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Institute of Medicine (US) Committee on the Review and Assessment of the NIH’s Strategic Research Plan and Budget to Reduce and Ultimately Eliminate Health Disparities; Thomson GE, Mitchell F, Williams MB, editors. Examining the Health Disparities Research Plan of the National Institutes of Health: Unfinished Business. Washington (DC): National Academies Press (US); 2006.

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Examining the Health Disparities Research Plan of the National Institutes of Health: Unfinished Business.

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2Health Disparities: Concepts, Measurements, and Understanding

Significant and persistent differences in disease rates and health outcomes between people of differing race, ethnicity, socioeconomic status, and area of residence have been well documented (Eberhardt and Pamuk, 2004; Hartley, 2004). The National Institutes of Health (NIH) Strategic Plan presents data on health among several selected populations that show marked differences in such diverse health indicators as infant mortality, cancer mortality, coronary heart disease mortality, and the prevalence of diabetes, end-stage renal disease, and stroke (see Table D-4, Appendix D). Not only do certain racial and ethnic minority groups have a lower life expectancy, but these groups also bear a disproportionate disease burden from diabetes, hypertension, AIDS, low birth weight, and very low birth weight, when compared to the white majority population. More recent data reveal differences in all-cause and cause-specific mortality as a function of socioeconomic characteristics and area of residence (Tables D-8 and D-9, Appendix D).

The patterns are complex, and some groups (e.g., Asian Americans, Hispanics) appear to have better health outcomes than white Americans. However, these data must be viewed with a clear understanding of several important methodological limitations including variation of age distribution within different racial/ethnic groups, differences in cause-specific death rates for different racial/ethnic groups, racial/ethnic misclassification, and intra-ethnic variation among subgroups.

Age adjustment is a routine statistical method used to compare rates of health events for populations or groups that differ in age structure. An age-adjusted rate is a weighted average of age-specific rates, where the weights are determined by the age structure of the age standard. (The current age standard used by the National Center for Health Statistics is the year 2000 standard population, which reflects the age distribution of the U.S. population in the year 2000.) Racial/ethnic populations in the United States vary considerably in age structure, with the median age for whites being older than that of all other major racial/ethnic groups. For this reason, the National Center for Health Statistics (NCHS, 2004) indicates that age-adjusted rates are relative indexes for comparison but not actual measures of risk—a distinction often overlooked.

With use of age-specific, rather than age-adjusted, data different patterns between racial and ethnic groups emerge (Table 2-1). These data document continuing racial and ethnic differences in death rates from heart disease, malignant neoplasms, cerebrovascular disease, chronic respiratory diseases, diabetes, HIV, and homicide. In contrast to an all-cause age-adjusted death rate that is about 30 percent higher than that of whites, age-specific rates reveal that African Americans have all-cause mortality rates that are about 75 percent higher than those of whites after age 45. With age-specific data, American Indian mortality rates at certain ages for cerebrovascular diseases, diabetes, and homicide are higher than those of the white population, a finding that is masked in the age-adjusted data. The all-cause age-adjusted mortality data for Hispanics indicate that this population has a lower death rate than that of whites, but a more complex pattern emerges with age-specific data with, depending on age, higher Hispanic death rates for cerebrovascular diseases, diabetes, HIV, and homicide.

TABLE 2-1. Age-Adjusted and Age-Specific Death Rates by Race/Ethnicity, 2002.


Age-Adjusted and Age-Specific Death Rates by Race/Ethnicity, 2002.

Mortality data are usually presented as all-cause and cause-specific; causes are selected for reporting based upon frequency in the general population. A review of cause-specific, age-specific mortality rates for various racial/ethnic populations reveals large differences (Table 2-1). For certain conditions, Hispanics have higher age-specific cause-specific mortality rates than whites, despite the lower all-cause mortality of these groups. Data gathering that is guided by leading causes of death in the majority population may miss important causes of morbidity and mortality in other racial/ethnic groups. For the purpose of identifying disparities, use of age-specific and cause-specific rates, in addition to all-cause data, provides a more accurate comparison of relative health status between groups.

