From Politics to Parity: Using a Health Disparitiies Index to Guide Legislative Efforts for Health Equity

RESEARCH AND PRACTICE

From Politics to Parity: Using a Health Disparities Index to
Guide Legislative Efforts for Health Equity
Bryant Cameron Webb, BA, Sean L. Simpson, PhD, and Kristen G. Hairston, MD, MPH

The US Congress took its first stand against
Objectives. We created an index quantifying the longitudinal burden of racial
minority health disparities with the passage of
health disparities by state and compared this index to variables to guide the
the Minority Health and Health Disparities
construction of, and validate support for, legislative efforts aimed at eliminating
Research and Education Act in October 2000. health disparities.
This measure commissioned the creation of Methods. We evaluated 5 focus areas of greatest racial disparities in health
the National Center for Minority Health and from 1999 to 2005 and compiled state health disparities index (HDI) scores. We
Health Disparities and mandated health dis- compared these scores with variables representing the purported social de-
parities research and reporting.1 The goal was to terminants of health.
conscientiously move the discourse from identi- Results. Massachusetts (0.35), Oklahoma (0.35), and Washington (0.39) aver-
fying health disparities to eliminating them. aged the fewest disparities. Michigan (1.22), Wisconsin (1.32), and Illinois (1.50)
The years that followed brought progress in averaged the greatest disparities. The statistical reference point for nationwide
average racial disparities was 1.00. The longitudinal mixed model procedure
researching causation, positing solutions, and
yielded statistically significant correlations between HDI scores and Black state
supporting promising models for the elimination
population percentage as well as with the racial gap in uninsured percentages.
of these disparities. The congressionally man-
We noted a trend for HDI correlations with median household income ratios.
dated Institutes of Medicine report Unequal Conclusions. On the basis of the HDI-established trends in the extent and
Treatment grouped factors of causation into 3 distribution of racial health disparities, and their correlated social determinants
basic areas: health system–level factors, care of health, policymakers should consider incorporating this tool to advise future
process variables, and patient-level variables.2 efforts in minority health legislation. (Am J Public Health. 2011;101:554–560. doi:
In addition, its authors proffered strategies 10.2105/AJPH.2009.171157)
for achieving health equity with recommen-
dations that included legal, regulatory, and
policy interventions.2 When considered in sum, these state and METHODS
With increasing research and dialogue, legis- federal legislative efforts have ushered in a new
lators began considering the next appropriate age of health disparities discourse. Champions Six of the most glaring indicators of racial
intervention. Congress has continued to debate of comprehensive health equity legislation and ethnic health disparities, as referenced by
solutions to the health care issues facing minority argue that it is a necessary adjunct to existing the Department of Health and Human Services,
communities, introducing 6 comprehensive mi- efforts to eliminate racial and ethnic health were the foundation for this HDI. These focus
nority health equity bills since 2000. In 2007, disparities. Skeptics assert that the disparities areas are: cancer screening and management,
the 110th Congress saw the introduction of an can be largely addressed through generally cardiovascular disease (CVD), diabetes, HIV/
unprecedented 16 health disparities–focused improving access to quality care for all Amer- AIDS, immunizations, and infant mortality.6
bills.3 Despite the increasing legislative interest in icans. Most, however, appreciate the utility in Mortality was selected as the primary outcome
improving minority health, no comprehensive bringing the discussion into the legislative for each condition as a proxy for disease severity,
minority health measure has become public law arena as this issue continues to gain momen- because of its value as a more precise endpoint
since the Minority Health and Health Disparities tum. than morbidity and its compelling significance
Research and Education Act of 2000. In this context, we recognized a need to to legislators. We omitted immunization statistics,
The proposition of legislative remedies for create tools to guide legislative efforts for as immunization is unique among the 6 focus
health disparities has not been unique to achieving minority health equity. The goals areas as it is a preventive measure rather than
Congress. Since 1999, a majority of state of our analysis were 3-fold: (1) to establish an a distinct cause of mortality.
