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A different kind of association between socio-histories and health Joan H. Fujimura
In the last 15 years, genetics researchers have developed new molecular genomic technologies for analysing human differences at the level of DNA. This was soon followed by an explosion of studies that aimed to find genetic explanations for the differential health outcomes between individuals and groups by examining association between DNA and disease. Meanwhile, other geneticists have used the new molecular technologies to examine DNA differences between individuals and groups to build theories about migration, language, and ancestry in human history. Many of these studies have organized DNA differences into groups that oftentimes correspond to institutionallyestablished racial categories as they currently exist in the USA. Some of this new research has rekindled debates about the relationship between biology and race in many fields, including sociology. In tandem with this new research on DNA differences is an explosion of social scientific research critiquing the revitalization of research on biological differences by race. Troy Duster is the originator of and inspiration for much of this critical research (Duster 2003, originally published in 1990). More significantly, Duster has in this BJS article assembled the findings of the research referred to below to show how these different fragments come together to make a coherent story about the ‘creeping molecularization’ (personal communication) of race in very different realms. Many have critiqued what Duster calls the creeping molecularization of race in genetics research because it threatens to reinvigorate the belief that human social classification systems like race have a biological, ‘natural’ basis. Some of these social scientific studies described the new genetic classificatory research as examples of a ‘genetic reinscription of race’ (Abu El-Haj 2007) and the ‘molecularization’ (Fullwiley 2007), ‘biologization’ and ‘geneticization’ of race (Gannett 2001; Ossorio and Duster 2005, Duster 2005, 2006; Montoya 2007; Bolnick 2008; Fullwiley 2008; Roberts 2011; TallBear 2013; Rajagopalan and Fujimura 2012; Kahn 2013; Toom 2014), or as ‘genome geography’ (Fujimura and Rajagopalan 2011). Others have argued that interpretations of DNA clusters as signifying a biological basis for US institutionalized race categories is Fujimura (Department of Sociology, University of Wisconsin-Madison) (Corresponding author email: [email protected]) © London School of Economics and Political Science 2015 ISSN 0007-1315 print/1468-4446 online. Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA on behalf of the LSE. DOI: 10.1111/1468-4446.12117 © London School of Economics and Political Science 2015
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simply based on incorrect understandings of the current genetic science (Bolnick 2008; Fujimura et al. 2014). The debates continue to escalate as genomics researchers collect and analyse massive databases of human DNA sequence information. Social scientists have also examined efforts of nations to ‘own’ ‘their’ genomes and claim genomic sovereignty (Benjamin 2009), as well as how individuals shape notions of self-identity and homeland through genetic ancestry tracing (Nelson 2008), governance and genomics (Abu El-Haj 2012; Lee C. 2013; Nash 2012), indigeneity, ethnicity and genetics (Reardon 2005; Tallbear 2013; Tsai 2010). Many others have studied the use (or not) of race in biomedical genomics (Lee C. 2009; Braun and Hammonds 2008; Lee, Koenig and Richardson 2008) and in pharmacogenomics and clinical medicine (Montoya 2003; Epstein 2007; Kahn 2013; Lee S. 2003; Sankar 2010; Sankar, Cho and Mountain 2007; Paradies et al. 2007). Other scholars examine how geneticists engaged in this race-making work and pedagogy themselves think about human difference (Morning 2011; Bliss 2012). Still others have examined the movement of genomics into forensic police practices (Cho and Sankar 2004; M’Charek 2008; Ossorio 2006; Ossorio and Duster 2005). If we move away from the USA, research on these issues is being conducted in Singapore (Sun 2014); Taiwan (Tsai 2010); in Brazil (Santos et al. 2014); in Canada (Hinterberger 2012); the UK (e.g., Hedgecoe and Martin 2003; Tutton et al. 2008; Ellison et al. 2008; Smart et al. 2008; Martin 2005); Germany (Bauer 2013; Plümecke 2013; Europe (M’Charek, Schramm, and Skinner 2014); South Africa (Braun and Hammonds 2008); to name just a few. This is not an exhaustive list. Duster’s critique is not a tirade against the new molecular research. His writings have been thoughtful about the benefits of and motivations behind new molecular research on diseases. Over the last thirty years, Duster has used this nuanced approach in his study of molecular genetic research. In this paper, Duster raises concerns about the unintended consequences, the