Race and health

Race and health refers to the relationship between individual health and one's race and ethnicity. Differences in health status, health outcomes, life expectancy, and many other indicators of health in different racial and ethnic groups is well documented, referred to as Health disparities. Race (human classification) is a complex concept, and the two major competing theories of race use biological definitions and social construction to define racial difference. Although this relationship can vary depending on the definitions used, race is generally used in the context of health research as a fluid concept to group populations of people according to various factors that include but are not limited to ancestry, social identity, visible phenotype, and genetic makeup. Determinants of health include environmental, social, and genetic factors.

Health disparities

Health disparities refer to gaps in the quality of health and health care across racial and ethnic groups. The US Health Resources and Services Administration defines health disparities as "population-specific differences in the presence of disease, health outcomes, or access to health care." Health is measured through variables such as life expectancy and incidence of diseases.

How researchers view race is often linked to how we address racial disparities because the national administrator of health uses these research findings to implement policies.

“79 percent of African Americans had health coverage in 2009 compared to 88 percent of white Americans.”

Defining race

Main article: Race (human classification)

There are various paradigms used to discuss race, including biological and social views. Definitions have changed throughout history to yield a modern understanding of race that is complex and fluid. Moreover, there is no one definition that stands, as there are many competing and interlocking ways to look at race. The terms race, genetic population, ethnicity, geographic population, and ancestry are used interchangeably in everyday discourse involving race.

Biological definitions of race encompass Essentialist and Anti-Essentialist views. The scientific community does not universally accept a single definition of race. Essentialism is a mode of thought that uses scientific data to argue that racial groups are genetically distinct populations. Essentialists describe “races as groups of people who share certain innate, inherited biological traits, aka use of biological evidence to demonstrate racial differences.” As its counterpart, Anti-essentialism uses biological evidence to demonstrate that “race groupings do not reflect patterns of human biological variation, countering essentialist claims to the contrary.”

Social definitions are commonly constructionist. Racial groups are “constructed” from differing historical, political, and economic contexts, rather than corresponding to inherited, biological variations. Proponents of the constructionist view claim that biological definitions have been used to justify racism in the past and still have the potential to be used to encourage racist thinking in the future.

Social views also better explain the ambiguity of racial definitions. An individual may self-identify as one race based on one set of determinants (for example, phenotype, culture, ancestry) while society may ascribe the person otherwise based on external forces and discrete racial standards. Dominant racial conceptions influence how individuals label both themselves and others within society. Modern human populations are becoming more difficult to define within traditional racial boundaries due to racial admixture. Most scientific studies, applications, and government documents ask individuals to self-identify race from a limited assortment of common racial categories. The conflict between self-identification and societal ascription further complicates biomedical research and public health policies. However complex its sociological roots, race has real biological ramifications; the intersection of race, science, and society permeates everyday life and influences human health via genetics, access to medical care, diagnosis, and treatment.

Race and disease

There are myriad factors that affect health disparities between racial groups. Among these factors are genetic differences within racial populations, cultural mores, and social and environmental factors.

Health disparities, which include variations in life expectancy and prevalence of disease, due to the differences in health conditions across various ethnic populations that can be attributed to inequalities in living environment and access to healthcare may also play a role.

Single-gene disorders

See also: genetic disorder

There are many single gene genetic disorders that differ in frequency between different populations due to the region, though many assume it to be solely based on race. Examples include:

• Cystic fibrosis, the most common life-limiting autosomal recessive disease among people of European heritage

• Sickle-cell anemia, most prevalent in populations with sub-Saharan African ancestry but also common among Latin-American, Indian, and Saudi Arab populations, as well as those people of Mediterranean regions such as Turkey, Greece, and Italy

• Thalassemia, most prevalent in populations having Mediterranean ancestry, to the point that the disease's name is derived from Greek thalasson, "sea"

• Tay–Sachs disease, an autosomal recessive disorder more frequent among Ashkenazi Jews than among other Jewish groups and non-Jewish populations

• Hereditary hemochromatosis, most common among persons having Northern European ancestry, in particular those people of Celtic descent

Multifactorial polygenic diseases

The table shows many diseases which differ in frequency between different populations. However, complex diseases are affected by multiple factors, both genetic and environmental. There is controversy over the extent to which some of these conditions are heritable, and ongoing research aims to identify the genetic loci that are linked to these diseases.

