2
Evidence of Disparities Among Ethnicity Groups

Research studies help provide an understanding of the extent of the health and health care disparities experienced by different racial and ethnic groups. While the Office of Management and Budget (OMB) race and Hispanic ethnicity categories can reveal many inequities, they also mask important disparities in health and health care. More discrete ethnicity groups, based on ancestry, differ in the extent of risk factors, degree of health problems, quality of care received, and outcomes of care. More granular ethnicity data could inform the development and targeting of interventions to ameliorate disparities in health care that contribute to poorer health.

The Institute of Medicine’s landmark report on racial and ethnic disparities in health care, Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare, emphasizes the need for standardized collection and reporting of race and ethnicity data (IOM, 2003). While Unequal Treatment recommends the Office of Management and Budget (OMB) race and ethnicity categories as the minimum standard by which collected race and ethnicity data should be parsed and reported, the recommendations go further, calling for better data on racial and ethnic populations “to reflect the diversity within racial and ethnic populations (e.g., subgroups of Hispanics, African Americans, Asian Americans, etc.), particularly at the local level” (IOM, 2003, p. 233).

Since the release of Unequal Treatment, evidence of disparities in health and health care among racial categories at the broad OMB level (Black or African American, Asian, Native Hawaiian or Other Pacific Islander [NHOPI], White, and American Indian or Alaska Native [AIAN]) has continued to be documented. Similarly, distinct differences continue to be shown between the broad Hispanic and non-Hispanic ethnic categories. For example, there is more information on varying life expectancy (IOM, 2008) and mortality risks or rates for certain medical conditions (Murthy et al., 2005; Wang et al., 2006), along with knowledge of disparities in general health status, access to health care, and utilization rates of services among these larger population categories (AHRQ, 2008a; Cohen, 2008; Flores and Tomany-Korman, 2008; Kaiser Family Foundation, 2008, 2009; Ting et al., 2008). Even as quality-of-care indicators such as screening for colorectal cancer show improvement for the overall population, disparities persist among the OMB race and Hispanic ethnicity categories (AHRQ, 2008a, 2008b; Moy, 2009; Trivedi et al., 2005).

In contrast, systematic analysis of similar quality-related data as a function of more discrete ethnic groups within the OMB categories has hardly progressed. After defining the term granular ethnicity, this chapter summarizes the evidence showing health and health care disparities at more fine-grained levels of ethnic categoriza-



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2 Evidence of Disparities Among Ethnicity Groups Research studies help provide an understanding of the extent of the health and health care disparities experienced by different racial and ethnic groups. While the Office of Management and Budget (OMB) race and Hispanic ethnicity categories can reveal many inequities, they also mask important disparities in health and health care. More discrete ethnicity groups, based on ancestry, differ in the extent of risk factors, degree of health problems, quality of care received, and outcomes of care. More granular ethnic - ity data could inform the development and targeting of interventions to ameliorate disparities in health care that contribute to poorer health. The Institute of Medicine’s landmark report on racial and ethnic disparities in health care, Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare, emphasizes the need for standardized collection and reporting of race and ethnicity data (IOM, 2003). While Unequal Treatment recommends the Office of Management and Budget (OMB) race and ethnicity categories as the minimum standard by which collected race and ethnicity data should be parsed and reported, the recommendations go further, calling for better data on racial and ethnic populations “to reflect the diversity within racial and ethnic populations (e.g., subgroups of Hispanics, African Americans, Asian Americans, etc.), particularly at the local level” (IOM, 2003, p. 233). Since the release of Unequal Treatment, evidence of disparities in health and health care among racial cat - egories at the broad OMB level (Black or African American, Asian, Native Hawaiian or Other Pacific Islander [NHOPI], White, and American Indian or Alaska Native [AIAN]) has continued to be documented. Similarly, distinct differences continue to be shown between the broad Hispanic and non-Hispanic ethnic categories. For example, there is more information on varying life expectancy (IOM, 2008) and mortality risks or rates for cer- tain medical conditions (Murthy et al., 2005; Wang et al., 2006), along with knowledge of disparities in general health status, access to health care, and utilization rates of services among these larger population categories (AHRQ, 2008a; Cohen, 2008; Flores and Tomany-Korman, 2008; Kaiser Family Foundation, 2008, 2009; Ting et al., 2008). Even as quality-of-care indicators such as screening for colorectal cancer show improvement for the overall population, disparities persist among the OMB race and Hispanic ethnicity categories (AHRQ, 2008a, 2008b; Moy, 2009; Trivedi et al., 2005). In contrast, systematic analysis of similar quality-related data as a function of more discrete ethnic groups within the OMB categories has hardly progressed. After defining the term granular ethnicity, this chapter sum- marizes the evidence showing health and health care disparities at more fine-grained levels of ethnic categoriza - 1

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2 RACE, ETHNICITY, AND LANGUAGE DATA tion. The literature has more to say about ethnicity and disparities in health than about ethnicity and disparities in health care; this is reflected in the balance of articles reviewed in this chapter. To complement the research studies, data are also presented for selected population characteristics that can place people at risk of disparities (e.g., low education levels, poverty, lack of facility with English among those speaking a non-English language at home, and place of origin). This focus on literature with respect to more granular detail on subgroups is not to negate the important dif - ferences found among the OMB racial groups and for Hispanics compared with non-Hispanics, but to learn more about where to focus interventions when categorical differences are masked by the OMB categories. Being able to focus interventions at the more granular level has been posited as a way to use resources most efficiently to reduce disparities. Awareness of health and health care disparities has been heightened through the release of multiple docu - ments besides Unequal Treatment, including—Healthy People 2010 and the National Healthcare Disparities Reports (AHRQ, 2008a; HHS, 2000), and successful initiatives have addressed some disparities using a variety of approaches. For example, some successful initiatives have applied general quality improvement concepts and techniques, while others have developed and used culturally sensitive outreach and education materials for health plan members, and still others have involved training of staff in culturally competent communications. Common to virtually all successful projects are some fundamental steps, including the acquisition of data on race and ethnicity, the stratification of quality-of-care data by race and ethnicity, the use of race and ethnicity to identify members of a target population to whom elements of an intervention would apply, and reanalysis of stratified quality data to evaluate the impact of the activities. Data on race and ethnicity are a fundamental requirement for disparity reduction initiatives. Without these data, it is impossible to identify disparities and track the impact of initiatives over time, and it is difficult to target those aspects of interventions that involve direct contact with individuals. The presence of data on race and ethnicity does not, in and of itself, guarantee any subsequent actions in terms of analysis of quality-of-care data to identify disparities or any actions to reduce or eliminate disparities that are found. The absence of data, however, essentially guarantees that none of those actions will occur. DEFINING RACIAL AND ETHNIC POPULATIONS IN THE UNITED STATES The United States is a diverse country whose composition is changing. Table 2-1 shows the results of Census 2000 on the size and percentage distribution of the total U.S. population primarily by the broad OMB racial and Hispanic ethnic groupings. The Black and Hispanic groups are of equivalent size; the Census has multiple check-off boxes for specific Hispanic groups (i.e., Mexican, Puerto Rican, Cuban, and a write-in option for other groups) that it routinely reports, but there are no such more specific check-off boxes under the Black or White races. Asians and Pacific Islanders have many specific groups listed on the Census form from which to choose as well. There are efforts to legislatively mandate expansions to the current Census categories (e.g., add Caribbeans in general and Dominicans specifically).1 The groups included in the OMB race and Hispanic ethnicity categories are defined in Chapter 1 (see Table 1-1). Defining Ethnicity Ethnicity is a concept that the subcommittee, for standardization purposes, distinguishes from race. The term ethnicity represents a common ancestral heritage that gives social groups a shared sense of identity that exists even though a particular ethnic group may contain persons who self-identify with different race categories. The OMB categories use the term ethnicity only in conjunction with Hispanic ethnicity. The U.S. Census captures data on a few discrete ethnic groups both under the Hispanic ethnicity question, by having check-off boxes for some Hispanic groups (e.g., Puerto Ricans, Dominicans), and under the race question, by listing some groups of 1In the first session of the 111th Congress, bills were introduced to include check-off boxes on Census Bureau questionnaires for Dominican ethnicity (HR 1504 and SB 1084) and for Caribbean ethnicity in general (HR 2071 and SB 1083).

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 EVIDENCE OF DISPARITIES AMONG ETHNICITY GROUPS TABLE 2-1 Census 2000 Population by Race and Hispanic Ethnicity Number Percent of Population Group (in millions) U.S. Population Total Population 281.4 100 Hispanic Ethnicitya Not Spanish, Hispanic, Latino 246.1 87.5 Spanish, Hispanic, Latino 35.2 12.5 Mexican, Mexican American, Chicano (20.9) (7.4) Puerto Rican (3.4) (1.2) Cuban (1.3) (0.4) Other Hispanic (9.6) (3.4) Raceb One Race White 211.4 75.1 Black, African American, or Negro 34.7 12.3 American Indian or Alaska Native 2.5 0.9 Asian 10.2 3.6 Native Hawaiian or Other Pacific Islander 0.4 0.1 Some Other Race 15.4 5.5 Two or More Races 6.8 2.4 NOTE: The number and percents on race in this table differ somewhat from later tables in this chapter because later tables combine persons that report a single race alone or in combination with other races (e.g., persons who are Black race alone plus multi-race persons who identify with both Black race and another race), whereas this table focuses on single-race reporting. a Ramirez, 2004. b Grieco and Cassidy, 2001. Asian and Pacific Islander heritage (e.g., Japanese, Samoan) and leaving an option for American Indian and Alaska Natives to indicate a tribal affiliation. Where one is born can make a significant difference in access to and use of health care, but the subcommittee adopts the concept of ethnicity (equated with one’s ancestry) as more encompassing than questions about country of birth or origin. A person born in the United States might identify culturally with a specific ethnicity in ways that can affect his or her health-related behaviors and approach to utilizing health services. Also the subcommittee prefers the use of ethnicity over questions such as national origin because inquiring about national origin could engender mistrust on the part of respondents that they are being asked about immigration status (Carter-Pokras and Zambrana, 2006).2 Defining Granular Ethnicity Granularity means a fine level of detail; the greater the level of granularity, the more finely detailed the data category is. The subcommittee adopts the term granular ethnicity to describe groups at a more specific level of categorization than the broad OMB categories, such as the ethnic groups that the Census lists as subgroups in its Hispanic ethnicity and race questions. The subcommittee, as will be examined in Chapter 3, believes a separate question on granular ethnicity would complement the OMB categories for race and Hispanic ethnicity without further intermingling the constructs of race and ethnicity. Additionally, this approach would allow more discrete categorization of large groups of the population who now have the option only of White or Black on the race question. 2 Personal communication, O. Carter-Pokras, University of Maryland School of Public Health, April 13, 2009.

