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Background: This study assessed associations between antenatal physical activity and the onset of spontaneous labor (SL). Methods: Data were taken from 541 participants in the third pregnancy, infection, and nutrition study who had no contraindications to antenatal physical activity. An interviewer-administered questionnaire assessed labor triggers, gestational age at birth, and physical activity within the week (24 h to 7 d) and the 24-hour period (0–24 h) prior to SL. A case-crossover design examined the association between physical activity (recreational, occupational, or any) and the risk of onset of SL within the subsequent 24 hours. Results: Overall, 21% (any), 26% (recreational), and 14% (occupational) of participants reported physical activity during the week; whereas 5% (any), 7% (recreational), and 3% (occupational) reported physical activity during the 24-hour period, prior to SL onset. Participants who reported any or occupational physical activity during the 24-hour period had a decreased likelihood of SL within the subsequent 24 hours, while participants who reported at least 30 minutes of recreational physical activity had an increased likelihood. Results remained consistent among early, full, or postterm participants. Conclusion: Recreational, but not occupational, physical activity at term may increase the likelihood of SL; however, the authors cannot rule out reverse causality.

Background: Gene expression analyses indicate that breast cancer is a heterogeneous disease with at least five immunohistologic subtypes. Despite growing evidence that these subtypes are etiologically and prognostically distinct, few studies have investigated whether they have divergent genetic risk factors. To help fill in this gap in our understanding, we examined associations between breast cancer subtypes and previously established susceptibility loci among white and African-American women in the Carolina Breast Cancer Study.Methods: We used Bayesian polytomous logistic regression to estimate ORs and 95% posterior intervals for the association between each of 78 single nucleotide polymorphisms (SNP) and five breast cancer subtypes. Subtypes were defined using five immunohistochemical markers: estrogen receptors (ER), progesterone receptors (PR), human epidermal growth factor receptors 1 and 2 (HER1/2), and cytokeratin (CK) 5/6.Results: Several SNPs in TNRC9/TOX3 were associated with luminal A (ER/PR+, HER2−) or basal-like breast cancer (ER−, PR−, HER2−, HER1, or CK 5/6+), and one SNP (rs3104746) was associated with both. SNPs in FGFR2 were associated with luminal A, luminal B (ER/PR+, HER2+), or HER2+/ER− disease, but none were associated with basal-like disease. We also observed subtype differences in the effects of SNPs in 2q35, 4p, TLR1, MAP3K1, ESR1, CDKN2A/B, ANKRD16, and ZM1Z1.Conclusion and Impact: We found evidence that genetic risk factors for breast cancer vary by subtype and further clarified the role of several key susceptibility genes. Cancer Epidemiol Biomarkers Prev; 23(1); 84–97. ©2013 AACR.

Background: Cigarette smoking is associated with increased head and neck cancer (HNC) risk. Tobacco-related carcinogens are known to cause bulky DNA adducts. Nucleotide excision repair (NER) genes encode enzymes that remove adducts and may be independently associated with HNC, as well as modifiers of the association between smoking and HNC.Methods: Using population-based case–control data from the Carolina Head and Neck Cancer Epidemiology (CHANCE) Study (1,227 cases and 1,325 controls), race-stratified (White, African American), conventional, and hierarchical logistic regression models were used to estimate ORs with 95% intervals (I) for the independent and joint effects of cigarette smoking and 84 single-nucleotide polymorphisms (SNP) from 15 NER genes on HNC risk.Results: The odds of HNC were elevated among ever cigarette smokers and increased with smoking duration and frequency. Among Whites, rs4150403 on ERCC3 was associated with increased HNC odds (AA+AG vs. GG; OR, 1.28; 95% CI, 1.01–1.61). Among African Americans, rs4253132 on ERCC6 was associated with decreased HNC odds (CC+CT vs. TT; OR, 0.62; 95% CI, 0.45–0.86). Interactions between ever cigarette smoking and three SNPs (rs4253132 on ERCC6, rs2291120 on DDB2, and rs744154 on ERCC4) suggested possible departures from additivity among Whites.Conclusions: We did not find associations between some previously studied NER variants and HNC. We did identify new associations between two SNPs and HNC and three suggestive cigarette–SNP interactions to consider in future studies.Impact: We conducted one of the most comprehensive evaluations of NER variants, identifying a few SNPs from biologically plausible candidate genes associated with HNC and possibly interacting with cigarette smoking. Cancer Epidemiol Biomarkers Prev; 22(8); 1428–45. ©2013 AACR.

PDF file - 147K, Betweeen SNP correlation tables (Tables S1a-S1f), Effect Estimates from race-stratified analysis (Tables S2 and S3), Effect estimates from maximum likelihood analysis (Table S4) and Effect estimates from Bayes sensitivity analysis (Table S5)

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PDF file - 195K, Table 1S. Single Nucleotide Polymorphisms (SNPs) in Nucleotide Excision Repair (NER) Genes Inclusion and Exclusion Criteria, Carolina Head and Neck Cancer Epidemiology (CHANCE) Study.: Table 2S. Odds Ratios for Environmental Tobacco Smoke and Head and Neck Cancer in the Carolina Head and Neck Cancer Epidemiology (CHANCE) Study.: Table 3S. Odds Ratios for Single Nucleotide Polymorphisms (SNPs) in ERCC3 and Head and Neck Cancer Tumor Sites Using Hierarchical Regression, the Carolina Head and Neck Cancer Epidemiology (CHANCE) Study, Whites.: Table 4S. Odds Ratios for Single Nucleotide Polymorphisms (SNPs) in ERCC6 Genes and Laryngeal Cancer Using Hierarchical Regression, the Carolina Head and Neck Cancer Epidemiology (CHANCE) Study, African Americans.: Table 5S. Odds Ratios for Single Nucleotide Polymorphisms (SNPs) in Nucleotide Excision Repair (NER) Genes and Head and Neck Cancer Using Conventional Logistic Regression, the Carolina Head and Neck Cancer Epidemiology (CHANCE) Study, Whites.: Table 6S. Odds Ratios for Single Nucleotide Polymorphisms (SNPs) in Nucleotide Excision Repair (NER) Genes and Head and Neck Cancer Using Conventional Logistic Regression, the Carolina Head and Neck Cancer Epidemiology (CHANCE) Study, African Americans.: Table 7S. Odds Ratios and Relative Excess Risk Due to Interaction Estimates for Joint Effects of Single Nucleotide Polymorphisms (SNPs) in Nucleotide Excision Repair (NER) Genes and Former/Current Cigarette Smoking on Head and Neck Cancer Risk Using Conventional Logistic Regression, the Carolina Head and Neck Cancer Epidemiology (CHANCE) Study, Whites.: Table 8S. Odds Ratios and Relative Excess Risk Due to Interaction Estimates for Joint Effects of Single Nucleotide Polymorphisms (SNPs) in Nucleotide Excision Repair (NER) Genes and Ever Environmental Tobacco Smoke on Head and Neck Cancer Risk Using Conventional Logistic Regression, the Carolina Head and Neck Cancer Epidemiology (CHANCE) Study, Whites.