“Risk is the probability that an event will occur. In epidemiology, it is most often used to express the probability that a particular outcome will occur following a particular exposure.” Different populations are labeled “high-risk” or “low-risk” groups for various diseases due to the probability of that particular population being more exposed to certain risk factors. Beyond genetic factors, history and culture, as well as current environmental and social conditions, influence a certain population’s exposure to some factors that makes it statistically more probable to contract specific diseases. While this chart references biomedical literature, further information on these diseases can be found in various health journals. The groups described in the chart below are race-based, though the studies conducted are more specifically population-based.

Diseases that differ in frequency among different populations.

Health defined group	High-risk groups	Low-risk groups	Reference(s)
Alcoholism	Native Americans, Aboriginal Australians	Europeans
Atrial fibrillation	European Americans	African Americans
Autism spectrum disorders	European Americans, Asian Americans	Hispanic Americans
Bipolar disorder	European Americans, African Americans	Asian Americans
Carotid artery disease	European Americans	African Americans
Coronary artery disease	European Americans	African Americans, West African men
Dementia	African Americans	European Americans
Focal segmental glomerulosclerosis	African Americans	European Americans
Hepatitis C clearance	European Americans	African Americans
HIV progression	African Americans	European Americans
HIV vertical transmission	European Americans	African Americans
Hypertension	African Americans, West Africans, Filipinos	Europeans
Hypertensive heart disease	African Americans	European Americans
Hypertensive retinopathy	African Americans	European Americans
Intracranial haemorrhage	African Americans	European Americans
Lupus nephritis with systemic lupus erythematosus	African Americans	European Americans
Lung cancer	African Americans	European Americans
Multiple sclerosis	Europeans	African Americans, Turkmens, Uzbeks, Native Siberians, New Zealand Maoris
Myeloma	African Americans	European Americans
Non-insulin dependent diabetes	African Americans, West Africans, Peninsular Arabs, Pacific Islanders, and Native Americans	European Americans, Europeans
Obesity	African women, Native Americans, Pacific Islanders, Aboriginal Australians, Hispanic women	European Americans, Europeans, Southeast Asians
Osteoporosis	European Americans, Asian Americans	African Americans
Pregnancy-related death	African Americans	European Americans
Prostate cancer	Africans and African Americans	European Americans
Renal disease, end stage	Native Americans and African populations	European Americans, Europeans
Skin cancer	Europeans	African Americans, Southeast Asians
Stroke	African Americans	European Americans
Systemic lupus erythematosus	African Americans, West Africans, Native Americans	Europeans
Systemic sclerosis	African Americans	European Americans

Disease progression

Groups may differ in how a disease progresses. Black men who were diagnosed with HIV generally fared worse than their white and Hispanic counterparts. The percentage of men studied with very low CD4+ T-cell count, defined as fewer than 50 cells per microliter, at AIDS diagnosis was 24.1% for white men, 27.8% for Hispanic men, and 34.4% for Black men. Black men were also significantly less likely to be alive three years after diagnosis (80.6%) than Hispanic or white men, who had 85.2% and 84.5% survival rates, respectively. However, the reasons for these differences are not clear, and should not be understood as an essential difference between races, but rather as effects of social and environmental factors.

Prevention

Different groups may require different preventive measures to prevent specific diseases. For example, disease prevention for melanoma, which can include proper use of sun screen and reducing the risks of sun exposure, could be targeted to groups that are much more likely to develop melanoma from sun exposure.

Race-based treatment

See also: Pharmacogenomics

"Race-based medicine" is the term for medicines that are targeted at specific ethnic clusters which are shown to have a propensity for a certain disorder. The first example of this in the U.S. was when BiDil, a medication for congestive heart failure, was licensed specifically for use in American patients that self-identify as black. Previous studies had shown that African American patients with congestive heart failure generally respond less effectively to traditional treatments than white patients with similar conditions.

After two trials, BiDil was licensed exclusively for use in African American patients. Critics have argued that this particular licensing was unwarranted, since the trials did not in fact show that the drug was more effective in African Americans than in other groups, but merely that it was more effective in African Americans than other similar drugs. It was also only tested in African American males, but not in any other racial groups or among women. This peculiar trial and licensing procedure has prompted suggestions that the licensing was in fact used as a race-based advertising scheme.

Critics are concerned that the trend of research on race-specific pharmaceutical treatments will result in inequitable access to pharmaceutical innovation and smaller minority groups may be ignored. This has led to a call for regulatory approaches to be put in place to ensure scientific validity of racial disparity in pharmacological treatment.

An alternative to “race-based medicine” is personalized medicine that involves identifying genetic, genomic (i.e. genomic sequencing), and clinical information—as opposed to using race as a proxy for these data—to better predict a patient’s predisposition to certain diseases.