When reviewing racial/ethnic health data, another important issue to consider is misclassification, particularly among American Indians. Unfavorable and widening disparities in cardiovascular disease mortality for American Indians/Native Alaskans have been largely unrecognized because of errors in national data that disproportionately affect this group (Rhoades, 2005). National mortality event data for the past several decades suggest that cardiovascular mortality for American Indians is lower than in the general U.S. population; such data are reflected in Table 2-1 (Lee et al., 1998). In contrast, the Strong Heart Study, a longitudinal epidemiological study of a diverse group of American Indians, found that incidence and mortality rates for cardiovascular disease are equal to, or higher than, those in comparable general populations (Howard et al., 1999). These discrepancies may be explained by racial misclassification in national vital event data. The National Center for Health Statistics found that death rates for American Indians/Native Alaskans were underestimated by nearly 21 percent, compared with an overestimation of 1 percent among white populations (Rosenberg et al., 1999). Research based on vital event data that does not account for racial misclassification is at risk of grossly underestimating mortality in these populations (Rhoades, 2005).

Data that incorporate large groupings by race and ethnicity fail to distinguish substantial differences in health status within some racial groups. For example, Asian/Pacific Islanders as a group have lower rates of infant deaths (4.8 per 1,000 live births) than whites (5.7), African Americans (13.6), American Indians (8.9), or Hispanics (5.5). However, the overall Asian/Pacific Islander rate masks substantial variation among Asians and Pacific Islanders: the rate for Hawaiians (8.7) is more than double that of Chinese (3.2), with intermediate rates shown by Japanese (4.5) and Filipinos (5.7). Similarly, among Hispanics, while the overall infant death rate is 5.5 per 1,000 births, Puerto Ricans experience a relatively high rate of 8.3 deaths, Cubans experience a low of 4.2 deaths per 1,000, and Mexicans and Central and South Americans experience intermediate rates (See Table D-6, Appendix D). Subgroup-specific data, if available, might clearly identify persistently disadvantaged Hispanic and Asian subpopulations.

These differences may reflect within-group and between-group variations in susceptibility to disease due to biological and genetic factors, as well as differences in social and environmental conditions. The study of disparities is the study of the multiple, complex, and sometimes subtle relationships among genetic susceptibility, individual behavior, social environment, physical surroundings, disease prevention, and treatment interventions that lead to the observed differences in health status and health outcomes. The science of disparities involves elucidating the individual mechanisms that are responsible for diseases and disabilities that contribute to health disparities, understanding the interactions among these individual mechanisms, and explaining the differential impact of these mechanisms and interactions on various population subgroups. Successful development of the science will require the full range of research approaches: basic, translational, clinical, epidemiological, behavioral, and health services research.

Creating scientific knowledge to reduce and ultimately eliminate health disparities involves significant definitional and methodological challenges. Proper review of the NIH Strategic Plan requires consideration of the current scientific context within which the goals and objectives are being established and pursued. The Committee identified several key conceptual and methodological issues central to the study of health disparities.1


The Distinction Between Difference and Disparity

Health disparities are not simply differences in health. The term disparity may connote a difference that is inequitable, unjust, or unacceptable (Krieger, 2005; Whitehead, 1992). Characterization of a difference as unjust has been discussed at length in the scientific literature (see discussion in Braveman and Gruskin, 2003). Such characterization requires a detailed understanding of the nature and etiology of the difference and is likely to involve multiple criteria such as avoidability, mutability, and detriment to groups that are disadvantaged in terms of opportunities and access to resources. For example, the 2003 Institute of Medicine report Unequal Treatment cites a model of the distinction between difference and disparity for health care quality (Appendix E). The term “health disparities” is, however, widely used to describe differences in health status without necessarily implying the presence of injustice (see Adler, Appendix D). Thus the term “health disparities” is used in the legislation establishing the NIH health disparities program, by NIH in its definitions, and by the NIH Strategic Plan.

Lack of Consensus Definition

Research on health disparities has already yielded substantial information about the magnitude of the problem, as well as preliminary understanding of etiologies and mechanisms. These insights suggest possible interventions to improve the nation’s health. Although previous research demonstrates the feasibility and importance of studying health disparities, further research is needed to maximize our ability to identify, measure, reduce, and eliminate disparities.

