Human genetic clustering

From Wikipedia, the free encyclopedia

Human genetic clustering is the degree to which human genetic variation can be partitioned into a small number of groups or clusters. A leading method of analysis uses mathematical cluster analysis of the degree of similarity of genetic data between individuals and groups in order to infer population structures and assign individuals to hypothesized ancestral groups. A similar analysis can be done using principal components analysis, and several recent studies deploy both methods.

Analysis of genetic clustering examines the degree to which regional groups differ genetically, the categorization of individuals into clusters, and what can be learned about human ancestry from this data. There is broad scientific agreement that a relatively small fraction of human genetic variation occurs between populations, continents, or clusters. Researchers of genetic clustering differ, however, on whether genetic variation is principally clinal or whether clusters inferred mathematically are important and scientifically useful.

Analysis of human genetic variation

Quantifying variation

One of the underlying questions regarding the distribution of human genetic diversity is related to the degree to which genes are shared between the observed clusters. It has been observed repeatedly that the majority of variation observed in the global human population is found within populations. This variation is usually calculated using Sewall Wright's fixation index (F_ST), which is an estimate of between to within group variation. The degree of human genetic variation is a little different depending upon the gene type studied, but in general it is common to claim that ~85% of genetic variation is found within groups, ~6–10% between groups within the same continent and ~6–10% is found between continental groups. Ryan Brown and George Armelagos described this as "a host of studies [that have] concluded that racial classification schemes can account for only a negligible proportion of human genetic diversity," including the studies listed in the table below.

Author(s)	Year	Title	Characteristic Studied	Proportion of Variation Within Groups (rather than among populations)
Lewontin	1972	The apportionment of human diversity	17 blood groups	85.4%
Barbujani et al.	1997	An apportionment of human DNA diversity	79 RFLP, 30 microsatellite loci	84.5%
Seielstad, Minch and Cavalli-Sforza	1998	Genetic evidence for a higher female migration rate in humans	29 autosomal microsatellite loci	97.8%
			10 Y chromosome microsatellite loci	83.5%

These average numbers, however, do not mean that every population harbors an equal amount of diversity. In fact, some human populations contain far more genetic diversity than others, which is consistent with the likely African origin of modern humans. Therefore, populations outside of Africa may have undergone serial founder effects that limited their genetic diversity.

The F_ST statistic has come under criticism by A. W. F. Edwards and Jeffrey Long and Rick Kittles. British statistician and evolutionary biologist A. W. F. Edwards faulted Lewontin's methodology for basing his conclusions on simple comparison of genes and rather on a more complex structure of gene frequencies. Long and Kittles' objection is also methodological: according to them the F_ST is based on a faulty underlying assumptions that all populations contain equally genetic diverse members and that continental groups diverged at the same time. Sarich and Miele have also argued that estimates of genetic difference between individuals of different populations understate differences between groups because they fail to take into account human diploidy.

Keith Hunley, Graciela Cabana, and Jeffrey Long created a revised statistical model to account for unequally divergent population lineages and local populations with differing degrees of diversity. Their 2015 paper applies this model to the Human Genome Diversity Project sample of 1,037 individuals in 52 populations. They found that least diverse population examined, the Surui, "harbors nearly 60% of the total species’ diversity." Long and Kittles had noted earlier that the Sokoto people of Africa contains virtually all of human genetic diversity. Their analysis also found that non-African populations are a taxonomic subgroup of African populations, that "some African populations are equally related to other African populations and to non-African populations," and that "outside of Africa, regional groupings of populations are nested inside one another, and many of them are not monophyletic."

Similarity of group members

Multiple studies since 1972 have backed up the claim that, "The average proportion of genetic differences between individuals from different human populations only slightly exceeds that between unrelated individuals from a single population."

Percentage similarity between two individuals from different clusters when 377 microsatellite markers are considered.

	Africans	Europeans	Asians
Europeans	36.5	—	—
Asians	35.5	38.3	—
Indigenous Americans	26.1	33.4	35

Edwards (2003) claims, "It is not true, as Nature claimed, that 'two random individuals from any one group are almost as different as any two random individuals from the entire world'" and Risch et al. (2002) state "Two Caucasians are more similar to each other genetically than a Caucasian and an Asian." However Bamshad et al. (2004) used the data from Rosenberg et al. (2002) to investigate the extent of genetic differences between individuals within continental groups relative to genetic differences between individuals between continental groups. They found that though these individuals could be classified very accurately to continental clusters, there was a significant degree of genetic overlap on the individual level, to the extent that, using 377 loci, individual Europeans were about 38% of the time more genetically similar to East Asians than to other Europeans.

Witherspoon et al. (2007) have argued that even when individuals can be reliably assigned to specific population groups, it may still be possible for two randomly chosen individuals from different populations/clusters to be more similar to each other than to a randomly chosen member of their own cluster, when sampling a small number of SNPs (as in the case with scientists James Watson, Craig Venter and Seong-Jin Kim). They state that using around one-thousand SNPs, individuals from different populations/clusters are never more similar, which they state some may find surprising. Witherspoon et al. conclude that "caution should be used when using geographic or genetic ancestry to make inferences about individual phenotypes".

Blood polymorphism study

A 1994 study by Cavalli-Sforza and colleagues evaluated genetic distances among 42 native populations based on 120 blood polymorphisms. The populations were grouped into nine clusters: African (sub-Saharan), Caucasoid (European), Caucasoid (extra-European), northern Mongoloid (excluding Arctic populations), northeast Asian Arctic, southern Mongoloid (mainland and insular Southeast Asia), Pacific islander, New Guinean and Australian, and American (Amerindian). Although the clusters demonstrate varying degrees of homogeneity, the nine-cluster model represents a majority (80 out of 120) of single-trait trees and is useful in demonstrating the phenetic relationship among these populations.

The greatest genetic distance between two continents is between Africa and Oceania, at 0.2470. This measure of genetic distance reflects the isolation of Australia and New Guinea since the end of the Last Glacial Maximum, when Oceania was isolated from mainland Asia due to rising sea levels. The next-largest genetic distance is between Africa and the Americas, at 0.2260. This is expected, since the longest geographic distance by land is between Africa and South America. The shortest genetic distance, 0.0155, is between European and extra-European Caucasoids. Africa is the most genetically divergent continent, with all other groups more related to each other than to sub-Saharan Africans. This is expected, according to the single-origin hypothesis. Europe has a general genetic variation about three times less than that of other continents; the genetic contribution of Asia and Africa to Europe is thought to be two-thirds and one-third, respectively.

Genetic cluster studies

Gene clusters from Rosenberg (2006) for K=7 clusters. (Cluster analysis divides a dataset into any prespecified number of clusters.) Individuals have genes from multiple clusters. The cluster prevalent only among the Kalash people (yellow) only splits off at K=7 and greater.

Genetic structure studies are carried out using statistical computer programs designed to find clusters of genetically similar individuals within a sample of individuals. Studies such as those by Risch and Rosenberg use a computer program called STRUCTURE to find human populations (gene clusters). It is a statistical program that works by placing individuals into one of an arbitrary number of clusters based on their overall genetic similarity, many possible pairs of clusters are tested per individual to generate multiple clusters. The basis for these computations are data describing a large number of single nucleotide polymorphisms (SNPs), genetic insertions and deletions (indels), microsatellite markers (or short tandem repeats, STRs) as they appear in each sampled individual. Cluster analysis divides a dataset into any prespecified number of clusters.

These clusters are based on multiple genetic markers that are often shared between different human populations even over large geographic ranges. The notion of a genetic cluster is that people within the cluster share on average similar allele frequencies to each other than to those in other clusters. (A. W. F. Edwards, 2003 but see also infobox "Multi Locus Allele Clusters") In a test of idealised populations, the computer programme STRUCTURE was found to consistently underestimate the numbers of populations in the data set when high migration rates between populations and slow mutation rates (such as single-nucleotide polymorphisms) were considered. In 2004, Lynn Jorde and Steven Wooding argued that "Analysis of many loci now yields reasonably accurate estimates of genetic similarity among individuals, rather than populations. Clustering of individuals is correlated with geographic origin or ancestry."

