Canadian Journal of Public Health

, Volume 95, Issue 6, pp 460–464 | Cite as

Potential Savings from Reducing Inequalities in Health

  • Noralou P. RoosEmail author
  • Kip Sullivan
  • Randy Walld
  • Leonard MacWilliam



Numerous studies have established that socio-economic position is positively related to health status, but we know little about the real costs of these differences across an entire population. This paper estimates the potential savings in morbidity and dollars from reducing the inequalities in health among Winnipeg residents.


We measure excess morbidity by examining rates of premature death, hip fracture, and heart attack according to the relative affluence of the Winnipeg neighbourhood. We also assess the total expenditures on physician and hospital care by neighbourhood of residence. We then estimate the savings that could have been achieved if 1) the health of the two poorest quintiles had been raised to the level of the middle quintile, and 2) the health of the poorest four quintiles had been raised to the level of the top quintile.


Thirty-seven percent of Winnipeg’s premature deaths, 22% of the heart attacks, 20% of the hip fractures and 15% of total expenditures on hospitals and physicians ($62 million in 1 999 dollars) could have been avoided if residents of the less wealthy 80% of neighbourhoods enjoyed health similar to those in the wealthiest neighbourhoods.


The potential savings from reducing the socio-economic-related differences in health are high, whether they are measured in terms of morbidity or dollars. Research is needed to determine the extent to which these potential savings are achievable.



De nombreuses études ont confirmé l’existence d’un lien positif entre le statut socio-économique et l’état de santé, mais on sait très peu de choses sur les coûts réels des écarts socio-économiques à l’échelle d’une population. Nous avons voulu évaluer les économies possibles, en morbidité et en argent, d’une réduction des inégalités sur le plan de la santé dans la population de Winnipeg.


Nous avons mesuré la surmorbidité en examinant les taux de décès prématurés, de fractures de la hanche et de crises cardiaques selon l’aisance relative des quartiers de Winnipeg. Nous avons aussi analysé les dépenses totales en soins médicaux et hospitaliers selon le quartier de résidence. Enfin, nous avons évalué les économies qui auraient pu être réalisées: 1) si la santé dans les deux quintiles les plus pauvres était haussée au niveau de celle du quintile intermédiaire et 2) si la santé dans les quatre quintiles les plus pauvres était haussée au niveau de celle du quintile supérieur.


À Winnipeg, 37 % des décès prématurés, 22 % des crises cardiaques, 20 % des fractures de la hanche et 15 % des dépenses totales en soins hospitaliers et médicaux (62 millions, en dollars de 1999) auraient pu être évités si l’état de santé des résidents des quartiers les moins aisés (80 %) était le même que dans les quartiers les plus aisés.


Il serait possible de réaliser d’importantes économies (qu’elles soient mesurées en morbidité ou en argent) en réduisant les écarts sur le plan de la santé liés au statut socio-économique. Il faudrait pousser la recherche pour déterminer la mesure dans laquelle de telles économies seraient réalisables.