spinoffs, of the Human Genome Project; concerns which should be taken seriously by social scientists, geneticists, and policy makers. The rationale behind the Human Genome Project, and for the Haplotype Map Project which followed, has always been the search for ways to improve our health. There have already been some health benefits, and there will certainly be more. Nonetheless, in this paper I will point to mounting evidence that the inadvertent and unintended spin-offs (into domains far removed from health concerns and clinical medical applications) of the revolution in human molecular biology will dwarf the health achievements. (Duster 2015: 4) Duster points toward the ‘subtle, sometimes inadvertent re-inscribing of race at the molecular level’ as the first unintended consequence. Other consequences include the use of markers for individual identification, for group (e.g. tribal) membership, and for forensics as used in the criminal justice system. British Journal of Sociology 66(1)
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‘These developments are a long way from the original goals of the mapping and sequencing of the human genome’ (Duster 2015: 4).Again, he shows us the ‘creeping molecularization’ of race to different realms of social life and practice. Although Duster focuses on admixture mapping techniques in this paper, his argument also applies to the application of PCA and STRUCTURE technologies used to cluster DNA (Fujimura et al. 2014). However, in my view, Duster’s main contribution is the question: Why should medical or epidemiological studies focus on race and ethnicity? Why is that difference so important? Should it not matter more whether people live near toxic waste dumps? Or in food deserts? Or in areas of the country, county, or city where medical care is inadequate or difficult to access? Or in areas of the county or city with high rates of violence? Duster has asked this question since his early research. He has continued to raise this question throughout his career. A major difficulty for Duster’s suggested re-direction is that our scientific institutions, educational programmes, and research infrastructures have been constructed in ways that promote a different kind of science. This scientific method finds it difficult to account for illnesses produced in bodies located near toxic waste dumps. Duster asks why this is so, and asks us to reevaluate our scientific methods. Duster also presents a model of how research can be done in ways that provide an alternative kind of evidence that challenges ideas of static, unchanging genetic or ‘internal’ causes or risks for disease. For example, he contrasts two styles of research to search for explanations for the current high rates of diabetes among the Pima Indians. In the first, researchers ‘attempt to explain the role of genetic admixture in diabetes, asthma, obesity and a number of other health outcomes (Morena-Estrada et al. 2014; Fernandez and Shriver 2004, as quoted in Duster 2015). In contrast, Duster suggests a style of research that takes into account broader socio-historical contexts. He calls for a socio-cultural history of the group being studied, in order to understand their current high rates of diabetes. For example, he cites the work of anthropologists who have studied the changes in the living conditions for the Pima Indians in Arizona, changes wrought by nineteenth century European colonialism and westward expansion across the USA. Duster associates these lifestyle changes with current high rates of disease among contemporary Pima Indians in Arizona. This European westward colonialism reduced Pima Indians from practicing a nineteenth century, self-sustaining healthy diet based on their own skilled farming of water-intensive crops, to water-deprived lands, poverty, and an unhealthy diet of boxed macaroni and cheese provided by the federal government; and from almost zero cases to very high rates of Type II diabetes. The new diet ‘was saturated with a diabetic’s nightmare: refined white flour, processed cheese, lard, candy and chips, refined sugar, grape juice, and lots of macaroni; in © London School of Economics and Political Science 2015
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contrast to wild plants and game animals’ (Duster 2015: 18–19) Duster is promoting this kind of association of sociohistory and disease incidence, to uncover the underlying reasons for health inequalities. Duster presents another example from the early twentieth century, when many Jewish people in the US were recent immigrants, classified as nonwhite, and considered to have the highest incidence of diabetes. The disease was called the ‘Jewish disease’, and medical reports framed causality in terms of ‘some hereditary defect,’ a supposedly sensitive nervous system, a ‘neurotic temperament’, or a ‘racial tendency to corpulence’ (Tuchman 2011 as quoted in Duster). (In that same era, Blacks