legislatures have passed minority health legis- index depicting variations in US racial health We obtained mortality statistics from the
lation.4 These laws have addressed cultural disparities; (2) to evaluate the association be- National Center for Health Statistics Com-
competency, health professional recruitment and tween this health disparities index (HDI) and pressed Mortality File from 1999 to 20057 for
retention, and disease burden or risk factor known social determinants of health; and (3) to each of the 5 disease processes. We specifically
management. Furthermore, 40 states created use statistical correlations to help guide mi- calculated crude mortality rates per 100 000 for
offices of minority health, and 4 states designated nority health legislative interventions at the Black and White populations aged 20 to 64
official minority health contacts.5 state and federal levels. years in all 50 states. For each disease process,

554 | Research and Practice | Peer Reviewed | Webb et al. American Journal of Public Health | March 2011, Vol 101, No. 3


we calculated a state disparity value (SDV). social determinants of health.8 These inclu- because of missing values. Additionally, 10
For example, we calculated the SDV for CVD ded income and social status, education and observations were removed from this latter
in Maryland during 2003 by using the for- literacy, health services, culture, and social analysis because of missing values for the gap
mula: environments. in uninsured percentages. We omitted from the
To evaluate income and social status, we analysis states with unreliable mortality data, as
ð1Þ SDVCVD in 2003 ¼ calculated income disparities as a ratio of defined in the Compressed Mortality File as
ðBlack mortalityfrom CVD in MD during 2003 White-to-Black median household incomes values fewer than 20 deaths per annum in any
À White mortalityfrom CVD in MD during 2003 Þ by using the 2000–2005 Annual Social and HDI subcategory.14
=White mortalityfrom CVD in MD during 2003 Economic Supplements of the US Census
Bureau’s Current Population Survey.9 Next, RESULTS
as our variable for education and literacy, we
This value is representative of the ratio of
calculated the ratio of Black-to-White high Thirty-three states had sufficient data for
excess Black mortality to the White mortality
school dropout rates as reported by the National the calculation of HDI scores from 1999 to
per 100 000 individuals for a single disease
Center for Educational Statistics between 2000 2005, with 17 states omitted.1 Among the
process in a specific state. Additionally, we
and 2005.10 As a proxy for culture and social states for which scores were compiled, Massa-
calculated a cumulative US disparity value
environment, we used 2 indicators: geographical chusetts (0.35), Oklahoma (0.35), Washington
(USDV) for each disease process during a par-
region, as divided by the US Census Bureau,11 (0.39), Nevada (0.53), and Kentucky (0.57)
ticular year. We calculated the HDI value per
and the percentage of each state’s population that had the lowest 7-year average HDI scores, in-
year, per disease process, per state with the
is Black. These variables were meant to loosely dicative of the least racial health disparity.
formula:
model the cultural and social environment in California (1.17), North Carolina (1.20), Michigan
each state. (1.22), Wisconsin (1.32), and Illinois (1.50) had
ð2Þ HDICVD in ðyearÞ ¼
We depicted health services through 3 the highest 7-year average HDI scores, making
SDVCVD in ðyearÞ =USDVCVD in ðyearÞ
separate variables. First, differences in access them the states averaging the most racial health
to health services were represented by the disparity between 1999 and 2005 (Table 1).
We calculated a comprehensive HDICOMP difference between Black and White unin- When we used Pearson’s correlation coeffi-
score for each year by using the following sured rates as reported in Behavior Risk cients, the HDI was positively correlated to
formula, for example: Factor Surveillance System questionnaire racial disparities in median household income
responses. In addition, state Medicaid pro- (P < .001), state Black population (P < .001),
ð3Þ HDI2003 ¼ gram eligibility was selected as a proxy for and Medicaid eligibility scores (P < .01). We
½HDICancer in 2003 1 HDICVD the size of the state’s safety net for its most found a negative correlation between HDI
1 HDIDiabetes 1 HDIHIV vulnerable populations. This value was scores and state health spending (P < .001).
1 HDIinfant mortility Š=5 extracted from Public Citizen Health Re- The longitudinal mixed model analysis in-
search Group’s analysis of state Medicaid cluded 5 years of data (2000–2004) for each
We calculated these HDI scores for the 7 programs, which evaluated each state Med- state rather than the entire 7-year data set.
