Quality of Life Research

, Volume 25, Issue 8, pp 1921–1929 | Cite as

Impact of nine chronic conditions for US adults aged 65 years and older: an application of a hybrid estimator of quality-adjusted life years throughout remainder of lifetime




To estimate quality-adjusted life years (QALY) loss due to each of the following nine chronic conditions—depression, diabetes mellitus, hypertension, heart disease, stroke, emphysema, asthma, arthritis, and cancer.


We ascertained respondents’ health-related quality of life scores and mortality status from the 2005 to 2008 National Health and Nutrition Examination Survey (NHANES) with mortality follow-up data through December 31, 2011. We included respondents aged 65 years and older (n = 2380). A hybrid estimator was used to calculate QALY from two parts: QALY during the follow-up period and QALY beyond the follow-up period. We calculated QALY by each of the nine chronic conditions.


For persons aged 65 and older, QALY throughout the reminder of lifetime was 12.3 years. After adjusting for age- and sex-related differences, depression had an associated 8.2 years of QALY loss; diabetes, 5.6 years; hypertension, 2.5 years; heart disease, 5.4 years; stroke, 6.4 years; emphysema, 8.0 years; asthma, 4.8 years; arthritis, 0.3 years; and cancer, 2.5 years. Compared to persons without any chronic conditions, persons with one condition had an associated 4.7 years of QALY loss; persons with two conditions, 7.9 years; and persons with three or more conditions, 10.8 years.


This study presents a QALY estimator for respondents in the NHANES-Linked Mortality File and demonstrates the utility of this method to other follow-up data. Continued application of our method would enable the burden of disease to be compared for a range of health conditions and risk factors in the ongoing effort to improve population health.


Quality-adjusted life year (QALY) Health-related quality of life (HRQOL) Chronic conditions Burden of disease 


Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interests regarding the publication of this paper.

Ethical statements

This analysis used de-identified data produced by federal agencies in the public domain. Data were downloaded from the Centers for Disease Control and Prevention Website (ftp://ftp.cdc.gov/pub).


