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1.  Professional Uncertainty and Disempowerment Responding to Ethnic Diversity in Health Care: A Qualitative Study 
PLoS Medicine  2007;4(11):e323.
Background
While ethnic disparities in health and health care are increasing, evidence on how to enhance quality of care and reduce inequalities remains limited. Despite growth in the scope and application of guidelines on “cultural competence,” remarkably little is known about how practising health professionals experience and perceive their work with patients from diverse ethnic communities. Using cancer care as a clinical context, we aimed to explore this with a range of health professionals to inform interventions to enhance quality of care.
Methods and Findings
We conducted a qualitative study involving 18 focus groups with a purposeful sample of 106 health professionals of differing disciplines, in primary and secondary care settings, working with patient populations of varying ethnic diversity in the Midlands of the UK. Data were analysed by constant comparison and we undertook processes for validation of analysis. We found that, as they sought to offer appropriate care, health professionals wrestled with considerable uncertainty and apprehension in responding to the needs of patients of ethnicities different from their own. They emphasised their perceived ignorance about cultural difference and were anxious about being culturally inappropriate, causing affront, or appearing discriminatory or racist. Professionals' ability to think and act flexibly or creatively faltered. Although trying to do their best, professionals' uncertainty was disempowering, creating a disabling hesitancy and inertia in their practice. Most professionals sought and applied a knowledge-based cultural expertise approach to patients, though some identified the risk of engendering stereotypical expectations of patients. Professionals' uncertainty and disempowerment had the potential to perpetuate each other, to the detriment of patient care.
Conclusions
This study suggests potential mechanisms by which health professionals may inadvertently contribute to ethnic disparities in health care. It identifies critical opportunities to empower health professionals to respond more effectively. Interventions should help professionals acknowledge their uncertainty and its potential to create inertia in their practice. A shift away from a cultural expertise model toward a greater focus on each patient as an individual may help.
From a qualitative study, Joe Kai and colleagues have identified opportunities to empower health professionals to respond more effectively to challenges in their work with patients from diverse ethnic communities.
Editors' Summary
Background.
Communities are increasingly diverse in terms of ethnicity (belonging to a group of people defined by social characteristics such as cultural tradition or national origin) and race (belonging to a group identified by inherited physical characteristics). Although health professionals and governments are striving to ensure that everybody has the same access to health care, there is increasing evidence of ethnic inequalities in health-care outcomes. Some of these inequalities reflect intrinsic differences between groups of people—Ashkenazi Jews, for example, often carry an altered gene that increases their chance of developing aggressive breast cancer. Often, however, these differences reflect inequalities in the health care received by different ethnic groups. To improve this situation, “cultural competence” has been promoted over recent years. Cultural competence is the development of skills by individuals and organizations that allow them to work effectively with people from different cultures. Health professionals are now taught about ethnic differences in health beliefs and practices, religion, and communication styles to help them provide the best service to all their patients.
Why Was This Study Done?
Numerous guidelines aim to improve cultural competency but little is known about how health professionals experience and perceive their work with patients from diverse ethnic groups. Is their behavior influenced by ethnicity in ways that might contribute to health care disparities? For example, do doctors sometimes avoid medical examinations for fear of causing offence because of cultural differences? If more were known about how health professionals handle ethnic diversity (a term used here to include both ethnicity and race) it might be possible to reduce ethnic inequalities in health care. In this qualitative study, the researchers have explored how health professionals involved in cancer care are affected by working with ethnically diverse patients. A qualitative study is one that collects nonquantitative data such as how doctors “feel” about treating people of different ethnic backgrounds; a quantitative study might compare clinical outcomes in different ethnic groups.
What Did the Researchers Do and Find?
The researchers enrolled 106 doctors, nurses, and other health-related professionals from different health-service settings in the Midlands, an ethnically diverse region of the UK. They organized 18 focus groups in which the health professionals described their experiences of caring for people from ethnic minority backgrounds. The participants were encouraged to recall actual cases and to identify what they saw as problems and strengths in their interactions with these patients. The researchers found that the health professionals wrestled with many challenges when providing health care for patients from diverse ethnic backgrounds. These challenges included problems with language and with general communication (for example, deciding when it was acceptable to touch a patient to show empathy). Health professionals also worried they did not know enough about cultural differences. As a result, they said they often felt uncertain of their ability to avoid causing affront or appearing racist. This uncertainty, the researchers report, disempowered the health professionals, sometimes making them hesitate or fail to do what was best for their patient.
What Do These Findings Mean?
These findings reveal that health professionals often experience considerable uncertainty when caring for ethnically diverse patients, even after training in cultural competency. They also show that this uncertainty can lead to hesitancy and inertia, which might contribute to ethnic health care inequalities. Because the study participants were probably already interested in ethnic diversity and health care, interviews with other health professionals (and investigations of patient experiences) are needed to confirm these findings. Nevertheless, the researchers suggest several interventions that might reduce health care inequalities caused by ethnic diversity. For example, health professionals should be encouraged to recognize their uncertainty and should have access to more information and training about ethnic differences. In addition, there should be a shift in emphasis away from relying on knowledge-based cultural information towards taking an “ethnographic” approach. In other words, health professionals should be helped to feel able to ask their patients about what matters most to them as individuals about their illness and treatment.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040323.
Information on cultural competence and health care is available from the US National Center for Cultural Competence (in English and Spanish) and DiversityRx
PROCEED (Professionals Responding to Cancer in Ethnic Diversity) is a multimedia training tool for educators within the health and allied professions developed from the results of this study; a press release on PROCEED is available from the University of Nottingham
Transcultural Health Care Practice: An educational resource for nurses and health care practitioners is available on the web site of the UK Royal College of Nursing
doi:10.1371/journal.pmed.0040323
PMCID: PMC2071935  PMID: 18001148
2.  Facilitating the Recruitment of Minority Ethnic People into Research: Qualitative Case Study of South Asians and Asthma 
PLoS Medicine  2009;6(10):e1000148.
Aziz Sheikh and colleagues report on a qualitative study in the US and the UK to investigate ways to bolster recruitment of South Asians into asthma studies, including making inclusion of diverse populations mandatory.
Background
There is international interest in enhancing recruitment of minority ethnic people into research, particularly in disease areas with substantial ethnic inequalities. A recent systematic review and meta-analysis found that UK South Asians are at three times increased risk of hospitalisation for asthma when compared to white Europeans. US asthma trials are far more likely to report enrolling minority ethnic people into studies than those conducted in Europe. We investigated approaches to bolster recruitment of South Asians into UK asthma studies through qualitative research with US and UK researchers, and UK community leaders.
Methods and Findings
Interviews were conducted with 36 researchers (19 UK and 17 US) from diverse disciplinary backgrounds and ten community leaders from a range of ethnic, religious, and linguistic backgrounds, followed by self-completion questionnaires. Interviews were digitally recorded, translated where necessary, and transcribed. The Framework approach was used for analysis. Barriers to ethnic minority participation revolved around five key themes: (i) researchers' own attitudes, which ranged from empathy to antipathy to (in a minority of cases) misgivings about the scientific importance of the question under study; (ii) stereotypes and prejudices about the difficulties in engaging with minority ethnic populations; (iii) the logistical challenges posed by language, cultural differences, and research costs set against the need to demonstrate value for money; (iv) the unique contexts of the two countries; and (v) poorly developed understanding amongst some minority ethnic leaders of what research entails and aims to achieve. US researchers were considerably more positive than their UK counterparts about the importance and logistics of including ethnic minorities, which appeared to a large extent to reflect the longer-term impact of the National Institutes of Health's requirement to include minority ethnic people.
Conclusions
Most researchers and community leaders view the broadening of participation in research as important and are reasonably optimistic about the feasibility of recruiting South Asians into asthma studies provided that the barriers can be overcome. Suggested strategies for improving recruitment in the UK included a considerably improved support structure to provide academics with essential contextual information (e.g., languages of particular importance and contact with local gatekeepers), and the need to ensure that care is taken to engage with the minority ethnic communities in ways that are both culturally appropriate and sustainable; ensuring reciprocal benefits was seen as one key way of avoiding gatekeeper fatigue. Although voluntary measures to encourage researchers may have some impact, greater impact might be achieved if UK funding bodies followed the lead of the US National Institutes of Health requiring recruitment of ethnic minorities. Such a move is, however, likely in the short- to medium-term, to prove unpopular with many UK academics because of the added “hassle” factor in engaging with more diverse populations than many have hitherto been accustomed to.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In an ideal world, everyone would have the same access to health care and the same health outcomes (responses to health interventions). However, health inequalities—gaps in health care and in health between different parts of the population—exist in many countries. In particular, people belonging to ethnic minorities in the UK, the US, and elsewhere have poorer health outcomes for several conditions than people belonging to the ethnic majority (ethnicity is defined by social characteristics such as cultural tradition or national origin). For example, in the UK, people whose ancestors came from the Indian subcontinent (also known as South Asians and comprising in the main of people of Indian, Pakistani, and Bangladeshi origin) are three times as likely to be admitted to hospital for asthma as white Europeans. The reasons underpinning ethnic health inequalities are complex. Some inequalities may reflect intrinsic differences between groups of people—some ethnic minorities may inherit genes that alter their susceptibility to a specific disease. Other ethnic health inequalities may arise because of differences in socioeconomic status or because different cultural traditions affect the uptake of health care services.