years in the analysis for all 50 states as suffi- icaid program for its coverage of optional The 1999 and 2005 data were eliminated
cient data allowed. eligibility groups.12 Finally, to capture the in- from the analysis because of the missing
A state HDI score of 1.00 represents racial creased spending that would be associated with values for median household income and
health disparities equivalent to those existing health disparities, we evaluated state health state health spending for those years. In the
among the entire US population. An HDI score spending, calculated as a percentage of the gross final analysis, 32 states were included (Ten-
of 0.00 would represent racial health parity, state product.13 nessee was ultimately omitted because of
and states with HDI scores of 0.01 to 0.99 a lack of a state Medicaid eligibility score),
experience less racial health disparity in mor- Statistical Analysis and a total of 150 observations. The longi-
tality than the inequalities among the US We first employed Pearson’s correlation co- tudinal mixed model analysis yielded a cor-
population at large. Lastly, states with HDI efficients to assess the association between relation between HDI scores and both
scores exceeding 1.00 exhibit more racial state HDI scores and variables representing the racial disparities in uninsured percentages
health disparity than US averages, indicating social determinants of health. We completed (P < .01) and state Black population (P < .01).
larger differences in Black and White mortality a second, more sophisticated longitudinal We found a trend toward significance be-
for the selected conditions. mixed model analysis to reassess correlations tween HDI scores and racial disparities in
in the data from 2000 to 2004. In the mixed median household income (P = .074). Table
Selection of Variables model we used yearly data for disparities in 2 details the outcomes of the statistical
To test the validity of the HDI as a tool uninsured percentages, state health spending, analysis both for Pearson’s correlation co-
to measure health disparities, we first evalu- and disparities in median household income, efficients and the longitudinal mixed model
ated its correlation to several of the known but averaged data for high school dropout rate analysis.

March 2011, Vol 101, No. 3 | American Journal of Public Health Webb et al. | Peer Reviewed | Research and Practice | 555


Tracking Progress in Reducing
TABLE 1—Health Disparities Index Scores by Rank, 1999–2005 Disparities
Statea 1999 2000 2001 2002 2003 2004 2005 Average Rankb According to HDI scores, most states failed
to significantly reduce the extent of health
Massachusetts 0.27 0.44 0.32 0.33 0.52 0.22 0.31 0.35 1 disparities between 1999 and 2005, an ob-
Oklahoma 0.46 0.35 0.28 0.36 0.26 0.29 0.44 0.35 2 servation consistent with the findings of the
Washington 0.63 0.18 0.15 0.36 0.48 0.34 0.61 0.39 3 National Healthcare Disparities Reports issued
Nevada 0.44 0.38 0.57 0.51 0.51 0.67 0.64 0.53 4 during the study period.15–17 The states with the
Kentucky 0.65 0.52 0.42 0.69 0.57 0.53 0.59 0.57 5 fewest disparities in 1999 generally maintained
New York 0.57 0.60 0.60 0.53 0.58 0.60 0.69 0.60 6 their status among the most equitable states by
Florida 0.68 0.66 0.59 0.66 0.56 0.59 0.55 0.61 7 2005, whereas states with the greatest disparities
Minnesota 0.85 0.65 0.59 0.29 0.36 0.64 0.91 0.61 8 largely remained among the states with the
Colorado 0.62 0.82 0.66 0.93 0.78 0.36 0.60 0.68 9 highest HDI scores throughout the duration of
Connecticut 0.63 0.84 1.02 0.73 0.69 0.58 0.81 0.75 10 the study. The profiles of the states at either end
Arkansas 0.90 0.89 0.73 0.73 0.73 0.65 0.76 0.77 11 of the rankings were noticeably divergent with
Mississippi 0.76 0.72 0.81 0.88 0.75 0.69 0.85 0.78 12 regard to the Black population percentage and
Alabama 0.94 0.76 0.92 0.74 0.83 0.63 0.75 0.79 13 racial disparities in uninsured percentages,
Georgia 0.86 0.82 0.78 0.78 0.78 0.82 0.78 0.80 14 whereas disparities in median household income
Indiana 0.96 0.72 0.76 0.91 0.86 0.83 0.81 0.84 15 were not significantly different among states at
Kansas 0.80 0.87 0.78 1.08 0.69 0.72 1.15 0.87 16 either end of the HDI rankings (Table 3).
