Prenatal Ambient Air Pollutant Mixture Exposure and Early School-age Lung Function

Methods: Analyses included 198 mother-child dyads recruited from two hospitals and affiliated community health centers in Boston, Massachusetts, USA. Daily prenatal pollutant exposures were estimated using satellite-based hybrid chemical-transport models, including nitrogen dioxide(NO), ozone(O), and fine particle constituents (elemental carbon [EC], organic carbon [OC], nitrate [NO ], sulfate [SO ], and ammonium [NH ]). Spirometry was performed at age 6.99 ± 0.89 years; forced expiratory volume in 1s (FEV), forced vital capacity (FVC), and forced mid-expiratory flow (FEF) z-scores accounted for age, sex, height, and race/ethnicity. We examined associations between weekly-averaged prenatal pollution mixture levels and outcomes using Bayesian Kernel Machine Regression-Distributed Lag Models (BKMR-DLMs) to identify susceptibility windows for each component and estimate a potentially complex mixture exposure-response relationship including nonlinear effects and interactions among exposures. We also performed linear regression models using time-weighted-mixture component levels derived by BKMR-DLMs adjusting for maternal age, education, perinatal smoking, and temperature.

Results: Most mothers were Hispanic (63%) or Black (21%) with ≤12 years of education (67%). BKMR-DLMs identified a significant effect for O exposure at 18-22 weeks gestation predicting lower FEV/FVC. Linear regression identified significant associations for O NH , and OC with decreased FEV/FVC, FEV, and FEF, respectively. There was no evidence of interactions among pollutants.

Conclusions: In this multi-pollutant model, prenatal O, OC, and NH were most strongly associated with reduced early childhood lung function.