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  1. 1.
    DHHS. Inequalities in health: A report of a research working group. London: DHSS, 1980.Google Scholar
  2. 2.
    Gorey KM, Holowaty EJ, Laukkanen E, Fehringer G, Richter NL. An international comparison of cancer survival: Advantage of Toronto’s poor over the near poor of Detroit. Can J Public Health 1998;89(2):102–4.Google Scholar
  3. 3.
    Lundberg O. Causal explanations for class inequality and health: An empirical analysis. Soc Sci Med 1991;32:385.CrossRefGoogle Scholar
  4. 4.
    Pappas G, Queen S, Hadden W, Fisher G. The increasing disparity in mortality between socioeconomic groups in the United States, 1960 and 1986. N Engl J Med 1993;329(2):103–9.CrossRefGoogle Scholar
  5. 5.
    Stamler R, Hardy RJ. Educational level and 5-year all-cause mortality in the hypertension detection and follow-up program. Hypertension 1987;9:641.CrossRefGoogle Scholar
  6. 6.
    Vagero D. Inequality in health — Some theoretical and empirical problems. Soc Sci Med 1991;32:367.CrossRefGoogle Scholar
  7. 7.
    Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Board on Health Sciences Policy, Institute of Medicine, 2003,
  8. 8.
    U.S. General Accounting Office. Public Health: A health status indicator for targeting federal aid to states. GAO/HEHS-97-13 November, 1996.Google Scholar
  9. 9.
    Kindig D. Purchasing Population Health: Paying for Results. Ann Arbor, MI: The University of Michigan Press, 1997.CrossRefGoogle Scholar
  10. 10.
    Mays N, Chinn S, Ho K. Interregional variations in measures of health from the health and lifestyle survey and their relation with indicators of health care need. J Epidemiol Community Health 1992;46:38–47.CrossRefGoogle Scholar
  11. 11.
    Reid RJ, Roos NP, MacWilliam L, Frohlich N, Black C. Assessing population need using a claims-based ACG morbidity measure: A validation analysis in the province of Manitoba. Health Serv Res 2002;37(5):1345–64.CrossRefGoogle Scholar
  12. 12.
    Wennberg JE, Freeman J, Culp W. Are hospital services rationed in New Haven or over-utilized in Boston? Lancet 1987;1(8543):1185–88.CrossRefGoogle Scholar
  13. 13.
    Wennberg JE, Cooper MM. Variations, Patient Need, Practice Style and Hospital Capacity. In: The Quality of Medical Care in the United States: A report on the Medicare Program, The Dartmouth Atlas of Health Care in the United States. Chicago: American Hospital Publishing Inc., 1999.Google Scholar
  14. 14.
    Canadian Institute for Health Information. DAD Resource Indicators for Use with Complexity. Ottawa, 1999.Google Scholar
  15. 15.
    Finlayson G, Roos NP, Jacobs P, Watson D. Using the Manitoba Hospital Management Information System: Comparing Average Cost Per Weighted Case and Financial Ratios of Manitoba Hospitals (1997/98). Winnipeg: Manitoba Centre for Health Policy, 2001. Available at Scholar
  16. 16.
    Roos LL, Sharp SM, Cohen MM. Comparing clinical information with claims data: Some similarities and differences. J Clin Epidemiol 1991;44(9):881–88.CrossRefGoogle Scholar
  17. 17.
    Roos LL, Nicol J, Cageorge S. Using administrative data for longitudinal research: Comparisons with primary data collection. J Chron Dis 1987;40(1):41–49.CrossRefGoogle Scholar
  18. 18.
    Roos LL, Sharp SM, Wajda A. Assessing data quality: A computerized approach. Soc Sci Med 1989;28(2):175–82.CrossRefGoogle Scholar
  19. 19.
    Manga P, Broyles R, Angus D. The determinants of hospital utilization under a universal public insurance programme in Canada. Med Care 1987;25:658–70.CrossRefGoogle Scholar
  20. 20.
    Siemiatycki J, Richardson L, Pless IB. Equality in medical care under national health insurance in Montreal. N Engl J Med 1980;303:10–15.CrossRefGoogle Scholar
  21. 21.
    Haan M, Kaplan GA, Camacho T. Poverty and health: Prospective evidence from the Alameda County Study. Am J Epidemiol 1987;125:989.CrossRefGoogle Scholar
  22. 22.
    Carstairs V, Morris R. Deprivation: Explaining differences in mortality between Scotland, England and Wales. BMJ 1989;29:866–89.Google Scholar
