Open Encyclopedia of Anthropology - Biopower

Diabetes

Rebecca Tishler — Mon, 01 May 2023 08:04:50 +0000

Person getting tested for high blood pressure and diabetes at Prince Mshiyeni Memorial Hospital in South Africa in 2012. Photo: GovernmentZA

Shir Lerman Ginzburg

Massachusetts College of Pharmacy and Health Sciences

Initially published 1 May 2023

http://doi.org/10.29164/23diabetes

Abstract:

Type 2 diabetes mellitus is a global disease that involves the body’s impaired ability to regulate blood sugar (glucose) due to malfunctioning insulin, a hormone produced in the pancreas which is responsible for transporting the glucose into the cells. Anthropologists have provided meaningful insights into the causes (aetiologies) and prevalence of diabetes, particularly focusing on the social, political, and economic factors that underlie the ways in which diabetes continues to afflict millions of people worldwide. As a chronic illness with no cure, diabetes poses unique challenges for people struggling to manage medications, food changes, and multiple medical appointments, particularly for those who are already suffering from other structural barriers to health. Furthermore, anthropologists have highlighted the importance of identifying the overlaps between diabetes and other chronic diseases in order to provide better treatment options and to understand the underlying structural conditions that contribute to diabetes, such as poverty and unemployment. The ‘syndemics’ framework is a useful tool for considering the multileveled approaches to diabetes aetiologies and preventions.

Introduction

Diabetes, a cluster of diseases that impact the body’s ability to process insulin, is well-established as a chronic illness, having been described as such as early as 1500 BCE, when an Egyptian manuscript described a ‘too great emptying of the urine’, although Apollonius of Memphis was the first to call the disease ‘diabetes’ in 250 BCE (Trikkalinou et al. 2017). Several centuries later, an unnamed seventeenth-century English surgeon called diabetes ‘the pissing evile’ due to the frequent urination common to people with the disease (Karamanou et al. 2016; Kelleher 1988). Unfortunately, most diabetes itself is rather less colourful, albeit equally dangerous if left unchecked. Diabetes is a chronic disease characterised by high glucose due to the body’s inability to produce and/or process insulin, a hormone that helps the body use energy (Carruth et al. 2019; Mendenhall et al. 2010; Schoenberg et al. 2005). People are clinically diagnosed with diabetes if their fasting glucose blood test levels are over 126 mg/L or have a three-month average hemoglobin (HbA1c) level of at least 6.0%.^[1] The number of adults (ages 20-79) worldwide living with diabetes reached 537 million people in 2021 and researchers estimate that by 2045, 783 million individuals worldwide will have diabetes.^[2]

Symptoms for diabetes include increased urination and thirst, unintentional weight loss, blurred vision, exhaustion, tingling hands and feet, and dry skin. Diabetes is sometimes called ‘the silent killer’ because these symptoms are so common that they are oftentimes attributed to other things, leading to worsening disease outcomes and decreased quality of life before a diagnosis is even made. Untreated diabetes can lead to coronary artery disease, renal failure, and blindness, and is correlated with high blood pressure (hypertension), high cholesterol (dyslipidaemia), arthritis, and depression (Mendenhall 2019; Trikkalinou et al. 2017).

Healthcare providers generally diagnose individuals as having one of three broad types of diabetes: type 1, type 2, and gestational. All three types share the same general symptoms and basic cause (a cellular inability to absorb glucose for fuel due to a failure to recognise insulin) but differ in the physiological details and cultural paradigms of aetiology and treatment. This entry will begin by outlining the three general types of diabetes and then discuss how anthropologists shed light on interacting cultural models of diabetes diagnosis, treatment, and long-term care.

Types of diabetes

Type 1 diabetes mellitus is an autoimmune reaction wherein the body’s defence system attacks the cells that create insulin, causing a severe insulin shortage in the body and allowing for a dangerous accumulation of glucose in the blood. Unchecked type 1 diabetes can contribute to nerve damage (neuropathy), kidney damage (nephropathy), eye damage (diabetic retinopathy), foot damage, heart disease, and skin infections.^[3] It is linked to both genetic and environmental factors, although the exact causes are not yet known and there is no known cure. Type 1 typically develops in children and young adults and requires individuals to inject insulin daily to remain healthy.^[4] Approximately 10% of people worldwide have type 1 diabetes as of July 2020.^[5]

Gestational diabetes develops in pregnant women who did not already have diabetes prior to pregnancy. This type of diabetes physiologically resembles the other types in that the body struggles to recognise insulin, which leads to higher levels of glucose in the bloodstream. While glucose levels generally return to normal after giving birth, women who have gestational diabetes are at higher risk for developing type 2 diabetes later in life.^[6]The precise origins of gestational diabetes are unknown, yet researchers suggest that the mother’s pre-pregnancy weight, physical inactivity during pregnancy, being of certain races or ethnicities (such as Black, Hispanic, and American Indian), having a family history of diabetes, and having polycystic ovarian syndrome are all contributing factors.^[7] Approximately 14% of women worldwide had gestational diabetes during pregnancy in 2021 (Wang et al. 2022).

Type 2 diabetes has become a pandemic, catching the attention of researchers and healthcare providers alike due to the urgent nature of its scope. Like the other diabetes types, type 2 involves high blood glucose levels, but unlike the other types, in type 2 the pancreas produces sufficient insulin. Instead, cells resist insulin’s efforts to transport glucose into the cells (insulin resistance), resulting in rising blood glucose levels and causing the pancreas to create more insulin. However, the cells continue to resist the insulin’s efforts, resulting in even higher glucose levels which can cause major health problems, such as heart disease, liver and kidney failure, and vision loss.^[8] Type 2 diabetes accounts for 95% of diabetes cases worldwide, with physical inactivity, being overweight or obese, and socioeconomic factors like poverty being major contributing factors.^[9]

This entry focuses on type 2 diabetes due to its overwhelming global prevalence and due to the biomedical focus on solely individual behaviours. Diabetes is commonly known among biomedical healthcare providers as the ‘lifestyle type’ due to its association with overconsumption and sedentary behaviours, which are generally blamed on individual patients (Carruth et al. 2019; Yates-Doerr 2011). However, this framing ignores the social, economic, and political contexts that impact the diabetes experiences of many patients. While anthropologists acknowledge the different clinical diabetes types, they also recognise the limitations of clinical diagnosis in getting to the deeper causes of diabetes.

Structural roots and barriers to care

Diabetes is what medical anthropologists term a ‘disease of modernisation’ due to its association with structural factors, such as poverty, unemployment, and colonisation (Baglar 2013; Ely et al. 2011; Mendenhall et al. 2010; Singer 2020; Wiedman 2012). At the same time, diabetes management has become exponentially more expensive due to the rise in transportation, housing, healthcare, and food costs, which negatively impact many peoples’ ability to consistently afford the many changes that are recommended by healthcare providers, particularly when many individuals are already struggling to pay for rent and other necessary living expenses (Mendenhall 2015; Thorsen et al. 2020; Vest et al. 2013; Weaver 2018). High costs of diagnosis and treatment contribute to diabetes being diagnosed later in its development and enable it to have more destructive effects.

Quality of life for people with diabetes depends on their financial resources, geographic proximity to healthcare services and social support networks, physical pain or discomfort levels, and dietary patterns. The uncertain, long-term benefits of living with minimal complications often conflict with the day-to-day difficulties of diabetes maintenance, which negatively impacts stress levels (Black et al. 2017; Speight et al. 2019). Anthropologists tend to note that not all populations experience the same quality of life in living with diabetes, as some communities face additional social, economic, and racial disparities on top of pre-existing health disparities that make a life of diabetes much harder (e.g. Rock 2003a; Wiedman 2021 and Weaver 2018). For example, Janet Page-Reeves and colleagues (2013) note that individual decisions and human agency is heavily constrained by social environments (structure) when it comes to diagnosing and treating diabetes. The social environment that Page-Reeves and others study is that of Hispanics in the state of New Mexico. They incorporate specific conceptual models of illness such as emotional regulation of symptom experience and biomedical diabetes aetiology, and core cultural values such as religiosity and prioritising the family to understand and deal with the disease. Page-Reeves and colleagues observe that in situations with limited economic resources, deciding where to spend money can be a difficult choice, particularly if family members with diabetes need to buy healthier (and more expensive) foods on top of multiple visits to the doctor.

The structural nature of diabetes reflects community-level inequalities in access to different foods, healthcare, education, and other necessary resources. While diabetes is currently present in all populations worldwide, it disproportionately affects low-income populations due to multiple factors that intersect with poverty, such as unemployment, food insecurity, unaffordable healthcare, and non-existent social support (Ferzacca 2012; Lerman Ginzburg 2020; Mendenhall et al. 2017; Rock 2003a; Solomon 2016; Weaver 2018).

