Longitudinal analysis of the strengths and difficulties questionnaire scores of the Millennium Cohort Study children in England using M-quantile random-effects regression.

PubMed

Tzavidis, Nikos; Salvati, Nicola; Schmid, Timo; Flouri, Eirini; Midouhas, Emily

2016-02-01

Multilevel modelling is a popular approach for longitudinal data analysis. Statistical models conventionally target a parameter at the centre of a distribution. However, when the distribution of the data is asymmetric, modelling other location parameters, e.g. percentiles, may be more informative. We present a new approach, M -quantile random-effects regression, for modelling multilevel data. The proposed method is used for modelling location parameters of the distribution of the strengths and difficulties questionnaire scores of children in England who participate in the Millennium Cohort Study. Quantile mixed models are also considered. The analyses offer insights to child psychologists about the differential effects of risk factors on children's outcomes.

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

PubMed

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.

Multivariate generalized hidden Markov regression models with random covariates: Physical exercise in an elderly population.

PubMed

Punzo, Antonio; Ingrassia, Salvatore; Maruotti, Antonello

2018-04-22

A time-varying latent variable model is proposed to jointly analyze multivariate mixed-support longitudinal data. The proposal can be viewed as an extension of hidden Markov regression models with fixed covariates (HMRMFCs), which is the state of the art for modelling longitudinal data, with a special focus on the underlying clustering structure. HMRMFCs are inadequate for applications in which a clustering structure can be identified in the distribution of the covariates, as the clustering is independent from the covariates distribution. Here, hidden Markov regression models with random covariates are introduced by explicitly specifying state-specific distributions for the covariates, with the aim of improving the recovering of the clusters in the data with respect to a fixed covariates paradigm. The hidden Markov regression models with random covariates class is defined focusing on the exponential family, in a generalized linear model framework. Model identifiability conditions are sketched, an expectation-maximization algorithm is outlined for parameter estimation, and various implementation and operational issues are discussed. Properties of the estimators of the regression coefficients, as well as of the hidden path parameters, are evaluated through simulation experiments and compared with those of HMRMFCs. The method is applied to physical activity data. Copyright © 2018 John Wiley & Sons, Ltd.

An Overview of Longitudinal Data Analysis Methods for Neurological Research

PubMed Central

Locascio, Joseph J.; Atri, Alireza

2011-01-01

The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models. PMID:22203825

Educational Investment, Family Context, and Children's Math and Reading Growth from Kindergarten through the Third Grade

ERIC Educational Resources Information Center

Cheadle, Jacob E.

2008-01-01

Drawing on longitudinal data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999, this study used IRT modeling to operationalize a measure of parental educational investments based on Lareau's notion of concerted cultivation. It used multilevel piece-wise growth models regressing children's math and reading achievement…

School Attendance Problems and Youth Psychopathology: Structural Cross-Lagged Regression Models in Three Longitudinal Data Sets

ERIC Educational Resources Information Center

Wood, Jeffrey J.; Lynne-Landsman, Sarah D.; Langer, David A.; Wood, Patricia A.; Clark, Shaunna L.; Eddy, J. Mark; Ialongo, Nick

2012-01-01

This study tests a model of reciprocal influences between absenteeism and youth psychopathology using 3 longitudinal datasets (Ns = 20,745, 2,311, and 671). Participants in 1st through 12th grades were interviewed annually or biannually. Measures of psychopathology include self-, parent-, and teacher-report questionnaires. Structural cross-lagged…

Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method.

PubMed

Leung, Denis H Y; Wang, You-Gan; Zhu, Min

2009-07-01

The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.

A generalized partially linear mean-covariance regression model for longitudinal proportional data, with applications to the analysis of quality of life data from cancer clinical trials.

PubMed

Zheng, Xueying; Qin, Guoyou; Tu, Dongsheng

2017-05-30

Motivated by the analysis of quality of life data from a clinical trial on early breast cancer, we propose in this paper a generalized partially linear mean-covariance regression model for longitudinal proportional data, which are bounded in a closed interval. Cholesky decomposition of the covariance matrix for within-subject responses and generalized estimation equations are used to estimate unknown parameters and the nonlinear function in the model. Simulation studies are performed to evaluate the performance of the proposed estimation procedures. Our new model is also applied to analyze the data from the cancer clinical trial that motivated this research. In comparison with available models in the literature, the proposed model does not require specific parametric assumptions on the density function of the longitudinal responses and the probability function of the boundary values and can capture dynamic changes of time or other interested variables on both mean and covariance of the correlated proportional responses. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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

PubMed

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 < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we 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. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation. Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models.

Retention of Children and Their Families in the Longitudinal Outcome Study of the Comprehensive Community Mental Health Services for Children and Their Families Program: A Multilevel Analysis

ERIC Educational Resources Information Center

Gebreselassie, Tesfayi; Stephens, Robert L.; Maples, Connie J.; Johnson, Stacy F.; Tucker, Alyce L.

2014-01-01

Predictors of retention of participants in a longitudinal study and heterogeneity between communities were investigated using a multilevel logistic regression model. Data from the longitudinal outcome study of the national evaluation of the Comprehensive Community Mental Health Services for Children and Their Families program and information on…

Semiparametric regression during 2003–2007*

PubMed Central

Ruppert, David; Wand, M.P.; Carroll, Raymond J.

2010-01-01

Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application. PMID:20305800

Predicting Depression among Patients with Diabetes Using Longitudinal Data. A Multilevel Regression Model.

PubMed

Jin, H; Wu, S; Vidyanti, I; Di Capua, P; Wu, B

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Depression is a common and often undiagnosed condition for patients with diabetes. It is also a condition that significantly impacts healthcare outcomes, use, and cost as well as elevating suicide risk. Therefore, a model to predict depression among diabetes patients is a promising and valuable tool for providers to proactively assess depressive symptoms and identify those with depression. This study seeks to develop a generalized multilevel regression model, using a longitudinal data set from a recent large-scale clinical trial, to predict depression severity and presence of major depression among patients with diabetes. Severity of depression was measured by the Patient Health Questionnaire PHQ-9 score. Predictors were selected from 29 candidate factors to develop a 2-level Poisson regression model that can make population-average predictions for all patients and subject-specific predictions for individual patients with historical records. Newly obtained patient records can be incorporated with historical records to update the prediction model. Root-mean-square errors (RMSE) were used to evaluate predictive accuracy of PHQ-9 scores. The study also evaluated the classification ability of using the predicted PHQ-9 scores to classify patients as having major depression. Two time-invariant and 10 time-varying predictors were selected for the model. Incorporating historical records and using them to update the model may improve both predictive accuracy of PHQ-9 scores and classification ability of the predicted scores. Subject-specific predictions (for individual patients with historical records) achieved RMSE about 4 and areas under the receiver operating characteristic (ROC) curve about 0.9 and are better than population-average predictions. The study developed a generalized multilevel regression model to predict depression and demonstrated that using generalized multilevel regression based on longitudinal patient records can achieve high predictive ability.

A Comparison of Various MRA Methods Applied to Longitudinal Evaluation Studies in Vocational Education.

ERIC Educational Resources Information Center

Kapes, Jerome T.; And Others

Three models of multiple regression analysis (MRA): single equation, commonality analysis, and path analysis, were applied to longitudinal data from the Pennsylvania Vocational Development Study. Variables influencing weekly income of vocational education students one year after high school graduation were examined: grade point averages (grades…

Predictors of Adolescent Breakfast Consumption: Longitudinal Findings from Project EAT

ERIC Educational Resources Information Center

Bruening, Meg; Larson, Nicole; Story, Mary; Neumark-Sztainer, Dianne; Hannan, Peter

2011-01-01

Objective: To identify predictors of breakfast consumption among adolescents. Methods: Five-year longitudinal study Project EAT (Eating Among Teens). Baseline surveys were completed in Minneapolis-St. Paul schools and by mail at follow-up by youth (n = 800) transitioning from middle to high school. Linear regression models examined associations…

What Are the Odds of that? A Primer on Understanding Logistic Regression

ERIC Educational Resources Information Center

Huang, Francis L.; Moon, Tonya R.

2013-01-01

The purpose of this Methodological Brief is to present a brief primer on logistic regression, a commonly used technique when modeling dichotomous outcomes. Using data from the National Education Longitudinal Study of 1988 (NELS:88), logistic regression techniques were used to investigate student-level variables in eighth grade (i.e., enrolled in a…

Predicting longitudinal trajectories of health probabilities with random-effects multinomial logit regression.

PubMed

Liu, Xian; Engel, Charles C

2012-12-20

Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.

Changes in aerobic power of men, ages 25-70 yr

NASA Technical Reports Server (NTRS)

Jackson, A. S.; Beard, E. F.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.; Blair, S. N.

1995-01-01

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak). The cross-sectional sample consisted of 1,499 healthy men ages 25-70 yr. The 156 men of the longitudinal sample were from the same population and examined twice, the mean time between tests was 4.1 (+/- 1.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill exercise test. The zero-order correlations between VO2peak and %fat (r = -0.62) and SR-PA (r = 0.58) were significantly (P < 0.05) higher that the age correlation (r = -0.45). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.46 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.79) showed that nearly 50% of this cross-sectional decline was due to %fat and SR-PA, adding these lifestyle variables to the multiple regression model reduced the age regression weight to -0.26 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results.

A Longitudinal Study of Welfare Exit among American Indian Families

ERIC Educational Resources Information Center

Pandey, Shanta; Guo, Baorong

2007-01-01

Data from a longitudinal survey of families from three reservations (Navajo Nation, San Carlos, and Salt River) in Arizona were used to examine their probability of welfare use. Logistic regression models were used to estimate the effects of individual, family, and structural factors on welfare exit. Results indicate that their probability of…

MIXOR: a computer program for mixed-effects ordinal regression analysis.

PubMed

Hedeker, D; Gibbons, R D

1996-03-01

MIXOR provides maximum marginal likelihood estimates for mixed-effects ordinal probit, logistic, and complementary log-log regression models. These models can be used for analysis of dichotomous and ordinal outcomes from either a clustered or longitudinal design. For clustered data, the mixed-effects model assumes that data within clusters are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from clustering of the data. Similarly, for longitudinal data, the mixed-effects approach can allow for individual-varying intercepts and slopes across time, and can estimate the degree to which these time-related effects vary in the population of individuals. MIXOR uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated, along with the effects of model covariates. Examples illustrating usage and features of MIXOR are provided.

Temporal patterns of variable relationships in person-oriented research: longitudinal models of configural frequency analysis.

PubMed

von Eye, Alexander; Mun, Eun Young; Bogat, G Anne

2008-03-01

This article reviews the premises of configural frequency analysis (CFA), including methods of choosing significance tests and base models, as well as protecting alpha, and discusses why CFA is a useful approach when conducting longitudinal person-oriented research. CFA operates at the manifest variable level. Longitudinal CFA seeks to identify those temporal patterns that stand out as more frequent (CFA types) or less frequent (CFA antitypes) than expected with reference to a base model. A base model that has been used frequently in CFA applications, prediction CFA, and a new base model, auto-association CFA, are discussed for analysis of cross-classifications of longitudinal data. The former base model takes the associations among predictors and among criteria into account. The latter takes the auto-associations among repeatedly observed variables into account. Application examples of each are given using data from a longitudinal study of domestic violence. It is demonstrated that CFA results are not redundant with results from log-linear modeling or multinomial regression and that, of these approaches, CFA shows particular utility when conducting person-oriented research.

Educational Subculture and Dropping out in Higher Education: A Longitudinal Case Study

ERIC Educational Resources Information Center

Venuleo, C.; Mossi, P.; Salvatore, S.

2016-01-01

The paper tests longitudinally the hypothesis that educational subcultures in terms of which students interpret their role and their educational setting affect the probability of dropping out of higher education. A logistic regression model was performed to predict drop out at the beginning of the second academic year for the 823 freshmen of a…

Estimating mono- and bi-phasic regression parameters using a mixture piecewise linear Bayesian hierarchical model

PubMed Central

Zhao, Rui; Catalano, Paul; DeGruttola, Victor G.; Michor, Franziska

2017-01-01

The dynamics of tumor burden, secreted proteins or other biomarkers over time, is often used to evaluate the effectiveness of therapy and to predict outcomes for patients. Many methods have been proposed to investigate longitudinal trends to better characterize patients and to understand disease progression. However, most approaches assume a homogeneous patient population and a uniform response trajectory over time and across patients. Here, we present a mixture piecewise linear Bayesian hierarchical model, which takes into account both population heterogeneity and nonlinear relationships between biomarkers and time. Simulation results show that our method was able to classify subjects according to their patterns of treatment response with greater than 80% accuracy in the three scenarios tested. We then applied our model to a large randomized controlled phase III clinical trial of multiple myeloma patients. Analysis results suggest that the longitudinal tumor burden trajectories in multiple myeloma patients are heterogeneous and nonlinear, even among patients assigned to the same treatment cohort. In addition, between cohorts, there are distinct differences in terms of the regression parameters and the distributions among categories in the mixture. Those results imply that longitudinal data from clinical trials may harbor unobserved subgroups and nonlinear relationships; accounting for both may be important for analyzing longitudinal data. PMID:28723910

Use of Longitudinal Regression in Quality Control. Research Report. ETS RR-14-31

ERIC Educational Resources Information Center

Lu, Ying; Yen, Wendy M.

2014-01-01

This article explores the use of longitudinal regression as a tool for identifying scoring inaccuracies. Student progression patterns, as evaluated through longitudinal regressions, typically are more stable from year to year than are scale score distributions and statistics, which require representative samples to conduct credibility checks.…

GWAS with longitudinal phenotypes: performance of approximate procedures

PubMed Central

Sikorska, Karolina; Montazeri, Nahid Mostafavi; Uitterlinden, André; Rivadeneira, Fernando; Eilers, Paul HC; Lesaffre, Emmanuel

2015-01-01

Analysis of genome-wide association studies with longitudinal data using standard procedures, such as linear mixed model (LMM) fitting, leads to discouragingly long computation times. There is a need to speed up the computations significantly. In our previous work (Sikorska et al: Fast linear mixed model computations for genome-wide association studies with longitudinal data. Stat Med 2012; 32.1: 165–180), we proposed the conditional two-step (CTS) approach as a fast method providing an approximation to the P-value for the longitudinal single-nucleotide polymorphism (SNP) effect. In the first step a reduced conditional LMM is fit, omitting all the SNP terms. In the second step, the estimated random slopes are regressed on SNPs. The CTS has been applied to the bone mineral density data from the Rotterdam Study and proved to work very well even in unbalanced situations. In another article (Sikorska et al: GWAS on your notebook: fast semi-parallel linear and logistic regression for genome-wide association studies. BMC Bioinformatics 2013; 14: 166), we suggested semi-parallel computations, greatly speeding up fitting many linear regressions. Combining CTS with fast linear regression reduces the computation time from several weeks to a few minutes on a single computer. Here, we explore further the properties of the CTS both analytically and by simulations. We investigate the performance of our proposal in comparison with a related but different approach, the two-step procedure. It is analytically shown that for the balanced case, under mild assumptions, the P-value provided by the CTS is the same as from the LMM. For unbalanced data and in realistic situations, simulations show that the CTS method does not inflate the type I error rate and implies only a minimal loss of power. PMID:25712081

Multilevel regression analyses to investigate the relationship between two variables over time: examining the longitudinal association between intrusion and avoidance.

PubMed

Suvak, Michael K; Walling, Sherry M; Iverson, Katherine M; Taft, Casey T; Resick, Patricia A

2009-12-01

Multilevel modeling is a powerful and flexible framework for analyzing nested data structures (e.g., repeated measures or longitudinal designs). The authors illustrate a series of multilevel regression procedures that can be used to elucidate the nature of the relationship between two variables across time. The goal is to help trauma researchers become more aware of the utility of multilevel modeling as a tool for increasing the field's understanding of posttraumatic adaptation. These procedures are demonstrated by examining the relationship between two posttraumatic symptoms, intrusion and avoidance, across five assessment points in a sample of rape and robbery survivors (n = 286). Results revealed that changes in intrusion were highly correlated with changes in avoidance over the 18-month posttrauma period.

Application of seemingly unrelated regression in medical data with intermittently observed time-dependent covariates.

PubMed

Keshavarzi, Sareh; Ayatollahi, Seyyed Mohammad Taghi; Zare, Najaf; Pakfetrat, Maryam

2012-01-01

BACKGROUND. In many studies with longitudinal data, time-dependent covariates can only be measured intermittently (not at all observation times), and this presents difficulties for standard statistical analyses. This situation is common in medical studies, and methods that deal with this challenge would be useful. METHODS. In this study, we performed the seemingly unrelated regression (SUR) based models, with respect to each observation time in longitudinal data with intermittently observed time-dependent covariates and further compared these models with mixed-effect regression models (MRMs) under three classic imputation procedures. Simulation studies were performed to compare the sample size properties of the estimated coefficients for different modeling choices. RESULTS. In general, the proposed models in the presence of intermittently observed time-dependent covariates showed a good performance. However, when we considered only the observed values of the covariate without any imputations, the resulted biases were greater. The performances of the proposed SUR-based models in comparison with MRM using classic imputation methods were nearly similar with approximately equal amounts of bias and MSE. CONCLUSION. The simulation study suggests that the SUR-based models work as efficiently as MRM in the case of intermittently observed time-dependent covariates. Thus, it can be used as an alternative to MRM.

Regression analysis of sparse asynchronous longitudinal data.

PubMed

Cao, Hongyuan; Zeng, Donglin; Fine, Jason P

2015-09-01

We consider estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent responses and covariates are observed intermittently within subjects. Unlike with synchronous data, where the response and covariates are observed at the same time point, with asynchronous data, the observation times are mismatched. Simple kernel-weighted estimating equations are proposed for generalized linear models with either time invariant or time-dependent coefficients under smoothness assumptions for the covariate processes which are similar to those for synchronous data. For models with either time invariant or time-dependent coefficients, the estimators are consistent and asymptotically normal but converge at slower rates than those achieved with synchronous data. Simulation studies evidence that the methods perform well with realistic sample sizes and may be superior to a naive application of methods for synchronous data based on an ad hoc last value carried forward approach. The practical utility of the methods is illustrated on data from a study on human immunodeficiency virus.

Using Hand Grip Force as a Correlate of Longitudinal Acceleration Comfort for Rapid Transit Trains

PubMed Central

Guo, Beiyuan; Gan, Weide; Fang, Weining

2015-01-01

Longitudinal acceleration comfort is one of the essential metrics used to evaluate the ride comfort of train. The aim of this study was to investigate the effectiveness of using hand grip force as a correlate of longitudinal acceleration comfort of rapid transit trains. In the paper, a motion simulation system was set up and a two-stage experiment was designed to investigate the role of the grip force on the longitudinal comfort of rapid transit trains. The results of the experiment show that the incremental grip force was linearly correlated with the longitudinal acceleration value, while the incremental grip force had no correlation with the direction of the longitudinal acceleration vector. The results also show that the effects of incremental grip force and acceleration duration on the longitudinal comfort of rapid transit trains were significant. Based on multiple regression analysis, a step function model was established to predict the longitudinal comfort of rapid transit trains using the incremental grip force and the acceleration duration. The feasibility and practicably of the model was verified by a field test. Furthermore, a comparative analysis shows that the motion simulation system and the grip force based model were valid to support the laboratory studies on the longitudinal comfort of rapid transit trains. PMID:26147730

Quantile regression in the presence of monotone missingness with sensitivity analysis

PubMed Central

Liu, Minzhao; Daniels, Michael J.; Perri, Michael G.

2016-01-01

In this paper, we develop methods for longitudinal quantile regression when there is monotone missingness. In particular, we propose pattern mixture models with a constraint that provides a straightforward interpretation of the marginal quantile regression parameters. Our approach allows sensitivity analysis which is an essential component in inference for incomplete data. To facilitate computation of the likelihood, we propose a novel way to obtain analytic forms for the required integrals. We conduct simulations to examine the robustness of our approach to modeling assumptions and compare its performance to competing approaches. The model is applied to data from a recent clinical trial on weight management. PMID:26041008

Changes in aerobic power of women, ages 20-64 yr

NASA Technical Reports Server (NTRS)

Jackson, A. S.; Wier, L. T.; Ayers, G. W.; Beard, E. F.; Stuteville, J. E.; Blair, S. N.

1996-01-01

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak) of women. The cross-sectional sample consisted of 409 healthy women, ages 20-64 yr. The 43 women of the longitudinal sample were from the same population and examined twice, the mean time between tests was 3.7 (+/-2.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill test. The zero-order correlation of -0.742 between VO2peak and %fat was significantly (P < 0.05) higher then the SR-PA (r = 0.626) and age correlations (r = -0.633). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.537 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.851) showed that adding %fat and SR-PA and their interaction to the regression model reduced the age regression weight of -0.537, to -0.265 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results. These findings are consistent with men's data from the same lab showing that about 50% of the cross-sectional age-related decline in VO2peak was due to %fat and SR-PA.

Can longitudinal generalized estimating equation models distinguish network influence and homophily? An agent-based modeling approach to measurement characteristics.

PubMed

Sauser Zachrison, Kori; Iwashyna, Theodore J; Gebremariam, Achamyeleh; Hutchins, Meghan; Lee, Joyce M

2016-12-28

Connected individuals (or nodes) in a network are more likely to be similar than two randomly selected nodes due to homophily and/or network influence. Distinguishing between these two influences is an important goal in network analysis, and generalized estimating equation (GEE) analyses of longitudinal dyadic network data are an attractive approach. It is not known to what extent such regressions can accurately extract underlying data generating processes. Therefore our primary objective is to determine to what extent, and under what conditions, does the GEE-approach recreate the actual dynamics in an agent-based model. We generated simulated cohorts with pre-specified network characteristics and attachments in both static and dynamic networks, and we varied the presence of homophily and network influence. We then used statistical regression and examined the GEE model performance in each cohort to determine whether the model was able to detect the presence of homophily and network influence. In cohorts with both static and dynamic networks, we find that the GEE models have excellent sensitivity and reasonable specificity for determining the presence or absence of network influence, but little ability to distinguish whether or not homophily is present. The GEE models are a valuable tool to examine for the presence of network influence in longitudinal data, but are quite limited with respect to homophily.

Working covariance model selection for generalized estimating equations.

PubMed

Carey, Vincent J; Wang, You-Gan

2011-11-20

We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice. Copyright © 2011 John Wiley & Sons, Ltd.

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

Controlled pattern imputation for sensitivity analysis of longitudinal binary and ordinal outcomes with nonignorable dropout.

PubMed

Tang, Yongqiang

2018-04-30

The controlled imputation method refers to a class of pattern mixture models that have been commonly used as sensitivity analyses of longitudinal clinical trials with nonignorable dropout in recent years. These pattern mixture models assume that participants in the experimental arm after dropout have similar response profiles to the control participants or have worse outcomes than otherwise similar participants who remain on the experimental treatment. In spite of its popularity, the controlled imputation has not been formally developed for longitudinal binary and ordinal outcomes partially due to the lack of a natural multivariate distribution for such endpoints. In this paper, we propose 2 approaches for implementing the controlled imputation for binary and ordinal data based respectively on the sequential logistic regression and the multivariate probit model. Efficient Markov chain Monte Carlo algorithms are developed for missing data imputation by using the monotone data augmentation technique for the sequential logistic regression and a parameter-expanded monotone data augmentation scheme for the multivariate probit model. We assess the performance of the proposed procedures by simulation and the analysis of a schizophrenia clinical trial and compare them with the fully conditional specification, last observation carried forward, and baseline observation carried forward imputation methods. Copyright © 2018 John Wiley & Sons, Ltd.

Model selection for semiparametric marginal mean regression accounting for within-cluster subsampling variability and informative cluster size.

PubMed

Shen, Chung-Wei; Chen, Yi-Hau

2018-03-13

We propose a model selection criterion for semiparametric marginal mean regression based on generalized estimating equations. The work is motivated by a longitudinal study on the physical frailty outcome in the elderly, where the cluster size, that is, the number of the observed outcomes in each subject, is "informative" in the sense that it is related to the frailty outcome itself. The new proposal, called Resampling Cluster Information Criterion (RCIC), is based on the resampling idea utilized in the within-cluster resampling method (Hoffman, Sen, and Weinberg, 2001, Biometrika 88, 1121-1134) and accommodates informative cluster size. The implementation of RCIC, however, is free of performing actual resampling of the data and hence is computationally convenient. Compared with the existing model selection methods for marginal mean regression, the RCIC method incorporates an additional component accounting for variability of the model over within-cluster subsampling, and leads to remarkable improvements in selecting the correct model, regardless of whether the cluster size is informative or not. Applying the RCIC method to the longitudinal frailty study, we identify being female, old age, low income and life satisfaction, and chronic health conditions as significant risk factors for physical frailty in the elderly. © 2018, The International Biometric Society.

Deadlines at work and sleep quality. Cross-sectional and longitudinal findings among Danish knowledge workers.

PubMed

Rugulies, Reiner; Martin, Marie H T; Garde, Anne Helene; Persson, Roger; Albertsen, Karen

2012-03-01

Exposure to deadlines at work is increasing in several countries and may affect health. We aimed to investigate cross-sectional and longitudinal associations between frequency of difficult deadlines at work and sleep quality. Study participants were knowledge workers, drawn from a representative sample of Danish employees who responded to a baseline questionnaire in 2006 (n = 363) and a follow-up questionnaire in 2007 (n = 302). Frequency of difficult deadlines was measured by self-report and categorized into low, intermediate, and high. Sleep quality was measured with a Total Sleep Quality Score and two indexes (Awakening Index and Disturbed Sleep Index) derived from the Karolinska Sleep Questionnaire. Analyses on the association between frequency of deadlines and sleep quality scores were conducted with multiple linear regression models, adjusted for potential confounders. In addition, we used multiple logistic regression models to analyze whether frequency of deadlines at baseline predicted caseness of sleep problems at follow-up among participants free of sleep problems at baseline. Frequent deadlines were cross-sectionally and longitudinally associated with poorer sleep quality on all three sleep quality measures. Associations in the longitudinal analyses were greatly attenuated when we adjusted for baseline sleep quality. The logistic regression analyses showed that frequent deadlines at baseline were associated with elevated odds ratios for caseness of sleep problems at follow-up, however, confidence intervals were wide in these analyses. Frequent deadlines at work were associated with poorer sleep quality among Danish knowledge workers. We recommend investigating the relation between deadlines and health endpoints in large-scale epidemiologic studies. Copyright © 2011 Wiley Periodicals, Inc.

Conditional Monte Carlo randomization tests for regression models.

PubMed

Parhat, Parwen; Rosenberger, William F; Diao, Guoqing

2014-08-15

We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.

Longitudinal Monitoring of Antibody Responses against Tumor Cells Using Magneto-nanosensors with a Nanoliter of Blood.

PubMed

Lee, Jung-Rok; Chan, Carmel T; Ruderman, Daniel; Chuang, Hui-Yen; Gaster, Richard S; Atallah, Michelle; Mallick, Parag; Lowe, Scott W; Gambhir, Sanjiv S; Wang, Shan X

2017-11-08

Each immunoglobulin isotype has unique immune effector functions. The contribution of these functions in the elimination of pathogens and tumors can be determined by monitoring quantitative temporal changes in isotype levels. Here, we developed a novel technique using magneto-nanosensors based on the effect of giant magnetoresistance (GMR) for longitudinal monitoring of total and antigen-specific isotype levels with high precision, using as little as 1 nL of serum. Combining in vitro serologic measurements with in vivo imaging techniques, we investigated the role of the antibody response in the regression of firefly luciferase (FL)-labeled lymphoma cells in spleen, kidney, and lymph nodes in a syngeneic Burkitt's lymphoma mouse model. Regression status was determined by whole body bioluminescent imaging (BLI). The magneto-nanosensors revealed that anti-FL IgG2a and total IgG2a were elevated and sustained in regression mice compared to non-regression mice (p < 0.05). This platform shows promise for monitoring immunotherapy, vaccination, and autoimmunity.

Statistical-learning strategies generate only modestly performing predictive models for urinary symptoms following external beam radiotherapy of the prostate: A comparison of conventional and machine-learning methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yahya, Noorazrul, E-mail: noorazrul.yahya@research.uwa.edu.au; Ebert, Martin A.; Bulsara, Max

Purpose: Given the paucity of available data concerning radiotherapy-induced urinary toxicity, it is important to ensure derivation of the most robust models with superior predictive performance. This work explores multiple statistical-learning strategies for prediction of urinary symptoms following external beam radiotherapy of the prostate. Methods: The performance of logistic regression, elastic-net, support-vector machine, random forest, neural network, and multivariate adaptive regression splines (MARS) to predict urinary symptoms was analyzed using data from 754 participants accrued by TROG03.04-RADAR. Predictive features included dose-surface data, comorbidities, and medication-intake. Four symptoms were analyzed: dysuria, haematuria, incontinence, and frequency, each with three definitions (grade ≥more » 1, grade ≥ 2 and longitudinal) with event rate between 2.3% and 76.1%. Repeated cross-validations producing matched models were implemented. A synthetic minority oversampling technique was utilized in endpoints with rare events. Parameter optimization was performed on the training data. Area under the receiver operating characteristic curve (AUROC) was used to compare performance using sample size to detect differences of ≥0.05 at the 95% confidence level. Results: Logistic regression, elastic-net, random forest, MARS, and support-vector machine were the highest-performing statistical-learning strategies in 3, 3, 3, 2, and 1 endpoints, respectively. Logistic regression, MARS, elastic-net, random forest, neural network, and support-vector machine were the best, or were not significantly worse than the best, in 7, 7, 5, 5, 3, and 1 endpoints. The best-performing statistical model was for dysuria grade ≥ 1 with AUROC ± standard deviation of 0.649 ± 0.074 using MARS. For longitudinal frequency and dysuria grade ≥ 1, all strategies produced AUROC>0.6 while all haematuria endpoints and longitudinal incontinence models produced AUROC<0.6. Conclusions: Logistic regression and MARS were most likely to be the best-performing strategy for the prediction of urinary symptoms with elastic-net and random forest producing competitive results. The predictive power of the models was modest and endpoint-dependent. New features, including spatial dose maps, may be necessary to achieve better models.« less

Walkability and cardiometabolic risk factors: Cross-sectional and longitudinal associations from the Multi-Ethnic Study of Atherosclerosis.

PubMed

Braun, Lindsay M; Rodríguez, Daniel A; Evenson, Kelly R; Hirsch, Jana A; Moore, Kari A; Diez Roux, Ana V

2016-05-01

We used data from 3227 older adults in the Multi-Ethnic Study of Atherosclerosis (2004-2012) to explore cross-sectional and longitudinal associations between walkability and cardiometabolic risk factors. In cross-sectional analyses, linear regression was used to estimate associations of Street Smart Walk Score® with glucose, triglycerides, HDL and LDL cholesterol, systolic and diastolic blood pressure, and waist circumference, while logistic regression was used to estimate associations with odds of metabolic syndrome. Econometric fixed effects models were used to estimate longitudinal associations of changes in walkability with changes in each risk factor among participants who moved residential locations between 2004 and 2012 (n=583). Most cross-sectional and longitudinal associations were small and statistically non-significant. We found limited evidence that higher walkability was cross-sectionally associated with lower blood pressure but that increases in walkability were associated with increases in triglycerides and blood pressure over time. Further research over longer time periods is needed to understand the potential for built environment interventions to improve cardiometabolic health. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genetic structured antedependence and random regression models applied to the longitudinal feed conversion ratio in growing Large White pigs.

PubMed

Huynh-Tran, V H; Gilbert, H; David, I

2017-11-01

The objective of the present study was to compare a random regression model, usually used in genetic analyses of longitudinal data, with the structured antedependence (SAD) model to study the longitudinal feed conversion ratio (FCR) in growing Large White pigs and to propose criteria for animal selection when used for genetic evaluation. The study was based on data from 11,790 weekly FCR measures collected on 1,186 Large White male growing pigs. Random regression (RR) using orthogonal polynomial Legendre and SAD models was used to estimate genetic parameters and predict FCR-based EBV for each of the 10 wk of the test. The results demonstrated that the best SAD model (1 order of antedependence of degree 2 and a polynomial of degree 2 for the innovation variance for the genetic and permanent environmental effects, i.e., 12 parameters) provided a better fit for the data than RR with a quadratic function for the genetic and permanent environmental effects (13 parameters), with Bayesian information criteria values of -10,060 and -9,838, respectively. Heritabilities with the SAD model were higher than those of RR over the first 7 wk of the test. Genetic correlations between weeks were higher than 0.68 for short intervals between weeks and decreased to 0.08 for the SAD model and -0.39 for RR for the longest intervals. These differences in genetic parameters showed that, contrary to the RR approach, the SAD model does not suffer from border effect problems and can handle genetic correlations that tend to 0. Summarized breeding values were proposed for each approach as linear combinations of the individual weekly EBV weighted by the coefficients of the first or second eigenvector computed from the genetic covariance matrix of the additive genetic effects. These summarized breeding values isolated EBV trajectories over time, capturing either the average general value or the slope of the trajectory. Finally, applying the SAD model over a reduced period of time suggested that similar selection choices would result from the use of the records from the first 8 wk of the test. To conclude, the SAD model performed well for the genetic evaluation of longitudinal phenotypes.

Specifying the Role of Exposure to Violence and Violent Behavior on Initiation of Gun Carrying: A Longitudinal Test of Three Models of Youth Gun Carrying

ERIC Educational Resources Information Center

Spano, Richard; Pridemore, William Alex; Bolland, John

2012-01-01

Two waves of longitudinal data from 1,049 African American youth living in extreme poverty are used to examine the impact of exposure to violence (Time 1) and violent behavior (Time 1) on first time gun carrying (Time 2). Multivariate logistic regression results indicate that (a) violent behavior (Time 1) increased the likelihood of initiation of…

Detecting a Change in School Performance: A Bayesian Analysis for a Multilevel Join Point Problem. CSE Technical Report 542.

ERIC Educational Resources Information Center

Thum, Yeow Meng; Bhattacharya, Suman Kumar

To better describe individual behavior within a system, this paper uses a sample of longitudinal test scores from a large urban school system to consider hierarchical Bayes estimation of a multilevel linear regression model in which each individual regression slope of test score on time switches at some unknown point in time, "kj."…

A tutorial on count regression and zero-altered count models for longitudinal substance use data

PubMed Central

Atkins, David C.; Baldwin, Scott A.; Zheng, Cheng; Gallop, Robert J.; Neighbors, Clayton

2012-01-01

Critical research questions in the study of addictive behaviors concern how these behaviors change over time - either as the result of intervention or in naturalistic settings. The combination of count outcomes that are often strongly skewed with many zeroes (e.g., days using, number of total drinks, number of drinking consequences) with repeated assessments (e.g., longitudinal follow-up after intervention or daily diary data) present challenges for data analyses. The current article provides a tutorial on methods for analyzing longitudinal substance use data, focusing on Poisson, zero-inflated, and hurdle mixed models, which are types of hierarchical or multilevel models. Two example datasets are used throughout, focusing on drinking-related consequences following an intervention and daily drinking over the past 30 days, respectively. Both datasets as well as R, SAS, Mplus, Stata, and SPSS code showing how to fit the models are available on a supplemental website. PMID:22905895

Sieve estimation in semiparametric modeling of longitudinal data with informative observation times.

PubMed

Zhao, Xingqiu; Deng, Shirong; Liu, Li; Liu, Lei

2014-01-01

Analyzing irregularly spaced longitudinal data often involves modeling possibly correlated response and observation processes. In this article, we propose a new class of semiparametric mean models that allows for the interaction between the observation history and covariates, leaving patterns of the observation process to be arbitrary. For inference on the regression parameters and the baseline mean function, a spline-based least squares estimation approach is proposed. The consistency, rate of convergence, and asymptotic normality of the proposed estimators are established. Our new approach is different from the usual approaches relying on the model specification of the observation scheme, and it can be easily used for predicting the longitudinal response. Simulation studies demonstrate that the proposed inference procedure performs well and is more robust. The analyses of bladder tumor data and medical cost data are presented to illustrate the proposed method.

Marginal regression models for clustered count data based on zero-inflated Conway-Maxwell-Poisson distribution with applications.

PubMed

Choo-Wosoba, Hyoyoung; Levy, Steven M; Datta, Somnath

2016-06-01

Community water fluoridation is an important public health measure to prevent dental caries, but it continues to be somewhat controversial. The Iowa Fluoride Study (IFS) is a longitudinal study on a cohort of Iowa children that began in 1991. The main purposes of this study (http://www.dentistry.uiowa.edu/preventive-fluoride-study) were to quantify fluoride exposures from both dietary and nondietary sources and to associate longitudinal fluoride exposures with dental fluorosis (spots on teeth) and dental caries (cavities). We analyze a subset of the IFS data by a marginal regression model with a zero-inflated version of the Conway-Maxwell-Poisson distribution for count data exhibiting excessive zeros and a wide range of dispersion patterns. In general, we introduce two estimation methods for fitting a ZICMP marginal regression model. Finite sample behaviors of the estimators and the resulting confidence intervals are studied using extensive simulation studies. We apply our methodologies to the dental caries data. Our novel modeling incorporating zero inflation, clustering, and overdispersion sheds some new light on the effect of community water fluoridation and other factors. We also include a second application of our methodology to a genomic (next-generation sequencing) dataset that exhibits underdispersion. © 2015, The International Biometric Society.

Desistance from intimate partner violence: the role of legal cynicism, collective efficacy, and social disorganization in Chicago neighborhoods.

PubMed

Emery, Clifton R; Jolley, Jennifer M; Wu, Shali

2011-12-01

This paper examined the relationship between reported Intimate Partner Violence (IPV) desistance and neighborhood concentrated disadvantage, ethnic heterogeneity, residential instability, collective efficacy and legal cynicism. Data from the Project on Human Development in Chicago Neighborhoods (PHDCN) Longitudinal survey were used to identify 599 cases of IPV in Wave 1 eligible for reported desistance in Wave 2. A Generalized Boosting Model was used to determine the best proximal predictors of IPV desistance from the longitudinal data. Controlling for these predictors, logistic regression of neighborhood characteristics from the PHDCN community survey was used to predict reported IPV desistance in Wave 2. The paper finds that participants living in neighborhoods high in legal cynicism have lower odds of reporting IPV desistance, controlling for other variables in the logistic regression model. Analyses did not find that IPV desistance was related to neighborhood concentrated disadvantage, ethnic heterogeneity, residential instability and collective efficacy.

Regression analysis of sparse asynchronous longitudinal data

PubMed Central

Cao, Hongyuan; Zeng, Donglin; Fine, Jason P.

2015-01-01

Summary We consider estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent responses and covariates are observed intermittently within subjects. Unlike with synchronous data, where the response and covariates are observed at the same time point, with asynchronous data, the observation times are mismatched. Simple kernel-weighted estimating equations are proposed for generalized linear models with either time invariant or time-dependent coefficients under smoothness assumptions for the covariate processes which are similar to those for synchronous data. For models with either time invariant or time-dependent coefficients, the estimators are consistent and asymptotically normal but converge at slower rates than those achieved with synchronous data. Simulation studies evidence that the methods perform well with realistic sample sizes and may be superior to a naive application of methods for synchronous data based on an ad hoc last value carried forward approach. The practical utility of the methods is illustrated on data from a study on human immunodeficiency virus. PMID:26568699

The PX-EM algorithm for fast stable fitting of Henderson's mixed model

PubMed Central

Foulley, Jean-Louis; Van Dyk, David A

2000-01-01

This paper presents procedures for implementing the PX-EM algorithm of Liu, Rubin and Wu to compute REML estimates of variance covariance components in Henderson's linear mixed models. The class of models considered encompasses several correlated random factors having the same vector length e.g., as in random regression models for longitudinal data analysis and in sire-maternal grandsire models for genetic evaluation. Numerical examples are presented to illustrate the procedures. Much better results in terms of convergence characteristics (number of iterations and time required for convergence) are obtained for PX-EM relative to the basic EM algorithm in the random regression. PMID:14736399

Latent Transition Analysis of Pre-Service Teachers' Efficacy in Mathematics and Science

ERIC Educational Resources Information Center

Ward, Elizabeth Kennedy

2009-01-01

This study modeled changes in pre-service teacher efficacy in mathematics and science over the course of the final year of teacher preparation using latent transition analysis (LTA), a longitudinal form of analysis that builds on two modeling traditions (latent class analysis (LCA) and auto-regressive modeling). Data were collected using the…

Sickness absence and psychosocial job quality: an analysis from a longitudinal survey of working Australians, 2005-2012.

PubMed

Milner, Allison; Butterworth, Peter; Bentley, Rebecca; Kavanagh, Anne M; LaMontagne, Anthony D

2015-05-15

Sickness absence is associated with adverse health, organizational, and societal outcomes. Using data from a longitudinal cohort study of working Australians (the Household, Income and Labour Dynamics in Australia (HILDA) Survey), we examined the relationship between changes in individuals' overall psychosocial job quality and variation in sickness absence. The outcome variables were paid sickness absence (yes/no) and number of days of paid sickness absence in the past year (2005-2012). The main exposure variable was psychosocial job quality, measured using a psychosocial job quality index (levels of job control, demands and complexity, insecurity, and perceptions of unfair pay). Analysis was conducted using longitudinal fixed-effects logistic regression models and negative binomial regression models. There was a dose-response relationship between the number of psychosocial job stressors reported by an individual and the odds of paid sickness absence (1 adversity: odds ratio (OR) = 1.26, 95% confidence interval (CI): 1.09, 1.45 (P = 0.002); 2 adversities: OR = 1.28, 95% CI: 1.09, 1.51 (P = 0.002); ≥3 adversities: OR = 1.58, 95% CI: 1.29, 1.94 (P < 0.001)). The negative binomial regression models also indicated that respondents reported a greater number of days of sickness absence in response to worsening psychosocial job quality. These results suggest that workplace interventions aiming to improve the quality of work could help reduce sickness absence. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Competing regression models for longitudinal data.

PubMed

Alencar, Airlane P; Singer, Julio M; Rocha, Francisco Marcelo M

2012-03-01

The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing this type of data via a practical example involving pretest-posttest longitudinal data. In particular, we consider log-normal linear mixed models (LNLMM), generalized linear mixed models (GLMM), and models based on generalized estimating equations (GEE). We show how some special features of the data, like a nonconstant coefficient of variation, may be handled in the three approaches and evaluate their performance with respect to the magnitude of standard errors of interpretable and comparable parameters. We also show how different diagnostic tools may be employed to identify outliers and comment on available software. We conclude by noting that the results are similar, but that GEE-based models may be preferable when the goal is to compare the marginal expected responses. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Making the Transition: An Explanatory Model of Special Education Students' Participation in Postsecondary Education.

ERIC Educational Resources Information Center

Butler-Nalin, Paul; And Others

The report of the National Longitudinal Transition Study presents initial findings on individual characteristics which relate to postsecondary education participation since 1985-86 among more than 8,000 youth (ages 13 to 23) with disabilities. A series of logistic regression models examines such factors as youth's background characteristics,…

The longitudinal association between social functioning and theory of mind in first-episode psychosis.

PubMed

Sullivan, Sarah; Lewis, Glyn; Mohr, Christine; Herzig, Daniela; Corcoran, Rhiannon; Drake, Richard; Evans, Jonathan

2014-01-01

There is some cross-sectional evidence that theory of mind ability is associated with social functioning in those with psychosis but the direction of this relationship is unknown. This study investigates the longitudinal association between both theory of mind and psychotic symptoms and social functioning outcome in first-episode psychosis. Fifty-four people with first-episode psychosis were followed up at 6 and 12 months. Random effects regression models were used to estimate the stability of theory of mind over time and the association between baseline theory of mind and psychotic symptoms and social functioning outcome. Neither baseline theory of mind ability (regression coefficients: Hinting test 1.07 95% CI -0.74, 2.88; Visual Cartoon test -2.91 95% CI -7.32, 1.51) nor baseline symptoms (regression coefficients: positive symptoms -0.04 95% CI -1.24, 1.16; selected negative symptoms -0.15 95% CI -2.63, 2.32) were associated with social functioning outcome. There was evidence that theory of mind ability was stable over time, (regression coefficients: Hinting test 5.92 95% CI -6.66, 8.92; Visual Cartoon test score 0.13 95% CI -0.17, 0.44). Neither baseline theory of mind ability nor psychotic symptoms are associated with social functioning outcome. Further longitudinal work is needed to understand the origin of social functioning deficits in psychosis.

Gene expression models for prediction of longitudinal dispersion coefficient in streams

NASA Astrophysics Data System (ADS)

Sattar, Ahmed M. A.; Gharabaghi, Bahram

2015-05-01

Longitudinal dispersion is the key hydrologic process that governs transport of pollutants in natural streams. It is critical for spill action centers to be able to predict the pollutant travel time and break-through curves accurately following accidental spills in urban streams. This study presents a novel gene expression model for longitudinal dispersion developed using 150 published data sets of geometric and hydraulic parameters in natural streams in the United States, Canada, Europe, and New Zealand. The training and testing of the model were accomplished using randomly-selected 67% (100 data sets) and 33% (50 data sets) of the data sets, respectively. Gene expression programming (GEP) is used to develop empirical relations between the longitudinal dispersion coefficient and various control variables, including the Froude number which reflects the effect of reach slope, aspect ratio, and the bed material roughness on the dispersion coefficient. Two GEP models have been developed, and the prediction uncertainties of the developed GEP models are quantified and compared with those of existing models, showing improved prediction accuracy in favor of GEP models. Finally, a parametric analysis is performed for further verification of the developed GEP models. The main reason for the higher accuracy of the GEP models compared to the existing regression models is that exponents of the key variables (aspect ratio and bed material roughness) are not constants but a function of the Froude number. The proposed relations are both simple and accurate and can be effectively used to predict the longitudinal dispersion coefficients in natural streams.

Doubly robust estimation of generalized partial linear models for longitudinal data with dropouts.

PubMed

Lin, Huiming; Fu, Bo; Qin, Guoyou; Zhu, Zhongyi

2017-12-01

We develop a doubly robust estimation of generalized partial linear models for longitudinal data with dropouts. Our method extends the highly efficient aggregate unbiased estimating function approach proposed in Qu et al. (2010) to a doubly robust one in the sense that under missing at random (MAR), our estimator is consistent when either the linear conditional mean condition is satisfied or a model for the dropout process is correctly specified. We begin with a generalized linear model for the marginal mean, and then move forward to a generalized partial linear model, allowing for nonparametric covariate effect by using the regression spline smoothing approximation. We establish the asymptotic theory for the proposed method and use simulation studies to compare its finite sample performance with that of Qu's method, the complete-case generalized estimating equation (GEE) and the inverse-probability weighted GEE. The proposed method is finally illustrated using data from a longitudinal cohort study. © 2017, The International Biometric Society.

Estimation of True Change with Three-Wave Data.

ERIC Educational Resources Information Center

Gupta, J. K.; And Others

1988-01-01

A multiple regression model for estimating true change of an individual by using information in addition to pretest-posttest data is described. Longitudinal panel or multi-wave data taken between the pretest and the posttest constitute the additional information. (TJH)

Bayesian shrinkage approach for a joint model of longitudinal and survival outcomes assuming different association structures.

PubMed

Andrinopoulou, Eleni-Rosalina; Rizopoulos, Dimitris

2016-11-20

The joint modeling of longitudinal and survival data has recently received much attention. Several extensions of the standard joint model that consists of one longitudinal and one survival outcome have been proposed including the use of different association structures between the longitudinal and the survival outcomes. However, in general, relatively little attention has been given to the selection of the most appropriate functional form to link the two outcomes. In common practice, it is assumed that the underlying value of the longitudinal outcome is associated with the survival outcome. However, it could be that different characteristics of the patients' longitudinal profiles influence the hazard. For example, not only the current value but also the slope or the area under the curve of the longitudinal outcome. The choice of which functional form to use is an important decision that needs to be investigated because it could influence the results. In this paper, we use a Bayesian shrinkage approach in order to determine the most appropriate functional forms. We propose a joint model that includes different association structures of different biomarkers and assume informative priors for the regression coefficients that correspond to the terms of the longitudinal process. Specifically, we assume Bayesian lasso, Bayesian ridge, Bayesian elastic net, and horseshoe. These methods are applied to a dataset consisting of patients with a chronic liver disease, where it is important to investigate which characteristics of the biomarkers have an influence on survival. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Statistical inference methods for sparse biological time series data.

PubMed

Ndukum, Juliet; Fonseca, Luís L; Santos, Helena; Voit, Eberhard O; Datta, Susmita

2011-04-25

Comparing metabolic profiles under different biological perturbations has become a powerful approach to investigating the functioning of cells. The profiles can be taken as single snapshots of a system, but more information is gained if they are measured longitudinally over time. The results are short time series consisting of relatively sparse data that cannot be analyzed effectively with standard time series techniques, such as autocorrelation and frequency domain methods. In this work, we study longitudinal time series profiles of glucose consumption in the yeast Saccharomyces cerevisiae under different temperatures and preconditioning regimens, which we obtained with methods of in vivo nuclear magnetic resonance (NMR) spectroscopy. For the statistical analysis we first fit several nonlinear mixed effect regression models to the longitudinal profiles and then used an ANOVA likelihood ratio method in order to test for significant differences between the profiles. The proposed methods are capable of distinguishing metabolic time trends resulting from different treatments and associate significance levels to these differences. Among several nonlinear mixed-effects regression models tested, a three-parameter logistic function represents the data with highest accuracy. ANOVA and likelihood ratio tests suggest that there are significant differences between the glucose consumption rate profiles for cells that had been--or had not been--preconditioned by heat during growth. Furthermore, pair-wise t-tests reveal significant differences in the longitudinal profiles for glucose consumption rates between optimal conditions and heat stress, optimal and recovery conditions, and heat stress and recovery conditions (p-values <0.0001). We have developed a nonlinear mixed effects model that is appropriate for the analysis of sparse metabolic and physiological time profiles. The model permits sound statistical inference procedures, based on ANOVA likelihood ratio tests, for testing the significance of differences between short time course data under different biological perturbations.

Quantile Regression in the Study of Developmental Sciences

PubMed Central

Petscher, Yaacov; Logan, Jessica A. R.

2014-01-01

Linear regression analysis is one of the most common techniques applied in developmental research, but only allows for an estimate of the average relations between the predictor(s) and the outcome. This study describes quantile regression, which provides estimates of the relations between the predictor(s) and outcome, but across multiple points of the outcome’s distribution. Using data from the High School and Beyond and U.S. Sustained Effects Study databases, quantile regression is demonstrated and contrasted with linear regression when considering models with: (a) one continuous predictor, (b) one dichotomous predictor, (c) a continuous and a dichotomous predictor, and (d) a longitudinal application. Results from each example exhibited the differential inferences which may be drawn using linear or quantile regression. PMID:24329596

Estimators for longitudinal latent exposure models: examining measurement model assumptions.

PubMed

Sánchez, Brisa N; Kim, Sehee; Sammel, Mary D

2017-06-15

Latent variable (LV) models are increasingly being used in environmental epidemiology as a way to summarize multiple environmental exposures and thus minimize statistical concerns that arise in multiple regression. LV models may be especially useful when multivariate exposures are collected repeatedly over time. LV models can accommodate a variety of assumptions but, at the same time, present the user with many choices for model specification particularly in the case of exposure data collected repeatedly over time. For instance, the user could assume conditional independence of observed exposure biomarkers given the latent exposure and, in the case of longitudinal latent exposure variables, time invariance of the measurement model. Choosing which assumptions to relax is not always straightforward. We were motivated by a study of prenatal lead exposure and mental development, where assumptions of the measurement model for the time-changing longitudinal exposure have appreciable impact on (maximum-likelihood) inferences about the health effects of lead exposure. Although we were not particularly interested in characterizing the change of the LV itself, imposing a longitudinal LV structure on the repeated multivariate exposure measures could result in high efficiency gains for the exposure-disease association. We examine the biases of maximum likelihood estimators when assumptions about the measurement model for the longitudinal latent exposure variable are violated. We adapt existing instrumental variable estimators to the case of longitudinal exposures and propose them as an alternative to estimate the health effects of a time-changing latent predictor. We show that instrumental variable estimators remain unbiased for a wide range of data generating models and have advantages in terms of mean squared error. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

The effect of service satisfaction and spiritual well-being on the quality of life of patients with schizophrenia.

PubMed

Lanfredi, Mariangela; Candini, Valentina; Buizza, Chiara; Ferrari, Clarissa; Boero, Maria E; Giobbio, Gian M; Goldschmidt, Nicoletta; Greppo, Stefania; Iozzino, Laura; Maggi, Paolo; Melegari, Anna; Pasqualetti, Patrizio; Rossi, Giuseppe; de Girolamo, Giovanni

2014-05-15

Quality of life (QOL) has been considered an important outcome measure in psychiatric research and determinants of QOL have been widely investigated. We aimed at detecting predictors of QOL at baseline and at testing the longitudinal interrelations of the baseline predictors with QOL scores at a 1-year follow-up in a sample of patients living in Residential Facilities (RFs). Logistic regression models were adopted to evaluate the association between WHOQoL-Bref scores and potential determinants of QOL. In addition, all variables significantly associated with QOL domains in the final logistic regression model were included by using the Structural Equation Modeling (SEM). We included 139 patients with a diagnosis of schizophrenia spectrum. In the final logistic regression model level of activity, social support, age, service satisfaction, spiritual well-being and symptoms' severity were identified as predictors of QOL scores at baseline. Longitudinal analyses carried out by SEM showed that 40% of QOL follow-up variability was explained by QOL at baseline, and significant indirect effects toward QOL at follow-up were found for satisfaction with services and for social support. Rehabilitation plans for people with schizophrenia living in RFs should also consider mediators of change in subjective QOL such as satisfaction with mental health services. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Hierarchical Bayesian Markov switching models with application to predicting spawning success of shovelnose sturgeon

USGS Publications Warehouse

Holan, S.H.; Davis, G.M.; Wildhaber, M.L.; DeLonay, A.J.; Papoulias, D.M.

2009-01-01

The timing of spawning in fish is tightly linked to environmental factors; however, these factors are not very well understood for many species. Specifically, little information is available to guide recruitment efforts for endangered species such as the sturgeon. Therefore, we propose a Bayesian hierarchical model for predicting the success of spawning of the shovelnose sturgeon which uses both biological and behavioural (longitudinal) data. In particular, we use data that were produced from a tracking study that was conducted in the Lower Missouri River. The data that were produced from this study consist of biological variables associated with readiness to spawn along with longitudinal behavioural data collected by using telemetry and archival data storage tags. These high frequency data are complex both biologically and in the underlying behavioural process. To accommodate such complexity we developed a hierarchical linear regression model that uses an eigenvalue predictor, derived from the transition probability matrix of a two-state Markov switching model with generalized auto-regressive conditional heteroscedastic dynamics. Finally, to minimize the computational burden that is associated with estimation of this model, a parallel computing approach is proposed. ?? Journal compilation 2009 Royal Statistical Society.

MODELING LEFT-TRUNCATED AND RIGHT-CENSORED SURVIVAL DATA WITH LONGITUDINAL COVARIATES

PubMed Central

Su, Yu-Ru; Wang, Jane-Ling

2018-01-01

There is a surge in medical follow-up studies that include longitudinal covariates in the modeling of survival data. So far, the focus has been largely on right censored survival data. We consider survival data that are subject to both left truncation and right censoring. Left truncation is well known to produce biased sample. The sampling bias issue has been resolved in the literature for the case which involves baseline or time-varying covariates that are observable. The problem remains open however for the important case where longitudinal covariates are present in survival models. A joint likelihood approach has been shown in the literature to provide an effective way to overcome those difficulties for right censored data, but this approach faces substantial additional challenges in the presence of left truncation. Here we thus propose an alternative likelihood to overcome these difficulties and show that the regression coefficient in the survival component can be estimated unbiasedly and efficiently. Issues about the bias for the longitudinal component are discussed. The new approach is illustrated numerically through simulations and data from a multi-center AIDS cohort study. PMID:29479122

The effects of cumulative risks and promotive factors on urban adolescent alcohol and other drug use: a longitudinal study of resiliency.

PubMed

Ostaszewski, Krzysztof; Zimmerman, Marc A

2006-12-01

Resiliency theory provides a conceptual framework for studying why some youth exposed to risk factors do not develop the negative behaviors they predict. The purpose of this study was to test compensatory and protective models of resiliency in a longitudinal sample of urban adolescents (80% African American). The data were from Years 1 (9th grade) and 4 (12th grade). The study examined effects of cumulative risk and promotive factors on adolescent polydrug use including alcohol, tobacco and marijuana. Cumulative measures of risk/promotive factors represented individual characteristics, peer influence, and parental/familial influences. After controlling for demographics, results of multiple regression of polydrug use support the compensatory model of resiliency both cross-sectionally and longitudinally. Promotive factors were also found to have compensatory effects on change in adolescent polydrug use. The protective model of resiliency evidenced cross-sectionally was not supported in longitudinal analysis. The findings support resiliency theory and the use of cumulative risk/promotive measures in resiliency research. Implications focused on utilizing multiple assets and resources in prevention programming are discussed.

Verbal Memory Declines More Rapidly with Age in HIV Infected versus Uninfected Adults

PubMed Central

Seider, Talia R.; Luo, Xi; Gongvatana, Assawin; Devlin, Kathryn N.; de la Monte, Suzanne M.; Chasman, Jesse D.; Yan, Peisi; Tashima, Karen T.; Navia, Bradford; Cohen, Ronald A.

2015-01-01

Objectives In the current era of effective antiretroviral treatment, the number of older adults living with HIV is rapidly increasing. This study investigated the combined influence of age and HIV infection on longitudinal changes in verbal and visuospatial learning and memory. Methods In this longitudinal, case-control design, 54 HIV seropositive and 30 seronegative individuals aged 40–74 received neurocognitive assessments at baseline visits and again one year later. Assessment included tests of verbal and visuospatial learning and memory. Linear regression was used to predict baseline performance and longitudinal change on each test using HIV serostatus, age, and their interaction as predictors. MANOVA was used to assess the effects of these predictors on overall baseline performance and overall longitudinal change. Results The interaction of HIV and age significantly predicted longitudinal change in verbal memory performance, as did HIV status, indicating that although the seropositive group declined more than the seronegative group overall, the rate of decline depended on age such that greater age was associated with a greater decline in this group. The regression models for visuospatial learning and memory were significant at baseline, but did not predict change over time. HIV status significantly predicted overall baseline performance and overall longitudinal change. Conclusions This is the first longitudinal study focused on the effects of age and HIV on memory. Findings suggest that age and HIV interact to produce larger declines in verbal memory over time. Further research is needed to gain a greater understanding of the effects of HIV on the aging brain. PMID:24645772

A varying-coefficient method for analyzing longitudinal clinical trials data with nonignorable dropout

PubMed Central

Forster, Jeri E.; MaWhinney, Samantha; Ball, Erika L.; Fairclough, Diane

2011-01-01

Dropout is common in longitudinal clinical trials and when the probability of dropout depends on unobserved outcomes even after conditioning on available data, it is considered missing not at random and therefore nonignorable. To address this problem, mixture models can be used to account for the relationship between a longitudinal outcome and dropout. We propose a Natural Spline Varying-coefficient mixture model (NSV), which is a straightforward extension of the parametric Conditional Linear Model (CLM). We assume that the outcome follows a varying-coefficient model conditional on a continuous dropout distribution. Natural cubic B-splines are used to allow the regression coefficients to semiparametrically depend on dropout and inference is therefore more robust. Additionally, this method is computationally stable and relatively simple to implement. We conduct simulation studies to evaluate performance and compare methodologies in settings where the longitudinal trajectories are linear and dropout time is observed for all individuals. Performance is assessed under conditions where model assumptions are both met and violated. In addition, we compare the NSV to the CLM and a standard random-effects model using an HIV/AIDS clinical trial with probable nonignorable dropout. The simulation studies suggest that the NSV is an improvement over the CLM when dropout has a nonlinear dependence on the outcome. PMID:22101223

Asymptotics of nonparametric L-1 regression models with dependent data

PubMed Central

ZHAO, ZHIBIAO; WEI, YING; LIN, DENNIS K.J.

2013-01-01

We investigate asymptotic properties of least-absolute-deviation or median quantile estimates of the location and scale functions in nonparametric regression models with dependent data from multiple subjects. Under a general dependence structure that allows for longitudinal data and some spatially correlated data, we establish uniform Bahadur representations for the proposed median quantile estimates. The obtained Bahadur representations provide deep insights into the asymptotic behavior of the estimates. Our main theoretical development is based on studying the modulus of continuity of kernel weighted empirical process through a coupling argument. Progesterone data is used for an illustration. PMID:24955016

Analysis of Longitudinal Studies With Repeated Outcome Measures: Adjusting for Time-Dependent Confounding Using Conventional Methods.

PubMed

Keogh, Ruth H; Daniel, Rhian M; VanderWeele, Tyler J; Vansteelandt, Stijn

2018-05-01

Estimation of causal effects of time-varying exposures using longitudinal data is a common problem in epidemiology. When there are time-varying confounders, which may include past outcomes, affected by prior exposure, standard regression methods can lead to bias. Methods such as inverse probability weighted estimation of marginal structural models have been developed to address this problem. However, in this paper we show how standard regression methods can be used, even in the presence of time-dependent confounding, to estimate the total effect of an exposure on a subsequent outcome by controlling appropriately for prior exposures, outcomes, and time-varying covariates. We refer to the resulting estimation approach as sequential conditional mean models (SCMMs), which can be fitted using generalized estimating equations. We outline this approach and describe how including propensity score adjustment is advantageous. We compare the causal effects being estimated using SCMMs and marginal structural models, and we compare the two approaches using simulations. SCMMs enable more precise inferences, with greater robustness against model misspecification via propensity score adjustment, and easily accommodate continuous exposures and interactions. A new test for direct effects of past exposures on a subsequent outcome is described.

Attributions and Coping Styles in Reducing Victimization

ERIC Educational Resources Information Center

Shelley, Danielle; Craig, Wendy M.

2010-01-01

To examine the role of attributions and coping on children's victimization over time, 220 children completed questionnaires twice over a 6-month period. Direct and mediational models were tested using regressions, cross-sectionally and longitudinally. Characterological self-blame was positively related to victimization within and across time for…

Use of Longitudinal Data in Genetic Studies in the Genome-wide Association Studies Era: Summary of Group 14

PubMed Central

Kerner, Berit; North, Kari E; Fallin, M Daniele

2010-01-01

Participants analyzed actual and simulated longitudinal data from the Framingham Heart Study for various metabolic and cardiovascular traits. The genetic information incorporated into these investigations ranged from selected single-nucleotide polymorphisms to genome-wide association arrays. Genotypes were incorporated using a broad range of methodological approaches including conditional logistic regression, linear mixed models, generalized estimating equations, linear growth curve estimation, growth modeling, growth mixture modeling, population attributable risk fraction based on survival functions under the proportional hazards models, and multivariate adaptive splines for the analysis of longitudinal data. The specific scientific questions addressed by these different approaches also varied, ranging from a more precise definition of the phenotype, bias reduction in control selection, estimation of effect sizes and genotype associated risk, to direct incorporation of genetic data into longitudinal modeling approaches and the exploration of population heterogeneity with regard to longitudinal trajectories. The group reached several overall conclusions: 1) The additional information provided by longitudinal data may be useful in genetic analyses. 2) The precision of the phenotype definition as well as control selection in nested designs may be improved, especially if traits demonstrate a trend over time or have strong age-of-onset effects. 3) Analyzing genetic data stratified for high-risk subgroups defined by a unique development over time could be useful for the detection of rare mutations in common multi-factorial diseases. 4) Estimation of the population impact of genomic risk variants could be more precise. The challenges and computational complexity demanded by genome-wide single-nucleotide polymorphism data were also discussed. PMID:19924713

Does Sedentary Behavior Predict Academic Performance in Adolescents or the Other Way Round? A Longitudinal Path Analysis

PubMed Central

Lizandra, Jorge; Devís-Devís, José; Pérez-Gimeno, Esther; Valencia-Peris, Alexandra; Peiró-Velert, Carmen

2016-01-01

This study examined whether adolescents’ time spent on sedentary behaviors (academic, technological-based and social-based activities) was a better predictor of academic performance than the reverse. A cohort of 755 adolescents participated in a three-year period study. Structural Equation Modeling techniques were used to test plausible causal hypotheses. Four competing models were analyzed to determine which model best fitted the data. The Best Model was separately tested by gender. The Best Model showed that academic performance was a better predictor of sedentary behaviors than the other way round. It also indicated that students who obtained excellent academic results were more likely to succeed academically three years later. Moreover, adolescents who spent more time in the three different types of sedentary behaviors were more likely to engage longer in those sedentary behaviors after the three-year period. The better the adolescents performed academically, the less time they devoted to social-based activities and more to academic activities. An inverse relationship emerged between time dedicated to technological-based activities and academic sedentary activities. A moderating auto-regressive effect by gender indicated that boys were more likely to spend more time on technological-based activities three years later than girls. To conclude, previous academic performance predicts better sedentary behaviors three years later than the reverse. The positive longitudinal auto-regressive effects on the four variables under study reinforce the ‘success breeds success’ hypothesis, with academic performance and social-based activities emerging as the strongest ones. Technological-based activities showed a moderating effect by gender and a negative longitudinal association with academic activities that supports a displacement hypothesis. Other longitudinal and covariate effects reflect the complex relationships among sedentary behaviors and academic performance and the need to explore these relationships in depth. Theoretical and practical implications for school health are outlined. PMID:27055121

Does Sedentary Behavior Predict Academic Performance in Adolescents or the Other Way Round? A Longitudinal Path Analysis.

PubMed

Lizandra, Jorge; Devís-Devís, José; Pérez-Gimeno, Esther; Valencia-Peris, Alexandra; Peiró-Velert, Carmen

2016-01-01

This study examined whether adolescents' time spent on sedentary behaviors (academic, technological-based and social-based activities) was a better predictor of academic performance than the reverse. A cohort of 755 adolescents participated in a three-year period study. Structural Equation Modeling techniques were used to test plausible causal hypotheses. Four competing models were analyzed to determine which model best fitted the data. The Best Model was separately tested by gender. The Best Model showed that academic performance was a better predictor of sedentary behaviors than the other way round. It also indicated that students who obtained excellent academic results were more likely to succeed academically three years later. Moreover, adolescents who spent more time in the three different types of sedentary behaviors were more likely to engage longer in those sedentary behaviors after the three-year period. The better the adolescents performed academically, the less time they devoted to social-based activities and more to academic activities. An inverse relationship emerged between time dedicated to technological-based activities and academic sedentary activities. A moderating auto-regressive effect by gender indicated that boys were more likely to spend more time on technological-based activities three years later than girls. To conclude, previous academic performance predicts better sedentary behaviors three years later than the reverse. The positive longitudinal auto-regressive effects on the four variables under study reinforce the 'success breeds success' hypothesis, with academic performance and social-based activities emerging as the strongest ones. Technological-based activities showed a moderating effect by gender and a negative longitudinal association with academic activities that supports a displacement hypothesis. Other longitudinal and covariate effects reflect the complex relationships among sedentary behaviors and academic performance and the need to explore these relationships in depth. Theoretical and practical implications for school health are outlined.

Serum Uric Acid Levels and Risk of Incident Hypertriglyceridemia: A Longitudinal Population-based Epidemiological Study.

PubMed

Zheng, Rongjiong; Ren, Ping; Chen, Qingmei; Yang, Tianmeng; Chen, Changxi; Mao, Yushan

2017-09-01

Hypertriglyceridemia is one of lipid metabolism abnormalities; however, it is still debatable whether serum uric acid is a cause or a consequence of hypertriglyceridemia. We performed the study to investigate the longitudinal association between serum uric acid levels and hypertriglyceridemia. The study included 4190 subjects without hypertriglyceridemia. The subjects had annual health examinations for 8 years to assess incident hyperglyceridemia, and the subjects were divided into groups based on the serum uric acid quartile. Cox regression models were used to analyze the risk factors of development hypertriglyceridemia. During follow-up, 1461 (34.9%) subjects developed hypertriglyceridemia over 8 years of follow-up. The cumulative incidence of hypertriglyceridemia was 28.2%, 29.1%, 36.9%, and 45.6% in quartile 1,2,3 and 4, respectively ( P for trend <0.001). Cox regression analyses indicated that serum uric acid levels were independently and positively associated with the risk of incident hypertriglyceridemia. Hypertriglyceridemia has become a serious public health problem. This longitudinal study demonstrates that high serum uric acid levels increase the risk of hypertriglyceridemia. © 2017 by the Association of Clinical Scientists, Inc.

Triglyceride and glucose (TyG) index as a predictor of incident hypertension: a 9-year longitudinal population-based study.

PubMed

Zheng, Rongjiong; Mao, Yushan

2017-09-13

Hypertension and the triglyceride and glucose index both have been associated with insulin resistance; however, the longitudinal association remains unclear. This study was designed to investigate the longitudinal association between the triglyceride and glucose index and incident hypertension among the Chinese population. We studied 4686 subjects (3177 males and 1509 females) and followed up for 9 years. The subjects were divided into four groups based on the triglyceride and glucose index. Univariate and multivariate Cox regression models were used to analyse the risk factors of hypertension. After 9 years of follow-up, 2047 subjects developed hypertension. The overall 9-year cumulative incidence of hypertension was 43.7%, ranging from 28.5% in quartile 1 to 36.9% in quartile 2, 49.2% in quartile 3 and 59.8% in quartile 4 (p for trend < 0.001). Cox regression analyses indicated that higher triglyceride and glucose index was associated with an increased risk of subsequent incident hypertension. The triglyceride and glucose index can predict the incident hypertension among the Chinese population.

Imaging-based biomarkers of cognitive performance in older adults constructed via high-dimensional pattern regression applied to MRI and PET.

PubMed

Wang, Ying; Goh, Joshua O; Resnick, Susan M; Davatzikos, Christos

2013-01-01

In this study, we used high-dimensional pattern regression methods based on structural (gray and white matter; GM and WM) and functional (positron emission tomography of regional cerebral blood flow; PET) brain data to identify cross-sectional imaging biomarkers of cognitive performance in cognitively normal older adults from the Baltimore Longitudinal Study of Aging (BLSA). We focused on specific components of executive and memory domains known to decline with aging, including manipulation, semantic retrieval, long-term memory (LTM), and short-term memory (STM). For each imaging modality, brain regions associated with each cognitive domain were generated by adaptive regional clustering. A relevance vector machine was adopted to model the nonlinear continuous relationship between brain regions and cognitive performance, with cross-validation to select the most informative brain regions (using recursive feature elimination) as imaging biomarkers and optimize model parameters. Predicted cognitive scores using our regression algorithm based on the resulting brain regions correlated well with actual performance. Also, regression models obtained using combined GM, WM, and PET imaging modalities outperformed models based on single modalities. Imaging biomarkers related to memory performance included the orbito-frontal and medial temporal cortical regions with LTM showing stronger correlation with the temporal lobe than STM. Brain regions predicting executive performance included orbito-frontal, and occipito-temporal areas. The PET modality had higher contribution to most cognitive domains except manipulation, which had higher WM contribution from the superior longitudinal fasciculus and the genu of the corpus callosum. These findings based on machine-learning methods demonstrate the importance of combining structural and functional imaging data in understanding complex cognitive mechanisms and also their potential usage as biomarkers that predict cognitive status.

Parenting Style and Behavior as Longitudinal Predictors of Adolescent Alcohol Use.

PubMed

Minaie, Matin Ghayour; Hui, Ka Kit; Leung, Rachel K; Toumbourou, John W; King, Ross M

2015-09-01

Adolescent alcohol use is a serious problem in Australia and other nations. Longitudinal data on family predictors are valuable to guide parental education efforts. The present study tested Baumrind's proposal that parenting styles are direct predictors of adolescent alcohol use. Latent class modeling was used to investigate adolescent perceptions of parenting styles and multivariate regression to examine their predictive effect on the development of adolescent alcohol use. The data set comprised 2,081 secondary school students (55.9% female) from metropolitan Melbourne, Australia, who completed three waves of annual longitudinal data starting in 2004. Baumrind's parenting styles were significant predictors in unadjusted analyses, but these effects were not maintained in multivariate models that also included parenting behavior dimensions. Family influences on the development of adolescent alcohol use appear to operate more directly through specific family management behaviors rather than through more global parenting styles.

Understanding Graduate School Aspirations: The Effect of Good Teaching Practices

ERIC Educational Resources Information Center

Hanson, Jana Marie

2013-01-01

This study examined the effects of good teaching practices on post-baccalaureate degree aspirations using logistic regression techniques on a multi-institutional, longitudinal sample of students at four-year colleges and universities. Using College Choice and College Outcomes models as a theoretical foundation, I examined whether eight good…

Attrition in Psychotherapy: A Survival Analysis

ERIC Educational Resources Information Center

Roseborough, David John; McLeod, Jeffrey T.; Wright, Florence I.

2016-01-01

Purpose: Attrition is a common problem in psychotherapy and can be defined as clients ending treatment before achieving an optimal response. Method: This longitudinal, archival study utilized data for 3,728 clients, using the Outcome Questionnaire 45.2. A Cox regression proportional hazards (hazard ratios) model was used in order to better…

Stressed and Losing Sleep: Sleep Duration and Perceived Stress among Affluent Adolescent Females

ERIC Educational Resources Information Center

DeSilva Mousseau, Angela M.; Lund, Terese J.; Liang, Belle; Spencer, Renée; Walsh, Jill

2016-01-01

This study examined the relationship between stress and sleep duration for adolescent females from affluent backgrounds. Participants were 218 students attending two independent single-sex secondary schools. Ordinary Least Squares (OLS) regression models (cross-sectional and longitudinal) were run to examine the association between stress and…

Gender differences in body consciousness and substance use among high-risk adolescents.

PubMed

Black, David Scott; Sussman, Steve; Unger, Jennifer; Pokhrel, Pallav; Sun, Ping

2010-08-01

This study explores the association between private and public body consciousness and past 30-day cigarette, alcohol, marijuana, and hard drug use among adolescents. Self-reported data from alterative high school students in California were analyzed (N = 976) using multilevel regression models to account for student clustering within schools. Separate regression analyses were conducted for males and females. Both cross-sectional baseline data and one-year longitudinal prediction models indicated that body consciousness is associated with specific drug use categories differentially by gender. Findings suggest that body consciousness accounts for additional variance in substance use etiology not explained by previously recognized dispositional variables.

Ethnicity and acculturation: do they predict weight status in a longitudinal study among Asian, Hispanic, and non-Hispanic White early adolescent females?

