Dataset Information

Prenatal exposure to PM2.5 and birth weight: A pooled analysis from three North American longitudinal pregnancy cohort studies.

ABSTRACT: A common practice when analyzing multi-site epidemiological data is to include a term for 'site' to account for unmeasured effects at each location. This practice should be carefully considered when site can have complex relationships with important demographic and exposure variables. We leverage data from three longitudinal North American pregnancy cohorts to demonstrate a novel method to assess study heterogeneity and potential combinability of studies for pooled analyses in order to better understand how to consider site in analyses. Results from linear regression and fixed effects meta-regression models run both prior to and following the proposed combinability analyses were compared. In order to exemplify this approach, we examined associations between prenatal exposure to particulate matter and birth weight. Analyses included mother-child dyads (N=1966) from the Asthma Coalition on Community Environment and Social Stress (ACCESS) Project and the PRogramming of Intergenerational Stress Mechanisms (PRISM) study in the northeastern United States, and the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study in Mexico City. Mothers' daily third trimester exposure to particulate matter?2.5?m in diameter (PM2.5) was estimated using a validated satellite-based spatio-temporally resolved model in all studies. Fenton birth weight for gestational age z-scores were calculated. Linear regression analyses within each cohort separately did not find significant associations between PM2.5 averaged over the third trimester and Fenton z-scores. The initial meta-regression model also did not find significant associations between prenatal PM2.5 and birthweight. Next, propensity scores and log linear models were used to assess higher order interactions and determine if sites were comparable with regard to sociodemographics and other covariates; these analyses demonstrated that PROGRESS and ACCESS were combinable. Adjusted linear regression models including a 2-level site variable according to the pooling indicated by the log linear models (ACCESS and PROGRESS as one level and PRISM as another) revealed that a 5?g/m3 increase in PM2.5 was associated with a 0.075 decrease in Fenton z-score (p<0.0001); linear models including a 3-level site variable did not reveal significant associations. By assessing the combinability of heterogeneous populations prior to combining data using a method that more optimally accounts for underlying cohort differences, we were able to identify significant associations between prenatal PM2.5 exposure and birthweight that were not detected using standard methods.

SUBMITTER: Rosa MJ

PROVIDER: S-EPMC5568041 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Publications

Prenatal exposure to PM<sub>2.5</sub> and birth weight: A pooled analysis from three North American longitudinal pregnancy cohort studies.

Rosa Maria José MJ Pajak Ashley A Just Allan C AC Sheffield Perry E PE Kloog Itai I Schwartz Joel J Coull Brent B Enlow Michelle Bosquet MB Baccarelli Andrea A AA Huddleston Kathi K Niederhuber John E JE Rojo Martha María Téllez MMT Wright Robert O RO Gennings Chris C Wright Rosalind J RJ

Environment international 20170722

A common practice when analyzing multi-site epidemiological data is to include a term for 'site' to account for unmeasured effects at each location. This practice should be carefully considered when site can have complex relationships with important demographic and exposure variables. We leverage data from three longitudinal North American pregnancy cohorts to demonstrate a novel method to assess study heterogeneity and potential combinability of studies for pooled analyses in order to better un ...[more]

PMID: 28738263

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Project description:Organophosphorous (OP) pesticides are associated with reduced fetal growth in animals, but human studies are inconsistent.We pooled data from four cohorts to examine associations of prenatal OP exposure with birth weight (n = 1,169), length (n = 1,152), and head circumference (n = 1,143).Data were from the CHAMACOS, HOME, Columbia, and Mount Sinai birth cohorts. Concentrations of three diethyl phosphate (?DEP) and three dimethyl phosphate (?DMP) metabolites of OP pesticides [summed to six dialkyl phosphates (?DAPs)] were measured in maternal urine. Linear regression and mixed-effects models were used to examine associations with birth outcomes.We found no significant associations of ?DEP, ?DMP, or ?DAPs with birth weight, length, or head circumference overall. However, among non-Hispanic black women, increasing urinary ?DAP and ?DMP concentrations were associated with decreased birth length (? = -0.4 cm; 95% CI: -0.9, 0.0 and ? = -0.4 cm; 95% CI: -0.8, 0.0, respectively, for each 10-fold increase in metabolite concentration). Among infants with the PON1192RR genotype, ?DAP and ?DMP were negatively associated with length (? = -0.4 cm; 95% CI: -0.9, 0.0 and ? = -0.5 cm; 95% CI: -0.9, -0.1).This study confirms previously reported associations of prenatal OP exposure among black women with decreased infant size at birth, but finds no evidence of smaller birth weight, length, or head circumference among whites or Hispanics. Contrary to our hypothesis, we found stronger inverse associations of DAPs and birth outcome in infants with the less susceptible PON1192RR genotype. The large pooled data set facilitated exploration of interactions by race/ethnicity and PON1 genotype, but was limited by differences in study populations.Harley KG, Engel SM, Vedar MG, Eskenazi B, Whyatt RM, Lanphear BP, Bradman A, Rauh VA, Yolton K, Hornung RW, Wetmur JG, Chen J, Holland NT, Barr DB, Perera FP, Wolff MS. 2016. Prenatal exposure to organophosphorous pesticides and fetal growth: pooled results from four longitudinal birth cohort studies. Environ Health Perspect 124:1084-1092; http://dx.doi.org/10.1289/ehp.1409362.

