1. Measuring Health Disparities in Healthy People 2010
Richard J. Klein, MPH
Suzanne P. Hallquist, MSPH
National Center for Health Statistics
Centers for Disease Control and Prevention
Atlanta, Georgia
August 2007

2. Healthy People 2010 Goal II
“… 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 2010: Understanding and Improving Health,
U.S. Department of Health and Human Services, 2000.

3. Identifying disparities
What is important?
. . . It depends…

4. Death rates for four leading causes, women aged 55-64 years, 2001
Am. Ind.
Asian
Hispanic
NH Black
NH White
Deaths per 100,000
100
200
300
400
500
Cancer
Diseases
of heart
CLRD
Stroke
SOURCE: National Vital Statistics System, NCHS/CDC.

5. Rank based on absolute difference from the “best” group rate, 2001
Am. Ind.
Asian
Hispanic
NH Black
NH White
Deaths per 100,000
Cancer
(NH Black)
(NH White)
Diseases of heart
100
200
300
400
500
Absolute difference (deaths per 100,000)
100
200
300
400
500
Cancer
Diseases
of heart
CLRD
Stroke
Absolute difference
SOURCE: National Vital Statistics System, NCHS/CDC.

6. Rank based on relative (%) difference from the “best” group rate, 2001
Am. Ind.
Asian
Hispanic
NH Black
NH White
Deaths per 100,000
100
200
300
400
500
Cancer
Diseases
of heart
CLRD
Stroke
Percent difference
Diseases of heart
(NH Black)
CLRD
(NH White)
(Am. Ind.) .
100
200
300
400
500
600
Percent difference
SOURCE: National Vital Statistics System, NCHS/CDC.

7. Number of deaths averted
Rank based on number of deaths averted if “best” group rate attained, 2001
Am. Ind.
Asian
Hispanic
NH Black
NH White
Deaths per 100,000
100
200
300
400
500
Cancer
Diseases
of heart
CLRD
Stroke
Number of deaths averted
Cancer
(NH White)
CLRD
Diseases of heart
(NH Black)
4,000
8,000
12,000
16,000
Number of deaths averted
SOURCE: National Vital Statistics System, NCHS/CDC.

8. Measuring Disparities in HP2010

9. Key measurement issues
Target attainment vs. disparity elimination
Choice of reference group
Type of statistic:
Absolute vs. relative
Pair-wise vs. summary
Type of outcome:
Adverse vs. favorable
Weighting of summary measures
Ordered categories

10. disparities not eliminated II. Target not attained;
Rate (log scale)
Time
Individual group rates
Rate (log scale)
II. Target not attained;
disparities eliminated
Rate (log scale)
III. Target attained;
disparities not eliminated
Rate (log scale)
IV. Target attained;
disparities eliminated

11. Hepatitis A Incidence, 1997-2003
Per 100,000 population
Hispanic
American Indian/Alaska Native
Black, not Hispanic
White, not Hispanic
Asian/Pacific Islander
2010 target (4.3)
Source: STD Surveillance System, NCHSTP,CDC

12. Key measurement issues
Target attainment vs. disparity elimination
Choice of reference group
Type of statistic:
Absolute vs. relative
Pair-wise vs. summary
Type of outcome:
Adverse vs. favorable
Weighting of summary measures
Ordered categories

13. Percent difference in infant mortality rates for Black non-Hispanic women compared to various reference groups
Reference group
Percent difference for Black non-Hispanics
Percent change in the percent difference
Mean of R/E group rates
69%
60%
- 13%
Total
91%
99% 9%
White non-Hispanic
136%
140% 3%
“Best” group (API)
161%
173% 7%
HP2010 target
282%
209%
- 26%
Percent change in the percent difference
-13% 9% 3% 7%
-26%
69%
91%
136%
161%
282%
60%
99%
140%
173%
209%

14. Key measurement issues
Target attainment vs. disparity elimination
Choice of reference group
Type of statistic:
Absolute vs. relative
Pair-wise vs. summary
Type of outcome:
Adverse vs. favorable
Weighting of summary measures
Ordered categories

15. Infant mortality (IM) rate Relative difference in IM rates
(per 1,000 live births) 50 40 30 20 10
1960
1970
1980
1990
2000
1950
Black
White
Absolute difference in IM rates
(per 1,000 live births) 30 20 10
1960
1970
1980
1990
2000
1950
Relative difference in IM rates
(Ratio: Black / White) 3 2 1
1960
1970
1980
1990
2000
1950
SOURCE: National Vital Statistics System, NCHS/CDC.

