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Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement (2009)

Chapter: 2 Evidence of Disparities Among Ethnicity Groups

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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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-

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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 differences 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 documents 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

1

In 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).

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

TABLE 2-1 Census 2000 Population by Race and Hispanic Ethnicity

Population Group

Number (in millions)

Percent of 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.

aRamirez, 2004.

bGrieco 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.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

The term granular has been used in describing more detailed categories in the Hospital Research & Educational 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 quality 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, insurance 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 functional 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.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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 improving 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 educational 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.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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 available 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 identifying 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 automatically 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).

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

TABLE 2-2 Selected Characteristics of the Hispanic/Latino/Spanish Population in the United States

Hispanic Groups

Number (in millions)

Percent of U.S. Hispanic Population

Percent of U.S. Population

Native Born (%)

Speak a Language Other Than English at Home and Speak English Less Than “Very Well” (%)

Less Than High School 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 Includes general responses such as Hispanic, Spanish, and Latino.

SOURCE: Ramirez, 2004.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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 proportion 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 (ambulatory care visits, emergency department [ED] visits, prescription medications, and inpatient hospitalizations). After controlling for sociodemographics, including income and health insurance coverage, multivariate regression 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.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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) compared the use of three cancer screening practices (Pap smear, mammogram, and clinical breast exam) for five categories 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 population 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 pattern 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.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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 assessing 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 interventions 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.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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 generally 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 cardiovascular 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 American 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 origins 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

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

TABLE 2-3 Selected Characteristics of the Black Population in the United States

Black Groups

Numbera (in millions)

Percent of U.S. Black Population

Percent of U.S. Population

Native Born (%)

Speak a Language Other Than English at Home and Speak English Less Than “Very Well” (%)

Less Than High School Graduationb (%)

Poverty Rate (%)

African-American

24.5

67.0

8.6

99.0

c

24.3

23.2

Afro-Caribbean

1.6

4.4

0.6

30.4

c

27.6

15.5

African

1.5

4.2

0.5

68.3

34.2c

21.2

22.3

Other or no ancestry reported

9.0

24.5

3.1

91.0

 

38.8

29.8

Total Black

36.6

100.0

12.8

92.8

36.1c

27.7d

24.3

Total U.S. population

285.2

12.8

NA

88.9

8.1

19.6

12.4

Blacks speaking Spanish at home

1.5

4.0

0.5

78.7

37.5c

32.3

30.1

Blacks speaking other Indo-European languages at home

0.9

2.5

0.3

39.6

38.5c

31.1

20.3

Blacks speaking Asian and Pacific Islander languages at home

0.06

0.2

0.02

67.7

29.8c

21.1

16.7

Blacks speaking all other languages at home

0.06

0.2

0.02

55.8

28.4c

22.4

28.7

a Black race alone and in combination.

b Population 25 and older (20.8 million).

c U.S. Census Bureau, 2006b. Calculations using Census data. Black race alone. Population 5 years and older.

d U.S. Census Bureau, 2006a. Calculations using Census data.

SOURCES: McKinnon and Bennett, 2005, and Subcommittee tabulations from the 2000 Public Use Microdata Sample (PUMS).

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

Caribbean-born non-Hispanic Blacks had lower rates than U.S.-born non-Hispanic Blacks for the types of cancer studied with the exception of prostate cancer. For that, the Caribbean-born group rate was significantly higher than that of any other group (Fang et al., 1997). The authors posit that differences in the Caribbean diet may be protective for certain types of cancers such as colon, rectum, and breast. Descriptive statistics indicated that more Caribbean Blacks graduated from high school, but cancer rates were not adjusted for educational attainment.