were considered to have unusually low rates of the disease.) In contrast, in the early twenty first century, Jews in the USA are now classified as white and considered to display low rates of diabetes, while Pima Indians in Arizona display high rates of the disease. Duster directs us to attend to the socio-historical contexts in which these attributions were and are being made. He argues that the method of collecting and correlating cross-sectional data on the physical characteristics of the target population used in both time periods leads research to miss the more likely explanation for the differences in disease incidence by groups. For both time periods, the overlap of poverty, illness, ethnicity and race has led some to argue for explanations internal to the bodies represented. For example, in the midtwentieth century, geneticists attributed the high rates of Type II diabetes in Native Americans to a theoretical ‘thrifty gene’. In contrast, Duster widens the lens to direct us to rates of diabetes incidence that follow patterns of urban versus rural habitation among six populations across the globe (King, H. and M. Rewers 1993, as cited in Duster 2015). Those who live in urban areas and consume a westernized diet have a very high rate of diabetes, but those who have lived in ‘traditional’ sites where they practice ‘traditional culture’ hardly experience any diabetes. (Duster 2015: 16–17). With respect to Native Americans, Duster (2015: 17) asks: Did they all have thrifty genes, and if so, what intervention is implied other than a dramatic shift in diet? Or from another perspective, since the sharp increase in Type II diabetes has come about in the last three decades – just in pure scientific logic, far more of the variance is explained by a systematic empirical investigation of shifting patterns of nutritional intake. I would like to provide related evidence from Hawaii, where public health researcher and physician Terry Shintani carried out an experiment in his desire to improve Native Hawaiian health. He engaged local residents to move back to a traditional Native Hawaiian diet (now called the ‘Waianae diet’ for a town on the North shore of Oahu) of taro, sweet potato, British Journal of Sociology 66(1)
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breadfruit, fish, seaweed (limu), and fruit and away from urban MacDonald’s and other fast food diets. Their rates of Type II diabetes, hypertension, and heart disease fell so dramatically that many could stop taking medications (Shintani et al. 1994). Duster’s question applies to changes in Native Hawaiian diets as well. Why would one look for genes for Type II diabetes in this particular community, when nutritional intake so well explains their changes in health? Duster is encouraging this ‘different kind of association’ between sociohistories and disease risk through a deep ethnographic public health and epidemiological method that is similar to that practiced by public health researchers Arline Geronimus (Geronimus 1992; Geronimus and Thompson 2004; Geronimus et al. 2006; Geronimus et al. in press), Sherman James (1994), Nancy Krieger (Krieger and Sidney 1996; Krieger et al. 1998; Krieger 2011), and Jay Pearson (2008) and by some medical anthropologists (Burton et al. 2005; Holmes 2013; Montoya 2003; Mullings and Wali 2001; and ViruellFuentes 2007). In related work, epidemiologists Kaufman and Cooper (1999, 2001) also argue against interpreting correlations between race categories with disease incidence in epidemiology as signs of genetic risk. In a recent inventive study, Cooper et al. (2014) use statistical methods to examine whether high blood pressure in persons of African descent is attributable to the genetic factors in African-origin populations, or a result of inadequately measured environmental exposures, such as racial discrimination. They conducted a multi-sited comparative study of communities in the African diaspora, drawn from metropolitan Chicago; Kingston, Jamaica; rural Ghana; Cape Town, South Africa, and the Seychelles. Their results data confirm that African-origin populations with lower social status in multiracial societies, such as the USA and South Africa, experience more hypertension than anticipated based on anthropometric and measurable socioeconomic risk factors. (Cooper et al. 2015: Abstract) These kinds of deep ethnographic epidemiological studies or multi-sited comparative studies of environmental disease risk aim to go beyond, as Duster shows, the single-frame correlation between race/ethnicity and disease incidence, to examine the specific socio-historical contexts in which people live, eat, change, and suffer. As noted, Duster has been promoting this kind of research since he began to do research on genetics and disease in the 1980s. As he notes, it is not that genetics has not made contributions to healthcare. For example, one need only look at BRCA 1 and BRCA 2 genetic tests for breast cancer. Nevertheless, the successes have been far fewer than had been expected, and health and health care in this wealthy country still do not match the dollars spent on research. This is Duster’s message and contribution. © London School of Economics and Political Science 2015
