The Role of Environmental and Public Health Factors in Children’s Long-term Health and Social Development
Citation:
Baxter, L., A. Liles, S. Zelasky, C. Martin, C. Weaver, AND K. Rappazzo. The Role of Environmental and Public Health Factors in Children’s Long-term Health and Social Development. International Society of Exposure Science Annual Conference, Lisbon, PORTUGAL, September 25 - 29, 2022.
Impact/Purpose:
Descriptions and quantifications of the relationships between environmental factors from this product could be used to add environmental data to future builds of the Opportunity Atlas, potentially be incorporated into tools such as EJScreen, or included as data layers in other mapping or indicator-based tools. In addition, these analyses could be used to inform long-term interventions in specific communities by helping target the most impactful environmental factors.
Description:
The Opportunity Atlas project traces upward social mobility and adulthood socioeconomic (SES) outcomes back to childhood residential neighborhood. In its initial analysis, the project found that half (R2=0.50) of the variation in adulthood socioeconomic outcomes was explained by neighborhood-level SES characteristics during childhood. This leads to the question: what other variables explain the remaining variability? To answer this question, using k-mean clustering we first clustered census tracts based on opportunity levels into 7 ranked clusters. We then used logistic regression to assess the associations between the “best” two or the “worst” cluster assignment and 26 census-level environmental variables for the entire US and for each of ten EPA regions. At the national level, seven variables (including higher PM2.5 concentrations and Reproductive Hazard Indices) were associated with the best opportunity clusters and thirteen variables (including higher Environmental Quality Index, Lead Paint Indicator, and Respiratory Hazard Indices) were associated with the worst clusters. For individual EPA regions, there was substantial variability in associated environmental variables, with percent of housing built before 1960 commonly associated with cluster assignment across many regions. Collectively, all 26 environmental exposure variables explained an exceptional proportion of the total variation in differentiating census tracts in the two best from the two worst opportunity clusters (McFadden’s R2 = 0.43). Our research suggests that some environmental variables have a cumulative impact on community level of opportunity; and thus, these exposures can be targeted directly in interventions to improve residents’ opportunity for social upward mobility and address environmental injustice.