Low Birthweight

Pallotto and colleagues (2000) used vital records from Illinois (1985–1990) to assess the low- birthweight distributions for infants born to U.S.-born Black women, Caribbean-born Black women, and U.S.-born White women. They classified women into low and high risk categories based on reproductive risk factors (e.g., trimester, parity) and socioeconomic risk factors (e.g., age, education). Even for the lowest risk mothers, there were differences in relative risks for moderately low birthweight infants (1,500–2,499 g); compared with infants of non-Hispanic White mothers, the risk for infants delivered of U.S.-born non-Hispanic Black mothers was 2.7 (95 percent CI 2.1–3.4) and for infants delivered of Caribbean-born Black mothers 1.2 (95 percent CI 0.4–3.1). This mirrored the relative risk profile for delivery of moderately low birthweight infants among all mothers in these ethnic groups regardless of whether they themselves were assessed as high or low risk for low birthweight outcomes. The relative risk for very low birthweight infants (less than 1,500 g) was elevated for both groups of Black mothers compared with non-Hispanic White mothers, but the Black groups were not significantly different from each other. A similar study of deliveries in Illinois found lower relative risk of low birthweight for infants whose mothers were born in Africa; in fact, for women classified as low risk on demographics and reproductive factors, the relative risk was similar for women born in Africa and for U.S. born White women, yet the risk remained high for U.S. born African-American women (David and Collins, 1997).

Cardiovascular Health

A study by Lancaster and colleagues (2006) used data from the National Health and Nutrition Examination Survey (NHANES) III to assess differences in dietary intake, coronary heart disease (CHD) risk factors, and predicted 10-year risk of CHD for subgroups of Black adults (non-Hispanic Blacks born in the United States and both non-Hispanic and Hispanic Blacks born outside of the United States). Multivariate analyses controlled for education as a socioeconomic marker as well as for age, sex, and body mass index. The study found that non-Hispanic Black, U.S.-born participants had a higher intake of calories and fat; a lower intake of fruits, fiber and micronutrients; and a higher predicted 10-year risk of developing CHD (5.8 percent) than both immigrant groups (non-Hispanic Black 3.7 percent, p <0.001; Hispanic Black 4.7 percent, p = 0.017). However, it is notable that there are differences between the two immigrant groups in terms of their 10-year risk as well. In addition, proportionally more non-Hispanic Black immigrants had elevated fasting glucose, while more Hispanic Blacks had elevated serum triglycerides and low HDL cholesterol. The authors conclude that there is a need to study dietary and health differences within the Black population and tailor dietary interventions to subgroups of Blacks.

Summary

In the Black category, U.S.-born Blacks disproportionately suffered worse mental health and cardiovascular outcomes and were at greater risk for having low-birth-weight infants than Blacks born in the Caribbean or Africa. A few notable exceptions were found, such as a significantly elevated incidence of prostate cancer among Caribbean men. The authors of these studies and other studies describe heterogeneity within the Black population in health and cultural factors such as diet, and the need to continue to examine the Black population in greater detail (Kington and Nickens, 2001). Differentials have been primarily explored by distinguishing Black populations born in the United States and elsewhere. Heterogeneity, however, was also described among various immigrant ethnicities.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

ASIAN GROUPS

While Census 1990 collected data for the single category “Asian or Pacific Islander,” Census 2000 split the categories into “Asian” and “Native Hawaiian or Other Pacific Islander,” as required by the 1997 OMB standards. The Census and OMB definition for who fits into the Asian category includes “people having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent” (OMB, 1997; U.S. Census Bureau, 2000).

Demographic Characteristics

In Census 2000, 4.2 percent of the U.S. population (11.8 million people) self-identified with the Asian category.9 The largest Asian ethnic groupings are listed in Table 2-4. Each group has different characteristics pertaining to amount of time in the United States, English proficiency, educational attainment, and risk of poverty. Many of Chinese and Japanese ethnicity have lived in the United States for generations, while Vietnamese and Hmong populations are more often recent immigrants. The median age for Japanese is almost 43 years compared with the Hmong population, which has a median age of 16 years (Reeves and Bennett, 2004).

Health-Related Differences Among Asian Groups

For the most part, the Asian categories have been subdivided according to country of ancestry, although some authors also include more general categories (e.g., South Asian). The available literature has examined access to and utilization of health care, cancer and cancer screening, low birthweight, and asthma outcomes.