Delaware 1.21 0.86 0.97 0.73 0.92 0.65 0.93 0.90 17 Although few states exhibited any meaningful
Ohio 0.82 0.86 0.85 0.95 0.95 1.02 0.94 0.91 18 diminution of health disparities, some displayed
Tennessee 0.96 1.03 0.93 0.95 0.85 0.85 0.84 0.91 19 steady improvement in their HDI scores over
Missouri 1.15 0.83 0.95 1.14 0.89 0.88 0.92 0.97 20 the study duration. Maryland, for example,
Texas 0.92 0.94 0.98 1.04 1.06 1.00 1.07 1.00 21 began the analysis as the state exhibiting the
Nebraska 1.12 0.91 0.92 0.88 1.21 1.01 0.98 1.01 22 third-most racial health care disparity in 1999,
Louisiana 1.07 1.02 1.03 1.11 1.12 1.06 0.96 1.05 23 with an HDI score of 1.25. By 2005, however,
New Jersey 1.10 1.09 1.12 1.08 1.11 1.04 1.05 1.08 24 this score had steadily decreased to a value of
South Carolina 1.11 1.13 1.13 1.05 1.18 1.11 0.90 1.09 25 0.93, a value that was below the average for
Maryland 1.25 1.24 1.23 1.02 1.11 0.96 0.93 1.11 26 racial health care disparity across the nation.
Pennsylvania 1.33 1.07 1.09 1.03 1.21 1.08 1.02 1.12 27 The greatest improvement was made in the
Virginia 1.03 1.12 1.20 1.32 0.96 1.20 1.02 1.12 28 interval between 2001 and 2002, as the HDI
California 1.09 1.16 1.16 1.18 1.18 1.23 1.22 1.17 29 score decreased from 1.23 to 1.02. Of note,
North Carolina 1.12 1.28 1.25 1.24 1.13 1.25 1.10 1.20 30 Maryland passed a total of 4 state laws ad-
Michigan 1.24 1.05 1.18 1.29 1.21 1.24 1.35 1.22 31 dressing health disparities in 2002 and 2003.18
Wisconsin 1.11 1.41 1.03 1.19 1.55 1.65 1.34 1.32 32 We are not, however, attributing Maryland’s
Illinois 1.47 1.44 1.42 1.52 1.57 1.58 1.51 1.50 33 decreasing HDI value solely to the passage of
Note. Health disparities index is an index depicting state variations in US racial health disparities. Values < 0.00 represent that state legislation. Rather, the legislative
a Black mortality rate that is better than the White mortality rate. Values of 0.00 represent parity in Black–White mortality. commitment to the reduction of disparities in
Values > 0.00 but < 1.00 represent state mortality disparities that are below the national average for mortality disparities. Maryland reflects a statewide emphasis on im-
Values of 1.00 represent state mortality disparities that equal the national average for mortality disparities. Values > 1.00
represent state mortality disparities that exceed the national average for mortality disparities. proving the health of minority communities.
a
Alaska, Arizona, Hawaii, Idaho, Iowa, Maine, Montana, New Hampshire, New Mexico, North Dakota, Oregon, Rhode Island, Furthermore, this commitment was statistically
South Dakota, Utah, Vermont, West Virginia, and Wyoming had insufficient data for the calculation of a health disparities reflected in the reduction of health care dispar-
index score.
b
State rank with respect to 33 states with sufficient data to be included in the analysis. ities as depicted by the HDI values.

