Post on 02-Feb-2016
description
Measuring Social Inequalities in Health:
Measurement and Value Judgments
Sam HarperMcGill University
NAACCR Seminar24 May 2011
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.”
2
“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 3
Summary Table of Advantages and Disadvantages of Potential Health Disparity Measures
Disparity Measure SymbolAbsolute or
RelativeReference
GroupAll Social
GroupsReflect SES
GradientSocial Group
Weighting
Inequality Aversion Parameter
Graphical Analogue
Total Disparity
Inter-Individual Difference IID Variable ATBOa No No No Yes No
Individual-Mean Difference IMD Variable Average No No No Yes No
Social Group Disparity
Absolute Difference AD Absolute Best No Yes No No Yes
Relative Difference RD Relative Best No Yes No No Yes
Regression-based Relative Effect RRE Relative Best Yes Yes Nob No Yes
Regression-based Absolute Effect RAE Absolute Best Yes Yes Nob No Yes
Slope Index of Inequality SII Absolute Average Yes Yes Yes No Yes
Relative Index of Inequality RII Relative Average Yes Yes Yes No Yes
Index of Disparity IDisp Relative Best Yes No No No No
Population Attributable Risk PAR Absolute Best Yes No Yes No Yes
Population Attributable Risk% PAR% Relative Best Yes No Yes No No
Index of Dissimilarity ID Absolute Average Yes No Yes No Yes
Index of Dissimilarity% ID% Relative Average Yes No Yes No No
Relative Concentration Index RCI Relative Average Yes Yes Yes Yes Yes
Absolute Concentration Index ACI Absolute Average Yes Yes Yes Yes Yes
Between Group Variance BGV Absolute Average Yes No Yes Yes No
Squared coefficient of Variation CV2 Relative Average Yes No Yes No No
Atkinson’s Measure A Relative Average Yes No Yes Yes No
Gini Coefficient Gini Relative Average Yes No Yes No Yes
Theil Index T Relative Average Yes No Yes Yes No
Mean Log Deviation MLD Relative Average Yes No Yes Yes No
Variance of Logarithms VarLog Relative Average Yes No Yes No NoaAll those better off.bIn the case of regression-with grouped data.
4
Health Inequalities: What Aspects of Inequality are Important?
1. Simple or complex measures of health inequality?
2. Scale: Is inequality relative or absolute?
3. Weighting: Who counts, and for how much?
4. Weighing lives: Do we care where changes in health inequality come from?
5. Reference points for measuring inequality: Different from what?
5
1. Simple vs. (More) Complex Measures of Inequality
Pairwise comparisons work well for a few groups
Source: Data2010
% of persons under 65 years of age with health insurance
7
Additional subgroups make summary measures appealing
Source: Data2010
% of persons under 65 years of age with health insurance
8
2. Absolute or Relative Inequality?
The Easy Case: Evidence of clear progress
Trends in esophageal cancer incidence, 1993-2004
0
1
2
3
4
5
6
7
8
9
10
1993 1995 1997 1999 2001 2003
Rat
e pe
r 10
0,00
0
Source: SEER*Stat, 2008
Non-Hispanic Black
Non-Hispanic White
10
The Easy Case: Evidence of clear progress
Trends in esophageal cancer incidence, 1993-2004
0
1
2
3
4
5
6
7
8
9
10
1993 1998 2003
Rat
e pe
r 10
0,00
0 po
pula
tion
1.0
1.3
1.5
1.8
2.0
2.3
2.5
Rat
e ra
tio
Non-Hispanic Black
Non-Hispanic White
Rate Ratio (Black Rate ÷ White Rate)
RateDifference(Black Rate − White Rate)
Source: SEER*Stat Database, 2008 11
12
Harder Case: US prostate cancer mortality, 1969-2005
Black
White
Source: SEER*Stat Database, 2008
“…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?
Rate Ratio
RateDifference
Source: SEER*Stat Database, 2008
26% Reduction
42.3
31.3
2.18
2.38
9% Increase
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
MRR=Mortality Rate Ratio
Evidence of Increasing Black-White Inequalities
16
Trends in black-white inequality in HIV mortality, US 1990-2004
Absolute and relative perspectives
Source: CDC WONDER, 2008
HAART introduced
Black-White Difference
Black-White Ratio
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, 2004World Bank Economist
18
3. Weighting: Should we count individuals equally or social groups equally when
evaluating inequality?
Milanovic’s 3 Concepts of Inequality
20
US educational attainment among those 25 and over, 1965-2003
Source: US Census Bureau21
Percent of the Projected Population by Race and Hispanic Origin for the United States: 2010 and
2050
Black
12%
AI/AN
1%
API
5%
Multi
2%Hispanic
16%
White
64%
API
8%
Multi
3%
AI/AN
1%Black
12%
Hispanic
30%
White
46%
2010 2050
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.”
Are geographic inequalities in life expectancy increasing?
County Life
Expectancy
Unweighted
Measure of
Inequality
Population Weighted Measure
PeriodMin , Max
Index of Disparity
Mean Log Deviation
1969-197356.2 , 85.0
16.8 4.2
1999-200362.0 , 96.1
20.4 3.8
% change in inequality
+21.2 -10.4
Source: Harper et al. (2010)
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?
Measuring Disparity Across Multiple GroupsDo we care whose health improves?
28
y i yrp /ni1
n
/ yrp
pi ln(y ) ln(y i) i1
n
Populationweighted
Difference in log of rates
Index of Disparity Mean Log Deviation
29
0%
10%
20%
30%
40%
50%
<12y 12y 13-15y 16+y
Smok
ing
prev
alen
ce
Before
After
Measuring Disparity Across Multiple GroupsDo we care whose health improves?
5% decline
Before After %Change
Index of Disparity 120.0 110.0 -8%
Mean Log Deviation
121.1 116.1 -5%
30
0%
10%
20%
30%
40%
50%
<12y 12y 13-15y 16+y
Smok
ing
prev
alen
ce
Before
After
Measuring Inequality Across Multiple GroupsDo we care whose health improves?
5% decline
Before After %Change
Index of Disparity 120.0 110.0 -8%
Mean Log Deviation
121.1 103.9 -15%
31
5. Reference points for measuring inequality: Different from what?
Time 2: 10 point increase for Group C
Changes in Index of Inequality Using Different Reference Points
Time 1 Time 2 %Change
Index of Disparity (Reference=Best rate)
300.0 333.3 +11.1%
Index of Disparity (Reference=Avg rate)
38 35.7 -7.1%
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 ”
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, 2004World 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.
40
“Measuring Health Disparities” computer-based file or a CD-ROM; Available at http://open.umich.edu/education/sph/health-disparities/fall2007
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