How to make the South Asian diabetic
A critical examination of Type 2 diabetes ethnic risk
categories and the prevention and management practices that
make them
Leia Clifton
12062111
Master of Medical Anthropology and Sociology
Supervisors: Prof. Dr. Amade M’charek and Dr. Alana Helberg-Proctor (A.E.G) Second Reader: Dr. Anja Hiddinga
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Table of Contents
Acknowledgments:
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Chapter One: Introduction
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Chapter Two: Situating South Asian Type 2 diabetes
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2.1. South Asian diaspora in the United Kingdom
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2.2 A history of categorisation of ethnic minorities in the UK
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2.3 South Asian diabetes prevention and management
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2.4 South Asian diabetes risk in academia: a brief literature review 16
2.5 Research Questions
Chapter Three: Theoretical Framework
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3.1 The problem of categorising ‘ethnicity’ as diabetes risk 19
3.2 Knowledge production 20
3.2.1. Producing difference in practice 21
3.3 Making the ‘health conscious citizen’ 22
3.3.1 Biological citizenship 22
3.4 Norm Theory and White Normativity 23
3.4.1. Othering
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3.4.2 ‘Culturalistic fallacy’ 24
3.5 Conclusion
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Chapter Four: Methodology
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4.1 Data collection
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4.1.1Ethnography
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4.1.2. Interviews
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4.1.3 Qualitative analysis of documents and online presence
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4.2 Data Analysis
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4.2.1 Coding framework
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4.3 Limitations
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4.4. Reflexivity
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4.5 Ethical considerations
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Findings
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Chapter Five: Making the South Asian ‘other’
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5.1 ‘Be Aware of Your Own Risk’ Score
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5.1.2 Binary variables in ethnic risk
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5.1.3 Infallibility of numbers and will to health
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5.2 Clinical studies and the ‘white control group’
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5.2.1 Institutional funding practices and the ‘South Asian unknown’ 42
5.2.2 White as the ‘neutral control’ 44
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Chapter Six: Making the risky South Asian body
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6.1 Predisposition and the unknown body
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6.1.2 Genetics
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6.2 South Asian risky lifestyle
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6.2.1 South Asian Education Book
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6.3 The risky body across the diabetes landscape
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6.4 Conclusion
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Chapter Seven: Making the risky South Asian culture
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7.1 The mysterious disappearance of ‘A’ in ‘BAME’
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7. 2. The cultural veiling of the socioeconomic impact on diabetes risk
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7.3. Cultural pathology in practice
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7.3.1. Arjun’s Story: Cultural pathology in made human
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7.3.2. Risky ethnic individual to the health conscious citizen
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7.4 Conclusion
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Chapter Eight: Making the South Asian risk category
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8.1 Chapter Summaries
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8.2 Research Limitations
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8.3 Future Research Recommendations
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8.3.1 Research Recommendation One 82
8.3.2. Research Recommendation Two 83
8.4 Final Reflections
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Bibliography:
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Acknowledgements:
I would like to take this opportunity to first thank a few people. Firstly, my supervisors Prof. Dr. Amade M’charek and Dr. Alana Helberg-Proctor, their work regarding race/ethnicity in their respective fields is nothing short of inspiring. I would like to thank them for their patience, input, support and guidance without which this thesis would not be possible. I would next like to thank the diabetes professionals that shared their work and experiences with me, contributing very enthusiastically to this research. To my proof readers Eva, Freya and Max and to Talia who always helps me with her amazing insight and clarity. Finally and most importantly I want to thank my Mum and Dayna who always support everything I do.
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Chapter One: Introduction
It is estimated that by 2025, Type 2 diabetes1 will impact almost half the UK population
(Diabetes UK 2009). Currently as the fifth leading cause of mortality (Diabetes UK 2009) it is framed as a major issue in public health. This is maintained across a plethora of other government and non-government health bodies that conclude it poses a serious threat to health services in the UK. With rates of diabetes increasing in the UK every year and public health spending ever dwindling, efficiency within prevention and management has become crucial with
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stratifying the population into categories of risk’ (Gray et al. 2010: 888) becoming central to prevention strategy. Across the diabetes landscape in the UK, differing rates of diabetes between ethnic groups have been centralised, so much so that seeing to be from a particular ethnic2 background is now seen as a risk factor in diabetes. In sum, SouthAsian communities make up the ‘second largest ethnic group in the UK after the white ethnic population’ (Hanif et al. 2018: 2) and statistically pertains to ‘11.2% of all diagnosed and undiagnosed cases of Type 2 diabetes’ (ibid). Through this stratification via ethnicity, ‘South Asian’ as an ethnic risk category is highlighted, prioritised and made of great importance to numerous health stakeholders in a multitude of locations tackling the diabetes rates in the UK. This has become so integral to diabetes prevention and management that it has been suggested that individuals considered to be ethnically ‘South Asian’ are ‘targeted for
screening and prevention programmes and are to receive individualized care in order to tackle this ever growing epidemic’ (Hanif et al. 2018: 2). Despite its wide use, the association of
1Type 2 diabetes is defined as impaired glycaemic control caused by a deficiency in insulin secretion and insulin
sensitivity. In the UK, adults are commonly diagnosed through a random blood glucose test in order to measure the Haemoglobin A1C (HBA1C) level (Diabetes UK 2019), the higher the HBA1C level the longer blood glucose has been in the blood and therefore not taken into the cells via insulin (ibid). See Appendix 1.
2 Ethnicity defined as ‘shared social origins or social background, distinct culture and customs, and a common
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ethnicity with Type 2 diabetes (which I will henceforth as simply ‘diabetes’) is under critical interrogation in this thesis for a number of reasons. The primary reason being that ethnicity does not function in the same way as other diabetes risk factors; it does not and cannot cause diabetes and has yet to be ‘proven in any way as part of a causal chain’ (Montoya 2011: 6) for diabetes onset. Secondly, despite its increasing use as an explanatory model, linking ethnicity to disease rates has been criticised by social scientists for its racialisation (Bridges 2011: 295) of minority groups, a notion that that holds within it a dangerous past
entanglement the 'genetic superiority’ (Risch 2002: 11) paradigm and acts to erase notions of structural inequalities that these are subject to.