Environmental factors

In multiracial societies such as the United States, racial groups differ greatly in regard to social and cultural factors such as socioeconomic status, healthcare, diet, and education. There is also the presence of racism which some see as an important explaining factor. Some argue that for many diseases racial differences would disappear if all environmental factors could be controlled for. See the article about race and health in the United States for a discussion of such factors. These factors may or may not be appropriate in other nations.

Ethnic minorities may also have specific health care needs which need to be considered by health services in order to tackle health disparities.

Ethnic groups undergoing urbanization can have their health affected by the process. For example, Type 2 Diabetes is highly prevalent in Mexicans as a result of economic development and urbanization of regions. When populations become more urban, it increases the availability of cheap sources of fat. A study done in 1995 showed that diabetes was most prevalent in India, China, and the United States as all three countries are highly urbanized. In addition, urbanization creates jobs that are less demanding as compared to non-urban areas. This results in a change of lifestyle and choices of recreation that is typically responsible for the high levels of obesity and diabetes in Mexicans.

Genetic factors

The fact that every human has a unique genetic code, is the key to techniques such as genetic fingerprinting. Versions of a trait, known as alleles, occur at different frequencies in different human populations; populations that are more geographically and ancestrally remote tend to differ more.

A phenotype is the "outward, physical manifestation" of an organism." For humans, phenotypic differences are most readily seen via skin color, eye color, hair color, or height; however, any observable structure, function, or behavior can be considered part of a phenotype. A genotype is the "internally coded, inheritable information" carried by all living organisms. The human genome is encoded in DNA

For any trait of interest, observed differences among individuals “may be due to differences in the genes” coding for a trait or “the result of variation in environmental condition”. This variability is due to gene-environment interactions that influence genetic expression patterns and trait heritability.

For humans, there is “more genetic variation among individual people than between larger racial groups.” In general, an average of 80% of genetic variation exists within local populations, around 10% is between local populations within the same continent, and approximately 8% of variation occurs between large groups living on different continents. Studies have found evidence of genetic differences between populations, but the distribution of genetic variants within and among human populations is impossible to describe succinctly because of the difficulty of defining a "population," the clinal nature of variation, and heterogeneity across the genome. Thus, the racialization of science and medicine can lead to controversy when the term population and race are used interchangeably.

Evolutionary factors

See also: Heterozygote advantage

Genes may be under strong selection in response to local diseases. For example, people who are duffy negative tend to have higher resistance to malaria. Most Africans are duffy negative and most non-Africans are duffy positive. A number of genetic diseases more prevalent in malaria-afflicted areas may provide some genetic resistance to malaria including sickle cell disease, thalassaemias, glucose-6-phosphate dehydrogenase, and possibly others.

Many theories about the origin of the cystic fibrosis have suggested that it provides a heterozygote advantage by giving resistance to diseases earlier common in Europe.

In earlier research, a common theory was the "common disease-common variant" model. It argues that for common illnesses, the genetic contribution comes from the additive or multiplicative effects of gene variants that each one is common in the population. Each such gene variant is argued to cause only a small risk of disease and no single variant is enough to cause the disease. An individual must have many of these common gene variants in order for the risk of disease to be substantial.

More recent research indicates that the "common disease-rare variant" may be a better explanation for many common diseases. In this model, rare but higher-risk gene variants cause common diseases. This model may be relevant for diseases that reduces fertility. In contrast, for common genes associated with common disease to persist they must either have little effect during the reproductive period of life (like Alzheimer's disease) or provide some advantage in the original environment (like genes causing autoimmune diseases also providing resistance against infections). In either case varying frequencies of genes variants in different populations may be an explanation for health disparities. Genetic variants associated with Alzheimer's disease, deep venous thrombosis, Crohn disease, and type 2 diabetes appear to adhere to "common disease-common variant" model.

Gene flow

Gene flow and admixture can also have an effect on relationships between race and race-linked disorders. Multiple sclerosis, for example, is typically associated with people of European descent, but due to admixture African Americans have elevated levels of the disorder relative to Africans.

Some diseases and physiological variables vary depending upon their admixture ratios. Examples include measures of insulin functioning and obesity.

Gene interactions

The same gene variant, or group of gene variants, may produce different effects in different populations depending on differences in the gene variants, or groups of gene variants, they interact with. One example is the rate of progression to AIDS and death in HIV–infected patients. In Caucasians and Hispanics, HHC haplotypes were associated with disease retardation, particularly a delayed progression to death. In contrast, for African Americans, possession of HHC haplotypes was associated with disease acceleration.

