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The Use of Small Area Estimates in Place-Based Health Research
Amanda Y Kong1, Xingyou Zhang1
1Amanda Y. Kong is with the Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. Xingyou Zhang is with the Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration, Rockville, MD.
Abstract:
Interest in the impact of the built environment on health behaviors, outcomes, and disparities is increasing, and the growing development of statistical modeling techniques has allowed researchers to better investigate these relationships. However, without enough data that are identifiable at smaller geographic levels (e.g., census tract), place-based health researchers are unable to reliably estimate the prevalence of a health outcome at these more granular and potentially more salient neighborhood levels.When reliable direct survey estimates cannot be produced because of small samples or a lack of samples, estimates based on small area estimation techniques are often used. As place-based health research and the production and secondary use of small area estimates increase, it is critical that researchers understand both the underlying methods used to create these estimates and their limitations. Without this foundation, researchers may fit inappropriate models, or interpret findings inaccurately.As a demonstrative example, we focus this discussion on the small area health indicator estimates recently produced through the 500 Cities Project by the Robert Wood Johnson Foundation, the Centers for Disease Control and Prevention (CDC), and the CDC Foundation.
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