16. Key measurement issues
Target attainment vs. disparity elimination
Choice of reference group
Type of statistic:
Absolute vs. relative
Pair-wise vs. summary
Type of outcome:
Adverse vs. favorable
Weighting of summary measures
Ordered categories

17. Percent difference in race/ethnic-specific nephritis death rates compared to the total population rate
Percent Difference*
Percent Difference*
- 20.5%
- 11.4%
Decreasing
Decreasing
Increasing
SOURCE: National Vital Statistics System, NCHS/CDC.

18. Measures disparity among several groups
Summary index
Measures disparity among several groups
∑i PDi
n – 1
PDi is the percent difference from the “best” group rate for each comparison group rate (i)
n is the number of groups

19. Index of disparity for nephritis death rates
SOURCE: National Vital Statistics System, NCHS/CDC.

20. Key measurement issues
Target attainment vs. disparity elimination
Choice of reference group
Type of statistic:
Absolute vs. relative
Pair-wise vs. summary
Type of outcome:
Adverse vs. favorable
Weighting of summary measures
Ordered categories

21. Percent of persons with and without health insurance coverage in two groups
Absolute difference:
80 – 75 = 5
Group 2
Group 1
Percent
Percent difference:
(80 – 75) / 75 = 6.7%
100 80 20 75 25
Percent with health insurance
Percent without health insurance
Absolute difference:
20 – 25 = - 5 80 60
Percent difference:
(20 – 25) / 25 = - 20% 40 20

22. Decisions for HP2010 Reference group: “best” group
Use relative statistics
Measure disparity using:
Pair-wise statistics (Percent Difference)
Summary statistics (Index of Disparity)
Restate measures in terms of adverse outcomes
Summary measures not weighted
Category order not considered

23. Letter to the Editor
“Trivedi and colleagues observed that absolute disparities decreased…for seven of nine measures of health care . Conclusions about changes in disparity over time depend on whether disparities are measured in absolute or relative terms, and whether measures are expressed in terms of favorable or adverse events. In Healthy People 2010…measures are expressed in terms of adverse events and reductions in relative disparities are required to demonstrate progress toward the goal of eliminating disparities. When the data…are analyzed in this way, reductions in absolute disparities for four measures become relative increases, and small increases for two measures become substantial relative increases…. “
Keppel et al, NEJM 2005

24. Table 1. From Trivedi, et al (NEJM, Aug 18, 2005) [Reanalysis based on adverse events and a relative measure of disparity]

25. HP2010 Midcourse Review

27. Decoding the disparity table
“B” identifies the “best” group
Colors indicate the size of the disparity between the individual group and the “best” group rate at the most recent data point:
Percent difference:
Less than 10% or not statistically significant
10-49%
50-99%
100% or more

28. Decoding the disparity table
Arrows indicate the size and direction of the change in disparity between the baseline and MR data points
Disparity Increasing
Disparity Decreasing
Magnitude of Change in Percentage Points
< 10 or not statistically significant
10-49
50-99
100

29. Summary of Findings
Substantial disparities between population groups are evident for many objectives
No change in disparity for any group for most objectives
No consistent pattern of change in disparity for any population group (except males)

30. Elimination of Disparities

32. Infant mortality rates for blacks and whites, 1950 – 2020
Deaths per 1,000 live births 50 40 30 20 10
1950
1960
1970
1980
1990
2000
Black
White
2010
Projected *
2020
* Projected rates are based on race-specific rates of decline from 1980 – 2000.
SOURCE: National Vital Statistics System, NCHS/CDC.

33. How close is close enough?
Given that all groups are unlikely to achieve exactly the
same rate…when are rates “close enough”:
Defined absolute difference (number of units)
Defined relative difference (percent difference from the “best” group)
Defined threshold value
Expert opinion
Smallest detectable difference
How close is close enough?
How might we decide how small a difference is small enough?
Here are some possible ways…

34. Observations
The ability to detect difference is limited by the variability of our data
The limit is greater for small samples
Determination of parity/disparity must consider more than just variability/sample size
1. Our ability to detect differences is limited by the reliability of our data.
The variability is greater for small populations.
Current sample selection schemes are not designed for the purpose of measuring differences between racial and ethnic groups.
I am not suggesting that we should use these calculations to define disparity but I am suggesting that these limits need to be kept in mind.
5. If we can’t detect a difference as small as the one we might choose then we are fooling ourselves.

35. Healthy People 2010 Challenge
To Define Parity / Disparity Ultimately, what is “close enough” is primarily a policy – not a statistical – consideration
The challenge to Healthy People is to define parity
If we can’t define what parity is, then we really don’t know what disparity is either.
So, the business of measuring disparities in Healthy People 2010 is unfinished…

36. Contact Information
Richard J. Klein, MPH
Acting Chief, Health Promotion Statistics Branch
CDC/National Center for Health Statistics
3311 Toledo Road, Room 6317
Hyattsville, MD 20782