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Duster ends his article with an appeal to action: As funding for research to address health disparities moves in the direction of the biological or genetic emphasis (as with diabetes and the Pima), or even to gene-environment interaction long-term studies, social scientists have three major choices. The first is to stand along the side-lines and continue to cite the mantra that race and ethnicity are socially constructed. While demonstrably true, that truth is overwhelmed by the megaphone of advancing, under-theorized admixture research and increasingly taken-forgranted scientized components (of 100 per cent statistical purity) undergirding admixture. The second choice is to accept new molecular reinscription of race and join in joint projects – uncritical and without examining the domain assumptions that have ‘hardened’ and gelled. The third choice is the one that I strongly recommend – namely, that social analysts go to the site of the production of knowledge, and closely examine the procedures, the domain assumptions of how race is being used in human molecular genetics, examine how heavily these assumptions are located in social, historical, and folk categories but are then transmogrified into the language of science and anointed with an imprimatur of legitimacy. (Duster 2015: 23) I am definitely in the third camp. We are conducting research into the infrastructures that construct biological knowledge. Duster implicates research in the life sciences themselves. His challenge is to change how we study and view disease, and change biomedical research and educational institutional structures towards incorporating deep ethnographic and sociohistorical methods that can better address more potent environmental risk factors for disease. (Date accepted: 8 January 2015)
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A different kind of association between socio-histories and health 65 Geronimus, Arlene T., Hicken, Margaret, Keene, Danya and Bound, John 2006 ‘ “Weathering” and Age Patterns of Allostatic Load Scores Amount Blacks and Whites in the United States’, American Journal of Public Health 96(5): 826–33. Geronimus, A. et al. in press, 2015 ‘Race/ Ethnicity, Poverty, Urban Stressors and Telomere Length in a Detroit CommunityBased Sample’, JHSB. Hedgecoe, Adam and Martin, Paul 2003 ‘The Drugs Don’t Work: Expectations and the Shaping of Pharmacogenetics’, Social Studies of Science 33(3): 327–64. Hinterberger, Amy 2012 ‘Investing in Life, Investing in Difference: Nations, Populations and Genomes’, Theory Culture Society 29: 72–93. Holmes, Seth M. 2013 Fresh Fruit, Broken Bodies: Indigenous Mexican Farmworkers in the United States, University of California Press. James, Sherman A. 1994 ‘John Henryism and the Health of African-Americans’, Cultural and Medical Psychiatry 18: 163– 82. Kahn, Jonathan 2013 Race in a Bottle: The Story of BiDil and Racialized Medicine in the Genomic Age, New York: Columbia University Press. Kaufman, Jay S. and Cooper, Richard S. 1999 ‘Seeking Causal Explanations in Social Epidemiology’, American Journal of Epidemiology 150: 113–20. Kaufman, Jay S. and Cooper, Richard S. 2001 ‘Commentary: Considerations for Use of Racial/Ethnic Classification in Etiologic Research’, American Journal of Epidemiology 154: 291–8. King, H. and Rewers, M. 1993 ‘Global Estimates for Prevalence of Diabetes Mellitus and Impaired Glucose Tolerance’, Diabetes Care 16: 157–77. Krieger, Nancy 2011 Epidemiology and the People’s Health, New York: Oxford University Press. Krieger, Nancy, Sidney, Stephen and Coakley, Eugenie 1998 ‘Racial Discrimination and Skin Color in the CARDIA Study: British Journal of Sociology 66(1)
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Morning, Ann 2011 The Nature of Race: How Scientists Think and Teach about Human Difference, Berkeley: University of California Press. Mullings, L. and Wali, A. 2001 Stress and Resilience: The Social Context of Reproduction in Central Harlem, New York, NY: Kluwer Academic/Plenum Publishers. Nash, Catherine 2012 ‘Genetics, Race and Relatedness: Human Mobility and Human Diversity in the Genographic Project’, Annals of the Association of American Geographers 102(3): 667–84. Nelson, A. 2008 ‘Bio Science: Genetic Geneology Testing and the Pursuit of African Ancestry’, Social Studies of Science 38(5): 759–83. Ossorio, P.N. 2006 ‘About Face: Forensic Genetic Testing for Race and Visible Traits’, Journal of Law, Medicine & Ethics 34(2): 277–92. Ossorio, P. and Duster, T. 2005 ‘Race and Genetics: Controversies in Biomedical, Behavioral, and Forensic Sciences’, American