BACKGROUND There is a lack of consensus in the literature about the association between meal patterning during pregnancy and birth outcomes. This study examined whether maternal meal patterning in the week before birth was associated with an increased likelihood of imminent spontaneous labor. METHODS Data came from 607 participants in the third phase of the Pregnancy, Infection, and Nutrition Study (PIN3). Data were collected through an interviewer-administered questionnaire after birth, before hospital discharge. Questions included the typical number of meals and snacks consumed daily, during both the week before labor onset and the 24-hour period before labor onset. A self-matched, case-crossover study design examined the association between skipping one or more meals and the likelihood of spontaneous labor onset within the subsequent 24 hours. RESULTS Among women who experienced spontaneous labor, 87.0% reported routinely eating three daily meals (breakfast, lunch, and dinner) during the week before their labor began, but only 71.2% reported eating three meals during the 24-hour period before their labor began. Compared with the week before their labor, the odds of imminent spontaneous labor were 5.43 times as high (95% CI: 3.41-8.65) within 24 hours of skipping 1 or more meals. The association between skipping 1 or more meals and the onset of spontaneous labor remained elevated for both pregnant individuals who birthed early (37

Prenatal organophosphorus pesticide (OPP) exposure has been associated with child attention-deficit/hyperactivity disorder (ADHD) in agricultural communities and those that are exposed to residentially applied insecticides. To examine this association in populations that are exposed primarily through diet, we estimate the associations between prenatal OPP exposure and preschool ADHD in the Norwegian Mother, Father and Child Cohort Study (MoBa), and describe modification by paraoxonase 1 (PON1) gene variants. We used participants from the MoBa Preschool ADHD Sub-study (n = 259 cases) and a random sample of MoBa sub-cohort participants (n = 547) with birth years from 2004 to 2008. Prenatal urinary dialkylphosphate (DAP) metabolites (total diethylphosphate [∑DEP] and total dimethylphosphate [∑DMP]) were measured by an ultra-performance liquid chromatography-time-of-flight system and summed by molar concentration. Maternal DNA was genotyped for coding variants of PON1 (Q192R and L55M). We used a multivariable logistic regression to calculate the odds ratios (OR) and 95% confidence intervals, adjusted for maternal education, parity, income dependency, age, marital status, ADHD-like symptoms, pesticide use, produce consumption, and season. We found no associations between DAP metabolite concentrations and preschool ADHD. The adjusted ORs for exposure quartiles 2–4 relative to 1 were slightly inverse. No monotonic trends were observed, and the estimates lacked precision, likely due to the small sample size and variation in the population. We found no evidence of modification by PON1 SNP variation or child sex. Maternal urinary DAP concentrations were not associated with preschool ADHD.

Rationale Bronchopulmonary dysplasia (BPD) is associated with post-prematurity respiratory disease (PRD) in survivors of extreme preterm birth. Identifying early biomarkers that correlate with later development of BPD and PRD may provide insights for intervention. In a preterm baboon model, elevated gastrin-releasing peptide (GRP) is associated with BPD, and GRP inhibition mitigates BPD occurrence. Objective We performed a prospective cohort study to investigate whether urine GRP levels obtained in the first postnatal week were associated with BPD, PRD, and other urinary biomarkers of oxidative stress. Methods Extremely low gestational age infants (23-28 completed weeks) were enrolled in a US multicenter observational study, The Prematurity and Respiratory Outcomes Program (http://clinicaltrials.gov/ct2/show/NCT01435187). We used multivariable logistic regression to examine the association between urine GRP in the first postnatal week and multiple respiratory outcomes: BPD, defined as supplemental oxygen use at 36 + 0 weeks postmenstrual age, and post-PRD, defined by positive quarterly surveys for increased medical utilization over the first year (PRD score). Results A total of 109 of 257 (42%) infants had BPD, and 120 of 217 (55%) had PRD. On adjusted analysis, GRP level more than 80 was associated with BPD (adjusted odds ratio [aOR], 1.83; 95% confidence interval [CI], 1.03-3.25) and positive PRD score (aOR, 2.46; 95% CI, 1.35-4.48). Urine GRP levels correlated with duration of NICU ventilatory and oxygen support and with biomarkers of oxidative stress: allantoin and 8-hydroxydeoxyguanosine. Conclusions Urine GRP in the first postnatal week was associated with concurrent urine biomarkers of oxidative stress and with later diagnoses of BPD and PRD.