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4 RACE, ETHNICITY, AND LANGUAGE DATA The term granular has been used in describing more detailed categories in the Hospital Research & Educa - tional Trust (HRET) Toolkit (Hasnain-Wynia et al., 2007), and the notion of the need for more detailed subgroup data has been raised in Unequal Treatment and by many others. Kaiser Permanente also uses the term granular ethnicity in describing its collection of more detailed information beyond the OMB categories (Tang, 2009). More detailed ethnicity categories provide a useful way of analyzing quality data about the populations served by providers, health plans, state and federal programs, and others to determine whether there are differential health needs and disparities in access to and use of appropriate health services. The level of detail for analysis for qual - ity improvement can be influenced by the size of the ethnic population under study; the number or proportion of those ethnicities that might have a specific condition such as diabetes or be of an age at which immunization for pneumonia is needed; and the actual associations among ethnicity, other correlated factors (e.g., income, insur- ance coverage), and quality of care. While there are hundreds of possible ethnic categories, not all will have local relevance nor always have added value for designing targeted approaches to remediate health care needs. This report’s recommendations are driven by a need to identify and address quality differentials not simply to collect information to classify and count people. OVERVIEW OF DIFFERENTIALS IN CARE AND POTENTIAL QUALITY IMPROVEMENT INTERVENTIONS Health is the physical, mental, and functional status of an individual or a population. Health has been shown to be the result of multiple factors, including nutrition, educational level, socioeconomic level, and lifestyle, and of the health care that the individual or population receives. Health care comprises the prevention, treatment, and rehabilitation interventions that are provided to an individual to maintain or improve health. Disparities in health care (e.g., in access, in the rate at which a treatment is provided when indicated, or in the incidence of adverse events in care) can be the cause of disparities in health (e.g., in the incidence or severity of a disease, in func - tional level, or in mortality rate). Therefore, analyses of disparities in health care can help identify opportunities for quality improvement in care provision that will reduce disparities in health. For the most part, entities use the same categories of race, ethnicity and language whether data are collected for health or health care purposes so the connections between health disparities and health care disparities can be drawn more easily. Illustration of Differences Among Ethnic Groups Within Broad OMB Categories A study by Blendon and colleagues (2007) illustrates the concept of differences among subgroups residing in the United States, even after controlling for demographic characteristics such as income, education, age, and sex. A number of differences in health care service utilization and satisfaction can be seen among more granular Black, Asian, and Hispanic ethnic groups. Blendon and colleagues’ telephone survey of 4,157 randomly selected adults in the United States found that fewer Caribbean- and African-born Blacks received any care than U.S.- born African Americans in the past year but it was the latter group that rated their care more poorly than Whites. Certain Hispanic American groups (Mexican and Central/South American Hispanic) and Asian American groups (Chinese, Korean, and Vietnamese) also received significantly less health care in the last year compared with Whites, even though other ethnicities within these broad OMB race and ethnicity categories fared as well as Whites. Native Americans also received less care compared with Whites and less often rated their care as good or excellent—the lowest rating of any of the groups. Regressions that controlled for demographic characteristics reduced the number of groups receiving no care in the past year by half, but significant differences remained for African-born Americans, Mexican Americans, Chinese Americans, and Korean Americans compared with Whites that were independent of the demographic factors (Blendon et al., 2007). While for some groups the access and utilization issues may stem from economic challenges, the reality remains that there are differences among ethnic groups in utilization and ratings of caregiving within the broad OMB categories.

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 EVIDENCE OF DISPARITIES AMONG ETHNICITY GROUPS Potential Applications for Quality Improvement Cooper and colleagues (2002) review a variety of successful interventions, and note that while there are many well-identified potential opportunities for certain conditions and services, there is a lack of information on “ethnic subgroups.” They also stress the need to improve the science of evaluating interventions to reduce disparities now that there is widespread acknowledgment of the existence of inequalities. A fundamental component of improv - ing quality is collecting reliable demographic data to use in focusing attention on where interventions might be best applied. Fiscella also observes that, “because disparities in healthcare represent inequities in the process of healthcare, they are potentially addressable through interventions designed to impact health delivery” (Fiscella, 2007, p. 142). Entities that collect race and detailed ethnicity data might use them in various ways to examine whether there are differentials in health care needs and to plan targeted interventions. For example, having read in published research that certain ethnic groups are at higher risk for cancer mortality and delays in care, a health plan could target edu - cational calls to persons of these ethnic groups to make screening appointments for different site-specific cancers rather than having to contact a much larger number of persons (Bates et al., 2008). Or a hospital could look at the characteristics of patients who did not receive care according to evidenced-based protocols for acute myocardial infarction. Then the hospital could assess whether there were specific barriers that interfered with the appropriate delivery of care to specific populations and make concerted efforts to remove those barriers. Or the hospital might also want to take what it learned from that effort to institute strategies that could be applied universally to ensure that all patients with that condition receive the right care at the right time. Another hospital might be experiencing a high readmission rate; analysis of its readmission data might reveal a higher than expected rate for a specific ethnic group. From there, the hospital could determine whether culturally specific interventions at discharge planning are necessary to prevent unnecessary readmissions, and whether this patient group needs access to regular primary care. Similarly, a health center might find that women of a certain group are not coming in for prenatal care until late in their pregnancy; this finding could lead the health center to send community health workers out into the community to change attitudes and practices related to seeking timely care. Physicians receiving feedback on their practice patterns might discover that they are not giving the same evidence-based care to all patients, even though they believe they are, and when this is called to their attention, their practice improves. Fiscella reviews a variety of quality improvement tools, including reminders, provider feedback, provider education, intensive outreach, practice guidelines, patient education, cultural competency training, and organizational change/practice redesign and community-based interventions, and concludes that “the elimination of healthcare disparities will require the development and implementation of tailored interventions directed at multiple levels. Success will depend on the vision, leadership commitment, and allocation of resources by government, health plans, hospitals, communities, and practices…” (2007, p. 164). The following sections examine further evidence of differences within the aggregate OMB categories. These studies are illustrative of how more granular ethnicity data reveal more precise opportunities for targeting health care quality improvement initiatives.3 Notations are made when the studies are controlled for socio-economic factors when comparing health or health care differences among populations. Statistically significant associations and trends are emphasized. HISPANIC OR LATINO GROUPS In Census 2000, 12.5 percent of the U.S. population (35.2 million people) self-identified as Hispanic, with persons of Mexican origin representing the largest ethnicity group at almost 60 percent of the Hispanic population (Ramirez, 2004). Hispanic is the one distinct ethnicity included in the OMB basic categories and is defined by the Census and OMB as a “person of Mexican, Puerto Rican, Cuban, South or Central American, or other Spanish 3 To identify relevant evidence on health and health care for this chapter, Medline articles were queried using keywords “subgroup,” “sub - population,” “health disparities,” “racial,” “ethnic,” “Hispanic,” “Latino,” “African,” “Black,” “White,” and “Asian” in various combinations. Literature since 1997 was scanned and culled, first by title, then abstract, then full text. Reference sections of relevant articles were also scanned to find other relevant literature.

