Autism spectrum disorder prevalence and associations with air concentrations of lead, mercury, and arsenic.

Lead, mercury, and arsenic are neurotoxicants with known effects on neurodevelopment. Autism spectrum disorder (ASD) is a neurodevelopmental disorder apparent by early childhood. Using data on 4486 children with ASD residing in 2489 census tracts in five sites of the Centers for Disease Control and Prevention's Autism and Developmental Disabilities Monitoring (ADDM) Network, we used multi-level negative binomial models to investigate if ambient lead, mercury, and arsenic concentrations, as measured by the US Environmental Protection Agency National-Scale Air Toxics Assessment (EPA-NATA), were associated with ASD prevalence. In unadjusted analyses, ambient metal concentrations were negatively associated with ASD prevalence. After adjusting for confounding factors, tracts with air concentrations of lead in the highest quartile had significantly higher ASD prevalence than tracts with lead concentrations in the lowest quartile (prevalence ratio (PR) = 1.36; 95 '% CI: 1.18, 1.57). In addition, tracts with mercury concentrations above the 75th percentile (>1.7 ng/m(3)) and arsenic concentrations below the 75th percentile (≤0.13 ng/m(3)) had a significantly higher ASD prevalence (adjusted RR = 1.20; 95 % CI: 1.03, 1.40) compared to tracts with arsenic, lead, and mercury concentrations below the 75th percentile. Our results suggest a possible association between ambient lead concentrations and ASD prevalence and demonstrate that exposure to multiple metals may have synergistic effects on ASD prevalence.

Autism spectrum disorder reporting in lower socioeconomic neighborhoods.

Utilizing surveillance data from five sites participating in the Autism and Developmental Disabilities Monitoring Network, we investigated contributions of surveillance subject and census tract population sociodemographic characteristics on variation in autism spectrum disorder ascertainment and prevalence estimates from 2000 to 2008 using ordinal hierarchical models for 2489 tracts. Multivariable analyses showed a significant increase in ascertainment of autism spectrum disorder cases through both school and health sources, the optimal ascertainment scenario, for cases with college-educated mothers (adjusted odds ratio = 1.06, 95% confidence interval = 1.02-1.09). Results from our examination of sociodemographic factors of tract populations from which cases were drawn also showed that after controlling for other covariates, statistical significance remained for associations between optimal ascertainment and percentage of Hispanic residents (adjusted odds ratio = 0.93, 95% confidence interval = 0.88-0.99) and percentage of residents with at least a bachelor's degree (adjusted odds ratio = 1.06, 95% confidence interval = 1.01-1.11). We identified sociodemographic factors associated with autism spectrum disorder prevalence estimates including race, ethnicity, education, and income. Determining which specific factors influence disparities is complicated; however, it appears that even in the presence of education, racial and ethnic disparities are still apparent. These results suggest disparities in access to autism spectrum disorder assessments and special education for autism spectrum disorder among ethnic groups may impact subsequent surveillance.

Autism spectrum disorder prevalence and proximity to industrial facilities releasing arsenic, lead or mercury.

Prenatal and perinatal exposures to air pollutants have been shown to adversely affect birth outcomes in offspring and may contribute to prevalence of autism spectrum disorder (ASD). For this ecologic study, we evaluated the association between ASD prevalence, at the census tract level, and proximity of tract centroids to the closest industrial facilities releasing arsenic, lead or mercury during the 1990s. We used 2000 to 2008 surveillance data from five sites of the Autism and Developmental Disabilities Monitoring (ADDM) network and 2000 census data to estimate prevalence. Multi-level negative binomial regression models were used to test associations between ASD prevalence and proximity to industrial facilities in existence from 1991 to 1999 according to the US Environmental Protection Agency Toxics Release Inventory (USEPA-TRI). Data for 2489 census tracts showed that after adjustment for demographic and socio-economic area-based characteristics, ASD prevalence was higher in census tracts located in the closest 10th percentile compared of distance to those in the furthest 50th percentile (adjusted RR=1.27, 95% CI: (1.00, 1.61), P=0.049). The findings observed in this study are suggestive of the association between urban residential proximity to industrial facilities emitting air pollutants and higher ASD prevalence.