Introduction: In low-middle income countries, urbanization leads to changes from traditional to Western diet, which are often accompanied by reductions in cardiometabolic health. Whether socioeconomic status buffers these urbanization-related diet changes over time is unknown. Objective: To examine whether the association between urbanization and a key indicator of Western diet, percent of calories from animal-source foods (1) varies depending on income and (2) whether this association changes over time. Materials and methods: We used data from nine waves of the longitudinal, population-based China Health and Nutrition Survey [n = 22,360 Chinese adults (1991–2015)], followed across 24 years, including diet data from 3 repeated 24-h dietary recalls. We used simultaneous year-stratified linear regression models to examine whether changes in the association between urbanization level and percent of calories from animal-source foods differed by income. Models allowed for variation in associations across the 24 years of urbanization, accounting for within-individual correlation over time and controlling for age, sex, region, physical activity, and caloric intake. Results: In 1991, on average 15% of calories for Chinese adults came from animal source foods and by 2015, this percentage rose to approximately one quarter of total calories. Over the 24 years of follow-up, urbanization and income were each strongly related to percent of calories from animal-source foods with differential association across income levels (p

In this article, we investigate group differences in phthalate exposure profiles using NHANES data. Phthalates are a family of industrial chemicals used in plastics and as solvents. There is increasing evidence of adverse health effects of exposure to phthalates on reproduction and neuro-development, and concern about racial disparities in exposure. We would like to identify a single set of low-dimensional factors summarizing exposure to different chemicals, while allowing differences across groups. Improving on current multi-group additive factor models, we propose a class of Perturbed Factor Analysis (PFA) models that assume a common factor structure after perturbing the data via multiplication by a group-specific matrix. Bayesian inference algorithms are defined using a matrix normal hierarchical model for the perturbation matrices. The resulting model is just as flexible as current approaches in allowing arbitrarily large differences across groups but has substantial advantages that we illustrate in simulation studies. Applying PFA to NHANES data, we learn common factors summarizing exposures to phthalates, while showing clear differences across groups.

In low-resource settings where vital registration of death is not routine it is often of critical interest to determine and study the cause of death (COD) for individuals and the cause-specific mortality fraction (CSMF) for populations. Post-mortem autopsies, considered the gold standard for COD assignment, are often difficult or impossible to implement due to deaths occurring outside the hospital, expense and/or cultural norms. For this reason, verbal autopsies (VAs) are commonly conducted, consisting of a questionnaire administered to next of kin recording demographic information, known medical conditions, symptoms and other factors for the decedent. This article proposes a novel class of hierarchical factor regression models that avoid restrictive assumptions of standard methods, allow both the mean and covariance to vary with COD category, and can include covariate information on the decedent, region or events surrounding death. Taking a Bayesian approach to inference, this work develops an MCMC algorithm and validates the FActor Regression for Verbal Autopsy (FARVA) model in simulation experiments. An application of FARVA to real VA data shows improved goodness-of-fit and better predictive performance in inferring COD and CSMF over competing methods. Code and a user manual are made available at https://github.com/kelrenmor/farva.

OBJECTIVE: To examine the association between neonatal jaundice and autism spectrum disorder (ASD) and non-ASD developmental disorder (DD). STUDY DESIGN: We analyzed data from the Study to Explore Early Development, a US multisite, case-control study conducted from 2007 to 2011. Developmental assessment classified children aged 2–5 years into: ASD (n= 636), DD (n= 777), or controls (POP; n= 926). Neonatal jaundice (n= 1054) was identified from medical records and maternal interviews. We examined associations between neonatal jaundice and ASD and DD using regression models to obtain adjusted odds ratios (aOR). RESULTS: Our results showed interaction between gestational age and neonatal jaundice. Neonatal jaundice was associated with ASD at 35–37 weeks (aOR = 1.83, 95%CI 1.05, 3.19), but not ≥38 weeks gestation (aOR = 0.97, 95%CI 0.76, 1.24). Similar results were observed with DD. CONCLUSIONS: Further exploration of timing and severity of neonatal jaundice and ASD/DD is warranted.

Previous studies have shown complications of pregnancy, often examined in aggregate, to be associated with autism spectrum disorder (ASD). Results for specific complications, such as maternal diabetes and hypertension, have not been uniformly consistent and should be investigated independently in relation to ASD in a large community-based sample. The Study to Explore Early Development (SEED), a US multisite case-control study, enrolled children born in 2003-2006 at 2-5 years of age. Children were classified into three groups based on confirmation of ASD (n = 698), non-ASD developmental delay (DD; n = 887), or controls drawn from the general population (POP; n = 979). Diagnoses of any diabetes or hypertensive disorder during pregnancy were identified from prenatal medical records and maternal self-report. Logistic regression models estimated adjusted odds ratios (aOR) and confidence intervals (CI) adjusting for maternal age, race/ethnicity, education, smoking during pregnancy, and study site. Models for hypertension were additionally adjusted for parity and plurality. Among 2,564 mothers, we identified 246 (9.6%) with any diabetes and 386 (15.1%) with any hypertension in pregnancy. After adjustment for covariates, any diabetes during pregnancy was not associated with ASD (aOR = 1.10 [95% CI 0.77, 1.56]), but any hypertension was associated with ASD (aOR = 1.69 [95% CI 1.26, 2.26]). Results were similar for DD, and any diabetes (aOR = 1.29 [95% CI 0.94, 1.78]) or any hypertension (aOR = 1.71 [95% CI 1.30, 2.25]). Some pregnancy complications, such as hypertension, may play a role in autism etiology and can possibly serve as a prompt for more vigilant ASD screening efforts. Autism Res 2019, 12: 967-975. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: We studied if common complications in pregnancy are associated with autism spectrum disorder (ASD) in a large sample of mothers and children. Our results show an association between conditions marked by high blood pressure and ASD, but no association with conditions marked by high blood sugar and ASD. Associations were similar for children who had a developmental disorder that was not ASD, suggesting that this relationship may not be specific to ASD.

Summary Modelling and computation for multivariate longitudinal surveys have proven challenging, particularly when data are not all continuous and Gaussian but contain discrete measurements. In many social science surveys, study participants are selected via complex survey designs such as stratified random sampling, leading to discrepancies between the sample and population, which are further compounded by missing data and loss to follow-up. Survey weights are typically constructed to address these issues, but it is not clear how to include them in models. Motivated by data on sexual development, we propose a novel non-parametric approach for mixed scale longitudinal data in surveys. In the approach proposed, the mixed scale multivariate response is expressed through an underlying continuous variable with dynamic latent factors inducing time varying associations. Bias from the survey design is adjusted for in posterior computation relying on a Markov chain Monte Carlo algorithm. The approach is assessed in simulation studies and applied to the National Longitudinal Study of Adolescent to Adult Health.

