Waist circumference and body mass index as predictors of health care costs

• Published in: PloS one Vol. 3; no. 7; p. e2619
• Main Authors: Højgaard, Betina, Gyrd-Hansen, Dorte, Olsen, Kim Rose, Søgaard, Jes, Sørensen, Thorkild I A
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 09-07-2008; Public Library of Science (PLoS)
• Subjects: Adult; Aged; Analysis; Anthropometry; Body Composition; Body mass; Body Mass Index; Cancer; Cohort Studies; Cost analysis; Costs; Economic aspects; Evidence-Based Healthcare/Health Services Research and Economics; Female; Health care; Health Care Costs; Health risk assessment; Humans; Male; Middle Aged; Mortality; Prospective Studies; Public Health and Epidemiology; Public Health and Epidemiology/Health Services Research and Economics; Regression analysis; Studies; Denmark
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0002619

In the present study we analyze the relationship between body mass index (BMI) and waist circumference (WC) and future health care costs. On the basis of the relation between these anthropometric measures and mortality, we hypothesized that for all levels of BMI increased WC implies added future health care costs (Hypothesis 1) and for given levels of WC increased BMI entails reduced future health care costs (Hypothesis 2). We furthermore assessed whether a combination of the two measures predicts health care costs better than either individual measure.
Data were obtained from the Danish prospective cohort study Diet, Cancer and Health. The population includes 15,334 men and 16,506 women 50 to 64 years old recruited in 1996 to 1997. The relationship between future health care costs and BMI and WC in combination was analyzed by use of categorized and continuous analyses. The analysis confirms Hypothesis 1, reflecting that an increased level of abdominal fat for a given BMI gives higher health care costs. Hypothesis 2, that BMI had a protective effect for a given WC, was only confirmed in the continuous analysis and for a subgroup of women (BMI<30 kg/m(2) and WC <88 cm). The relative magnitude of the estimates supports that the regressions including WC as an explanatory factor provide the best fit to the data.
The study showed that WC for given levels of BMI predicts increased health costs, whereas BMI for given WC did not predict health costs except for a lower cost in non-obese women with normal WC. Combining WC and BMI does not give a better prediction of costs than WC alone.