Access to and Utilization of Health Care Services

Huang and Carrasquillo (2008) used cross-sectional analyses of CPS data to examine differences in insurance coverage across the six largest distinct groups of Asian populations in the United States: Chinese, Filipino, Indian, Korean, Vietnamese, and Japanese. Differences among Asian subgroups in coverage can be greater than the difference between all Asians and non-Hispanic Whites. Persons of Korean heritage had the highest overall proportion lacking coverage (29.8 percent), followed by 21.5 percent in the Vietnamese group and 16.8 percent in the Chinese group (Huang and Carrasquillo, 2008). U.S. born-Koreans reported about twice the rate of uninsurance of other Asian subgroups born in the United States. People of Asian Indian, Filipino, and Japanese heritage had insurance rates similar or better than those of non-Hispanic Whites. The authors note that insurance expansions based solely on income may not resolve the higher rates of uninsurance for Koreans who may have incomes too high to qualify for public programs, but as small business owners find affordability of insurance an issue.

A lack of health coverage can lead to problems in having a usual source of health care. A recent study released by the Kaiser Family Foundation and the Asian and Pacific Islander American Health Forum found that uninsured Asians are more than four times as likely to lack a usual source of care compared with insured Asians (Kaiser Family Foundation and APIAHF, 2008). The same study found that 20 percent of Asian Indians and 21 percent of those falling into the Other Asian category lack a usual source of care, while Chinese and Filipino Americans have rates similar to those for non-Hispanic Whites. The percentage of uninsured persons having a doctor’s visit in the past year also varies among subgroup ethnicities. The differential among Asian American groups—for example, fewer insured Filipinos lack a usual source of care (7 percent) compared with insured Asian Indians (13 percent)—is greater than a comparison of the broad Asian category (11 percent) with insured non-Hispanic Whites (9 percent).

Analyses of NHIS survey data from 2004–2006 reveal differences among Asian subgroups in access and utilization (CDC, 2008). For example, 25 percent of Korean adults are without a usual source of car, about twice

9

3.6 percent reported Asian alone; Hispanic Asians make up about 1.0 percent of the Asian population. Of those checking more than one race, the largest combinations in order were Asian and White (0.9 million, 0.3 percent of the total population), Asian and “Some other race” (0.2 million, 0.1 percent), Asian and NHOPI (0.1 million), and Asian and Black or African American (0.1 million).

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

TABLE 2-4 Selected Characteristics of the Asian Population in the United States

Asian Groups

Numbera (in 000s)

Percent of U.S. Asian Population

Percent of U.S. Population

Native Born (%)

Speak a Language OtherTthan English at Home and Speak English Less Than “Very Well” (%)

Less Than High School Graduationb (%)

Poverty Rate (%)

Chinese

2,858

23.8

1.02

29.1

49.6

23.0

13.5

Filipino

2,385

18.3

0.85

32.3

24.1

12.7

6.3

Asian Indian

1,855

16.2

0.66

24.6

23.1

13.3

9.8

Vietnamese

1,212

10.9

0.43

23.9

62.4

38.1

16.0

Korean

1,226

10.5

0.44

22.3

50.5

13.7

14.8

Japanese

1,152

7.8

0.41

60.5

27.2

8.9

9.7

Cambodian

212

1.8

0.08

34.2

53.5

53.3

29.3

Hmong

184

1.7

0.07

44.4

58.6

59.6

37.8

Laotian

196

1.6

0.07

31.9

52.8

49.6

18.5

Pakistani

209

1.5

0.07

24.5

31.7

18.0

16.5

Thai

150

1.1

0.05

22.2

46.9

20.9

14.4

Other Asiansc

561

4.7

0.20

43.5

32.7

19.1

15.6

Total Asian

11,859

100

NA

31.1

39.5

19.6

12.6

Total U.S. Population

281,412

NA

4.21

88.9

8.1

19.6

12.4

a Asian alone and in combination.

b Population 25 and older.

c Bangladeshi, Bhutanese, Burmese, Indo Chinese, Indonesian, Iwo Jiman, Malaysian, Maldivian, Nepalese, Okinawan, Singaporean, Sri Lankan, Taiwanese.