OBJECTIVES: Population-based recruitment of a cohort of women who are currently pregnant or who may become pregnant in a given timeframe presents challenges unique to identifying pregnancy status or the likelihood of future pregnancy. Little is known about the performance of individual eligibility items on pregnancy screeners although they are critical to participant recruitment. This paper examined the patterns and respondent characteristics of key pregnancy screener items used in a large national study. METHODS: Cross-sectional analyses were conducted. Descriptive statistics and multivariable logistic regression models were used to examine nonresponse patterns to three questions (currently pregnant, trying to get pregnant and able to get pregnant). The questions were asked of 50,529 women in 17 locations across the U.S., as part of eligibility screening for the National Children’s Study Vanguard Study household-based recruitment. RESULTS: Most respondents were willing to provide information about current pregnancy, trying, and able to get pregnant: 99.3% of respondents answered all three questions and 97.4% provided meaningful answers. Nonresponse ranged from 0.3% to 2.5% for individual items. Multivariable logistic regression results identified small but statistically significant differences in nonresponse by respondent age, marital status, race/ethnicity-language, and household-based recruitment group. CONCLUSIONS FOR PRACTICE: The high levels of response to pregnancy-related items are impressive considering that the eligibility questions were fairly sensitive, were administered at households, and were not part of a respondent-initiated encounter.

Background Prenatal phthalate exposure has been linked with altered neurodevelopment, including externalizing behaviors and attention-deficit hyperactivity disorder (ADHD). However, the implicated metabolite, neurobehavioral endpoint, and child sex have not always been consistent across studies, possibly due to heterogeneity in neurodevelopmental instruments. The complex set of findings may be synthesized using executive function (EF), a construct of complex cognitive processes that facilitate ongoing goal-directed behaviors. Impaired EF can be presented with various phenotypes of poor neurodevelopment, differently across structured conditions, home/community, or preschool/school. We evaluated the relationship between prenatal phthalate exposure and comprehensive assessment of preschool EF. Methods Our study comprised 262 children with clinically significant/subthreshold ADHD symptoms and 78 typically developing children who were born between 2003 and 2008 and participated in the Preschool ADHD Substudy, which is nested within a population-based prospective cohort study, the Norwegian Mother, Father, and Child Cohort (MoBa). Twelve phthalate metabolites were measured from urine samples that their mothers had provided during pregnancy, at 17 weeks’ gestation. All children, at approximately 3.5-years, took part in a detailed clinical assessment that included parent-and teacher-rated inventories and administered tests. We used instruments that measured constructs related to EF, which include a parent-and teacher-reported Behavior Rating Inventory of Executive Function-Preschool (BRIEF-P) and three performance-based tests: A Developmental NEuroPSYchological Assessment (NEPSY), Stanford-Binet intelligence test V (SB5), and the cookie delay task (CDT). The standard deviation change in test score per interquartile range (IQR) increase in phthalate metabolite was estimated with multivariable linear regression. We applied weighting in all models to account for the oversampling of children with clinically significant or subthreshold symptoms of ADHD. Additionally, we assessed modification by child sex and potential co-pollutant confounding. Results Elevated exposure to mono-benzyl phthalate (MBzP) during pregnancy was associated with poorer EF, across all domains and instruments, in both sex. For example, an IQR increase in MBzP was associated with poorer working memory rated by parent (1.23 [95% CI: 0.20, 2.26]) and teacher (1.13 [0.14, 2.13]) using BRIEF-P, and administered tests such as SB5 (no-verbal: 0.19 [0.09, 0.28]; verbal: 0.13 [0.01, 0.25]). Adverse associations were also observed for mono-n-butyl phthalate (MnBP) and mono-iso-butyl phthalate (MiBP), although results varied by instruments. EF domains reported by parents using BRIEF-P were most apparently implicated, with stronger associations among boys (e.g., MnBP and inhibition: 2.74 [1.77, 3.72]; MiBP and inhibition: 1.88 [0.84, 2.92]) than among girls (e.g., MnBP and inhibition: −0.63 [−2.08, 0.83], interaction p-value: 0.04; MiBP and inhibition: −0.15 [−1.04, 0.74], interaction p-value: 0.3). Differences by sex, however, were not found for the teacher-rated BRIEF-P or administered tests including NEPSY, SB5, and CDT. Conclusion and relevance Elevated mid-pregnancy MBzP, MiBP, and MnBP were associated with more adverse profiles of EF among preschool-aged children across a range of instruments and raters, with some associations found only among boys. Given our findings and accumulating evidence of the prenatal period as a critical window for phthalate exposure, there is a timely need to expand the current phthalate regulations focused on baby products to include pregnancy exposures.

There is a very rich literature proposing Bayesian approaches for clustering starting with a prior probability distribution on partitions. Most approaches assume exchangeability, leading to simple representations in terms of Exchangeable Partition Probability Functions (EPPF). Gibbs-type priors encompass a broad class of such cases, including Dirichlet and Pitman-Yor processes. Even though there have been some proposals to relax the exchangeability assumption, allowing covariate-dependence and partial exchangeability, limited consideration has been given on how to include concrete prior knowledge on the partition. For example, we are motivated by an epidemiological application, in which we wish to cluster birth defects into groups and we have prior knowledge of an initial clustering provided by experts. As a general approach for including such prior knowledge, we propose a Centered Partition (CP) process that modifies the EPPF to favor partitions close to an initial one. Some properties of the CP prior are described, a general algorithm for posterior computation is developed, and we illustrate the methodology through simulation examples and an application to the motivating epidemiology study of birth defects.

We aim to infer bioactivity of each chemical by assay endpoint combination, addressing sparsity of toxicology data. We propose a Bayesian hierarchical framework which borrows information across different chemicals and assay endpoints, facilitates out-of-sample prediction of activity for chemicals not yet assayed, quantifies uncertainty of predicted activity, and adjusts for multiplicity in hypothesis testing. Furthermore, this paper makes a novel attempt in toxicology to simultaneously model heteroscedastic errors and a nonparametric mean function, leading to a broader definition of activity whose need has been suggested by toxicologists. Real application identifies chemicals most likely active for neurodevelopmental disorders and obesity.

