Skip to main content
SpringerLink
Log in

Comparison of a single global item and an index of a multi-item health status measure among persons with and without diabetes in the US

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

This study examined the hypothesis that a single global item can be substituted for an index of a multi-item assessment and lead to equivalent interpretative outcomes. Substitutability would be demonstrated if: (1) the two measures were strongly correlated, and regression analysis showed that the same variables accounted for variation in each measure, and (2) difference scores between multi-item and global scores were close to zero and remained so as socio-demographic and co-morbid conditions varied. A multi-item assessment was constructed by mapping items from the NHANES I Epidemiologic Follow-up Study (NHEFS), using available data for persons with and without diabetes, onto the health-status classification system of the Health Utilities Index Mark 1 (HUI), creating the NHEFS-HUI. NHEFS-HUI data, when correlated to the self-assessed health status (SAHS) item, revealed a coefficient of 0.55. Regression analyses identified 9 of 14 variables contributed to the variability of each health status index, but differences existed in which variables were significant for which measure. Five of the possible 14 difference scores for persons with diabetes and non-diabetics approached zero. Persons with diabetes had lower NHEFS-HUI scores than non-diabetics. These data were considered insufficient for demonstrating substitutability. Suggestions were made on how optimal substitutability could be achieved.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Bartman BA, Rosen MJ, Bradham DD, Weissman J, Hochberg M, Revicki D. Relationship between health status and utility measures in older claudicants. Qual Life Res 1998; 7(1): 67-73.

    Google Scholar 

  2. Bernier J, Berthelor J-M, Barofsky I, Erickson P. Comparison of the health utility index mark III (HUI-III) and the self-assessed health status item in the Canadian population. Qual Life Res 2001; 10(3): 197 (abstract).

    Google Scholar 

  3. Blanch M, Atherton P, Novotny P, Parkinson J, Maurer M, Sloan JA. Comparison of a single versus multiple item quality of life measures in a series of North Central Cancer Treatment Group (NCCTG) clinical trials. Qual Life Res 2002; 11: 635 (abstract).

    Google Scholar 

  4. Bronfort G, Bouter LM. Responsiveness of the general health status in chronic low back pain: A comparison of the COOP Charts and the SF-36. Pain 1999; 83: 201-209.

    Google Scholar 

  5. Coast J, Peters TJ, Richards SH, Gunnell DJ. Use of the EuroQoL among elderly acute care patients. Qual Life Res 1998; 7: 1-10.

    Google Scholar 

  6. Fryback D, Dasbach EJ, Klein R, et al. The Beaver Dam Health Outcomes Study: Initial catalog of health-state quality factors. Med Dec Making 1993; 13(2): 89-102.

    Google Scholar 

  7. Sloan JA, Loprinzi CL, Kuross SA, et al. Randomized comparison of four tools measuring overall quality of life in patients with advanced cancer. J Clin Oncol 1998; 16: 3662-3673.

    Google Scholar 

  8. Cohen, J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. New Jersey: Lawrence Erlbaum, 1988.

    Google Scholar 

  9. Hurny C, Bernhard J, Coates A, et al. Responsiveness of a single item-indicator versus a multi-item scale: Assessment of emotional well-being in an international adjuvant breast cancer trial. Med Care 1996; 34(3): 234-248.

    Google Scholar 

  10. Jenkinson C, Lawrence K, McWhinnie D, Gordon J. Sensitivity to change of healths status measures in a randomized controlled trial: Comparison of the COOP charts and the SF-36. Qual Life Res 1995; 4: 47-52.

    Google Scholar 

  11. Sloan JA, Aaronson N, Cappelleri JC, Fairclough DL, Varricchio C, and the Clinical Significance Consensus Meeting Group. Assessing the clinical significance of single items relative to summated scores. Mayo Clinic Pro 2002; 77: 479-487.

    Google Scholar 

  12. Youngblut JM, Casper GR. Single-item indicators in nursing research. Res Nursing Health 1993; 16(6): 459-465.

    Google Scholar 

  13. Fairclough DL. Summary measures and statistics for comparison of quality of life in clinical trials for cancer therapy. Stat Med 1997; 16: 1197-1209.

    Google Scholar 

  14. Vickers AJ, McCarney R. Use of a single global assessment to reduce missing data in a clinical trial with follow-up at one year. Controlled Clin Trials 2003; 24: 731-735.