This thesis aims to explore South Asian risk as made in practices rather than as ‘given in nature’ (Krebbekx, Spronk, M’charek 2016: 639). I will investigate practices, objects, tools as well and research materials in locations across the diabetes landscape. This is in order to determine how South Asian risk is constructed through knowledge making practices at different sites that make up the ‘diabetes landscape’. Under this framework I will not take these locations as objective rather social sites and therefore ‘shaped by their historical and organisation context’ (Law 2004:8), therefore wider views regarding South Asian
communities and how these shape risk are explored. Importantly, I view and discuss this relationship as dialogical, holding the view that categorising South Asian ethnicity as a risk could have repercussions upon wider perceptions of these communities. As Montoya (2011) states, increased uses of ethnicity in health science has already ‘changed the way we talk about human difference, biology and disease’ (ibid: I) within society. This is especially delicate in the current healthcare policy climate of the UK in which austerity and
Conservative Government ‘hostile environment’3policy measures have meant that ethnic
3Conservative government hostile environment policy requiring health service staff to perform
identification checks and deny or charge for services if the patient cannot provide paperwork proving legal citizenship status (Hill 2017).
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minorities have been denied healthcare treatment due to being perceived as ‘foreign’ (Docs Not Cops 2019) and therefore undeserving of medical attention. The interaction between this climate and the categorisation of ethnicity as a health risk in of itself, if left unquestioned, could have implications for the right to healthcare of these communities.
The present thesis aims to present research through the following structure: Chapter two aims to situate the making of South Asian risk within the relevant current historical and political context regarding ethnicity and categorisation before situating it in the wider context of the diabetes landscape. It is important to note at this stage, that through viewing the South Asian risk category as made in practices I view the categorisation of ethnic bodies as inherently political. It is therefore important within this chapter to situate categories within the overall context of how a nation deals with and makes difference. In chapter three, I outline the theoretical framework that will inform analysis. Opening with an outline of race/no race debates issues of ethnic risk categories are situated in then turn to an outline of theories that direct this thesis in the approaching categories as the making of difference. With this
approach in mind, I turn to theories that will guide my theorising of neoliberal public health promotion, ‘biological citizenship’ (Rose and Novas 2005: 133) and the functioning white norms in diabetes. Chapter four provides the methodology used in this research, detailing the locations where South Asian risk is made and the multi-method approach employed in order to attend to these knowledge making practices across the diabetes landscape. Limitations and ethical implications are also discussed as well my reflections and position within this
complex and sensitive topic.
Findings of how the South Asian ethnic risk category is made are presented in chapters five, six and seven. Chapter Five introduces the reader to the making of the ‘South Asian other’ through the producing and functioning of white normativity. The chapter discusses this in three locations; a risk score, clinical institutional funding and within the practices of clinical
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studies. Following on from the construction of the ‘other’ (Douglas 1992), chapter six explores the ways in which the South Asian risky body is positioned, emphasising the ways in which explanations of an unhealthy lifestyle balance on an ‘unknown’ genetic
predisposition thus emphasising how this reflects the requirements of the ‘biological citizen’ (Rose and Novas 2005: 133). Chapter seven critically analyses the ways in which the South Asian culture is made risky and made pathological. I then focus on the way in which this favouring of the culture-as-risk model displaces experiences of health inequality that contribute to high rates of diabetes in South Asian communities. Chapter eight draws the findings to a close with a final discussion including reflections, implications and suggestions for further research before final thoughts resituates discussion firmly in concerns for ethnic minority wellbeing in the UK with regards to health.
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Chapter Two: Situating South Asian diabetes
The aim of this chapter is to contextualise the focus on South Asian communities within diabetes prevention in the UK. This is established by firstly by a description of what is meant by South Asian communities in the UK before. Discussion then turns to the ways in which these communities have been categorised as health risks in the historical and current political context, attending to the impact of diabetes categorisation on the wider narrative around South Asian communities. Following this is an exploration of the places in which South Asian diabetes has been made relevant and how it is framed in public health and targeted intervention. Finally, the breadth of information in academia including biomedicine,
epidemiology and social science regarding why South Asian communities have such a high diabetes risk is discussed. It is pertinent to note at this stage, that this thesis does not intend to entangle itself with these causal mechanisms, discussing this background is purely for reader clarity surrounding concepts discussed in later empirical chapters. At the end of this chapter I will present the resulting research questions that will guide this thesis.
2.1 South Asian diaspora in the United Kingdom
In the United Kingdom, the latest figures show that under the ‘Asian’ category there were 1.4 million people of Indian origin, 1.1 million of Pakistani origin, 447,201 of Bangladeshi origin and 835,000 of ‘Asian other’ origin (Office for National Statistics 2019). In total and combined with other ethnicities also deemed ‘Asian’ by the UK census, this category is the largest ethnic group after ‘White’ (Office for National Statistics 2019). Figure 2, depicts the migration history of the South Asian diaspora to the United Kingdom and the reasons for movement, depicted as within a mass migration deeply rooted within British colonisation. Within even a brief overview of migration history categorised as ‘South Asian’ it is possible
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to see categorising South Asian communities as a single, homogenous ethnic groups has the potential to be an impossible task.
Figure 2: ‘Timeline of large-scale migration from South Asian to the United Kingdom,’ (Pollard 2009: 147)
2.2 A history of categorisation of ethnic minorities in the UK
The categorising of South Asian and ethnic minority bodies as health risks by the state can be traced back to first migration to the UK in the 1950’s as delineated above. During my time on thesis research, I attended a talk in Euston, London that was organised by migrant health solidarity groups regarding the access of ethnic minority groups to healthcare. Specifically, it focussed on ways in which healthcare workers could counteract the 2017 UK Conservative government ‘hostile environment’ (Hill 2017) policies. I refer to the content of this talk in order to situate the ways in which categorising ethnic minorities as risks has impacted and continues to impact minority groups in detrimental ways, including access to healthcare. One of the speakers at the talk, a member of the South Asian solidarity group spoke of her time as a migrant health activist in 1970’s Britain. She took the time to highlight issues she wished
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the audience to recognise and reflect on regarding issues from the past which are resurfacing in the current policy climate.
The following quotes are excerpts from her talk:
‘The British state has always wanted cheap labour. Cheap labour without people who get sick and so on… immigrants were seen to carry disease, the government had black, Asian and minority ethnic directed policies and the passing of resolutions saying that immigrants must be examined for disease. These people were dangerous and not seen as responsible. We
were never to be acknowledged except to be told there was something wrong with our immigrant bodies.’
She goes on to say:
‘There is a point of always recognising colonialism that has influenced this also the ongoing forces of imperialism. It is important to remember we are here,
because you were there.’
The activist’s words succinctly capture issues regarding the highly political nature of categorising immigrant bodies across time and space. From the first instances of mass
migration in the 1960’s after the end of the British occupation in the Indian Subcontinent and other colonies, migrant bodies continued to be politicised and pathologised by the state upon arrival to the UK. The re-categorisation of migrant groups ethnic minority groups as
explained by the activist is viewed by cultural scholars as having its origins in the in the problematisation and control of ‘visible minorities’. The breaking down of the 1970’s ‘politically black’ (Alexander 2018: 1038) migrant solidarity movement and subsequent division and categorisation via ethnicity led to the re-categorisation of these groups into the acronym Black, Asian and Minority Ethnic (BAME). This is said to be the result of ‘divide and rule’ (Hall 1992: 196) policy making, reflective of colonial control tactics. Her comment
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also highlights the realities of postcolonial migration as encouraged by the British state in order to stabilise labour shortages. When migrants moved over they were met policies categorising them as ‘diseased ethnic bodies’.
