Race and gender associations between obesity and nine health-related quality-of-life measures
- 571 Downloads
To assess how health-related quality of life (HRQoL) varies by body mass index (BMI) category among gender and racial subgroups using nine HRQoL measures.
Among 3,710 US adults, we evaluated self-reported height, weight, and HRQoL that was measured by six indexes (EQ-5D; HUI2; HUI3; SF-6D; QWB-SA; HALex) and three summary measures (theta; PCS; MCS). Mean HRQoL was estimated by weighted regression for normal, overweight, and obese subgroups (BMI: 18.5–24.9 kg/m2; 25–29.9; and 30–50).
HRQoL was significantly lower (P < 0.0001) with increasing BMI category except for MCS. Obese individuals were 5.3 units lower on PCS (1–100 scale) and 0.05–0.11 lower on the HRQoL indexes (0–1 scale) than those with normal weight. MCS scores were significantly lower for obese than normal-weight among women (P = 0.04) but not men (P = 0.11). Overweight blacks had higher HRQoL than blacks in other BMI categories (P = 0.033).
Six commonly used HRQoL indexes and two of three health status summary measures indicated lower HRQoL with obesity and overweight than with normal BMI, but the degree of decrement varied by index. The association appeared driven primarily by physical health, although mental health also played a role among women. Counter to hypotheses, blacks may have highest HRQoL when overweight.
KeywordsBody mass index Obesity Health-related quality of life Health status EQ-5D SF-6D
Body mass index
Health-related quality of life
Health utilities index mark 2
Health utilities index mark 3
Quality of well-being scale—self-administered
Health and activities limitations index
Physical component score of SF-36v2™
Mental component score of SF-36v2™
Clinically important difference
This work was supported by grant #P01-AG020679 from National Institute on Aging to University of Wisconsin. Dasha Cherepanov was supported by a grant (T32 HS000046) to the University of California, Los Angeles, and the RAND Corporation (Santa Monica, CA) from the Agency for Healthcare Research and Quality for a postdoctoral fellowship in health services research.
Conflict of interest
David Feeny has a proprietary interest in Health Utilities Incorporated, Dundas, Ontario, Canada. HUInc. Distributes copyrighted Health Utilities Index (HUI) materials and provides methodological advice on the use of HUI. None of the other authors declare a conflict of interest.
- 1.Ogden, C., Carroll, M., McDowell, M., & Flegal, K. (2007). Obesity among adults in the United States–no change since 2003–2004. NCHS data brief no 1. Hyattsville, MD: National Center for Health Statistics.Google Scholar
- 3.Centers for Disease Control and Prevention, Physical Activity and Obesity, National Center for Chronic Disease Prevention and Health Promotion Overweight and Obesity Data and Statistics [Internet]. (2009). Accessed May 7, 2009, at: http://www.cdc.gov/obesity/data/index.html.
- 19.Brooks, R., Rabin, R., & de Charro, F. (2003). The measurement and valuation of health status using EQ-5D: A European perspective. Evidence from the EuroQol BIOMED research program. Dordrecht, The Netherlands: Kluwer Academic Publishers.Google Scholar
- 27.Ware, J. E., Jr, Kosinski, M., Bayliss, McHorney, C. A., Rogers, W. H., & Raczek, A. (1995). Comparison of methods for the scoring and statistical analysis of SF-36 health profile and summary measures: Summary of results from the Medical Outcomes Study. Medical Care, 33(4 Suppl), AS264–AS279.PubMedGoogle Scholar
- 33.Ware, J. E., Kosinski, M., & Keller, S. D. (1994). SF-36 physical and mental health summary scales: A user’s manual. Boston, MA: The Health Institute, New England Medical Center.Google Scholar
- 40.Gold, M. R., Siegel, J. E., Russell, L. B., & Weinstein, M. C. (Eds.). (1996). Cost-effectiveness in health and medicine. New York: Oxford University Press.Google Scholar
- 54.Connor Gorber, S., Shields, M., Tremblay, M. S., & McDowell, I. (2008). The feasibility of establishing correction factors to adjust self-reported estimates of obesity. Health Report, 19(3), 71–82.Google Scholar
- 55.Pereira C. C. A, Palta M., Mullahy J., Fryback D. G. Race and preference-based health-related quality of life measures in the United States. Quality of Life Research. (In press).Google Scholar