There is not complete agreement on how to define or measure health disparities because observed differences vary depending on which groups are observed and what is measured. Numerous approaches have been taken, including comparing the health of minorities to that of nonminorities, comparing the health of specific groups with that of the overall population, and comparing specific groups to each other. Still another approach is to start with an observed difference in health and then establish whether this difference constitutes a disparity (i.e., whether it is inequitable or unjust). Groups may be described by gender, race, ethnicity, education, occupation, income, place of residence, or other characteristics chosen by the observer. The choice of group characteristics may be based on a conceptual model, observed empirical differences, or beliefs regarding what is just.

Lack of Appropriate Measures of Health Status

Unlike inequities in health care, which are relatively straightforward to identify and characterize, disparities in health status may be difficult to discern. The pattern and extent of health disparities vary depending on what measures of health are used. Although disparities in mortality are well documented, mortality is a significantly limited end point for studies. For that reason, intermediate indicators of health may be more useful in identifying the underlying mechanisms of disparities. Both mortality and morbidity are functions of multiple factors including biological vulnerability, exposure/resistance to disease, behavioral risk/protective factors, quality of diagnosis and treatment, and availability and accessibility of services, each of which may show different patterns of inequality. Furthermore, measuring health should not solely consist of counting adverse outcomes. Health services researchers have developed several quality-of-life measures, but there is no single, summative measure of the overall health and functioning of individuals that can be aggregated to assess the comparative health of groups. Adequate understanding of health disparities will require valid and consistent measurement of disparities as well as the variables that shape them.


Data on Racial and Ethnic Health Disparities

Existing data on inequalities in health status, health care access and quality, and health outcomes for certain racial and ethnic minority groups are subject to several limitations. As previously mentioned, much of the available data is based on large groupings by race and ethnicity. This frequently omits some groups. For example, many studies report only black/white differences, resulting in a relative paucity of data on Hispanics, Asians/Pacific Islanders, and American Indians/ Alaska Natives. Furthermore, as previously discussed, these broad categories serve to mask substantial variation in health within some of the groups.

Members of the same ethnic group from different countries and areas of origin show different patterns of health and disease. This has been demonstrated repeatedly among subgroups of Hispanics and Asians/Pacific Islanders; substantial variation by subgroup also exists among African Americans and American Indians. Further complicating the examination of racial/ethnic group differences, the health status of immigrants appears to vary by their length of time in the United States. Understanding and addressing racial/ethnic health disparities will clearly require looking at subgroups within large ethnic categories, despite the difficulty in obtaining adequate data.

Data on Socioeconomic Health Disparities

Many health outcomes vary with socioeconomic status—though again, the patterns of disparity vary depending on the measures of health used and socioeconomic variables studied. Researchers and public health agencies often fail to collect empirical data on income, education, and occupation. Studies that do measure socioeconomic status often do so in an incomplete or inconsistent manner. Experts agree that poverty is causally related to poor health status; however, there is continuing debate about whether relative inequality in income—i.e., the shape of income distribution in a population—matters in itself, apart from the effects of absolute income levels and particularly poverty.

Currently, the empirical data reveal a discontinuous association between mortality and education, thus suggesting that education confers benefits due to a credentialing function rather than simply due to knowledge accumulation. Moreover, the same level of schooling results in differences in other dimensions of socioeconomic status for women and racial/ethnic minorities—for instance, income. Much of the data from other countries use occupation as a principal determinant of social class, but the association between occupational class and health is less consistently described in the United States.

Data on Rural Health Disparities

People living in rural areas seem to have worse health outcomes than people living in metropolitan areas, but this pattern does not hold across all racial and ethnic groups (Committee on the Future of Rural Health Care, 2005; NCHS, 2004). For some indicators, suburban counties show better health status than either rural areas or urban centers, thus suggesting the need for finer differentiations than simply urban and rural (Eberhardt and Pamuk, 2004). In addition to determining differences by the degree of urban or rural locale, health status differs by geographic region (Hartley, 2004). It is unclear whether this is explained by the fact that some areas of the country are more rural than others, by regional differences in socioeconomic levels, or by other relevant differences in living conditions in various parts of the country.