This context highlights the ways in which categorising health risk via ethnicity is more than just a variable - it has a specific political history. State categorisation of ethnic minority bodies as a risk in health has a history of problematizing them, assigning them ‘dangerous’ and ‘irresponsible’ status. As this talk occurred in 2019 it is clear these issues of ethnic minority categorisation are becoming more relevant due to hostile environment policies making life for ethnic minority groups more challenging in healthcare. The context of past and present approaches of state categorisation and its consequences directs this research to being concerned with the assigning of ‘risk’ to ethnic minority groups in healthcare or otherwise. Despite having intentions of improving minority health, categories have the ability to oppress when transformed into action by the state and as the activist describes, can have a detrimental impact on those categorised as risks.
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2.3 South Asian diabetes prevention and management
This section aims to briefly contextualise how South Asian communities being ‘at risk’ of diabetes are approached in prevention and management with the aim of placing it in the wider context of public health.
Currently as the fifth leading cause of mortality (Diabetes UK 2009), diabetes is considered a major health issue in public health. As Figure 3 shows above,
messaging daily across public health,
media and diabetes charities report that the National Health Service (NHS) spends ‘10% of its overall budget’ (Diabetes UK 2018) on the condition and is generally framed as a burden to healthcare and more so, public funds.
Approaches to reducing the rates of diabetes in the UK is strategized firstly around
prevention. This is with the aim of preventing those categorised as ‘at risk’ from developing the condition. If this fails and diabetes is developed then attention turns to managing those within the condition, from preventing further complications. Even though prevention
technically occurs in the action in ‘pre-diabetes’ (Diabetes UK, 2019) phase and management in the ‘diabetes’ phase, practices in both are widely the same. This is as firstly, diabetes is considered widely framed as ‘disease of lifestyle’ (Hu et al. 2002: 791) in health policy. This is to suggest that develop the condition are more likely to be engaging in activities which are viewed as detrimental to overall health such ‘lack of exercise and poor diet’ (Hu et al. 2002:
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791). Therefore both prevention and management activities revolve around mitigating risk through improving lifestyle. Secondly, it is as diabetes is not considered to be in and itself a problem. It is ultimately the complications to essential body parts such as eyes, kidneys and feet (Diabetes UK, 2018) from diabetes that debilitates the individual and therefore impacts health services economically. As Figure 4 shows, the rates of diabetes when looking into South Asian communities positions them as a ‘high risk group’ that requires targeted
intervention in the overall management of the UK ‘diabetes epidemic’ (Hanif et al. 2018: 2) Prevention and management of diabetes includes a wide network of actors including professionals across a wide range of agencies that form the ‘diabetes professional network’ (Diabetes UK, 2019). This includes government agencies such as Public Health England (PHE) and the National Institute for Care and Excellence (NICE) as well as non-government agencies such as charities, universities, research institutes, UK and internationally based research institutes that research and produce information regarding diabetes risk.
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2.4 South Asian diabetes risk in academia:
A brief literature review
The following section outlines a brief literature review of South Asian risk in academia, to present background for work that this thesis builds on. Despite being grouped together based on ethnicity, the communities within the ‘South Asian’ risk category are a highly
heterogeneous group from many parts of the Indian subcontinent. Currently, risk as
associated with the South Asian ethnicity remains in a liminal space across disciplines. With regards causation there is currently no ‘specific, coherent or clear explanation for the high prevalence’ (Patel 2016: 25) of diabetes that exists in South Asian communities. However there are explanatory models that exist and are consistent over academic disciplines such as the biomedical, epidemiological and social sciences to name but a few. Keval (2015) refers to this continuation of these consistent ideas over disciplines as the South Asian ‘risk package’ (Keval 2015: 45).
On the one hand academic research suggests that, a ‘genetic predisposition’ (Rees et al 2008: 12) contributes to the high prevalence of diabetes. Despite lack of evidence, genetic
susceptibility is still briefly mentioned across research proposals and causation models (Gray et al. 2010: 887) across diabetes research. This is mostly in relation to the way in which genes determine the South Asian body. This idea is highly prevalent in explanations of South Asian risk in relation to abdominal or ‘truncal fat’ (Montesi, Caletti and Marchesini 2016: 37) and therefore obesity is highlighted as a risk factor. Furthermore, diabetes risk is also centred on the association of diabetes, insulin resistance and obesity. McNaughton (2013) refers to this compounding of three factors as ‘diabesity’ (McNaughton 2013: 274), in that across public health and academia at the moment, there is a focus on obesity as the central cause of diabetes.
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However, much of the literature also focuses on the South Asian culture as an issue that to target in the mitigation of diabetes risk. South Asian diet and a low active lifestyle culturally has suggested to contribute (Patel 2016: 25) to high rates of diabetes seen in this population. However as Bhopal (2001) argues, identities highly vary within this ethnic group in many aspects including migration, religion, food practices, education and levels of English speaking ability (ibid: 7) to name but a few. These widely differing factors impact rates and experiences of diabetes, meaning creating prevention and harm reduction programmes around culture would in turn produce a reductive image of an irrational and problematic culture (Ahmad 1996). The social sciences is not exempt from this as attention mostly centres around diabetes ‘illness experience’ (Patel et al. 2016: 1) of the South Asian individual as caught between their illness and culture. Bhopal (2013) however, argues that levels of diabetes in the population are no worse than that of other ethnic groups (Bhopal 2013) and therefore cultural practices cannot ‘provide conclusive explanations for the high levels of risk’ (Patel et al. 2016: 25). It is clear from this academic context that research locations as well as the construction body and culture are central to the construction of the risk category. This will be incorporated into forming research questions that will guide this research as defined below.
2.5 Research Questions
In this chapter I have put forward the relevant context regarding the categorisation of ‘South Asian’ as a risk. Emphasis was placed on the highly political nature of ethnic risk
categorisation as well as the overall background of how the problem is presented in public health and academia. Based on this context I have constructed research questions to guide this research through examining the practices in which South Asian risk is made.
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The overarching research question is:
How is the ‘South Asian’ ethnicity made risky in Type 2 diabetes practices across the diabetes landscape in the UK?
With this view of categories as situated and therefore influenced by a particular context rather than as a whole object, it is possible to form additional research questions to direct this
research and illuminate how practices across the diabetes landscape make ethnicity a risk in practice. This thinking will in turn shape the empirical chapters five, six and seven.