A significant ethnography on the structural experiences of vulnerable populations with diabetes is Carolyn Smith-Morris’ 2006 ethnography of diabetes among the Akimel O’odham (colloquially known by outsiders as the Pima), a Native American tribe based by the Gila River in the state of Arizona and the northern Mexican desert. Smith-Morris found that the sweltering Arizona heat, unemployment, and poverty were all factors in the Akimel O’odham developing diabetes. Here, starkly high levels of unemployment and high reliance on government assistance coupled with limited economic resources, reduced physical exercise due to the heat, limited affordable healthy food options on the Pima reservation, and use of food as a comfort against daily struggles, were all contributing factors to developing diabetes. Although the Akimel O’odham have lived near the Gila River for centuries and are familiar with the high temperatures, their responses to it have changed in the past hundred years. As the Gila River has dried up, the Akimel O’odham lost their traditional farms and increasingly relied on government-subsidised foodstuffs (Smith-Morris 2006). Notably, the drying up of the Gila River was not a natural phenomenon, but resulted from the Arizona government’s extensive irrigation efforts as well as damming by non-Native farmers. However, policies of the US Department of Agriculture (USDA), which extended into the 1980s, forbade the Akimel O’odham from receiving help from agricultural loans. Combined with the loss of traditional food pathways, these policies forced the Akimel O’odham to obtain sedentary jobs and rely on high-calorie, poor-nutrition governmental food handouts (Booth et al. 2017; Smith-Morris 2006). Indeed, diabetes is so ubiquitous in the Akimel O’odham that participants in Smith-Morris’ research naturalised it more and more, observing, ‘it’s just how Pimas are’ (2006: 33).

Smith-Morris’s work with the Akimel O’odham highlights how political and economic factors contributed to diabetes aetiology in a population already facing racism and other abuses from the very government that was supposed to care for them. Recent work in Nepal supports these findings. Here, governmental inaction in the face of rigid social hierarchies and discrimination against the Dalits–members of the lowest social caste–creates structural situations of high diabetes risk (Thapa 2014). While caste-based discrimination is officially illegal in Nepal, social hierarchies forbid Dalits from participating in many social, religious, educational, and employment opportunities, forcing them into poverty, food insecurity, and occupational and housing uncertainty—all of which elevate diabetes risk. Given that existing social hierarchies are deeply entrenched, the Nepalese government has found it difficult to enforce anti-discrimination laws; in doing so, the Nepalese government failed to take care of its most vulnerable members and reduce Dalit diabetes risk. In this example, it is government negligence, rather than active mismanagement, that increases diabetes risk.

Additionally, colonisation is a structural factor that boosts diabetes risk, particularly as its effects continue for generations after the dissolution of the original colonising state. Indigenous communities that have experienced colonisation face extremely high diabetes rates due to a loss of traditional lands and food sources, cycles of food insecurity, and mental distress from oppressive regimes. In Canada, the diabetes prevalence rate is four times higher among Indigenous communities than in the general population due to decades of the Canadian government enforcing starvation, stress, food insecurity, and the environmental degradation of traditional food sources such as fishing (Temblay et al. 2021). Similarly, high diabetes rates in the Marshall Islands have been linked to the World War II-era devastation of breadfruit trees, which were a traditional food source for Indigenous communities (Duke 2017). The US began distributing canned meat and white rice when it colonised the Marshall Islands after the war. This abrupt change in food acquisition and preparation negatively impacted the Marshallese’s relationship with their environments and their bodies by increasing their reliance on imported canned foods, which are high in additives, rather than on fresh and local resources.

The geographic diversity of these case studies emphasises an urgent need for studying the complex historical, structural, and traumatic roots of diabetes in greater depth. Prolonged exposure to colonialism is associated with a profound loss of traditional food acquisition, preparation and consumption, and subsequently high levels of food insecurity and malnutrition even when a colonising regime no longer exists. The loss of traditional livelihoods and diminished community self-determination undermine socioeconomic development among oppressed communities. Particularly, it leaves rural communities in debilitating working conditions with only limited access to comprehensive primary care or physical activity options, like walking trails, that are weather-safe for year-round use (Rice et al. 2016; Tremblay et al. 2021).

The colonial roots of diabetes serve as a stark reminder that health is due as much to structural environments as it is to biology. As these and other ethnographies demonstrate, structural environments contribute to diabetes being a social disease as participants shared stories about their etiological foundations of diabetes and the ways in which adjusting to a new life required new perspectives.

Diabetes and biopower

Although, as the ethnographies above elucidate, anthropologists have studied diabetes susceptibility among different populations, anthropological literature has also cautioned against relying on rigid, overly simplistic ethnic categories to understand diabetes because they miss the nuanced biological human variations between and among ethnic groups that contribute to diabetes risk (Montoya 2007). Labelling individuals or entire populations as ‘at risk’ for diabetes based on easy single-gene categories risks ‘naïve genetic determinism’ that glosses over the need for deeper analysis of the social and environmental histories of different populations that shape their susceptibility to diabetes (Montoya 2007). Anthropologists have contributed valuable insight into the social, political, and environmental pressures that individuals and populations face, particularly by incorporating biopower—the regulation of human life at the population and individual body levels—and the politics of health, body image, illness metaphors, and explanatory models into the frameworks of diabetes aetiologies and lived experiences (Ferzacca 2012).

For example, research on the clinical encounters of diabetes highlights the difference between clinicians’ perspectives on diabetes and the perspectives of patients with diabetes (Guell 2011; Hernandez 1995; Hunt et al. 1998). Cheri Hernandez (1995), in an ethnographic study on the clinical parameters of diabetes management, observed that while healthcare providers emphasise maintaining acceptable glucose levels and adhering to medication and weight loss regimens, patients prioritise learning how to live with diabetes. Patients with diabetes often found biomedical explanations for diabetes to be insufficient and attributed their diabetes to personally-relevant triggering events and behaviours. Those who believed that their own behaviours were causes of diabetes tended to be more involved in their treatment; the act of being involved in treatment was associated with long-term behaviour change (Hunt et al. 1998).

While Hernandez and Linda Hunt et al. focused on the individual’s biomedical encounters for diabetes treatment, others have expanded this approach to the collective diabetes experience. Cornelia Guell (2011) draws attention to the conflicting hierarchies of diabetes knowledge in Germany that arose among Turkish migrants in Berlin. Tensions arose between Turkish healthcare providers and layperson self-help groups over conflicting values and knowledge hierarchies about diabetes. Along with fierce competition for limited funding for community diabetes clinics and health education classes, these differences in diabetes knowledge not only pitted the community and healthcare providers against one another but also created rifts in a community already facing severe marginalisation. Similarly, healthcare providers frequently place the responsibility for diabetes management squarely on the patient, making them ‘morally liable for their own ill health’, as Rebecca Seligman and colleagues have highlighted in their work on Mexican immigrants with diabetes in the city of Chicago (2015: 64). Many physicians believed that structural and social interventions were not part of their jobs, preferring to focus solely on clinical treatments without being concerned for the underlying social and structural roots of diabetes (Mendenhall et al. 2017). This arbitrary dividing of responsibility is harmful and perpetuates the deeper structures contributing to diabetes. It also conflicts with how people living with diabetes view their own diabetes aetiologies. Many people who spoke with Seligman et al. (2015) attributed their diabetes to structural factors, such as interpersonal violence, poverty, and unemployment, indicating that the biomedical emphasis on individual patient responsibility overlooks patients’ lived experiences with diabetes.

Diabetes management is complex and fraught with overlapping layers of meaning. A major theme in the anthropological literature on diabetes is that of responsibility and control over diabetic bodies. Biomedicine, in its fervent pursuit of individualised health, places the locus of control directly onto the patient to manage self-care; when diabetic bodies do not behave according to biomedically prescribed plans, the onus of responsibility falls squarely on the patient. Biopower, or the regulation of human life at the population and individual body levels, is used to discipline misbehaving bodies into docile conformity through state-controlled sites, such as schools, hospitals, and prisons (Foucault 1976). Bodies become political and economic battlegrounds between policymakers and healthcare providers as debates rage over the best ways to prevent and treat diabetes, while at the same time these forces exert control over the individuals who are inhabiting the very bodies at the centre of these debates (Gibson and Dempsey 2015).

One example of biopower in a colonisation framework is among Indigenous communities in Canada. Indigenous children at residential schools in Canada developed negative relationships with food due to malnourishment, abuse, punishment, and humiliation perpetuated in the residential school environment (Howard 2014). These collective traumas and negative lived experiences of residential school food were passed on to subsequent generations, where, aided by a loss of traditional food pathways due to aggressive colonisation by the Canadian government, they are embodied as diabetes among Canada’s Indigenous communities. Indigenous interactions with contemporary healthcare systems in Canada have reinforced colonisation through racism, stereotyping, and discrimination (Jacklin et al. 2017). Patients reported being repeatedly ignored or patronised at medical appointments despite having travelled long distances for check-ups. Physician shortages and geographic isolation from clinics contributed to diabetes mismanagement, as patients sometimes waited for several months without seeing a physician or having their medications refilled. In both cases, colonialism reinforced the stereotype of misbehaving diabetic bodies and placed the blame firmly on Indigenous communities for their own diabetes while diffusing blame from the state-sanctioned violence of colonisation that is responsible for diabetes perpetuation.

