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Effects of Neighborhood- and Individual-Level Economic and Mental Health Stressors as Susceptibility Factors for Environmental Exposures on Child ASD

Tanya K. Taiwo1, 2*
  • 1 University of California, Davis, United States
  • 2 Bastyr University, United States

Abstract Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that has demonstrated a high degree of inheritability and evidence of susceptibility to in-utero exposures. Objective: This study examined the effects of both neighborhood- and individual-level economic and mental health stressors as susceptibility factors for the influences of exogenous environmental exposures on neurodevelopment. Study Design/Methods: Children aged 2 to 5 years (488 with ASD and 329 controls) were enrolled in the CHARGE (Childhood Autism Risks from Genetics and the Environment) study, a population-based, case-control investigation between January 2003 and September 2012. Eligible children were born in California, had parents who spoke English or Spanish, and were living with a biological parent in selected regions of California. Children’s diagnoses were confirmed using standardized assessments. Neighborhood level environmental exposures and sociodemographic factors were obtained from the California Communities Environmental Health Screening Tool (CalEnviroScreen), developed by Office of Environmental Health Hazard Assessment. The tool ranks census tracts based on environmental exposures, socioeconomic factors, and prevalence of certain health conditions. Principal component analysis (PCA) was used to visualize the data, reduce the number of measures and derive composite variables. Odd ratios (OR’s) for financial hardship, maternal mood disorders and principal components and their 95% confidence intervals (CIs) were calculated with multivariate logistic regression models. Results: Based on PCA, principal components related to CalEnviroScreen rankings for socioeconomic status, air quality, waste disposal pollution sources, health indicators, and water quality were created. The principal component describing air quality measures included: diesel particulate matter (PM), toxic releases from facilities, traffic density and PM2.5 concentrations. This variable remained significantly associated with child ASD risk in unadjusted and adjusted logistic regression. We found increased odds of ASD among children whose mothers reported financial hardship compared with those whose mothers did not (OR = 1.5; 95% CI [1.1, 1.9]). Additionally, higher levels of CalEnviroScreen measures for air quality were associated with increased risk of ASD (OR = 1.1; 95% CI [1.01, 1.3]). Children whose mothers reported mood disorders exhibited higher risk of ASD (OR = 1.9; 95% CI [1.5, 2.3]) when compared to children whose mothers reported no mood disorders. There was also evidence of increased risk with higher indicators of poor air quality (OR = 1.2; 95% CI [1.05, 1.3]) when controlling for maternal mental health. We found increasing odds ratios at increasing levels of the AirQ principal component when adjusting for maternal mood disorders, and significant persistent risk when adjusting for financial hardship. Conclusions: These findings are consistent with previous studies showing that prenatal exposures including air-pollutants, maternal stress and mood disorders are associated with child’s ASD. We found that community-level variables impact ASD risk even when controlling for the family’s SES and maternal mental health. Results add to our understanding that maternal prenatal stress and mental state are vitally important to current prevention and intervention strategies. Additionally, there is a critical need for action to reduce air pollution from multiple sources, with a focus on those communities with the highest exposure levels and socioeconomic vulnerabilities.

Acknowledgements

Dissertation committee: Irva Hertz-Picciotto, Beatriz Martinez-Lopez, Ana Maria Iosif Funding: National Institute of Environmental Health Sciences of the National Institutes of Health under Award Number R01ES01535

References

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Keywords: Austism spectrum disorder, environment, Socioecologic framework, Socioeconomial impact, prenatal

Conference: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019.

Presentation Type: Regular oral presentation

Topic: Emerging GIS, data science and sensor technologies adapted to animal, plant and human health, including precision medicine and precision farming

Citation: Taiwo TK (2019). Effects of Neighborhood- and Individual-Level Economic and Mental Health Stressors as Susceptibility Factors for Environmental Exposures on Child ASD. Front. Vet. Sci. Conference Abstract: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data. doi: 10.3389/conf.fvets.2019.05.00019

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Received: 07 Jun 2019; Published Online: 27 Sep 2019.

* Correspondence: Dr. Tanya K Taiwo, University of California, Davis, Davis, United States, tmkhemet@ucdavis.edu