p regression linear decomposition analysis indicated that 50 % of differences in expenditures among adults with and without depression can be explained by differences in need factors. Among individuals with coexisting osteoarthritis and depression, excess healthcare expenditures associated with depression were mainly due to comorbid anxiety, chronic conditions and poor health status. These expenditures may potentially be reduced by providing timely intervention for need factors or by providing care under a collaborative care model.

The association between sugar-sweetened beverages and dental caries among third-grade students in Georgia.

Science.gov (United States)

Wilder, Jocelyn R; Kaste, Linda M; Handler, Arden; Chapple-McGruder, Theresa; Rankin, Kristin M

2016-01-01

The purpose of this study is to examine the association between sugar-sweetened beverage (SSB) consumption and caries experience among Georgia third graders. The 2010-2011 Georgia Third Grade Oral Health Study provided a school-based sample for analysis. Data were weighted to be representative of the state of Georgia's third graders. Log-binomial regression was used to assess the association between SSB consumption and caries experience after adjusting for socio-demographic and maternal and child oral health characteristics. Georgia third graders consumed approximately two servings of SSB per day on average (1.7, 95% CI 1.6-1.8). Fifty-two percent of Georgia third graders had caries experience. Daily consumption of SSB and prevalence of caries experience differed significantly by demographic characteristics. After adjustment for socio-demographic and maternal oral health characteristics, caries experience increased 22 percent (adjusted PR = 1.2, 95% CI 1.1, 1.3) for every additional reported serving of SSB consumed per day. Higher consumption of SSBs is associated with higher caries prevalence among Georgia third graders after adjustment for important covariates. Consequently, health messages about SSBs from dentists, physicians, and other healthcare providers as well as policy approaches at the school, state, and national levels to limit consumption of SSBs may collectively impact both the development of dental caries and obesity, leading to overall better health for children. © 2015 American Association of Public Health Dentistry.

INTRODUCTION TO A COMBINED MULTIPLE LINEAR REGRESSION AND ARMA MODELING APPROACH FOR BEACH BACTERIA PREDICTION

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Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...

Effects of enamel fluorosis and dental caries on quality of life.

Science.gov (United States)

Onoriobe, U; Rozier, R G; Cantrell, J; King, R S

2014-10-01

The objectives of this study were to determine the impact of enamel fluorosis and dental caries on oral health-related quality of life (OHRQoL) in North Carolina schoolchildren and their families. Students (n = 7,686) enrolled in 398 classrooms in grades K-12 were recruited for a onetime survey. Parents of students in grades K-3 and 4-12 completed the Early Childhood Oral Health Impact Scale (ECOHIS) and Family Impact Scale (FIS), respectively. Students in grades 4-12 completed the Child Perceptions Questionnaire (CPQ8-10 in grades 4-5; CPQ11-14 in grades 6-12). All students were examined for fluorosis (Dean's index) and caries experience (d2-3fs or D2-3MFS indices). OHRQoL scores (sum response codes) were analyzed for their association with fluorosis categories and sum of d2-3fs and D2-3MFS according to ordinary least squares regression with SAS procedures for multiple imputation and analysis of complex survey data. Differences in OHRQoL scores were evaluated against statistical and minimal important difference (MID) thresholds. Of 5,484 examined students, 71.8% had no fluorosis; 24.4%, questionable to very mild fluorosis; and 3.7%, mild, moderate, or severe fluorosis. Caries categories were as follows: none (43.1%), low (28.6%), and moderate to high (28.2%). No associations between fluorosis and any OHRQoL scales met statistical or MID thresholds. The difference (5.8 points) in unadjusted mean ECOHIS scores for the no-caries and moderate-to-high caries groups exceeded the MID estimate (2.7 points) for that scale. The difference in mean FIS scores (1.5 points) for the no-caries and moderate-to-high groups exceeded the MID value (1.2 points). The sum of d2-3fs and D2-3MFS scores was positively associated with CPQ11-14 (B = 0.240, p caries experience negatively affects OHRQoL, while fluorosis has little impact. © International & American Associations for Dental Research.

Daily Suspended Sediment Discharge Prediction Using Multiple Linear Regression and Artificial Neural Network

Science.gov (United States)

Uca; Toriman, Ekhwan; Jaafar, Othman; Maru, Rosmini; Arfan, Amal; Saleh Ahmar, Ansari

2018-01-01

Prediction of suspended sediment discharge in a catchments area is very important because it can be used to evaluation the erosion hazard, management of its water resources, water quality, hydrology project management (dams, reservoirs, and irrigation) and to determine the extent of the damage that occurred in the catchments. Multiple Linear Regression analysis and artificial neural network can be used to predict the amount of daily suspended sediment discharge. Regression analysis using the least square method, whereas artificial neural networks using Radial Basis Function (RBF) and feedforward multilayer perceptron with three learning algorithms namely Levenberg-Marquardt (LM), Scaled Conjugate Descent (SCD) and Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS). The number neuron of hidden layer is three to sixteen, while in output layer only one neuron because only one output target. The mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2 ) and coefficient of efficiency (CE) of the multiple linear regression (MLRg) value Model 2 (6 input variable independent) has the lowest the value of MAE and RMSE (0.0000002 and 13.6039) and highest R2 and CE (0.9971 and 0.9971). When compared between LM, SCG and RBF, the BFGS model structure 3-7-1 is the better and more accurate to prediction suspended sediment discharge in Jenderam catchment. The performance value in testing process, MAE and RMSE (13.5769 and 17.9011) is smallest, meanwhile R2 and CE (0.9999 and 0.9998) is the highest if it compared with the another BFGS Quasi-Newton model (6-3-1, 9-10-1 and 12-12-1). Based on the performance statistics value, MLRg, LM, SCG, BFGS and RBF suitable and accurately for prediction by modeling the non-linear complex behavior of suspended sediment responses to rainfall, water depth and discharge. The comparison between artificial neural network (ANN) and MLRg, the MLRg Model 2 accurately for to prediction suspended sediment discharge (kg

Computer software for linear and nonlinear regression in organic NMR; Programa de computador para regressao linear e nao linear em R.M.N. organica

Energy Technology Data Exchange (ETDEWEB)

Canto, Eduardo Leite do; Rittner, Roberto [Universidade Estadual de Campinas, SP (Brazil). Inst. de Quimica

1992-12-31

Calculation involving two variable linear regressions, require specific procedures generally not familiar to chemist. For attending the necessity of fast and efficient handling of NMR data, a self explained and Pc portable software has been developed, which allows user to produce and use diskette recorded tables, containing chemical shift or any other substituent physical-chemical measurements and constants ({sigma}{sub T}, {sigma}{sup o}{sub R}, E{sub s}, ...) 9 refs., 1 fig.

Straight line fitting and predictions: On a marginal likelihood approach to linear regression and errors-in-variables models

Science.gov (United States)

Christiansen, Bo

2015-04-01

Linear regression methods are without doubt the most used approaches to describe and predict data in the physical sciences. They are often good first order approximations and they are in general easier to apply and interpret than more advanced methods. However, even the properties of univariate regression can lead to debate over the appropriateness of various models as witnessed by the recent discussion about climate reconstruction methods. Before linear regression is applied important choices have to be made regarding the origins of the noise terms and regarding which of the two variables under consideration that should be treated as the independent variable. These decisions are often not easy to make but they may have a considerable impact on the results. We seek to give a unified probabilistic - Bayesian with flat priors - treatment of univariate linear regression and prediction by taking, as starting point, the general errors-in-variables model (Christiansen, J. Clim., 27, 2014-2031, 2014). Other versions of linear regression can be obtained as limits of this model. We derive the likelihood of the model parameters and predictands of the general errors-in-variables model by marginalizing over the nuisance parameters. The resulting likelihood is relatively simple and easy to analyze and calculate. The well known unidentifiability of the errors-in-variables model is manifested as the absence of a well-defined maximum in the likelihood. However, this does not mean that probabilistic inference can not be made; the marginal likelihoods of model parameters and the predictands have, in general, well-defined maxima. We also include a probabilistic version of classical calibration and show how it is related to the errors-in-variables model. The results are illustrated by an example from the coupling between the lower stratosphere and the troposphere in the Northern Hemisphere winter.

Relationship between dental caries and metabolic syndrome among 13 998 middle-aged urban Chinese.

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Cao, Xia; Wang, Dongliang; Zhou, Jiansong; Yuan, Hong; Chen, Zhiheng

2017-04-01

The association between dental caries and metabolic syndrome (MetS) is inconsistent. The aim of the present study was to assess the relationship between dental caries and MetS and its components in a middle-aged Chinese population. A cross-sectional analysis was performed of 13 998 participants aged 45-65 years undergoing a health check during 2013-14. An index variable of decayed, missing, and filled teeth (DMFT) was calculated. Logistic regression was used to estimate odds ratios (ORs) and 95 % confidence intervals (CIs) after adjustment for sex, age, education level, dietary habits, alcohol use, smoking, physical activity, and periodontitis. Of the 13 998 participants, 6164 had dental caries and 7834 did not; 3571 had MetS, whereas 10 427 did not. Participants with severe caries showed a higher prevalence of MetS, abdominal obesity, elevated blood pressure, dyslipidemia, and hyperglycemia than those with mild or no caries (all P dental caries and those with two or more DMFT were 1.12 (95 % CI 1.14-1.74) and 1.09 (95 % CI, 0.89-1.21), respectively (P trend  caries were associated with MetS among subjects with hyperglycemia (OR 1.14 [95%CI, 0.98-1.34]; P caries and abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol, and elevated blood pressure (adjusted ORs [95 % CIs] 0.98 [0.82-1.16], 1.01 [0.85-1.19], 0.84 [0.70-1.00], and 0.96 [0.86-1.13], respectively; all P > 0.05). Dental caries were associated with MetS among middle-aged Chinese in the present study. © 2016 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.

The detection of influential subsets in linear regression using an influence matrix

OpenAIRE

Peña, Daniel; Yohai, Víctor J.

1991-01-01

This paper presents a new method to identify influential subsets in linear regression problems. The procedure uses the eigenstructure of an influence matrix which is defined as the matrix of uncentered covariance of the effect on the whole data set of deleting each observation, normalized to include the univariate Cook's statistics in the diagonal. It is shown that points in an influential subset will appear with large weight in at least one of the eigenvector linked to the largest eigenvalue...

Association of caries experience and dental plaque with sociodemographic characteristics in elementary school-aged children: a cross-sectional study.

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Bashirian, Saeed; Shirahmadi, Samaneh; Seyedzadeh-Sabounchi, Shabnam; Soltanian, Ali Reza; Karimi-Shahanjarini, Akram; Vahdatinia, Farshid

2018-01-10

Dental caries among Iranian elementary school children aged 6-12 years continue to rise. To estimate treatment needs and guide health initiatives, current epidemiologic data are required. Such data are currently unavailable for dental health. The purpose of this study was to assess caries experience, dental plaque, and associated factors in elementary school-aged children from Iran. In this cross-sectional study, 988 elementary school children aged 7-12 years were selected by multistage cluster sampling. Dental caries was studied using the WHO criteria, dental plaque was examined according to O'Leary index. Data on parental education and occupation, living district, dental pain within the past year, and tooth brushing habits under parental supervision were collected through interviews based on questionnaire. The data were analyzed with descriptive statistics and logistic and linear regression. The mean (SD) age of the elementary school children was 9.64 (1.73) years. The highest dmft was seen in elementary school children aged 7-8 years 6.53 (4.37) and the highest DMFT and dental plaque was in 12 year olds recorded as 1.17 (1.77) and 51.97 (25.86), respectively. The proportion of decayed teeth in 7 years old elementary school based on dmft index was 80.36%, moreover, the proportion in 12 years old elementary school was 40.17% based on the DMFT index. Age, gender, and dental pain within the past year were significantly associated with DMFT and dmft. The odds of developing dental caries (DMFT) was 1.70 times higher in girls than in boys (p elementary school children in Hamadan were high and they were influenced by their sociodemographic factors. The associations found can be used as a helpful guide for planning accurate preventive programs for elementary school children in this region.

