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Updated: Mar 23, 2026

Multidisciplinary Approach to Obesity Management: A Case Report
Published on: May 30, 2025
Obesity, Prediabetes, and Perceived Stress in Municipal Workers
Louise C O'Keefe1, Kathleen C Brown2, Karen H Frith1
11 University of Alabama in Huntsville.
Identifying obesity and prediabetes predictors in municipal workers is crucial for heart disease prevention. Age, race, and lifestyle factors significantly predict obesity, while age, race, and BMI predict prediabetes.
Area of Science:
- Occupational Health
- Cardiovascular Disease Epidemiology
- Metabolic Health
Background:
- Heart disease is a leading cause of death in the US, with obesity and diabetes as major risk factors.
- Stress exacerbates the risk of heart disease, highlighting the need to understand contributing factors in working populations.
- Identifying predictors of obesity and prediabetes is clinically valuable for preventative strategies in occupational settings.
Purpose of the Study:
- To examine the relationships among obesity, prediabetes, and perceived stress in a municipal working population.
- To identify significant predictors of obesity and prediabetes within this demographic.
- To inform occupational health nurses' evaluations and interventions.
Main Methods:
- Cross-sectional, correlational study design.
- Utilized a subset of worksite wellness program data from municipal employees screened in 2010-2011.
- Employed multiple regression models to analyze predictor variables.
Main Results:
- Obesity predictors included age, gender, race, HA1c, shift schedule, physical activity, and occupation (p < .01).
- Prediabetes predictors were age, Black race, and body mass index (BMI) (p < .01).
- Perceived stress was not a significant predictor of obesity or prediabetes in this cohort.
Conclusions:
- Age, race, BMI, and lifestyle factors are key predictors of obesity and prediabetes in municipal workers.
- Perceived stress did not emerge as a significant predictor in this study.
- Findings offer guidance for occupational health nurses in risk assessment and highlight areas for further research.
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