BACKGROUND: Latent class models (LCMs) have been used in exploring dietary behaviors over a wide set of foods and beverages in a given population, but are prone to overgeneralize these habits in the presence of variation by subpopulations. OBJECTIVES: This study aimed to highlight unique dietary consumption differences by both study site and ethnic background of Hispanic/Latino populations in the United States, that otherwise might be missed in a traditional LCM of the overall population. This was achieved using a new model-based clustering method, referred to as robust profile clustering (RPC). METHODS: A total of 11,320 individuals aged 18–74 y from the Hispanic Community Health Study/Study of Latinos (2008–2011) with complete diet data were classified into 9 subpopulations, defined by study site (Bronx, Chicago, Miami, San Diego) and ethnic background. At baseline, dietary intake was ascertained using a food propensity questionnaire. Dietary patterns were derived from 132 food groups using the RPC method to identify patterns of the general Hispanic/Latino population and those specific to an identified subpopulation. Dietary patterns derived from the RPC were compared to those identified from an LCM. RESULTS: The LCM identified 48 shared consumption behaviors of foods and beverages across the entire cohort, whereas significant consumption differences in subpopulations were identified in the RPC model for these same foods. Several foods were common within study site (e.g., chicken, orange juice, milk), ethnic background (e.g., papayas, plantain, coffee), or both (e.g., rice, tomatoes, seafood). Post hoc testing revealed an improved model fit in the RPC model [Deviance Information Criterion DIC(RPC) = 2.3 × 10(4), DIC(LCM) = 9.5 × 10(6)]. CONCLUSIONS: Dietary pattern behaviors of Hispanics/Latinos in the United States tend to align by ethnic background for some foods and by location for other foods. Consideration of both factors is imperative to better understand their contributions to population health and developing targeted nutrition intervention studies.

To compare receipt of contraception and method effectiveness in the early postpartum period among women with and without a recent preterm birth (PTB). We used data from North Carolina birth certificates linked to Medicaid claims. We assessed contraceptive claims with dates of service within 90 days of delivery among a retrospective cohort of women who had a live birth covered by Medicaid between September 2011 and 2012 (n = 58,201). To estimate the odds of receipt of contraception by PTB status (24–36 weeks compared to 37–42 weeks [referent]), we used logistic regression and tested for interaction by parity. To estimate the relationship between PTB and method effectiveness based on the Center for Disease Control and Prevention Levels of Effectiveness of Family Planning Methods (most, moderate and least effective [referent]), we used multinomial logistic regression. Less than half of all women with a live birth covered by Medicaid in North Carolina had a contraceptive claim within 90 days postpartum. Women with a recent PTB had a lower prevalence of contraceptive receipt compared to women with a term birth (45.7% vs. 49.6%). Women who experienced a PTB had a lower odds of receiving contraception. When we stratified by parity, women with a PTB had a lower odds of contraceptive receipt among women with more than two births (0.79, 95% CI 0.74–0.85), but not among women with two births or fewer. One-fourth of women received a most effective method. Women with a preterm birth had a lower odds of receiving a most effective method (0.83, 95% CI 0.77–0.88) compared to women with a term birth. Contraceptive receipt was low among women with a live birth covered by Medicaid in North Carolina. To optimize contraceptive use among women at risk for subsequent preterm birth, family planning strategies that are responsive to women’s priorities and context, including a history of preterm birth, are needed. Access to free or affordable highly effective contraception is associated with reductions in preterm birth. Self-report data indicate that women with a very preterm birth (PTB) are less likely to use highly or moderately effective contraception postpartum compared to women delivering at later gestational ages. Using Medicaid claims data, we found that less than half of all women with a Medicaid covered delivery in North Carolina in 2011–2012 had a contraceptive claim within 90 days postpartum, and one fourth received a most effective method. Women with a PTB and more than two children were least likely to receive any method. Family planning strategies that are responsive to women’s priorities and context, including a history of preterm birth, are needed so that women may access their contraceptive method of choice in the postpartum period.

In epidemiology, it is often of interest to assess how individuals with different trajectories over time in an environmental exposure or biomarker differ with respect to a continuous response. For ease in interpretation and presentation of results, epidemiologists typically categorize predictors prior to analysis. To extend this approach to time-varying predictors, one can cluster individuals by their predictor trajectory, with the cluster index included as a predictor in a regression model for the response. This article develops a semiparametric Bayes approach, which avoids assuming a pre-specified number of clusters and allows the response to vary nonparametrically over predictor clusters. This methodology is motivated by interest in relating trajectories in weight gain during pregnancy to the distribution of birth weight adjusted for gestational age at delivery. In this setting, the proposed approach allows the tails of the birth weight density to vary flexibly over weight gain clusters.

Unlike zero-inflated Poisson regression, marginalized zero-inflated Poisson (MZIP) models for counts with excess zeros provide estimates with direct interpretations for the overall effects of covariates on the marginal mean. In the presence of missing covariates, MZIP and many other count data models are ordinarily fitted using complete case analysis methods due to lack of appropriate statistical methods and software. This article presents an estimation method for MZIP models with missing covariates. The method, which is applicable to other missing data problems, is illustrated and compared with complete case analysis by using simulations and dental data on the caries preventive effects of a school-based fluoride mouthrinse program.