  23. 23.
    Keskimaki I, Salinto M, Aro S. Socioeconomic equity in Finnish hospital care in relation to need. Soc Sci Med 1995;41:425.CrossRefGoogle Scholar
  24. 24.
    Pamuk E, Makuc D, Heck K, Reuben C, Lochner K. Socioeconomic Status and Health Chartbook. Health, United States, 1998. Hyattsville: National Center for Health Statistics, 1998.Google Scholar
  25. 25.
    Marmot M. Multilevel approaches to understanding social determinants. In: Berkman LF, Kawachi I (Eds.), Social Epidemiology. London, England: Oxford University Press, 2000;349–67.Google Scholar
  26. 26.
    Mustard CA, Derksen S, Berthelot J-M, Wolfson M. Assessing ecologic proxies for household income: A comparison of household and neighbourhood level income measures in the study of population health status. Health and Place 1999;5(2):157–71.CrossRefGoogle Scholar
  27. 27.
    Krieger N. Women in social class: A methodologie study comparing individual, household and census measures as predictors of black/white differences in reproductive history. J Clin Epidemiol Community Health 1991;45:35–42.CrossRefGoogle Scholar
  28. 28.
    Diez Roux AV, Nieto FJ, Muntaner C, Tyroler HA, Comstock GW, Shahar E, et al. Neighborhood environments and coronary heart disease: A multilevel analysis. Am J Epidemiol 1997;146(1):48–62.CrossRefGoogle Scholar
  29. 29.
    Veugelers PJ, Yip AM. Socioeconomic disparities in health care use: Does universal coverage reduce inequalities in health? J Epidemiol Community Health 2003;57:424–28.CrossRefGoogle Scholar
  30. 30.
    Finkelstein M. Ecologie proxies for household income: How well do they work for the analysis of health and health care utilization? Can J Public Health 2004;95(2):90–94.Google Scholar
  31. 31.
    Mustard CA, Finlayson M, Derksen S, Berthelot J-M. What determines the need for nursing home admission in a universally insured system. J Health Serv Res Policy 1999;4:197–203.CrossRefGoogle Scholar
  32. 32.
    Roos NP, Stranc L, Peterson S, Mitchell L, Bogdanovic B, Shapiro E. A look at home care in Manitoba. Winnipeg, MB: Manitoba Centre for Health Policy, 2001.Google Scholar
  33. 33.
    Metge C, Black C, Peterson S, Kozyrskyj A. The population’s use of pharmaceuticals. Med Care 1999;37(Suppl.):JS42–JS59.CrossRefGoogle Scholar
  34. 34.
    Gupta S, Roos LL, Walld R, Traverse D, Dahl M. Delivering equitable care: Comparing preventive services in Manitoba. Am J Public Health 2003;93(12):2086–92.CrossRefGoogle Scholar
  35. 35.
    Mechanic D. Disadvantage, inequality, and social policy. Health Affairs 2002;21:48–59.CrossRefGoogle Scholar
  36. 36.
    Roos NP, Mustard CA. Variation in health and health care use by socioeconomic status in Winnipeg, Canada: Does the system work well? Yes and no. Milbank Q 1997;75:89–111.CrossRefGoogle Scholar
  37. 37.
    Manton K. The dynamics of population aging: Demography and policy analysis. Milbank Q 1991;69(2):309–38.CrossRefGoogle Scholar
  38. 38.
    Bailar JC, Gornik HL. Cancer undefeated. N Engl J Med 1997;336:1569–1574.CrossRefGoogle Scholar
  39. 39.
    Tsevat J, Weinstein M, Williams W, Tosteson A, Goldman L. Expected gains in life expectancy from various coronary heart disease risk factor modifications. Circulation 1991;83:1194–201.CrossRefGoogle Scholar
  40. 40.
    Roos NP, Forget E, Walld R, MacWilliam L. Does universal comprehensive insurance coverage encourage unnecessary use? Evidence from Manitoba says “no”. CMAJ 2004;170(2):209–14.PubMedPubMedCentralGoogle Scholar

Copyright information

© The Canadian Public Health Association 2004

Authors and Affiliations

  • Noralou P. Roos
    • 1
    Email author
  • Kip Sullivan
    • 2
  • Randy Walld
    • 1
  • Leonard MacWilliam
    • 1
  1. 1.Manitoba Centre for Health Policy, Department of Community Health Sciences, Faculty of MedicineUniversity of ManitobaWinnipegCanada
  2. 2.Independent Contractor for the Manitoba Centre for Health PolicyCanada

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