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Measuring Social Inequalities in Health: Measurement and Value Judgments

Measuring Social Inequalities in Health: Measurement and Value Judgments. Sam Harper McGill University NAACCR Seminar 24 May 2011. Healthy People Inequality-Related Goals, United States. Healthy People 2010:

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Measuring Social Inequalities in Health: Measurement and Value Judgments

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  1. Measuring Social Inequalities in Health:Measurement and Value Judgments Sam Harper McGill University NAACCR Seminar 24 May 2011

  2. Healthy People Inequality-Related Goals, United States Healthy People 2010: “to eliminate health disparities among segments of the population, including differences that occur by gender, race or ethnicity, education or income, disability, geographic location, or sexual orientation.” Healthy People 2020: “Achieve health equity, eliminate disparities, and improve the health of all groups.”

  3. “Inequality” is an ambiguous concept “If a concept has some basic ambiguity, then a precise representation of that ambiguous concept must preserve that ambiguity…This issue is quite central to the need for descriptive accuracy in inequality measurement, which has to be distinguished from fully ranked, unambiguous assertions.” -Amartya Sen, On Economic Inequality, 1997

  4. Health Inequalities: What Aspects of Inequality are Important? • Simple or complex measures of health inequality? • Scale: Is inequality relative or absolute? • Weighting: Who counts, and for how much? • Weighing lives: Do we care where changes in health inequality come from? • Reference points for measuring inequality: Different from what?

  5. 1. Simple vs. (More) Complex Measures of Inequality

  6. Pairwise comparisons work well for a few groups % of persons under 65 years of age with health insurance Source: Data2010

  7. Additional subgroups make summary measures appealing % of persons under 65 years of age with health insurance Source: Data2010

  8. 2. Absolute or Relative Inequality?

  9. The Easy Case: Evidence of clear progress Non-Hispanic Black Non-Hispanic White Source: SEER*Stat, 2008

  10. The Easy Case: Evidence of clear progress Non-Hispanic Black Rate Ratio (Black Rate ÷ White Rate) Non-Hispanic White Rate Difference (Black Rate − White Rate) Source: SEER*Stat Database, 2008

  11. Harder Case: US prostate cancer mortality, 1969-2005 Black White Source: SEER*Stat Database, 2008

  12. “…racial disparities in mortality from cancers potentially affected by screening and treatment increased over most of the interval since 1975.”

  13. Diverging Measures of Inequality: Are we making progress? 9% Increase Rate Ratio 2.38 2.18 42.3 Rate Difference 26% Reduction 31.3 Source: SEER*Stat Database, 2008

  14. “National Black-White disparities widened significantly after the introduction of HAART, especially among women and the elderly…In no case was there overlap in the age-specific 95% confidence intervals for the pre-HAART versus post-HAART period.” “These data show that Black–White risks increased after the introduction of HAART.” -Levine et al. (2007)

  15. Evidence of Increasing Black-White Inequalities MRR=Mortality Rate Ratio

  16. Trends in black-white inequality in HIV mortality, US 1990-2004Absolute and relative perspectives Black-White Difference Black-White Ratio HAART introduced Source: CDC WONDER, 2008

  17. “Inequality” is an ambiguous concept “There is no economic theory that tells us that inequality is relative, not absolute. It is not that one concept is right and the other wrong. Nor are they two ways of measuring the same thing. Rather, they are two different concepts.” -Martin Ravallion, 2004 World Bank Economist

  18. 3. Weighting: Should we count individuals equally or social groups equally when evaluating inequality?

  19. Milanovic’s 3 Concepts of Inequality

  20. US educational attainment among those 25 and over, 1965-2003 Source: US Census Bureau

  21. Percent of the Projected Population by Race and Hispanic Origin for the United States: 2010 and 2050 2050 2010 Source: US Census Bureau, 2008

  22. Impact of population weighting on health inequality trends

  23. “We report the standard deviation (SD) of life expectancies of the 2,068 county units in the United States” “There was a steady increase in mortality inequality across the US counties between 1983 and 1999, resulting from stagnation or increase in mortality among the worst-off segment of the population.”