1. How is the South Asian risk category brought into knowing?
2. How is the South Asian body made risky and how is risk communicated through this? 3. How is the South Asian culture made risky and how is risk communicated through
this?
As discussed within this chapter, focussing on the construction of the ‘body’ and ‘culture’ as points of analysis reflects the ways in which professionals across the diabetes prevention and management discuss South Asian risk. I therefore see it as important to analyse both aspects in equal measure order to examine how the South Asian risk category functions to produce the individual as risky. Theories that will guide this will be delineated in the chapter three.
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Chapter Three: Theoretical Framework
In the previous chapter I aimed to show how the historical, political and public health context of South Asian diabetes formed research questions that informed my research questions. The questions centre on the South Asian ethnicity being made risky in practices across the
diabetes landscape. The following chapter aims to outline and explain the relevant theory that will be used in my analysis. Discussion opens with the theoretical arguments behind using ethnicity as a variable in health situating the discussion in wider race/no race debates that currently exist. I will then turn to theory that delineates South Asian risk does not exist ‘out there’ in nature but is constructed in social sites of scientific knowledge making. Knowledge making as ‘socio-material practice’ (Latour and Woolgar 1979) then directs this framework in using a range of concepts that view ethnicity as a risk as constructed and how they construct the subjects against assigned norms. I then discuss the notion of norms as they function in the UK context. This chapter then concludes on how this produces notions of citizenship and following constructions of culture.
3.1 The problem of categorising ‘ethnicity’ as diabetes risk
Apposite to the topic of this thesis is the wider discussion surrounding the use and relevance of ‘ethnicity’ as a valid risk factor within science. This has been highly debated within the realm of race/no race debates. As Montoya (2011) argues, the issue ‘lies in the difference between ethnicity and race’ (2014: 14) and whether scientific enterprise that approaches ethnicity actually reifies old ‘folk taxonomies’ (Marks 1995: 123) of race. Arguments
surrounding use of ethnicity however have now developed far beyond the existence of race as a social or biological construct. As Montoya (2011) argues the turn of the genomic age has constructed a ‘genetic determinism’ (ibid: 5) in which all phenomena, physical and mental, is
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reduced to the composition of DNA. It is argued that assigning differences in ethnic risk via genetics is but one way race is now ‘gaining in reality’ (Hartigan 2008: 164). This is not only in the public consciousness but adds to a network of not just the scientific but society, the media and the epidemiological (M’charek 2010: 231). Race is now transformed into ‘bio-ethnicity’ (Montoya 2011: 184) and is acknowledged as a variable representing confluence of ‘biology and social history’ (ibid 184). The argument follows, that if the ‘ethnicity variable’ (Bonham and Knerr 2008: 272) were not used, disease burden suffered by migrant groups would not be brought to the attention of governments. Montoya (2011) further argues, that as ethnicity is not yet part of a ‘causal chain’ (2011: 6), discussion should therefore centre upon locations and practices that translate ethnicity into risk, determining whether or not the communities being studied are being subjected to racializing gaze (Keval 2005: 276).
3.2 Knowledge production
The assertion that risk is socially constructed is the main difference between a clinical risk conceptualisation and what is apparent when looking into the field of social sciences today. Ewald (1991) argues there must be an acknowledgement that pre-existing risk does not exist, but that now everything is a risk or at least has the potential to be. While the material and social worlds in which individuals exist are primarily understood as objective within the natural sciences, within constructive thought it is conceptualised that realities are dependent upon the social interactions and definitions which produce forms of knowledge and the meanings associated with them (Lupton, 1999). There is therefore a constant interaction between the individual and the social environment, which bonds any knowledge about ethnicity as a risk category to the socio-cultural context where a specific category is produced.
Science and Technology Studies (STS) goes a step further with the social construction of risk knowledge. Latour and Woolgar (1979), approach the laboratory not as the location
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discovering objective scientific fact in nature but rather as a ‘site of socio-material practice’ (ibid) of knowledge production, This transforms locations into sites where scientific fact is crafted within a particular context, before knowledge claims become separated and
transported independently. ‘Reality’, as science constructs, is not only ‘historically, culturally and materially located’ (Mol 1999: 75) but also is ‘done and enacted, rather than observed’ (ibid 75). Under this framework ‘universities, research institutes, expert centres and scientific publications’ (Krebbekx, Spronk, M’charek 2016: 639), become sites in which knowledge is produced and constructed. This non-objective approach also attends to the ‘productivity or performativity’ (Law 2019: 1) of categories in that they also ‘shape the elements that make them up the agendas that they carry’ (Law 2019: 1).
3.2.1 Producing difference in practice
Through this, the making of categories becomes the ‘production of difference’ and therefore relies on and is informed by knowledge making techniques used within these locations. Hacking (2006) suggests that classification in the human sciences is the process of ‘making up people’ (ibid: 161). Practices involved in the creation of categories such as ‘surveying, naming, dividing and merging groups’ (Krebbekx, Spronk, M’charek 2016: 639) are social processes that produce categories and form the ways in which individuals within that category become known. Categories are made natural through ‘engines for making up people…counting, quantifying, correlating, medicalising, biologising, geneticising, normalising, bureaucratising, reclaiming’ (Hacking 2006: 163). The notion of categorising in biomedicine creates as Hacking (1982) suggest a ‘productive’ (ibid: 272) class. Therefore, it is not only what is suggested through ethnicity as a category that matter that matters but the very formation of the category that should be explored.
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3.3 Making the ‘health conscious citizen’
Through this STS approach to categories, knowledge is made within social sites. Therefore the purpose of these locations as sites of health promotion becomes critical in the forming of disease risk. Diabetes prevention and management as an example of ‘health promotion within neoliberal rationality’ (Ayo 2012: 99) is concerned with ‘health risk management through individual responsibility’ (Ayo 2012: 99) and therefore frames any health inequality as the ‘consequence of choice’ (ibid 99). Critics of neoliberal public health refer to this framing as ‘lifestyle drift’ (Popay et al. 2010: 10) which they argue is becoming more prolific in public policy. As a result of this, responsibility is placed further on the individual whilst ultimately removing responsibility from the state. Neoliberal public health practices aim to create the ‘health conscious citizen’ (Ayo 2012: 99). This relates to wider notions of governmentality (Foucault 1991) as a form of social and political control in health thus ‘educating desires and configuring habits, aspirations and beliefs’ (Li 2007: 275). As a result people are encouraged to engage in ‘self-managing practices’ (Ayo 2012: 101) and made into the health conscious citizen. This is theorised as an example of the ways individuals are made into a particular ‘type of subject’ (Markula and Pringle 2006: 43) by the state. ‘Healthism’ (Ayo 2012: 101) is also central to this idea, in that the citizen should live and work in order to maximise their own health which in turn benefits the individual but also wider society (ibid). Individuals that do not comply with neoliberal practices are therefore constructed as not only a threat to themselves but the wider population.
