Pre-pregnancy ozone and ultrafine particulate matter exposure during second year of life associated with decreased cognitive and adaptive functioning at aged 2-5 years.

BACKGROUND: This study sought to investigate the association of prenatal and early life exposure to a mixture of air pollutants on cognitive and adaptive outcomes separately in children with or without autism spectrum disorder (ASD). METHODS: Utilizing data from the CHARGE case-control study (birth years: 2000-2016), we predicted daily air concentrations of NO2, O3, and particulate matter <0.1 µm (PM0.1), between 0.1 and 2.5 µm (PM0.1-2.5), and between 2.5 and 10 µm (PM2.5-10) using chemical transport models with ground-based monitor adjustments. Exposures were evaluated for pre-pregnancy, each trimester, and the first two years of life. Individual and combined effects of pollutants were assessed with Vineland Adaptive Behavior Scales (VABS) and Mullen Scales of Early Learning (MSEL), separately for children with ASD (n = 660) and children without ASD (typically developing (TD) and developmentally delayed (DD) combined; n = 753) using hierarchical Bayesian Kernel Machine Regression (BKMR) models with three groups: PM size fractions (PM0.1, PM0.1-2.5, PM2.5-10), NO2, and O3. RESULTS: Pre-pregnancy Ozone was strongly negatively associated with all scores in the non-ASD group (group posterior inclusion probability (gPIP) = 0.83-1.00). The PM group during year 2 was also strongly negatively associated with all scores in the non-ASD group (gPIP = 0.59-0.93), with PM0.1 driving the group association (conditional PIP (cPIP) = 0.73-0.96). Weaker and less consistent associations were observed between PM0.1-2.5 during pre-pregnancy and ozone during year 1 and VABS scores in the ASD group. CONCLUSIONS: These findings prompt further investigation into ozone and ultrafine PM as potential environmental risk factors for neurodevelopment.

Ultrafine particulate matter exposure during second year of life, but not before, associated with increased risk of autism spectrum disorder in BKMR mixtures model of multiple air pollutants.

Prenatal and early postnatal air pollution exposures have been shown to be associated with autism spectrum disorder (ASD) risk but results regarding specific air pollutants and exposure timing are mixed and no study has investigated the effects of combined exposure to multiple air pollutants using a mixtures approach. We aimed to evaluate prenatal and early life multipollutant mixtures for the drivers of associations of air pollution with ASD. This study examined 484 typically developing (TD) and 660 ASD children from the CHARGE case-control study. Daily air concentrations for NO2, O3, ultrafine (PM0.1), fine (PM0.1-2.5), and coarse (PM2.5-10) particles were predicted from chemical transport models with statistical bias adjustment based on ground-based monitors. Daily averages were calculated for each exposure period (pre-pregnancy, each trimester of pregnancy, first and second year of life) between 2000 and 2016. Air pollution variables were natural log-transformed and then standardized. Individual and joint effects of pollutant exposure with ASD, and potential interactions, were evaluated for each period using hierarchical Bayesian Kernel Machine Regression (BKMR) models, with three groups: PM size fractions (PM0.1, PM0.1-2.5, PM2.5-10), NO2, and O3. In BKMR models, the PM group was associated with ASD in year 2 (group posterior inclusion probability (gPIP) = 0.75), and marginally associated in year 1 (gPIP = 0.497). PM2.5-10 appeared to drive the association (conditional PIP (cPIP) = 0.64) in year 1, while PM0.1 appeared to drive the association in year 2 (cPIP = 0.76), with both showing a moderately strong increased risk. Pre-pregnancy O3 showed a slight J-shaped risk of ASD (gPIP = 0.55). No associations were observed for exposures during pregnancy. Pre-pregnancy O3 and year 2 p.m.0.1 exposures appear to be associated with an increased risk of ASD. Future research should examine ultrafine particulate matter in relation to ASD.