PubMed Central

Fialkowski, Marie K; Ettienne, Reynolette; Shvetsov, Yurii B; Rivera, Rebecca L; Van Loan, Marta D; Savaiano, Dennis A; Boushey, Carol J

2015-01-01

Background The prevalence of overweight and obesity among adolescents has increased over the past decade. Prevalence rates are disparate among certain racial and ethnic groups. This study sought to longitudinally examine the relationship between overweight status (≥85th percentile according to the Centers for Disease Control and Prevention growth charts) and ethnic group, as well as acculturation (generation and language spoken in the home) in a sample of adolescent females. Methods Asian (n=160), Hispanic (n=217), and non-Hispanic White (n=304) early adolescent girls participating in the multistate calcium intervention study with complete information on weight, ethnicity, and acculturation were included. Multiple methods of assessing longitudinal relationships (binary logistic regression model, linear regression model, Cox proportional-hazards regression analysis, and Kaplan–Meier survival analysis) were used to examine the relationship. Results The total proportion of girls overweight at baseline was 36%. When examining by ethnic group, the proportion varied with Hispanic girls having the highest percentage (46%) in comparison to their Asian (23%) and Non-Hispanic White (35%) counterparts. Although the total proportion of overweight was 36% at 18 months, the variation across the ethnic groups remained with the proportion of Hispanic girls becoming overweight (55%) being greater than their Asian (18%) and non-Hispanic White (34%) counterparts. However, regardless of the statistical approach used, there were no significant associations between overweight status and acculturation over time. Conclusion These unexpected results warrant further exploration into factors associated with overweight, especially among Hispanic girls, and further investigation of acculturation’s role is warranted. Identifying these risk factors will be important for developing targeted obesity prevention initiatives. PMID:25624775

School Readiness as a Longitudinal Predictor of Social-Emotional and Reading Performance across the Elementary Grades

ERIC Educational Resources Information Center

Quirk, Matthew; Dowdy, Erin; Goldstein, Ariel; Carnazzo, Katherine

2017-01-01

This study is a brief psychometric report examining the Kindergarten Student Entrance Profile (KSEP). Multiple regression models were tested examining associations between kindergarten teachers' ratings of children's social-emotional and cognitive readiness during the first month of kindergarten with academic and social-emotional outcomes almost 6…

Factors Contributing to the Upward Transfer of Baccalaureate Aspirants Beginning at Community Colleges. WISCAPE Working Paper

ERIC Educational Resources Information Center

Wang, Xueli

2010-01-01

Incorporating the psychological perspective, this study examines factors associated with the upward transfer of baccalaureate aspirants beginning at community colleges. Based on data from the National Education Longitudinal Study of 1988 and the Postsecondary Education Transcript Study, the study tests a logistic regression model to predict…

Academic Performance of Community College Transfers: Psychological, Sociodemographic, and Educational Correlates

ERIC Educational Resources Information Center

Wang, Xueli

2012-01-01

This study focuses on the academic performance of community college transfer students at four-year institutions. It uses a nationally representative sample from the National Education Longitudinal Study of 1988 (NELS: 88/2000) and the Postsecondary Education Transcript Study (PETS). Results from an Ordinary Least Squares regression model suggest…

Compulsive Internet use: the role of online gaming and other internet applications.

PubMed

van Rooij, Antonius J; Schoenmakers, Tim M; van de Eijnden, Regina J J M; van de Mheen, Dike

2010-07-01

Increasing research on Internet addiction makes it necessary to distinguish between the medium of Internet and its specific applications. This study explores the relationship between time spent on various Internet applications (including online gaming) and Compulsive Internet Use in a large sample of adolescents. The 2007 (N=4,920) and 2008 (N=4,753) samples of a longitudinal survey study among adolescents were used, as well as the 2007-2008 cohort subsample (N=1421). Compulsive Internet Use was predicted from the time spent on the various Internet applications in two cross-sectional multiple linear regression models and one longitudinal regression model in which changes in behavior were related to changes in Compulsive Internet Use. In both samples, downloading, social networking, MSN use, Habbo Hotel, chatting, blogging, online games, and casual games were shown to be associated with Compulsive Internet Use. Off these, online gaming was shown to have the strongest association with Compulsive Internet Use. Moreover, changes in online gaming were most strongly associated with changes in Compulsive Internet Use over time for the longitudinal cohort. A clear relationship was shown between online gaming and Compulsive Internet Use. It is further argued that a subgroup of compulsive Internet users should be classified as compulsive online gamers. Copyright (c) 2010 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Motivational and behavioural models of change: A longitudinal analysis of change among men with chronic haemophilia-related joint pain.

PubMed

Elander, J; Richardson, C; Morris, J; Robinson, G; Schofield, M B

2017-09-01

Motivational and behavioural models of adjustment to chronic pain make different predictions about change processes, which can be tested in longitudinal analyses. We examined changes in motivation, coping and acceptance among 78 men with chronic haemophilia-related joint pain. Using cross-lagged regression analyses of changes from baseline to 6 months as predictors of changes from 6 to 12 months, with supplementary structural equation modelling, we tested two models in which motivational changes influence behavioural changes, and one in which behavioural changes influence motivational changes. Changes in motivation to self-manage pain influenced later changes in pain coping, consistent with the motivational model of pain self-management, and also influenced later changes in activity engagement, the behavioural component of pain acceptance. Changes in activity engagement influenced later changes in pain willingness, consistent with the behavioural model of pain acceptance. Based on the findings, a combined model of changes in pain self-management and acceptance is proposed, which could guide combined interventions based on theories of motivation, coping and acceptance in chronic pain. This study adds longitudinal evidence about sequential change processes; a test of the motivational model of pain self-management; and tests of behavioural versus motivational models of pain acceptance. © 2017 European Pain Federation - EFIC®.

The development of video game enjoyment in a role playing game.

PubMed

Wirth, Werner; Ryffel, Fabian; von Pape, Thilo; Karnowski, Veronika

2013-04-01

This study examines the development of video game enjoyment over time. The results of a longitudinal study (N=62) show that enjoyment increases over several sessions. Moreover, results of a multilevel regression model indicate a causal link between the dependent variable video game enjoyment and the predictor variables exploratory behavior, spatial presence, competence, suspense and solution, and simulated experiences of life. These findings are important for video game research because they reveal the antecedents of video game enjoyment in a real-world longitudinal setting. Results are discussed in terms of the dynamics of video game enjoyment under real-world conditions.

Numerical investigations of hybrid rocket engines

NASA Astrophysics Data System (ADS)

Betelin, V. B.; Kushnirenko, A. G.; Smirnov, N. N.; Nikitin, V. F.; Tyurenkova, V. V.; Stamov, L. I.

2018-03-01

Paper presents the results of numerical studies of hybrid rocket engines operating cycle including unsteady-state transition stage. A mathematical model is developed accounting for the peculiarities of diffusion combustion of fuel in the flow of oxidant, which is composed of oxygen-nitrogen mixture. Three dimensional unsteady-state simulations of chemically reacting gas mixture above thermochemically destructing surface are performed. The results show that the diffusion combustion brings to strongly non-uniform fuel mass regression rate in the flow direction. Diffusive deceleration of chemical reaction brings to the decrease of fuel regression rate in the longitudinal direction.

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer’s Disease

PubMed Central

Jie, Biao; Liu, Mingxia; Liu, Jun

2016-01-01

Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer’s disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). However, most existing sparse learning-based studies only adopt cross-sectional analysis methods, where the sparse model is learned using data from a single time-point. Actually, multiple time-points of data are often available in brain imaging applications, which can be used in some longitudinal analysis methods to better uncover the disease progression patterns. Accordingly, in this paper we propose a novel temporally-constrained group sparse learning method aiming for longitudinal analysis with multiple time-points of data. Specifically, we learn a sparse linear regression model by using the imaging data from multiple time-points, where a group regularization term is first employed to group the weights for the same brain region across different time-points together. Furthermore, to reflect the smooth changes between data derived from adjacent time-points, we incorporate two smoothness regularization terms into the objective function, i.e., one fused smoothness term which requires that the differences between two successive weight vectors from adjacent time-points should be small, and another output smoothness term which requires the differences between outputs of two successive models from adjacent time-points should also be small. We develop an efficient optimization algorithm to solve the proposed objective function. Experimental results on ADNI database demonstrate that, compared with conventional sparse learning-based methods, our proposed method can achieve improved regression performance and also help in discovering disease-related biomarkers. PMID:27093313

Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data

PubMed Central

Müller, Christian; Schillert, Arne; Röthemeier, Caroline; Trégouët, David-Alexandre; Proust, Carole; Binder, Harald; Pfeiffer, Norbert; Beutel, Manfred; Lackner, Karl J.; Schnabel, Renate B.; Tiret, Laurence; Wild, Philipp S.; Blankenberg, Stefan

2016-01-01

Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data. PMID:27272489

Developmental Differences in Parenting Behavior: Comparing Adolescent, Emerging Adult, and Adult Mothers

ERIC Educational Resources Information Center

Lewin, Amy; Mitchell, Stephanie J.; Ronzio, Cynthia R.

2013-01-01

The nationally representative Early Childhood Longitudinal Study-Birth cohort data set was used to compare parenting behaviors of adolescent mothers (less than 19 years old), emerging adult mothers (19-25 years old), and adult mothers (greater than 25 years old) when their children were 2 years old. Regression models controlling for socioeconomic…

Persistent Nonmedical Use of Prescription Stimulants among College Students: Possible Association with ADHD Symptoms

ERIC Educational Resources Information Center

Arria, Amelia M.; Garnier-Dykstra, Laura M.; Caldeira, Kimberly M.; Vincent, Kathryn B.; O'Grady, Kevin E.; Wish, Eric D.

2011-01-01

Objective: To investigate the possible association between untreated ADHD symptoms (as measured by the Adult ADHD Self-Report Scale) and persistent nonmedical use of prescription stimulants. Method: Multinomial regression modeling was used to compare ADHD symptoms among three groups of college students enrolled in a longitudinal study over 4…

General Education Development (GED) Recipients' Life Course Experiences: Humanizing the Findings

ERIC Educational Resources Information Center

Hartigan, Lacey A.

2017-01-01

This study examines a range of GED recipients' life course contexts and experiences and their relationship with long-term outcomes. Using descriptive comparisons, bivariate tests, and propensity-score matched regression models to analyze data from rounds 1-15 of the National Longitudinal Survey of Youth, 1997, analyses aim to examine: (1)…

Genetic and Environmental Contributions to the Development of Childhood Aggression

ERIC Educational Resources Information Center

Lubke, Gitta H.; McArtor, Daniel B.; Boomsma, Dorret I.; Bartels, Meike

2018-01-01

Longitudinal data from a large sample of twins participating in the Netherlands Twin Register (n = 42,827, age range 3-16) were analyzed to investigate the genetic and environmental contributions to childhood aggression. Genetic auto-regressive (simplex) models were used to assess whether the same genes are involved or whether new genes come into…

Progression of MDS-UPDRS Scores Over Five Years in De Novo Parkinson Disease from the Parkinson's Progression Markers Initiative Cohort.

PubMed

Holden, Samantha K; Finseth, Taylor; Sillau, Stefan H; Berman, Brian D

2018-01-01

The Movement Disorder Society Unified Parkinson Disease Rating Scale (MDS-UDPRS) is a commonly used tool to measure Parkinson disease (PD) progression. Longitudinal changes in MDS-UPDRS scores in de novo PD have not been established. Determine progression rates of MDS-UPDRS scores in de novo PD. 362 participants from the Parkinson's Progression Markers Initiative, a multicenter longitudinal cohort study of de novo PD, were included. Longitudinal progression of MDS-UPDRS total and subscale scores were modeled using mixed model regression. MDS-UPDRS scores increased in a linear fashion over five years in de novo PD. MDS-UPDRS total score increased an estimated 4.0 points/year, Part I 0.25 points/year, Part II 1.0 points/year, and Part III 2.4 points/year. The expected average progression of MDS-UPDRS scores in de novo PD from this study can assist in clinical monitoring and provide comparative data for detection of disease modification in treatment trials.

Modeling time-location patterns of inner-city high school students in New York and Los Angeles using a longitudinal approach with generalized estimating equations.

PubMed

Decastro, B Rey; Sax, Sonja N; Chillrud, Steven N; Kinney, Patrick L; Spengler, John D

2007-05-01

The TEACH Project obtained subjects' time-location information as part of its assessment of personal exposures to air toxics for high school students in two major urban areas. This report uses a longitudinal modeling approach to characterize the association between demographic and temporal predictors and the subjects' time-location behavior for three microenvironments--indoor-home, indoor-school, and outdoors. Such a longitudinal approach has not, to the knowledge of the authors, been previously applied to time-location data. Subjects were 14- to 19-year-old, self reported non-smokers, and were recruited from high schools in New York, NY (31 subjects: nine male, 22 female) and Los Angeles, CA (31 subjects: eight male, 23 female). Subjects reported their time-location in structured 24-h diaries with 15-min intervals for three consecutive weekdays in each of winter and summer-fall seasons in New York and Los Angeles during 1999-2000. The data set contained 15,009 observations. A longitudinal logistic regression model was run for each microenvironment where the binary outcome indicated the subject's presence in a microenvironment during a 15-min period. The generalized estimating equation (GEE) technique with alternating logistic regressions was used to account for the correlation of observations within each subject. The multivariate models revealed complex time-location patterns, with subjects predominantly in the indoor-home microenvironment, but also with a clear influence of the school schedule. The models also found that a subject's presence in a particular microenvironment may be significantly positively correlated for as long as 45 min before the current observation. Demographic variables were also predictive of time-location behavior: for the indoor-home microenvironment, having an after school job (OR=0.67 [95% confidence interval: 0.54:0.85]); for indoor-school, living in New York (0.42 [0.29:0.59]); and for outdoor, being 16-year-old (0.80 [0.67:0.96]), 17-year-old (0.71 [0.54:0.92]), and having an after school job (1.29 [1.07:1.56]).

The association of longitudinal trend of fasting plasma glucose with retinal microvasculature in people without established diabetes.

PubMed

Hu, Yin; Niu, Yong; Wang, Dandan; Wang, Ying; Holden, Brien A; He, Mingguang

2015-01-22

Structural changes of retinal vasculature, such as altered retinal vascular calibers, are considered as early signs of systemic vascular damage. We examined the associations of 5-year mean level, longitudinal trend, and fluctuation in fasting plasma glucose (FPG) with retinal vascular caliber in people without established diabetes. A prospective study was conducted in a cohort of Chinese people age ≥40 years in Guangzhou, southern China. The FPG was measured at baseline in 2008 and annually until 2012. In 2012, retinal vascular caliber was assessed using standard fundus photographs and validated software. A total of 3645 baseline nondiabetic participants with baseline and follow-up data on FPG for 3 or more visits was included for statistical analysis. The associations of retinal vascular caliber with 5-year mean FPG level, longitudinal FPG trend (slope of linear regression-FPG), and fluctuation (standard deviation and root mean square error of FPG) were analyzed using multivariable linear regression analyses. Multivariate regression models adjusted for baseline FPG and other potential confounders showed that a 10% annual increase in FPG was associated independently with a 2.65-μm narrowing in retinal arterioles (P = 0.008) and a 3.47-μm widening in venules (P = 0. 0.004). Associations with mean FPG level and fluctuation were not statistically significant. Annual rising trend in FPG, but not its mean level or fluctuation, is associated with altered retinal vasculature in nondiabetic people. Copyright 2015 The Association for Research in Vision and Ophthalmology, Inc.

Do Our Means of Inquiry Match our Intentions?

PubMed Central

Petscher, Yaacov

2016-01-01

A key stage of the scientific method is the analysis of data, yet despite the variety of methods that are available to researchers they are most frequently distilled to a model that focuses on the average relation between variables. Although research questions are frequently conceived with broad inquiry in mind, most regression methods are limited in comprehensively evaluating how observed behaviors are related to each other. Quantile regression is a largely unknown yet well-suited analytic technique similar to traditional regression analysis, but allows for a more systematic approach to understanding complex associations among observed phenomena in the psychological sciences. Data from the National Education Longitudinal Study of 1988/2000 are used to illustrate how quantile regression overcomes the limitations of average associations in linear regression by showing that psychological well-being and sex each differentially relate to reading achievement depending on one’s level of reading achievement. PMID:27486410

Bayesian hierarchical piecewise regression models: a tool to detect trajectory divergence between groups in long-term observational studies.

PubMed

Buscot, Marie-Jeanne; Wotherspoon, Simon S; Magnussen, Costan G; Juonala, Markus; Sabin, Matthew A; Burgner, David P; Lehtimäki, Terho; Viikari, Jorma S A; Hutri-Kähönen, Nina; Raitakari, Olli T; Thomson, Russell J

2017-06-06

Bayesian hierarchical piecewise regression (BHPR) modeling has not been previously formulated to detect and characterise the mechanism of trajectory divergence between groups of participants that have longitudinal responses with distinct developmental phases. These models are useful when participants in a prospective cohort study are grouped according to a distal dichotomous health outcome. Indeed, a refined understanding of how deleterious risk factor profiles develop across the life-course may help inform early-life interventions. Previous techniques to determine between-group differences in risk factors at each age may result in biased estimate of the age at divergence. We demonstrate the use of Bayesian hierarchical piecewise regression (BHPR) to generate a point estimate and credible interval for the age at which trajectories diverge between groups for continuous outcome measures that exhibit non-linear within-person response profiles over time. We illustrate our approach by modeling the divergence in childhood-to-adulthood body mass index (BMI) trajectories between two groups of adults with/without type 2 diabetes mellitus (T2DM) in the Cardiovascular Risk in Young Finns Study (YFS). Using the proposed BHPR approach, we estimated the BMI profiles of participants with T2DM diverged from healthy participants at age 16 years for males (95% credible interval (CI):13.5-18 years) and 21 years for females (95% CI: 19.5-23 years). These data suggest that a critical window for weight management intervention in preventing T2DM might exist before the age when BMI growth rate is naturally expected to decrease. Simulation showed that when using pairwise comparison of least-square means from categorical mixed models, smaller sample sizes tended to conclude a later age of divergence. In contrast, the point estimate of the divergence time is not biased by sample size when using the proposed BHPR method. BHPR is a powerful analytic tool to model long-term non-linear longitudinal outcomes, enabling the identification of the age at which risk factor trajectories diverge between groups of participants. The method is suitable for the analysis of unbalanced longitudinal data, with only a limited number of repeated measures per participants and where the time-related outcome is typically marked by transitional changes or by distinct phases of change over time.

Order-restricted inference for multivariate longitudinal data with applications to the natural history of hearing loss.

PubMed

Rosen, Sophia; Davidov, Ori

2012-07-20

Multivariate outcomes are often measured longitudinally. For example, in hearing loss studies, hearing thresholds for each subject are measured repeatedly over time at several frequencies. Thus, each patient is associated with a multivariate longitudinal outcome. The multivariate mixed-effects model is a useful tool for the analysis of such data. There are situations in which the parameters of the model are subject to some restrictions or constraints. For example, it is known that hearing thresholds, at every frequency, increase with age. Moreover, this age-related threshold elevation is monotone in frequency, that is, the higher the frequency, the higher, on average, is the rate of threshold elevation. This means that there is a natural ordering among the different frequencies in the rate of hearing loss. In practice, this amounts to imposing a set of constraints on the different frequencies' regression coefficients modeling the mean effect of time and age at entry to the study on hearing thresholds. The aforementioned constraints should be accounted for in the analysis. The result is a multivariate longitudinal model with restricted parameters. We propose estimation and testing procedures for such models. We show that ignoring the constraints may lead to misleading inferences regarding the direction and the magnitude of various effects. Moreover, simulations show that incorporating the constraints substantially improves the mean squared error of the estimates and the power of the tests. We used this methodology to analyze a real hearing loss study. Copyright © 2012 John Wiley & Sons, Ltd.

Predicting infant cortical surface development using a 4D varifold-based learning framework and local topography-based shape morphing.

PubMed

Rekik, Islem; Li, Gang; Lin, Weili; Shen, Dinggang

2016-02-01

Longitudinal neuroimaging analysis methods have remarkably advanced our understanding of early postnatal brain development. However, learning predictive models to trace forth the evolution trajectories of both normal and abnormal cortical shapes remains broadly absent. To fill this critical gap, we pioneered the first prediction model for longitudinal developing cortical surfaces in infants using a spatiotemporal current-based learning framework solely from the baseline cortical surface. In this paper, we detail this prediction model and even further improve its performance by introducing two key variants. First, we use the varifold metric to overcome the limitations of the current metric for surface registration that was used in our preliminary study. We also extend the conventional varifold-based surface registration model for pairwise registration to a spatiotemporal surface regression model. Second, we propose a morphing process of the baseline surface using its topographic attributes such as normal direction and principal curvature sign. Specifically, our method learns from longitudinal data both the geometric (vertices positions) and dynamic (temporal evolution trajectories) features of the infant cortical surface, comprising a training stage and a prediction stage. In the training stage, we use the proposed varifold-based shape regression model to estimate geodesic cortical shape evolution trajectories for each training subject. We then build an empirical mean spatiotemporal surface atlas. In the prediction stage, given an infant, we select the best learnt features from training subjects to simultaneously predict the cortical surface shapes at all later timepoints, based on similarity metrics between this baseline surface and the learnt baseline population average surface atlas. We used a leave-one-out cross validation method to predict the inner cortical surface shape at 3, 6, 9 and 12 months of age from the baseline cortical surface shape at birth. Our method attained a higher prediction accuracy and better captured the spatiotemporal dynamic change of the highly folded cortical surface than the previous proposed prediction method. Copyright © 2015 Elsevier B.V. All rights reserved.

Bayesian hierarchical modelling of continuous non‐negative longitudinal data with a spike at zero: An application to a study of birds visiting gardens in winter

PubMed Central

Buckland, Stephen T.; King, Ruth; Toms, Mike P.

2015-01-01

The development of methods for dealing with continuous data with a spike at zero has lagged behind those for overdispersed or zero‐inflated count data. We consider longitudinal ecological data corresponding to an annual average of 26 weekly maximum counts of birds, and are hence effectively continuous, bounded below by zero but also with a discrete mass at zero. We develop a Bayesian hierarchical Tweedie regression model that can directly accommodate the excess number of zeros common to this type of data, whilst accounting for both spatial and temporal correlation. Implementation of the model is conducted in a Markov chain Monte Carlo (MCMC) framework, using reversible jump MCMC to explore uncertainty across both parameter and model spaces. This regression modelling framework is very flexible and removes the need to make strong assumptions about mean‐variance relationships a priori. It can also directly account for the spike at zero, whilst being easily applicable to other types of data and other model formulations. Whilst a correlative study such as this cannot prove causation, our results suggest that an increase in an avian predator may have led to an overall decrease in the number of one of its prey species visiting garden feeding stations in the United Kingdom. This may reflect a change in behaviour of house sparrows to avoid feeding stations frequented by sparrowhawks, or a reduction in house sparrow population size as a result of sparrowhawk increase. PMID:25737026

The Effect of College Selection Factors on Persistence: An Examination of Black and Latino Males in the Community College

ERIC Educational Resources Information Center

Wood, J. Luke; Harris, Frank, III

2015-01-01

The purpose of this study was to understand the relationship (if any) between college selection factors and persistence for Black and Latino males in the community college. Using data derived from the Educational Longitudinal Study, backwards stepwise logistic regression models were developed for both groups. Findings are contextualized in light…

The Influence of Neighborhood Characteristics and Parenting Practices on Academic Problems and Aggression Outcomes among Moderately to Highly Aggressive Children

ERIC Educational Resources Information Center

Barry, Tammy D.; Lochman, John E.; Fite, Paula J.; Wells, Karen C.; Colder, Craig R.

2012-01-01

The current study utilized a longitudinal design to examine the effects of neighborhood and parenting on 120 at-risk children's academic and aggressive outcomes, concurrently and at two later timepoints during the transition to middle school. Random effects regression models were estimated to examine whether neighborhood characteristics and harsh…

Analysis of oscillatory motion of a light airplane at high values of lift coefficient

NASA Technical Reports Server (NTRS)

Batterson, J. G.

1983-01-01

A modified stepwise regression is applied to flight data from a light research air-plane operating at high angles at attack. The well-known phenomenon referred to as buckling or porpoising is analyzed and modeled using both power series and spline expansions of the aerodynamic force and moment coefficients associated with the longitudinal equations of motion.

What Works after School? The Relationship between After-School Program Quality, Program Attendance, and Academic Outcomes

ERIC Educational Resources Information Center

Leos-Urbel, Jacob

2015-01-01

This article examines the relationship between after-school program quality, program attendance, and academic outcomes for a sample of low-income after-school program participants. Regression and hierarchical linear modeling analyses use a unique longitudinal data set including 29 after-school programs that served 5,108 students in Grades 4 to 8…

Aerodynamic parameters of High-Angle-of attack Research Vehicle (HARV) estimated from flight data

NASA Technical Reports Server (NTRS)

Klein, Vladislav; Ratvasky, Thomas R.; Cobleigh, Brent R.

1990-01-01

Aerodynamic parameters of the High-Angle-of-Attack Research Aircraft (HARV) were estimated from flight data at different values of the angle of attack between 10 degrees and 50 degrees. The main part of the data was obtained from small amplitude longitudinal and lateral maneuvers. A small number of large amplitude maneuvers was also used in the estimation. The measured data were first checked for their compatibility. It was found that the accuracy of air data was degraded by unexplained bias errors. Then, the data were analyzed by a stepwise regression method for obtaining a structure of aerodynamic model equations and least squares parameter estimates. Because of high data collinearity in several maneuvers, some of the longitudinal and all lateral maneuvers were reanalyzed by using two biased estimation techniques, the principal components regression and mixed estimation. The estimated parameters in the form of stability and control derivatives, and aerodynamic coefficients were plotted against the angle of attack and compared with the wind tunnel measurements. The influential parameters are, in general, estimated with acceptable accuracy and most of them are in agreement with wind tunnel results. The simulated responses of the aircraft showed good prediction capabilities of the resulting model.

Women's work stress and cortisol levels: a longitudinal study of the association between the psychosocial work environment and serum cortisol.

PubMed

Evolahti, Annika; Hultcrantz, Malou; Collins, Aila

2006-11-01

The aim of the present study was to investigate whether there is an association between serum cortisol and work-related stress, as defined by the demand-control model in a longitudinal design. One hundred ten women aged 47-53 years completed a health questionnaire, including the Swedish version of the Job Content Scale, and participated in a psychological interview at baseline and in a follow-up session 2 years later. Morning blood samples were drawn for analyses of cortisol. Multiple stepwise regression analyses and logistic regression analyses showed that work demands and lack of social support were significantly associated with cortisol. The results of this study showed that negative work characteristics in terms of high demands and low social support contributed significantly to the biological stress levels in middle-aged women. Participation in the study may have served as an intervention, increasing the women's awareness and thus improving their health profiles on follow-up.

Longitudinal cognitive biomarkers predicting symptom onset in presymptomatic frontotemporal dementia.

PubMed

Jiskoot, Lize C; Panman, Jessica L; van Asseldonk, Lauren; Franzen, Sanne; Meeter, Lieke H H; Donker Kaat, Laura; van der Ende, Emma L; Dopper, Elise G P; Timman, Reinier; van Minkelen, Rick; van Swieten, John C; van den Berg, Esther; Papma, Janne M

2018-06-01

We performed 4-year follow-up neuropsychological assessment to investigate cognitive decline and the prognostic abilities from presymptomatic to symptomatic familial frontotemporal dementia (FTD). Presymptomatic MAPT (n = 15) and GRN mutation carriers (n = 31), and healthy controls (n = 39) underwent neuropsychological assessment every 2 years. Eight mutation carriers (5 MAPT, 3 GRN) became symptomatic. We investigated cognitive decline with multilevel regression modeling; the prognostic performance was assessed with ROC analyses and stepwise logistic regression. MAPT converters declined on language, attention, executive function, social cognition, and memory, and GRN converters declined on attention and executive function (p < 0.05). Cognitive decline in ScreeLing phonology (p = 0.046) and letter fluency (p = 0.046) were predictive for conversion to non-fluent variant PPA, and decline on categorical fluency (p = 0.025) for an underlying MAPT mutation. Using longitudinal neuropsychological assessment, we detected a mutation-specific pattern of cognitive decline, potentially suggesting prognostic value of neuropsychological trajectories in conversion to symptomatic FTD.

On Models for Binomial Data with Random Numbers of Trials

PubMed Central

Comulada, W. Scott; Weiss, Robert E.

2010-01-01

Summary A binomial outcome is a count s of the number of successes out of the total number of independent trials n = s + f, where f is a count of the failures. The n are random variables not fixed by design in many studies. Joint modeling of (s, f) can provide additional insight into the science and into the probability π of success that cannot be directly incorporated by the logistic regression model. Observations where n = 0 are excluded from the binomial analysis yet may be important to understanding how π is influenced by covariates. Correlation between s and f may exist and be of direct interest. We propose Bayesian multivariate Poisson models for the bivariate response (s, f), correlated through random effects. We extend our models to the analysis of longitudinal and multivariate longitudinal binomial outcomes. Our methodology was motivated by two disparate examples, one from teratology and one from an HIV tertiary intervention study. PMID:17688514

Prospective inverse associations of sex hormone concentrations in men with biomarkers of inflammation and oxidative stress.

PubMed

Haring, Robin; Baumeister, Sebastian E; Völzke, Henry; Dörr, Marcus; Kocher, Thomas; Nauck, Matthias; Wallaschofski, Henri

2012-01-01

The suggested associations between sex hormone concentrations and inflammatory biomarkers in men originate from cross-sectional studies and small-scale clinical trials. But prior studies have not investigated longitudinal associations. Overall, 1344 men aged 20-79 years from the population-based cohort Study of Health in Pomerania were followed up for 5.0 (median) years. We used multivariable regression models to analyze cross-sectional and longitudinal associations of serum sex hormone concentrations (total testosterone [TT], sex hormone-binding globulin [SHBG], calculated free testosterone [free T], and dehydroepiandrosterone sulfate [DHEAS]) with biomarkers of inflammation (fibrinogen, high-sensitive C-reactive protein [hsCRP], and white blood cell count [WBC]) and oxidative stress (γ-glutamyl transferase [GGT]) using ordinary least square regression and generalized estimating equation models, respectively. Cross-sectional models revealed borderline associations of sex hormone concentrations with hsCRP, WBC, and GGT levels that were not retained after multivariable adjustment. Longitudinal multivariable analyses revealed an inverse association of baseline TT, free T, and DHEAS concentrations with change in fibrinogen levels (per SD decrement in TT, 0.25 [95% confidence interval, 0.04-0.45]; in free T, 0.30 [0.09-0.51]; and in DHEAS, 0.23 [0.11-0.36]). Furthermore, baseline DHEAS concentrations were inversely associated with change in WBC levels (per SD decrement, 0.53 [0.24-0.82]). Baseline TT, SHBG, free T, and DHEAS concentrations were also inversely associated with change in GGT after multivariable adjustment. The present study is the first to demonstrate prospective inverse associations between sex hormone concentrations and markers of inflammation and oxidative stress in men. Additional studies are warranted to elucidate potential mechanisms underlying the revealed associations.

Analysis strategies for longitudinal attachment loss data.

PubMed

Beck, J D; Elter, J R

2000-02-01

The purpose of this invited review is to describe and discuss methods currently in use to quantify the progression of attachment loss in epidemiological studies of periodontal disease, and to make recommendations for specific analytic methods based upon the particular design of the study and structure of the data. The review concentrates on the definition of incident attachment loss (ALOSS) and its component parts; measurement issues including thresholds and regression to the mean; methods of accounting for longitudinal change, including changes in means, changes in proportions of affected sites, incidence density, the effect of tooth loss and reversals, and repeated events; statistical models of longitudinal change, including the incorporation of the time element, use of linear, logistic or Poisson regression or survival analysis, and statistical tests; site vs person level of analysis, including statistical adjustment for correlated data; the strengths and limitations of ALOSS data. Examples from the Piedmont 65+ Dental Study are used to illustrate specific concepts. We conclude that incidence density is the preferred methodology to use for periodontal studies with more than one period of follow-up and that the use of studies not employing methods for dealing with complex samples, correlated data, and repeated measures does not take advantage of our current understanding of the site- and person-level variables important in periodontal disease and may generate biased results.

Modeling time-to-event (survival) data using classification tree analysis.

PubMed

Linden, Ariel; Yarnold, Paul R

2017-12-01

Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

Event time analysis of longitudinal neuroimage data.

PubMed

Sabuncu, Mert R; Bernal-Rusiel, Jorge L; Reuter, Martin; Greve, Douglas N; Fischl, Bruce

2014-08-15

This paper presents a method for the statistical analysis of the associations between longitudinal neuroimaging measurements, e.g., of cortical thickness, and the timing of a clinical event of interest, e.g., disease onset. The proposed approach consists of two steps, the first of which employs a linear mixed effects (LME) model to capture temporal variation in serial imaging data. The second step utilizes the extended Cox regression model to examine the relationship between time-dependent imaging measurements and the timing of the event of interest. We demonstrate the proposed method both for the univariate analysis of image-derived biomarkers, e.g., the volume of a structure of interest, and the exploratory mass-univariate analysis of measurements contained in maps, such as cortical thickness and gray matter density. The mass-univariate method employs a recently developed spatial extension of the LME model. We applied our method to analyze structural measurements computed using FreeSurfer, a widely used brain Magnetic Resonance Image (MRI) analysis software package. We provide a quantitative and objective empirical evaluation of the statistical performance of the proposed method on longitudinal data from subjects suffering from Mild Cognitive Impairment (MCI) at baseline. Copyright © 2014 Elsevier Inc. All rights reserved.

Structural nested mean models for assessing time-varying effect moderation.

PubMed

Almirall, Daniel; Ten Have, Thomas; Murphy, Susan A

2010-03-01

This article considers the problem of assessing causal effect moderation in longitudinal settings in which treatment (or exposure) is time varying and so are the covariates said to moderate its effect. Intermediate causal effects that describe time-varying causal effects of treatment conditional on past covariate history are introduced and considered as part of Robins' structural nested mean model. Two estimators of the intermediate causal effects, and their standard errors, are presented and discussed: The first is a proposed two-stage regression estimator. The second is Robins' G-estimator. The results of a small simulation study that begins to shed light on the small versus large sample performance of the estimators, and on the bias-variance trade-off between the two estimators are presented. The methodology is illustrated using longitudinal data from a depression study.

Functional Additive Mixed Models

PubMed Central

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2014-01-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach. PMID:26347592

Functional Additive Mixed Models.

PubMed

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2015-04-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.

Symptoms of Depression Depend on Rigid Parenting Attitudes, Gender, and Race in an At-Risk Sample of Early Adolescents

ERIC Educational Resources Information Center

Weed, Keri; Morales, Dawn A.; Harjes, Rachel

2013-01-01

Trajectories of depressive symptoms were compared between European American and African American boys and girls from ages 8 to 14 in a longitudinal sample of 130 children born to adolescent mothers. Mixed-effects regression modeling was used to analyze individual and group differences in level of depressive symptoms and their changes over time.…

The effectiveness of a monetary incentive offer on survey response rates and response completeness in a longitudinal study.

PubMed

Yu, Shengchao; Alper, Howard E; Nguyen, Angela-Maithy; Brackbill, Robert M; Turner, Lennon; Walker, Deborah J; Maslow, Carey B; Zweig, Kimberly C

2017-04-26

Achieving adequate response rates is an ongoing challenge for longitudinal studies. The World Trade Center Health Registry is a longitudinal health study that periodically surveys a cohort of ~71,000 people exposed to the 9/11 terrorist attacks in New York City. Since Wave 1, the Registry has conducted three follow-up surveys (Waves 2-4) every 3-4 years and utilized various strategies to increase survey participation. A promised monetary incentive was offered for the first time to survey non-respondents in the recent Wave 4 survey, conducted 13-14 years after 9/11. We evaluated the effectiveness of a monetary incentive in improving the response rate five months after survey launch, and assessed whether or not response completeness was compromised due to incentive use. The study compared the likelihood of returning a survey for those who received an incentive offer to those who did not, using logistic regression models. Among those who returned surveys, we also examined whether those receiving an incentive notification had higher rate of response completeness than those who did not, using negative binomial regression models and logistic regression models. We found that a $10 monetary incentive offer was effective in increasing Wave 4 response rates. Specifically, the $10 incentive offer was useful in encouraging initially reluctant participants to respond to the survey. The likelihood of returning a survey increased by 30% for those who received an incentive offer (AOR = 1.3, 95% CI: 1.1, 1.4), and the incentive increased the number of returned surveys by 18%. Moreover, our results did not reveal any significant differences on response completeness between those who received an incentive offer and those who did not. In the face of the growing challenge of maintaining a high response rate for the World Trade Center Health Registry follow-up surveys, this study showed the value of offering a monetary incentive as an additional refusal conversion strategy. Our findings also suggest that an incentive offer could be particularly useful near the end of data collection period when an immediate boost in response rate is needed.

Sufficient Dimension Reduction for Longitudinally Measured Predictors

PubMed Central

Pfeiffer, Ruth M.; Forzani, Liliana; Bura, Efstathia

2013-01-01

We propose a method to combine several predictors (markers) that are measured repeatedly over time into a composite marker score without assuming a model and only requiring a mild condition on the predictor distribution. Assuming that the first and second moments of the predictors can be decomposed into a time and a marker component via a Kronecker product structure, that accommodates the longitudinal nature of the predictors, we develop first moment sufficient dimension reduction techniques to replace the original markers with linear transformations that contain sufficient information for the regression of the predictors on the outcome. These linear combinations can then be combined into a score that has better predictive performance than the score built under a general model that ignores the longitudinal structure of the data. Our methods can be applied to either continuous or categorical outcome measures. In simulations we focus on binary outcomes and show that our method outperforms existing alternatives using the AUC, the area under the receiver-operator characteristics (ROC) curve, as a summary measure of the discriminatory ability of a single continuous diagnostic marker for binary disease outcomes. PMID:22161635

Examining the Association between Patient-Reported Symptoms of Attention and Memory Dysfunction with Objective Cognitive Performance: A Latent Regression Rasch Model Approach.

PubMed

Li, Yuelin; Root, James C; Atkinson, Thomas M; Ahles, Tim A

2016-06-01

Patient-reported cognition generally exhibits poor concordance with objectively assessed cognitive performance. In this article, we introduce latent regression Rasch modeling and provide a step-by-step tutorial for applying Rasch methods as an alternative to traditional correlation to better clarify the relationship of self-report and objective cognitive performance. An example analysis using these methods is also included. Introduction to latent regression Rasch modeling is provided together with a tutorial on implementing it using the JAGS programming language for the Bayesian posterior parameter estimates. In an example analysis, data from a longitudinal neurocognitive outcomes study of 132 breast cancer patients and 45 non-cancer matched controls that included self-report and objective performance measures pre- and post-treatment were analyzed using both conventional and latent regression Rasch model approaches. Consistent with previous research, conventional analysis and correlations between neurocognitive decline and self-reported problems were generally near zero. In contrast, application of latent regression Rasch modeling found statistically reliable associations between objective attention and processing speed measures with self-reported Attention and Memory scores. Latent regression Rasch modeling, together with correlation of specific self-reported cognitive domains with neurocognitive measures, helps to clarify the relationship of self-report with objective performance. While the majority of patients attribute their cognitive difficulties to memory decline, the Rash modeling suggests the importance of processing speed and initial learning. To encourage the use of this method, a step-by-step guide and programming language for implementation is provided. Implications of this method in cognitive outcomes research are discussed. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Analyzing musculoskeletal neck pain, measured as present pain and periods of pain, with three different regression models: a cohort study.

PubMed

Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats

2009-06-19

In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session > or = 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors.

Analyzing musculoskeletal neck pain, measured as present pain and periods of pain, with three different regression models: a cohort study

PubMed Central

Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats

2009-01-01

Background In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Methods Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Results Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session ≥ 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). Conclusion By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors. PMID:19545386

Health shocks adversely impact participation in the labour force in a working age population: a longitudinal analysis.

PubMed

Carter, Kristie N; Gunasekara, Fiona Imlach; Blakely, Tony; Richardson, Ken

2013-06-01

It is well understood that health affects labour force participation (LFP). However, much of the published research has been on older (retiring age) populations and using subjective health measures. This paper aims to assess the impact of an objective measure of 'health shock' (cancer registration or hospitalisation) on LFP in a working age population using longitudinal panel study data and fixed effect regression analyses. Seven waves of data from 2002-09 from the longitudinal Survey of Family, Income and Employment (SoFIE) were used, including working aged individuals who consented to have their survey information linked to health records (n=6,780). Fixed effect conditional logistic regression was used to model the impact of health shocks (hospitalisation or cancer registration) in the previous year on labour force participation at date of annual interview. Models were stratified by gender, age group (25-39 years, 40-54 years) and gender by age group. A health shock was associated with a significantly increased risk of subsequent non-participation in the labour force (odds ratio 1.54, 95%CI 1.30-1.82). Although interactions of age, sex and age by sex with health shock were not statistically significant, the association was largest in younger men and women. Using an objective measure of health, we have shown that a health shock adversely affects subsequent labour force participation. There are a number of policy and practice implications relating to support for working age people who have hospitalisations. © 2013 The Authors. ANZJPH © 2013 Public Health Association of Australia.

Risk factors for intimate partner violence in women in the Rakai Community Cohort Study, Uganda, from 2000 to 2009

PubMed Central

2013-01-01

Background Intimate partner violence (IPV) is a significant public health problem. There is a lack of data on IPV risk factors from longitudinal studies and from low and middle income countries. Identifying risk factors is needed to inform the design of appropriate IPV interventions. Methods Data were from the Rakai Community Cohort Study annual surveys between 2000 and 2009. Female participants who had at least one sexual partner during this period and had data on IPV over the study period were included in analyses (N = 15081). Factors from childhood and early adulthood as well as contemporary factors were considered in separate models. Logistic regression was used to assess early risk factors for IPV during the study period. Longitudinal data analysis was used to assess contemporary risk factors in the past year for IPV in the current year, using a population-averaged multivariable logistic regression model. Results Risk factors for IPV from childhood and early adulthood included sexual abuse in childhood or adolescence, earlier age at first sex, lower levels of education, and forced first sex. Contemporary risk factors included younger age, being married, relationships of shorter duration, having a partner who is the same age or younger, alcohol use before sex by women and by their partners, and thinking that violence is acceptable. HIV infection and pregnancy were not associated with an increased odds of IPV. Conclusions Using longitudinal data, this study identified a number of risk factors for IPV. These findings are useful for the development of prevention strategies to prevent and mitigate IPV in women. PMID:23759123

Systematic Review and Meta-Analysis: Dose-Response Relationship of Selective Serotonin Reuptake Inhibitors in Major Depressive Disorder.

PubMed

Jakubovski, Ewgeni; Varigonda, Anjali L; Freemantle, Nicholas; Taylor, Matthew J; Bloch, Michael H

2016-02-01

Previous studies suggested that the treatment response to selective serotonin reuptake inhibitors (SSRIs) in major depressive disorder follows a flat response curve within the therapeutic dose range. The present study was designed to clarify the relationship between dosage and treatment response in major depressive disorder. The authors searched PubMed for randomized placebo-controlled trials examining the efficacy of SSRIs for treating adults with major depressive disorder. Trials were also required to assess improvement in depression severity at multiple time points. Additional data were collected on treatment response and all-cause and side effect-related discontinuation. All medication doses were transformed into imipramine-equivalent doses. The longitudinal data were analyzed with a mixed-regression model. Endpoint and tolerability analyses were analyzed using meta-regression and stratified subgroup analysis by predefined SSRI dose categories in order to assess the effect of SSRI dosing on the efficacy and tolerability of SSRIs for major depressive disorder. Forty studies involving 10,039 participants were included. Longitudinal modeling (dose-by-time interaction=0.0007, 95% CI=0.0001-0.0013) and endpoint analysis (meta-regression: β=0.00053, 95% CI=0.00018-0.00088, z=2.98) demonstrated a small but statistically significant positive association between SSRI dose and efficacy. Higher doses of SSRIs were associated with an increased likelihood of dropouts due to side effects (meta-regression: β=0.00207, 95% CI=0.00071-0.00342, z=2.98) and decreased likelihood of all-cause dropout (meta-regression: β=-0.00093, 95% CI=-0.00165 to -0.00021, z=-2.54). Higher doses of SSRIs appear slightly more effective in major depressive disorder. This benefit appears to plateau at around 250 mg of imipramine equivalents (50 mg of fluoxetine). The slightly increased benefits of SSRIs at higher doses are somewhat offset by decreased tolerability at high doses.

Evolution of deep gray matter volume across the human lifespan.

PubMed

Narvacan, Karl; Treit, Sarah; Camicioli, Richard; Martin, Wayne; Beaulieu, Christian

2017-08-01

Magnetic resonance imaging of subcortical gray matter structures, which mediate behavior, cognition and the pathophysiology of several diseases, is crucial for establishing typical maturation patterns across the human lifespan. This single site study examines T1-weighted MPRAGE images of 3 healthy cohorts: (i) a cross-sectional cohort of 406 subjects aged 5-83 years; (ii) a longitudinal neurodevelopment cohort of 84 subjects scanned twice approximately 4 years apart, aged 5-27 years at first scan; and (iii) a longitudinal aging cohort of 55 subjects scanned twice approximately 3 years apart, aged 46-83 years at first scan. First scans from longitudinal subjects were included in the cross-sectional analysis. Age-dependent changes in thalamus, caudate, putamen, globus pallidus, nucleus accumbens, hippocampus, and amygdala volumes were tested with Poisson, quadratic, and linear models in the cross-sectional cohort, and quadratic and linear models in the longitudinal cohorts. Most deep gray matter structures best fit to Poisson regressions in the cross-sectional cohort and quadratic curves in the young longitudinal cohort, whereas the volume of all structures except the caudate and globus pallidus decreased linearly in the longitudinal aging cohort. Males had larger volumes than females for all subcortical structures, but sex differences in trajectories of change with age were not significant. Within subject analysis showed that 65%-80% of 13-17 year olds underwent a longitudinal decrease in volume between scans (∼4 years apart) for the putamen, globus pallidus, and hippocampus, suggesting unique developmental processes during adolescence. This lifespan study of healthy participants will form a basis for comparison to neurological and psychiatric disorders. Hum Brain Mapp 38:3771-3790, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort.

PubMed

Milner, A; Krnjacki, L; LaMontagne, A D

2016-11-01

Perceived social support is associated with better mental health. There has been limited attention to how these relationships are modified by age and gender. We assessed this topic using 13 years of cohort data. Prospective cohort study. The outcome was the Mental Health Inventory-5 (MHI-5), a reliable and valid screening instrument for mood disorders. The main exposure was a social support scale composed of 10 items. We used longitudinal fixed-effects regression modelling to investigate within-person changes in mental health. Analytic models controlled for within-person sources of bias. We controlled for time-related factors by including them into regression modelling. The provision of higher levels of social support was associated with greater improvements in mental health for people aged under 30 years than for older age groups. The mental health of females appeared to benefit slightly more from higher levels of social support than males. Improvements in the MHI-5 were on a scale that could be considered clinically significant. The benefits of social support for young people may be connected to age-related transitions in self-identity and peer friendship networks. Results for females may reflect their tendency to place greater emphasis on social networks than males. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Mechanistic analysis of challenge-response experiments.

PubMed

Shotwell, M S; Drake, K J; Sidorov, V Y; Wikswo, J P

2013-09-01

We present an application of mechanistic modeling and nonlinear longitudinal regression in the context of biomedical response-to-challenge experiments, a field where these methods are underutilized. In this type of experiment, a system is studied by imposing an experimental challenge, and then observing its response. The combination of mechanistic modeling and nonlinear longitudinal regression has brought new insight, and revealed an unexpected opportunity for optimal design. Specifically, the mechanistic aspect of our approach enables the optimal design of experimental challenge characteristics (e.g., intensity, duration). This article lays some groundwork for this approach. We consider a series of experiments wherein an isolated rabbit heart is challenged with intermittent anoxia. The heart responds to the challenge onset, and recovers when the challenge ends. The mean response is modeled by a system of differential equations that describe a candidate mechanism for cardiac response to anoxia challenge. The cardiac system behaves more variably when challenged than when at rest. Hence, observations arising from this experiment exhibit complex heteroscedasticity and sharp changes in central tendency. We present evidence that an asymptotic statistical inference strategy may fail to adequately account for statistical uncertainty. Two alternative methods are critiqued qualitatively (i.e., for utility in the current context), and quantitatively using an innovative Monte-Carlo method. We conclude with a discussion of the exciting opportunities in optimal design of response-to-challenge experiments. © 2013, The International Biometric Society.

Bayesian hierarchical modelling of continuous non-negative longitudinal data with a spike at zero: An application to a study of birds visiting gardens in winter.

PubMed

Swallow, Ben; Buckland, Stephen T; King, Ruth; Toms, Mike P

2016-03-01

The development of methods for dealing with continuous data with a spike at zero has lagged behind those for overdispersed or zero-inflated count data. We consider longitudinal ecological data corresponding to an annual average of 26 weekly maximum counts of birds, and are hence effectively continuous, bounded below by zero but also with a discrete mass at zero. We develop a Bayesian hierarchical Tweedie regression model that can directly accommodate the excess number of zeros common to this type of data, whilst accounting for both spatial and temporal correlation. Implementation of the model is conducted in a Markov chain Monte Carlo (MCMC) framework, using reversible jump MCMC to explore uncertainty across both parameter and model spaces. This regression modelling framework is very flexible and removes the need to make strong assumptions about mean-variance relationships a priori. It can also directly account for the spike at zero, whilst being easily applicable to other types of data and other model formulations. Whilst a correlative study such as this cannot prove causation, our results suggest that an increase in an avian predator may have led to an overall decrease in the number of one of its prey species visiting garden feeding stations in the United Kingdom. This may reflect a change in behaviour of house sparrows to avoid feeding stations frequented by sparrowhawks, or a reduction in house sparrow population size as a result of sparrowhawk increase. © 2015 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Does informal caregiving affect self-esteem? Results from a population-based study of individuals aged 40 and over in Germany from 2002 to 2014.

PubMed

Hajek, André; König, Hans-Helmut

2017-11-29

While it is known that informal caregiving is associated with care-derived self-esteem cross-sectionally, little is known about the impact of informal caregiving on general self-esteem longitudinally. Thus, we aimed at examining whether informal caregiving affects general self-esteem using a longitudinal approach. Data were gathered from a population-based sample of community-dwelling individuals aged 40 and over in Germany from 2002 to 2014 (n = 21 271). General self-esteem was quantified using the Rosenberg scale. Individuals were asked whether they provide informal care regularly. Fixed effects regressions showed no significant effect of informal caregiving on general self-esteem longitudinally. General self-esteem decreased with increasing morbidity, increasing age, decreasing social ties, whereas it was not associated with changes in employment status, marital status and body mass index. Additional models showed that decreases in self-esteem were associated with decreases in functional health and increases in depressive symptoms. Our longitudinal study emphasises that the occurrence of informal caregiving did not affect general self-esteem longitudinally. Further research is needed in other cultural settings using panel data methods. © 2017 Nordic College of Caring Science.

Longitudinal study of stress, social support, and depression in married Arab immigrant women.

PubMed

Aroian, Karen; Uddin, Nizam; Blbas, Hazar

2017-02-01

Using a stress and social support framework, this study explored the trajectory of depression in 388 married Arab immigrant women. The women provided three panels of data approximately 18 months apart. Depression at Time 3 was regressed on Time 1 depression, socio-demographic variables, and rate of change over time in stress and social support. The regression model was significant and accounted for 41.16% of the variation in Time 3 depression scores. Time 1 depression, English reading ability, husband's employment status, changes over time in immigration demands, daily hassles, and social support from friends were associated with Time 3 depression.

Longitudinal Study of Stress, Social Support, and Depression In Married Arab Immigrant Women

PubMed Central

Aroian, Karen; Uddin, Nizam; Blbas, Hazar

2017-01-01

Using a stress and social support framework, this study explored the trajectory of depression in 388 married Arab immigrant women. The women provided three panels of data approximately 18 months apart. Depression at Time 3 was regressed on Time 1 depression, socio-demographic variables, and rate of change over time in stress and social support. The regression model was significant and accounted for 41.16% of the variation in Time 3 depression scores. Time 1 depression, English reading ability, husband’s employment status, and changes over time in immigration demands, daily hassles, and social support from friends were associated with Time 3 Depression. PMID:27791495

Filtering data from the collaborative initial glaucoma treatment study for improved identification of glaucoma progression.

PubMed

Schell, Greggory J; Lavieri, Mariel S; Stein, Joshua D; Musch, David C

2013-12-21

Open-angle glaucoma (OAG) is a prevalent, degenerate ocular disease which can lead to blindness without proper clinical management. The tests used to assess disease progression are susceptible to process and measurement noise. The aim of this study was to develop a methodology which accounts for the inherent noise in the data and improve significant disease progression identification. Longitudinal observations from the Collaborative Initial Glaucoma Treatment Study (CIGTS) were used to parameterize and validate a Kalman filter model and logistic regression function. The Kalman filter estimates the true value of biomarkers associated with OAG and forecasts future values of these variables. We develop two logistic regression models via generalized estimating equations (GEE) for calculating the probability of experiencing significant OAG progression: one model based on the raw measurements from CIGTS and another model based on the Kalman filter estimates of the CIGTS data. Receiver operating characteristic (ROC) curves and associated area under the ROC curve (AUC) estimates are calculated using cross-fold validation. The logistic regression model developed using Kalman filter estimates as data input achieves higher sensitivity and specificity than the model developed using raw measurements. The mean AUC for the Kalman filter-based model is 0.961 while the mean AUC for the raw measurements model is 0.889. Hence, using the probability function generated via Kalman filter estimates and GEE for logistic regression, we are able to more accurately classify patients and instances as experiencing significant OAG progression. A Kalman filter approach for estimating the true value of OAG biomarkers resulted in data input which improved the accuracy of a logistic regression classification model compared to a model using raw measurements as input. This methodology accounts for process and measurement noise to enable improved discrimination between progression and nonprogression in chronic diseases.

Regression to the Mean and Changes in Risk Behavior following Study Enrollment in a Cohort of US Women at Risk for HIV

PubMed Central

Hughes, James P.; Haley, Danielle F.; Frew, Paula M.; Golin, Carol E.; Adimora, Adaora A; Kuo, Irene; Justman, Jessica; Soto-Torres, Lydia; Wang, Jing; Hodder, Sally

2015-01-01

Purpose Reductions in risk behaviors are common following enrollment in HIV prevention studies. We develop methods to quantify the proportion of change in risk behaviors that can be attributed to regression to the mean versus study participation and other factors. Methods A novel model that incorporates both regression to the mean and study participation effects is developed for binary measures. The model is used to estimate the proportion of change in the prevalence of “unprotected sex in the past 6 months” that can be attributed to study participation versus regression to the mean in a longitudinal cohort of women at risk for HIV infection who were recruited from ten US communities with high rates of HIV and poverty. HIV risk behaviors were evaluated using audio computer-assisted self-interviews at baseline and every 6 months for up to 12 months. Results The prevalence of “unprotected sex in the past 6 months” declined from 96% at baseline to 77% at 12 months. However, this change could be almost completely explained by regression to the mean. Conclusions Analyses that examine changes over time in cohorts selected for high or low risk behaviors should account for regression to the mean effects. PMID:25883065

Learning-based subject-specific estimation of dynamic maps of cortical morphology at missing time points in longitudinal infant studies.

PubMed

Meng, Yu; Li, Gang; Gao, Yaozong; Lin, Weili; Shen, Dinggang

2016-11-01

Longitudinal neuroimaging analysis of the dynamic brain development in infants has received increasing attention recently. Many studies expect a complete longitudinal dataset in order to accurately chart the brain developmental trajectories. However, in practice, a large portion of subjects in longitudinal studies often have missing data at certain time points, due to various reasons such as the absence of scan or poor image quality. To make better use of these incomplete longitudinal data, in this paper, we propose a novel machine learning-based method to estimate the subject-specific, vertex-wise cortical morphological attributes at the missing time points in longitudinal infant studies. Specifically, we develop a customized regression forest, named dynamically assembled regression forest (DARF), as the core regression tool. DARF ensures the spatial smoothness of the estimated maps for vertex-wise cortical morphological attributes and also greatly reduces the computational cost. By employing a pairwise estimation followed by a joint refinement, our method is able to fully exploit the available information from both subjects with complete scans and subjects with missing scans for estimation of the missing cortical attribute maps. The proposed method has been applied to estimating the dynamic cortical thickness maps at missing time points in an incomplete longitudinal infant dataset, which includes 31 healthy infant subjects, each having up to five time points in the first postnatal year. The experimental results indicate that our proposed framework can accurately estimate the subject-specific vertex-wise cortical thickness maps at missing time points, with the average error less than 0.23 mm. Hum Brain Mapp 37:4129-4147, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects

NASA Astrophysics Data System (ADS)

Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

2016-03-01

Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI.

Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

PubMed

Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

2013-01-01

In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

Parametric Study of Shear Strength of Concrete Beams Reinforced with FRP Bars

NASA Astrophysics Data System (ADS)

Thomas, Job; Ramadass, S.

2016-09-01

Fibre Reinforced Polymer (FRP) bars are being widely used as internal reinforcement in structural elements in the last decade. The corrosion resistance of FRP bars qualifies its use in severe and marine exposure conditions in structures. A total of eight concrete beams longitudinally reinforced with FRP bars were cast and tested over shear span to depth ratio of 0.5 and 1.75. The shear strength test data of 188 beams published in various literatures were also used. The model originally proposed by Indian Standard Code of practice for the prediction of shear strength of concrete beams reinforced with steel bars IS:456 (Plain and reinforced concrete, code of practice, fourth revision. Bureau of Indian Standards, New Delhi, 2000) is considered and a modification to account for the influence of the FRP bars is proposed based on regression analysis. Out of the 196 test data, 110 test data is used for the regression analysis and 86 test data is used for the validation of the model. In addition, the shear strength of 86 test data accounted for the validation is assessed using eleven models proposed by various researchers. The proposed model accounts for compressive strength of concrete ( f ck ), modulus of elasticity of FRP rebar ( E f ), longitudinal reinforcement ratio ( ρ f ), shear span to depth ratio ( a/ d) and size effect of beams. The predicted shear strength of beams using the proposed model and 11 models proposed by other researchers is compared with the corresponding experimental results. The mean of predicted shear strength to the experimental shear strength for the 86 beams accounted for the validation of the proposed model is found to be 0.93. The result of the statistical analysis indicates that the prediction based on the proposed model corroborates with the corresponding experimental data.

Sexual Minority Disparities in Substance Use Willingness Among Youth.

PubMed

Gamarel, Kristi E; Mereish, Ethan H; Colby, Suzanne M; Barnett, Nancy P; Hayes, Kerri; Jackson, Kristina M

2018-01-02

Disparities in substance use have been observed in sexual minority youth, but less is known about willingness to use substances, an important precursor to actual use. The goal of this study was to examine willingness to use cigarettes, alcohol, and marijuana among sexual minority youth compared to their non-sexual minority counterparts using both cross-sectional and longitudinal data. The present study drew on two waves (Times 1 and 2; 6 months apart) of data collected during high school as part of a prospective study of substance use initiation and progression in Rhode Island. At Time 1, participants (N = 443) ranged in age from 15 to 20 years (M age = 16.7 years, 26.6% sexual minority, 59.5% female, 72.0% White). Participants self-reported their sexual identity and attraction, lifetime use of alcohol, cigarettes and marijuana, and cigarette, alcohol, and marijuana use willingness (i.e., if offered by a best friend or group of friends). In cross-sectional multivariate regression models, sexual minority youth were more likely to report willingness to use cigarettes (p <.05) and marijuana (p <.01) compared to their non-sexual minority counterparts. Longitudinal multivariate regression models revealed that sexual minorities were only significantly more likely to report cigarette willingness at Time 2 compared to their non-sexual minority counterparts (p <.01). There were no significant differences in alcohol use willingness in multivariable cross-sectional or longitudinal models by sexual minority status. Sexual minority youth reported more willingness than non-sexual minority youth to use substances offered by peers; however, longitudinal analyses revealed that peers appear to play a role only in willingness to smoke cigarettes for these youth, and thus peer influence may be a contributing factor in explaining tobacco-related disparities among sexual minority youth. Given that stigma and peer groups may a particular risk factor for tobacco among sexual minority youth, our findings highlight the importance of prevention programs such as social marketing approaches that correct social norms, reduce stigma, and provide refusal-skills training to reduce tobacco-related disparities among sexual minorities.

Estimating increment-decrement life tables with multiple covariates from panel data: the case of active life expectancy.

PubMed

Land, K C; Guralnik, J M; Blazer, D G

1994-05-01

A fundamental limitation of current multistate life table methodology-evident in recent estimates of active life expectancy for the elderly-is the inability to estimate tables from data on small longitudinal panels in the presence of multiple covariates (such as sex, race, and socioeconomic status). This paper presents an approach to such an estimation based on an isomorphism between the structure of the stochastic model underlying a conventional specification of the increment-decrement life table and that of Markov panel regression models for simple state spaces. We argue that Markov panel regression procedures can be used to provide smoothed or graduated group-specific estimates of transition probabilities that are more stable across short age intervals than those computed directly from sample data. We then join these estimates with increment-decrement life table methods to compute group-specific total, active, and dependent life expectancy estimates. To illustrate the methods, we describe an empirical application to the estimation of such life expectancies specific to sex, race, and education (years of school completed) for a longitudinal panel of elderly persons. We find that education extends both total life expectancy and active life expectancy. Education thus may serve as a powerful social protective mechanism delaying the onset of health problems at older ages.

Still the Favorite? Parents' Differential Treatment of Siblings Entering Young Adulthood.

PubMed

Siennick, Sonja E

2013-08-01

This study examined within-family stability in parents' differential treatment of siblings from adolescence to young adulthood and the effect of differential treatment in young adulthood on grown siblings' relationship quality. The author used longitudinal data on parent - child and sibling relations from the sibling sample of the National Longitudinal Study of Adolescent Health ( N = 1,470 sibling dyads). Within-dyad fixed effects regression models revealed that the adolescent sibling who was closer to parents went on to be the young adult sibling who was closer to and received more material support from parents. Results from an actor - partner interdependence model revealed that differential parental financial assistance of young adult siblings predicted worse sibling relationship quality. These findings demonstrate the lasting importance of affect between parents and offspring earlier in the family life course and the relevance of within-family inequalities for understanding family relations.

Still the Favorite? Parents’ Differential Treatment of Siblings Entering Young Adulthood

PubMed Central

Siennick, Sonja E.

2013-01-01

This study examined within-family stability in parents’ differential treatment of siblings from adolescence to young adulthood and the effect of differential treatment in young adulthood on grown siblings’ relationship quality. The author used longitudinal data on parent – child and sibling relations from the sibling sample of the National Longitudinal Study of Adolescent Health (N = 1,470 sibling dyads). Within-dyad fixed effects regression models revealed that the adolescent sibling who was closer to parents went on to be the young adult sibling who was closer to and received more material support from parents. Results from an actor – partner interdependence model revealed that differential parental financial assistance of young adult siblings predicted worse sibling relationship quality. These findings demonstrate the lasting importance of affect between parents and offspring earlier in the family life course and the relevance of within-family inequalities for understanding family relations. PMID:24244050

Longitudinal methods to investigate the role of health determinants in the dynamics of income-related health inequality☆

PubMed Central

Allanson, Paul; Petrie, Dennis

2013-01-01

The usual starting point for understanding changes in income-related health inequality (IRHI) over time has been regression-based decomposition procedures for the health concentration index. However the reliance on repeated cross-sectional analysis for this purpose prevents both the appropriate specification of the health function as a dynamic model and the identification of important determinants of the transition processes underlying IRHI changes such as those relating to mortality. This paper overcomes these limitations by developing alternative longitudinal procedures to analyse the role of health determinants in driving changes in IRHI through both morbidity changes and mortality, with our dynamic modelling framework also serving to identify their contribution to long-run or structural IRHI. The approach is illustrated by an empirical analysis of the causes of the increase in IRHI in Great Britain between 1999 and 2004. PMID:24036199

Can Predictive Modeling Identify Head and Neck Oncology Patients at Risk for Readmission?

PubMed

Manning, Amy M; Casper, Keith A; Peter, Kay St; Wilson, Keith M; Mark, Jonathan R; Collar, Ryan M

2018-05-01

Objective Unplanned readmission within 30 days is a contributor to health care costs in the United States. The use of predictive modeling during hospitalization to identify patients at risk for readmission offers a novel approach to quality improvement and cost reduction. Study Design Two-phase study including retrospective analysis of prospectively collected data followed by prospective longitudinal study. Setting Tertiary academic medical center. Subjects and Methods Prospectively collected data for patients undergoing surgical treatment for head and neck cancer from January 2013 to January 2015 were used to build predictive models for readmission within 30 days of discharge using logistic regression, classification and regression tree (CART) analysis, and random forests. One model (logistic regression) was then placed prospectively into the discharge workflow from March 2016 to May 2016 to determine the model's ability to predict which patients would be readmitted within 30 days. Results In total, 174 admissions had descriptive data. Thirty-two were excluded due to incomplete data. Logistic regression, CART, and random forest predictive models were constructed using the remaining 142 admissions. When applied to 106 consecutive prospective head and neck oncology patients at the time of discharge, the logistic regression model predicted readmissions with a specificity of 94%, a sensitivity of 47%, a negative predictive value of 90%, and a positive predictive value of 62% (odds ratio, 14.9; 95% confidence interval, 4.02-55.45). Conclusion Prospectively collected head and neck cancer databases can be used to develop predictive models that can accurately predict which patients will be readmitted. This offers valuable support for quality improvement initiatives and readmission-related cost reduction in head and neck cancer care.

Kidney function changes with aging in adults: comparison between cross-sectional and longitudinal data analyses in renal function assessment.

PubMed

Chung, Sang M; Lee, David J; Hand, Austin; Young, Philip; Vaidyanathan, Jayabharathi; Sahajwalla, Chandrahas

2015-12-01

The study evaluated whether the renal function decline rate per year with age in adults varies based on two primary statistical analyses: cross-section (CS), using one observation per subject, and longitudinal (LT), using multiple observations per subject over time. A total of 16628 records (3946 subjects; age range 30-92 years) of creatinine clearance and relevant demographic data were used. On average, four samples per subject were collected for up to 2364 days (mean: 793 days). A simple linear regression and random coefficient models were selected for CS and LT analyses, respectively. The renal function decline rates per year were 1.33 and 0.95 ml/min/year for CS and LT analyses, respectively, and were slower when the repeated individual measurements were considered. The study confirms that rates are different based on statistical analyses, and that a statistically robust longitudinal model with a proper sampling design provides reliable individual as well as population estimates of the renal function decline rates per year with age in adults. In conclusion, our findings indicated that one should be cautious in interpreting the renal function decline rate with aging information because its estimation was highly dependent on the statistical analyses. From our analyses, a population longitudinal analysis (e.g. random coefficient model) is recommended if individualization is critical, such as a dose adjustment based on renal function during a chronic therapy. Copyright © 2015 John Wiley & Sons, Ltd.

Social support at work and leisure time and its association with self-rated health and sickness absence.

PubMed

Falkenberg, A; Nyfjäll, M; Hellgren, C; Vingård, E

2012-01-01

The aim of this longitudinal study is to investigate how different aspects of social support at work and in leisure time are associated with self rated health and sickness absence. The 541 participants in the study were representative for a working population in the public sector in Sweden with a majority being woman. Most of the variables were created from data from a questionnaire in March-April 2005. There were four independent variables and two dependent variables. The dependent were based on data from November 2006. A logistic regression model was used for the analysis of associations. A separate model was adapted for each of the explanatory variables for each outcome, which gave five models per independent variable. The study has given a greater awareness of the importance of employees receiving social support, regardless of type of support or from whom the support is coming. Social support has a strong association with SRH in a longitudinal perspective and no association between social support and sickness absence.

Longitudinal Analysis of Gender Differences in Academic Productivity among Medical Faculty across 24 Medical Schools in the United States

PubMed Central

Raj, Anita; Carr, Phyllis L.; Kaplan, Samantha E.; Terrin, Norma; Breeze, Janis L.; Freund, Karen M.

2017-01-01

Purpose This study examines gender differences in academic productivity, as indicated by publications and federal grant funding acquisition, among a longitudinal cohort of medical faculty from 24 medical schools across the United States, 1995 to 2012. Method Data for this research was taken from the National Faculty Study involving a survey with medical faculty recruited from medical schools in 1995, and followed up in 2012. Data included surveys and publication and grant funding databases. Outcomes were number of publications, h-index and principal investigator on a federal grant in the prior two years. Gender differences were assessed using negative binomial regression models for publication and h-index outcomes, and logistic regression for the grant funding outcome; analyses adjusted for race/ethnicity, rank, specialty area and years since first academic appointment. Results Data were available for 1,244 of the 1,275 (98%) subjects eligible for the follow up study. Men were significantly more likely than women to be married/partnered, have children, and hold the rank of professor (P < .0001). Adjusted regression models document that women have a lower rate of publication (relative number = .71; 95% CI = .63, .81; P < .0001) and h-index (relative number = .81; 95% CI = .73, .90; P < .0001) relative to men, though there was no gender difference in grant funding. Conclusions Women faculty acquire federal funding at similar rates as male faculty, yet lag behind in terms of publications and their impact. Medical academia must consider how to help address ongoing gender disparities in publication records. PMID:27276002

The potential of composite cognitive scores for tracking progression in Huntington's disease.

PubMed

Jones, Rebecca; Stout, Julie C; Labuschagne, Izelle; Say, Miranda; Justo, Damian; Coleman, Allison; Dumas, Eve M; Hart, Ellen; Owen, Gail; Durr, Alexandra; Leavitt, Blair R; Roos, Raymund; O'Regan, Alison; Langbehn, Doug; Tabrizi, Sarah J; Frost, Chris

2014-01-01

Composite scores derived from joint statistical modelling of individual risk factors are widely used to identify individuals who are at increased risk of developing disease or of faster disease progression. We investigated the ability of composite measures developed using statistical models to differentiate progressive cognitive deterioration in Huntington's disease (HD) from natural decline in healthy controls. Using longitudinal data from TRACK-HD, the optimal combinations of quantitative cognitive measures to differentiate premanifest and early stage HD individuals respectively from controls was determined using logistic regression. Composite scores were calculated from the parameters of each statistical model. Linear regression models were used to calculate effect sizes (ES) quantifying the difference in longitudinal change over 24 months between premanifest and early stage HD groups respectively and controls. ES for the composites were compared with ES for individual cognitive outcomes and other measures used in HD research. The 0.632 bootstrap was used to eliminate biases which result from developing and testing models in the same sample. In early HD, the composite score from the HD change prediction model produced an ES for difference in rate of 24-month change relative to controls of 1.14 (95% CI: 0.90 to 1.39), larger than the ES for any individual cognitive outcome and UHDRS Total Motor Score and Total Functional Capacity. In addition, this composite gave a statistically significant difference in rate of change in premanifest HD compared to controls over 24-months (ES: 0.24; 95% CI: 0.04 to 0.44), even though none of the individual cognitive outcomes produced statistically significant ES over this period. Composite scores developed using appropriate statistical modelling techniques have the potential to materially reduce required sample sizes for randomised controlled trials.

Height reduction among prenatally exposed atomic-bomb survivors: A longitudinal study of growth

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakashima, Eiji; Funamoto, Sachiyo; Carter, R.L.

Using a random coefficient regression model, sex-specific longitudinal analyses of height were made on 801 (392 male and 409 female) atomic-bomb survivors exposed in utero to detect dose effects on standing height. The data set resulted from repeated measurements of standing height of adolescents (age 10-18 y). The dose effect, if any, was assumed to be linear. Gestational ages at the time of radiation exposure were divided into trimesters. Since an earlier longitudinal data analysis has demonstrated radiation effects on height, the emphasis in this paper is on the interaction between dose and gestational age at exposure and radiation effectsmore » on the age of occurrence of the adolescent growth spurt. For males, a cubic polynomial growth-curve model applied to the data was affected significantly by radiation. The dose by trimester interaction effect was not significant. The onset of adolescent growth spurt was estimated at about 13 y at 0 Gy. There was no effect of radiation on the adolescent growth spurt For females, a quadratic polynomial growth-curve model was fitted to the data. The dose effect was significant, while the dose by trimester interaction was again not significant. 27 refs., 3 figs., 4 tabs.« less

Longitudinal predictors of aerobic performance in adolescent soccer players.

PubMed

Valente-dos-Santos, João; Coelho-e-Silva, Manuel J; Duarte, João; Figueiredo, António J; Liparotti, João R; Sherar, Lauren B; Elferink-Gemser, Marije T; Malina, Robert M

2012-01-01

The importance of aerobic performance in youth soccer is well established. The aim of the present study was to evaluate the contributions of chronological age (CA), skeletal age (SA), body size, and training to the longitudinal development of aerobic performance in youth male soccer players aged 10 to 18 years. Players (n=83) were annually followed up during 5 years, resulting in an average of 4.4 observations per player. Decimal CA was calculated, and SA, stature, body weight, and aerobic performance were measured once per year. Fat-free mass (FFM) was estimated from age- and gender-specific anthropometric formulas, and annual volume training was recorded. After testing for multicollinearity, multilevel regression modeling was used to analyze the longitudinal data aligned by CA and SA (Model 1 and 2, respectively) and to develop aerobic performance scores. The following equations provide estimations of the aerobic performance for young soccer players: ŷ(Model 1 [deviance from the null model =388.50; P<0.01]) =57.75+9.06×centered CA-0.57×centered CA(2)+0.03×annual volume training and ŷ(Model 2 [deviance from the null model=327.98; P<0.01])=13.03+4.04×centered SA-0.12×centered SA(2)+0.99×FFM+0.03×annual volume training. The development of aerobic performance in young soccer players was found to be significantly related to CA, biological development, and volume of training.

Health and social exclusion in older age: evidence from Understanding Society, the UK household longitudinal study.

PubMed

Sacker, Amanda; Ross, Andy; MacLeod, Catherine A; Netuveli, Gopal; Windle, Gill

2017-07-01

Social exclusion of the elderly is a key policy focus but evidence on the processes linking health and social exclusion is hampered by the variety of ways that health is used in social exclusion research. We investigated longitudinal associations between health and social exclusion using an analytical framework that did not conflate them. Data employed in this study came from 4 waves of Understanding Society, the UK Household Longitudinal Study 2009-2013. The sample comprised all adults who took part in all 4 waves, were 65 years or more in Wave 3, and had complete data on our variables of interest for each analysis. We used linear regression to model the relationship between Wave 2/3 social exclusion and Wave1-2 health transitions (N=4312) and logistic regression to model the relationship between Wave2/3 social exclusion and Wave 4 health states, conditional on Wave 3 health (N=4244). There was a dose-response relationship between poor health in Waves 1 and 2 and later social exclusion. Use of a car, mobile phone and the internet moderated the association between poor health and social exclusion. Given the health status in Wave 3, those who were more socially excluded had poorer outcomes on each of the three domains of health in Wave 4. Use of the internet and technology protected older adults in poor health from social exclusion. Age-friendly hardware and software design might have public health benefits. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Functional Logistic Regression Approach to Detecting Gene by Longitudinal Environmental Exposure Interaction in a Case-Control Study

PubMed Central

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-01-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (GxE) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying GxE interactions which may be partly due to limited statistical power and inaccurately measured exposures. While existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes which may modify this association. PMID:25219575

Longitudinal data analysis in support of functional stability concepts for leachate management at closed municipal landfills

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gibbons, Robert D., E-mail: rdg@uchicago.edu; Morris, Jeremy W.F., E-mail: jmorris@geosyntec.com; Prucha, Christopher P., E-mail: cprucha@wm.com

2014-09-15

Highlights: • Longitudinal data analysis using a mixed-effects regression model. • Dataset consisted of a total of 1402 samples from 101 closed municipal landfills. • Target analytes and classes generally showed predictable degradation trends. • Validates historical studies focused on macro organic indicators such as BOD. • BOD can serve as “gateway” indicator for planning leachate management. - Abstract: Landfill functional stability provides a target that supports no environmental threat at the relevant point of exposure in the absence of active control systems. With respect to leachate management, this study investigates “gateway” indicators for functional stability in terms of themore » predictability of leachate characteristics, and thus potential threat to water quality posed by leachate emissions. Historical studies conducted on changes in municipal solid waste (MSW) leachate concentrations over time (longitudinal analysis) have concentrated on indicator compounds, primarily chemical oxygen demand (COD) and biochemical oxygen demand (BOD). However, validation of these studies using an expanded database and larger constituent sets has not been performed. This study evaluated leachate data using a mixed-effects regression model to determine the extent to which leachate constituent degradation can be predicted based on waste age or operational practices. The final dataset analyzed consisted of a total of 1402 samples from 101 MSW landfills. Results from the study indicated that all leachate constituents exhibit a decreasing trend with time in the post-closure period, with 16 of the 25 target analytes and aggregate classes exhibiting a statistically significant trend consistent with well-studied indicators such as BOD. Decreasing trends in BOD concentration after landfill closure can thus be considered representative of trends for many leachate constituents of concern.« less

Functional logistic regression approach to detecting gene by longitudinal environmental exposure interaction in a case-control study.