  1. 1.
    Institute of Medicine. (2012). Living well with chronic illness: A call for public health action. Washington, DC: The National Academies Press.Google Scholar
  2. 2.
    Roglic, G., & Unwin, N. (2010). Mortality attributable to diabetes: Estimates for the year 2010. Diabetes Research and Clinical Practice, 87(1), 15–19.CrossRefPubMedGoogle Scholar
  3. 3.
    Holmes, J., McGill, S., Kind, P., Bottomley, J., Gillam, S., & Murphy, M. (2000). Health-related quality of life in type 2 diabetes (TARDIS-2). Value in Health, 3(Suppl 1), 47–51.CrossRefPubMedGoogle Scholar
  4. 4.
    Field, M. J., & Gold, M. R. (Eds.). (1998). Summarizing population health: Directions for the development and application of population metrics. Washington, DC: Institute of Medicine, National Academy Press.Google Scholar
  5. 5.
    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
  6. 6.
    Brown, D. S., Jia, H., Zack, M. M., Thompson, W. W., Haddix, A. C., & Kaplan, R. M. (2013). Using health-related quality of life and quality-adjusted life expectancy for effective public health surveillance and prevention. Expert Review of Pharmacoeconomics and Outcomes Research, 13(4), 425–427.CrossRefPubMedGoogle Scholar
  7. 7.
    Gold, M. R., Stevenson, D., & Fryback, D. G. (2002). HALYS and QALYS and DALYS, Oh My: Similarities and differences in summary measures of population health. Annual Review of Public Health, 23, 115–134.CrossRefPubMedGoogle Scholar
  8. 8.
    Murray, C. J., Vos, T., Lozano, R., Naghavi, M., Flaxman, A. D., Michaud, C., et al. (2012). Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: A systematic analysis for the global burden of disease study 2010. Lancet, 380(9859), 2197–2223.CrossRefPubMedGoogle Scholar
  9. 9.
    Sullivan, D. (1971). A single index of mortality and morbidity. HSMHA Health Reports, 86, 347–354.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Chiang, C. L. (1984). Statistical inference regarding life table functions. In C. L. Chiang (Ed.), The life table and its applications (pp. 153–167). Malabar, FL: Robert E. Krieger Publishers.Google Scholar
  11. 11.
    National Research Council. (2010). Accounting for health and health care: Approaches to measuring the sources and costs of their improvement. Panel to Advance a research program on the Design of National Health Accounts, Committee on National Statistics, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.Google Scholar
  12. 12.
    Jia, H., Zack, H. H., & Thompson, W. W. (2011). State quality-adjusted life expectancy for US adults from 1993 to 2008. Quality of Life Research, 20(6), 853–863.CrossRefPubMedGoogle Scholar
  13. 13.
    Glasziou, P. P., Simes, R. J., & Gelber, R. D. (1990). Quality adjusted survival analysis. Statistics in Medicine, 9, 1259–1276.CrossRefPubMedGoogle Scholar
  14. 14.
    Shen, L. Z., Pulkstenis, E., & Moseyni, M. (1999). Estimation of mean quality adjusted survival time. Statistics in Medicine, 18, 1541–1554.CrossRefPubMedGoogle Scholar
  15. 15.
    Gong, Q., & Fang, L. (2012). Asymptotic properties of mean survival estimate based on the Kaplan–Meier curve with an extrapolated tail. Pharmaceutical Statistics, 11, 135–140.CrossRefPubMedGoogle Scholar
  16. 16.
    Stewart, S. T., Cutler, D. M., & Rosen, A. B. (2013). US trends in quality-adjusted life expectancy from 1987 to 2008: Combining national surveys to more broadly track the health of the nation. American Journal of Public Health, 103(11), e78–e87.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Jia, H., Zack, M. M., & Thompson, W. W. (2013). The effects of diabetes, hypertension, asthma, heart disease, and stroke on quality-adjusted life expectancy. Value in Health, 16(1), 140–147.CrossRefPubMedGoogle Scholar
  18. 18.
    Jia, H., Zack, M. M., Thompson, W. W., & Dube, S. R. (2013). Quality-adjusted life expectancy (QALE) loss due to smoking in the United States. Quality of Life Research, 22(1), 27–35.CrossRefPubMedGoogle Scholar
  19. 19.
    Lee, H. Y., Hwang, J. S., Jeng, J. S., & Wang, J. D. (2010). Quality-adjusted life expectancy (QALE) and loss of QALE for patients with ischemic stroke and intracerebral hemorrhage: A 13-year follow-up. Stroke, 41(4), 739–744.CrossRefPubMedGoogle Scholar
  20. 20.
    Oyunbileg, S., Wang, J. D., Sumberzul, N., Chang, Y. Y., & Erdenchimeg, E. (2011). Health impact of pneumoconiosis in Mongolia: Estimation of losses in life expectancy and quality adjusted life expectancy. American Journal of Indian Medicine, 54(4), 285–292.CrossRefGoogle Scholar
  21. 21.
    Richardson, G., & Manca, A. (2004). Calculation of quality adjusted life years in the published literature: A review of methodology and transparency. Health Economics, 12, 1203–1210.CrossRefGoogle Scholar
  22. 22.