3.3.1 Biological citizenship
The notion of ‘biological citizenship’ (Rose and Novas 2005: 133) is particularly relevant when looking at ethnic minorities. Biological citizenship (Rose and Novas 2005: 133) is the idea that rights claims can be made on a biological basis and therefore the state is able to root
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the ideological notion of citizenship in science and biological categories. Biological responsibilities of citizens are delineated by and embodied within ‘norms of health and of health education’ (Rose and Novas 2005: 134). Furthermore, this brings forth the idea of ‘genetic responsibility’ (Rose and Novas 2005: 134) in which the individual is required to ‘manage the complications of their own genome’ (ibid) to be a productive member of society. This approach by the state is problematic for bodies that are categorised as risks, as they by definition do not meet the constructed norms. This in turn can be used to ‘distinguish and disenfranchise’ (ibid: 361) individuals the state deems ‘undeserving’ (ibid: 361), preventing them from accessing resources appointed to the citizen.
3.4 Norm theory and White Normativity
As knowledge making is theorised as located as a ‘socio-material practice’ (Latour and Woolgar 1979) it renders the view that science itself has its own norms. Within a discussion of ethnicity in the UK context, this directs discussion to the concept and functioning of ‘white normativity’ (Morris 2016: 950). As Morris (2016) discusses in the US context, medical and scientific knowledge is historically constructed around ‘white majority’ (ibid: 961). This majority defined the standard with regards to ‘normal functioning of the human body’ (Morris 2016: 961) with minority bodies therefore being known as abnormal and other. This ‘white normativity’ (Morris 2016: 950) functions in many locations across health science. Within the clinic, doctors are theorised to come from a ‘white normative perspective’ (Morris 2016: 958) which may often attribute behaviour in ethnic minority patients as different to that of the white majority and interpret their experience. However these norms infiltrate science from wider society, as Mol (2002) states when discussing notions of the normal and the pathological ‘laboratories can establish facts, but not norms’ (ibid: 123).
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3.4.1 Othering
These above norms construct the risky ‘other’ which can be attributed to the work of Mary Douglas (Douglas 1992). Douglas argues that these underlying cultural logics that construct categories of sick, function to attribute difference (ibid). This theory brings to light how certain people and categories are selected as risks rather than others, as well as how risk serves to act between the category of the self and the ‘other’. This research intends to use this critical approach to categorisation as a social process which often reflects societal norms and reproducing ideas of the other in order to study the production of the South Asian diabetic risk category. This thesis will incorporate ‘othering’ into a wider framework of focussing on categorising and risk making practices as the production of difference.
3.4.2 ‘Culturalistic fallacy’
From ‘norm theory’ (Morris 2016: 958) as delineated above, the opposition is constructed within the ‘culturalistic fallacy’ (ibid: 173). Within the medical approach, when an individual from a different ethnic background fails to meet said norms of the wider culture, medical professionals ascribe non-conformity to the ‘assumed cultural background’ (Meershoek and Krumeich 2008: 173) of the patient. This in turn, produces an essentialised notion of culture that is reminiscent of racialisation. Further attending to epidemiological notions of risk, Keval (2016) theorises practice that focus on culture have formed a cultural pathology, in which alleviation of disease burden within ethnic groups rest solely upon altering problematized ethnic practices, thus, traits, customs, beliefs and norms’ as markers of these groups are problematized.
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3.5 Conclusion
To conclude, the overall approach to the categorisation of South Asian risk as made in practices rather than existing in nature points this research in a few overarching directions. The discussion of race/no race arguments as a starting point, I have shown ethnic risk as a ‘socio-material practice’ (Latour and Woolgar 1979), which has rendered it no longer objective but able to be influenced by the wider context. Prevention practices as sites of ‘neoliberal health promotion’ (Ayo 2012: 99) influence the ideas that construct the South Asian as a risk category. As a result the notions of individual health promotion and biological citizenship become relevant. Alongside this, social sites of knowledge making also have norms in the form of ‘white normativity’ (Morris 2016: 950) from which those that do not conform are known as the other and their culture problematized. I will use these theories to discuss the research questions throughout this thesis focusing on the ways in which the South Asian risk category comes into knowing as well as the functioning of the risky body and culture within.
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Chapter Four: Methodology
As delineated in the theoretical framework, this research considers categories as made rather than existing in nature to be discovered and found, this dictates both the research methods and locations of research. Within this framework and from this moment on I reconceptualise diabetes prevention and management as the ‘diabetes landscape’. I define this as South Asian risk not just as made in physical locations such as ‘universities, research institutes, expert centres’ (Krebbekx, Spronk, M’charek 2016: 639) but also within ‘concepts, methodologies, theories, inventions’ (Keval 2016: 45) that make and reinforce risk as associated with
ethnicity. These thus also become points of analysis. As I stated earlier, South Asian diabetes is not just know within the realm of science and medicine but knowledge is created,
maintained and upheld by a range of actors, including both government and
non-governmental organisations. This shows that concern regarding diabetes crosses traditional disciplinary divides. With the above locations where the South Asian risk category and knowledge within it is made, in this chapter I aim to establish how the multi-method
approach across locations within the diabetes landscape was best suited for this research. This includes an ethnography of diabetes conference, interviews professionals as well as an
analysis of a range of materials aimed at conceptualising reducing the risk of South Asian diabetes.
4.1 Data collection
In consideration of the above methodology regarding locations of knowledge production, it is pertinent at this point to describe and explain the data collection across the multi-method approach that produced the data for this thesis. It is important to note that I present this chronologically, ordering this temporally is only for the sake of narrative clarity as I explain
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my methods. In reality, and consistent with the theoretical framework of this thesis, the methodological practices I delineate below often work ‘simultaneously and inform each other’ (Krebbekx, Spronk, M’charek 2016: 639).
4.1.1 Ethnography
As this research considers categories of South Asian risk as not pre-existing then it follows to explore how categories are done, ethnographically. This was undertaken mainly at a diabetes professional conference I attended at the beginning of the research period. As observation focussed on a ‘particular aspect of a topic’ (Bryman 2016: 432) and lasted only a ‘short period of time’ (ibid), this method is as a ‘micro-ethnography’ (ibid).