Psychologist 60(1): 115–28. Paradies, Yin C., Montoya, Michael J. and Fullerton, Stephanie M. 2007 ‘Racialized Genetics and the Study of Complex Diseases: The Thrifty Genotype Revisited’, Perspectives in Biology and Medicine 50: 203–27. Pearson, Jay A. 2008 ‘Can’t Buy Me Whiteness: New Lessons from the Titanic on Race, Ethnicity, and Health’, DuBois Review: Social Science Research on Race 5(1): 27–47. Plümecke, Tino 2013 Rasse in der Ära der Genetik. Die Ordnung des Menschen in den Lebenswissenschaften, Verlag, Bielefeld. Rajagopalan, Ramya and Fujimura, Joan H. 2012 ‘Making History Via DNA, Making DNA From History: Deconstructing the Race-disease Connection in Admixture Mapping’ in K. Wailoo, C. Lee, A. Nelson (eds) Genetics and the Unsettled Past: The Collision between DNA, Race, and History, New Brunswick, NJ: Rutgers University Press. Reardon, Jenny 2005 Race to the Finish: Identity and Governance in an Age of © London School of Economics and Political Science 2015
Genomics, Princeton, NJ: Princeton University Press. Roberts, Dorothy 2011 Fatal Invention: How Science, Politics, and Big Business Re-create Race in the Twenty-First Century, New York: The New Press. Sankar, Pamela 2010 ‘Forensic DANN Phenotyping: Reinforcing Race in Law Enforcement’ in I. Whitmarch and D.S. Jones (eds) What Is the Use of Race?: Modern Governance and the Biology of Difference, Cambridge, MA: The MIT Press. Sankar, P., Cho, M.K. and Mountain, J. 2007 ‘Race and Ethnicity in Genetic Research’, American Journal of Medical Genetics 9(143A): 961–70. Shintani, T.T., Beckham, S.K., O’Connor, H.K., Hughes, C. and Sato, A. 1994 ‘The Waianae Diet Program: A Culturally Sensitive, Community-Based Obesity and Clinical Intervention Program for the Native Hawaiian Population’, Hawaii Medical Journal 53(5): 136–41, 147. Smart, A., Tutton, R., Martin, P.A., Ellison, G.T.H. and Ashcroft, R. 2008 ‘The Standardisation of Race and Ethnicity in Biomedical Science Editorial and UKBiobanks’, Social Studies of Science 38(3): 407–23. Sun, H. 2014 ‘The Study of Human Genetic Variation in a Transnational Context: Asianism and the Racialization of Ethniity’, Presented at the American Sociological Asociatin Annual Meeting 2014, August 16, San Francisco, USA. Tallbear, Kimberley 2013 Native American DNA: Tribal Belonging and the False Promise of Genetic Science, Minneapolis, MN: University of Minnesota Press. Toom, Victor 2014 ‘Trumping Communitarianism: Crime Control and Forensic DNA Typing and Databasing in Singapore’, East Asian Science, Technology and Society: An International Journal 8(3): 273–96. Tsai, Yu-yueh 2010 ‘Geneticizing Ethnicity: A Study on the “Taiwan Bio-Bank” East Asian Science’, Technology and Society 4(3): 433–55. British Journal of Sociology 66(1)
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A different kind of association between socio-histories and health Joan H. Fujimura
In the last 15 years, genetics researchers have developed new molecular genomic technologies for analysing human differences at the level of DNA. This was soon followed by an explosion of studies that aimed to find genetic explanations for the differential health outcomes between individuals and groups by examining association between DNA and disease. Meanwhile, other geneticists have used the new molecular technologies to examine DNA differences between individuals and groups to build theories about migration, language, and ancestry in human history. Many of these studies have organized DNA differences into groups that oftentimes correspond to institutionallyestablished racial categories as they currently exist in the USA. Some of this new research has rekindled debates about the relationship between biology and race in many fields, including sociology. In tandem with this new research on DNA differences is an explosion of social scientific research critiquing the revitalization of research on biological differences by race. Troy Duster is the originator of and inspiration for much of this critical research (Duster 2003, originally published in 1990). More significantly, Duster has in this BJS article assembled the findings of the research referred to below to show how these different fragments come together to make a coherent story about the ‘creeping molecularization’ (personal communication) of race in very different realms. Many have critiqued what Duster calls the creeping molecularization of race in genetics research because it threatens to reinvigorate the belief that human social classification systems like race have a biological, ‘natural’ basis. Some of these social scientific studies described the new genetic classificatory research as examples of a ‘genetic reinscription of race’ (Abu El-Haj 2007) and the ‘molecularization’ (Fullwiley 2007), ‘biologization’ and ‘geneticization’ of race (Gannett 2001; Ossorio and Duster 2005, Duster 2005, 2006; Montoya 2007; Bolnick 2008; Fullwiley 2008; Roberts 2011; TallBear 2013; Rajagopalan and Fujimura 2012; Kahn 2013; Toom 2014), or as ‘genome geography’ (Fujimura and Rajagopalan 2011). Others have argued that interpretations of DNA clusters as signifying a biological basis for US institutionalized race categories is Fujimura (Department of Sociology, University of Wisconsin-Madison) (Corresponding author email: [email protected]) © London School of Economics and Political Science 2015 ISSN 0007-1315 print/1468-4446 online. Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA on behalf of the LSE. DOI: 10.1111/1468-4446.12117 © London School of Economics and Political Science 2015