    Ong, K. L., Wu, B. J., Cheung, B. M., Barter, P. J., & Rye, K. A. (2013). Arthritis: Its prevalence, risk factors, and association with cardiovascular diseases in the United States, 1999 to 2008. Annals of Epidemiology, 23(2), 80–86.CrossRefPubMedGoogle Scholar
  23. 23.
    Heron, M. (2015). Deaths: Leading causes for 2011. National Vital Statistics Reports, 64(7), 1–96.Google Scholar
  24. 24.
    U.S. Burden of Disease Collaborators. (2013). The state of US health, 1990–2010: Burden of diseases, injuries, and risk factors. JAMA, 310(6), 591–608.CrossRefGoogle Scholar
  25. 25.
    Centers for Disease Control and Prevention (CDC). National Center for Health Statistics (NCHS). National Health and Nutrition Examination Survey Data. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 2005–2006. http://wwwn.cdc.gov/nchs/nhanes/search/nhanes05_06.aspx. Accessed 20 July 2015.
  26. 26.
    Centers for Disease Control and Prevention (CDC). National Center for Health Statistics (NCHS). NCHS Data Linked to Mortality Files. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 2011. http://www.cdc.gov/nchs/data_access/data_linkage/mortality.htm. Accessed 20 July 2015.
  27. 27.
    Centers for Disease Control and Prevention. (2000). Measuring healthy days: Population assessment of health-related quality of life. U.S. Department of Health and Human Services. Centers for Disease Control and Prevention. National Center for Chronic Disease Prevention and Health Promotion. Division of Adult and Community Health. http://www.cdc.gov/hrqol/pdfs/mhd.pdf. Accessed 20 July 2015.
  28. 28.
    Jia, H., & Lubetkin, E. I. (2008). Estimating EuroQol EQ-5D scores from population healthy days data. Medical Decision Making, 28(4), 491–499.CrossRefPubMedGoogle Scholar
  29. 29.
    Jia, H., Zack, M. M., Moriarty, D. G., & Fryback, D. G. (2011). Predicting the EuroQol Group’s EQ-5D Index from CDC’s “Healthy Days” in a US sample. Medical Decision Making, 31(1), 174–185.CrossRefPubMedGoogle Scholar
  30. 30.
    Kroenke, K., Strine, T. W., Spitzer, R. L., Williams, J. B., Berry, J. T., & Mokdad, A. H. (2009). The PHQ-8 as a measure of current depression in the general population. Journal of Affective Disorders, 114(1–3), 163–173.CrossRefPubMedGoogle Scholar
  31. 31.
    Austin, P. C. (2011). An introduction to propensity score methods for reducing the effects confounding in observational studies. Multivariate Behavioral Research, 46(3), 399–424.CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Ferrari, A. J., Charlson, F. J., Norman, R. E., Patten, S. B., Freedman, G., & Murray, C. J. (2013). Burden of depressive disorders by country, sex, age, and year: Findings from the global burden of disease study. PLoS Medicine, 10(11), e1001547.CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Jia, H., Zack, M. M., Thompson, W. W., Crosby, A. E., & Gottesman, I. I. (2015). Impact of depression on quality-adjusted life expectancy (QALE) directly as well as indirectly through suicide. Social Psychiatry and Psychiatric Epidemiology, 50(6), 939–949.CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    American Cancer Society. Cancer Facts & Figures 2015. Atlanta: American Cancer Society; 2015. http://www.cancer.org/acs/groups/content/@editorial/documents/document/acspc-044552.pdf. Accessed on 20 July 2015.
  35. 35.
    Ford, E. S. (2014). Trends in mortality from chronic obstructive pulmonary disease among adults in the United States. Chest,. doi: 10.1378/chest.14-2311.Google Scholar
  36. 36.
    Welch, H. G., & Black, W. C. (2010). Overdiagnosis in cancer. Journal of the National Cancer Institute, 102, 605–613.CrossRefPubMedGoogle Scholar
  37. 37.
    Vos, T., Flaxman, A. D., Naghavi, M., Lozano, R., Michaud, C., Ezzati, M., et al. (2012). Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: A systematic analysis for the global burden of disease study 2010. Lancet, 380(9859), 2163–2196.CrossRefPubMedGoogle Scholar
  38. 38.
    Vogeli, C., Shields, A. E., Lee, T. A., Gibson, T. B., Marder, W. D., Weiss, K. B., et al. (2007). Multiple chronic conditions: Prevalence, health consequences, and implications for quality, care management, and costs. Journal of General Internal Medicine, 22(Suppl 3), 391–395.CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Seligman, F., & Nemeroff, C. B. (2015). The interface of depression and cardiovascular disease: Therapeutic implications. Annals of the New York Academy of Science, 1345(1), 25–35.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Biostatistics, Mailman School of Public Health and School of NursingColumbia UniversityNew YorkUSA
  2. 2.Department of Community Health and Social MedicineSophie Davis School of Biomedical Education/CUNY Medical SchoolNew YorkUSA

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