ArticlePloS one2021
Geographic disparities and temporal changes of diabetes prevalence and diabetes self-management education program participation in Florida.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Referrals and utilization of diabetes self-management education and support (DSMES) among patients with type 1 and type 2 diabetes at a regional medical center in Kentucky.BMC public health · 2025Article
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- A Shared-Frailty Spatial Scan Statistic Model for Time-to-Event Data.Biometrical journal. Biometrische Zeitschrift · 2024Article
- Determinants of disparities of diabetes-related hospitalization rates in Florida: a retrospective ecological study using a multiscale geographically weighted regression approach.International journal of health geographics · 2024Article
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- Geographic disparities and predictors of COVID-19 vaccination in Missouri: a retrospective ecological study.Frontiers in public health · 2024Article
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- Investigation of predictors of severity of diabetes complications among hospitalized patients with diabetes in Florida, 2016-2019.BMC public health · 2023Article
- Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States.BMC public health · 2023Article
- Geographic disparities in COVID-19 testing and outcomes in Florida.BMC public health · 2023Article
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Authors and funding
5 authors.
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Abstract
backgroundAlthough Diabetes Self-Management Education (DSME) programs are recommended to help reduce the burden of diabetes and diabetes-related complications, Florida is one of the states with the lowest DSME participation rates. Moreover, there is evidence of geographic disparities of not only DSME participation rates but the burden of diabetes as well. Understanding these disparities is critical for guiding control programs geared at improving participation rates and diabetes outcomes. Therefore, the objectives of this study were to: (a) investigate geographic disparities of diabetes prevalence and DSME participation rates; and (b) identify predictors of the observed disparities in DSME participation rates.
methodsBehavioral Risk Factor Surveillance System (BRFSS) data for 2007 and 2010 were obtained from the Florida Department of Health. Age-adjusted diabetes prevalence and DSME participation rates were computed at the county level and their geographic distributions visualized using choropleth maps. Significant changes in diabetes prevalence and DSME participation rates between 2007 and 2010 were assessed and counties showing significant changes were mapped. Clusters of high diabetes prevalence before and after adjusting for common risk factors and DSME participation rates were identified, using Tango's flexible spatial scan statistics, and their geographic distribution displayed in maps. Determinants of the geographic distribution of DSME participation rates and predictors of the identified high rate clusters were identified using ordinary least squares and logistic regression models, respectively.
resultsCounty level age-adjusted diabetes prevalence varied from 4.7% to 17.8% while DSME participation rates varied from 26.6% to 81.2%. There were significant (p≤0.05) increases in both overall age-adjusted diabetes prevalence and DSME participation rates from 2007 to 2010 with diabetes prevalence increasing from 7.7% in 2007 to 8.6% in 2010 while DSME participation rates increased from 51.4% in 2007 to 55.1% in 2010. Generally, DSME participation rates decreased in rural areas while they increased in urban areas. High prevalence clusters of diabetes (both adjusted and unadjusted) were identified in northern and central Florida, while clusters of high DSME participation rates were identified in central Florida. Rural counties and those with high proportion of Hispanics tended to have low DSME participation rates.
conclusionsThe findings confirm that geographic disparities in both diabetes prevalence and DSME participation rates exist. Specific attention is required to address these disparities especially in areas that have high diabetes prevalence but low DSME participation rates. Study findings are useful for guiding resource allocation geared at reducing disparities and improving diabetes outcomes.
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