SOURCES: Barnes and Bennett, 2002; Reeves and Bennett, 2004.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

the rate of other Asian subgroups. Vietnamese adults are more likely to identify a clinic or a health center as their usual source of care (23 percent) compared with other groups (13–14 percent for Japanese, Asian Indians, and Filipinos). The Japanese group was more likely than others to receive influenza and pneumonia vaccinations; Asian Indians are more likely to have received hepatitis B vaccines. A study of Asian and Pacific Islander children using NHIS data from 1997–2000 showed that children identified as falling into the heterogeneous “other Asian and Pacific Islander” category were the most likely to lack a usual source of care (6.3 percent) compared with Chinese (3.8), Filipino children (3.6), Asian Indian (1.9) and non-Hispanic Whites (1.7) (Yu et al., 2004). The poverty rate was greatest among these categories for the Asian Indian and other Asian and Pacific Islander families, but their rates of access differed.

Health Status

Asian Americans tend to rate their health status more highly than do other groups, just 11 percent of Asian Americans rate their health status as fair or poor, compared with 13 percent of non-Hispanic Whites, 18 percent of Hispanics, 22 percent of African Americans, and 23 percent of American Indians/Alaska Natives (Kaiser Family Foundation and APIAHF, 2008). Among Asian American ethnic groups, the proportion rating their health status as fair or poor ranges from 8 percent among those of Japanese ethnicity to 15 percent among those of Vietnamese or South East Asian extraction. Thus, the difference among some Asian groups is greater than the difference revealed by simply comparing the rates for all Asian Americans to non-Hispanic Whites.

Cancer and Cancer Screening among Asian Ethnicities

Breast and cervical cancer screening rates are lower for Asian American women than for any other ethnic group in California. To better understand Asian intragroup differences, Kagawa-Singer and colleagues (2007) used the 2001 California Health Interview Survey to evaluate Pap smear and mammography screening rates for a representative sample of 2,239 Asian American women. Reported rates of Pap test use for those aged 18 and older ranged from 81 percent (Filipina) to 61 percent (Vietnamese). Reported mammography rates for women aged 40 and older ranged from 78 percent (Japanese) to 53 percent (Korean). Somewhat surprisingly, Korean and Japanese immigrants with more than 10 years of U.S. residency had higher rates of Pap screening than their U.S. born counterparts, but this pattern did not hold up for Korean immigrants on mammogram screening. While trends suggested increased used of screening with increasing income, the difference was only found to be significant for Chinese Americans utilizing Pap tests. For women whose income was less than 200 percent of the federal poverty limit (FPL), the Pap screening rates still varied by ethnicity from 53 percent for Chinese Americans to 78 percent for Filipina Americans. Similarly among insured women, the range was 64 percent for Vietnamese and Cambodian Americans to 82 percent for Filipina Americans. Utilization of mammography among women below 200 percent of FPL also varied by ethnicity, from 53 percent for Korean American women to 86 percent among Asian Indian women. Rates for insured women also varied from 59 percent among Korean Americans to 78 percent among Japanese American women. The authors stress that “different factors were independently associated with lower screening rates for each group” (p. 706), and thus it is important to tailor interventions to specific ethnic subgroups.

Asian groups differ with respect to not only screening rates but also mortality. Using data from the California Cancer Registry, which collects approximately 140,000 new cancer case reports annually, the Kaplan-Meier method was applied to calculate 5- and 10-year survival probabilities for cervical cancer by Asian subgroup, and the Cox proportional hazard method was applied for calculating adjusted survival rates (Bates et al., 2008). Among the California women, once adjusted for age, socioeconomic status, stage, and treatment, the risk of mortality was found to be significantly lower for all groups compared to non-Hispanic Whites except Chinese and Japanese women. Of the six groups studied (Chinese, Filipino, Japanese, Korean, South Asian, and Vietnamese), South Asian women were found to have the highest unadjusted survival rates at both 5 and 10 years (85.8 percent for both), followed by Korean (85.7 and 82.5 percent), and Vietnamese (82.1 and 79.7 percent) groups, compared with non-Hispanic Whites (77.5 and 75.4 percent) and Japanese (72.3 and 69.5 percent). Incidence rates are highest among Vietnamese, Filipino, and Korean ethnic groups and lowest among Chinese, Japanese, and South Asian

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

groups; the authors note that incidence rates tend to mirror rates found in international surveillance reports for distinct ethnicities with a few exceptions.