  24. Are geographic inequalities in life expectancy increasing?

  25. Issues to consider regarding weighting • Weighting individuals equally is consistent with practice for estimating population average health, and allows for inequality measures to be responsive to demographic change. • Weighting social groups equally (and therefore individuals unequally in most cases) may make sense if one is concerned with disproportionate impacts on small or marginalized social groups.

  26. 4. Weighting: Do we care where changes in health inequality come from?

  27. Measuring Disparity Across Multiple GroupsDo we care whose health improves?

  28. Index of Disparity Mean Log Deviation Difference in log of rates Population weighted

  29. Measuring Disparity Across Multiple GroupsDo we care whose health improves? 5% decline

  30. Measuring Inequality Across Multiple GroupsDo we care whose health improves? 5% decline

  31. 5. Reference points for measuring inequality: Different from what?

  32. Time 2: 10 point increase for Group C Group

  33. Example of all social groups moving away from target rate

  34. Movement away from targets may reduce inequality

  35. “we have systematically compared this same set of summary measures of disparity across 22 separate analyses of cancer incidence, mortality, and risk factors and found that, in nearly half of all cases, a substantive judgment about disparity trends required a priori decisions about whether disparities should be measured in absolute or relative terms or whether to use population-weighted versus unweighted disparity measures ”

  36. Value judgments are inherent in the measurement of inequality “[T]he implicit values in empirical work matter greatly to the conclusions drawn about the distributive justice of current globalization processes. And arguments can be made both ways.” -Martin Ravallion, 2004 World Bank Economist

  37. Understanding inequality is not only challenging for health Absolute measures Relative measures

  38. Conclusions • Measures of health inequality are not value neutral. • Scale of measurement • Weighting: how much and to whom? • Reference points: different from what standard? • The choices above have an important impact on our judgments of both the magnitude of health inequality and whether health inequalities are worsening or improving. • Monitoring health inequalities requires both precise measurement and value judgments—they are inseparable. • A suite of health inequality measures is likely necessary to provide a complete description of the magnitude of inequality.

  39. Resources, Methods, and Empirical Examples • Harper S, Lynch J. Methods for Measuring Cancer Disparities: A Review Using Data Relevant to Healthy People 2010 Cancer-Related Objectives. Washington: NCI, 2005 • Harper S, Lynch J. Selected Comparisons of Measures of Health Disparities Using Databases Containing Data Relevant to Healthy People 2010 Cancer-Related Objectives. Washington DC: NCI, 2007 • Harper S, Lynch J, Meersman SC, Breen N, Davis WW, Reichman ME. An Overview of Methods for Monitoring Social Disparities in Cancer with an Example Using Trends in Lung Cancer Incidence by Area-Socioeconomic Position and Race-Ethnicity, 1992-2004. Am J Epidemiol. 2008;167: 889-99. • Harper S, Lynch J, Meersman SC, Breen N, Davis WW, Reichman MC. Trends in Area-Socioeconomic and Race-Ethnic Disparities in Breast Cancer Incidence, Stage at Diagnosis, Screening, Mortality, and Survival among Women Ages 50 Years and Over (1987-2005). Cancer Epid Biomarkers Prev 2009;18:121-31. • Harper S, King NB, Meersman SC, Reichman ME, Breen N, Lynch J. (2010) Implicit Value Judgments in the Measurement of Health Inequalities. Milbank Quarterly. 2010;88:4-29. “Measuring Health Disparities” computer-based file or a CD-ROM; Available at http://open.umich.edu/education/sph/health-disparities/fall2007

  40. Acknowledgements • NCI collaborators: • Steve Meersman • Marsha Reichman • Nancy Breen • Bill Davis • Steve Scoppa • Dave Campbell • John Lynch, University of Adelaide • Nicholas B. King, McGill University • WHO Scientific Resource Group On Health Equity Analysis And Research • Canadian Institutes for Health Research • Fonds de la Recherche en Santé du Québec

  41. Thank you sam.harper@mcgill.ca

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