Spatial Statistics for Alcohol Epidemiology

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DESCRIPTION (provided by applicant): We propose an interdisciplinary research program addressing spatial analytic methods in the analysis of existing alcohol epidemiology data sets from Houston and Austin, Texas, and Sacramento, California. The project builds the foundation for long-term research collaborations in this area via a team of prevention scientists and spatial statisticians. The Specific Aims involve three methodological goals: 1. Define and apply hierarchical generalized linear models with spatial correlation. We will develop and apply linear, binomial, and Poisson regression models with correlated errors to model spatial patterns in counts and rates in the data sets. Particular efforts include estimation of associations between local alcohol outlet density, illegal drug use and violent outcomes across a variety of spatial scales. 2. Define and apply variable coefficient models for alcohol epidemiology. We propose development and comparison of statistical methods with location-by-risk factor interactions where associations vary across the study area. Applications include estimation of local variations in association between alcohol across the study area. Applications include estimation of local variations in association between alcohol outlet density, illegal drug use and violent incomes in the example data sets. 3. Define and apply methods for the spatial analysis of location distributions on a network. We will develop and apply analytic approaches on "network space" where distances are defined via network travel rather than straight lines. This work links geographic information systems (GISs) with spatial statistics in new and non-standard ways and enables novel quantification of spatial patterns of alcohol outlets and the associations between these patterns and patterns of criminal activity in the Austin data. Summary. Our specific aims address three areas of methodological development but each provides tools addressing specific hypotheses in alcohol epidemiology. The methods enable investigation of specific questions ranging from "Do outlet densities affect violence rates?" to "Are there disparities in exposures and/or health risks for different demographic groups?" within a geographic context.