Controversy regarding race in biomedicine

See also: Race (classification of humans) and Race and genetics

There is a controversy regarding race as a method for classifying humans. Different sources argue it is purely social construct or a biological reality reflecting average genetic group differences. New interest in human biological variation has resulted in a resurgence of the use of race in biomedicine.

The main impetus for this development is the possibility of improving the prevention and treatment of certain diseases by predicting hard-to-ascertain factors, such as genetically conditioned health factors, based on more easily ascertained characteristics such as phenotype and racial self-identification. Since medical judgment often involves decision making under uncertain conditions, many doctors consider it useful to take race into account when treating disease because diseases and treatment responses tend to cluster by geographic ancestry. The discovery that more diseases than previously thought correlate with racial identification have further sparked the interest in using race as a proxy for bio-geographical ancestry and genetic buildup.

Race in medicine is used as an approximation for more specific genetic and environmental risk factors. Race is thus partly a surrogate for environmental factors such as differences in socioeconomic status that are known to affect health. It is also an imperfect surrogate for ancestral geographic regions and differences in gene frequencies between different ancestral populations and thus differences in genes that can affect health. This can give an approximation of probability for disease or for preferred treatment, although the approximation is less than perfect.

Distribution of the sickle cell trait

Distribution of Malaria.

Taking the example of sickle-cell disease, in an emergency room, knowing the geographic origin of a patient may help a doctor doing an initial diagnosis if a patient presents with symptoms compatible with this disease. This is unreliable evidence with the disease being present in many different groups as noted above with the trait also present in some Mediterranean European populations. Definitive diagnosis comes from examining the blood of the patient. In the US, screening for sickle cell anemia is done on all newborns regardless of race.

The continued use of racial categories has been criticized. Apart from the general controversy regarding race, some argue that the continued use of racial categories in health care and as risk factors could result in increased stereotyping and discrimination in society and health services. Some of those who are critical of race as a biological concept see race as socially meaningful group that is important to study epidemiologically in order to reduce disparities. For example, some racial groups are less likely than others to receive adequate treatment for osteoporosis, even after risk factors have been assessed. Since the 19th century, blacks have been thought to have thicker bones than whites have and to lose bone mass more slowly with age. In a recent study, African Americans were shown to be substantially less likely to receive prescription osteoporosis medications than Caucasians. Men were also significantly less likely to be treated compared with women. This discrepancy may be due to physicians’ knowledge that, on average, African Americans are at lower risk for osteoporosis than Caucasians. It may be possible that these physicians generalize this data to high-risk African-Americans, leading them to fail to appropriately assess and manage these individuals’ osteoporosis. On the other hand, some of those who are critical of race as a biological concept see race as socially meaningful group that is important to study epidemiologically in order to reduce disparities.

David Williams (1994) argued, after an examination of articles in the journal Health Services Research during the 1966-90 period, that how race was determined and defined was seldom described. At a minimum, researchers should describe if race was assessed by self-report, proxy report, extraction from records, or direct observation. Race was also often used questionable, such as an indicator of socioeconomic status. Racial genetic explanations may be overemphasized, ignoring the interaction with and the role of the environment.

From concepts of race to ethnogenetic layering

There is general agreement that a goal of health-related genetics should be to move past the weak surrogate relationships of racial health disparity and get to the root causes of health and disease. This includes research which strives to analyze human genetic variation in smaller groups than races across the world.

One such method is called ethnogenetic layering. It works by focusing on geographically identified microethnic groups. For example, in the Mississippi Delta region ethnogenetic layering might include such microethnic groups as the Cajun (as a subset of European Americans), the Creole and Black groups [with African origins in Senegambia, Central Africa and Bight of Benin] (as a subset of African Americans), and Choctaw, Houmas, Chickasaw, Coushatta, Caddo, Atakapa, Karankawa and Chitimacha peoples (as subsets of Native American Indians).

Better still may be individual genetic assessment of relevant genes. As genotyping and sequencing have become more accessible and affordable, avenues for determining individual genetic makeup have opened dramatically. Even when such methods become commonly available, race will continue to be important when looking at groups instead of individuals such as in epidemiologic research.

Association studies

See also: Genetic association

One area in which population categories can be important considerations in genetics research is in controlling for confounding between population genetic substructure, environmental exposures, and health outcomes. Association studies can produce spurious results if cases and controls have differing allele frequencies for genes that are not related to the disease being studied, although the magnitude of its problem in genetic association studies is subject to debate. Various techniques detect and account for population substructure, but these methods can be difficult to apply in practice.