Why Was This Study Done?
Minority ethnic groups are often under-represented in health research, which could limit the generalizability of research findings. That is, an asthma treatment that works well in a trial where all the participants are white Europeans might not be suitable for South Asians. Clinicians might nevertheless use the treatment in all their patients irrespective of their ethnicity and thus inadvertently increase ethnic health inequality. So, how can ethnic minorities be encouraged to enroll into research studies? In this qualitative study, the investigators try to answer this question by talking to US and UK asthma researchers and UK community leaders about how they feel about enrolling ethnic minorities into research studies. The investigators chose to compare the feelings of US and UK asthma researchers because minority ethnic people are more likely to enroll into US asthma studies than into UK studies, possibly because the US National Institute of Health's (NIH) Revitalization Act 1993 mandates that all NIH-funded clinical research must include people from ethnic minority groups; there is no similar mandatory policy in the UK.
What Did the Researchers Do and Find?
The investigators interviewed 16 UK and 17 US asthma researchers and three UK social researchers with experience of working with ethnic minorities. They also interviewed ten community leaders from diverse ethnic, religious and linguistic backgrounds. They then analyzed the interviews using the “Framework” approach, an analytical method in which qualitative data are classified and organized according to key themes and then interpreted. By comparing the data from the UK and US researchers, the investigators identified several barriers to ethnic minority participation in health research including: the attitudes of researchers towards the scientific importance of recruiting ethnic minority people into health research studies; prejudices about the difficulties of including ethnic minorities in health research; and the logistical challenges posed by language and cultural differences. In general, the US researchers were more positive than their UK counterparts about the importance and logistics of including ethnic minorities in health research. Finally, the investigators found that some community leaders had a poor understanding of what research entails and about its aims.
What Do These Findings Mean?
These findings reveal a large gap between US and UK researchers in terms of policy, attitudes, practices, and experiences in relation to including ethnic minorities in asthma research. However, they also suggest that most UK researchers and community leaders believe that it is both important and feasible to increase the participation of South Asians in asthma studies. Although some of these findings may have been affected by the study participants sometimes feeling obliged to give “politically correct” answers, these findings are likely to be generalizable to other diseases and to other parts of Europe. Given their findings, the researchers warn that a voluntary code of practice that encourages the recruitment of ethnic minority people into health research studies is unlikely to be successful. Instead, they suggest, the best way to increase the representation of ethnic minority people in health research in the UK might be to follow the US lead and introduce a policy that requires their inclusion in such research.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000148.
Families USA, a US nonprofit organization that campaigns for high-quality, affordable health care for all Americans, has information about many aspects of minority health in the US, including an interactive game about minority health issues
The US Agency for Healthcare Research and Quality has a section on minority health
The UK Department of Health provides information on health inequalities and a recent report on the experiences of patients in Black and minority ethnic groups
The UK Parliamentary Office of Science and Technology also has a short article on ethnicity and health
Information on the NIH Revitalization Act 1993 is available
NHS Evidences Ethnicity and Health has a variety of policy, clinical, and research resources on ethnicity and health
doi:10.1371/journal.pmed.1000148
PMCID: PMC2752116  PMID: 19823568
3.  The medical ethos and social responsibility in clinical medicine. 
The medical profession will face many challenges in the new millennium. As medicine looks forward to advances in molecular genetics and the prospect of unprecedented understanding of the causes and cures of human disease, clinicians, scientists and bioethicists may benefit from reflection upon the origins of the medical ethos and its relevance to postmodern medicine. Past distortions of the medical ethos, such as Nazism and the Tuskegee Syphilis Study, as well as more recent experience with the ethical challenges of employer-based market driven managed care, provide important lessons as medicine contemplates the future. Racial and ethnic disparities in health status and access to care serve as a reminders that the racial doctrines that fostered the horrors of the Holocaust and the Tuskegee Syphilis Study have not been completely removed from contemporary thinking. Inequalities in health status based on race and ethnicity, as well as socioeconomic status, attest to the inescapable reality of racism in America. When viewed against a background of historical distortions and disregard for the traditional tenets of the medical ethos, persistent racial and ethnic disparities and health and the prospect of genetic engineering raise the specter of discrimination because of genotype, a postmodern version of "racist medicine" or of a "new eugenics." There is a need to balance medicine's devotion to the wellbeing of the patient and the primacy of the patient-physician relationship against with the need to meet the health care needs of society. The challenge facing the medical profession in the new millennium is to establish an equilibrium between the responsibility to assure quality health care for the individual patient while affecting societal changes to achieve "health for all."
PMCID: PMC2593974  PMID: 11405593
4.  Advancing Genomic Research and Reducing Health Disparities: What Can Nurse Scholars Do? 
Purpose
Advances in genomic research are improving our understanding of human diseases and evoking promise of an era of genomic medicine. It is unclear whether genomic medicine may exacerbate or attenuate extant racial group health disparities. We delineate how nurse scholars could engage in the configuration of an equitable genomic medicine paradigm.
Organizing Construct
We identify as legitimate subjects for nursing scholarship the scientific relevance, ethical, and public policy implications for employing racial categories in genomic research in the context of reducing extant health disparities.
Findings
Since genomic research is largely population specific, current classification of genomic data will center on racial and ethnic groups. Nurse scholars should be involved in clarifying how putative racial group differences should be elucidated in light of the current orthodoxy that genomic solutions may alleviate racial health disparities.
Conclusions
Nurse scholars are capable of employing their expertise in concept analysis to elucidate how race is used as a variable in scientific research, and to use knowledge brokering to delineate how race variables that imply human ancestry could be utilized in genomic research pragmatically in the context of health disparities.
Clinical Relevance
In an era of genomic medicine, nurse scholars should recognize and understand the challenges and complexities of genomics and race and their relevance to health care and health disparities.
doi:10.1111/j.1547-5069.2012.01482.x
PMCID: PMC3674174  PMID: 23452096
Genomic medicine; concept analysis; knowledge brokering; racial categories; health disparities
5.  Reinterpreting Ethnic Patterns among White and African American Men Who Inject Heroin: A Social Science of Medicine Approach 
PLoS Medicine  2006;3(10):e452.
Background
Street-based heroin injectors represent an especially vulnerable population group subject to negative health outcomes and social stigma. Effective clinical treatment and public health intervention for this population requires an understanding of their cultural environment and experiences. Social science theory and methods offer tools to understand the reasons for economic and ethnic disparities that cause individual suffering and stress at the institutional level.
Methods and Findings
We used a cross-methodological approach that incorporated quantitative, clinical, and ethnographic data collected by two contemporaneous long-term San Francisco studies, one epidemiological and one ethnographic, to explore the impact of ethnicity on street-based heroin-injecting men 45 years of age or older who were self-identified as either African American or white. We triangulated our ethnographic findings by statistically examining 14 relevant epidemiological variables stratified by median age and ethnicity. We observed significant differences in social practices between self-identified African Americans and whites in our ethnographic social network sample with respect to patterns of (1) drug consumption; (2) income generation; (3) social and institutional relationships; and (4) personal health and hygiene. African Americans and whites tended to experience different structural relationships to their shared condition of addiction and poverty. Specifically, this generation of San Francisco injectors grew up as the children of poor rural to urban immigrants in an era (the late 1960s through 1970s) when industrial jobs disappeared and heroin became fashionable. This was also when violent segregated inner city youth gangs proliferated and the federal government initiated its “War on Drugs.” African Americans had earlier and more negative contact with law enforcement but maintained long-term ties with their extended families. Most of the whites were expelled from their families when they began engaging in drug-related crime. These historical-structural conditions generated distinct presentations of self. Whites styled themselves as outcasts, defeated by addiction. They professed to be injecting heroin to stave off “dopesickness” rather than to seek pleasure. African Americans, in contrast, cast their physical addiction as an oppositional pursuit of autonomy and pleasure. They considered themselves to be professional outlaws and rejected any appearance of abjection. Many, but not all, of these ethnographic findings were corroborated by our epidemiological data, highlighting the variability of behaviors within ethnic categories.
Conclusions
Bringing quantitative and qualitative methodologies and perspectives into a collaborative dialog among cross-disciplinary researchers highlights the fact that clinical practice must go beyond simple racial or cultural categories. A clinical social science approach provides insights into how sociocultural processes are mediated by historically rooted and institutionally enforced power relations. Recognizing the logical underpinnings of ethnically specific behavioral patterns of street-based injectors is the foundation for cultural competence and for successful clinical relationships. It reduces the risk of suboptimal medical care for an exceptionally vulnerable and challenging patient population. Social science approaches can also help explain larger-scale patterns of health disparities; inform new approaches to structural and institutional-level public health initiatives; and enable clinicians to take more leadership in changing public policies that have negative health consequences.
Bourgois and colleagues found that the African American and white men in their study had a different pattern of drug use and risk behaviors, adopted different strategies for survival, and had different personal histories.
Editors' Summary
Background.
There are stark differences in the health of different ethnic groups in America. For example, the life expectancy for white men is 75.4 years, but it is only 69.2 years for African-American men. The reasons behind these disparities are unclear, though there are several possible explanations. Perhaps, for example, different ethnic groups are treated differently by health professionals (with some groups receiving poorer quality health care). Or maybe the health disparities are due to differences across ethnic groups in income level (we know that richer people are healthier). These disparities are likely to persist unless we gain a better understanding of how they arise.
