Gestational Exposure to Toxicants and Autistic Behaviors using Bayesian Quantile Regression

Abstract

BACKGROUND AND AIM: Autism Spectrum Disorder, which is characterized by impaired social communication and stereotypic behaviors, affects 1-2% of children. While prenatal exposure to toxicants has been associated with autistic behaviors, most studies have focused on shifts in mean behavior scores. METHODS: We used Bayesian quantile regression to assess the associations between log₂-transformed toxicant concentrations and autistic behaviors across the distribution of behaviors. We used data from the Maternal-Infant Research on Environmental Chemicals study, a pan-Canadian cohort (2008-2011). We measured metal, pesticide, polychlorinated biphenyl, phthalate, bisphenol-A, and triclosan concentrations in blood or urine samples collected during the first trimester of pregnancy. Autistic behaviors were assessed in 478 3-4-year-old children using the Social Responsiveness Scale (SRS), where higher scores denote more autistic-like behaviors. RESULTS:Lead, cadmium, and most phthalate metabolites were associated with mild increases in SRS scores at the 90th percentile of the SRS distribution. Manganese and some pesticides were associated with mild decreases in SRS scores at the 90th percentile of the SRS distribution. We identified several monotonic trends where associations increased in magnitude from the bottom to the top of the SRS distribution. CONCLUSIONS:These results suggest that Quantile regression can reveal nuanced relationships and should thus be more widely used by epidemiologists. KEYWORDS: Endocrine disrupting chemicals; Neurodevelopmental outcomes