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Assessing environmental quality: the implications for social justice
Citation:
JAGAI, J. S., B. J. ROSENBAUM, S. M. Pierson, L. C. Messer, AND K. Rappazzo. Assessing environmental quality: the implications for social justice. Presented at American Public Health Association Annual Meeting and Exposition (APHA), Denver, CO, November 06 - 10, 2010.
Impact/Purpose:
Principle components analysis (PCA) was used to create an environmental quality index for all counties in the United States. The air domain was represented with data from the National Emissions Inventory and the National Air Toxics Assessment and the socio-demographic domain with Census 2000 data of percent population in poverty and time spent commuting.
Description:
Individuals experience simultaneous exposure to pollutants and social factors, which cluster to affect human health outcomes. The optimal approach to combining these factors is unknown, therefore we developed a method to model simultaneous exposure using criteria air pollutants, hazardous air pollutants, and selected socio-demographic measures. Principle components analysis (PCA) was used to create an environmental quality index for all counties in the United States. The air domain was represented with data from the National Emissions Inventory and the National Air Toxics Assessment and the socio-demographic domain with Census2000 data of percent population in poverty and time spent commuting. In PCA index construction, 35 variables were included for 2308 counties with complete data. Because exposures vary by urbanicity, counties were stratified by percentage of population living in urban areas (urban: greater than or equal to 50%); urban and rural indices were calculated. Overall, the first two components explained 41% of the total variance. Indices derived from the first two components ranged from -0.73 to 12.30, and -9.94 to 10.99, respectively; all indices were standardized to mean of 0, standard deviation of 1. Hazardous pollutants generally contributed more strongly in urban counties and criteria pollutants in the rural counties (PM2.5 loadings were 0.23 urban versus 0.31 rural). This work presents a test case of the development of an environmental quality index, focusing on air and socio-demographic factors. Indices combining multiple domains have the potential to be useful tools for identifying environmental quality disparities.