Population genetic substructure also can aid genetic association studies. For example, populations that represent recent mixtures of separated ancestral groups can exhibit longer-range linkage disequilibrium between susceptibility alleles and genetic markers than is the case for other populations. Genetic studies can use this disequilibrium to search for disease alleles with fewer markers than would be needed otherwise. Association studies also can take advantage of the contrasting experiences of racial or ethnic groups, including migrant groups, to search for interactions between particular alleles and environmental factors that might influence health.

Human genome projects

The Human Genome Diversity Project has collected genetic samples from 52 indigenous populations.

Sources of racial disparities in care

In a report by the Institute of Medicine called Unequal Treatment, three major source categories are put forth as potential explanations for disparities in health care: patient-level variables, healthcare system-level factors, and care process-level variables.

Patient-level variables

There are many individual factors that could explain the established differences in health care between different racial and ethnic groups. First, attitudes and behaviors of minority patients are different. They are more likely to refuse recommended services, adhere poorly to treatment regimens, and delay seeking care, yet despite this, these behaviors and attitudes are unlikely to explain the differences in health care. In addition to behaviors and attitudes, biological based racial differences have been documented, but these also seem unlikely to explain the majority of observed disparities in care.

Health system-level factors

Health system-level factors include any aspects of health systems that can have different effects on patient outcomes. Some of these factors include different access to services, access to insurance or other means to pay for services, access to adequate language and interpretation services, and geographic availability of different services. Many studies assert that these factors explain portions of the existing disparities in health of racial and ethnic minorities in the United States when compared to their white counterparts.

Care process-level variables

Three major mechanisms are suggested by the Institute of Medicine that may contribute to healthcare disparities from the provider's side: bias (or prejudice) against racial and ethnic minorities; greater clinical uncertainty when interacting with minority patients; and beliefs held by the provider about the behavior or health of minorities. Research in this area is new and ongoing.

See also

• Ethnicity and health
• ACE inhibitor; a type of drugs found to work less effectively with people of African origin
• HapMap
• Health and intelligence
• Human stature#Average height around the world
• List of countries by life expectancy
• Ethnic bioweapon
• Social determinants of health
• Medical genetics of Jews
• Hispanic Paradox
• Category:Human genome projects

United States:

• Race and health in the United States
• Center for Minority Health, US.

General:

• Health disparities
• Pharmacogenomics
• Medical genetics
• Personal genomics

Further reading

Textbooks and practitioner guides

• Gluckman, Peter; Beedle, Alan; Hanson, Mark (2009). Principles of Evolutionary Medicine. Oxford: Oxford University Press. ISBN 978-0-19-923639-8. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)
• Hamilton, Matthew B. (2009). Population Genetics. Wiley-Blackwell. ISBN 978-1-4051-3277-0. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)
• Speicher, Michael R.; Antonarakis, Stylianos E.; Motulsky, Arno G., eds. (2010). Vogel and Motulsky's Human Genetics: Problems and Approaches. Heidelberg: Springer Scientific. doi:10.1007/978-3-540-37654-5. ISBN 978-3-540-37653-8. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help) This authoritative textbook includes sections by Arno G. Motulsky, Stylianos E. Antonarakis, Michael R. Speicher, Michael Dean, Jon F. Robinson, Nicholas Katsanis, Andrew G. Clark, Jacques S. Beckmann, Bernhard Horsthemke, David N. Cooper, George P. Patrinos, Alexandre Alcaïs, Laurent Abel, Jean-Laurent Casanova, Stefan Mundlos, Ian Tomlinson, Romulo Martin Brena, Joseph F. Costello, Emmanouil T. Dermitzakis, Alan H. Bittles, Michael Hofreiter, Ross C. Hardison, Sohini Ramachandran, Hua Tang, Ryan N. Gutenkunst, Carlos D. Bustamante, Sophia S. Wang , Terri H. Beaty, Muin J. Khoury, Nicole M. Walley, Paola Nicoletti, David B. Goldstein, Jonathan Flint, Saffron Willis-Owen, David L. Nelson, Thomas D. Bird, Brett S. Abrahams Daniel H. Geschwind, David Goldman, Francesca Ducci, Michael R. Speicher, Markus M. Nöthen, Sven Cichon, Christine Schmael, Marcella Rietschel, Antonio Baldini, Morgan Tucker, Min Han, Ruth Johnson, Ross Cagan, Heidi G. Parker, Elaine A. Ostrander, Siew Hong Lam, Zhiyuan Gong, Tiemo Grimm, Klaus Zerres, Vivian W. Choi, R. Jude Samulski, Ian Wilmut, Jane Taylor, Paul de Sousa, Richard Anderson, Christopher Shaw, David J. Weatherall, Rachel A. Harte, Donna Karolchik, Robert M. Kuhn, W. James Kent, David Haussler, Xosé M. Fernández, Ewan Birney, Roberta A. Pagon, Ada Hamosh, Johan den Dunnen, Helen V. Firth, Donna R. Maglott, Stephen T. Sherry, Michael Feolo, David Cooper, and Peter Stenson. This book includes the chapter