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6 RACE, ETHNICITY, AND LANGUAGE DATA culture or origin regardless of race” (OMB, 1997; Ramirez, 2004). The question about Hispanic ethnicity used by the Census includes additional labels, such as Latino and Spanish, to delineate more clearly who is included since different people identify with one of the terms but not the others. Demographic Characteristics This ethnic category usually has been subdivided in the literature according to ancestry or according to regional designations of South and Central America (Table 2-2).4 From this table, one sees that individual Hispanic groups5 have different characteristics with respect to U.S. nativity, proficiency with English, educational attainment, and risk of poverty―factors that have been shown to impact the quality of care those populations receive and their health outcomes. More than 40 percent of most ethnic groups who speak Spanish at home do not speak English very well, and some groups have almost twice the poverty rate of others (Ramirez, 2004). Health-Related Differences Among Hispanic or Latino Groups Differences in dimensions of health and health care among specific Hispanic or Latino populations in the United States have been identified and studied more extensively than other racial and ethnic populations. The avail - able literature includes studies of health and health care disparities between Hispanic groups by overall self-rated health, access to care, mental health, cancer and cancer screening, low birthweight, asthma, and cardiovascular health. Overall Self-Rated Health In a national study comparing the overall mental and physical health of multiple Hispanic ethnicity groups, the Mexican group tended to have better scores on both components of the SF-12 than Whites and other Hispanic groups, whether those of Mexican ancestry were born in the United States or Mexico (Jerant et al., 2008). The study is based on cross-sectional analyses of linked data from the 1998–2004 National Health Interview Survey (NHIS) and the 1999–2005 Medical Expenditure Panel Survey (MEPS); the study population compared four Hispanic groups—Mexican (13,522 persons), Cuban (778), Puerto Rican (1,360) and Dominican (829) including persons born in the United States and elsewhere—with 45,422 English-speaking Whites born in the United States. After regressions adjusting for demographic and socioeconomic variables, those of Cuban ancestry had the worst mental health scores, while those of Puerto Rican heritage had the worst physical health scores; the scores for Cuban, Puerto Rican and Dominican groups on both components were worse than Whites. The authors’ suggest that the “paradox” of better health status among the Mexican group even with low socioeconomic status can mask poorer health status of other smaller groups of Hispanics when the Hispanic data are examined as one group. The authors also underscored that the observed ethnic differences within the Hispanic groups on the mental health component met a criterion for clinical significance. Access to Health Care Services Shah and Carrasquillo (2006) used cross-sectional analyses of the Census Bureau’s Current Population Survey (CPS) to examine differences in insurance coverage, focusing on Hispanic populations. As of 2004, those identify - ing with the Mexican ethnicity category had the highest rate of uninsurance (35.6 percent), and the Puerto Rican category the lowest rate (17.6 percent), with Cuban (22.1 percent), Dominican (25.3 percent) and other Hispanic 4 The form for this survey had check-off boxes for three specific categories (Mexican, Puerto Rican, Cuban), followed by a check-off box for “Other Spanish, Hispanic/Latino,” accompanied by a space for writing in another specific Hispanic origin group. The numerous other identified subgroups are based on the “other” responses. 5 The Census Bureau allows people of Brazilian heritage to self-identify whether they are Hispanic or not, but the Census does not automati - cally classify Brazilians who speak Portuguese as Hispanics. About half of Brazilians identified as non-Hispanic in both Census 2000 and the Current Population Survey (del Pinal and Schmidley, 2000).

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TABLE 2-2 Selected Characteristics of the Hispanic/Latino/Spanish Population in the United States Speak a Language Other Than English Percent of Percent of at Home and Speak Less Than Number U.S. Hispanic U.S. Native English Less Than High School Hispanic Groups (in millions) Population Population Born (%) “Very Well” (%) Graduationa (%) Poverty Rate (%) Mexican 20.9 59.3 7.4 58.5 43.1 54.2 23.5 Puerto Rican 3.4 9.7 1.2 98.6b 26.7 36.7 25.8 Cuban 1.2 3.5 0.4 31.5 45.9 37.1 14.6 Central American 1.8 5.1 0.6 24.5 56.8 54.0 19.9 Costa Ricanc (0.07) (0.2) Guatemalan (0.37) (1.1) Honduran (0.22) (0.6) Nicaraguan (0.18) (0.5) Panamanian (0.09) (0.3) Salvadoran (0.66) (1.9) Other (0.10) (0.3) South American 1.4 4.0 0.5 23.4 47.6 23.9 15.0 Argentinean (0.10) (0.3) Bolivian (0.04) (0.1) Chilean (0.07) (0.2) Colombian (0.47) (1.3) Ecuadorian (0.26) (0.7) Paraguayan (0.01) (0.0) Peruvian (0.23) (0.7) Uruguayan (0.02) (0.1) Venezuelan (0.09) (0.3) Other South American (0.06) (0.2) Dominican 0.8 2.2 0.3 31.8 53.7 48.9 27.5 Spaniard 0.1 0.3 — 59.8 25.3 23.0 12.8 Other Hispanicc 5.5 15.7 2.0 72.4 29.8 40.0 21.5 Total Hispanic 35.3 100 NA 59.8 40.6 47.6 22.6 Total U.S. Population 281.4 NA 12.5 88.9 8.1 19.6 12.4 a Population 25 and older. b Persons born in Puerto Rico are automatically U.S. citizens. In the case of Puerto Ricans, they are not considered foreign-born. c I ncludes general responses such as Hispanic, Spanish, and Latino. SOURCE: Ramirez, 2004. 

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 RACE, ETHNICITY, AND LANGUAGE DATA groups (32.5 percent) having intermediate values (Shah and Carrasquillo, 2006). The socioeconomic profile of the groups did not always parallel the rate of uninsurance, for example the subgroups with the greatest propor - tion under 200 percent of poverty were Mexican and Puerto Rican. Weinick and colleagues (2004) using MEPS data similarly showed that persons identifying with Mexican ethnicity had higher uninsurance rates than Cuban and Puerto Rican groups, but persons with Central American and Caribbean ethnicities had even higher rates of uninsurance than the Mexican group. Additionally, Weinick and colleagues (2004) examined differences in use of four health care services (ambu - latory care visits, emergency department [ED] visits, prescription medications, and inpatient hospitalizations). After controlling for sociodemographics, including income and health insurance coverage, multivariate regres - sion analyses of MEPS data showed that persons of Mexican and Cuban ancestry had lower rates of ED visits than other Hispanics. Additionally, more recent immigrants were less likely to have made any ambulatory care or emergency department visits in the past year. The English-speaking subgroups had a higher rate of ED visits and hospitalizations, and foreign-born Hispanics showed lower rates of ambulatory visits, ED visits, and prescription medications. Based on these results, the authors concluded that understanding disparities in health care utilization will require disaggregation of patient demographic data by ethnic groups, language, and length of U.S. residence (Weinick et al., 2004). Mental Health Alegría and colleagues (2007) examined the prevalence of depressive, anxiety, and substance use disorders among Hispanics living in the United States using data from the National Latino and Asian American Study (NLAAS).6 Weighted logistic regression analyses controlled for age. In terms of lifetime prevalence, compared with the comparable Puerto Rican gender group, those of Mexican ethnicity showed lower rates of depressive disorders whether male or female and lower rates of substance abuse disorders for women, and lower overall psychiatric disorders for men. Cuban men were less likely to suffer from anxiety disorders and overall psychiatric disorders. Puerto Ricans tended to have the highest rates of lifetime and past year depressive, anxiety, substance use, and overall psychiatric disorders. Looking at all Hispanic groups in combination, those with higher English proficiency were significantly more likely to suffer from overall lifetime or past year psychiatric disorders than those with fair or poor English skills. Cancer and Cancer Screening Gorin and Heck (2005) used the 2000 NHIS to examine data from 5,377 Latinos on the use in the past 12 months of Pap smears, mammograms, breast self-examinations, and clinical breast exams among women; prostate-specific antigen (PSA) tests among men; and fecal occult blood tests (FOBT), sigmoidoscopy, colonoscopy, and proctoscopy among both men and women. Cancer risk factors such as smoking varied by ethnic group (e.g., over 25 percent of Puerto Rican and “other” Hispanics smoked while 13.9 percent of Dominicans did). For persons of average risk for cancer (i.e., did not have a personal or family history of cancer), ethnic group variations were apparent in use of Pap smears and clinical breast exams, but differed less on some tests such as FOBT where use was low for all groups. Multivariate logistic regression analyses revealed that Dominican women were 2.4 times more likely to have had mammography than other Latino women. Puerto Rican and the Central or South American groups had half the rate of colorectal cancer screening by endoscopy of others. Cuban males were five times more likely to have had a PSA test. Additionally persons with health insurance were 1.5 to 2.2 times as likely to have screening tests compared with the uninsured. Having visited a doctor in the past year, increased the odds of having screening tests to a level similar to having insurance, with the exception of PSA screening where the odds were almost five- 6 A survey of 2,554 Latinos aged 18 years and older, half monolingual Spanish, 868 Mexican, 495 Puerto Rican, 577 Cuban, and 614 other Hispanics. The NLAAS population was similar to the Census 2000 population distribution by gender, age, education, marital status, and geographic distribution, but differed in terms of nativity and household income.

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9 EVIDENCE OF DISPARITIES AMONG ETHNICITY GROUPS fold greater. Greater acculturation,7 visits to a primary care provider, and use of other screening tests, predicted the likelihood of Pap smear screening. Clinical breast exam rates were also predicted by greater acculturation, visits to a primary care provider in the last month, and use of other screening tests, along with having a bachelor’s degree and a personal history of cancer (Gorin and Heck, 2005). Using multiple logistic regression analyses of NHIS data pooled from 1990 and 1992, Zambrana (1999) com - pared the use of three cancer screening practices (Pap smear, mammogram, and clinical breast exam) for five cat - egories of Hispanic women including women who identify as Mexican versus Mexican-American. While Mexican women were the least likely to have been screened in the past three years, no statistically significant differences were found in the rates between the Mexican-American (referent group) and any of the other Hispanic groups. In this study, access measures such as having a usual source of care and knowledge of other clinical cancer screening techniques were more strongly associated than ethnic or language factors with screening rates for the population studied (Zambrana et al., 1999). The authors posit that the higher than expected rates of screening in the sample popu- lation may be attributable largely to contemporaneous intervention strategies and community outreach to increase screening among Hispanic women, concluding that such efforts appeared effective and should be expanded. The National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) data from 1992–1995 showed that while all Hispanic women had a greater likelihood of larger tumor size and advanced tumor stage than non-Hispanic Whites, women born in Latin America had higher odds of large tumors (e.g., larger than 1 cm and 2 cm) than Hispanic women born in the United States (Hedeen and White, 2001). The researchers were only able to identify the ethnic subgroup for 38 percent of the Hispanic women in the SEER database. Low Birthweight Logistic regressions on 2002 U.S. Natality Detail Data (n = 634,797) showed that after controlling for a variety of demographic, educational and clinical factors, foreign-born Latino mothers had a lower risk of having low-birth- weight infants compared with U.S.-born Latino women. However, nativity patterns among Mexican-origin women explained these overall trends among Latino women and infants. Foreign-born women with Mexican ethnicity had about a 21 percent reduced risk of low birthweight, but the same phenomenon was not observed for other Latino women who were born outside the continental United States (i.e., Puerto Ricans, Cubans, Central/South Americans) (Acevedo-Garcia et al., 2007). Across each of the three regression models, Puerto Rican women had higher odds than other Hispanic subgroups of having a low-birthweight infant. The regression models for this study did not control for income or insurance status. Asthma Large differences also exist in asthma burden among Hispanic children. Based on weighted logistic regression analyses of merged 1997–2001 NHIS data, Puerto Rican children had the highest prevalence (26 percent) and rate of recent asthma attacks (12 percent) compared with children of Mexican heritage whose prevalence and recent attack rates were 10 percent and four percent, respectively (Lara et al., 2006). Rates for Cuban and Dominican ethnicities were intermediate and similar to Black children. Adjusted odds ratios followed the same relative pat - tern among Hispanic subgroups (e.g., lifetime odds of 2.3 for Puerto Rican children vs. 0.90 for Mexican children compared with the non-Hispanic White referent group). Birthplace influenced the association between ethnicity and lifetime asthma diagnosis differently for Puerto Rican and Mexican children. When both Puerto Rican children and their parents were born in the continental United States, the adjusted odds ratio (OR) was 1.95 (95 percent CI 1.48–2.57) but 2.5 (95 percent CI 1.51–4.13) for those who were island-born; the odds ratios were calculated using as the referent group U.S.-born non-Hispanic White children whose parents were born in the United States (Lara et al., 2006). In contrast, U.S.-born Mexican families had a higher adjusted OR for lifetime asthma diagnosis of 1.05 (95 percent CI 0.90–1.22) than the 0.43 (95 percent CI 0.29–0.64) for those born outside of the continental United States. Similar patterns were observed for recent asthma attacks. Birthplace was the only co-variant that affected 7 Acculturation was measured using a modified Marin Short Acculturation Scale.

