BAYES METHODS FOR COMBINING DISEASE AND EXPOSURE DATA IN ASSESSING ENVIRONMENTAL JUSTICE

Environmental justice reflects the equitable distribution of the burde n of environmental hazards across various sociodemographic groups. The issue is important in environmental regulation, siting of hazardous w aste repositories and prioritizing remediation of existing sources of exposure. We propose a statistical framework for assessing environment al justice. The framework includes a quantitative assessment of enviro nmental equity based on the cumulative distribution of exposure within population subgroups linked to disease incidence through a dose-respo nse function. This approach avoids arbitrary binary classifications of individuals solely as `exposed' or `unexposed'. We present a Bayesian inferential approach, implemented using Markov chain Monte Carlo meth ods, that accounts for uncertainty in both exposure and response. We i llustrate our method using data on leukaemia deaths and exposure to to xic chemical releases in Allegheny County, Pennsylvania.