A number of genetic cluster studies have been conducted since 2002, including the following:

Authors	Year	Title	Sample size / number of populations sampled	Sample	Markers
Rosenberg et al.	2002	Genetic Structure of Human Populations	1056 / 52	Human Genome Diversity Project (HGDP-CEPH)	377 STRs
Serre & Pääbo	2004	Worldwide Human Relationships Inferred from Genome-Wide Patterns of Variation	89 / 15	a: HGDP	20 STRs
			90 / geographically distributed individuals	b: Jorde 1997
Rosenberg et al.	2005	Clines, Clusters, and the Effect of Study Design on the Inference of Human Population Structure	1056 / 52	Human Genome Diversity Project (HGDP-CEPH)	783 STRs + 210 indels
Li et  al.	2008	Worldwide Human Relationships Inferred from Genome-Wide Patterns of Variation	938 / 51	Human Genome Diversity Project (HGDP-CEPH)	650,000 SNPs
Tishkoff et al.	2009	The Genetic Structure and History of Africans and African Americans	~3400 / 185	HGDP-CEPH plus 133 additional African populations and Indian individuals	1327 STRs + indels
Xing et al.	2010	Toward a more uniform sampling of human genetic diversity: A survey of worldwide populations by high-density genotyping	850 / 40	HapMap plus 296 individuals	250,000 SNPs

In a 2005 paper, Rosenberg and his team acknowledged that findings of a study on human population structure are highly influenced by the way the study is designed. They reported that the number of loci, the sample size, the geographic dispersion of the samples and assumptions about allele-frequency correlation all have an effect on the outcome of the study.

In a review of studies of human genome diversity, Guido Barbujani and colleagues note that various cluster studies have identified different numbers of clusters with different boundaries. They write that discordant patterns of genetic variation and high within-population genetic diversity "make it difficult, or impossible, to define, once and for good, the main genetic clusters of humankind."

Genetic clustering was also criticized by Penn State anthropologists Kenneth Weiss and Brian Lambert. They asserted that understanding human population structure in terms of discrete genetic clusters misrepresents the path that produced diverse human populations that diverged from shared ancestors in Africa. Ironically, by ignoring the way population history actually works as one process from a common origin rather than as a string of creation events, structure analysis that seems to present variation in Darwinian evolutionary terms is fundamentally non-Darwinian."

Clusters by Rosenberg et al. (2002, 2005)

A major finding of Rosenberg and colleagues (2002) was that when five clusters were generated by the program (specified as K=5), "clusters corresponded largely to major geographic regions." Specifically, the five clusters corresponded to Africa, Europe plus the Middle East plus Central and South Asia, East Asia, Oceania, and the Americas. The study also confirmed prior analyses by showing that, "Within-population differences among individuals account for 93 to 95% of genetic variation; differences among major groups constitute only 3 to 5%."

Human population structure can be inferred from multilocus DNA sequence data (Rosenberg et al. 2002, 2005). Individuals from 52 populations were examined at 993 DNA markers. This data was used to partition individuals into K = 2, 3, 4, 5, or 6 gene clusters. In this figure, the average fractional membership of individuals from each population is represented by horizontal bars partitioned into K colored segments.

Rosenberg and colleagues (2005) have argued, based on cluster analysis, that populations do not always vary continuously and a population's genetic structure is consistent if enough genetic markers (and subjects) are included. "Examination of the relationship between genetic and geographic distance supports a view in which the clusters arise not as an artifact of the sampling scheme, but from small discontinuous jumps in genetic distance for most population pairs on opposite sides of geographic barriers, in comparison with genetic distance for pairs on the same side. Thus, analysis of the 993-locus dataset corroborates our earlier results: if enough markers are used with a sufficiently large worldwide sample, individuals can be partitioned into genetic clusters that match major geographic subdivisions of the globe, with some individuals from intermediate geographic locations having mixed membership in the clusters that correspond to neighboring regions." They also wrote, regarding a model with five clusters corresponding to Africa, Eurasia (Europe, Middle East, and Central/South Asia), East Asia, Oceania, and the Americas: "For population pairs from the same cluster, as geographic distance increases, genetic distance increases in a linear manner, consistent with a clinal population structure. However, for pairs from different clusters, genetic distance is generally larger than that between intracluster pairs that have the same geographic distance. For example, genetic distances for population pairs with one population in Eurasia and the other in East Asia are greater than those for pairs at equivalent geographic distance within Eurasia or within East Asia. Loosely speaking, it is these small discontinuous jumps in genetic distance—across oceans, the Himalayas, and the Sahara—that provide the basis for the ability of STRUCTURE to identify clusters that correspond to geographic regions".

Rosenberg stated that their findings "should not be taken as evidence of our support of any particular concept of biological race (...). Genetic differences among human populations derive mainly from gradations in allele frequencies rather than from distinctive 'diagnostic' genotypes." The study's overall results confirmed that genetic difference within populations is between 93 and 95%. Only 5% of genetic variation is found between groups.

Criticism

The Rosenberg study has been criticised on several grounds.

The existence of allelic clines and the observation that the bulk of human variation is continuously distributed, has led some scientists to conclude that any categorization schema attempting to partition that variation meaningfully will necessarily create artificial truncations. (Kittles & Weiss 2003). It is for this reason, Reanne Frank argues, that attempts to allocate individuals into ancestry groupings based on genetic information have yielded varying results that are highly dependent on methodological design. Serre and Pääbo (2004) make a similar claim:

The absence of strong continental clustering in the human gene pool is of practical importance. It has recently been claimed that "the greatest genetic structure that exists in the human population occurs at the racial level" (Risch et al. 2002). Our results show that this is not the case, and we see no reason to assume that "races" represent any units of relevance for understanding human genetic history.

In a response to Serre and Pääbo (2004), Rosenberg et al. (2005) maintain that their clustering analysis is robust. Additionally, they agree with Serre and Pääbo that membership of multiple clusters can be interpreted as evidence for clinality (isolation by distance), though they also comment that this may also be due to admixture between neighbouring groups (small island model). Thirdly they comment that evidence of clusterdness is not evidence for any concepts of "biological race".

Clustering does not particularly correspond to continental divisions. Depending on the parameters given to their analytical program, Rosenberg and Pritchard were able to construct between divisions of between 4 and 20 clusters of the genomes studied, although they excluded analysis with more than 6 clusters from their published article. Probability values for various cluster configurations varied widely, with the single most likely configuration coming with 16 clusters although other 16-cluster configurations had low probabilities. Overall, "there is no clear evidence that K=6 was the best estimate" according to geneticist Deborah Bolnick (2008:76-77). The number of genetic clusters used in the study was arbitrarily chosen. Although the original research used different number of clusters, the published study emphasized six genetic clusters. The number of genetic clusters is determined by the user of the computer software conducting the study. Rosenberg later revealed that his team used pre-conceived numbers of genetic clusters from six to twenty "but did not publish those results because Structure [the computer program used] identified multiple ways to divide the sampled individuals". Dorothy Roberts, a law professor, asserts that "there is nothing in the team's findings that suggests that six clusters represent human population structure better than ten, or fifteen, or twenty." When instructed to find two clusters, the program identified two populations anchored around by Africa and by the Americas. In the case of six clusters, the entirety of Kalesh people, an ethnic group living in Northern Pakistan, was added to the previous five.

Commenting on Rosenberg's study, law professor Dorothy Roberts wrote that "the study actually showed that there are many ways to slice the expansive range of human genetic variation.

Clusters in Tishkoff et al. 2009

Sarah A. Tishkoff and colleagues analyzed a global sample consisting of 952 individuals from the HGDP-CEPH survey, 2432 Africans from 113 ethnic groups, 98 African Americans, 21 Yemenites, 432 individuals of Indian descent, and 10 Native Australians. A global STRUCTURE analysis of these individuals examined 1327 polymorphic markers, including of 848 STRs, 476 indels, and 3 SNPs. The authors reported cluster results for K=2 to K=14. Within Africa, six ancestral clusters were inferred through Bayesian analysis, which were closely linked with ethnolinguistic heritage.  Bantu populations grouped with other Niger-Congo-speaking populations from West Africa. African Americans largely belonged to this Niger-Congo cluster, but also had significant European ancestry. Nilo-Saharan populations formed their own cluster. Chadic populations clustered with the Nilo-Saharan groups, suggesting that most present-day Chadic speakers originally spoke languages from the Nilo-Saharan family and later adopted Afro-Asiatic languages. Nilotic populations from the African Great Lakes largely belonged to this Nilo-Saharan cluster too, but also had some Afro-Asiatic influence due to assimilation of Cushitic groups over the last 3,000 years. Khoisan populations formed their own cluster, which grouped closest with the Pygmy cluster. The Cape Coloured showed assignments from the Khoisan, European and other clusters due to the population's mixed heritage. The Hadza and Sandawe populations formed their own cluster. An Afro-Asiatic cluster was also discerned, with the Afro-Asiatic speakers from North Africa and the Horn of Africa forming a contiguous group. Afro-Asiatic speakers in the Great Lakes region largely belonged to this Afro-Asiatic cluster as well, but also had some Bantu and Nilotic influence due to assimilation of adjacent groups over the last 3,000 years. The remaining inferred ancestral clusters were associated with European, Middle Eastern, Oceanian, Indian, Native American and East Asian populations.