Multivariate linear regression of high-dimensional fMRI data with multiple target variables.

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Valente, Giancarlo; Castellanos, Agustin Lage; Vanacore, Gianluca; Formisano, Elia

2014-05-01

Multivariate regression is increasingly used to study the relation between fMRI spatial activation patterns and experimental stimuli or behavioral ratings. With linear models, informative brain locations are identified by mapping the model coefficients. This is a central aspect in neuroimaging, as it provides the sought-after link between the activity of neuronal populations and subject's perception, cognition or behavior. Here, we show that mapping of informative brain locations using multivariate linear regression (MLR) may lead to incorrect conclusions and interpretations. MLR algorithms for high dimensional data are designed to deal with targets (stimuli or behavioral ratings, in fMRI) separately, and the predictive map of a model integrates information deriving from both neural activity patterns and experimental design. Not accounting explicitly for the presence of other targets whose associated activity spatially overlaps with the one of interest may lead to predictive maps of troublesome interpretation. We propose a new model that can correctly identify the spatial patterns associated with a target while achieving good generalization. For each target, the training is based on an augmented dataset, which includes all remaining targets. The estimation on such datasets produces both maps and interaction coefficients, which are then used to generalize. The proposed formulation is independent of the regression algorithm employed. We validate this model on simulated fMRI data and on a publicly available dataset. Results indicate that our method achieves high spatial sensitivity and good generalization and that it helps disentangle specific neural effects from interaction with predictive maps associated with other targets. Copyright © 2013 Wiley Periodicals, Inc.

An Investigation of the Fit of Linear Regression Models to Data from an SAT[R] Validity Study. Research Report 2011-3

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Kobrin, Jennifer L.; Sinharay, Sandip; Haberman, Shelby J.; Chajewski, Michael

2011-01-01

This study examined the adequacy of a multiple linear regression model for predicting first-year college grade point average (FYGPA) using SAT[R] scores and high school grade point average (HSGPA). A variety of techniques, both graphical and statistical, were used to examine if it is possible to improve on the linear regression model. The results…

Uncertainty of pesticide residue concentration determined from ordinary and weighted linear regression curve.

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Yolci Omeroglu, Perihan; Ambrus, Árpad; Boyacioglu, Dilek

2018-03-28

Determination of pesticide residues is based on calibration curves constructed for each batch of analysis. Calibration standard solutions are prepared from a known amount of reference material at different concentration levels covering the concentration range of the analyte in the analysed samples. In the scope of this study, the applicability of both ordinary linear and weighted linear regression (OLR and WLR) for pesticide residue analysis was investigated. We used 782 multipoint calibration curves obtained for 72 different analytical batches with high-pressure liquid chromatography equipped with an ultraviolet detector, and gas chromatography with electron capture, nitrogen phosphorus or mass spectrophotometer detectors. Quality criteria of the linear curves including regression coefficient, standard deviation of relative residuals and deviation of back calculated concentrations were calculated both for WLR and OLR methods. Moreover, the relative uncertainty of the predicted analyte concentration was estimated for both methods. It was concluded that calibration curve based on WLR complies with all the quality criteria set by international guidelines compared to those calculated with OLR. It means that all the data fit well with WLR for pesticide residue analysis. It was estimated that, regardless of the actual concentration range of the calibration, relative uncertainty at the lowest calibrated level ranged between 0.3% and 113.7% for OLR and between 0.2% and 22.1% for WLR. At or above 1/3 of the calibrated range, uncertainty of calibration curve ranged between 0.1% and 16.3% for OLR and 0% and 12.2% for WLR, and therefore, the two methods gave comparable results.

Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

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Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

2015-08-01

A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as 1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

The regression-calibration method for fitting generalized linear models with additive measurement error

OpenAIRE

James W. Hardin; Henrik Schmeidiche; Raymond J. Carroll

2003-01-01

This paper discusses and illustrates the method of regression calibration. This is a straightforward technique for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). Discussion will include specified measurement error, measurement error estimated by replicate error-prone proxies, and measurement error estimated by instrumental variables. The discussion focuses on s...

"MI" caries management--an overview.

Science.gov (United States)

Banerjee, Avijit

2012-04-01

Minimum intervention dentistry, with its non-operative prevention and control of disease, underpins the basis of a patient-centred, team-based approach to managing dental caries in patients, who must take an active responsibility in maintaining their personal oral health. In patients where cavities are present causing pain, poor aesthetics and/or functional problems, restorations will need to be placed. Minimally invasive caries excavation strategies can be deployed depending on the patient's caries risk, lesion-pulp proximity and vitality, the extent of remaining supra-gingival tooth structure and clinical factors (e.g., moisture control, access) present in each case treated. Excavation instruments, including burs/handpieces, hand excavators, chemo-mechanical agents and/or air-abrasives which limit caries removal selectively to the more superficial caries-infected dentine and partial removal of caries-affected dentine when required, help create smaller cavities with healthy enamel/dentine margins. Using adhesive restorative materials, the operator can, if handling with care, optimize the histological substrate coupled with the applied chemistry of the material so helping to form a durable peripheral seal and bond to aid retention of the restoration as well as arresting the carious process within the remaining tooth structure. Achieving a smooth tooth-restoration interface clinically to aid the co-operative, motivated patient in biofilm removal, is an essential pre-requisite to prevent further secondary caries.

Nature vs. nurture in dental caries.

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Mandel, I D

1994-10-01

Why are some people more resistant to dental caries than others? Certainly diet plays a part, but are there hereditary factors that affect caries development? This report explores genetic components that appear related to caries resistance and susceptibility.

Dental caries experience in high risk soft drinks factory workers of South India: a comparative study.

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Kumar, Sandeep; Acharya, Shashidhar; Vasthare, Ramprasad; Singh, Siddharth Kumar; Gupta, Anjali; Debnath, Nitai

2014-01-01

The consumption of soft-drinks has been associated with dental caries development. The aim was to evaluate dental caries experience amongst the workers working in soft-drink industries located in South India and compare it with other factory workers. To evaluate the validity of specific caries index (SCI), which is newer index for caries diagnosis. This was a cross-sectional study carried out among 420 workers (210 in soft-drinks factory and 210 in other factories), in the age group of 20-45 years of Udupi district, Karnataka, India. Index used for clinical examination was decayed, missing, filled surfaces (DMFS) index and SCI. The mean and standard deviation (SD) of decayed surface (5.8 ± 1.8), missing surface (4.3 ± 2) and filled surface (1.94 ± 1.95) and total DMFS score (12.11 ± 3.8) in soft-drinks factory workers were found to be significantly higher than the other factory workers. The total SCI score (mean and SD) was found to be significantly higher in soft-drinks factory workers (5.83 ± 1.80) compared with other factory workers (4.56 ± 1.45). There was a high correlation obtained between SCI score and DMFS score. The regression equation given by DMFS = 1.178 + 1.866 (SCI scores). The caries experience was higher in workers working in soft-drinks factory and this study also showed that specific caries index can be used as a valid index for assessing dental caries experience.

Patient caries risk assessment

DEFF Research Database (Denmark)

Twetman, Svante; Fontana, Margherita

2009-01-01

Risk assessment is an essential component in the decision-making process for the correct prevention and management of dental caries. Multiple risk factors and indicators have been proposed as targets in the assessment of risk of future disease, varying sometimes based on the age group at which...... they are targeted. Multiple reviews and systematic reviews are available in the literature on this topic. This chapter focusses primarily on results of reviews based on longitudinal studies required to establish the accuracy of caries risk assessment. These findings demonstrate that there is a strong body...... of evidence to support that caries experience is still, unfortunately, the single best predictor for future caries development. In young children, prediction models which include a variety of risk factors seem to increase the accuracy of the prediction, while the usefulness of additional risk factors...

Time-Frequency Analysis of Non-Stationary Biological Signals with Sparse Linear Regression Based Fourier Linear Combiner

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Yubo Wang

2017-06-01

Full Text Available It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC. In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976 ratio and outperforms existing methods such as short-time Fourier transfrom (STFT, continuous Wavelet transform (CWT and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.

Time-Frequency Analysis of Non-Stationary Biological Signals with Sparse Linear Regression Based Fourier Linear Combiner.

Science.gov (United States)

Wang, Yubo; Veluvolu, Kalyana C

2017-06-14

It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC). In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976) ratio and outperforms existing methods such as short-time Fourier transfrom (STFT), continuous Wavelet transform (CWT) and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.

Nutrition and Experimental Dental Caries

OpenAIRE

田村, 俊吉; タムラ, シュンキチ; Shunkichi, TAMURA

1983-01-01

Nutrition is an effective factor for the inhibition of the development of dental caries. The constitution of diet has a strong bearing on the development of dental caries. However the theoretical background regarding the development of dental caries has not been sastifactorily established. Experimentally, we have clarified the relation of nutrition and dental caries in rats. Experimental animals used in this study were Wistar strain Albino rats (closed colony, Tamura, 1950). Young rats of 21 ...

Streptococcus mutans, Streptococcus sobrinus and Candida albicans in oral samples from caries-free and caries-active children.

Science.gov (United States)

Fragkou, S; Balasouli, C; Tsuzukibashi, O; Argyropoulou, A; Menexes, G; Kotsanos, N; Kalfas, S

2016-10-01

This was to examine the occurrence of S. mutans, S. sobrinus and C. albicans in dental plaque and saliva from caries-free and caries-active Greek children. Saliva and dental plaque samples from 46 caries-free and 51 caries-active 3-to-13-year-old children were examined using selective media for the three microbes. Identification of isolated mutans streptococci (S. mutans and S. sobrinus) was performed with biochemical test and specific DNA probes. The salivary levels of mutans streptococci were additionally determined by a chair-side test (Dentocult ® SM strips). The isolation frequencies of S. mutans, S. sobrinus and C. albicans were 66, 11 and 18 %, respectively. Caries-active children harboured more frequently and at significantly higher numbers the specific microbes than caries-free children. A similar pattern was observed with the Dentocult ® SM strip scores. No correlation was found between the presence of these microbes and the age or gender of the children. Caries experience was statistically significantly related to the presence of all three microbes under study, both in dental plaque and saliva.

Heteroscedasticity as a Basis of Direction Dependence in Reversible Linear Regression Models.

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Wiedermann, Wolfgang; Artner, Richard; von Eye, Alexander

2017-01-01

Heteroscedasticity is a well-known issue in linear regression modeling. When heteroscedasticity is observed, researchers are advised to remedy possible model misspecification of the explanatory part of the model (e.g., considering alternative functional forms and/or omitted variables). The present contribution discusses another source of heteroscedasticity in observational data: Directional model misspecifications in the case of nonnormal variables. Directional misspecification refers to situations where alternative models are equally likely to explain the data-generating process (e.g., x → y versus y → x). It is shown that the homoscedasticity assumption is likely to be violated in models that erroneously treat true nonnormal predictors as response variables. Recently, Direction Dependence Analysis (DDA) has been proposed as a framework to empirically evaluate the direction of effects in linear models. The present study links the phenomenon of heteroscedasticity with DDA and describes visual diagnostics and nine homoscedasticity tests that can be used to make decisions concerning the direction of effects in linear models. Results of a Monte Carlo simulation that demonstrate the adequacy of the approach are presented. An empirical example is provided, and applicability of the methodology in cases of violated assumptions is discussed.

The prevalence of questionable occlusal caries

DEFF Research Database (Denmark)

Makhija, Sonia K; Gilbert, Gregg H; Funkhouser, Ellen

2012-01-01

Questionable occlusal caries (QOC) can be defined as clinically suspected caries with no cavitation or radiographic evidence of occlusal caries. To the authors' knowledge, no one has quantified the prevalence of QOC, so this quantification was the authors' objective in conducting this study...