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40 RACE, ETHNICITY, AND LANGUAGE DATA the Hispanic subgroup results; numerous factors were considered including family income and insurance status. Overall Hispanic data mirror the Mexican ethnicity data, thus masking the results for Puerto Rican children. Cardiovascular Health Borrell and Crawford used NHIS data (1997–2005) to perform descriptive and logistic regression analyses assess- ing the strength of association between Hispanic ethnic groups and self-reported hypertension; self-report was based on the question of whether they had ever been told by a health professional that they had hypertension. Dominican ethnicity and non-Hispanic Black adults had an adjusted odds ratio of 1.67 and 1.48, respectively, compared with the referent group of non-Hispanic Whites. Results were adjusted for age, sex, marital status, survey year, U.S. region, nativity status/length in the United States, health insurance, education, income, and occupation. In contrast, persons of Cuban, Central or South American, Mexican (whether born in the United States or not), and other Hispanic groups all had lower odds than non-Hispanic Whites or Blacks or those of Dominican ethnicity (Borrell and Crawford, 2008). Another study examined hypertension-related mortality rates among women of various Hispanic subgroups using data from the National Vital Statistics System’s Multiple Cause Mortality Files and further tracked whether changes occurred over time (1995–1996 to 2001–2002). In 1995–1996, the age-standardized death rate per 100,000 for hypertension-related mortality was higher among the Puerto Rican group (248.5) than for non-Hispanic Whites (188.7), while Mexican American (185.4), and Cuban (139.7) rates were lower. Over time, the mortality rate decreased for Puerto Rican (215.5), non-Hispanic White (171.9), and Cuban American (104.6) women, with each group keeping their relative position. At the same time the rate for Mexican American women increased to 205.5, now making their risk higher than non-Hispanic White women. The authors suggest the need for strengthening inter- ventions to reach these higher risk ethnicity groups and those who provide their care (Zambrana et al., 2007). Summary In the broad Hispanic ethnicity category, more granular ethnicities are associated with different levels on health indicators and access to and utilization of health care depending on ancestry. The authors of the studies reviewed in this section stress the importance of not viewing the Hispanic population as monolithic, and they point out the masking effect that the larger Mexican ethnicity group has on overall statistics when data are viewed to represent all Hispanic groups as one. Even after adjustment for factors such as insurance, education, and income, many ethnic differences were found to remain. The authors also comment on how Hispanic populations beyond Mexican, Cuban and Puerto Rican ethnicity are not well characterized, because in surveys their numbers are small resulting in heterogeneous groups being lumped into an “other” Hispanic category. BLACK OR AFRICAN AMERICAN GROUPS In Census 2000, 12.9 percent of the U.S. population (36.2 million people) self-identified with the Black or African American category.8 The OMB and Census definition for the Black or African American race category is “a person having origins in any of the Black racial groups of Africa” (OMB, 1997; U.S. Census Bureau, 2000). Demographic Characteristics The Black population, like the AIAN and White populations, is more likely than other groups to be born in the United States (nearly 94 percent vs. 89 percent for the total U.S. population, as compared with 59.8 percent of Hispanics, 31.1 percent of Asians, and 80.1 percent of NHOPI). The origins of foreign-born Blacks are as follows: approximately 59 percent from the Caribbean, 24 percent from Africa, and 13 percent from Central and 8 12.2 percent reported Black alone with the remainder reporting more than one race; of those checking more than one race, the largest combinations in order were 784,764 reporting both Black and White, followed by 417,249 reporting Black and “Some other race,” generally Hispanic, and then 182,494 reporting Black and American Indian/Alaska Native.

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41 EVIDENCE OF DISPARITIES AMONG ETHNICITY GROUPS South America (McKinnon and Bennett, 2005). While English is the primary language of 94 percent of Blacks, nearly one-third of those over age 5 who speak a language other than English at home speak English less than “very well”; additional detail is provided in Table 2-3 on groups who speak a language other than English at home. One in four Blacks live in poverty; 14 percent over age 25 have a bachelor’s degree, while 19.6 percent have not graduated from high school. Health-Related Differences Among Black or African American Groups For the most part, few studies subdivide the Black population for study; when they are, the literature has gen - erally subdivided this category into U.S.-born Blacks, Caribbean-born Blacks, and African-born Blacks although some have distinguished other groups by using additional countries of birth which may not necessarily represent ethnicity (e.g., born in Europe to African parents). The available literature has examined health and health care differences among these groups by overall self-rated health, mental health, cancer, low birthweight, and cardio - vascular health. Overall Self-Rated Health In a study comparing U.S.-born, European-born, African-born, and West-Indian-born Black ethnic groups aged 18 and older (utilizing merged 2000–2001 NHIS data), groups were examined for differences in self-rated health status, any self-assessed activity limitation in general and then specifically due to hypertension (Read et al., 2005b). Multivariate regression analyses adjusted for demographic characteristics and socioeconomic status including educational attainment, insurance status and income. The study does not distinguish between Blacks of different ethnicities born in the United States. U.S.- and European-born Blacks had worse ratings on all the measures compared with those born in Africa or Whites born in the United States. West Indian-born Blacks had poorer self-rated health status, more activity limitation, and more hypertension-related activity limitation compared with those born in Africa. European-born Blacks had the worst results of all categories; those who are African born had the best values. These findings lead the authors to conclude that the health advantage ascribed to Black immigrants in other studies can be due to the influence of data on African-born groups. Mental Health Williams and colleagues (2007) studied mental health among Caribbean Black groups of different ethnicities as well as African Americans with no Caribbean roots by using data derived from the National Survey of Ameri - can Life. The Caribbean groups included persons born in the United States as well as those who immigrated to this country. Caribbean Black women had significantly lower odds than African-American women of suffering from any mental disorder in terms of either lifetime prevalence or occurrence in the last 12 months. Caribbean Black men were significantly more likely to suffer from any disorder in the past 12 months but not for lifetime prevalence compared with U.S. African American men. Among the Caribbean ethnicities, those whose ethnic ori - gins were in Spanish-speaking countries had higher odds of lifetime prevalence of any disorder than those from English speaking countries. Using first-generation Blacks as the reference group, third-generation immigrants had greater odds of lifetime prevalence of any disorder. The authors note the importance of understanding associations between ethnicity and other factors in order to better describe heterogeneous populations, concluding “that the mental health risk profile of Caribbean Blacks differs from that of other African-Americans. Moreover, the Black Caribbean immigrant category itself masks considerable heterogeneity” (p. 57) as is illustrated by the differences exhibited for Spanish- and English-speaking countries of origin. Rates of Cancer Mortality Data on differences in cancer mortality rates among Blacks at more granular ethnicity levels are limited. One study, based on New York City death certificates dating from 1988–1992 linked with U.S. Census data, found that