    Google Scholar 

  15. Nunnally JC, Bernstein IH. Psychometric Theory. New York: McGraw Hill, 1994.

    Google Scholar 

  16. Mc Horney CA, Ware JE, Rogers W, Raczek AE, Lu JFR. The validity and relative precision of MOS short-and-longform health status scales and Dartmouth COOP charts: Results from the Medical Outcome Study. Med Care 1992; 30: MS253-MS265.

    Google Scholar 

  17. Tourangeau R, Rips LJ, Rasinski K. The Psychology of Survey Response. New York: Cambridge, 2000.

    Google Scholar 

  18. World Health Organization. 'World Health Organization constitution.' In Basic Documents. Geneva: World Health Organization, 1947.

    Google Scholar 

  19. Torrance GW, Boyle MH, Horwood SP. Application of multi-attribute utility theory to measure social preferences for health states. Oper Res 1982; 30: 1042-1069.

    Google Scholar 

  20. Kempen GIJM, Miedema I, van den Bos GAM, Ormel J. Relationship of domain-specific measures of health to perceived overall health among older subjects. J Clin Epidemiol 1998; 51: 11-18.

    Google Scholar 

  21. Ware JE Jr, Snow KK, Kosinski M, Gandek B. SF-36 Health Survey: Manual and Interpretation Guide. Boston, MA: The Health Institute: New England Medical Center, 1993.

    Google Scholar 

  22. Bland JM, Altman DG. Comparing two methods of clinical measurement: A personal history. J Epidemiol Comm Health 1995; 47: S7-S14.

    Google Scholar 

  23. Glasgow RE, Ruggiero L, Eakin EG, Dryfoos J, Chodanian L. Quality of life and associated characteristics in a large national sample of adults with diabetes. Diabetes Care 1997; 20(4): 562-567.

    Google Scholar 

  24. Jacobson AM, DeGroot M, Samson JA. The evaluation of two measures of quality of life in patients with type I and type II diabetes. Diabetes Care 1994; 17(4); 267-274.

    Google Scholar 

  25. Miller H. Plan and Operation of the Health and Nutrition Examination Survey. Vital and Health Statistics Series 1, Numbers 10a and 10b. Hyattsville, Maryland: National Center for Health Statistics, 1973.

    Google Scholar 

  26. Engel A, Murphy RS, Maurer K, Collins E. Plan and Operation of the HANES I Augmentation Survey of Adults 25-74 Years. Vital and Health Statistics Series 1, Number 14. Hyattsville, Maryland: National Center for Health Statistics, 1978.

    Google Scholar 

  27. Cohen BB, Barbano HE, Cox CS, et al. Plan and Operation of the NHANES I Epidemiologic Follow-up Study: 1982-1984. Vital and Health Statistics Series 1, Number 22. Hyattsville, Maryland: National Center for Health Statistics, 1987.

    Google Scholar 

  28. Stewart AL, Hays RD, Ware JE. The MOS Short-form General Health Survey: Reliability and Validity in a Patient Population. Med Care 1988; 26: 724-735.

    Google Scholar 

  29. Department of Health and Human Services. Healthy People 2000: National Health Promotion and Disease Prevention Objectives. Washington, DC: U.S. Government Printing Office, 1990.

    Google Scholar 

  30. National Center for Health Statistics. Healthy People 2000 Review, 1994. Hyattsville, Maryland: Public Health Service, 1995.

    Google Scholar 

  31. Erickson P, Anderson JP, Kendall EA, Kaplan M. Using retrospective data for measuring quality of life: National Health Interview Survey data and Quality of Well-being scale. Qual Life Cardio Care 1988; 4: 179-184.

    Google Scholar 

  32. Erickson P, Kendall EA, Anderson JP, Kaplan RM. Using composite health status measures to assess the Nation's health. Med Care 1989; 27(Suppl 3): S66-S76.

    Google Scholar 

  33. Stewart AL, Hays RD, Ware JE Jr. Methods of validating MOS health measures. In: Stewart AL, Ware JE Jr (eds.), Measuring Function and Well-Being, Durham, NC: Duke University Press, 1992, pp. 309-324.

    Google Scholar 

  34. Keeney RL, Raiffa H. Decisions with Multiple Objectives: Preferences and Tradeoffs. New York: Wiley, 1976.

    Google Scholar 

  35. Torrance GW. Health states worse than death. In: von Eimeren W, Engelbrecht R, Flagle CD (eds.), Third International Conference on Systems Science in Health Care. Berlin: Springer Verlag, 1984, pp. 1085-1089.