Why Was This Study Done?
The researchers wanted to study the health of a very vulnerable community of people: heroin users living on the streets in the San Francisco Bay Area. The health status of this community is extremely poor, and its members are highly stigmatized—including by health professionals themselves. The researchers wanted to know whether African American men and white men who live on the streets have a different pattern of drug use, whether they adopt varying strategies for survival, and whether they have different personal histories. Knowledge of such differences would help the health community to provide more tailored and culturally appropriate interventions. Physicians, nurses, and social workers often treat street-based drug users, especially in emergency rooms and free clinics. These health professionals regularly report that their interactions with street-based drug users are frustrating and confrontational. The researchers hoped that their study would help these professionals to have a better understanding of the cultural backgrounds and motivations of their drug-using patients.
What Did the Researchers Do and Find?
Over the course of six years, the researchers directly observed about 70 men living on the streets who injected heroin as they went about their usual lives (this type of research is called “participant observation”). The researchers specifically looked to see whether there were differences between the white and African American men. All the men gave their consent to be studied in this way and to be photographed. The researchers also studied a database of interviews with almost 7,000 injection drug users conducted over five years, drawing out the data on differences between white and African men. The researchers found that the white men were more likely to supplement their heroin use with inexpensive fortified wine, while African American men were more likely to supplement heroin with crack. Most of the white men were expelled from their families when they began engaging in drug-related crime, and these men tended to consider themselves as destitute outcasts. African American men had earlier and more negative contact with law enforcement but maintained long-term ties with their extended families, and these men tended to consider themselves as professional outlaws. The white men persevered less in attempting to find a vein in which to inject heroin, and so were more likely to inject the drug directly under the skin—this meant that they were more likely to suffer from skin abscesses. The white men generated most of their income from panhandling (begging for money), while the African American men generated most of their income through petty crime and/or through offering services such as washing car windows at gas stations.
What Do These Findings Mean?
Among street-based heroin users, there are important differences between white men and African American men in the type of drugs used, the method of drug use, their social backgrounds, the way in which they identify themselves, and the health risks that they take. By understanding these differences, health professionals should be better placed to provide tailored and appropriate care when these men present to clinics and emergency rooms. As the researchers say, “understanding of different ethnic populations of drug injectors may reduce difficult clinical interactions and resultant physician frustration while improving patient access and adherence to care.” One limitation of this study is that the researchers studied one specific community in one particular area of the US—so we should not assume that their findings would apply to street-based heroin users elsewhere.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0030452.
The US Centers for Disease Control (CDC) has a web page on HIV prevention among injection drug users
The World Health Organization has collected documents on reducing the risk of HIV in injection drug users and on harm reduction approaches
The International Harm Reduction Association has information relevant to a global audience on reducing drug-related harm among individuals and communities
US-focused information on harm reduction is available via the websites of the Harm Reduction Coalition and the Chicago Recovery Alliance
Canada-focused information can be found at the Street Works Web site
The Harm Reduction Journal publishes open-access articles
The CDC has a web page on eliminating racial and ethnic health disparities
The Drug Policy Alliance has a web page on drug policy in the United States
doi:10.1371/journal.pmed.0030452
PMCID: PMC1621100  PMID: 17076569
6.  "A NEW CONCEPTUALIZATION OF ETHNICITY FOR SOCIAL EPIDEMIOLOGIC AND HEALTH EQUITY RESEARCH" 
Social science & medicine (1982)  2010;71(2):251-258.
Although social stratification persists in the US, differentially influencing the well-being of ethnically defined groups, ethnicity concepts and their implications for health disparities remain under-examined. Ethnicity is a complex social construct that influences personal identity and group social relations. Ethnic identity, ethnic classification systems, the groupings that compose each system and the implications of assignment to one or another ethnic category are place-, time- and context-specific. In the US, racial stratification uniquely shapes expressions of and understandings about ethnicity. Ethnicity is typically invoked via the term, ‘race/ethnicity’; however, it is unclear whether this heralds a shift away from racialization or merely extends flawed racial taxonomies to populations whose cultural and phenotypic diversity challenge traditional racial classification. We propose that ethnicity be conceptualized as a two-dimensional, context-specific, social construct with an attributional dimension that describes group characteristics (e.g., culture, nativity) and a relational dimension that indexes a group’s location within a social hierarchy (e.g., minority vs. majority status). This new conceptualization extends prior definitions in ways that facilitate research on ethnicization, social stratification and health inequities. While federal ethnic and racial categories are useful for administrative purposes such as monitoring the inclusion of minorities in research, and traditional ethnicity concepts (e.g., culture) are useful for developing culturally appropriate interventions, our relational dimension of ethnicity is useful for studying the relationships between societal factors and health inequities. We offer a new conceptualization of ethnicity and outline next steps for employing socially meaningful measures of ethnicity in empirical research. Ethnicity is both increasingly complex and increasingly central to social life; therefore, improving its conceptualization and measurement is crucial for advancing research on ethnic health inequities.
doi:10.1016/j.socscimed.2010.04.008
PMCID: PMC2908006  PMID: 20488602
USA; ethnic groups; ethnicity; health disparities; race relations; social epidemiology; social stratification; concepts
7.  Medical ethos and social responsibility in clinical medicine 
The medical profession will face many challenges in the new millenium. As medicine looks forward to advances in molecular genetics and the prospect of unprecedented understanding of the causes and cures of human disease, clinicians, scientists, and bioethicists may benefit from reflection on the origins of the medical ethos and its relevance to postmodern medicine. Past distortions of the medical ethos, such as Nazism and the Tuskegee Syphilis Study, as well as more recent experience with the ethical challenges of employer-based, market-driven managed care, provide important lessons as medicine contemplates the future. Racial and ethnic disparities in health status and access to care serve as reminders that the racial doctrines that fostered the horrors of the Holocaust and the Tuskegee Syphilis Study have not been removed completely from contemporary thinking. Inequalities in health status based on race and ethnicity, as well as socioeconomic status, attest to the inescapable reality of racism in America. When viewed against a background of historical distortions and disregard for the traditional tenets of the medical ethos, persistent racial and ethnic disparities in health and the prospect of genetic engineering raise the specter of discrimination because of genotype, a postmodern version of “racist medicine” or of a “new eugenics”. There is a need to balance medicine’s devotion to the well-being of the patient and the primacy of the patient-physician relationship against the need to meet the health care needs of society. The challenge facing the medical profession in the new millennium is to establish an equilibrium between the responsibility to ensure quality health care for the individual patient while effecting societal changes to achieve “health for all”.
doi:10.1093/jurban/78.1.29
PMCID: PMC3456207  PMID: 11368201
Access to Care; Medical Ethos; Racism; Social Responsibility; Tuskegee
8.  Racial Healthcare Disparities: A Social Psychological Analysis 
Around the world, members of racial/ethnic minority groups typically experience poorer health than members of racial/ethnic majority groups. The core premise of this article is that thoughts, feelings, and behaviors related to race and ethnicity play a critical role in healthcare disparities. Social psychological theories of the origins and consequences of these thoughts, feelings, and behaviors offer critical insights into the processes responsible for these disparities and suggest interventions to address them. We present a multilevel model that explains how societal, intrapersonal, and interpersonal factors can influence ethnic/racial health disparities. We focus our literature review, including our own research, and conceptual analysis at the intrapersonal (the race-related thoughts and feelings of minority patients and non-minority physicians) and interpersonal levels (intergroup processes that affect medical interactions between minority patients and non-minority physicians). At both levels of analysis, we use theories of social categorization, social identity, contemporary forms of racial bias, stereotype activation, stigma, and other social psychological processes to identify and understand potential causes and processes of health and healthcare disparities. In the final section, we identify theory-based interventions that might reduce ethnic/racial disparities in health and healthcare.
doi:10.1080/10463283.2013.840973
PMCID: PMC4151477  PMID: 25197206
ethnicity/race; health and healthcare; disparities; explicit and implicit bias; intergroup processes
9.  The Fall and Rise of US Inequities in Premature Mortality: 1960–2002 
PLoS Medicine  2008;5(2):e46.
Background
Debates exist as to whether, as overall population health improves, the absolute and relative magnitude of income- and race/ethnicity-related health disparities necessarily increase—or derease. We accordingly decided to test the hypothesis that health inequities widen—or shrink—in a context of declining mortality rates, by examining annual US mortality data over a 42 year period.
Methods and Findings
Using US county mortality data from 1960–2002 and county median family income data from the 1960–2000 decennial censuses, we analyzed the rates of premature mortality (deaths among persons under age 65) and infant death (deaths among persons under age 1) by quintiles of county median family income weighted by county population size. Between 1960 and 2002, as US premature mortality and infant death rates declined in all county income quintiles, socioeconomic and racial/ethnic inequities in premature mortality and infant death (both relative and absolute) shrank between 1966 and 1980, especially for US populations of color; thereafter, the relative health inequities widened and the absolute differences barely changed in magnitude. Had all persons experienced the same yearly age-specific premature mortality rates as the white population living in the highest income quintile, between 1960 and 2002, 14% of the white premature deaths and 30% of the premature deaths among populations of color would not have occurred.
