Abstract
BackgroundLeft unchecked, pre-diabetes progresses to diabetes and its complications that are important health burdens in the United States. There is evidence of geographic disparities in the condition with some areas having a significantly high risks of the condition and its risk factors. Identifying these disparities, their determinants, and changes in burden are useful for guiding control programs and stopping the progression of pre-diabetes to diabetes. Therefore, the objectives of this study were to investigate geographic disparities of pre-diabetes prevalence in Florida, identify predictors of the observed spatial patterns, as well as changes in disease burden between 2013 and 2016.MethodsThe 2013 and 2016 Behavioral Risk Factor Surveillance System data were obtained from the Florida Department of Health. Counties with significant changes in the prevalence of the condition between 2013 and 2016 were identified using tests for equality of proportions adjusted for multiple comparisons using the Simes method. Flexible scan statistics were used to identify significant high prevalence geographic clusters. Multivariable regression models were used to identify determinants of county-level pre-diabetes prevalence.ResultsThe state-wide age-adjusted prevalence of pre-diabetes increased significantly (p ≤ 0.05) from 8.0% in 2013 to 10.5% in 2016 with 72% (48/67) of the counties reporting statistically significant increases. Significant local geographic hotspots were identified. High prevalence of pre-diabetes tended to occur in counties with high proportions of non-Hispanic black population, low median household income, and low proportion of the population without health insurance coverage.ConclusionsGeographic disparities of pre-diabetes continues to exist in Florida with most counties reporting significant increases in prevalence between 2013 and 2016. These findings are critical for guiding health planning, resource allocation and intervention programs.
Highlights
People with pre-diabetes are considered to be at higher risk of developing diabetes and subsequent complications than those that do not have the condition
High pre-diabetes prevalence was not limited to rural counties and occurred in some large central and large fringe metropolitan areas such as the Jacksonville region (Duval County) and Palm Beach County (Figs. 1, 2A–2B)
The existence of spatial disparities of pre-diabetes prevalence observed in this study is consistent with findings from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, which reported that the odds of pre-diabetes among adults ≥45 years old living in the ‘‘stroke belt’’ were higher than for those living outside this region (Barker et al, 2011; Lee et al, 2014)
Summary
People with pre-diabetes are considered to be at higher risk of developing diabetes and subsequent complications than those that do not have the condition. Like many other chronic conditions, there are geographic disparities in the prevalence of pre-diabetes Previous studies investigating these disparities have been limited in that they have been descriptive in nature and very few have used rigorous statistical/epidemiological spatial cluster investigation techniques to identify these disparities and disease hotspots at sub-state levels and yet findings from such investigations are critically important for guiding health planning and resource allocation. That study found that predictors of pre-diabetes and diabetes at the individual level differed based on whether individuals lived inside or outside a hotspot county This suggests that detailed investigations at sub-state levels, using rigorous statistical/epidemiolocal approaches, are critically important to guide needs-based planning, resources allocation, service provision, prevention and control strategies as well as policy. Geographic disparities of pre-diabetes continues to exist in Florida with most counties reporting significant increases in prevalence between 2013 and 2016 These findings are critical for guiding health planning, resource allocation and intervention programs
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