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0 RACE, ETHNICITY, AND LANGUAGE DATA high levels of health disparities compared with other groups in the United States as well. For example, Native Hawaiians aged 36–65 are nearly 1.5 times as likely to experience heart disease as other racial groups in the United States (Asian & Pacific Islander American Health Forum, 2006). In California, NHOPI and Filipino adults have higher rates of obesity and being overweight (70 and 46 percent, respectively) compared with the state average (34 percent) (Ponce et al., 2009). Native Hawaiians also have the second highest rate of Type II diabetes among racial groups in the United States (Mau et al., 2001). However, sparse information on Pacific Islander subgroups may be related to the fact their numbers are proportionately small nationally and thus are not reflected in sufficient numbers for analysis in national surveys. WHITE GROUPS In Census 2000, 77 percent of the U.S. population (216.9 million people) self-identified with the White race (Grieco, 2001b).11 Because this is the largest racial group in the United States, it heavily influences reported levels of quality of health and health care achieved in the nation, as well as national rates of indicators, such as poverty. The OMB definition for the White race is “a person having origins in any of the original peoples of Europe, the Middle East, or North Africa,” (OMB, 1997) and the Census Bureau definition further elaborates with examples including Irish, German, Italian, Lebanese, Near Easterner, Arab, or Polish (U.S. Census Bureau, 2000). Demographic Characteristics The poverty rate among those of White race alone in 2007 was 10.5 percent, nearly the same as the overall average rate for Asian and Pacific Islanders but half the rate among Blacks and Hispanics. The national poverty rate for the total U.S. population as of 2007 was 12.5 percent (DeNavas-Walt et al., 2008). With respect to the number of persons in poverty, however, there are more Whites (25.1 million) in poverty than Blacks (9.2 million) and Hispanics (9.9 million) combined. Similarly, as of 2000, White non-Hispanics included a lower percentage of persons aged 25 and older who did not graduate from high school (14.5 percent) compared with Blacks (27.7 percent) and Hispanics of any race (47.6 percent) (U.S. Census Bureau, 2006a)—a rate that still translates into 19.4 million White non-Hispanics over age 25 without a high school diploma (U.S. Census Bureau, 2003a). The White population, like the AIAN and Black populations, is more likely to be born in the United States than other racial groups (Malone et al., 2003). (See Table 2-6.) Comparative information on different ethnicities within the White population is limited for both demograph - ics and health and health care differences. The Census has published only one in depth analysis of an ancestry grouping that falls within the White category, and that is of the U.S. Arab population. Three-fifths of the Arab population is of Lebanese, Syrian, and Egyptian ancestry (de la Cruz and Brittingham, 2003), but Lebanese are the largest group, consisting of more than a quarter (28.8 percent) of the U.S. Arab population (Brittingham and de la Cruz, 2005). About half of all Arabs in the country were born here (46.4 percent) (Brittingham and de la Cruz, 2005). Of those who speak Arabic at home, approximately one in four speak English less than very well. Sixteen percent of Arabs here over age 25 have not graduated from high school. The overall poverty rate for U.S. Arab groups (16.7 percent) is somewhat higher than the national rate (12.5 percent) (Brittingham and de la Cruz, 2005); some Arab ancestry groups (e.g., Palestinian, Moroccan, Iraqi) have higher poverty rates. About half of the Arab population resides in only five states: California, Florida, Michigan, New Jersey, and New York (de la Cruz and Brittingham, 2003). 11 The number identifying as White alone or in combination was 216.9 million, 211.5 of which were White alone, followed by White in combination with “Some other race” at 2.2 million, White and AIAN at 1.1 million, White and Asian at 0.9 million, and White and Black at 0.8 million.

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TABLE 2-6 Selected Characteristics of the White Population in the United States Speak a Language Percent of U.S. Other Than English non-Hispanic at Home and Speak Less Than White Groups Based on Number White Percent of Native English Less Than High School Language Ability (in millions) Populationd U.S. Population Born (%) “Very Well” (%) Graduationb (%) Poverty Rate (%) Whites speaking only English 175.0a 93.7 66.7 97.9 at home Whites speaking Spanish at 2.7a 1.4 1.0 91.5 46.7c 13.6 11.0 home Whites speaking other Indo- 8.6a 4.6 3.3 46.5 32.9c 23.8 11.6 European languages at home Whites speaking Asian and 0.4a 0.2 0.1 59.0 26.7c 12.6 10.0 Pacific Islander languages at home Whites speaking all other 0.1a 0.03 0.02 61.5 29.4c 19.0 16.8 languages at home Total White 186.8a NA 71.2 95.4 41.4 (31.3) c 14.2 8.1 Total U.S. Population 281.4 NA 93.2 88.9 8.1 19.6 12.4 a White non-Hispanic alone and in combination, 5 years of age and older. b Population 25 and older (186.8 million). c U .S. Census Bureau, 2003b, 2006b. Calculations using Census data. 41.4 is the White alone population aged 5 and older, and 31.3 is the White alone, not Hispanic or Latino figure. d 2 62.4 was used as a denominator for this column (U.S. Census Bureau, 2003b). SOURCES: Grieco, 2001b, and Subcommittee tabulations from the 2000 Public Use Microdata Sample (PUMS). 1

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2 RACE, ETHNICITY, AND LANGUAGE DATA Health-Related Differences Among Select White Groups While recent research is limited in this area, differences in health care and health outcomes among ethnicities who categorize themselves as White among the OMB categories have been documented. The sections that follow review more recent evidence on this topic, with an emphasis on differences found between groups of Arab and European descent. Reliable data on differences among other ethnic groups within the broad White category could not be identified, representing an area that could benefit from more study that would be informed by granular ethnicity data collection. Self-Reported Health Naturalized Middle Eastern immigrants reported worse health compared with their non-naturalized Middle Eastern counterparts in a study based on data from the NHIS. Overall, however, Arab Americans were less likely to report health-related limitations than U.S.-born Whites of European descent (Read et al., 2005a). Cancer Screening Lower rates of mammography have been found among Middle Eastern women than in the population as a whole. One telephone survey of 365 Arab American women in metropolitan Detroit found that only 70 percent reported ever having had a mammogram, compared with the overall rate for Michigan of 92.6 percent (Schwartz et al., 2008). This 70 percent rate is lower than the rate for other racial and ethnic groups nationally for mammo - grams as well. One group, Lebanese women, was considerably more likely than other groups of Arab women to have ever had a mammogram. Other predictors of screening among Middle Eastern women in this sample included being married, having health insurance, and having resided in the United States for 10 or more years (Schwartz et al., 2008). Cultural beliefs pertaining to cancer among Middle Eastern immigrants in New York appear to be signifi - cantly different from those of their White peers of European descent and can affect their access to optimal care. In a qualitative study of focus groups designed to explore barriers to cancer care for Arab immigrants, barriers that emerged included experiences of discrimination, fears of immigration enforcement, and differences in beliefs surrounding causes of cancer (Shah et al., 2008). However, another study that examined participation in breast cancer genetic counseling found no correla - tion between ethnicity of the participants in the study, which included European American women and women of Ashkenazi Jewish ancestry, and willingness to accept such counseling (Culver et al., 2001). This study did not control for socioeconomic factors except for level of education attained, because the genetic counseling was being offered at no charge in order to remove cost and access barriers for the participants. Preterm Birth A study found lower rates of preterm birth among mothers of Middle Eastern nativity than among those who were U.S.-born of Middle Eastern descent and U.S.-born non-Hispanic Whites (El Reda et al., 2007). Summary Disparities in health for non-Hispanic Whites compared with other racial groups include high levels of mortal - ity from melanoma, chronic lower respiratory deaths, and prostate cancer, each of which is potentially responsive to health care interventions (Keppel, 2007). While the data on differences among White subgroups is very limited, significant differences can be found among persons of Middle Eastern and European descent. International statis - tics provide some insight into the differences among European nations, which make up the ancestry of significant portions of the U.S. citizenry as well as the recent immigrant population (Brittenham and de la Cruz, 2004). For example, life expectancy in Eastern European countries and Russia is lower than in Western Europe (Ginther, 2009;

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 EVIDENCE OF DISPARITIES AMONG ETHNICITY GROUPS WHO, 2009). Foodways, the eating practices and customs of a group of people (e.g., lack of vitamin C intake among Russian men), and high rates of smoking and alcohol consumption all contribute. A high incidence of more lethal cancers, particularly of lung cancer, is common in Eastern Europe (Bray et al., 2002). Men and women in these countries also have the highest mortality rates from ischemic heart disease of all the Organisation for Eco - nomic Co-operation and Development (OECD) countries (OECD, 2007). Breast cancer incidence and mortality differs across Europe, being higher in Denmark than other northern European nations (Althuis et al., 2005). These findings represent very preliminary evidence in favor of the collection and reporting of more granular ethnicity data separately for White subgroups. It remains to be seen which other White subgroups experience considerable differences in care or health outcomes, and collecting granular ethnicity data will make the picture clearer. AMERICAN INDIAN OR ALASKA NATIVE GROUPS The number and proportion of persons in the American Indian or Alaska Native (AIAN) racial group is heav - ily influenced by whether the numbers are for AIAN alone or AIAN in combination with other racial groups. In Census 2000, 2.4 million persons (0.87 percent) in the U.S. population, fell in the AIAN alone group, but AIAN in combination with other races numbered 4.3 million (1.5 percent of the U.S. population). 12 The Census and the OMB define the term AIAN as referring to persons with origins in the indigenous persons of North, Central, or South America (Ogunwole, 2006), while the Indian Health Service (a U.S. Department of Health and Human Ser- vices agency responsible for providing federal health services to AIAN persons) uses its own narrower definition, which is confined to those enrolled in any of the federally or state-recognized tribes within the United States.13 To accommodate these identifications, Census 2000 provided space for a respondent to write in the name of his or her enrolled or principal tribe or affiliation. Demographic Characteristics As in the previous sections, Table 2-7 presents the larger population figures for the AIAN population alone and in combination with other races, along with variations in English proficiency and poverty rates for selected tribes. Not displayed in the table is the place of residence of the AIAN populations; one-third of American Indians live in tribal areas, 2.4 percent in Alaska Native villages, and the remaining 64.1 percent outside of tribal areas. Outside of tribal areas, 27.2 percent of AIAN individuals over age of 25 have less than a high school education, compared with 31.8–33.1 percent living in tribal areas (Ogunwole, 2006). Health-Related Differences Among American Indian or Alaska Native Tribal Groups In the literature, the AIAN group has been subdivided primarily based on tribal affiliation and/or geographic location. The available literature has examined health differences among these groups by measures of cancer, end- stage renal disease (ESRD), type II diabetes, and metabolic syndrome. Cancer Cancer rates among AIAN populations vary and are often misreported because of misclassification of race/ ethnicity data in national AIAN cancer registries (Wiggins et al., 2008). This has posed problems for cancer sur- veillance, research, and overall public health practice (Johnson et al., 2009; Wiggins et al., 2008). Using popula - tion-based cancer registries, Wiggins and colleagues (2008) examined the incidence rates of cancer in AIAN and non-Hispanic Whites during 1999–2004 and found that national data masks regional and thereby tribal variation. When combining incidence rates for all cancer sites, AIAN rates were found to be higher than non-Hispanic White rates in the Northern Plains (538.1 versus 464.8 per 100,000), Southern Plains (492.6 versus 461.2), and Alaska 12 The most frequent combinations reported are AIAN and White (1.0 million), AIAN and Black (0.18 million). 13 The Indian Healthcare Improvement Act, Public Law 94-437, 25 U.S.C. 1603(c)-(d).