Two Paradoxes in Linear Regression Analysis

Science.gov (United States)

FENG, Ge; PENG, Jing; TU, Dongke; ZHENG, Julia Z.; FENG, Changyong

2016-01-01

Summary Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection. PMID:28638214

How to deal with continuous and dichotomic outcomes in epidemiological research: linear and logistic regression analyses

NARCIS (Netherlands)

Tripepi, Giovanni; Jager, Kitty J.; Stel, Vianda S.; Dekker, Friedo W.; Zoccali, Carmine

2011-01-01

Because of some limitations of stratification methods, epidemiologists frequently use multiple linear and logistic regression analyses to address specific epidemiological questions. If the dependent variable is a continuous one (for example, systolic pressure and serum creatinine), the researcher

A comparative evaluation of bifidobacteria levels in early childhood caries and severe early childhood caries

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Suraj Nair

2017-01-01

Full Text Available Background: Bifidobacteria levels in saliva were found to be significantly correlated in adults with dental caries but less information available in the literature regarding its role in children. Aim: The aim is to compare the salivary levels of Bifidobacteria in children who are caries free with that of early childhood caries (ECC and severe ECC (S-ECC. Materials and Methods: Saliva was collected using the tongue-loop method from a total of 60 children between the age group of 3–5 years and they were further divided into 3 groups. In addition, the age and gender of the children, sugar amount in diet, sugar frequency in diet, were recorded. Results: Bifidobacteria was isolated from all the three groups, but more were from S-ECC, followed by ECC and very few cases of caries-free children and was found to statistically significant (P < 0.001. Salivary levels of Bifidobacteria were significantly correlated with amount of sugar in the diet and frequency of sugar consumption. Conclusions: Salivary levels of Bifidobacteria were significantly associated with S-ECC and ECC, followed by caries free group. In future, it can be used as a salivary marker for caries risk assesment.

Oral Lactobacilli and Dental Caries

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Caufield, P.W.; Schön, C.N.; Saraithong, P.; Li, Y.; Argimón, S.

2015-01-01

Lactobacilli have been associated with dental caries for over a century. Here, we review the pertinent literature along with findings from our own study to formulate a working hypothesis about the natural history and role of lactobacilli. Unlike most indigenous microbes that stably colonize a host, lactobacilli appear to be planktonic, opportunistic settlers that can gather and multiply only in certain restrictive niches of the host, at least within the oral cavity. We postulate that the following essential requirements are necessary for sustained colonization of lactobacilli in humans: 1) a stagnant, retentive niche that is mostly anaerobic; 2) a low pH milieu; and 3) ready access to carbohydrates. Three sites on the human body meet these specifications: caries lesions, the stomach, and the vagina. Only a handful of Lactobacillus species is found in caries lesions, but they are largely absent in caries-free children. Lactobacilli present in caries lesions represent both a major contributor to caries progression and a major reservoir to the gastrointestinal (GI) tract. We extend the assertion from other investigators that lactobacilli found in the GI tract originate in the oral cavity by proposing that lactobacilli in the oral cavity arise from caries lesions. This, in turn, leads us to reflect on the health implications of the lactobacilli in the mouth and downstream GI and to ponder whether these or any of the Lactobacillus species are truly indigenous to the human GI tract or the oral cavity. PMID:25758458

BFLCRM: A BAYESIAN FUNCTIONAL LINEAR COX REGRESSION MODEL FOR PREDICTING TIME TO CONVERSION TO ALZHEIMER'S DISEASE.

Science.gov (United States)

Lee, Eunjee; Zhu, Hongtu; Kong, Dehan; Wang, Yalin; Giovanello, Kelly Sullivan; Ibrahim, Joseph G

2015-12-01

The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer's disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM.

Toward Customer-Centric Organizational Science: A Common Language Effect Size Indicator for Multiple Linear Regressions and Regressions With Higher-Order Terms.

Science.gov (United States)

Krasikova, Dina V; Le, Huy; Bachura, Eric

2018-01-22

To address a long-standing concern regarding a gap between organizational science and practice, scholars called for more intuitive and meaningful ways of communicating research results to users of academic research. In this article, we develop a common language effect size index (CLβ) that can help translate research results to practice. We demonstrate how CLβ can be computed and used to interpret the effects of continuous and categorical predictors in multiple linear regression models. We also elaborate on how the proposed CLβ index is computed and used to interpret interactions and nonlinear effects in regression models. In addition, we test the robustness of the proposed index to violations of normality and provide means for computing standard errors and constructing confidence intervals around its estimates. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Sociobehavioral Factors Associated with Caries Increment: A Longitudinal Study from 24 to 36 Months Old Children in Thailand

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Karl Peltzer

2014-10-01

Full Text Available The aim of this study is to investigate sociobehavioral risk factors from the prenatal period until 36 months of age, and the caries increment from 24 to 36 months of the child in Thailand. The data utilized in this study come from the prospective cohort study of Thai children (PCTC from prenatal to 36 months of the child in Mueang Nan district, Northern Thailand. The total sample size recruited was 783 infants. The sample size with dental caries data was 603 and 597, at 24 months and at 36 months, respectively. The sample size of having two assessment points with a dental examination (at 24 months and at 36 months was 597. Results indicate that the caries increment was 52.9%, meaning from 365 caries free children at 24 months 193 had developed dental caries at 36 months. The prevalence of dental caries was 34.2% at 24 months (n = 206 and 68.5% at 36 months of age (n = 409. In bivariate analysis, higher education of the mother, lower household income, bottle feeding of the infant, frequent sweet candy consumptions, and using rain or well water as drinking water were associated with dental caries increment, while in multivariate conditional logistic regression analysis lower household income, higher education of the mother, and using rain or well water as drinking water remained associated with dental caries increment. In conclusion, a very significant increase in caries development was observed, and oral health may be influenced by sociobehavioural risk factors.

Factors related to tooth loss due to dental caries among workers in an industrial estates in Thailand.

Science.gov (United States)

Chatrchaiwiwatana, Supaporn; Ratanasiri, Amornrat; Jaidee, Jeeratip; Soontorn, Surasak

2012-11-01

The present study aimed to evaluate the prevalence and factors related to tooth loss due to dental caries among workers in industrial estates in Pathumthani and Phranakhorn Si Ayutthaya provinces in central Thailand. The present study utilized quantitative and qualitative methodologies. A quantitative study was done using a cross-sectional analytic method with a sample group of 457 adults (283 males; 174 females) between 19 and 53 years. Data were obtained through an oral examination and oral health behavior questionnaire. Data analyses were done using descriptive, bivariate and multivariable logistic regression statistics. In-depth interviews were used to collect qualitative data from 11 subjects. Most (62.2%) participants had tooth loss due to caries and findings from the final multivariable logistic regression model revealed that such loss was associated with education, residency, use of social security welfare, decayed teeth and filled teeth. Relatedly, the in-depth interview confirmed that tooth loss due to dental caries was related to (1) lack of time to visit a dentist (2) have a negative attitude toward or a phobia regarding dental treatment (3) inability to afford the high cast of dental treatment (4) lack of knowledge in regarding dental caries prevention, root canal treatment and the harmful effects of losing teeth (5) choosing to get an extraction upon having caries exposed pulp and (6) lack of oral health promotion programs provided by either the government or private sectors. The government and non-government organizations should promote oral health in an industrial estates and provide services and welfare for dental health of workers in an industrial estate appropriate to their socio-economic needs.

Caries og de nye nationale indkaldeintervaller

DEFF Research Database (Denmark)

Ekstrand, Kim; Bruun, Gitte; Bakhshandeh, Azam

2015-01-01

obligatorisk at gøre under de nye retningslinjer. Det gennemgås, hvilke behandlinger der er relevante for patienten i forhold til de tre cariesdiagnoser: Caries dentalis progressiva superficialis (CS), Caries dentalis progressiva media (CM) og Caries dentalis progressiva profunda (CP). Diagnoserne angiver...

Caries risk assessment in chilean adolescents and adults and its association with caries experience

OpenAIRE

Giacaman,Rodrigo Andrés; Miranda Reyes,Paulina; Bravo León,Valeria

2013-01-01

Cariogram is a computer program that uses an algorithm to assess caries risk. Although the use of Cariogram has recently increased, little information is available regarding its effectiveness in adults. This study aimed to determine whether caries risk from Cariogram relates to caries experience in adults. One hundred and eighty Cariogram files were completed from patients aged ten to fifty-six years (mean: 23.28 years). Seven factors from the software were included from patient records to co...

The Influence of Lifestyle on the Incidence of Dental Caries among 3-Year-Old Japanese Children

Science.gov (United States)

Watanabe, Masako; Wang, Da-Hong; Ijichi, Akihiro; Shirai, Chika; Zou, Yu; Kubo, Masayuki; Takemoto, Kei; Masatomi, Chie; Ogino, Keiki

2014-01-01

The present cohort study examined how lifestyle, household environment, and caries activity test score of Japanese children at age 1.5 years affected their dental caries incidence at age 3. Inclusion criteria were 1.5-year-old children with no dental caries. Dental examinations were performed for 33,655 children who participated in routine dental examinations at 1.5 years of age, and the exam was repeated approximately 21 months later (at age 3) at the Kobe City Public Health Center in Japan. After excluding 622 children who had caries at age 1.5 and 1831 children with missing lifestyle and household environment data in the questionnaires, the final data analysis was performed on a total of 31,202 children (16,052 boys, 15,150 girls).The multivariate logistic regression analysis indicated a strong association of the consumption of sugar-sweetened beverages/snacks, less frequent tooth brushing by the parents, lack of fluoride varnish, family history of smoking, with the risk of developing dental caries. A child’s late bedtime is also one of the major risk factors for dental caries development. Further investigation is needed to examine whether the short duration or the irregularity of the sleep-wake cycle would affect early childhood oral health and whether there is a relationship between late bedtime and late night snack intake. PMID:25489996

The Influence of Lifestyle on the Incidence of Dental Caries among 3-Year-Old Japanese Children

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Masako Watanabe

2014-12-01

Full Text Available The present cohort study examined how lifestyle, household environment, and caries activity test score of Japanese children at age 1.5 years affected their dental caries incidence at age 3. Inclusion criteria were 1.5-year-old children with no dental caries. Dental examinations were performed for 33,655 children who participated in routine dental examinations at 1.5 years of age, and the exam was repeated approximately 21 months later (at age 3 at the Kobe City Public Health Center in Japan. After excluding 622 children who had caries at age 1.5 and 1831 children with missing lifestyle and household environment data in the questionnaires, the final data analysis was performed on a total of 31,202 children (16,052 boys, 15,150 girls.The multivariate logistic regression analysis indicated a strong association of the consumption of sugar-sweetened beverages/snacks, less frequent tooth brushing by the parents, lack of fluoride varnish, family history of smoking, with the risk of developing dental caries. A child’s late bedtime is also one of the major risk factors for dental caries development. Further investigation is needed to examine whether the short duration or the irregularity of the sleep-wake cycle would affect early childhood oral health and whether there is a relationship between late bedtime and late night snack intake.

A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

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Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C

2011-09-01

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.