One of the most fundamental contributing factors to biopower and diabetes is the question of control over the very parameters of health. US doctors who led medical missions to Belize taught the locals that diabetes was the individual’s responsibility, rather than the doctor’s liability (Moran-Thomas 2019). This biomedical focus on patient responsibility for diabetes maintenance absolved doctors of the obligation to consider the roles of broader social, economic, and political milieus in which their patients lived. Doctors did not spend much time helping patients identify the early warning signs of diabetes but simply told them to lose weight and get more physical activity, despite limited access to healthy, affordable foods, safe infrastructure for outdoor activity, or disposable income for gym memberships. Amy Moran-Thomas notes that this lack of comprehensive medical care is notable because, as diabetes is not transmitted between people, there is less biomedical focus on the ways in which people’s interactions propagate the disease and more on the individual’s genetics and decisions that make someone more at risk for diabetes, despite the blatant social risk factors. As such, patients are blamed for noncompliance, frequently without evidence, despite the structural factors that exacerbate diabetes risk.

The physical body is also shaped by cultural metaphors of health and diabetes and naturalises certain cultural norms while stigmatising others (Martin 1987; Solomon 2016; Hardin 2018). This is evident in the ways in which diabetes is stigmatised due to its socially perceived associations with uncontrollable food consumption (Aghamohammadi-Kalkhoran and Valizadeh 2016; Broom and Whittaker 2004; Ferzacca 2012; Lee et al. 2015). For example, Amanda Willig and colleagues (2014) found that African American women with diabetes reported experiencing diabetes stigma when they were the only ones in their extended families with the disease, as they were perceived as having no self-control over their health and were treated as children without the ability to make decisions for themselves. Denise Bockwoldt and colleagues (2016) found that African Americans are less likely to adhere to insulin-based medication regimes due to a plethora of negative emotions associated with insulin, such as self-blame, frustration, fear of complications, and of being a burden on loved ones. Some study participants admitted to hiding their insulin from their loved ones so as to not be outed as insulin dependent. These results were replicated by Kryseana Harper et al. (2018), who found that family-based diabetes stigma was common in their mixed-gender African American cohort. This stigma both perpetuated a reduction in diabetes self-management and created resentment towards diabetes for the disruption it caused to peoples’ personal lives.

Additionally, healthcare providers sometimes stigmatise people with diabetes if they do not lose weight or adhere to their prescribed medication regimens, which further discourages people from visiting a healthcare provider (McNaughton 2013; Shahab et al. 2019). People with diabetes who need to inject insulin may also be mistaken for and stigmatised as drug users should they need to inject insulin in public (Balfe and Jackson 2007; Bock 2012). In the United States, a country in which productivity is highly valued, any loss of individual productivity is devalued and stigmatised, particularly if the cause of that loss is concealed or is a manageable disease, as diabetes is commonly thought to be (Ferzacca 2012; Hopper 1981; Shahab et al. 2019). External stigma over perceived loss of productivity and lack of individual discipline that are thought to contribute to diabetes become internalised among those living with diabetes or are involved in its treatment, and perpetuate individual and biomedical diabetes mismanagement (Aghamohammadi-Kalkhoran and Valizadeh 2016; Ferzacca 2012; Seligman et al. 2015).

Anthropologists reject the overly simplistic categorisations of diabetes as a disease of racial and genetic determinism, preferring instead to trace the overlapping intersections between biological pathways and structural factors. In her work with the Native community in Chicago, Margaret Pollak (2018) notes that anthropologists reject the thrifty genotype hypotheses, which speculates that people are biologically predisposed to diabetes, which is then triggered by social environments. Instead, the alarmingly high diabetes rates among certain communities are explored in relation to external influences, such as colonisation and land loss among American Indians in Chicago. Diabetes care is also a multigenerational, life-long social activity in Native communities, with friends and family helping one another inject insulin, manage medication schedules, and eat diabetes-friendly meals. In this way, diabetes is transformed from a biological disease into a form of social cohesion against colonial forces that attempt to destroy Native physical and collective bodies.

As these studies and ethnographies highlight, the biological and social spheres of diabetes consistently intersect, and these intersections manifest differently depending on the population and their social, psychological, and structural circumstances.

Syndemic interactions

In keeping with the anthropological emphasis on complex, multileveled interactions that underscore disease perpetuations, scholars have drawn attention to the ways in which structural factors exacerbate diabetes outcomes by focusing on parts of the world that have reported abrupt increases in diabetes prevalence (Mendenhall 2012; Weaver 2018).

The theory of syndemics has gained traction in anthropological diabetes research, as it provides a framework for understanding the social, political, and economic underpinnings of illness and disease interactions. Syndemics examines the concentration and deleterious interaction of two or more diseases or other health conditions in a population, particularly as a consequence of social inequality and the unjust exercise of power (Singer 2009: xv). Multiple anthropologists have observed that diabetes is a common component of syndemics research due to its increased incidence and prevalence (Everett and Wieland 2013; Lerman 2017, 2022; Mendenhall 2012; Ryan and Raja 2016; Weaver 2018; Weaver and Mendenhall 2014). Specifically, diabetes interacts synergistically with two other common occurrences: depression and food insecurity.

Research indicates that slightly over one-third of individuals with diabetes will develop depression and vice versa, and that individuals with diabetes are twice as likely as individuals without diabetes to develop depression (Gask et al. 2011; Katon et al. 2010; McSharry et al. 2013; Mendenhall 2012). While some evidence implicates depression as a precursor and major contributor to diabetes (Joseph and Golden 2017; Mendenhall 2015; Vrshek-Schallhorn et al. 2013), diabetes also increases the risk for developing depression (Katon 2010; Gask et al. 2011; Nash 2013). Depression, in turn, contributes to decreased diabetes self-care and access to healthcare, including decreased glucose monitoring, missed medical appointments, and increased likelihood of diabetes complications through diabetes mismanagement (Nash 2013; Weaver and Hadley 2011). Conversely, diabetes contributes to depression by deteriorating social networks, draining financial resources, and changing dietary patterns (Katon et al. 2010; McSharry et al. 2013). Food is a cohesive force: holidays, meetings, family meals, and casual gatherings often include food sharing (Lerman Ginzburg 2022b). When an individual cannot partake due to diabetes-related dietary limitations, the ensuing feelings of guilt or shame may provoke reluctance to attend the event, adding to social isolation. This is particularly true of women, who tend to be the primary cooks in their families and do not always receive support from their families to prepare healthier meals (Lerman Ginzburg 2022b).

The relationship between food insecurity and diabetes is rooted in structural factors. For example, Olayinka Shiyanbola and colleagues (2018) found that African Americans with diabetes attributed their disease outcomes to eating habits that were rooted in slavery and an ensuing consistent lack of healthy foods. Shiyanbola and colleagues’ work adds on to Lisa Sumlin and Sharon Brown (2017), who found that African American women attributed their diabetes rates to dietary patterns and cultural culinary practices that are grounded in slavery and expounded by centuries of poverty. Populations that have been abruptly introduced to and adopted Westernised dietary patterns, such as the Pima Native Americans in Arizona and the Nauruan Islanders in Micronesia, are exceptionally vulnerable to developing diabetes due to rapid changes in nutrition, through increased consumption of highly processed foods that are high in sodium, fats, and carbohydrates (Hardin 2015; Smith-Morris 2006; Solomon 2016; Weaver 2018). Western eating patterns were oftentimes forcibly imposed on unwilling communities, and these forced eating patterns went hand-in-hand with overlapping structural factors that accentuated the incidence of diabetes among the affected communities (Hardin 2015; Smith-Morris 2006).

Diabetes and food insecurity are also correlated with poverty, particularly in combination with the absence of affordable healthcare and housing (McNaughton 2013; Mendenhall 2015; Vest et al. 2013). In their study on diabetes among Canadians living in poverty, Dennis Raphael and colleagues (2012) found that since the government’s public policy dictates the incidence and experience of poverty, and that poverty and ensuing material deprivation are contributors to increased rates of diabetes, mitigating diabetes levels require changes at the government level, and not merely at the individual level. Studies such as these serve as a reminder that food insecurity cannot be attributed merely to individual-level food decisions, but also depends on government policies that impact access to financial assistance for low-income families. For example, my research in Puerto Rico explores participants’ experiences of eating whichever food was most easily economically and geographically accessible due to an influx of food taxes, high-end supermarkets in gated communities, and economic and political instability (Lerman Ginzburg 2022a). Thus, merely turning health and treatment into easy formulae ignores the agricultural, historical, social, and political specificities that are interwoven into food consumption (Emily Yates-Doerr 2015). This critical scholarship underscores the need for ethnographic research that situates food insecurity and diabetes not merely within biomedical milieus, but also as products of social, political, and economic forces.