Background Contemporary human populations are exposed to elevated concentrations of organophosphate esters (OPEs) and phthalates. Some metabolites have been linked with altered thyroid function, however, inconsistencies exist across thyroid function biomarkers. Research on OPEs is sparse, particularly during pregnancy, when maintaining normal thyroid function is critical to maternal and fetal health. In this paper, we aimed to characterize relationships between OPEs and phthalates exposure and maternal thyroid function during pregnancy, using a cross-sectional investigation of pregnant women nested within the Norwegian Mother, Father, and Child Cohort (MoBa). Methods We included 473 pregnant women, who were euthyroid and provided bio-samples at 17 weeks' gestation (2004–2008). Four OPE and six phthalate metabolites were measured from urine; six thyroid function biomarkers were estimated from blood. Relationships between thyroid function biomarkers and log-transformed concentrations of OPE and phthalate metabolites were characterized using two approaches that both accounted for confounding by co-exposures: co-pollutant adjusted general linear model (GLM) and Bayesian Kernal Machine Regression (BKMR). Results We restricted our analysis to common-detect OPE and phthalate metabolites (>94%): diphenyl phosphate (DPHP), di-n-butyl phosphate (DNBP), and all phthalate metabolites. In GLM, pregnant women with summed di-isononyl phthalate metabolites (∑DiNP) concentrations in the 75th percentile had a 0.37 ng/μg lower total triiodothyronine (TT3): total thyroxine (TT4) ratio (95% credible interval: [−0.59, −0.15]) as compared to those in the 25th percentile, possibly due to small but diverging influences on TT3 (−1.99 ng/dL [−4.52, 0.53]) and TT4 (0.13 μg/dL [−0.01, 0.26]). Similar trends were observed for DNBP and inverse associations were observed for DPHP, monoethyl phthalate, mono-isobutyl phthalate, and mono-n-butyl phthalate. Most associations observed in co-pollutants adjusted GLMs were attenuated towards the null in BKMR, except for the case of ∑DiNP and TT3:TT4 ratio (−0.48 [−0.96, 0.003]). Conclusions Maternal thyroid function varied modestly with ∑DiNP, whereas results for DPHP varied by the type of statistical models.

Neurodevelopmental outcomes including behavior, executive functioning, and IQ exhibit complex correlational structures, although they are often treated as independent in etiologic studies. We performed a principal components analysis of the behavioral assessment system for children, the behavior rating inventory of executive functioning, and the Wechsler scales of intelligence in a prospective birth cohort, and estimated associations with early life characteristics. We identified seven factors: (1) impulsivity and externalizing, (2) executive functioning, (3) internalizing, (4) perceptual reasoning, (5) adaptability, (6) processing speed, and (7) verbal intelligence. Prenatal fish consumption, maternal education, preterm birth, and the home environment were important predictors of various neurodevelopmental factors. Although maternal smoking was associated with more adverse externalizing, executive functioning, and adaptive composite scores in our sample, of the orthogonally-rotated factors, smoking was only associated with the impulsivity and externalizing factor ( $$\hat{\beta}$$ − 0.82, 95% CI − 1.42, − 0.23). These differences may be due to correlations among outcomes that were accounted for by using a phenotypic approach. Dimension reduction may improve upon traditional approaches by accounting for correlations among neurodevelopmental traits.

Prenatal exposure to organophosphorus pesticides (OPs) has been associated with different neurodevelopmental outcomes across different cohorts. A phenotypic approach may address some of these differences by incorporating information across scales and accounting for the complex correlational structure of neurodevelopmental outcomes. Additionally, Bayesian hierarchical modeling can account for confounding by collinear co-exposures. We use this framework to examine associations between prenatal exposure to OPs and behavior, executive functioning, and IQ assessed at age 6-9 years in a cohort of 404 mother/infant pairs recruited during pregnancy. We derived phenotypes of neurodevelopment with a factor analysis, and estimated associations between OP metabolites and these phenotypes in Bayesian hierarchical models for exposure mixtures. We report seven factors: 1) Impulsivity and Externalizing, 2) Executive Functioning, 3) Internalizing, 4) Perceptual Reasoning, 5) Adaptability, 6) Processing Speed, and 7) Verbal Intelligence. These, along with the Working Memory Index, were standardized and scaled so that positive values reflected positive attributes and negative values represented adverse outcomes. Standardized dimethylphosphate metabolites were negatively associated with Internalizing factor scores (β^ - 0.13, 95% CI - 0.26, 0.00) but positively associated with Executive Functioning factor scores (β^ 0.18, 95% CI 0.04, 0.31). Standardized diethylphosphate metabolites were negatively associated with the Working Memory Index (β^ - 0.17, 95% CI - 0.33, - 0.03). Associations with factor scores were generally stronger and more precise than associations with individual instrument-specific items. Factor analysis of outcomes may provide some advantages in etiological studies of childhood neurodevelopment by incorporating information across scales to reduce dimensionality and improve precision.

SummaryWe consider shape-restricted nonparametric regression on a closed set $\mathcal{X} \subset \mathbb{R},$ where it is reasonable to assume that the function has no more than $H$ local extrema interior to $\mathcal{X}$. Following a Bayesian approach we develop a nonparametric prior over a novel class of local extremum splines. This approach is shown to be consistent when modelling any continuously differentiable function within the class considered, and we use itto develop methods for testing hypotheses on the shape of the curve. Sampling algorithms are developed, and the method is applied in simulation studies and data examples where the shape of the curve is of interest.

Introduction Daily or weekly averages of physical activity and sedentary behavior could mask patterns of behavior throughout the week that independently affect cardiovascular health. We examined associations between day-to-day physical activity and sedentary behavior latent classes and cardiovascular disease (CVD) risk factors in U.S. youth. Methods Data were from 3984 youth ages 6-17 yr from the National Health and Nutrition Examination Survey (2003-2006) and from previously published accelerometry latent classes characterizing average counts per minute and percent of wear time in moderate-to-vigorous physical activity (MVPA) and sedentary behavior. Multiple linear regression was used to examine associations of the classes with waist circumference, systolic and diastolic blood pressure, HDL-C and LDL-C, triglycerides, glucose, and insulin. Results Participants spent 50.4% of the day in sedentary behavior and 5.3% of the day in moderate-to-vigorous physical activity. Average counts per minute were 516.4 for a 7-d period. Significant differences in CVD risk factors were between extreme classes with few differences observed in intermediate classes. Youth in latent class 4 (highest average counts per minute) had lower systolic blood pressure (-4.11 mm Hg, 95% confidence interval [CI] = -7.74 to -0.55), lower glucose (-4.25 mg·dL, 95% CI = -7.84 to -0.66]), and lower insulin (-6.83 μU·mL, 95% CI = -8.66 to -4.99]) compared with youth in class 1 (lowest average counts per minute). Waist circumference was lower for the least sedentary class (-2.54 cm, 95% CI = -4.90 to -0.19) compared with the most sedentary class. Some associations were attenuated when classes were adjusted for mean physical activity or sedentary level. Conclusions There is some indication that patterns, in addition to the total amount of physical activity and sedentary behavior, may be important for cardiovascular health in youth. Longitudinal studies are needed to examine associations between physical activity and sedentary behavior patterns and changes in CVD risk factors.

