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Race and preference-based health-related quality of life measures in the United States

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Abstract

Background

Health-related quality of life instruments (HRQoL) are widely used to produce measures that summarize population health and to inform decision-making and health policy. Although the literature about the relationship between health and race in the United States is quite extensive, there is a lack of studies that comprehensively examine the relationship between race and preference-based HRQoL. Given the widespread use of these measures, it becomes important to understand the extent of the race differences in HRQoL scores and factors associated with any such differences.

Methods

We examined the differences in HRQoL, between blacks and whites and associated factors, using the summary scores of the SF-6D, EQ-5D, QWB-SA, HUI2, HUI3, administered by telephone to a nationally representative sample of 3,578 black and white US adults between the ages of 35 and 89 in the National Health Measurement Study (NHMS).

Results

Black women had substantially lower HRQoL than white women. The difference was largely explained by sociodemographic and socioeconomic variables. Black men did not differ significantly from white men, except for the EQ-5D. HRQoL among black men was higher at higher income levels, while the HRQoL of black women was especially low compared to other groups at high income levels.

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References

  1. Williams, D., & Mohammed, S. (2009). Discrimination and racial disparities in health: evidence and needed research. Journal of Behavioral Medicine, 32, 20–47.

    Article  PubMed  Google Scholar 

  2. Barr, D. A. (2008). Health disparities in the United States : Social class, race, ethnicity, and health. Baltimore: Johns Hopkins University Press.

    Google Scholar 

  3. Williams, D. R., Yan, Y., Jackson, J. S., & Anderson, N. B. (1997). Racial differences in physical and mental health: Socio-economic status, stress and discrimination. Journal of Health Psychology, 2, 335–351.

    Article  Google Scholar 

  4. Quittner, A. L., Schechter, M. S., Rasouliyan, L., Haselkorn, T., Pasta, D. J., & Wagener, J. S. (2010). Impact of socioeconomic status, race, and ethnicity on quality of life in patients with cystic fibrosis in the United States. Chest, 137(3), 642–650.

    Article  PubMed  Google Scholar 

  5. Xie, J., Wu, E., Zheng, Z., Sullivan, P., Zhan, L., & Labarthe, D. (2008). Patient-reported health status in coronary heart disease in the United States: Age, sex, racial, and ethnic differences. Circulation, 118, 491–497.

    Article  PubMed  Google Scholar 

  6. Gaskin, D., & Frick, K. (2008). Race and ethnic disparities in valuing health. Medical Decision Making, 28, 12–20.

    Article  PubMed  Google Scholar 

  7. Luo, N., Johnson, J., Shaw, J., Feeny, D., & Coons, S. (2005). Self-reported health status of the general adult U.S. population as assessed by the EQ-5D and health utilities index. Medical Care, 43, 1078–1086.

    Article  PubMed  Google Scholar 

  8. Lubetkin, E., Jia, H., Franks, P., & Gold, M. (2005). Relationship among sociodemographic factors, clinical conditions, and health-related quality of life: Examining the EQ-5D in the U.S. general population. Quality of Life Research, 14, 2187–2196.

    Article  PubMed  Google Scholar 

  9. Brooks, R., Rabin, R., & de Charro, F. (2003). The measurement and valuation of health status using EQ-5D: A European perspective. Dordrecht, Netherlands: Kluwer Academic Publishers.

    Google Scholar 

  10. Shaw, J. W., Johnson, J. A., & Coons, S. J. (2005). US valuation of the EQ-5D health states: Development and testing of the DI valuation model. Medical Care, 43(3), 203–220.

    Article  PubMed  Google Scholar 

  11. Torrance, W. G., Feeny, D. H., Furlong, W. J., Barr, R. D., Zhang, Y., & Wang, Q. (1996). Multiattribute utility function for a comprehensive health status classification system: Health utilities index mark 2. Medical Care, 34(7), 702–722.

    Article  PubMed  CAS  Google Scholar 

  12. Feeny, D., Furlong, W., Torrance, G. W., Goldsmith, C. H., Zhu, Z., DePauw, S., et al. (2002). Multiattribute and singleattribute utility functions for the health utilities index mark 3 system. Medical Care, 40, 113–128.