PubMed

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-11-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (G × E) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying G × E interactions, which may be partly due to limited statistical power and inaccurately measured exposures. Although existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here, we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes that may modify this association. © 2014 Wiley Periodicals, Inc.

Marginalized zero-altered models for longitudinal count data.

PubMed

Tabb, Loni Philip; Tchetgen, Eric J Tchetgen; Wellenius, Greg A; Coull, Brent A

2016-10-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias.

Marginalized zero-altered models for longitudinal count data

PubMed Central

Tabb, Loni Philip; Tchetgen, Eric J. Tchetgen; Wellenius, Greg A.; Coull, Brent A.

2015-01-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias. PMID:27867423

Differences in Causal Estimates from Longitudinal Analyses of Residualized versus Simple Gain Scores: Contrasting Controls for Selection and Regression Artifacts

ERIC Educational Resources Information Center

Larzelere, Robert E.; Ferrer, Emilio; Kuhn, Brett R.; Danelia, Ketevan

2010-01-01

This study estimates the causal effects of six corrective actions for children's problem behaviors, comparing four types of longitudinal analyses that correct for pre-existing differences in a cohort of 1,464 4- and 5-year-olds from Canadian National Longitudinal Survey of Children and Youth (NLSCY) data. Analyses of residualized gain scores found…

An investigation of emotion dynamics in major depressive disorder patients and healthy persons using sparse longitudinal networks.

PubMed

de Vos, Stijn; Wardenaar, Klaas J; Bos, Elisabeth H; Wit, Ernst C; Bouwmans, Mara E J; de Jonge, Peter

2017-01-01

Differences in within-person emotion dynamics may be an important source of heterogeneity in depression. To investigate these dynamics, researchers have previously combined multilevel regression analyses with network representations. However, sparse network methods, specifically developed for longitudinal network analyses, have not been applied. Therefore, this study used this approach to investigate population-level and individual-level emotion dynamics in healthy and depressed persons and compared this method with the multilevel approach. Time-series data were collected in pair-matched healthy persons and major depressive disorder (MDD) patients (n = 54). Seven positive affect (PA) and seven negative affect (NA) items were administered electronically at 90 times (30 days; thrice per day). The population-level (healthy vs. MDD) and individual-level time series were analyzed using a sparse longitudinal network model based on vector autoregression. The population-level model was also estimated with a multilevel approach. Effects of different preprocessing steps were evaluated as well. The characteristics of the longitudinal networks were investigated to gain insight into the emotion dynamics. In the population-level networks, longitudinal network connectivity was strongest in the healthy group, with nodes showing more and stronger longitudinal associations with each other. Individually estimated networks varied strongly across individuals. Individual variations in network connectivity were unrelated to baseline characteristics (depression status, neuroticism, severity). A multilevel approach applied to the same data showed higher connectivity in the MDD group, which seemed partly related to the preprocessing approach. The sparse network approach can be useful for the estimation of networks with multiple nodes, where overparameterization is an issue, and for individual-level networks. However, its current inability to model random effects makes it less useful as a population-level approach in case of large heterogeneity. Different preprocessing strategies appeared to strongly influence the results, complicating inferences about network density.

Causal inference and longitudinal data: a case study of religion and mental health.

PubMed

VanderWeele, Tyler J; Jackson, John W; Li, Shanshan

2016-11-01

We provide an introduction to causal inference with longitudinal data and discuss the complexities of analysis and interpretation when exposures can vary over time. We consider what types of causal questions can be addressed with the standard regression-based analyses and what types of covariate control and control for the prior values of outcome and exposure must be made to reason about causal effects. We also consider newer classes of causal models, including marginal structural models, that can assess questions of the joint effects of time-varying exposures and can take into account feedback between the exposure and outcome over time. Such feedback renders cross-sectional data ineffective for drawing inferences about causation. The challenges are illustrated by analyses concerning potential effects of religious service attendance on depression, in which there may in fact be effects in both directions with service attendance preventing the subsequent depression, but depression itself leading to lower levels of the subsequent religious service attendance. Longitudinal designs, with careful control for prior exposures, outcomes, and confounders, and suitable methodology, will strengthen research on mental health, religion and health, and in the biomedical and social sciences generally.

A Two-Step Approach for Analysis of Nonignorable Missing Outcomes in Longitudinal Regression: an Application to Upstate KIDS Study.

PubMed

Liu, Danping; Yeung, Edwina H; McLain, Alexander C; Xie, Yunlong; Buck Louis, Germaine M; Sundaram, Rajeshwari

2017-09-01

Imperfect follow-up in longitudinal studies commonly leads to missing outcome data that can potentially bias the inference when the missingness is nonignorable; that is, the propensity of missingness depends on missing values in the data. In the Upstate KIDS Study, we seek to determine if the missingness of child development outcomes is nonignorable, and how a simple model assuming ignorable missingness would compare with more complicated models for a nonignorable mechanism. To correct for nonignorable missingness, the shared random effects model (SREM) jointly models the outcome and the missing mechanism. However, the computational complexity and lack of software packages has limited its practical applications. This paper proposes a novel two-step approach to handle nonignorable missing outcomes in generalized linear mixed models. We first analyse the missing mechanism with a generalized linear mixed model and predict values of the random effects; then, the outcome model is fitted adjusting for the predicted random effects to account for heterogeneity in the missingness propensity. Extensive simulation studies suggest that the proposed method is a reliable approximation to SREM, with a much faster computation. The nonignorability of missing data in the Upstate KIDS Study is estimated to be mild to moderate, and the analyses using the two-step approach or SREM are similar to the model assuming ignorable missingness. The two-step approach is a computationally straightforward method that can be conducted as sensitivity analyses in longitudinal studies to examine violations to the ignorable missingness assumption and the implications relative to health outcomes. © 2017 John Wiley & Sons Ltd.

Future Orientation, Social Support, and Psychological Adjustment among Left-behind Children in Rural China: A Longitudinal Study.

PubMed

Su, Shaobing; Li, Xiaoming; Lin, Danhua; Zhu, Maoling

2017-01-01

Existing research has found that parental migration may negatively impact the psychological adjustment of left-behind children. However, limited longitudinal research has examined if and how future orientation (individual protective factor) and social support (contextual protective factor) are associated with the indicators of psychological adjustment (i.e., life satisfaction, school satisfaction, happiness, and loneliness) of left-behind children. In the current longitudinal study, we examined the differences in psychological adjustment between left-behind children and non-left behind children (comparison children) in rural areas, and explored the protective roles of future orientation and social support on the immediate (cross-sectional effects) and subsequent (lagged effects) status of psychological adjustment for both groups of children, respectively. The sample included 897 rural children ( M age = 14.09, SD = 1.40) who participated in two waves of surveys across six months. Among the participants, 227 were left-behind children with two parents migrating, 176 were with one parent migrating, and 485 were comparison children. Results showed that, (1) left-behind children reported lower levels of life satisfaction, school satisfaction, and happiness, as well as a higher level of loneliness in both waves; (2) After controlling for several demographics and characteristics of parental migration among left-behind children, future orientation significantly predicted life satisfaction, school satisfaction, and happiness in both cross-sectional and longitudinal regression models, as well as loneliness in the longitudinal regression analysis. Social support predicted immediate life satisfaction, school satisfaction, and happiness, as well as subsequent school satisfaction. Similar to left-behind children, comparison children who reported higher scores in future orientation, especially future expectation, were likely to have higher scores in most indicators of psychological adjustment measured at the same time and subsequently. However, social support seemed not exhibit as important in the immediate status of psychological adjustment of comparison children as that of left-behind children. Findings, implications, and limitations of the present study were discussed.

Threshold regression to accommodate a censored covariate.

PubMed

Qian, Jing; Chiou, Sy Han; Maye, Jacqueline E; Atem, Folefac; Johnson, Keith A; Betensky, Rebecca A

2018-06-22

In several common study designs, regression modeling is complicated by the presence of censored covariates. Examples of such covariates include maternal age of onset of dementia that may be right censored in an Alzheimer's amyloid imaging study of healthy subjects, metabolite measurements that are subject to limit of detection censoring in a case-control study of cardiovascular disease, and progressive biomarkers whose baseline values are of interest, but are measured post-baseline in longitudinal neuropsychological studies of Alzheimer's disease. We propose threshold regression approaches for linear regression models with a covariate that is subject to random censoring. Threshold regression methods allow for immediate testing of the significance of the effect of a censored covariate. In addition, they provide for unbiased estimation of the regression coefficient of the censored covariate. We derive the asymptotic properties of the resulting estimators under mild regularity conditions. Simulations demonstrate that the proposed estimators have good finite-sample performance, and often offer improved efficiency over existing methods. We also derive a principled method for selection of the threshold. We illustrate the approach in application to an Alzheimer's disease study that investigated brain amyloid levels in older individuals, as measured through positron emission tomography scans, as a function of maternal age of dementia onset, with adjustment for other covariates. We have developed an R package, censCov, for implementation of our method, available at CRAN. © 2018, The International Biometric Society.

Regression to the mean and changes in risk behavior following study enrollment in a cohort of U.S. women at risk for HIV.

PubMed

Hughes, James P; Haley, Danielle F; Frew, Paula M; Golin, Carol E; Adimora, Adaora A; Kuo, Irene; Justman, Jessica; Soto-Torres, Lydia; Wang, Jing; Hodder, Sally

2015-06-01

Reductions in risk behaviors are common following enrollment in human immunodeficiency virus (HIV) prevention studies. We develop methods to quantify the proportion of change in risk behaviors that can be attributed to regression to the mean versus study participation and other factors. A novel model that incorporates both regression to the mean and study participation effects is developed for binary measures. The model is used to estimate the proportion of change in the prevalence of "unprotected sex in the past 6 months" that can be attributed to study participation versus regression to the mean in a longitudinal cohort of women at risk for HIV infection who were recruited from ten U.S. communities with high rates of HIV and poverty. HIV risk behaviors were evaluated using audio computer-assisted self-interviews at baseline and every 6 months for up to 12 months. The prevalence of "unprotected sex in the past 6 months" declined from 96% at baseline to 77% at 12 months. However, this change could be almost completely explained by regression to the mean. Analyses that examine changes over time in cohorts selected for high- or low- risk behaviors should account for regression to the mean effects. Copyright © 2015 Elsevier Inc. All rights reserved.

Dental caries clusters among adolescents.

PubMed

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 were useful means in presenting longitudinal caries data. Findings suggest that high caries incidence in adolescence is associated with lower maternal educational level, less frequent tooth brushing, lower 100% juice consumption and being female. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Job Strain and Tobacco Smoking: An Individual-Participant Data Meta-Analysis of 166 130 Adults in 15 European Studies

PubMed Central

Heikkilä, Katriina; Nyberg, Solja T.; Fransson, Eleonor I.; Alfredsson, Lars; De Bacquer, Dirk; Bjorner, Jakob B.; Bonenfant, Sébastien; Borritz, Marianne; Burr, Hermann; Clays, Els; Casini, Annalisa; Dragano, Nico; Erbel, Raimund; Geuskens, Goedele A.; Goldberg, Marcel; Hooftman, Wendela E.; Houtman, Irene L.; Joensuu, Matti; Jöckel, Karl-Heinz; Kittel, France; Knutsson, Anders; Koskenvuo, Markku; Koskinen, Aki; Kouvonen, Anne; Leineweber, Constanze; Lunau, Thorsten; Madsen, Ida E. H.; Hanson, Linda L. Magnusson; Marmot, Michael G.; Nielsen, Martin L.; Nordin, Maria; Pentti, Jaana; Salo, Paula; Rugulies, Reiner; Steptoe, Andrew; Siegrist, Johannes; Suominen, Sakari; Vahtera, Jussi; Virtanen, Marianna; Väänänen, Ari; Westerholm, Peter; Westerlund, Hugo; Zins, Marie; Theorell, Töres; Hamer, Mark; Ferrie, Jane E.; Singh-Manoux, Archana; Batty, G. David; Kivimäki, Mika

2012-01-01

Background Tobacco smoking is a major contributor to the public health burden and healthcare costs worldwide, but the determinants of smoking behaviours are poorly understood. We conducted a large individual-participant meta-analysis to examine the extent to which work-related stress, operationalised as job strain, is associated with tobacco smoking in working adults. Methodology and Principal Findings We analysed cross-sectional data from 15 European studies comprising 166 130 participants. Longitudinal data from six studies were used. Job strain and smoking were self-reported. Smoking was harmonised into three categories never, ex- and current. We modelled the cross-sectional associations using logistic regression and the results pooled in random effects meta-analyses. Mixed effects logistic regression was used to examine longitudinal associations. Of the 166 130 participants, 17% reported job strain, 42% were never smokers, 33% ex-smokers and 25% current smokers. In the analyses of the cross-sectional data, current smokers had higher odds of job strain than never-smokers (age, sex and socioeconomic position-adjusted odds ratio: 1.11, 95% confidence interval: 1.03, 1.18). Current smokers with job strain smoked, on average, three cigarettes per week more than current smokers without job strain. In the analyses of longitudinal data (1 to 9 years of follow-up), there was no clear evidence for longitudinal associations between job strain and taking up or quitting smoking. Conclusions Our findings show that smokers are slightly more likely than non-smokers to report work-related stress. In addition, smokers who reported work stress smoked, on average, slightly more cigarettes than stress-free smokers. PMID:22792154

Hearing Impairment and Incident Dementia: Findings from the English Longitudinal Study of Ageing.

PubMed

Davies, Hilary R; Cadar, Dorina; Herbert, Annie; Orrell, Martin; Steptoe, Andrew

2017-09-01

To determine whether hearing loss is associated with incident physician-diagnosed dementia in a representative sample. Retrospective cohort study. English Longitudinal Study of Ageing. Adults aged 50 and older. Cross-sectional associations between self-reported (n = 7,865) and objective hearing measures (n = 6,902) and dementia were examined using multinomial-logistic regression. The longitudinal association between self-reported hearing at Wave 2 (2004/05) and cumulative physician-diagnosed dementia up to Wave 7 (2014/15) was modelled using Cox proportional hazards regression. After adjustment for potential confounders, in cross-sectional analysis, participants who had self-reported or objective moderate and poor hearing were more likely to have a dementia diagnosis than those with normal hearing (self-reported: odds ratio OR = 1.6, 95% CI = 1.1-2.4 moderate hearing; OR = 2.6, 95% CI = 1.7-3.9 poor hearing, objective: OR = 1.6, 95% CI = 1.0-2.8 moderate hearing; OR = 4.4, 95% CI = 1.9-9.9 poor hearing). Longitudinally, the hazard of developing dementia was 1.4 (95% CI = 1.0-1.9) times as high in individuals who reported moderate hearing and 1.6 (95% CI = 1.1-2.0) times as high in those who reported poor hearing. Older adults with hearing loss are at greater risk of dementia than those with normal hearing. These findings are consistent with the rationale that correction of hearing loss could help delay the onset of dementia, or that hearing loss itself could serve as a risk indicator for cognitive decline. © 2017, The Authors. The Journal of the American Geriatrics Society published by Wiley Periodicals, Inc. on behalf of The American Geriatrics Society.

Testing healthy immigrant effects among late life immigrants in the United States: using multiple indicators.

PubMed

Choi, Sunha H

2012-04-01

This study tested a healthy immigrant effect (HIE) and postimmigration health status changes among late life immigrants. Using three waves of the Second Longitudinal Study of Aging (1994-2000) and the linked mortality file through 2006, this study compared (a) chronic health conditions, (b) longitudinal trajectories of self-rated health, (c) longitudinal trajectories of functional impairments, and (d) mortality between three groups (age 70+): (i) late life immigrants with less than 15 years in the United States (n = 133), (ii) longer term immigrants (n = 672), and (iii) U.S.-born individuals (n = 8,642). Logistic and Poisson regression, hierarchical generalized linear modeling, and survival analyses were conducted. Late life immigrants were less likely to suffer from cancer, had lower numbers of chronic conditions at baseline, and displayed lower hazards of mortality during the 12-year follow-up. However, their self-rated health and functional status were worse than those of their counterparts over time. A HIE was only partially supported among older adults.

Child, Parent, and Peer Predictors of Early-Onset Substance Use: A Multisite Longitudinal Study

PubMed Central

Kaplow, Julie B.; Curran, Patrick J.; Dodge, Kenneth A.

2009-01-01

The purpose of this study was to identify kindergarten-age predictors of early-onset substance use from demographic, environmental, parenting, child psychological, behavioral, and social functioning domains. Data from a longitudinal study of 295 children were gathered using multiple-assessment methods and multiple informants in kindergarten and 1st grade. Annual assessments at ages 10, 11, and 12 reflected that 21% of children reported having initiated substance use by age 12. Results from longitudinal logistic regression models indicated that risk factors at kindergarten include being male, having a parent who abused substances, lower levels of parental verbal reasoning, higher levels of overactivity, more thought problems, and more social problem solving skills deficits. Children with no risk factors had less than a 10% chance of initiating substance use by age 12, whereas children with 2 or more risk factors had greater than a 50% chance of initiating substance use. Implications for typology, etiology, and prevention are discussed. PMID:12041707

Differential and Long-Term Language Impact on Math

ERIC Educational Resources Information Center

Chen, Fang; Chalhoub-Deville, Micheline

2016-01-01

Literature provides consistent evidence that there is a strong relationship between language proficiency and math achievement. However, research results show conflicts supporting either an increasing or a decreasing longitudinal relationship between the two. This study explored a longitudinal data and adopted quantile regression analyses to…

Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

PubMed

Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

2016-09-01

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion. © 2016 Poultry Science Association Inc.

Do repeated assessments of performance status improve predictions for risk of death among patients with cancer? A population-based cohort study.

PubMed

Su, Jiandong; Barbera, Lisa; Sutradhar, Rinku

2015-06-01

Prior work has utilized longitudinal information on performance status to demonstrate its association with risk of death among cancer patients; however, no study has assessed whether such longitudinal information improves the predictions for risk of death. To examine whether the use of repeated performance status assessments improve predictions for risk of death compared to using only performance status assessment at the time of cancer diagnosis. This was a population-based longitudinal study of adult outpatients who had a cancer diagnosis and had at least one assessment of performance status. To account for each patient's changing performance status over time, we implemented a Cox model with a time-varying covariate for performance status. This model was compared to a Cox model using only a time-fixed (baseline) covariate for performance status. The regression coefficients of each model were derived based on a randomly selected 60% of patients, and then, the predictive ability of each model was assessed via concordance probabilities when applied to the remaining 40% of patients. Our study consisted of 15,487 cancer patients with over 53,000 performance status assessments. The utilization of repeated performance status assessments improved predictions for risk of death compared to using only the performance status assessment taken at diagnosis. When studying the hazard of death among patients with cancer, if available, researchers should incorporate changing information on performance status scores, instead of simply baseline information on performance status. © The Author(s) 2015.

Ready-to-use supplementary food increases fat mass and BMI in Haitian school-aged children.

PubMed

Iannotti, Lora L; Henretty, Nicole M; Delnatus, Jacques Raymond; Previl, Windy; Stehl, Tom; Vorkoper, Susan; Bodden, Jaime; Maust, Amanda; Smidt, Rachel; Nash, Marilyn L; Tamimie, Courtney A; Owen, Bridget C; Wolff, Patricia B

2015-04-01

In Haiti and other countries, large-scale investments in school feeding programs have been made with marginal evidence of nutrition outcomes. We aimed to examine the effectiveness of a fortified ready-to-use supplementary food (RUSF), Mamba, on reduced anemia and improved body composition in school-aged children compared to an unfortified cereal bar, Tablet Yo, and control groups. A cluster, randomized trial with children ages 3-13 y (n = 1167) was conducted in the north of Haiti. Six schools were matched and randomized to the control group, Tablet Yo group (42 g, 165 kcal), or Mamba group (50 g, 260 kcal, and >75% of the RDA for critical micronutrients). Children in the supplementation groups received the snack daily for 100 d, and all were followed longitudinally for hemoglobin concentrations, anthropometry, and bioelectrical impedance measures: baseline (December 2012), midline (March 2013), and endline (June 2013). Parent surveys were conducted at baseline and endline to examine secondary outcomes of morbidities and dietary intakes. Longitudinal regression modeling using generalized least squares and logit with random effects tested the main effects. At baseline,14.0% of children were stunted, 14.5% underweight, 9.1% thin, and 73% anemic. Fat mass percentage (mean ± SD) was 8.1% ± 4.3% for boys and 12.5% ± 4.4% for girls. In longitudinal modeling, Mamba supplementation increased body mass index z score (regression coefficient ± SEE) 0.25 ± 0.06, fat mass 0.45 ± 0.14 kg, and percentage fat mass 1.28% ± 0.27% compared with control at each time point (P < 0.001). Among boys, Mamba increased fat mass (regression coefficient ± SEE) 0.73 ± 0.19 kg and fat-free mass 0.62 ± 0.34 kg compared with control (P < 0.001). Mamba reduced the odds of developing anemia by 28% compared to control (adjusted OR: 0.72; 95% CI: 0.57, 0.91; P < 0.001). No treatment effect was found for hemoglobin concentration. To our knowledge, this is the first study to give evidence of body composition effects from an RUSF in school-aged children. © 2015 American Society for Nutrition.

Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models

PubMed Central

Liu, Fengchen; Porco, Travis C.; Amza, Abdou; Kadri, Boubacar; Nassirou, Baido; West, Sheila K.; Bailey, Robin L.; Keenan, Jeremy D.; Solomon, Anthony W.; Emerson, Paul M.; Gambhir, Manoj; Lietman, Thomas M.

2015-01-01

Background Trachoma programs rely on guidelines made in large part using expert opinion of what will happen with and without intervention. Large community-randomized trials offer an opportunity to actually compare forecasting methods in a masked fashion. Methods The Program for the Rapid Elimination of Trachoma trials estimated longitudinal prevalence of ocular chlamydial infection from 24 communities treated annually with mass azithromycin. Given antibiotic coverage and biannual assessments from baseline through 30 months, forecasts of the prevalence of infection in each of the 24 communities at 36 months were made by three methods: the sum of 15 experts’ opinion, statistical regression of the square-root-transformed prevalence, and a stochastic hidden Markov model of infection transmission (Susceptible-Infectious-Susceptible, or SIS model). All forecasters were masked to the 36-month results and to the other forecasts. Forecasts of the 24 communities were scored by the likelihood of the observed results and compared using Wilcoxon’s signed-rank statistic. Findings Regression and SIS hidden Markov models had significantly better likelihood than community expert opinion (p = 0.004 and p = 0.01, respectively). All forecasts scored better when perturbed to decrease Fisher’s information. Each individual expert’s forecast was poorer than the sum of experts. Interpretation Regression and SIS models performed significantly better than expert opinion, although all forecasts were overly confident. Further model refinements may score better, although would need to be tested and compared in new masked studies. Construction of guidelines that rely on forecasting future prevalence could consider use of mathematical and statistical models. PMID:26302380

Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models.

PubMed

Liu, Fengchen; Porco, Travis C; Amza, Abdou; Kadri, Boubacar; Nassirou, Baido; West, Sheila K; Bailey, Robin L; Keenan, Jeremy D; Solomon, Anthony W; Emerson, Paul M; Gambhir, Manoj; Lietman, Thomas M

2015-08-01

Trachoma programs rely on guidelines made in large part using expert opinion of what will happen with and without intervention. Large community-randomized trials offer an opportunity to actually compare forecasting methods in a masked fashion. The Program for the Rapid Elimination of Trachoma trials estimated longitudinal prevalence of ocular chlamydial infection from 24 communities treated annually with mass azithromycin. Given antibiotic coverage and biannual assessments from baseline through 30 months, forecasts of the prevalence of infection in each of the 24 communities at 36 months were made by three methods: the sum of 15 experts' opinion, statistical regression of the square-root-transformed prevalence, and a stochastic hidden Markov model of infection transmission (Susceptible-Infectious-Susceptible, or SIS model). All forecasters were masked to the 36-month results and to the other forecasts. Forecasts of the 24 communities were scored by the likelihood of the observed results and compared using Wilcoxon's signed-rank statistic. Regression and SIS hidden Markov models had significantly better likelihood than community expert opinion (p = 0.004 and p = 0.01, respectively). All forecasts scored better when perturbed to decrease Fisher's information. Each individual expert's forecast was poorer than the sum of experts. Regression and SIS models performed significantly better than expert opinion, although all forecasts were overly confident. Further model refinements may score better, although would need to be tested and compared in new masked studies. Construction of guidelines that rely on forecasting future prevalence could consider use of mathematical and statistical models. Clinicaltrials.gov NCT00792922.

Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets.

PubMed

Gruber, Susan; Logan, Roger W; Jarrín, Inmaculada; Monge, Susana; Hernán, Miguel A

2015-01-15

Inverse probability weights used to fit marginal structural models are typically estimated using logistic regression. However, a data-adaptive procedure may be able to better exploit information available in measured covariates. By combining predictions from multiple algorithms, ensemble learning offers an alternative to logistic regression modeling to further reduce bias in estimated marginal structural model parameters. We describe the application of two ensemble learning approaches to estimating stabilized weights: super learning (SL), an ensemble machine learning approach that relies on V-fold cross validation, and an ensemble learner (EL) that creates a single partition of the data into training and validation sets. Longitudinal data from two multicenter cohort studies in Spain (CoRIS and CoRIS-MD) were analyzed to estimate the mortality hazard ratio for initiation versus no initiation of combined antiretroviral therapy among HIV positive subjects. Both ensemble approaches produced hazard ratio estimates further away from the null, and with tighter confidence intervals, than logistic regression modeling. Computation time for EL was less than half that of SL. We conclude that ensemble learning using a library of diverse candidate algorithms offers an alternative to parametric modeling of inverse probability weights when fitting marginal structural models. With large datasets, EL provides a rich search over the solution space in less time than SL with comparable results. Copyright © 2014 John Wiley & Sons, Ltd.

Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets

PubMed Central

Gruber, Susan; Logan, Roger W.; Jarrín, Inmaculada; Monge, Susana; Hernán, Miguel A.

2014-01-01

Inverse probability weights used to fit marginal structural models are typically estimated using logistic regression. However a data-adaptive procedure may be able to better exploit information available in measured covariates. By combining predictions from multiple algorithms, ensemble learning offers an alternative to logistic regression modeling to further reduce bias in estimated marginal structural model parameters. We describe the application of two ensemble learning approaches to estimating stabilized weights: super learning (SL), an ensemble machine learning approach that relies on V -fold cross validation, and an ensemble learner (EL) that creates a single partition of the data into training and validation sets. Longitudinal data from two multicenter cohort studies in Spain (CoRIS and CoRIS-MD) were analyzed to estimate the mortality hazard ratio for initiation versus no initiation of combined antiretroviral therapy among HIV positive subjects. Both ensemble approaches produced hazard ratio estimates further away from the null, and with tighter confidence intervals, than logistic regression modeling. Computation time for EL was less than half that of SL. We conclude that ensemble learning using a library of diverse candidate algorithms offers an alternative to parametric modeling of inverse probability weights when fitting marginal structural models. With large datasets, EL provides a rich search over the solution space in less time than SL with comparable results. PMID:25316152

Clinical Pharmacology Quality Assurance (CPQA) Program: Models for Longitudinal Analysis of Antiretroviral (ARV) Proficiency Testing for International Laboratories

PubMed Central

DiFrancesco, Robin; Rosenkranz, Susan L.; Taylor, Charlene R.; Pande, Poonam G.; Siminski, Suzanne M.; Jenny, Richard W.; Morse, Gene D.

2013-01-01

Among National Institutes of Health (NIH) HIV Research Networks conducting multicenter trials, samples from protocols that span several years are analyzed at multiple clinical pharmacology laboratories (CPLs) for multiple antiretrovirals (ARV). Drug assay data are, in turn, entered into study-specific datasets that are used for pharmacokinetic analyses, merged to conduct cross-protocol pharmacokinetic analysis and integrated with pharmacogenomics research to investigate pharmacokinetic-pharmacogenetic associations. The CPLs participate in a semi-annual proficiency testing (PT) program implemented by the Clinical Pharmacology Quality Assurance (CPQA) program. Using results from multiple PT rounds, longitudinal analyses of recovery are reflective of accuracy and precision within/across laboratories. The objectives of this longitudinal analysis of PT across multiple CPLs were to develop and test statistical models that longitudinally: (1)assess the precision and accuracy of concentrations reported by individual CPLs; (2)determine factors associated with round-specific and long-term assay accuracy, precision and bias using a new regression model. A measure of absolute recovery is explored as a simultaneous measure of accuracy and precision. Overall, the analysis outcomes assured 97% accuracy (±20% of the final target concentration of all (21)drug concentration results reported for clinical trial samples by multiple CPLs).Using the CLIA acceptance of meeting criteria for ≥2/3 consecutive rounds, all ten laboratories that participated in three or more rounds per analyte maintained CLIA proficiency. Significant associations were present between magnitude of error and CPL (Kruskal Wallis [KW]p<0.001), and ARV (KW p<0.001). PMID:24052065

Clinical pharmacology quality assurance program: models for longitudinal analysis of antiretroviral proficiency testing for international laboratories.

PubMed

DiFrancesco, Robin; Rosenkranz, Susan L; Taylor, Charlene R; Pande, Poonam G; Siminski, Suzanne M; Jenny, Richard W; Morse, Gene D

2013-10-01

Among National Institutes of Health HIV Research Networks conducting multicenter trials, samples from protocols that span several years are analyzed at multiple clinical pharmacology laboratories (CPLs) for multiple antiretrovirals. Drug assay data are, in turn, entered into study-specific data sets that are used for pharmacokinetic analyses, merged to conduct cross-protocol pharmacokinetic analysis, and integrated with pharmacogenomics research to investigate pharmacokinetic-pharmacogenetic associations. The CPLs participate in a semiannual proficiency testing (PT) program implemented by the Clinical Pharmacology Quality Assurance program. Using results from multiple PT rounds, longitudinal analyses of recovery are reflective of accuracy and precision within/across laboratories. The objectives of this longitudinal analysis of PT across multiple CPLs were to develop and test statistical models that longitudinally: (1) assess the precision and accuracy of concentrations reported by individual CPLs and (2) determine factors associated with round-specific and long-term assay accuracy, precision, and bias using a new regression model. A measure of absolute recovery is explored as a simultaneous measure of accuracy and precision. Overall, the analysis outcomes assured 97% accuracy (±20% of the final target concentration of all (21) drug concentration results reported for clinical trial samples by multiple CPLs). Using the Clinical Laboratory Improvement Act acceptance of meeting criteria for ≥2/3 consecutive rounds, all 10 laboratories that participated in 3 or more rounds per analyte maintained Clinical Laboratory Improvement Act proficiency. Significant associations were present between magnitude of error and CPL (Kruskal-Wallis P < 0.001) and antiretroviral (Kruskal-Wallis P < 0.001).

A comparison of multiple imputation methods for incomplete longitudinal binary data.

PubMed

Yamaguchi, Yusuke; Misumi, Toshihiro; Maruo, Kazushi

2018-01-01

Longitudinal binary data are commonly encountered in clinical trials. Multiple imputation is an approach for getting a valid estimation of treatment effects under an assumption of missing at random mechanism. Although there are a variety of multiple imputation methods for the longitudinal binary data, a limited number of researches have reported on relative performances of the methods. Moreover, when focusing on the treatment effect throughout a period that has often been used in clinical evaluations of specific disease areas, no definite investigations comparing the methods have been available. We conducted an extensive simulation study to examine comparative performances of six multiple imputation methods available in the SAS MI procedure for longitudinal binary data, where two endpoints of responder rates at a specified time point and throughout a period were assessed. The simulation study suggested that results from naive approaches of a single imputation with non-responders and a complete case analysis could be very sensitive against missing data. The multiple imputation methods using a monotone method and a full conditional specification with a logistic regression imputation model were recommended for obtaining unbiased and robust estimations of the treatment effect. The methods were illustrated with data from a mental health research.

Parent and child cigarette use: a longitudinal, multigenerational study.

PubMed

Vuolo, Mike; Staff, Jeremy

2013-09-01

Using longitudinal data from the multigenerational Youth Development Study (YDS), this article documents how parents' long-term smoking trajectories are associated with adolescent children's likelihood of smoking. Prospective data from the parents (from age 14-38 years) enable unique comparisons of the parents' and children's smoking behavior, as well as that of siblings. Smoking trajectories are constructed using latent class analysis for the original YDS cohort (n = 1010). Multigenerational longitudinal data from 214 parents and 314 offspring ages 11 years and older are then analyzed by using logistic regression with cluster-corrected SEs. Four latent smoking trajectories emerged among the original cohort: stable nonsmokers (54%), early-onset light smokers who quit/reduce (16%), late-onset persistent smokers (14%), and early-onset persistent heavy smokers (16%). Although 8% of children of stable nonsmokers smoked in the last year, the other groups' children had much higher percentages, ranging from 23% to 29%. Multivariate logistic regression models confirm that these significant differences were robust to the inclusion of myriad child- and parent-level measures (for which child age and grade point average [GPA] are significant predictors). Older sibling smoking, however, mediated the link between parental heavy smoking and child smoking. Even in an era of declining rates of teenage cigarette use in the United States, children of current and former smokers face an elevated risk of smoking. Prevention efforts to weaken intergenerational associations should consider parents' long-term cigarette use, as well as the smoking behavior of older siblings in the household.

Entry into romantic partnership is associated with obesity.

PubMed

The, Natalie S; Gordon-Larsen, Penny

2009-07-01

BMI is highly correlated between spouses; however, less is understood about the underlying mechanism(s) by which the development of obesity in one individual increases the risk of obesity in his/her spouse. The objective of this study is to investigate whether romantic partnership and duration of cohabitation are related to incident obesity and obesity-promoting behaviors. We used two data sets from the National Longitudinal Study of Adolescent Health: (i) 6,949 US adolescents (wave II, 1996) followed into adulthood (wave III, 2001-2002) and (ii) 1,293 dating, cohabiting, and married romantic couples from wave III, including measured anthropometry and self-report behavior data. In the longitudinal cohort, we used sex-stratified logistic regression models to examine the risk of incident obesity by longitudinal romantic relationship status and duration of time spent living with a romantic partner. In the Couples Sample, we used multinomial logistic regression to predict concordance in outcomes: obesity, moderate-to-vigorous physical activity, and screen time by romantic partnership and duration of time living with a romantic partner. Individuals who transitioned from single/dating to cohabiting or married were more likely to become obese than those who were dating at both waves. Partner concordance for negative, obesity-related behaviors was strongest for married couples and couples who lived together > or =2 years. The shared household environment may increase the likelihood of becoming obese, influence partner concordance, and may be an important target for obesity intervention.

Neuropsychometric tests in cross sectional and longitudinal studies - a regression analysis of ADAS - cog, SKT and MMSE.

PubMed

Ihl, R; Grass-Kapanke, B; Jänner, M; Weyer, G

1999-11-01

In clinical and drug studies, different neuropsychometric tests are used. So far, no empirical data have been published to compare studies using different tests. The purpose of this study was to calculate a regression formula allowing a comparison of cross-sectional and longitudinal data from three neuropsychometric tests that are frequently used in drug studies (Alzheimer's Disease Assessment Scale, ADAS-cog; Syndrom Kurz Test, SKT; Mini Mental State Examination, MMSE). 177 patients with dementia according to ICD10 criteria were studied for the cross sectional and 61 for the longitudinal analysis. Correlations and linear regressions were calculated between tests. Significance was proven with ANOVA and t-tests using the SPSS statistical package. Significant Spearman correlations and slopes in the regression occurred in the cross sectional analysis (ADAS-cog-SKT r(s) = 0.77, slope = 0.45, SKT-ADAS-cog slope = 1.3, r2 = 0.59; ADAS-cog-MMSE r2 = 0.76, slope = -0.42, MMSE-ADAS-cog slope = -1.5, r2 = 0.64; MMSE-SKT r(s) = -0.79, slope = -0.87, SKT-MMSE slope = -0.71, r2 = 0.62; p<0.001 after Bonferroni correction; N = 177) and in the longitudinal analysis (SKT-ADAS-cog, r(s) = 0.48, slope = 0.69, ADAS-cog-SKT slope = 0.69, p<0.001, r2 = 0.32, MMSE-SKT, r(s) = 0.44, slope = -0.41, SKT-MMSE, slope = -0.55, p<0.001, r2 = 0.21). The results allow calculation of ADAS-scores when SKT scores are given, and vice versa. In longitudinal studies or in the course of the disease, scores assessed with the ADAS-cog and the SKT may now be statistically compared. In all comparisons, bottom and ceiling effects of the tests have to be taken into account.

MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors.

PubMed

Hedeker, D; Gibbons, R D

1996-05-01

MIXREG is a program that provides estimates for a mixed-effects regression model (MRM) for normally-distributed response data including autocorrelated errors. This model can be used for analysis of unbalanced longitudinal data, where individuals may be measured at a different number of timepoints, or even at different timepoints. Autocorrelated errors of a general form or following an AR(1), MA(1), or ARMA(1,1) form are allowable. This model can also be used for analysis of clustered data, where the mixed-effects model assumes data within clusters are dependent. The degree of dependency is estimated jointly with estimates of the usual model parameters, thus adjusting for clustering. MIXREG uses maximum marginal likelihood estimation, utilizing both the EM algorithm and a Fisher-scoring solution. For the scoring solution, the covariance matrix of the random effects is expressed in its Gaussian decomposition, and the diagonal matrix reparameterized using the exponential transformation. Estimation of the individual random effects is accomplished using an empirical Bayes approach. Examples illustrating usage and features of MIXREG are provided.

VARIABLE SELECTION FOR REGRESSION MODELS WITH MISSING DATA

PubMed Central

Garcia, Ramon I.; Ibrahim, Joseph G.; Zhu, Hongtu

2009-01-01

We consider the variable selection problem for a class of statistical models with missing data, including missing covariate and/or response data. We investigate the smoothly clipped absolute deviation penalty (SCAD) and adaptive LASSO and propose a unified model selection and estimation procedure for use in the presence of missing data. We develop a computationally attractive algorithm for simultaneously optimizing the penalized likelihood function and estimating the penalty parameters. Particularly, we propose to use a model selection criterion, called the ICQ statistic, for selecting the penalty parameters. We show that the variable selection procedure based on ICQ automatically and consistently selects the important covariates and leads to efficient estimates with oracle properties. The methodology is very general and can be applied to numerous situations involving missing data, from covariates missing at random in arbitrary regression models to nonignorably missing longitudinal responses and/or covariates. Simulations are given to demonstrate the methodology and examine the finite sample performance of the variable selection procedures. Melanoma data from a cancer clinical trial is presented to illustrate the proposed methodology. PMID:20336190

Advanced Issues in Propensity Scores: Longitudinal and Missing Data

ERIC Educational Resources Information Center

Kupzyk, Kevin A.; Beal, Sarah J.

2017-01-01

In order to investigate causality in situations where random assignment is not possible, propensity scores can be used in regression adjustment, stratification, inverse-probability treatment weighting, or matching. The basic concepts behind propensity scores have been extensively described. When data are longitudinal or missing, the estimation and…

A longitudinal analysis of the influence of the neighborhood built environment on walking for transportation: the RESIDE study.

PubMed

Knuiman, Matthew W; Christian, Hayley E; Divitini, Mark L; Foster, Sarah A; Bull, Fiona C; Badland, Hannah M; Giles-Corti, Billie

2014-09-01

The purpose of the present analysis was to use longitudinal data collected over 7 years (from 4 surveys) in the Residential Environments (RESIDE) Study (Perth, Australia, 2003-2012) to more carefully examine the relationship of neighborhood walkability and destination accessibility with walking for transportation that has been seen in many cross-sectional studies. We compared effect estimates from 3 types of logistic regression models: 2 that utilize all available data (a population marginal model and a subject-level mixed model) and a third subject-level conditional model that exclusively uses within-person longitudinal evidence. The results support the evidence that neighborhood walkability (especially land-use mix and street connectivity), local access to public transit stops, and variety in the types of local destinations are important determinants of walking for transportation. The similarity of subject-level effect estimates from logistic mixed models and those from conditional logistic models indicates that there is little or no bias from uncontrolled time-constant residential preference (self-selection) factors; however, confounding by uncontrolled time-varying factors, such as health status, remains a possibility. These findings provide policy makers and urban planners with further evidence that certain features of the built environment may be important in the design of neighborhoods to increase walking for transportation and meet the health needs of residents. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Bumps in river profiles: uncertainty assessment and smoothing using quantile regression techniques

NASA Astrophysics Data System (ADS)

Schwanghart, Wolfgang; Scherler, Dirk

2017-12-01

The analysis of longitudinal river profiles is an important tool for studying landscape evolution. However, characterizing river profiles based on digital elevation models (DEMs) suffers from errors and artifacts that particularly prevail along valley bottoms. The aim of this study is to characterize uncertainties that arise from the analysis of river profiles derived from different, near-globally available DEMs. We devised new algorithms - quantile carving and the CRS algorithm - that rely on quantile regression to enable hydrological correction and the uncertainty quantification of river profiles. We find that globally available DEMs commonly overestimate river elevations in steep topography. The distributions of elevation errors become increasingly wider and right skewed if adjacent hillslope gradients are steep. Our analysis indicates that the AW3D DEM has the highest precision and lowest bias for the analysis of river profiles in mountainous topography. The new 12 m resolution TanDEM-X DEM has a very low precision, most likely due to the combined effect of steep valley walls and the presence of water surfaces in valley bottoms. Compared to the conventional approaches of carving and filling, we find that our new approach is able to reduce the elevation bias and errors in longitudinal river profiles.

Vitamin D and Male Sexual Function: A Transversal and Longitudinal Study.

PubMed

Tirabassi, Giacomo; Sudano, Maurizio; Salvio, Gianmaria; Cutini, Melissa; Muscogiuri, Giovanna; Corona, Giovanni; Balercia, Giancarlo

2018-01-01

The effects of vitamin D on sexual function are very unclear. Therefore, we aimed at evaluating the possible association between vitamin D and sexual function and at assessing the influence of vitamin D administration on sexual function. We retrospectively studied 114 men by evaluating clinical, biochemical, and sexual parameters. A subsample ( n = 41) was also studied longitudinally before and after vitamin D replacement therapy. In the whole sample, after performing logistic regression models, higher levels of 25(OH) vitamin D were significantly associated with high values of total testosterone and of all the International Index of Erectile Function (IIEF) questionnaire parameters. On the other hand, higher levels of total testosterone were positively and significantly associated with high levels of erectile function and IIEF total score. After vitamin D replacement therapy, total and free testosterone increased and erectile function improved, whereas other sexual parameters did not change significantly. At logistic regression analysis, higher levels of vitamin D increase (Δ-) were significantly associated with high values of Δ-erectile function after adjustment for Δ-testosterone. Vitamin D is important for the wellness of male sexual function, and vitamin D administration improves sexual function.

The Categorical Stability of Gambling Motives Among Community-Recruited Gamblers: A Longitudinal Assessment.

PubMed

McGrath, Daniel S; Konkolÿ Thege, Barna

2018-03-01

Over the past decade, several motivational models have been proposed to explain the role of motives in gambling disorder. In the model captured by the four-factor Gambling Motives Questionnaire Financial (GMQ-F), gamblers are described as being primarily motivated to gamble for 'coping', 'enhancement', 'social', and 'financial' reasons. Although this model has received significant empirical support; to date, research assessing the role of motives in gambling disorder has been primarily cross-sectional in nature. Thus, the extent to which gambling motives remain stable over time has yet to be explored. In the current study, the stability versus fluidity of self-assessed gambling motives was investigated using the Quinte Longitudinal Study, a longitudinal dataset of gambling behaviour collected over 5 years. Gambling motives of 2795 gamblers were examined over all five annual assessments. The total proportion of gamblers who stayed in the same primary motive category across each of the 5 consecutive assessments was 22%, indicating substantial fluidity in category membership. Substantial movement between categories was seen for each GMQ-F group, as well as an additional group of non-classified motives. Logistic regression analyses suggest that greater resistance to gambling fallacies significantly predicted stability between the baseline assessment and a follow-up 1 year later, but gambling severity did not. Potential limitations in the study design and opportunities for future research are discussed.

On the Use of Machine Learning Techniques for the Mechanical Characterization of Soft Biological Tissues.

PubMed

Cilla, M; Pérez-Rey, I; Martínez, M A; Peña, Estefania; Martínez, Javier

2018-06-23

Motivated by the search for new strategies for fitting a material model, a new approach is explored in the present work. The use of numerical and complex algorithms based on machine learning techniques such as support vector machines for regression, bagged decision trees and artificial neural networks is proposed for solving the parameter identification of constitutive laws for soft biological tissues. First, the mathematical tools were trained with analytical uniaxial data (circumferential and longitudinal directions) as inputs, and their corresponding material parameters of the Gasser, Ogden and Holzapfel strain energy function as outputs. The train and test errors show great efficiency during the training process in finding correlations between inputs and outputs; besides, the correlation coefficients were very close to 1. Second, the tool was validated with unseen observations of analytical circumferential and longitudinal uniaxial data. The results show an excellent agreement between the prediction of the material parameters of the SEF and the analytical curves. Finally, data from real circumferential and longitudinal uniaxial tests on different cardiovascular tissues were fitted, thus the material model of these tissues was predicted. We found that the method was able to consistently identify model parameters, and we believe that the use of these numerical tools could lead to an improvement in the characterization of soft biological tissues. This article is protected by copyright. All rights reserved.

The impact of covariance misspecification in multivariate Gaussian mixtures on estimation and inference: an application to longitudinal modeling.

PubMed

Heggeseth, Brianna C; Jewell, Nicholas P

2013-07-20

Multivariate Gaussian mixtures are a class of models that provide a flexible parametric approach for the representation of heterogeneous multivariate outcomes. When the outcome is a vector of repeated measurements taken on the same subject, there is often inherent dependence between observations. However, a common covariance assumption is conditional independence-that is, given the mixture component label, the outcomes for subjects are independent. In this paper, we study, through asymptotic bias calculations and simulation, the impact of covariance misspecification in multivariate Gaussian mixtures. Although maximum likelihood estimators of regression and mixing probability parameters are not consistent under misspecification, they have little asymptotic bias when mixture components are well separated or if the assumed correlation is close to the truth even when the covariance is misspecified. We also present a robust standard error estimator and show that it outperforms conventional estimators in simulations and can indicate that the model is misspecified. Body mass index data from a national longitudinal study are used to demonstrate the effects of misspecification on potential inferences made in practice. Copyright © 2013 John Wiley & Sons, Ltd.

Specifying the role of exposure to violence and violent behavior on initiation of gun carrying: a longitudinal test of three models of youth gun carrying.

PubMed

Spano, Richard; Pridemore, William Alex; Bolland, John

2012-01-01

Two waves of longitudinal data from 1,049 African American youth living in extreme poverty are used to examine the impact of exposure to violence (Time 1) and violent behavior (Time 1) on first time gun carrying (Time 2). Multivariate logistic regression results indicate that (a) violent behavior (Time 1) increased the likelihood of initiation of gun carrying (Time 2) by 76% after controlling for exposure to violence at Time 1, which is consistent with the stepping stone model of youth gun carrying, and (b) youth who were both exposed to violence at Time 1 and engaged in violent behavior at Time 1 were more than 2.5 times more likely to initiate gun carrying at Time 2 compared to youth who had neither of these characteristics, which supports the cumulative risk model of youth gun carrying. The authors discuss the implications of these findings in clarifying the role of violence in the community on youth gun carrying and the primary prevention of youth gun violence.

Association of antidiabetic medication use, cognitive decline, and risk of cognitive impairment in older people with type 2 diabetes: Results from the population-based Mayo Clinic Study of Aging.

PubMed

Wennberg, Alexandra M V; Hagen, Clinton E; Edwards, Kelly; Roberts, Rosebud O; Machulda, Mary M; Knopman, David S; Petersen, Ronald C; Mielke, Michelle M

2018-06-05

To determine the cross-sectional and longitudinal associations between diabetes treatment type and cognitive outcomes among type II diabetics. We examined the association between metformin use, as compared to other diabetic treatment (ie, insulin, other oral medications, and diet/exercise) and cognitive test performance and mild cognitive impairment (MCI) diagnosis among 508 cognitively unimpaired at baseline type II diabetics enrolled in the Mayo Clinic Study of Aging. We created propensity scores to adjust for treatment effects. We used multivariate linear and logistic regression models to investigate the cross-sectional association between treatment type and cognitive test z scores, respectively. Mixed effects models and competing risk regression models were used to determine the longitudinal association between treatment type and change in cognitive test z scores and risk of developing incident MCI. In linear regression analyses adjusted for age, sex, education, body mass index, APOE ε4, insulin treatment, medical comorbidities, number of medications, duration of diabetes, and propensity score, we did not observe an association between metformin use and cognitive test performance. Additionally, we did not observe an association between metformin use and cognitive test performance over time (median = 3.7-year follow-up). Metformin was associated with an increased risk of MCI (subhazard ratio (SHR) = 2.75; 95% CI = 1.64, 4.63, P < .001). Similarly, other oral medications (SHR = 1.96; 95% CI = 1.19, 3.25; P = .009) and insulin (SHR = 3.17; 95% CI = 1.27, 7.92; P = .014) use were also associated with risk of MCI diagnosis. These findings suggest that metformin use, as compared to management of diabetes with other treatments, is not associated with cognitive test performance. However, metformin was associated with incident MCI diagnosis. Copyright © 2018 John Wiley & Sons, Ltd.

Self-Perceived Quality of Life Among Patients with Alzheimer's Disease: Two Longitudinal Models of Analysis.

PubMed

Conde-Sala, Josep L; Turró-Garriga, Oriol; Portellano-Ortiz, Cristina; Viñas-Diez, Vanesa; Gascón-Bayarri, Jordi; Reñé-Ramírez, Ramón

2016-04-12

The objective was to analyze the factors that influence self-perceived quality of life (QoL) in patients with Alzheimer's disease (AD), contrasting two different longitudinal models. A total of 127 patients were followed up over 24 months. The instruments applied were: Quality of Life in Alzheimer's Disease scale (QoL-AD), Geriatric Depression Scale-15, Anosognosia Questionnaire-Dementia, Disability Assessment in Dementia, Neuropsychiatric Inventory, and the Mini-Mental State Examination. Two models for grouping patients were tested: 1) Baseline score on the QoL-AD (QoL-Baseline), and 2) Difference in QoL-AD score between baseline and follow-up (QoL-Change). Generalized estimating equations were used to analyze longitudinal data, and multinomial regression analyses were performed. Over the follow-up period the QoL-Baseline model showed greater variability between groups (Wald χ2 = 172.3, p < 0.001) than did the QoL-Change model (Wald χ2  = 1.7, p = 0.427). In the QoL-Baseline model the predictive factors were greater depression (odds ratio [OR] = 1.20; 95% CI: 1.00- 1.45) and lower functional ability (OR = 0.92; 95% CI: 0.85- 0.99) for the Low QoL group (< 33 QoL-AD), and less depression (OR = 0.68; 95% CI: 0.52- 0.88), more anosognosia (OR = 1.07; 95% CI: 1.01- 1.13), and fewer neuropsychiatric symptoms (OR = 0.95; 95% CI: 0.91- 0.99) for the High-QoL group (>37 QoL-AD). The model based on baseline scores (QoL-Baseline) was better than the QoL-Change model in terms of identifying trajectories and predictors of QoL in AD.

KMgene: a unified R package for gene-based association analysis for complex traits.

PubMed

Yan, Qi; Fang, Zhou; Chen, Wei; Stegle, Oliver

2018-02-09

In this report, we introduce an R package KMgene for performing gene-based association tests for familial, multivariate or longitudinal traits using kernel machine (KM) regression under a generalized linear mixed model (GLMM) framework. Extensive simulations were performed to evaluate the validity of the approaches implemented in KMgene. http://cran.r-project.org/web/packages/KMgene. qi.yan@chp.edu or wei.chen@chp.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

Comparison of three lifecourse models of poverty in predicting cardiovascular disease risk in youth.

PubMed

Kakinami, Lisa; Séguin, Louise; Lambert, Marie; Gauvin, Lise; Nikiema, Béatrice; Paradis, Gilles

2013-08-01

Childhood poverty heightens the risk of adulthood cardiovascular disease (CVD), but the underlying pathways are poorly understood. Three lifecourse models have been proposed but have never been tested among youth. We assessed the longitudinal association of childhood poverty with CVD risk factors in 10-year-old youth according to the timing, accumulation, and mobility models. The Québec Longitudinal Study of Child Development birth cohort was established in 1998 (n = 2120). Poverty was defined as annual income below the low-income thresholds defined by Statistics Canada. Multiple imputation was used for missing data. Multivariable linear regression models adjusted for gender, pubertal stage, parental education, maternal age, whether the household was a single parent household, whether the child was overweight or obese, the child's physical activity in the past week, and family history. Approximately 40% experienced poverty at least once, 16% throughout childhood, and 25% intermittently. Poverty was associated with significantly elevated triglycerides and insulin according to the timing and accumulation models, although the timing model was superior for predicting insulin and the accumulation model was superior for predicting triglycerides. Early and prolonged exposure to poverty significantly increases CVD risk among 10-year-old youth. Copyright © 2013 Elsevier Inc. All rights reserved.

Functional linear models for zero-inflated count data with application to modeling hospitalizations in patients on dialysis.

PubMed

Sentürk, Damla; Dalrymple, Lorien S; Nguyen, Danh V

2014-11-30

We propose functional linear models for zero-inflated count data with a focus on the functional hurdle and functional zero-inflated Poisson (ZIP) models. Although the hurdle model assumes the counts come from a mixture of a degenerate distribution at zero and a zero-truncated Poisson distribution, the ZIP model considers a mixture of a degenerate distribution at zero and a standard Poisson distribution. We extend the generalized functional linear model framework with a functional predictor and multiple cross-sectional predictors to model counts generated by a mixture distribution. We propose an estimation procedure for functional hurdle and ZIP models, called penalized reconstruction, geared towards error-prone and sparsely observed longitudinal functional predictors. The approach relies on dimension reduction and pooling of information across subjects involving basis expansions and penalized maximum likelihood techniques. The developed functional hurdle model is applied to modeling hospitalizations within the first 2 years from initiation of dialysis, with a high percentage of zeros, in the Comprehensive Dialysis Study participants. Hospitalization counts are modeled as a function of sparse longitudinal measurements of serum albumin concentrations, patient demographics, and comorbidities. Simulation studies are used to study finite sample properties of the proposed method and include comparisons with an adaptation of standard principal components regression. Copyright © 2014 John Wiley & Sons, Ltd.

Change in Coping and Defense Mechanisms across Adulthood: Longitudinal Findings in a European American Sample

ERIC Educational Resources Information Center

Diehl, Manfred; Chui, Helena; Hay, Elizabeth L.; Lumley, Mark A.; Grühn, Daniel; Labouvie-Vief, Gisela

2014-01-01

This study examined longitudinal changes in coping and defense mechanisms in an age- and gender-stratified sample of 392 European American adults. Nonlinear age-related changes were found for the coping mechanisms of sublimation and suppression and the defense mechanisms of intellectualization, doubt, displacement, and regression. The change…

Estimating a Meaningful Point of Change: A Comparison of Exploratory Techniques Based on Nonparametric Regression

ERIC Educational Resources Information Center

Klotsche, Jens; Gloster, Andrew T.

2012-01-01

Longitudinal studies are increasingly common in psychological research. Characterized by repeated measurements, longitudinal designs aim to observe phenomena that change over time. One important question involves identification of the exact point in time when the observed phenomena begin to meaningfully change above and beyond baseline…

Does employment security modify the effect of housing affordability on mental health?

PubMed

Bentley, Rebecca; Baker, Emma; LaMontagne, Anthony; King, Tania; Mason, Kate; Kavanagh, Anne

2016-12-01

This paper uses longitudinal data to examine the interrelationship between two central social determinants of mental health - employment security and housing affordability. Data from ten annual waves of the longitudinal Household, Income and Labour Dynamics in Australia (HILDA) survey (which commenced in 2000/1 and is ongoing) were analysed using fixed-effects longitudinal linear regression. Change in the SF-36 Mental Component Summary (MCS) score of working age individuals (25-64 years) (51,885 observations of 10,776 people), associated with changes in housing affordability was examined. Models were adjusted for income, age, survey year, experience of serious injury/illness and separation/divorce. We tested for an additive interaction between the security of a household's employment arrangements and housing affordability. People in insecurely employed households appear more vulnerable than people in securely employed households to negative mental health effects of housing becoming unaffordable. In adjusted models, people in insecurely employed households whose housing became unaffordable experienced a decline in mental health (B=-1.06, 95% CI -1.75 to -0.38) while people in securely employed households experienced no difference on average. To progress our understanding of the Social Determinants of Health this analysis provides evidence of the need to bridge the (largely artificial) separation of social determinants, and understand how they are related.

Factors Associated with Dental Caries in a Group of American Indian Children at age 36 Months

PubMed Central

Warren, John J.; Blanchette, Derek; Dawson, Deborah V.; Marshall, Teresa A.; Phipps, Kathy R.; Starr, Delores; Drake, David R.

2015-01-01

Objectives Early childhood caries (ECC) is rampant among American Indian children, but there has been relatively little study of this problem. This paper reports on risk factors for caries for a group of American Indian children at age 36 months as part of a longitudinal study. Methods Pregnant women from a Northern Plains Tribal community were recruited to participate in a longitudinal study of caries and caries risk factors. Standardized dental examinations were completed on children and questionnaires were completed by mothers at baseline and when children were 4, 8, 12, 16, 22, 28 and 36 months of age. Examinations were surface-specific for dental caries, and the questionnaires collected data on demographic, dietary and behavioral factors. Non-parametric bivariate tests and logistic regression models were used to identify risk factors for caries at 36 months, and negative binomial regression was used to identify factors related to caries severity (dmf counts). Results Among the 232 children, and caries prevalence for cavitated lesions was 80%, with an additional 15% having only non-cavitated lesions. The mean dmfs was 9.6, and of the total dmfs, nearly 62% of affected surfaces were decayed, 31% were missing, and 7% were filled. Logistic regression identified higher added sugar beverage consumption, younger maternal age at baseline, higher maternal DMFS at baseline, and greater number of people in the household as significant (p<0.05) risk factors. Negative binomial regression found that only maternal DMFS was associated with child dmf counts. Conclusions By the age of 36 months, dental caries is nearly universal in this population of American Indian children. Caries risk factors included sugared beverage consumption, greater household size and maternal factors, but further analyses are needed to better understand caries in this population. PMID:26544674

Fruit and vegetable intake, physical activity, and depressive symptoms in the African American Health (AAH) study.

PubMed

Ribeiro, Sandra M L; Malmstrom, Theodore K; Morley, John E; Miller, Douglas K

2017-10-01

Healthy diet and physical activity (PA) have been associated with reduced depressive symptoms, but few studies have examined them simultaneously in African Americans. To investigate fruit and vegetable intake (FVI) and PA as predictors of clinically-relevant levels of depressive symptoms (CRLDS) in African Americans. African American Health (AAH) is a population-based longitudinal study of African Americans in St. Louis, MO, who were born in 1936-1950 (inclusive) and empaneled in 2000-01 (wave 1). At wave 8, participants self-reported fruit and vegetable intake (FVI) and completed the Yale Physical Activity Scale. At both waves 8 and 10, the CES-D 11-item scale was used to identify those who met criteria for CRLDS. Sequential logistic regression modeling was used to examine the associations of components of FVI/PA with CRLDS, both cross-sectionally (n = 680, including imputed values) and longitudinally (n = 582, including imputed values). Modeling employed gender, age, perceived income adequacy, and education as potential confounders. Cross-sectionally, vigorous PA, and leisurely walking PA, were independently associated with lower odds of CRLDS in all but the fifth model and green vegetables in all models. Longitudinally, green vegetables and interactions between the FVI summary score, the PA summary score, and other factors at wave 8 were most consistently associated with CRLDS at wave 10. In both cross-sectional and longitudinal models, the socioeconomic variables showed the strongest association as risk factors for CRLDS. Both FVI and PA were self-reported rather than observed, our cohort had limited geographic- and age-ranges, and confidence intervals for some results were broad. Green vegetables, total FVI, and various aspects of PA showed protective effects regarding CRLDS. Therefore, the promotion of such lifestyles is likely to help prevent CRLDS in this population. Copyright © 2017. Published by Elsevier B.V.

Income inequality and depressive symptoms in South Africa: A longitudinal analysis of the National Income Dynamics Study.

PubMed

Adjaye-Gbewonyo, Kafui; Avendano, Mauricio; Subramanian, S V; Kawachi, Ichiro

2016-11-01

Research suggests that income inequality may detrimentally affect mental health. We examined the relationship between district-level income inequality and depressive symptoms among individuals in South Africa-one of the most unequal countries in the world-using longitudinal data from Wave 1 (2008) and Wave 3 (2012) of the National Income Dynamics Study. Depressive symptoms were measured using the Center for Epidemiological Studies of Depression Short Form while district Gini coefficients were estimated from census and survey sources. Age, African population group, being single, being female, and having lower household income were independently associated with higher depressive symptoms. However, in longitudinal, fixed-effects regression models controlling for several factors, district-level Gini coefficients were not significantly associated with depressive symptoms scores. Our results do not support the hypothesis of a causal link between income inequality and depressive symptoms in the short-run. Possible explanations include the high underlying levels of inequality in all districts, or potential lags in the effect of inequality on depression. Copyright © 2016 Elsevier Ltd. All rights reserved.

Similarities and differences regarding changes in attachment preferences and attachment styles in relation to romantic relationship length: longitudinal and concurrent analyses.

PubMed

Umemura, Tomotaka; Lacinová, Lenka; Kotrčová, Kristína; Fraley, R Chris

2018-04-01

This study examines whether attachment preferences and attachment styles with different figures (mother, father, romantic partner, and friends) change over the course of a romantic relationship. Study 1 employed a three-wave longitudinal sample of Czech young adults who were currently in a romantic relationship (N = 870; mean age = 21.57; SD = 1.51; 81% females). Multilevel modeling analyses revealed that, as romantic relationships progressed, attachment preferences for romantic partners increased and preferences for friends decreased. However, preferences for the mother or for the father did not change over time. The parallel pattern was found for attachment avoidance; as romantic relationships progressed, attachment avoidance with romantic partners decreased and avoidance with the best friend increased. Avoidance with mother or with father, however, did not change over time. Study 2 employed a cross-sectional international sample (n = 2,593; mean age = 31.99; SD = 12.13; 79% females). Multiple regression analyses replicated the findings of attachment avoidance in the longitudinal data.

Cross-Sectional and Longitudinal Effects of Racism on Mental Health Among Residents of Black Neighborhoods in New York City

PubMed Central

Goodman, Melody S.

2015-01-01

Objectives. We investigated the impact of reported racism on the mental health of African Americans at cross-sectional time points and longitudinally, over the course of 1 year. Methods. The Black Linking Inequality, Feelings, and the Environment (LIFE) Study recruited Black residents (n = 144) from a probability sample of 2 predominantly Black New York City neighborhoods during December 2011 to June 2013. Respondents completed self-report surveys, including multiple measures of racism. We conducted assessments at baseline, 2-month follow-up, and 1-year follow-up. Weighted multivariate linear regression models assessed changes in racism and health over time. Results. Cross-sectional results varied by time point and by outcome, with only some measures associated with distress, and effects were stronger for poor mental health days than for depression. Individuals who denied thinking about their race fared worst. Longitudinally, increasing frequencies of racism predicted worse mental health across all 3 outcomes. Conclusions. These results support theories of racism as a health-defeating stressor and are among the few that show temporal associations with health. PMID:25521873

Cross-sectional and longitudinal effects of racism on mental health among residents of Black neighborhoods in New York City.

PubMed

Kwate, Naa Oyo A; Goodman, Melody S

2015-04-01

We investigated the impact of reported racism on the mental health of African Americans at cross-sectional time points and longitudinally, over the course of 1 year. The Black Linking Inequality, Feelings, and the Environment (LIFE) Study recruited Black residents (n = 144) from a probability sample of 2 predominantly Black New York City neighborhoods during December 2011 to June 2013. Respondents completed self-report surveys, including multiple measures of racism. We conducted assessments at baseline, 2-month follow-up, and 1-year follow-up. Weighted multivariate linear regression models assessed changes in racism and health over time. Cross-sectional results varied by time point and by outcome, with only some measures associated with distress, and effects were stronger for poor mental health days than for depression. Individuals who denied thinking about their race fared worst. Longitudinally, increasing frequencies of racism predicted worse mental health across all 3 outcomes. These results support theories of racism as a health-defeating stressor and are among the few that show temporal associations with health.

Sleep was associated with depression and anxiety status during pregnancy: a prospective longitudinal study.

PubMed

Yu, Yunxian; Li, Minchao; Pu, Liuyan; Wang, Shuojia; Wu, Jinhua; Ruan, Lingli; Jiang, Shuying; Wang, Zhaopin; Jiang, Wen

2017-10-01

The purpose of this study was to reveal the cross-sectional and longitudinal association of sleep with depression and anxiety among Chinese pregnant women. Pregnant women were recruited in Zhoushan Pregnant Women Cohort at Zhoushan Maternal and Child Care Hospital from 2011 to 2015. Self-rating depression scales (SDS) and self-rating anxiety scales (SAS) were used for evaluating depression and anxiety status at each trimester; corresponding sleep quality and duration were reported by pregnant women. Ordinary or multilevel linear and logistic regression model were used to estimate the cross-sectional or longitudinal association of sleep with depression and anxiety. The prevalence rates were 35.64, 24.23, and 26.24% for depression and 22.57, 17.41, and 21.04% for anxiety at 1st (T1), 2nd (T2), and 3rd trimester (T3), respectively. Controlling for potential confounders, it revealed significant cross-sectional and longitudinal associations of sleep with depression and anxiety status. In cross-sectional analysis, women who slept less than 8 h/day had higher risk of depression (T1: OR (95%CI) = 1.75 (1.39, 2.20); T2: 1.52 (1.26, 2.05); T3: 1.60 (1.18, 2.05)) and anxiety (T1: 2.00 (1.57, 2.55); T2: 1.86 (1.37, 2.54); T3: 1.33 (0.99, 1.79)). In the longitudinal analysis, multilevel model revealed that women with subjective "fair" or "bad" sleep quality had elevated risk of depression (OR ranging from 1.54 to 3.71) and anxiety (2.38 to 7.53) during pregnancy. Prenatal depression and anxiety status were prevalent in pregnant women. Sleep quality was associated with depression and anxiety status in both cross-sectional and longitudinal analyses, implying that improving sleep quality should benefit for mental health of pregnant women.

Longitudinal follow-up of nutritional status and its influencing factors in adults undergoing allogeneic hematopoietic cell transplantation.

PubMed

Urbain, P; Birlinger, J; Lambert, C; Finke, J; Bertz, H; Biesalski, H-K

2013-03-01

There are few longitudinal data on nutritional status and body composition of patients undergoing allogeneic hematopoietic cell transplantation (alloHCT). We assessed nutritional status of 105 patients before alloHCT and its course during the early post-transplant period to day +30 and day +100 via weight history, body mass index (BMI) normalized for gender and age, Subjective Global Assessment, phase angle normalized for gender, age, and BMI, and fat-free and body fat masses. Furthermore, we present a multivariate regression model investigating the impact of factors on body weight. At admission, 23.8% reported significant weight losses (>5%) in the previous 6 months, and we noted 31.5% with abnormal age- and sex-adjusted BMI values (10th, 90th percentiles). BMI decreased significantly (P<0.0001) in both periods by 11% in total, meaning a weight loss of 8.6±5.7 kg. Simultaneously, the patients experienced significant losses (P<0.0001) of both fat-free and body fat masses. Multivariate regression model revealed clinically relevant acute GVHD (parameter estimate 1.43; P=0.02) and moderate/severe anorexia (parameter estimate 1.07; P=0.058) as independent factors influencing early weight loss. In conclusion, our results show a significant deterioration in nutritional status during the early post-transplant period. Predominant alloHCT-associated complications such as anorexia and acute GVHD became evident as significant factors influencing nutritional status.

Longitudinal Study of Headache Trajectories in the Year After Mild Traumatic Brain Injury: Relation to Posttraumatic Stress Disorder Symptoms.

PubMed

Sawyer, Kathryn; Bell, Kathleen R; Ehde, Dawn M; Temkin, Nancy; Dikmen, Sureyya; Williams, Rhonda M; Dillworth, Tiara; Hoffman, Jeanne M

2015-11-01

To examine headache trajectories among persons with mild traumatic brain injury (MTBI) in the year after injury and the relation of headache trajectory to posttraumatic stress disorder (PTSD) at 1 year postinjury. Prospective, longitudinal study. Participants were recruited through a university medical center and participated in follow-up assessments by telephone. Prospectively enrolled individuals (N=212) within 1 week of MTBI who were hospitalized for observation or other system injuries. Participants were assessed at baseline and 3, 6, and 12 months postinjury. Not applicable. Participants rated average headache pain intensity using the 0 to 10 numerical rating scale at each assessment period. The PTSD Checklist-Civilian Version was completed at 12 months postinjury. Latent class growth analysis produced a 4-trajectory group model, with groups labeled resolved, worsening, improving, and chronic. Multivariate regression modeling revealed that younger age and premorbid headache correlated with membership in the worse trajectory groups (worsening and chronic; P<.001). Univariate regression revealed a significant association between PTSD and membership in the worse trajectory groups (P<.001). Headache is common in the year after MTBI, with younger people, persons who previously had headaches, and persons with PTSD more likely to report chronic or worsening headache. Further research is needed to examine whether PTSD symptoms exacerbate headaches or whether problematic headache symptoms exacerbate PTSD. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Social relationships and longitudinal changes in body mass index and waist circumference: the coronary artery risk development in young adults study.

PubMed

Kershaw, Kiarri N; Hankinson, Arlene L; Liu, Kiang; Reis, Jared P; Lewis, Cora E; Loria, Catherine M; Carnethon, Mercedes R

2014-03-01

Few studies have examined longitudinal associations between close social relationships and weight change. Using data from 3,074 participants in the Coronary Artery Risk Development in Young Adults Study who were examined in 2000, 2005, and 2010 (at ages 33-45 years in 2000), we estimated separate logistic regression random-effects models to assess whether patterns of exposure to supportive and negative relationships were associated with 10% or greater increases in body mass index (BMI) (weight (kg)/height (m)(2)) and waist circumference. Linear regression random-effects modeling was used to examine associations of social relationships with mean changes in BMI and waist circumference. Participants with persistently high supportive relationships were significantly less likely to increase their BMI values and waist circumference by 10% or greater compared with those with persistently low supportive relationships after adjustment for sociodemographic characteristics, baseline BMI/waist circumference, depressive symptoms, and health behaviors. Persistently high negative relationships were associated with higher likelihood of 10% or greater increases in waist circumference (odds ratio = 1.62, 95% confidence interval: 1.15, 2.29) and marginally higher BMI increases (odds ratio = 1.50, 95% confidence interval: 1.00, 2.24) compared with participants with persistently low negative relationships. Increasingly negative relationships were associated with increases in waist circumference only. These findings suggest that supportive relationships may minimize weight gain, and that adverse relationships may contribute to weight gain, particularly via central fat accumulation.

Social Relationships and Longitudinal Changes in Body Mass Index and Waist Circumference: The Coronary Artery Risk Development in Young Adults Study

PubMed Central

Kershaw, Kiarri N.; Hankinson, Arlene L.; Liu, Kiang; Reis, Jared P.; Lewis, Cora E.; Loria, Catherine M.; Carnethon, Mercedes R.

2014-01-01

Few studies have examined longitudinal associations between close social relationships and weight change. Using data from 3,074 participants in the Coronary Artery Risk Development in Young Adults Study who were examined in 2000, 2005, and 2010 (at ages 33–45 years in 2000), we estimated separate logistic regression random-effects models to assess whether patterns of exposure to supportive and negative relationships were associated with 10% or greater increases in body mass index (BMI) (weight (kg)/height (m)2) and waist circumference. Linear regression random-effects modeling was used to examine associations of social relationships with mean changes in BMI and waist circumference. Participants with persistently high supportive relationships were significantly less likely to increase their BMI values and waist circumference by 10% or greater compared with those with persistently low supportive relationships after adjustment for sociodemographic characteristics, baseline BMI/waist circumference, depressive symptoms, and health behaviors. Persistently high negative relationships were associated with higher likelihood of 10% or greater increases in waist circumference (odds ratio = 1.62, 95% confidence interval: 1.15, 2.29) and marginally higher BMI increases (odds ratio = 1.50, 95% confidence interval: 1.00, 2.24) compared with participants with persistently low negative relationships. Increasingly negative relationships were associated with increases in waist circumference only. These findings suggest that supportive relationships may minimize weight gain, and that adverse relationships may contribute to weight gain, particularly via central fat accumulation. PMID:24389018

Parent and Child Cigarette Use: A Longitudinal, Multigenerational Study

PubMed Central

Staff, Jeremy

2013-01-01

OBJECTIVES: Using longitudinal data from the multigenerational Youth Development Study (YDS), this article documents how parents’ long-term smoking trajectories are associated with adolescent children’s likelihood of smoking. Prospective data from the parents (from age 14–38 years) enable unique comparisons of the parents’ and children’s smoking behavior, as well as that of siblings. METHODS: Smoking trajectories are constructed using latent class analysis for the original YDS cohort (n = 1010). Multigenerational longitudinal data from 214 parents and 314 offspring ages 11 years and older are then analyzed by using logistic regression with cluster-corrected SEs. RESULTS: Four latent smoking trajectories emerged among the original cohort: stable nonsmokers (54%), early-onset light smokers who quit/reduce (16%), late-onset persistent smokers (14%), and early-onset persistent heavy smokers (16%). Although 8% of children of stable nonsmokers smoked in the last year, the other groups’ children had much higher percentages, ranging from 23% to 29%. Multivariate logistic regression models confirm that these significant differences were robust to the inclusion of myriad child- and parent-level measures (for which child age and grade point average [GPA] are significant predictors). Older sibling smoking, however, mediated the link between parental heavy smoking and child smoking. CONCLUSIONS: Even in an era of declining rates of teenage cigarette use in the United States, children of current and former smokers face an elevated risk of smoking. Prevention efforts to weaken intergenerational associations should consider parents’ long-term cigarette use, as well as the smoking behavior of older siblings in the household. PMID:23918887

Motivational and neurocognitive deficits are central to the prediction of longitudinal functional outcome in schizophrenia.

