Abstract #301524

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JSM 2003 Abstract #301524
Activity Number: 16
Type: Contributed
Date/Time: Sunday, August 3, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Health Policy Statistics
Abstract - #301524
Title: Small Area Estimation of Prevalence of Access Sensitive Health Conditions for California Legislative Districts
Author(s): Hongjian Yu*+
Companies: University of California, Los Angeles
Address: 3001 Cordova Court, West Covina, CA, 91791-4206,
Keywords: small area estimate ; hierarchical logistic regression
Abstract:

Policy makers want information about their constituencies, but few health surveys can provide direct estimates of chronic conditions for small areas. As a result, we have developed methods to provide small area estimates for a variety of chronic conditions. Hierarchical logistic regression is applied to predict the probability of having conditions sensitive to health care access, such as asthma, using the California Health Interview Survey that was designed to provide county-level estimates. The predictors include demographic variables at individual level and ecological variables at ZIP and county levels. The predicted probability is then merged into the ZCTA file in the census. We convert the merged file into census block groups through which the boundary of the legislative districts is drawn. The prevalence of asthma in each district then can be calculated by aggregating the estimates in the block groups in the district. The resulting maps and prevalence data for legislative districts statewide provide a powerful tool for planning.

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