The Centers for Disease Control and Prevention (CDC, 2008, p. 2) states that “although cancer mortality rates for Asian Americans are low compared with other U.S. populations, Asian Americans have the highest incidence rates of liver and stomach cancer for both sexes compared with Hispanic, non-Hispanic Whites, or non-Hispanic Blacks” (CDC, 2008). Furthermore, subgroup differences can be illustrated by differential mortality rates for liver cancer for different Asian ethnicities in California data: specifically 54.3 per 100,000 males for Vietnamese, 33.9 for Korean, 23.3 for Chinese, 16.8 for Filipino, and 9.3 for Japanese compared with a rate of 6.8 for non-Hispanic White males in the state. Disproportionate risks exist for some Asian subgroups, but not all, for a variety of other conditions, including chronic obstructive pulmonary disease, chronic hepatitis B, tuberculosis, and diabetes.

Low Birthweight

Comparisons of the birthweight outcomes for two Asian subgroups (Asian Indian and Chinese) were derived from analysis of the National Center for Health Statistics Natality File for 293,211 singleton births during 1998–2003. Een when the mothers were themselves born in the United States there were ethnic differences in outcomes. Infants born to Asian Indian mothers were more likely to have a lower mean birthweight as well as higher proportions of very low birthweight (VLBW) and moderately low birthweight (MLBW) compared with Chinese mothers, once data were adjusted for age, education, marital status, and parity. Infants born of U.S.-born Asian Indian mothers were 1.87 times as likely to be VLBW and 1.59 times more likely to be MLBW than infants born to U.S.-born Chinese mothers. The likelihood of VLBW and MLBW infants was even higher for non-U.S.-born Asian Indian mothers compared with non-U.S.-born Chinese mothers (Hayes et al., 2008).

Asthma

A large study published by Davis and colleagues (2006) compared asthma prevalence among various Asian American and Pacific Islander ethnic groups using data from the California Healthy Kids Survey on 462,147 public school students in the state from school years spanning 2001–2002 and 2002–2003. While the analyses could not adjust for sociodemographic characteristics beyond grade and gender, the existence of distinct rates among the groups is clear. Pacific Islander and Filipino groups had higher lifetime prevalence rates for asthma (21.0 and 23.8 percent, respectively) than eight other subgroups (e.g., Korean [10.9 percent], Vietnamese [13.6 percent], Chinese [14.4 percent], and Asian Indians [16.3 percent]). The authors note that prevalence studies can be influenced substantially by the composition of the population under study, and recommend more precise categorization by subgroups for utilization in such studies.

Summary

In the Asian category, differences exist across ethnic groups, and disparities differ on health care and health measures. For example, Japanese persons appear less likely to experience cancer screening disparities compared with the reference population, while differences were often noted for Korean, and Vietnamese subgroups. Yet Japanese women have high cervical cancer mortality. Each study stresses the importance of distinct reporting by subgroup to illuminate differences in order to tailor responses accordingly. Pooling of data over several years is often necessary to have a substantial sample to distinguish among subgroups.

NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER GROUPS

In Census 2000, 0.31 percent of the U.S. population (860,965 people) self-identified with the Native Hawaiian or Other Pacific islander (NHOPI) category.10 This grouping is defined by the Census and OMB as “people

10

0.13 percent (378,782) reported being NHOPI alone.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands” (OMB, 1997; U.S. Census Bureau, 2000).

Demographic Characteristics

The largest NHOPI groups are listed in Table 2-5. Native Hawaiians, Samoans, and Guamanians make up 74 percent of the Pacific Islander population. Fully 80 percent of NHOPIs are native to the United States since persons born in American Samoa, Guam, or Hawaii are included in the native-born population. Native Hawaiians fare better on ability to speak English, graduation from high school, and having a lower poverty rate relative to most of the other Pacific Islander subgroups (Harris and Jones, 2005).

