ArticlePreventing chronic disease2023
County-Level Geographic Disparities in Disabilities Among US Adults, 2018.
Article in Preventing chronic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Factors Associated With the Rising Trend in Self-Reported Cognitive Disability Among U.S. Adults Aged 18-39 From 2013-2024.Annals of clinical and translational neurology · 2026Article
- Trends In Care Needs Among Older US Adults Diverged By Age, 2011-22.Health affairs (Project Hope) · 2026Article
- Population Estimates and Hypertension and Diabetes Prevalence: Cross-Sectional Quantitative Study Comparing Electronic Health Record-Derived Counts, Census, and Centers for Disease Control and Prevention Population Level Analysis and Community Estimates.JMIR public health and surveillance · 2026Article
- Reaching the Unreached: Unmet Needs and the Promise of Telehealth Among People with Mobility Disabilities in Low-Resource Areas in Alabama.Disabilities (Basel, Switzerland) · 2026Article
- Application of a comprehensive disability measure: Disability prevalence among US Veterans and non-veterans from the National Health Interview Survey Data from 2015 to 2018.Preventive medicine · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionLocal data are increasingly needed for public health practice. County-level data on disabilities can be a valuable complement to existing estimates of disabilities. The objective of this study was to describe the county-level prevalence of disabilities among US adults and identify geographic clusters of counties with a higher or lower prevalence of disabilities.
methodsWe applied a multilevel logistic regression and poststratification approach to geocoded 2018 Behavioral Risk Factor Surveillance System data, Census 2018 county-level population estimates, and American Community Survey 2014-2018 poverty estimates to generate county-level estimates for 6 functional disabilities and any disability type. We used cluster-outlier spatial statistical methods to identify clustered counties.
resultsAmong 3,142 counties, median estimated prevalence was 29.5% for any disability and differed by type: hearing (8.0%), vision (4.9%), cognition (11.5%), mobility (14.9%), self-care (3.7%), and independent living (7.2%). The spatial autocorrelation statistic, Moran's I, was 0.70 for any disability and 0.60 or greater for all 6 types of disability, indicating that disabilities were highly clustered at the county level. We observed similar spatial cluster patterns in all disability types except hearing disability.
conclusionThe results suggest substantial differences in disability prevalence across US counties. These data, heretofore unavailable from a health survey, may help with planning programs at the county level to improve the quality of life for people with disabilities.
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