Just as structural factors, such as interpersonal violence and poverty, are critical syndemic perpetuators, similarly community responsibility and collective care play a role in diabetes management. Jessica Hardin (2018), in her ethnographic work on cardiometabolic disorders in Samoa, highlights how healing is both individualistic and collective that both ‘transform individual bodies while impacting the broader community, making evident the problems of the collective in the bodies of individual Christians’, a process which she calls ‘embodied critique’ (5-6). Hardin found that her Samoan participants encouraged one another to link illness events with the state of their relationships. Concepts such as embodied critique move beyond individual bodies to encompass the broader community and the structural factors that underlie diabetes aetiology. While part of the responsibility was on the individual to manage their diabetes, including taking medications, structural factors like poverty and unemployment also contributed to diabetes, which made it harder for study participants to make the necessary changes.

In Puerto Rico too, the participants I worked with linked diabetes with broader socio-political problems, such as Puerto Rico's status as a US territory (Lerman Ginzburg 2017, 2022a). The 1917 Jones Act forced food shipped to Puerto Rico to be marked up in price to compensate for the shipping, but this cost is borne by Puerto Ricans. Their experiences of eating whichever foods were most easily economically and geographically accessible connected food insecurity and diabetes with US colonisation and political nepotism. People developed depression because of the high unemployment and crime rates, ate large quantities of cheap high-fat food because of food insecurity and food apartheid, and developed diabetes. Similarly, in tracing the syndemic underpinnings of diabetes and COVID-19, anthropologists like Merrill Singer (2020) have commented that NAFTA created ‘diabetes-inducing’ environments in Mexico by triggering a growing dependence on unhealthy food imports, mostly from the US, amid a national agricultural deficit that limited Mexicans’ access to the fresh produce grown in their own backyards. The rapid change in agricultural output and ensuing urbanisation created situations of stress, identity loss, and profound changes in dietary practices that contributed to diabetes risk.

Corporate influences on diabetes

Most of this entry has focused on the structural factors that impact the lived experiences of diabetes. However, there is also a corporate component to diabetes that impacts the quality of care. Medical anthropologists studying diabetes in the United States have argued that clinical care in the country is increasingly driven by large corporations, with a mounting emphasis on financial and managerial logics that reduce diabetes care to a narrow set of quantifiable metrics (Hunt et al. 2019). Healthcare providers measure successful diabetes management by monitoring glucose and HbA1c levels, medication regimen adherence, and significant weight loss, all of which are easily enumerated but difficult to achieve due to the multiple structural barriers associated with diabetes. Health insurance plans in the US use these quantitative parameters to determine approval of healthcare expenses while ignoring the underlying structural and social barriers that might prevent patients from managing their diabetes. Scholars also argue that screening, diagnosis, and treatment guidelines over the past forty years have changed under pressure from the pharmaceutical industry despite weak evidence of efficacy in order to benefit from promoting expensive medications to unsuspecting patients (Hunt et al. 2019). Additionally, easing the diagnostic criteria for diabetes means that more people are diagnosed with the illness, and therefore required to take medications. In tracing these linkages, scholars have recommended that individual vigilance over diabetes management be augmented with systemic surveillance by healthcare providers and by policymakers who are at the forefront of medical innovations, healthcare funding, and institutional policies (Rock 2003b). Such recommendations reiterate that structural factors that impact underserved populations with high diabetes rates are rooted in unjust policies that can only be remedied at a higher political level.

Conclusion

Diabetes continues to be a globally pervasive disease, particularly in low- and middle-income countries which are facing rapid changes in the mechanisation of labour, political stability, economic independence, and profound social unrest. Despite the advances in biomedical treatment options, diabetes continues to afflict millions of people around the world, which indicates that there is a pressing need for accessible treatment options. For example, the price of insulin is ten times more expensive in the US than in any other developed country, leading many people with diabetes to ration their insulin and risk their health if their health insurance doesn’t cover the cost (Rajkumar 2020). This travesty highlights the need for thorough healthcare reform in the US in particular. Furthermore, it is imperative that the structural factors underlying diabetes in societies throughout the world be considered during treatment. Multiple, overlapping factors, such as colonisation, poverty, and unemployment are inexorably linked to diabetes, and it is those factors which we must address as we move forward with diabetes treatment options. Thinking of syndemics is a useful way for digging more deeply into the aetiologies of diabetes, so that culturally-specific and affordable preventions might be developed and rapidly implemented.

References

Aghamohammadi-Kalkhoran, Masoumeh and Sousan Valizadeh. 2016. “Fears and concerns of Iranian diabetic women: A phenomenological study.” Journal of Health Psychology 21, no. 7: 1322–30.

Baglar, Rosslyn. 2013. “Oh God, save us from sugar”: An ethnographic exploration of diabetes mellitus in the United Arab Emirates.” Medical Anthropology: Cross-Cultural Studies in Health and Illness 32, no. 2: 109–25.

Balfe, Myles and Peter Jackson. 2007. “Technologies, diabetes, and the student body.” Health & Place 13, no. 4: 775–87.

Berkowitz, Seth A., Travis P. Baggett, Deborah J. Wexler, Karen Huskey and Christina C. Wee. 2013. “Food insecurity and metabolic control among U.S. adults with diabetes.” Diabetes Care 36: 3093–99.

Black, Stephen, Catherine Maitland, Julieanne Hilbers and Kirsty Orinuela. 2017. “Diabetes literacy and informal social support: a qualitative study of patients at a diabetes centre.” Journal of Clinical Nursing 26, no. 1: 248–57.

Bock, Sheila. 2012. “Contextualization, reflexivity, and the study of diabetes-related stigma.” Journal of Folklore Research 49, no. 2: 153–78.

Bockwoldt, Denise, Beth A. Staffileno, Lola Coke and Lauretta Quinn. 2016. “Perceptions of insulin treatment among African Americans with uncontrolled type 2 diabetes.” Journal of Transcultural Nursing 27, no. 2: 172–80.

Booth, Clayton, Maziar M. Nourian, Shannon Weaver and Bethany Gull. 2017. Policy and social factors influencing diabetes among Pima Indians in Arizona, USA.” Public Policy and Administration Research 7, no. 3: 35–9.

Broom, Dorothy and Andrea Whittaker. 2004. “Controlling diabetes, controlling diabetics: Moral language in the management of diabetes type 2.” Social Science & Medicine 58: 2371–82.

Bunkley, Emma. 2021. “Diagnosing diabetes, diagnosing colonialism: An ethnography of the classification and counting of a Senegalese metabolic disease.” Medical Anthropology Theory 8, no. 2: 1–26.

Carruth, Lauren, Sarah Chard, Heather A. Howard, Lenore Manderson, Emily Mendenhall, Emily Vasquez and Emily Yates-Doerr. 2019. “Disaggregating diabetes: New subtypes, causes, and care.” Medical Anthropology Theory 6, no. 4: 119–26.

Duke, Michael. 2017. “Neo-colonialism and health care access among Marshall Islanders in the United States.” Medical Anthropology Quarterly 31, no. 3: 422–49.

Ely, John, Tony Zavaskis and Susan L. Wilson. 2011. “Diabetes and stress: An anthropological review for study of modernizing populations in the US-Mexico border region.” Rural and Remote Health 11, no. 3: 1758.

Everett, Margaret and Josef Wieland. 2013. “Diabetes among Oaxaca’s transnational population: An emerging syndemic.” Annals of Anthropological Practice 36, no. 2: 295–311.

Everson, Susan A., Siobhan C. Maty, John W. Lynch and George A. Kaplan. 2002. “Epidemiologic evidence for the relation between socioeconomic status and depression, obesity, and diabetes.” Journal of Psychosomatic Research 53, no. 4: 891–5.

Ferzacca, Steve. 2000. “‘Actually, I don’t feel that bad’: Managing diabetes and the clinical encounter.” Medical Anthropology Quarterly 14, no. 1: 28–50.

———. 2012. “Diabetes and culture.” Annual Review of Anthropology 41: 411–26.

Foucault, Michel. 1976. The history of sexuality, volume 1. Translated by Robert Hurley. New York: Vintage Books.

Gask, Linda, Wendy Macdonald and Peter Bower. 2011. “What is the relationship between diabetes and depression? A qualitative meta-synthesis of patient experience of co-morbidity.” Chronic Illness 7, no. 3: 239–52.

Gibson, Kristina and Sarah Dempsey. 2015. “Make good choices, kid: Biopolitics of children’s bodies and school lunch reform in Jamie Oliver’s Food Revolution.” Children’s Geographies 13, no. 1: 44–58.