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simply based on incorrect understandings of the current genetic science (Bolnick 2008; Fujimura et al. 2014). The debates continue to escalate as genomics researchers collect and analyse massive databases of human DNA sequence information. Social scientists have also examined efforts of nations to ‘own’ ‘their’ genomes and claim genomic sovereignty (Benjamin 2009), as well as how individuals shape notions of self-identity and homeland through genetic ancestry tracing (Nelson 2008), governance and genomics (Abu El-Haj 2012; Lee C. 2013; Nash 2012), indigeneity, ethnicity and genetics (Reardon 2005; Tallbear 2013; Tsai 2010). Many others have studied the use (or not) of race in biomedical genomics (Lee C. 2009; Braun and Hammonds 2008; Lee, Koenig and Richardson 2008) and in pharmacogenomics and clinical medicine (Montoya 2003; Epstein 2007; Kahn 2013; Lee S. 2003; Sankar 2010; Sankar, Cho and Mountain 2007; Paradies et al. 2007). Other scholars examine how geneticists engaged in this race-making work and pedagogy themselves think about human difference (Morning 2011; Bliss 2012). Still others have examined the movement of genomics into forensic police practices (Cho and Sankar 2004; M’Charek 2008; Ossorio 2006; Ossorio and Duster 2005). If we move away from the USA, research on these issues is being conducted in Singapore (Sun 2014); Taiwan (Tsai 2010); in Brazil (Santos et al. 2014); in Canada (Hinterberger 2012); the UK (e.g., Hedgecoe and Martin 2003; Tutton et al. 2008; Ellison et al. 2008; Smart et al. 2008; Martin 2005); Germany (Bauer 2013; Plümecke 2013; Europe (M’Charek, Schramm, and Skinner 2014); South Africa (Braun and Hammonds 2008); to name just a few. This is not an exhaustive list. Duster’s critique is not a tirade against the new molecular research. His writings have been thoughtful about the benefits of and motivations behind new molecular research on diseases. Over the last thirty years, Duster has used this nuanced approach in his study of molecular genetic research. In this paper, Duster raises concerns about the unintended consequences, the spinoffs, of the Human Genome Project; concerns which should be taken seriously by social scientists, geneticists, and policy makers. The rationale behind the Human Genome Project, and for the Haplotype Map Project which followed, has always been the search for ways to improve our health. There have already been some health benefits, and there will certainly be more. Nonetheless, in this paper I will point to mounting evidence that the inadvertent and unintended spin-offs (into domains far removed from health concerns and clinical medical applications) of the revolution in human molecular biology will dwarf the health achievements. (Duster 2015: 4) Duster points toward the ‘subtle, sometimes inadvertent re-inscribing of race at the molecular level’ as the first unintended consequence. Other consequences include the use of markers for individual identification, for group (e.g. tribal) membership, and for forensics as used in the criminal justice system. British Journal of Sociology 66(1)
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‘These developments are a long way from the original goals of the mapping and sequencing of the human genome’ (Duster 2015: 4).Again, he shows us the ‘creeping molecularization’ of race to different realms of social life and practice. Although Duster focuses on admixture mapping techniques in this paper, his argument also applies to the application of PCA and STRUCTURE technologies used to cluster DNA (Fujimura et al. 2014). However, in my view, Duster’s main contribution is the question: Why should medical or epidemiological studies focus on race and ethnicity? Why is that difference so important? Should it not matter more whether people live near toxic waste dumps? Or in food deserts? Or in areas of the country, county, or city where medical care is inadequate or difficult to access? Or in areas of the county or city with high rates of violence? Duster has asked this question since his early research. He has continued to raise this question throughout his career. A major difficulty for Duster’s suggested re-direction is that our scientific institutions, educational programmes, and research infrastructures have been