Recent regulatory action requires the assessment of environmental justice (equitable protection from the burdens of environmental hazards across sociodemographic subpopulations) in the siting of hazardous waste sites, and prioritization of environmental remediation efforts. Assessments of environmental justice require linking exposure, demographic, and health data. The geographic nature of the data makes the use of geographic information systems attractive for environmental justice assessments. Typical geographic assessments compare the composition of 'exposed' populations, while typical statistical assessments focus on differences in health outcomes between population subgroups, possibly adjusted for exposure. We outline an alternate approach based on summarized differences between exposure distributions within each population subgroup. We illustrate how such summaries provide a tool for site evaluation (e.g., defining exposure inequities resulting from locating a new potential hazard at any of a number of possible sites). In addition, we describe summaries, based on dose- response relationships, to describe risk differences imposed by the observed exposure differences. Reported toxic emissions from Allegheny County, Pennsylvania illustrate the approach.
|Original language||English (US)|
|Number of pages||10|
|Journal||Journal of Exposure Analysis and Environmental Epidemiology|
|State||Published - 1999|
Bibliographical noteFunding Information:
This research was supported in part by the National Institute of Environmental Health Sciences, NIH, grant number 1 R01 ES07750-01A1 (LAW, TAL, BPC). The leukemia data were supplied by the Allegheny County Health Department, Pittsburgh, Pennsylvania. The Allegheny County Health Department specifically disclaims responsibility for any analyses, interpretations or conclusions. The contents are solely the responsibility of the authors and do not necessarily represent the official views of NIEHS, NIH, or the Allegheny County Health Department, and no official endorsement should be inferred. The authors thank the editor and referees for constructive comments on an earlier version of this paper.
- Bayesian methods
- Environmental equity
- Geographic information systems
- Hierarchical model