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4 TABLE 2-7 Selected Characteristics of the American Indian or Alaska Native (AIAN) Population in the United States Speak a Language Other Than English at Home and Speak Less Than Numbera Percent of Percent of English Less Than High School AIAN Tribal Groupings (in millions) U.S. AIAN U.S. Population “Very Well” (%) Graduationb (%) Poverty Rate (%) AI, one tribe 2.88 1.02 9.9 27.4 25.8 Apache (0.10) 0.04 12.4 31.0 33.9 Cherokee (0.88) 0.31 2.0 23.4 18.1 Chippewa (0.16) 0.06 1.6 22.1 23.7 Choctaw (0.17) 0.06 4.3 20.4 18.5 Creek (0.08) 0.03 2.4 18.1 18.0 Iroquois (0.09) 0.03 2.0 20.4 19.0 Lumbee (0.06) 0.02 0.8 35.3 18.2 Navajo (0.31) 0.11 24.5 37.3 37.0 Pueblo (0.07) 0.03 17.5 23.7 29.1 Sioux (0.17) 0.06 3.4 23.8 38.9 AN, one tribe 0.12 0.04 9.3 25.4 19.5 Alaskan Athabascan (0.02) 0.01 3.8 24.6 22.9 Aleut (0.02) 0.01 3.0 22.5 15.0 Eskimo (0.06) 0.02 15.7 29.7 21.3 Tlingit-Haida (0.02) 0.01 1.7 17.6 15.2 One or more other specified tribe 1.78 0.45 Unspecified tribal grouping 1.01 0.36 Total AIAN 4.32 NA 10.3 29.1 25.7 Total U.S. Population 281.41 NA 1.53 8.1 19.6 12.4 aAIAN alone and in combination. bPopulation 25 and older. SOURCE: Ogunwole, 2006.

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 EVIDENCE OF DISPARITIES AMONG ETHNICITY GROUPS (511.0 versus 486.8). Rates in the Southwest, Pacific Coast, and the East, however, were found to be lower in AIANs than non-Hispanic Whites (218.3–308.9 per 100,000 vs. 398.9–574.4 per 100,000, respectively). When separating by cancer type, lung cancer, and colorectal cancer rates were found to be higher in AIANs than non- Hispanic Whites in Alaska and the Northern Plains. Stomach, gallbladder, kidney, and liver cancer rates were also found to be higher among AIANs than among non-Hispanic Whites overall, in Alaska, in the Plains regions, and in the Southwest (Wiggins et al., 2008). The analyses were limited to persons living within the Contract Health Service Delivery Areas of the Indian Health Service. Kelly and colleagues (2006) found subgroup differences when comparing the cancer incidence rates of Ameri - can Indians from New Mexico and Alaska.14 Between 1993 and 2002, Alaska Indians had a higher incidence rate for all cancer sites combined than either New Mexico Indians or U.S. Whites; in-fact, the overall cancer incidence rate of Alaska Indians was 2.5 times higher than that of New Mexico Indians. The largest variations between the two Indian groups were found in rates of oral cavity/pharynx, esophagus, colon and rectum, pancreas, larynx, lung, prostate, and bladder cancer. Differences in esophageal, larynx, prostate, and bladder cancer were found only in men, while both Alaska Indian men and women had 7 to 10 times higher rates of lung cancer and approximately two-fold rates of all cancers. Cultural use of tobacco was credited as a major factor in these differences (Kelly et al., 2006). No data were collected on income in the different populations. End-Stage Renal Disease Using data from the U.S. Renal Data System, Hochman and colleagues (2007) examined the prevalence and incidence of ESRD in 200,000 adult members of the Navajo Nation in Arizona, New Mexico, and Utah. Preva - lence and incidence rates are compared for ESRD among all adults in the United States; all Native Americans in the country; and Native Americans living in Arizona, New Mexico, and Utah and Colorado (outside of the Navajo Reservation). After adjusting for age, they found that the prevalence of ESRD in the Navajo Nation was 0.63 per- cent, higher than that in all U.S. adults (0.19 percent) and Native American adults (0.36 percent). However, this rate was lower than the prevalence among other Native American adults in the Southwest (0.89 percent) (Hochman et al., 2007). Incidence rates followed the same pattern. The study did not control for socioeconomic status. Type II Diabetes Type II diabetes affects a disproportionate number of AIANs; the highest rates in the country are among the Pima Indians of Arizona (Knowler, 1978). From 1990 to1997, the number of AIANs diagnosed with diabetes increased dramatically, from 43,262 to 64,474 (Burrows et al., 2000). While documentation of specific tribal dif - ferences is limited, Burrows and colleagues found prevalence to vary by region (3.0 percent in the Alaska region vs. 17.4 percent in the Atlantic region), suggesting tribal differences in population rates of diabetes (Burrows et al., 2000). Since no socioeconomic data were analyzed in this study, it is difficult to determine whether the regional differences alone are the underlying cause of the perceived tribal differences in diabetes rates, or regional location is correlated with other factors that could influence these rates. Metabolic Syndrome Often a predictor of diabetes, metabolic syndrome varies widely in prevalence across different AIAN adult populations. Shumacher and colleagues examined the prevalence of metabolic syndrome 15 among four groups, including the Navajo Nation from the southwestern United States and three within Alaska (Schumacher et al., 14 Alaska Native people comprise three major ethnic groups: Eskimo, Indian, and Aleut. 15 The National Cholesterol Education Program defines metabolic syndrome “by a group of metabolic risk factors in one person…. Abdomi - nal obesity (excessive fat tissue in and around the abdomen); Atherogenic dyslipidemia (blood fat disorders—high triglycerides, low HDL cholesterol and high LDL cholesterol—that foster plaque buildups in artery walls); Elevated blood pressure; Insulin resistance or glucose intolerance (the body can’t properly use insulin or blood sugar); Prothrombotic state (e.g., high fibrinogen or plasminogen activator inhibitor-1 in the blood); Proinflammatory state (e.g., elevated C-reactive protein in the blood)” (American Heart Association, 2009).

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6 RACE, ETHNICITY, AND LANGUAGE DATA 2008). Rates were age-adjusted to the 2000 U.S. adult population and compared with the rates of U.S. Whites, using NHANES data. Among those from the Navajo Nation, 43.2 percent of men and 47.3 percent of women had metabolic syndrome. These were much higher than rates in Alaska, where prevalence varied by region among men from 18.9 percent in western Alaska to 35.1 percent in southeast Alaska, and among women from 22.0 percent in western Alaska to 38.4 percent in southeast Alaska. Summary Studies have shown that disparities exist among AIAN groups. For conditions such as cancer, for which disparities appear to be even greater when one adjusts for misclassification of race/ethnicity, standardized col - lection of tribal identification as a granular ethnicity could provide the basis for better, more tailored health care responses. SUMMARY The available evidence on health and heath care disparities among granular ethnic groups in the U.S. popula - tion is limited primarily to those groups for which discrete categorization on national survey instruments currently exists. Many studies include large data sets, often national ones, pooled over multiple years that usually provide information that is sufficiently powered to support reliable inferences and conclusions. Evidence of health and heath care disparities among population subgroups is only beginning to emerge and our gaps in knowledge from the published literature are substantial. This is especially true for groups not captured in national data sets that may be of interest to local quality improvement efforts. However, the research reviewed in this chapter consistently finds significant variation across some of subgroups under each of the OMB categories, confirming the utility of collection and reporting of racial and ethnic data at a group level. Indeed, the need for further disaggregation beyond OMB race and ethnicity categories was emphasized by authors of many of the studies reviewed (Bilheimer and Sisk, 2008; Borrell and Crawford, 2008; Canino et al., 2006; Davis et al., 2006; Hayes et al., 2008; Huang and Carrasquillo, 2008; Jerant et al., 2008; Kagawa-Singer et al., 2007; Lancaster et al., 2006; Read et al., 2005b). After controlling for socioeconomic conditions, many of these differential effects remain. The scientific findings in this chapter demonstrate the existence of disparities in health and health care at a level of categorization that is more detailed than the OMB categories of race and Hispanic ethnicity. Therefore, the subcommittee concludes that use of the broad OMB categories alone can mask identification of disparities at the more granular level. Standardization of categories of granular ethnicity would enable valid comparisons across settings, across geographic locations, and over time. The level of granularity necessary for analysis will vary according to the composition of the population being served or studied, whether the size of subgroups is sufficiently large to make statistically reliable comparisons, and whether the pattern of differences experienced by subgroups identifies dis - tinct needs that are not already revealed by data aggregated into broader categories. A recommendation regarding how ethnicity data should be collected to help inform improvements in health and health care quality among racial and ethnic subgroups is discussed in the next chapter. REFERENCES Acevedo-Garcia, D., M. J. Soobader, and L. F. Berkman. 2007. Low birthweight among US Hispanic/Latino subgroups: The effect of maternal foreign-born status and education. Social Science and Medicine 65(12):2503-2516. AHRQ (Agency for Healthcare Research and Quality). 2008a. National Healthcare Disparities Report. Rockville, MD: AHRQ. ———. 2008b. National Healthcare Quality Report. Rockville, MD: AHRQ. Alegría, M., N. Mulvaney-Day, M. Torres, A. Polo, Z. Cao, and G. Canino. 2007. Prevalence of psychiatric disorders across Latino subgroups in the United States. American Journal of Public Health 97(1):68-75. Althuis, M. D., J. M. Dozier, W. F. Anderson, S. S. Devesa, and L. A. Brinton. 2005. Global trends in breast cancer incidence and mortality 1973-1997. International Journal of Epidemiology 34(2):405-412. American Heart Association. 2009. Metabolic syndrome. http://www.americanheart.org/presenter.jhtml?identifier=4756 (accessed April 30, 2009).