Ramachandran, Sohini; Tang, Hua; Gutenkunst, Ryan N.; Bustamante, Carlos D. (2010). "Chapter 20: Genetics and Genomics of Human Population Structure". In Speicher, Michael R.; Antonarakis, Stylianos E.; Motulsky, Arno G. (eds.). Vogel and Motulsky's Human Genetics: Problems and Approaches (PDF). Heidelberg: Springer Scientific. pp. 589–615. doi:10.1007/978-3-540-37654-5. ISBN 978-3-540-37653-8. Retrieved 29 October 2013. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)

• Krimsky, Sheldon; Sloan, Kathleen, eds. (2011). Race and the Genetic Revolution: Science, Myth, and Culture. Columbia University Press. ISBN 978-0-231-52769-9. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help) This review of current research includes chapters by Michael Yudell, Robert Pollack, Michael T. Risher, Helen Wallace, Troy Duster, Duana Fullwiley, Jonathan Kahn, Joseph L. Graves, Jr., Pilar N. Ossorio, Robert J. Sternberg, Elena L. Grigorenko, Kenneth K. Kidd, and Steven E. Stemler, Patricia J. Williams, and Osagie K. Obasogie.
• Whitmarsh, Ian; Jones, David S., eds. (2010). What's the Use of Race?: Modern Governance and the Biology of Difference. Cambridge (MA): MIT Press. ISBN 978-0-262-51424-8. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help) This review of current research includes chapters by Ian Whitmarsh, David S. Jones, Jonathan Kahn, Pamela Sankar, Steven Epstein, Simon M. Outram, George T. H. Ellison, Richard Tutton, Andrew Smart, Richard Ashcroft, Paul Martin, George T. H. Ellison, Amy Hinterberger, Joan H. Fujimura, Ramya Rajagopalan, Pilar N. Ossorio, Kjell A. Doksum, Jay S. Kaufman, Richard S. Cooper, Angela C. Jenks, Nancy Krieger, and Dorothy Roberts. This includes the chapter

Kaufman, Jay S.; Cooper, Richard S. (2010). "Racial and Ethnic Identity in Medical Evaluations and Treatments". In Whitmarsh, Ian; Jones, David S. (eds.). What's the Use of Race?: Modern Governance and the Biology of Difference. Cambridge (MA): MIT Press. ISBN 978-0-262-51424-8. {{cite book}}: Invalid |ref=harv (help)