Dental caries in schoolchildren: influence of inattention, hyperactivity and executive functions

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Isabella MOTA-VELOSO

2018-06-01

Full Text Available Abstract Attention-deficit/hyperactivity disorder (ADHD is characterized by inappropriate levels of hyperactivity, impulsivity, and/or inattention. Individuals with ADHD may present limitations with regard to executive functions and performing activities that involve planning and/or attention/concentration. The aim of the study was to investigate the association between dental caries and signs of ADHD in a representative sample of schoolchildren. A representative sample of 851 schoolchildren aged seven to 12 years was randomly selected from public and private schools. Data acquisition involved a clinical dental examination for cavitated permanent and deciduous teeth using the DMFT/dmft indices. Neuropsychological evaluations, including the assessment of intelligence (Raven’s Colored Progressive Matrix Test and executive functions (Corsi Tapping Blocks tests and Digit Span test were also performed. Parents/caregivers and teachers answered the SNAP-IV Questionnaire for the investigation of signs of inattention and hyperactivity in the family and school environment. Parents/caregivers also answered questionnaires addressing socioeconomic and socio-demographic characteristics. Descriptive analysis of the variables and Poisson regression with robust variance were performed. Parental reports of signs of inattention (PR: 1.28; p < 0.05 and hyperactivity (PR: 1.15; p < 0.05 were associated with a greater occurrence of caries. A better performance on the backward order of the Corsi Tapping Blocks tests (PR: 0.94; p < 0.05 and higher level of mother’s schooling were associated with a lower frequency of caries. A better performance on executive function tasks was a protective factor against dental caries, whereas children considered inattentive and/or hyperactive by their parents had a higher prevalence rate of dental caries.

Dental caries and erosion status of 12-year-old Hong Kong children.

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Zhang, Shinan; Chau, Alex Mh; Lo, Edward Cm; Chu, Chun-Hung

2014-01-08

This study aimed to assess the dental caries and erosion status of 12-year-old Hong Kong children and study the determinants of dental caries and dental erosion of these children. The survey was performed from 2011 to 2012 with ethics approval. Stratified random sampling was adopted to select 12-year-old children in 7 primary schools in Hong Kong. The participating parents were asked to complete a self-administered questionnaire concerning their children's diet and oral health habits. The children were examined for caries status with WHO criteria by 3 calibrated examiners. Detection of dental erosion followed Basic Erosive Wear Examination (BEWE) criteria. A total of 704 children were recruited and 600 (316 boys, 53%) participated in the survey. There were 124 children (21%) with caries experience (DMFT > 0) and their DMFT was 0.34 ± 0.76. About half of their decay was unfilled (DT = 0.16 ± 0.52) The DMFT of girls and boys were 0.45 ± 0.89 and 0.23 ± 0.61, respectively (p = 0.001). Girls also had a higher DT (0.21 ± 0.62 compared with 0.11 ± 0.41, p = 0.013) and FT than boys (0.23 ± 0.63 compared with 0.12 ± 0.44, p = 0.016). Most children (75%) had at least some sign of erosion (BEWE > 0), but no severe erosion (BEWE = 3). Logistic regression showed girls who consumed soft drinks and took vitamin C supplements had higher caries risk. Dental erosion was more severe among the children who had caries experience and consumed fruit juice. The 12-year-old Hong Kong children had low caries experience, and almost half of the decay was left untreated. Although severe erosion was not found, many children had early signs of erosion.

Risk factors for dental caries in childhood: a five-year survival analysis.

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Lee, Hyo-Jin; Kim, Jin-Bom; Jin, Bo-Hyoung; Paik, Dai-Il; Bae, Kwang-Hak

2015-04-01

The purpose of this study was to examine the risk factors of dental caries at the level of an individual person with survival analysis of the prospective data for 5 years. A total of 249 first-grade students participated in a follow-up study for 5 years. All participants responded to a questionnaire inquiring about socio-demographic variables and oral health behaviors. They also received an oral examination and were tested for Dentocult SM and LB. Over 5 years, the participants received yearly oral follow-up examinations to determine the incidence of dental caries. The incidence of one or more dental caries (DC1) and four or more dental caries (DC4) were defined as one or more and four or more decayed, missing, and filled permanent teeth increments, respectively. Socio-demographic variables, oral health behaviors, and status and caries activity tests were assessed as risk factors for DC1 and DC4. The adjusted hazard ratios (HRs) of risk factors for DC1 and DC4 were calculated using Cox proportional hazard regression models. During the 5-year follow-up period, DC1 and DC4 occurred in 87 and 25 participants, respectively. In multivariate hazard models, five or more decayed, missing, and filled primary molar teeth [HR 1.93, 95% confidence interval (CI) 1.19-3.13], and Dentocult LB of two or three (HR 2.21, 95% CI 1.37-3.56) were independent risk factors of DC1. For DC4, only Dentocult LB of two or three was an independent risk factor (HR 2.95, 95% CI 1.11-7.79). Our results suggest that dental caries incidence at an individual level can be associated with the experience of dental caries in primary teeth and Dentocult LB based on the survival models for the 5-year prospective data. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Responsiveness of Patients' Quality of Life to Dental Caries Treatment-A Prospective Study.

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Yeh, Ding-Yu; Kuo, Hsiao-Ching; Yang, Yi-Hsin; Ho, Pei-Shan

2016-01-01

The objective of this study was to determine the responsiveness of oral health-related quality of life (OHRQoL) (oral health impact profile [OHIP] and oral impact on daily performance [OIDP]) and health-related quality of life (HRQoL) (World Health Organization quality of life scale, brief [WHOQOL-BREF]) in dental caries restoration treatment. The study also aimed to assess the influence of treatment on the responsiveness of patients' quality of life (QoL). A total of 126 patients (aged 16-40 years) received dental caries restoration treatment with a 2-week follow-up and pre- and posttreatment interviews by questionnaire. Patients were assessed for their perceptions of OHRQoL and HRQoL by using the OHIP, OIDP, and WHOQOL-BREF measures. The responsiveness of all outcome measurements was assessed by effect size (ES). Stepwise multiple regression analysis was used to examine the association with the responsiveness of all outcome measurements. Significant differences were found between OIDP (ES = 0.39), OHIP (ES = 0.54), and WHOQOL-BREF (ES = 0.13) with regard to pretreatment and posttreatment (p-values: caries status at baseline were significantly associated with responsiveness by all measurements. This study suggests that dental caries treatment moderately improves OHRQoL, but is less related to HRQoL. Furthermore, the number of dental caries and restoration are important factors affecting the improvement of patients' perceived OHRQoL.

The Responsiveness of Patients’ Quality of Life to Dental Caries Treatment—A Prospective Study

Science.gov (United States)

Yeh, Ding-Yu; Kuo, Hsiao-Ching; Yang, Yi-Hsin

2016-01-01

The objective of this study was to determine the responsiveness of oral health–related quality of life (OHRQoL) (oral health impact profile [OHIP] and oral impact on daily performance [OIDP]) and health-related quality of life (HRQoL) (World Health Organization quality of life scale, brief [WHOQOL-BREF]) in dental caries restoration treatment. The study also aimed to assess the influence of treatment on the responsiveness of patients’ quality of life (QoL). A total of 126 patients (aged 16–40 years) received dental caries restoration treatment with a 2-week follow-up and pre- and posttreatment interviews by questionnaire. Patients were assessed for their perceptions of OHRQoL and HRQoL by using the OHIP, OIDP, and WHOQOL-BREF measures. The responsiveness of all outcome measurements was assessed by effect size (ES). Stepwise multiple regression analysis was used to examine the association with the responsiveness of all outcome measurements. Significant differences were found between OIDP (ES = 0.39), OHIP (ES = 0.54), and WHOQOL-BREF (ES = 0.13) with regard to pretreatment and posttreatment (p-values: caries status at baseline were significantly associated with responsiveness by all measurements. This study suggests that dental caries treatment moderately improves OHRQoL, but is less related to HRQoL. Furthermore, the number of dental caries and restoration are important factors affecting the improvement of patients’ perceived OHRQoL. PMID:27776148

Genetic factors affecting dental caries risk.

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Opal, S; Garg, S; Jain, J; Walia, I

2015-03-01

This article reviews the literature on genetic aspects of dental caries and provides a framework for the rapidly changing disease model of caries. The scope is genetic aspects of various dental factors affecting dental caries. The PubMed database was searched for articles with keywords 'caries', 'genetics', 'taste', 'diet' and 'twins'. This was followed by extensive handsearching using reference lists from relevant articles. The post-genomic era will present many opportunities for improvement in oral health care but will also present a multitude of challenges. We can conclude from the literature that genes have a role to play in dental caries; however, both environmental and genetic factors have been implicated in the aetiology of caries. Additional studies will have to be conducted to replicate the findings in a different population. Identification of genetic risk factors will help screen and identify susceptible patients to better understand the contribution of genes in caries aetiopathogenesis. Information derived from these diverse studies will provide new tools to target individuals and/or populations for a more efficient and effective implementation of newer preventive measures and diagnostic and novel therapeutic approaches in the management of this disease. © 2015 Australian Dental Association.

Introduction to regression graphics

CERN Document Server

Cook, R Dennis

2009-01-01

Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava

Impact of malocclusion and dentofacial anomalies on the prevalence and severity of dental caries among adolescents.

Science.gov (United States)

Feldens, Carlos Alberto; Dos Santos Dullius, Angela Isabel; Kramer, Paulo Floriani; Scapini, Annarosa; Busato, Adair Luiz Stefanello; Vargas-Ferreira, Fabiana

2015-11-01

To investigate the association between malocclusion/dentofacial anomalies and dental caries among adolescents. A cross-sectional study was conducted with 509 adolescents aged 11 to 14 years enrolled at public schools in the city of Osório in southern Brazil. Parents/caregivers answered a structured questionnaire on demographic and socioeconomic variables. A trained examiner recorded the presence of malocclusion (Dental Aesthetic Index [DAI]), traumatic dental injury, and dental caries. Data analysis involved the chi-square, Mann-Whitney, and Kruskal-Wallis tests. Poisson regression with robust variance was used for the multivariable analysis. A total of 44.8% of the adolescents had dental caries (mean DFMT  =  1.33 ± 1.84). The DAI index ranged from 15 to 77 (mean  =  29.0 ± 7.9); 43.6% of the sample had severe malocclusion and 11.6% had traumatic dental injury. The prevalence and severity of dental caries were significantly greater among adolescents with severe malocclusion. The multivariate analysis demonstrated that adolescents with severe or handicapping malocclusion had a 31% greater probability of having dental caries (prevalence ratio: 1.31; 95% CI: 1.02-1.67), independently of demographic, socioeconomic, or clinical aspects. The orthodontic characteristics associated with the occurrence and severity of caries were maxillary irregularity ≥3 mm (P  =  .021) and abnormal molar relationship (P  =  .021). Handicapping malocclusion, maxillary irregularity, and abnormal molar relationship were associated with the occurrence and severity of dental caries. The findings suggest that the prevention and treatment of these conditions can contribute to a reduction in dental caries among adolescents.

Dental caries and pulpal disease.

Science.gov (United States)

Zero, Domenick T; Zandona, Andrea Ferreira; Vail, Mychel Macapagal; Spolnik, Kenneth J

2011-01-01

This article reviews the diagnostic process, from the first clinically evident stages of the caries process to development of pulpal pathosis. The caries diagnostic process includes 4 interconnected components-staging caries lesion severity, assessing caries lesion activity, and risk assessments at the patient and tooth surface level - which modify treatment decisions for the patient. Pulpal pathosis is diagnosed as reversible pulpitis, irreversible pulpitis (asymptomatic), irreversible pulpitis (symptomatic), and pulp necrosis. Periapical disease is diagnosed as symptomatic apical periodontitis, asymptomatic apical periodontitis, acute apical abscess, and chronic apical abscess. Ultimately, the goal of any diagnosis should be to achieve better treatment decisions and health outcomes for the patient. Copyright © 2011 Elsevier Inc. All rights reserved.

Hippocampal atrophy and developmental regression as first sign of linear scleroderma "en coup de sabre".

