Disparities in the Use of Diabetes Screening in Appalachia

Bibliographic Data

ID19431965
AuthorsJennifer M Lobo (0000-0001-8375-2475, Department of Public Health Sciences, School of Medicine University of Virginia Charlottesville Virginia), Roger Anderson (Department of Public Health Sciences, School of Medicine University of Virginia Charlottesville Virginia), Roger T Anderson (0000-0001-8112-4117, University of Virginia), George J Stukenborg (Department of Public Health Sciences, School of Medicine University of Virginia Charlottesville Virginia), Anthony Mccall (Internal Medicine, School of Medicine University of Virginia Charlottesville Virginia), Anthony L McCall (0000-0002-4190-5311, University of Virginia), Hyojung Kang (0000-0001-5725-3963, Department of Systems and Information Engineering University of Virginia Charlottesville Virginia), Fabian Camacho (0000-0002-4878-0283, Department of Public Health Sciences, School of Medicine University of Virginia Charlottesville Virginia), Min-Woong Sohn (0000-0002-9474-2907, University of Virginia, corresponding author), Min‐Woong Sohn (Department of Public Health Sciences, School of Medicine University of Virginia Charlottesville Virginia)
Year2018
Volume34
Issue2
Pages173-181
Publication date2018-03-01
Open AccessYes
TypeARTICLE
VenueThe Journal of Rural Health (JOURNAL)
Journal identifiersISSN: 0890-765X • E-ISSN: 1748-0361
PublisherWiley (PUBLISHER • GB)
DOI10.1111/jrh.12247
PMID28686786
OpenAlexW2729846598
LanguageEN
Citations received1
References cited15

PURPOSE: The Appalachian region presents disproportionately high rates of chronic disease compared to the rest of the United States. Early diagnosis of diabetes through screening is an important step in reducing diabetes complications. This study examines disparities in the use of diabetes screening in Appalachia. METHODS: We analyzed 2009 and 2010 Behavioral Risk Factor Surveillance System data for 96,111 adults aged ≥45 years from 11 Appalachian states. Based on economic status, Appalachian counties were grouped into distressed (least affluent), at-risk, transitional, and competitive (most affluent). Logistic regression analyses were used to estimate the statistical significance and effect size of factors associated with diabetes screening. RESULTS: Competitive counties had the highest rate of diabetes screening (65.4%). At-risk counties had the lowest rate (60.3%), about 7.8% lower compared to competitive counties (P < .001). After adjusting for socioeconomic factors, differences in screening rates between county economic levels in Appalachia were not statistically significant. Among respondents ≥65 years, at-risk counties had an 8.1% lower screening rate compared to competitive counties; this difference was not adequately explained by differences in socioeconomic factors. Screening rates in distressed and transitional counties were not significantly different from competitive counties in unadjusted or adjusted models. CONCLUSIONS: At-risk counties had significantly lower screening rates than competitive counties. They should receive more policy attention similar to that received by distressed counties. Social policies that improve socioeconomic status and educational attainment, and health policies that reduce barriers to access to care may reduce disparities in diabetes screening rates in the less affluent Appalachian counties

Appalachia · Appalachian Region · Behavioral Risk Factor Surveillance System · Diabetes mellitus · Environmental health · Geography · Logistic regression · Population · Socioeconomic status · Demography · Diabetes Management and Education · Diabetes, Cardiovascular Risks, and Lipoproteins · Global Cancer Incidence and Screening · Medicine · Gerontology

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