    Article  PubMed  Google Scholar 

  13. Andresen, E. M., Rothenberg, B. M., & Kaplan, R. M. (1998). Performance of a self-administered mailed version of the quality of well-being (QWB-SA) questionnaire among older adults. Medical Care, 36, 1349–1360.

    Article  PubMed  CAS  Google Scholar 

  14. Brazier, J., Roberts, J., & Deverill, M. (2002). The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics, 21, 271–292.

    Article  PubMed  Google Scholar 

  15. Brazier, J., & Roberts, J. (2004). The estimation of a preference-based measure of health from the SF-12. Medical Care, 42, 851–859.

    Article  PubMed  Google Scholar 

  16. Sullivan, P., Lawrence, W., & Ghushchyan, V. (2005). A national catalog of preference-based scores for chronic conditions in the United States. Medical Care, 43, 736–749.

    Article  PubMed  Google Scholar 

  17. House, J., & Williams, D. R. (2003). Understanding and reducing socioeconomic and racial/ethnic disparities in health. In R. Hofrichter (Ed.), Health and social justice: A reader on the politics, ideology, and inequity in the distribution of disease (pp. 89–131). San Francisco: Jossey-Bass.

    Google Scholar 

  18. Fryback, D., Dunham, N., Palta, M., Hanmer, J., Buechner, J., Cherepanov, D., et al. (2007). US norms for six generic health-related quality-of-life indexes from the national health measurement study. Medical Care, 45, 1162–1170.

    Article  PubMed  Google Scholar 

  19. Cherepanov, D., Palta, M., Fryback, D. G., & Robert, S. A. (2010). Gender differences in health-related quality-of-life are partly explained by sociodemographic and socioeconomic variation between adult men and women in the US: Evidence from four US nationally representative data sets. Quality of Life Research (in press).

  20. Robert, S. A., Cherepanov, D., Palta, M., Dunham, N. C., Feeny, D., & Fryback, D. G. (2009). Socioeconomic status and age variations in health-related quality of life: Results from the national health measurement study. Journal of Gerontology: Social Science, 64B, 378–389.

    Article  Google Scholar 

  21. Schafer, J. L. (1997). Analysis of incomplete multivariate data. London: Chapman & Hall.

    Book  Google Scholar 

  22. Kaplan, R. M. (2005). The minimally clinically important difference in generic utility-based measures. COPD, 21, 91–97.

    Article  Google Scholar 

  23. Walters, S. J., & Brazier, J. E. (2003). What is the relationship between the minimally important difference and health state utility values? The case of the SF-6D. Health and Quality of Life Outcomes, 11, 1–4.

    Google Scholar 

  24. Walters, S. J., & Brazier, J. E. (2005). Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Health and Quality of Life Outcomes, 146, 1523–1532.

    Google Scholar 

  25. Coons, S., & Shaw, J. (2005). Generic adult health status measures. In P. Hayers & R. Hays (Eds.), Assessing quality of life in clinical trials (p. 467). New York: Oxford University Press.

    Google Scholar 

  26. National Center for Health Statistics. (2007). Chartbook on trends in the health of Americans. In Health, United States, 2007 (p. 551). Hyattsville, MD.

  27. Ware, D., & Livingston, I. (2004). The life expectancy of the black male: Pressing issues from the cradle to the grave. In I. L. Livingston (Ed.), Praeger handbook of Black American health: Policies, issues behind disparities in health. Westport, CT: Praeger.

    Google Scholar 

  28. Shaw, J., Johnson, J., Chen, S., Levin, J., & Coons, S. (2007). Racial/ethnic differences in preferences for the EQ-5D health states: Results from the U.S. valuation study. Journal of Clinical Epidemiology, 60, 479–490.

    Article  PubMed  Google Scholar 

  29. Perkins, A., Stump, T., Monahan, P., & McHorney, C. (2006). Assessment of differential item functioning for demographic comparisons in the MOS SF-36 health survey. Quality of Life Research, 15, 331–348.

    Article  PubMed  Google Scholar 

  30. Hanmer, J., Hays, R. D., Fryback, D. G., et al. (2007). Mode of administration is important in US national estimates of health-related quality of life. Medical Care, 45, 1171–1179.