Background: Little is known about intergenerational differences in associations of urbanization-related lifestyle behaviors with cardiometabolic risk factors in children and their parents in rapidly urbanizing China.Objective: We tested the intergenerational differences in longitudinal associations of away-from-home eating, snacking, screen time, and leisure-time sports with high waist-to-height ratio (WHtR), elevated blood pressure (BP), elevated glycated hemoglobin (HbA1c), and elevated C-reactive protein (CRP) among Chinese children and their parents.Design: We studied children enrolled in the longitudinal China Health and Nutrition Survey (1991-2009, 7 surveys) aged 7-17 y in ≥2 surveys (average follow-up: 2.3 surveys out of a possible 4 surveys with the age restriction; n = 3875, including 1175 siblings) and their parents (2947 mothers, 2632 fathers) living in the same household. We used 3 consecutive interviewer-administered 24-h dietary recalls to derive a 3-d average for away-from-home eating (nonconsumer, >0 and 1 and ≤2, or >2 h/d) and leisure-time sports (any or none). Random-effects logistic regression was used to examine the associations of lagged (average: 3 y) behaviors with cardiometabolic risk factors (WHtR, BP, HbA1c, and CRP).Results: We detected intergenerational differences in associations between lagged behaviors and risk factors (P-interaction 2 compared with ≤1 h/d) was positively associated with parents' (OR: 2.58; 95% CI: 1.56, 4.28) and children's high WHtR (OR: 2.26; 95% CI: 1.06, 4.83).Conclusion: Parent-offspring differences in associations between lifestyle behaviors and cardiometabolic risk factors provide insight into intergenerational differences in cardiometabolic risk with urbanization.

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.

Background While chronic kidney disease (CKD) is a growing public health concern in low- and middle-income countries, such as China, few studies have investigated the association between urbanization and the occurrence of CKD in those countries. Methods We investigated the association between urbanization and estimated glomerular filtration rate (eGFR), an important CKD risk marker. Data came from the China Health and Nutrition Survey wave 2009, in which we collected fasting serum, individual and household data along with community level urbanization data, which was used to derive a study-specific urbanization measure, in 218 communities across nine provinces. A total of 3644 men and 4154 women participants aged 18 years or older were included in the analysis. Reduced renal function was defined as eGFR of less than 60 mL/min/1.73 m2 measured using serum creatinine concentration (mg/dL). Results After adjusting for socio-demographic (e.g., age, education and household income), a sex-stratified multilevel logistic model revealed that living in a more urbanized community was associated with higher odds of reduced eGFR (odds ratio [OR] = 1.38 per one-standard deviation [SD] increase in the CHNS specific urbanization index, 95% confidence interval [CI] = 1.11–1.73 for men; OR = 1.35, 95% CI = 1.11–1.62 for women). After adjusting for behavioral variables (i.e., alcohol consumption, smoking, physical activity and diet), as well as obesity and cardiometabolic risk factors, the association was attenuated in men (OR = 1.25, 95% CI = 0.98–1.59), but remained statistically significant in women (OR = 1.24, 95% CI = 1.01–1.52). Conclusion Our findings suggest that living in an urban environment is linked with higher odds of reduced renal function independently of behavioral and cardiometabolic risk factors, which have been shown to increase along with urbanization. Electronic supplementary material The online version of this article (doi:10.1186/s12882-017-0577-7) contains supplementary material, which is available to authorized users.

It is hypothesized that certain chemicals in personal care products may alter the risk of adverse health outcomes. The primary aim of this study was to use a data-centered approach to classify complex patterns of exposure to personal care products and to understand how these patterns vary according to use of exogenous hormone exposures, oral contraceptives (OCs) and post-menopausal hormone therapy (HT). The NIEHS Sister Study is a prospective cohort study of 50,884 US women. Limiting the sample to non-Hispanic blacks and whites (N = 47,019), latent class analysis (LCA) was used to identify groups of individuals with similar patterns of personal care product use based on responses to 48 survey questions. Personal care products were categorized into three product types (beauty, hair, and skincare products) and separate latent classes were constructed for each type. Adjusted prevalence differences (PD) were calculated to estimate the association between exogenous hormone use, as measured by ever/never OC or HT use, and patterns of personal care product use. LCA reduced data dimensionality by grouping of individuals with similar patterns of personal care product use into mutually exclusive latent classes (three latent classes for beauty product use, three for hair, and four for skin care. There were strong differences in personal care usage by race, particularly for haircare products. For both blacks and whites, exogenous hormone exposures were associated with higher levels of product use, especially beauty and skincare products. Relative to individual product use questions, latent class variables capture complex patterns of personal care product usage. These patterns differed by race and were associated with ever OC and HT use. Future studies should consider personal care product exposures with other exogenous exposures when modeling health risks.