Health-Related Differences Among Native Hawaiian or Other Pacific Islander Groups

The NHOPI group has been subdivided for analysis according to islands of ancestry. Few studies are available for examining this population in greater detail. Philippine Islanders are classified under the Asian category according the OMB convention; however, some studies examine their health and health care profile along with groups classified as Pacific Islanders by OMB definition.

Access to and Utilization of Health Care Services

A study using a three-year average from CPS data found that the most recent estimate of uninsurance for the NHOPI population was 20.5 percent (DeNavas-Walt et al., 2008). Another study found that the level of uninsurance to be 24 percent (Kaiser Family Foundation and APIAHF, 2008). Several studies also note the low health care utilization rates of Native Hawaiian women compared with other Asian populations (Blaisdell-Brennan and Goebert, 2001; Van Ta and Chen, 2008).

Cancer among Pacific Islander Groups

Among Pacific Islander groups living in all 17 SEER registry sites of the United States, significant health disparities have been found for Native Hawaiian and Samoan groups (Goggins and Wong, 2007; Miller et al., 2008). A study by Goggins and Wong (2007) showed that Samoans were significantly more likely to present with advanced cancer and had the poorest cause-specific survival of all groups studied, including Native Hawaiians, other Pacific Islanders, African Americans, Native Americans, and Whites. While all Pacific Islander ethnicities had poorer cause-specific survival than Whites, Samoan women had an especially elevated risk of mortality from breast cancer (relative risk [RR] = 3.05, 95 percent CI 2.31–4.02) and Samoan men had an especially elevated risk of mortality from prostate cancer (RR = 4.82, 95 percent CI 3.38–6.88). Similar findings are presented in a study by Miller and colleagues (2008), where overall cancer incidence rates were lower for Asians and Pacific Islanders in the sample (i.e., Asian Indians, Chinese, Filipinos, Guamanians, Japanese, Koreans, Native Hawaiians, Samoans, and Vietnamese) compared with White non-Hispanics in the United States; the one exception was Native Hawaiian women. The age-adjusted all cancer mortality rate among Asian and Pacific Islander men was highest for Native Hawaiians (263.7 per 100,000) and Samoans (293.9) in contrast to Guamanians (147.0) and Asian populations such as Japanese (173.7) or Vietnamese (159.9). The pattern of mortality rates among women was the same. The authors suggest that the higher risk for poor outcomes among Samoans may be due to failure to target interventions to small groups whose outcomes are masked when their data are combined with all Pacific Islander and Asian data.

Summary

Pacific Islander groups are little studied in comparative research, but among those studied, Samoans appear to suffer disproportionate rates of poor cancer outcomes. Additional data sources indicate that NHOPIs experience

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

TABLE 2-5 Selected Characteristics of the NHOPI Population in the United Statesa

NHOPI Groups

Numberb (in 000s)

Percent of U.S. NHOPI

Percent of U.S. Population

Native Born (%)

Speak a Language Other Than English at Home and Speak English Less Than “Very Well” (%)

Less Than High School Graduationc (%)

Poverty Rate (%)

Native Hawaiian

400

36.8

0.14

97.8

04.3

16.8

15.6

Samoan

128

22.5

0.05

79.1

19.5

24.2

20.2

Guamanian

91

14.6

0.03

87.6

15.4

22.2

13.7

Tongan

37

7.3

0.01

48.6

32.7

34.7

19.5

Fijian

14

2.7

0.01

22.4

25.2

33.2

10.5

Marshallese

7

1.5

 

23.9

41.4

32.3

38.3

Other Pacific Islander

209

14.6

0.07

61.7

19.4

23.3

21.4

Tahitiand

(3.3)

 

 

 

 

 

 

Tokelauan

(0.6)

 

 

 

 

 

 

Mariana Islander

(0.1)

 

 

 

 

 

 

Saipanese

(0.5)

 

 

 

 

 

 

Palauan

(3.4)

 

 

 