Interactions Among Sociodemographic Factors Associated with Disparities

Characteristics such as minority racial/ethnic status, low socioeconomic position, and rural residence frequently coexist within populations, reflecting exposures and vulnerabilities that may interact to produce health disparities. Education and income are nonrandomly distributed across racial and ethnic groups. Both African Americans and Hispanics are overrepresented in lower categories of socioeconomic status. For some health outcomes, the differences between racial/ethnic minorities and whites become nonsignificant, once income is controlled. For many health outcomes, the gap between races diminishes with higher income, though a difference remains at each income level. Whether this residual effect reflects poor measurement of economic status or the importance of other factors (e.g., discrimination) warrants further investigation.

The meaning of specific indicators of socioeconomic status may differ across groups (Williams, 1999). At each level of income, for example, African Americans and Hispanics have lower net worth and live in poorer neighborhoods than whites (Williams and Jackson, 2005). The meaning of educational attainment also varies across groups (Farmer and Ferraro, 2005). Higher education confers fewer health benefits on minorities and women, consistent with lower social and economic returns on education. Special problems arise for groups that have received their education in other countries with different educational systems and accreditation levels. The data suggest that one cannot adequately study racial and ethnic disparities in health without considering socioeconomic factors and vice versa (Kawachi et al., 2005; Lillie-Blanton and LaVeist, 1996). Therefore, it may be fruitful to examine the effects of socioeconomic status within racial/ethnic groups (Adler, Appendix D). Similarly, evaluations of disparities in rural and urban health need to consider race/ethnicity and socioeconomic status (Probst et al., 2004).

As Adler points out, “whites make up 84 percent of rural populations, African Americans comprise 8 percent, non-black Hispanics comprise 5 percent, and Asians/Pacific Islanders and American Indians/Native Alaskans comprise less than 2 percent each. There are differences in racial/ethnic composition of rural populations in different regions of the country. Rural African Americans are predominantly in the South . . . and rural Hispanics are living primarily in the West” (Adler, Appendix D). As shown in Table D-15, Appendix D, there are substantial differences in educational attainment by both race/ethnicity and area of residence. “Of working-age adults, 40 percent of African Americans in rural areas lack a high school diploma, compared to 19 percent in urban areas; comparable figures are 50 percent to 42 percent for Hispanics and 15 percent to 9 percent for whites, in rural versus urban areas. Differences are less marked among older adults for whom a lack of high school graduation was more common and show smaller discrepancies by either race/ethnicity or rural/urban residence. Rural residence is also associated with an increased likelihood of being in a low-paying job. The increased likelihood holds for all three ethnic groups, although the difference between urban and rural rates is less for Hispanics than for whites or African Americans” (Adler, Appendix D).

Recent Progress

In July 2005, as part of the Healthy People 2010 monitoring process, the Centers for Disease Control and Prevention’s National Center for Health Statistics issued a report titled Methodological Issues in Measuring Health Disparities (Keppel et al., 2005). This report contains 11 specific guidelines intended to “bring greater consistency to the measurement of differences in quantifiable indicators of health.” Although the report represents an important step, it deals with just a limited number of technical issues in the definition and measurement of disparities. The guidelines standardize the reference group to be used in documenting disparities. If midpoint assessments of the Healthy People 2010 indicators are performed using these guidelines, the resulting body of empirical data will be a useful resource for researchers studying disparities. Regarding health care disparities, the Agency for Healthcare Research and Quality has, since 2003, issued an annual National Healthcare Disparities Report. This report summarizes disparities in health care access and quality for racial and ethnic minorities. The annual data, presented in a consistent format, will allow indicators of health care access and quality to be monitored over time.


One striking finding about health disparities is their occurrence across a wide range of diseases with differing etiologic risk factors. Elucidating the mechanisms by which health disparities occur will require identifying both common backgrounds for multiple diseases and disease-specific mechanisms. Known determinants of health, such as genetic vulnerabilities, access to and the quality of health care, the physical environment, the social environment, health-related behaviors, and exposure to stress, should be considered in the investigation of the causes of disparities (Bulatao and Anderson, 2004; Singer and Ryff, 2001).

Biological Factors

Recent scientific advances have resulted in unprecedented opportunities to explore the biological determinants of disease. New technologies allow for rapid accumulation of vast amounts of biological data, and new techniques involving bioinformatics and biomathematics provide new tools to analyze these data. These advances provide an opportunity to study pathophysiologic processes at the cellular and molecular levels, making it possible to understand how differences in genetic variation and metabolic processes contribute to health disparities and how genetic susceptibility interacts with behavioral, nutritional, pharmacological, and environmental variables.

