A national study on the effects of air pollution and temperature on children's neurodevelopmental outcomes

PROJECT SUMMARY/ABSTRACT Evidence suggests that the prevalence of certain developmental disorders, specifically autism spectrum disorders (ASD) and attention deficit hyperactivity disorder (ADHD), has increased sharply in recent decades. Recent studies have shown a moderate heritability for neurodevelopmental delays (NDDs), suggesting a nongenetic component contributing to its etiology. The estimated annual cost of environmentally mediated NDDs in US children is $18.3 billion. Epidemiologic studies examined prenatal and early childhood exposure to air pollutants and NDDs, with non-conclusive evidence on the effects of different pollutants, interactions, sensitive windows of exposure and chemical components of PM2.5. In addition, the role of socioeconomic status (SES) in these associations is complex. Our overarching goal is to comprehensively investigate the independent and joint prenatal and early childhood exposure to PM2.5, NO2 and O3, PM2.5 chemical components and interactions with temperature on NDDs as well as effect modification by SES. The specific aims of this application are: 1) Quantify the association prenatal and early childhood exposure to PM2.5, NO2, O3, temperature and NDDs, 2) Examine the association between prenatal and early childhood exposure to PM2.5 chemical speciation and NDDs, and 3) Examine pathways and synergistic effects, among environmental exposures and SES on NDDs. We have established a birth cohort of more than 4 million pregnancies from two population-based databases—the Medicaid Analytic eXtract and IBM MarketScan—that include rich information on location and individual-level characteristics. By 8 years of age, 23.9% of publicly insured children and 11.0% of privately insured children received a diagnosis of 1 or more NDDs. For all pollutants, PM2.5 chemical components and temperature, we have validated highly resolved daily predictions for the entire continental US. The unique composition of these two cohorts, allows us to determine the extent to which SES modifies these associations. For our analyses, we will adjust for a wide range of individual-level characteristics and spatiotemporal covariates. We will estimate hazard ratios and their 95% confidence intervals using cox regression, distributed-linear/non-linear lag models, and we will examine effect modification by infant sex. We will use advanced statistical methods to estimate the effects of mixtures. Our prior work and data support both the hypothesis for and the feasibility of the proposed study. The proposed research is innovative because it will be the first study to: 1) investigate associations between air pollutants, temperature and NDDs on a national scale; 2) use state-of-the-art spatiotemporal models to assess individual exposures to PM2.5, NO2, O3 and temperature; 3) employ innovative resources of clinical data by leveraging two large pregnancy cohorts. The proposed research is of great significance because it will guide decisions and pollutant regulations to protect the health of pregnant women and children, inform heat wave warning systems, potentially reducing rates of NDDs and subsequent social, financial, and public health burden.