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A Methodological Approach to Small Area Estimation for the Behavioral Risk Factor Surveillance System
Carol Pierannunzi1, Fang Xu2, Robyn C Wallace3
1National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, 3719 North Peachtree Rd, Bldg 100, Mailstop F-78, Chamblee, GA 30341.
Preventing Chronic Disease
|July 16, 2016
Summary
A new statistical method enhances prevalence estimates for small geographic areas using Behavioral Risk Factor Surveillance System (BRFSS) data. This approach proved reliable in internal and external validity tests, offering accurate public health insights.
Area of Science:
- Public Health
- Biostatistics
- Geographic Information Systems
Background:
- Small area estimation (SAE) is crucial for public health research in regions with limited direct data.
- The Behavioral Risk Factor Surveillance System (BRFSS) is frequently utilized for such modeling.
Purpose of the Study:
- To introduce a novel BRFSS small area estimation (SAE) methodology.
- To evaluate the internal and external validity of prevalence estimates generated by the new BRFSS SAE method.
Main Methods:
- Developed a new BRFSS SAE method integrating four distinct datasets.
- Combined BRFSS, American Community Survey Public Use Microdata Sample, Nielsen Claritas population totals, and Missouri Census Geographic Equivalency File data.
- Constructed a single, weighted dataset for analysis.
Main Results:
- Internal and external validity tests demonstrated successful performance across numerous estimates.
- The developed BRFSS SAE method produced reliable prevalence estimates for small geographic areas.
Conclusions:
- The new BRFSS SAE method is a viable tool for generating dependable small area prevalence estimates.
- This methodology contributes to the array of available techniques for robust public health surveillance.
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