measuring social inequalities in health: measurement and value judgments

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.

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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

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“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)

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MRR=Mortality Rate Ratio

Evidence of Increasing Black-White Inequalities

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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

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“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

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3. Weighting: Should we count individuals equally or social groups equally when

evaluating inequality?

Milanovic’s 3 Concepts of Inequality

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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

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“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.

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

Measuring Disparity Across Multiple GroupsDo we care whose health improves?

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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

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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%

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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%

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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

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Example of all social groups moving away from target rate

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Movement away from targets may reduce inequality

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“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

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Understanding inequality is not only challenging for health

Absolute measures

Relative measures

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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.

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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.

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“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

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Thank you

sam.harper@mcgill.ca