• Roberts, Dorothy (2011). Fatal Invention: How Science, Politics, and Big Business Re-create Race in the Twenty-first Century. New Press. ISBN 978-1-59558-495-3. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)
• Stone, Linda; Lurquin, Paul F.; Cavalli-Sforza, L. Luca (2007). Genes, Culture, and Human Evolution: A Synthesis. Malden (MA): Wiley-Blackwell. ISBN 978-1-4051-5089-7. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)
• Al-Chalabi, Ammar; Almasy, Laura, eds. (2009). Genetics of Complex Human Diseases: A Laboratory Manual. Cold Spring Harbor (NY): Cold Spring Harbor Laboratory Press. ISBN 978-0-87969-883-6. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help) This practitioner's manual includes contributions by Janet Sinsheimer, Ingrid B. Borecki, John P. Rice, John Gallacher, Laura Almasy, John Blangero, Hon-Cheong So, Pak C. Sham, Cathryn M. Lewis, Jo Knight, Ammar Al-Chalabi, Benjamin M. Neale, Paul I.W. de Bakker, Benjamin M. Neale, Mark J. Daly, Ruth J.F. Loos, Nicholas J. Wareham, Eden R. Martin, Evadnie Rampersaud, Dheeraj Malhatra, Jonathan Sebat, Simon J. Furney, Gunes Gundem, Nuria Lopez-Bigas, Brage Storstein Andresen, Adrian R. Krainer, Howard J. Edenberg, Yunlong Liu, Inti Pedroso, and Gerome Breen.
• Crawford, Michael, ed. (2006). Anthropological Genetics: Theory, Methods and Applications. Cambridge: Cambridge University Press. ISBN 978-0-521-54697-3. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help) This textbook includes chapters by M. H. Crawford, Lorena Madrigal, Guido Barbujani, Joe Terwilliger, Joe Lee, James H. Mielke, Alan Fix, Rohina Rubicz, Phil Melton, John Relethford, Dennis O'Rourke, Moses Schanfield, Ric Devor, John Blangero, Jeff T. Williams, Laura Almasy, Sarah Williams-Blangero, Sarah A. Tishkoff, Mary Katherine Gonder, Barbara Arredi, Estella S. Poloni, Chris Tyler-Smith, Elizabeth Matisoo Smith, Francisco Salzano, and Henry Harpending.
• Fullwiley, Duana (21 November 2011). The Enculturated Gene: Sickle Cell Health Politics and Biological Difference in West Africa. Princeton University Press. ISBN 0-691-12317-9. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)
• Hartl, Daniel L.; Jones, Elizabeth W. (2009). Genetics : analysis of genes and genomes. Sudbury (MA): Jones & Bartlett. ISBN 9780763765392. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)
• Koenig, Barbara A.; Lee, Sandra Soo-jin; Richardson, Sarah S., eds. (2008). Revisiting Race in a Genomic Age. New Brunswick (NJ): Rutgers University Press. ISBN 978-0-8135-4324-6. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help) This review of current research includes chapters by Jonathan Marks, John Dupré, Sally Haslanger, Deborah A. Bolnick, Marcus W. Feldman, Richard C. Lewontin, Sarah K. Tate, David B. Goldstein, Jonathan Kahn, Duana Fullwiley, Molly J. Dingel, Barbara A. Koenig, Mark D. Shriver, Rick A. Kittles, Henry T. Greely, Kimberly Tallbear, Alondra Nelson, Pamela Sankar, Sally Lehrman, Jenny Reardon, Jacqueline Stevens, and Sandra Soo-Jin Lee.
• Krimsky, Sheldon; Gruber, Jeremy, eds. (26 February 2013). Genetic Explanations: Sense and Nonsense. Harvard University Press. ISBN 978-0-674-06446-1. Retrieved 12 November 2013. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)
• Morning, Ann (24 June 2011). The Nature of Race: How Scientists Think and Teach about Human Difference. University of California Press. p. 223–224. ISBN 978-0-520-27031-2. A straightforward explanation of why essentialist concepts are more popular than constructivist ones might simply be that the former are true and the latter false. But there are several reasons to be skeptical of such a conclusion. First and foremost, many experts believe there is a great deal of empirical evidence that refutes the biological model of race (Barbujani 2006; Koenig, Lee, and Richardson 2008; Marks 1995). Analysis of human DNA has not revealed any 'race gene' whose alleles (i.e., variants) correspond to racial-group membership, nor any complex of genes that together indicate a person's race (pace Leroi 2005). Instead, it has demonstrated extraordinary similarity in human beings' genetic makeup, regardless of their outward appearance: 99.9 percent of our genome is identical (Barbujani et al. 1997; Lewontin 1972). The genetic variation variation that does exist among human beings can mostly be found within the boundaries of any one racial group (Feldman and Lewontin 2008). {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)
• Park, Michael Alan (2009). Biological Anthropology (Sixth ed.). New York: McGraw-Hill. ISBN 978-0-07814000-6. {{cite book}}: Cite has empty unknown parameters: |laysummary= and |laydate= (help); Invalid |ref=harv (help)
• Richards, Julia E.; Hawley, R. Scott (12 December 2010). The Human Genome: A User's Guide. Academic Press. ISBN 978-0-12-333445-9. Retrieved 24 November 2013. {{cite book}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)