Examining effects of sampling in Xing et al. 2010

Jinchuan Xing and colleagues used an alternate dataset of human genotypes including HapMap samples and their own samples (296 new individuals from 13 populations), for a total of 40 populations distributed roughly evenly across the Earth's land surface. They found that the alternate sampling reduced the F_ST estimate of inter-population differences from 0.18 to 0.11, suggesting that the higher number may be an artifact of uneven sampling. They conducted a cluster analysis using the ADMIXTURE program and found that "genetic diversity is distributed in a more clinal pattern when more geographically intermediate populations are sampled."

HUGO Asian study

A study by the HUGO Pan-Asian SNP Consortium in 2009 using the similar principal components analysis found that East Asian and South-East Asian populations clustered together, and suggested a common origin for these populations. At the same time they observed a broad discontinuity between this cluster and South Asia, commenting "most of the Indian populations showed evidence of shared ancestry with European populations". It was noted that "genetic ancestry is strongly correlated with linguistic affiliations as well as geography".

Controversy of genetic clustering and associations with "race"

Studies of clustering reopened a debate on the scientific reality of race, or lack thereof. In the late 1990s Harvard evolutionary geneticist Richard Lewontin stated that "no justification can be offered for continuing the biological concept of race. (...) Genetic data shows that no matter how racial groups are defined, two people from the same racial group are about as different from each other as two people from any two different racial groups. This view has been affirmed by numerous authors and the American Association of Physical Anthropologists since. A.W.F. Edwards as well as Rick Kittles and Jeffrey Long have criticized Lewontin's methodology, with Long noting that there are more similarities between humans and chimpanzees than differences, and more genetic variation within chimps and humans than between them. Edwards also charged that Lewontin made an "unjustified assault on human classification, which he deplored for social reasons". In their 2015 article, Keith Hunley, Graciela Cabana, and Jeffrey Long recalculate the apportionment of human diversity using a more complex model than Lewontin and his successors. They conclude: "In sum, we concur with Lewontin’s conclusion that Western-based racial classifications have no taxonomic significance, and we hope that this research, which takes into account our current understanding of the structure of human diversity, places his seminal finding on firmer evolutionary footing."

Genetic clustering studies, and particularly the five-cluster result published by Rosenberg's team in 2002, have been interpreted by journalist Nicholas Wade, evolutionary biologist Armand Marie Leroi, and others as demonstrating the biological reality of race. For Leroi, "Race is merely a shorthand that enables us to speak sensibly, though with no great precision, about genetic rather than cultural or political differences." He states that, "One could sort the world's population into 10, 100, perhaps 1,000 groups", and describes Europeans, Basques, Andaman Islanders, Ibos, and Castillians each as a "race". In response to Leroi's claims, the Social Science Research Council convened a panel of experts to discuss race and genomics online. In their 2002 and 2005 papers, Rosenberg and colleagues disagree that their data implies the biological reality of race.

In 2006, Lewontin wrote that any genetic study requires some priori concept of race or ethnicity in order to package human genetic diversity into a defined, limited number of biological groupings. Informed by genetics, zoologists have long discarded the concept of race for dividing groups of non-human animal populations within a species. Defined on varying criteria, in the same species a widely varying number of races could be distinguished. Lewontin notes that genetic testing revealed that "because so many of these races turned out to be based on only one or two genes, two animals born in the same litter could belong to different 'races'".

Studies that seek to find genetic clusters are only as informative as the populations they sample. For example, Risch and Burchard relied on two or three local populations from five continents, which together were supposed to represent the entire human race. Another genetic clustering study used three sub-Saharan population groups to represent Africa; Chinese, Japanese, and Cambodian samples for East Asia; Northern European and Northern Italian samples to represent "Caucasians". Entire regions, subcontinents, and landmasses are left out of many studies. Furthermore, social geographical categories such "East Asia" and "Caucasians" were not defined. "A handful of ethnic groups to symbolize an entire continent mimic a basic tenet of racial thinking: that because races are composed of uniform individuals, anyone can represent the whole group" notes Roberts.

The model of Big Few fails when including overlooked geographical regions such as India. The 2003 study which examined fifty-eight genetic markers found that Indian populations owe their ancestral lineages to Africa, Central Asia, Europe, and southern China. Reardon, from Princeton University, asserts that flawed sampling methods are built into many genetic research projects. The Human Genome Diversity Project (HGDP) relied on samples which were assumed to be geographically separate and isolated. The relatively small sample sizes of indigenous populations for the HGDP do not represent the human species' genetic diversity, nor do they portray migrations and mixing population groups which has been happening since prehistoric times. Geographic areas such as the Balkans, the Middle East, North and East Africa, and Spain are seldom included in genetic studies. East and North African indigenous populations, for example, are never selected to represent Africa because they do not fit the profile of "black" Africa. The sampled indigenous populations of the HGDP are assumed to be "pure"; the law professor Roberts claims that "their unusual purity is all the more reason they cannot stand in for all the other populations of the world that marked by intermixture from migration, commerce, and conquest."

King and Motulsky, in a 2002 Science article, state that "While the computer-generated findings from all of these studies offer greater insight into the genetic unity and diversity of the human species, as well as its ancient migratory history, none support dividing the species into discrete, genetically determined racial categories". Cavalli-Sforza asserts that classifying clusters as races would be a "futile exercise" because "every level of clustering would determine a different population and there is no biological reason to prefer a particular one". Bamshad, in 2004 paper published in Nature, asserts that a more accurate study of human genetic variation would use an objective sampling method, which would choose populations randomly and systematically across the world, including those populations which are characterized by historical intermingling, instead of cherry-picking population samples which fit a priori concepts of racial classification. Roberts states that "if research collected DNA samples continuously from region to region throughout the world, they would find it impossible to infer neat boundaries between large geographical groups."

Anthropologists such as C. Loring Brace, philosophers Jonathan Kaplan and Rasmus Winther, and geneticist Joseph Graves, have argued that while it is certainly possible to find biological and genetic variation that corresponds roughly to the groupings normally defined as "continental races", this is true for almost all geographically distinct populations. The cluster structure of the genetic data is therefore dependent on the initial hypotheses of the researcher and the populations sampled. When one samples continental groups the clusters become continental; if one had chosen other sampling patterns the clustering would be different. Weiss and Fullerton have noted that if one sampled only Icelanders, Mayans and Maoris, three distinct clusters would form and all other populations could be described as being clinally composed of admixtures of Maori, Icelandic and Mayan genetic materials. Kaplan and Winther therefore argue that seen in this way both Lewontin and Edwards are right in their arguments. They conclude that while racial groups are characterized by different allele frequencies, this does not mean that racial classification is a natural taxonomy of the human species, because multiple other genetic patterns can be found in human populations that cross-cut racial distinctions. Moreover, the genomic data under-determines whether one wishes to see subdivisions (i.e., splitters) or a continuum (i.e., lumpers). Under Kaplan and Winther's view, racial groupings are objective social constructions (see Mills 1998 ) that have conventional biological reality only insofar as the categories are chosen and constructed for pragmatic scientific reasons.

Commercial ancestry testing and individual ancestry

Commercial ancestry testing companies, who use genetic clustering data, have been also heavily criticized. Limitations of genetic clustering are intensified when inferred population structure is applied to individual ancestry. The type of statistical analysis conducted by scientists translates poorly into individual ancestry because they are looking at difference in frequencies, not absolute differences between groups. Commercial genetic genealogy companies are guilty of what Pillar Ossorio calls the "tendency to transform statistical claims into categorical ones". Not just individuals of the same local ethnic group, but two siblings may end up beings as members of different continental groups or "races" depending on the alleles they inherit.