Health Care Access and Quality

Health care deficiencies involve both poor access to care and poor quality of care. Access to care is a concept that has been extensively studied and for which reliable measures exist. The report Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare provides extensive documentation of the differences in the appropriateness and quality of care received by members of racial and ethnic minority groups (Smedley et al., 2003). Disparities in access and quality also impact the poor and, although not well studied, likely affect those in rural locations, and residents of disadvantaged neighborhoods.

Physical Environment

Physical locations vary with respect to exposures to toxins, pathogens, and carcinogens. The built, or manmade, environment may present differential risks from chemical substances, such as lead paint, crowding, and noise. The built environment can also constrain exercise, reduce access to healthy foods, facilitate risky behaviors, and discourage health-promoting activities.

Social Environment

At the individual level, the social environment is described by factors such as social connectedness and social support. These factors may benefit health in diverse ways: providing the ability to mobilize resources when needed to deal with problems and threats, buffering the effects of stress exposure, and facilitating access to information from others about health issues. At the aggregate level, lower morbidity and mortality are evident in communities with greater social capital, which may be defined as the resources available to individuals and groups within communities as a result of their social network of connections. Social capital can be measured by indicators such as levels of interpersonal trust, norms of reciprocity, and patterns of social engagement. A related concept to social capital is collective efficacy, which refers to the ability of community residents to undertake collective action for mutual benefit. Collective efficacy and social capital have been shown to contribute to health even when the socioeconomic status of a neighborhood is controlled for—although greater social capital and collective efficacy are generally associated with more advantaged communities.

Behavioral Factors

Health behaviors and lifestyle contribute significantly to morbidity and premature mortality. Both health-promoting and risky behaviors may be rooted in cultural norms and also be influenced by family socialization early in life. Behavior patterns are often formed during childhood or adolescence, with lasting impacts on adult health. Behaviors are also influenced by education, both formal and experiential. Behaviors that impair or support good health may also be facilitated or discouraged by environmental factors, for example, the influence of the built environment on patterns of physical activity.


Exposure to stress and the resulting behavioral and biological responses put individuals at risk for a range of diseases. Studies documenting greater stress exposure for groups disadvantaged by race, ethnicity, or socioeconomic status suggest that differential stress exposure, which can include perceived discrimination, may be an important mechanism by which social disadvantage gets “into the body” to affect health. The concept of allostatic load refers to the overburdening of the normal functioning of allostasis, which is the process of maintaining physiological stability in response to stress, through metabolic change. It was developed to describe the damage to physiological systems caused by exposure to chronic stress. Allostatic load provides a summative measure of the cumulative effects of stress and may reflect the multiple biological pathways by which social disadvantage can affect a range of health outcomes (McEwen, 1998; McEwen and Stellar, 1993).


In addition to the indirect effects of discrimination on health through social and economic pathways, associated community exposure, increased barriers to quality health care, institutional racism and other forms of discrimination, some research suggests that the experience of discrimination may itself be detrimental to health (Williams, 1999). The associations are complex and appear to demonstrate that not only exposure, but also responses to that exposure, have health consequences. Current research on how to best measure experiences of discrimination has added to our understanding of this type of risk factor for African Americans, but less is known about the discrimination experiences of other groups (Seeman, 2004).

Conceptual Models

As illustrated in the Adler paper (Appendix D), several conceptual models have been developed to explain the complex pathways by which biological, medical, behavioral, and environmental determinants of health differentially affect individuals and groups (Baum et al., 1999; Brunner and Marmot, 1999; Hertzman, 1999; House, 2002; House and Williams, 2000; Kaplan, 1999; Kuh and Ben-Shlomo, 1997; Kuh et al., 1997). Some models focus on a single determinant, while others provide unifying contexts of multiple determinants. Still other models suggest additional pathways and approaches to identifying the mechanisms by which health disparities occur. These conceptual models generate important considerations for disparities research: (a) that race, ethnicity, socioeconomic status, and other demographic variables have direct, indirect, and interactive effects on health; (b) the importance of considering individual, family, and community levels of influence on health; and (c) the temporal continuity throughout life. Adequate understanding of health disparities will require measurement of the potential variables that shape differences in health. The choice of variables examined should be explicitly linked to models or theories of disparities, which can provide principles for selecting the variables with the greatest research yield for reducing health disparities.