Greenhalgh, Susan and Megan Carney. 2014. “Bad biocitizens? Latinos and the US ‘obesity epidemic’.” Human Organization 73, no. 3: 267–76.

Guell, Cornelia. 2011. “Candi(e)d action: Biosocialities of Turkish Berliners living with diabetes.” Medical Anthropology Quarterly 25, no. 3: 377–94.

Hardin, Jessica. 2018. Faith and the pursuit of health: Cardiometabolic disorders in Samoa. New Brunswick, N.J.: Rutgers University Press.

Harper, Kryseana, Chandra Y. Osborn and Lindsay Satterwhite Mayberry. 2018. “Patient-perceived family stigma of type 2 diabetes and its consequences.” Families, Systems, & Health 36, no. 1: 113–7.

Hay, M. Cameron. 2010. “Suffering in a productive world: Chronic illness, visibility, and the space beyond agency.” American Ethnologist 37, no. 2: 259–74.

Hernandez, Cheri A. 1995. “The experiences of living with insulin-dependent diabetes: Lessons for the diabetes educator.” The Diabetes Educator 21, no. 1: 33–7.

Howard, Heather A. 2014. “Canadian residential schools and urban Indigenous knowledge production about diabetes.” Medical Anthropology Quarterly 33, no. 6: 529–45.

Hunt, Linda M., Miguel Valenzuela, & Jacqueline Pugh. 1998. “Porque me tocó a mi? Mexican American diabetes patients’ causal stories and their relationship to treatment behaviors.” Social Science & Medicine 26, no. 8: 959–69.

Hunt, Linda M., Hannah S. Bell, Anna C. Martinez-Hume, Funmi Odumosu, and Heather A. Howard. 2019. “Corporate logic in clinical care: The case of diabetes management.” Medical Anthropology Quarterly 33, no. 4: 463–82.

Hunt, Linda M., Elisabeth A. Arndt, Hannah S. Bell, and Heather A. Howard. 2021. “Are corporations re-defining illness and health? The diabetes epidemic, goal numbers, and blockbuster drugs.” Journal of Bioethical Inquiry 18, no. 3: 477–97.

Jacklin, Kristen M., Rita I. Henderson, Michael E. Green, Leah M. Walker, Betty Calam and Lynden J. Crowshoe. 2017. “Health care experiences of Indigenous people living with type 2 diabetes in Canada.” Canadian Medical Association Journal 189, no. 3: E106–12.

Joseph, Joseph J. and Sherita H. Golden. 2017. “Cortisol dysregulation: The bidirectional link between stress, depression, and type 2 diabetes mellitus.” Annals of the New York Academy of Sciences 1391, no. 1: 20–34.

Karamanou, Marianna, Athanase Protogerou, Gregory Tsoucalas, George Androutsos and Effie Poulakou-Rebelakou. 2016. “Milestones in the history of diabetes mellitus: The main contributors.” World Journal of Diabetes 7, no. 1: 1–7.

Katon, Wayne, Mario Maj and Norman Sartorius, eds. 2010. Depression and diabetes. West Sussex, UK: Wiley-Blackwell.

Kelleher, David. 1988. “Coming to terms with diabetes: Coping strategies and non-compliance.” In Living with chronic illness: The experience of patients and their families, edited by Robert Anderson and Michael Bury, 137–55. Boston: Unwin Hyman.

Lee, See-Muah, L.C. Lim, and David Koh. 2015. “Stigma among workers attending a hospital specialist diabetes clinic.” Occupational Medicine 65, no. 1: 67–71.

Lerman, Shir. 2017. “Disordered minds and disordered bodies: Stigma, depression, and obesity syndemics in Puerto Rico.” In Foundations of biosocial health: Stigma and illness interactions, edited by Shir Lerman, Bayla Ostrach and Merrill Singer, 47–83. Lanham, MD: Lexington Press.

Lerman Ginzburg, Shir. 2022a. “Colonial comida: The colonization of food insecurity in Puerto Rico.” Food, Culture & Society 25, no. 1: 18–31.

Lerman Ginzburg, Shir. 2022b. “Sweetened syndemics: Diabetes, obesity, and politics in Puerto Rico.” Journal of Public Health: From Theory to Practice 30, no. 1: 701–9.

Martin, Emily. 1987. The woman in the body: A cultural analysis of reproduction. Boston: Beacon Press.

Manderson, Lenore and Carolyn Smith-Morris, eds. 2010. Chronic conditions, fluid states: Chronicity and the anthropology of illness. New Brunswick, N.J.: Rutgers University Press.

McNoughton, Darlene. 2013. “‘Diabesity’ and the stigmatizing of lifestyle in Australia.” In Obesity: The meaning of measures and the measure of meanings, edited by M. B. McCullough and Jessica H. Hardin, 71–86. New York: Berghahn Press.

McSharry, Jennifer, Felicity L. Bishop, Rona Moss-Morris and Tony Kendrick. 2013. “‘The chicken and egg thing’: Cognitive representations and self-management of multimorbidity in people with diabetes and depression.” Psychology & Health 28, no. 1: 103-19.

Mendenhall, Emily. 2015. “The ‘cost’ of health care: Poverty, depression, and diabetes among Mexican immigrants in the United States.” In Global mental health: Anthropological perspectives, edited by Brandon Kohrt and Emily Mendenhall, 205–20. Walnut Creek, Calif.: Left Coast Press.

Mendenhall, Emily. 2019. Rethinking diabetes: Entanglements with trauma, poverty, and HIV. Ithaca: Cornell University Press.

Mendenhall, Emily, Rebecca Seligman, Alicia Fernandez and Elizabeth A. Jacobs. 2010. “Speaking through diabetes: Rethinking the significance of lay discourses on diabetes.” Medical Anthropology Quarterly 24, no. 2: 220–39.

Mendenhall, Emily, Brandon A. Kohrt, Shane A. Norris, David Ndetei and Dorairaj Prabhakaran. 2017. “Non-communicable disease syndemics: poverty, depression, and diabetes among low-income populations.” The Lancet 389, no. 10072: 951–93.

Montoya, Michael. 2007. “Bioethnic conscription: Genes, race, and Mexicana/o ethnicity in diabetes research.” Cultural Anthropology 22, no. 1: 94–128.

———. 2011. Making the Mexican diabetic: Race, science, and the genetics of inequality. Berkeley: University of California Press.

Moran-Thomas, Amy. 2019. Traveling with sugar: Chronicles of a global epidemic. Oakland: The University of California Press.

Nash, Jen. 2013. Diabetes and wellbeing: Managing the psychological and emotional challenges of diabetes types 1 and 2. Hoboken, N.J.: John Wiley & Sons.

Page-Reeves, Janet, Shiraz I. Mishra, Joshua Niforatos, Lidia Regino, and Robert Bulten. 2013. “An integrated approach to diabetes prevention: Anthropology, public health, and community engagement.” The Qualitative Report 18, no. 2: 1–22.

Pollak, Margaret. 2018. “Care in the context of a chronic epidemic: Caring for diabetes in Chicago’s Native community.” Medical Anthropology Quarterly 32, no. 2: 196–213.

Rajkumar, S. Vincent. 2020. “The high cost of insulin in the United States: An urgent call to action.” Mayo Clinic Proceedings 95, no. 1: P22–8.

Rasmussen, Nicolas. 2019. Fat in the Fifties: America’s first obesity crisis. Baltimore: Johns Hopkins University Press.

Rice, Kathleen, Braden Te Hiwi, Merrick Zwarenstein, Barry Lavallee, Douglas Edward Barre, Stewart B. Harris, and the FORGE AHEAD program team. 2016. “Best practices for the prevention and management of diabetes and obesity-related chronic disease among Indigenous peoples in Canada: A review.” Canadian Journal of Diabetes 40, no. 3: 216–25.

Rock, Melanie. 2003a. “Sweet blood and social suffering: Rethinking cause-effect relationships in diabetes, distress, and duress.” Medical Anthropology: Cross-Cultural Studies in Health and Illness 22, no. 2: 31–74.

———. 2003b. “Death, taxes, public opinion, and the Midas touch of Mary Tyler Moore: Accounting for promises by politicians to help avert and control diabetes.” Medical Anthropology Quarterly 17, no. 2: 200–32.

Ryan, Maria Emanuel and Veena Raja. 2016. Diet, obesity, diabetes, and periodontitis: A syndemic approach to management.” Current Oral Health Reports 3: 14–27.

Schoenberg, Nancy, Elaine M. Drew, Eleanor Palo Stoller and Cary S. Kart. 2005. “Situating stress: Lessons from lay discourses on diabetes.” Medical Anthropology Quarterly 19, no. 2: 171–93.