Many commercial companies use data from the International HapMap Project (HapMap)'s initial phrase, where population samples were collected from four ethnic groups in the world: Han Chinese, Japanese, Yoruba Nigerian, and Utah residents of Northern European ancestry. If a person has ancestry from a region where the computer program does not have samples, it will compensate with the closest sample that may have nothing to do with the customer's actual ancestry: "Consider a genetic ancestry testing performed on an individual we will call Joe, whose eight great-grandparents were from southern Europe. The HapMap populations are used as references for testing Joe's genetic ancestry. The HapMap's European samples consist of "northern" Europeans. In regions of Joe's genome that vary between northern and southern Europe (such regions might include the lactase gene), the genetic ancestry test is using the HapMap reference population is likely to incorrectly assign the ancestry of that portion of the genome to a non-European population because that genomic region will appear to be more similar to the HapMap's Yoruba or Han Chinese samples than to Northern European samples. Likewise, a person having Western European and Western African ancestries may have ancestors from Western Europe and West Africa, or instead be assigned to East Africa where various ancestries can be found. "Telling customers that they are a composite of several anthropological groupings reinforces three central myths about race: that there are pure races, that each race contains people who are fundamentally the same and fundamentally different from people in other races, and that races can be biologically demarcated." Many companies base their findings on inadequate and unscientific sampling methods. Researchers have never sampled the world's populations in a systematic and random fashion.

Geographical and continental groupings

Roberts argues against the use of broad geographical or continental groupings: "molecular geneticists routinely refer to African ancestry as if everyone on the continent is more similar to each other than they are to people of other continents, who may be closer both geographically and genetically. Ethiopians have closer genetic affinity with Armenians than with Bantu populations. Similarly, Somalis are genetically more similar to Gulf Arab populations than to other populations in Africa. Braun and Hammonds (2008) asserts that the misperception of continents as natural population groupings is rooted in the assumption that populations are natural, isolated, and static. Populations came to be seen as "bounded units amenable to scientific sampling, analysis, and classification". Human beings are not naturally organized into definable, genetically cohesive populations.

Race and health in the United States

From Wikipedia, the free encyclopedia

Research on race and health in the United States shows many health disparities between the different racial/ethnic groups. The possible causes, such as genetics, socioeconomic factors, and racism, continue to be debated. Different health problems, in both mental and physical health, are present in all races but are not always equally treated. Health care professionals show "implicit bias" in the way that they treat patients. In America, racism consists of stereotypes mainly that are political and economic. While this article focuses mainly on racism towards African Americans in the health field, it covers various other backgrounds including racism towards Native Americans, Asian Americans, and others while drawing comparisons between various incomes and ages. Race and health in the United States is a topic that has been researched many times over the years. There are various specific diseases that are more present among various races as well as different means for life expectancy.

Background

Health ratings in US by race

In biomedical research conducted in the U.S., the 2000 US census definition of race is often applied. According to the Census Bureau in 2000, race refers to one's self-identification with a certain racial group. The Bureau also specifies that race is a social concept, and has no relation to science or anthropology. This grouping recognizes five races: black or African American, White (European American), Asian, native Hawaiian or other Pacific Islander, and American Indian or Alaska native. According to the Journal of Behavioral Medicine, America continues to become more diverse. Although the population is increasingly less homogeneous, healthcare is unequally distributed among these five racial groups. The 2000 U.S. Census further specifies the amount of Americans who identified with each racial group; in 2000, 34.6 million identified as African American, 10.2 million as Asian American, and 35.3 million as Hispanic or Latino. It is important to consider that the 2000 U.S. Census definition is inconsistently applied across the range of studies that address race as a medical factor, making assessment of the utility of racial categorization in medicine more difficult. However, this definition is inconsistently applied across the range of studies that address race as a medical factor, making assessment of the utility of racial categorization in medicine more difficult. Bias stems from racism, creating stress on the race that is being discriminated against, leading to issues with a person's bodily and mental health. Repeated stress overtime on one’s body can lead to health problems such as depression, anxiety, insomnia, heart disease, skin rashes, and gastrointestinal problems, which are also more likely to develop in children. Racism has many detrimental effects on the health of Americans across the entire country, arising mainly from limited access to healthcare, mental health resources, and support. There are a wide range of patterns of health disparities that are caused by different levels of income across ethnic groups. Anthony Ong, a professor at Cornell University’s College of Human Ecology conveyed that this regular treatment of discrimination and backlash can have detrimental effects to a person’s self-esteem and can take opportunities of individuals. It can also cause individuals from being able to receive a full nights sleep.

Mental Health

Stress can be derived from many individualistic factors or experiences,has multiple effects on health. Stress is also associated with chronic diseases. Stress that is derived from racism has specific contextual factors, which adds a daily burden to African-Americans and other demographic groups that are discriminated against. These demographic groups do not often realize that these stressors may be contributing to the state of their mental health. Groups of people are also affected in ways that may not be outward acts of racism by another person, but through education, economics, the justice system, and largely through law enforcement. It is also possible that people who hold racist ideals have mental health problems as well, such as self-centeredness, inability to empathize, and paranoia over groups of people they are discriminating against. Individuals can develop complexes about ethnic groups and races, automatically displaying emotions without learning about the people themselves, and will cut off all friendliness to them.

Life expectancy

The twentieth century witnessed a great expansion of the upper bounds of the human life span. At the beginning of the century, average life expectancy in the United States was 47 years. By century's end, the average life expectancy had risen to over 70 years, and it was not unusual for Americans to exceed 80 years of age. However, although longevity in the U.S. population has increased substantially, race disparities in longevity have been persistent. African American life expectancy at birth is persistently five to seven years lower than European Americans.

The vast majority of studies focus on the black-white contrast, but a rapidly growing literature describes variations in health status among America's increasingly diverse racial populations. Today, Asian Americans live the longest (87.1 years), followed by Latinos (83.3 years), whites (78.9 years), Native Americans (76.9 years), and African Americans (75.4 years). Where people live, combined with race and income, play a huge role in whether they may die young. A 2001 study found large racial differences exist in healthy life expectancy at lower levels of education.

A study by Jack M. Guralnik, Kenneth C. Land, Dan Blazer, Gerda G. Fillenbaum, and Laurence G. Branch found that education had a substantially stronger relation to total life expectancy and active life expectancy than did race. Still, sixty-five-year-old black men had a lower total life expectancy (11.4 years) and active life expectancy (10 years) than white men (total life expectancy, 12.6 years; active life expectancy, 11.2 years) The differences were reduced when the data were controlled for education.

During the 20th century, the difference in life expectancy between black and white men in the United States did not decline.

Socioeconomic and regional factors

A study by Christopher Murray contends the differences are so stark it is "as if there are eight separate Americas instead of one." Leading the nation in longevity are Asian-American women who live in Bergen County, N.J., and typically reach their 91st birthdays, concluded Murray's county-by-county analysis. On the opposite extreme are Native American men in swaths of South Dakota, who die around 58.

• Asian-Americans, average per capita income of $21,566, have a life expectancy of 84.9 years (However Filipino Americans are slightly lower at 81.5 years);
• Northern low-income rural Whites, $17,758, 79 years;
• Middle America (mostly White), $24,640, 77.9 years;
• Low-income Whites in Appalachia, Mississippi Valley, and Texas $16,390, 75 years;
• Western Native Americans, $10,029, 72.7 years;
• Black Middle America, $15,412, 72.9 years;
• Southern low-income rural Blacks, $10,463, 71.2 years;
• High-risk urban Blacks, $14,800, 71.1 years.

The risks for many diseases are elevated for socially, economically, and politically disadvantaged groups in the United States, suggesting that socioeconomic inequities are the root causes of most of the differences. However, other dimensions of inequality than those reflected by socioeconomic status also affect racial disparities in health, because other forms of social adversity are also important factors.

Specific diseases

Health disparities are well documented in minority populations such as African Americans, Native Americans, and Latinos. When compared to European Americans and Asian Americans, these minority groups have higher incidence of chronic diseases, higher mortality, and poorer health outcomes.

