Autism Spectrum Disorder Prevalence and Proximity to Industrial Facilities Releasing Arsenic, Lead, or Mercury

Background:  The etiology of autism spectrum disorder (ASD) is poorly understood. Environmental factors such as exposure to heavy metals have been associated with ASD in previous literature. Prenatal and perinatal exposures to arsenic, lead, and mercury as well as air pollutants have been shown to adversely affect birth outcomes in offspring. Additionally, previous studies have reported that proximity to sources of airborne pollutants, including industrial facilities and high-traffic roadways, was associated with ASD diagnosis and school-reported administrative prevalence, respectively. 

Objectives:  To evaluate the association between ASD prevalence, at the census tract level, and proximity of tract geometric centers to industrial facilities releasing arsenic, lead, or mercury during the 1990s.

Methods:  We used data from five participating sites of the Autism and Developmental Disabilities Monitoring (ADDM) Network: Arizona, Maryland, New Jersey, South Carolina, and Utah. ADDM is a multi-state public health surveillance system for ASD and other developmental disabilities established by the Centers for Disease Control and Prevention in 2000 to measure ASD prevalence among 8-year-old children. ASD case status is determined through a systematic review of records from healthcare and education sources such as primary care clinics, hospitals, schools, and diagnostic and treatment centers. These records are reviewed by expert clinician reviewers to determine if behaviors are described in the abstracted data that meet the number and pattern required for an ASD diagnosis based on the Diagnostic and Statistical Manual of Mental Disorders, 4^th edition, Text Revision. ADDM data were obtained for 2000, 2002, 2004, 2006, and 2008 surveillance years. Multi-level negative binomial regression models were used to test associations between census tract level ASD prevalence and proximity to industrial facilities, defined by ≤10^th percentile (≤10.46km), 10^th-20^th percentile (10.47km to 19.01km), 20^th-30^th percentile (19.03km to 27.64km), 30^th-40^th percentile (27.67km to 37.38km), and >50^th percentile (>46.92km), which were documented to have released arsenic, lead, and/or mercury from 1991 to 1999 according to the US Environmental Protection Agency Toxics Release Inventory.

Results:  Data from 4,488 ASD cases residing in 2,558 census tracts revealed that in unadjusted analyses, ASD prevalence was higher for tracts within the closest 10^th percentile (RR=1.46, 95% CI: 1.13, 1.88), 10^th-20^th percentile (RR=1.30, 95% CI: 1.04, 1.63), 20^th-30^th percentile (RR=1.43, 95% CI: 1.15, 1.76), and 30^th-40^th percentile (RR=1.32, 95% CI: 1.08, 1.60) in comparison to tracts located in the furthest 50^th percentile from industrial facilities. After adjustment for demographic and socio-economic area-based characteristics, including proportion of each tract population that was White, Hispanic, college-educated, residing in a rural area, and living below the poverty line, ASD prevalence was only higher in census tracts within the closest 10^th percentile compared to those in the furthest 50^th percentile (RR=1.27, 95% CI: 1.001, 1.611).

Conclusions:  While the results of this analysis are suggestive of a potential association between residential proximity to industrial facilities emitting arsenic, lead, or mercury and ASD prevalence, care should be taken not to over interpret this observation given the borderline statistical significance, the inability to account for other potentially confounding factors, and known inadequacies in the TRI database.