Air Pollution and Autism Spectrum Disorder: Unveiling Multipollutant Risks and Sociodemographic Influences in California.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition of increasing prevalence worldwide. Air pollution may be a major contributor to the rise in ASD cases. This study investigated how the risk of ASD from prenatal and early postnatal exposure to specific air pollutants is being modified by key sociodemographic factors exploring vulnerable exposure periods. We conducted a California (CA) population-based cohort study of 44,173 ASD cases among 2,371,379 children born between 2013-2018 (CA birth registry) linked to CA Department of Developmental Services (DDS) records to extract ASD diagnoses prior to the end of 2022. Prenatal and 1-year postnatal air pollution exposures (fine particulate matter - PM2.5, nitrogen dioxide - NO2, and Ozone - O3) were estimated using an advanced land-use regression (LUR) spatiotemporal model with machine learning. Logistic regression was used to estimate odds ratios and 95% confidence intervals for four models: single-pollutant at a single-period (prenatal or postnatal), multi-pollutant at a single-period, single-pollutant with dual-periods (prenatal and postnatal), and multi-pollutant with dual-time period co-adjustment, adjusting for relevant individual and regional covariates. Prenatal and postnatal PM2.5 exposure increased ASD odds in all models. NO2 was associated with ASD pre- and postnatally in single and multi-pollutant but postnatally only in dual time period models. In contrast, O3 showed the opposite pattern of NO2 with slightly negative associations in single and multi-pollutant models that turned positive for the prenatal period in dual time period models. The postnatal NO2 effect was strongest among Black and Hispanic children, suggesting higher contributions from traffic-related exposures. Exposure to specific air pollutants during pregnancy and in the postnatal periods are associated with an increased risk of ASD, with sociodemographic differences potentially highlighting exposure hot spots and sources as well as subpopulation vulnerabilities. https://doi.org/10.1289/EHP15573.