constructed in ways that promote a different kind of science. This scientific method finds it difficult to account for illnesses produced in bodies located near toxic waste dumps. Duster asks why this is so, and asks us to reevaluate our scientific methods. Duster also presents a model of how research can be done in ways that provide an alternative kind of evidence that challenges ideas of static, unchanging genetic or ‘internal’ causes or risks for disease. For example, he contrasts two styles of research to search for explanations for the current high rates of diabetes among the Pima Indians. In the first, researchers ‘attempt to explain the role of genetic admixture in diabetes, asthma, obesity and a number of other health outcomes (Morena-Estrada et al. 2014; Fernandez and Shriver 2004, as quoted in Duster 2015). In contrast, Duster suggests a style of research that takes into account broader socio-historical contexts. He calls for a socio-cultural history of the group being studied, in order to understand their current high rates of diabetes. For example, he cites the work of anthropologists who have studied the changes in the living conditions for the Pima Indians in Arizona, changes wrought by nineteenth century European colonialism and westward expansion across the USA. Duster associates these lifestyle changes with current high rates of disease among contemporary Pima Indians in Arizona. This European westward colonialism reduced Pima Indians from practicing a nineteenth century, self-sustaining healthy diet based on their own skilled farming of water-intensive crops, to water-deprived lands, poverty, and an unhealthy diet of boxed macaroni and cheese provided by the federal government; and from almost zero cases to very high rates of Type II diabetes. The new diet ‘was saturated with a diabetic’s nightmare: refined white flour, processed cheese, lard, candy and chips, refined sugar, grape juice, and lots of macaroni; in © London School of Economics and Political Science 2015
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contrast to wild plants and game animals’ (Duster 2015: 18–19) Duster is promoting this kind of association of sociohistory and disease incidence, to uncover the underlying reasons for health inequalities. Duster presents another example from the early twentieth century, when many Jewish people in the US were recent immigrants, classified as nonwhite, and considered to have the highest incidence of diabetes. The disease was called the ‘Jewish disease’, and medical reports framed causality in terms of ‘some hereditary defect,’ a supposedly sensitive nervous system, a ‘neurotic temperament’, or a ‘racial tendency to corpulence’ (Tuchman 2011 as quoted in Duster). (In that same era, Blacks were considered to have unusually low rates of the disease.) In contrast, in the early twenty first century, Jews in the USA are now classified as white and considered to display low rates of diabetes, while Pima Indians in Arizona display high rates of the disease. Duster directs us to attend to the socio-historical contexts in which these attributions were and are being made. He argues that the method of collecting and correlating cross-sectional data on the physical characteristics of the target population used in both time periods leads research to miss the more likely explanation for the differences in disease incidence by groups. For both time periods, the overlap of poverty, illness, ethnicity and race has led some to argue for explanations internal to the bodies represented. For example, in the midtwentieth century, geneticists attributed the high rates of Type II diabetes in Native Americans to a theoretical ‘thrifty gene’. In contrast, Duster widens the lens to direct us to rates of diabetes incidence that follow patterns of urban versus rural habitation among six populations across the globe (King, H. and M. Rewers 1993, as cited in Duster 2015). Those who live in urban areas and consume a westernized diet have a very high rate of diabetes, but those who have lived in ‘traditional’ sites where they practice ‘traditional culture’ hardly experience any diabetes. (Duster 2015: 16–17). With respect to Native Americans, Duster (2015: 17) asks: Did they all have thrifty genes, and if so, what intervention is implied other than a dramatic shift in diet? Or from another perspective, since the sharp increase in Type II diabetes has come about in the last three decades – just in pure scientific logic, far more of the variance is explained by a systematic empirical investigation of shifting patterns of nutritional intake. I would like to provide related evidence from Hawaii, where public health researcher and physician Terry Shintani carried out an experiment in his desire to improve Native Hawaiian health. He engaged local residents to move back to a traditional Native Hawaiian diet (now called the ‘Waianae diet’ for a town on the North shore of Oahu) of taro, sweet potato, British Journal of Sociology 66(1)
