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Mapping Obesity Coverage in Florida Counties Using Interactive Web-Based Mapping Tools to Support Targeted Policy and

Justice Moses K Aheto1,2, Ovie A Utuama2, Getachew A Dagne2

  • 1Department of Biostatistics, School of Public Health, College of Health Sciences, University of Ghana, Accra, Ghana, ug.edu.gh.

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Summary

Geographical location significantly impacts obesity prevalence in Florida, with sedentary lifestyles being a key predictor. This study highlights the need for targeted, local public health interventions to address obesity disparities across counties.

Keywords:
FloridaUSAadultsgeospatial modelingobesityprevalencerisk factorsweb-based mapping

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Area of Science:

  • Public Health
  • Epidemiology
  • Geospatial Analysis

Background:

  • Obesity is a major 21st-century public health challenge, significantly contributing to cardiovascular disease and mortality.
  • Understanding geographical variations in obesity is crucial for effective policy and intervention strategies.
  • Florida faces a substantial burden of adult obesity, necessitating localized approaches.

Purpose of the Study:

  • To quantify county-level geographical differences in obesity prevalence across Florida.
  • To identify predictors associated with obesity at the county level.
  • To inform targeted public health policies and interventions for obesity control.

Main Methods:

  • Utilized 2019 Florida Behavioral Risk Factor Surveillance System (BRFSS) data from 54,260 adults across 67 counties.
  • Applied Bayesian geospatial models and interactive web-based mapping for analysis.
  • Presented estimated coefficients as log means with 95% credible intervals.

Main Results:

  • Identified sedentary lifestyle as the sole independent risk factor for increased obesity burden (log mean=0.023).
  • Revealed significant geographical disparities in obesity prevalence, ranging from 59.0% to 75.7% (overall 68.6%).
  • Holmes County showed the highest obesity burden, with high prevalence also noted in Levy, Columbia, and other specified counties.

Conclusions:

  • Substantial county-level geographical differences in obesity underscore the importance of local public health strategies.
  • Geospatial modeling and mapping tools can guide the geographical prioritization of interventions.
  • Targeted public health policies are essential to combat adult obesity and associated mortality.