Science.gov (United States)

Verhelst, Helene E; Beele, Hilde; Joos, Rik; Vanneuville, Benedicte; Van Coster, Rudy N

2008-11-01

An 8-year-old girl with linear scleroderma "en coup de sabre" is reported who, at preschool age, presented with intractable simple partial seizures more than 1 year before skin lesions were first noticed. MRI revealed hippocampal atrophy, controlaterally to the seizures and ipsilaterally to the skin lesions. In the following months, a mental and motor regression was noticed. Cerebral CT scan showed multiple foci of calcifications in the affected hemisphere. In previously reported patients the skin lesions preceded the neurological signs. To the best of our knowledge, hippocampal atrophy was not earlier reported as presenting symptom of linear scleroderma. Linear scleroderma should be included in the differential diagnosis in patients with unilateral hippocampal atrophy even when the typical skin lesions are not present.

Bayesian quantile regression-based partially linear mixed-effects joint models for longitudinal data with multiple features.

Science.gov (United States)

Zhang, Hanze; Huang, Yangxin; Wang, Wei; Chen, Henian; Langland-Orban, Barbara

2017-01-01

In longitudinal AIDS studies, it is of interest to investigate the relationship between HIV viral load and CD4 cell counts, as well as the complicated time effect. Most of common models to analyze such complex longitudinal data are based on mean-regression, which fails to provide efficient estimates due to outliers and/or heavy tails. Quantile regression-based partially linear mixed-effects models, a special case of semiparametric models enjoying benefits of both parametric and nonparametric models, have the flexibility to monitor the viral dynamics nonparametrically and detect the varying CD4 effects parametrically at different quantiles of viral load. Meanwhile, it is critical to consider various data features of repeated measurements, including left-censoring due to a limit of detection, covariate measurement error, and asymmetric distribution. In this research, we first establish a Bayesian joint models that accounts for all these data features simultaneously in the framework of quantile regression-based partially linear mixed-effects models. The proposed models are applied to analyze the Multicenter AIDS Cohort Study (MACS) data. Simulation studies are also conducted to assess the performance of the proposed methods under different scenarios.

Influence of socioeconomic and working status of the parents on the incidence of their children's dental caries.

Science.gov (United States)

Gokhale, Niraj; Nuvvula, Sivakumar

2016-01-01

In the contemporary scenario of both parents employed, there seems to be limited focus on the dietary habits and dental health of their children. Hence, we attempted to correlate the socioeconomic and working status of the parents to the incidence of their children's dental caries. One thousand school children aged between 3 and 12 years were enrolled in the study. Socioeconomic and working status of their parents was obtained by a pretested questionnaire following which these children were examined for their dental caries status. The data collected were statistically analyzed using logistic regression analysis and calculation of odds ratio. A significant correlation was observed between working status of the parents and dental caries status of their children. Though, the socioeconomic status and dental caries had a weak correlation, the odds ratio was high, indicating that the children of lower socioeconomic status or family with both parents employed were at a higher risk for dental caries. Efforts are needed to implement programs at the school level to enhance the oral and dental health among children, as parental responsibilities toward this maybe inadequate due to economic or time constraints.

Improved ability of biological and previous caries multimarkers to predict caries disease as revealed by multivariate PLS modelling

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Ericson Thorild

2009-11-01

Full Text Available Abstract Background Dental caries is a chronic disease with plaque bacteria, diet and saliva modifying disease activity. Here we have used the PLS method to evaluate a multiplicity of such biological variables (n = 88 for ability to predict caries in a cross-sectional (baseline caries and prospective (2-year caries development setting. Methods Multivariate PLS modelling was used to associate the many biological variables with caries recorded in thirty 14-year-old children by measuring the numbers of incipient and manifest caries lesions at all surfaces. Results A wide but shallow gliding scale of one fifth caries promoting or protecting, and four fifths non-influential, variables occurred. The influential markers behaved in the order of plaque bacteria > diet > saliva, with previously known plaque bacteria/diet markers and a set of new protective diet markers. A differential variable patterning appeared for new versus progressing lesions. The influential biological multimarkers (n = 18 predicted baseline caries better (ROC area 0.96 than five markers (0.92 and a single lactobacilli marker (0.7 with sensitivity/specificity of 1.87, 1.78 and 1.13 at 1/3 of the subjects diagnosed sick, respectively. Moreover, biological multimarkers (n = 18 explained 2-year caries increment slightly better than reported before but predicted it poorly (ROC area 0.76. By contrast, multimarkers based on previous caries predicted alone (ROC area 0.88, or together with biological multimarkers (0.94, increment well with a sensitivity/specificity of 1.74 at 1/3 of the subjects diagnosed sick. Conclusion Multimarkers behave better than single-to-five markers but future multimarker strategies will require systematic searches for improved saliva and plaque bacteria markers.

Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

International Nuclear Information System (INIS)

Chen, Q G; Xu, Y; Zhu, H H; Chen, H; Lin, B

2015-01-01

A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565–750 nm. The spectral parameter, defined as the ratio of wavebands at 565–750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as <0.66, 0.66–1.06, 1.06–1.62, and >1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems. (paper)

Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors

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Avval Zhila Mohajeri

2015-01-01

Full Text Available This paper deals with developing a linear quantitative structure-activity relationship (QSAR model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino [1,2-α] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR technique combined with the stepwise (SW and the genetic algorithm (GA methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.

A computer tool for a minimax criterion in binary response and heteroscedastic simple linear regression models.

Science.gov (United States)

Casero-Alonso, V; López-Fidalgo, J; Torsney, B

2017-01-01

Binary response models are used in many real applications. For these models the Fisher information matrix (FIM) is proportional to the FIM of a weighted simple linear regression model. The same is also true when the weight function has a finite integral. Thus, optimal designs for one binary model are also optimal for the corresponding weighted linear regression model. The main objective of this paper is to provide a tool for the construction of MV-optimal designs, minimizing the maximum of the variances of the estimates, for a general design space. MV-optimality is a potentially difficult criterion because of its nondifferentiability at equal variance designs. A methodology for obtaining MV-optimal designs where the design space is a compact interval [a, b] will be given for several standard weight functions. The methodology will allow us to build a user-friendly computer tool based on Mathematica to compute MV-optimal designs. Some illustrative examples will show a representation of MV-optimal designs in the Euclidean plane, taking a and b as the axes. The applet will be explained using two relevant models. In the first one the case of a weighted linear regression model is considered, where the weight function is directly chosen from a typical family. In the second example a binary response model is assumed, where the probability of the outcome is given by a typical probability distribution. Practitioners can use the provided applet to identify the solution and to know the exact support points and design weights. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Income trajectories affect treatment of dental caries from childhood to young adulthood: a birth cohort study.

Science.gov (United States)

Peres, Marco Aurelio; Liu, Pingzhou; Demarco, Flavio Fernando; Silva, Alexandre Emidio Ribeiro; Wehrmeister, Fernando Cesar; Menezes, Ana Maria; Peres, Karen Glazer

2018-01-01

We aimed to analyze the effects of family income trajectories on the increase in dental caries from childhood to young adulthood. Data from the 1993 Pelotas (Brazil) birth cohort study, in which dental caries was measured at ages 6, 12, and 18 years, were analyzed. Family income of 302 participants was assessed at birth, and at 4, 11, 15, and 18 years of age. Mother's education, toothbrushing frequency, dental visiting, dental caries in primary dentition, and birth weight were covariates. A latent class growth analysis was conducted to characterize trajectories of time-varying variables. The influence of income trajectories on the increase in dental caries from age 6 to age 18 was evaluated by a generalized linear mixed model. After adjustment, the increases in numbers of decayed and missing teeth (DMT) from age 6 to age 18 were associated with family income trajectory. The incident rate ratios (IRR) of DMT compared with the group of stable high incomes were 2.36 for stable low incomes, 1.71 for downward, and 1.64 for upward. The IRR of teeth being filled in stable low-income groups compared with stable high-income groups was 0.55. Family income mobility affected treatment patterns of dental caries. Differences across income trajectory groups were found in the components of dental caries indices rather than in the experience of disease.

Two-Sample Tests for High-Dimensional Linear Regression with an Application to Detecting Interactions.

Science.gov (United States)

Xia, Yin; Cai, Tianxi; Cai, T Tony

2018-01-01

Motivated by applications in genomics, we consider in this paper global and multiple testing for the comparisons of two high-dimensional linear regression models. A procedure for testing the equality of the two regression vectors globally is proposed and shown to be particularly powerful against sparse alternatives. We then introduce a multiple testing procedure for identifying unequal coordinates while controlling the false discovery rate and false discovery proportion. Theoretical justifications are provided to guarantee the validity of the proposed tests and optimality results are established under sparsity assumptions on the regression coefficients. The proposed testing procedures are easy to implement. Numerical properties of the procedures are investigated through simulation and data analysis. The results show that the proposed tests maintain the desired error rates under the null and have good power under the alternative at moderate sample sizes. The procedures are applied to the Framingham Offspring study to investigate the interactions between smoking and cardiovascular related genetic mutations important for an inflammation marker.

Dental Calculus Arrest of Dental Caries.

Science.gov (United States)

Keyes, Paul H; Rams, Thomas E

An inverse relationship between dental calculus mineralization and dental caries demineralization on teeth has been noted in some studies. Dental calculus may even form superficial layers over existing dental caries and arrest their progression, but this phenomenon has been only rarely documented and infrequently considered in the field of Cariology. To further assess the occurrence of dental calculus arrest of dental caries, this study evaluated a large number of extracted human teeth for the presence and location of dental caries, dental calculus, and dental plaque biofilms. A total of 1,200 teeth were preserved in 10% buffered formal saline, and viewed while moist by a single experienced examiner using a research stereomicroscope at 15-25× magnification. Representative teeth were sectioned and photographed, and their dental plaque biofilms subjected to gram-stain examination with light microscopy at 100× magnification. Dental calculus was observed on 1,140 (95%) of the extracted human teeth, and no dental carious lesions were found underlying dental calculus-covered surfaces on 1,139 of these teeth. However, dental calculus arrest of dental caries was found on one (0.54%) of 187 evaluated teeth that presented with unrestored proximal enamel caries. On the distal surface of a maxillary premolar tooth, dental calculus mineralization filled the outer surface cavitation of an incipient dental caries lesion. The dental calculus-covered carious lesion extended only slightly into enamel, and exhibited a brown pigmentation characteristic of inactive or arrested dental caries. In contrast, the tooth's mesial surface, without a superficial layer of dental calculus, had a large carious lesion going through enamel and deep into dentin. These observations further document the potential protective effects of dental calculus mineralization against dental caries.

Dental Calculus Arrest of Dental Caries

Science.gov (United States)

Keyes, Paul H.; Rams, Thomas E.

2016-01-01

Background An inverse relationship between dental calculus mineralization and dental caries demineralization on teeth has been noted in some studies. Dental calculus may even form superficial layers over existing dental caries and arrest their progression, but this phenomenon has been only rarely documented and infrequently considered in the field of Cariology. To further assess the occurrence of dental calculus arrest of dental caries, this study evaluated a large number of extracted human teeth for the presence and location of dental caries, dental calculus, and dental plaque biofilms. Materials and methods A total of 1,200 teeth were preserved in 10% buffered formal saline, and viewed while moist by a single experienced examiner using a research stereomicroscope at 15-25× magnification. Representative teeth were sectioned and photographed, and their dental plaque biofilms subjected to gram-stain examination with light microscopy at 100× magnification. Results Dental calculus was observed on 1,140 (95%) of the extracted human teeth, and no dental carious lesions were found underlying dental calculus-covered surfaces on 1,139 of these teeth. However, dental calculus arrest of dental caries was found on one (0.54%) of 187 evaluated teeth that presented with unrestored proximal enamel caries. On the distal surface of a maxillary premolar tooth, dental calculus mineralization filled the outer surface cavitation of an incipient dental caries lesion. The dental calculus-covered carious lesion extended only slightly into enamel, and exhibited a brown pigmentation characteristic of inactive or arrested dental caries. In contrast, the tooth's mesial surface, without a superficial layer of dental calculus, had a large carious lesion going through enamel and deep into dentin. Conclusions These observations further document the potential protective effects of dental calculus mineralization against dental caries. PMID:27446993

A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection

OpenAIRE

Kwan, Johnny S. H.; Kung, Annie W. C.; Sham, Pak C.