Minorities also have higher rates of cardiovascular disease, HIV/AIDS, and infant mortality than whites. U.S. ethnic groups can exhibit substantial average differences in disease incidence, disease severity, disease progression, and response to treatment:

• African Americans have higher rates of mortality than does any other racial or ethnic group for 8 of the top 10 causes of death. The cancer incidence rate among African Americans is 10% higher than among European Americans;
• U.S. Latinos have higher rates of death from diabetes, liver disease, and infectious diseases than do non-Latinos;
• Adult African Americans and Latinos have approximately twice the risk as European Americans of developing diabetes;
• Asian Americans are 60% more likely to being at risk of developing diabetes in comparison to European Americans and are more likely to develop the disease at lower BMIs and lower body weights. South Asians are especially more likely to developing diabetes as it is estimated South Asians are four times more likely to developing the disease in comparison to European Americans;
• Native Americans suffer from higher rates of diabetes, tuberculosis, pneumonia, influenza, and alcoholism than does the rest of the U.S. population;
• European Americans die more often from heart disease and cancer than do Native Americans, Asian Americans, or Hispanics;
• White Americans have far higher incident rates of melanoma of the skin or skin cancer than any other race/ethnicity in the US. In 2007 incident rates among white American males were approximately 25/100,000 people, whereas the next highest group (Hispanics and natives) has an incidence rate of approximately 5/100,000 people;
• Asian Americans are at higher risk for hepatitis B, liver cancer, tuberculosis, and lung cancer. The subgroup of Filipino Americans suffer health risks similar to that of African Americans and European Americans combined;
• According to the NIH, African Americans are more likely to develop diabetes. Usually, type 2 diabetes is more prominent in middle-aged adults. Being obese or having a family history can also affect this. Over the past 30 years in the US, "black adults are nearly twice as likely as white adults to develop type 2 diabetes." Besides this difference just being between black and white adults, we see the greatest margin of comparison between black and white women;
• Sickle cell disease is more susceptible to be found in those of descent from places such as those in the Mediterranean, Italy, Turkey, and Greece, as well as Africa and regions of South and Central America. The disease affects how oxygen is delivered to the red blood cells and is often diagnosed at a young age, discovered through a diagnosis of anemia.

Women and Infants

African American women are three to four times more likely to die in childbirth than white women, while their babies are twice as likely to die than white babies, even when controlled for many factors such as education, income, and health. “White racism” is the highest cause of unrest in communities, pushing them further apart, and causing more black women and infants to die because of it. Racism in education has decreased significantly over the past century, however this does not help increases in income for blacks, and increased incomes don’t provide better health opportunities, especially for mothers and infants. Higher education and income levels for black mothers does not effect this mortality rate. There are also higher chances that a complication will occur during birth. The ‘toxin’ of these rates is racism, which has created a toxic environment for minority groups to live in with multiple stressors that effect health.

African-Americans

History

Disparities in health and life span among blacks and whites in the US have existed since before the period of slavery. David R. Williams and Chiquita Collins write that, although racial taxonomies are socially constructed and arbitrary, race is still one of the major bases of division in American life. Throughout US history racial disparities in health have been pervasive. In a 2001 paper, Williams and Collins also argued that, although it is no longer being legally enforced, racial segregation is still one of the primary causes of racial disparities in health because it determines socioeconomic status by limiting access to education and employment opportunities. Clayton and Byrd write that there have been two periods of health reform specifically addressing the correction of race-based health disparities. The first period (1865–1872) was linked to Freedmen's Bureau legislation and the second (1965–1975) was a part of the Civil Rights Movement. Both had dramatic and positive effects on black health status and outcome, but were discontinued. Even though African-American health status and outcome is slowly improving, black health has generally stagnated or deteriorated compared to whites since 1980.

Demographic changes can have broad effects on the health of ethnic groups. Cities in the United States have undergone major social transitions during the 1970s 1980s and 1990s. Notable factors in these shifts have been sustained rates of black poverty and intensified racial segregation, often as a result of redlining. Indications of the effect of these social forces on black-white differentials in health status have begun to surface in the research literature.

Race has played a decisive role in shaping systems of medical care in the United States. The divided health system persists, in spite of federal efforts to end segregation, health care remains, at best widely segregated both exacerbating and distorting racial disparities. Furthermore, the risks for many diseases are elevated for socially, economically, and politically disadvantaged groups in the United States, suggesting to some that environmental factors and not genetics are the causes of most of the differences.

Racism

Racial differences in health often persist even at equivalent socioeconomic levels. Individual and institutional discrimination, along with the stigma of inferiority, can adversely affect health. Racism can also directly affect health in multiple ways. Residence in poor neighborhoods, racial bias in medical care, the stress of experiences of discrimination and the acceptance of the societal stigma of inferiority can have deleterious consequences for health. Racism is a key determinant of socioeconomic status (SES) in the United States, and SES, in turn, is a fundamental cause of racial inequities in health. Using The Schedule of Racist Events (SRE), an 18-item self-report inventory that assesses the frequency of racist discrimination. Hope Landrine and Elizabeth A. Klonoff found that racist discrimination was frequent in the lives of African Americans and is strongly correlated to psychiatric symptoms.

A study on racist events in the lives of African American women found that lifetime racism was positively correlated to lifetime history of both physical disease and frequency of recent common colds. These relationships were largely unaccounted for by other variables. Demographic variables such as income and education were not related to experiences of racism. The results suggest that racism can be detrimental to African American's well being. The physiological stress caused by racism has been documented in studies by Claude Steele, Joshua Aronson, and Steven Spencer on what they term "stereotype threat."

Kennedy et al. found that both measures of collective disrespect were strongly correlated with black mortality (r = 0.53 to 0.56), as well as with white mortality (r = 0.48 to 0.54). A 1 percent increase in the prevalence of those who believed that blacks lacked innate ability was associated with an increase in age-adjusted black mortality rate of 359.8 per 100,000 (95% confidence interval: 187.5 to 532.1 deaths per 100,000). These data suggest that racism, measured as an ecologic characteristic, is associated with higher mortality in both blacks and whites.

Princeton Survey Research Associates found that in 1999 most whites were unaware that race and ethnicity may affect the quality and ease of access to health care.

Inequalities in health care

There is a great deal of research into inequalities in health care. In 2003, the Institute of Medicine released a report showing that race and ethnicity were significantly associated with the quality of healthcare received, even after controlling for socioeconomic factors such as access to care. In some cases these inequalities are a result of income and a lack of health insurance, a barrier to receiving services. Almost two-thirds (62 percent) of Hispanic adults aged 19 to 64 (15 million people) were uninsured at some point during the past year, a rate more than triple that of working-age white adults (20 percent). One-third of working-age black adults (more than 6 million people) were also uninsured or experienced a gap in coverage during the year. Blacks had the most problems with medical debt, with 61 percent of uninsured black adults reporting medical bill or debt problems, vs. 56 percent of whites and 35 percent of Hispanics.

Compared with white women, black women are twice as likely and Hispanic women are nearly three times as likely to be uninsured. However, a survey conducted in 2009, which examined whether patient race influences physician's prescribing, found that racial differences in outpatient prescribing patterns for hypertension, hypercholesterolemia, and diabetes are likely attributable to factors other than prescribing decisions based on patient race. Medications were recommended at comparable rates for hypercholesterolemia, hypertension and diabetes between Caucasians and African Americans.

It has been argued that other cases inequalities in health care reflect a systemic bias in the way medical procedures and treatments are prescribed for different ethnic groups. Raj Bhopal writes that the history of racism in science and medicine shows that people and institutions behave according to the ethos of their times and warns of dangers to avoid in the future. Nancy Krieger contended that much modern research supported the assumptions needed to justify racism. Racism underlies unexplained inequities in health care, including treatment for heart disease, renal failure, bladder cancer, and pneumonia. Raj Bhopal writes that these inequalities have been documented in numerous studies. The consistent and repeated findings that black Americans receive less health care than white Americans—particularly where this involves expensive new technology—is an indictment of American health care.

The infant mortality rate for African Americans is approximately twice the rate for European Americans, but, in a study that looked at members of these two groups who belonged to the military and received care through the same medical system, their infant mortality rates were essentially equivalent. Recently a study was conducted by the KFF, the Henry J Kaiser Family Foundation, in order to learn more about the infant mortality rate throughout the United States. All fifty states were surveyed. Different distributions of racial categories used in the study includes, "Non-Hispanic White, Non-Hispanic Black, American Indian or Alaska Native, Asian or Pacific Islander, or Hispanic". The infant mortality rate was compiled by the number of infant deaths per one thousand live births. In 2015, on an average nationwide, the United States reported that for Non-Hispanic white had a infant mortality rate of NSD meaning there as not enough sufficient data, Non-Hispanic black's rate was 11.3, Indian or Alaska Native's was 8.3, Pacific Islander was 4.2, and the infant mortality rate on average for Hispanic was 5.0.