We have described the scientific context within which the NIH health disparities research program should develop the scientific knowledge base about the biological, genetic, behavioral, social, and environmental determinants of health disparities. NIH’s research agenda is impacted by the nature and extent of health disparities; the conceptual and methodological issues involved in defining and measuring them; the complex nature of the relationships between race, ethnicity, gender, income, education, occupation, and area of residence; and the challenge of identifying the complicated, multifaceted, interrelated causes of health disparities. There is a clear need for continued theoretical and empirical work to develop, refine, and evaluate measures of health, health outcomes, and health disparities. There is also a need for creative and sophisticated research to understand the biological, behavioral, and environmental pathways by which health disparities are created. The need to examine common pathways to multiple diseases will require the sustained attention of multiple Institutes and Centers (ICs) as well as true collaboration across NIH. The design and conduct of research to eliminate health disparities will require trans-NIH initiatives, as well as engaging other agencies within the Department of Health and Human Services and other departments within the federal government.


  1. Lack of consensus regarding conceptual and operational definitions of disparities and the complexity of measuring health and health determinants pose challenges for the identification, understanding, monitoring and elimination of health disparities.
  2. There is a continuing need for NIH-funded research to develop, test, and refine measures and conceptual approaches for assessing and monitoring health disparities. Research is required to answer fundamental questions: Which factors are most critical to monitor? How can they best be measured?
  3. Currently available information does not provide a full and accurate description of disparities between, and within, racial and ethnic groups and across the full spectrum of socioeconomic status. Detailed, accurate data on Hispanic, Asian/Pacific Islander, African American, and American Indian/Alaska Native subgroups are needed, including data on income, education, and occupation. Such data will provide an important source for research on disparities and for monitoring progress toward reducing and eliminating disparities across the nation.
  4. Sophisticated and creative approaches to studying the processes that cause health disparities are needed. Coordinated, collaborative trans-NIH initiatives, with the active involvement of multiple ICs, will be needed to understand common backgrounds for multiple diseases. Coordinated, collaborative trans-agency approaches will be required to successfully investigate the complex relationships and interactions among race, ethnicity, gender, income, education, occupation, immigrant generation, and area of residence.

Recommendation 1: NIH, through the National Center on Minority Health and Health Disparities and the ICs and, when appropriate, collaborating agencies, should undertake research to further refine and develop the conceptual, definitional, and methodological issues involved in health disparities research and to further the understanding of the causes of disparities.

For such research, priority areas should include, first, the development and refinement of valid measures of exposures relevant to understanding and evaluating health disparities. For example:

  • Interagency disparity research initiatives to develop valid and reliable measures of health effects of social factors; genetic risk; stress; racial/ethnic discrimination; and health care access and quality.
  • Disparities research embedded into large studies (molecular, clinical, and epidemiological), national data sets, and public health monitoring measures through the greater inclusion of appropriate measures of race, ethnicity, socioeconomic status, and residential characteristics, and of the psychosocial and environmental factors that are likely to shape health disparities in the population being studied at each time point of data collection.
  • In population-based studies, the inclusion of information on racial and ethnic subpopulations and other relevant characteristics, such as immigrant status, language preference, and detailed socioeconomic data, should be encouraged. Investigators funded by the ICs should be encouraged to gather information on socioeconomic status and other dimensions of social stratification.

Second, priority areas should include initiatives to further enhance understanding of the etiology of health disparities. For example:

  • Multidisciplinary initiatives to advance the study of disparities, including gene-environment interactions and biological mechanisms mediating disparities.
  • Trans-NIH disparity research initiatives to elucidate the pathways and mechanisms by which health disparities occur, including the identification of common backgrounds for multiple diseases and disease-specific mechanisms that may facilitate the development of strategies for intervention.



A detailed discussion of several of these issues is presented in Overview of Health Disparities by Nancy E. Adler, Appendix D.

Copyright © 2006, National Academy of Sciences.
Bookshelf ID: NBK57052


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