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 EVIDENCE OF DISPARITIES AMONG ETHNICITY GROUPS Asian & Pacific Islander American Health Forum. 2006. Health brief: Native Hawaiians in the United States. San Francisco, CA: Asian & Pacific Islander American Health Forum. Barger, S. D., and L. C. Gallo. 2008. Ability of ethnic self-identification to partition modifiable health risk among US residents of Mexican ancestry. American Journal of Public Health 98(11):1971-1978. Barnes, J. S., and C. E. Bennett. 2002. The Asian population: 2000. Washington, DC: U.S. Census Bureau. Bates, J. H., B. M. Hofer, and A. Parikh-Patel. 2008. Cervical cancer incidence, mortality, and survival among Asian subgroups in California, 1990-2004. Cancer 113(10 Suppl.):2955-2963. Bilheimer, L. T., and J. E. Sisk. 2008. Collecting adequate data on racial and ethnic disparities in health: The challenges continue. Health Affairs 27(2):383-391. Blaisdell-Brennan, H. K., and D. Goebert. 2001. Health care utilization among women on O’ahu: Implications for Native Hawaiian women. Pacific Health Dialog 8(2):274-279. Blendon, R. J., T. Buhr, E. F. Cassidy, D. J. Perez, K. A. Hunt, C. Fleischfresser, J. M. Benson, and M. J. Herrmann. 2007. Disparities in health: Perspectives of a multi-ethnic, multi-racial America. Health Affairs 26(5):1437-1447. Borrell, L. N., and N. D. Crawford. 2008. Disparities in self-reported hypertension in Hispanic subgroups, non-Hispanic Black and non- Hispanic White adults: The National Health Interview Survey. Annals of Epidemiology 18:803-812. Bray, F., R. Sankila, J. Ferlay, and D. M. Parkin. 2002. Estimates of cancer incidence and mortality in Europe in 1995. European Journal of Cancer 38(1):99-166. Brittingham, A., and G. P. de la Cruz. 2005. We the people of Arab ancestry in the United States. Washington, DC: U.S. Census Bureau. Burrows, N. R., L. S. Geiss, M. M. Engelgau, and K. J. Acton. 2000. Prevalence of diabetes among Native Americans and Alaska Natives, 1990- 1997: An increasing burden. Diabetes Care 23(12):1786-1790. Canino, G., D. Koinis-Mitchell, A. N. Ortega, E. L. McQuaid, G. K. Fritz, and M. Alegría. 2006. Asthma disparities in the prevalence, morbidity, and treatment of Latino children. Social Science and Medicine 63:12:2926-2937. Carter-Pokras, O., and R.E. Zambrana. 2006. Collection of legal status information: Caution! American Journal of Public Health 96(3):399. CDC (Centers for Disease Control and Prevention). 2008. Health characteristics of the Asian adult population: United States, 2004–2006. http://www.cdc.gov/nchs/data/ad/ad394.pdf (accessed June 15, 2009). Cohen, L. L. 2008. Racial/ethnic disparities in hospice care: A systematic review. Journal of Palliative Medicine 11(5):763-768. Cooper, L. A., M. N. Hill, and N. R. Powe. 2002. Designing and evaluating interventions to eliminate racial and ethnic disparities in health care. Journal of General Internal Medicine 17:477-486. Culver, J., W. Burke, Y. Yasui, S. Durfy, and N. Press. 2001. Participation in breast cancer genetic counseling: The influence of educational level, ethnic background, and risk perception. Journal of Genetic Counseling 10(3):215-231. David, R. J., and J. W. Collins. 1997. Differing birth weight among infants of U.S.-born Blacks, African-born Blacks, and U.S.-born Whites. New England Journal of Medicine 337(17):1209-1214. Davis, A. M., R. Kreutzer, M. Lipsett, G. King, and N. Shaikh. 2006. Asthma prevalence in Hispanic and Asian American ethnic subgroups: Results from the California Healthy Kids Survey. Pediatrics 118(2):e363-e370. de la Cruz, G. P., and A. Brittingham. 2003. The Arab population: 2000. Washington, DC: U.S. Census Bureau. del Pinal, J. and D. Schmidley. 2005. Matched race and Hispanic origin responses from Census 2000 and Current Population Survey February to May 2000. Working paper 79. Washington DC: U.S. Census Bureau. DeNavas-Walt, C., B. D. Procter, and J. Smith. 2008. Current populations report. Income, poverty, and health insurance coverage in the United States: 200. Washington, DC: U.S. Census Bureau. El Reda, D. K., V. Grigorescu, S. F. Posner, and A. Davis-Harrier. 2007. Lower rates of preterm birth in women of Arab ancestry: An epidemio- logic paradox–Michigan, 1993-2002. Maternal and Child Health Journal 11(6):622-627. Fang, J., S. Madhavan, and M. H. Alderman. 1997. Influence of nativity on cancer mortality among Black New Yorkers. Cancer 80(1):129-135. Fiscella, K. 2007. Eliminating disparities in healthcare through quality improvement. In Eliminating healthcare disparities in America: Beyond the IOM report, edited by Williams, R. A. Totawa, NJ: Humana Press, Inc. Flores, G., and S. C. Tomany-Korman. 2008. Racial and ethnic disparities in medical and dental health, access to care, and use of services in US children. Pediatrics 121(2):e286-e298. Ginther, E. 2009. Diets of Central Europeans and Russians. http://www.faqs.org/nutrition/Ca-De/Central-Europeans-and-Russians-Diets- of.html (accessed June 16, 2009). Goggins, W. B., and G. K. Wong. 2007. Poor survival for US Pacific Islander cancer patients: Evidence from the Surveillance, Epidemiology, and End Results Database: 1991 to 2004. Journal of Clinical Oncology 25(36):5738-5741. Gorin, S. S., and J. E. Heck. 2005. Cancer screening among Latino subgroups in the United States. Preventive Medicine 40(5):515-526. Grieco, E. M. 2001a. The Native Hawaiian and Other Pacific Islander population: 2000. Washington, DC: U.S. Census Bureau. ———. 2001b. The White population: 2000. Washington, DC: U.S. Census Bureau. Grieco, E. M., and R. C. Cassidy. 2001. Overview of race and Hispanic origin. Washington, DC: U.S. Census Bureau. Harris, P. M., and N. A. Jones. 2005. We the people: Pacific Islanders in the United States. Washington, DC: U. S. Census Bureau. Hasnain-Wynia, R., D. Pierce, A. Haque, C. H. Greising, V. Prince, and J. Reiter. 2007. Health Research and Educational Trust Disparities Toolkit. www.hretdisparities.org (accessed December 18, 2008). Hayes, D. K., S. L. Lukacs, and K. C. Schoendorf. 2008. Heterogeneity within Asian subgroups: A comparison of birthweight between infants of US and non-US born Asian Indian and Chinese mothers. Maternal and Child Health Journal 12:549–556.