Recent immigrants to the United States from Mexico have better indicators on some measures of health than do Mexican Americans who are more assimilated into American culture. Diabetes and obesity are more common among Native Americans living on U.S. reservations than among those living outside reservations. The number of Native Americans diagnosed increased by 29% just between the years of 1990 and 1997. The prevalence of this among women and men shows that women more often have diabetes than men, especially in communities of Native American people.

A report from Wisconsin’s Department of Health and Family Services showed that while black women are more likely to die from breast cancer, white women are more likely to be diagnosed with breast cancer. Even after diagnosis, black women are less likely to get treatment compared to white women. University of Wisconsin African-American studies Professor Michael Thornton said the report’s results show racism still exists today. "There’s a lot of research that suggests that who gets taken seriously in hospitals and doctors’ offices is related to race and gender," Thornton said. "It’s related to the fact that many black women are less likely to be taken seriously compared to the white women when they go in for certain illnesses."

Krieger writes that given growing appreciation of how race is a social, not biological, construct, some epidemiologists are proposing that studies omit data on "race" and instead collect better socioeconomic data. Krieger writes that this suggestion ignores a growing body of evidence on how noneconomic as well as economic aspects of racial discrimination are embodied and harm health across the lifecourse. Gilbert C. Gee's study A Multilevel Analysis of the Relationship Between Institutional and Individual Racial Discrimination and Health Status found that individual (self-perceived) and institutional (segregation and redlining) racial discrimination is associated with poor health status among members of an ethnic group.

Cardiovascular disease

Research has explored the effect of encounters with racism or discrimination on physiological activity. Most of the research has focused on traits that cause exaggerated responses, such as neuroticism, strong racial identification, or hostility. Several studies suggest that higher blood pressure levels are associated with a tendency not to downplay racist and discriminatory incidents, or that directly addressing or challenging unfair situations reduces blood pressure. Personal experiences of racist behaviors increase stress and blood pressure.

Although the relationship racism and health is unclear and findings have been inconsistent, three likely mechanisms for cardiovascular damage have been identified:

• Institutional racism leads to limited opportunities for socioeconomic mobility, differential access to goods and resources, and poor living conditions.
• Personal experiences of racism acts as a stressor and can induce psychophysiological reactions that negatively affect cardiovascular health.
• Negative self-evaluations and accepting negative cultural stereotypes as true (internalized racism) can harm cardiovascular health.

Fear of racism

It has been argued that while actual racism continues to harm health, fear of racism, due to historical precedents, can also cause some minority populations to avoid seeking medical help. For example, a 2003 study found that a large percentage of respondents perceived discrimination targeted at African American women in the area of reproductive health. Likewise beliefs such as "The government is trying to limit the Black population by encouraging the use of condoms" have also been studied as possible explanations for the different attitudes of whites and blacks towards efforts to prevent the spread of HIV/AIDS.

Infamous examples of real racism in the past, such as the Tuskegee Syphilis Study (1932–1972), have injured the level of trust in the Black community towards public health efforts. The Tuskegee study deliberately left Black men diagnosed with syphilis untreated for 40 years. It was the longest nontherapeutic experiment on human beings in medical history. The AIDS epidemic has exposed the Tuskegee study as a historical marker for the legitimate discontent of Blacks with the public health system. The false belief that AIDS is a form of genocide is rooted in recent experiences of real racism. These theories range from the belief that the government promotes drug abuse in Black communities to the belief that HIV is a manmade weapon of racial warfare. Researchers in public health hope that open and honest conversations about racism in the past can help rebuild trust and improve the health of people in these communities.

Environmental racism

Environmental racism is the intentional or unintentional targeting of minority communities for the siting of polluting industries such as toxic waste disposal, through the race-based differential enforcement of environmental rules and regulations and exclusion of people of color from public and private boards and regulatory bodies, resulting in greater exposure of the community to pollution. RD Bullard writes that a growing body of evidence reveals that people of color and low-income persons have borne greater environmental and health risks than the society at large in their neighbourhoods, workplaces and playgrounds.

Environmental racism stems from the environmental movement of the 1960s and 1970s, which focused on environmental reform and wildlife preservation and protection, and was led primarily by the middle class. The early environmental movement largely ignored the plight of poor people and people of color who, even in the mid-20th century, were increasingly exposed to environmental hazards.

Policies related to redlining and urban decay can also acts as a form of environmental racism, and in turn affect public health. Urban minority communities may face environmental racism in the form of parks that are smaller, less accessible and of poorer quality than those in more affluent or white areas in some cities. This may have an indirect affect health since young people have fewer places to play and adults have fewer opportunities for exercise.

Although impoverished or underdeveloped communities are at greater risk of contracting illnesses from public areas and disposal sites, they are also less likely to be located near a distinguished hospital or treatment center. Hospitals relocate to wealthier areas where the majority of patients are privately insured, thus reducing the number of low-income patients. Whereas hospitals were previously established in the areas with the greatest need, most are now focused on economic gain from private insurance companies, and are threatened by Medicare funding cuts.

Robert Wallace writes that the pattern of the AIDS outbreak during the 80s was affected by the outcomes of a program of 'planned shrinkage' directed in African-American and Hispanic communities, and implemented through systematic denial of municipal services, particularly fire extinguishment resources, essential for maintaining urban levels of population density and ensuring community stability. Institutionalized racism affects general health care as well as the quality of AIDS health intervention and services in minority communities. The overrepresentation of minorities in various disease categories, including AIDS, is partially related to environmental racism. The national response to the AIDS epidemic in minority communities was slow during the 80s and 90s showing an insensitivity to ethnic diversity in prevention efforts and AIDS health services.

Institutionalized racism

A major downfall of the U.S. healthcare system is the unconscious racial biases held by many white American doctors, often resulting in decreased quality of care for African American patients. One such example is the discrepancy in cardiovascular surgical procedures between white and black patients. Compared to their white counterparts, black patients are less likely to receive necessary coronary bypass surgeries and lipid-lowering medications upon discharge from the hospital. This means that black patients leave treatment centers with a significantly different health outcome.
One potential cause of this discrepancy in treatment is the systematic racism present in the medical field that targets the work of African American scientists. Research shows that doctors and scientists of color are significantly underfunded in the medical community, and are less likely than their white colleagues to win research awards from the National Institute of Health (NIH). Since patients of color are often treated by white doctors, miscommunication is common; research shows that many Americans feel their doctors do not listen to their questions or concerns, or are too uncomfortable to ask certain medical questions.

Segregation

Some researchers suggest that racial segregation may lead to disparities in health and mortality. Thomas LaVeis (1989; 1993) tested the hypothesis that segregation would aid in explaining race differences in infant mortality rates across cities. Analyzing 176 large and midsized cities, LaVeist found support for the hypothesis. Since LaVeist's studies, segregation has received increased attention as a determinant of race disparities in mortality. Studies have shown that mortality rates for male and female African Americans are lower in areas with lower levels of residential segregation. Mortality for male and female European Americans was not associated in either direction with residential segregation.

In a study by Sharon A. Jackson, Roger T. Anderson, Norman J. Johnson and Paul D. Sorlie the researchers found that, after adjustment for family income, mortality risk increased with increasing minority residential segregation among Blacks aged 25 to 44 years and non-Blacks aged 45 to 64 years. In most age/race/gender groups, the highest and lowest mortality risks occurred in the highest and lowest categories of residential segregation, respectively. These results suggest that minority residential segregation may influence mortality risk and underscore the traditional emphasis on the social underpinnings of disease and death.

Rates of heart disease among African Americans are associated with the segregation patterns in the neighborhoods where they live (Fang et al. 1998). Stephanie A. Bond Huie writes that neighborhoods affect health and mortality outcomes primarily in an indirect fashion through environmental factors such as smoking, diet, exercise, stress, and access to health insurance and medical providers. Moreover, segregation strongly influences premature mortality in the US.

Racism towards doctors and health care professionals

Many healthcare professionals have experienced hate and racist remarks towards them at work. Whether it be at a hospital, a walk-in clinic, or a family doctor's office, people are hit with bias based comments concerning "general bias, ethnicity / national origin, race, age, gender, accent, religion, political views, weight, medical education from outside the US, sexual orientation, and more". This study conducted by WebMD and Medscape features the races of "African American/Black, Asian, Caucasian, and Hispanic"  Training for doctors to handle this type of prejudice at their work is very low.

Homicide

Homicide plays a significant role in the racial gap in life expectancy. In 2008, homicide accounted for 19% of the gap among black men, though it did not play a significant role in the decline in the gap from 2003 to 2008. A report from the U.S. Department of Justice states "In 2005, homicide victimization rates for blacks were 6 times higher than the rates for whites" and "94% of black victims were killed by blacks." Research by Robert J. Sampson indicates that the high degree of residential segregation in African American neighborhoods is responsible for the high homicide rate among African Americans.