 

 

 

Carolinian

(0.2)

 

 

 

 

 

 

Kosraean

(0.2)

 

 

 

 

 

 

Pohnpeian

(0.7)

 

 

 

 

 

 

Chuukese

(0.7)

 

 

 

 

 

 

Yapese

(0.4)

 

 

 

 

 

 

I-Kiribati

(0.2)

 

 

 

 

 

 

Papua New Guinea

(0.2)

 

 

 

 

 

 

Solomon Islander

(0.03)

 

 

 

 

 

 

Ni-Vanuatu

(0.02)

 

 

 

 

 

 

Unspecified

(193.6)

 

 

 

 

 

 

Total NHOPI

860

100

NA

80.1

14.5

21.7

17.7

Total U.S. Population

281,412

NA

0.31

88.9

08.1

19.6

12.4

a Data for Pacific Islanders living in the U.S. Island Areas of Guam, American Samoa, and the Commonwealth of the Northern Mariana Islands are not included in the count.

b NHOPI alone and in combination.

c Population 25 and older.

d Ethnicities of Other Pacific Islanders from Grieco, 2001a.

SOURCE: Harris and Jones, 2005.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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 demographics 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.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

TABLE 2-6 Selected Characteristics of the White Population in the United States

White Groups Based on Language Ability

Number (in millions)

Percent of U.S. non-Hispanic White Populationd

Percent of U.S. Population

Native Born (%)

Speak a Language Other Than English at Home and Speak English Less Than “Very Well” (%)

Less Than High School Graduationb (%)

Poverty Rate (%)

Whites speaking only English at home

175.0a

93.7

66.7

97.9

 

 

 

Whites speaking Spanish at home

2.7a

1.4

1.0

91.5

46.7c

13.6

11.0

Whites speaking other Indo-European languages at home

8.6a

4.6

3.3

46.5

32.9c

23.8

11.6

Whites speaking Asian and Pacific Islander languages at home

0.4a

0.2

0.1

59.0

26.7c

12.6

10.0

Whites speaking all other languages at home

0.1a

0.03

0.02

61.5

29.4c

19.0

16.8

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 262.4 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).

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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 mammograms 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 significantly 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 correlation 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 mortality 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 statistics 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;

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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 Economic 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 heavily 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 Services 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 surveillance, research, and overall public health practice (Johnson et al., 2009; Wiggins et al., 2008). Using population-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).

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

TABLE 2-7 Selected Characteristics of the American Indian or Alaska Native (AIAN) Population in the United States

AIAN Tribal Groupings

Numbera (in millions)

Percent of U.S. AIAN

Percent of U.S. Population

Speak a Language Other Than English at Home and Speak English Less Than “Very Well” (%)

Less Than High School 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

a AIAN alone and in combination.

b Population 25 and older.

SOURCE: Ogunwole, 2006.

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

(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 American 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. Prevalence 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 percent, 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 to 1997, the number of AIANs diagnosed with diabetes increased dramatically, from 43,262 to 64,474 (Burrows et al., 2000). While documentation of specific tribal differences 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 syndrome15 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…. Abdominal 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).

Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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 collection 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. population 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 distinct 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.

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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×

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×

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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
×
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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Suggested Citation:"2 Evidence of Disparities Among Ethnicity Groups." Institute of Medicine. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. doi: 10.17226/12696.
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The goal of eliminating disparities in health care in the United States remains elusive. Even as quality improves on specific measures, disparities often persist. Addressing these disparities must begin with the fundamental step of bringing the nature of the disparities and the groups at risk for those disparities to light by collecting health care quality information stratified by race, ethnicity and language data. Then attention can be focused on where interventions might be best applied, and on planning and evaluating those efforts to inform the development of policy and the application of resources. A lack of standardization of categories for race, ethnicity, and language data has been suggested as one obstacle to achieving more widespread collection and utilization of these data.

Race, Ethnicity, and Language Data identifies current models for collecting and coding race, ethnicity, and language data; reviews challenges involved in obtaining these data, and makes recommendations for a nationally standardized approach for use in health care quality improvement.

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