The conference I attended occurs annually bringing together working professionals working within the diabetes field. The aim is for professionals to come together, to share experiences and latest research in diabetes prevention and management. Over the course of the three days I attended a series of lectures and presentations by professionals from interdisciplinary backgrounds involved with diabetes. The conference also had questions and answer sessions, workshops and a multitude of exhibits put on by organisations across the NHS, healthcare and industry. This provided me with a sufficient starting point for research and as Montoya (2007) explores, conferences are important locations of information exchange in which it is possible to view how risk is communicated across a ‘multitude of disciplines’ (Montoya 2007: 112). This is also consistent with the nature of ethnography as a method as it ‘doesn’t necessarily distinguish very cleanly between science, medicine, social science or any other forms of inquiry’ (Law 2004:19), it instead ‘finds continuity’ (ibid) across all these aspects. Therefore using ethnography as a method was beneficial in allowing me to communication across the diabetes landscape.
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As the conference was vast and for optimal efficiency I constructed a pre-planned schedule to direct myself around the conference. This was based on key words included in the description of a session such as ‘South Asian’ or ‘ethnicity. From a logistical standpoint, the conference provided me with a good point of contact with professionals enabling me to form contacts across the field for future use in supplementary interviews.
4.1.2 Interviews
Qualitative interviews were performed with fifteen diabetes professionals working in different areas across the defined diabetes landscape. This included biomedical scientists involved in clinical studies around diabetes risk (n=5), clinicians (n=2), healthcare
professionals running diabetes prevention or management programmes (n=4), diabetes non-government body professionals (n=2), policy makers (n=1), biostatisticians (n=1). In line with research ethnic pertaining to establish proper consent, I approached all the professionals at the diabetes professional conference, asking whether they would be interested in taking part in my research. I then contacted them via email at a later date and interviews were then organised around the availability of the professional in question.
The interviews were semi-structured and directed via an interview guide dictated by broad brush thematic headings (May, 2011: 135) of aspects I knew I was interested in. I did this in to construct and navigate themes across the diabetes landscape which involves a wide range of varying practices, opinions and approaches to diabetes risk as associated with ethnicity. Interviews conducted lasted between 60–90 minutes, they were recorded and immediately transcribed in post. The majority of interviews took place in person (n=10) with some over the phone (n=5), this was mainly due to location limitations. Not meeting the professionals in person did limit the content of interviews as it I was unable to view ‘visual cues or nonverbal cues’ (Aquilino 1994: 212) or have access to physical materials that for confidentiality
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reasons they were unable to send me over email. The format of interviews were generally the same, I opened interviews by asking what was considered ‘South Asian risk’ in their line of work so I was able to in order fully clarify and establish what field the professional was speaking from.
The aim of the interview was to discover ‘how’ (Law 2004: 8) the practices of the professionals in diabetes prevention made South Asian risk, therefore the majority of questions were for professionals to describe how the practices they are involved with make South Asian risk. During the interviews that happened in person, I made notes of visual cues including actions and reactions that would not have been noticeable in a recording.
4.1.3 Qualitative analysis of documents and online presence
As this thesis attends to practices in which South Asian risk is made, this includes research practices in the form of written materials and technologies involved in diabetes prevention which attaches risk to ethnicity. These materials were either highlighted during the
conference or during interviews. During interviews, I asked participants to bring any relevant materials regarding their approach to studying the South Asian risk category. As
professionals were from a range of different backgrounds, materials brought to the interview included policy documents, risk scores, research proposals, questionnaires and reports as well as education books and manuals specifically aimed at those deemed to have ‘South Asian risk’.
4.2 Data Analysis
As discussed above, I employed a multi method approach, which entailed analysis of a wide variety of of data. In order to analyse the practices within these materials that pertain to the making of South Asian risk, it was pertinent to perform abductive analysis in order to observe
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risk as made in the diabetes landscape practices I was analysing rather than based on any pre-assumptions I had. This was in order to prevent myself from ‘naturalising categories of ethnic risk’ (Krebbekx, Spronk, M’charek 2016: 639) as much as I was able.
4.2.1 Coding framework
Transcripts and notes were read through numerous times first, in order to observe what elements seemed significant, this also enabled the beginnings of provisional codes to appear. Preliminary coding followed the initial research questions regarding notions of how the South Asian risk category comes into knowing as well as the construction of the how the risky South Asian body and culture, as these themes appeared relevant during interviews. After this initial coding, I devised a ‘coding scheme’ (Bryman 2014: 304) which was adapted over the course of analysis. ATLAS Ti was then utilised in order in order to effectively store and analyse a wide variety of data. Using this tool aided me in finding thematic similarities over a wide range of data from different methods as well as from across a range of disciplines that approach and discuss ethnic risk in different ways.
4.3. Limitations
The first limitation was that the sample size of data is relatively small. Whilst my aim was to build a diverse sample across the diabetes landscape, there were many locations that did not contribute to this data. This leaves my data perhaps unable truly form a cohesive view of risk formation across the diabetes landscape as a whole. As I interviewed more participants from the clinical and biomedical research spheres, this potentially presents a skewed view in the data that reflects scientific determinism (Sherman 1981: 62).
It was my initial intention to investigate more locations ethnographically however this was not possible due to time or logistical restrictions. Other restrictions were ethical, for example
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I was unable to perform observation within the clinical setting due to NHS research ethnic committee (Health Research Authority, 2019). Unfortunately this type of observation could have provided critical points of analysis. However in keeping with research ethical
considerations as outlined by the NHS research ethics committee (Health Research Authority, 2019) my research was unable to include this. I overcame limitations in ethnographic
research by performing supplementary interviews with professionals which bolstered my data set. Although best efforts were made to effectively ‘distil’ (Heuts and Mol 2013: 134)
practices from interviews, it is salient to note that direct observation of these risk making practices would have provided me with better understanding of practices that the STS framework lends itself to. Furthermore, research interviews were ‘constructed and artificial environments’ (Brinkmann, 2016: 525) in which those I interviewed described practices from their point of view, based on what they wished to present, therefore direct observation would have been preferable to truly discern risk making practices. During my fieldwork period, I recognised these limitations and therefore when it came to analysis of data, these limitations were considered throughout the process. Despite these limitations I felt the steps taken to overcome them as I delineated above, still yielded significant and valuable findings.
4.4. Reflexivity
From limitations I have discussed above it is possible to see the ways in which reflexivity is an essential part of this research as it is the process in which I am ‘willing to recognise that methods also craft realities’ (Law 2004: 153). Attending to the process in this way means attending to the ways in which methods and thesis writing makes and remakes knowledge and subjects. A peculiar yet interesting aspect of research is that by situating South Asian risk knowledge production within the ‘diabetes landscape’ as a location that includes research materials, theories and concepts, the thesis paper I construct will, by definition, add to my
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sites of research. This means during the writing process it is important to reflect on what I as the writer of this thesis aims to add to the landscape as not only another source of information but as also another location in which South Asian risk is made, thereby attending to its
construction.