Trends

Based on data for 1945 to 1999, forecasts for relative black:white age-adjusted, all-cause mortality and white:black life expectancy at birth showed trends toward increasing disparities. From 1980 to 1998, average numbers of excess deaths per day among American blacks relative to whites increased by 20%. David Williams writes that higher disease rates for blacks (or African Americans) compared to whites are pervasive and persistent over time, with the racial gap in mortality widening in recent years for multiple causes of death.

Criticisms

The study of a genetic basis for racial health disparity in the United States is criticised for the use of a "melting pot" perspective and for neglecting to include indigenous North Americans. This is based on studies suggesting the genetic difference between "races" is greatest with populations that have been reproductively isolated for long periods of time. The United States is the opposite of this with a wide variety of cultures in close proximity along with a decreasing social stigma against interracial relationships.

This issue is illustrated with the example of those who identify themselves as Hispanic/Latino, typically a mix of Caucasian, Native American and African ancestry. Some studies include this as a "race", whereas others do not have that option and force members of this group to choose between identifying themselves as "Caucasian", "Other" or whatever group that individual identifies with. Such admixture of genetic ancestry would lend results more to cultural, environmental and socio-economic explanations of health disparity rather than a genetic explanation.

Political economy in anthropology

From Wikipedia, the free encyclopedia

Political Economy in anthropology is the application of the theories and methods of Historical Materialism to the traditional concerns of anthropology, including, but not limited to, non-capitalist societies. Political Economy introduced questions of history and colonialism to ahistorical anthropological theories of social structure and culture. Most anthropologists moved away from modes of production analysis typical of structural Marxism, and focused instead on the complex historical relations of class, culture and hegemony in regions undergoing complex colonial and capitalist transitions in the emerging world system.

Political Economy was introduced in American anthropology primarily through the support of Julian Steward, a student of Kroeber. Steward’s research interests centered on “subsistence” — the dynamic interaction of man, environment, technology, social structure, and the organization of work. This emphasis on subsistence and production - as opposed to exchange - is what distinguishes the Political Economy approach. Steward's most theoretically productive years were from 1946-1953, while teaching at Columbia University. At this time, Columbia saw an influx of World War II veterans who were attending school thanks to the GI Bill. Steward quickly developed a coterie of students who would go on to develop Political Economy as a distinct approach in anthropology, including Sidney Mintz, Eric Wolf, Eleanor Leacock, Roy Rappaport, Stanley Diamond, Robert Manners, Morton Fried, Robert F. Murphy, and influenced other scholars such as Elman Service, Marvin Harris and June Nash. Many of these students participated in the Puerto Rico Project, a large-scale group research study that focused on modernization in Puerto Rico.

Three main areas of interest rapidly developed. The first of these areas was concerned with the "pre-capitalist" societies that were subject to evolutionary "tribal" stereotypes. Sahlins' work on hunter-gatherers as the "original affluent society" did much to dissipate that image. The second area was concerned with the vast majority of the world's population at the time, the peasantry, many of whom were involved in complex revolutionary wars such as in Vietnam. The third area was on colonialism, imperialism, and the creation of the capitalist world-system.

More recently, these political economists have more directly addressed issues of industrial (and post-industrial) capitalism around the world.

Theory

Cultural materialism

Cultural materialism is a research orientation introduced by Marvin Harris in 1968 (The Rise of Anthropological Theory), as a theoretical paradigm and research strategy. Indeed, it is said to be the most enduring achievement of that work. Harris subsequently developed a defense of the paradigm in his 1979 book Cultural Materialism. To Harris, cultural materialism "is based on the simple premise that human social life is a response to the practical problems of earthly existence".

Harris' approach was influenced by but distinct from Marx. Harris' method was to demonstrate how particular cultural practices (like the Hindu prohibition on harming cattle) served a materialistic function (such as preserving an essential source of fertilizer from being consumed).

Economic behavior has a cultural side which indicates that the works of anthropologists is relevant to economics. The Motivation behind cultural materialism is mainly to show that cultures adapt to the environment they're produced in.

Structural Marxism

Structural Marxism was an approach to Marxist philosophy based on structuralism, primarily associated with the work of the French philosopher Louis Althusser and his students. It was influential in France during the 1960s and 1970s, and also came to influence philosophers, political theorists and anthropologists outside France during the 1970s. French structuralist Marxism melded Marxist political economy with Levi-Strauss's structural methodology, eliminating the human subject, dialectical reason and history in the process. Structural Marxists introduced two major concepts, mode of production and social formation, that allowed for a more prolonged and uneven transition to capitalism than either dependency or World systems theory allowed for. A mode of production consisting of producers, non-producers and means of production, combined in a variety of ways, formed the deep structure of a "social formation." A social formation combined (or "articulated") several modes of production, only one of which was dominant or determinant. Primary anthropological theorists of this school included Maurice Godelier, Claude Meillassoux, Emmanuel Terray and Pierre-Philippe Rey. Structural Marxism arose in opposition to the humanistic Marxism that dominated many western universities during the 1970s. In contrast to Humanistic Marxism, Althusser stressed that Marxism was a science that examined objective structures.

Cultural materialism

Critical influences on Structural Marxism, primarily from the British Marxist historical tradition, included E.P. Thompson, Eric Hobsbawm and Raymond Williams. They criticized the functionalist emphasis in Structural Marxism, that neglected individuals in favour of the structural elements of their model. The British school was more interested in class, culture and politics, and placed human subjects at the centre of analysis. Where mode of production analysis was abstract, they focused on people. Where world-systems theory had little to say about the local, the Cultural Materialists began and ended there. Others connected with this school of thought concentrated on issues such as ethnic formation, labor migration, remittances, household formation, food production and the processes of colonialism.

The anthropology of pre-capitalist societies

Dobe !Kung men lighting a fire.

As anthropologists embraced "mode of production" analysis in the 1950s, they struggled to adapt its evolutionary model to the groups that they had traditionally worked with. While Marxist analysis was developed to account for capitalist society and its class dynamics, it had little to say about "pre-capitalist" societies, other than to define them by what they were not. One of the first attempts to theorize Hunter-gatherer society was Marshall Sahlins Stone Age Economics (1972) which overturned nineteenth century ideas that characterized life in such societies as "nasty, brutish and short". Sahlins demonstrated that actual existing hunter-gatherers lived in "the original affluent society"; their needs were met with relatively little work leaving them with far more leisure time than western industrial societies. Richard B. Lee's work amongst the Dobe !Kung of Botswana provided a detailed case study of the argument, even in one of the most hostile desert environments. The second part of Sahlins' book applies Chayanov's theories to develop a theory of a "Domestic mode of production." Given the argument of the "original affluent society" that many of these societies had abundant resources, Sahlins argued that the limit on production was the amount of labour available. Young families with many dependent children had to work harder, whereas older families with mature children and many workers worked much less. The final sections developed a theory of reciprocity discussed above.

An alternate model of the Domestic Mode of Production was developed by Eric Wolf, who rejected the evolutionary implications of Sahlins' model and argued that this mode of production should be viewed as the product of developing colonial trade relations.

Several collections addressing the question of mode of production analysis in classless societies came out in this period, including "The Anthropology of Pre-Capitalist Societies" and "Marxist Analysis and Social Anthropology".

Development of the state

Political economists such as Morton Fried, Elman Service, and Eleanor Leacock took a Marxist approach and sought to understand the origins and development of inequality in human society. Marx and Engels had drawn on the ethnographic work of Lewis H. Morgan, and these authors now extended that tradition. In particular, they were interested in the evolution of social systems over time.

Colonialism and imperialism

Cecil Rhodes, driving force of British imperialism in Africa

Articulated modes of production

The articulation of modes of production within a single formation was meant to account for the influence of colonialism on lineage modes of production, primarily in the African context. According to Hann and Hart, the short lived success of the theory was that

it produced a version of structural-functionalism at once sufficiently different from the original to persuade English-speakers that they were learning Marxism and similar enough to allow them to retain their customary way of thinking, which had been temporarily discredited by its role in the administration of empire.