Seligman, Rebecca, Emily Mendenhall, Maria D. Valdovinos, Alicia Fernandez and Elizabeth A. Jacobs. 2015. “Self-care and subjectivity among Mexican diabetes patients in the United States.” Medical Anthropology Quarterly 29, no. 1: 61–79.

Shahab, Yasin, Olataga Alofivae-Doorbinnia, Jennifer Reath, Freya MacMillan, David Simmons, Kate McBride and Penelope Abbott. 2019. “Samoan migrants’ perspectives on diabetes: A qualitative study.” Health Promotion Journal of Australia 30, no. 3: 317–23.

Shiyanbola, Olayinka O., Earlise Ward and Carolyn Brown. 2018. “Sociocultural influences on African Americans’ representations of type 2 diabetes: A qualitative study.” Ethnicity & Disease 28, no. 1: 25–32.

Singer, Merrill. 2009. Introduction to syndemics: A critical systems approach to public and community health. San Francisco: John Wiley & Sons.

———. 2020. “Deadly companions: COVID-19 and diabetes in Mexico.” Medical Anthropology: Cross-Cultural Studies in Health and Illness 39, no. 8: 660–5.

Smith-Morris, Carolyn. 2006. Diabetes among the Pima: Stories of survival. Tucson: University of Arizona Press.

Solomon, Harris. 2016. Metabolic living: Food, fat, and the absorption of illness in India. Durham, N.C.: Duke University Press.

Speight, Jane, Elizabeth Holmes-Truscott, Christel Hendrieckx, and Soren E. Skovlund. 2019. “Assessing the impact of diabetes on quality of life: What have the past 25 years taught us?” Diabetic Medicine 37, no. 3: 483–92.

SturtzSreetharan, Cindi L., Sarah Trainer, Amber Wutich and Alexandra A. Brewis. 2018. “Moral biocitizenship: Discursively managing food and the body after bariatric surgery.” Journal of Linguistic Anthropology 25, no. 2: 221–40.

Sumlin, Lisa L. and Sharon A. Brown. 2017. “Culture and food practices of African American women with type 2 diabetes.” The Diabetes Educator 43, no. 6: 565–75.

Thapa, Tirtha B. 2014. “Living with diabetes: Lay narratives as idioms of distress among the low-caste Dalit of Nepal.” Medical Anthropology: Cross-Cultural Studies in Health and Illness 33, no. 5: 428–40.

Thorsen, Maggie, Ronald McGarvey and Andreas Thorsen. 2020. “Diabetes management at community health centers: Examining associations with patient and regional characteristics, efficiency, and staffing patterns.” Social Science & Medicine 255: 113017.

Tremblay, Marie-Claude, Maude Bradette-Laplante, Holly O. Witteman, Maman Joyce Dogba, Pascale Breault, Jean-Sebastien Paquette, Emmanuelle Careau, and Sandro Echaquan. 2021. “Providing culturally safe care to Indigenous people living with diabetes: Identifying barriers and enablers from different perspectives.” Health Expectations 24, no. 2: 296–306.

Ulijaszek, Stanley and Hayley Lofink. 2006. “Obesity in biocultural perspective.” Annual Review of Anthropology 35: 337–60.

Vest, Bonnie M., Linda S. Kahn, Andrew Danzo, Laurene Tumiel-Berhalter, Roseanne C. Schuster, Renee Karl, Robert Taylor, Kathryn Glaser, Alexandra Danakas, and Chester H. Fox. 2013. “Diabetes self-management in a low-income population: Impacts of social support and relationships with the health care system.” Chronic Illness 9, no. 2: 145-55.

Vrshek-Schallhorn, Suzanne, Catherine B. Stroud, Leah D. Doane, Susan Minekia, Richard E. Zinbarg, Michelle G. Craske and Emma K. Adam. 2013. “The cortisol awakening response predicts major depression: predictive stability over a 4-year follow-up and effect of depression history.” Psychological Medicine 43, no. 3: 483–93.

Wang, Hui, Ninghua Li, Tawanda Chivese, Mahmoud Werfalli, Hong Sun, Lili Yuen et al and the IDF Diabetes Atlas Committee Hyperglaecemia in Pregnancy Special Interest Group. 2022. “IDF diabetes atlas: Estimation of global and regional gestational diabetes mellitus prevalence for 2021 by International Association of Diabetes in Pregnancy Study Group’s criteria. Diabetes Research and Clinical Practice 183: 109050. https://doi.org/10.1016/j.diabres.2021.109050

Weaver, Lesley Jo. 2018. Sugar and tension: Diabetes and gender in modern India. New Brunswick, N.J.: Rutgers University Press.

Weaver, Lesley Jo and Craig Hadley. 2011. “Social pathways in the comorbidity between type 2 diabetes and mental health concerns in a pilot study of urban middle- and upper-class Indian women.” Ethos 29, no. 2: 211–25.

Weaver, Lesley Jo and Emily Mendenhall. 2014. “Applying syndemics and chronicity: Interpretations from studies of poverty, depression, and diabetes.” Medical Anthropology: Cross-Cultural Studies in Health and Illness 33, no. 2: 92–108.

Weaver, Lesley Jo, Carol M. Worthman, Jason A. DeCaro and S.V. Madhu. 2015. “The signs of stress: Embodiment of biosocial stress among type 2 diabetic women in New Delhi, India.” Social Science & Medicine 131: 122–30.

Wiedman, Dennis. 2012. “Native American embodiment of the chronicities of modernity: Reservation food, diabetes, and the metabolic syndrome among the Kiowa, Comanche, and Apache.” Medical Anthropology Quarterly 26, no. 4: 595–612.

Willig, Amanda L., Brittany S. Richardson, April Agne and Andrea Cherrington. 2014. “Intuitive eating practices among African-American women living with type 2 diabetes: A qualitative study.” Journal of the Academy of Nutrition and Dietetics 114, no. 6: 889–96.

Yates-Doerr, Emily. 2015. The weight of obesity: Hunger and global health in postwar Guatemala. Oakland: The University of California Press.

Note on contributor

Shir Lerman Ginzburg is an assistant professor of public health at Massachusetts College of Pharmacy and Health Sciences. Her research interests include mental health, diabetes, food insecurity, health disparities, Hispanics, obesity, syndemics, and colonisation. She earned her PhD in medical anthropology from the University of Connecticut. She practices yoga and meditation in her free time.

[1] International Diabetes Federation. 2021. “Diabetes facts & figures.” https://www.idf.org/aboutdiabetes/what-is-diabetes/facts-figures.html. Accessed 18 January 2022.

[2] International Diabetes Federation. 2021. “Diabetes facts & figures.” https://www.idf.org/aboutdiabetes/what-is-diabetes/facts-figures.html. Accessed 18 January 2022.

[3] Mayo Clinic. 2022a. “Type 1 diabetes.” https://www.mayoclinic.org/diseases-conditions/type-1-diabetes/symptoms-causes/syc-20353011. Accessed 28 November 2022.

[4] Mayo Clinic. 2022a. “Type 1 diabetes.” https://www.mayoclinic.org/diseases-conditions/type-1-diabetes/symptoms-causes/syc-20353011. Accessed 28 November 2022.

[5] International Diabetes Federation. 2020. “Type 1 diabetes.” https://idf.org/aboutdiabetes/type-1-diabetes.html. Accessed 28 November 2022.

[6] Mayo Clinic. 2002b. “Gestational diabetes.” https://www.mayoclinic.org/diseases-conditions/gestational-diabetes/symptoms-causes/syc-20355339. Accessed 29 November 2022.

[7] National Institute of Diabetes and Digestive and Kidney Diseases. 2022. “Gestational diabetes.” https://www.niddk.nih.gov/health-information/diabetes/overview/what-is-diabetes/gestational. Accessed 29 November 2022.

[8] Harvard Medical School. 2022. “Type 2 diabetes mellitus.” https://www.health.harvard.edu/a_to_z/type-2-diabetes-mellitus-a-to-z. Accessed 29 November 2022.

[9] International Diabetes Federation. 2021. “Diabetes facts & figures.” https://www.idf.org/aboutdiabetes/what-is-diabetes/facts-figures.html. Accessed 18 January 2022.

Editor:

Riddhi Bhandari

Metrics

Felix Stein — Wed, 14 Oct 2020 08:44:52 +0000

Marlee Tichenor

University of Edinburgh

Initially published 14 Oct 2020

http://doi.org/10.29164/20metrics

Abstract:

Numbers, enumeration, and the quantification of contemporary life seem to govern our existence more and more. Particularly since the dawn of the twenty-first century, the importance of quantification for governance has grown, and anthropologists have increasingly turned their attention to the ramifications of metrics, or numeric representation that translates assumed realities into numbers (Rottenburg & Merry 2015: 2). They study whether and how the production, synthesis, analysis, and use of metrics is tied to the rise and decentralization of audit and accountability in contemporary capitalism. This entry will first provide a theoretical framework for the anthropology of metrics, drawing on science and technology studies and the history of science. Then, it will discuss how anthropologists have analysed the social impact of enumerative practices. Looking at the practices and infrastructures that produce metrics and that metrics in turn produce, this entry will highlight the importance of colonial legacies for shaping what is ‘knowable’ in the realms of global governance, economics, and health. Finally, the entry will point to tensions at the heart of contemporary critiques of metrics: in our ‘post-truth’ world, these critiques cannot reject the usefulness of truthfully describing and estimating human phenomena. However, these critiques foreground the idea that metrics are always just one form of evidence among many.

