Translating Statewide Health Survey Data into Local Action: The Arkansas Health Survey
This paper describes the development of the Arkansas Health Survey (AHS) and AR-COMPASS Explorer as an integrated surveillance-to-action infrastructure that uses representative statewide survey data to produce publicly accessible estimates at the state, county, and census tract levels. The AHS is an annual, statewide, population-based survey of adult Arkansans. Year 1 used address-based sampling to improve representation of lower-income, racially and ethnically diverse, and rural census tracts. Responses were geocoded, imputed as needed, weighted to represent Arkansas adults, and prepared for small-area estimation and public dissemination. A total of 9932 respondents met eligibility and completion criteria. Weighted baseline estimates identified substantial disease and behavioral health need, including hypertension, obesity, clinically relevant depressive symptoms, past-30-day tobacco or nicotine use, and hazardous alcohol use. Baseline estimates provide the empirical foundation for AR-COMPASS, which disseminates AHS indicators through interactive maps, local profiles, comparison tools, and downloadable outputs. The AHS and AR-COMPASS illustrate an approach to designing population health surveillance with a localized dissemination component. This model offers a replicable framework for states seeking geographically granular, publicly useful data infrastructure.
Authors
- Ana Julia Bridges (ORCID: https://orcid.org/0000-0001-9836-9946)
- Michael Niño (ORCID: https://orcid.org/0000-0003-1638-5585)
- Shauna A. Morimoto (ORCID: https://orcid.org/0000-0003-1869-156X)
- Page D. Dobbs (ORCID: https://orcid.org/0000-0003-1913-6488)
- Benjamin C. Amick (ORCID: https://orcid.org/0000-0003-3468-9451)
- Mark Williams
- Johanna Thomas
Institutions
- University of Arkansas at Fayetteville (US)
- University of Arkansas for Medical Sciences (US)
Publication Details
- Journal
- Trends in Public Health
- Published
- 2026-09-24
- DOI
- https://doi.org/10.3390/tph1030017
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00