Conclusions
The observed trends refute arguments that health inequities inevitably widen—or shrink—as population health improves. Instead, the magnitude of health inequalities can fall or rise; it is our job to understand why.
Nancy Krieger and colleagues found evidence of decreasing, and then increasing or stagnating, socioeconomic and racial inequities in US premature mortality and infant death from 1960 to 2002.
Editors' Summary
Background
One of the biggest aims of public health advocates and governments is to improve the health of the population. Improving health increases people's quality of life and helps the population be more economically productive. But within populations are often persistent differences (usually called “disparities” or “inequities”) in the health of different subgroups—between women and men, different income groups, and people of different races/ethnicities, for example. Researchers study these differences so that policy makers and the broader public can be informed about what to do to intervene. For example, if we know that the health of certain subgroups of the population—such as the poor—is staying the same or even worsening as the overall health of the population is improving, policy makers could design programs and devote resources to specifically target the poor.
To study health disparities, researchers use both relative and absolute measures. Relative inequities refer to ratios, while absolute inequities refer to differences. For example, if one group's average income level increases from $1,000 to $10,000 and another group's from $2,000 to $20,000, the relative inequality between the groups stays the same (i.e., the ratio of incomes between the two groups is still 2) but the absolute difference between the two groups has increased from $1,000 to $10,000.
Examining the US population, Nancy Krieger and colleagues looked at trends over time in both relative and absolute differences in mortality between people in different income groups and between whites and people of color.
Why Was This Study Done?
There has been a lot of debate about whether disparities have been widening or narrowing as overall population health improves. Some research has found that both total health and health disparities are getting better with time. Other research has shown that overall health gains mask worsening disparities—such that the rich get healthier while the poor get sicker.
Having access to more data over a longer time frame meant that Krieger and colleagues could provide a more complete picture of this sometimes contradictory story. It also meant they could test their hypothesis about whether, as population health improves, health inequities necessarily widen or shrink within the time period between the 1960s through the 1990s during which certain events and policies likely would have had an impact on the mortality trends in that country.
What Did the Researchers Do and Find?
In order to investigate health inequities, the authors chose to look at two common measures of population health: rates of premature mortality (dying before the age of 65 years) and rates of infant mortality (death before the age of 1).
To determine mortality rates, the authors used death statistics data from different counties, which are routinely collected by state and national governments. To be able to rank mortality rates for different income groups, they used data on the median family incomes of people living within those counties (meaning half the families had income above, and half had incomes below, the median value). They calculated mortality rates for the total population and for whites versus people of color. They used data from 1960 through 2002. They compared rates for 1966–1980 with two other time periods: 1960–1965 and 1981–2002. They also examined trends in the annual mortality rates and in the annual relative and absolute disparites in these rates by county income level.
Over the whole period 1960–2002, the authors found that premature mortality (death before the age of 65) and infant mortality (death before the age of 1) decreased for all income groups. But they also found that disparities between income groups and between whites and people of color were not the same over this time period. In fact, the economic disparities narrowed then widened. First, they shrank between 1966 and 1980, especially for Americans of color. After 1980, however, the relative health inequities widened and the absolute differences did not change. The authors conclude that if all people in the US population experienced the same health gains as the most advantaged did during these 42 years (i.e., as the whites in the highest income groups), 14% of the premature deaths among whites and 30% of the premature deaths among people of color would have been prevented.
What Do These Findings Mean?
The findings provide an overview of the trends in inequities in premature and infant mortality over a long period of time. Different explanations for these trends can now be tested. The authors discuss several potential reasons for these trends, including generally rising incomes across America and changes related to specific diseases, such as the advent of HIV/AIDS, changes in smoking habits, and better management of cancer and cardiovascular disease. But they find that these do not explain the fall then rise of inequities. Instead, the authors suggest that explanations lie in the social programs of the 1960s and the subsequent roll-back of some of these programmes in the 1980s. The US “War on Poverty,” civil rights legislation, and the establishment of Medicare occurred in the mid 1960s, which were intended to reduce socioeconomic and racial/ethnic inequalities and improve access to health care. In the 1980s there was a general cutting back of welfare state provisions in America, which included cuts to public health and antipoverty programs, tax relief for the wealthy, and worsening inequity in the access to and quality of health care. Together, these wider events could explain the fall then rise trends in mortality disparities.
The authors say their findings are important to inform and help monitor the progress of various policies and programmes, including those such as the Healthy People 2010 initiative in America, which aims to increase the quality and years of healthy life and decrease health disparities by the end of this decade.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed. 0050046.
Healthy People 2010 was created by the US Department of Health and Human Services along with scientists inside and outside of government and includes a comprehensive set of disease prevention and health promotion objectives for the US to achieve by 2010, with two overarching goals: to increase quality and years of healthy life and to eliminate health disparities
Johan Mackenbach and colleagues provide an overview of mortality inequalities in six Western European countries—Finland, Sweden, Norway, Denmark, England/Wales, and Italy—and conclude that eliminating mortality inequalities requires that more cardiovascular deaths among lower socioeconomic groups be prevented, as well as more attention be paid to rising death rates of lung cancer, breast cancer, respiratory disease, gastrointestinal disease, and injuries among women and men in the lower income groups.
The WHO Health for All program promotes health equity
A primer on absolute versus relative differences is provided by the American College of Physicians
doi:10.1371/journal.pmed.0050046
PMCID: PMC2253609  PMID: 18303941
10.  The Reversal of Fortunes: Trends in County Mortality and Cross-County Mortality Disparities in the United States  
PLoS Medicine  2008;5(4):e66.
Background
Counties are the smallest unit for which mortality data are routinely available, allowing consistent and comparable long-term analysis of trends in health disparities. Average life expectancy has steadily increased in the United States but there is limited information on long-term mortality trends in the US counties This study aimed to investigate trends in county mortality and cross-county mortality disparities, including the contributions of specific diseases to county level mortality trends.
Methods and Findings
We used mortality statistics (from the National Center for Health Statistics [NCHS]) and population (from the US Census) to estimate sex-specific life expectancy for US counties for every year between 1961 and 1999. Data for analyses in subsequent years were not provided to us by the NCHS. We calculated different metrics of cross-county mortality disparity, and also grouped counties on the basis of whether their mortality changed favorably or unfavorably relative to the national average. We estimated the probability of death from specific diseases for counties with above- or below-average mortality performance. We simulated the effect of cross-county migration on each county's life expectancy using a time-based simulation model. Between 1961 and 1999, the standard deviation (SD) of life expectancy across US counties was at its lowest in 1983, at 1.9 and 1.4 y for men and women, respectively. Cross-county life expectancy SD increased to 2.3 and 1.7 y in 1999. Between 1961 and 1983 no counties had a statistically significant increase in mortality; the major cause of mortality decline for both sexes was reduction in cardiovascular mortality. From 1983 to 1999, life expectancy declined significantly in 11 counties for men (by 1.3 y) and in 180 counties for women (by 1.3 y); another 48 (men) and 783 (women) counties had nonsignificant life expectancy decline. Life expectancy decline in both sexes was caused by increased mortality from lung cancer, chronic obstructive pulmonary disease (COPD), diabetes, and a range of other noncommunicable diseases, which were no longer compensated for by the decline in cardiovascular mortality. Higher HIV/AIDS and homicide deaths also contributed substantially to life expectancy decline for men, but not for women. Alternative specifications of the effects of migration showed that the rise in cross-county life expectancy SD was unlikely to be caused by migration.
Conclusions
There was a steady increase in mortality inequality across the US counties between 1983 and 1999, resulting from stagnation or increase in mortality among the worst-off segment of the population. Female mortality increased in a large number of counties, primarily because of chronic diseases related to smoking, overweight and obesity, and high blood pressure.
Majid Ezzati and colleagues analyze US county-level mortality data for 1961 to 1999, and find a steady increase in mortality inequality across counties between 1983 and 1999.
Editors' Summary
Background.
It has long been recognized that the number of years that distinct groups of people in the United States would be expected to live based on their current mortality patterns (“life expectancy”) varies enormously. For example, white Americans tend to live longer than black Americans, the poor tend to have shorter life expectancies than the wealthy, and women tend to outlive men. Where one lives might also be a factor that determines his or her life expectancy, because of social conditions and health programs in different parts of the country.
Why Was the Study Done?
While life expectancies have generally been rising across the United States over time, there is little information, especially over the long term, on the differences in life expectancies across different counties. The researchers therefore set out to examine whether there were different life expectancies across different US counties over the last four decades. The researchers chose to look at counties—the smallest geographic units for which data on death rates are collected in the US—because it allowed them to make comparisons between small subgroups of people that share the same administrative structure.
What Did the Researchers Do and Find?
The researchers looked at differences in death rates between all counties in US states plus the District of Columbia over four decades, from 1961 to 1999. They obtained the data on number of deaths from the National Center for Health Statistics, and they obtained data on the number of people living in each county from the US Census. The NCHS did not provide death data after 2001. They broke the death rates down by sex and by disease to assess trends over time for women and men, and for different causes of death.