Introduction

Since the dawn of the twenty-first century, the importance of quantification for governance has gained momentum, and anthropologists have increasingly turned their attention to the ramifications of numbers, enumeration, and the quantification of contemporary life. As historians and philosophers of science and technology have made clear, statistics, and the rendering of the world into numbers, have long played a fundamental role in the rise of the modern nation-state (Foucault 1973; Porter 1990; Hacking 1990; Desrosières 1998; Scott 1998). For example, quantification practices co-created the notion that ‘populations’ existed and could be governed from above (Foucault 1973; Scott 1998). Thus, numbers have long contributed to giving meaning to various aspects of modern and contemporary life. What is new in recent decades, however, is that the increased use of metrics has led to ‘new forms of global governmentality’ (Shore & Wright 2015: 22). This means that our lives are increasingly governed by numbers and numerical surveillance – not only those used by nation-states, which have long used numbers as a means of governing from above, but also by non-state forces. In this way, these metrics increasingly define what it means, for example, for educational or health institutions to be effective or for individuals to be healthy and happy.

Metrics, or the standard means of measuring or evaluating processes and phenomena for the purpose of governance, are the ‘translation of (assumed) realities into numbers’ (Rottenburg & Merry 2015: 2). Their production, synthesis, analysis, and use are tightly tied to the rise of audit and accountability in contemporary capitalism, where governing practices such as assessing corporate sales performance or student achievements become more decentralised (Power 1999; Strathern 2000). These numerical representations are often presented as objective truth, yet they are produced through technical and social practices that are always at least partially specific. Most statisticians and data scientists producing quantified data and syntheses of, say, ‘gross national products’ or ‘burdens of disease’ know that there are many reasons for why these simplified metrics are not perfectly objective. This can be due to a human element of designing and implementing surveys, unclear or distorted categories in which data are placed, missing data, changing statistical equations, and statistical uncertainty. However, because these subjective components can be neatly packed away when metrics travel, the power they have in determining national budgets, international funding flows, social justice claims, and so on, is considerable.

The metrics discussed here are not merely numbers, which have multiple points of historical and geographical origin. Instead, they are the indices, indicators, statistics, and biometric standards used on the part of governments, international and non-governmental organizations, private companies, and governance scholars. They are meant to be replicable and universal, creating comparability between different countries, economies, corporate entities, or populations. According to Vincanne Adams (2016), these metrics were born out of a desire in the West to aspire to the universal, as well as out of the rise of statistics that occurred simultaneously with the ascent of the modern nation-state, serving ‘as the invented conceptual counterpart to the hubris of the age of imperialism’ (Adams 2016: 20). The anthropology of metrics investigates the politics of evidence, analysing why certain numerical forms, whether crime rates or funding flows, are taken as legitimate over other (less numerical) forms. It also pays close attention to the ways that counting practices and their associated categories can produce the very phenomena that they are supposed to measure. This can occur when sorting and separating phenomena into categories that come with built-in theories about the world – like degrees of ‘development’ or economic prosperity. Here, specific notions of what makes a good life are suggested and perpetuated by acts of measurement. The proliferation of indicators and rankings is thereby ‘creating new forms of power and governance, and new kinds of subjectivity^[1] (Shore & Wright 2015: 22), as institutions and individuals are assumed to be appropriate entities for external audit and governance through numbers. This includes how universities in the United Kingdom, for example, are now ranked specifically by the quantified impact of research by the Research Excellence Framework, which has material effects on their funding and the focus of their activities (Stein 2018).

Some authors have included the ways that numbers and counting practices have wide and varied symbolic and practical meanings in different cultures within an ‘anthropology of numbers’ (Crump 1990). Most of the anthropology of metrics, however, focuses specifically on the use of numbers, statistics, and counting technologies in the practice of governing, at different scales of human experience. This entry will first provide a theoretical framework for the anthropology of metrics, which stands in conversation with science and technology studies (STS). Anthropologists of metrics both contribute to the larger interdisciplinary STS conversation and speak beyond it by using their discipline’s particular methodologies, including ethnography and participant-observation. They investigate infrastructures and practices of measurement and they pay close attention to how these impact the lived experiences of both practitioners and targets of technologies of measurement. For example, numerical surveillance on the cellular level – like counting the quantity of virus in a given amount of bodily fluid – has become a language that some living with HIV/AIDS in Miami, Florida use to describe their ‘suffering, personal triumph, and achievement’ and to define their personal experience of risk (Sangaramoorthy 2012: 293). Next, the entry discusses engagements with metrics within the field itself, tracing histories of the impact of numbers and outlining key contributions such as anthropologists’ analysis of how metrics in the realms of global governance, economics, and health shape our lived experience and institutions.

Finally, the entry will point to anthropologists’ ambivalence toward metrics. Although the focus of this entry is on the anthropology of metrics, that is, with metrics and their efects as central objects of study, anthropology is also done with metrics. Applied anthropology in business and development, for example, makes use of both quantitative and qualitative methods. A further ambivalence arises with the conflict between qualitative and quantitative approaches to understanding the world around us. It is reflected in critiques of metrics that argue for the importance of stories over numbers (Moats 2016) or for situated knowledges^[2] over a singular, objective truth (Haraway 1988). Yet, we exist in a world where scientific expertise in general and statistics in particular are being cast by some world leaders as suspect, and where ‘alternative facts’ – an ingenious rebranding of ‘lies and falsehoods’ – become more widely disseminated as official accounts of the effects of climate change, of the origins of gun violence in the US context, or of reasonable public health approaches to the COVID-19 pandemic. In this ‘post-truth’ world, an anthropology of metrics calls for nuance. It does not make the case to end all metrics, but wants to understand them better so that they may actually enrich our lives.

Social sciences of metrology

The anthropology of metrics is situated within a larger social scientific critique of quantification and enumeration. The history and philosophy of science has long attended to the ways that the sciences have aspired to and produce objective representations of world phenomena, situating the development of these practices in particular historical moments and as resulting from a specific trajectory of theoretical thinking. Metrics are part of the effort to create ‘objective’ representations of the world. Lorraine Daston and others categorise three types of objectivity: mechanical, where objectivity suppresses the ‘human propensity to judge and aestheticize’; aperspectival, where objectivity eliminates idiosyncrasies; and ontological, where objectivity brings about a ‘fit between theory and the world’ (1992: 597). Quantification aspires to all three forms of objectivity, producing a rule-bound, un-self-interested, true representation of the world.

Quantification is an exemplary practice of the production of objectivity, as it replaces arbitrariness, idiosyncracy, and judgment by explicit rules (Porter 1992: 633). Quantification is thus in part a ‘technology of distance’, meant to remove all forms of subjectivity. It creates international communities with a common language, and can be used by politicians and institutions to garner the trust of the populations they serve (Porter 1995: ix). The rise of the power of statistics was therefore tied to the rise of the modern nation-state, and by the middle of the nineteenth century in Europe, statistics came to be perceived as the premier means of producing general knowledge for the populace and as a fundamental tool for addressing corruption within the democratic political system (Porter 1995; Merry 2011).

In the rise of the nation-state, statistics were particularly important for producing the concept of population upon which new forms of power could be exerted, as can be seen in Michel Foucault’s concept of biopower. This new form of power was based on new forms of thinking about life and disease in the seventeenth and eighteenth centuries. Foucault argues that, at the beginning of the seventeenth century, the power of a sovereign ruler shifted from the simple power to kill someone (the power over death), to aiming at making populations grow (i.e. exerting power over life). Biopower was born, as a form of power that regulates the individual body and populations at large. According to Foucault, it became the main mode of sovereign power: controlling sexuality, economic life, and personal health, for example, often through the use of statistics. As a result, people’s subjectivities, or the way that they understand themselves in the world and live their lives, began to change. They started to conceive of their bodies as if they were machines, and began adhering to better eating and exercise habits, for example. New intellectual disciplines, like sociology and epidemiology, contributed to these emerging forms of controlling the body. Better knowledge of life and health were also indispensable for the development of capitalism, as the institutions of power that control health are also those that condition bodies to function in the machinery of production (1978: 141). For example, the ‘ideal worker’ became a self-disciplined and regulated self, produced and maintained by social scientific and medical texts about the moral value of productivity and the responsibility of the individual to stay healthy.

