Health-Related Factors Associated With the Healthcare Costs of Office Workers

Objective: The purpose of this study was to assess the relative importance of factors associated with total health care costs (THC) among office workers. Methods: Biometnc and anthropometrie values health-related survey responses, and THC for 214 employees wer analyzed. Factors that had a statistica...

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Bibliographic Details
Published in:Journal of occupational and environmental medicine 2008-05, Vol.50 (5), p.593-601
Main Authors: Wilkerson, Gary B., Boer, Nicholas F., Smith, Christine B., Heath, Gregory W.
Format: Article
Language:English
Subjects:
Adult
Age Factors
Anthropometry
Biological and medical sciences
Chronic Disease
Exercise
Female
Health Benefit Plans, Employee
Health Care Costs
Health care expenditures
Health Status Indicators
Health Surveys
Humans
Male
Medical sciences
Metabolic Syndrome - diagnosis
Metabolic Syndrome - economics
Metabolic Syndrome - epidemiology
Middle Aged
Miscellaneous
Obesity - economics
Obesity - epidemiology
Occupational health
Occupational medicine
Occupations - statistics & numerical data
ORIGINAL ARTICLES
Public health. Hygiene-occupational medicine
Regression Analysis
Risk factors
Studies
Transportation
United States
Variance analysis
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Summary:Objective: The purpose of this study was to assess the relative importance of factors associated with total health care costs (THC) among office workers. Methods: Biometnc and anthropometrie values health-related survey responses, and THC for 214 employees wer analyzed. Factors that had a statistically significant (P < 0.05) bivariate correlation with logarithmically transformed THC data wer entered into multiple regression analysis. Results: Age, gender, and SF-36 physical component summary score were identified as THC predictors (F₃₂₁₀ = 20.78, P < 0.001, $R_{adj}^2$ = 0.218). With physical component summary score excluded, age, gender, and exercise level collectively accounted for an almost identical amount of variance (F₃₂₁₀ = 19.64, P < 0.001, $R_{adj}^2$ = 0.212). Factorial ANOVA identified a significant interaction between age category and exercise level (F₃₁₉₈ = 3.04, P = 0.030). Conclusions: Inactivity was the only modifiable factor found to be predictive of THC, which appears to have an increasing effect with advancing age.
ISSN:1076-2752
1536-5948
DOI:10.1097/JOM.0b013e318162f5ad