Background: Organophosphate compounds are commonly used in residential furniture, electronics, and baby products as flame retardants and are also used in other consumer products as plasticizers. Although the levels of exposure biomarkers are generally higher among children and decrease with age, relatively little is known about the individual characteristics associated with higher levels of exposure. Here, we investigate urinary metabolites of several organophosphate flame retardants (PFRs) in a cohort of pregnant women to evaluate patterns of exposure. Methods: Pregnant North Carolina women (n = 349) provided information on their individual characteristics (e.g. age and body mass index (BMI)) as a part of the Pregnancy Infection and Nutrition Study (2002–2005). Women also provided second trimester urine samples in which six PFR metabolites were measured using mass spectrometry methods. Results: PFR metabolites were detected in every urine sample, with BDCIPP, DHPH, ip-PPP and BCIPHIPP detected in >80% of samples. Geometric mean concentrations were higher than what has been reported previously for similarly-timed cohorts. Women with higher pre-pregnancy BMI tended to have higher levels of urinary metabolites. For example, those classified as obese at the start of pregnancy had ip-PPP levels that were 1.52 times as high as normal weight range women (95% confidence interval: 1.23, 1.89). Women without previous children also tended to have higher urinary levels of DPHP, but lower levels of ip-PPP. In addition, we saw strong evidence of seasonal trends in metabolite concentrations (e.g. higher DPHP, BDCIPP, and BCIPHIPP in summer, and evidence of increasing ip-PPP between 2002 and 2005). Conclusions: Our results indicate ubiquitous exposure to PFRs among NC women in the early 2000s. Additionally, our work suggests that individual characteristics are related to exposure and that temporal variation, both seasonal and annual, may exist. Keywords: Organophosphate flame retardants (PFRs), Pregnancy, Exposure

Missing data due to non-wear are common in accelerometer studies measuring physical activity and sedentary behavior. Accelerometer output are high-dimensional time-series data that are episodic and often highly skewed, presenting unique challenges for handling missing data. Common methods for missing accelerometry either are ad-hoc, require restrictive parametric assumptions, or do not appropriately impute bouts. This study developed a flexible hot deck multiple imputation (MI; i.e., "replacing" missing data with observed values) procedure to handle missing accelerometry. For each missing segment of accelerometry, "donor pools" contained observed segments from either the same or different participants, and 10 imputed segments were randomly drawn from the donor pool according to selection weights, where the donor pool and selection weight depended on variables associated with non-wear and/or accelerometer-based measures. A simulation study of 2,550 women compared hot deck MI to two standard methods in the field: available case (AC) analysis (i.e., analyzing all observed accelerometry with no restriction on wear time or number of days) and complete case (CC) analysis (i.e., analyzing only participants that wore the accelerometer for ≥10 hours for 4-7 days). This was repeated using accelerometry from the entire 24-hour day and daytime (10am- 8pm) only, and data were missing at random. For the entire 24-hour day, MI produced less bias and better 95% confidence interval (CI) coverage than AC and CC. For the daytime only, MI produced less bias and better 95% CI coverage than AC; CC produced similar bias and 95% CI coverage, but longer 95% CIs than MI.

The National Birth Defects Prevention Study (NBDPS) is a case-control study of birth defects conducted across 10 U.S. states. Researchers are interested in characterizing the etiologic role of maternal diet, collected using a food frequency questionnaire. Because diet is multi-dimensional, dimension reduction methods such as cluster analysis are often used to summarize dietary patterns. In a large, heterogeneous population, traditional clustering methods, such as latent class analysis, used to estimate dietary patterns can produce a large number of clusters due to a variety of factors, including study size and regional diversity. These factors result in a loss of interpretability of patterns that may differ due to minor consumption changes. Based on adaptation of the local partition process, we propose a new method, Robust Profile Clustering, to handle these data complexities. Here, participants may be clustered at two levels: (1) globally, where women are assigned to an overall population-level cluster via an overfitted finite mixture model, and (2) locally, where regional variations in diet are accommodated via a beta-Bernoulli process dependent on subpopulation differences. We use our method to analyze the NBDPS data, deriving pre-pregnancy dietary patterns for women in the NBDPS while accounting for regional variability., 45 pages, 6 figures

PURPOSE: Studies suggest exposure to ambient particulate matter less than 2.5 μg/m(3) in aerodynamic diameter (PM(2.5)) may be associated with preterm birth (PTB), but few have evaluated how this is modified by ambient temperature. We investigated the relationship between PM(2.5) exposure during pregnancy and PTB in infants without birth defects (1999–2006) and enrolled in the National Birth Defects Prevention Study and how it is modified by concurrent temperature. METHODS: PTB was defined as spontaneous or iatrogenic delivery before 37 weeks. Exposure was assigned using inverse distance weighting with up to four monitors within 50 kilometers of maternal residence. To account for state-level variations, a Bayesian two-level hierarchal model was developed. RESULTS: PTB was associated with PM(2.5) during the third and fourth months of pregnancy (range: (odds ratio (95% confidence interval) = 1.00 (0.35, 2.15) to 1.49 (0.82, 2.68) and 1.31 (0.56, 2.91) to 1.62 (0.7, 3.32), respectively); no week of exposure conveyed greater risk. Temperature may modify this relationship; higher local average temperatures during pregnancy yielded stronger positive relationships between PM(2.5) and PTB compared to nonstratified results. CONCLUSIONS: Results add to literature on associations between PM(2.5) and PTB, underscoring the importance of considering co-exposures when estimating effects of PM(2.5) exposure during pregnancy.

Today there are approximately 85,000 chemicals regulated under the Toxic Substances Control Act, with around 2,000 new chemicals introduced each year. It is impossible to screen all of these chemicals for potential toxic effects either via full organism in vivo studies or in vitro high-throughput screening (HTS) programs. Toxicologists face the challenge of choosing which chemicals to screen, and predicting the toxicity of as-yet-unscreened chemicals. Our goal is to describe how variation in chemical structure relates to variation in toxicological response to enable in silico toxicity characterization designed to meet both of these challenges. With our Bayesian partially Supervised Sparse and Smooth Factor Analysis ($\text{BS}^3\text{FA}$) model, we learn a distance between chemicals targeted to toxicity, rather than one based on molecular structure alone. Our model also enables the prediction of chemical dose-response profiles based on chemical structure (that is, without in vivo or in vitro testing) by taking advantage of a large database of chemicals that have already been tested for toxicity in HTS programs. We show superior simulation performance in distance learning and modest to large gains in predictive ability compared to existing methods. Results from the high-throughput screening data application elucidate the relationship between chemical structure and a toxicity-relevant high-throughput assay. An R package for $\text{BS}^3\text{FA}$ is available online at https://github.com/kelrenmor/bs3fa.