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1. Prenatal weight and regional body composition trajectories and neonatal body composition: The NICHD Foetal Growth Studies.

Author

Widen, Elizabeth, Burns, Natalie, Kahn, Linda, Grewal, Jagteshwar, Backlund, Grant, Nichols, Amy, Rickman, Rachel, Foster, Saralyn, Nhan-Chang, Chia-Ling, Zhang, Cuilin, Wapner, Ronald, Wing, Deborah, Owen, John, Skupski, Daniel, Ranzini, Angela, Newman, Roger, Grobman, William, and Daniels, Michael

Subjects
Humans, Obesity, Weight Gain, Body Mass Index, Prospective Studies, Body Composition, Fetal Development, Pregnancy, Infant, Infant, Newborn, United States, Female, Overweight, National Institute of Child Health and Human Development (U.S.)
Abstract

BackgroundGestational weight gain (GWG) and anthropometric trajectories may affect foetal programming and are potentially modifiable.ObjectivesTo assess concomitant patterns of change in weight, circumferences and adiposity across gestation as an integrated prenatal exposure, and determine how they relate to neonatal body composition.MethodsData are from a prospective cohort of singleton pregnancies (n = 2182) enrolled in United States perinatal centres, 2009-2013. Overall and by prepregnancy BMI group (overweight/obesity and healthy weight), joint latent trajectory models were fit with prenatal weight, mid-upper arm circumference (MUAC), triceps (TSF) and subscapular (SSF) skinfolds. Differences in neonatal body composition by trajectory class were assessed via weighted least squares.ResultsSix trajectory patterns reflecting co-occurring changes in weight and MUAC, SSF and TSF across pregnancy were identified overall and by body mass index (BMI) group. Among people with a healthy weight BMI, some differences were observed for neonatal subcutaneous adipose tissue, and among individuals with overweight/obesity some differences in neonatal lean mass were found. Neonatal adiposity measures were higher among infants born to individuals with prepregnancy overweight/obesity.ConclusionsSix integrated trajectory patterns of prenatal weight, subcutaneous adipose tissue and circumferences were observed that were minimally associated with neonatal body composition, suggesting a stronger influence of prepregnancy BMI.

Published
2023

2. Gestational weight change and childhood body composition trajectories from pregnancy to early adolescence

Author

Widen, Elizabeth M, Burns, Natalie, Daniels, Michael, Backlund, Grant, Rickman, Rachel, Foster, Saralyn, Nichols, Amy R, Hoepner, Lori A, Kinsey, Eliza W, Ramirez‐Carvey, Judyth, Hassoun, Abeer, Perera, Frederica P, Bukowski, Radek, and Rundle, Andrew G

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Nutrition, Obesity, Prevention, Perinatal Period - Conditions Originating in Perinatal Period, Pregnancy, Pediatric, Women's Health, Maternal Health, Childhood Obesity, Adolescent, Body Composition, Body Mass Index, Child, Child, Preschool, Female, Gestational Weight Gain, Humans, Male, Waist Circumference, Weight Gain, Endocrinology & Metabolism
Abstract

ObjectiveA mother-child dyad trajectory model of weight and body composition spanning from conception to adolescence was developed to understand how early life exposures shape childhood body composition.MethodsAfrican American (49.3%) and Dominican (50.7%) pregnant mothers (n = 337) were enrolled during pregnancy, and their children (47.5% female) were followed from ages 5 to 14. Gestational weight gain (GWG) was abstracted from medical records. Child weight, height, percentage body fat, and waist circumference were measured. GWG and child body composition trajectories were jointly modeled with a flexible latent class model with a class membership component that included prepregnancy BMI.ResultsFour prenatal and child body composition trajectory patterns were identified, and sex-specific patterns were observed for the joint GWG-postnatal body composition trajectories with more distinct patterns among girls but not boys. Girls of mothers with high GWG across gestation had the highest BMI z score, waist circumference, and percentage body fat trajectories from ages 5 to 14; however, boys in this high GWG group did not show similar growth patterns.ConclusionsJointly modeled prenatal weight and child body composition trajectories showed sex-specific patterns. Growth patterns from childhood though early adolescence appeared to be more profoundly affected by higher GWG patterns in females, suggesting sex differences in developmental programming.

Published
2022

3. A Hybrid Scan Gibbs Sampler for Bayesian Models with Latent Variables

Author

Backlund, Grant, Hobert, James P., Jung, Yeun Ji, and Khare, Kshitij

Subjects
Mathematics - Statistics Theory
Abstract

Gibbs sampling is a widely popular Markov chain Monte Carlo algorithm that can be used to analyze intractable posterior distributions associated with Bayesian hierarchical models. There are two standard versions of the Gibbs sampler: The systematic scan (SS) version, where all variables are updated at each iteration, and the random scan (RS) version, where a single, randomly selected variable is updated at each iteration. The literature comparing the theoretical properties of SS and RS Gibbs samplers is reviewed, and an alternative hybrid scan Gibbs sampler is introduced, which is particularly well suited to Bayesian models with latent variables. The word "hybrid" reflects the fact that the scan used within this algorithm has both systematic and random elements. Indeed, at each iteration, one updates the entire set of latent variables, along with a randomly chosen block of the remaining variables. The hybrid scan (HS) Gibbs sampler has important advantages over the two standard scan Gibbs samplers. Firstly, the HS algorithm is often easier to analyze from a theoretical standpoint. In particular, it can be much easier to establish the geometric ergodicity of a HS Gibbs Markov chain than to do the same for the corresponding SS and RS versions. Secondly, the sandwich methodology developed in Hobert and Marchev (2008), which is also reviewed, can be applied to the HS Gibbs algorithm (but not to the standard scan Gibbs samplers). It is shown that, under weak regularity conditions, adding sandwich steps to the HS Gibbs sampler always results in a theoretically superior algorithm. Three specific Bayesian hierarchical models of varying complexity are used to illustrate the results. One is a simple location-scale model for data from the Student's $t$ distribution, which is used as a pedagogical tool. The other two are sophisticated, yet practical Bayesian regression models., Comment: 35 pages, 2 figures

Published
2018

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