Abstract
BACKGROUND: Single-pollutant models have linked prenatal PM(2.5) exposure to lower birthweight. However, analyzing air pollutant mixtures better captures pollutant interactions and total effects. Unfortunately, strong correlations between pollutants restrict traditional methods. OBJECTIVES: We explored the association between exposure to a mixture of air pollutants during different gestational age windows of pregnancy and birthweight. METHODS: We included 4,635 mother-infant dyads from a New York State birth cohort born 2008-2010. Air pollution data were sourced from the EPA's Community Multiscale Air Quality model and matched to the census tract centroid of each maternal home address. Birthweight and gestational age were extracted from vital records. We applied linear regression to study the association between prenatal exposure to PM(2.5), PM(10), NO(X), SO(2), and CO and birthweight during six sensitive windows. We then utilized Bayesian kernel machine regression to examine the non-linear effects and interactions within this five-pollutant mixture. Final models adjusted for maternal socio-demographics, infant characteristics, and seasonality. RESULTS: Single-pollutant linear regression models indicated that most pollutants were associated with a decrement in birthweight, specifically during the two-week window before birth. An interquartile range increase in PM(2.5) exposure (IQR: 3.3 µg/m(3)) from the median during this window correlated with a 34 g decrement in birthweight (95 % CI: -54, -14), followed by SO(2) (IQR: 2.0 ppb; β: -31), PM(10) (IQR: 4.6 µg/m(3); β: -29), CO (IQR: 60.8 ppb; β: -27), and NO(X) (IQR: 7.9 ppb; β: -26). Multi-pollutant BKMR models revealed that PM(2.5), NO(X), and CO exposure were negatively and non-linearly linked with birthweight. As the five-pollutant mixture increased, birthweight decreased until the median level of exposure. DISCUSSION: Prenatal exposure to air pollutants, notably PM(2.5), during the final two weeks of pregnancy may negatively impact birthweight. The non-linear relationships between air pollution and birthweight highlight the importance of studying pollutant mixtures and their interactions.