PubMed

Fervaha, G; Foussias, G; Agid, O; Remington, G

2014-10-01

Functional impairment is characteristic of most individuals with schizophrenia; however, the key variables that undermine community functioning are not well understood. This study evaluated the association between selected clinical variables and one-year longitudinal functional outcomes in patients with schizophrenia. The sample included 754 patients with schizophrenia who completed both baseline and one-year follow-up visits in the CATIE study. Patients were evaluated with a comprehensive battery of assessments capturing symptom severity and cognitive performance among other variables. The primary outcome variable was functional status one-year postbaseline measured using the Heinrichs-Carpenter Quality of Life Scale. Factor analysis of negative symptom items revealed two factors reflecting diminished expression and amotivation. Multivariate regression modeling revealed several significant independent predictors of longitudinal functioning scores. The strongest predictors were baseline amotivation and neurocognition. Both amotivation and neurocognition also had independent predictive value for each of the domains of functioning assessed (e.g., vocational). Both motivational and neurocognitive deficits independently contribute to longitudinal functional outcomes assessed 1 year later among patients with schizophrenia. Both of these domains of psychopathology impede functional recovery; hence, it follows that treatments ameliorating each of these symptoms should promote community functioning among individuals with schizophrenia. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Longitudinal Association Between Early Childhood Obesity and Fathers' Involvement in Caregiving and Decision-Making.

PubMed

Wong, Michelle S; Jones-Smith, Jessica C; Colantuoni, Elizabeth; Thorpe, Roland J; Bleich, Sara N; Chan, Kitty S

2017-10-01

Fathers have increased their involvement in child caregiving; however, their changing role in childhood obesity is understudied. This study assessed the longitudinal association between changes in obesity among children aged 2 to 4 years and changes in fathers' involvement with raising children. Longitudinal data from the Early Childhood Longitudinal Study-Birth Cohort were used to conduct child fixed-effects linear and logistic regression analyses to assess the association between changes in childhood obesity-related outcomes (sugar-sweetened beverage consumption, screen time, BMI z score, overweight/obesity, obesity) and fathers' involvement with raising children (caregiving and influencing child-related decisions). Fixed-effects models control for all time-invariant characteristics. Analyses were controlled for time-varying confounders, including child age, maternal and paternal employment, and family poverty status. Children whose fathers increased their frequency of taking children outside and involvement with physical childcare experienced a decrease in their odds of obesity from age 2 to age 4. Obesity-related outcomes were not associated with fathers' decision-making influence. Increases in fathers' involvement with some aspects of caregiving may be associated with lower odds of childhood obesity. Encouraging fathers to increase their involvement with raising children and including fathers in childhood obesity prevention efforts may help reduce obesity risk among young children. © 2017 The Obesity Society.

A longitudinal examination of offending and specialization among a sample of Massachusetts domestic violence offenders.

PubMed

Richards, Tara N; Jennings, Wesley G; Tomsich, Elizabeth A; Gover, Angela R

2013-02-01

A paucity of existing research focuses on longitudinal examinations of criminal trajectories among reoffenses committed by domestic violence offenders. Specifically, few studies have longitudinally assessed whether domestic violence offenders specialize, recidivating in domestic violence assault, or generalize, committing a range of personal and property crimes. Acknowledging these research deficiencies, the current study uses longitudinal data from a cohort of 317 batterers who were processed in a domestic violence court to investigate the trajectories of domestic violence arrests and nondomestic violence arrests over a 10-year period. The degree of overlap between domestic and nondomestic violence arrest trajectory groups is examined through a cross-tabulation and chi-square analysis. Logistic and multinomial regression models are applied to identify risk factors that distinguish trajectory groups. A PROC TRAJ procedure identifies two trajectory groups for domestic violence arrests (low and high rate) and three trajectory groups for nondomestic violence arrests (very low, low, and high rate). Results indicate that specialization among domestic violence offenders is rare-prior alcohol and drug crimes predict membership in the high-rate domestic violence arrest trajectory group and prior domestic violence arrests predict membership in both the low-rate and high-rate nondomestic violence arrest trajectories. Implications for future research and policy are discussed in this article.

Socioeconomic gradients of cardiovascular risk factors in China and India: results from the China health and retirement longitudinal study and longitudinal aging study in India.

PubMed

Hu, Peifeng; Wang, Serena; Lee, Jinkook

2017-09-01

Cardiovascular disease has become a major public health challenge in developing countries. The goal of this study is to compare socioeconomic status (SES) gradients of cardiovascular risk factors (CVRF) both within and between China and India. We used multivariable logistic regression models to examine the associations between SES and CVRF, using data from the China health and retirement longitudinal study and the longitudinal aging study in India. The results showed that, compared to illiteracy, the odds ratios of completing junior high school for high-risk waist circumference were 4.99 (95% confidence interval: 1.77-14.06) among Indian men, 3.42 (95% confidence interval: 1.66-7.05) among Indian women, but 0.74 (95% confidence interval: 0.59-0.92) among Chinese women. Similar patterns were observed between educational attainment and high-risk body mass index, and between education and hypertension, based on self-reported physician diagnosis and direct blood pressure measurements. SES is associated with CVRF in both China and India. However, this relationship showed opposite patterns across two countries, suggesting that this association is not fixed, but is subjective to underlying causal pathways, such as patterns of risky health behaviors and different social and health policies.

Accounting for Heaping in Retrospectively Reported Event Data – A Mixture-Model Approach

PubMed Central

Bar, Haim Y.; Lillard, Dean R.

2012-01-01

When event data are retrospectively reported, more temporally distal events tend to get “heaped” on even multiples of reporting units. Heaping may introduce a type of attenuation bias because it causes researchers to mismatch time-varying right-hand side variables. We develop a model-based approach to estimate the extent of heaping in the data, and how it affects regression parameter estimates. We use smoking cessation data as a motivating example, but our method is general. It facilitates the use of retrospective data from the multitude of cross-sectional and longitudinal studies worldwide that collect and potentially could collect event data. PMID:22733577

The Use of Linear Instrumental Variables Methods in Health Services Research and Health Economics: A Cautionary Note

PubMed Central

Terza, Joseph V; Bradford, W David; Dismuke, Clara E

2008-01-01

Objective To investigate potential bias in the use of the conventional linear instrumental variables (IV) method for the estimation of causal effects in inherently nonlinear regression settings. Data Sources Smoking Supplement to the 1979 National Health Interview Survey, National Longitudinal Alcohol Epidemiologic Survey, and simulated data. Study Design Potential bias from the use of the linear IV method in nonlinear models is assessed via simulation studies and real world data analyses in two commonly encountered regression setting: (1) models with a nonnegative outcome (e.g., a count) and a continuous endogenous regressor; and (2) models with a binary outcome and a binary endogenous regressor. Principle Findings The simulation analyses show that substantial bias in the estimation of causal effects can result from applying the conventional IV method in inherently nonlinear regression settings. Moreover, the bias is not attenuated as the sample size increases. This point is further illustrated in the survey data analyses in which IV-based estimates of the relevant causal effects diverge substantially from those obtained with appropriate nonlinear estimation methods. Conclusions We offer this research as a cautionary note to those who would opt for the use of linear specifications in inherently nonlinear settings involving endogeneity. PMID:18546544

Consistency between cross-sectional and longitudinal SNP: blood lipid associations.

PubMed

Costanza, Michael C; Beer-Borst, Sigrid; James, Richard W; Gaspoz, Jean-Michel; Morabia, Alfredo

2012-02-01

Various studies have linked different genetic single nucleotide polymorphisms (SNPs) to different blood lipids (BL), but whether these "connections" were identified using cross-sectional or longitudinal (i.e., changes over time) designs has received little attention. Cross-sectional and longitudinal assessments of BL [total, high-, low-density lipoprotein cholesterol (TC, HDL, LDL), triglycerides (TG)] and non-genetic factors (body mass index, smoking, alcohol intake) were measured for 2,002 Geneva, Switzerland, adults during 1999-2008 (two measurements, median 6 years apart), and 20 SNPs in 13 BL metabolism-related genes. Fixed and mixed effects repeated measures linear regression models, respectively, were employed to identify cross-sectional and longitudinal SNP:BL associations among the 1,516 (76%) study participants who reported not being treated for hypercholesterolemia at either measurement time. One-third more (12 vs. 9) longitudinal than cross-sectional associations were found [Bonferroni-adjusted two-tailed p < 0.00125 (=0.05/2)/20) for each of the four ensembles of 20 SNP:individual BL associations tested under the two study designs]. There was moderate consistency between the cross-sectional and longitudinal findings, with eight SNP:BL associations consistently identified across both study designs: [APOE.2 and APOE.4 (rs7412 and rs429358)]:TC; HL/LIPC (rs2070895):HDL; [APOB (rs1367117), APOE.2 and APOE.4 (rs7412 and rs429358)]:LDL; [APOA5 (rs2072560) and APOC III (rs5128)]:TG. The results suggest that cross-sectional studies, which include most genome-wide association studies (GWAS), can assess the large majority of SNP:BL associations. In the present analysis, which was much less powered than a GWAS, the cross-sectional study was around 2/3 (67%) as efficient as the longitudinal study.

Central Obesity is the Key Component in the Association of Metabolic Syndrome With Left Ventricular Global Longitudinal Strain Impairment.

PubMed

Cañon-Montañez, Wilson; Santos, Angela B S; Nunes, Lisandra A; Pires, Julio C G; Freire, Claudia M V; Ribeiro, Antonio L P; Mill, José G; Bessel, Marina; Duncan, Bruce B; Schmidt, Maria Inês; Foppa, Murilo

2017-11-13

Subclinical systolic dysfunction is one of the proposed mechanisms for increased cardiovascular risk associated with metabolic syndrome (MS). This study investigated the association between MS and impaired left ventricular global longitudinal strain (GLS) and the role of each MS criteria in this association. We analyzed a random sample of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) after excluding participants with prevalent heart disease. Among the 1055 participants fulfilling the inclusion criteria (53% women; 52±9 years), 444 (42%) had MS. Those with MS had worse GLS (-18.0%±2.5%) than those without (-19.0%±2.4%; P<.0001). In multiple linear regression models, MS was associated with worse GLS after adjustment for various risk factors (GLS difference=0.86%; P <.0001), even after inclusion of body mass index. Adjusted PR for impaired GLS as assessed by 3 cutoffs (1, 1.5, and 2 standard deviations) were higher among participants with than without MS: GLS -16.1% (PR, 1.76; 95%CI, 1.30-2.39); GLS -14.8% (PR, 2.35; 95%CI, 1.45-3.81); and GLS -13.5% (PR, 2.07; 95%CI, 0.97-4.41). After inclusion of body mass index in the models, these associations were attenuated, suggesting that they may, at least in part, be mediated by obesity. In quantile regression analyses, elevated waist circumference was the only MS component found to be independently associated with GLS across the whole range of values. Metabolic syndrome is independently associated with impaired GLS. Among the MS criteria, central obesity best depicted the link between metabolic derangement and cardiac function. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Prevalence of and Progression to Abnormal Non-Invasive Markers of Liver Disease (APRI and FIB-4) among US HIV-infected Youth

PubMed Central

Kapogiannis, Bill G.; Leister, Erin; Siberry, George K.; Van Dyke, Russell B.; Rudy, Bret; Flynn, Patricia; Williams, Paige L.

2015-01-01

Objective To longitudinally characterize non-invasive markers of liver disease in HIV-infected youth. Design HIV infection, without viral hepatitis co-infection, may contribute to liver disease. Non-invasive markers of liver disease [FIB-4 (Fibrosis-4) and APRI (aspartate aminotransferase-to-platelet ratio index)] have been evaluated in adults with concomitant HIV and hepatitis C, but are less studied in children. Methods In prospective cohorts of HIV-infected and HIV-uninfected youth, we used linear regression models to compare log-transformed FIB-4 and APRI measures by HIV status based on a single visit at ages 15–20 years. We also longitudinally modeled trends in these measures in HIV-infected youth with ≥2 visits to compare those with behavioral vs perinatal HIV infection (PHIV) using mixed effect linear regression, adjusting for age, gender, body mass index, and race/ethnicity. Results Of 1785 participants, 41% were male, 57% black non-Hispanic and 27% Hispanic. More HIV-infected than uninfected youth had an APRI score >0.5 (13% vs 3%, p<0.001). Among 1307 HIV-infected participants with longitudinal measures, FIB-4 scores increased 6% per year (p<0.001) among all HIV-infected youth, whereas APRI scores increased 2% per year (p=0.007) only among PHIV youth. The incidence rates (95% CI) of progression of APRI to >0.5 and >1.5 were 7.5 (6.5–8.7) and 1.4 (1.0–1.9) cases per 100 person-years of follow up, respectively. The incidence of progression of FIB-4 to >1.5 and >3.25 were 1.6 (1.2–2.2) and 0.3 (0.2–0.6) cases per 100 person-years, respectively. Conclusions APRI and FIB-4 scores were higher among HIV-infected youth. Progression to scores suggesting subclinical fibrosis or worse was common. PMID:26959353

Understanding bias in relationships between the food environment and diet quality: the Coronary Artery Risk Development in Young Adults (CARDIA) study.

PubMed

Rummo, Pasquale E; Guilkey, David K; Ng, Shu Wen; Meyer, Katie A; Popkin, Barry M; Reis, Jared P; Shikany, James M; Gordon-Larsen, Penny

2017-12-01

The relationship between food environment exposures and diet behaviours is unclear, possibly because the majority of studies ignore potential residual confounding. We used 20 years (1985-1986, 1992-1993 2005-2006) of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study across four US cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; Oakland, California) and instrumental variables (IV) regression to obtain causal estimates of longitudinal associations between the percentage of neighbourhood food outlets (per total food outlets within 1 km network distance of respondent residence) and an a priori diet quality score, with higher scores indicating higher diet quality. To assess the presence and magnitude of bias related to residual confounding, we compared results from causal models (IV regression) to non-causal models, including ordinary least squares regression, which does not account for residual confounding at all and fixed-effects regression, which only controls for time-invariant unmeasured characteristics. The mean diet quality score across follow-up was 63.4 (SD=12.7). A 10% increase in fast food restaurants (relative to full-service restaurants) was associated with a lower diet quality score over time using IV regression (β=-1.01, 95% CI -1.99 to -0.04); estimates were attenuated using non-causal models. The percentage of neighbourhood convenience and grocery stores (relative to supermarkets) was not associated with diet quality in any model, but estimates from non-causal models were similarly attenuated compared with causal models. Ignoring residual confounding may generate biased estimated effects of neighbourhood food outlets on diet outcomes and may have contributed to weak findings in the food environment literature. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

The change of longitudinal relaxation rate in oxygen enhanced pulmonary MRI depends on age and BMI but not diffusing capacity of carbon monoxide in healthy never-smokers.

PubMed

Kindvall, Simon Sven Ivan; Diaz, Sandra; Svensson, Jonas; Wollmer, Per; Olsson, Lars E

2017-01-01

Oxygen enhanced pulmonary MRI is a promising modality for functional lung studies and has been applied to a wide range of pulmonary conditions. The purpose of this study was to characterize the oxygen enhancement effect in the lungs of healthy, never-smokers, in light of a previously established relationship between oxygen enhancement and diffusing capacity of carbon monoxide in the lung (DL,CO) in patients with lung disease. In 30 healthy never-smoking volunteers, an inversion recovery with gradient echo read-out (Snapshot-FLASH) was used to quantify the difference in longitudinal relaxation rate, while breathing air and 100% oxygen, ΔR1, at 1.5 Tesla. Measurements were performed under multiple tidal inspiration breath-holds. In single parameter linear models, ΔR1 exhibit a significant correlation with age (p = 0.003) and BMI (p = 0.0004), but not DL,CO (p = 0.33). Stepwise linear regression of ΔR1 yields an optimized model including an age-BMI interaction term. In this healthy, never-smoking cohort, age and BMI are both predictors of the change in MRI longitudinal relaxation rate when breathing oxygen. However, DL,CO does not show a significant correlation with the oxygen enhancement. This is possibly because oxygen transfer in the lung is not diffusion limited at rest in healthy individuals. This work stresses the importance of using a physiological model to understand results from oxygen enhanced MRI.

Semiparametric Estimation of the Impacts of Longitudinal Interventions on Adolescent Obesity using Targeted Maximum-Likelihood: Accessible Estimation with the ltmle Package

PubMed Central

Decker, Anna L.; Hubbard, Alan; Crespi, Catherine M.; Seto, Edmund Y.W.; Wang, May C.

2015-01-01

While child and adolescent obesity is a serious public health concern, few studies have utilized parameters based on the causal inference literature to examine the potential impacts of early intervention. The purpose of this analysis was to estimate the causal effects of early interventions to improve physical activity and diet during adolescence on body mass index (BMI), a measure of adiposity, using improved techniques. The most widespread statistical method in studies of child and adolescent obesity is multi-variable regression, with the parameter of interest being the coefficient on the variable of interest. This approach does not appropriately adjust for time-dependent confounding, and the modeling assumptions may not always be met. An alternative parameter to estimate is one motivated by the causal inference literature, which can be interpreted as the mean change in the outcome under interventions to set the exposure of interest. The underlying data-generating distribution, upon which the estimator is based, can be estimated via a parametric or semi-parametric approach. Using data from the National Heart, Lung, and Blood Institute Growth and Health Study, a 10-year prospective cohort study of adolescent girls, we estimated the longitudinal impact of physical activity and diet interventions on 10-year BMI z-scores via a parameter motivated by the causal inference literature, using both parametric and semi-parametric estimation approaches. The parameters of interest were estimated with a recently released R package, ltmle, for estimating means based upon general longitudinal treatment regimes. We found that early, sustained intervention on total calories had a greater impact than a physical activity intervention or non-sustained interventions. Multivariable linear regression yielded inflated effect estimates compared to estimates based on targeted maximum-likelihood estimation and data-adaptive super learning. Our analysis demonstrates that sophisticated, optimal semiparametric estimation of longitudinal treatment-specific means via ltmle provides an incredibly powerful, yet easy-to-use tool, removing impediments for putting theory into practice. PMID:26046009

Longitudinal comparative evaluation of the equivalence of an integrated peer-support and clinical staffing model for residential mental health rehabilitation: a mixed methods protocol incorporating multiple stakeholder perspectives.

PubMed

Parker, Stephen; Dark, Frances; Newman, Ellie; Korman, Nicole; Meurk, Carla; Siskind, Dan; Harris, Meredith

2016-06-02

A novel staffing model integrating peer support workers and clinical staff within a unified team is being trialled at community based residential rehabilitation units in Australia. A mixed-methods protocol for the longitudinal evaluation of the outcomes, expectations and experiences of care by consumers and staff under this staffing model in two units will be compared to one unit operating a traditional clinical staffing. The study is unique with regards to the context, the longitudinal approach and consideration of multiple stakeholder perspectives. The longitudinal mixed methods design integrates a quantitative evaluation of the outcomes of care for consumers at three residential rehabilitation units with an applied qualitative research methodology. The quantitative component utilizes a prospective cohort design to explore whether equivalent outcomes are achieved through engagement at residential rehabilitation units operating integrated and clinical staffing models. Comparative data will be available from the time of admission, discharge and 12-month period post-discharge from the units. Additionally, retrospective data for the 12-month period prior to admission will be utilized to consider changes in functioning pre and post engagement with residential rehabilitation care. The primary outcome will be change in psychosocial functioning, assessed using the total score on the Health of the Nation Outcome Scales (HoNOS). Planned secondary outcomes will include changes in symptomatology, disability, recovery orientation, carer quality of life, emergency department presentations, psychiatric inpatient bed days, and psychological distress and wellbeing. Planned analyses will include: cohort description; hierarchical linear regression modelling of the predictors of change in HoNOS following CCU care; and descriptive comparisons of the costs associated with the two staffing models. The qualitative component utilizes a pragmatic approach to grounded theory, with collection of data from consumers and staff at multiple time points exploring their expectations, experiences and reflections on the care provided by these services. It is expected that the new knowledge gained through this study will guide the adaptation of these and similar services. For example, if differential outcomes are achieved for consumers under the integrated and clinical staffing models this may inform staffing guidelines.

Associations between ADHD and sleep quality: Longitudinal analyses from a nationally-representative cohort of twins

PubMed Central

Gregory, Alice M.; Agnew-Blais, Jessica C.; Matthews, Timothy; Moffitt, Terrie E.; Arseneault, Louise

2017-01-01

Objective Attention-deficit/hyperactivity disorder (ADHD) is associated with poor sleep quality but there is more to learn about the longitudinal association and aetiology of this association. We investigated: 1) is there an association between childhood ADHD and poor sleep quality in young adulthood?; 2) is this driven by the long-term effects of childhood ADHD or concurrent associations with ADHD in young adulthood?; and 3) to what extent do genetic and environmental influences explain the overlap between symptoms of ADHD and poor sleep quality? Method Participants were from the Environmental Risk Longitudinal Twin Study of 2,232 twin children born in the UK in 1994–1995. We ascertained ADHD diagnoses at ages 5, 7, 10, 12 and 18. We assessed sleep quality using the Pittsburgh Sleep Quality Index at age 18. We used regression models to examine longitudinal associations and bivariate twin modelling to test genetic and environmental influences. Results Children with ADHD had poorer sleep quality in young adulthood, but only if their ADHD persisted. Adults with ADHD had more sleep problems than those without ADHD, over and above psychiatric comorbidity and maternal insomnia. ADHD and sleep problems in young adulthood were associated because of genetic (55%) and nonshared environmental influences (45%). Conclusions Should ADHD remit, children with ADHD do not appear to have an increased risk of later sleep problems. Good quality sleep is important for multiple areas of functioning, and a better understanding of why adults with ADHD have poorer sleep quality will further the goal of improving treatments. PMID:27485465

Longitudinal trajectory patterns of social support: correlates and associated mental health in an Australian national cohort of young women.

PubMed

Holden, Libby; Dobson, Annette J; Ware, Robert S; Hockey, Richard; Lee, Christina

2015-09-01

Although social support is a significant contributor to health and well-being, little is known about patterns of perceived social support over time in young adulthood. It is also unclear which personal characteristics are associated with different patterns, and whether there is an association between social support and mental health over time. We explore these issues in a large national cohort of young women. We used six waves of longitudinal data spanning 16 years, from 10,369 women from the Australian Longitudinal Study on Women's Health, initially aged 18-23. We used group-based trajectory modelling to identify patterns of social support across Surveys 2-6; multinomial logistic regression to identify socio-demographic and health-behaviour predictors at Survey 1 and correlates at Survey 6 for each trajectory group; and generalised linear mixed modelling to estimate mean levels of mental health over the trajectory period for each group, adjusted for confounders. Four distinct trajectory groups of social support were identified: 'High' (58.5 %), 'Decreasing' (20.6 %), 'Low' (9.3 %), and 'Increasing' (11.6 %). Poor health and living outside metropolitan areas at both Surveys 1 and 6 were characteristics of women in all trajectory groups other than the 'High' group, as were early motherhood and being un-partnered at age 34-39. Other characteristics were specific to one or two trajectory groups. Patterns of mental health over time were consistent with patterns of social support. Longitudinal trajectory patterns of social support are associated with mental health, health behaviours, and demographic factors even in early adulthood.

ADHD and Sleep Quality: Longitudinal Analyses From Childhood to Early Adulthood in a Twin Cohort.

PubMed

Gregory, Alice M; Agnew-Blais, Jessica C; Matthews, Timothy; Moffitt, Terrie E; Arseneault, Louise

2017-01-01

Attention-deficit/hyperactivity disorder (ADHD) is associated with poor sleep quality, but there is more to learn about the longitudinal association and aetiology of this association. We investigated the following: (a) Is there an association between childhood ADHD and poor sleep quality in young adulthood? (b) Is this driven by the long-term effects of childhood ADHD or concurrent associations with ADHD in young adulthood? (c) To what extent do genetic and environmental influences explain the overlap between symptoms of ADHD and poor sleep quality? Participants were from the Environmental Risk Longitudinal Twin Study of 2,232 twin children born in the United Kingdom in 1994-1995. We ascertained ADHD diagnoses at ages 5, 7, 10, 12, and 18. We assessed sleep quality using the Pittsburgh Sleep Quality Index at age 18. We used regression models to examine longitudinal associations and bivariate twin modelling to test genetic and environmental influences. Children with ADHD had poorer sleep quality in young adulthood, but only if their ADHD persisted. Adults with ADHD had more sleep problems than those without ADHD, over and above psychiatric comorbidity and maternal insomnia. ADHD and sleep problems in young adulthood were associated because of genetic (55%) and nonshared environmental influences (45%). Should ADHD remit, children with ADHD do not appear to have an increased risk of later sleep problems. Good quality sleep is important for multiple areas of functioning, and a better understanding of why adults with ADHD have poorer sleep quality will further the goal of improving treatments.

Association between the Type of Workplace and Lung Function in Copper Miners

PubMed Central

Gruszczyński, Leszek; Wojakowska, Anna; Ścieszka, Marek; Turczyn, Barbara; Schmidt, Edward

2016-01-01

The aim of the analysis was to retrospectively assess changes in lung function in copper miners depending on the type of workplace. In the groups of 225 operators, 188 welders, and 475 representatives of other jobs, spirometry was performed at the start of employment and subsequently after 10, 20, and 25 years of work. Spirometry Longitudinal Data Analysis software was used to estimate changes in group means for FEV1 and FVC. Multiple linear regression analysis was used to assess an association between workplace and lung function. Lung function assessed on the basis of calculation of longitudinal FEV1 (FVC) decline was similar in all studied groups. However, multiple linear regression model used in cross-sectional analysis revealed an association between workplace and lung function. In the group of welders, FEF75 was lower in comparison to operators and other miners as early as after 10 years of work. Simultaneously, in smoking welders, the FEV1/FVC ratio was lower than in nonsmokers (p < 0,05). The interactions between type of workplace and smoking (p < 0,05) in their effect on FVC, FEV1, PEF, and FEF50 were shown. Among underground working copper miners, the group of smoking welders is especially threatened by impairment of lung ventilatory function. PMID:27274987

Health care funding levels and patient outcomes: a national study.

PubMed

Byrne, Margaret M; Pietz, Kenneth; Woodard, Lechauncy; Petersen, Laura A

2007-04-01

Health care funding levels differ significantly across geographic regions, but there is little correlation between regional funding levels and outcomes of elderly Medicare beneficiaries. Our goal was to determine whether this relationship holds true in a non-Medicare population cared for in a large integrated health care system with a capitated budget allocation system. We explored the association between health care funding and risk-adjusted mortality in the 22 Veterans Affairs (VA) geographic Networks over a six-year time period. Allocations to Networks were adjusted for illness burden using Diagnostic Cost Groups. To test the association between funding and risk-adjusted three-year mortality, we ran logistic regressions with single-year patient cohorts, as well as hierarchical regressions on a six year longitudinal data set, clustering on VA Network. A 1000 dollar increase in funding per unit of patient illness burden was associated with a 2-8% reduction in three-year mortality in cross sectional regressions. However, in longitudinal hierarchical regressions clustering on Network, the significant effect of funding level was eliminated. When longitudinal data are used, the significant cross sectional effect of funding levels on mortality disappear. Thus, the factors driving differences in mortality are Network effects, although part of the Network effect may be due to past levels of funding. Our results provide a caution for cross sectional examinations of the association between regional health care funding levels and health outcomes. Copyright (c) 2006 John Wiley & Sons, Ltd.

Changing Attitudes Toward Euthanasia and Suicide for Terminally Ill Persons, 1977 to 2016: An Age-Period-Cohort Analysis.

PubMed

Attell, Brandon K

2017-01-01

Several longitudinal studies show that over time the American public has become more approving of euthanasia and suicide for terminally ill persons. Yet, these previous findings are limited because they derive from biased estimates of disaggregated hierarchical data. Using insights from life course sociological theory and cross-classified logistic regression models, I better account for this liberalization process by disentangling the age, period, and cohort effects that contribute to longitudinal changes in these attitudes. The results of the analysis point toward a continued liberalization of both attitudes over time, although the magnitude of change was greater for suicide compared with euthanasia. More fluctuation in the probability of supporting both measures was exhibited for the age and period effects over the cohort effects. In addition, age-based differences in supporting both measures were found between men and women and various religious affiliations.

Influence of xerostomia on oral health-related quality of life in the elderly: a 5-year longitudinal study.

PubMed

Enoki, Kaori; Matsuda, Ken-Ich; Ikebe, Kazunori; Murai, Shunsuke; Yoshida, Minoru; Maeda, Yoshinobu; Thomson, William Murray

2014-06-01

Xerostomia and tooth loss are major oral health problems in the elderly. The aim of this longitudinal study was to characterize the influence of xerostomia on oral health-related quality of life (OHRQoL) among elderly Japanese people. A total of 99 community-dwelling, independently living individuals aged 60 years and older were interviewed and underwent dental examination at baseline and at a 5-year follow-up. The Oral Health Impact Profile-14 and the Xerostomia Inventory were used to assess OHRQoL and xerostomia severity, respectively. Participants whose xerostomia worsened over the 5-year period had a significantly poorer follow-up OHRQoL. Linear regression models showed that tooth loss and worsening xerostomia were significant predictors of poorer follow-up OHRQoL. Tooth loss and worsening xerostomia result in poorer OHRQoL among older Japanese people. Copyright © 2014 Elsevier Inc. All rights reserved.

Innovating patient care delivery: DSRIP's interrupted time series analysis paradigm.

PubMed

Shenoy, Amrita G; Begley, Charles E; Revere, Lee; Linder, Stephen H; Daiger, Stephen P

2017-12-08

Adoption of Medicaid Section 1115 waiver is one of the many ways of innovating healthcare delivery system. The Delivery System Reform Incentive Payment (DSRIP) pool, one of the two funding pools of the waiver has four categories viz. infrastructure development, program innovation and redesign, quality improvement reporting and lastly, bringing about population health improvement. A metric of the fourth category, preventable hospitalization (PH) rate was analyzed in the context of eight conditions for two time periods, pre-reporting years (2010-2012) and post-reporting years (2013-2015) for two hospital cohorts, DSRIP participating and non-participating hospitals. The study explains how DSRIP impacted Preventable Hospitalization (PH) rates of eight conditions for both hospital cohorts within two time periods. Eight PH rates were regressed as the dependent variable with time, intervention and post-DSRIP Intervention as independent variables. PH rates of eight conditions were then consolidated into one rate for regressing with the above independent variables to evaluate overall impact of DSRIP. An interrupted time series regression was performed after accounting for auto-correlation, stationarity and seasonality in the dataset. In the individual regression model, PH rates showed statistically significant coefficients for seven out of eight conditions in DSRIP participating hospitals. In the combined regression model, the coefficient of the PH rate showed a statistically significant decrease with negative p-values for regression coefficients in DSRIP participating hospitals compared to positive/increased p-values for regression coefficients in DSRIP non-participating hospitals. Several macro- and micro-level factors may have likely contributed DSRIP hospitals outperforming DSRIP non-participating hospitals. Healthcare organization/provider collaboration, support from healthcare professionals, DSRIP's design, state reimbursement and coordination in care delivery methods may have led to likely success of DSRIP. IV, a retrospective cohort study based on longitudinal data. Copyright © 2017 Elsevier Inc. All rights reserved.

Effect of Abdominal Visceral Fat Change on Regression of Erosive Esophagitis: Prospective Cohort Study.

PubMed

Nam, Su Youn; Kim, Young Woo; Park, Bum Joon; Ryu, Kum Hei; Kim, Hyun Boem

2018-05-04

Although abdominal visceral fat has been associated with erosive esophagitis in cross-sectional studies, there are few data on the longitudinal effect. We evaluated the effects of abdominal visceral fat change on the regression of erosive esophagitis in a prospective cohort study. A total of 163 participants with erosive esophagitis at baseline were followed up at 34 months and underwent esophagogastroduodenoscopy and computed tomography at both baseline and follow-up. The longitudinal effects of abdominal visceral fat on the regression of erosive esophagitis were evaluated using relative risk (RR) and 95% confidence intervals (CIs). Regression was observed in approximately 49% of participants (n=80). The 3rd (RR, 0.13; 95% CI, 0.02 to 0.71) and 4th quartiles (RR, 0.07; 95% CI, 0.01 to 0.38) of visceral fat at follow-up were associated with decreased regression of erosive esophagitis. The highest quartile of visceral fat change reduced the probability of the regression of erosive esophagitis compared to the lowest quartile (RR, 0.10; 95% CI, 0.03 to 0.28). Each trend showed a dose-dependent pattern (p for trend <0.001). The presence of baseline Helicobacter pylori increased the regression of erosive esophagitis (RR, 2.40; 95% CI, 1.05 to 5.48). Higher visceral fat at follow-up and a greater increase in visceral fat reduced the regression of erosive esophagitis in a dose-dependent manner.

Two-Part and Related Regression Models for Longitudinal Data

PubMed Central

Farewell, V.T.; Long, D.L.; Tom, B.D.M.; Yiu, S.; Su, L.

2017-01-01

Statistical models that involve a two-part mixture distribution are applicable in a variety of situations. Frequently, the two parts are a model for the binary response variable and a model for the outcome variable that is conditioned on the binary response. Two common examples are zero-inflated or hurdle models for count data and two-part models for semicontinuous data. Recently, there has been particular interest in the use of these models for the analysis of repeated measures of an outcome variable over time. The aim of this review is to consider motivations for the use of such models in this context and to highlight the central issues that arise with their use. We examine two-part models for semicontinuous and zero-heavy count data, and we also consider models for count data with a two-part random effects distribution. PMID:28890906

Comparing multiple imputation methods for systematically missing subject-level data.

PubMed

Kline, David; Andridge, Rebecca; Kaizar, Eloise

2017-06-01

When conducting research synthesis, the collection of studies that will be combined often do not measure the same set of variables, which creates missing data. When the studies to combine are longitudinal, missing data can occur on the observation-level (time-varying) or the subject-level (non-time-varying). Traditionally, the focus of missing data methods for longitudinal data has been on missing observation-level variables. In this paper, we focus on missing subject-level variables and compare two multiple imputation approaches: a joint modeling approach and a sequential conditional modeling approach. We find the joint modeling approach to be preferable to the sequential conditional approach, except when the covariance structure of the repeated outcome for each individual has homogenous variance and exchangeable correlation. Specifically, the regression coefficient estimates from an analysis incorporating imputed values based on the sequential conditional method are attenuated and less efficient than those from the joint method. Remarkably, the estimates from the sequential conditional method are often less efficient than a complete case analysis, which, in the context of research synthesis, implies that we lose efficiency by combining studies. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Improving CSF biomarker accuracy in predicting prevalent and incident Alzheimer disease

PubMed Central

Fagan, A.M.; Williams, M.M.; Ghoshal, N.; Aeschleman, M.; Grant, E.A.; Marcus, D.S.; Mintun, M.A.; Holtzman, D.M.; Morris, J.C.

2011-01-01

Objective: To investigate factors, including cognitive and brain reserve, which may independently predict prevalent and incident dementia of the Alzheimer type (DAT) and to determine whether inclusion of identified factors increases the predictive accuracy of the CSF biomarkers Aβ42, tau, ptau181, tau/Aβ42, and ptau181/Aβ42. Methods: Logistic regression identified variables that predicted prevalent DAT when considered together with each CSF biomarker in a cross-sectional sample of 201 participants with normal cognition and 46 with DAT. The area under the receiver operating characteristic curve (AUC) from the resulting model was compared with the AUC generated using the biomarker alone. In a second sample with normal cognition at baseline and longitudinal data available (n = 213), Cox proportional hazards models identified variables that predicted incident DAT together with each biomarker, and the models' concordance probability estimate (CPE), which was compared to the CPE generated using the biomarker alone. Results: APOE genotype including an ε4 allele, male gender, and smaller normalized whole brain volumes (nWBV) were cross-sectionally associated with DAT when considered together with every biomarker. In the longitudinal sample (mean follow-up = 3.2 years), 14 participants (6.6%) developed DAT. Older age predicted a faster time to DAT in every model, and greater education predicted a slower time in 4 of 5 models. Inclusion of ancillary variables resulted in better cross-sectional prediction of DAT for all biomarkers (p < 0.0021), and better longitudinal prediction for 4 of 5 biomarkers (p < 0.0022). Conclusions: The predictive accuracy of CSF biomarkers is improved by including age, education, and nWBV in analyses. PMID:21228296

Stress increases the risk of type 2 diabetes onset in women: A 12-year longitudinal study using causal modelling

PubMed Central

Oldmeadow, Christopher; Hure, Alexis; Luu, Judy; Loxton, Deborah

2017-01-01

Background Type 2 diabetes is associated with significant morbidity and mortality. Modifiable risk factors have been found to contribute up to 60% of type 2 diabetes risk. However, type 2 diabetes continues to rise despite implementation of interventions based on traditional risk factors. There is a clear need to identify additional risk factors for chronic disease prevention. The aim of this study was to examine the relationship between perceived stress and type 2 diabetes onset, and partition the estimates into direct and indirect effects. Methods and findings Women born in 1946–1951 (n = 12,844) completed surveys for the Australian Longitudinal Study on Women’s Health in 1998, 2001, 2004, 2007 and 2010. The total causal effect was estimated using logistic regression and marginal structural modelling. Controlled direct effects were estimated through conditioning in the regression model. A graded association was found between perceived stress and all mediators in the multivariate time lag analyses. A significant association was found between hypertension, as well as physical activity and body mass index, and diabetes, but not smoking or diet quality. Moderate/high stress levels were associated with a 2.3-fold increase in the odds of diabetes three years later, for the total estimated effect. Results were only slightly attenuated when the direct and indirect effects of perceived stress on diabetes were partitioned, with the mediators only explaining 10–20% of the excess variation in diabetes. Conclusions Perceived stress is a strong risk factor for type 2 diabetes. The majority of the effect estimate of stress on diabetes risk is not mediated by the traditional risk factors of hypertension, physical activity, smoking, diet quality, and body mass index. This gives a new pathway for diabetes prevention trials and clinical practice. PMID:28222165

Examining the Predictive Relations between Two Aspects of Self-Regulation and Growth in Preschool Children’s Early Literacy Skills

PubMed Central

Lonigan, Christopher J.; Allan, Darcey M.; Phillips, Beth M.

2016-01-01

There is strong evidence that self-regulatory processes are linked to early academic skills both concurrently and longitudinally. The majority of extant longitudinal studies, however, have been conducted using autoregressive techniques that may not accurately model change across time. The purpose of this study was to examine the unique associations between two components of self-regulation, attention and executive functioning (EF), and growth in early literacy skills over the preschool year using latent-growth-curve analysis. The sample included 1,082 preschool children (M-age = 55.0 months, SD = 3.73). Children completed measures of vocabulary, syntax, phonological awareness, print knowledge, cognitive ability, and self-regulation, and children’s classroom teachers completed a behavior rating measure. To examine the independent relations of the self-regulatory skills and cognitive ability with children’s initial early literacy skills and growth across the preschool year, growth models in which the intercept and slope were simultaneously regressed on each of the predictor variables were examined. Because of the significant relation between intercept and slope for most outcomes, slope was regressed on intercept in the models to allow a determination of direct and indirect effects of the predictors on growth in children’s language and literacy skills across the preschool year. In general, both teacher-rated inattention and directly measured EF were uniquely associated with initial skills level; however, only teacher-rated inattention uniquely predicted growth in early literacy skills. These findings suggest that teacher-ratings of inattention may measure an aspect of self-regulation that is particularly associated with the acquisition of academic skills in early childhood. PMID:27854463

Educational Attainment of 25 Year Old Norwegians According to Birth Order and Gender

ERIC Educational Resources Information Center

Kristensen, Petter; Bjerkedal, Tor

2010-01-01

This register-based longitudinal study of 392 969 Norwegians examined associations between birth order, gender and educational attainment at age 25 years within families (fixed effects regression) and between families (ordinary OLS regression). Data were retrieved from national registers for births of mothers with single births only and a first…

The impact of parental and peer social support on dating violence perpetration and victimization among female adolescents: a longitudinal study.

PubMed

Richards, Tara N; Branch, Kathryn A; Ray, Katherine

2014-01-01

Little is known about the role social support may play in reducing the risk of adolescent dating violence perpetration and victimization. This study is a longitudinal analysis of the independent impact of social support from friends and parents on the risk of emotional and physical dating violence perpetration and victimization among a large sample of female youth (n = 346). Findings indicate that 22% of the sample indicated perpetrating physical dating violence against a partner, whereas almost 16% revealed being the victim of physical dating violence; 34% of the sample indicated perpetrating emotional dating violence against a partner, whereas almost 39% revealed being the victim of emotional dating violence. Negative binomial regression models indicated that increased levels of support from friends at Time 1 was associated with significantly less physical and emotional dating violence perpetration and emotional (but not physical) dating violence victimization at Time 2. Parental support was not significantly related to dating violence in any model. Implications for dating violence curriculum and future research are addressed.

Direct and interactive effects of parent, friend and schoolmate drinking on alcohol use trajectories.

PubMed

Lynch, Alicia Doyle; Coley, Rebekah Levine; Sims, Jacqueline; Lombardi, Caitlin McPherran; Mahalik, James R

2015-01-01

This study considered the unique and interactive roles of social norms from parents, friends and schools in predicting developmental trajectories of adolescent drinking and intoxication. Using data from the National Longitudinal Study of Adolescent Health, which followed adolescents (N = 18,921) for 13 years, we used discrete mixture modelling to identify unique developmental trajectories of drinking and of intoxication. Next, multilevel multinomial regression models examined the role of alcohol-related social norms from parents, friends and schoolmates in the prediction of youths' trajectory group membership. Results demonstrated that social norms from parents, friends and schoolmates that were favourable towards alcohol use uniquely predicted drinking and intoxication trajectory group membership. Interactions between social norms revealed that schoolmate drinking played an important moderating role, frequently augmenting social norms from parents and friends. The current findings suggest that social norms from multiple sources (parents, friends and schools) work both independently and interactively to predict longitudinal trajectories of adolescent alcohol use. Results highlight the need to identify and understand social messages from multiple developmental contexts in efforts to reduce adolescent alcohol consumption and alcohol-related risk-taking.

Multidimensional Ultrasound Imaging of the Wrist: Changes of Shape and Displacement of the Median Nerve and Tendons in Carpal Tunnel Syndrome

PubMed Central

Filius, Anika; Scheltens, Marjan; Bosch, Hans G.; van Doorn, Pieter A.; Stam, Henk J.; Hovius, Steven E.R.; Amadio, Peter C.; Selles, Ruud W.

2015-01-01

Dynamics of structures within the carpal tunnel may alter in carpal tunnel syndrome (CTS) due to fibrotic changes and increased carpal tunnel pressure. Ultrasound can visualize these potential changes, making ultrasound potentially an accurate diagnostic tool. To study this, we imaged the carpal tunnel of 113 patients and 42 controls. CTS severity was classified according to validated clinical and nerve conduction study (NCS) classifications. Transversal and longitudinal displacement and shape (changes) were calculated for the median nerve, tendons and surrounding tissue. To predict diagnostic value binary logistic regression modeling was applied. Reduced longitudinal nerve displacement (p≤0.019), increased nerve cross-sectional area (p≤0.006) and perimeter (p≤0.007), and a trend of relatively changed tendon displacements were seen in patients. Changes were more convincing when CTS was classified as more severe. Binary logistic modeling to diagnose CTS using ultrasound showed a sensitivity of 70-71% and specificity of 80-84%. In conclusion, CTS patients have altered dynamics of structures within the carpal tunnel. PMID:25865180

Sociodemographic Factors Associated With Changes in Successful Aging in Spain: A Follow-Up Study.

PubMed

Domènech-Abella, Joan; Perales, Jaime; Lara, Elvira; Moneta, Maria Victoria; Izquierdo, Ana; Rico-Uribe, Laura Alejandra; Mundó, Jordi; Haro, Josep Maria

2017-06-01

Successful aging (SA) refers to maintaining well-being in old age. Several definitions or models of SA exist (biomedical, psychosocial, and mixed). We examined the longitudinal association between various SA models and sociodemographic factors, and analyzed the patterns of change within these models. This was a nationally representative follow-up in Spain including 3,625 individuals aged ≥50 years. Some 1,970 individuals were interviewed after 3 years. Linear regression models were used to analyze the survey data. Age, sex, and occupation predicted SA in the biomedical model, while marital status, educational level, and urbanicity predicted SA in the psychosocial model. The remaining models included different sets of these predictors as significant. In the psychosocial model, individuals tended to improve over time but this was not the case in the biomedical model. The biomedical and psychosocial components of SA need to be addressed specifically to achieve the best aging trajectories.

Birth weight and cognitive development in adolescence: causal relationship or social selection?

PubMed

Gorman, Bridget K

2002-01-01

Using data from the National Longitudinal Survey of Adolescent Health (Add Health), I investigate the relationship between birth weight and cognitive development among adolescents aged 12-17. Initial OLS regression models reveal a significant, positive relationship between low birth weight and verbal ability. Controlling for demographic, socioeconomic, and other adolescent characteristics modifies, but does not eliminate, this relationship. Additional models that stratify the sample by parental education illustrate the greater importance of other family and adolescent characteristics for cognitive development in adolescence, and a diminished role of birth weight. In the final section of the paper, fixed effects models of non-twin full siblings indicate no significant association between birth weight and verbal ability, suggesting that traditional cross-sectional models overstate the influence of birth weight for cognitive development in adolescence.

Constrained inference in mixed-effects models for longitudinal data with application to hearing loss.

PubMed

Davidov, Ori; Rosen, Sophia

2011-04-01

In medical studies, endpoints are often measured for each patient longitudinally. The mixed-effects model has been a useful tool for the analysis of such data. There are situations in which the parameters of the model are subject to some restrictions or constraints. For example, in hearing loss studies, we expect hearing to deteriorate with time. This means that hearing thresholds which reflect hearing acuity will, on average, increase over time. Therefore, the regression coefficients associated with the mean effect of time on hearing ability will be constrained. Such constraints should be accounted for in the analysis. We propose maximum likelihood estimation procedures, based on the expectation-conditional maximization either algorithm, to estimate the parameters of the model while accounting for the constraints on them. The proposed methods improve, in terms of mean square error, on the unconstrained estimators. In some settings, the improvement may be substantial. Hypotheses testing procedures that incorporate the constraints are developed. Specifically, likelihood ratio, Wald, and score tests are proposed and investigated. Their empirical significance levels and power are studied using simulations. It is shown that incorporating the constraints improves the mean squared error of the estimates and the power of the tests. These improvements may be substantial. The methodology is used to analyze a hearing loss study.

Modeling developmental changes in functional capacities and soccer-specific skills in male players aged 11-17 years.

PubMed

Valente-dos-Santos, João; Coelho-e-Silva, Manuel J; Simões, Filipe; Figueiredo, Antonio J; Leite, Neiva; Elferink-Gemser, Marije T; Malina, Robert M; Sherar, Lauren

2012-11-01

This study evaluates the contributions of age, growth, skeletal maturation, playing position and training to longitudinal changes in functional and skill performance in male youth soccer. Players were annually followed over 5 years (n = 83, 4.4 measurements per player). Composite scores for functional and skill domains were calculated to provide an overall estimate of performance. Players were also classified by maturity status and playing position at baseline. After testing for multicollinearity, two-level multilevel (longitudinal) regression models were obtained for functional and skill composite scores. The scores improved with age and training. Body mass was an additional predictor in both models [functional (late maturing): 13.48 + 1.05 × centered on chronological age (CA)-0.01 × centered CA(2)-0.19 × fat mass (FM) + 0.004 × annual volume training-1.04 × dribbling speed; skills (defenders): 7.62 + 0.62 × centered CA-0.06 × centered CA(2) + 0.04 × fat-free mass-0.03 x FM + 0.005 × annual volume training-0.19 × repeated-sprint ability + 0.02 × aerobic endurance]. Skeletal maturity status was a significant predictor of functional capacities and playing position of skill performance. Sound accuracy of each multilevel model was demonstrated on an independent cross-sectional sample (n = 52).

Q-learning residual analysis: application to the effectiveness of sequences of antipsychotic medications for patients with schizophrenia.

PubMed

Ertefaie, Ashkan; Shortreed, Susan; Chakraborty, Bibhas

2016-06-15

Q-learning is a regression-based approach that uses longitudinal data to construct dynamic treatment regimes, which are sequences of decision rules that use patient information to inform future treatment decisions. An optimal dynamic treatment regime is composed of a sequence of decision rules that indicate how to optimally individualize treatment using the patients' baseline and time-varying characteristics to optimize the final outcome. Constructing optimal dynamic regimes using Q-learning depends heavily on the assumption that regression models at each decision point are correctly specified; yet model checking in the context of Q-learning has been largely overlooked in the current literature. In this article, we show that residual plots obtained from standard Q-learning models may fail to adequately check the quality of the model fit. We present a modified Q-learning procedure that accommodates residual analyses using standard tools. We present simulation studies showing the advantage of the proposed modification over standard Q-learning. We illustrate this new Q-learning approach using data collected from a sequential multiple assignment randomized trial of patients with schizophrenia. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Association between kindergarten and first-grade food insecurity and weight status in U.S. children.

PubMed

Lee, Arthur M; Scharf, Rebecca J; DeBoer, Mark D

The aim of this study was to determine if food insecurity is an independent risk factor for obesity in U.S. children. We analyzed data from a nationally representative sample of children participating in the Early Childhood Longitudinal Study-Kindergarten Cohort 2011. Statistical analyses were performed to evaluate longitudinal associations between food security and body mass index (BMI) z-score. All regression models included race/ethnicity, household income, and parental education. Survey and anthropometric data was collected from teachers and parents of 8167 U.S. children entering kindergarten in fall 2010 with regular follow-up through third grade. Complete data regarding food security, socioeconomic assessment, and BMI z-score data were included for statistical analyses. All analyses were weighted to be nationally representative. Children with household food insecurity had increased obesity prevalence from kindergarten through grade 3; for example, at kindergarten, with food insecurity 16.4% (95% confidence interval [CI], 13.7-19) versus food secure 12.4% (95% CI, 11.3-13.6). Adjusted means analysis showed first-grade food insecurity was significantly correlated with increased BMI z-score in first through third grades; for example, at first grade, with food insecurity 0.6 (95% CI, 0.5-0.7) versus food secure 0.4 (95% CI, 0.4-0.5). Logistic regression showed first-grade food insecurity was correlated with increased risk for obesity in that grade (odds ratio 1.4; 95% CI, 1.1-2). Obesity is more prevalent among food-insecure children. First-grade food insecurity is an independent risk factor for longitudinal increases in BMI z-score. There are differences in the association between food insecurity and weight status between kindergarten and first grade. Copyright © 2018 Elsevier Inc. All rights reserved.

Controlling for selection effects in the relationship between child behavior problems and exposure to intimate partner violence.

PubMed

Emery, Clifton R

2011-05-01

This article used the Project on Human Development in Chicago Neighborhoods (PHDCN) data to examine the relationship between exposure to intimate partner violence (IPV) and child behavior problems (externalizing and internalizing), truancy, grade repetition, smoking, drinking, and use of marijuana. Longitudinal data analysis was conducted on 1,816 primary caregivers and their children. Fixed-effects regression models were employed to address concerns with selection bias. IPV was associated with significantly greater internalizing behavior, externalizing behavior, and truancy. Findings from age interaction models suggested that the relationship between IPV and child behavior problems may attenuate as the age of the child at time of exposure increases.

Dynamic modelling of n-of-1 data: powerful and flexible data analytics applied to individualised studies.

PubMed

Vieira, Rute; McDonald, Suzanne; Araújo-Soares, Vera; Sniehotta, Falko F; Henderson, Robin

2017-09-01

N-of-1 studies are based on repeated observations within an individual or unit over time and are acknowledged as an important research method for generating scientific evidence about the health or behaviour of an individual. Statistical analyses of n-of-1 data require accurate modelling of the outcome while accounting for its distribution, time-related trend and error structures (e.g., autocorrelation) as well as reporting readily usable contextualised effect sizes for decision-making. A number of statistical approaches have been documented but no consensus exists on which method is most appropriate for which type of n-of-1 design. We discuss the statistical considerations for analysing n-of-1 studies and briefly review some currently used methodologies. We describe dynamic regression modelling as a flexible and powerful approach, adaptable to different types of outcomes and capable of dealing with the different challenges inherent to n-of-1 statistical modelling. Dynamic modelling borrows ideas from longitudinal and event history methodologies which explicitly incorporate the role of time and the influence of past on future. We also present an illustrative example of the use of dynamic regression on monitoring physical activity during the retirement transition. Dynamic modelling has the potential to expand researchers' access to robust and user-friendly statistical methods for individualised studies.

The effects of airbags and seatbelts on occupant injury in longitudinal barrier crashes.

PubMed

Gabauer, Douglas J; Gabler, Hampton C

2010-02-01

Longitudinal barriers, such as guardrails, are designed to prevent a vehicle that leaves the roadway from impacting a more dangerous object while minimizing the risk of injury to the vehicle occupants. Current full-scale test procedures for these devices do not consider the effect of occupant restraints such as seatbelts and airbags. The purpose of this study was to determine the extent to which restraints are used or deployed in longitudinal barrier collisions and their subsequent effect on occupant injury. Binary logistic regression models were generated to predict occupant injury risk using data from the National Automotive Sampling System / Crashworthiness Data System from 1997 through 2007. In tow-away longitudinal barrier crashes, airbag deployment rates were 70% for airbag-equipped vehicles. Compared with unbelted occupants without an airbag available, seat belt restrained occupants with an airbag available had a dramatically decreased risk of receiving a serious (MAIS 3+) injury (odds-ratio (OR)=0.03; 95% CI: 0.004-0.24). A similar decrease was observed among those restrained by seat belts, but without an airbag available (OR=0.03; 95% CI: 0.001- 0.79). No significant differences in risk of serious injuries were observed between unbelted occupants with an airbag available compared with unbelted occupants without an airbag available (OR=0.53; 95% CI=0.10-2.68). This study refutes the perception in the roadside safety community that airbags rarely deploy in frontal barrier crashes, and suggests that current longitudinal barrier occupant risk criteria may over-estimate injury potential for restrained occupants involved in a longitudinal barrier crash. Copyright 2010 Elsevier Ltd. All rights reserved.

Effort-reward imbalance and work ability: cross-sectional and longitudinal findings from the Second German Sociomedical Panel of Employees

PubMed Central

2012-01-01

Background Although data from longitudinal studies are sparse, effort-reward imbalance (ERI) seems to affect work ability. However, the potential pathway from restricted work ability to ERI must also be considered. Therefore, the aim of our study was to analyse cross-sectional and longitudinal associations between ERI and work ability and vice versa. Methods Data come from the Second German Sociomedical Panel of Employees. Logistic regression models were estimated to determine cross-sectional and longitudinal associations. The sample used to predict new cases of poor or moderate work ability was restricted to cases with good or excellent work ability at baseline. The sample used to predict new cases of ERI was restricted to persons without ERI at baseline. Results The cross-sectional analysis included 1501 full-time employed persons. The longitudinal analyses considered 600 participants with good or excellent baseline work ability and 666 participants without baseline ERI, respectively. After adjustment for socio-demographic variables, health-related behaviour and factors of the work environment, ERI was cross-sectionally associated with poor or moderate work ability (OR = 1.980; 95% CI: 1.428 to 2.747). Longitudinally, persons with ERI had 2.1 times higher odds of poor or moderate work ability after one year (OR = 2.093; 95% CI: 1.047 to 4.183). Conversely, persons with poor or moderate work ability had 2.6 times higher odds of an ERI after one year (OR = 2.573; 95% CI: 1.314 to 5.041). Conclusions Interventions that enable workers to cope with ERI or address indicators of ERI directly could promote the maintenance of work ability. Integration management programmes for persons with poor work ability should also consider their psychosocial demands. PMID:23067110

Predicting missing biomarker data in a longitudinal study of Alzheimer disease.

PubMed

Lo, Raymond Y; Jagust, William J

2012-05-01

To investigate predictors of missing data in a longitudinal study of Alzheimer disease (AD). The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a clinic-based, multicenter, longitudinal study with blood, CSF, PET, and MRI scans repeatedly measured in 229 participants with normal cognition (NC), 397 with mild cognitive impairment (MCI), and 193 with mild AD during 2005-2007. We used univariate and multivariable logistic regression models to examine the associations between baseline demographic/clinical features and loss of biomarker follow-ups in ADNI. CSF studies tended to recruit and retain patients with MCI with more AD-like features, including lower levels of baseline CSF Aβ(42). Depression was the major predictor for MCI dropouts, while family history of AD kept more patients with AD enrolled in PET and MRI studies. Poor cognitive performance was associated with loss of follow-up in most biomarker studies, even among NC participants. The presence of vascular risk factors seemed more critical than cognitive function for predicting dropouts in AD. The missing data are not missing completely at random in ADNI and likely conditional on certain features in addition to cognitive function. Missing data predictors vary across biomarkers and even MCI and AD groups do not share the same missing data pattern. Understanding the missing data structure may help in the design of future longitudinal studies and clinical trials in AD.

Predicting missing biomarker data in a longitudinal study of Alzheimer disease

PubMed Central

Jagust, William J.; Aisen, Paul; Jack, Clifford R.; Toga, Arthur W.; Beckett, Laurel; Gamst, Anthony; Soares, Holly; C. Green, Robert; Montine, Tom; Thomas, Ronald G.; Donohue, Michael; Walter, Sarah; Dale, Anders; Bernstein, Matthew; Felmlee, Joel; Fox, Nick; Thompson, Paul; Schuff, Norbert; Alexander, Gene; DeCarli, Charles; Bandy, Dan; Chen, Kewei; Morris, John; Lee, Virginia M.-Y.; Korecka, Magdalena; Crawford, Karen; Neu, Scott; Harvey, Danielle; Kornak, John; Saykin, Andrew J.; Foroud, Tatiana M.; Potkin, Steven; Shen, Li; Buckholtz, Neil; Kaye, Jeffrey; Dolen, Sara; Quinn, Joseph; Schneider, Lon; Pawluczyk, Sonia; Spann, Bryan M.; Brewer, James; Vanderswag, Helen; Heidebrink, Judith L.; Lord, Joanne L.; Petersen, Ronald; Johnson, Kris; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Morris, John C.; Mintun, Mark A.; Schneider, Stacy; Marson, Daniel; Griffith, Randall; Clark, David; Grossman, Hillel; Tang, Cheuk; Marzloff, George; Toledo-Morrell, Leylade; Shah, Raj C.; Duara, Ranjan; Varon, Daniel; Roberts, Peggy; Albert, Marilyn S.; Pedroso, Julia; Toroney, Jaimie; Rusinek, Henry; de Leon, Mony J; De Santi, Susan M; Doraiswamy, P. Murali; Petrella, Jeffrey R.; Aiello, Marilyn; Clark, Christopher M.; Pham, Cassie; Nunez, Jessica; Smith, Charles D.; Given, Curtis A.; Hardy, Peter; Lopez, Oscar L.; Oakley, MaryAnn; Simpson, Donna M.; Ismail, M. Saleem; Brand, Connie; Richard, Jennifer; Mulnard, Ruth A.; Thai, Gaby; Mc-Adams-Ortiz, Catherine; Diaz-Arrastia, Ramon; Martin-Cook, Kristen; DeVous, Michael; Levey, Allan I.; Lah, James J.; Cellar, Janet S.; Burns, Jeffrey M.; Anderson, Heather S.; Laubinger, Mary M.; Bartzokis, George; Silverman, Daniel H.S.; Lu, Po H.; Graff-Radford MBBCH, Neill R; Parfitt, Francine; Johnson, Heather; Farlow, Martin; Herring, Scott; Hake, Ann M.; van Dyck, Christopher H.; MacAvoy, Martha G.; Benincasa, Amanda L.; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Graham, Simon; Caldwell, Curtis; Hsiung, Ging-Yuek Robin; Feldman, Howard; Assaly, Michele; Kertesz, Andrew; Rogers, John; Trost, Dick; Bernick, Charles; Munic, Donna; Wu, Chuang-Kuo; Johnson, Nancy; Mesulam, Marsel; Sadowsky, Carl; Martinez, Walter; Villena, Teresa; Turner, Scott; Johnson, Kathleen B.; Behan, Kelly E.; Sperling, Reisa A.; Rentz, Dorene M.; Johnson, Keith A.; Rosen, Allyson; Tinklenberg, Jared; Ashford, Wes; Sabbagh, Marwan; Connor, Donald; Jacobson, Sandra; Killiany, Ronald; Norbash, Alexander; Nair, Anil; Obisesan, Thomas O.; Jayam-Trouth, Annapurni; Wang, Paul; Lerner, Alan; Hudson, Leon; Ogrocki, Paula; DeCarli, Charles; Fletcher, Evan; Carmichael, Owen; Kittur, Smita; Mirje, Seema; Borrie, Michael; Lee, T-Y; Bartha, Dr Rob; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Potkin, Steven G.; Preda, Adrian; Nguyen, Dana; Tariot, Pierre; Fleisher, Adam; Reeder, Stephanie; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Hendin, Barry A.; Scharre, Douglas W.; Kataki, Maria; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Gandy, Sam; Marenberg, Marjorie E.; Rovner, Barry W.; Pearlson, Godfrey; Anderson, Karen; Saykin, Andrew J.; Santulli, Robert B.; Englert, Jessica; Williamson, Jeff D.; Sink, Kaycee M.; Watkins, Franklin; Ott, Brian R.; Wu, Chuang-Kuo; Cohen, Ronald; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Rosen, Howard J.; Miller, Bruce L.; Mintzer, Jacobo

2012-01-01

Objective: To investigate predictors of missing data in a longitudinal study of Alzheimer disease (AD). Methods: The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a clinic-based, multicenter, longitudinal study with blood, CSF, PET, and MRI scans repeatedly measured in 229 participants with normal cognition (NC), 397 with mild cognitive impairment (MCI), and 193 with mild AD during 2005–2007. We used univariate and multivariable logistic regression models to examine the associations between baseline demographic/clinical features and loss of biomarker follow-ups in ADNI. Results: CSF studies tended to recruit and retain patients with MCI with more AD-like features, including lower levels of baseline CSF Aβ42. Depression was the major predictor for MCI dropouts, while family history of AD kept more patients with AD enrolled in PET and MRI studies. Poor cognitive performance was associated with loss of follow-up in most biomarker studies, even among NC participants. The presence of vascular risk factors seemed more critical than cognitive function for predicting dropouts in AD. Conclusion: The missing data are not missing completely at random in ADNI and likely conditional on certain features in addition to cognitive function. Missing data predictors vary across biomarkers and even MCI and AD groups do not share the same missing data pattern. Understanding the missing data structure may help in the design of future longitudinal studies and clinical trials in AD. PMID:22491869

Analyzing Health-Related Quality of Life Data to Estimate Parameters for Cost-Effectiveness Models: An Example Using Longitudinal EQ-5D Data from the SHIFT Randomized Controlled Trial.

PubMed

Griffiths, Alison; Paracha, Noman; Davies, Andrew; Branscombe, Neil; Cowie, Martin R; Sculpher, Mark

2017-03-01

The aim of this article is to discuss methods used to analyze health-related quality of life (HRQoL) data from randomized controlled trials (RCTs) for decision analytic models. The analysis presented in this paper was used to provide HRQoL data for the ivabradine health technology assessment (HTA) submission in chronic heart failure. We have used a large, longitudinal EuroQol five-dimension questionnaire (EQ-5D) dataset from the Systolic Heart Failure Treatment with the I f Inhibitor Ivabradine Trial (SHIFT) (clinicaltrials.gov: NCT02441218) to illustrate issues and methods. HRQoL weights (utility values) were estimated from a mixed regression model developed using SHIFT EQ-5D data (n = 5313 patients). The regression model was used to predict HRQoL outcomes according to treatment, patient characteristics, and key clinical outcomes for patients with a heart rate ≥75 bpm. Ivabradine was associated with an HRQoL weight gain of 0.01. HRQoL weights differed according to New York Heart Association (NYHA) class (NYHA I-IV, no hospitalization: standard care 0.82-0.46; ivabradine 0.84-0.47). A reduction in HRQoL weight was associated with hospitalizations within 30 days of an HRQoL assessment visit, with this reduction varying by NYHA class [-0.07 (NYHA I) to -0.21 (NYHA IV)]. The mixed model explained variation in EQ-5D data according to key clinical outcomes and patient characteristics, providing essential information for long-term predictions of patient HRQoL in the cost-effectiveness model. This model was also used to estimate the loss in HRQoL associated with hospitalizations. In SHIFT many hospitalizations did not occur close to EQ-5D visits; hence, any temporary changes in HRQoL associated with such events would not be captured fully in observed RCT evidence, but could be predicted in our cost-effectiveness analysis using the mixed model. Given the large reduction in hospitalizations associated with ivabradine this was an important feature of the analysis. The Servier Research Group.

An economic analysis of community-level fast food prices and individual-level fast food intake: longitudinal effects

PubMed Central

Gordon-Larsen, Penny; Guilkey, David K.; Popkin, Barry M.

2011-01-01

Background While dietary intake is shaped by cost, there is minimal research on the association between community-level food prices and dietary intake. Methods We used nationally representative, longitudinal data to examine how community-level food price variation was associated with individual-level fast food intake by race/ethnicity and income across waves II (1996) and III (2001–02) of The National Longitudinal Study of Adolescent Health (n=11,088) from 158 baseline and 363 follow-up US counties. Results Negative binomial regression models predicting the number of fast food meals per week show strong relationships between fast food consumption and prices of fast food and soda that varied by gender and race/ethnicity. We found relatively stronger association between food prices and fast food intake for males and relatively greater price sensitivity for soda versus burgers. In the group with strongest associations (black males), a 20% increase in price of soda was associated with a decrease of a 0.25 visits to a fast food restaurant per week. Conclusions Economic incentives may be an effective mechanism to address fast food intake in an age group at high risk for obesity. PMID:21852178

A longitudinal analysis of shooter games and their relationship with conduct disorder and cself-reported delinquency.

PubMed

Smith, Sven; Ferguson, Chris; Beaver, Kevin

Despite several decades of research, little scholarly consensus has emerged regarding the role of violent video games in the development of youth psychopathology or crime. The current study employed the Avon Longitudinal Study of Parents and Children longitudinal dataset to examine the impact of the shooter game genre ownership in childhood on later adolescent conduct disorder and criminal behavior. Multivariate Poisson regressions with the robust estimator correlation matrix were performed comparing effects of independent and confounding variables. Results revealed that early childhood mental health symptoms at age seven related to ADHD, depression and early conduct disorder predicted criminal behavior at age fifteen. Male gender also predicted criminal behavior at age fifteen. However, exposure to shooter games did not predict adolescent conduct disorder or criminal behavior. We have found support that suggests that the role of violent video games in the development of youth psychopathology or crime is very little if any. Lack of a relationship between exposure to shooter games and later conduct and criminal behavior problems may be understood within the context of the Catalyst Model. Copyright © 2018 Elsevier Ltd. All rights reserved.

It Works Both Ways: The Relationship between Exposure to Sexual Content in the Media and Adolescent Sexual Behavior

PubMed Central

Bleakley, Amy; Hennessy, Michael; Fishbein, Martin; Jordan, Amy

2010-01-01

Using a longitudinal web-based survey of adolescents 14-16 years of age, we estimate regression models where self-reported sexual behavior and content analytic-based exposure to sex in the media are related cross-sectionally and longitudinally. We find evidence for both cross-sectional non-recursive and prospective longitudinal relationships even after adjusting for both established predictors of sexual behavior (e.g., physical development, having a romantic partner, parental monitoring, peer and parental norms, respondent's age) and of exposure to sexual media content (e.g., time the respondent goes to bed, extracurricular activities, television in the bedroom, total time spent with television, music, videogames, and magazines). Sexually active adolescents are more likely to expose themselves to sex in the media and those exposed to sex in the media are more likely to progress in their sexual activity. These findings are consistent with others in the literature that demonstrate a causal effect of exposure to sexual content on sexual behavior but extend established results by also looking at the causal effect of sexual behavior on exposure both cross-sectionally and over time. PMID:20376301

Longitudinal impacts of pubertal timing and weight status on adolescent Internet use: Analysis from a cohort study of Taiwanese youths.

PubMed

Tsai, Meng-Che; Strong, Carol; Chen, Wan-Ting; Lee, Chih-Ting; Lin, Chung-Ying

2018-01-01

To investigate the longitudinal impacts of pubertal timing and weight status on Internet use in adolescents. Three waves of data on a longitudinal cohort of 7th grade students (N = 2430) were retrieved from the Taiwan Youth Project. Univariate and multivariate regression models were applied using crude and adjusted odds ratios (OR) with 95% confidence intervals (CI) to examine the concomitant impacts of pubertal timing and weight status on adolescent Internet use. The dataset identified 210 (8.7%) students using the Internet for more than 20 hours/week, and 81 (3.3%) were viewing pornographic material online. Early maturing and thin-weight adolescents were at 35% and 46% increased risks of spending long hours on Internet use, respectively. While early puberty was associated with online pornography viewing among males (adjusted OR 1.84, 95% CI 1.04-3.28), early puberty was contrarily a protective factor against online gaming in females (adjusted OR 0.59, 95% CI 0.36-0.96). Early puberty was found to be positively related to adolescent Internet use. Appropriate health education and guidance regarding Internet use should be provided to those with different developing needs.

Effect of Victimization on Impulse Control and Binge Drinking among Serious Juvenile Offenders from Adolescence to Young Adulthood.

PubMed

Davis, Jordan P; Dumas, Tara M; Berey, Benjamin L; Merrin, Gabriel J; Cimpian, Joseph R; Roberts, Brent W

2017-07-01

A vast literature has found longitudinal effects of early life stress on substance use and self-regulatory processes. These associations may vary by period-specific development among youth involved in the juvenile justice system. The current study used an accelerated longitudinal design and auto-regressive latent trajectory with structure residuals (ALT-SR) model to examine the within-person cross-lagged associations between binge drinking, impulse control, and victimization from 15 to 25 years of age. A large sample (N = 1100) of justice-involved youth were followed longitudinally for 7 years (M age baseline  = 15.8, M age conclusion  = 22.8). In general, the sample was ethnically diverse (41% Black, 34% Hispanic, 21% White, 4.3% Other) and primarily male (87.2%). Participants reported on their frequency of binge drinking, impulse control, and frequency of victimization at each time point. The results indicated that, during adolescence, victimization and binge drinking attenuated impulse control, which resulted in more binge drinking and victimization during young adulthood. The current study highlights the importance of assessing developmental processes and period-specific transitions among at risk youth, especially for youth experiencing early life stress.

Time-varying effect moderation using the structural nested mean model: estimation using inverse-weighted regression with residuals

PubMed Central

Almirall, Daniel; Griffin, Beth Ann; McCaffrey, Daniel F.; Ramchand, Rajeev; Yuen, Robert A.; Murphy, Susan A.

2014-01-01

This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use. PMID:23873437

Frailty Transitions in the San Antonio Longitudinal Study of Aging

PubMed Central

Espinoza, Sara E.; Jung, Inkyung; Hazuda, Helen

2012-01-01

OBJECTIVES To examine frailty transitions in Mexican American (MA) and European American (EA) older adults. DESIGN Longitudinal, observational cohort study. SETTING Socioeconomically diverse neighborhoods in San Antonio, Texas. PARTICIPANTS 312 MA and 285 EA community-dwelling older adults (65+) with frailty information at baseline (1992–96) and transition information at follow-up (2000–01) in the San Antonio Longitudinal Study of Aging (SALSA). MEASUREMENTS Five frailty characteristics (weight loss, exhaustion, weakness, slowness, and low physical activity), frailty score (0–5), and overall frailty state (non-frail = 0 characteristics, pre-frail = 1 or 2, frail = 3+) were assessed at baseline. Transitions (progressed, regressed, or no change) were assessed for frailty score and state. Odds ratios (OR) of progression and regression in individual characteristics were estimated using generalized estimating equations, adjusting for age, sex, ethnic group, socioeconomic status, comorbidity, diabetes, and follow-up interval. RESULTS Diabetes with macrovascular complications (OR=1.84, 95%CI: 1.02–3.33), fewer years of education (OR=0.96, 95%CI: 0.93–1.0) and follow-up interval (OR=1.3, 95%CI: 1.17–1.46) were significant predictors of progression in any frailty characteristic. Mortality increased by frailty state, and pre-frail individuals were more likely than frail to regress. CONCLUSION Diabetes with macrovascular complications and fewer years of education are important predictors of progression in any frailty characteristic. Because of increased risk of death compared with the non-frail state and the increased likelihood of regression compared with the frail state, the pre-frail state may be an optimal target for intervention. PMID:22316162

Sleep-disordered breathing, sleep duration, and childhood overweight: a longitudinal cohort study.

PubMed

Bonuck, Karen; Chervin, Ronald D; Howe, Laura D

2015-03-01

To examine independent associations between sleep-disordered breathing (SDB), sleep duration from birth through 6.75 years, and body mass index (BMI) through 15 years of age in a population-based cohort. The Avon Longitudinal Study of Parents and Children collected parent questionnaire data on child sleep duration and SDB symptoms from birth through 6.75 years and child BMI from the Avon Longitudinal Study of Parents and Children research clinics (n = 1899). For SDB, logistic regression models-minimal, confounder, and confounder + sleep duration adjusted-examined associations with BMI at 7, 10, and 15 years of age. For short sleep duration (≤10th percentile), comparable SDB-adjusted models examined associations with BMI at 15 years of age. Children with the worst SDB symptoms vs asymptomatic children, had increased odds of overweight at 7 (OR = 2.08, 95% CI = 1.04-4.17), 10 (OR = 1.79, 95% CI = 1.02-3.16), and 15 years of age (OR = 2.25, 95% CI = 1.27-3.97) in models adjusted for sleep duration. Similarly, short sleep duration at ≈5-6 years was associated with overweight at 15 years, independent of SDB. Children with short sleep duration at 4.75 years were more likely to be overweight at 15 years in minimally (OR = 2.21, 95% CI = 1.52-3.20), confounder (OR = 1.99, 95% CI = 1.34-2.96), and SDB-adjusted (OR = 2.04, 95% CI = 1.36-3.04) models. Both SDB and short sleep duration significantly and independently increase children's odds of becoming overweight. Findings underscore the potential importance of early identification and remediation of SDB, along with insufficient sleep, as strategies for reducing childhood obesity. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Impact of transverse and longitudinal dispersion on first-order degradation rate constant estimation

NASA Astrophysics Data System (ADS)

Stenback, Greg A.; Ong, Say Kee; Rogers, Shane W.; Kjartanson, Bruce H.