2011-01-01

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias. © The Author(s) 2011.

Predicting blood β-hydroxybutyrate using milk Fourier transform infrared spectrum, milk composition, and producer-reported variables with multiple linear regression, partial least squares regression, and artificial neural network.

Science.gov (United States)

Pralle, R S; Weigel, K W; White, H M

2018-05-01

Prediction of postpartum hyperketonemia (HYK) using Fourier transform infrared (FTIR) spectrometry analysis could be a practical diagnostic option for farms because these data are now available from routine milk analysis during Dairy Herd Improvement testing. The objectives of this study were to (1) develop and evaluate blood β-hydroxybutyrate (BHB) prediction models using multivariate linear regression (MLR), partial least squares regression (PLS), and artificial neural network (ANN) methods and (2) evaluate whether milk FTIR spectrum (mFTIR)-based models are improved with the inclusion of test-day variables (mTest; milk composition and producer-reported data). Paired blood and milk samples were collected from multiparous cows 5 to 18 d postpartum at 3 Wisconsin farms (3,629 observations from 1,013 cows). Blood BHB concentration was determined by a Precision Xtra meter (Abbot Diabetes Care, Alameda, CA), and milk samples were analyzed by a privately owned laboratory (AgSource, Menomonie, WI) for components and FTIR spectrum absorbance. Producer-recorded variables were extracted from farm management software. A blood BHB ≥1.2 mmol/L was considered HYK. The data set was divided into a training set (n = 3,020) and an external testing set (n = 609). Model fitting was implemented with JMP 12 (SAS Institute, Cary, NC). A 5-fold cross-validation was performed on the training data set for the MLR, PLS, and ANN prediction methods, with square root of blood BHB as the dependent variable. Each method was fitted using 3 combinations of variables: mFTIR, mTest, or mTest + mFTIR variables. Models were evaluated based on coefficient of determination, root mean squared error, and area under the receiver operating characteristic curve. Four models (PLS-mTest + mFTIR, ANN-mFTIR, ANN-mTest, and ANN-mTest + mFTIR) were chosen for further evaluation in the testing set after fitting to the full training set. In the cross-validation analysis, model fit was greatest for ANN, followed

Method validation using weighted linear regression models for quantification of UV filters in water samples.

Science.gov (United States)

da Silva, Claudia Pereira; Emídio, Elissandro Soares; de Marchi, Mary Rosa Rodrigues

2015-01-01

This paper describes the validation of a method consisting of solid-phase extraction followed by gas chromatography-tandem mass spectrometry for the analysis of the ultraviolet (UV) filters benzophenone-3, ethylhexyl salicylate, ethylhexyl methoxycinnamate and octocrylene. The method validation criteria included evaluation of selectivity, analytical curve, trueness, precision, limits of detection and limits of quantification. The non-weighted linear regression model has traditionally been used for calibration, but it is not necessarily the optimal model in all cases. Because the assumption of homoscedasticity was not met for the analytical data in this work, a weighted least squares linear regression was used for the calibration method. The evaluated analytical parameters were satisfactory for the analytes and showed recoveries at four fortification levels between 62% and 107%, with relative standard deviations less than 14%. The detection limits ranged from 7.6 to 24.1 ng L(-1). The proposed method was used to determine the amount of UV filters in water samples from water treatment plants in Araraquara and Jau in São Paulo, Brazil. Copyright © 2014 Elsevier B.V. All rights reserved.

Linear and evolutionary polynomial regression models to forecast coastal dynamics: Comparison and reliability assessment

Science.gov (United States)

Bruno, Delia Evelina; Barca, Emanuele; Goncalves, Rodrigo Mikosz; de Araujo Queiroz, Heithor Alexandre; Berardi, Luigi; Passarella, Giuseppe

2018-01-01

In this paper, the Evolutionary Polynomial Regression data modelling strategy has been applied to study small scale, short-term coastal morphodynamics, given its capability for treating a wide database of known information, non-linearly. Simple linear and multilinear regression models were also applied to achieve a balance between the computational load and reliability of estimations of the three models. In fact, even though it is easy to imagine that the more complex the model, the more the prediction improves, sometimes a "slight" worsening of estimations can be accepted in exchange for the time saved in data organization and computational load. The models' outcomes were validated through a detailed statistical, error analysis, which revealed a slightly better estimation of the polynomial model with respect to the multilinear model, as expected. On the other hand, even though the data organization was identical for the two models, the multilinear one required a simpler simulation setting and a faster run time. Finally, the most reliable evolutionary polynomial regression model was used in order to make some conjecture about the uncertainty increase with the extension of extrapolation time of the estimation. The overlapping rate between the confidence band of the mean of the known coast position and the prediction band of the estimated position can be a good index of the weakness in producing reliable estimations when the extrapolation time increases too much. The proposed models and tests have been applied to a coastal sector located nearby Torre Colimena in the Apulia region, south Italy.

Improving ASTER GDEM Accuracy Using Land Use-Based Linear Regression Methods: A Case Study of Lianyungang, East China

Directory of Open Access Journals (Sweden)

Xiaoyan Yang

2018-04-01

Full Text Available The Advanced Spaceborne Thermal-Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM is important to a wide range of geographical and environmental studies. Its accuracy, to some extent associated with land-use types reflecting topography, vegetation coverage, and human activities, impacts the results and conclusions of these studies. In order to improve the accuracy of ASTER GDEM prior to its application, we investigated ASTER GDEM errors based on individual land-use types and proposed two linear regression calibration methods, one considering only land use-specific errors and the other considering the impact of both land-use and topography. Our calibration methods were tested on the coastal prefectural city of Lianyungang in eastern China. Results indicate that (1 ASTER GDEM is highly accurate for rice, wheat, grass and mining lands but less accurate for scenic, garden, wood and bare lands; (2 despite improvements in ASTER GDEM2 accuracy, multiple linear regression calibration requires more data (topography and a relatively complex calibration process; (3 simple linear regression calibration proves a practicable and simplified means to systematically investigate and improve the impact of land-use on ASTER GDEM accuracy. Our method is applicable to areas with detailed land-use data based on highly accurate field-based point-elevation measurements.

Estimating integrated variance in the presence of microstructure noise using linear regression

Science.gov (United States)

Holý, Vladimír

2017-07-01

Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.

Face Hallucination with Linear Regression Model in Semi-Orthogonal Multilinear PCA Method

Science.gov (United States)

Asavaskulkiet, Krissada

2018-04-01

In this paper, we propose a new face hallucination technique, face images reconstruction in HSV color space with a semi-orthogonal multilinear principal component analysis method. This novel hallucination technique can perform directly from tensors via tensor-to-vector projection by imposing the orthogonality constraint in only one mode. In our experiments, we use facial images from FERET database to test our hallucination approach which is demonstrated by extensive experiments with high-quality hallucinated color faces. The experimental results assure clearly demonstrated that we can generate photorealistic color face images by using the SO-MPCA subspace with a linear regression model.

Genomic prediction based on data from three layer lines using non-linear regression models.

Science.gov (United States)

Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L

2014-11-06

Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional

Caries og drikkevandets kvalitet

DEFF Research Database (Denmark)

Arvin, Erik; Bardow, Allan; Bruvo, Maja

2011-01-01

Drikkevandskvaliteten har stor betydning for forekomsten af caries blandt 15 årige skolebørn, også selv om de bruger fluoridholdigt tandpasta. Ud over den kendte effekt af fluorid har vi vist, at calcium også har en væsentlig betydning. Begge ioner forebygger caries. Denne viden har væsentlig...

A longitudinal study of the relationship between dental caries and obesity in late childhood and adolescence.

Science.gov (United States)

Hall-Scullin, Emma Patricia; Whitehead, Hilary; Rushton, Helen; Milsom, Keith; Tickle, Martin

2017-10-30

To determine whether caries experience in late childhood (aged 7-9 years) was predictive of adolescent obesity (ages 12-16 years) to inform the use of a common risk factor approach (CRFA) for prevention. A cohort study was conducted in an area of North West England. Clinical assessment of caries took place using the same methodology at ages 7-9 years and 12-16 years. Body mass index (BMI) category was calculated from height and weight measurements using age and gender specific cut-offs at 12-16 years only. The association between dependent variable (BMI category dichotomized as underweight/normal and overweight/obese) and explanatory variables (baseline and follow-up dental caries and sociodemographic status) adjusted for age, was assessed. At baseline, 5,470 (96.8 percent) participants took part and information was available for 2,958 (54.1 percent) participants at follow-up. Univariate analysis indicated that BMI category in adolescence was not shown to be significantly associated with: the presence or absence of caries in late childhood (P = 0.61); in adolescence (P = 0.06); gender (P = 0.91); or deprivation (P = 0.35). Multivariate logistic regression indicated that BMI category in adolescence was not predicted by caries in late childhood or adolescence, after adjusting for sociodemographic variables. Caries and obesity were highly prevalent in this population. Caries in childhood was not shown to be associated with obesity in adolescence and there was no cross-sectional association between the two diseases in adolescence. A CRFA is not precluded, however, the results suggest that additional interventions, specific for each disease, are required to prevent obesity and caries. © 2017 American Association of Public Health Dentistry.

Caries risk assessment in young adults

DEFF Research Database (Denmark)

Petersson, Gunnel Hänsel; Twetman, Svante

2015-01-01

BACKGROUND: To validate baseline caries risk classifications according to the Cariogram model with the actual caries development over a 3-year period in a group of young adults living in Sweden. METHODS: The study group consisted of 1,295 19-year-old patients that completed a comprehensive clinical...... baseline examination, including radiographs and salivary tests. An individual caries risk profile was computed and the patient was placed in one of five risk categories. After 3 years, 982 patients (75.8%) were re-examined and caries increment for each patient was calculated. The outcome was expressed...... as sensitivity, specificity and predictive values and compared with a risk assessment scheme used in Public Dental Service. RESULTS: The drop-outs displayed more risk factors and a significantly higher caries burden at baseline compared with those that remained in the project (p 

Food insecurity and dental caries in schoolchildren: a cross-sectional survey in the western Brazilian Amazon.

Science.gov (United States)

Frazão, Paulo; Benicio, Maria H D; Narvai, Paulo C; Cardoso, Marly A

2014-06-01

We analyzed the association between food insecurity and dental caries in 7- to 9-yr-old schoolchildren. We performed a cross-sectional survey nested in a population-based cohort study of 203 schoolchildren. The participants lived in the urban area of a small town within the western Brazilian Amazon. Dental examinations were performed according to criteria recommended by the World Health Organization. The number of decayed deciduous and permanent teeth as a count variable was the outcome measure. Socio-economic status, food security, behavioral variables, and child nutritional status, measured by Z-score for body mass index (BMI), were investigated, and robust Poisson regression models were used. The results showed a mean (SD) of 3.63 (3.26) teeth affected by untreated caries. Approximately 80% of schoolchildren had at least one untreated decayed tooth, and nearly 60% lived in food-insecure households. Sex, household wealth index, mother's education level, and food-insecurity scores were associated with dental caries in the crude analysis. Dental caries was 1.5 times more likely to be associated with high food-insecurity scores after adjusting for socio-economic status and sex. A significant dose-response relationship was observed. In conclusion, food insecurity is highly associated with dental caries in 7- to 9-yr-old children and may be seen as a risk factor. These findings suggest that food-security policies could reduce dental caries. © 2014 Eur J Oral Sci.