Over these four decades, the researchers found that the overall US life expectancy increased from 67 to 74 years of age for men and from 74 to 80 years for women. Between 1961 and 1983 the death rate fell in both men and women, largely due to reductions in deaths from cardiovascular disease (heart disease and stroke). During this same period, 1961–1983, the differences in death rates among/across different counties fell. However, beginning in the early 1980s the differences in death rates among/across different counties began to increase. The worst-off counties no longer experienced a fall in death rates, and in a substantial number of counties, mortality actually increased, especially for women, a shift that the researchers call “the reversal of fortunes.” This stagnation in the worst-off counties was primarily caused by a slowdown or halt in the reduction of deaths from cardiovascular disease coupled with a moderate rise in a number of other diseases, such as lung cancer, chronic lung disease, and diabetes, in both men and women, and a rise in HIV/AIDS and homicide in men. The researchers' key finding, therefore, was that the differences in life expectancy across different counties initially narrowed and then widened.
What Do these Findings Mean?
The findings suggest that beginning in the early 1980s and continuing through 1999 those who were already disadvantaged did not benefit from the gains in life expectancy experienced by the advantaged, and some became even worse off. The study emphasizes how important it is to monitor health inequalities between different groups, in order to ensure that everyone—and not just the well-off—can experience gains in life expectancy. Although the “reversal of fortune” that the researchers found applied to only a minority of the population, the authors argue that their study results are troubling because an oft-stated aim of the US health system is the improvement of the health of “all people, and especially those at greater risk of health disparities” (see, for example http://www.cdc.gov/osi/goals/SIHPGPostcard.pdf).
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050066.
A study by Nancy Krieger and colleagues, published in PLoS Medicine in February 2008, documented a similar “fall and rise” in health inequities. Krieger and colleagues reported that the difference in health between rich and poor and between different racial/ethnic groups, as measured by rates of dying young and of infant deaths, shrank in the US from 1966 to 1980 then widened from 1980 to 2002
Murray and colleagues, in a 2006 PLoS Medicine article, calculated US mortality rates according to “race-county” units and divided into the “eight Americas,” and found disparities in life expectancy across them
The US Centers for Disease Control has an Office of Minority Health and Health Disparities. The office “aims to accelerate CDC's health impact in the US population and to eliminate health disparities for vulnerable populations as defined by race/ethnicity, socioeconomic status, geography, gender, age, disability status, risk status related to sex and gender, and among other populations identified to be at-risk for health disparities”
Wikipedia has a chapter on health disparities (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
In 2001 the US Agency for Healthcare Research and Quality sponsored a workshop on “strategies to reduce health disparities”
doi:10.1371/journal.pmed.0050066
PMCID: PMC2323303  PMID: 18433290
11.  Exclusion and Inclusion of Nonwhite Ethnic Minority Groups in 72 North American and European Cardiovascular Cohort Studies 
PLoS Medicine  2006;3(3):e44.
Background
Cohort studies are recommended for understanding ethnic disparities in cardiovascular disease. Our objective was to review the process for identifying, including, and excluding ethnic minority populations in published cardiovascular cohort studies in Europe and North America.
Methods and Findings
We found the literature using Medline (1966–2005), Embase (1980–2001), Cinahl, Web of Science, and citations from references; consultations with colleagues; Internet searches; and RB's personal files. A total of 72 studies were included, 39 starting after 1975. Decision-making on inclusion and exclusion of racial/ethnic groups, the conceptual basis of race/ethnicity, and methods of classification of racial/ethnic groups were rarely explicit. Few publications provided details on the racial/ethnic composition of the study setting or sample, and 39 gave no description. Several studies were located in small towns or in occupational settings, where ethnic minority populations are underrepresented. Studies on general populations usually had too few participants for analysis by race/ethnicity. Eight studies were explicitly on Caucasians/whites, and two excluded ethnic minority groups from the whole or part of the study on the basis of language or birthplace criteria. Ten studies were designed to compare white and nonwhite populations, while five studies focused on one nonwhite racial/ethnic group; all 15 of these were performed in the US.
Conclusions
There is a shortage of information from cardiovascular cohort studies on racial/ethnic minority populations, although this has recently changed in the US. There is, particularly in Europe, an inequity resulting from a lack of research data in nonwhite populations. Urgent action is now required in Europe to address this disparity.
A systematic review reveals a shortage of information on racial and ethnic minority populations. This compromises the relevance of the evidence underlying health policies and guidelines for nonwhite patients.
doi:10.1371/journal.pmed.0030044
PMCID: PMC1324792  PMID: 16379500
12.  Transition to the new race/ethnicity data collection standards in the Department of Veterans Affairs 
Background
Patient race in the Department of Veterans Affairs (VA) information system was previously recorded based on an administrative or clinical employee's observation. Since 2003, the VA started to collect self-reported race in compliance with a new federal guideline. We investigated the implications of this transition for using race/ethnicity data in multi-year trends in the VA and in other healthcare data systems that make the transition.
Methods
All unique users of VA healthcare services with self-reported race/ethnicity data in 2004 were compared with their prior observer-recorded race/ethnicity data from 1997 – 2002 (N = 988,277).
Results
In 2004, only about 39% of all VA healthcare users reported race/ethnicity values other than "unknown" or "declined." Females reported race/ethnicity at a lower rate than males (27% vs. 40%; p < 0.001). Over 95% of observer-recorded data agreed with self-reported data. Compared with the patient self-reported data, the observer-recorded White and African American races were accurate for 98% (kappa = 0.89) and 94% (kappa = 0.93) individuals, respectively. Accuracy of observer-recorded races was much worse for other minority groups with kappa coefficients ranging between 0.38 for American Indian or Alaskan Natives and 0.79 for Hispanic Whites. When observer-recorded race/ethnicity values were reclassified into non-African American groups, they agreed with the self-reported data for 98% of all individuals (kappa = 0.93).
Conclusion
For overall VA healthcare users, the agreement between observer-recorded and self-reported race/ethnicity was excellent and observer-recorded and self-reported data can be used together for multi-year trends without creating serious bias. However, this study also showed that observation was not a reliable method of race/ethnicity data collection for non-African American minorities and racial disparity might be underestimated if observer-recorded data are used due to systematic patterns of inaccurate race/ethnicity assignments.
doi:10.1186/1478-7954-4-7
PMCID: PMC1539022  PMID: 16824220
13.  Racial and Ethnic Health Disparities in Reproductive Medicine: An Evidence-Based Overview 
Seminars in reproductive medicine  2013;31(5):317-324.
Racial and ethnic health disparities in reproductive medicine exist across the life span and are costly and burdensome to our healthcare system. Reduction and ultimate elimination of health disparities is a priority of the National Institutes of Health who requires reporting of race and ethnicity for all clinical research it supports. Given the increasing rates of admixture in our population, the definition and subsequent genetic significance of self-reported race and ethnicity used in health disparity research is not straightforward. Some groups have advocated using self-reported ancestry or carefully selected single-nucleotide polymorphisms, also known as ancestry informative markers, to sort individuals into populations. Despite the limitations in our current definitions of race and ethnicity in research, there are several clear examples of health inequalities in reproductive medicine extending from puberty and infertility to obstetric outcomes. We acknowledge that socioeconomic status, education, insurance status, and overall access to care likely contribute to the differences, but these factors do not fully explain the disparities. Epigenetics may provide the biologic link between these environmental factors and the transgenerational disparities that are observed. We propose an integrated view of health disparities across the life span and generations focusing on the metabolic aspects of fetal programming and the effects of environmental exposures. Interventions aimed at improving nutrition and minimizing adverse environmental exposures may act synergistically to reverse the effects of these epigenetic marks and improve the outcome of our future generations.
doi:10.1055/s-0033-1348889
PMCID: PMC4152894  PMID: 23934691
racial disparities; ancestry informative markers; admixture; infertility; transgenerational; epigenetic; developmental origins of adult disease
14.  Implicit Bias among Physicians and its Prediction of Thrombolysis Decisions for Black and White Patients 
Journal of General Internal Medicine  2007;22(9):1231-1238.
Context
Studies documenting racial/ethnic disparities in health care frequently implicate physicians’ unconscious biases. No study to date has measured physicians’ unconscious racial bias to test whether this predicts physicians’ clinical decisions.
Objective
To test whether physicians show implicit race bias and whether the magnitude of such bias predicts thrombolysis recommendations for black and white patients with acute coronary syndromes.
Design, Setting, and Participants
An internet-based tool comprising a clinical vignette of a patient presenting to the emergency department with an acute coronary syndrome, followed by a questionnaire and three Implicit Association Tests (IATs). Study invitations were e-mailed to all internal medicine and emergency medicine residents at four academic medical centers in Atlanta and Boston; 287 completed the study, met inclusion criteria, and were randomized to either a black or white vignette patient.
Main Outcome Measures
IAT scores (normal continuous variable) measuring physicians’ implicit race preference and perceptions of cooperativeness. Physicians’ attribution of symptoms to coronary artery disease for vignette patients with randomly assigned race, and their decisions about thrombolysis. Assessment of physicians’ explicit racial biases by questionnaire.
Results
Physicians reported no explicit preference for white versus black patients or differences in perceived cooperativeness. In contrast, IATs revealed implicit preference favoring white Americans (mean IAT score = 0.36, P < .001, one-sample t test) and implicit stereotypes of black Americans as less cooperative with medical procedures (mean IAT score 0.22, P < .001), and less cooperative generally (mean IAT score 0.30, P < .001). As physicians’ prowhite implicit bias increased, so did their likelihood of treating white patients and not treating black patients with thrombolysis (P = .009).
