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

Maria José Rosa, Ashley Pajak, Allan C. Just, Perry E. Sheffield, Itai Kloog, Joel Schwartz, Brent Coull, Michelle Bosquet Enlow, Andrea A. Baccarelli, Kathi Huddleston, John E. Niederhuber, Martha María Téllez Rojo, Robert O. Wright, Chris Gennings, Rosalind J. Wright

Research output: Contribution to journalArticlepeer-review

31 Scopus citations


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 μm 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 μg/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.

Original languageEnglish
Pages (from-to)173-180
Number of pages8
JournalEnvironment international
StatePublished - 1 Jan 2017


  • Air pollution
  • Birth weight
  • Propensity scores

ASJC Scopus subject areas

  • General Environmental Science


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