2004-09-01

A two-dimensional analytical model is employed for estimating the first-order degradation rate constant of hydrophobic organic compounds (HOCs) in contaminated groundwater under steady-state conditions. The model may utilize all aqueous concentration data collected downgradient of a source area, but does not require that any data be collected along the plume centerline. Using a least squares fit of the model to aqueous concentrations measured in monitoring wells, degradation rate constants were estimated at a former manufactured gas plant (FMGP) site in the Midwest U.S. The estimated degradation rate constants are 0.0014, 0.0034, 0.0031, 0.0019, and 0.0053 day -1 for acenaphthene, naphthalene, benzene, ethylbenzene, and toluene, respectively. These estimated rate constants were as low as one-half those estimated with the one-dimensional (centerline) approach of Buscheck and Alcantar [Buscheck, T.E., Alcantar, C.M., 1995. Regression techniques and analytical solutions to demonstrate intrinsic bioremediation. In: Hinchee, R.E., Wilson, J.T., Downey, D.C. (Eds.), Intrinsic Bioremediation, Battelle Press, Columbus, OH, pp. 109-116] which does not account for transverse dispersivity. Varying the transverse and longitudinal dispersivity values over one order of magnitude for toluene data obtained from the FMGP site resulted in nearly a threefold variation in the estimated degradation rate constant—highlighting the importance of reliable estimates of the dispersion coefficients for obtaining reasonable estimates of the degradation rate constants. These results have significant implications for decision making and site management where overestimation of a degradation rate may result in remediation times and bioconversion factors that exceed expectations. For a complex source area or non-steady-state plume, a superposition of analytical models that incorporate longitudinal and transverse dispersion and time may be used at sites where the centerline method would not be applicable.

Alterations of papilla dimensions after orthodontic closure of the maxillary midline diastema: a retrospective longitudinal study.

PubMed

Jeong, Jin-Seok; Lee, Seung-Youp; Chang, Moontaek

2016-06-01

The aim of this study was to evaluate alterations of papilla dimensions after orthodontic closure of the diastema between maxillary central incisors. Sixty patients who had a visible diastema between maxillary central incisors that had been closed by orthodontic approximation were selected for this study. Various papilla dimensions were assessed on clinical photographs and study models before the orthodontic treatment and at the follow-up examination after closure of the diastema. Influences of the variables assessed before orthodontic treatment on the alterations of papilla height (PH) and papilla base thickness (PBT) were evaluated by univariate regression analysis. To analyze potential influences of the 3-dimensional papilla dimensions before orthodontic treatment on the alterations of PH and PBT, a multiple regression model was formulated including the 3-dimensional papilla dimensions as predictor variables. On average, PH decreased by 0.80 mm and PBT increased after orthodontic closure of the diastema (P<0.01). Univariate regression analysis revealed that the PH (P=0.002) and PBT (P=0.047) before orthodontic treatment influenced the alteration of PH. With respect to the alteration of PBT, the diastema width (P=0.045) and PBT (P=0.000) were found to be influential factors. PBT before the orthodontic treatment significantly influenced the alteration of PBT in the multiple regression model. PH decreased but PBT increased after orthodontic closure of the diastema. The papilla dimensions before orthodontic treatment influenced the alterations of PH and PBT after closure of the diastema. The PBT increased more when the diastema width before the orthodontic treatment was larger.

Declines in Strength and Mortality Risk Among Older Mexican Americans: Joint Modeling of Survival and Longitudinal Data.

PubMed

Peterson, Mark D; Zhang, Peng; Duchowny, Kate A; Markides, Kyriakos S; Ottenbacher, Kenneth J; Snih, Soham Al

2016-12-01

Grip strength is a noninvasive method of risk stratification; however, the association between changes in strength and mortality is unknown. The purposes of this study were to examine the association between grip strength and mortality among older Mexican Americans and to determine the ability of changes in strength to predict mortality. Longitudinal data were included from 3,050 participants in the Hispanic Established Population for the Epidemiological Study of the Elderly. Strength was assessed using a hand-held dynamometer and normalized to body mass. Conditional inference tree analyses were used to identify sex- and age-specific weakness thresholds, and the Kaplan-Meier estimator was used to determine survival estimates across various strata. We also evaluated survival with traditional Cox proportional hazard regression for baseline strength, as well as with joint modeling of survival and longitudinal strength change trajectories. Survival estimates were lower among women who were weak at baseline for only 65- to 74-year-olds (11.93 vs 16.69 years). Survival estimates were also lower among men who were weak at baseline for only ≥75-year-olds (5.80 vs 7.39 years). Lower strength at baseline (per 0.1 decrement) was significantly associated with mortality (hazard ratio [HR]: 1.10; 95% confidence interval [CI]: 1.01-1.19) for women only. There was a strong independent, longitudinal association between strength decline and early mortality, such that each 0.10 decrease in strength, within participants over time, resulted in a HR of 1.12 (95% CI: 1.00-1.25) for women and a HR of 1.15 (95% CI: 1.04-1.28) for men. Longitudinal declines in strength are significantly associated with all-cause mortality in older Mexican Americans. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Body size estimation and other psychosocial risk factors for obesity onset among US adolescents: findings from a longitudinal population level study.

PubMed

Liechty, J M; Lee, M-J

2015-04-01

The purpose of this study was to examine the longitudinal effects of body size over- and underestimation and other psychosocial factors on the risk for onset of overweight (OW) or obesity (OB) 1 year later among US adolescents. Participants with non-missing height and weight were drawn from the first two waves of the National Longitudinal Study of Adolescent to Adult Health (n=13,568). Multinomial logistic regressions were conducted to assess longitudinal risk factors for OW and OB onset, controlling for baseline weight status, age, race/ethnicity, parent education and family structure. Analyses were stratified by sex. Compared with accurate body size perception, body size overestimation increased the relative risk (RR) of OW onset among women and men (RR=3.34, confidence interval (CI)=2.39-4.68; RR=6.01, CI=4.09-8.83, respectively, P<0.001) in fully adjusted models including body mass index z-scores. Body size underestimation decreased the RR of OW onset among women and men (RR= 0.08, CI=0.03-0.20; RR=0.13, CI=0.06-0.27, respectively) and OB onset (RR=0.05, CI=0.02-0.14; RR=0.19, CI=0.08-0.47, respectively, P<0.001 for all) in fully adjusted models. Dieting, extreme weight loss behaviors and skipping breakfast at Wave 1 increased the risk of OB onset by Wave 2. Contrary to a common assumption, body size underestimation did not increase, but in fact decreased, the RR for the onset of OW and of OB among adolescents using a prospective longitudinal design. However, body size overestimation predicted onset of OW 1 year later. Body size self-concept and other psychosocial factors have an important role in risk for OW and for OB among both males and females during adolescence.

The association of variants in the FTO gene with longitudinal body mass index profiles in non-Hispanic white children and adolescents.

PubMed

Hallman, D M; Friedel, V C; Eissa, M A H; Boerwinkle, E; Huber, J C; Harrist, R B; Srinivasan, S R; Chen, W; Dai, S; Labarthe, D R; Berenson, G S

2012-01-01

To investigate possible age-related changes in associations between polymorphisms in the fat mass and obesity-associated (FTO) gene and higher body mass index (BMI). Multilevel mixed regression models were used to examine associations between four FTO variants and longitudinal BMI profiles in non-Hispanic white and African American children and adolescents 8-17 years of age from two different longitudinal cohort studies, the Bogalusa Heart Study (BHS) and Project HeartBeat! (PHB). In the BHS, there were 1551 examinations of 478 African Americans and 3210 examinations of 1081 non-Hispanic whites; in PHB, there were 971 examinations of 131 African Americans and 4458 examinations of 505 non-Hispanic whites. In African Americans, no significant FTO associations with BMI were found. In non-Hispanic whites, linkage disequilibrium among all four variants made haplotype analysis superfluous, so we focused on the single-nucleotide polymorphism, rs9939609. In longitudinal multilevel models, the A/A genotype of rs9939609 was associated with higher BMI in non-Hispanic whites in both cohorts at all ages. A significant age-by-genotype interaction found only in the BHS cohort predicted that in those with the A/A genotype, BMI would be ∼0.7 kg m(-2) higher at age 8 and ∼1.6 kg m(-2) higher at age 17 than in those with A/T or T/T genotypes. The design of PHB limited follow-up of any single individual to 4 years, and may have reduced the ability to detect any age-by-genotype interaction in this cohort. The A/A genotype of rs9939609 in the FTO gene is associated with higher longitudinal BMI profiles in non-Hispanic whites from two different cohorts. The association may change with age, with the A/A genotype being associated with a larger BMI difference in late adolescence than in childhood, though this was observed only in the BHS cohort and requires verification.

Maturity-associated variation in change of direction and dribbling speed in early pubertal years and 5-year developmental changes in young soccer players.

PubMed

Valente-Dos-Santos, J; Coelho-E-Silva, M J; Vaz, V; Figueiredo, A J; Capranica, L; Sherar, L B; Elferink-Gemser, M T; Malina, R M

2014-06-01

The purpose of the current study was to assess the developmental changes in change of direction and dribbling speed in youth soccer players taking into account skeletal age (SA), maturity status, body size, estimated fat mass, aerobic endurance, lower limb explosive strength and annual volume of training. Eighty-three male soccer players aged 10-15 years (SA) at baseline were annually followed over 5 years, resulting in an average 4.4 observations per player. After testing for multicollinearity, multi-level regression modeling was used to examine the longitudinal developmental changes on change of direction and dribbling speed. Maturity-associated variability was significant in change of direction and also dribbling speed among young soccer players aged 12-14 years with better scores being performed by late maturers. Moreover, the predicted longitudinal scores for change of direction and dribbling speed improved with SA (P<0.01), SA2 (P<0.01) and skeletal maturity status entered as an additional developmental predictor (P<0.05). Estimated fat-free mass (P<0.01), aerobic endurance (P<0.01) and lower limb strength (P<0.01) were additional predictors in both models. The soccer-specific skill, dibbling speed, was also explained by annual volume of training (P<0.05). Skeletal maturity status explains inter-individual variability on maximal short-term run performances with and without the ball possession at early ages of participation in competitive soccer. The effects tend to persist across ages combined with longitudinal changes in body composition and functional fitness. In the particular case of the ball test, annual volume of training was also a longitudinal performance predictor.

Ethnic disparities in childhood BMI trajectories and obesity and potential causes among 29,250 US children: Findings from the Early Childhood Longitudinal Study-Birth and Kindergarten Cohorts.

PubMed

Min, Jungwon; Wen, Xiaozhong; Xue, Hong; Wang, Youfa

2018-06-15

Study sex- and ethnic-specific childhood BMI growth trajectories of US children, and explore the potential causes of ethnic disparities in childhood BMI trajectories, including household socio-economic status (SES) and parenting practice using nationally representative longitudinal data. BMI trajectory curves between 7 months to 16 years of age were fitted using mixed effect models with fractional polynomial functions using pooled 10-year (1998-2008) longitudinal data collected from 29,254 children from two US nationally representative cohorts-Early Childhood Longitudinal Study-Birth (ECLS-B, 2001) and Kindergarten (ECLS-K, 1998-99). A multivariable regression model was used to examine the effects of SES and parenting factors on ethnic disparities in childhood BMI trajectory. Hispanic boys (HB) and African-American girls (AAG) continuously had the highest prevalence of overweight and obesity (HB: 52.5%, AAG: 49.1% around age of 11) and mean BMI after adiposity rebound than their counterparts. They had the earliest adiposity rebound (age mean [SD]: HB- 57.9 [7.8]; AAG- 59.0 [7.2] months), steeper BMI growth velocity (HB- 5.7 [1.8]; AAG- 7.0 [1.5] 10 -2  kg/m 2 /month), and highest area under curve (HB- 2724.5 [489.8]; AAG- 2681.2 [426.7] kg/m 2 *month) from adiposity rebound to 16 years of age. The racial/ethnic disparities in childhood BMI trajectories were associated with household SES and family rules for children's regular bedtime (p < 0.05). In the US, ethnic disparities in childhood BMI trajectories and obesity are apparent starting from adiposity rebound around age of five. Some minority groups have unfavorable BMI trajectories. These disparities are partially explained by household SES and parenting factors.

Drug Use Patterns and Continuous Enrollment in College:Results From a Longitudinal Study

PubMed Central

Arria, Amelia M.; Garnier-Dykstra, Laura M.; Caldeira, Kimberly M.; Vincent, Kathryn B.; Winick, Emily R.; O’Grady, Kevin E.

2013-01-01

Objective: Few longitudinal studies have examined the relationship between illicit drug use and academic outcomes among college students. This study characterized drug use patterns of a cohort of young adults who were originally enrolled as first-time, first-year college students in a longitudinal study. It evaluated the association between these drug use patterns and continuous enrollment during college, holding constant demographic characteristics, high school grade point average, fraternity/sorority involvement, personality/temperament characteristics, nicotine dependence, and alcohol use disorder. Method: Participants (n = 1,133; 47% male) were purposively selected from one university and interviewed annually for 4 years, beginning with their first year of college, regardless of continued college attendance. Enrollment data were culled from administrative records. Group-based trajectory analyses characterized 4-year longitudinal drug use patterns. Two grouping variables were derived based on (a) marijuana use frequency and (b) number of illicit drugs used other than marijuana. Seventy-one percent of the sample was continuously enrolled in the home institution during the first 4 years of study. Results: Multivariable logistic regression models demonstrated that infrequent, increasing, and chronic/heavy marijuana use patterns were significantly associated with discontinuous enrollment (adjusted odds ratio = 1.66, 1.74, and 1.99, respectively), compared with minimal use, holding constant covariates. In separate models, drug use other than marijuana also was significantly associated with discontinuous enrollment. Conclusions: Marijuana use and other illicit drug use are both associated with a decreased likelihood of continuous enrollment in college, independent of several other possible risk factors. These findings highlight the need for early intervention with illicit drug users to mitigate possible negative academic consequences. PMID:23200152

Longitudinal Association of Anthropometry with Mammographic Breast Density in the Study of Women's Health Across the Nation (Swan)

PubMed Central

Reeves, Katherine W.; Stone, Roslyn A.; Modugno, Francesmary; Ness, Roberta B.; Vogel, Victor G.; Weissfeld, Joel L.; Habel, Laurel A.; Sternfeld, Barbara; Cauley, Jane A.

2009-01-01

High percent mammographic breast density is strongly associated with increased breast cancer risk. Though body mass index (BMI) is positively associated with risk of postmenopausal breast cancer, BMI is negatively associated with percent breast density in cross-sectional studies. Few longitudinal studies have evaluated associations between BMI and weight and mammographic breast density. We studied the longitudinal relationships between anthropometry and breast density in a prospective cohort of 834 pre- and perimenopausal women enrolled in an ancillary study to the Study of Women's Health Across the Nation (SWAN). Routine screening mammograms were collected and read for breast density. Random intercept regression models were used to evaluate whether annual BMI change was associated with changes over time in dense breast area and percent density. The study population was 7.4% African American, 48.8% Caucasian, 21.8% Chinese, and 21.9% Japanese. Mean follow-up was 4.8 years. Mean annual weight change was +0.32 kg/year, mean change in dense area was -0.77 cm2/year, and mean change in percent density was -1.14%/year. In fully adjusted models, annual change in BMI was not significantly associated with changes in dense breast area (-0.17 cm2, 95% CI -0.64, 0.29). Borderline significant negative associations were observed between annual BMI change and annual percent density change, with percent density decreasing 0.36% (95% CI -0.74, 0.02) for a one unit increase in BMI over a year. This longitudinal study provides modest evidence that changes in BMI are not associated with changes in dense area, yet may be negatively associated with percent density. PMID:19065651

Examining solutions to missing data in longitudinal nursing research.

PubMed

Roberts, Mary B; Sullivan, Mary C; Winchester, Suzy B

2017-04-01

Longitudinal studies are highly valuable in pediatrics because they provide useful data about developmental patterns of child health and behavior over time. When data are missing, the value of the research is impacted. The study's purpose was to (1) introduce a three-step approach to assess and address missing data and (2) illustrate this approach using categorical and continuous-level variables from a longitudinal study of premature infants. A three-step approach with simulations was followed to assess the amount and pattern of missing data and to determine the most appropriate imputation method for the missing data. Patterns of missingness were Missing Completely at Random, Missing at Random, and Not Missing at Random. Missing continuous-level data were imputed using mean replacement, stochastic regression, multiple imputation, and fully conditional specification (FCS). Missing categorical-level data were imputed using last value carried forward, hot-decking, stochastic regression, and FCS. Simulations were used to evaluate these imputation methods under different patterns of missingness at different levels of missing data. The rate of missingness was 16-23% for continuous variables and 1-28% for categorical variables. FCS imputation provided the least difference in mean and standard deviation estimates for continuous measures. FCS imputation was acceptable for categorical measures. Results obtained through simulation reinforced and confirmed these findings. Significant investments are made in the collection of longitudinal data. The prudent handling of missing data can protect these investments and potentially improve the scientific information contained in pediatric longitudinal studies. © 2017 Wiley Periodicals, Inc.

Population Income and Longitudinal Trends in Living Kidney Donation in the United States

PubMed Central

Dong, Jianghu; Gill, John

2015-01-01

Living kidney donation is declining in the United States. We examined longitudinal trends in living donation as a function of median household income and donor relation to assess the effect of financial barriers on donation in a changing economic environment. The zip code–level median household income of all 71,882 living donors was determined by linkage to the 2000 US Census. Longitudinal changes in the rate of donation were determined in income quintiles between 1999 and 2004, when donations were increasing, and between 2005 and 2010, when donations were declining. Rates were adjusted for population differences in age, sex, race, and ESRD rate using multilevel linear regression models. Between 1999 and 2004, the rate of growth in living donation per million population was directly related to income, increasing progressively from the lowest to highest income quintile, with annualized changes of 0.55 (95% confidence interval [95% CI], 0.14 to 1.05) for Q1 and 1.77 (95% CI, 0.66 to 2.77) for Q5 (P<0.05). Between 2005 and 2010, donation declined in Q1, Q2, and Q3; was stable in Q4; and continued to grow in Q5. Longitudinal changes varied by donor relationship, and the association of income with longitudinal changes also varied by donor relationship. In conclusion, changes in living donation in the past decade varied by median household income, resulting in increased disparities in donation between low- and high-income populations. These findings may inform public policies to support living donation during periods of economic volatility. PMID:25035519

Longitudinal analysis of pulmonary dysfunction in the initial years of employment in the grain industry.

PubMed

Olfert, S M; Pahwa, P; Dosman, J A

2005-11-01

The negative health effects of exposure to grain dust have previously been examined, but few studies have observed the effects on newly hired employees. Young grain workers are of interest because changes in pulmonary function may occur after a short duration of employment, and because older grain workers may represent a survivor population. The New Grain Workers Study (NGWS), a longitudinal study of 299 newly hired male grain industry workers, was conducted between 1980 and 1985. The objectives were to determine the effects of employment in the grain industry on pulmonary function. Pre-employment physical examinations and pulmonary function tests were conducted on subjects at the Division of Respiratory Medicine, Department of Medicine, Royal University Hospital, University of Saskatchewan. The Grain Dust Medical Surveillance Program (GDMSP) was a Labour Canada program that began in 1978. All subjects were grain workers employed in the grain industry in Saskatchewan. All subjects completed a respiratory symptoms questionnaire and underwent pulmonary function testing. Baseline observations were recorded every three years between 1978 and 1993. Data were available on 2184 grain workers. Generalized estimating equations were used to fit marginal and transitional multivariable regression models to determine the effects of grain dust exposure on pulmonary function. Marginal and transitional models were then compared. Height, exposure weeks, and previous FVC were predictive of FVC in the NGWS, while exposure weeks and previous FEV1 were predictive of FEV1. These models, as well as a transitional regression model built using the GDMSP data, were used to compute predicted mean annual decline inpulmonary function. Non-smoking grain workers in the NGWS had the highest pulmonary function test values, but also had the greatest predicted annual decline in pulmonary function. Ever-smoking grain workers in the GDMSP had the lowest pulmonary function test values. Non-smoking grain workers in the GDMSP had the least predicted annual decline in pulmonary function.

Factors associated with dental caries in a group of American Indian children at age 36 months.

PubMed

Warren, John J; Blanchette, Derek; Dawson, Deborah V; Marshall, Teresa A; Phipps, Kathy R; Starr, Delores; Drake, David R

2016-04-01

Early childhood caries (ECC) is rampant among American Indian children, but there has been relatively little study of this problem. This article reports on risk factors for caries for a group of American Indian children at age 36 months as part of a longitudinal study. Pregnant women from a Northern Plains Tribal community were recruited to participate in a longitudinal study of caries and caries risk factors. Standardized dental examinations were completed on children, and questionnaires were completed by mothers at baseline and when children were 4, 8, 12, 16, 22, 28, and 36 months of age. Examinations were surface-specific for dental caries, and the questionnaires collected data on demographic, dietary, and behavioral factors. Nonparametric bivariate tests and logistic regression models were used to identify risk factors for caries at 36 months, and negative binomial regression was used to identify factors related to caries severity (dmf counts). Among the 232 children, and caries prevalence for cavitated lesions was 80%, with an additional 15% having only noncavitated lesions. The mean dmfs was 9.6, and of the total dmfs, nearly 62% of affected surfaces were decayed, 31% were missing, and 7% were filled. Logistic regression identified higher added-sugar beverage consumption, younger maternal age at baseline, higher maternal DMFS at baseline, and greater number of people in the household as significant (P < 0.05) risk factors. Negative binomial regression found that only maternal DMFS was associated with child dmf counts. By the age of 36 months, dental caries is nearly universal in this population of American Indian children. Caries risk factors included sugared beverage consumption, greater household size, and maternal factors, but further analyses are needed to better understand caries in this population. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Long Term Exposure to NO2 and Diabetes Incidence in the Black Women's Health Study

PubMed Central

Coogan, Patricia F.; White, Laura F.; Yu, Jeffrey; Burnett, Richard T.; Marshall, Julian D.; Seto, Edmund; Brook, Robert D.; Palmer, Julie R.; Rosenberg, Lynn; Jerrett, Michael

2016-01-01

While laboratory studies show that air pollutants can potentiate insulin resistance, the epidemiologic evidence regarding the association of air pollution with diabetes incidence is conflicting. The purpose of the present study was to assess the association of the traffic-related nitrogen dioxide (NO2) with the incidence of diabetes in a longitudinal cohort study of African American women. We used Cox proportional hazards models to calculate hazard ratios and 95% confidence intervals (CI) for diabetes associated with exposure to NO2 among 43,003 participants in the Black Women's Health Study (BWHS). Pollutant levels at participant residential locations were estimated with 1) a land use regression model for participants living in 56 metropolitan areas, and 2) a dispersion model for participants living in 27 of the cities. From 1995-2011, 4387 cases of diabetes occurred. The hazard ratios per interquartile range of NO2 (9.7 ppb), adjusted for age, metropolitan area, education, vigorous exercise, body mass index, smoking, and diet, were 0.96 (95% CI 0.88-1.06) using the land use regression model estimates and 0.94 (95% CI 0.80, 1.10) using the dispersion model estimates. The present results do not support the hypothesis that exposure to NO2 contributes to diabetes incidence in African American women. PMID:27124624

Dynamic Network Logistic Regression: A Logistic Choice Analysis of Inter- and Intra-Group Blog Citation Dynamics in the 2004 US Presidential Election

PubMed Central

2013-01-01

Methods for analysis of network dynamics have seen great progress in the past decade. This article shows how Dynamic Network Logistic Regression techniques (a special case of the Temporal Exponential Random Graph Models) can be used to implement decision theoretic models for network dynamics in a panel data context. We also provide practical heuristics for model building and assessment. We illustrate the power of these techniques by applying them to a dynamic blog network sampled during the 2004 US presidential election cycle. This is a particularly interesting case because it marks the debut of Internet-based media such as blogs and social networking web sites as institutionally recognized features of the American political landscape. Using a longitudinal sample of all Democratic National Convention/Republican National Convention–designated blog citation networks, we are able to test the influence of various strategic, institutional, and balance-theoretic mechanisms as well as exogenous factors such as seasonality and political events on the propensity of blogs to cite one another over time. Using a combination of deviance-based model selection criteria and simulation-based model adequacy tests, we identify the combination of processes that best characterizes the choice behavior of the contending blogs. PMID:24143060

Gastrointestinal Spatiotemporal mRNA Expression of Ghrelin vs Growth Hormone Receptor and New Growth Yield Machine Learning Model Based on Perturbation Theory.

PubMed

Ran, Tao; Liu, Yong; Li, Hengzhi; Tang, Shaoxun; He, Zhixiong; Munteanu, Cristian R; González-Díaz, Humberto; Tan, Zhiliang; Zhou, Chuanshe

2016-07-27

The management of ruminant growth yield has economic importance. The current work presents a study of the spatiotemporal dynamic expression of Ghrelin and GHR at mRNA levels throughout the gastrointestinal tract (GIT) of kid goats under housing and grazing systems. The experiments show that the feeding system and age affected the expression of either Ghrelin or GHR with different mechanisms. Furthermore, the experimental data are used to build new Machine Learning models based on the Perturbation Theory, which can predict the effects of perturbations of Ghrelin and GHR mRNA expression on the growth yield. The models consider eight longitudinal GIT segments (rumen, abomasum, duodenum, jejunum, ileum, cecum, colon and rectum), seven time points (0, 7, 14, 28, 42, 56 and 70 d) and two feeding systems (Supplemental and Grazing feeding) as perturbations from the expected values of the growth yield. The best regression model was obtained using Random Forest, with the coefficient of determination R(2) of 0.781 for the test subset. The current results indicate that the non-linear regression model can accurately predict the growth yield and the key nodes during gastrointestinal development, which is helpful to optimize the feeding management strategies in ruminant production system.

Gastrointestinal Spatiotemporal mRNA Expression of Ghrelin vs Growth Hormone Receptor and New Growth Yield Machine Learning Model Based on Perturbation Theory

PubMed Central

Ran, Tao; Liu, Yong; Li, Hengzhi; Tang, Shaoxun; He, Zhixiong; Munteanu, Cristian R.; González-Díaz, Humberto; Tan, Zhiliang; Zhou, Chuanshe

2016-01-01

The management of ruminant growth yield has economic importance. The current work presents a study of the spatiotemporal dynamic expression of Ghrelin and GHR at mRNA levels throughout the gastrointestinal tract (GIT) of kid goats under housing and grazing systems. The experiments show that the feeding system and age affected the expression of either Ghrelin or GHR with different mechanisms. Furthermore, the experimental data are used to build new Machine Learning models based on the Perturbation Theory, which can predict the effects of perturbations of Ghrelin and GHR mRNA expression on the growth yield. The models consider eight longitudinal GIT segments (rumen, abomasum, duodenum, jejunum, ileum, cecum, colon and rectum), seven time points (0, 7, 14, 28, 42, 56 and 70 d) and two feeding systems (Supplemental and Grazing feeding) as perturbations from the expected values of the growth yield. The best regression model was obtained using Random Forest, with the coefficient of determination R2 of 0.781 for the test subset. The current results indicate that the non-linear regression model can accurately predict the growth yield and the key nodes during gastrointestinal development, which is helpful to optimize the feeding management strategies in ruminant production system. PMID:27460882

APOL1 genetic variants are not associated with longitudinal blood pressure in young black adults.

PubMed

Chen, Teresa K; Estrella, Michelle M; Vittinghoff, Eric; Lin, Feng; Gutierrez, Orlando M; Kramer, Holly; Lewis, Cora E; Kopp, Jeffrey B; Allen, Norrina B; Winkler, Cheryl A; Bibbins-Domingo, Kirsten B; Peralta, Carmen A

2017-10-01

Whether APOL1 polymorphisms contribute to the excess risk of hypertension among blacks is unknown. To assess this we evaluated whether self-reported race and, in blacks, APOL1 risk variants (high-risk [2 risk alleles] versus low-risk [0-1 risk allele]) were associated with longitudinal blood pressure. Blood pressure trajectories were determined using linear mixed-effects (slope) and latent class models (5 distinct groups) during 25 years of follow-up in the Coronary Artery Risk Development in Young Adults Study. Associations of race and APOL1 genotypes with blood pressure change, separately, using linear mixed-effects and multinomial logistic regression models, adjusting for demographic, socioeconomic, and traditional hypertension risk factors, anti-hypertensive medication use, and kidney function were evaluated. Among 1700 whites and 1330 blacks (13% APOL1 high-risk, mean age 25 years; 46% male) mean mid-, ([systolic + diastolic blood pressure]/2), systolic, and diastolic blood pressures were 89, 110, and 69 mm Hg, respectively. One percent of participants used anti-hypertensive medications at baseline. Compared to whites, blacks, regardless of APOL1 genotype, had significantly greater increases in mid-blood pressure and were more likely to experience significantly increasing mid-blood pressure trajectories with adjusted relative risk ratios of 5.21 and 7.27 for moderate-increasing and elevated-increasing versus low-stable blood pressure, respectively. Among blacks, longitudinal mid-blood pressure changes and mid-blood pressure trajectory classification were similar by APOL1 risk status. Modeling systolic and diastolic blood pressure as outcomes yielded similar findings. From young adulthood to mid-life, blacks have greater blood pressure increases versus whites that are not fully explained by traditional risk factors. Thus APOL1 variants are not associated with longitudinal blood pressure in blacks. Copyright © 2017 International Society of Nephrology. All rights reserved.

Retinol-Binding Protein 4 and Lipids Prospectively Measured During Early to Mid-Pregnancy in Relation to Preeclampsia and Preterm Birth Risk.

PubMed

Mendola, Pauline; Ghassabian, Akhgar; Mills, James L; Zhang, Cuilin; Tsai, Michael Y; Liu, Aiyi; Yeung, Edwina H

2017-06-01

Maternal retinol-binding protein 4 (RBP4) and lipids may relate to preeclampsia and preterm birth risk but longitudinal data are lacking. This study examines these biomarkers longitudinally during pregnancy in relation to preeclampsia and preterm birth risk. Maternal serum samples from the Calcium for Preeclampsia Prevention (CPEP) trial were analyzed at baseline: average 15 gestational weeks; mid-pregnancy: average 27 weeks; and at >34 weeks. We measured RBP4, total cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides and lipoprotein (a) (Lp(a)). Cross-sectional logistic regression analyses estimated the odds ratio (OR) and 95% confidence intervals (CI) for preterm preeclampsia (n = 63), term preeclampsia (n = 104), and preterm delivery (n = 160) associated with RBP4 and lipids at baseline and mid-pregnancy compared with controls (n = 136). Longitudinal trajectories across pregnancy were assessed using mixed linear models with fixed effects. Adjusted models included clinical and demographic factors. RBP4 concentrations at baseline and mid-pregnancy were associated with a 4- to 8-fold increase in preterm preeclampsia risk but were not associated with term preeclampsia. RBP4 measured mid-pregnancy was also associated with preterm birth (OR = 6.67, 95% CI: 1.65, 26.84). Higher triglyceride concentrations in mid-pregnancy were associated with a 2- to 4-fold increased risk for both preeclampsia and preterm birth. Longitudinal models demonstrate that both preterm preeclampsia and preterm birth cases had elevated RBP4 throughout gestation. Elevated RBP4 is detectable early in pregnancy and its strong relation with preterm preeclampsia merits further investigation and confirmation to evaluate its potential use as a predictor, particularly among high-risk women. © Published by Oxford University Press on behalf of American Journal of Hypertension Ltd 2017. This work is written by (a) US Government employees(s) and is in the public domain in the US.

Associations of physical activity and sport and exercise with at-risk substance use in young men: a longitudinal study.

PubMed

Henchoz, Yves; Dupuis, Marc; Deline, Stéphane; Studer, Joseph; Baggio, Stéphanie; N'Goran, Alexandra Adjua; Daeppen, Jean-Bernard; Gmel, Gerhard

2014-07-01

This study aims to measure the associations of physical activity and one of its components, sport and exercise, with at-risk substance use in a population of young men. Baseline (2010-2012) and follow-up (2012-2013) data of 4748 young Swiss men from the Cohort Study on Substance Use Risk Factors (C-SURF) were used. Cross-sectional and prospective associations between at-risk substance use and both sport and exercise and physical activities were measured using Chi-squared tests and logistic regression models adjusting for covariates. At baseline, logistic regression indicated that sport and exercise is negatively associated with at-risk use of cigarettes and cannabis. A positive association was obtained between physical activity and at-risk alcohol use. At baseline, sport and exercise was negatively associated with at-risk use of cigarettes and cannabis at follow-up. Adjusted for sport and exercise, physical activity was positively associated with at-risk use of cigarettes and cannabis. Sport and exercise is cross-sectionally and longitudinally associated with a low prevalence of at-risk use of cigarettes and cannabis. This protective effect was not observed for physical activity broadly defined. Taking a substance use prevention perspective, the promotion of sport and exercise among young adults should be encouraged. Copyright © 2014 Elsevier Inc. All rights reserved.

Identifying patterns of item missing survey data using latent groups: an observational study

PubMed Central

McElwee, Paul; Nathan, Andrea; Burton, Nicola W; Turrell, Gavin

2017-01-01

Objectives To examine whether respondents to a survey of health and physical activity and potential determinants could be grouped according to the questions they missed, known as ‘item missing’. Design Observational study of longitudinal data. Setting Residents of Brisbane, Australia. Participants 6901 people aged 40–65 years in 2007. Materials and methods We used a latent class model with a mixture of multinomial distributions and chose the number of classes using the Bayesian information criterion. We used logistic regression to examine if participants’ characteristics were associated with their modal latent class. We used logistic regression to examine whether the amount of item missing in a survey predicted wave missing in the following survey. Results Four per cent of participants missed almost one-fifth of the questions, and this group missed more questions in the middle of the survey. Eighty-three per cent of participants completed almost every question, but had a relatively high missing probability for a question on sleep time, a question which had an inconsistent presentation compared with the rest of the survey. Participants who completed almost every question were generally younger and more educated. Participants who completed more questions were less likely to miss the next longitudinal wave. Conclusions Examining patterns in item missing data has improved our understanding of how missing data were generated and has informed future survey design to help reduce missing data. PMID:29084795

Multi-Axis Identifiability Using Single-Surface Parameter Estimation Maneuvers on the X-48B Blended Wing Body

NASA Technical Reports Server (NTRS)

Ratnayake, Nalin A.; Koshimoto, Ed T.; Taylor, Brian R.

2011-01-01

The problem of parameter estimation on hybrid-wing-body type aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aero- dynamic control effectors that act in coplanar motion. This fact adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of system inputs must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, asymmetric, single-surface maneuvers are used to excite multiple axes of aircraft motion simultaneously. Time history reconstructions of the moment coefficients computed by the solved regression models are then compared to each other in order to assess relative model accuracy. The reduced flight-test time required for inner surface parameter estimation using multi-axis methods was found to come at the cost of slightly reduced accuracy and statistical confidence for linear regression methods. Since the multi-axis maneuvers captured parameter estimates similar to both longitudinal and lateral-directional maneuvers combined, the number of test points required for the inner, aileron-like surfaces could in theory have been reduced by 50%. While trends were similar, however, individual parameters as estimated by a multi-axis model were typically different by an average absolute difference of roughly 15-20%, with decreased statistical significance, than those estimated by a single-axis model. The multi-axis model exhibited an increase in overall fit error of roughly 1-5% for the linear regression estimates with respect to the single-axis model, when applied to flight data designed for each, respectively.

Sibling dilution hypothesis: a regression surface analysis.

PubMed

Marjoribanks, K

2001-08-01

This study examined relationships between sibship size (the number of children in a family), birth order, and measures of academic performance, academic self-concept, and educational aspirations at different levels of family educational resources. As part of a national longitudinal study of Australian secondary school students data were collected from 2,530 boys and 2,450 girls in Years 9 and 10. Regression surfaces were constructed from models that included terms to account for linear, interaction, and curvilinear associations among the variables. Analysis suggests the general propositions (a) family educational resources have significant associations with children's school-related outcomes at different levels of sibling variables, the relationships for girls being curvilinear, and (b) sibling variables continue to have small significant associations with affective and cognitive outcomes, after taking into account variations in family educational resources. That is, the investigation provides only partial support for the sibling dilution hypothesis.

Change in active travel and changes in recreational and total physical activity in adults: longitudinal findings from the iConnect study

PubMed Central

2013-01-01

Background To better understand the health benefits of promoting active travel, it is important to understand the relationship between a change in active travel and changes in recreational and total physical activity. Methods These analyses, carried out in April 2012, use longitudinal data from 1628 adult respondents (mean age 54 years; 47% male) in the UK-based iConnect study. Travel and recreational physical activity were measured using detailed seven-day recall instruments. Adjusted linear regression models were fitted with change in active travel defined as ‘decreased’ (<−15 min/week), ‘maintained’ (±15 min/week) or ‘increased’ (>15 min/week) as the primary exposure variable and changes in (a) recreational and (b) total physical activity (min/week) as the primary outcome variables. Results Active travel increased in 32% (n=529), was maintained in 33% (n=534) and decreased in 35% (n=565) of respondents. Recreational physical activity decreased in all groups but this decrease was not greater in those whose active travel increased. Conversely, changes in active travel were associated with commensurate changes in total physical activity. Compared with those whose active travel remained unchanged, total physical activity decreased by 176.9 min/week in those whose active travel had decreased (adjusted regression coefficient −154.9, 95% CI −195.3 to −114.5) and was 112.2 min/week greater among those whose active travel had increased (adjusted regression coefficient 135.1, 95% CI 94.3 to 175.9). Conclusion An increase in active travel was associated with a commensurate increase in total physical activity and not a decrease in recreational physical activity. PMID:23445724

Estimating inverse-probability weights for longitudinal data with dropout or truncation: The xtrccipw command.

PubMed

Daza, Eric J; Hudgens, Michael G; Herring, Amy H

Individuals may drop out of a longitudinal study, rendering their outcomes unobserved but still well defined. However, they may also undergo truncation (for example, death), beyond which their outcomes are no longer meaningful. Kurland and Heagerty (2005, Biostatistics 6: 241-258) developed a method to conduct regression conditioning on nontruncation, that is, regression conditioning on continuation (RCC), for longitudinal outcomes that are monotonically missing at random (for example, because of dropout). This method first estimates the probability of dropout among continuing individuals to construct inverse-probability weights (IPWs), then fits generalized estimating equations (GEE) with these IPWs. In this article, we present the xtrccipw command, which can both estimate the IPWs required by RCC and then use these IPWs in a GEE estimator by calling the glm command from within xtrccipw. In the absence of truncation, the xtrccipw command can also be used to run a weighted GEE analysis. We demonstrate the xtrccipw command by analyzing an example dataset and the original Kurland and Heagerty (2005) data. We also use xtrccipw to illustrate some empirical properties of RCC through a simulation study.

Estimating inverse-probability weights for longitudinal data with dropout or truncation: The xtrccipw command

PubMed Central

Hudgens, Michael G.; Herring, Amy H.

2017-01-01

Individuals may drop out of a longitudinal study, rendering their outcomes unobserved but still well defined. However, they may also undergo truncation (for example, death), beyond which their outcomes are no longer meaningful. Kurland and Heagerty (2005, Biostatistics 6: 241–258) developed a method to conduct regression conditioning on nontruncation, that is, regression conditioning on continuation (RCC), for longitudinal outcomes that are monotonically missing at random (for example, because of dropout). This method first estimates the probability of dropout among continuing individuals to construct inverse-probability weights (IPWs), then fits generalized estimating equations (GEE) with these IPWs. In this article, we present the xtrccipw command, which can both estimate the IPWs required by RCC and then use these IPWs in a GEE estimator by calling the glm command from within xtrccipw. In the absence of truncation, the xtrccipw command can also be used to run a weighted GEE analysis. We demonstrate the xtrccipw command by analyzing an example dataset and the original Kurland and Heagerty (2005) data. We also use xtrccipw to illustrate some empirical properties of RCC through a simulation study. PMID:29755297

Estimation of longitudinal stability and control derivatives for an icing research aircraft from flight data

NASA Technical Reports Server (NTRS)

Batterson, James G.; Omara, Thomas M.

1989-01-01

The results of applying a modified stepwise regression algorithm and a maximum likelihood algorithm to flight data from a twin-engine commuter-class icing research aircraft are presented. The results are in the form of body-axis stability and control derivatives related to the short-period, longitudinal motion of the aircraft. Data were analyzed for the baseline (uniced) and for the airplane with an artificial glaze ice shape attached to the leading edge of the horizontal tail. The results are discussed as to the accuracy of the derivative estimates and the difference between the derivative values found for the baseline and the iced airplane. Additional comparisons were made between the maximum likelihood results and the modified stepwise regression results with causes for any discrepancies postulated.

The challenge of staying happier: testing the Hedonic Adaptation Prevention model.

PubMed

Sheldon, Kennon M; Lyubomirsky, Sonja

2012-05-01

The happiness that comes from a particular success or change in fortune abates with time. The Hedonic Adaptation Prevention (HAP) model specifies two routes by which the well-being gains derived from a positive life change are eroded--the first involving bottom-up processes (i.e., declining positive emotions generated by the positive change) and the second involving top-down processes (i.e., increased aspirations for even more positivity). The model also specifies two moderators that can forestall these processes--continued appreciation of the original life change and continued variety in change-related experiences. The authors formally tested the predictions of the HAP model in a 3-month three-wave longitudinal study of 481 students. Temporal path analyses and moderated regression analyses provided good support for the model. Implications for the stability of well-being, the feasibility of "the pursuit of happiness," and the appeal of overconsumption are discussed.

A Multi-Study Analysis of Conceptual and Measurement Issues Related to Health Research on Acculturation in Latinos

PubMed Central

Andrews, Arthur R.; Bridges, Ana J.; Gomez, Debbie

2014-01-01

Purpose The aims of the study were to evaluate the orthogonality of acculturation for Latinos. Design Regression analyses were used to examine acculturation in two Latino samples (N = 77; N = 40). In a third study (N = 673), confirmatory factor analyses compared unidimensional and bidimensional models. Method Acculturation was assessed with the ARSMA-II (Studies 1 and 2), and language proficiency items from the Children of Immigrants Longitudinal Study (Study 3). Results In Studies 1 and 2, the bidimensional model accounted for slightly more variance (R2Study 1 = .11; R2Study 2 = .21) than the unidimensional model (R2Study 1 = .10; R2Study 2 = .19). In Study 3, the bidimensional model evidenced better fit (Akaike information criterion = 167.36) than the unidimensional model (Akaike information criterion = 1204.92). Discussion/Conclusions Acculturation is multidimensional. Implications for Practice Care providers should examine acculturation as a bidimensional construct. PMID:23361579

Low self-esteem prospectively predicts depression in adolescence and young adulthood.

PubMed

Orth, Ulrich; Robins, Richard W; Roberts, Brent W

2008-09-01

Low self-esteem and depression are strongly correlated in cross-sectional studies, yet little is known about their prospective effects on each other. The vulnerability model hypothesizes that low self-esteem serves as a risk factor for depression, whereas the scar model hypothesizes that low self-esteem is an outcome, not a cause, of depression. To test these models, the authors used 2 large longitudinal data sets, each with 4 repeated assessments between the ages of 15 and 21 years and 18 and 21 years, respectively. Cross-lagged regression analyses indicated that low self-esteem predicted subsequent levels of depression, but depression did not predict subsequent levels of self-esteem. These findings held for both men and women and after controlling for content overlap between the self-esteem and depression scales. Thus, the results supported the vulnerability model, but not the scar model, of self-esteem and depression.

Income and Child Maltreatment in Unmarried Families: Evidence from the Earned Income Tax Credit.

PubMed

Berger, Lawrence M; Font, Sarah A; Slack, Kristen S; Waldfogel, Jane

2017-12-01

This study estimates the associations of income with both (self-reported) child protective services (CPS) involvement and parenting behaviors that proxy for child abuse and neglect risk among unmarried families. Our primary strategy follows the instrumental variables (IV) approach employed by Dahl and Lochner (2012), which leverages variation between states and over time in the generosity of the total state and federal Earned Income Tax Credit for which a family is eligible to identify exogenous variation in family income. As a robustness check, we also estimate standard OLS regressions (linear probability models), reduced form OLS regressions, and OLS regressions with the inclusion of a control function (each with and without family-specific fixed effects). Our micro-level data are drawn from the Fragile Families and Child Wellbeing Study, a longitudinal birth-cohort of relatively disadvantaged urban children who have been followed from birth to age nine. Results suggest that an exogenous increase in income is associated with reductions in behaviorally-approximated child neglect and CPS involvement, particularly among low-income single-mother families.

Longitudinal Assessment of Effort-Reward Imbalance and Job Strain Across Pregnancy: A Preliminary Study.

PubMed

Meyer, John D; Muntaner, Carles; O'Campo, Patricia; Warren, Nicolas

2016-07-01

To assess longitudinal changes in occupational effort-reward imbalance (ERI) and demand-control (DC) scores across pregnancy and examine associations with blood pressure (BP) during pregnancy. A pilot repeated-measures survey was administered four times to a sample of working women across pregnancy using the ERI and DC instruments. Demographic data and blood pressure measurements were collected at each interval. Growth mixture modeling was used to examine trajectories of change in occupational characteristics. Associations with BP were examined using repeated-measures linear regression models. ERI model components (effort, reward, and overcommitment) all declined across pregnancy while job control remained stable. Increasing ERI trajectory was associated with higher systolic BP (b = 8.8; p < 0.001) as was high overcommitment; declining ERI also showed a lesser association with higher BP. Associations between DC trajectories and BP were much smaller, and non-significant once controlled for overcommitment. Self-assessed efforts, rewards, and overcommitment at work decline across pregnancy in our participants, while job control remains stable. Replication in a more diverse pregnant working population is warranted to confirm these results. These preliminary data suggest that further investigation into the factors that may be linked with improved work psychosocial climate during pregnancy may be useful in order to improve pregnancy outcomes.

Scoping review of response shift methods: current reporting practices and recommendations.

PubMed

Sajobi, Tolulope T; Brahmbatt, Ronak; Lix, Lisa M; Zumbo, Bruno D; Sawatzky, Richard

2018-05-01

Response shift (RS) has been defined as a change in the meaning of an individual's self-evaluation of his/her health status and quality of life. Several statistical model- and design-based methods have been developed to test for RS in longitudinal data. We reviewed the uptake of these methods in patient-reported outcomes (PRO) literature. CINHAHL, EMBASE, Medline, ProQuest, PsycINFO, and Web of Science were searched to identify English-language articles about RS published until 2016. Data on year and country of publication, PRO measure adopted, RS detection method, type of RS detected, and testing of underlying model assumptions were extracted from the included articles. Of the 1032 articles identified, 101 (9.8%) articles were included in the study. While 54.5 of the articles reported on the Then-test, 30.7% of the articles reported on Oort's or Schmitt's structural equation modeling (SEM) procedure. Newer RS detection methods, such as relative importance analysis and random forest regression, have been used less frequently. Less than 25% reported on testing the assumptions underlying the adopted RS detection method(s). Despite rapid methodological advancements in RS research, this review highlights the need for further research about RS detection methods for complex longitudinal data and standardized reporting guidelines.

Modeling radiation dosimetry to predict cognitive outcomes in pediatric patients with CNS embryonal tumors including medulloblastoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merchant, Thomas E.; Kiehna, Erin N.; Li Chenghong

2006-05-01

Purpose: Model the effects of radiation dosimetry on IQ among pediatric patients with central nervous system (CNS) tumors. Methods and Materials: Pediatric patients with CNS embryonal tumors (n = 39) were prospectively evaluated with serial cognitive testing, before and after treatment with postoperative, risk-adapted craniospinal irradiation (CSI) and conformal primary-site irradiation, followed by chemotherapy. Differential dose-volume data for 5 brain volumes (total brain, supratentorial brain, infratentorial brain, and left and right temporal lobes) were correlated with IQ after surgery and at follow-up by use of linear regression. Results: When the dose distribution was partitioned into 2 levels, both had amore » significantly negative effect on longitudinal IQ across all 5 brain volumes. When the dose distribution was partitioned into 3 levels (low, medium, and high), exposure to the supratentorial brain appeared to have the most significant impact. For most models, each Gy of exposure had a similar effect on IQ decline, regardless of dose level. Conclusions: Our results suggest that radiation dosimetry data from 5 brain volumes can be used to predict decline in longitudinal IQ. Despite measures to reduce radiation dose and treatment volume, the volume that receives the highest dose continues to have the greatest effect, which supports current volume-reduction efforts.« less

Longitudinal assessment of effort-reward imbalance and job strain across pregnancy: A preliminary study

PubMed Central

Meyer, John D; Muntaner, Carles; O'Campo, Patricia; Warren, Nicolas

2016-01-01

Objectives To assess longitudinal changes in occupational effort-reward imbalance (ERI) and demand-control (DC) scores across pregnancy and examine associations with blood pressure (BP) during pregnancy. Methods A pilot repeated-measures survey was administered four times to a sample of working women across pregnancy using the ERI and DC instruments. Demographic data and blood pressure measurements were collected at each interval. Growth mixture modeling was used to examine trajectories of change in occupational characteristics. Associations with BP were examined using repeated-measures linear regression models. Results ERI model components (effort, reward, and overcommitment) all declined across pregnancy while job control remained stable. Increasing ERI trajectory was associated with higher systolic BP (b=8.8; p<0.001) as was high overcommitment; declining ERI also showed a smaller association with higher BP. Associations between DC trajectories and BP were much smaller, and non-significant once controlled for overcommitment. Conclusions Self-assessed efforts, rewards, and overcommitment at work decline across pregnancy in our participants, while job control remains stable. Replication in a more diverse pregnant working population is warranted to confirm these results. These preliminary data suggest that further investigation into the factors that may be linked with improved work psychosocial climate during pregnancy may be useful in order to improve pregnancy outcomes. PMID:26948376

Multiple dimensions of spirituality in recovery: a lagged mediational analysis of Alcoholics Anonymous' principal theoretical mechanism of behavior change.

PubMed

Krentzman, Amy R; Cranford, James A; Robinson, Elizabeth A R

2013-01-01

Alcoholics Anonymous (AA) states that recovery is possible through spiritual experiences and spiritual awakenings. Research examining spirituality as a mediator of AA's effect on drinking has been mixed. It is unknown whether such findings are due to variations in the operationalization of key constructs, such as AA and spirituality. To answer these questions, the authors used a longitudinal model to test 2 dimensions of AA as focal predictors and 6 dimensions of spirituality as possible mediators of AA's association with drinking. Data from the first 18 months of a 3-year longitudinal study of 364 alcohol-dependent individuals were analyzed. Structural equation modeling was used to replicate the analyses of Kelly et al. (Alcohol Clin Exp Res. 2011;35:454-463) and to compare AA attendance and AA involvement as focal predictors. Multiple regression analyses were used to determine which spirituality dimensions changed as the result of AA participation. A trimmed, data-driven model was employed to test multiple mediation paths simultaneously. The findings of the Kelly et al. study were replicated. AA involvement was a stronger predictor of drinking outcomes than AA attendance. AA involvement predicted increases in private religious practices, daily spiritual experiences, and forgiveness of others. However, only private religious practices mediated the relationship between AA and drinking.

Are Evidence-based Practices Associated With Effective Prevention of Hospital-acquired Pressure Ulcers in US Academic Medical Centers?

PubMed

Padula, William V; Gibbons, Robert D; Valuck, Robert J; Makic, Mary B F; Mishra, Manish K; Pronovost, Peter J; Meltzer, David O

2016-05-01

In 2008, the Centers for Medicare and Medicaid Services (CMS) established nonpayment policies resulting from costliness of hospital-acquired pressure ulcers (HAPUs) to hospitals. This prompted hospitals to adopt quality improvement (QI) interventions that increase use of evidence-based practices (EBPs) for HAPU prevention. To evaluate the longitudinal impact of CMS policy and QI adoption on HAPU rates. We characterized longitudinal adoption of 25 QI interventions that support EBPs through hospital leadership, staff, information technology, and performance and improvement. Quarterly counts of HAPU incidence and inpatient characteristics were collected from 55 University HealthSystem Consortium hospitals between 2007 and 2012. Mixed-effects regression models tested the longitudinal association of CMS policy, HAPU coding, and QI on HAPU rates. The models assumed level-2 random intercepts and random effects for CMS policy and EBP implementation to account for between-hospital variability in HAPU incidence. Controlling for all 25 QI interventions, specific updates to EBPs for HAPU prevention had a significant, though modest reduction on HAPU rates (-1.86 cases/quarter; P=0.002) and the effect of CMS nonpayment policy on HAPU prevention was much greater (-11.32 cases/quarter; P<0.001). HAPU rates were significantly lower after changes in CMS reimbursement. Reductions are associated with hospital-wide implementation of EBPs for HAPU prevention. Given that administrative data were used, it remains unknown whether these improvements were due to changes in coding or improved quality of care.

Are Evidence-based Practices Associated with Effective Prevention of Hospital-acquired Pressure Ulcers in U.S. Academic Medical Centers?

PubMed Central

Padula, William V.; Gibbons, Robert D.; Valuck, Robert J.; Makic, Mary Beth F.; Mishra, Manish K.; Pronovost, Peter J.; Meltzer, David O.

2016-01-01

Background In 2008, the Centers for Medicare and Medicaid Services (CMS) established nonpayment policies resulting from costliness of hospital-acquired pressure ulcers (HAPUs) to hospitals. This prompted hospitals to adopt quality improvement (QI) interventions that increase use of evidence-based practices (EBPs) for HAPU prevention. Objective To evaluate the longitudinal impact of CMS policy and QI adoption on HAPU rates. Methods We characterized longitudinal adoption of 25 QI interventions that support EBPs through hospital leadership, staff, information technology, and performance and improvement. Quarterly counts of HAPU incidence and inpatient characteristics were collected from 55 UHC hospitals between 2007–2012. Mixed-effects regression models tested the longitudinal association of CMS policy, HAPU coding and QI on HAPU rates. The models assumed level-2 random-intercepts and random effects for CMS policy and EBP implementation to account for between-hospital variability in HAPU incidence. Results Controlling for all 25 QI interventions, specific updates to EBPs for HAPU prevention had a significant, though modest reduction on HAPU rates (−1.86 cases/quarter; p=0.002) and the effect of CMS nonpayment policy on HAPU prevention was much greater (−11.32 cases/quarter; p<0.001). Conclusions HAPU rates were significantly lower following changes in CMS reimbursement. Reductions are associated with hospital-wide implementation of EBPs for HAPU prevention. Given that administrative data were used, it remains unknown whether these improvements were due to changes in coding or improved quality of care. PMID:27078824

Traffic-related air pollution and spectacles use in schoolchildren

PubMed Central

Nieuwenhuijsen, Mark J.; Basagaña, Xavier; Alvarez-Pedrerol, Mar; Dalmau-Bueno, Albert; Cirach, Marta; Rivas, Ioar; Brunekreef, Bert; Querol, Xavier; Morgan, Ian G.; Sunyer, Jordi

2017-01-01

Purpose To investigate the association between exposure to traffic-related air pollution and use of spectacles (as a surrogate measure for myopia) in schoolchildren. Methods We analyzed the impact of exposure to NO2 and PM2.5 light absorbance at home (predicted by land-use regression models) and exposure to NO2 and black carbon (BC) at school (measured by monitoring campaigns) on the use of spectacles in a cohort of 2727 schoolchildren (7–10 years old) in Barcelona (2012–2015). We conducted cross-sectional analyses based on lifelong exposure to air pollution and prevalent cases of spectacles at baseline data collection campaign as well as longitudinal analyses based on incident cases of spectacles use and exposure to air pollution during the three-year period between the baseline and last data collection campaigns. Logistic regression models were developed to quantify the association between spectacles use and each of air pollutants adjusted for relevant covariates. Results An interquartile range increase in exposure to NO2 and PM2.5 absorbance at home was respectively associated with odds ratios (95% confidence intervals (CIs)) for spectacles use of 1.16 (1.03, 1.29) and 1.13 (0.99, 1.28) in cross-sectional analyses and 1.15 (1.00, 1.33) and 1.23 (1.03, 1.46) in longitudinal analyses. Similarly, odds ratio (95% CIs) of spectacles use associated with an interquartile range increase in exposures to NO2 and black carbon at school was respectively 1.32 (1.09, 1.59) and 1.13 (0.97, 1.32) in cross-sectional analyses and 1.12 (0.84, 1.50) and 1.27 (1.03, 1.56) in longitudinal analyses. These findings were robust to a range of sensitivity analyses that we conducted. Conclusion We observed increased risk of spectacles use associated with exposure to traffic-related air pollution. These findings require further confirmation by future studies applying more refined outcome measures such as quantified visual acuity and separating different types of refractive errors. PMID:28369072

Epidemiological evidence for the link between sleep duration and high blood pressure: a systematic review and meta-analysis.

PubMed

Guo, Xiaofan; Zheng, Liqiang; Wang, Jun; Zhang, Xiaoyu; Zhang, Xingang; Li, Jue; Sun, Yingxian

2013-04-01

We aim to assess if the relationship between short or long sleep duration and hypertension is present among adults from epidemiological evidence and to investigate the relationship quantitatively. We performed a comprehensive search of cross-sectional and longitudinal studies using PubMed and the Cochrane Library through February 2012. Our search was supplemented by reviewing reference lists of original and relevant reviews. After the related data were extracted by two investigators independently, pooled odds ratios (ORs) or relative risks (RRs) were estimated using a random-effects model or a fixed-effects model. Publication bias was evaluated, while sensitivity and meta-regression analyses were performed. Twenty-four adult studies met our inclusion criteria, with ages ranging from 18 to 106 years. Twenty-one studies involving 225,858 subjects were included in the meta-analysis. The pooled results from the cross-sectional studies showed that short sleep duration was associated with a greater risk for hypertension (OR, 1.21; 95% confidence interval [CI], 1.09-1.34; P<0.001), and long sleep duration also increased the risk for hypertension (OR, 1.11; 95% CI, 1.04-1.18; P=0.003). There was no evidence of publication bias. Pooled analysis from the longitudinal studies indicated a significant association between short sleep duration and hypertension (RR, 1.23; 95% CI, 1.06-1.42; P=0.005), but an insignificant relationship between long sleep duration and hypertension (RR, 1.02; 95% CI, 0.91-1.14; P=0.732). The effects of sleep duration differed by gender, location of the population, and definitions of short or long sleep duration. Meta regression analysis including seven variables did not find the sources of heterogeneity. Among adults, a U-shaped relationship between habitual sleep duration and hypertension was found at the cross-sectional level. Short sleep duration was associated with a higher risk for hypertension even longitudinally. We must pay more attention to this lifestyle factor. Copyright © 2012 Elsevier B.V. All rights reserved.

Early school attainment in late-preterm infants.

PubMed

Peacock, Philip J; Henderson, John; Odd, David; Emond, Alan

2012-02-01

To investigate whether infants born late-preterm have poorer school attainment compared to those born at term. This study used data from the Avon Longitudinal Study of Parents and Children. Key stage one (KS1) school assessment results were obtained from local education authorities. Logistic regression models were used to investigate the effect of gestation, that is, late-preterm (32-36 weeks) versus term (37-41 weeks), on success in KS1 teacher assessments. Regression models were adjusted for potential confounders, including maternal education and markers of socioeconomic status. There were 12 089 term infants and 734 late-preterm infants. 71% of late-preterm children were successful in KS1 assessments compared to 79% of those born at term (OR 0.64 (95% CI 0.53 to 0.78); p<0.001). This difference persisted on adjusting for potential confounders (OR 0.74 (95% CI 0.59 to 0.92); p=0.007). Children born late-preterm are less likely to be successful in early school assessments than those born at term. This group of vulnerable children warrants closer surveillance for early identification of potential educational failure.

Longitudinal Mediators of Relations Between Family Violence and Adolescent Dating Aggression Perpetration

PubMed Central

Reyes, H. Luz McNaughton; Foshee, Vangie A.; Fortson, Beverly L.; Valle, Linda A.; Breiding, Matthew J.; Merrick, Melissa T.

2015-01-01

Few longitudinal studies have examined the pathways through which family violence leads to dating aggression. In the current study the authors used 3 waves of data obtained from 8th- and 9th-grade adolescents (N = 1,965) to examine the hypotheses that the prospective relationship between witnessing family violence and directly experiencing violence and physical dating aggression perpetration is mediated by 3 constructs: (a) normative beliefs about dating aggression (norms), (b) anger dysregulation, and (c) depression. Results from cross-lagged regression models suggest that the relationship between having been hit by an adult and dating aggression is mediated by changes in norms and anger dysregulation, but not depression. No evidence of indirect effects from witnessing family violence to dating aggression was found through any of the proposed mediators. Taken together, the findings suggest that anger dysregulation and normative beliefs are potential targets for dating abuse prevention efforts aimed at youth who have directly experienced violence. PMID:26719602

Which types of mental work demands may be associated with reduced risk of dementia?

PubMed

Then, Francisca S; Luck, Tobias; Heser, Kathrin; Ernst, Annette; Posselt, Tina; Wiese, Birgitt; Mamone, Silke; Brettschneider, Christian; König, Hans-Helmut; Weyerer, Siegfried; Werle, Jochen; Mösch, Edelgard; Bickel, Horst; Fuchs, Angela; Pentzek, Michael; Maier, Wolfgang; Scherer, Martin; Wagner, Michael; Riedel-Heller, Steffi G

2017-04-01

Previous studies have demonstrated that an overall high level of mental work demands decreased dementia risk. In our study, we investigated whether this effect is driven by specific mental work demands and whether it is exposure dependent. Patients aged 75+ years were recruited from general practitioners and participated in up to seven assessment waves (every 1.5 years) of the longitudinal AgeCoDe study. Analyses of the impact of specific mental work demands on dementia risk were carried out via multivariate regression modeling (n = 2315). We observed a significantly lower dementia risk in individuals with a higher level of "information processing" (HR, 0.888), "pattern detection" (HR, 0.878), "mathematics" (HR, 0.878), and "creativity" (HR, 0.878). Yet, exposure-dependent effects were only significant for "information processing" and "pattern detection." Our longitudinal observations suggest that dementia risk may be reduced by some but not all types of mental work demands. Copyright © 2016 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Perceived Social Support as a Determinant of Quality of Life Among Medical Students: 6-Month Follow-up Study.

PubMed

Hwang, In Cheol; Park, Kwi Hwa; Kim, Jin Joo; Yim, Jun; Ko, Kwang Pil; Bae, Seung Min; Kyung, Sun Young

2017-04-01

This longitudinal study aimed to identify the relevant factors related to quality of life (QoL) changes in medical students. For this 6-month follow-up study, we enrolled 109 students from a Korean medical school. To assess students' QoL, we used the World Health Organization QoL scale. Possible determinants of student QoL included demographics, fatigue, and social support. A stepwise multivariate analysis identified factors associated with changes of student QoL. Among sources of support, the "friends" category was the main position affecting their overall QoL, and "significant other" had the strongest influence on psychological and social domains. The impact of support from friends on QoL was confirmed in the longitudinal analysis. Final regression models revealed that providing students with more social support and promoting fatigue reduction best improved medical student sense of well-being. Creating stronger student support programs to prevent social detachment and implementing strategies to reduce fatigue can improve QoL in medical students.

Sexual Identity Mobility and Depressive Symptoms: A Longitudinal Analysis of Sexual Minority Women

PubMed Central

Everett, Bethany; Talley, Amelia; Hughes, Tonda; Wilsnack, Sharon; Johnson, Timothy P.

2016-01-01

Sexual minority identity (bisexual, lesbian) is a known risk factor for depression in women. This study examines a facet of minority stress prevalent among women—sexual identity mobility—as an identity-related contributor to higher levels of depressive symptoms. We used three waves of data from the Chicago Health and Life Experiences of Women (CHLEW) study, a longitudinal study of sexual minority women (N = 306). Random effects OLS regression models were constructed to examine the effect of sexual-identity changes on depressive symptoms. We found that 25.6% of the sample reported a sexual-identity change between Wave I and Wave II, and 24.91% reported a sexual identity change between Waves II and III. Women who reported a change in sexual identity also reported more depressive symptoms subsequent to identity change. This effect was moderated by the number of years participants’ had reported their baseline identity and by whether the participant had initiated a romantic relationship with a male partner. PMID:27255306

Assisted and unassisted suicide in men and women: longitudinal study of the Swiss population.

PubMed

Steck, Nicole; Egger, Matthias; Zwahlen, Marcel

2016-05-01

In Switzerland assisted suicide is legal if no self-interest is involved. To compare the strength and direction of associations with sociodemographic factors between assisted and unassisted suicides. We calculated rates and used Cox and logistic regression models in a longitudinal study of the Swiss population. Analyses were based on 5 004 403 people, 1301 assisted and 5708 unassisted suicides from 2003 to 2008. The rate of unassisted suicides was higher in men than in women, rates of assisted suicides were similar in men and women. Higher education was positively associated with assisted suicide, but negatively with unassisted. Living alone, having no children and no religious affiliation were associated with higher rates of both. Some situations that indicate greater vulnerability such as living alone were associated with both assisted and unassisted suicide. Among the terminally ill, women were more likely to choose assisted suicide, whereas men died more often by unassisted suicide. © The Royal College of Psychiatrists 2016.

Association between sports participation, motor competence and weight status: A longitudinal study.

PubMed

Henrique, Rafael S; Ré, Alessandro H N; Stodden, David F; Fransen, Job; Campos, Carolina M C; Queiroz, Daniel R; Cattuzzo, Maria T

2016-10-01

The aim of this study was to investigate if baseline motor competence, weight status and sports participation in early childhood predict sports participation two years later. longitudinal study. In 2010, motor competence (object control and locomotor skills), weight status and sports participation were assessed in 292 children between three and five years-of-age. In 2012, sports participation was re-evaluated in 206 of the original 292 children. Logistic regression was implemented to examine if initial sports participation, motor competence and weight status would predict sports participation two years later. In the final model, sports participation in 2010 (OR=9.68, CI: 3.46 to 27.13) and locomotor skills (OR=1.21, CI: 1.01 to 1.46) significantly predicted sports participation after two years. These results suggest that initial sports participation and more advanced locomotor skills in preschool years may be important to promote continued participation in sports across childhood. Copyright © 2015 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Pets, Social Participation, and Aging-in-Place: Findings from the Canadian Longitudinal Study on Aging.

PubMed

Toohey, Ann M; Hewson, Jennifer A; Adams, Cindy L; Rock, Melanie J

2018-06-01

ABSTRACTThe objective of this study was to assess whether pet ownership contributes to social participation and life satisfaction for older adults. We used baseline data from the Canadian Longitudinal Study on Aging (CLSA) for this purpose, and logistic regression models to estimate associations between social participation and life satisfaction for pet owners and non-owners. One third of all older adults (≥ 65 years, n = 7,474) in our sample reported pet ownership. Pet owners were less likely than non-pet owners to report life satisfaction and to participate frequently in social, recreational, or cultural activities, but pet owners were no less satisfied than were non-owners with their current levels of social participation. For pet owners experiencing barriers to social participation, pets appeared protective of life satisfaction in some circumstances. Both individual characteristics and structural factors linked to the World Health Organization's age-friendly communities framework were relevant to understanding these findings.

A longitudinal examination of adolescent career planning and exploration using a social cognitive career theory framework.

PubMed

Rogers, Mary E; Creed, Peter A

2011-02-01

This study used social cognitive career theory (Lent, Brown, & Hackett, 1994), as a framework to investigate predictors of career choice actions, operationalised as career planning and career exploration. The model was tested cross-sectionally and longitudinally with 631 high school students enrolled in Grades 10-12. Students completed measures of self-efficacy, outcome expectations, goals, supports and personality. Results of the hierarchical regression analyses indicated strong support for self-efficacy and goals predicting career planning and exploration across all grades at T1, and predicting change in career planning and exploration from T1 to T2. Whilst support for pathways among other predictor variables (personality, contextual influences and biographic variables) to choice actions was found, these pathways varied across grades at T1, and also from T1 to T2. Implications for social cognitive career theory, career counselling practice and future research are discussed. Copyright © 2010 The Association for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Unemployment transitions and self-rated health in Europe: A longitudinal analysis of EU-SILC from 2008 to 2011.

PubMed

Tøge, Anne Grete; Blekesaune, Morten

2015-10-01

The Great Recession of 2008 has led to elevated unemployment in Europe and thereby revitalised the question of causal health effects of unemployment. This article applies fixed effects regression models to longitudinal panel data drawn from the European Union Statistics on Income and Living Conditions for 28 European countries from 2008 to 2011, in order to investigate changes in self-rated health around the event of becoming unemployed. The results show that the correlation between unemployment and health is partly due to a decrease in self-rated health as people enter unemployment. Such health changes vary by country of domicile, and by individual age; older workers have a steeper decline than younger workers. Health changes after the unemployment spell reveal no indication of adverse health effects of unemployment duration. Overall, this study indicates some adverse health effects of unemployment in Europe--predominantly among older workers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Parenting and adolescents' psychological adjustment: Longitudinal moderation by adolescents' genetic sensitivity.

PubMed

Stocker, Clare M; Masarik, April S; Widaman, Keith F; Reeb, Ben T; Boardman, Jason D; Smolen, Andrew; Neppl, Tricia K; Conger, Katherine J

2017-10-01

We examined whether adolescents' genetic sensitivity, measured by a polygenic index score, moderated the longitudinal associations between parenting and adolescents' psychological adjustment. The sample included 323 mothers, fathers, and adolescents (177 female, 146 male; Time 1 [T1] average age = 12.61 years, SD = 0.54 years; Time 2 [T2] average age = 13.59 years, SD = 0.59 years). Parents' warmth and hostility were rated by trained, independent observers using videotapes of family discussions. Adolescents reported their symptoms of anxiety, depressed mood, and hostility at T1 and T2. The results from autoregressive linear regression models showed that adolescents' genetic sensitivity moderated associations between observations of both mothers' and fathers' T1 parenting and adolescents' T2 composite maladjustment, depression, anxiety, and hostility. Compared to adolescents with low genetic sensitivity, adolescents with high genetic sensitivity had worse adjustment outcomes when parenting was low on warmth and high on hostility. When parenting was characterized by high warmth and low hostility, adolescents with high genetic sensitivity had better adjustment outcomes than their counterparts with low genetic sensitivity. The results support the differential susceptibility model and highlight the complex ways that genes and environment interact to influence development.

Reciprocal Influences Between Maternal Parenting and Child Adjustment in a High-risk Population: A Five-Year Cross-Lagged Analysis of Bidirectional Effects

PubMed Central

Barbot, Baptiste; Crossman, Elizabeth; Hunter, Scott R.; Grigorenko, Elena L.; Luthar, Suniya S.

2014-01-01

This study examines longitudinally the bidirectional influences between maternal parenting (behaviors and parenting stress) and mothers' perceptions of their children's adjustment, in a multivariate approach. Data was gathered from 361 low-income mothers (many with psychiatric diagnoses) reporting on their parenting behavior, parenting stress and their child's adjustment, in a two-wave longitudinal study over 5 years. Measurement models were developed to derive four broad parenting constructs (Involvement, Control, Rejection, and Stress) and three child adjustment constructs (Internalizing problems, Externalizing problems, and Social competence). After measurement invariance of these constructs was confirmed across relevant groups and over time, both measurement models were integrated in a single crossed-lagged regression analysis of latent constructs. Multiple reciprocal influence were observed between parenting and perceived child adjustment over time: Externalizing and internalizing problems in children were predicted by baseline maternal parenting behaviors, while child social competence was found to reduce parental stress and increase parental involvement and appropriate monitoring. These findings on the motherhood experience are discussed in light of recent research efforts to understand mother-child bi-directional influences, and their potential for practical applications. PMID:25089759

Job insecurity and work-family conflict in teachers in Sweden: Examining their relations with longitudinal cross-lagged modeling.

PubMed

Richter, Anne; Näswall, Katharina; Lindfors, Petra; Sverke, Magnus

2015-06-01

Job insecurity and work-family conflict are increasingly prevalent in contemporary working life and numerous studies have documented their antecedents and negative consequences. The present study used longitudinal questionnaire data collected among teachers in Sweden to test the direction of the relation between job insecurity and work-family conflict using cross-lagged modeling. Multiple-group comparisons were conducted to account for the skewed gender composition in the teachers' group. After controlling for baseline levels of job insecurity, work-family conflict, and four potential confounders (age, children under 12 living at home, university education, and relationship status), we found that the reciprocal relationship between job insecurity and work-family conflict over a 1-year time period fitted the data best for the men. For women, however, only the auto regression coefficients were significant. The results provide some empirical support for gender differences in the relation between job insecurity and work-family conflict. Moreover, this study partially supports theoretical assumptions suggesting that job insecurity and work-family conflict influence each other. © 2015 The Institute of Psychology, Chinese Academy of Sciences and Wiley Publishing Asia Pty Ltd.

Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

PubMed

Yap, John Stephen; Fan, Jianqing; Wu, Rongling

2009-12-01

Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.

U.S. military service and the prevalence of metabolic syndrome: Findings from a cross-sectional analysis of the Cooper Center Longitudinal Study, 1979-2013.

PubMed

Janak, Jud C; Pérez, Adriana; Alamgir, Hasanat; Orman, Jean A; Cooper, Sharon P; Shuval, Kerem; DeFina, Laura; Barlow, Carolyn E; Gabriel, Kelley Pettee

2017-02-01

U.S. military service confers both health benefits and risks potentially associated with a clustering of cardiovascular risk factors called metabolic syndrome. However, the association between prior military service and metabolic syndrome has not sufficiently been examined. The purpose of the study was to compare the prevalence of metabolic syndrome by prior military service status. Among 42,370 men (887 with prior military service) examined from 1979 to 2013 at the Cooper Clinic (Dallas, TX), we used a cross-sectional study design to examine the association between military service and metabolic syndrome. First, an unadjusted log binomial regression model was performed by regressing the prevalence of metabolic syndrome on prior service. This was followed by performing Kleinbaum's modeling strategy for assessing confounding. The same methodology was used to explore the association between individual metabolic syndrome risk factors and prior service. Prior military service was not significantly associated with the prevalence of metabolic syndrome (PR=0.98, 0.89-1.07). None of the variables explored were identified as confounders. Participants with prior military service had lower prevalence of both elevated levels of triglycerides (PR=0.89, 0.80-0.99) and low levels of high-density lipoprotein-cholesterol (PR=0.78, 0.70-0.88). They had a higher prevalence of elevated resting systolic blood pressure (PR=1.23, 1.12-1.35). However, none of these associations were significant after adjusting for identified confounders: age; cardiorespiratory fitness; and exam year. Study findings indicate that military service was not independently associated with the prevalence of metabolic syndrome or its components. Future research is warranted longitudinally assessing the impact of military service on long-term outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Trichuriasis and low-iron status in schoolchildren from Northwest Mexico.

PubMed

Quihui-Cota, L; Morales-Figueroa, G G; Esparza-Romero, J; Valencia, M E; Astiazarán-García, H; Méndez, R O; Pacheco-Moreno, B I; Crompton, D W T; Diaz-Camacho, S P

2010-10-01

The aim of this study was to investigate the association between trichuriasis and iron status in rural schoolchildren from Northwest Mexico. A total of 73 schoolchildren (37 boys, 36 girls) between the ages of 6 and 10 years were voluntarily recruited from the public primary school of the rural community of El Higueral in Culiacan, Sinaloa (Northwest Mexico) for a cross-sectional study with a longitudinal follow-up of 5 weeks. Data were collected on socioeconomic status, anthropometry, haematological and biochemical indices of iron status, daily iron intake, and prevalence and intensity of trichuriasis. Multiple regression models, independent t-test and paired t-test were used to analyse the association between trichuriasis and iron status in cross-sectional and longitudinal samples, respectively. Adjusted models were tested for linear regression assumptions using residual plots. The mean age of the Trichuris-free and Trichuris-infected groups was 7.7±1.3 and 7.7±1.5 years respectively (P=0.92). The height for age was significantly higher in the Trichuris-free group than the Trichuris-infected group (P=0.02). No differences were found in the socioeconomic variables between the two groups. At baseline, significantly higher concentrations of haemoglobin, haematocrit, blood cell count (RBC) and serum iron were measured in the Trichuris-free group compared with the Trichuris-infected children (P<0.05). An association was found between trichuriasis and haemoglobin adjusted for socioeconomic variables, age and sex. Haemoglobin, RBC and serum ferritin concentrations were significantly increased in the infected children 5 weeks after treatment (P<0.05). Trichuriasis could be a risk factor for low-iron status in the schoolchildren of Northwest Mexico.

