posted on 2022-12-22, 22:29authored byMd Mostafijur Rahman, Sarah A. Carter, Jane C. Lin, Ting Chow, Xin Yu, Mayra P. Martinez, Zhanghua Chen, Jiu-Chiuan Chen, Daniel Rud, Juan P. Lewinger, Aaron van Donkelaar, Randall V. Martin, Sandrah Proctor Eckel, Joel Schwartz, Fred Lurmann, Michael J. Kleeman, Rob McConnell, Anny H. Xiang
This retrospective cohort study examined associations
of autism
spectrum disorder (ASD) with prenatal exposure to major fine particulate
matter (PM2.5) components estimated using two independent
exposure models. The cohort included 318 750 mother–child
pairs with singleton deliveries in Kaiser Permanente Southern California
hospitals from 2001 to 2014 and followed until age five. ASD cases
during follow-up (N = 4559) were identified by ICD
codes. Prenatal exposures to PM2.5, elemental (EC) and
black carbon (BC), organic matter (OM), nitrate (NO3–), and sulfate (SO42–) were constructed using (i) a source-oriented
chemical transport model and (ii) a hybrid model. Exposures were assigned
to each maternal address during the entire pregnancy, first, second,
and third trimester. In single-pollutant models, ASD was associated
with pregnancy-average PM2.5, EC/BC, OM, and SO42– exposures
from both exposure models, after adjustment for covariates. The direction
of effect estimates was consistent for EC/BC and OM and least consistent
for NO3–. EC/BC, OM, and SO42– were generally
robust to adjustment for other components and for PM2.5. EC/BC and OM effect estimates were generally larger and more consistent
in the first and second trimester and SO42– in the third trimester. Future
PM2.5 composition health effect studies might consider
using multiple exposure models and a weight of evidence approach when
interpreting effect estimates.