    Google Scholar 

  36. Gold M, Franks P, Erickson P. Assessing the health of the nation. The predictive validity of a preference-based measure and self-rated health. Med Care 1996; 34(2): 163-177.

    Google Scholar 

  37. Kaplan RM, Erickson P. Gender differences in qualityadjusted survival using a Health Utilities Index. Am J Pre Med 2000; 18(1): 77-82.

    Google Scholar 

  38. Kopec JA, Schultz SE, Goel V, Williams JI. Can the Health Utilities Index measure change? Med Care 2001; 39: 562-574.

    Google Scholar 

  39. Torrance GW, Furlong D, Feeny D, Boyle M. Multi-attribute preference functions. Pharmoco Eco 1995; 7: 503-520.

    Google Scholar 

  40. Guilford JP. Fundamental Statistics in Psychology and Education. 4th edn. New York: McGraw-Hill Book Company, 1956.

    Google Scholar 

  41. Fisher GH. The development and history of the poverty thresholds. Soc Sec Bull 1992; 55(4): 3-14.

    Google Scholar 

  42. Revision in Poverty Statistics, 1959 to 1968. Bureau of the Census; Current Population Reports, Series P-23, No. 28, August 12, 1969.

  43. Statistical Analysis System (SAS) Version 6.08. User's Guide. Cary, North Carolina: SAS Institute, Inc, 1990.

    Google Scholar 

  44. Shah BV, Barnwell BG, Hunt PN, La Vange, LM. SUDAAN User's Manual, Release 5.50. Research Triangle Park: North Carolina: Research Triangle Institute, 1991.

    Google Scholar 

  45. Ingram DD, Makuc D. Statistical Issues in Analyzing the NHANES I Epidemiologic Follow-up Study. Vital and Health Statistics Series 2, Number 121. Hyattsville, Maryland: National Center for Health Statistics, 1994.

    Google Scholar 

  46. Ware JE, Karmos AH. Scales for measuring general health perceptions. Health Ser Res 1976; 11: 396-415.

    Google Scholar 

  47. Bjorner JB, Kristensen TS, Orth-Gomer K, Tibblin G, Sullivan M, Westerholm P. Self-rated Health. Stockholm: Forskningsrådsnämnden, 1996.

    Google Scholar 

  48. National Center for Health Statistics. Health United States: 1994. Hyattsville, Maryland: National Center for Health Statistics, 1995.

    Google Scholar 

  49. Park DC, Nisbett R, Hedden T. Aging, culture and cognition. J Geronte 1999; 54B(2): 75-84.

    Google Scholar 

  50. Jobe JB, White AA, Kelley CL, Mingay DJ, Sanchez MJ, Loftus EF. Recall strategies and memory for health-care visits. Milbank Quart 1990; 68(2): 171-189.

    Google Scholar 

  51. Badia Llach X, Herdman M, Schiaffino A. Determining correspondence between scores on the EQ-5D 'thermometer' and a 5-point categorical rating scale. Med Care 1999; 37(7): 671-677.

    Google Scholar 

  52. Stewart AL, Hays RD, Ware JE Jr. Health Perceptions, Energy/Fatigue and Health Distress Measures. In: Stewart AL, Ware JE Jr (eds.), Measuring Function and Well-Being, Durham, NC: Duke University Press, 1992, pp. 142-172.

    Google Scholar 

  53. Jylh M. Self-rated health revisited: Exploring survey interview episodes with elderly respondents. Soc Sci Med 1994; 39(7): 983-990.

    Google Scholar 

  54. Krause NM, Jay GM. What do global self-rated health items measure? Med Care 1994; 32(9): 930-942.

    Google Scholar 

  55. Tarlov AR, Ware JE, Greenfield S, Nelson EC, Perrin E, Zubkoff M. The Medical Outcome Study: An application of methods for monitoring the results of medical care. JAMA 1989; 262: 925-930.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. The Johns Hopkins School of Medicine, 25 Oak Ridge Road, MA, USA

    I. Barofsky

  2. Pennsylvania State University, USA

    P. Erickson

  3. Centers for Disease Control and Prevention, USA

    M. Eberhardt

Authors
  1. I. Barofsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. Erickson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. Eberhardt
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Barofsky, I., Erickson, P. & Eberhardt, M. Comparison of a single global item and an index of a multi-item health status measure among persons with and without diabetes in the US. Qual Life Res 13, 1671–1681 (2004). https://doi.org/10.1007/s11136-004-0258-4

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-004-0258-4

Search

Navigation