Conclusions
This study represents the first evidence of unconscious (implicit) race bias among physicians, its dissociation from conscious (explicit) bias, and its predictive validity. Results suggest that physicians’ unconscious biases may contribute to racial/ethnic disparities in use of medical procedures such as thrombolysis for myocardial infarction.
doi:10.1007/s11606-007-0258-5
PMCID: PMC2219763  PMID: 17594129
unconscious bias; thrombolysis; race; clinical decisions; disparities
15.  Early Emergence of Ethnic Differences in Type 2 Diabetes Precursors in the UK: The Child Heart and Health Study in England (CHASE Study) 
PLoS Medicine  2010;7(4):e1000263.
Peter Whincup and colleagues carry out a cross-sectional study examining ethnic differences in precursors of of type 2 diabetes among children aged 9–10 living in three UK cities.
Background
Adults of South Asian origin living in the United Kingdom have high risks of type 2 diabetes and central obesity; raised circulating insulin, triglyceride, and C-reactive protein concentrations; and low HDL-cholesterol when compared with white Europeans. Adults of African-Caribbean origin living in the UK have smaller increases in type 2 diabetes risk, raised circulating insulin and HDL-cholesterol, and low triglyceride and C-reactive protein concentrations. We examined whether corresponding ethnic differences were apparent in childhood.
Methods and Findings
We performed a cross-sectional survey of 4,796 children aged 9–10 y in three UK cities who had anthropometric measurements (68% response) and provided blood samples (58% response); ethnicity was based on parental definition. In age-adjusted comparisons with white Europeans (n = 1,153), South Asian children (n = 1,306) had higher glycated haemoglobin (HbA1c) (% difference: 2.1, 95% CI 1.6 to 2.7), fasting insulin (% difference 30.0, 95% CI 23.4 to 36.9), triglyceride (% difference 12.9, 95% CI 9.4 to 16.5), and C-reactive protein (% difference 43.3, 95% CI 28.6 to 59.7), and lower HDL-cholesterol (% difference −2.9, 95% CI −4.5 to −1.3). Higher adiposity levels among South Asians (based on skinfolds and bioimpedance) did not account for these patterns. Black African-Caribbean children (n = 1,215) had higher levels of HbA1c, insulin, and C-reactive protein than white Europeans, though the ethnic differences were not as marked as in South Asians. Black African-Caribbean children had higher HDL-cholesterol and lower triglyceride levels than white Europeans; adiposity markers were not increased.
Conclusions
Ethnic differences in type 2 diabetes precursors, mostly following adult patterns, are apparent in UK children in the first decade. Some key determinants operate before adult life and may provide scope for early prevention.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Worldwide, nearly 250 million people have diabetes, and the number of people affected by this chronic disease is increasing rapidly. Diabetes is characterized by dangerous amounts of sugar (glucose) in the blood. Blood sugar levels are normally controlled by insulin, a hormone that the pancreas releases when blood sugar levels rise after eating (digestion of food produces glucose). In people with type 2 diabetes (the most common type of diabetes), blood sugar control fails because the fat and muscle cells that usually respond to insulin by removing sugar from the blood become less responsive to insulin (insulin resistant). Type 2 diabetes can be controlled with diet and exercise, and with drugs that help the pancreas make more insulin or that make cells more sensitive to insulin. Long-term complications of diabetes include kidney failure, blindness, nerve damage, and an increased risk of developing cardiovascular problems, including heart disease and stroke.
Why Was This Study Done?
South Asians and African-Caribbeans living in Western countries tend to have higher rates of type 2 diabetes than host populations. South Asian adults living in the UK, for example, have a 3-fold higher risk of developing type 2 diabetes than white Europeans. They also have higher fasting blood levels of glucose, insulin and triglycerides (a type of fat), higher blood levels of “glycated hemoglobin” (HbA1c; an indicator of average of blood-sugar levels over time), more body fat (increased adiposity), raised levels of a molecule called C-reactive protein, and lower levels of HDL-cholesterol (another type of fat) than white Europeans. Most of these “diabetes precursors” (risk factors) are also seen in black African-Caribbean adults living in the UK except that individuals in this ethnic group often have raised HDL-cholesterol levels and low triglyceride levels. Ethnic differences in type 2 diabetes precursors are also present in adolescents, but the extent to which they are present in childhood remains unclear. Knowing this information could have implications for diabetes prevention. In this population-based study, therefore, the researchers investigate patterns of diabetes precursors in 9- to 10-year-old UK children of white European, South Asian, and black African-Caribbean origin.
What Did the Researchers Do and Find?
The researchers enrolled nearly 5,000 children (including 1,153 white European, 1,306 South Asian and 1,215 black African-Caribbean children) from primary schools with high prevalences of ethnic minority pupils in London, Birmingham, and Leicester in the Child Heart and Health study in England (CHASE). They measured and weighed more than two-thirds of the enrolled children and determined their adiposity. They also took blood samples for measurement of diabetes precursors from nearly two-thirds of the children. The recorded ethnicity of each child was based on parental definition. The researchers' analysis of these data showed that, compared with white Europeans, South Asian children had higher levels of HbA1c, insulin, triglycerides, and C-reactive protein but lower HDL-cholesterol levels. In addition, they had higher adiposity levels than the white European children, but this did not account for the observed differences in the other diabetes precursors. Black African-Caribbean children also had higher levels of HbA1c, insulin, and C-reactive protein than white European children, although the differences were smaller than those between South Asians and white Europeans. Similar to black African-Caribbean adults, however, children of this ethnic origin had higher HDL-cholesterol and lower triglyceride levels than white Europeans.
What Do These Findings Mean?
These findings indicate that ethnic differences in diabetes precursors are already present in apparently healthy children before they are 10 years old. Furthermore, most of the ethnic differences in diabetes precursors seen among the children follow the pattern seen in adults. Although these findings need confirming in more children, they suggest that the ethnic differences in type 2 diabetes susceptibility first described in immigrants to the UK are persisting in UK-born South Asian and black African-Caribbean children. Most importantly, these findings suggest that some of the factors thought to be responsible for ethnic differences in type 2 diabetes—for example, varying levels of physical activity and dietary differences—are operating well before adult life. Interventions that target these factors early could, therefore, offer good opportunities for diabetes prevention in high-risk ethnic groups, provided such interventions are carefully tailored to the needs of these groups.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000263.
The International Diabetes Federation provides information about all aspects of diabetes (in English, French and Spanish)
The US National Diabetes Information Clearinghouse provides detailed information about diabetes for patients, health-care professionals and the general public, including information on diabetes in specific US populations (in English and Spanish)
The UK National Health Service also provides information for patients and carers about type 2 diabetes (in several languages)
MedlinePlus provides links to further resources and advice about diabetes (in English and Spanish)
The US Agency for Healthcare Research and Quality has a fact sheet on diabetes disparities among racial and ethnic minorities
doi:10.1371/journal.pmed.1000263
PMCID: PMC2857652  PMID: 20421924
16.  Looking to the Future: Incorporating Genomic Information into Disparities Research to Reduce Measurement Error and Selection Bias 
Health Services Research  2012;47(3 Pt 2):1387-1410.
Objective
To extend recent conceptual and methodological advances in disparities research to include the incorporation of genomic information in analyses of racial/ethnic disparities in health care and health outcomes.
Data Sources
Published literature on human genetic variation, the role of genetics in disease and response to treatment, and methodological developments in disparities research.
Study Design
We present a conceptual framework for incorporating genomic information into the Institute of Medicine definition of racial/ethnic disparities in health care, identify key concepts used in disparities research that can be informed by genomics research, and illustrate the incorporation of genomic information into current methods using the example of HER-2 mutations guiding care for breast cancer.
Principal Findings
Genomic information has not yet been incorporated into disparities research, though it has direct relevance to concepts of race/ethnicity, health status, appropriate care, and socioeconomic status. The HER-2 example demonstrates how available genetic information can be incorporated into current disparities methods to reduce selection bias and measurement error. Advances in health information infrastructure may soon make standardized genetic information more available to health services researchers.
Conclusion
Genomic information can refine measurement of racial/ethnic disparities in health care and health outcomes and should be included wherever possible in disparities research.
doi:10.1111/j.1475-6773.2012.01413.x
PMCID: PMC3418832  PMID: 22515190
Health economics; social determinants of health; racial/ethnic differences in health and health care; personalized medicine; genomics
17.  Self-reported race/ethnicity in the age of genomic research: its potential impact on understanding health disparities 
Human Genomics  2015;9(1):1.