Associations between sensory loss and social networks, participation, support, and loneliness: Analysis of the Canadian Longitudinal Study on Aging.

PubMed

Mick, Paul; Parfyonov, Maksim; Wittich, Walter; Phillips, Natalie; Kathleen Pichora-Fuller, M

2018-01-01

To determine if hearing loss, vision loss, and dual sensory loss were associated with social network diversity, social participation, availability of social support, and loneliness, respectively, in a population-based sample of older Canadians and to determine whether age or sex modified the associations. Cross-sectional population-based study. Canada. The sample included 21 241 participants in the Canadian Longitudinal Study on Aging tracking cohort. The sample was nationally representative of English- and French-speaking, non-institutionalized 45- to 89-year-old Canadians who did not live on First Nations reserves and who had normal cognition. Participants with missing data for any of the variables in the multivariable regression models were excluded from analysis. Hearing and vision loss were determined by self-report. Dual sensory loss was defined as reporting both hearing and vision loss. Univariate analyses were performed to assess cross-sectional associations between hearing, vision, and dual sensory loss, and social, demographic, and medical variables. Multivariable regression models were used to analyze cross-sectional associations between each type of sensory loss and social network diversity, social participation, availability of social support, and loneliness. Vision loss (in men) and dual sensory loss (in 65- to 85-year-olds) were independently associated with reduced social network diversity. Vision loss and dual sensory loss (in 65- to 85-year-olds) were each independently associated with reduced social participation. All forms of sensory loss were associated with both low availability of social support and loneliness. Sensory impairment is associated with reduced social function in older Canadians. Interventions and research that address the social needs of older individuals with sensory loss are needed. Copyright© the College of Family Physicians of Canada.

The accuracy of caries risk assessment in children attending South Australian School Dental Service: a longitudinal study

PubMed Central

Ha, Diep H; Spencer, A John; Slade, Gary D; Chartier, Andrew D

2014-01-01

Objectives To determine the accuracy of the caries risk assessment system and performance of clinicians in their attempts to predict caries for children during routine practice. Design Longitudinal study. Setting and participants Data on caries risk assessment conducted by clinicians during routine practice while providing care for children in the South Australian School Dental Service (SA SDS) were collected from electronic patient records. Baseline data on caries experience, clinicians’ ratings of caries risk status and child demographics were obtained for all SA SDS patients aged 5–15 years examined during 2002–2005. Outcome measure Children’s caries incidence rate, calculated using examination data after a follow-up period of 6–48 months from baseline, was used as the gold standard to compute the sensitivity (Se) and specificity (Sp) of clinicians’ baseline ratings of caries risk. Multivariate binomial regression models were used to evaluate effects of children's baseline characteristics on Se and Sp. Results A total of 133 clinicians rated caries risk status of 71 430 children during 2002–2005. The observed Se and Sp were 0.48 and 0.86, respectively (Se+Sp=1.34). Caries experience at baseline was the strongest factor influencing accuracy in multivariable regression model. Among children with no caries experience at baseline, overall accuracy (Se+Sp) was only 1.05, whereas it was 1.28 among children with at least one tooth surfaces with caries experience at baseline. Conclusions Clinicians’ accuracy in predicting caries risk during routine practice was similar to levels reported in research settings that simulated patient care. Accuracy was acceptable in children who had prior caries experience at the baseline examination, while it was poor among children with no caries experience. PMID:24477318

Epilepsy, birth weight and academic school readiness in Canadian children: Data from the national longitudinal study of children and youth.

PubMed

Prasad, A N; Corbett, B

2017-02-01

Birth weight is an important indicator of prenatal/in-utero environment. Variations in birth weight have been reportedly associated with risks for cognitive problems. The National Longitudinal Survey of Children and Youth (NLSCY) dataset was explored to examine relationships between birth weight, academic school readiness and epilepsy. A population based sample of 32,900 children of the NLSCY were analyzed to examine associations between birth weight, and school readiness scores in 4-5-year-old children. Logistic and Linear regression was used to examine associations between having epilepsy and these outcomes. Gestation data was available on 19,867 children, full-term children represented 89.67% (gestation >259days), while 10.33% of children were premature (gestation <258days). There were 20 children with reported epilepsy in the sample. Effects of confounding variables (diabetes in pregnancy, smoking in pregnancy, high blood pressure during pregnancy, and gender of the infant) on birth weight and epilepsy were controlled using a separate structural equation model. Logistic regression analysis identified an association between epilepsy and lower birth weights, as well as an association between lower birth weight, having epilepsy and lower PPVT-R Scores. Model results show the relationship between low birth weight and epilepsy remains statistically significant even when controlling for the influence of afore mentioned confounding variables. Low birth weight appears to be associated with both epilepsy and academic school readiness. The data suggest that an abnormal prenatal environment can influence both childhood onset of epilepsy and cognition. Additional studies with larger sample sizes are needed to verify this relationship in detail. Copyright © 2017 Elsevier B.V. All rights reserved.

Payment systems and oral health in Swedish dental care: Observations over six years.

PubMed

Andås, C A; Hakeberg, M

2016-12-01

The aim of this longitudinal study of patients in regular dental care was to compare the findings of manifest caries and fillings after a 6-year adherence to either of two optional payment models, the traditional fee-for service (FFS) model, or the new capitation model 'Dental Care for Health' (DCH). Data on manifest caries lesions, the number of fillings and a number of background variables were collected from both a register and a questionnaire completed by 6,299 regular dental patients who met the inclusion criteria. The influence of payment system adherence and background variables on the number of manifest caries lesions at study end was examined by the means of negative binomial regression analysis. The incidence rate ratio of manifest caries lesions after six years in FFS was 1.5 compared to DCH, after controlling for age, gender, education and pre-baseline caries incidence. The number of fillings was higher in FFS than in DCH at study start and at study end, and was also described by a steeper slope. At group level, this study showed a statistically significant difference between the caries situation after six years in DCH compared with FFS, when some important background factors, including pre-baseline caries, were kept constant in a regression model. Copyright© 2016 Dennis Barber Ltd

Median regression spline modeling of longitudinal FEV1 measurements in cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) patients.

PubMed

Conrad, Douglas J; Bailey, Barbara A; Hardie, Jon A; Bakke, Per S; Eagan, Tomas M L; Aarli, Bernt B

2017-01-01

Clinical phenotyping, therapeutic investigations as well as genomic, airway secretion metabolomic and metagenomic investigations can benefit from robust, nonlinear modeling of FEV1 in individual subjects. We demonstrate the utility of measuring FEV1 dynamics in representative cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) populations. Individual FEV1 data from CF and COPD subjects were modeled by estimating median regression splines and their predicted first and second derivatives. Classes were created from variables that capture the dynamics of these curves in both cohorts. Nine FEV1 dynamic variables were identified from the splines and their predicted derivatives in individuals with CF (n = 177) and COPD (n = 374). Three FEV1 dynamic classes (i.e. stable, intermediate and hypervariable) were generated and described using these variables from both cohorts. In the CF cohort, the FEV1 hypervariable class (HV) was associated with a clinically unstable, female-dominated phenotypes while stable FEV1 class (S) individuals were highly associated with the male-dominated milder clinical phenotype. In the COPD cohort, associations were found between the FEV1 dynamic classes, the COPD GOLD grades, with exacerbation frequency and symptoms. Nonlinear modeling of FEV1 with splines provides new insights and is useful in characterizing CF and COPD clinical phenotypes.

A longitudinal investigation of nutrition and dietary patterns in children of mothers with eating disorders.

PubMed

Easter, Abigail; Naumann, Ulrike; Northstone, Kate; Schmidt, Ulrike; Treasure, Janet; Micali, Nadia

2013-07-01

To investigate dietary patterns and nutritional intake in children of mothers with eating disorders. Mothers (N = 9423) from a longitudinal general population birth cohort study, the Avon Longitudinal Study of Parents and Children, completed Food Frequency Questionnaires on their children at 3, 4, 7, and 9 years of age. Macronutrient intake was estimated, and dietary patterns were obtained using principal components analysis. Linear regression and mixed-effects models were used to assess dietary patterns and nutritional intake among children of women with lifetime anorexia nervosa (AN, n = 140), bulimia nervosa (BN, n = 170), or AN+BN (n = 71), compared with children of women without eating disorders (unexposed women, n = 9037). Children in the maternal AN and BN groups had higher scores on the "health conscious/vegetarian" dietary pattern compared with unexposed children. Less adherence to the "traditional" dietary pattern was observed in children of exposed mothers, with more pronounced differences in early childhood. Children of women with AN and BN had higher intake of energy and children of women with BN had higher intake of carbohydrates and starch and lower intake of fat, compared with children in the unexposed group. Maternal eating disorders are associated with altered offspring dietary patterns and macronutrient intake. Longitudinal changes in patterns of diet in children of women with eating disorders may increase the risk of weight gain or disordered eating later in life. Copyright © 2013 Mosby, Inc. All rights reserved.

Examining Solutions to Missing Data in Longitudinal Nursing Research

PubMed Central

Roberts, Mary B.; Sullivan, Mary C.; Winchester, Suzy B.

2017-01-01

Purpose Longitudinal studies are highly valuable in pediatrics because they provide useful data about developmental patterns of child health and behavior over time. When data are missing, the value of the research is impacted. The study’s purpose was to: (1) introduce a 3-step approach to assess and address missing data; (2) illustrate this approach using categorical and continuous level variables from a longitudinal study of premature infants. Methods A three-step approach with simulations was followed to assess the amount and pattern of missing data and to determine the most appropriate imputation method for the missing data. Patterns of missingness were Missing Completely at Random, Missing at Random, and Not Missing at Random. Missing continuous-level data were imputed using mean replacement, stochastic regression, multiple imputation, and fully conditional specification. Missing categorical-level data were imputed using last value carried forward, hot-decking, stochastic regression, and fully conditional specification. Simulations were used to evaluate these imputation methods under different patterns of missingness at different levels of missing data. Results The rate of missingness was 16–23% for continuous variables and 1–28% for categorical variables. Fully conditional specification imputation provided the least difference in mean and standard deviation estimates for continuous measures. Fully conditional specification imputation was acceptable for categorical measures. Results obtained through simulation reinforced and confirmed these findings. Practice Implications Significant investments are made in the collection of longitudinal data. The prudent handling of missing data can protect these investments and potentially improve the scientific information contained in pediatric longitudinal studies. PMID:28425202

Alterations of papilla dimensions after orthodontic closure of the maxillary midline diastema: a retrospective longitudinal study

PubMed Central

2016-01-01

Purpose The aim of this study was to evaluate alterations of papilla dimensions after orthodontic closure of the diastema between maxillary central incisors. Methods Sixty patients who had a visible diastema between maxillary central incisors that had been closed by orthodontic approximation were selected for this study. Various papilla dimensions were assessed on clinical photographs and study models before the orthodontic treatment and at the follow-up examination after closure of the diastema. Influences of the variables assessed before orthodontic treatment on the alterations of papilla height (PH) and papilla base thickness (PBT) were evaluated by univariate regression analysis. To analyze potential influences of the 3-dimensional papilla dimensions before orthodontic treatment on the alterations of PH and PBT, a multiple regression model was formulated including the 3-dimensional papilla dimensions as predictor variables. Results On average, PH decreased by 0.80 mm and PBT increased after orthodontic closure of the diastema (P<0.01). Univariate regression analysis revealed that the PH (P=0.002) and PBT (P=0.047) before orthodontic treatment influenced the alteration of PH. With respect to the alteration of PBT, the diastema width (P=0.045) and PBT (P=0.000) were found to be influential factors. PBT before the orthodontic treatment significantly influenced the alteration of PBT in the multiple regression model. Conclusions PH decreased but PBT increased after orthodontic closure of the diastema. The papilla dimensions before orthodontic treatment influenced the alterations of PH and PBT after closure of the diastema. The PBT increased more when the diastema width before the orthodontic treatment was larger. PMID:27382507

The impact of diabetes on employment and work productivity.

PubMed

Tunceli, Kaan; Bradley, Cathy J; Nerenz, David; Williams, L Keoki; Pladevall, Manel; Elston Lafata, Jennifer

2005-11-01

The purpose of this study was to longitudinally examine the effect of diabetes on labor market outcomes. Using secondary data from the first two waves (1992 and 1994) of the Health and Retirement Study, we identified 7,055 employed respondents (51-61 years of age), 490 of whom reported having diabetes in wave 1. We estimated the effect of diabetes in wave 1 on the probability of working in wave 2 using probit regression. For those working in wave 2, we modeled the relationships between diabetic status in wave 1 and the change in hours worked and work-loss days using ordinary least-squares regressions and modeled the presence of health-related work limitations using probit regression. All models control for health status and job characteristics and are estimated separately by sex. Among individuals with diabetes, the absolute probability of working was 4.4 percentage points less for women and 7.1 percentage points less for men relative to that of their counterparts without diabetes. Change in weekly hours worked was not statistically significantly associated with diabetes. Women with diabetes had 2 more work-loss days per year compared with women without diabetes. Compared with individuals without diabetes, men and women with diabetes were 5.4 and 6 percentage points (absolute increase), respectively, more likely to have work limitations. This article provides evidence that diabetes affects patients, employers, and society not only by reducing employment but also by contributing to work loss and health-related work limitations for those who remain employed.

Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models.

PubMed

De Haas, Y; Janss, L L G; Kadarmideen, H N

2007-10-01

Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.

Prediction of near-term increases in suicidal ideation in recently depressed patients with bipolar II disorder using intensive longitudinal data.

PubMed

Depp, Colin A; Thompson, Wesley K; Frank, Ellen; Swartz, Holly A

2017-01-15

There are substantial gaps in understanding near-term precursors of suicidal ideation in bipolar II disorder. We evaluated whether repeated patient-reported mood and energy ratings predicted subsequent near-term increases in suicide ideation. Secondary data were used from 86 depressed adults with bipolar II disorder enrolled in one of 3 clinical trials evaluating Interpersonal and Social Rhythm Therapy and/or pharmacotherapy as treatments for depression. Twenty weeks of daily mood and energy ratings and weekly Hamilton Depression Rating Scale (HDRS) were obtained. Penalized regression was used to model trajectories of daily mood and energy ratings in the 3 week window prior to HDRS Suicide Item ratings. Participants completed an average of 68.6 (sd=52) days of mood and energy ratings. Aggregated across the sample, 22% of the 1675 HDRS Suicide Item ratings were non-zero, indicating presence of at least some suicidal thoughts. A cross-validated model with longitudinal ratings of energy and depressed mood within the three weeks prior to HDRS ratings resulted in an AUC of 0.91 for HDRS Suicide item >2, accounting for twice the variation when compared to baseline HDRS ratings. Energy, both at low and high levels, was an earlier predictor than mood. Data derived from a heterogeneous treated sample may not generalize to naturalistic samples. Identified suicidal behavior was absent from the sample so it could not be predicted. Prediction models coupled with intensively gathered longitudinal data may shed light on the dynamic course of near-term risk factors for suicidal ideation in bipolar II disorder. Copyright © 2016 Elsevier B.V. All rights reserved.

Stressful work environment and wellbeing: What comes first?

PubMed

Elovainio, Marko; Heponiemi, Tarja; Jokela, Markus; Hakulinen, Christian; Presseau, Justin; Aalto, Anna-Mari; Kivimäki, Mika

2015-07-01

The association between the psychosocial work environment, including job demands, job control, and organizational justice, and employee wellbeing has been well established. However, the exposure to adverse work environments is typically measured only using self-reported measures that are vulnerable to reporting bias, and thus any associations found may be explained by reverse causality. Using linear regression models and cross-lagged structural equation modeling (SEM), we tested the direction of the association between established job stress models (job demand control and organizational justice models) and 3 wellbeing indicators (psychological distress, sleeping problems, and job satisfaction) among 1524 physicians in a 4-year follow-up. Results from the longitudinal cross-lagged analyses showed that the direction of the association was from low justice to decreasing wellbeing rather than the reverse. Although the pattern was similar in job demands and job control, a reciprocal association was found between job control and psychological distress. (c) 2015 APA, all rights reserved).

An evaluation of fruit and vegetable consumption and cigarette smoking among youth.

PubMed

Haibach, Jeffrey P; Homish, Gregory G; Collins, R Lorraine; Ambrosone, Christine B; Giovino, Gary A

2015-06-01

Research across the past 4 decades has supported a cross-sectional association between adult cigarette smoking and lower fruit and vegetable consumption (FVC), and emerging research suggests higher FVC may predict cessation. Among youth, findings are limited to a few cross-sectional studies with somewhat mixed results. Here we evaluated the FVC-smoking association among youth both cross-sectionally and longitudinally. We analyzed data from a subsample of the National Longitudinal Survey of Youth 1979: Child and Young Adult. The subsample included adolescents aged 14-18 years at baseline in the year 2004. Multivariable cross-sectional analyses assessed whether baseline FVC was associated with smoking frequency among ever-smokers (n = 578). Longitudinally, the study assessed whether baseline FVC predicted smoking progression among baseline never-smokers who tried a cigarette by 4-year follow-up (n = 388). Multivariable regression models adjusted for age, gender, race/ethnicity, parental education, and health behavior orientation. Cross-sectionally, youth who consumed fruit ≥2 times per day were 53% less likely (RR = 0.47; p < .05) than those who typically did not consume fruit to be in a higher smoking frequency category. Longitudinally, the fruit consumption and smoking association was not significant (RR = 0.61; p = .282). There were no significant associations observed between vegetable consumption and smoking. Fruit consumption, but not vegetable consumption, was inversely associated with smoking frequency cross-sectionally but not longitudinally. Further research is needed to provide information on the consistency of the FVC-smoking relationship among youth and may help to elucidate possible explanatory mechanisms. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The comorbidity of anxiety and depressive symptoms in older adults with attention-deficit/hyperactivity disorder: a longitudinal study.

PubMed

Michielsen, Marieke; Comijs, Hannie C; Semeijn, Evert J; Beekman, Aartjan T F; Deeg, Dorly J H; Sandra Kooij, J J

2013-06-01

Comorbidity between Attention-Deficit/Hyperactivity Disorder (ADHD) and depression and anxiety disorders in children and young to middle-aged adults has been well documented in the literature. Yet, it is still unknown whether this comorbidity persists into later life. The aim of this study is therefore to examine the comorbidity of anxiety and depressive symptoms among older adults with ADHD. This is examined both using cross-sectional and longitudinal data. Data were used from the Longitudinal Aging Study Amsterdam (LASA). Participants were examined in three measurement cycles, covering six years. They were asked about depressive and anxiety symptoms. To diagnose ADHD, the DIVA 2.0, a diagnostic interview was administered among a subsample (N=231, age 60-94). In addition to the ADHD diagnosis, the association between the sum score of ADHD symptoms and anxiety and depressive symptoms was examined. Data were analyzed by means of linear regression analyses and linear mixed models. Both ADHD diagnosis and more ADHD symptoms were associated with more anxiety and depressive symptoms cross-sectionally as well as longitudinally. The longitudinal analyses showed that respondents with higher scores of ADHD symptoms reported an increase of depressive symptoms over six years whereas respondents with fewer ADHD symptoms remained stable. The ADHD diagnosis is based on the DSM-IVcriteria, which were developed for children, and have not yet been validated in (older) adults. It appears that the association between ADHD and anxiety/depression remains in place with aging. This suggests that, in clinical practice, directing attention to both in concert may be fruitful. Copyright © 2012 Elsevier B.V. All rights reserved.

Nonsuicidal Self-Injury Among “Privileged” Youths: Longitudinal and Cross-Sectional Approaches to Developmental Process

PubMed Central

Yates, Tuppett M.; Luthar, Suniya S.; Tracy, Allison J.

2015-01-01

This investigation examined process-level pathways to nonsuicidal self-injury (NSSI; e.g., self-cutting, -burning, -hitting) in 2 cohorts of suburban, upper-middle-class youths: a cross-sectional sample of 9th–12th graders (n = 1,036, 51.9% girls) on the West Coast and a longitudinal sample followed annually from the 6th through 12th grades (n = 245, 53.1% girls) on the East Coast. High rates of NSSI were found in both the cross-sectional (37.2%) and the longitudinal (26.1%) samples. Zero-inflated Poisson regression models estimated process-level pathways from perceived parental criticism to NSSI via youth-reported alienation toward parents. Pathways toward the initiation of NSSI were distinct from those accounting for its frequency. Parental criticism was associated with increased NSSI, and youth alienation toward parents emerged as a relevant process underlying this pathway, particularly for boys. The specificity of these pathways was explored by examining separate trajectories toward delinquent outcomes. The findings illustrate the prominence of NSSI among “privileged” youths, the salience of the caregiving environment in NSSI, the importance of parental alienation in explaining these relations, and the value of incorporating multiple systems in treatment approaches for adolescents who self-injure. PMID:18229983

Evaluating Alzheimer's disease biomarkers as mediators of age-related cognitive decline.

PubMed

Hohman, Timothy J; Tommet, Doug; Marks, Shawn; Contreras, Joey; Jones, Rich; Mungas, Dan

2017-10-01

Age-related changes in cognition are partially mediated by the presence of neuropathology and neurodegeneration. This manuscript evaluates the degree to which biomarkers of Alzheimer's disease, (AD) neuropathology and longitudinal changes in brain structure, account for age-related differences in cognition. Data from the AD Neuroimaging Initiative (n = 1012) were analyzed, including individuals with normal cognition and mild cognitive impairment. Parallel process mixed effects regression models characterized longitudinal trajectories of cognitive variables and time-varying changes in brain volumes. Baseline age was associated with both memory and executive function at baseline (p's < 0.001) and change in memory and executive function performances over time (p's < 0.05). After adjusting for clinical diagnosis, baseline, and longitudinal changes in brain volume, and baseline levels of cerebrospinal fluid biomarkers, age effects on change in episodic memory and executive function were fully attenuated, age effects on baseline memory were substantially attenuated, but an association remained between age and baseline executive function. Results support previous studies that show that age effects on cognitive decline are fully mediated by disease and neurodegeneration variables but also show domain-specific age effects on baseline cognition, specifically an age pathway to executive function that is independent of brain and disease pathways. Copyright © 2017 Elsevier Inc. All rights reserved.

Longitudinal Predictors of Institutionalization in Old Age.

PubMed

Hajek, André; Brettschneider, Christian; Lange, Carolin; Posselt, Tina; Wiese, Birgitt; Steinmann, Susanne; Weyerer, Siegfried; Werle, Jochen; Pentzek, Michael; Fuchs, Angela; Stein, Janine; Luck, Tobias; Bickel, Horst; Mösch, Edelgard; Wagner, Michael; Jessen, Frank; Maier, Wolfgang; Scherer, Martin; Riedel-Heller, Steffi G; König, Hans-Helmut

2015-01-01

To investigate time-dependent predictors of institutionalization in old age using a longitudinal approach. In a representative survey of the German general population aged 75 years and older predictors of institutionalization were observed every 1.5 years over six waves. Conditional fixed-effects logistic regressions (with 201 individuals and 960 observations) were performed to estimate the effects of marital status, depression, dementia, and physical impairments (mobility, hearing and visual impairments) on the risk of admission to old-age home or nursing home. By exploiting the longitudinal data structure using panel econometric models, we were able to control for unobserved heterogeneity such as genetic predisposition and personality traits. The probability of institutionalization increased significantly with occurrence of widowhood, depression, dementia, as well as walking and hearing impairments. In particular, the occurrence of widowhood (OR = 78.3), dementia (OR = 154.1) and substantial mobility impairment (OR = 36.7) were strongly associated with institutionalization. Findings underline the strong influence of loss of spouse as well as dementia on institutionalization. This is relevant as the number of old people (a) living alone and (b) suffering from dementia is expected to increase rapidly in the next decades. Consequently, it is supposed that the demand for institutionalization among the elderly will increase considerably. Practitioners as well as policy makers should be aware of these upcoming challenges.

Nonsuicidal self-injury among "privileged" youths: longitudinal and cross-sectional approaches to developmental process.

PubMed

Yates, Tuppett M; Tracy, Allison J; Luthar, Suniya S

2008-02-01

This investigation examined process-level pathways to nonsuicidal self-injury (NSSI; e.g., self-cutting, -burning, -hitting) in 2 cohorts of suburban, upper-middle-class youths: a cross-sectional sample of 9th-12th graders (n = 1,036, 51.9% girls) on the West Coast and a longitudinal sample followed annually from the 6th through 12th grades (n = 245, 53.1% girls) on the East Coast. High rates of NSSI were found in both the cross-sectional (37.2%) and the longitudinal (26.1%) samples. Zero-inflated Poisson regression models estimated process-level pathways from perceived parental criticism to NSSI via youth-reported alienation toward parents. Pathways toward the initiation of NSSI were distinct from those accounting for its frequency. Parental criticism was associated with increased NSSI, and youth alienation toward parents emerged as a relevant process underlying this pathway, particularly for boys. The specificity of these pathways was explored by examining separate trajectories toward delinquent outcomes. The findings illustrate the prominence of NSSI among "privileged" youths, the salience of the caregiving environment in NSSI, the importance of parental alienation in explaining these relations, and the value of incorporating multiple systems in treatment approaches for adolescents who self-injure.

Adiposity trajectory and its associations with plasma adipokine levels in children and adolescents-A prospective cohort study.

PubMed

Li, Shenghui; Liu, Rong; Arguelles, Lester; Wang, Guoying; Zhang, Jun; Shen, Xiaoming; Wang, Xiaobin

2016-02-01

This study aimed to examine the associations of longitudinal adiposity measures with two adipokines, leptin and adiponectin, and their ratio in children and adolescents. A total of 953 children and adolescents participated in a 6-year longitudinal study. Body mass index (BMI), percentage body fat (%BF), and fat mass index (FMI) were used to assess adiposity status. After adjusting for possible confounders, our regression models revealed that BMI, %BF, and FMI, in both the baseline and follow-up surveys were independently associated with a higher level of leptin and the leptin/adiponectin ratio at the follow-up survey, whereas the significant association with adiponectin only partly existed in adiposity measures at the follow-up visit. Moreover, the longitudinal change in adiposity measures was found to be a significant predictor for follow-up plasma adipokine levels. Compared with the low→low group, the medium→medium group, up-trend group, and high→high group all showed a significantly increased level of leptin and leptin/adiponectin ratio. The up-trend group and high→high group also had significantly decreased adiponectin levels. These findings highlight the importance of adiposity surveillance and the utility of adipokines as biomarkers for adverse metabolic consequences of childhood adiposity. © 2015 The Obesity Society.

Longitudinal impacts of pubertal timing and weight status on adolescent Internet use: Analysis from a cohort study of Taiwanese youths

PubMed Central

Strong, Carol; Chen, Wan-Ting; Lee, Chih-Ting; Lin, Chung-Ying

2018-01-01

Aim To investigate the longitudinal impacts of pubertal timing and weight status on Internet use in adolescents. Methods Three waves of data on a longitudinal cohort of 7th grade students (N = 2430) were retrieved from the Taiwan Youth Project. Univariate and multivariate regression models were applied using crude and adjusted odds ratios (OR) with 95% confidence intervals (CI) to examine the concomitant impacts of pubertal timing and weight status on adolescent Internet use. Results The dataset identified 210 (8.7%) students using the Internet for more than 20 hours/week, and 81 (3.3%) were viewing pornographic material online. Early maturing and thin-weight adolescents were at 35% and 46% increased risks of spending long hours on Internet use, respectively. While early puberty was associated with online pornography viewing among males (adjusted OR 1.84, 95% CI 1.04–3.28), early puberty was contrarily a protective factor against online gaming in females (adjusted OR 0.59, 95% CI 0.36–0.96). Conclusion Early puberty was found to be positively related to adolescent Internet use. Appropriate health education and guidance regarding Internet use should be provided to those with different developing needs. PMID:29795649

Do changes in residents' fear of crime impact their walking? Longitudinal results from RESIDE.

PubMed

Foster, Sarah; Knuiman, Matthew; Hooper, Paula; Christian, Hayley; Giles-Corti, Billie

2014-05-01

To examine the influence of fear of crime on walking for participants in a longitudinal study of residents in new suburbs. Participants (n=485) in Perth, Australia, completed a questionnaire about three years after moving to their neighbourhood (2007-2008), and again four years later (2011-2012). Measures included fear of crime, neighbourhood perceptions and walking (min/week). Objective environmental measures were generated for each participant's neighbourhood, defined as the 1600 m road network distance from home, at each time-point. Linear regression models examined the impact of changes in fear of crime on changes in walking, with progressive adjustment for other changes in the built environment, neighbourhood perceptions and demographics. An increase in fear of crime was associated with a decrease in residents' walking inside the local neighbourhood. For each increase in fear of crime (i.e., one level on a five-point Likert scale) total walking decreased by 22 min/week (p=0.002), recreational walking by 13 min/week (p=0.031) and transport walking by 7 min/week (p=0.064). This study provides longitudinal evidence that changes in residents' fear of crime influence their walking behaviours. Interventions that reduce fear of crime are likely to increase walking and produce public health gains. Copyright © 2014 Elsevier Inc. All rights reserved.

Functional Data Analysis for Dynamical System Identification of Behavioral Processes

PubMed Central

Trail, Jessica B.; Collins, Linda M.; Rivera, Daniel E.; Li, Runze; Piper, Megan E.; Baker, Timothy B.

2014-01-01

Efficient new technology has made it straightforward for behavioral scientists to collect anywhere from several dozen to several thousand dense, repeated measurements on one or more time-varying variables. These intensive longitudinal data (ILD) are ideal for examining complex change over time, but present new challenges that illustrate the need for more advanced analytic methods. For example, in ILD the temporal spacing of observations may be irregular, and individuals may be sampled at different times. Also, it is important to assess both how the outcome changes over time and the variation between participants' time-varying processes to make inferences about a particular intervention's effectiveness within the population of interest. The methods presented in this article integrate two innovative ILD analytic techniques: functional data analysis and dynamical systems modeling. An empirical application is presented using data from a smoking cessation clinical trial. Study participants provided 42 daily assessments of pre-quit and post-quit withdrawal symptoms. Regression splines were used to approximate smooth functions of craving and negative affect and to estimate the variables' derivatives for each participant. We then modeled the dynamics of nicotine craving using standard input-output dynamical systems models. These models provide a more detailed characterization of the post-quit craving process than do traditional longitudinal models, including information regarding the type, magnitude, and speed of the response to an input. The results, in conjunction with standard engineering control theory techniques, could potentially be used by tobacco researchers to develop a more effective smoking intervention. PMID:24079929

Air pollution exposure during pregnancy and ultrasound and birth measures of fetal growth: A prospective cohort study in Korea.

PubMed

Lamichhane, Dirga Kumar; Ryu, Jia; Leem, Jong-Han; Ha, Mina; Hong, Yun-Chul; Park, Hyesook; Kim, Yangho; Jung, Dal-Young; Lee, Ji-Young; Kim, Hwan-Cheol; Ha, Eun-Hee

2018-04-01

Few studies have examined the effects of air pollution on fetal growth based on ultrasound measures during pregnancy. More data is needed to evaluate the windows of special vulnerability. Our aim was to investigate the association of ambient air pollution during pregnancy with fetal and neonatal characteristics in a cohort of Korean women. Maternal exposure to particulate matter with an aerodynamic diameter<10μm (PM 10 ) and nitrogen dioxide (NO 2 ) was estimated using land-use regression models based on residential address. The biparietal diameter (BPD), abdominal circumference (AC), femur length (FL), and estimated fetal weight (EFW) were evaluated via ultrasonography, and birth weight (BW), birth length (BL), and head circumference at birth (BHC) were obtained from medical records. The multiple linear regression model was used to adjust for confounders, and the mixed-effect model was used to evaluate longitudinal effect. The negative effects for NO 2 and PM 10 were estimated; in the adjusted analyses the decreases of BPD were -0.26mm (95% confidence interval [CI]=-0.41 to -0.11, with a 10μg/m 3 increase) in the second trimester for NO 2 , and -0.30mm (95% CI=-0.59 to -0.03, with a 10μg/m 3 increase) in the third trimester for PM 10 . Both NO 2 and PM 10 levels (10μg/m 3 ) during third trimester were inversely associated with BHC, and NO 2 level was inversely associated with BL in all exposure windows. No significant associations for AC, FL, and EFW were observed. The longitudinal analyses showed inverse association of NO 2 exposure with head and length growth (P<0.001). Our findings suggest that ambient air pollution is associated with impaired fetal head size from mid-gestation onwards. Copyright © 2017 Elsevier B.V. All rights reserved.

Medication Use by Race and Ethnicity in Women Transitioning Through the Menopause: A Study of Women's Health Across the Nation Drug Epidemiology Study

PubMed Central

Ruppert, Kristine; Greendale, Gail A.; Lian, Yinjuan; Selzer, Faith; Finkelstein, Joel S.

2016-01-01

Abstract Background: Medication utilization and costs increased over the last decade, but the effects of race/ethnicity have never been well studied in longitudinal data. We analyzed reports of prescription medication use to (1) identify trajectories of use and (2) determine predictors associated with a large increase in use. Specifically, variations in medication use by race/ethnicity were examined. Methods: We analyzed the Study of Women's Health Across the Nation cohort with a median of 14 years of follow-up. Group-based trajectory models helped distinguish women with a low use of medications versus those with heavy use. Logistic regression was used to estimate the odds ratio (OR) for each racial/ethnic group associated with heavy use, controlling for potential baseline confounders. Results: The 2,798 women sampled had a mean age of 46 years at baseline and the median number of medications at baseline was 2, increasing to 4 over the follow-up period. Trajectory models identified that 16% of participants demonstrated heavy use of medications, from a median of 5 at baseline to 10 medications at final follow-up. Regression models controlling for age, obesity, number of comorbid conditions, and pain found that Hispanic (OR = 0.085, 95% confidence interval [CI]: 0.037–0.20), Chinese (OR = 0.32, 95% CI: 0.16–0.63), Japanese (OR = 0.33, 95% CI: 0.17–0.64), and Black (OR = 0.79, 95% CI: 0.57–1.11) women had lower odds for heavy use compared with White women. Conclusions: Longitudinal medication use among women in Study of Women's Health Across the Nation (SWAN) differed by race/ethnicity with non-White women having a lower odds of heavy use. PMID:27028503

Imaging muscle as a potential biomarker of denervation in motor neuron disease

PubMed Central

Jenkins, Thomas M; Alix, James J P; David, Charlotte; Pearson, Eilish; Rao, D Ganesh; Hoggard, Nigel; O’Brien, Eoghan; Baster, Kathleen; Bradburn, Michael; Bigley, Julia; McDermott, Christopher J; Wilkinson, Iain D; Shaw, Pamela J

2018-01-01

Objective To assess clinical, electrophysiological and whole-body muscle MRI measurements of progression in patients with motor neuron disease (MND), as tools for future clinical trials, and to probe pathophysiological mechanisms in vivo. Methods A prospective, longitudinal, observational, clinicoelectrophysiological and radiological cohort study was performed. Twenty-nine patients with MND and 22 age-matched and gender-matched healthy controls were assessed with clinical measures, electrophysiological motor unit number index (MUNIX) and T2-weighted whole-body muscle MRI, at first clinical presentation and 4 months later. Between-group differences and associations were assessed using age-adjusted and gender-adjusted multivariable regression models. Within-subject longitudinal changes were assessed using paired t-tests. Patterns of disease spread were modelled using mixed-effects multivariable regression, assessing associations between muscle relative T2 signal and anatomical adjacency to site of clinical onset. Results Patients with MND had 30% higher relative T2 muscle signal than controls at baseline (all regions mean, 95% CI 15% to 45%, p<0.001). Higher T2 signal was associated with greater overall disability (coefficient −0.009, 95% CI −0.017 to –0.001, p=0.023) and with clinical weakness and lower MUNIX in multiple individual muscles. Relative T2 signal in bilateral tibialis anterior increased over 4 months in patients with MND (right: 10.2%, 95% CI 2.0% to 18.4%, p=0.017; left: 14.1%, 95% CI 3.4% to 24.9%, p=0.013). Anatomically, contiguous disease spread on MRI was not apparent in this model. Conclusions Whole-body muscle MRI offers a new approach to objective assessment of denervation over short timescales in MND and enables investigation of patterns of disease spread in vivo. Muscles inaccessible to conventional clinical and electrophysiological assessment may be investigated using this methodology. PMID:29089397

Adolescent Psychosocial Development: A Review of Longitudinal Models and Research

ERIC Educational Resources Information Center

Meeus, Wim

2016-01-01

This review used 4 types of longitudinal models (descriptive models, prediction models, developmental sequence models and longitudinal mediation models) to identify regular patterns of psychosocial development in adolescence. Eight patterns of adolescent development were observed across countries: (1) adolescent maturation in multiple…

Inequality and adolescent violence: an exploration of community, family, and individual factors.

PubMed Central

Bruce, Marino A.

2004-01-01

PURPOSE: The study seeks to examine whether the relationships among community, family, individual factors, and violent behavior are parallel across race- and gender-specific segments of the adolescent population. METHODS: Data from the National Longitudinal Study of Adolescent Health are analyzed to highlight the complex relationships between inequality, community, family, individual behavior, and violence. RESULTS: The results from robust regression analysis provide evidence that social environmental factors can influence adolescent violence in race- and gender-specific ways. CONCLUSIONS: Findings from this study establish the plausibility of multidimensional models that specify a complex relationship between inequality and adolescent violence. PMID:15101669

Association between economic fluctuations and road mortality in OECD countries.

PubMed

Chen, Gang

2014-08-01

Using longitudinal data from 32 Organization for Economic Co-operation and Development (OECD) countries (1970-2010), this article investigates association between annual variations in road mortality and the economic fluctuations. Two regression models (fixed-effects and random-coefficients) were adopted for estimation. The cross-country data analyses suggested that road mortality is pro-cyclical and that the cyclicality is symmetric. Based on data from 32 OECD countries, an increase of on average 1% in economic growth is associated with a 1.1% increase in road mortality, and vice versa. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Oil Extraction and Indigenous Livelihoods in the Northern Ecuadorian Amazon

PubMed Central

Bozigar, Matthew; Gray, Clark L.; Bilsborrow, Richard E.

2015-01-01

Globally, the extraction of minerals and fossil fuels is increasingly penetrating into isolated regions inhabited by indigenous peoples, potentially undermining their livelihoods and well-being. To provide new insight to this issue, we draw on a unique longitudinal dataset collected in the Ecuadorian Amazon over an 11-year period from 484 indigenous households with varying degrees of exposure to oil extraction. Fixed and random effects regression models of the consequences of oil activities for livelihood outcomes reveal mixed and multidimensional effects. These results challenge common assumptions about these processes and are only partly consistent with hypotheses drawn from the Dutch disease literature. PMID:26543302

The relationship between odour annoyance scores and modelled ambient air pollution in Sarnia, "Chemical Valley", Ontario.

PubMed

Atari, Dominic Odwa; Luginaah, Isaac N; Fung, Karen

2009-10-01

This study aimed at establishing the relationship between annoyance scores and modelled air pollution in "Chemical Valley", Sarnia, Ontario (Canada). Annoyance scores were taken from a community health survey (N = 774); and respondents' exposure to nitrogen dioxide (NO(2)) and sulphur dioxide (SO(2)) were estimated using land use regression (LUR) models. The associations were examined by univariate analysis while multivariate logistic regression was used to examine the determinants of odour annoyance. The results showed that odour annoyance was significantly correlated to modelled pollutants at the individual (NO(2), r = 0.15; SO(2), r = 0.13) and census tract (NO(2), r = 0.56; SO(2), r = 0.67) levels. The exposure-response relationships show that residents of Sarnia react to very low pollution concentrations levels even if they are within the Ontario ambient air quality criteria. The study found that exposure to high NO(2) and SO(2) concentrations, gender, and perception of health effects were significant determinants of individual odour annoyance reporting. The observed association between odour annoyance and modelled ambient pollution suggest that individual and census tract level annoyance scores may serve as proxies for air quality in exposed communities because they capture the within area spatial variability of pollution. However, questionnaire-based odour annoyance scores need to be validated longitudinally and across different scales if they are to be adopted for use at the national level.

Estimating Time to Event From Longitudinal Categorical Data: An Analysis of Multiple Sclerosis Progression.

PubMed

Mandel, Micha; Gauthier, Susan A; Guttmann, Charles R G; Weiner, Howard L; Betensky, Rebecca A

2007-12-01

The expanded disability status scale (EDSS) is an ordinal score that measures progression in multiple sclerosis (MS). Progression is defined as reaching EDSS of a certain level (absolute progression) or increasing of one point of EDSS (relative progression). Survival methods for time to progression are not adequate for such data since they do not exploit the EDSS level at the end of follow-up. Instead, we suggest a Markov transitional model applicable for repeated categorical or ordinal data. This approach enables derivation of covariate-specific survival curves, obtained after estimation of the regression coefficients and manipulations of the resulting transition matrix. Large sample theory and resampling methods are employed to derive pointwise confidence intervals, which perform well in simulation. Methods for generating survival curves for time to EDSS of a certain level, time to increase of EDSS of at least one point, and time to two consecutive visits with EDSS greater than three are described explicitly. The regression models described are easily implemented using standard software packages. Survival curves are obtained from the regression results using packages that support simple matrix calculation. We present and demonstrate our method on data collected at the Partners MS center in Boston, MA. We apply our approach to progression defined by time to two consecutive visits with EDSS greater than three, and calculate crude (without covariates) and covariate-specific curves.

Hospital Contributions to the Delivery of Public Health Activities in US Metropolitan Areas: National and Longitudinal Trends

PubMed Central

Mays, Glen P.; Mamaril, Cezar B.

2015-01-01

Objectives. We investigated changes in hospital participation in local public health systems and the delivery of public health activities over time and assessed the relationship between hospital participation and the scope of activities available in local public health systems. Methods. We used longitudinal observations from the National Longitudinal Survey of Public Health Systems to examine how hospital contributions to the delivery of core public health activities varied in 1998, 2006, and 2012. We then used multivariate regression to assess the relationship between the level of hospital contributions and the overall availability of public health activities in the system. Results. Hospital participation in public health activities increased from 37% in 1998 to 41% in 2006 and down to 39% in 2012. Regression results indicated a positive association between hospital participation in public health activities and the total availability of public health services in the systems. Conclusions. Hospital collaboration does play an important role in the overall availability of public health services in local public health systems. Efforts to increase hospital participation in public health may have a positive impact on the scope of services provided and population health in US communities. PMID:26066929

Dietary patterns in the Avon Longitudinal Study of Parents and Children

PubMed Central

Jones, Louise R.; Northstone, Kate

2015-01-01

Publications from the Avon Longitudinal Study of Parents and Children that used empirically derived dietary patterns were reviewed. The relationships of dietary patterns with socioeconomic background and childhood development were examined. Diet was assessed using food frequency questionnaires and food records. Three statistical methods were used: principal components analysis, cluster analysis, and reduced rank regression. Throughout childhood, children and parents have similar dietary patterns. The “health-conscious” and “traditional” patterns were associated with high intakes of fruits and/or vegetables and better nutrient profiles than the “processed” patterns. There was evidence of tracking in childhood diet, with the “health-conscious” patterns tracking most strongly, followed by the “processed” pattern. An “energy-dense, low-fiber, high-fat” dietary pattern was extracted using reduced rank regression; high scores on this pattern were associated with increasing adiposity. Maternal education was a strong determinant of pattern score or cluster membership; low educational attainment was associated with higher scores on processed, energy-dense patterns in both parents and children. The Avon Longitudinal Study of Parents and Children has provided unique insights into the value of empirically derived dietary patterns and has demonstrated that they are a useful tool in nutritional epidemiology. PMID:26395343

Gender aspects of the relationship between migraine and cardiovascular risk factors: A cross-sectional evaluation in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

PubMed

Goulart, Alessandra C; Santos, Itamar S; Lotufo, Paulo A; Benseñor, Isabela M

2015-10-01

The relationship between cardiovascular risk factors (CVRF) and migraine is controversial and might be different in both genders. These associations were evaluated in Brazilian middle-aged men and women from the Longitudinal Study of Adult Health (ELSA-Brasil). The cross-sectional relationship between our main outcome, which was migraine headache (definite, probable and overall), and CVRF was evaluated in the total sample and according to gender. We calculated frequencies and odds ratios (95% CI) for this relationship using binary and multinomial logistic regression analyses in crude, age-adjusted and multivariable models adjusted by potential confounders. Of 14,953 individuals who completed the data about headache and CVRF, the frequency of one-year migraine was of 29.5% (22.5% in women and 7.0% in men). In the multivariable-adjusted regression analyses, an inverse association between hypertension (OR, 0.53; 95% CI, 0.36-0.79), metabolic syndrome (OR, 0.65; 95% CI, 0.43-0.99) and definite migraine were confirmed for men, but not for women. In the opposite direction, a positive association between migraine headaches (definite, probable and overall) and dyslipidemia (overall migraine OR, 1.25; 95% CI, 1.13-1.38) was observed only for women, but not for men. A gender influence on the relationship between migraine and CVRF was verified in the ELSA-Brasil. © International Headache Society 2015.

Longitudinal Poisson Regression To Evaluate the Epidemiology of Cryptosporidium, Giardia, and Fecal Indicator Bacteria in Coastal California Wetlands

PubMed Central

Hogan, Jennifer N.; Daniels, Miles E.; Watson, Fred G.; Conrad, Patricia A.; Oates, Stori C.; Miller, Melissa A.; Hardin, Dane; Byrne, Barbara A.; Dominik, Clare; Melli, Ann; Jessup, David A.

2012-01-01

Fecal pathogen contamination of watersheds worldwide is increasingly recognized, and natural wetlands may have an important role in mitigating fecal pathogen pollution flowing downstream. Given that waterborne protozoa, such as Cryptosporidium and Giardia, are transported within surface waters, this study evaluated associations between fecal protozoa and various wetland-specific and environmental risk factors. This study focused on three distinct coastal California wetlands: (i) a tidally influenced slough bordered by urban and agricultural areas, (ii) a seasonal wetland adjacent to a dairy, and (iii) a constructed wetland that receives agricultural runoff. Wetland type, seasonality, rainfall, and various water quality parameters were evaluated using longitudinal Poisson regression to model effects on concentrations of protozoa and indicator bacteria (Escherichia coli and total coliform). Among wetland types, the dairy wetland exhibited the highest protozoal and bacterial concentrations, and despite significant reductions in microbe concentrations, the wetland could still be seen to influence water quality in the downstream tidal wetland. Additionally, recent rainfall events were associated with higher protozoal and bacterial counts in wetland water samples across all wetland types. Notably, detection of E. coli concentrations greater than a 400 most probable number (MPN) per 100 ml was associated with higher Cryptosporidium oocyst and Giardia cyst concentrations. These findings show that natural wetlands draining agricultural and livestock operation runoff into human-utilized waterways should be considered potential sources of pathogens and that wetlands can be instrumental in reducing pathogen loads to downstream waters. PMID:22427504

Identifying patterns of item missing survey data using latent groups: an observational study.

PubMed

Barnett, Adrian G; McElwee, Paul; Nathan, Andrea; Burton, Nicola W; Turrell, Gavin

2017-10-30

To examine whether respondents to a survey of health and physical activity and potential determinants could be grouped according to the questions they missed, known as 'item missing'. Observational study of longitudinal data. Residents of Brisbane, Australia. 6901 people aged 40-65 years in 2007. We used a latent class model with a mixture of multinomial distributions and chose the number of classes using the Bayesian information criterion. We used logistic regression to examine if participants' characteristics were associated with their modal latent class. We used logistic regression to examine whether the amount of item missing in a survey predicted wave missing in the following survey. Four per cent of participants missed almost one-fifth of the questions, and this group missed more questions in the middle of the survey. Eighty-three per cent of participants completed almost every question, but had a relatively high missing probability for a question on sleep time, a question which had an inconsistent presentation compared with the rest of the survey. Participants who completed almost every question were generally younger and more educated. Participants who completed more questions were less likely to miss the next longitudinal wave. Examining patterns in item missing data has improved our understanding of how missing data were generated and has informed future survey design to help reduce missing data. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Matsuda-DeFronzo insulin sensitivity index is a better predictor than HOMA-IR of hypertension in Japanese: the Tanno-Sobetsu study.

PubMed

Furugen, M; Saitoh, S; Ohnishi, H; Akasaka, H; Mitsumata, K; Chiba, M; Furukawa, T; Miyazaki, Y; Shimamoto, K; Miura, T

2012-05-01

Here we examined whether the Matsuda-DeFronzo insulin sensitivity index (ISI-M) is more efficient than the homeostasis model assessment of insulin resistance (HOMA-IR) for assessing risk of hypertension. Cross-sectional and longitudinal analyses were conducted using normotensive subjects who were selected among 1399 subjects in the Tanno-Sobetsu cohort. In the cross-sectional analysis (n=740), blood pressure (BP) level was correlated with HOMA-IR and with ISI-M, but correlation coefficients indicate a tighter correlation with ISI-M. Multiple linear regression analysis adjusted by age, sex, body mass index (BMI) and serum triglyceride level (TG) showed contribution of ISI-M and fasting plasma glucose, but not of HOMA-IR. In the longitudinal analysis (n=607), 241 subjects (39.7%) developed hypertension during a 10-year follow-up period, and multiple logistic regression indicated that age, TG, systolic BP and ISI-M, but not HOMA-IR, were associated with development of hypertension. In subjects <60 years old, odds ratio of new-onset hypertension was higher in the low ISI-M group (ISI-M, less than the median) than in the high ISI-M group for any tertile of BMI. In conclusion, ISI-M is a better predictor of hypertension than is HOMA-IR. Non-hepatic IR may be a determinant, which is independent of TG, BP level and BMI, of the development of hypertension.

The association between green space and mental health varies across the lifecourse. A longitudinal study.

PubMed

Astell-Burt, Thomas; Mitchell, Richard; Hartig, Terry

2014-06-01

Epidemiological studies on green space and health have relied almost exclusively on cross-sectional designs, restricting understanding on how this relationship could vary across the lifecourse. We used multilevel linear regression to analyse variation in minor psychiatric morbidity over nine annual waves of the British Household Panel Survey (1996-2004). The sample was restricted to residents of urban areas who remained within their neighbourhoods for at least 12 months. The 12-item General Health Questionnaire and confounders were reported for 29 626 male and 35 781 female observations (person-years). This individual-level dataset was linked to a measure of green space availability within each ward of residence. Regression models included age, gender, employment status, household tenure, marital status, education, smoking status and household income. When not considering age, green space was associated with better mental health among men, but not women. Interaction terms fitted between age and green space revealed variation in the association between green space and mental health across the lifecourse and by gender. For men, the benefit of more green space emerged in early to mid-adulthood. Among older women, a curvilinear association materialised wherein those with a moderate availability of green space had better mental health. These findings illustrate how the relationship between urban green space and health can vary across the lifecourse, and they highlight the need for longitudinal studies to answer why green space may be better for health at some points in the lifecourse than others.

Poverty and Child Development: A Longitudinal Study of the Impact of the Earned Income Tax Credit

PubMed Central

Hamad, Rita; Rehkopf, David H.

2016-01-01

Although adverse socioeconomic conditions are correlated with worse child health and development, the effects of poverty-alleviation policies are less understood. We examined the associations of the Earned Income Tax Credit (EITC) on child development and used an instrumental variable approach to estimate the potential impacts of income. We used data from the US National Longitudinal Survey of Youth (n = 8,186) during 1986–2000 to examine effects on the Behavioral Problems Index (BPI) and Home Observation Measurement of the Environment inventory (HOME) scores. We conducted 2 analyses. In the first, we used multivariate linear regressions with child-level fixed effects to examine the association of EITC payment size with BPI and HOME scores; in the second, we used EITC payment size as an instrument to estimate the associations of income with BPI and HOME scores. In linear regression models, higher EITC payments were associated with improved short-term BPI scores (per $1,000, β = −0.57; P = 0.04). In instrumental variable analyses, higher income was associated with improved short-term BPI scores (per $1,000, β = −0.47; P = 0.01) and medium-term HOME scores (per $1,000, β = 0.64; P = 0.02). Our results suggest that both EITC benefits and higher income are associated with modest but meaningful improvements in child development. These findings provide valuable information for health researchers and policymakers for improving child health and development. PMID:27056961

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

PubMed

Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

2017-07-01

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

Longitudinal study of bad dreams in preschool-aged children: prevalence, demographic correlates, risk and protective factors.

PubMed

Simard, Valérie; Nielsen, Tore A; Tremblay, Richard E; Boivin, Michel; Montplaisir, Jacques Y

2008-01-01

To (1) clarify the epidemiology of bad dreams in children and investigate risk and protective factors related to (2) the child's sleep, (3) parental sleep-enabling practices, and (4) the child's temperament. Longitudinal with 6 time points from 5 months to 6 years. Subjects' homes. Representative sample of 987 children in the Province of Quebec. None. Longitudinal logistic regression analysis models with primary endpoints of presence or absence of parent-rated bad dreams at 29 months, 41 months, 50 months, 5 years, and 6 years and predictor variables of demographic characteristics, parent ratings of child's sleep characteristics, parental sleep-enabling practices (e.g., cosleeping), and child's psychological characteristics at 5 and 17 months (anxiousness, temperament). Mothers' ratings indicated lower than expected prevalence of frequent bad dreams (1.3% to 3.9%). Demographic correlates of bad dreams were high family income, absence of siblings at 29 months, and a non-immigrant mother. The best predictor at 41 and 50 months was the presence of bad dreams the preceding year, whereas at 5 and 6 years, it was their earlier presence at 29 months. Early protective factors were parental practices favoring emotional nurturance after night awakenings (29 and 41 months); early risk factors were sleep-onset emotional nurturance (29 months), difficult temperament (5 months), and anxiousness (17 months). Bad dreams in preschoolers are less prevalent than thought but, when present, are trait-like in nature and associated with personality characteristics measured as early as 5 months. A stress-diathesis model may best account for the observed pattern of predictive factors.

Attention Deficit Disorder, Stimulant Use, and Childhood Body Mass Index Trajectory

PubMed Central

Bailey-Davis, Lisa; Bandeen-Roche, Karen; Pollak, Jonathan; Hirsch, Annemarie G.; Nau, Claudia; Liu, Ann Y.; Glass, Thomas A.

2014-01-01

BACKGROUND: Childhood attention-deficit/hyperactivity disorder (ADHD) has been associated with childhood and adult obesity, and stimulant use with delayed childhood growth, but the independent influences are unclear. No longitudinal studies have examined associations of ADHD diagnosis and stimulant use on BMI trajectories throughout childhood and adolescence. METHODS: We used longitudinal electronic health record data from the Geisinger Health System on 163 820 children ages 3 to 18 years in Pennsylvania. Random effects linear regression models were used to model BMI trajectories with increasing age in relation to ADHD diagnosis, age at first stimulant use, and stimulant use duration, while controlling for confounding variables. RESULTS: Mean (SD) age at first BMI was 8.9 (5.0) years, and children provided a mean (SD) of 3.2 (2.4) annual BMI measurements. On average, BMI trajectories showed a curvilinear relation with age. There were consistent associations of unmedicated ADHD with higher BMIs during childhood compared with those without ADHD or stimulants. Younger age at first stimulant use and longer duration of stimulant use were each associated with slower BMI growth earlier in childhood but a more rapid rebound to higher BMIs in late adolescence. CONCLUSIONS: The study provides the first longitudinal evidence that ADHD during childhood not treated with stimulants was associated with higher childhood BMIs. In contrast, ADHD treated with stimulants was associated with slower early BMI growth but a rebound later in adolescence to levels above children without a history of ADHD or stimulant use. The findings have important clinical and neurobiological implications. PMID:24639278

Longitudinal performance of plasma neurofilament light and tau in professional fighters: The Professional Fighters Brain Health Study.

PubMed

Bernick, Charles; Zetterberg, Henrik; Shan, Guogen; Banks, Sarah; Blennow, Kaj

2018-04-02

The objective of this study is to evaluate longitudinal change in plasma neurofilament light (NF-L) and tau levels in relationship to clinical and radiological measures in professional fighters. Participants (active and retired professional fighters and control group) underwent annual blood sampling, 3 Tesla MRI brain imaging, computerized cognitive testing, and assessment of exposure to head trauma. Plasma tau and NF-L concentrations were measured using Simoa assays. Multiple linear regression models were used to compare the difference across groups in regard to baseline measurements, while mixed linear models was used for the longitudinal data with multiple measurements for each participant. Plasma samples were available on 471 participants. Baseline NF-L measures differed across groups (F_3,393=6.99, p=0.0001), with the active boxers having the highest levels. Higher NF-L levels at baseline were correlated with lower baseline MRI regional volumes and lower cognitive scores. The number of sparring rounds completed by the active fighters was correlated with NF-L (95% CI 0.0116-0.4053, p=0.0381), but not tau, levels. Among 126 subjects having multiple yearly samples, there was a significant difference in average yearly percentage change in tau across groups (F_3,83=3.87, p=0.0121).). We conclude that plasma NF-L and tau behave differently in a group of active and retired fighters; NF-L better reflects acute exposure whereas the role of plasma tau levels in signifying chronic change in brain structure over time requires further study.

Measuring women's cumulative neighborhood deprivation exposure using longitudinally linked vital records: a method for life course MCH research.

PubMed

Kramer, Michael R; Dunlop, Anne L; Hogue, Carol J R

2014-02-01

A life course conceptual framework for MCH research demands new tools for understanding population health and measuring exposures. We propose a method for measuring population-based socio-environmental trajectories for women of reproductive age. We merged maternal longitudinally-linked births to Georgia-resident women from 1994 to 2007 with census economic and social measures using residential geocodes to create woman-centered socio-environmental trajectories. We calculated a woman's neighborhood deprivation index (NDI) at the time of each of her births and, from these, we calculated a cumulative NDI. We fit Loess curves to describe average life course NDI trajectories and binomial regression models to test specific life course theory hypotheses relating cumulative NDI to risk for preterm birth. Of the 1,815,944 total live births, we linked 1,000,437 live births to 413,048 unique women with two or more births. Record linkage had high specificity but relatively low sensitivity which appears non-differential with respect to maternal characteristics. Georgia women on average experienced upward mobility across the life course, although differences by race, early life neighborhood quality, and age at first birth produced differences in cumulative NDI. Adjusted binomial models found evidence for modification of the effect of history of prior preterm birth and advancing age on risk for preterm birth by cumulative NDI. The creation of trajectories from geocoded maternal longitudinally-linked vital records is one method to carry out life course MCH research. We discuss approaches for investigating the impact of truncation of the life course, selection bias from migration, and misclassification of cumulative exposure.

Identification of the predictors of cognitive impairment in patients with cancer in palliative care: a prospective longitudinal analysis.

PubMed

Kurita, Geana Paula; Benthien, Kirstine Skov; Sjøgren, Per; Kaasa, Stein; Hjermstad, Marianne Jensen

2017-03-01

Studies with neuropsychological assessments in patients with cancer are sparse, and the evidence is very limited regarding their status of cognitive function over time. This study aimed at assessing the prevalence and predictors of cognitive impairment in patients with cancer in palliative care. Prospective longitudinal investigation derived from the European Palliative Care Cancer Symptom study (2011-2013) including patients with cancer in palliative care, ≥18 years, and with at least one assessment post-inclusion. For cognitive assessment, a 4-item version of the Mini Mental State Examination was applied at inclusion and after 4 to 16 weeks. Logistic regression model with multiple imputations was applied. The sample consisted of 1568 patients (50% male, mean age 65.5, 42% with 10-12 years schooling, mean Karnofsky Performance Status-KPS 68%). Longitudinal analysis of the patients with complete MMSE at both assessments (n = 801) showed that 64.5% were not impaired, 12.5% remained cognitively impaired, 11.4% developed impairment, and 11.6% improved. Those who improved cognitively also reported reduced pain intensity and increased appetite. The predictive model (n = 1351) showed that those with low KPS (OR = 1.6, 95% CI 1.0-2.5) most often developed cognitive impairment, while patients with breast cancer (OR = 0.4, 95% CI 0.2-0.7) had lower odds for impairment. During palliative care, a substantial number of patients remained cognitively impaired or developed cognitive impairment; however, it is noteworthy that improvement was also observed. Physical performance and cancer type may predict cognitive impairment.

Psychological distress, depression, anxiety, and burnout among international humanitarian aid workers: a longitudinal study.

PubMed

Lopes Cardozo, Barbara; Gotway Crawford, Carol; Eriksson, Cynthia; Zhu, Julia; Sabin, Miriam; Ager, Alastair; Foy, David; Snider, Leslie; Scholte, Willem; Kaiser, Reinhard; Olff, Miranda; Rijnen, Bas; Simon, Winnifred

2012-01-01

International humanitarian aid workers providing care in emergencies are subjected to numerous chronic and traumatic stressors. To examine consequences of such experiences on aid workers' mental health and how the impact is influenced by moderating variables. We conducted a longitudinal study in a sample of international non-governmental organizations. Study outcomes included anxiety, depression, burnout, and life and job satisfaction. We performed bivariate regression analyses at three time points. We fitted generalized estimating equation multivariable regression models for the longitudinal analyses. Study participants from 19 NGOs were assessed at three time points: 212 participated at pre-deployment; 169 (80%) post-deployment; and 154 (73%) within 3-6 months after deployment. Prior to deployment, 12 (3.8%) participants reported anxiety symptoms, compared to 20 (11.8%) at post-deployment (p = 0.0027); 22 (10.4%) reported depression symptoms, compared to 33 (19.5%) at post-deployment (p = 0.0117) and 31 (20.1%) at follow-up (p = .00083). History of mental illness (adjusted odds ratio [AOR] 4.2; 95% confidence interval [CI] 1.45-12.50) contributed to an increased risk for anxiety. The experience of extraordinary stress was a contributor to increased risk for burnout depersonalization (AOR 1.5; 95% CI 1.17-1.83). Higher levels of chronic stress exposure during deployment were contributors to an increased risk for depression (AOR 1.1; 95% CI 1.02-1.20) comparing post- versus pre-deployment, and increased risk for burnout emotional exhaustion (AOR 1.1; 95% CI 1.04-1.19). Social support was associated with lower levels of depression (AOR 0.9; 95% CI 0.84-0.95), psychological distress (AOR = 0.9; [CI] 0.85-0.97), burnout lack of personal accomplishment (AOR 0.95; 95% CI 0.91-0.98), and greater life satisfaction (p = 0.0213). When recruiting and preparing aid workers for deployment, organizations should consider history of mental illness and take steps to decrease chronic stressors, and strengthen social support networks.

Associations Between Statin Use and Physical Function in Older Adults from The Netherlands and Australia: Longitudinal Aging Study Amsterdam and Australian Longitudinal Study on Women's Health.

PubMed

van Boheemen, Laurette; Tett, Susan E; Sohl, Evelien; Hugtenburg, Jacqueline G; van Schoor, Natasja M; Peeters, G M E E

2016-06-01

Statin therapy may cause myopathy, but long-term effects on physical function are unclear. We investigated whether statin use is associated with poorer physical function in two population-based cohorts of older adults. Data were from 691 men and women (aged 69-102 years in 2005/2006) in the LASA (Longitudinal Aging Study Amsterdam) and 5912 women (aged 79-84 years in 2005) in the ALSWH (Australian Longitudinal Study on Women's Health). Statin use and dose were sourced from containers (LASA) and administrative databases (ALSWH). Physical function was assessed using performance tests, questionnaires on functional limitations and the SF-12 (LASA) and SF-36 (ALSWH) questionnaires. Cross-sectional (both studies) and 3-year prospective associations (ALSWH) were analysed for different statin dosage using linear and logistic regression. In total, 25 % of participants in LASA and 61 % in ALSWH used statins. In the cross-sectional models in LASA, statin users were less likely to have functional limitations (percentage of subjects with at least 1 limitation 63.9 vs. 64.2; odds ratio [OR] 0.6; 95 % confidence interval [CI] 0.3-0.9) and had better SF-12 physical component scores (mean [adjusted] 47.3 vs. 44.5; beta [B] = 2.8; 95 % CI 1.1-4.5); in ALSWH, statin users had better SF-36 physical component scores (mean [adjusted] 37.4 vs. 36.5; B = 0.9; 95 % CI 0.3-1.5) and physical functioning subscale scores (mean [adjusted] 55.1 vs. 52.6; B = 2.4; 95 % CI 1.1-3.8) than non-users. Similar associations were found for low- and high-dose users and in the prospective models. In contrast, no significant associations were found with performance tests. Two databases from longitudinal population studies in older adults gave comparable results, even though different outcome measures were used. In these two large cohorts, statin use was associated with better self-perceived physical function.

Longitudinal validity and responsiveness of the Food Allergy Quality of Life Questionnaire - Parent Form in children 0-12 years following positive and negative food challenges.

PubMed

DunnGalvin, A; Cullinane, C; Daly, D A; Flokstra-de Blok, B M J; Dubois, A E J; Hourihane, J O'B

2010-03-01

There are no published studies of longitudinal health-related quality of life (HRQL) assessments of food-allergic children using a disease-specific measure. This study assessed the longitudinal measurement properties of the Food Allergy Quality of Life Questionnaire - Parent Form (FAQLQ-PF) in a sample of children undergoing food challenge. Parents of children 0-12 years completed the FAQLQ-PF and the Food Allergy Independent Measure (FAIM) pre-challenge and at 2 and 6 months post food challenge. In order to evaluate longitudinal validity, differences between Group A (positive challenge) and Group B (negative challenge) were expected over time. We computed correlation coefficients between change scores in the FAQLQ-PF and change scores in the FAIM. To determine the minimally important difference (MID), we used distributional criterion and effect size approaches. A logistic regression model profiled those children falling below this point. Eighty-two children underwent a challenge (42 positive; 40 negative). Domains and total score improved significantly at pos-challenge time-points for both groups (all P<0.05). Sensitivity was demonstrated by significant differences between positive and negative groups at 6 months [F(2, 59)=6.221, P<0.003] and by differing improvement on relevant subscales (P<0.05). MID was 0.45 on a seven-point response scale. Poorer quality of life at baseline increased the odds by over 2.0 of no improvement in HRQL scores 6-month time-point. General maternal health (OR 1.252), number of foods avoided (OR 1.369) and children >9 years (OR 1.173) were also predictors. The model correctly identified 84% of cases below MID. The FAQLQ-PF is sensitive to change, and has excellent longitudinal reliability and validity in a food-allergic patient population. The standard error of measurement value of 0.5 points as a threshold for meaningful change in HRQL questionnaires was confirmed. The FAQLQ-PF may be used to identify problems in children, to assess the effectiveness of clinical trials or interventions, and to guide the development of regulatory policies.

Quantitative Evaluation of the Fetal Right and Left Ventricular Fractional Area Change Using Speckle Tracking Technology.

PubMed

DeVore, Greggory R; Klas, Berthold; Satou, Gary; Sklansky, Mark

2018-03-14

The purpose of this study was to measure the fractional area change (FAC) of the right and left ventricles in normal fetal hearts between 20 and 40 weeks of gestation using speckle-tracking software. The 4-chamber view of the fetal heart was obtained in 200 control fetuses between 20 and 40 weeks of gestation. The FAC was computed from the ventricular areas [((end-diastolic area) - (end-systolic area)/(end-diastolic area)) x 100] for the right and left ventricles and regressed against 7 independent biometric and age variables. The FAC was correlated with longitudinal fractional shortening (LFS) [((end-diastolic longitudinal length) - (end-systolic longitudinal length) /(end-diastolic longitudinal length)) x 100] obtained from the mid ventricular basal-apical lengths of the right and left ventricular chambers and the transverse fractional shortening (TFS) [((end-diastolic transverse length) - (end-systolic transverse length)/(end-diastolic transverse length)) x 100] from three transverse positions (base, mid, apical) located within each ventricular chamber. To evaluate potential clinical utility, the FAC, LFS, and TFS results were examined in 9 fetuses with congenital heart defects (CHD). Regression analysis demonstrated significant associations between the FAC and the biometric and age independent variables (R 2 = 0.13 - 0.15). The FAC was significantly correlated with the LFS (R 2 =0.18 to 0.28) and TFS (R 2 = 0.13 to 0.33). The 9 fetuses with CHD illustrated the interrelationship between the FAC, LFS, and TFS when identifying abnormal ventricular function. This study reports results from measuring the FAC of the right and left ventricles, and demonstrates a correlation with longitudinal fractional shortening (LFS) and transverse fractional shortening (TFS). This article is protected by copyright. All rights reserved.

Generation of longitudinal vibrations in piano strings: From physics to sound synthesis

NASA Astrophysics Data System (ADS)

Bank, Balázs; Sujbert, László

2005-04-01

Longitudinal vibration of piano strings greatly contributes to the distinctive character of low piano notes. In this paper a simplified modal model is developed, which describes the generation of phantom partials and longitudinal free modes jointly. The model is based on the simplification that the coupling from the transverse vibration to the longitudinal polarization is unidirectional. The modal formulation makes it possible to predict the prominent components of longitudinal vibration as a function of transverse modal frequencies. This provides a qualitative insight into the generation of longitudinal vibration, while the model is still capable of explaining the empirical results of earlier works. The semi-quantitative agreement with measurement results implies that the main source of phantom partials is the transverse to longitudinal coupling, while the string termination and the longitudinal to transverse coupling have only small influence. The results suggest that the longitudinal component of the tone can be treated as a quasi-harmonic spectrum with formantlike peaks at the longitudinal modal frequencies. The model is further simplified and applied for the real-time synthesis of piano sound with convincing sonic results. .

Tank Tests of Models of Flying Boat Hulls Having Longitudinal Steps

NASA Technical Reports Server (NTRS)

Allison, John M; Ward, Kenneth E

1936-01-01

Four models with longitudinal steps on the forebody were developed by modification of a model of a conventional hull and were tested in the National Advisory Committee for Aeronautics (NACA) tank. Models with longitudinal steps were found to have smaller resistance at high speed and greater resistance at low speed than the parent model that had the same afterbody but a conventional V-section forebody. The models with a single longitudinal step had better performance at hump speed and as low high-speed resistance except at very light loads. Spray strips at angles from 0 degrees to 45 degrees to the horizontal were fitted at the longitudinal steps and at the chine on one of the two step models having two longitudinal steps. The resistance and the height of the spray were less with each of the spray strips than without; the most favorable angle was found to lie between 15 degrees and 30 degrees.

Using Telephone and Informant Assessments to Estimate Missing Modified Mini-Mental State Exam Scores and Rates of Cognitive Decline

PubMed Central

Arnold, Alice M.; Newman, Anne B.; Dermond, Norma; Haan, Mary; Fitzpatrick, Annette

2009-01-01

Aim To estimate an equivalent to the Modified Mini-Mental State Exam (3MSE), and to compare changes in the 3MSE with and without the estimated scores. Methods Comparability study on a subset of 405 participants, aged ≥70 years, from the Cardiovascular Health Study (CHS), a longitudinal study in 4 United States communities. The 3MSE, the Telephone Interview for Cognitive Status (TICS) and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) were administered within 30 days of one another. Regression models were developed to predict the 3MSE score from the TICS and/or IQCODE, and the predicted values were used to estimate missing 3MSE scores in longitudinal follow-up of 4,274 CHS participants. Results The TICS explained 67% of the variability in 3MSE scores, with a correlation of 0.82 between predicted and observed scores. The IQCODE alone was not a good estimate of 3MSE score, but improved the model fit when added to the TICS model. Using estimated 3MSE scores classified more participants with low cognition, and rates of decline were greater than when only the observed 3MSE scores were considered. Conclusions 3MSE scores can be reliably estimated from the TICS, with or without the IQCODE. Incorporating these estimates captured more cognitive decline in older adults. PMID:19407461

New evidence on the validity of the Arnett Caregiver Interaction Scale: Results from the Early Childhood Longitudinal Study-Birth Cohort

PubMed Central

Colwell, Nicole; Gordon, Rachel A.; Fujimoto, Ken; Kaestner, Robert; Korenman, Sanders

2013-01-01

The Arnett Caregiver Interaction Scale (CIS) has been widely used in research studies to measure the quality of caregiver–child interactions. The scale was modeled on a well-established theory of parenting, but there are few psychometric studies of its validity. We applied factor analyses and item response theory methods to assess the psychometric properties of the Arnett CIS in a national sample of toddlers in home-based care and preschoolers in center-based care from the Early Childhood Longitudinal Study-Birth Cohort. We found that a bifactor structure (one common factor and a second set of specific factors) best fits the data. In the Arnett CIS, the bifactor model distinguishes a common substantive dimension from two methodological dimensions (for positively and negatively oriented items). Despite the good fit of this model, the items are skewed (most teachers/caregivers display positive interactions with children) and, as a result, the Arnett CIS is not well suited to distinguish between caregivers who are “highly” versus “moderately” positive in their interactions with children, according to the items on the scale. Regression-adjusted associations between the Arnett CIS and child outcomes are small, especially for preschoolers in centers. We encourage future scale development work on measures of child care quality by early childhood scholars. PMID:24058264

Extracurricular activity participation moderates impact of family and school factors on adolescents' disruptive behavioural problems.

PubMed

Driessens, Corine M E F

2015-11-11

The prevalence of problem behaviours among British adolescents has increased in the past decades. Following Erikson's psychosocial developmental theory and Bronfenbrenner's developmental ecological model, it was hypothesized that youth problem behaviour is shaped in part by social environment. The aim of this project was to explore potential protective factors within the social environment of British youth's for the presentation of disruptive behavioural problems. This study used secondary data from the Longitudinal Study of Young People in England, a cohort study of secondary school students. These data were analysed with generalized estimation equations to take the correlation between the longitudinal observations into account. Three models were built. The first model determined the effect of family, school, and extracurricular setting on presentation of disruptive behavioural problems. The second model expanded the first model by assuming extracurricular activities as protective factors that moderated the interaction between family and school factors with disruptive behavioural problems. The third model described the effect of prior disruptive behaviour on current disruptive behaviour. Associations were found between school factors, family factors, involvement in extracurricular activities and presence of disruptive behavioural problems. Results from the second generalized estimating equation (GEE) logistic regression models indicated that extracurricular activities buffered the impact of school and family factors on the presence of disruptive behavioural problems. For instance, participation in sports activities decreased the effect of bullying on psychological distress. Results from the third model indicated that prior acts of disruptive behaviour reinforced current disruptive behaviour. This study supports Erikson's psychosocial developmental theory and Bronfenbrenner's developmental ecological model; social environment did influence the presence of disruptive behavioural problems for British adolescents. The potential of extracurricular activities to intervention strategies addressing disruptive behavioural problems of adolescents is discussed.

The Latent Curve ARMA (P, Q) Panel Model: Longitudinal Data Analysis in Educational Research and Evaluation

ERIC Educational Resources Information Center

Sivo, Stephen; Fan, Xitao

2008-01-01

Autocorrelated residuals in longitudinal data are widely reported as common to longitudinal data. Yet few, if any, researchers modeling growth processes evaluate a priori whether their data have this feature. Sivo, Fan, and Witta (2005) found that not modeling autocorrelated residuals present in longitudinal data severely biases latent curve…

Adjustment Disorders as a Stress-Related Disorder: A Longitudinal Study of the Associations among Stress, Resources, and Mental Health

PubMed Central

Kocalevent, Rüya-Daniela; Mierke, Annett; Danzer, Gerhard; Klapp, Burghard F.