As my interest in this topic lies within being South Asian myself, it was critical to remain aware of potential experience bias distorting my analysis. This was a challenge as this was at least in part the reason for my interest in the topic in the first place. However in remaining cognisant of my positionality, I do not believe this compromised the credibility of my findings. Moreover, my personal relation to the topic was also advantageous due to an ‘insider perspective’ (Bryman 2014: 386). This became a point of interest within the
interviewing experience as in a few instances, participants assumed I had insider experience due to being from a South Asian background.
4.5 Ethical considerations
Ethics was a central concern within this research, mostly for the wellbeing of participants. As race/ethnicity is a highly sensitive and controversial topic this added a layer of complexity to the ethical considerations. It made any approaches to towards consent for instance even more salient for my participants. As some participants particularly from a scientific background had shared with me that they were already nervous about discussing ethnicity for fear of its links with ‘genetic superiority’ (Risch 2002: 11) of race based science. Therefore I attended to approaching the topic of race within research and writing with the utmost sensitivity, particularly in the ways my interviewers could come across. Viewing ethnic risk as ‘constructed’ partially aided this, as it looked beyond issues such as these constructed in ‘race/no race debates’ (Montoya 2011: 14) and rather its use within places it is made
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attending the conference, I gained permission from organisers who were aware of the purpose of this research. Organisers also informed all staff and presenters of my attendance. As a result, I experienced difficulty in accessing true participants through the ‘open route’ (Bryman 2016: 432). As not all those in attendance were aware of my researcher status it could be suggested I accessed participants through the ‘overt route’ (Bryman 2016: 432). For interviews, participants were emailed an information sheet regarding all information about this research as well as what was to be done with the information they gave me. On the day of the interview, this was reiterated a second time, going over what my research topic was, whether they were still comfortable to go ahead with the interview, how their
information would be used and stored and that names and organisations would be
anonymised and replaced with pseudonyms. Furthermore, I made explicit right to opt out at any time during the research process and have their information and recording destroyed. Participants were made aware their information would be recorded and transcribed with audio recorded files being kept in a folder that was password protected.
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Findings
In following three empirical chapters I delineate the results of my findings through the above multi-method approach and analysis. In the first chapter I analyse of the making of the South Asian risk category within epidemiological and laboratory practices to examine how white norms function as the standard from which South Asian risk can be known, thus creating the risky other risky ‘other’ in whilst privileging neutrality in the form of white normativity to the White European category. This chapter discusses this in three locations; a risk score, clinical institutional funding and within the practices of clinical studies.
In chapter two I discuss the making the risky South Asian body. In particular, how the positioning of the South Asian risky body is constructed through suggestion of a ‘pre-disposition’ and an unknown ethnic cause of disease. I then turn to the ways in which this mystery cause is discussed as the result of a genetic susceptibility and how this further communicates notions of risk. Discussion then turns to the ways in which risk is
communicated through the body as the South Asian risky ‘lifestyle’. This then concludes on how these explanatory models rest on each other via the notion of biological citizenship’ (Rose and Novas 2005: 133).
In chapter three I analyse of how powerful the culture-as-risk paradigm functions as the ‘culturalistic fallacy’ (Meershoek and Krumeich 2008: 173) leads to the cultural pathology (Keval 2015: 232) of the South Asian risk category in prevention practices with a specific focus on how it veils discrimination and structural inequalities within diabetes risk despite the condition being widely understood by healthcare professionals as being one of deprivation. Irrationality and noncompliance rather of experiences socioeconomic status and structural racism.
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Chapter Five: Making the South Asian ‘other’
This section aims to answer the question ‘how is the South Asian risk category brought into
knowing?’ Key to answering this question and the making and mobilising of South Asian
risk, is to understand the ways in which they category is made different. One of the ways South Asian risk comes into knowing is through a comparative relationship with ‘the white population’. In this first data chapter I analyse how South Asian diabetic risk comes into knowing through practices that function and rely on its comparison to ‘white normativity’ (Morris 2016: 950). As Bhopal and Donaldson (1998) explain it is common epidemiological practice to ‘seek understanding through comparison’ (1998: 1304) and it can therefore be an especially useful tool in understanding and interpreting burden of disease. However, this study aims to investigate the logics within this form of categorisation, discussing how these practices across diabetes prevention mobilise ‘White’ as the ‘norm’ in order to produce the South Asian risk category as the oppositional ethnic ‘risky other’ (Lupton 2013). As Hacking (2006) conceptualises this in the making of categories, there must be a ‘creation of norms’ (ibid 2006: 164) from which the pathological can deviate. This chapter will therefore discuss the ways in which South Asian risk becomes known in the practices of three locations; a risk score, institutional funding and clinical studies.
5.1 ‘Be Aware of Your Own Risk’ Score
Risk scores in diabetes have been used globally in T2D detection and prevention these tools being central to diabetes prevention in the UK. One of which, I will refer to as ‘Be Aware of Risk’ tool is one of the main strategies, with many other marketing and advertising
campaigns centralising around encouraging the public to use this tool and determine their own risk of Type 2 Diabetes through a self-administered questionnaire. Screening is an integral part to surveillance with diabetes science in order to overall risk such as development
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of future complications. The making of a risk score such as this involves extrapolating from patient data studies and the use of logistic regression to determine risk based factors in the population. Risk scores are not a new phenomenon in healthcare but were traditionally implemented through standardised tools and health professionals in healthcare settings in order to identify ‘real or potential problems’ (Savic, Hunter and Lubman 2016: 577) in health. However, with the technological intervention turn in UK health practices these tools are now online, with individuals gaining direct access and having to ‘self-administer their own risk via the internet’ (Savic, Hunter and Lubman 2016: 566). In the ‘Be Aware of Your Risk’ tool as shown in Figure 5, users answer questions with ranked answers that have different factors and attached values of risk. These are grouped via unchangeable
‘non-modifiable’ risk factors such as age, sex, ethnicity and family history. As well as ‘‘non-modifiable’ factors including waist measurement, body mass index (BMI) and blood pressure.
As shown in Figure 5, ‘Only White European’ groups are given a score of 0 with ‘Other ethnic group’ is receiving a score of ‘6’ as one of the highest risk numbers other than the traditional markers of diabetes, obesity and age.
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After the risk score is completed, depending on the total score given by responses, as seen in Figure 6, the user is then placed into categories of low, medium and high risk, given an attached or future chance of having diabetes and suggestions of how to proceed to improve the health of the individual.
