title: Health-related factors associated with the healthcare costs of office workers.
abstract: 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
  Biometric and anthropometric values, health-related survey responses, and THC for 214 employees were analyzed. Factors that had a statistically significant (P < 0.05) bivariate correlation with logarithmically transformed THC data were 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, Radj = 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, Radj = 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.
authors.affiliation: Department of Health and Human Performance, University of Tennessee at Chattanooga, Tennessee 37403, USA. Gary-Wilkerson@utc.edu
authors.forename: Gary B
authors.initials: GB
authors.lastname: Wilkerson
authors.forename: Nicholas F
authors.initials: NF
authors.lastname: Boer
authors.forename: Christine B
authors.initials: CB
authors.lastname: Smith
authors.forename: Gregory W
authors.initials: GW
authors.lastname: Heath
mesh_terms: D000328:Adult; D000367:Age Factors; D000886:Anthropometry; D002908:Chronic Disease; D015444:Exercise; D005260:Female; D006264:Health Benefit Plans, Employee; D017048:Health Care Costs; D006305:Health Status Indicators; D006306:Health Surveys; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000175:diagnosis / Q000191:economics / Q000453:epidemiology; D008875:Middle Aged; D009765:Obesity / Q000191:economics* / Q000453:epidemiology; D009790:Occupations / Q000706:statistics & numerical data*; D012044:Regression Analysis; D014186:Transportation; D014481:United States