Statistical Methods for Assessing Environmental JusticeEPA Grant Number: U915899
Title: Statistical Methods for Assessing Environmental Justice
Investigators: Tassone, Eric C.
Institution: Emory University
EPA Project Officer: Cobbs-Green, Gladys M.
Project Period: January 1, 2001 through January 1, 2004
Project Amount: $78,810
RFA: STAR Graduate Fellowships (2001) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Fellowship - Public Health Sciences , Health Effects
The U.S. Environmental Protection Agency defines environmental justice (EJ) as the "fair treatment for people of all races, cultures, and incomes, regarding the development of environmental laws, regulations, and policies." Although decisionmakers often evaluate EJ claims under the general standard of "disparate impact,"the specific methods employed by parties pursuing, defending, or investigating EJ complaints have developed ad hoc. Increasingly, geographic information system (GIS) methods using data from ostensibly objective sources, such as the U.S. Census, appear as tools for evaluating the demographics of allegedly affected populations and other issues that arise in EJ disputes. However, uniform methods for the evaluation of issues such as "What is the affected population?" and "Is the difference in exposure between the populations statistically significant?" have yet to emerge. The objective of this research project is to develop robust statistical methodologies to assess questions of this type so that the evaluation of EJ claims can be more objective and consistent.
First, methods that employ the already-present stratification of the population by race will be developed, thereby avoiding the need for an analyst-defined exposure dichotomy. Following the work of Waller (1999), estimates of cumulative distribution functions will be formed and compared based on the work of Handcock (1999), which will allow sophisticated and powerful inference. By extending the methods of Reader (2000), techniques of survival analysis will be employed in the spatial domain, in contrast to the typical temporal domain, as a complement to spatial K-function analysis. This will allow the mature inferential techniques of survival analysis to be brought to bear on the "disparate impact" issue in an EJ inquiry. This approach will offer a robust analytic framework for the statistical assessment of EJ claims.
Waller LA, Louis TA, Carlin BP. Environmental justice and statistical summaries of differences in exposure distributions. Journal of Exposure Analysis and Environmental Epidemiology 1999;9:56-65.
Handcock M, Morris M. Relative distribution methods in the social sciences. New York: Springer-Verlag, 1999.
Reader S. Using survival analysis to study spatial point patterns in geographical epidemiology. Social Science and Medicine 2000;50:985-1000.