OCR for page 31
 RACE, ETHNICITY, AND LANGUAGE DATA Hedeen, A. N., and E. White. 2001. Breast cancer size and stage in Hispanic American women, by birthplace: 1992-1995. American Journal of Public Health 91(1):122-125. HHS. 2000. Healthy People 2010: Understanding and improving health. Washington, DC: U.S. Department of Health and Human Services. Hochman, M. E., J. P. Watt, R. Reid, and K. L. O’Brien. 2007. The prevalence and incidence of end-stage renal disease in Native American adults on the Navajo reservation. Kidney International 71(9):931-937. Huang, K., and O. Carrasquillo. 2008. The role of citizenship, employment, and socioeconomic characteristics in health insurance coverage among Asian subgroups in the United States. Medical Care 46(10):1093–1098. IOM (Institute of Medicine). 2003. Unequal treatment: Confronting racial and ethnic disparities in healthcare. Edited by Smedley, B. D., A. Y. Stith and A. R. Nelson. Washington, DC: The National Academies Press. ———. 2008. Challenges and successes in reducing health disparities: Workshop summary. Washington, DC: The National Academies Press. Jerant, A., R. Arellanes, and P. Franks. 2008. Health status among US Hispanics: Ethnic variation, nativity, and language moderation. Medical Care 46(7):709-717. Johnson, J. C., A. S. Soliman, D. Tadgerson, G. E. Copeland, D. A. Seefeld, N. L. Pingatore, R. Haverkate, M. Banerjee, and M. A. Roubidoux. 2009. Tribal linkage and race data quality for American Indians in a state cancer registry. American Journal of Preventive Medicine 36(6):549-554. Kagawa-Singer, M., N. Pourat, N. Breen, S. Coughlin, T. A. McLean, T. S. McNeel, and N. Ponce. 2007. Breast and cervical cancer screening rates of subgroups of Asian American women in California. Medical Care Research and Review 64(6):706-730. Kaiser Family Foundation and Asian & Pacific Islander American Health Forum (APIAHF). 2008. Race, ethnicity and health care: Fact sheet. Health coverage and access to care among Asian Americans, Native Hawaiians and Pacific Islanders. Menlo Park, CA: The Henry J. Kaiser Family Foundation. ———. 2009. Putting women’s health care disparities on the map: Examining racial and ethnic disparities at the state level. Menlo Park, CA: The Henry J. Kaiser Family Foundation. Kelly, J. J., A. P. Lanier, S. Alberts, and C. L. Wiggins. 2006. Differences in cancer incidence among Indians in Alaska and New Mexico and U.S. Whites, 1993-2002. Cancer Epidemiology, Biomarkers and Prevention 15(8):1515-1519. Keppel, K. G. 2007. Ten largest racial and ethnic health disparities in the United States based on Healthy People 2010 objectives. American Journal of Epidemiology 166(1):97-103. Kington R.S. and H.W. Nickens. 2001. Racial and ethnic differences in health: recent trends, current patterns, future directions. In America becoming: racial trends and their consequences Vol. II, edited by Smelser, N.J., W.J. Wilson, and F. Mitchell. Washington, DC: National Research Council. Knowler, W. C., P. H. Bennett, R. F. Hamman, and M. Miller. 1978. Diabetes incidence and prevalence in Pima Indians: A 19-fold greater inci- dence than in Rochester, Minnesota. American Journal of Epidemiology 108(6):497-505. Lancaster, K. J., S. O. Watts, and L. B. Dixon. 2006. Dietary intake and risk of coronary heart disease differ among ethnic subgroups of Black Americans. Journal of Nutrition 136:446-451. Lara, M., L. Akinbami, G. Flores, and H. Morgenstern. 2006. Heterogeneity of childhood asthma among Hispanic children: Puerto Rican chil- dren bear a disproportionate burden. Pediatrics 117(1):43-53. Malone, N., K. F. Baluja, J. M. Costano, and C. J. Davis. 2003. The foreign-born population: 2000. Washington, DC: U.S. Census Bureau. Mau, M. K., K. Glanz, R. Severino, J. S. Grove, B. Johnson, and J. D. Curb. 2001. Mediators of lifestyle behavior change in Native Hawaiians. Diabetes Care 24(10):1770-1775. McKinnon, J. D., and C. E. Bennett. 2005. We the people: Blacks in the United States. Washington, DC: U.S. Census Bureau. Miller, B., K. Chu, B. Hankey, and L. Ries. 2008. Cancer incidence and mortality patterns among specific Asian and Pacific Islander populations in the U.S. Cancer Causes and Control 19(3):227-256. Moy. 2009. Lessons learned in developing NHQR and NHDR. Agency for Healthcare Research and Quality. Presentation to the IOM Com- mittee on Future Directions for the National Healthcare Quality and Disparities Reports, February 9, 2009. Washington, DC. PowerPoint Presentation. Murthy, B. V. R., D. A. Molony, and A. G. Stack. 2005. Survival advantage of Hispanic patients initiating dialysis in the United States is modi- fied by race. Journal of the American Society of Nephrology 16(3):782-790. OECD (Organisation for Economic Co-operation and Development). 2007. Health at a glance 200: OECD indicators. http://www.oecd.org/ health/healthataglance (accessed June 16, 2009). Ogunwole, S. U. 2006. We the people: American Indians and Alaska Natives in the United States. Washington, DC: U.S. Census Bureau. OMB (Office of Management and Budget). 1997. Revisions to the standards for the classification of federal data on race and ethnicity. Federal Register 62:58781-58790. Pallotto, E. K., J. W. Collins, and R. J. David. 2000. Enigma of maternal race and infant birth weight: A population-based study of US-born Black and Caribbean-born Black women. American Journal of Epidemiology 151(11):1080-1085. Ponce, N., W. Tseng, P. Ong, Y. L. Shek, S. Ortiz, M. Gatchell, and The University of California Asian American & Pacific Islander Policy Multi-Campus Research Program (MRP). 2009. The state of Asian American, Native Hawaiian and Pacific Islander health in California report. Sacramento, CA: California Asian Pacific Islander Joint Legislative Caucus. Ramirez, R. R. 2004. We the people: Hispanics in the United States: Census 2000 special reports. Washington, DC: U.S. Census Bureau. Read, J. G., B. Amick, and K. M. Donato. 2005a. Arab immigrants: A new case for ethnicity and health? Social Science and Medicine 61(1):77-82.

OCR for page 31
9 EVIDENCE OF DISPARITIES AMONG ETHNICITY GROUPS Read, J. G., M. O. Emerson, and A. Tarlov. 2005b. Implications of Black immigrant health for U.S. racial disparities in health. Journal of Im- migrant Health 7(3):205-212. Reeves, T. J., and C. E. Bennett. 2004. We the people: Asians in the United States. Washington, DC: U.S. Census Bureau. Schumacher, C., E. D. Ferucci, A. P. Lanier, M. L. Slattery, C. D. Schraer, T. W. Raymer, D. Dillard, M. A. Murtaugh, and L. Tom-Orme. 2008. Metabolic syndrome: Prevalence among American Indian and Alaska Native people living in the Southwestern United States and in Alaska. Metabolic Syndrome & Related Disorders 6(4):267-273. Schwartz, K., M. Fakhouri, M. Bartoces, J. Monsur, and A. Younis. 2008. Mammography screening among Arab American women in metro- politan Detroit. Journal of Immigrant & Minority Health 10(6):541-549. Shah, N. S., and O. Carrasquillo. 2006. Twelve-year trends in health insurance coverage among Latinos, by subgroup and immigration status. Health Affairs 25(6):1612-1619. Shah, S. M., C. Ayash, N. A. Pharaon, and F. M. Gany. 2008. Arab American immigrants in New York: Health care and cancer knowledge, at- titudes, and beliefs. Journal of Immigrant & Minority Health 10(5):429-436. Tang, G. 2009. Defining race, ethnicity and language populations. Kaiser Permanente. Presentation to the IOM Committee on Future Directions for the National Healthcare Quality and Disparities Reports, March 11, 2009. Newport Beach, CA. PowerPoint Presentation. Ting, H. H., E. H. Bradley, Y. Wang, J. H. Lichtman, B. K. Nallamothu, M. D. Sullivan, B. J. Gersh, V. L. Roger, J. P. Curtis, and H. M. Krum- holz. 2008. Factors associated with longer time from symptom onset to hospital presentation for patients with ST-elevation myocardial infarction. Archives of Internal Medicine 168(9):959-968. Trivedi, A. N., A. M. Zaslavsky, E. C. Schneider, and J. Z. Ayanian. 2005. Trends in the quality of care and racial disparities in Medicare man- aged care. New England Journal of Medicine 353(7):692-700. U.S. Census Bureau. 2000. State & county quickfacts. http://quickfacts.census.gov/qfd/meta/long_68184.htm (accessed June 14, 2009). ———. 2003a. Educational attainment: 2000. Washington, DC: U.S. Census Bureau. ______. 2003b. PHC-T-37 Table 1a. In Ability to Speak English by Language Spoken at Home. Washington, DC: U.S. Census Bureau. ———. 2006a. PHC-T-41 Table 3. In A Half-Century of Learning: Historical Statistics on Educational Attainment in the United States, 1940 to 2000. Washington, DC: U.S. Census Bureau. ———. 2006b. PHC-T-42 Table 1a. In America Speaks: A Demographic Profile of Foreign-Language Speakers for the United States: 2000. Washington, DC: U.S. Census Bureau. Van Ta, M., and T. Chen. 2008. Substance abuse among Native Hawaiian women in the United States: A review of current literature and recom- mendations for future research. Journal of Psychoactive Drugs 40(Suppl 5):411-422. Wang, J., D. E. Williams, K. M. V. Narayan, and L. S. Geiss. 2006. Declining death rates from hyperglycemic crisis among adults with diabetes, U.S., 1985-2002. Diabetes Care 29(9):2018-2022. Weinick, R. M., E. A. Jacobs, L. C. Stone, A. N. Ortega, and H. Burstin. 2004. Hispanic healthcare disparities: Challenging the myth of a mono- lithic Hispanic population. Medical Care 42(4):313-320. WHO (World Health Organization). 2009. European Health for All Database (HFA-DB). http://www.euro.who.int/hfadb (accessed June 16, 2009). Wiggins, C. L., D. K. Espey, P. A. Wingo, J. S. Kaur, R. T. Wilson, J. Swan, B. A. Miller, M. A. Jim, J. J. Kelly, and A. P. Lanier. Cancer among American Indians and Alaska Natives in the United States, 1994-2004. Cancer 113 (Suppl 5):1142-1152. Williams, D. R., R. Haile, H. M. Gonzalez, H. Neighbors, R. Baser, and J. S. Jackson. 2007 The mental health of Black Caribbean immigrants: Results from the National Survey of American Life. American Journal of Public Health 97(1):52-59. Yu, S. M., Z. J. Huang, and G. K. Singh. 2004. Health status and health services utilization among U.S. Chinese, Asian Indian, Filipino, and Other Asian/Pacific Islander children. Pediatrics 113(1):101-107. Zambrana, R., C. Ayala, O. Carter-Pokras, J. Minaya, and G. A. Mensah. 2007. Disparities in hypertension-related mortality among selected Hispanic subgroups and non-Hispanic White women ages 45 years and older - United States, 1995–1996 and 2001–2002. Ethnicity and Disparities 17(3):434-440. Zambrana, R. E., N. Breen, S. A. Fox, and M. L. Gutierrez-Mohamed. 1999. Use of cancer screening practices by Hispanic women: Analyses by subgroup. Preventive Medicine 29(6):466-477.

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