This review explores the limitations of self-reported race, ethnicity, and genetic ancestry in biomedical research. Various terminologies are used to classify human differences in genomic research including race, ethnicity, and ancestry. Although race and ethnicity are related, race refers to a person’s physical appearance, such as skin color and eye color. Ethnicity, on the other hand, refers to communality in cultural heritage, language, social practice, traditions, and geopolitical factors. Genetic ancestry inferred using ancestry informative markers (AIMs) is based on genetic/genomic data. Phenotype-based race/ethnicity information and data computed using AIMs often disagree. For example, self-reporting African Americans can have drastically different levels of African or European ancestry. Genetic analysis of individual ancestry shows that some self-identified African Americans have up to 99% of European ancestry, whereas some self-identified European Americans have substantial admixture from African ancestry. Similarly, African ancestry in the Latino population varies between 3% in Mexican Americans to 16% in Puerto Ricans. The implication of this is that, in African American or Latino populations, self-reported ancestry may not be as accurate as direct assessment of individual genomic information in predicting treatment outcomes. To better understand human genetic variation in the context of health disparities, we suggest using “ancestry” (or biogeographical ancestry) to describe actual genetic variation, “race” to describe health disparity in societies characterized by racial categories, and “ethnicity” to describe traditions, lifestyle, diet, and values. We also suggest using ancestry informative markers for precise characterization of individuals’ biological ancestry. Understanding the sources of human genetic variation and the causes of health disparities could lead to interventions that would improve the health of all individuals.
doi:10.1186/s40246-014-0023-x
PMCID: PMC4307746  PMID: 25563503
Genome; Race; Ethnicity; Ancestry; Ancestry informative markers; Ancestry haplotype; Admixture; Health disparity
18.  Investigating the Relationship between Socially-Assigned Ethnicity, Racial Discrimination and Health Advantage in New Zealand 
PLoS ONE  2013;8(12):e84039.
Background
While evidence of the contribution of racial discrimination to ethnic health disparities has increased significantly, there has been less research examining relationships between ascribed racial/ethnic categories and health. It has been hypothesized that in racially-stratified societies being assigned as belonging to the dominant racial/ethnic group may be associated with health advantage. This study aimed to investigate associations between socially-assigned ethnicity, self-identified ethnicity, and health, and to consider the role of self-reported experience of racial discrimination in any relationships between socially-assigned ethnicity and health.
Methods
The study used data from the 2006/07 New Zealand Health Survey (n = 12,488), a nationally representative cross-sectional survey of adults 15 years and over. Racial discrimination was measured as reported individual-level experiences across five domains. Health outcome measures examined were self-reported general health and psychological distress.
Results
The study identified varying levels of agreement between participants' self-identified and socially-assigned ethnicities. Individuals who reported both self-identifying and being socially-assigned as always belonging to the dominant European grouping tended to have more socioeconomic advantage and experience less racial discrimination. This group also had the highest odds of reporting optimal self-rated health and lower mean levels of psychological distress. These differences were attenuated in models adjusting for socioeconomic measures and individual-level racial discrimination.
Conclusions
The results suggest health advantage accrues to individuals who self-identify and are socially-assigned as belonging to the dominant European ethnic grouping in New Zealand, operating in part through socioeconomic advantage and lower exposure to individual-level racial discrimination. This is consistent with the broader evidence of the negative impacts of racism on health and ethnic inequalities that result from the inequitable distribution of health determinants, the harm and chronic stress linked to experiences of racial discrimination, and via the processes and consequences of racialization at a societal level.
doi:10.1371/journal.pone.0084039
PMCID: PMC3877153  PMID: 24391876
19.  Race Matters: A Systematic Review of Racial/Ethnic Disparity in Society for Assisted Reproductive Technology (SART) Reported Outcomes 
Fertility and sterility  2012;98(2):406-409.
Objective
To systematically review the reporting of race/ethnicity in SART Clinic Outcome Reporting System (CORS) publications.
Design
Systematic review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology of literature published in PUBMED on race/ethnicity that includes data from SART CORS.
Setting
Systematic review was performed on behalf of the ASRM Health Disparities Special Interest Group.
Population
IVF cycles reported to SART
Exposure
Race/ethnicity
Main Outcome Measure
Any outcomes reported in SART CORS
Results
Seven publications were identified that assessed racial/ethnic disparities in IVF outcomes using SART data. All reported a racial/ethnic disparity. However, over 35% of cycles were excluded from analysis because of missing race/ethnicity data.
Conclusions
Review of current publications of SART data suggests significant racial/ethnic disparities in IVF outcomes. However, the potential for selection bias limits confidence in these findings given that fewer than 65% of SART reported cycles include race/ethnicity. Our understanding of how race/ethnicity influences ART outcome could be greatly improved if information on race/ethnicity was available for all reported cycles.
doi:10.1016/j.fertnstert.2012.05.012
PMCID: PMC3409320  PMID: 22698638
race; ethnicity; disparity; in-vitro fertilization; SART
20.  Reliability of Internet- Versus Telephone-Administered Questionnaires in a Diverse Sample of Smokers 
Background
Smoking is more prevalent among lower-income individuals and certain racial/ethnic minorities. Addressing tobacco cessation among diverse populations is an urgent public health priority. As Internet use continues to rise among all segments of the US population, Web-based interventions have enormous potential to reach priority populations. Conducting Web-based smoking cessation research in priority populations requires psychometrically sound measurement instruments. To date, only one published study has examined the psychometric properties of Internet-administered measures commonly used in Web-based cessation trials. However, the sample was homogeneous with regard to race/ethnicity and income. We sought to replicate and extend these findings in a more diverse sample of smokers.
Objective
The aim was to examine the internal consistency and test-retest reliability of measures commonly used in smoking cessation clinical trials among racial/ethnic minorities and smokers with lower income.
Methods
Participants were enrolled in a randomized trial of the efficacy of an Internet smoking cessation program between June 2005 and September 2006. Following a baseline telephone assessment and randomization into the parent trial, participants were recruited to the reliability substudy. In phase I of recruitment, all participants in the parent trial were recruited to the substudy; in phase II, all consecutive racial/ethnic minority participants in the parent trial were recruited. Race and ethnicity were assessed via self-report using two standard items from the US Office of Management and Budget. An email was sent 2 days after the telephone assessment with a link to the Internet survey. Measures examined were quit methods, perceived stress, depression, social support, smoking temptations, alcohol use, perceived health status, and income. Internal consistency and test-retest reliability of Internet- versus telephone-administered measures were examined within four strata defined by race/ethnicity (non-Hispanic White, racial/ethnic minority) and annual household income (US $40,000 or less, more than $40,000).
Results
Of the 442 individuals invited, 319 participated (72% response rate): 52.4% were non-Hispanic White, 22.9% Black, 11.6% Hispanic, 7.8% Asian, 4.4% American Indian / Alaska Native, and 1% Native Hawaiian / Other Pacific Islander. About half (49.4%) reported an annual household income of US $40,000 or less, and 25.7% had a high school degree or less. Test-retest reliability was satisfactory to excellent across all strata for the majority of measures examined: 9 of 12 continuous variables had intraclass correlation coefficients ≥ 0.70, and 10 of 18 binary variables and both ordinal variables had kappa coefficients ≥ 0.70. Test-retest reliability of several quit methods varied across strata.
Conclusions
Race/ethnicity and income do not affect the psychometric properties of most Internet-administered measures examined. This knowledge adds to the confidence of conducting Web-based smoking cessation research and strengthens the scientific rigor of collecting information via the Internet on racial/ethnic minority and low-income subgroups.
Trial registration
clinicaltrials.gov NCT00282009 (parent trial)
doi:10.2196/jmir.987
PMCID: PMC2483847  PMID: 18364345
Reliability; smoking; Internet; diversity; measurement; psychometrics; minority groups; questionnaires; socioeconomic factors; social class; poverty; African Americans; Hispanic Americans
21.  Physicians’ knowledge, beliefs, and use of race and human genetic variation: new measures and insights 
Background
Understanding physician perspectives on the intersection of race and genomics in clinical decision making is critical as personalized medicine and genomics become more integrated in health care services. There is a paucity of literature in the United States of America (USA) and globally regarding how health care providers understand and use information about race, ethnicity and genetic variation in their clinical decision making. This paper describes the development of three scales related to addressing this gap in the literature: the Bonham and Sellers Genetic Variation Knowledge Assessment Index--GKAI, Health Professionals Beliefs about Race—HPBR, and Racial Attributes in Clinical Evaluation—RACE scales.
Methods
A cross-sectional, web survey of a national random sample of general internists in the USA (N = 787) was conducted. Confirmatory factor analysis was used to assess the construct validity of the scales. Scale items were developed through focus groups, cognitive interviews, expert advisory panels, and exploratory factor analysis of pilot data.
Results
GKAI was measured as a count of correct answers (Mean = 3.28 SD = 1.17). HPBR yielded two domains: beliefs about race as a biological phenomenon (HPBR-BD, alpha = .69, 4 items) and beliefs about the clinical value of race and genetic variation for understanding risk for disease (HPBR-CD alpha = .61, 3 items). RACE yielded one factor (alpha = .86, 7 items).
Conclusions
GKAI is a timely knowledge scale that can be used to assess health professional knowledge of race and human genetic variation. HPBR is a promising new tool for assessing health professionals’ beliefs about the role of race and its relationship with human genetic variation in clinical practice. RACE offers a valid and reliable tool for assessing explicit use of racial attributes in clinical decision making.
doi:10.1186/1472-6963-14-456
PMCID: PMC4283084  PMID: 25277068
Scale development; Medical decision making; Personalized medicine; RACE (Racial Attributes in Clinical Evaluation); GKAI (Genetic Variation Knowledge Assessment Index); Explicit use of race
22.  Family Physicians’ Beliefs about Genetic Contributions to Racial/Ethnic and Gender Differences in Health and Clinical Decision-Making 
Community Genetics  2008;11(6):352-358.