Tracking Health Disparities in Minority
DISCUSSION created to depict variations in the extent and Health Focus Areas
distribution of the racial disparities that are The HDI offers states the opportunity to
The HDI has several strengths, including its known to persist. The HDI builds upon the track disparities in mortality among cancer,
evaluation of health disparities. Rather than corpus of health disparities literature to depict CVD, diabetes, HIV/AIDS, and infant mortal-
focusing the analysis on well described gaps the racial health inequalities for each state ity. Figure 1 illustrates the HDI disease-specific
between Black and White health statuses within the larger, national context of health scores for these 5 focus areas in the 2 states at
according to various indicators, the HDI was disparities discourse. polar ends of the HDI rankings. This index



Application of the HDI to the
TABLE 2—Statistical Correlations Between Health Disparities Index Scores Development of Minority Health
and Selected Variables Legislation
Health Disparities Index Scores Through statistical correlations, the HDI
becomes a valuable tool to evaluate health-
Pearson’s Correlation Coefficients
inequalities in relation to variations in the
Coefficient P Longitudinal Mixed Analysis, P
social determinants of health. As such, corre-
Geographical region NA .243 lations found between the HDI and the se-
State Black population (n = 238) 0.65 <.001 .001 lected variables have implications for both
Disparities in uninsured percentages (n = 218) 0.1 .124 .008 understanding racial and ethnic health dis-
Disparities in high-school drop-out rates (n = 224) –0.09 .203 .466 parities and crafting future minority health
Disparities in median household income (n = 204) 0.78 <.001 .074 legislation.
State health spending (n = 204) –0.38 <.001 .958 Blacks are 3 times more likely to live in
State Medicaid eligibility score (n = 238) 0.18 .006 .779 poverty than are Whites, a remarkable fact
when one considers how income signifi-
cantly influences health status, access to
constitutes another mechanism by which states management. By allowing states to identify health care, and health insurance coverage.19
can track disparities in certain disease pro- disease processes that contribute significantly The positive correlation between the HDI
cesses to identify state priorities in addressing to the health disparities burden in their state, and racial disparities in median family
disparities. Importantly, each of these condi- specific interventions can be crafted to assist income corroborates studies touting the im-
tions can be addressed through better pre- in addressing these inequalities in minority
pact of disparities in income on racial health
vention, surveillance, and disease communities.
inequalities. Additionally, we found a correla-
tion between states with the largest Black
populations and those having the most racial
TABLE 3—Changes Over Study Duration (1999–2005) in Health Disparities health disparity. Notably, the income dispar-
Index (HDI) Scores and Selected Variables Among States With the Lowest and ities and Black state population variables,
Highest HDI Scores in 1999 themselves, were positively correlated, sup-
porting claims of their interrelatedness in
State HDI Score HDI Rank Black Population, % Health Insurance Gap, % Income Gap contributing to poor health outcomes.
Least disparities We employed the longitudinal mixed
Massachusetts model analysis because of the potential for
1999 0.27 1 5.34 6.80 1.76 confounding variables. Not only did it ex-
2005 0.31 1 6.51 8.60 1.81 plicitly model state change in HDI scores
Nevada over time, but it also simultaneously and
1999 0.44 2 6.50 NA 1.75 explicitly modeled between- and within-state
2005 0.64 7 8.02 NA 1.53 variation. In discerning the relationship of
Oklahoma variables to the HDI over the duration of the
1999 0.46 3 6.38 –0.40 1.82 study, this analysis afforded flexible model-
2005 0.44 2 8.11 9.00 1.55 ing of covariance structure of the repeated
Most disparities measures, allowing us to determine whether
Maryland variables such as Black percentage of the
1999 1.25 31 27.72 5.50 1.47 population and disparities in income were
2005 0.93 20 29.52 10.60 1.5 confounders or independently associated
Pennsylvania with the HDI.