2014-01-01

Objective Adjustment disorders are re-conceptualized in the DSM-5 as a stress-related disorder; however, besides the impact of an identifiable stressor, the specification of a stress concept, remains unclear. This study is the first to examine an existing stress-model from the general population, in patients diagnosed with adjustment disorders, using a longitudinal design. Methods The study sample consisted of 108 patients consecutively admitted for adjustment disorders. Associations of stress perception, emotional distress, resources, and mental health were measured at three time points: the outpatients’ presentation, admission for inpatient treatment, and discharge from the hospital. To evaluate a longitudinal stress model of ADs, we examined whether stress at admission predicted mental health at each of the three time points using multiple linear regressions and structural equation modeling. A series of repeated-measures one-way analyses of variance (rANOVAs) was performed to assess change over time. Results Significant within-participant changes from baseline were observed between hospital admission and discharge with regard to mental health, stress perception, and emotional distress (p<0.001). Stress perception explained nearly half of the total variance (44%) of mental health at baseline; the adjusted R2 increased (0.48), taking emotional distress (i.e., depressive symptoms) into account. The best predictor of mental health at discharge was the level of emotional distress (i.e., anxiety level) at baseline (β = −0.23, R2 corr = 0.56, p<0.001). With a CFI of 0.86 and an NFI of 0.86, the fit indices did not allow for acceptance of the stress-model (Cmin/df = 15.26; RMSEA = 0.21). Conclusions Stress perception is an important predictor in adjustment disorders, and mental health-related treatment goals are dependent on and significantly impacted by stress perception and emotional distress. PMID:24825165

A Study of the Factors Associated with Risk for Development of Pressure Ulcers: A Longitudinal Analysis.

PubMed

Thomas, Elizebeth; Vinodkumar, Sudhaya; Mathew, Silvia; Setia, Maninder Singh

2015-01-01

Pressure ulcers (PUs) are prevalent in hospitalized patients; they may cause clinical, psychological, and economic problems in these patients. Previous studies are cross-sectional, have used pooled data, or cox-regression models to assess the risk for developing PU. However, PU risk scores change over time and models that account for time varying variables are useful for cohort analysis of data. The present longitudinal study was conducted to compare the risk of PU between surgical and nonsurgical patients, and to evaluate the factors associated with the development of these ulcers over a period of time. We evaluated 290 hospitalized patients over a 4 months period. The main outcomes for our analysis were: (1) Score on the pressure risk assessment scale; and (2) the proportion of individuals who were at severe risk for developing PUs. We used random effects models for longitudinal analysis of the data. The mean PU score was significantly higher in the nonsurgical patients compared with surgical patients at baseline (15.23 [3.86] vs. 9.33 [4.57]; P < 0.01). About 7% of the total patients had a score of >20 at baseline and were considered as being at high-risk for PU; the proportion was significantly higher among the nonsurgical patients compared with the surgical patients (14% vs. 4%, P = 0.003). In the adjusted models, there was no difference for severe risk for PU between surgical and nonsurgical patients (odds ratios [ORs]: 0.37, 95% confidence interval [CI]: 0.01-12.80). An additional day in the ward was associated with a significantly higher likelihood of being at high-risk for PU (OR: 1.47, 95% CI: 1.16-1.86). There were no significant differences between patients who were admitted for surgery compared with those who were not. An additional day in the ward, however, is important for developing a high-risk score for PU on the monitoring scale, and these patients require active interventions.

Assessing the Relationship Between Chronic Health Conditions and Productivity Loss Trajectories

PubMed Central

Pranksy, Glenn

2014-01-01

Objective: To examine the relationship between health conditions and the risk for membership in longitudinal trajectories of productivity loss. Methods: Trajectories of productivity loss from the ages of 25 to 44 years, previously identified in the National Longitudinal Survey of Youth (NLSY79), were combined with information on health conditions from the age 40 years health module in the NLSY79. Multinomial logistic regression was used to examine the relative risk of being in the low-risk, early-onset increasing risk, late-onset increasing risk, or high-risk trajectories compared with the no-risk trajectory for having various health conditions. Results: The trajectories with the greatest probability of productivity loss longitudinally had a greater prevalence of the individual health conditions and a greater total number of health conditions experienced. Conclusions: Health conditions are associated with specific longitudinal patterns of experiencing productivity loss. PMID:25479294

Longitudinal Study of Bad Dreams in Preschool-Aged Children: Prevalence, Demographic Correlates, Risk and Protective Factors

PubMed Central

Simard, Valérie; Nielsen, Tore A.; Tremblay, Richard E.; Boivin, Michel; Montplaisir, Jacques Y.

2008-01-01

Study objectives: To (1) clarify the epidemiology of bad dreams in children and investigate risk and protective factors related to (2) the child's sleep, (3) parental sleep-enabling practices, and (4) the child's temperament. Design: Longitudinal with 6 time points from 5 months to 6 years. Setting: Subjects' homes. Participants: Representative sample of 987 children in the Province of Quebec. Interventions: None. Measurements and Results: Longitudinal logistic regression analysis models with primary endpoints of presence or absence of parent-rated bad dreams at 29 months, 41 months, 50 months, 5 years, and 6 years and predictor variables of demographic characteristics, parent ratings of child's sleep characteristics, parental sleep-enabling practices (e.g., cosleeping), and child's psychological characteristics at 5 and 17 months (anxiousness, temperament). Mothers' ratings indicated lower than expected prevalence of frequent bad dreams (1.3% to 3.9%). Demographic correlates of bad dreams were high family income, absence of siblings at 29 months, and a non-immigrant mother. The best predictor at 41 and 50 months was the presence of bad dreams the preceding year, whereas at 5 and 6 years, it was their earlier presence at 29 months. Early protective factors were parental practices favoring emotional nurturance after night awakenings (29 and 41 months); early risk factors were sleep-onset emotional nurturance (29 months), difficult temperament (5 months), and anxiousness (17 months). Conclusions: Bad dreams in preschoolers are less prevalent than thought but, when present, are trait-like in nature and associated with personality characteristics measured as early as 5 months. A stress-diathesis model may best account for the observed pattern of predictive factors. Citation: Simard V; Nielsen TA; Tremblay RE; Boivin M; Montplaisir JY. Longitudinal study of bad dreams in preschool-aged children: prevalence, demographic correlates, risk and protective factors. SLEEP 2008;31(1):62-70. PMID:18220079

Associations between residential traffic noise exposure and smoking habits and alcohol consumption-A population-based study.

PubMed

Roswall, Nina; Christensen, Jeppe Schultz; Bidstrup, Pernille Envold; Raaschou-Nielsen, Ole; Jensen, Steen Solvang; Tjønneland, Anne; Sørensen, Mette

2018-05-01

Traffic noise stresses and disturbs sleep. It has been associated with various diseases, and has recently also been associated with lifestyle. Hence, the association between traffic noise and disease could partly operate via a pathway of lifestyle habits, including smoking and alcohol intake. We investigated associations between modelled residential traffic noise and smoking habits and alcohol consumption. In a cohort of 57,053 participants, we performed cross-sectional analyses using data from a baseline questionnaire (1993-97), and longitudinal analyses of change between baseline and follow-up (2000-02). Smoking status (never, former, current) and intensity (tobacco, g/day) and alcohol consumption (g/day) was self-reported at baseline and follow-up. Address history from 1987-2002 for all participants were found in national registries, and road traffic and railway noise was modelled 1 and 5 years before enrolment, and from baseline to follow-up. Analyses were performed using logistic and linear regression, and adjusted for demographics, socioeconomic variables, leisure-time sports, and noise from the opposite source (road/railway). Road traffic noise exposure 5 years before baseline was positively associated with alcohol consumption (adjusted difference per 10 dB: 1.38 g/day, 95% confidence interval (CI): 1.10-1.65), smoking intensity (adjusted difference per 10 dB: 0.40 g/day, 95% CI: 0.19-0.61), and odds for being a current vs. never/former smoker at baseline (odds ratio (OR): 1.14; 95% CI: 1.10-1.17). In longitudinal analyses, we found no association between road traffic noise and change in smoking and alcohol habits. Railway noise was not associated with smoking habits and alcohol consumption, neither in cross-sectional nor in longitudinal analyses. The study suggests that long-term exposure to residential road traffic is associated with smoking habits and alcohol consumption, albeit only in cross-sectional, but not in longitudinal analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Direct and maternal genetic effects for preweaning growth in Retinta cattle estimated by a longitudinal approach throughout the calving trajectory of the cow.

PubMed

Morales, R; Menéndez-Buxadera, A; Avilés, C; Molina, A

2013-12-01

The direct and maternal genetic effects were estimated for the preweaning growth of Retinta calves with a multitrait model across parities, using a longitudinal approach with random regression models (RRM). The 120 (P120) and 180 days (P180) weights (5972 calves) were considered as different traits in each calving. The heritability of direct effect across parities was on average 0.37 for P120 and 0.58 for P180, slightly higher than the estimates by univariate (0.30 and 0.56) and bivariate models (0.30 and 0.51, respectively). The heritability for maternal effects was 0.16 for P120 and 0.26 for P180 and very similar by uni- (0.16 and 0.23) and multivariate model (0.16 and 0.22, respectively). The correlation between direct and maternal effects by RRM showed a pronounced antagonism -0.64 for P120 and -0.78 for P180), likewise uni- (-0.62 and -0.72) and multivariate case (-0.64 and -0.74, respectively). The preweaning weights should be considered as different traits across parities, because the genetic correlations were different from unity. The RRM also allowed us to estimate all the parameters throughout the calving trajectory of the cow. The use of multiple traits RRM across parities can provide very useful information for the breeding programmes. © 2013 Blackwell Verlag GmbH.

Hypersonic Wind Tunnel Calibration Using the Modern Design of Experiments

NASA Technical Reports Server (NTRS)

Rhode, Matthew N.; DeLoach, Richard

2005-01-01

A calibration of a hypersonic wind tunnel has been conducted using formal experiment design techniques and response surface modeling. Data from a compact, highly efficient experiment was used to create a regression model of the pitot pressure as a function of the facility operating conditions as well as the longitudinal location within the test section. The new calibration utilized far fewer design points than prior experiments, but covered a wider range of the facility s operating envelope while revealing interactions between factors not captured in previous calibrations. A series of points chosen randomly within the design space was used to verify the accuracy of the response model. The development of the experiment design is discussed along with tactics used in the execution of the experiment to defend against systematic variation in the results. Trends in the data are illustrated, and comparisons are made to earlier findings.

Health-related quality of life measured by the SF12 in working populations: associations with psychosocial work characteristics.

PubMed

Kudielka, Brigitte M; Hanebuth, Dirk; von Känel, Roland; Gander, Marie-Louise; Grande, Gesine; Fischer, Joachim E

2005-10-01

This study investigated the contribution of psychosocial work characteristics (decision latitude, job demand, social support at work, and effort-reward imbalance) to health-related quality of life. Data were derived from 2 aircraft manufacturing plants (N=1,855) at the start of a longitudinal study. Regression analysis showed that work characteristics (1st model) explained 19% of the variance in the mental summary score of the Short Form-12 Health Survey. R2 change for work characteristics decreased to 13%, accounting for demographics, socioeconomic status, body mass index, and medical condition (5th model). Including health behavior and personality factors (full model), R2 change for work characteristics remained significant. Psychosocial work characteristics account for relevant proportions in the subjective perception of mental health beyond a wide array of medical variables and personality factors. Copyright (c) 2005 APA, all rights reserved.

Longitudinal Psychiatric Symptoms in Prodromal Huntington's Disease: A Decade of Data.

PubMed

Epping, Eric A; Kim, Ji-In; Craufurd, David; Brashers-Krug, Thomas M; Anderson, Karen E; McCusker, Elizabeth; Luther, Jolene; Long, Jeffrey D; Paulsen, Jane S

2016-02-01

Psychiatric symptoms are a significant aspect of Huntington's disease, an inherited neurodegenerative illness. The presentation of these symptoms is highly variable, and their course does not fully correlate with motor or cognitive disease progression. The authors sought to better understand the development and longitudinal course of psychiatric manifestations in individuals who carry the Huntington's disease mutation, starting from the prodromal period prior to motor diagnosis. Longitudinal measures for up to 10 years of psychiatric symptoms from the Symptom Checklist-90-Revised were obtained from 1,305 participants (1,007 carrying the Huntington's disease mutation and 298 without [classified as controls]) and 1,235 companions enrolled in the Neurobiological Predictors of Huntington's Disease (PREDICT-HD) study. Participants with the mutation were stratified into three groups according to probability of motor diagnosis within 5 years. Using linear mixed-effects regression models, differences in psychiatric symptoms at baseline and over time between the mutation-positive groups and the controls were compared, as well as between ratings by mutation-positive participants and their companions. Nineteen of 24 psychiatric measures (12 participant ratings and 12 companion ratings) were significantly higher at baseline and showed significant increases longitudinally in the individuals with the Huntington's disease mutation compared with controls. The differences were greatest in comparisons of symptom reports from companions compared with self-reports, especially in participants who were closest to motor diagnosis. The results indicate that psychiatric manifestations develop more often than previously thought in the Huntington's disease prodrome. Symptoms also increase with progression of disease severity. Greater symptom ratings by companions than by mutation-positive participants suggest decreasing awareness in those affected.

A longitudinal test of the predictions of the interpersonal-psychological theory of suicidal behaviour for passive and active suicidal ideation in a large community-based cohort.

PubMed

Batterham, Philip J; Walker, Jennie; Leach, Liana S; Ma, Jennifer; Calear, Alison L; Christensen, Helen

2018-02-01

The Interpersonal-Psychological Theory of Suicide (IPTS) aims to elucidate the key antecedents of suicide deaths. Limited research has tested the IPTS in a community setting, and very little longitudinal research has been conducted. The current study longitudinally tested the predictions of the IPTS for suicidal ideation in a large population-based sample. The PATH through Life study assesses three age cohorts (20's, 40's, 60's) every four years. Two interpersonal factors were estimated at the third wave of assessment: thwarted belongingness (TB) and perceived burdensomeness (PB). The roles of these factors in suicide ideation (active and passive) four years later were estimated using logistic regression models (n = 4545). A one SD increase in TB was associated with increased odds of 37% for passive ideation and 24% for active ideation. For PB, odds were increased 2.5-fold for passive ideation and 2.4-fold for active ideation. A significant negative PB × TB interaction was found for passive but not active ideation. Effects were not consistent by age group or gender. Proxy measures were used to assess the constructs. The extended timeframe and low prevalence of suicidal ideation limited power to find effects within subgroups. Although TB and PB were individually associated with suicidal thoughts, little evidence was found for the key predictions of the IPTS longitudinally. Further investigation of the dynamic interplay between interpersonal factors over time is needed. Copyright © 2017 Elsevier B.V. All rights reserved.

Longitudinal synergies between cortisol reactivity and diurnal testosterone and antisocial behavior in young adolescents.

PubMed

Susman, Elizabeth J; Peckins, Melissa K; Bowes, Jacey L; Dorn, Lorah D

2017-10-01

The aims were to identify the correspondence between simultaneous, longitudinal changes in cortisol reactivity and diurnal testosterone and to test the hypothesis that cortisol reactivity and diurnal testosterone interact so as to influence antisocial behavior. Participants were 135 children and young adolescents assessed at 6-month intervals over 1 year. Upon enrollment girls were age 8, 10, or 12 years (N = 69, M = 10.06 years) and boys were age 9, 11, or 13 years (N = 66, M = 10.94 years). Assessments included Tanner staging by a nurse, cortisol reactivity (Trier Social Stress Test for Children), diurnal testosterone, and interviews and questionnaires. Growth models showed that cortisol reactivity and diurnal testosterone basal levels (intercept) and rate of change (slopes) were not related, suggesting different mechanisms of growth. Longitudinal regression analyses assessed cortisol reactivity and diurnal testosterone longitudinally. The interactions of cortisol reactivity and diurnal testosterone showed that when diurnal testosterone was low, boys with low cortisol reactivity were reported to have more behavior problems (i.e., oppositional defiant disorder symptoms and attention problems) than when testosterone was high. In addition, when diurnal testosterone was high, boys with high or moderate cortisol reactivity were significantly higher on total antisocial behavior, attention behavior problems, and oppositional defiant disorder symptoms than when testosterone was low or moderate. The results were similar but less frequent for girls. These findings advance the science of young adolescence by showing the interaction between preexisting sensitivity to stressors and the normative testosterone changes of puberty and antisocial behavior.

Longitudinal association of obesity, metabolic syndrome and diabetes with risk of elevated aminotransferase levels in a cohort of Mexican health workers.

PubMed

Flores, Yvonne N; Auslander, Allyn; Crespi, Catherine M; Rodriguez, Michael; Zhang, Zuo-Feng; Durazo, Francisco; Salmerón, Jorge

2016-05-01

In Mexico, chronic liver disease have been increasingly found along with the rapidly growing prevalence of obesity, diabetes and metabolic syndrome (MS). We aimed to investigate the longitudinal association between these three factors and risk of elevated alanine aminotransferase (ALT) levels (>40 U/L), a marker for liver damage, in a cohort of Mexican adults. Data were obtained from two separate waves of the Mexican Health Worker Cohort Study: Wave 1 (2004-2006) and Wave 2 (2011-2013). Unconditional logistic regression models were employed to determine the cross-sectional and longitudinal association between these risk factors and elevated ALT levels. The prevalence of elevated ALT was significantly higher among men, individuals aged under 60 years, those who were overweight or obese, diabetic, with MS or heavy/binge drinkers. The longitudinal results indicated that weight gain between waves that resulted in a change in body mass index, along with remaining overweight or obese, were significantly associated with an increased risk of elevated ALT levels. A significantly increased risk of developing elevated ALT was also observed among those who acquired diabetes or MS from Wave 1 to Wave 2. Weight gain and acquiring diabetes or MS are associated with a significant risk of having elevated ALT. These results, within the context of the rapid increase in global obesity rates, call urgently for programs to help to prevent chronic liver disease. © 2016 Chinese Medical Association Shanghai Branch, Chinese Society of Gastroenterology, Renji Hospital Affiliated to Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.

Prevalence and determinants of overweight and obesity in old age in Germany.

PubMed

Hajek, André; Lehnert, Thomas; Ernst, Annette; Lange, Carolin; Wiese, Birgitt; Prokein, Jana; Weyerer, Siegfried; Werle, Jochen; Pentzek, Michael; Fuchs, Angela; Luck, Tobias; Bickel, Horst; Mösch, Edelgard; Heser, Kathrin; Wagner, Michael; Maier, Wolfgang; Scherer, Martin; Riedel-Heller, Steffi G; König, Hans-Helmut

2015-07-14

Mean body weight gradually increases with age. Yet, little data exists on the prevalence of excess weight in populations aged 80 years or older. Moreover, little is known about predictors of overweight and obesity in old age. Thus, the purpose of this study was: To present data on the prevalence of excess weight in old age in Germany, to investigate predictors of excess weight in a cross-sectional approach and to examine factors affecting excess weight in a longitudinal approach. Subjects consisted of 1,882 individuals aged 79 years or older. The course of excess weight was observed over 3 years. Excess weight was defined as follows: Overweight (25 kg/m(2) ≤ BMI < 30 kg/m(2)) and obesity (BMI ≥ 30 kg/m(2)). We used fixed effects regressions to estimate effects of time dependent variables on BMI, and overweight or obesity, respectively. The majority was overweight (40.0%) or obese (13.7%). Cross-sectional regressions revealed that BMI was positively associated with younger age, severe walking impairments and negatively associated with cognitive impairments. Excess weight was positively associated with younger age, elementary education, walking impairments and physical inactivity, while excess weight was negatively associated with cognitive impairment. Longitudinal regressions showed that age and severely impaired walking disabilities reduced BMI. The probability of transitions to excess weight decreased considerably with older age and occurrence of severe walking impairments (overweight). Marked differences between predictors in cross- and longitudinal setting exist, underlining the complex nature of excess weight in old age.

Analyzing longitudinal data with the linear mixed models procedure in SPSS.

PubMed

West, Brady T

2009-09-01

Many applied researchers analyzing longitudinal data share a common misconception: that specialized statistical software is necessary to fit hierarchical linear models (also known as linear mixed models [LMMs], or multilevel models) to longitudinal data sets. Although several specialized statistical software programs of high quality are available that allow researchers to fit these models to longitudinal data sets (e.g., HLM), rapid advances in general purpose statistical software packages have recently enabled analysts to fit these same models when using preferred packages that also enable other more common analyses. One of these general purpose statistical packages is SPSS, which includes a very flexible and powerful procedure for fitting LMMs to longitudinal data sets with continuous outcomes. This article aims to present readers with a practical discussion of how to analyze longitudinal data using the LMMs procedure in the SPSS statistical software package.

Cross-Sectional Analysis of Longitudinal Mediation Processes.

PubMed

O'Laughlin, Kristine D; Martin, Monica J; Ferrer, Emilio

2018-01-01

Statistical mediation analysis can help to identify and explain the mechanisms behind psychological processes. Examining a set of variables for mediation effects is a ubiquitous process in the social sciences literature; however, despite evidence suggesting that cross-sectional data can misrepresent the mediation of longitudinal processes, cross-sectional analyses continue to be used in this manner. Alternative longitudinal mediation models, including those rooted in a structural equation modeling framework (cross-lagged panel, latent growth curve, and latent difference score models) are currently available and may provide a better representation of mediation processes for longitudinal data. The purpose of this paper is twofold: first, we provide a comparison of cross-sectional and longitudinal mediation models; second, we advocate using models to evaluate mediation effects that capture the temporal sequence of the process under study. Two separate empirical examples are presented to illustrate differences in the conclusions drawn from cross-sectional and longitudinal mediation analyses. Findings from these examples yielded substantial differences in interpretations between the cross-sectional and longitudinal mediation models considered here. Based on these observations, researchers should use caution when attempting to use cross-sectional data in place of longitudinal data for mediation analyses.

Gambling disorder-related illegal acts: Regression model of associated factors

PubMed Central

Gorsane, Mohamed Ali; Reynaud, Michel; Vénisse, Jean-Luc; Legauffre, Cindy; Valleur, Marc; Magalon, David; Fatséas, Mélina; Chéreau-Boudet, Isabelle; Guilleux, Alice; JEU Group; Challet-Bouju, Gaëlle; Grall-Bronnec, Marie

2017-01-01

Background and aims Gambling disorder-related illegal acts (GDRIA) are often crucial events for gamblers and/or their entourage. This study was designed to determine the predictive factors of GDRIA. Methods Participants were 372 gamblers reporting at least three DSM-IV-TR (American Psychiatric Association, 2000) criteria. They were assessed on the basis of sociodemographic characteristics, gambling-related characteristics, their personality profile, and psychiatric comorbidities. A multiple logistic regression was performed to identify the relevant predictors of GDRIA and their relative contribution to the prediction of the presence of GDRIA. Results Multivariate analysis revealed a higher South Oaks Gambling Scale score, comorbid addictive disorders, and a lower level of income as GDRIA predictors. Discussion and conclusion An original finding of this study was that the comorbid addictive disorder effect might be mediated by a disinhibiting effect of stimulant substances on GDRIA. Further studies are necessary to replicate these results, especially in a longitudinal design, and to explore specific therapeutic interventions. PMID:28198636

Gambling disorder-related illegal acts: Regression model of associated factors.

PubMed

Gorsane, Mohamed Ali; Reynaud, Michel; Vénisse, Jean-Luc; Legauffre, Cindy; Valleur, Marc; Magalon, David; Fatséas, Mélina; Chéreau-Boudet, Isabelle; Guilleux, Alice; Challet-Bouju, Gaëlle; Grall-Bronnec, Marie

2017-03-01

Background and aims Gambling disorder-related illegal acts (GDRIA) are often crucial events for gamblers and/or their entourage. This study was designed to determine the predictive factors of GDRIA. Methods Participants were 372 gamblers reporting at least three DSM-IV-TR (American Psychiatric Association, 2000) criteria. They were assessed on the basis of sociodemographic characteristics, gambling-related characteristics, their personality profile, and psychiatric comorbidities. A multiple logistic regression was performed to identify the relevant predictors of GDRIA and their relative contribution to the prediction of the presence of GDRIA. Results Multivariate analysis revealed a higher South Oaks Gambling Scale score, comorbid addictive disorders, and a lower level of income as GDRIA predictors. Discussion and conclusion An original finding of this study was that the comorbid addictive disorder effect might be mediated by a disinhibiting effect of stimulant substances on GDRIA. Further studies are necessary to replicate these results, especially in a longitudinal design, and to explore specific therapeutic interventions.

Work stress, sleep deficiency and predicted 10-year cardiometabolic risk in a female patient care worker population

PubMed Central

Jacobsen, Henrik Børsting; Reme, Silje Endresen; Sembajwe, Grace; Hopcia, Karen; Stiles, Tore C.; Sorensen, Glorian; Porter, James H.; Marino, Miguel; Buxton, Orfeu M.

2014-01-01

Objectives The aim of this study was to investigate the longitudinal effect of work-related stress, sleep deficiency and physical activity on 10-year cardiometabolic risk among an all-female worker population. Methods Data on patient care workers (n=99) was collected two years apart. Baseline measures included: job stress, physical activity, night work and sleep deficiency. Biomarkers and objective measurements were used to estimate 10-year cardiometabolic risk at follow-up. Significant associations (P<0.05) from baseline analyses were used to build a multivariable linear regression model. Results The participants were mostly white nurses with a mean age of 41 years. Adjusted linear regression showed that having sleep maintenance problems, a different occupation than nurse, and/or not exercising at recommended levels at baseline increased the 10-year cardiometabolic risk at follow-up. Conclusions In female workers prone to work-related stress and sleep deficiency, maintaining sleep and exercise patterns had a strong impact on modifiable 10-year cardiometabolic risk. PMID:24809311

Work stress, sleep deficiency, and predicted 10-year cardiometabolic risk in a female patient care worker population.

PubMed

Jacobsen, Henrik B; Reme, Silje E; Sembajwe, Grace; Hopcia, Karen; Stiles, Tore C; Sorensen, Glorian; Porter, James H; Marino, Miguel; Buxton, Orfeu M

2014-08-01

The aim of this study was to investigate the longitudinal effect of work-related stress, sleep deficiency, and physical activity on 10-year cardiometabolic risk among an all-female worker population. Data on patient care workers (n=99) was collected 2 years apart. Baseline measures included: job stress, physical activity, night work, and sleep deficiency. Biomarkers and objective measurements were used to estimate 10-year cardiometabolic risk at follow-up. Significant associations (P<0.05) from baseline analyses were used to build a multivariable linear regression model. The participants were mostly white nurses with a mean age of 41 years. Adjusted linear regression showed that having sleep maintenance problems, a different occupation than nurse, and/or not exercising at recommended levels at baseline increased the 10-year cardiometabolic risk at follow-up. In female workers prone to work-related stress and sleep deficiency, maintaining sleep and exercise patterns had a strong impact on modifiable 10-year cardiometabolic risk. © 2014 Wiley Periodicals, Inc.

Fitting parametric random effects models in very large data sets with application to VHA national data

PubMed Central

2012-01-01

Background With the current focus on personalized medicine, patient/subject level inference is often of key interest in translational research. As a result, random effects models (REM) are becoming popular for patient level inference. However, for very large data sets that are characterized by large sample size, it can be difficult to fit REM using commonly available statistical software such as SAS since they require inordinate amounts of computer time and memory allocations beyond what are available preventing model convergence. For example, in a retrospective cohort study of over 800,000 Veterans with type 2 diabetes with longitudinal data over 5 years, fitting REM via generalized linear mixed modeling using currently available standard procedures in SAS (e.g. PROC GLIMMIX) was very difficult and same problems exist in Stata’s gllamm or R’s lme packages. Thus, this study proposes and assesses the performance of a meta regression approach and makes comparison with methods based on sampling of the full data. Data We use both simulated and real data from a national cohort of Veterans with type 2 diabetes (n=890,394) which was created by linking multiple patient and administrative files resulting in a cohort with longitudinal data collected over 5 years. Methods and results The outcome of interest was mean annual HbA1c measured over a 5 years period. Using this outcome, we compared parameter estimates from the proposed random effects meta regression (REMR) with estimates based on simple random sampling and VISN (Veterans Integrated Service Networks) based stratified sampling of the full data. Our results indicate that REMR provides parameter estimates that are less likely to be biased with tighter confidence intervals when the VISN level estimates are homogenous. Conclusion When the interest is to fit REM in repeated measures data with very large sample size, REMR can be used as a good alternative. It leads to reasonable inference for both Gaussian and non-Gaussian responses if parameter estimates are homogeneous across VISNs. PMID:23095325

Evaluation of modeled bacteria loads along an impaired stream reach receiving discharge from a municipal separate storm sewer system in Independence, Mo.

USGS Publications Warehouse

Flickinger, Allison; Christensen, Eric D.

2017-01-01

The Little Blue River in Jackson County, Missouri, was listed as impaired in 2012 due to Escherichia coli (E. coli) from urban runoff and storm sewers. A study was initiated to characterize E. coli concentrations and loads to aid in the development of a total maximum daily load implementation plan. Longitudinal sampling along the stream revealed spatial and temporal variability in E. coli loads. Regression models were developed to better represent E. coli variability in the impaired reach using continuous hydrologic and water-quality parameters as predictive parameters. Daily loads calculated from main-stem samples were significantly higher downstream compared to upstream even though there was no significant difference between the upstream and downstream measured concentrations and no significant conclusions could be drawn from model-estimated loads due to model-associated uncertainty. Increasing sample frequency could decrease the bias and increase the accuracy of the modeled results.

Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields.

PubMed

Yousefi, Siamak; Balasubramanian, Madhusudhanan; Goldbaum, Michael H; Medeiros, Felipe A; Zangwill, Linda M; Weinreb, Robert N; Liebmann, Jeffrey M; Girkin, Christopher A; Bowd, Christopher

2016-05-01

To validate Gaussian mixture-model with expectation maximization (GEM) and variational Bayesian independent component analysis mixture-models (VIM) for detecting glaucomatous progression along visual field (VF) defect patterns (GEM-progression of patterns (POP) and VIM-POP). To compare GEM-POP and VIM-POP with other methods. GEM and VIM models separated cross-sectional abnormal VFs from 859 eyes and normal VFs from 1117 eyes into abnormal and normal clusters. Clusters were decomposed into independent axes. The confidence limit (CL) of stability was established for each axis with a set of 84 stable eyes. Sensitivity for detecting progression was assessed in a sample of 83 eyes with known progressive glaucomatous optic neuropathy (PGON). Eyes were classified as progressed if any defect pattern progressed beyond the CL of stability. Performance of GEM-POP and VIM-POP was compared to point-wise linear regression (PLR), permutation analysis of PLR (PoPLR), and linear regression (LR) of mean deviation (MD), and visual field index (VFI). Sensitivity and specificity for detecting glaucomatous VFs were 89.9% and 93.8%, respectively, for GEM and 93.0% and 97.0%, respectively, for VIM. Receiver operating characteristic (ROC) curve areas for classifying progressed eyes were 0.82 for VIM-POP, 0.86 for GEM-POP, 0.81 for PoPLR, 0.69 for LR of MD, and 0.76 for LR of VFI. GEM-POP was significantly more sensitive to PGON than PoPLR and linear regression of MD and VFI in our sample, while providing localized progression information. Detection of glaucomatous progression can be improved by assessing longitudinal changes in localized patterns of glaucomatous defect identified by unsupervised machine learning.

Determinants of Anemia and Hemoglobin Concentration in Haitian School-Aged Children

PubMed Central

Iannotti, Lora L.; Delnatus, Jacques R.; Odom, Audrey R.; Eaton, Jacob C.; Griggs, Jennifer J.; Brown, Sarah; Wolff, Patricia B.

2015-01-01

Anemia diminishes oxygen transport in the body, resulting in potentially irreversible growth and developmental consequences for children. Limited evidence for determinants of anemia exists for school-aged children. We conducted a cluster randomized controlled trial in Haiti from 2012 to 2013 to test the efficacy of a fortified school snack. Children (N = 1,047) aged 3–13 years were followed longitudinally at three time points for hemoglobin (Hb) concentrations, anthropometry, and bioelectrical impedance measures. Dietary intakes, infectious disease morbidities, and socioeconomic and demographic factors were collected at baseline and endline. Longitudinal regression modeling with generalized least squares and logit models with random effects identified anemia risk factors beyond the intervention effect. At baseline, 70.6% of children were anemic and 2.6% were severely anemic. Stunting increased the odds of developing anemia (adjusted odds ratio [OR]: 1.48, 95% confidence interval [CI]: 1.05–2.08) and severe anemia (adjusted OR: 2.47, 95% CI: 1.30–4.71). Parent-reported vitamin A supplementation and deworming were positively associated with Hb concentrations, whereas fever and poultry ownership showed a negative relationship with Hb concentration and increased odds of severe anemia, respectively. Further research should explore the full spectrum of anemia etiologies in school children, including genetic causes. PMID:26350448

Life satisfaction and bone mineral density among postmenopausal women: cross-sectional and longitudinal associations.

PubMed

Rauma, Päivi H; Koivumaa-Honkanen, Heli; Williams, Lana J; Tuppurainen, Marjo T; Kröger, Heikki P; Honkanen, Risto J

2014-01-01

The purpose of this study was to determine whether and how global life satisfaction is associated with bone mineral density (BMD) and bone loss. A total of 2167 women from a cohort of Finnish women born in 1932 to 1941 were included in the cross-sectional and 1147 women in the 10-year longitudinal part of the present study. Participants responded to a postal enquiry and underwent femoral BMD densitometry in 1999 (baseline) and 2009 (follow-up). During the follow-up, their life satisfaction was repeatedly measured using a four-item scale. Self-reported data on health, life-style, and medication were used to adjust the multivariate linear regression models. Mean (standard deviation) femoral BMD decreased over the 10-year follow-up from 880 (125) to 846 (122) mg/cm. In the multivariate model, life satisfaction (p = .028) and its improvement (p = .001) predicted reduced bone loss, whereas hospitalization due to depression predicted increased bone loss (B = -0.523 annual % change, standard error = 0.212, p = .014). These effects were independent of each other. Easily assessed global life satisfaction should be taken into account when effects of aging and prevention of osteoporosis as well as health promotion in postmenopausal women are considered.

Do occupation and work conditions really matter? A longitudinal analysis of psychological distress experiences among Canadian workers.

PubMed

Marchand, Alain; Demers, Andrée; Durand, Pierre

2005-07-01

This study analyses the relationship between occupation, work conditions and the experience of psychological distress within a model encompassing the stress promoted by constraints-resources embedded in macrosocial structures (occupational structure), structures of daily life (workplace, family, social networks outside the workplace) and agent personality (demography, physical health, psychological traits, life habits, stressful childhood events). Longitudinal data were derived from Statistics Canada's National Population Health Survey and comprised 6,359 workers nested in 471 occupations, followed four times between 1994-1995 and 2000-2001. Discrete time survival multilevel regressions were conducted on first and repeated episodes of psychological distress. Results showed that 42.9 per cent of workers had reported one episode of psychological distress and 18.7 per cent had done so more than once. Data supported the model and challenged the results of previous studies. The individual's position in the occupational structure plays a limited role when the structures of daily life and agent personality are accounted for. In the workplace, job insecurity and social support are important determinants, but greater decision authority increases the risk of psychological distress. Workplace constraints-resources are not moderated either by the other structures of daily life or by agent personality.

Parenting and adolescents’ psychological adjustment: Longitudinal moderation by adolescents’ genetic sensitivity

PubMed Central

Stocker, Clare M.; Masarik, April S.; Widaman, Keith F.; Reeb, Ben T.; Boardman, Jason D.; Smolen, Andrew; Neppl, Tricia K.; Conger, Katherine J.

2017-01-01

We examined whether adolescents’ genetic sensitivity, measured by a polygenic index score, moderated the longitudinal associations between parenting and adolescents’ internalizing and externalizing problems. The sample included 323 mothers, fathers, and adolescents (177 female, 146 male; Time 1 [T1] average age = 12.61 [SD = 0.54] years, Time 2 [T2] average age = 13.59 [SD = 0.59] years). Parents’ warmth and hostility were rated by trained, independent observers using videotapes of family discussions. Adolescents reported their symptoms of anxiety, depressed mood, and hostility at T1 and T2. Results from autoregressive linear regression models showed that adolescents’ genetic sensitivity moderated associations between observations of mothers’ T1 parenting and adolescents’ T2 symptoms of depression, anxiety, and hostility. For fathers, the same pattern was found for adolescents’ anxiety and hostility, but not for depressed mood. Compared to adolescents with low genetic sensitivity, adolescents with high genetic sensitivity had worse adjustment outcomes when parenting was low on warmth and high on hostility. When parenting was characterized by high warmth and low hostility, adolescents with high genetic sensitivity had better adjustment outcomes than their counterparts with low genetic sensitivity. Results support the differential susceptibility model and highlight the complex ways that genes and environment interact to influence development. PMID:28027713

Metabolic syndrome and mammographic density: The Study of Women’s Health Across the Nation (SWAN)

PubMed Central

Conroy, Shannon M.; Butler, Lesley M.; Harvey, Danielle; Gold, Ellen B.; Sternfeld, Barbara; Greendale, Gail A.; Habel, Laurel A.

2013-01-01

The metabolic syndrome (MetS) is associated with an increase in breast cancer risk. In this study, we evaluated whether the MetS was associated with an increase in percent mammographic density (MD), a breast cancer risk factor. We used linear regression and mixed models to examine the cross-sectional and longitudinal associations of the MetS and components of the MetS to percent MD in 790 pre- and early perimenopausal women enrolled in the Study of Women’s Health Across the Nation (SWAN). In cross-sectional analyses adjusted for body mass index (BMI), modest inverse associations were observed between percent MD and the MetS (β = −2.5, SE = 1.9, p = 0.19), abdominal adiposity (β = −4.8, SE = 1.9, p = 0.01) and raised glucose (β = −3.7, SE = 2.4, p = 0.12). In longitudinal models adjusted for covariates including age and BMI, abdominal adiposity (β = 0.34, SE = 0.17, p = 0.05) was significantly positively associated with slower annual decline in percent MD with time. In conclusion, our results do not support the hypothesis that the MetS increases breast cancer risk via a mechanism reflected by an increase in percent MD. PMID:21105041

Longitudinal assessment of treatment effects on pulmonary ventilation using 1H/3He MRI multivariate templates

NASA Astrophysics Data System (ADS)

Tustison, Nicholas J.; Contrella, Benjamin; Altes, Talissa A.; Avants, Brian B.; de Lange, Eduard E.; Mugler, John P.

2013-03-01

The utitlity of pulmonary functional imaging techniques, such as hyperpolarized 3He MRI, has encouraged their inclusion in research studies for longitudinal assessment of disease progression and the study of treatment effects. We present methodology for performing voxelwise statistical analysis of ventilation maps derived from hyper­ polarized 3He MRI which incorporates multivariate template construction using simultaneous acquisition of IH and 3He images. Additional processing steps include intensity normalization, bias correction, 4-D longitudinal segmentation, and generation of expected ventilation maps prior to voxelwise regression analysis. Analysis is demonstrated on a cohort of eight individuals with diagnosed cystic fibrosis (CF) undergoing treatment imaged five times every two weeks with a prescribed treatment schedule.

The spatial and temporal association of neighborhood drug markets and rates of sexually transmitted infections in an urban setting.

PubMed

Jennings, Jacky M; Woods, Stacy E; Curriero, Frank C

2013-09-01

This study examined temporal and spatial relationships between neighborhood drug markets and gonorrhea among census block groups from 2002 to 2005. This was a spatial, longitudinal ecologic study. Poisson regression was used with adjustment in final models for socioeconomic status, residential stability and vacant housing. Increased drug market arrests were significantly associated with a 11% increase gonorrhea (adjusted relative risk (ARR) 1.11; 95% CI 1.05, 1.16). Increased drug market arrests in adjacent neighborhoods were significantly associated with a 27% increase in gonorrhea (ARR 1.27; 95% CI 1.16, 1.36), independent of focal neighborhood drug markets. Increased drug market arrests in the previous year in focal neighborhoods were not associated with gonorrhea (ARR 1.04; 95% CI 0.98, 1.10), adjusting for focal and adjacent drug markets. While the temporal was not supported, our findings support an associative link between drug markets and gonorrhea. The findings suggest that drug markets and their associated sexual networks may extend beyond local neighborhood boundaries indicating the importance of including spatial lags in regression models investigating these associations. Copyright © 2013 Elsevier Ltd. All rights reserved.

The spatial and temporal association of neighborhood drug markets and rates of sexually transmitted infections in an urban setting

PubMed Central

Jennings, Jacky M.; Woods, Stacy E.; Curriero, Frank C.

2013-01-01

This study examined temporal and spatial relationships between neighborhood drug markets and gonorrhea among census block groups from 2002 to 2005. This was a spatial, longitudinal ecologic study. Poisson regression was used with adjustment in final models for socioeconomic status, residential stability and vacant housing. Increased drug market arrests were significantly associated with a 11% increase gonorrhea (Adjusted Relative Risk (ARR) 1.11; 95% CI 1.05, 1.16). Increased drug market arrests in adjacent neighborhoods were significantly associated with a 27% increase in gonorrhea (ARR 1.27; 95% CI 1.16, 1.36), independent of focal neighborhood drug markets. Increased drug market arrests in the previous year in focal neighborhoods were not associated with gonorrhea (ARR 1.04; 95% CI 0.98, 1.10), adjusting for focal and adjacent drug markets. While the temporal was not supported, our findings support an associative link between drug markets and gonorrhea. The findings suggest that drug markets and their associated sexual networks may extend beyond local neighborhood boundaries indicating the importance of including spatial lags in regression models investigating these associations. PMID:23872251

The association between cognitive decline and incident depressive symptoms in a sample of older Puerto Rican adults with diabetes.

PubMed

Bell, Tyler; Dávila, Ana Luisa; Clay, Olivio; Markides, Kyriakos S; Andel, Ross; Crowe, Michael

2017-08-01

Older Puerto Rican adults have particularly high risk of diabetes compared to the general US population. Diabetes is associated with both higher depressive symptoms and cognitive decline, but less is known about the longitudinal relationship between cognitive decline and incident depressive symptoms in those with diabetes. This study investigated the association between cognitive decline and incident depressive symptoms in older Puerto Rican adults with diabetes over a four-year period. Households across Puerto Rico were visited to identify a population-based sample of adults aged 60 years and over for the Puerto Rican Elderly: Health Conditions study (PREHCO); 680 participants with diabetes at baseline and no baseline cognitive impairment were included in analyses. Cognitive decline and depressive symptoms were measured using the Mini-Mental Cabán (MMC) and Geriatric Depression Scale (GDS), respectively. We examined predictors of incident depressive symptoms (GDS ≥ 5 at follow-up but not baseline) and cognitive decline using regression modeling. In a covariate-adjusted logistic regression model, cognitive decline, female gender, and greater diabetes-related complications were each significantly associated with increased odds of incident depressive symptoms (p < 0.05). In a multiple regression model adjusted for covariates, incident depressive symptoms and older age were associated with greater cognitive decline, and higher education was related to less cognitive decline (p < 0.05). Incident depressive symptoms were more common for older Puerto Ricans with diabetes who also experienced cognitive decline. Efforts are needed to optimize diabetes management and monitor for depression and cognitive decline in this population.

Joint modeling of longitudinal data and discrete-time survival outcome.

PubMed

Qiu, Feiyou; Stein, Catherine M; Elston, Robert C

2016-08-01

A predictive joint shared parameter model is proposed for discrete time-to-event and longitudinal data. A discrete survival model with frailty and a generalized linear mixed model for the longitudinal data are joined to predict the probability of events. This joint model focuses on predicting discrete time-to-event outcome, taking advantage of repeated measurements. We show that the probability of an event in a time window can be more precisely predicted by incorporating the longitudinal measurements. The model was investigated by comparison with a two-step model and a discrete-time survival model. Results from both a study on the occurrence of tuberculosis and simulated data show that the joint model is superior to the other models in discrimination ability, especially as the latent variables related to both survival times and the longitudinal measurements depart from 0. © The Author(s) 2013.

Intimate Partner Violence and Depression Symptom Severity among South African Women during Pregnancy and Postpartum: Population-Based Prospective Cohort Study

PubMed Central

Tsai, Alexander C.; Tomlinson, Mark; Comulada, W. Scott; Rotheram-Borus, Mary Jane

2016-01-01

Background Violence against women by intimate partners remains unacceptably common worldwide. The evidence base for the assumed psychological impacts of intimate partner violence (IPV) is derived primarily from studies conducted in high-income countries. A recently published systematic review identified 13 studies linking IPV to incident depression, none of which were conducted in sub-Saharan Africa. To address this gap in the literature, we analyzed longitudinal data collected during the course of a 3-y cluster-randomized trial with the aim of estimating the association between IPV and depression symptom severity. Methods and Findings We conducted a secondary analysis of population-based, longitudinal data collected from 1,238 pregnant women during a 3-y cluster-randomized trial of a home visiting intervention in Cape Town, South Africa. Surveys were conducted at baseline, 6 mo, 18 mo, and 36 mo (85% retention). The primary explanatory variable of interest was exposure to four types of physical IPV in the past year. Depression symptom severity was measured using the Xhosa version of the ten-item Edinburgh Postnatal Depression Scale. In a pooled cross-sectional multivariable regression model adjusting for potentially confounding time-fixed and time-varying covariates, lagged IPV intensity had a statistically significant association with depression symptom severity (regression coefficient b = 1.04; 95% CI, 0.61–1.47), with estimates from a quantile regression model showing greater adverse impacts at the upper end of the conditional depression distribution. Fitting a fixed effects regression model accounting for all time-invariant confounding (e.g., history of childhood sexual abuse) yielded similar findings (b = 1.54; 95% CI, 1.13–1.96). The magnitudes of the coefficients indicated that a one–standard-deviation increase in IPV intensity was associated with a 12.3% relative increase in depression symptom severity over the same time period. The most important limitations of our study include exposure assessment that lacked measurement of sexual violence, which could have caused us to underestimate the severity of exposure; the extended latency period in the lagged analysis, which could have caused us to underestimate the strength of the association; and outcome assessment that was limited to the use of a screening instrument for depression symptom severity. Conclusions In this secondary analysis of data from a population-based, 3-y cluster-randomized controlled trial, IPV had a statistically significant association with depression symptom severity. The estimated associations were relatively large in magnitude, consistent with findings from high-income countries, and robust to potential confounding by time-invariant factors. Intensive health sector responses to reduce IPV and improve women’s mental health should be explored. PMID:26784110

The longitudinal effects of neighbourhood social and material deprivation change on psychological distress in urban, community-dwelling Canadian adults.

PubMed

Blair, A; Gariépy, G; Schmitz, N

2015-07-01

The purpose of this study was to assess how longitudinal changes in neighbourhood material and social deprivation affect distress outcomes in adult Canadians. This study used a prospective cohort approach. We paired data from 2745 urban participants of Canada's National Population Health Survey-who completed the Kessler 6-Item psychological distress screening tool at baseline and follow-up-with neighbourhood social and material deprivation data from the census-based Pampalon Deprivation Index. Data were paired using participants' postal code. We conducted multiple linear regression models, which were stratified by baseline deprivation level and controlled for key confounders. Most participants lived in neighbourhoods that did not change drastically in social or material deprivation level during the six years between baseline and follow-up. We found that a worsening of material settings was significantly associated with worsening distress scores at follow-up. This finding is discussed in the context of existing literature, and made relevant for urban health research and policy. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Longitudinal Associations Among Bullying, Homophobic Teasing, and Sexual Violence Perpetration Among Middle School Students.

PubMed

Espelage, Dorothy L; Basile, Kathleen C; De La Rue, Lisa; Hamburger, Merle E

2015-09-01

Bullying perpetration and sexual harassment perpetration among adolescents are major public health issues. However, few studies have addressed the empirical link between being a perpetrator of bullying and subsequent sexual harassment perpetration among early adolescents in the literature. Homophobic teasing has been shown to be common among middle school youth and was tested as a moderator of the link between bullying and sexual harassment perpetration in this 2-year longitudinal study. More specifically, the present study tests the Bully-Sexual Violence Pathway theory, which posits that adolescent bullies who also participate in homophobic name-calling toward peers are more likely to perpetrate sexual harassment over time. Findings from logistical regression analyses (n = 979, 5th-7th graders) reveal an association between bullying in early middle school and sexual harassment in later middle school, and results support the Bully-Sexual Violence Pathway model, with homophobic teasing as a moderator, for boys only. Results suggest that to prevent bully perpetration and its later association with sexual harassment perpetration, prevention programs should address the use of homophobic epithets. © The Author(s) 2014.

A bidirectional relationship between physical activity and executive function in older adults

PubMed Central

Daly, Michael; McMinn, David; Allan, Julia L.

2015-01-01

Physically active lifestyles contribute to better executive function. However, it is unclear whether high levels of executive function lead people to be more active. This study uses a large sample and multi-wave data to identify whether a reciprocal association exists between physical activity and executive function. Participants were 4555 older adults tracked across four waves of the English Longitudinal Study of Aging. In each wave executive function was assessed using a verbal fluency test and a letter cancelation task and participants reported their physical activity levels. Fixed effects regressions showed that changes in executive function corresponded with changes in physical activity. In longitudinal multilevel models low levels of physical activity led to subsequent declines in executive function. Importantly, poor executive function predicted reductions in physical activity over time. This association was found to be over 50% larger in magnitude than the contribution of physical activity to changes in executive function. This is the first study to identify evidence for a robust bidirectional link between executive function and physical activity in a large sample of older adults tracked over time. PMID:25628552

Longitudinal Differences in Spirituality and Religiousness between Men and Women in Treatment for Alcohol Use Disorders

PubMed Central

Krentzman, Amy R.

2016-01-01

This study compares men and women with alcohol use disorders on levels and trajectories of spirituality and religiousness over 30 months while controlling for critical covariates. Men (n=92) and women (n=65) entering abstinence-based treatment were assessed for drinking behavior, spirituality, and psychosocial variables in a longitudinal panel study. Multiple regression tested for baseline differences and multi-level models tested for differences from baseline to 6 months (early recovery) and from 6 to 30 months (later recovery) in seven dimensions of spirituality/religiousness. Between baseline and 6 months, women had higher scores than men for forgiveness of others and lower scores than men for negative religious coping. Between 6 and 30 months, the acceleration of positive change in self forgiveness was significantly greater for women than men. Differences in negative religious coping and forgiveness might relate to differences in shame and guilt and their resolution by gender. Future research should examine whether gender differences in spirituality serve as an asset to women as they pursue addiction recovery. PMID:29250216

Longitudinal Effects of Activities, Social Environment, and Psychotropic Medication Use on Behavioral Symptoms of Individuals With Alzheimer's Disease in Nursing Homes.

PubMed

Inventor, Ben R; Farran, Carol J; Paun, Olimpia; Cothran, Fawn; Rajan, Kumar; Swantek, Sandra S; McCann, Judith J

2018-05-08

A secondary data analysis of 25,560 minutes of structured clinical observations from a longitudinal study examined the impact of time-varying background factors, social environment, and psychotropic medication use on behavioral symptoms of nursing home residents with Alzheimer's disease (AD). Data were collected at baseline (N = 177), 12 months (N = 138), and 24 months (N = 111). Mixed-effects regression modeling showed that at 24 months: (a) higher cognitive and physical function and having a private bedroom/bathroom had the most positive influence on resident positive behaviors; (b) use of antipsychotic medications and solitary activities had the most negative influence on resident positive behaviors; (c) higher cognitive function significantly decreased negative behaviors; and (d) care-related activities and total number of psychotropic medications significantly increased negative behaviors. The current study describes risk factors for behavioral disturbances and the impact of activities, social environment, and psychotropic medications on behavioral outcomes in nursing home residents with AD. [Journal of Psychosocial Nursing and Mental Health Services, xx(x), xx-xx.]. Copyright 2018, SLACK Incorporated.

A longitudinal ecological study of the influences of political, economic, and health services characteristics on under-five mortality in less-developed countries.

PubMed

Chuang, Ying-Chih; Sung, Pei-Wei; Chao, Hsing Jasmine; Bai, Chyi-Huey; Chang, Chia-Jung

2013-09-01

This study used a longitudinal dataset and lagged dependent-variable panel regression models to examine whether political and economic characteristics directly predict under-5-year mortality rates (U5MR), and moderate the effects of health services and environment on U5MR. We used a sample of 46 less-developed countries from 1980 to 2009. Our results showed that the effects of political and economic characteristics on U5MR varied by non-sub-Saharan and sub-Saharan countries. After controlling for baseline U5MR and other socioeconomic variables, while foreign investment and health services were negatively associated U5MR, democracy was positively associated with U5MR in nonsub-Saharan countries. In contrast, debt was positively associated with and democracy and foreign investment were negatively associated with U5MR in sub-Saharan countries. The interaction analyses indicated that for sub-Saharan countries, the effects of health services on U5MR only existed for countries with low foreign investment. Copyright © 2013 Elsevier Ltd. All rights reserved.

Growth in stature in fragile X families: A mixed longitudinal study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loesch, D.Z.; Huggins, R.M.; Hoang, N.H.

1995-09-11

The effect of fragile X on growth in stature was estimated in individuals aged 5-20 years from 50 fragile X families. The multivariate normal model for pedigree analysis was applied to the mixed longitudinal data, which varied with regard to intervals between the measurements and their number in individual subjects, totalling 349 measurement data points from fragile X families, and 292 data points from unrelated normal subjects. The results of genetic and regression analysis showed that, in fragile X boys and girls, total pubertal height gain is impaired, whereas the rate of growth during the preadolescent period is increased, comparedmore » with the growth rate of nonfragile X subjects. Moreover, the growth parameters in fragile X males were found to be correlated with the size of CGG trinucleotide expansion. The hypothesis of premature activation of the hypothalamo-pituitary gonadal axis is postulated as the cause of growth impairment in fragile X boys and girls, which should be verified by data on the timing of pubertal stages, hormone levels, and bone maturation. 33 refs., 2 figs., 3 tabs.« less

Longitudinal Associations Among Bullying, Homophobic Teasing, and Sexual Violence Perpetration Among Middle School Students

PubMed Central

Espelage, Dorothy L.; Basile, Kathleen C.; De La Rue, Lisa; Hamburger, Merle E.

2015-01-01

Bullying perpetration and sexual harassment perpetration among adolescents are major public health issues. However, few studies have addressed the empirical link between being a perpetrator of bullying and subsequent sexual harassment perpetration among early adolescents in the literature. Homophobic teasing has been shown to be common among middle school youth and was tested as a moderator of the link between bullying and sexual harassment perpetration in this 2-year longitudinal study. More specifically, the present study tests the Bully–Sexual Violence Pathway theory, which posits that adolescent bullies who also participate in homophobic name-calling toward peers are more likely to perpetrate sexual harassment over time. Findings from logistical regression analyses (n = 979, 5th–7th graders) reveal an association between bullying in early middle school and sexual harassment in later middle school, and results support the Bully–Sexual Violence Pathway model, with homophobic teasing as a moderator, for boys only. Results suggest that to prevent bully perpetration and its later association with sexual harassment perpetration, prevention programs should address the use of homophobic epithets. PMID:25315484

Longitudinal Differences in Spirituality and Religiousness between Men and Women in Treatment for Alcohol Use Disorders.

PubMed

Krentzman, Amy R

2017-01-01

This study compares men and women with alcohol use disorders on levels and trajectories of spirituality and religiousness over 30 months while controlling for critical covariates. Men (n=92) and women (n=65) entering abstinence-based treatment were assessed for drinking behavior, spirituality, and psychosocial variables in a longitudinal panel study. Multiple regression tested for baseline differences and multi-level models tested for differences from baseline to 6 months (early recovery) and from 6 to 30 months (later recovery) in seven dimensions of spirituality/religiousness. Between baseline and 6 months, women had higher scores than men for forgiveness of others and lower scores than men for negative religious coping. Between 6 and 30 months, the acceleration of positive change in self forgiveness was significantly greater for women than men. Differences in negative religious coping and forgiveness might relate to differences in shame and guilt and their resolution by gender. Future research should examine whether gender differences in spirituality serve as an asset to women as they pursue addiction recovery.

Longitudinal predictive ability of mapping models: examining post-intervention EQ-5D utilities derived from baseline MHAQ data in rheumatoid arthritis patients.

PubMed

Kontodimopoulos, Nick; Bozios, Panagiotis; Yfantopoulos, John; Niakas, Dimitris

2013-04-01

The purpose of this methodological study was to to provide insight into the under-addressed issue of the longitudinal predictive ability of mapping models. Post-intervention predicted and reported utilities were compared, and the effect of disease severity on the observed differences was examined. A cohort of 120 rheumatoid arthritis (RA) patients (60.0% female, mean age 59.0) embarking on therapy with biological agents completed the Modified Health Assessment Questionnaire (MHAQ) and the EQ-5D at baseline, and at 3, 6 and 12 months post-intervention. OLS regression produced a mapping equation to estimate post-intervention EQ-5D utilities from baseline MHAQ data. Predicted and reported utilities were compared with t test, and the prediction error was modeled, using fixed effects, in terms of covariates such as age, gender, time, disease duration, treatment, RF, DAS28 score, predicted and reported EQ-5D. The OLS model (RMSE = 0.207, R(2) = 45.2%) consistently underestimated future utilities, with a mean prediction error of 6.5%. Mean absolute differences between reported and predicted EQ-5D utilities at 3, 6 and 12 months exceeded the typically reported MID of the EQ-5D (0.03). According to the fixed-effects model, time, lower predicted EQ-5D and higher DAS28 scores had a significant impact on prediction errors, which appeared increasingly negative for lower reported EQ-5D scores, i.e., predicted utilities tended to be lower than reported ones in more severe health states. This study builds upon existing research having demonstrated the potential usefulness of mapping disease-specific instruments onto utility measures. The specific issue of longitudinal validity is addressed, as mapping models derived from baseline patients need to be validated on post-therapy samples. The underestimation of post-treatment utilities in the present study, at least in more severe patients, warrants further research before it is prudent to conduct cost-utility analyses in the context of RA by means of the MHAQ alone.

Bayesian analysis of longitudinal dyadic data with informative missing data using a dyadic shared-parameter model.

PubMed

Ahn, Jaeil; Morita, Satoshi; Wang, Wenyi; Yuan, Ying

2017-01-01

Analyzing longitudinal dyadic data is a challenging task due to the complicated correlations from repeated measurements and within-dyad interdependence, as well as potentially informative (or non-ignorable) missing data. We propose a dyadic shared-parameter model to analyze longitudinal dyadic data with ordinal outcomes and informative intermittent missing data and dropouts. We model the longitudinal measurement process using a proportional odds model, which accommodates the within-dyad interdependence using the concept of the actor-partner interdependence effects, as well as dyad-specific random effects. We model informative dropouts and intermittent missing data using a transition model, which shares the same set of random effects as the longitudinal measurement model. We evaluate the performance of the proposed method through extensive simulation studies. As our approach relies on some untestable assumptions on the missing data mechanism, we perform sensitivity analyses to evaluate how the analysis results change when the missing data mechanism is misspecified. We demonstrate our method using a longitudinal dyadic study of metastatic breast cancer.

Longitudinal Control for Mengshi Autonomous Vehicle via Cloud Model

NASA Astrophysics Data System (ADS)

Gao, H. B.; Zhang, X. Y.; Li, D. Y.; Liu, Y. C.

2018-03-01

Dynamic robustness and stability control is a requirement for self-driving of autonomous vehicle. Longitudinal control method of autonomous is a key technique which has drawn the attention of industry and academe. In this paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle. An experiments is applied to test the implementation of the longitudinal control algorithm. Empirical results show that if the longitudinal control algorithm based Gauss cloud model are applied to calculate the acceleration, and the vehicles drive at different speeds, a stable longitudinal control effect is achieved.

Bayesian Covariate Selection in Mixed-Effects Models For Longitudinal Shape Analysis

PubMed Central

Muralidharan, Prasanna; Fishbaugh, James; Kim, Eun Young; Johnson, Hans J.; Paulsen, Jane S.; Gerig, Guido; Fletcher, P. Thomas

2016-01-01

The goal of longitudinal shape analysis is to understand how anatomical shape changes over time, in response to biological processes, including growth, aging, or disease. In many imaging studies, it is also critical to understand how these shape changes are affected by other factors, such as sex, disease diagnosis, IQ, etc. Current approaches to longitudinal shape analysis have focused on modeling age-related shape changes, but have not included the ability to handle covariates. In this paper, we present a novel Bayesian mixed-effects shape model that incorporates simultaneous relationships between longitudinal shape data and multiple predictors or covariates to the model. Moreover, we place an Automatic Relevance Determination (ARD) prior on the parameters, that lets us automatically select which covariates are most relevant to the model based on observed data. We evaluate our proposed model and inference procedure on a longitudinal study of Huntington's disease from PREDICT-HD. We first show the utility of the ARD prior for model selection in a univariate modeling of striatal volume, and next we apply the full high-dimensional longitudinal shape model to putamen shapes. PMID:28090246

Functional data analysis for dynamical system identification of behavioral processes.

PubMed

Trail, Jessica B; Collins, Linda M; Rivera, Daniel E; Li, Runze; Piper, Megan E; Baker, Timothy B

2014-06-01

Efficient new technology has made it straightforward for behavioral scientists to collect anywhere from several dozen to several thousand dense, repeated measurements on one or more time-varying variables. These intensive longitudinal data (ILD) are ideal for examining complex change over time but present new challenges that illustrate the need for more advanced analytic methods. For example, in ILD the temporal spacing of observations may be irregular, and individuals may be sampled at different times. Also, it is important to assess both how the outcome changes over time and the variation between participants' time-varying processes to make inferences about a particular intervention's effectiveness within the population of interest. The methods presented in this article integrate 2 innovative ILD analytic techniques: functional data analysis and dynamical systems modeling. An empirical application is presented using data from a smoking cessation clinical trial. Study participants provided 42 daily assessments of pre-quit and post-quit withdrawal symptoms. Regression splines were used to approximate smooth functions of craving and negative affect and to estimate the variables' derivatives for each participant. We then modeled the dynamics of nicotine craving using standard input-output dynamical systems models. These models provide a more detailed characterization of the post-quit craving process than do traditional longitudinal models, including information regarding the type, magnitude, and speed of the response to an input. The results, in conjunction with standard engineering control theory techniques, could potentially be used by tobacco researchers to develop a more effective smoking intervention. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Contrasting olfaction, vision, and audition as predictors of cognitive change and impairment in non-demented older adults.

PubMed

MacDonald, Stuart W S; Keller, Connor J C; Brewster, Paul W H; Dixon, Roger A

2018-05-01

This study examines the relative utility of a particular class of noninvasive functional biomarkers-sensory functions-for detecting those at risk of cognitive decline and impairment. Three central research objectives were examined including whether (a) olfactory function, vision, and audition exhibited significant longitudinal declines in nondemented older adults; (b) multiwave change for these sensory function indicators predicted risk of mild cognitive impairment (MCI); and (c) change within persons for each sensory measure shared dynamic time-varying associations with within-person change in cognitive functioning. A longitudinal sample (n = 408) from the Victoria Longitudinal Study was assembled. Three cognitive status subgroups were identified: not impaired cognitively, single-assessment MCI, and multiple-assessment MCI. We tested independent predictive associations, contrasting change in sensory function as predictors of cognitive decline and impairment, utilizing both linear mixed models and logistic regression analysis. Olfaction and, to a lesser extent, vision were identified as the most robust predictors of cognitive status and decline; audition showed little predictive influence. These findings underscore the potential utility of deficits in olfactory function, in particular, as an early marker of age- and pathology-related cognitive decline. Functional biomarkers may represent potential candidates for use in the early stages of a multistep screening approach for detecting those at risk of cognitive impairment, as well as for targeted intervention. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Longitudinal body composition of children born to mothers with normal weight, overweight, and obesity.

PubMed

Andres, Aline; Hull, Holly R; Shankar, Kartik; Casey, Patrick H; Cleves, Mario A; Badger, Thomas M

2015-06-01

The longitudinal trajectories of body composition of children born to mothers with normal weight, overweight, and obesity have not been evaluated using precise body composition methods. This study investigated the relationship between maternal prepregnancy BMI and offspring body composition trajectories during the first 6 years of life. Healthy infants (N = 325) were assessed longitudinally (at ages 0.25, 0.5, 0.75, 1, 2, 3, 4, 5, and 6 years) using dual-energy X-ray absorptiometry. Mixed-effects regression for repeated measures was used to model each continuous outcome as a function of maternal BMI and covariates (race, gestational age, birth weight, and mode of infant feeding). Maternal obesity differentially impacted body fat, but not bone mineral content or density, of girls and boys. Boys born to mothers with obesity have higher body fat from ages 2-6 years compared to boys born to normal-weight and overweight mothers (P < 0.05), whereas body composition of girls born to mothers with obesity was not different across groups during the first 6 years of life (P > 0.05). This clinical observational study demonstrates a sexual dimorphism in offspring body composition until age 6 years based on maternal BMI, with a greater effect of maternal adiposity seen in boys than in girls. © 2015 The Obesity Society.

The "Nursing Home Compare" measure of urinary/fecal incontinence: cross-sectional variation, stability over time, and the impact of case mix.

PubMed

Li, Yue; Schnelle, John; Spector, William D; Glance, Laurent G; Mukamel, Dana B

2010-02-01

To assess the impact of facility case mix on cross-sectional variations and short-term stability of the "Nursing Home Compare" incontinence quality measure (QM) and to determine whether multivariate risk adjustment can minimize such impacts. Retrospective analyses of the 2005 national minimum data set (MDS) that included approximately 600,000 long-term care residents in over 10,000 facilities in each quarterly sample. Mixed logistic regression was used to construct the risk-adjusted QM (nonshrinkage estimator). Facility-level ordinary least-squares models and adjusted R(2) were used to estimate the impact of case mix on cross-sectional and short-term longitudinal variations of currently published and risk-adjusted QMs. At least 50 percent of the cross-sectional variation and 25 percent of the short-term longitudinal variation of the published QM are explained by facility case mix. In contrast, the cross-sectional and short-term longitudinal variations of the risk-adjusted QM are much less susceptible to case-mix variations (adjusted R(2)<0.10), even for facilities with more extreme or more unstable outcome. Current "Nursing Home Compare" incontinence QM reflects considerable case-mix variations across facilities and over time, and therefore it may be biased. This issue can be largely addressed by multivariate risk adjustment using risk factors available in the MDS.

Etiology of the stability of reading difficulties: the longitudinal twin study of reading disabilities.

PubMed

Astrom, Raven L; Wadsworth, Sally J; DeFries, John C

2007-06-01

Results obtained from previous longitudinal studies of reading difficulties indicate that reading deficits are generally stable. However, little is known about the etiology of this stability. Thus, the primary objective of this first longitudinal twin study of reading difficulties is to provide an initial assessment of genetic and environmental influences on the stability of reading deficits. Data were analyzed from a sample of 56 twin pairs, 18 identical (monozygotic, MZ) and 38 fraternal (dizygotic, DZ), in which at least one member of each pair was classified as reading-disabled in the Colorado Learning Disabilities Research Center, and on whom follow-up data were available. The twins were tested at two time points (average age of 10.3 years at initial assessment and 16.1 years at follow-up). A composite measure of reading performance (PIAT Reading Recognition, Reading Comprehension and Spelling) was highly stable, with a stability correlation of .84. Data from the initial time point were first subjected to univariate DeFries-Fulker multiple regression analysis and the resulting estimate of the heritability of the group deficit (h2g) was .84 (+/-.26). When the initial and follow-up data were then fitted to a bivariate extension of the basic DF model, bivariate heritability was estimated at .65, indicating that common genetic influences account for approximately 75% of the stability between reading measures at the two time points.

Positive association between sugar consumption and dental decay prevalence independent of oral hygiene in pre-school children: a longitudinal prospective study.

PubMed

Skafida, V; Chambers, S

2017-12-29

Few studies explore how the longitudinal cumulative and combined effects of dietary habits and oral hygiene habits relate to dental decay in very young children. Using longitudinal survey data, logistic regression models were specified to predict dental decay by age 5. Predictor variables included questions on diet and oral hygiene from ages 2 to 5. Compared to mainly eating meals, children who snacked all day but had no real meals had a higher chance of dental decay (odds ratios (OR) = 2.32). There was an incremental association between a decreasing frequency of toothbrushing at age 2 and higher chances of dental decay at age 5 (OR range from 1.39 to 2.17). Among children eating sweets or chocolate more frequently (once/day or more), toothbrushing more often (once/day; twice/day or more) reduced the chance of decay (OR of 2.11-2.26 compared to OR 3.60 for the least frequent brushing group). Compared to mothers in managerial and professional occupations, those who had never worked had children with a much higher chance of decay (OR = 3.47). This study has shown that toothbrushing can only in part attenuate the association between snacking and long term sugar consumption on dental decay outcomes in children under 5. © The Author(s) 2017. Published by Oxford University Press on behalf of Faculty of Public Health.

Adverse Childhood Experiences and Alcohol Consumption in Midlife and Early Old-Age

PubMed Central

Leung, Jessica Pui Kei; Britton, Annie; Bell, Steven

2016-01-01

Aims To examine the individual and cumulative effects of adverse childhood experiences (ACEs) on alcohol consumption in midlife and early old-age, and the role of ACEs in 10-year drinking trajectories across midlife. Methods Data were from the Whitehall II study, a longitudinal British civil service-based cohort study (N = 7870, 69.5% male). Multinomial logistic regression was used to examine the individual and cumulative effects of ACEs on weekly alcohol consumption. Mixed-effect multilevel modelling was used to explore the relationship between ACEs and change in alcohol consumption longitudinally. Results Participants who were exposed to parental arguments/fights in childhood were 1.24 (95% CI 1.06, 1.45) times more likely to drink at hazardous levels in midlife (mean age 56 years) after controlling for covariates and other ACEs. For each additional exposure to an ACE, the risk of hazardous drinking versus moderate drinking was increased by 1.12 (95% CI 1.03, 1.21) after adjusting for sex, age, adult socio-economic status, ethnicity and marital status. No associations between ACEs and increased risk of hazardous drinking in early old-age (mean age 66 years) were found. In longitudinal analyses, ACEs did not significantly influence 10-year drinking trajectories across midlife. Conclusion The effect of exposure to parental arguments on hazardous drinking persists into midlife. PMID:26553290

Tea Consumption Reduces the Incidence of Neurocognitive Disorders: Findings from the Singapore Longitudinal Aging Study.

PubMed

Feng, L; Chong, M-S; Lim, W-S; Gao, Q; Nyunt, M S; Lee, T-S; Collinson, S L; Tsoi, T; Kua, E-H; Ng, T-P

2016-01-01

To examine the relationships between tea consumption habits and incident neurocognitive disorders (NCD) and explore potential effect modification by gender and the apolipoprotein E (APOE) genotype. Population-based longitudinal study. The Singapore Longitudinal Aging Study (SLAS). 957 community-living Chinese elderly who were cognitively intact at baseline. We collected tea consumption information at baseline from 2003 to 2005 and ascertained incident cases of neurocognitive disorders (NCD) from 2006 to 2010. Odds ratio (OR) of association were calculated in logistic regression models that adjusted for potential confounders. A total of 72 incident NCD cases were identified from the cohort. Tea intake was associated with lower risk of incident NCD, independent of other risk factors. Reduced NCD risk was observed for both green tea (OR=0.43) and black/oolong tea (OR=0.53) and appeared to be influenced by the changing of tea consumption habit at follow-up. Using consistent non-tea consumers as the reference, only consistent tea consumers had reduced risk of NCD (OR=0.39). Stratified analyses indicated that tea consumption was associated with reduced risk of NCD among females (OR=0.32) and APOE ε4 carriers (OR=0.14) but not males and non APOE ε4 carriers. Regular tea consumption was associated with lower risk of neurocognitive disorders among Chinese elderly. Gender and genetic factors could possibly modulate this association.

Longitudinal trends in gasoline price and physical activity: The CARDIA study

PubMed Central

Hou, Ningqi; Popkin, Barry M; Jacobs, David R; Song, Yan; Guilkey, David K; He, Ka; Lewis, Cora E.; Gordon-Larsen, Penny

2011-01-01

Objective To investigate longitudinal associations between community-level gasoline price and physical activity (PA). Method In the Coronary Artery Risk Development in Young Adults study, 5,115 black and white participants aged 18–30 at baseline 1985–86 were recruited from four U.S. cities (Birmingham, Chicago, Minneapolis and Oakland) and followed over time. We used data from 3 follow-up exams: 1992–93, 1995–96, and 2000–01, when the participants were located across 48 states. From questionnaire data, a total PA score was summarized in exercise units (EU) based on intensity and frequency of 13 PA categories. Using Geographic Information Systems, participants’ residential locations were linked to county-level inflation-adjusted gasoline price data collected by the Council for Community & Economic Research. We used a random-effect longitudinal regression model to examine associations between time-varying gasoline price and time-varying PA, controlling for age, race, gender, baseline study center, and time-varying education, marital status, household income, county cost of living, county bus fare, census block-group poverty, and urbanicity. Results Holding all control variables constant, a 25-cent increase in inflation-adjusted gasoline price was significantly associated with an increase of 9.9 EU in total PA (95%CI: 0.8–19.1). Conclusion Rising prices of gasoline may be associated with an unintended increase in leisure PA. PMID:21338621

Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

PubMed

Olivera, André Rodrigues; Roesler, Valter; Iochpe, Cirano; Schmidt, Maria Inês; Vigo, Álvaro; Barreto, Sandhi Maria; Duncan, Bruce Bartholow

2017-01-01

Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. Comparison of machine-learning algorithms to develop predictive models using data from ELSA-Brasil. After selecting a subset of 27 candidate variables from the literature, models were built and validated in four sequential steps: (i) parameter tuning with tenfold cross-validation, repeated three times; (ii) automatic variable selection using forward selection, a wrapper strategy with four different machine-learning algorithms and tenfold cross-validation (repeated three times), to evaluate each subset of variables; (iii) error estimation of model parameters with tenfold cross-validation, repeated ten times; and (iv) generalization testing on an independent dataset. The models were created with the following machine-learning algorithms: logistic regression, artificial neural network, naïve Bayes, K-nearest neighbor and random forest. The best models were created using artificial neural networks and logistic regression. -These achieved mean areas under the curve of, respectively, 75.24% and 74.98% in the error estimation step and 74.17% and 74.41% in the generalization testing step. Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.

Longitudinal associations of lifestyle factors and weight status with insulin resistance (HOMA-IR) in preadolescent children: the large prospective cohort study IDEFICS.