5.1.2 Binary variables in ethnic risk
The risk score uses information from a real life data set and then uses logistic regression analyses in order to produce factors which would relate to chances of getting or already having diabetes. Through this method, risk factors or the ‘independent variables’ are correlated to the predication of having or being at high risk of diabetes, the dependent
variable. This enables the comparison of several factors concurrently. Logistic regression also asks for ‘binary variables’ in the modifiable risk factor section resulting in either/or
estimations of risk and associated scores.
In the making of the risk score, with regards to ethnicity, the choice made by the biostatisticians working on the project was to group risk within the binary ‘Only White European/Other ethnic group’ with the former receiving the score of ‘0’ and the ‘other’ group
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a score of 6. The use of binary variables in terms of risk and ethnicity has been criticised by STS scholars for the production of an asymmetry, producing the normally White ‘reference group or norm’ (Krebbekx, Spronk, M’charek 2016: 638) for the comparable ‘other
particular’ (ibid: 638) ethnic group. The scores of ‘0’ privileges the ‘white’ side of the binary a neutral position regarding diabetes risk. However, the ‘6’ for other ethnic group, places the highly heterogeneous groups within this as the risky ethnic other. Furthermore, the use of binary oppositions regarding ethnicity and communicating diabetic risk also reflects the ‘black/white configurations of race’ (Perea 1997: 127). In the UK context, the categories chosen in the risk score reflects that of ‘White’ and ‘BAME’ groups, which have a long history of the former population being held as the ‘standard’ against which the latter is measured compared and measured, therefore constructing the highly problematic notion of normative ideals. This is not to say that there is no difference in risk between different ethnic groups, however dichotomies such as this hold notions of risky othering (Lupton 2013) and problematize of ethnic groups. With ‘6’ as the mark of ethnic inferiority and diabetes made the problem of the risky ethnic other as a homogenous whole. Furthermore, ethnicity as presented within the screening tools cannot acknowledge the migration history, life experiences, socioeconomic status that have led to higher rates of diabetes associated with being a of non-White European decent. It treats all ethnicities as well as BMI’s, waist
measurements the same, despite potentially differing routes to these measurements, therefore reducing life experience to a single score and category.
5.1.3 Infallibility of numbers and will to health
Risk scores through the apparent use of calculations and resulting numbers are positioned as accurate and objective technologies. This differs from traditional diagnosis in the clinic which is seen as open to interpretation and therefore subjective, this privileges new
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technologies with an ‘algorithmic authority’ (Cheney-Lippold 2011: 1164) giving them standing as ‘decontextualized and fact like’ (Fosket 2004: 300). However, on analysis of the practice in forming ‘any other ethnic group’ score of ‘6’, the motivation behind forming the numbers is not entirely as neutral as the numbers portray. Risk scores are produced to ‘prompt users into making a decision regarding their health’ (Lupton 2014: 132), which is especially pertinent regarding the ‘other ethnic group’. As Lucy, a biostatistician who worked on the formation of the risk score explains:
Lucy: Pragmatically, we know most ethnic groups have a higher risk than White Europeans therefore everyone would get 6 points because they are not white European. They’re an ‘other’ ethnicity. Going on from that we decided we would overestimate the risk, than under estimate it, because it’s a screening tool in a battery of tests. We’d rather send people through than reassure them, encourage them to act.
Although the calculation from the regression analysis is based on what is presented as real life data, as Lucy explains within the making of the score there was an aspect of
‘overestimating’. This is in order to place all those with the ‘other ethnic group’ variable into potentially a higher category of risk, giving them a higher chance of having Type 2 diabetes and encouraging them to engage with the biomedical system. Lucy within her comment acknowledges the role of the risk score as ‘holding a mirror’ (Savic, Hunter and Lubman 2016: 569) up to lives of the ‘other ethnic group’ category in order to prompt action. Lucy’s description also reflects the ways in which risk tools endorse ‘neoliberal imperative of self-care’ (Moore and Fraser 2006) in which health problems are portrayed as problems of
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‘individual deficit’ (Zajdow and MacLean, 2014: 524) and require higher levels of self-regulation. This form of health based action or encouragement through risk profiling has been discussed as ‘blurring the boundaries between coercion and consent’ (Rose 2001: 10) as placing people into high risk groups as a method of contemporary bio-politics aims to change their health subjectivities of those within those groups as a form of ‘population management’ (Rose 2001: 9). Furthermore, the ‘0’ of the ‘only White European’ category communicates that risk as not the problem of this population. However, as Montoya (2011) discusses, this is related to the workings of how diseases are made ‘ethno-racial’ (Montoya 2011: 11) as
numbers are often used to communicate that minority populations are hit ‘harder’ (ibid: 104) than the white population, therefore giving ‘unequal weight to prevalence over raw incidence numbers’ (ibid: 104). This weighting enables the white populations to be seen as
unproblematic and risk-neutral.
Furthermore, algorithms and numbers projects an objectivity that shrouds the bio-political control and neoliberal logic risk score format. Statistics and the making of the risk score is not the result of neutral calculations which are free of wider values but driven by a set of decisions located in a wider culture. The individual in that category is decontextualized from their lives and transformed into a ‘6’, overestimated in order to be placed into a higher risk category. Scores such as this in the form of binary variables is an incidence of how diabetes becomes racialized and legitimised through the infallibility and authority of biomedicine, epidemiology and numbers. Ethnic risk categories are thus brought into knowing through the binary distinctions of white and ethnic, which as the White category is deemed wholly unproblematic, is also the construction of the normal and pathological. The latter ethnic category being held as inherently riskier than the White former. Beyond its inclusion in the ‘other ethnic group’ category, the South Asian body is further subject to this racialisation
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through other diabetes practices in the clinical study setting, which will be discussed in the next section.
5.2 Clinical studies and the ‘white control group’
In the previous section of this chapter, the making of a diabetes risk score was analysed in order to at how the infallibility of numbers constructs the risky ethnic body through the binary relationship to the White European category which is presented as neutral and unproblematic thus making diabetes an ‘ethnoracial’ (Montoya 2011: 11) problem. This section delineates the clinical research practices bring the South Asian risk category into knowing through a comparison to white as the norm. This further constructs the ways in which the category is known as other and risky across the diabetes landscape. The following excerpts are from interviews conducted with four researchers leading different clinical studies investigating diabetes and include ‘South Asian ethnicity’ within both the inclusion criteria and as a listed research group cohort of interest. The main interest with these researchers was to enquire how their different clinical trials studied what they considered to be contributing or potentially contributing factors to the high rates of diabetes seen in UK South Asian
communities. Pertinent to this, are the ways in which researchers discuss ethnicity as only a recently fundable aspect of diabetes research and the way in which this has constructed new and unknown ‘South Asian’ diabetes as formed from a relational difference from known and ‘White diabetes. This has further led to the technique of using ‘White’ as the control group from which the South Asian risk category can be known.