1999 1.33 32 9.60 4.30 1.66 Using the longitudinal mixed model analysis,
2005 1.02 25 10.68 10.80 1.79 we identified correlations between the HDI
Illinois and both racial disparities in uninsured per-
1999 1.47 33 14.50 13.40 1.67 centages as well as the state Black population.
2005 1.51 33 15.13 15.40 1.82 Additionally, we noted a statistically insignifi-
Notes. NA = not available. Of the 17 states without HDI scores, 16 have Black populations of less than 4%, and represent the cant trend correlating the HDI and racial
16 states with the smallest Black populations. disparities in median household income. The
presence of both the correlation for state



We found no correlation between the
HDI and state inclusion of optional eligibility
groups in their Medicaid programs. Greater
access should not be confused with greater
accessibility. For a state’s most vulnerable
populations, increasing access without the
infrastructural support to increase actual ac-
cessibility to quality care will not sufficiently
reduce racial health disparities.
In a review of comprehensive minority
health equity legislation that has been in-
troduced into Congress, several trends in
policy-based interventions recur. Each bill
has called for health disparities research
and improving health care quality, and most
included provisions to increase access to care,
health workforce diversity, and training for
cultural competency. Several bills proposed
grants for community programming, public
health education, and promoting healthy
lifestyles. Each intervention is supported by
extensive health disparities research and
evidence-based recommendations for health
disparities solutions. The challenge, how-
ever, comes in the prioritization of these
interventions and the specification of efforts
that constitute best practices in achieving
Note: CVD = cardiovascular disease; HDI = health disparities index. Value of 0.00 represents racial/ethnic parity in mortality health equity.
rates, while a value of 1.00 represents the average Black–White mortality disparities across the United States.
Advisory tools are needed for identifying
FIGURE 1—Component disease processes of HDI for a) Massachusetts and b) Illinois. Y-axis specific community program grants that
values are HDI scores for each disease process or for state disparities as a whole. legislation should support, as well as the ap-
propriate improvements to create quality, ac-
cessible care. Using the HDI as a guide,
Black population and the trend for disparities our analysis, however, we found no statisti- minority health legislation should focus
in income support claims that these variables cally significant correlation between dropout primarily on decreasing the number of
are independently related to health disparities rates and the HDI, indicating that this factor uninsured, as well as closing the significant
and not merely a function of each other. As alone is not related to health disparities across income gaps that persist between Blacks
such, we believe that legislation to eliminate states. and Whites. Furthermore, the preponder-
racial health disparities must be accompanied by As a primary reason for escalating health ance of health disparities in states with
efforts to address the income disparities that care costs, chronic diseases, such as those larger Black populations indicates that the
impact health. composing the HDI, account for more than states with the greatest disparities are also
Higher education levels have been linked 75 cents of every dollar spent on health care the states with the largest segment of the
to the utilization of preventive services and in the United States.21 Additionally, minority population that would benefit from such
longer life. Conversely, the lower rates of health disparities cost $229.4 billion in direct targeted legislative initiatives. The percent-
educational attainment documented among medical care expenses between 2003 and age of the population affected in the states
Blacks compared with Whites and Asians are 2006.11 In our analysis, state health spending with the most racial health disparity should
considered a factor in poor health status.20 was inversely related to racial health disparities encourage legislators to seek to improve
With the impact of increased dropout rates in mortality. Although increased spending may minority health on behalf of these individ-
unlikely to manifest for many years, these be associated with less mortality, this is not uals, their constituents.