    Article  PubMed  Google Scholar 

  31. United States Census Bureau. (2009). Current population survey, 2004 panel. Washington, DC.

  32. Department of Health, Human Services. (2001). Mental health: Culture, race, and ethnicity—a supplement to mental health: A report of the surgeon general. Rockville, MD: Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services.

    Google Scholar 

  33. McHorney, C., Ware, J., Lu, J., & Sherbourne, C. (1994). The MOS 36-item short-form health survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Medical Care, 32, 40–66.

    Article  PubMed  CAS  Google Scholar 

  34. Shavers-Hornaday, V., Lynch, C., Burmeister, L., & Torner, J. (1997). Why are African Americans under-represented in medical research studies? Impediments to participation. Ethnicity and Health, 2, 31–45.

    Article  PubMed  CAS  Google Scholar 

  35. Katz, R., Green, B., Kressin, N., Kegeles, S., Wang, M., James, S., et al. (2008). The legacy of the Tuskegee syphilis study: Assessing its impact on willingness to participate in biomedical studies. Journal of Health Care for the Poor and Underserved, 19, 1168–1180.

    Article  PubMed  Google Scholar 

  36. Thomas, S., & Quinn, S. (1991). The Tuskegee syphilis study, 1932 to 1972: Implications for HIV education and AIDS risk education programs in the black community. American Journal of Public Health, 81, 1498–1505.

    Article  PubMed  CAS  Google Scholar 

  37. Thorpe, R. J., Weiss, C., Xue, Q., & Fried, L. (2009). Transitions among disability levels or death in African American and white older women. Journal of Gerontology Series A Biological Sciences Medical Sciences, 64, 670–674.

    Article  Google Scholar 

  38. Skarupski, K. A., Mendes de Leon, C. F., Bienas, J. L., Scherr, P. A., Zack, M. M., Moriarty, D. G., et al. (2007). Black-white differences in health-related quality of life among older adulta. Quality of Life Research, 16, 287–296.

    Article  PubMed  Google Scholar 

  39. Bratter, J., & Eschbach, K. (2005). Race/ethnic differences in nonspecific psychological distress: Evidence from the national health interview survey. Social Science Quarterly, 86, 620–644.

    Article  Google Scholar 

  40. Ferraro, K. (1993). Are black older adults health-pessimistic? Journal of Health and Social Behavior, 34, 201–214.

    Article  PubMed  CAS  Google Scholar 

  41. Kessler, R., & Neighbors, H. (1986). A new perspective on the relationships among race, social class, and psychological distress. Journal of Health and Social Behavior, 27, 107–115.

    Article  PubMed  CAS  Google Scholar 

  42. Brown, D. (2003). A conceptual model of mental well-being for African American women. In D. Brown & V. Keith (Eds.), In and out of our right minds: The mental health of African American women (Vol. xv, 301 p). New York: Columbia University Press.

    Google Scholar 

Download references

Acknowledgments

Claudia Pereira was funded through a CAPES/Fulbright fellowship. Data collection (The National Health Measurement Study) was funded through grant P01 AG020679 from the National Institute of Aging as was Mari Palta’s effort on the paper.

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Authors and Affiliations

  1. Fundação Oswaldo Cruz, Escola Nacional de Saúde Pública Sergio Arouca, Departamento de Administração e Planejamento em Saúde, Rua Leopoldo Bulhões 1480, sala 724 Manguinhos, Rio de Janeiro, RJ, 21041-210, Brazil

    Claudia C. A. Pereira

  2. Population Health Sciences, and Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin, 689 Warf Office Building, 610 Walnut St, Madison, WI, 53726, USA

    Mari Palta

  3. Population Health Sciences, School of Medicine and Public Health, University of Wisconsin, 787 Warf Office Building, 610 Walnut St, Madison, WI, 53726, USA

    John Mullahy

  4. Population Health Sciences, School of Medicine and Public Health, University of Wisconsin, 16451 Harbour Ln., Huntington Beach, CA, 92649, USA

    Dennis G. Fryback

Authors
  1. Claudia C. A. Pereira
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  2. Mari Palta
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  4. Dennis G. Fryback
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Correspondence to Mari Palta.

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Pereira, C.C.A., Palta, M., Mullahy, J. et al. Race and preference-based health-related quality of life measures in the United States. Qual Life Res 20, 969–978 (2011). https://doi.org/10.1007/s11136-010-9813-3

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