Journal articles and book chapters

• Barbujani, Guido; Colonna, Vincenza (15 September 2011). "Chapter 6: Genetic Basis of Human Biodiversity: An Update". In Zachos, Frank E.; Habel, Jan Christian (eds.). Biodiversity Hotspots: Distribution and Protection of Conservation Priority Areas. Springer. pp. 97–119. doi:10.1007/978-3-642-20992-5_6. ISBN 978-3-642-20992-5. Retrieved 23 November 2013. The massive efforts to study the human genome in detail have produced extraordinary amounts of genetic data. Although we still fail to understand the molecular bases of most complex traits, including many common diseases, we now have a clearer idea of the degree of genetic resemblance between humans and other primate species. We also know that humans are genetically very close to each other, indeed more than any other primates, that most of our genetic diversity is accounted for by individual differences within populations, and that only a small fraction of the species' genetic variance falls between populations and geographic groups thereof. {{cite book}}: Cite has empty unknown parameters: |laysummary= and |laydate= (help); Invalid |ref=harv (help)
• Barbujani, Guido; Ghirotto, S.; Tassi, F. (2013). "Nine things to remember about human genome diversity". Tissue Antigens. 82 (3): 155–164. doi:10.1111/tan.12165. ISSN 0001-2815. {{cite journal}}: Invalid |ref=harv (help)
• Cavalli-Sforza, Luigi Luca (September 2007). "Human Evolution and Its Relevance for Genetic Epidemiology". Annual Review of Genomics and Human Genetics. 8. Annual Reviews: 1–15. doi:10.1146/annurev.genom.8.080706.092403. ISBN 978-0-8243-3708-7. ISSN 1527-8204. PMID 17408354. Retrieved 23 November 2013. {{cite journal}}: Invalid |ref=harv (help); Unknown parameter |laydate= ignored (help); Unknown parameter |laysummary= ignored (help)
• Hawks, John (2013). "Significance of Neandertal and Denisovan Genomes in Human Evolution". Annual Review of Anthropology. 42. Annual Reviews: 433–449, 438. doi:10.1146/annurev-anthro-092412-155548. ISBN 978-0-8243-1942-7. ISSN 0084-6570. Retrieved 4 January 2014. The shared evolutionary history of living humans has resulted in a high relatedness among all living people, as indicated for example by the very low fixation index (F_ST) among living human populations. {{cite journal}}: Invalid |ref=harv (help)
• Johnson, Wendy; Penke, Lars; Spinath, Frank M. (2011). "Understanding Heritability: What it is and What it is Not" (PDF). European Journal of Personality. 25 (4): 287–294. doi:10.1002/per.835. ISSN 0890-2070. Archived from the original on 2011. Retrieved 15 December 2013. {{cite journal}}: Check date values in: |archivedate= (help); Invalid |ref=harv (help); Unknown parameter |deadurl= ignored (|url-status= suggested) (help)
• Lee, Sandra; Mountain, Joanna; Koenig, Barbara; Altman, Russ; Brown, Melissa; Camarillo, Albert; Cavalli-Sforza, Luca; Cho, Mildred; Eberhardt, Jennifer; Feldman, Marcus; Ford, Richard; Greely, Henry; King, Roy; Markus, Hazel; Satz, Debra; Snipp, Matthew; Steele, Claude; Underhill, Peter (2008). "The ethics of characterizing difference: guiding principles on using racial categories in human genetics" (PDF). Genome Biology. 9 (7): 404. doi:10.1186/gb-2008-9-7-404. ISSN 1465-6906. Retrieved 3 December 2013. {{cite journal}}: Invalid |ref=harv (help); Unknown parameter |displayauthors= ignored (|display-authors= suggested) (help)CS1 maint: unflagged free DOI (link)
• Novembre, John; Ramachandran, Sohini (2011). "Perspectives on Human Population Structure at the Cusp of the Sequencing Era" (PDF). Annual Review of Genomics and Human Genetics. 12: 245–274. doi:10.1146/annurev-genom-090810-183123. ISBN 978-0-8243-3712-4. ISSN 1527-8204. PMID 21801023. Archived from the original on 9 September 2011. Retrieved 23 November 2013. Surveys of population structure have been ongoing for decades, but in the past three years, single-nucleotide-polymorphism (SNP) array technology has provided unprecedented detail on human population structure at global and regional scales. These studies have confirmed well-known relationships between distantly related populations and uncovered previously unresolvable relationships among closely related human groups. {{cite journal}}: Invalid |ref=harv (help); Unknown parameter |deadurl= ignored (|url-status= suggested) (help)
• Race, Ethnicity, and Genetics Working Group (2005). "The Use of Racial, Ethnic, and Ancestral Categories in Human Genetics Research". American Journal of Human Genetics. 77 (4): 519–32. doi:10.1086/491747. PMC 1275602. PMID 16175499. Retrieved 23 September 2013. {{cite journal}}: Invalid |ref=harv (help)CS1 maint: multiple names: authors list (link)

External links

• Cultural Diversity in Healthcare Speaker Series University of Wisconsin School of Medicine and Public Health
• Cultural Diversity in Healthcare Research Symposium University of Wisconsin School of Medicine and Public Health
• News-Medical.net
• Unnatural causes, videos on how racial inequalities influence health

Governmental

• United States Office of Minority Health
• United Kingdom National Health Service - Ethnicity & Health
• Multicultural Mental Health Australia