Richard E Hoskins, PhD MPH, Epidemiology, Health Statistics and the Public Health Laboratory, Washington State Department of Health, 1102 Quince Street, Olympia, WA 98504-7812, (360) 236-4270, healthmaps@attbi.com

The vital statistics data of Washington State, and various disease and conditions registries were geocoded to longitude and latitude back to early years where complete address data were first available. An iterative geocoding process brought street level geocoding often up to the 98% level. Then spatial analytic methods which included spatial scan statistics, boundary detection, Monte Carlo simulation, a variety of cluster detection methods, Bayesian smoothing and hierarchical modeling methods were used to develop maps and comparisons of regions where conditions such as low birth weight, heart disease and various cancers could be compared to regions of high socioeconomic status (SES) vs. lower SES and in relation to potentially toxic waste emitting sites. This was done on the scale of the entire state from 1989 to 2002. Using 1990 and 2000 census data and intercensal estimates, significant differences were found with respect to SES and the likelihood that minorities and economically compromised families are more likely to live near toxic waste sites and have worse health status. In addition it was found that irrespective of toxic waste site exposure that above and beyond individual characteristics, the SES characteristics of a neighborhood maybe the greatest determinant of disease status. We propose a protocol concerning making this assessment that can be applied by health departments which can lead to targeted public health intervention strategies.

Learning Objectives:

• 1. Participants will have the opportunity to see how a state public health agency is taking seriously the issues of environmental equity and applying new statistical technology to its assessment.
• 2. Participants will be able to see how environmental equity assessments are actively used to determine potential new public health interventions.
• 3. Participants will see how they can apply new statistical technology for this kind of assessment without being a specialist and how to obtain and use much of the new statistical technology for low cost or no cost at all.
• 4. Participants will be guided with respect to developing their own polices and guidelines to doing similar investigations and how to develop an effective dialog among other public health practitioners

Keywords: Environmental Justice, Geographic Information Systems

Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.