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breadfruit, fish, seaweed (limu), and fruit and away from urban MacDonald’s and other fast food diets. Their rates of Type II diabetes, hypertension, and heart disease fell so dramatically that many could stop taking medications (Shintani et al. 1994). Duster’s question applies to changes in Native Hawaiian diets as well. Why would one look for genes for Type II diabetes in this particular community, when nutritional intake so well explains their changes in health? Duster is encouraging this ‘different kind of association’ between sociohistories and disease risk through a deep ethnographic public health and epidemiological method that is similar to that practiced by public health researchers Arline Geronimus (Geronimus 1992; Geronimus and Thompson 2004; Geronimus et al. 2006; Geronimus et al. in press), Sherman James (1994), Nancy Krieger (Krieger and Sidney 1996; Krieger et al. 1998; Krieger 2011), and Jay Pearson (2008) and by some medical anthropologists (Burton et al. 2005; Holmes 2013; Montoya 2003; Mullings and Wali 2001; and ViruellFuentes 2007). In related work, epidemiologists Kaufman and Cooper (1999, 2001) also argue against interpreting correlations between race categories with disease incidence in epidemiology as signs of genetic risk. In a recent inventive study, Cooper et al. (2014) use statistical methods to examine whether high blood pressure in persons of African descent is attributable to the genetic factors in African-origin populations, or a result of inadequately measured environmental exposures, such as racial discrimination. They conducted a multi-sited comparative study of communities in the African diaspora, drawn from metropolitan Chicago; Kingston, Jamaica; rural Ghana; Cape Town, South Africa, and the Seychelles. Their results data confirm that African-origin populations with lower social status in multiracial societies, such as the USA and South Africa, experience more hypertension than anticipated based on anthropometric and measurable socioeconomic risk factors. (Cooper et al. 2015: Abstract) These kinds of deep ethnographic epidemiological studies or multi-sited comparative studies of environmental disease risk aim to go beyond, as Duster shows, the single-frame correlation between race/ethnicity and disease incidence, to examine the specific socio-historical contexts in which people live, eat, change, and suffer. As noted, Duster has been promoting this kind of research since he began to do research on genetics and disease in the 1980s. As he notes, it is not that genetics has not made contributions to healthcare. For example, one need only look at BRCA 1 and BRCA 2 genetic tests for breast cancer. Nevertheless, the successes have been far fewer than had been expected, and health and health care in this wealthy country still do not match the dollars spent on research. This is Duster’s message and contribution. © London School of Economics and Political Science 2015
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Duster ends his article with an appeal to action: As funding for research to address health disparities moves in the direction of the biological or genetic emphasis (as with diabetes and the Pima), or even to gene-environment interaction long-term studies, social scientists have three major choices. The first is to stand along the side-lines and continue to cite the mantra that race and ethnicity are socially constructed. While demonstrably true, that truth is overwhelmed by the megaphone of advancing, under-theorized admixture research and increasingly taken-forgranted scientized components (of 100 per cent statistical purity) undergirding admixture. The second choice is to accept new molecular reinscription of race and join in joint projects – uncritical and without examining the domain assumptions that have ‘hardened’ and gelled. The third choice is the one that I strongly recommend – namely, that social analysts go to the site of the production of knowledge, and closely examine the procedures, the domain assumptions of how race is being used in human molecular genetics, examine how heavily these assumptions are located in social, historical, and folk categories but are then transmogrified into the language of science and anointed with an imprimatur of legitimacy. (Duster 2015: 23) I am definitely in the third camp. We are conducting research into the infrastructures that construct biological knowledge. Duster implicates research in the life sciences themselves. His challenge is to change how we study and view disease, and change biomedical research and educational institutional structures towards incorporating deep ethnographic and sociohistorical methods that can better address more potent environmental risk factors for disease. (Date accepted: 8 January 2015)
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