Quantification and Management of Manifest Occlusal Caries Lesions in Adults: A Methodological and a Clinical Study

DEFF Research Database (Denmark)

Bakhshandeh, Azam

2010-01-01

teeth with primary occlusal lesions. Randomization was performed in cases of more than one lesion in the same patient, so that the final material consisted of 60 resin sealed and 12 restored lesions. After 2-3 years, there was a drop-out of 15%; 2 patients did not show up for the control and 9...... extension of the lesions from baseline and the last control radiograph, there was scored caries progression beneath 5 (10%) of 49 sealants, caries regression beneath 1 (2%) sealant and unchanged lesion depth beneath 43 (88%) sealants and all restorations (p = 0.64). The methodological study included 110...

Linear regression based on Minimum Covariance Determinant (MCD) and TELBS methods on the productivity of phytoplankton

Science.gov (United States)

Gusriani, N.; Firdaniza

2018-03-01

The existence of outliers on multiple linear regression analysis causes the Gaussian assumption to be unfulfilled. If the Least Square method is forcedly used on these data, it will produce a model that cannot represent most data. For that, we need a robust regression method against outliers. This paper will compare the Minimum Covariance Determinant (MCD) method and the TELBS method on secondary data on the productivity of phytoplankton, which contains outliers. Based on the robust determinant coefficient value, MCD method produces a better model compared to TELBS method.

In vivo Dentin Caries Model using Rat Molars

OpenAIRE

Takashi, HIGASHI; Junji, TAGAMI; Nobuhiro, HANADA; Cariology and Operative Dentistry, Department of Restorative Sciences, Tokyo Medical and Dental University; Cariology and Operative Dentistry, Department of Restorative Sciences, Tokyo Medical and Dental University; Department of Oral Science The National Institute of Infectious Diseases(NIID)

2000-01-01

Experimental dentinal caries was induced in rat molars which were inoculated orally with Streptococcus mutans and maintained on a carionenic diet 2000. After 30 days on the diet, the rats were sacrificed. The caries lesions were confirmed with a caries detector, then nanohardness determination of caries dentin were measured with nanoindentation. After hardness measurement, the lesion was examined by SEM and EDS. Dentin caries in sixteen fissures was induced among 20 fissures in the mandibular...

U.S. Army Armament Research, Development and Engineering Center Grain Evaluation Software to Numerically Predict Linear Burn Regression for Solid Propellant Grain Geometries

Science.gov (United States)

2017-10-01

ENGINEERING CENTER GRAIN EVALUATION SOFTWARE TO NUMERICALLY PREDICT LINEAR BURN REGRESSION FOR SOLID PROPELLANT GRAIN GEOMETRIES Brian...distribution is unlimited. AD U.S. ARMY ARMAMENT RESEARCH, DEVELOPMENT AND ENGINEERING CENTER Munitions Engineering Technology Center Picatinny...U.S. ARMY ARMAMENT RESEARCH, DEVELOPMENT AND ENGINEERING CENTER GRAIN EVALUATION SOFTWARE TO NUMERICALLY PREDICT LINEAR BURN REGRESSION FOR SOLID

Isotherms and thermodynamics by linear and non-linear regression analysis for the sorption of methylene blue onto activated carbon: Comparison of various error functions

International Nuclear Information System (INIS)

Kumar, K. Vasanth; Porkodi, K.; Rocha, F.

2008-01-01

A comparison of linear and non-linear regression method in selecting the optimum isotherm was made to the experimental equilibrium data of methylene blue sorption by activated carbon. The r 2 was used to select the best fit linear theoretical isotherm. In the case of non-linear regression method, six error functions, namely coefficient of determination (r 2 ), hybrid fractional error function (HYBRID), Marquardt's percent standard deviation (MPSD), average relative error (ARE), sum of the errors squared (ERRSQ) and sum of the absolute errors (EABS) were used to predict the parameters involved in the two and three parameter isotherms and also to predict the optimum isotherm. For two parameter isotherm, MPSD was found to be the best error function in minimizing the error distribution between the experimental equilibrium data and predicted isotherms. In the case of three parameter isotherm, r 2 was found to be the best error function to minimize the error distribution structure between experimental equilibrium data and theoretical isotherms. The present study showed that the size of the error function alone is not a deciding factor to choose the optimum isotherm. In addition to the size of error function, the theory behind the predicted isotherm should be verified with the help of experimental data while selecting the optimum isotherm. A coefficient of non-determination, K 2 was explained and was found to be very useful in identifying the best error function while selecting the optimum isotherm

Association between Peritonsillar Abscess and Molar Caries

Directory of Open Access Journals (Sweden)

M Shayani Nasab

2006-05-01

Full Text Available Background: Peritonsillar abscess is the most common deep neck infections that are related with periodontal disease which has the same pathogenesis. We determined the relationship between peritonsillar infection and molar caries. Methods: In a cross-sectional study, 33 consecutive patients whom referred to Hamadan university clinic of otolaryngologic for peritonsillar abscess were examined by otolaryngologist and dentist who investigated relationship between peritonsillar infection and molar caries. Results: There were 27 males and 6 females with mean age 26.7+_7 years. The frequency caries on ipsilateral peritonsillar infection sides was in relation to molars caries on opposite sides (conterol group. This corrolation was significant with odds ratio 2.5. Conclusion: Molar caries were seen 2.5 times more likely to have peritonsillar infection compared with normal molar sides. Key Words: Peritonsillar abscess, Infection, Periodontal disease, Dental caries

A Matlab program for stepwise regression

Directory of Open Access Journals (Sweden)

Yanhong Qi

2016-03-01

Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

Relation Between Past and Present Dietary Sugar Intake and Dental Caries in A High Caries Population

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T. Malek Mohammadi

2008-06-01

Full Text Available Objective: The main objective of this study was to investigate relationship between re-ported dietary habits and dental caries in five and six-year-old children referred for dental extractions.Materials and Methods: Two hundred children were examined using standard caries di-agnostic criteria. The numbers of decayed, missing and filled deciduous teeth were re-corded. A food frequency table was completed by the parents of each child and analyzedthrough weighting the cariogenic potentialby the frequency of consumption, and summing the two scores.Results: The mean number of decayed, missing and filled teeth (dmft was 7.1 (SD=3.29. There was no statistically significant correlation between the reported dietary intake and the caries rate in the study population P=0.07.Use of bottles with sugared drinks during infancy was associated with increased caries levels (P<0.01.Conclusion: Poor infant feeding practices promote caries in childhood. A method of diet assessment which would evaluate diet-related health education is required.

Logistic regression for dichotomized counts.

Science.gov (United States)

Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

2016-12-01

Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

Aspects of robust linear regression

NARCIS (Netherlands)

Davies, P.L.

1993-01-01

Section 1 of the paper contains a general discussion of robustness. In Section 2 the influence function of the Hampel-Rousseeuw least median of squares estimator is derived. Linearly invariant weak metrics are constructed in Section 3. It is shown in Section 4 that $S$-estimators satisfy an exact

Early life factors and dental caries in 5-year-old children in China.

Science.gov (United States)

Sun, Xiangyu; Bernabé, Eduardo; Liu, Xuenan; Gallagher, Jennifer E; Zheng, Shuguo

2017-09-01

This study aimed to explore the association between early life factors and dental caries among 5-year-old Chinese children. Data from 9722 preschool children who participated in the third National Oral Health Survey of China were analysed. Information on early life (birth weight, breastfeeding and age when toothbrushing started), child (sex, ethnicity, birth order and dental behaviours) and family factors (parental education, household income, place of residence, number of children in the family, respondent's age and relation to the child) were obtained from parental questionnaires. Children were also clinically examined to assess dental caries experience using the decayed, missing and filled teeth (dmft) index. The association of early life factors with dmft was evaluated in negative binomial regression models. We found that birth weight was not associated with dental caries experience; children who were exclusively and predominantly formula-fed had lower dmft values than those exclusively breastfed; and children who started brushing later in life had higher dmft values than those who were brushing within the first year. Only one in seven of all children received regular toothbrushing twice per day, and only 34.7% had commenced toothbrushing by the age of 3 years. This study shows certain early life factors play a role in dental caries among Chinese preschool children and provides important insights to shape public health initiatives on the importance of introducing early toothbrushing. The early environment, especially the age when parents introduce toothbrushing to their children, can be an important factor to prevent childhood dental caries. Copyright © 2017 Elsevier Ltd. All rights reserved.

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

Science.gov (United States)

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Assessment of caries status among schoolchildren according to decayed-missing-filled teeth/decayed-extract-filled teeth index, International Caries Detection and Assessment System, and Caries Assessment Spectrum and Treatment criteria

Directory of Open Access Journals (Sweden)

E Rajendra Reddy

2017-01-01

Full Text Available Background: Detection and evaluation of dental caries is of epidemiological importance. Its early detection is important to commence appropriate treatment planning. Cavitated, noncavitated, and initial lesions of dental caries can be detected by various indices. Objectives: The objective of the study was to assess the caries experience in schoolchildren using decayed-missing-filled teeth (DMFT/decayed-extracted-filled teeth (deft, International Caries Detection and Assessment System-II (ICDAS-II, and Caries Assessment Spectrum and Treatment (CAST systems. Materials and Methods: An epidemiological survey was carried out among 1550 schoolchildren (37,644 teeth between the age ranges of 4 and 14 years. American Dental Association type III examination was performed using plane mouth mirrors and community periodontal index probes using DMFT/deft, ICDAS II, and CAST indices. Results: Out of 37,644 teeth examined, 2,718 teeth had shown caries. Caries experience with DMFT/deft index was 5.54%. Highest score of DMFT was observed in deciduous dentition period (59.02%. Overall prevalence of dental caries with ICDAS and CAST system was 6.7% and 6.95%, respectively. The highest percentage of noncavitated lesions (ICDAS - 2.26% and CAST - 3.9% and greater prevalence of caries among deciduous teeth (ICDAS - 53.2% and CAST - 58.7% was observed with both ICDAS and CAST systems. Conclusion: A high prevalence of noncavitated lesions and less number of sealants and restorations indicates the lack of awareness for prevention and treatment of oral diseases, which suggests a strong need for preventive and operative treatments.

Three Incomplete Caries Removal Techniques Compared Over Two Years in Primary Molars with Asymptomatic Deep Caries or Reversible Pulpitis.

Science.gov (United States)

Chompu-inwai, Papimon; Boonsongsawat, Kamolthip; Sastraruji, Thanapat; Sophasri, Tidarat; Mankaen, Siripun; Nondon, Sutasinee; Tunlek, Sumattaya; Katwong, Supitchaya

2015-01-01

To directly compare the survival rates of three incomplete caries removal techniques that differed in the amount of caries removal and the base material used. Ninety-six primary molars with asymptomatic deep caries or reversible pulpitis were randomly assigned to three groups: (1) indirect pulp treatment (IPT); (2) minimal caries removal with both resin-modified glass ionomer base material and luting cement (MCRB/L); and (3) minimal caries removal with only resin-modified glass ionomer luting cement (MCRL). The treatments were followed clinically and radiographically for two years. The two-year survival probabilities in the IPT, MCRB/L, and MCRL groups were 0.90 (95 percent confidence interval [CI] equals 0.73 to 0.97), 0.93 (95 percent CI equals 0.76 to 0.98), and 0.77 (95 percent CI equals 0.58 to 0.89), respectively. There was no significant difference in the two-year survival probabilities of the three studied groups (generalized Wilcoxon P=.07). Following two years, neither the amount of caries removal nor the base material affected the success of incomplete caries removal treatment. However, minimal caries removal with MCRB/L presented the highest survival rate among the tested groups and resulted in no incidence of pulp exposure.