values function as an educational snapshot of a sustainable mechanism to combat disparities in For state legislators, the HDI would be
the community in comparison with other health care in light of our nation’s economic an effective tool to identify the need for
states, allowing us to reasonably extrapolate climate, and current health care trends in disease-specific minority health legislation, as
those values to the community as a whole. In spending. well as a mechanism to track the progress in



decreasing mortality. Federally, the reality national racial health disparities. We chose our Contributors
that the Black–White mortality gap has not point of comparison with focus on the unique B. C. Webb originated the study, completed the analysis,
led the writing, and supervised all aspects of its imple-
improved significantly over the past 4 decades disparities within each state. Even still, we mentation. K. G. Hairston assisted with study design
warrants the utilization of the HDI to better recognize that this could understate particu- and oversaw study implementation. S. L. Simpson pro-
define this egregious disparity and reliably larly concerning Black mortality rates in states vided statistical support. All authors helped to concep-
tualize ideas, interpret findings, and review drafts of the
track current and future efforts to close that with higher mortality among Whites as well. article.
gap.22 Although this analysis focused on evalu- We were unable to calculate HDI scores
ating trends in the social determinants of health, for 17 states because of unreliable mortality Acknowledgments
future variables could be increasingly specific to data. Notably, of the states without HDI scores, This research was supported financially by the Student
predict the impact that diversifying the physician 16 have Black populations of less than 4% National Medical Association/Pfizer David M. Satcher
Research Fellowship.
workforce, improving patient lifestyle factors, and are the states with the smallest Black Ronny A. Bell, PhD, Capri G. Foy, PhD, Jaimie Hunter,
and increasing funding for community grants populations in the nation. To better elucidate MPH, David L. Mount, PsyD, John H. Stewart IV, MD,
would have on the elimination of health dispar- health disparities causation and the most Ashley C. Augustus, MPH, and Orita McCorkle all
contributed to creative, analytical, and structural guid-
ities. With both state and federal legislation, promising policy solutions, reporting for some ance and support on this project.
an understanding of the correlation between primary outcome—be it mortality, incidence, or
social determinants and the HDI can effectively prevalence—must be sufficient to reliably evaluate Human Participant Protection
serve as a sound basis for legislative initiatives the health status of minority populations in No human participants were involved.
using pertinent positive and negative correlations each state.
to identify targets for policy intervention up- Finally, we realize that the index proves References
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About the Authors
Because Whites have an older age distribution Bryant Cameron Webb is an MD candidate at Wake 8. Williams DR, Jackson PB. Social sources of racial
than do Blacks, age confounds the relationship Forest University School of Medicine, Winston-Salem, NC, disparities in health. Health Aff (Millwood). 2005;24(2):
and a JD candidate at Loyola University Chicago School of 325–334.
between race and mortality. Future studies
Law, Chicago, IL. Kristen G. Hairston, MD, MPH, is with
should consider adjusting the mortality rates 9. US Census Bureau. Current population survey,
the Section on Endocrinology and Metabolism at Wake
2008 detailed data tables. Household income 2007.
accordingly. Forest University School of Medicine. Sean L. Simpson,
Available at: https://www.census.gov. Accessed Octo-
Next, our index compares the mortality for PhD, is with the Department of Biostatistical Sciences at
ber 17, 2008.
Wake Forest University Health Science’s Division of Public
Blacks in each state against the mortality of Health Sciences. 10. US Department of Education, Institute of Education
Whites within the same state. As such, it does Correspondence should be sent to Bryant Cameron Sciences, National Center for Education Statistics. Total
not compare within-state Black mortality to Webb, 973 E 61st St, Apt 1, Chicago, IL 60637 (e-mail: dropout rate by state and race 2000–2001 to 2004–
bwebb@wfubmc.edu). Reprints can be ordered at http:// 2005 [statistics from Common Core of Data database].
a national standard for mortality rates, but www.ajph.org by clicking the ‘‘Reprints/Eprints’’ link. Available at: http://nces.ed.gov/ccd. Accessed October 1,
rather state racial health disparities against This article was accepted June 21, 2010. 2008.



11. US Census Bureau. Census regions and divisions of
the United States [US Census Bureau Web Site]. 2009.
Available at: http://www.census.gov/geo/www/us_reg
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