World-systems theory and dependency theory

Dependency Theory arose as a theory in Latin America in reaction to modernization theory. It argues that resources flow from a "periphery" of poor and underdeveloped states to a "core" of wealthy states, enriching the latter at the expense of the former. It is a central contention of dependency theory that poor states are impoverished and rich ones enriched by the way poor states are integrated into the "World-system" and hence poor countries will not follow Rostow's predicted path of modernization. Dependency Theory rejected Rostow's view, arguing that underdeveloped countries are not merely primitive versions of developed countries, but have unique features and structures of their own; and, importantly, are in the situation of being the weaker members in a world market economy and hence unable to change the system.

Immanuel Wallerstein's "world-systems theory" was the version of Dependency Theory that most North American anthropologists engaged with. His theories are similar to Dependency Theory, although he placed more emphasis on the system as system, and focused on the developments of the core rather than periphery. Wallerstein also provided an historical account of the development of capitalism which had been missing from Dependency Theory.

Both versions of Dependency Theory were critiqued throughout the 1970s for the static historical accounts they provided. Their influence was slowly replaced by more dynamic and historically sensitive versions, such as Eric Wolf's "Europe and the People Without History."

Eric Wolf and Europe and the people without history

16th-century Portuguese (blue) and Spanish (white) trade routes

"Europe and the people without history" is history written on a global scale, tracing the connections between communities, regions, peoples and nations that are usually treated as discrete subjects. The book begins in 1400 with a description of the trade routes a world traveller might have encountered, the people and societies they connected, and the civilizational processes trying to incorporate them. From this, Wolf traces the emergence of Europe as a global power, and the reorganization of particular world regions for the production of goods now meant for global consumption. Wolf differs from World Systems theory in that he sees the growth of Europe until the late eighteenth century operating in a tributary framework, and not capitalism. He examines the way that colonial state structures were created to protect tributary populations involved in the silver, fur and slave trades. Whole new "tribes" were created as they were incorporated into circuits of mercantile accumulation. The final section of the book deals with the transformation in these global networks as a result of the growth of capitalism with the industrial revolution. Factory production of textiles in England, for example transformed cotton production in the American South and Egypt, and eliminated textile production in India. All these transformations are connected in a single structural change. Each of the world's regions are examined in terms of the goods they produced in the global division of labour, as well as the mobilization and migration of whole populations (such as African slaves) to produce these goods. Wolf uses labor market segmentation to provide a historical account of the creation of ethnic segmentation. Where World Systems theory had little to say about the periphery, Wolf's emphasis is on the people "without history" (i.e. not given a voice in western histories) and on how they were active participants in the creation of new cultural and social forms emerging in the context of commercial empire.

Maritime Fur Trade, 1790-1840.

Wolf distinguishes between three modes of production: capitalist, kin-ordered, and tributary. Wolf does not view them as an evolutionary sequence. He begins with capitalism because he argues our understanding of kin-ordered and tributary modes is coloured by our understanding of capitalism. He argues they are not evolutionary precursors of capitalism, but the product of the encounter between the West and the Rest. In the tributary mode, direct producers possess their own means of production, but their surplus production is taken from them through extra economic means. This appropriation is usually by some form of strong or weak state. In the kin-ordered mode of production, social labour is mobilized through kin relations (such as lineages), although his description makes its exact relations with tributary and capitalist modes unclear. The kin mode was further theorized by French structuralist Marxists in terms of 'articulated modes of production.' The kin-ordered mode is distinct again from Sahlins' formulation of the domestic mode of production.

Unfree labour and slavery

Liberal and neo-liberal market-based societies are predicated upon the concept of "free labour" - workers enter a labour market freely, and enter into contractual relations with employers voluntarily. "Unfree labour" - otherwise known as bond labour, debt bondage, debt peonage, and slavery, are thought to be archaic forms that will be eliminated with capitalist development. Anthropologists working in a wide variety of current situations have documented that the incidence of bonded labour is much greater than capitalist ideology would lead us to expect.

Tom Brass argues that unfree labour is not an archaic holdover in today's world, but an active process of deproletarianization of agricultural workers to provide rural agrarian capitalists with cheaper labour. In the constant drive to cheapen the cost of agricultural labour, debt bondage is used to tie workers to specific employers, lower their wages, and extract further unpaid labour from them. He illustrates this process at work in Peru and India.

An early study of debt bondage was Ann Laura Stoler's Capitalism and Confrontation in Sumatra's Plantation Belt, 1870-1979 (1985). Stoler examined the tobacco plantations of the Deli Maatschappij, one of the most profitable Dutch colonial corporations of the 19th century. The Deli company imported large numbers of Chinese indentured labourers to Sumatra, Indonesia, where they were treated not as employees, but as contractors. As contractors they had to buy all their supplies at inflated prices from the company, take all the risks of cultivation and processing, and finally sell their tobacco to the company at prices it set. They were kept in perpetual debt, unable to change employers, in working conditions that resulted in extraordinarily high death rates. Jan Breman extended this analysis of the "Coolie regulation" (which allowed for indentured labour) to the Dutch mining industry in the Netherlands East Indies (Indonesia).

Slavery is but one form of unfree (or bound) labour. Structural Marxists sought to theorize it as a mode of production. Claude Meillassoux has refined this approach in his study of pre-colonial African slavery. He analyzed the military and aristocratic systems that organized the capture of slaves and situated it within the politics of the merchants who organized the trade in slaves. His work focuses on the forces at play within a kinship organized polity that define slaves culturally as "anti-kin."

Peasant studies and agrarian change

Simple commodity production and the peasantry

Simple commodity production (also known as "petty commodity production") is a term coined by Frederick Engels to describe productive activities under the conditions of what Marx had called the "simple exchange" of commodities, where independent producers such as peasants trade their own products. The use of the word "simple" does not refer to the nature of the producers or of their production, but to the relatively simple and straightforward exchange processes involved. Simple commodity production is compatible with many different relations of production, ranging from self-employment where the producer owns his means of production, and family labour, to forms of slavery, peonage, indentured labour, and serfdom.

Capitalist transitions and agrarian change

Michael Taussig, for example, examined the reactions of peasant farmers in Columbia as they struggled to understand how money could make interest. Taussig highlights that we have fetishized money. We view money as an active agent, capable of doing things, of growth. In viewing money as an active agent, we obscure the social relationships that actually give money its power. The Columbian peasants, seeking to explain how money could bear interest, turned to folk beliefs like the "baptism of money" to explain how money could grow. Dishonest individuals would have money baptized, which would then become an active agent; whenever used to buy goods, it would escape the till and return to its owner.

Peasant wars of the twentieth century

Written in 1969 by Eric Wolf, Peasant Wars of the Twentieth Century, is a comparative view of the peasant revolutions of Mexico, Russia, China, Vietnam, Algeria, and Cuba.

The moral economy of the peasant

The concept of a moral economy was first elaborated by English historian E.P. Thompson, and was developed further in anthropological studies of other peasant economies. Thompson wrote of the moral economy of the poor in the context of widespread food riots in the English countryside in the late eighteenth century. According to Thompson these riots were generally peaceable acts that demonstrated a common political culture rooted in feudal rights to “set the price” of essential goods in the market. These peasants held that a traditional “fair price” was more important to the community than a “free” market price and they punished large farmers who sold their surpluses at higher prices outside the village while there were still those in need within the village. The notion of a non-capitalist cultural mentalité using the market for its own ends has been linked by others (with Thompson's approval) to subsistence agriculture and the need for subsistence insurance in hard times.

Cambodian rice farming

The concept was widely popularized in anthropology through the book, "The Moral Economy of the Peasant: Rebellion and Subsistence in Southeast Asia" by James C. Scott (1976). The book begins with a telling metaphor of peasants being like a man standing up to his nose in water; the smallest wave will drown him. Similarly, peasants generally live so close to the subsistence line that it takes little to destroy their livelihoods. From this, he infers a set of economic principles that it would be rational for them to live by. It is important to emphasize that this book was not based on fieldwork, and itself proposed a cross-cultural universalistic model of peasant economic behaviour based upon a set of fixed theoretical principles, not a reading of peasant culture. Firstly, he argued that peasants were "risk averse", or, put differently, followed a "safety first" principle. They would not adopt risky new seeds or technologies, no matter how promising, because tried and true traditional methods had demonstrated, not promised, effectiveness. This gives peasants an unfair reputation as "traditionalist" when in fact they are just risk averse. Secondly, Scott argues that peasant society provides "subsistence insurance" for its members to tide them over those occasions when natural or man-made disaster strikes. Although fieldwork has not supported many of Scott's conclusions, the book encouraged a generation of researchers.