Characteristics and Properties of a Simple Linear Regression Model

Directory of Open Access Journals (Sweden)

Kowal Robert

2016-12-01

Full Text Available A simple linear regression model is one of the pillars of classic econometrics. Despite the passage of time, it continues to raise interest both from the theoretical side as well as from the application side. One of the many fundamental questions in the model concerns determining derivative characteristics and studying the properties existing in their scope, referring to the first of these aspects. The literature of the subject provides several classic solutions in that regard. In the paper, a completely new design is proposed, based on the direct application of variance and its properties, resulting from the non-correlation of certain estimators with the mean, within the scope of which some fundamental dependencies of the model characteristics are obtained in a much more compact manner. The apparatus allows for a simple and uniform demonstration of multiple dependencies and fundamental properties in the model, and it does it in an intuitive manner. The results were obtained in a classic, traditional area, where everything, as it might seem, has already been thoroughly studied and discovered.

Exhaustive Search for Sparse Variable Selection in Linear Regression

Science.gov (United States)

Igarashi, Yasuhiko; Takenaka, Hikaru; Nakanishi-Ohno, Yoshinori; Uemura, Makoto; Ikeda, Shiro; Okada, Masato

2018-04-01

We propose a K-sparse exhaustive search (ES-K) method and a K-sparse approximate exhaustive search method (AES-K) for selecting variables in linear regression. With these methods, K-sparse combinations of variables are tested exhaustively assuming that the optimal combination of explanatory variables is K-sparse. By collecting the results of exhaustively computing ES-K, various approximate methods for selecting sparse variables can be summarized as density of states. With this density of states, we can compare different methods for selecting sparse variables such as relaxation and sampling. For large problems where the combinatorial explosion of explanatory variables is crucial, the AES-K method enables density of states to be effectively reconstructed by using the replica-exchange Monte Carlo method and the multiple histogram method. Applying the ES-K and AES-K methods to type Ia supernova data, we confirmed the conventional understanding in astronomy when an appropriate K is given beforehand. However, we found the difficulty to determine K from the data. Using virtual measurement and analysis, we argue that this is caused by data shortage.

Soil moisture estimation using multi linear regression with terraSAR-X data

Directory of Open Access Journals (Sweden)

G. García

2016-06-01

Full Text Available The first five centimeters of soil form an interface where the main heat fluxes exchanges between the land surface and the atmosphere occur. Besides ground measurements, remote sensing has proven to be an excellent tool for the monitoring of spatial and temporal distributed data of the most relevant Earth surface parameters including soil’s parameters. Indeed, active microwave sensors (Synthetic Aperture Radar - SAR offer the opportunity to monitor soil moisture (HS at global, regional and local scales by monitoring involved processes. Several inversion algorithms, that derive geophysical information as HS from SAR data, were developed. Many of them use electromagnetic models for simulating the backscattering coefficient and are based on statistical techniques, such as neural networks, inversion methods and regression models. Recent studies have shown that simple multiple regression techniques yield satisfactory results. The involved geophysical variables in these methodologies are descriptive of the soil structure, microwave characteristics and land use. Therefore, in this paper we aim at developing a multiple linear regression model to estimate HS on flat agricultural regions using TerraSAR-X satellite data and data from a ground weather station. The results show that the backscatter, the precipitation and the relative humidity are the explanatory variables of HS. The results obtained presented a RMSE of 5.4 and a R2  of about 0.6

Linear Regression Based Real-Time Filtering

Directory of Open Access Journals (Sweden)

Misel Batmend

2013-01-01

Full Text Available This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications. Advantage over Kalman filter is that it is computationally less expensive. The paper further deals with application of introduced method on filtering data used to evaluate a position of engraved material with respect to engraving machine. The filter was implemented to the CNC engraving machine control system. Experiments showing its performance are included.

A unified framework for testing in the linear regression model under unknown order of fractional integration

DEFF Research Database (Denmark)

Christensen, Bent Jesper; Kruse, Robinson; Sibbertsen, Philipp

We consider hypothesis testing in a general linear time series regression framework when the possibly fractional order of integration of the error term is unknown. We show that the approach suggested by Vogelsang (1998a) for the case of integer integration does not apply to the case of fractional...

Caries risk assessment in pregnant women using cariogram

Directory of Open Access Journals (Sweden)

Dolić Olivera

2017-01-01

Full Text Available Introduction/Objective. “Cariogram” takes into account interactions between caries-related factors and expresses a graphic assessment of the caries risk. The aim of this study was to evaluate the relationship between caries risk and different variables of Cariogram in pregnant women. Methods. This study included 96 pregnant women. At baseline, data on general health, diet, oral hygiene, and fluoride exposure were obtained. DMFT (decayed, missing, and filled teeth index was calculated by clinical examination. Saliva analyses included mutans streptococci and lactobacilli counts, buffer capacity, and secretion rate. Scores were entered and caries risk was assessed. The women were divided into five groups according to their Cariogram caries risk. Results. The results of the study showed that 29.17% (28 of the pregnant women had high caries risk, 21.88% (21 – medium, 17.71% (17 – low, 16.67% (16 – very high, and 14.58% (14 – very low caries risk. In an average caries risk profile of pregnant women, the dominant sector was “Bacteria” (18.85% of the risk structure profile, followed by “Diet” (17.97%, “Circumstances” (15.68%, and “Susceptibility” sector (14.65%. Conclusion. Cariogram shows that pregnant women in Banja Luka, Bosnia and Herzegovina, had 46.14% chance of avoiding caries in the future. The Cariogram model can successfully determine caries risk profiles for pregnant women.

Use of multiple linear regression and logistic regression models to investigate changes in birthweight for term singleton infants in Scotland.

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Bonellie, Sandra R

2012-10-01

To illustrate the use of regression and logistic regression models to investigate changes over time in size of babies particularly in relation to social deprivation, age of the mother and smoking. Mean birthweight has been found to be increasing in many countries in recent years, but there are still a group of babies who are born with low birthweights. Population-based retrospective cohort study. Multiple linear regression and logistic regression models are used to analyse data on term 'singleton births' from Scottish hospitals between 1994-2003. Mothers who smoke are shown to give birth to lighter babies on average, a difference of approximately 0.57 Standard deviations lower (95% confidence interval. 0.55-0.58) when adjusted for sex and parity. These mothers are also more likely to have babies that are low birthweight (odds ratio 3.46, 95% confidence interval 3.30-3.63) compared with non-smokers. Low birthweight is 30% more likely where the mother lives in the most deprived areas compared with the least deprived, (odds ratio 1.30, 95% confidence interval 1.21-1.40). Smoking during pregnancy is shown to have a detrimental effect on the size of infants at birth. This effect explains some, though not all, of the observed socioeconomic birthweight. It also explains much of the observed birthweight differences by the age of the mother.   Identifying mothers at greater risk of having a low birthweight baby as important implications for the care and advice this group receives. © 2012 Blackwell Publishing Ltd.

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics.

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Miguel-Hurtado, Oscar; Guest, Richard; Stevenage, Sarah V; Neil, Greg J; Black, Sue

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications.

Disparities in Early Childhood Caries

Directory of Open Access Journals (Sweden)

Ronzio Cynthia R

2006-06-01

Full Text Available Abstract Despite remarkable reduction in the prevalence of dental caries in the United States, dental caries is still a highly prevalent disease among children who are socially disadvantaged (racial/ethnic minority, poor, rural, immigrants. Consequently, caries sequelae such as dental pain, need for dental treatment under general anesthesia, and future orthodontic treatment, are also concentrated among the most socially disadvantaged children. To make the situation more appalling, those children who need treatment the most are the ones least likely to visit the dentist. Low income children are less likely to visit the dentist in part because of family's competing needs for limited resources, shortage of pediatric dentists, and dentists not taking uninsured or publicly insured patients. In the same vein, if these children do not have access to dental care, they are deprived from effective caries preventive measures that are dentist-dependent such as sealants and professionally applied fluoride. Dentistry has done well at devising caries preventive and treatment strategies; but these strategies have missed the most needed segment of society: disadvantaged children. The challenge now is to develop innovative strategies to reach these children.

Credit Scoring Problem Based on Regression Analysis

OpenAIRE

Khassawneh, Bashar Suhil Jad Allah

2014-01-01

ABSTRACT: This thesis provides an explanatory introduction to the regression models of data mining and contains basic definitions of key terms in the linear, multiple and logistic regression models. Meanwhile, the aim of this study is to illustrate fitting models for the credit scoring problem using simple linear, multiple linear and logistic regression models and also to analyze the found model functions by statistical tools. Keywords: Data mining, linear regression, logistic regression....

Relation between Dental Caries and Body Mass Index-for-age among Schoolchildren of Jazan City, Kingdom of Saudi Arabia.

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Quadri, Mir Fa; Hakami, Bassam M; Hezam, Asma Aa; Hakami, Raed Y; Saadi, Fadwa A; Ageeli, Layla M; Alsagoor, Wafqah H; Faqeeh, Mohammad A; Dhae, Mohammed A

2017-04-01

To analyze and report the type of relation present between dental caries and body mass index (BMI)-for-age among schoolchildren in Jazan region of Kingdom of Saudi Arabia. A cross-sectional study with multi-staged random sampling technique was designed to recruit the sample of schoolchildren. Caries was examined using the World Health Organization recommended "decayed and filled teeth"/"decayed missing and filled teeth (dft/DMFT)" method. The BMI-for-age was calculated using the value obtained from body weight and height (kg/m 2 ) of each child. The obtained results were plotted on age- and gender-specific percentile curves by the Centers for Disease Control and Prevention and categorized accordingly. Chi-squared test was conducted to analyze the relation between BMI-for-age and dental caries. Logistic regression was performed to judge the predictor variables. The p-value Dental caries, fast food, and snacks between meals were significant independent predictor variables for BMI (p Dental caries was a strong predictor, and the analysis showed that children with untreated caries had 81% (odds ratio = 0.19; confidence interval = 0.65, 0.58) higher chance of suffering from low BMI. To conclude, this is the first study attempted to see the relationship between BMI-for-age and dental caries among schoolchildren in Jazan city of Kingdom of Saudi Arabia. Negative relation between dental caries and BMI should warrant health promoters about dental caries as a reason for low BMI in a subset of children. High and alarming percentage of untreated dental caries demonstrates the oral health needs among the schoolgoing children in Jazan region. Public health dentists should develop and implement prevention programs so that the oral health issues among schoolchildren are addressed.

A tissue-dependent hypothesis of dental caries.

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Simón-Soro, A; Belda-Ferre, P; Cabrera-Rubio, R; Alcaraz, L D; Mira, A

2013-01-01

Current understanding of dental caries considers this disease a demineralization of the tooth tissues due to the acid produced by sugar-fermenting microorganisms. Thus, caries is considered a diet- and pH-dependent process. We present here the first metagenomic analysis of the bacterial communities present at different stages of caries development, with the aim of determining whether the bacterial composition and biochemical profile are specific to the tissue affected. The data show that microbial composition at the initial, enamel-affecting stage of caries is significantly different from that found at subsequent stages, as well as from dental plaque of sound tooth surfaces. Although the relative proportion of Streptococcus mutans increased from 0.12% in dental plaque to 0.72% in enamel caries, Streptococcus mitis and Streptococcus sanguinis were the dominant streptococci in these lesions. The functional profile of caries-associated bacterial communities indicates that genes involved in acid stress tolerance and dietary sugar fermentation are overrepresented only at the initial stage (enamel caries), whereas other genes coding for osmotic stress tolerance as well as collagenases and other proteases enabling dentin degradation are significantly overrepresented in dentin cavities. The results support a scenario in which pH and diet are determinants of the disease during the degradation of enamel, but in dentin caries lesions not only acidogenic but also proteolytic bacteria are involved. We propose that caries disease is a process of varying etiology, in which acid-producing bacteria are the vehicle to penetrate enamel and allow dentin degrading microorganisms to expand the cavity. © 2013 S. Karger AG, Basel.