Greater attention towards genetics as a contributor to group health differences may lead to inappropriate use of race/ethnicity and gender as genetic heuristics and exacerbate health disparities. As part of a web-based survey, 1,035 family physicians (FPs) rated the contribution of genetics and environment to racial/ethnic and gender differences in health outcomes, and the importance of race/ethnicity and gender in their clinical decision-making. FPs attributed racial/ethnic and gender differences in health outcomes equally to environment and genetics. These beliefs were not associated with rated importance of race/ethnicity or gender in clinical decision-making. FPs appreciate the complexity of genetic and environmental influences on health differences by race/ethnicity and gender.
doi:10.1159/000133307
PMCID: PMC3399248  PMID: 18690003
Genetics; Race; Ethnicity; Gender; Clinical practice; Health disparities
23.  Racism and health inequity among Americans. 
Research reports often cite socioeconomic status as an underlying factor in the pervasive disparities in health observed for racial/ethnic minority populations. However, often little information or consideration is given to the social history and prevailing social climate that is responsible for racial/ethnic socioeconomic disparities, namely, the role of racism/racial discrimination. Much of the epidemiologic research on health disparities has focused on the relationship between demographic/clinical characteristics and health outcomes in main-effects multivariate models. This approach, however, does not examine the relationship between covariate levels and the processes that create them. It is important to understand the synergistic nature of these relationships to fully understand the impact they have on health status. PURPOSE: A review of the literature was conducted on the role that discrimination in education, housing, employment, the judicial system and the healthcare system plays in the origination, maintenance and perpetuation of racial/ethnic health disparities to serve as background information for funding Program Announcement, PA-05-006, The Effect of Racial/ Ethnic Discrimination/Bias on Healthcare Delivery (http:// grants.nih.gov/grants/ guide/pa-files/PA-05-006.html). The effect of targeted marketing of harmful products and environmental justice are also discussed as they relate to racial/ethnic disparities in health. CONCLUSION: Racial/ethnic disparities in health are the result of a combination of social factors that influence exposure to risk factors, health behavior and access to and receipt of appropriate care. Addressing these disparities will require a system that promotes equity and mandates accountability both in the social environment and within health delivery systems.
PMCID: PMC2576116  PMID: 16573303
24.  Eight Americas: Investigating Mortality Disparities across Races, Counties, and Race-Counties in the United States 
PLoS Medicine  2006;3(9):e260.
Background
The gap between the highest and lowest life expectancies for race-county combinations in the United States is over 35 y. We divided the race-county combinations of the US population into eight distinct groups, referred to as the “eight Americas,” to explore the causes of the disparities that can inform specific public health intervention policies and programs.
Methods and Findings
The eight Americas were defined based on race, location of the county of residence, population density, race-specific county-level per capita income, and cumulative homicide rate. Data sources for population and mortality figures were the Bureau of the Census and the National Center for Health Statistics. We estimated life expectancy, the risk of mortality from specific diseases, health insurance, and health-care utilization for the eight Americas. The life expectancy gap between the 3.4 million high-risk urban black males and the 5.6 million Asian females was 20.7 y in 2001. Within the sexes, the life expectancy gap between the best-off and the worst-off groups was 15.4 y for males (Asians versus high-risk urban blacks) and 12.8 y for females (Asians versus low-income southern rural blacks). Mortality disparities among the eight Americas were largest for young (15–44 y) and middle-aged (45–59 y) adults, especially for men. The disparities were caused primarily by a number of chronic diseases and injuries with well-established risk factors. Between 1982 and 2001, the ordering of life expectancy among the eight Americas and the absolute difference between the advantaged and disadvantaged groups remained largely unchanged. Self-reported health plan coverage was lowest for western Native Americans and low-income southern rural blacks. Crude self-reported health-care utilization, however, was slightly higher for the more disadvantaged populations.
Conclusions
Disparities in mortality across the eight Americas, each consisting of millions or tens of millions of Americans, are enormous by all international standards. The observed disparities in life expectancy cannot be explained by race, income, or basic health-care access and utilization alone. Because policies aimed at reducing fundamental socioeconomic inequalities are currently practically absent in the US, health disparities will have to be at least partly addressed through public health strategies that reduce risk factors for chronic diseases and injuries.
US mortality rates were calculated according to "race-county" units and divided into the "eight Americas", across which there are enormous disparities in life expectancy.
Editors' Summary
Background.
It has been recognized for a long time that the number of years that people in the United States can expect to live (“life expectancy”) varies enormously. For example, white Americans tend to live longer than black Americans, and life expectancy is much greater in some of the roughly 3,000 counties of the US than it is in others. However, there is a lack of information and understanding on how big a part is played in “health inequalities” by specific diseases and injuries, by risk factors (such as tobacco, alcohol, and obesity), and by variations in access to effective health care.
Why Was This Study Done?
The researchers wanted to find a way of dividing the people of the US into groups based on a small number of characteristics—such as location of county of residence, race, and income—that would help demonstrate the most important factors accounting for differences in life expectancy.
What Did the Researchers Do and Find?
The researchers used figures from the US Census Bureau and the National Center for Health Statistics to calculate mortality (death) rates for the years 1982–2001. They took note of the county of residence and of the race of all the people who died during that period of time. This enabled them to calculate the mortality rates for all 8,221 “race-county units” (all of the individuals of a given race in a given county). They experimented with different ways of combining the race-counties into a small and manageable number of groups. They eventually settled on the idea of there being “eight Americas,” defined on the basis of race-county, population density, income, and homicide rate. Each group contains millions or tens of millions of people. For each of the eight groups the researchers estimated life expectancy, the risk of mortality from specific diseases, the proportion of people who had health insurance, and people's routine encounters with health-care services. (The researchers also created maps of life expectancies for the US counties.) They describe their eight Americas as follows: Asians, northland low-income rural whites, Middle America, low-income whites in Appalachia and the Mississippi Valley, western Native Americans, black Middle America, low-income southern rural blacks, and high-risk urban blacks.
Many striking differences in life expectancy were found between the eight groups. For example, in 2001, the life expectancy gap between the 3.4 million high-risk urban black males and the 5.6 million Asian females was nearly 21 years. Within the sexes, the life expectancy gap between the best-off and the worst-off groups was 15.4 years for males (Asians versus high-risk urban blacks) and 12.8 years for females (Asians versus low-income rural blacks in the South). The causes of death that were mainly responsible for these variations were various chronic diseases and injury. The gaps between best-off and worst-off were similar in 2001 to what they were in 1987.
What Do These Findings Mean?
Health inequalities in the US are large and are showing no sign of reducing. Social and economic reforms would certainly help change the situation. At the same time, the public health system should also improve the way in which it deals with risk factors for chronic diseases and injuries so that groups with the highest death rates receive larger benefits.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0030260.
A Perspective article by Gregory Pappas in this issue of PLoS Medicine (DOI: 10.1371/journal.pmed.0030357) discusses the methods of this piece of research and the findings
The American Medical Students' Association deals with the question “What are Health Disparities?” on its web site
The National Institutes of Health's “Strategic Research Plan to Reduce and Ultimately Eliminate Health Disparities” may be seen at the NIH web site
The Office of Minority Health at the Centers for Disease Control and Prevention has a Web page called “Eliminating Racial and Ethnic Health Disparities”
The issue of health inequalities in the US has also been dealt with by the Robert Wood Johnson Foundation
doi:10.1371/journal.pmed.0030260
PMCID: PMC1564165  PMID: 16968116
25.  Non-hispanic whites have higher risk for pulmonary impairment from pulmonary tuberculosis 
BMC Public Health  2012;12:119.
Background
Disparities in outcomes associated with race and ethnicity are well documented for many diseases and patient populations. Tuberculosis (TB) disproportionately affects economically disadvantaged, racial and ethnic minority populations. Pulmonary impairment after tuberculosis (PIAT) contributes heavily to the societal burden of TB. Individual impacts associated with PIAT may vary by race/ethnicity or socioeconomic status.
Methods
We analyzed the pulmonary function of 320 prospectively identified patients with pulmonary tuberculosis who had completed at least 20 weeks standard anti-TB regimes by directly observed therapy. We compared frequency and severity of spirometry-defined PIAT in groups stratified by demographics, pulmonary risk factors, and race/ethnicity, and examined clinical correlates to pulmonary function deficits.
Results
Pulmonary impairment after tuberculosis was identified in 71% of non-Hispanic Whites, 58% of non-Hispanic Blacks, 49% of Asians and 32% of Hispanics (p < 0.001). Predictors for PIAT varied between race/ethnicity. PIAT was evenly distributed across all levels of socioeconomic status suggesting that PIAT and socioeconomic status are not related. PIAT and its severity were significantly associated with abnormal chest x-ray, p < 0.0001. There was no association between race/ethnicity and time to beginning TB treatment, p = 0.978.
Conclusions
Despite controlling for cigarette smoking, socioeconomic status and time to beginning TB treatment, non-Hispanic White race/ethnicity remained an independent predictor for disproportionately frequent and severe pulmonary impairment after tuberculosis relative to other race/ethnic groups. Since race/ethnicity was self reported and that race is not a biological construct: these findings must be interpreted with caution. However, because race/ethnicity is a proxy for several other unmeasured host, pathogen or environment factors that may contribute to disparate health outcomes, these results are meant to suggest hypotheses for further research.
doi:10.1186/1471-2458-12-119
PMCID: PMC3305434  PMID: 22325005

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