Abstract
INTRODUCTION: Neurotoxicity resulting from air pollution is of increasing concern. Considering exposure timing effects on neurodevelopmental impairments may be as important as the exposure dose. We used distributed lag regression to determine the sensitive windows of prenatal exposure to fine particulate matter (PM(2.5)) on children's cognition in a birth cohort in Mexico. METHODS: Analysis included 553 full-term (≥37 weeks gestation) children. Prenatal daily PM(2.5) exposure was estimated using a validated satellite-based spatiotemporal model. McCarthy Scales of Children's Abilities (MSCA) were used to assess children's cognitive function at 4-5 years old (lower scores indicate poorer performance). To identify susceptibility windows, we used Bayesian distributed lag interaction models to examine associations between prenatal PM(2.5) levels and MSCA. This allowed us to estimate vulnerable windows while testing for effect modification. RESULTS: After adjusting for maternal age, socioeconomic status, child age, and sex, Bayesian distributed lag interaction models showed significant associations between increased PM(2.5) levels and decreased general cognitive index scores at 31-35 gestation weeks, decreased quantitative scale scores at 30-36 weeks, decreased motor scale scores at 30-36 weeks, and decreased verbal scale scores at 37-38 weeks. Estimated cumulative effects (CE) of PM(2.5) across pregnancy showed significant associations with general cognitive index (CE^ = -0.35, 95% confidence interval [CI] = -0.68, -0.01), quantitative scale (CE^ = -0.27, 95% CI = -0.74, -0.02), motor scale (CE^ = -0.25, 95% CI = -0.44, -0.05), and verbal scale (CE^ = -0.2, 95% CI = -0.43, -0.02). No significant sex interactions were observed. CONCLUSIONS: Prenatal exposure to PM(2.5), particularly late pregnancy, was inversely associated with subscales of MSCA. Using data-driven methods to identify sensitive window may provide insight into the mechanisms of neurodevelopmental impairment due to pollution.