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Project description:OBJECTIVES:We applied three statistical approaches for evaluating associations between prenatal urinary concentrations of a mixture of phthalate metabolites and birth weight. METHODS:We included 300 women who provided 732 urine samples during pregnancy and delivered a singleton infant. We measured urinary concentrations of metabolites of di(2-ethylhexyl)-phthalate, di-isobutyl-, di-n-butyl-, butylbenzyl-, and diethyl phthalates. We applied 1) linear regressions; 2) classification methods [principal component analysis (PCA) and structural equation models (SEM)]; and 3) Bayesian kernel machine regression (BKMR), to evaluate associations between phthalate metabolite mixtures and birth weight adjusting for potential confounders. Data were presented as mean differences (95% CI) in birth weight (grams) as each phthalate increased from the 10th to the 90th percentile. RESULTS:When analyzing individual phthalate metabolites using linear regressions, each metabolite demonstrated a modest inverse association with birth weight [from -93 (-206, 21) to -49 (-164, 65)]. When simultaneously including all metabolites in a multivariable model, inflation of the estimates and standard errors were noted. PCA identified two principal components, both inversely associated with birth weight [-23 (-68, 22), -27 (-71, 17), respectively]. These inverse associations were confirmed when applying SEM. BKMR further identified that monoethyl and mono(2-ethylhexyl) phthalate and phthalate concentrations were linearly related to lower birth weight [-51(-164, 63) and -122 (-311, 67), respectively], and suggested no evidence of interaction between metabolites. CONCLUSIONS:While none of the methods produced significant results, we demonstrated the potential issues arising using linear regression models in the context of correlated exposures. Among the other selected approaches, classification techniques identified common sources of exposures with implications for interventions, while BKMR further identified specific contributions of individual metabolites.

Project description:Knowledge of plant architecture allows retrospective study of plant development, hence provides powerful tools, through modelling and simulation, to link this development with environmental constraints, and then predict its response to global change. The present study aims to determine some of the main endogenous and exogenous variables driving the architectural development of three North American conifers. We measured architectural traits retrospectively on the trunk, branches and twigs of whole tree crowns for each species: annual shoot length (ASL), needle length, branching patterns and reproduction organs (male and female). We fitted a partial least square (PLS) regression to explain each architectural trait with respect to topological, ontogenic and climatic variables. Results showed a significant weight of these three groups of variables for previous and current year, corresponding, respectively, to organogenesis and elongation. Topological and ontogenic variables had the greatest weight in models. Particularly, all architectural traits were strongly correlated with ASL. We highlighted a negative architectural response of two species to higher than average temperatures, whereas the third one took advantage of these higher temperatures to some degree. Tree architectural development weekly but significantly improved with higher precipitation. Our study underlines the strong weight of topology and ontogeny in tree growth patterns at twig and branch scales. The correlation between ASL and other tree architectural traits should be integrated into architectural development models. Climate variables are secondary in importance at the twig scale. However, interannual climate variations influence all axis categories and branching orders and therefore significantly impact crown development as a whole. This latter impact may increase with climate change, especially as climate affects architectural traits over at least 2 years, through organogenesis and elongation.

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Dataset Information

Prenatal exposure to PM2.5 and birth weight: A pooled analysis from three North American longitudinal pregnancy cohort studies.

Publications

Prenatal exposure to PM<sub>2.5</sub> and birth weight: A pooled analysis from three North American longitudinal pregnancy cohort studies.

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