PubMed

Peplies, Jenny; Börnhorst, Claudia; Günther, Kathrin; Fraterman, Arno; Russo, Paola; Veidebaum, Toomas; Tornaritis, Michael; De Henauw, Stefaan; Marild, Staffan; Molnar, Dénes; Moreno, Luis A; Ahrens, Wolfgang

2016-09-02

This study investigates prospective associations of anthropometrical and lifestyle indices with insulin resistance (IR) in European children from the IDEFICS cohort. Insulin resistance (IR) is a growing concern in childhood obesity and a central aspect of the metabolic syndrome (MS). It most likely represents the link between obesity and type 2 diabetes. This longitudinal study included 3348 preadolescent children aged 3 to 10.9 years from 8 European countries who were observed from 2007/2008 to 2009/2010. The main outcome measure in the present analysis is HOMA-IR (homeostasis model assessment as a common proxy indicator to quantify IR) at follow-up and in its longitudinal development. Anthropometrical measures and lifestyle indices, including objectively determined physical activity, were considered, among others factors, as determinants of IR. Prospective associations between IR at follow-up and anthropometrical and lifestyle indices were estimated by logistic regression models. Country-specific prevalence rates of IR in the IDEFICS cohort of European children showed a positive trend with weight category. Prospective multivariate analyses showed the strongest positive associations of IR with BMI z-score (OR = 2.6 for unit change from the mean, 95 % CI 2.1-3.1) and z-score of waist circumference (OR = 2.2 for unit change from the mean, 95 % CI 1.9-2.6), which were analysed in separate models, but also for sex (OR = 2.2 for girls vs. boys, 95 % CI 1.5-3.1 up to OR 2.5, 95 % CI 1.8-3.6 depending on the model), audio-visual media time (OR = 1.2 for an additional hour per day, 95 % CI 1.0-1.4 in both models) and an inverse association of objectively determined physical activity (OR = 0.5 for 3(rd) compared to 1(st) quartile, 95 % CI 0.3-0.9 in both models). A longitudinal reduction of HOMA-IR was accompanied with a parallel decline in BMI. This study is, to our knowledge, the first prospective study on IR in a preadolescent children's population. It supports the common hypothesis that overweight and obesity are the main determinants of IR. Our data also indicate that physical inactivity and a sedentary lifestyle are likewise associated with the development of IR, independent of weight status. The promotion of physical activity should thus be considered as an equal option to dietary intervention for the treatment of IR in the paediatric practice.

A longitudinal multilevel CFA-MTMM model for interchangeable and structurally different methods

PubMed Central

Koch, Tobias; Schultze, Martin; Eid, Michael; Geiser, Christian

2014-01-01

One of the key interests in the social sciences is the investigation of change and stability of a given attribute. Although numerous models have been proposed in the past for analyzing longitudinal data including multilevel and/or latent variable modeling approaches, only few modeling approaches have been developed for studying the construct validity in longitudinal multitrait-multimethod (MTMM) measurement designs. The aim of the present study was to extend the spectrum of current longitudinal modeling approaches for MTMM analysis. Specifically, a new longitudinal multilevel CFA-MTMM model for measurement designs with structurally different and interchangeable methods (called Latent-State-Combination-Of-Methods model, LS-COM) is presented. Interchangeable methods are methods that are randomly sampled from a set of equivalent methods (e.g., multiple student ratings for teaching quality), whereas structurally different methods are methods that cannot be easily replaced by one another (e.g., teacher, self-ratings, principle ratings). Results of a simulation study indicate that the parameters and standard errors in the LS-COM model are well recovered even in conditions with only five observations per estimated model parameter. The advantages and limitations of the LS-COM model relative to other longitudinal MTMM modeling approaches are discussed. PMID:24860515

The Multigroup Multilevel Categorical Latent Growth Curve Models

ERIC Educational Resources Information Center

Hung, Lai-Fa

2010-01-01

Longitudinal data describe developmental patterns and enable predictions of individual changes beyond sampled time points. Major methodological issues in longitudinal data include modeling random effects, subject effects, growth curve parameters, and autoregressive residuals. This study embedded the longitudinal model within a multigroup…

Friendships Lost: The Social Consequences of Violent Victimization.

PubMed

Wallace, Lacey N; Ménard, Kim S

2017-01-01

Few studies have examined the impact of violent victimization on friendship networks. This study used two waves of data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine the effects of violent victimization on number peer- and self-reported friendships. Guided by stigma theory (Goffman, 1963), fixed-effect regression models controlling for depression, delinquency, substance use, and school engagement were completed to predict changes in number of friends following victimization. Consistent with the theory, results indicate that experiencing violent victimization (e.g., jumped, stabbed, shot at) was associated with a decrease in number of friends. These effects were magnified for females and for individuals with a greater number of depressive symptoms. These results were consistent even when models were run separately for each individual type of victimization. Treatment and prevention implications are discussed.

Determinants of residential mobility decisions: the role of government services in relation to other factors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Varady, D.P.

This article is one of the first to test for the relative importance of concerns about public services in affecting residential mobility decisions over and beyond normal mobility factors. A secondary aim is to test for the validity of a residential mobility model formulated by Speare and associates. Multiple regression analysis was employed using 1974 to 1977 data from the longitudinal version of the Annual Housing Survey. Concerns about public services did not play a meaningful role in the analysis. This implies that efforts to hold middle-income residents in declining neighborhoods, through improved services, will not succeed. The results supportedmore » the Speare mobility model; housing satisfaction acted as an intermediary variable between background characteristics and mobility behavior. 30 references, 4 figures, 5 tables.« less

Hierarchy of higher-level physical functions: a longitudinal investigation on a nationally representative population of community-dwelling middle-aged and elderly persons.

PubMed

Yeh, Chih-Jung; Wang, Ching-Yi; Tang, Pei-Fang; Lee, Meng-Chih; Lin, Hui-Sheng; Chen, Hui-Ya

2012-01-01

Understanding the hierarchy of higher-level physical functions to infer disability level (mild, moderate or severe) is essential for the precise targeting of preventive interventions and has been examined previously in a cross-sectional study. Based on longitudinal data, this study evaluated the hierarchy of higher-level physical functions. Data from a cohort of 2729 community-dwelling persons aged over 50 with no initial disability were drawn from the "Survey of Health and Living Status of the Elderly in Taiwan" from 1996 through 2007. The three-level hierarchy of eight chosen activities was examined by the median ages to disability onset with survival analyses and by Cox regressions, which examined the effects of sex and age on the development of this hierarchy. The progression of incident disability was as follows: mild level-running, carrying weight, and squatting; moderate level-climbing stairs, walking, and standing; and severe level-grasping and raising arms up. Women and older persons were at greater risk of developing more severe levels of disability. Another Cox regression with one index activity from each hierarchical level revealed similar results. The three-level hierarchy of higher-level physical functions has been validated longitudinally, suggesting rich research and clinical implications.

Emotional exhaustion and cognitive performance in apparently healthy teachers: a longitudinal multi-source study.

PubMed

Feuerhahn, Nicolas; Stamov-Roßnagel, Christian; Wolfram, Maren; Bellingrath, Silja; Kudielka, Brigitte M

2013-10-01

We investigate how emotional exhaustion (EE), the core component of burnout, relates to cognitive performance, job performance and health. Cognitive performance was assessed by self-rated cognitive stress symptoms, self-rated and peer-rated cognitive impairments in everyday tasks and a neuropsychological test of learning and memory (LGT-3); job performance and physical health were gauged by self-reports. Cross-sectional linear regression analyses in a sample of 100 teachers confirm that EE is negatively related to cognitive performance as assessed by self-rating and peer-rating as well as neuropsychological testing (all p < .05). Longitudinal linear regression analyses confirm similar trends (p < .10) for self-rated and peer-rated cognitive performance. Executive control deficits might explain impaired cognitive performance in EE. In longitudinal analyses, EE also significantly predicts physical health. Contrary to our expectations, EE does not affect job performance. When reversed causation is tested, none of the outcome variables at Time 1 predict EE at Time 2. This speaks against cognitive dysfunctioning serving as a vulnerability factor for exhaustion. In sum, results underpin the negative consequences of EE for cognitive performance and health, which are relevant for individuals and organizations alike. In this way, findings might contribute to the understanding of the burnout syndrome. Copyright © 2012 John Wiley & Sons, Ltd.

Investigation of 2‐stage meta‐analysis methods for joint longitudinal and time‐to‐event data through simulation and real data application

PubMed Central

Tudur Smith, Catrin; Gueyffier, François; Kolamunnage‐Dona, Ruwanthi

2017-01-01

Background Joint modelling of longitudinal and time‐to‐event data is often preferred over separate longitudinal or time‐to‐event analyses as it can account for study dropout, error in longitudinally measured covariates, and correlation between longitudinal and time‐to‐event outcomes. The joint modelling literature focuses mainly on the analysis of single studies with no methods currently available for the meta‐analysis of joint model estimates from multiple studies. Methods We propose a 2‐stage method for meta‐analysis of joint model estimates. These methods are applied to the INDANA dataset to combine joint model estimates of systolic blood pressure with time to death, time to myocardial infarction, and time to stroke. Results are compared to meta‐analyses of separate longitudinal or time‐to‐event models. A simulation study is conducted to contrast separate versus joint analyses over a range of scenarios. Results Using the real dataset, similar results were obtained by using the separate and joint analyses. However, the simulation study indicated a benefit of use of joint rather than separate methods in a meta‐analytic setting where association exists between the longitudinal and time‐to‐event outcomes. Conclusions Where evidence of association between longitudinal and time‐to‐event outcomes exists, results from joint models over standalone analyses should be pooled in 2‐stage meta‐analyses. PMID:29250814

Using Marginal Structural Modeling to Estimate the Cumulative Impact of an Unconditional Tax Credit on Self-Rated Health.

PubMed

Pega, Frank; Blakely, Tony; Glymour, M Maria; Carter, Kristie N; Kawachi, Ichiro

2016-02-15

In previous studies, researchers estimated short-term relationships between financial credits and health outcomes using conventional regression analyses, but they did not account for time-varying confounders affected by prior treatment (CAPTs) or the credits' cumulative impacts over time. In this study, we examined the association between total number of years of receiving New Zealand's Family Tax Credit (FTC) and self-rated health (SRH) in 6,900 working-age parents using 7 waves of New Zealand longitudinal data (2002-2009). We conducted conventional linear regression analyses, both unadjusted and adjusted for time-invariant and time-varying confounders measured at baseline, and fitted marginal structural models (MSMs) that more fully adjusted for confounders, including CAPTs. Of all participants, 5.1%-6.8% received the FTC for 1-3 years and 1.8%-3.6% for 4-7 years. In unadjusted and adjusted conventional regression analyses, each additional year of receiving the FTC was associated with 0.033 (95% confidence interval (CI): -0.047, -0.019) and 0.026 (95% CI: -0.041, -0.010) units worse SRH (on a 5-unit scale). In the MSMs, the average causal treatment effect also reflected a small decrease in SRH (unstabilized weights: β = -0.039 unit, 95% CI: -0.058, -0.020; stabilized weights: β = -0.031 unit, 95% CI: -0.050, -0.007). Cumulatively receiving the FTC marginally reduced SRH. Conventional regression analyses and MSMs produced similar estimates, suggesting little bias from CAPTs. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Freedom Solo Versus Trifecta Bioprotheses: Clinical and Hemodynamic Evaluation after Propensity Score Matching.

PubMed

J Cerqueira, Rui; Melo, Renata; Moreira, Soraia; A Saraiva, Francisca; Andrade, Marta; Salgueiro, Elson; Almeida, Jorge; J Amorim, Mário; Pinho, Paulo; Lourenço, André; F Leite-Moreira, Adelino

2017-01-01

To compare stentless Freedom Solo and stented Trifecta aortic bioprostheses regarding hemodynamic profile, left ventricular mass regression, early and late postoperative outcomes and survival. Longitudinal cohort study of consecutive patients undergoing aortic valve replacement (from 2009 to 2016) with either Freedom Solo or Trifecta at one centre. Local databases and national records were queried. Postoperative echocardiography (3-6 months) was obtained for hemodynamic profile (mean transprosthetic gradient and effective orifice area) and left ventricle mass determination. After propensity score matching (21 covariates), Kaplan-Meier analysis and cumulative incidence analysis were performed for survival and combined outcome of structural valve deterioration and endocarditis, respectively. Hemodynamics and left ventricle mass regression were assessed by a mixed- -effects model including propensity score as a covariate. From a total sample of 397 Freedom Solo and 525 Trifecta patients with a median follow-up time of 4.0 (2.2- 6.0) and 2.4 (1.4-3.7) years, respectively, a matched sample of 329 pairs was obtained. Well-balanced matched groups showed no difference in survival (hazard ratio=1.04, 95% confidence interval=0.69-1.56) or cumulative hazards of combined outcome (subhazard ratio=0.54, 95% confidence interval=0.21-1.39). Although Trifecta showed improved hemodynamic profile compared to Freedom Solo, no differences were found in left ventricle mass regression. Trifecta has a slightly improved hemodynamic profile compared to Freedom Solo but this does not translate into differences in the extent of mass regression, postoperative outcomes or survival, which were good and comparable for both bioprostheses. Long-term follow-up is needed for comparisons with older models of bioprostheses.

Interrupted Time Series Versus Statistical Process Control in Quality Improvement Projects.

PubMed

Andersson Hagiwara, Magnus; Andersson Gäre, Boel; Elg, Mattias

2016-01-01

To measure the effect of quality improvement interventions, it is appropriate to use analysis methods that measure data over time. Examples of such methods include statistical process control analysis and interrupted time series with segmented regression analysis. This article compares the use of statistical process control analysis and interrupted time series with segmented regression analysis for evaluating the longitudinal effects of quality improvement interventions, using an example study on an evaluation of a computerized decision support system.

Relationship between long working hours and depression: a 3-year longitudinal study of clerical workers.

PubMed

Amagasa, Takashi; Nakayama, Takeo

2013-08-01

To clarify how long working hours affect the likelihood of current and future depression. Using data from four repeated measurements collected from 218 clerical workers, four models associating work-related factors to the depressive mood scale were established. The final model was constructed after comparing and testing the goodness-of-fit index using structural equation modeling. Multiple logistic regression analysis was also performed. The final model showed the best fit (normed fit index = 0.908; goodness-of-fit index = 0.936; root-mean-square error of approximation = 0.018). Its standardized total effect indicated that long working hours affected depression at the time of evaluation and 1 to 3 years later. The odds ratio for depression risk was 14.7 in employees who were not long-hours overworked according to the initial survey but who were long-hours overworked according to the second survey. Long working hours increase current and future risks of depression.

Longitudinal assessment of the impact of the use of the UK clinical aptitude test for medical student selection.

PubMed

Mathers, Jonathan; Sitch, Alice; Parry, Jayne

2016-10-01

Medical schools are increasingly using novel tools to select applicants. The UK Clinical Aptitude Test (UKCAT) is one such tool and measures mental abilities, attitudes and professional behaviour conducive to being a doctor using constructs likely to be less affected by socio-demographic factors than traditional measures of potential. Universities are free to use UKCAT as they see fit but three broad modalities have been observed: 'borderline', 'factor' and 'threshold'. This paper aims to provide the first longitudinal analyses assessing the impact of the different uses of UKCAT on making offers to applicants with different socio-demographic characteristics. Multilevel regression was used to model the outcome of applications to UK medical schools during the period 2004-2011 (data obtained from UCAS), adjusted for sex, ethnicity, schooling, parental occupation, educational attainment, year of application and UKCAT use (borderline, factor and threshold). The three ways of using the UKCAT did not differ in their impact on making the selection process more equitable, other than a marked reversal for female advantage when applied in a 'threshold' manner. Our attempt to model the longitudinal impact of the use of the UKCAT in its threshold format found again the reversal of female advantage, but did not demonstrate similar statistically significant reductions of the advantages associated with White ethnicity, higher social class and selective schooling. Our findings demonstrate attenuation of the advantage of being female but no changes in admission rates based on White ethnicity, higher social class and selective schooling. In view of this, the utility of the UKCAT as a means to widen access to medical schools among non-White and less advantaged applicants remains unproven. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Reduced diaphyseal strength associated with high intracortical vascular porosity within long bones of children with Osteogenesis Imperfecta

PubMed Central

Jameson, John; Smith, Peter; Harris, Gerald

2015-01-01

Osteogenesis Imperfecta is a genetic disorder resulting in bone fragility. The mechanisms behind this fragility are not well understood. In addition to characteristic bone mass deficiencies, research suggests that bone material properties are compromised in individuals with this disorder. However, little data exists regarding bone properties beyond the microstructural scale in individuals with this disorder. Specimens were obtained from long bone diaphyses of nine children with osteogenesis imperfecta during routine osteotomy procedures. Small rectangular beams, oriented longitudinally and transversely to the diaphyseal axis, were machined from these specimens and elastic modulus, yield strength, and maximum strength were measured in three-point bending. Intracortical vascular porosity, bone volume fraction, osteocyte lacuna density, and volumetric tissue mineral density were determined by synchrotron micro-computed tomography, and relationships among these mechanical properties and structural parameters were explored. Modulus and strength were on average 64–68% lower in the transverse vs. longitudinal beams (P<0.001, linear mixed model). Vascular porosity ranged between 3–42% of total bone volume. Longitudinal properties were associated negatively with porosity (P≤0.006, linear regressions). Mechanical properties, however, were not associated with osteocyte lacuna density or volumetric tissue mineral density (P≥0.167). Bone properties and structural parameters were not associated significantly with donor age (p≥0.225, linear mixed models). This study presents novel data regarding bone material strength in children with osteogenesis imperfecta. Results confirm that these properties are anisotropic. Elevated vascular porosity was observed in most specimens, and this parameter was associated with reduced bone material strength. These results offer insight towards understanding bone fragility and the role of intracortical porosity on the strength of bone tissue in children with osteogenesis imperfecta. PMID:24928496

Association between Cardiovascular Health Score and Carotid Intima-Media Thickness: Cross-Sectional Analysis of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) Baseline Assessment.

PubMed

Santos, Itamar S; Goulart, Alessandra C; Pereira, Alexandre C; Lotufo, Paulo A; Benseñor, Isabela M

2016-12-01

The American Heart Association aims to reduce the burden of cardiovascular disease in this decade by improving seven ideal cardiovascular health (CVH) characteristics in the population. The aim of this study was to quantify the association between the American Heart Association's CVH score and values for carotid intima-media thickness (CIMT) in the Brazilian Longitudinal Study of Adult Health baseline assessment. The Brazilian Longitudinal Study of Adult Health is a multicenter cohort study of civil servants aged 35 to 74 years in Brazil. In this study, the investigators analyzed 9,662 individuals with no previous cardiovascular disease. The distribution of CIMT values (categorized into age-, sex-, and race-specific quartiles) was analyzed according to CVH scores using χ 2 trend tests. Linear and multinomial regression models were built to evaluate the association between CIMT and CVH score. A significant increase was observed in the proportion of individuals within the first and second CIMT quartiles, as well as a decrease within the fourth quartile with higher CVH score strata (P for trend < .001). A 1-point increase in CVH score was associated in adjusted models with a decrease of 0.011 mm in CIMT and an odds ratio of 0.79 (95% CI, 0.77-0.81) of having CIMT in the fourth quartile. However, nearly 16% of individuals with optimal CVH scores had CIMT values in the highest quartile. In this study, significant associations were found between CIMT and CVH score in a large sample of middle-aged adults. However, a high CVH score did not warrant the absence of a significant subclinical atherosclerotic burden. Copyright © 2016 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.

Longitudinal and concurrent links between memory span, anxiety symptoms, and subsequent executive functioning in young children

PubMed Central

Visu-Petra, Laura; Stanciu, Oana; Benga, Oana; Miclea, Mircea; Cheie, Lavinia

2014-01-01

It has been conjectured that basic individual differences in attentional control influence higher-level executive functioning and subsequent academic performance in children. The current study sets out to complement the limited body of research on early precursors of executive functions (EFs). It provides both a cross-sectional, as well as a longitudinal exploration of the relationship between EF and more basic attentional control mechanisms, assessed via children's performance on memory storage tasks, and influenced by individual differences in anxiety. Multiple measures of verbal and visuospatial short-term memory (STM) were administered to children between 3 and 6 years old, alongside a non-verbal measure of intelligence, and a parental report of anxiety symptoms. After 9 months, children were re-tested on the same STM measures, at which time we also administered multiple measures of executive functioning: verbal and visuospatial working memory (WM), inhibition, and shifting. A cross-sectional view of STM development indicated that between 3 and 6 years the trajectory of visuospatial STM and EF underwent a gradual linear improvement. However, between 5 and 6 years progress in verbal STM performance stagnated. Hierarchical regression models revealed that trait anxiety was negatively associated with WM and shifting, while non-verbal intelligence was positively related to WM span. When age, gender, non-verbal intelligence, and anxiety were controlled for, STM (measured at the first assessment) was a very good predictor of overall executive performance. The models were most successful in predicting WM, followed by shifting, yet poorly predicted inhibition measures. Further longitudinal research is needed to directly address the contribution of attentional control mechanisms to emerging executive functioning and to the development of problematic behavior during early development. PMID:24904462

Determinants of exercise among children. II. A longitudinal analysis.

PubMed

DiLorenzo, T M; Stucky-Ropp, R C; Vander Wal, J S; Gotham, H J

1998-01-01

Research has demonstrated that physical activity serves an important preventive function against the development of cardiovascular disease. The recognition that U.S. children are often sedentary, coupled with the observation that physical activity habits tend to persist into adulthood, has prompted the investigation of exercise determinants consistent with social learning theory. The purposes of the present study were to identify social learning variables relevant to children's exercise and to explore the longitudinal predictive value of the determinants. Data were collected from 111 families (N = 54 girls, N = 57 boys) who were interviewed in both Phase 1 (fifth and sixth grades) and Phase 2 (eight and ninth grades) of this study. Data from mothers (N = 111) were collected during both phases; data from 80 fathers were collected at Phase 2 only. The results of simultaneous stepwise regression analyses indicated that child's enjoyment of physical activity was the only consistent predictor of physical activity during Phase 1. At Phase 2, child's exercise knowledge, mother's physical activity, and child's and mother's friend modeling/support emerged as predictors for girls. For boys, child's self-efficacy for physical activity, exercise knowledge, parental modeling, and interest in sports media were important. Longitudinally, mother's self-efficacy, barriers to exercise, enjoyment of physical activity, and child's self-efficacy for physical activity were important for girls. Only child's exercise knowledge predicted boys' physical activity. The addition of information from fathers nearly doubled the explanatory power of the predictors for both genders. Socialization in the family unit exerts a tremendous influence on health-related behaviors such as exercise. The relative importance of determinants seems to differ for girls and boys and the pattern of these determinants appears to change over time.

Longitudinal changes in white matter disease and cognition in the first year of the Alzheimer disease neuroimaging initiative.

PubMed

Carmichael, Owen; Schwarz, Christopher; Drucker, David; Fletcher, Evan; Harvey, Danielle; Beckett, Laurel; Jack, Clifford R; Weiner, Michael; DeCarli, Charles

2010-11-01

To evaluate relationships between magnetic resonance imaging (MRI)-based measures of white matter hyperintensities (WMHs), measured at baseline and longitudinally, and 1-year cognitive decline using a large convenience sample in a clinical trial design with a relatively mild profile of cardiovascular risk factors. Convenience sample in a clinical trial design. A total of 804 participants in the Alzheimer Disease Neuroimaging Initiative who received MRI scans, cognitive testing, and clinical evaluations at baseline, 6-month follow-up, and 12-month follow-up visits. For each scan, WMHs were detected automatically on coregistered sets of T1, proton density, and T2 MRI images using a validated method. Mixed-effects regression models evaluated relationships between risk factors for WMHs, WMH volume, and change in outcome measures including Mini-Mental State Examination (MMSE), Alzheimer Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Clinical Dementia Rating Scale sum of boxes scores. Covariates in these models included race, sex, years of education, age, apolipoprotein E genotype, baseline clinical diagnosis (cognitively normal, mild cognitive impairment, or Alzheimer disease), cardiovascular risk score, and MRI-based hippocampal and brain volumes. Higher baseline WMH volume was associated with greater subsequent 1-year increase in ADAS-Cog and decrease in MMSE scores. Greater WMH volume at follow-up was associated with greater ADAS-Cog and lower MMSE scores at follow-up. Higher baseline age and cardiovascular risk score and more impaired baseline clinical diagnosis were associated with higher baseline WMH volume. White matter hyperintensity volume predicts 1-year cognitive decline in a relatively healthy convenience sample that was similar to clinical trial samples, and therefore should be considered as a covariate of interest at baseline and longitudinally in future AD treatment trials.

Residential exposure to traffic noise and leisure-time sports - A population-based study.

PubMed

Roswall, Nina; Ammitzbøll, Gunn; Christensen, Jeppe Schultz; Raaschou-Nielsen, Ole; Jensen, Steen Solvang; Tjønneland, Anne; Sørensen, Mette

2017-08-01

Traffic levels have been found a significant environmental predictor for physical inactivity. A recent study suggested that traffic noise annoyance was associated with lower physical activity. We investigated associations between modelled residential traffic noise and leisure-time sports. In the Diet, Cancer and Health cohort, we performed cross-sectional analyses using data from the baseline questionnaire (1993-97), and longitudinal analyses of change between baseline and follow-up (2000-02). People reported participation (yes/no) and hours of leisure-time sport, from which we calculated MET hrs/week. Present and historical addresses from 1987 to 2002 were found in national registries, and traffic noise was modelled 1 and 5 years before enrolment, and from baseline to follow-up. Analyses were performed using logistic and linear regression. Traffic noise exposure 5 years before baseline was associated with higher prevalence odds ratio of non-participation in leisure-time sports; significantly for road traffic noise (odds ratio (OR): 1.10; 95% confidence interval (CI): 1.07-1.13) and borderline for railway noise (OR: 1.03; 95% CI: 0.99-1.07), per 10dB. In longitudinal analyses, a 10dB higher road traffic noise was associated with a higher prevalence odds ratio of ceasing (OR: 1.12; 95% CI: 1.07-1.18) and a lower prevalence odds ratio of initiating (OR: 0.92; 95% CI: 0.87-0.96) leisure-time sports. Exposure to railway noise was negatively associated with baseline MET hrs/week, whereas no association was found in longitudinal analyses, or for road traffic noise. The study suggests that long-term exposure to residential road traffic noise is negatively associated with leisure-time sports. Results for railway noise were less consistent. Copyright © 2017 Elsevier GmbH. All rights reserved.

Socioeconomic Position Is Associated With Carotid Intima-Media Thickness in Mid-Childhood: The Longitudinal Study of Australian Children.

PubMed

Liu, Richard S; Mensah, Fiona K; Carlin, John; Edwards, Ben; Ranganathan, Sarath; Cheung, Michael; Dwyer, Terence; Saffery, Richard; Magnussen, Costan G; Juonala, Markus; Wake, Melissa; Burgner, David P

2017-08-09

Lower socioeconomic position (SEP) predicts higher cardiovascular risk in adults. Few studies differentiate between neighborhood and family SEP or have repeated measures through childhood, which would inform understanding of potential mechanisms and the timing of interventions. We investigated whether neighborhood and family SEP, measured biennially from ages 0 to 1 year onward, was associated with carotid intima-media thickness (IMT) at ages 11 to 12 years. Data were obtained from 1477 families participating in the Child Health CheckPoint study, nested within the Longitudinal Study of Australian Children. Disadvantaged family and neighborhood SEP was cross-sectionally associated with thicker maximum carotid IMT in separate univariable linear regression models. Associations with family SEP were not attenuated in multivariable analyses, and associations with neighborhood SEP were attenuated only in models adjusted for family SEP. The difference in maximum carotid IMT between the highest and lowest family SEP quartile measured at ages 10 to 11 years was 10.7 μm (95% CI, 3.4-18.0; P =0.004), adjusted for age, sex, pubertal status, passive smoking exposure, body mass index, blood pressure, and arterial lumen diameter. In longitudinal analyses, family SEP measured as early as age 2 to 3 years was associated with maximum carotid IMT at ages 11 to 12 years (difference between highest and lowest quartile: 8.5 μm; 95% CI, 1.3-15.8; P =0.02). No associations were observed between SEP and mean carotid IMT. We report a robust association between lower SEP in early childhood and carotid IMT in mid-childhood. Further investigation of mechanisms may inform pediatric cardiovascular risk assessment and prevention strategies. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Reduced diaphyseal strength associated with high intracortical vascular porosity within long bones of children with osteogenesis imperfecta.

PubMed

Albert, Carolyne; Jameson, John; Smith, Peter; Harris, Gerald

2014-09-01

Osteogenesis imperfecta is a genetic disorder resulting in bone fragility. The mechanisms behind this fragility are not well understood. In addition to characteristic bone mass deficiencies, research suggests that bone material properties are compromised in individuals with this disorder. However, little data exists regarding bone properties beyond the microstructural scale in individuals with this disorder. Specimens were obtained from long bone diaphyses of nine children with osteogenesis imperfecta during routine osteotomy procedures. Small rectangular beams, oriented longitudinally and transversely to the diaphyseal axis, were machined from these specimens and elastic modulus, yield strength, and maximum strength were measured in three-point bending. Intracortical vascular porosity, bone volume fraction, osteocyte lacuna density, and volumetric tissue mineral density were determined by synchrotron micro-computed tomography, and relationships among these mechanical properties and structural parameters were explored. Modulus and strength were on average 64-68% lower in the transverse vs. longitudinal beams (P<0.001, linear mixed model). Vascular porosity ranged between 3 and 42% of total bone volume. Longitudinal properties were associated negatively with porosity (P≤0.006, linear regressions). Mechanical properties, however, were not associated with osteocyte lacuna density or volumetric tissue mineral density (P≥0.167). Bone properties and structural parameters were not associated significantly with donor age (P≥0.225, linear mixed models). This study presents novel data regarding bone material strength in children with osteogenesis imperfecta. Results confirm that these properties are anisotropic. Elevated vascular porosity was observed in most specimens, and this parameter was associated with reduced bone material strength. These results offer insight toward understanding bone fragility and the role of intracortical porosity on the strength of bone tissue in children with osteogenesis imperfecta. Copyright © 2014 Elsevier Inc. All rights reserved.

Predictive 5-Year Survivorship Model of Cystic Fibrosis

PubMed Central

Liou, Theodore G.; Adler, Frederick R.; FitzSimmons, Stacey C.; Cahill, Barbara C.; Hibbs, Jonathan R.; Marshall, Bruce C.

2007-01-01

The objective of this study was to create a 5-year survivorship model to identify key clinical features of cystic fibrosis. Such a model could help researchers and clinicians to evaluate therapies, improve the design of prospective studies, monitor practice patterns, counsel individual patients, and determine the best candidates for lung transplantation. The authors used information from the Cystic Fibrosis Foundation Patient Registry (CFFPR), which has collected longitudinal data on approximately 90% of cystic fibrosis patients diagnosed in the United States since 1986. They developed multivariate logistic regression models by using data on 5,820 patients randomly selected from 11,630 in the CFFPR in 1993. Models were tested for goodness of fit and were validated for the remaining 5,810 patients for 1993. The validated 5-year survivorship model included age, forced expiratory volume in 1 second as a percentage of predicted normal, gender, weight-for-age z score, pancreatic sufficiency, diabetes mellitus, Staphylococcus aureus infection, Burkerholderia cepacia infection, and annual number of acute pulmonary exacerbations. The model provides insights into the complex nature of cystic fibrosis and supplies a rigorous tool for clinical practice and research. PMID:11207152

Static Aeroelastic and Longitudinal Trim Model of Flexible Wing Aircraft Using Finite-Element Vortex-Lattice Coupled Solution

NASA Technical Reports Server (NTRS)

Ting, Eric; Nguyen, Nhan; Trinh, Khanh

2014-01-01

This paper presents a static aeroelastic model and longitudinal trim model for the analysis of a flexible wing transport aircraft. The static aeroelastic model is built using a structural model based on finite-element modeling and coupled to an aerodynamic model that uses vortex-lattice solution. An automatic geometry generation tool is used to close the loop between the structural and aerodynamic models. The aeroelastic model is extended for the development of a three degree-of-freedom longitudinal trim model for an aircraft with flexible wings. The resulting flexible aircraft longitudinal trim model is used to simultaneously compute the static aeroelastic shape for the aircraft model and the longitudinal state inputs to maintain an aircraft trim state. The framework is applied to an aircraft model based on the NASA Generic Transport Model (GTM) with wing structures allowed to flexibly deformed referred to as the Elastically Shaped Aircraft Concept (ESAC). The ESAC wing mass and stiffness properties are based on a baseline "stiff" values representative of current generation transport aircraft.

Phenological models to predict the main flowering phases of olive ( Olea europaea L.) along a latitudinal and longitudinal gradient across the Mediterranean region

NASA Astrophysics Data System (ADS)

Aguilera, Fátima; Fornaciari, Marco; Ruiz-Valenzuela, Luis; Galán, Carmen; Msallem, Monji; Dhiab, Ali Ben; la Guardia, Consuelo Díaz-de; del Mar Trigo, María; Bonofiglio, Tommaso; Orlandi, Fabio

2015-05-01

The aim of the present study was to develop pheno-meteorological models to explain and forecast the main olive flowering phenological phases within the Mediterranean basin, across a latitudinal and longitudinal gradient that includes Tunisia, Spain, and Italy. To analyze the aerobiological sampling points, study periods from 13 years (1999-2011) to 19 years (1993-2011) were used. The forecasting models were constructed using partial least-squares regression, considering both the flowering start and full-flowering dates as dependent variables. The percentages of variance explained by the full-flowering models (mean 84 %) were greater than those explained by the flowering start models (mean 77 %). Moreover, given the time lag from the North African areas to the central Mediterranean areas in the main olive flowering dates, the regional full-flowering predictive models are proposed as the most useful to improve the knowledge of the influence of climate on the olive tree floral phenology. The meteorological parameters related to the previous autumn and both the winter and the spring seasons, and above all the temperatures, regulate the reproductive phenology of olive trees in the Mediterranean area. The mean anticipation of flowering start and full flowering for the future period from 2081 to 2100 was estimated at 10 and 12 days, respectively. One question can be raised: Will the olive trees located in the warmest areas be northward displaced or will they be able to adapt their physiology in response to the higher temperatures? The present study can be considered as an approach to design more detailed future bioclimate research.

Variables associated with sleep quality in chronic tension-type headache: A cross-sectional and longitudinal design.

PubMed

Benito-González, Elena; Palacios-Ceña, Maria; Fernández-Muñoz, Juan J; Castaldo, Matteo; Wang, Kelun; Catena, Antonella; Arendt-Nielsen, Lars; Fernández-de-Las-Peñas, César

2018-01-01

To investigate variables associated at baseline (cross-sectional design) and at one year (longitudinal design) with the quality of sleep in chronic tension-type headache (CTTH). One hundred and eighty (n = 180) and 135 individuals with CTTH participated in the cross-sectional and longitudinal design respectively. Clinical features were collected with a 4-weeks headache diary at baseline and one-year follow-up. Sleep quality was assessed at baseline and 1-year follow-up with the Pittsburgh Sleep Quality Index. Anxiety and depression (Hospital Anxiety and Depression Scale-HADS), burden of headache (Headache Disability Inventory-HDI), quality of life (SF-36 questionnaire), and pressure pain thresholds (PPTs) at trigeminal, extra-trigeminal and widespread area were assessed at baseline. Hierarchical regression analyses were conducted to determine the associations between variables at baseline and 1-year follow-up with sleep quality. At baseline positive correlations between sleep quality and headache intensity, headache frequency, headache duration, emotional and physical burden of headache and depression were observed. The regression analyses found that depression and emotional burden of headache explained 27.5% of the variance in sleep quality at baseline (r2 = .262; F = 23.72 P < .001). At one-year, sleep quality was significantly associated with baseline burden of headache, depression, widespread PPTs, vitality and mental health domains. Regression analyses revealed that vitality, PPT over the second metacarpal and PPT over the neck explained 30.0% of the variance of sleep quality at one-year (r2 = .269, F = 9.71, P < .001). It seems that sleep quality exhibits a complex interaction in individuals with CTTH since depression and the emotional burden were associated with sleep quality at baseline, but vitality and PPTs over extra-trigeminal areas were associated with the quality of sleep at one-year.

Alcohol Misuse and Psychological Resilience among U.S. Iraq and Afghanistan Era Veteran Military Personnel

PubMed Central

Green, Kimberly T.; Beckham, Jean C.; Youssef, Nagy; Elbogen, Eric B.

2013-01-01

Objective The present study sought to investigate the longitudinal effects of psychological resilience against alcohol misuse adjusting for socio-demographic factors, trauma-related variables, and self-reported history of alcohol abuse. Methodology Data were from National Post-Deployment Adjustment Study (NPDAS) participants who completed both a baseline and one-year follow-up survey (N=1090). Survey questionnaires measured combat exposure, probable posttraumatic stress disorder (PTSD), psychological resilience, and alcohol misuse, all of which were measured at two discrete time periods (baseline and one-year follow-up). Baseline resilience and change in resilience (increased or decreased) were utilized as independent variables in separate models evaluating alcohol misuse at the one-year follow-up. Results Multiple linear regression analyses controlled for age, gender, level of educational attainment, combat exposure, PTSD symptom severity, and self-reported alcohol abuse. Accounting for these covariates, findings revealed that lower baseline resilience, younger age, male gender, and self-reported alcohol abuse were related to alcohol misuse at the one-year follow-up. A separate regression analysis, adjusting for the same covariates, revealed a relationship between change in resilience (from baseline to the one-year follow-up) and alcohol misuse at the one-year follow-up. The regression model evaluating these variables in a subset of the sample in which all the participants had been deployed to Iraq and/or Afghanistan was consistent with findings involving the overall era sample. Finally, logistic regression analyses of the one-year follow-up data yielded similar results to the baseline and resilience change models. Conclusions These findings suggest that increased psychological resilience is inversely related to alcohol misuse and is protective against alcohol misuse over time. Additionally, it supports the conceptualization of resilience as a process which evolves over time. Moreover, our results underscore the importance of assessing resilience as part of alcohol use screening for preventing alcohol misuse in Iraq and Afghanistan era military veterans. PMID:24090625

Physical exercise and cognitive function across the life span: Results of a nationwide population-based study.

PubMed

Gaertner, Beate; Buttery, Amanda K; Finger, Jonas D; Wolfsgruber, Steffen; Wagner, Michael; Busch, Markus A

2018-05-01

To examine cross-sectional and longitudinal associations between physical exercise and cognitive function across different age groups in a nationwide population-based sample of adults aged 18-79 years in Germany. Cross-sectional/prospective. Cognitive function was assessed in the mental health module of the German Health Interview and Examination Survey for Adults (DEGS1-MH, 2009-2012, n=3535), using a comprehensive neuropsychological test battery. Cognitive domain scores for executive function and memory were derived from confirmatory factor analysis. Regular physical exercise in the last three months was assessed by self-report and defined as no exercise, <2 and ≥2h (hours) of exercise per week. A subgroup of DEGS1-MH participants who previously participated in the German National Health Interview and Examination Survey 1998 (GNHIES98, 1997-1999, n=1624) enabled longitudinal analyses with a mean follow-up of 12.4 years. Compared to no exercise, more weekly physical exercise was associated with better executive function in cross-sectional (<2h: β=0.12; ≥2h: β=0.17; all p<0.001) and longitudinal analyses (<2h: β=0.14, p<0.001; ≥2h: β=0.15, p=0.001) using linear regression models adjusted for age, sex, education, smoking, alcohol consumption, fruit and vegetable consumption and obesity. Slightly weaker associations were found for memory in cross-sectional (<2h: β=0.08, p=0.009; ≥2h: β=0.08, p=0.026) and longitudinal analysis (<2h: β=0.09, p=0.036; ≥2h: β=0.08, p=0.114). There was no evidence of interaction between physical exercise and age. Higher levels of physical exercise were associated with better executive function and memory in cross-sectional and longitudinal analyses with no evidence for differential effects by age. Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Family food involvement and frequency of family dinner meals among Australian children aged 10-12years. Cross-sectional and longitudinal associations with dietary patterns.

PubMed

Leech, Rebecca M; McNaughton, Sarah A; Crawford, David A; Campbell, Karen J; Pearson, Natalie; Timperio, Anna

2014-04-01

Involvement in meal preparation and eating meals with the family are associated with better dietary patterns in adolescents, however little research has included older children or longitudinal study designs. This 3-year longitudinal study examines cross-sectional and longitudinal associations between family food involvement, family dinner meal frequency and dietary patterns during late childhood. Questionnaires were completed by parents of 188 children from Greater Melbourne, Australia at baseline in 2002 (mean age=11.25years) and at follow-up in 2006 (mean age=14.16years). Principal components analysis (PCA) was used to identify dietary patterns. Factor analysis (FA) was used to determine the principal factors from six indicators of family food involvement. Multiple linear regression models were used to predict the dietary patterns of children and adolescents at baseline and at follow-up, 3years later, from baseline indicators of family food involvement and frequency of family dinner meals. PCA revealed two dietary patterns, labeled a healthful pattern and an energy-dense pattern. FA revealed one factor for family food involvement. Cross-sectionally among boys, family food involvement score (β=0.55, 95% CI: 0.02, 1.07) and eating family dinner meals daily (β=1.11, 95% CI: 0.27, 1.96) during late childhood were positively associated with the healthful pattern. Eating family dinner meals daily was inversely associated with the energy-dense pattern, cross-sectionally among boys (β=-0.56, 95% CI: -1.06, -0.06). No significant cross-sectional associations were found among girls and no significant longitudinal associations were found for either gender. Involvement in family food and eating dinner with the family during late childhood may have a positive influence on dietary patterns of boys. No evidence was found to suggest the effects on dietary patterns persist into adolescence. Copyright © 2014 Elsevier Ltd. All rights reserved.

A crash-prediction model for multilane roads.

PubMed

Caliendo, Ciro; Guida, Maurizio; Parisi, Alessandra

2007-07-01

Considerable research has been carried out in recent years to establish relationships between crashes and traffic flow, geometric infrastructure characteristics and environmental factors for two-lane rural roads. Crash-prediction models focused on multilane rural roads, however, have rarely been investigated. In addition, most research has paid but little attention to the safety effects of variables such as stopping sight distance and pavement surface characteristics. Moreover, the statistical approaches have generally included Poisson and Negative Binomial regression models, whilst Negative Multinomial regression model has been used to a lesser extent. Finally, as far as the authors are aware, prediction models involving all the above-mentioned factors have still not been developed in Italy for multilane roads, such as motorways. Thus, in this paper crash-prediction models for a four-lane median-divided Italian motorway were set up on the basis of accident data observed during a 5-year monitoring period extending between 1999 and 2003. The Poisson, Negative Binomial and Negative Multinomial regression models, applied separately to tangents and curves, were used to model the frequency of accident occurrence. Model parameters were estimated by the Maximum Likelihood Method, and the Generalized Likelihood Ratio Test was applied to detect the significant variables to be included in the model equation. Goodness-of-fit was measured by means of both the explained fraction of total variation and the explained fraction of systematic variation. The Cumulative Residuals Method was also used to test the adequacy of a regression model throughout the range of each variable. The candidate set of explanatory variables was: length (L), curvature (1/R), annual average daily traffic (AADT), sight distance (SD), side friction coefficient (SFC), longitudinal slope (LS) and the presence of a junction (J). Separate prediction models for total crashes and for fatal and injury crashes only were considered. For curves it is shown that significant variables are L, 1/R and AADT, whereas for tangents they are L, AADT and junctions. The effect of rain precipitation was analysed on the basis of hourly rainfall data and assumptions about drying time. It is shown that a wet pavement significantly increases the number of crashes. The models developed in this paper for Italian motorways appear to be useful for many applications such as the detection of critical factors, the estimation of accident reduction due to infrastructure and pavement improvement, and the predictions of accidents counts when comparing different design options. Thus this research may represent a point of reference for engineers in adjusting or designing multilane roads.

Multistate transitional models for measuring adherence to breast cancer screening: A population-based longitudinal cohort study with over two million women.

PubMed

Sutradhar, R; Gu, S; Paszat, L F

2017-06-01

Objective Prior work on the disparities among women in breast cancer screening adherence has been methodologically limited. This longitudinal study determines and examines the factors associated with becoming adherent. Methods In a cohort of Canadian women aged 50-74, a three-state transitional model was used to examine adherence to screening for breast cancer. The proportion of time spent being non-adherent with screening was calculated for each woman during her observation window. Using age as the time scale, a relative rate multivariable regression was implemented under the three-state transitional model, to examine the association between covariates (all time-varying) and the rate of becoming adherent. Results The cohort consisted of 2,537,960 women with a median follow-up of 8.46 years. Nearly 31% of women were continually up-to-date with breast screening. Once a woman was non-adherent, the rate of becoming adherent was higher among longer term residents (relative rate = 1.289, 95% confidence interval 1.275-1.302), those from wealthier neighbourhoods, and those who had an identifiable primary care provider who was female or had graduated in Canada. Conclusion Individual and physician-level characteristics play an important role in a woman's adherence to screening. This work improves the quality of evidence regarding disparities among women in adherence to breast cancer screening and provides a novel methodological foundation to investigate adherence for other types of screening, including cervix and colorectal cancer screening.

Personality disorder risk factors for suicide attempts over 10 years of follow-up.

PubMed

Ansell, Emily B; Wright, Aidan G C; Markowitz, John C; Sanislow, Charles A; Hopwood, Christopher J; Zanarini, Mary C; Yen, Shirley; Pinto, Anthony; McGlashan, Thomas H; Grilo, Carlos M

2015-04-01

Identifying personality disorder (PD) risk factors for suicide attempts is an important consideration for research and clinical care alike. However, most prior research has focused on single PDs or categorical PD diagnoses without considering unique influences of different PDs or of severity (sum) of PD criteria on the risk for suicide-related outcomes. This has usually been done with cross-sectional or retrospective assessment methods. Rarely are dimensional models of PDs examined in longitudinal, naturalistic prospective designs. In addition, it is important to consider divergent risk factors in predicting the risk of ever making a suicide attempt versus the risk of making an increasing number of attempts within the same model. This study examined 431 participants who were followed for 10 years in the Collaborative Longitudinal Personality Disorders Study. Baseline assessments of personality disorder criteria were summed as dimensional counts of personality pathology and examined as predictors of suicide attempts reported at annual interviews throughout the 10-year follow-up period. We used univariate and multivariate zero-inflated Poisson regression models to simultaneously evaluate PD risk factors for ever attempting suicide and for increasing numbers of attempts among attempters. Consistent with prior research, borderline PD was uniquely associated with ever attempting. However, only narcissistic PD was uniquely associated with an increasing number of attempts. These findings highlight the relevance of both borderline and narcissistic personality pathology as unique contributors to suicide-related outcomes. (c) 2015 APA, all rights reserved).

Physical activity and asthma: A longitudinal and multi-country study.

PubMed

Russell, Melissa A; Janson, Christer; Real, Francisco Gómez; Johannessen, Ane; Waatevik, Marie; Benediktsdóttir, Bryndis; Holm, Mathias; Lindberg, Eva; Schlünssen, Vivi; Raza, Wasif; Dharmage, Shyamali C; Svanes, Cecilie

2017-11-01

To investigate the impact of physical activity on asthma in middle-aged adults, in one longitudinal analysis, and one multi-centre cross-sectional analysis. The Respiratory Health in Northern Europe (RHINE) is a population-based postal questionnaire cohort study. Physical activity, height and weight were self-reported in Bergen, Norway, at RHINE II (1999-2001) and all centres at RHINE III (2010-2012). A longitudinal analysis of Bergen data investigated the association of baseline physical activity with follow-up asthma, incident asthma and symptoms, using logistic and zero-inflated Poisson regression (n = 1782). A cross-sectional analysis of all RHINE III centres investigated the association of physical activity with concurrent asthma and symptoms (n = 13,542) using mixed-effects models. Body mass index (BMI) was categorised (<20, 20-24.99, 25-29.99, 30+ kg/m 2 ) and physical activity grouped by amount and frequency of lighter (no sweating/heavy breathing) and vigorous (sweating/heavy breathing) activity. In the Bergen longitudinal analysis, undertaking light activity 3+ times/week at baseline was associated with less follow-up asthma (odds ratio [OR] 0.44, 95% confidence interval [CI] 0.22, 0.89), whilst an effect from undertaking vigorous activity 3+ times/week was not detected (OR 1.22, 95% CI 0.44, 2.76). The associations were attenuated with BMI adjustment. In the all-centre cross-sectional analysis an interaction was found, with the association between physical activity and asthma varying across BMI categories. These findings suggest potential longer-term benefit from lighter physical activity, whilst improvement in asthma outcomes from increasing activity intensity was not evident. Additionally, it appears the benefit from physical activity may differ according to BMI.

Willingness to Participate in Longitudinal Research Among People with Chronic Pain Who Take Medical Cannabis: A Cross-Sectional Survey.

PubMed

Bachhuber, Marcus A; Arnsten, Julia H; Starrels, Joanna L; Cunningham, Chinazo O

2018-01-01

Background: Regulatory barriers limit clinical trials of medical cannabis in the United States. Longitudinal cohort studies may be one feasible alternative that could yield clinically relevant information. Willingness to participate in such studies is not known. Materials and Methods: In October 2016, we surveyed a convenience sample of patients with chronic pain from two New York registered organizations (responsible for growing, processing, distributing, and retailing medical cannabis products). After a vignette describing a longitudinal cohort study involving weekly patient-reported outcomes and quarterly assessments of physical functioning and urine and blood tests, we asked about respondents' willingness to participate. We examined willingness to participate, duration of participation, and frequency of data collections overall and by subgroups, using multivariable logistic regression models. Results: Of 405 respondents (estimated response rate: 30%), 54% were women and 81% were white non-Hispanic. Neuropathy was the most common pain condition (67%) followed by inflammatory bowel disease (19%). Of respondents, 94% (95% CI 92-97%) thought that the study should be done, 85% (95% CI 81-88%) would definitely or probably enroll if asked, 76% (95% CI 72-81%) would participate for ≥1 year, and 59% (95% CI 54-64%) would respond to questions at least daily. Older age was the only factor associated with lower willingness to participate, lower willingness to participate for ≥1 year, and lower willingness to respond to questions at least daily. Conclusions: Nearly all respondents were supportive of the proposed study and most reported that they would enroll if asked. Enhanced engagement with older individuals may be needed to promote equal enrollment. Recruitment for longitudinal cohort studies with frequent data collection appears feasible in this patient population.

Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C]PiB.

PubMed

Resnick, S M; Sojkova, J; Zhou, Y; An, Y; Ye, W; Holt, D P; Dannals, R F; Mathis, C A; Klunk, W E; Ferrucci, L; Kraut, M A; Wong, D F

2010-03-09

To investigate whether longitudinal declines in cognition are associated with higher fibrillar amyloid-beta (Abeta) deposition in vivo in individuals without dementia. [(11)C]PiB images were obtained to measure fibrillar Abeta burden in 57 participants without dementia from the Baltimore Longitudinal Study of Aging. Participants (33 men, 24 women) had a mean (SD) age of 78.7 (6.2) years. Six participants (4 men, 2 women) had mild cognitive impairment defined as Clinical Dementia Rating = 0.5. To measure [(11)C]PiB retention, distribution volume ratios (DVR) for 15 regions of interest were estimated by fitting a simplified reference tissue model to the measured time activity curves. Mixed effects regression was used to predict cognitive trajectories over time using data before and including time of PiB (mean follow-up 10.8 years), with mean cortical DVR, age at baseline, sex, and education as independent predictors. Voxel-based analysis identified local associations. [(11)C]PiB retention was higher in older individuals. Greater declines over time in mental status and verbal learning and memory, but not visual memory, were associated significantly with higher PiB retention. Voxel-based analysis showed significant associations in frontal and lateral temporal regions. Higher Abeta deposition is associated with greater longitudinal decline in mental status and verbal memory in the preceding years. The differential association for verbal but not visual memory may reflect the greater reliance of verbal word list learning on prefrontal regions, which show early Abeta deposition. Prospective imaging may help distinguish between individuals with evolving neuropathology who develop accelerated cognitive decline vs those with normal aging.

Longitudinal Association between Periodontitis and Development of Diabetes Running title: Periodontitis and Diabetes Development.

PubMed

Joshipura, Kaumudi J; Muñoz-Torres, Francisco J; Dye, Bruce A; Leroux, Brian G; Ramírez-Vick, Margarita; Pérez, Cynthia M

2018-04-18

Clinical trials have shown very modest short-term improvements in glycemic control among participants with diabetes after periodontitis treatment. Few longitudinal studies suggest that periodontitis may be related to prediabetes/diabetes risk. We evaluated 1,206 diabetes free participants in the San Juan Overweight Adults Longitudinal Study (SOALS) and 941 with complete 3-year follow-up data were included. The National Health and Nutrition Examination Survey (NHANES) methods were used to assess periodontitis. Diabetes and prediabetes were classified using American Diabetes Association cutoffs for fasting and 2-hour post-load glucose and HbA1c. We used Poisson regression adjusting for baseline age, gender, smoking, education, family history of diabetes, physical activity, waist circumference, and alcohol intake. Over the 3-year follow-up, 69 (7.3%) of the 941 individuals developed type 2 diabetes, and 142 (34.9%) of the 407 with normal glycemia at baseline developed prediabetes. In multivariable models, greater mean pocket depth and mean attachment loss at baseline were associated with lower risk of developing prediabetes/diabetes over the follow-up (IRR=0.81; 95% CI: 0.67-0.99, and IRR=0.86; 95% CI: 0.74-0.99, respectively). Increase in periodontal attachment loss from baseline to follow-up was associated with higher prediabetes/diabetes risk (multivariate IRR=1.25; 95% CI: 1.09-1.42), and increase in pocket depth was associated with >20% fasting glucose increase (multivariate IRR=1.43; 95% CI: 1.14-1.79). The inverse associations persisted after additionally adjusting for baseline income, sugar-sweetened beverages, number of teeth, oral hygiene, glycemia, or previous periodontal therapy. There is no association between periodontitis and risk of prediabetes/diabetes in this longitudinal study. Copyright © 2018 Elsevier B.V. All rights reserved.

Does relationship satisfaction and financial aid from offspring influence the quality of life of older parents?: a longitudinal study based on findings from the Korean longitudinal study of aging, 2006-2012.

PubMed

Ju, Yeong Jun; Han, Kyu-Tae; Lee, Tae-Hoon; Kim, Woorim; Kim, Juyeong; Park, Eun-Cheol

2016-07-26

Quality of life (QoL) in old age is of major importance because the global population is aging rapidly. Offspring support, including financial and emotional support, is important in later life and directly affects the wellbeing of elderly individuals. The aim of this study was to examine the relationship between QoL in older parents and offspring support. We used baseline data from the 2006-2012 Korean Longitudinal Study of Aging, from 3,274 individuals aged 65 years or older. We measured the individual's QoL using a visual analog scale and included both relationship satisfaction and regular economic support as variables. A generalized estimating equation (GEE) model was used to perform longitudinal regression analysis on the data. Regarding the QoL of older parents, those with an unsatisfying relationship with their offspring had a QoL of -21.93 (SE = 0.55; P < 0.0001) compared to those with satisfying offspring relationships. Those receiving no regular financial aid from their offspring had a QoL of -0.92 (SE = 0.38; P = 0.0171) compared to those who received such economic support. Combination effects were observed, with cases living alone - and having poor offspring relationships and no regular financial support from their offspring - showing the most drastic decrease in QoL (-23.46; SE = 1.03; P < 0.0001). Offspring support influences the QoL of elderly individuals, and Korean children appear to play a crucial role in the QoL of their (older) parents. Considering that the role of offspring is rapidly diminishing due to industrialization policies, initiatives are required to revitalize offspring support for elderly parents.

Multi-country analysis of the effects of diarrhoea on childhood stunting

PubMed Central

Checkley, William; Buckley, Gillian; Gilman, Robert H; Assis, Ana MO; Guerrant, Richard L; Morris, Saul S; Mølbak, Kåre; Valentiner-Branth, Palle; Lanata, Claudio F; Black, Robert E

2008-01-01

Diarrhoea is an important cause of death and illness among children in developing countries; however, it remains controversial as to whether diarrhoea leads to stunting. We conducted a pooled analysis of nine studies that collected daily diarrhoea morbidity and longitudinal anthropometry to determine the effects of the longitudinal history of diarrhoea prior to 24 months on stunting at age 24 months. Data covered a 20-year period and five countries. We used logistic regression to model the effect of diarrhoea on stunting. The prevalence of stunting at age 24 months varied by study (range 21–90%), as did the longitudinal history of diarrhoea prior to 24 months (incidence range 3.6–13.4 episodes per child-year, prevalence range 2.4–16.3%). The effect of diarrhoea on stunting, however, was similar across studies. The odds of stunting at age 24 months increased multiplicatively with each diarrhoeal episode and with each day of diarrhoea before 24 months (all P < 0.001). The adjusted odds of stunting increased by 1.13 for every five episodes (95% CI 1.07–1.19), and by 1.16 for every 5% unit increase in longitudinal prevalence (95% CI 1.07–1.25). In this assembled sample of 24-month-old children, the proportion of stunting attributed to ≥5 diarrhoeal episodes before 24 months was 25% (95% CI 8–38%) and that attributed to being ill with diarrhoea for ≥2% of the time before 24 months was 18% (95% CI 1–31%). These observations are consistent with the hypothesis that a higher cumulative burden of diarrhoea increases the risk of stunting. PMID:18567626

Retinal vessel caliber among people with acquired immunodeficiency syndrome: relationships with visual function.

PubMed

Kalyani, Partho S; Fawzi, Amani A; Gangaputra, Sapna; van Natta, Mark L; Hubbard, Larry D; Danis, Ronald P; Thorne, Jennifer E; Holland, Gary N

2012-03-01

To evaluate relationships between retinal vessel caliber and tests of visual function among people with AIDS. Longitudinal, observational cohort study. We evaluated data for participants without ocular opportunistic infections at initial examination (baseline) in the Longitudinal Studies of the Ocular Complications of AIDS (1998-2008). Visual function was evaluated with best-corrected visual acuity, Goldmann perimetry, automated perimetry (Humphrey Field Analyzer), and contrast sensitivity (CS) testing. Semi-automated grading of fundus photographs (1 eye/participant) determined central retinal artery equivalent (CRAE), central retinal vein equivalent (CRVE), and arteriole-to-venule ratio (AVR) at baseline. Multiple linear regression models, using forward selection, sought independent relationships between indices and visual function variables. Included were 1250 participants. Smaller AVR was associated with reduced visual field by Goldmann perimetry (P = .003) and worse mean deviation (P = .02) on automated perimetry and possibly with worse pattern standard deviation (PSD) on automated perimetry (P = .06). There was a weak association between smaller AVR and worse CS (P = .07). Relationships were independent of antiretroviral therapy and level of immunodeficiency (CD4+ T lymphocyte count, human immunodeficiency virus [HIV] RNA blood level). On longitudinal analysis, retinal vascular indices at baseline did not predict changes in visual function. Variation in retinal vascular indices is associated with abnormal visual function in people with AIDS, manifested by visual field loss and possibly by reduced CS. Relationships are consistent with the hypothesis that HIV-related retinal vasculopathy is a contributing factor to vision dysfunction among HIV-infected individuals. Longitudinal studies are needed to determine whether changes in indices predict change in visual function. Copyright © 2012 Elsevier Inc. All rights reserved.

Willingness to Participate in Longitudinal Research Among People with Chronic Pain Who Take Medical Cannabis: A Cross-Sectional Survey

PubMed Central

Bachhuber, Marcus A.; Arnsten, Julia H.; Starrels, Joanna L.; Cunningham, Chinazo O.

2018-01-01

Abstract Background: Regulatory barriers limit clinical trials of medical cannabis in the United States. Longitudinal cohort studies may be one feasible alternative that could yield clinically relevant information. Willingness to participate in such studies is not known. Materials and Methods: In October 2016, we surveyed a convenience sample of patients with chronic pain from two New York registered organizations (responsible for growing, processing, distributing, and retailing medical cannabis products). After a vignette describing a longitudinal cohort study involving weekly patient-reported outcomes and quarterly assessments of physical functioning and urine and blood tests, we asked about respondents' willingness to participate. We examined willingness to participate, duration of participation, and frequency of data collections overall and by subgroups, using multivariable logistic regression models. Results: Of 405 respondents (estimated response rate: 30%), 54% were women and 81% were white non-Hispanic. Neuropathy was the most common pain condition (67%) followed by inflammatory bowel disease (19%). Of respondents, 94% (95% CI 92–97%) thought that the study should be done, 85% (95% CI 81–88%) would definitely or probably enroll if asked, 76% (95% CI 72–81%) would participate for ≥1 year, and 59% (95% CI 54–64%) would respond to questions at least daily. Older age was the only factor associated with lower willingness to participate, lower willingness to participate for ≥1 year, and lower willingness to respond to questions at least daily. Conclusions: Nearly all respondents were supportive of the proposed study and most reported that they would enroll if asked. Enhanced engagement with older individuals may be needed to promote equal enrollment. Recruitment for longitudinal cohort studies with frequent data collection appears feasible in this patient population. PMID:29607410

Longitudinal changes in telomere length and associated genetic parameters in dairy cattle analysed using random regression models.

PubMed

Seeker, Luise A; Ilska, Joanna J; Psifidi, Androniki; Wilbourn, Rachael V; Underwood, Sarah L; Fairlie, Jennifer; Holland, Rebecca; Froy, Hannah; Bagnall, Ainsley; Whitelaw, Bruce; Coffey, Mike; Nussey, Daniel H; Banos, Georgios

2018-01-01

Telomeres cap the ends of linear chromosomes and shorten with age in many organisms. In humans short telomeres have been linked to morbidity and mortality. With the accumulation of longitudinal datasets the focus shifts from investigating telomere length (TL) to exploring TL change within individuals over time. Some studies indicate that the speed of telomere attrition is predictive of future disease. The objectives of the present study were to 1) characterize the change in bovine relative leukocyte TL (RLTL) across the lifetime in Holstein Friesian dairy cattle, 2) estimate genetic parameters of RLTL over time and 3) investigate the association of differences in individual RLTL profiles with productive lifespan. RLTL measurements were analysed using Legendre polynomials in a random regression model to describe TL profiles and genetic variance over age. The analyses were based on 1,328 repeated RLTL measurements of 308 female Holstein Friesian dairy cattle. A quadratic Legendre polynomial was fitted to the fixed effect of age in months and to the random effect of the animal identity. Changes in RLTL, heritability and within-trait genetic correlation along the age trajectory were calculated and illustrated. At a population level, the relationship between RLTL and age was described by a positive quadratic function. Individuals varied significantly regarding the direction and amount of RLTL change over life. The heritability of RLTL ranged from 0.36 to 0.47 (SE = 0.05-0.08) and remained statistically unchanged over time. The genetic correlation of RLTL at birth with measurements later in life decreased with the time interval between samplings from near unity to 0.69, indicating that TL later in life might be regulated by different genes than TL early in life. Even though animals differed in their RLTL profiles significantly, those differences were not correlated with productive lifespan (p = 0.954).

Longitudinal changes in telomere length and associated genetic parameters in dairy cattle analysed using random regression models

PubMed Central

Ilska, Joanna J.; Psifidi, Androniki; Wilbourn, Rachael V.; Underwood, Sarah L.; Fairlie, Jennifer; Holland, Rebecca; Froy, Hannah; Bagnall, Ainsley; Whitelaw, Bruce; Coffey, Mike; Nussey, Daniel H.; Banos, Georgios

2018-01-01

Telomeres cap the ends of linear chromosomes and shorten with age in many organisms. In humans short telomeres have been linked to morbidity and mortality. With the accumulation of longitudinal datasets the focus shifts from investigating telomere length (TL) to exploring TL change within individuals over time. Some studies indicate that the speed of telomere attrition is predictive of future disease. The objectives of the present study were to 1) characterize the change in bovine relative leukocyte TL (RLTL) across the lifetime in Holstein Friesian dairy cattle, 2) estimate genetic parameters of RLTL over time and 3) investigate the association of differences in individual RLTL profiles with productive lifespan. RLTL measurements were analysed using Legendre polynomials in a random regression model to describe TL profiles and genetic variance over age. The analyses were based on 1,328 repeated RLTL measurements of 308 female Holstein Friesian dairy cattle. A quadratic Legendre polynomial was fitted to the fixed effect of age in months and to the random effect of the animal identity. Changes in RLTL, heritability and within-trait genetic correlation along the age trajectory were calculated and illustrated. At a population level, the relationship between RLTL and age was described by a positive quadratic function. Individuals varied significantly regarding the direction and amount of RLTL change over life. The heritability of RLTL ranged from 0.36 to 0.47 (SE = 0.05–0.08) and remained statistically unchanged over time. The genetic correlation of RLTL at birth with measurements later in life decreased with the time interval between samplings from near unity to 0.69, indicating that TL later in life might be regulated by different genes than TL early in life. Even though animals differed in their RLTL profiles significantly, those differences were not correlated with productive lifespan (p = 0.954). PMID:29438415

Gestational dietary patterns are not associated with blood pressure changes during pregnancy and early postpartum in a Brazilian prospective cohort.

PubMed

Eshriqui, Ilana; Vilela, Ana Amélia Freitas; Rebelo, Fernanda; Farias, Dayana Rodrigues; Castro, Maria Beatriz Trindade; Kac, Gilberto

2016-02-01

To identify gestational dietary patterns and evaluate the association between these patterns and the blood pressure (BP) rate of change during pregnancy and the postpartum. Prospective cohort study composed of 191 healthy pregnant women. Systolic BP (SBP) and diastolic BP (DBP) were obtained at the 5th-13th, 20th-26th, 30th-36th gestational weeks, and with 30-45 days postpartum. A food frequency questionnaire administered at the 30th-36th gestational week was used to measure dietary intake during pregnancy. Principal component analysis was performed to identify the dietary patterns. A longitudinal linear mixed-effects regression model was used to evaluate the association between the dietary patterns and BP (adjusted for time elapsed after conception and the women's age, education, parity, body mass index and total energy intake). Three gestational dietary patterns were identified: healthy, common-Brazilian and processed. SBP/DBP mean values (SD) were 110.1 (9.0)/66.9 (7.5), 108.7 (9.0)/64.9 (6.7), 111.3 (9.2)/67.0 (6.9) and 115.0 (10.7)/73.7 (8.6) mmHg at the first, second and third gestational trimesters and postpartum, respectively. Women with higher/lower adherence to the processed pattern presented SBP of 117.9 and 113.0 mmHg (P = 0.037), respectively, during postpartum. No association was found between any of the three dietary patterns and SBP in the multiple longitudinal linear regression models, whereas 1 SD increase in the common-Brazilian pattern was associated with a small change of DBP (β = 0.0006; 95% CI 4.66e-06, 0.001; P = 0.048). The three dietary patterns identified revealed no association with changes of SBP and DBP levels during pregnancy and at early postpartum in this sample of healthy Brazilian women.

Vitamin D over the first decade and susceptibility to childhood allergy and asthma.

PubMed

Hollams, Elysia M; Teo, Shu Mei; Kusel, Merci; Holt, Barbara J; Holt, Kathryn E; Inouye, Michael; De Klerk, Nicholas H; Zhang, Guicheng; Sly, Peter D; Hart, Prue H; Holt, Patrick G

2017-02-01

Vitamin D (25(OH)D) deficiency has been implicated as a possible risk factor for asthma development, but studies at selected time points measuring 25(OH)D levels during childhood have yielded conflicting findings. Prospective studies tracking 25(OH)D levels during the initiation phase of asthma in early childhood have not been reported. We sought to elucidate relationships between 25(OH)D levels from birth to age 10 years and susceptibility to allergic sensitization, respiratory tract infections, and asthma. Asthma-, allergy-, and respiratory tract infection-associated phenotypes (including pathogen identification) were characterized in a high-risk birth cohort. Plasma 25(OH)D concentrations were quantified at birth and at clinical follow-ups at the ages of 0.5, 1, 2, 3, 4, 5, and 10 years, and relationships with clinical outcomes were examined. Cross-sectional analyses demonstrated inverse associations between 25(OH)D concentrations and the risk for concurrent sensitization at age 0.5, 2, and 3 years, and mixed-effects regression demonstrated inverse longitudinal associations of 25(OH)D levels with both sensitization and eczema. Multivariate regression modeling suggested that the number of 25(OH)D-deficient follow-ups was positively associated with risk for asthma/wheeze, eczema, and sensitization at 10 years; adjustment for sensitization (particularly by 2 years) in the asthma/wheeze models reduced 25(OH)D associations with these latter outcomes. 25(OH)D levels were also inversely associated with early nasopharyngeal colonization with Streptococcus species and age of first febrile lower respiratory illness, both of which are known asthma risk factors. 25(OH)D deficiency in early childhood is associated with increased risk for persistent asthma, potentially through modulating susceptibility to early allergic sensitization, upper respiratory tract colonization with bacterial pathogens, or both. These relationships are only evident if 25(OH)D status is monitored prospectively and longitudinally. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Risk factors for COPD exacerbations in inhaled medication users: the COPDGene study biannual longitudinal follow-up prospective cohort.

PubMed

Busch, Robert; Han, MeiLan K; Bowler, Russell P; Dransfield, Mark T; Wells, J Michael; Regan, Elizabeth A; Hersh, Craig P

2016-02-10

Despite inhaled medications that decrease exacerbation risk, some COPD patients experience frequent exacerbations. We determined prospective risk factors for exacerbations among subjects in the COPDGene Study taking inhaled medications. 2113 COPD subjects were categorized into four medication use patterns: triple therapy with tiotropium (TIO) plus long-acting beta-agonist/inhaled-corticosteroid (ICS ± LABA), tiotropium alone, ICS ± LABA, and short-acting bronchodilators. Self-reported exacerbations were recorded in telephone and web-based longitudinal follow-up surveys. Associations with exacerbations were determined within each medication group using four separate logistic regression models. A head-to-head analysis compared exacerbation risk among subjects using tiotropium vs. ICS ± LABA. In separate logistic regression models, the presence of gastroesophageal reflux, female gender, and higher scores on the St. George's Respiratory Questionnaire were significant predictors of exacerbator status within multiple medication groups (reflux: OR 1.62-2.75; female gender: OR 1.53 - OR 1.90; SGRQ: OR 1.02-1.03). Subjects taking either ICS ± LABA or tiotropium had similar baseline characteristics, allowing comparison between these two groups. In the head-to-head comparison, tiotropium users showed a trend towards lower rates of exacerbations (OR = 0.69 [95 % CI 0.45, 1.06], p = 0.09) compared with ICS ± LABA users, especially in subjects without comorbid asthma (OR = 0.56 [95% CI 0.31, 1.00], p = 0.05). Each common COPD medication usage group showed unique risk factor patterns associated with increased risk of exacerbations, which may help clinicians identify subjects at risk. Compared to similar subjects using ICS ± LABA, those taking tiotropium showed a trend towards reduced exacerbation risk, especially in subjects without asthma. ClinicalTrials.gov NCT00608764, first received 1/28/2008.

Utility of combinations of biomarkers, cognitive markers, and risk factors to predict conversion from mild cognitive impairment to Alzheimer disease in patients in the Alzheimer's disease neuroimaging initiative.

PubMed

Gomar, Jesus J; Bobes-Bascaran, Maria T; Conejero-Goldberg, Concepcion; Davies, Peter; Goldberg, Terry E

2011-09-01

Biomarkers have become increasingly important in understanding neurodegenerative processes associated with Alzheimer disease. Markers include regional brain volumes, cerebrospinal fluid measures of pathological Aβ1-42 and total tau, cognitive measures, and individual risk factors. To determine the discriminative utility of different classes of biomarkers and cognitive markers by examining their ability to predict a change in diagnostic status from mild cognitive impairment to Alzheimer disease. Longitudinal study. We analyzed the Alzheimer's Disease Neuroimaging Initiative database to study patients with mild cognitive impairment who converted to Alzheimer disease (n = 116) and those who did not convert (n = 204) within a 2-year period. We determined the predictive utility of 25 variables from all classes of markers, biomarkers, and risk factors in a series of logistic regression models and effect size analyses. The Alzheimer's Disease Neuroimaging Initiative public database. Primary outcome measures were odds ratios, pseudo- R(2)s, and effect sizes. In comprehensive stepwise logistic regression models that thus included variables from all classes of markers, the following baseline variables predicted conversion within a 2-year period: 2 measures of delayed verbal memory and middle temporal lobe cortical thickness. In an effect size analysis that examined rates of decline, change scores for biomarkers were modest for 2 years, but a change in an everyday functional activities measure (Functional Assessment Questionnaire) was considerably larger. Decline in scores on the Functional Assessment Questionnaire and Trail Making Test, part B, accounted for approximately 50% of the predictive variance in conversion from mild cognitive impairment to Alzheimer disease. Cognitive markers at baseline were more robust predictors of conversion than most biomarkers. Longitudinal analyses suggested that conversion appeared to be driven less by changes in the neurobiologic trajectory of the disease than by a sharp decline in functional ability and, to a lesser extent, by declines in executive function.

Investigation of 2-stage meta-analysis methods for joint longitudinal and time-to-event data through simulation and real data application.

PubMed

Sudell, Maria; Tudur Smith, Catrin; Gueyffier, François; Kolamunnage-Dona, Ruwanthi

2018-04-15

Joint modelling of longitudinal and time-to-event data is often preferred over separate longitudinal or time-to-event analyses as it can account for study dropout, error in longitudinally measured covariates, and correlation between longitudinal and time-to-event outcomes. The joint modelling literature focuses mainly on the analysis of single studies with no methods currently available for the meta-analysis of joint model estimates from multiple studies. We propose a 2-stage method for meta-analysis of joint model estimates. These methods are applied to the INDANA dataset to combine joint model estimates of systolic blood pressure with time to death, time to myocardial infarction, and time to stroke. Results are compared to meta-analyses of separate longitudinal or time-to-event models. A simulation study is conducted to contrast separate versus joint analyses over a range of scenarios. Using the real dataset, similar results were obtained by using the separate and joint analyses. However, the simulation study indicated a benefit of use of joint rather than separate methods in a meta-analytic setting where association exists between the longitudinal and time-to-event outcomes. Where evidence of association between longitudinal and time-to-event outcomes exists, results from joint models over standalone analyses should be pooled in 2-stage meta-analyses. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Mental disorders and harmful substance use in children of substance abusing parents: A longitudinal register-based study on a complete birth cohort born in 1991.

PubMed

Jääskeläinen, Marke; Holmila, Marja; Notkola, Irma-Leena; Raitasalo, Kirsimarja

2016-11-01

Adverse childhood experiences and their accumulation over childhood have negative outcomes to children, yet earlier findings on the independent effect of parental substance abuse seem inconsistent. Our aims were to examine: (i) whether parental substance abuse is associated with children's mental disorders in mid-childhood (7-12 years) and mental disorders and own substance use in adolescence (13-17 years); and (ii) whether children are affected differently by a mother or father's substance abuse. A register-based longitudinal data on a complete birth cohort of children born in Finland in 1991 (n = 65 117) and their biological parents. The children were followed until their 18 th birthday. Data were derived from the Finnish administrative registries. Bivariate and multivariate logistic regression models were used in the analysis. Maternal, paternal and both parents' substance abuse were significant predictors of mental disorders and harmful substance use in children aged 13-17 years, even after controlling for other adverse childhood experiences, parental education and child's gender. Parental substance abuse predicted mental disorders in children aged 7-12 years in bivariate model but in multivariate model the association disappeared. Maternal substance abuse had stronger effect on harmful substance use in adolescent children than paternal. There were no significant interactions between substance abusing parents' gender and the child's gender. Early identification, prevention and treatment of substance abuse in families with children in primary health care, child welfare and other services are crucial in preventing intergenerational transmission of the problems associated with parental substance abuse. [Jääskeläinen M, Holmila M, Notkola I-L, Raitasalo K. Mental disorders and harmful substance use in children of substance abusing parents: A longitudinal register-based study on a complete birth cohort born in 1991. Drug Alcohol Rev 2016;35:728-740]. © 2016 Australasian Professional Society on Alcohol and other Drugs.