The concept of """"""""environmental justice"""""""" plays an increasingly important role in developing environmental regulations to protect the public's health. This form of justice relates to equity among all segments of the population with respect to exposure to environmental hazard and to health outcomes. Subpopulations of particular interest include pregnant women, children, ethnic, and racial minorities, and other historically disadvantaged groups. While data availability, storage, and processing flexibility have increased enormously in recent years, development of appropriate statistical methodology has not kept pace. Exposure and health outcomes data can be displayed in striking maps via Geographic Information Systems (GIS), but the best way to develop numerical inputs for these displays is not yet clear. A four-year research program is proposed to develop and evaluate the following: (1) methods that exploit spatial structure to stabilize rate estimates based on small numbers of people and thereby to maintain geographic and demographic resolution of stabilized rates; (2) statistical methods and models to detect areas of elevated exposure to environmental hazards, areas of increased disease incidence, and areas of increased risk while controlling for known confounding factors in both time and space; (3) guidelines and methods to allow for the combining of misaligned data from several sources (e.g./ exposure data, outcome data, and demographic data) into a cogent collection for analysis; and (4) a suite of software routines implementing the developed methods that will serve as the prototype system of analysis for statisticians, epidemiologists and geographers investigating environmental justice with GIS.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Research Project (R01)
Project #
5R01ES007750-04
Application #
6043478
Study Section
Special Emphasis Panel (ZRG7-STA (01))
Project Start
1996-08-01
Project End
2001-04-30
Budget Start
1999-08-01
Budget End
2001-04-30
Support Year
4
Fiscal Year
1999
Total Cost
Indirect Cost
Name
Emory University
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
042250712
City
Atlanta
State
GA
Country
United States
Zip Code
30322
Tassone, Eric C; Waller, Lance A; Casper, Michele L (2009) Small-area racial disparity in stroke mortality: an application of bayesian spatial hierarchical modeling. Epidemiology 20:234-41
Waller, Lance A; Hill, Elizabeth G; Rudd, Rose Anne (2006) The geography of power: statistical performance of tests of clusters and clustering in heterogeneous populations. Stat Med 25:853-65
Jin, Xiaoping; Carlin, Bradley P (2005) Multivariate parametric spatiotemporal models for county level breast cancer survival data. Lifetime Data Anal 11:5-27
Jin, Xiaoping; Carlin, Bradley P; Banerjee, Sudipto (2005) Generalized hierarchical multivariate CAR models for areal data. Biometrics 61:950-61
Banerjee, Sudipto; Carlin, Bradley P (2004) Parametric spatial cure rate models for interval-censored time-to-relapse data. Biometrics 60:268-75
Hodges, James S; Carlin, Bradley P; Fan, Qiao (2003) On the precision of the conditionally autoregressive prior in spatial models. Biometrics 59:317-22
Short, Margaret; Carlin, Bradley P; Bushhouse, Sally (2002) Using hierarchical spatial models for cancer control planning in Minnesota (United States). Cancer Causes Control 13:903-16
Waller, L A (2000) A civil action and statistical assessments of the spatial pattern of disease: do we have a cluster? Regul Toxicol Pharmacol 32:174-83
Eberly, L E; Carlin, B P (2000) Identifiability and convergence issues for Markov chain Monte Carlo fitting of spatial models. Stat Med 19:2279-94
Hill, E G; Ding, L; Waller, L A (2000) A comparison of three tests to detect general clustering of a rare disease in Santa Clara County, California. Stat Med 19:1363-78

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