Within the context of the medical sciences, the growing influence of physicians was key for developing statistical thinking and ideas of what counts as ‘normal’ and ‘pathological’. Opening up corpses, for example, was pivotal for the production of biopower, as it allowed for a direct comparison between bodies, which in turn facilitated the development of statistical averages against which individuals could be compared (Lock & Nguyen 2010). This comparability and the practice of making things commensurate are central to the work that numbers and metrics do, by putting diverse phenomena into the same category in order to start counting. Importantly, that which may seem quite simple, ‘like how to name things and how to store data’, actually ‘constitute much of human interaction and much of what we come to know as natural’ (Bowker & Starr 2000: 326). Quantification may be a seemingly natural technology of classification, yet as Foucault (2001) has shown, the ranking and separating of countries, institutions, and projects through evaluative indicators and data production have specific histories and always reflect more than mere ‘common sense’.

In the twentieth century, the power of the nation-state became less centralised and all-encompassing than in Foucault’s analysis. Local and international governing agencies increasingly determined people’s everyday lives. This changed the role that quantification took in governance. According to Michael Powers, this decentralisation led to an ‘audit explosion’ (1994) which has been central to contemporary forms of governance since the 1990s. Quantification practices have often themselves become the link between populations and the local, national, or international entities that govern their economic, social, and physical wellbeing. These forms of wellbeing, as well as the accountability of governing organizations to secure them, have become objects to monitor. Practices of accountability – of counting and holding to account – have, for example, become a main mode of instilling trust in institutions which are now are measured against pre-defined quantitative indicators determining their success. This ‘governance by numbers’ has reached new levels with the United Nation’s Sustainable Development Goals (SDG), introduced in 2015, whereby all UN member states are obligated to produce data and monitor their progress across 17 goals and 231 individual indicators (Fukada-Parr & McNeill 2019). Sakiko Fukada-Parr and Desmond McNeill are among the scholars who argue that these indicators ‘have distinctive effects on knowledge (how things are conceptualized) and on governance (behaviour of actors, policy choices)’ (2019: 6). In this way, the means by which the SDG global development agenda is implemented – through the measurement of 231 individual indicators on such wide policy issues as health, education, poverty, and environment – is at the mercy of group consensus on statistical methodologies for how we measure poverty or ill-health, as well as what kinds of quantified data are actually available. What is measurable becomes what is implementable in our global development agenda and in global public policy.

Contemporary metrics-based modes of defining and determining good governance tend to have their origins in New Public Management (NPM), a school of thought that aims to render administrative structures and processes more business-like (Strathern 2000; Hulme 2007). Under the guise of ‘good governance’, they are often aimed at increasing economic efficiency. Thereby, they frequently join together ‘the financial and the moral’ (Strathern 2000: 1), presenting what is financially sound as being morally valuable. Accountability in this way holds its older meanings of responsibility to one’s fellow citizens or those under one’s care, while also gaining new meanings about promoting efficiency and balancing one’s cheque-book. One way of making sense of these developments is to consider them as part of the on-going rise of neoliberalism. In the context of a continued retreat of the state in the neoliberal present, business and finance-based auditing and accountability practices have expanded outward, becoming the means of defining success for medical, educational, and other social services institutions. University rankings incite students to apply to one university rather than another, while key performance indicators increasingly determine public sector budget allocations. Metrics also drive private investment by ranking corruption levels and the quality of life of entire countries. They even evaluate our day-to-day activities, such as our eating habits and exercising routines (Merry 2011: S84; Rottenburg & Merry 2015), designating each of us as a ‘quantified self’ accountable to ourselves and our fellow citizens for our individual and group well-being (Moore 2017). In this way, the governing power of the metric – in the context of global shifts of decentralization and the continued retreat of the state’s responsibility for our wellbeing – has gained the ability to assert new relationships of responsibility, alongside its ability to measure economic efficiency. Thus, much of our social lives is now assessed by managerial techniques of accountancy and performance management that do not just describe what we do but also assert our activities’ moral worth, often with an economistic bent (Shore & Wright 2015).

An anthropology of metrics

Drawing these debates into anthropology, scholars have asked whether the increased use of evaluative metrics has impacted both our societal structures and how we see ourselves. After all, the quality of our sleep or ability to be mindful, and even our societies’ levels of happiness, are closely linked to who we are. Since rankings enable comparability and competition between countries, institutions, and individuals, they have come to be a foundational component of how we situate ourselves and others in the world. It may define our individual sense of success where our university sits on ranking systems, or whether our country is ‘lower-middle income’ or ‘upper-middle income’. Further, indicators and evaluative metrics are a language through which we communicate urgency, morality, and our responsibility to one another, invoking or requiring redress or action. For example, the Bill & Melinda Gates Foundation uses its estimations on global health burden to justify its own – non-transparent – investment in global health (Tichenor & Sridhar 2020). On the other hand, the Programme for Action for Cancer Therapy uses the evocative statement that ‘One woman dies every 50 seconds’ from breast cancer to both advocate for more funding for research and development for treating breast cancer, while also invoking women into action to attend to their own health through screening or genetic testing. In this way, metrics are tools of both the powerful and the resistance, and the viability of metrics is determined by the power structures within which they are produced and amplified.

Anthropologists have tended to study metrics through ethnography. Merry defines this methodology as

examining the history of the creation of an indicator and its underlying theory, observing expert group meetings and international discussions where the terms of the indicator are debated and defined, interviewing expert statisticians and other experts about the meaning and the process of producing indicators, observing data-collection processes, and examining the ways indicators affect decision making and public perceptions (2011: S85).

There has been a rise in the number of ethnographic analyses of monitoring and evaluation practices in the domains of justice, economy, and health.

A. Metrics in global governance

Take the example of global governance, which is a governing system headed by the United Nations and the member-states, agencies like the World Health Organization, and other international organizations like the Bill & Melinda Gates Foundation. Within the system of global governance, countries are evaluated based on their Gross Domestic Product (GDP) or their Human Development Index (HDI), or the World Bank’s newly introduced Human Capital Index (HCI). These evaluations have concrete impacts on what kinds of funding countries can receive from the World Bank or the International Monetary Fund, including the quality of their credit. In global health, countries are ranked based on the quality of their health systems and are provided with funding to fight certain diseases based on their perceived need through a metric known as the Global Burden of Disease (GBD). Yet, the nature of these indicators and the means of their production ‘involves a range of discretionary and sometimes arbitrary decisions’, despite their assumed objectivity and ability to represent reality (Jerven 2013: 4). There are missing data and questionable assumptions, and the debates about what can be counted and what cannot will remain hidden under the final indicator produced.

Morten Jerven (2013) has shown this by spending extensive time in statistics offices in different countries across Anglophone Africa, interrogating how the assumption that most of the ‘least developed countries’ are in Africa is based on partial and often inadequate information. Working with very limited resources and limited data, these statistics offices must regularly produce statistics on Gross Domestic Product (GDP) and Gross National Income (GNI). In order to be ‘legible’ or acceptable, they must reinforce existing assumptions about income levels in-country, assumptions which then help both the international community and government agencies choose where to invest funds in the country.

It is not a trivial matter that GDP is, in this way, created based on existing assumptions that international agencies have about the level of ‘development’ of a country. As Lorenzo Fioramonti (2014: 15) shows, GDP is founded on the idea that ‘that which is not priced, what does not involve formal financial transaction based on money does not count’ toward one’s country’s social or economic wellbeing. GDP has thus given more power to the economy over politics and society. Further, these practices of enumeration and the defining of countries’ levels of ‘development’ or economic prosperity based on metrics have their origins in colonial projects. In the context of the British colonial power in India, ‘exoticization and enumeration were complicated strands of a single colonial project’ (Appadurai 1993: 315). Here, censes, maps, agrarian surveys, racial studies, and other projects of quantification were a crucial component of the categorization and essentialization of the ‘other’ under colonial rule. Metrics contributed to creating Orientalism (Said 1978), which was the process by which Western artists, scholars, and government officials exoticised populations in ‘the Orient’ – or the Arab world and Asia – through cultural and governmental representations of these populations, and which was a necessary and destructive foundation for colonial rule. Defining a country’s ‘development’ or ‘underdevelopment’ based on what is quantifiable and carries a price, and using statistical estimates based on pre-existing assumptions about ‘development’ levels, risks perpetuating the exoticising practices of colonialism. These measurement practices are all the more important as our current geopolitical system is based upon them.

The fact that evaluative metrics often carry with them ideas of financial value that enable the economic valuation of diverse human experiences becomes particularly obvious in development contexts. Gerhard Anders (2008: 187), who has studied the World Bank and the International Monetary Fund’s work in Malawi, calls this normative infusion of monitoring and evaluation the ‘normativity of numbers’. He shows how loans from both organizations came with conditionalities – that is, particular policy requirements attached to them. Conditional loans were meant to reconcile the organizations’ twin goals of respecting country ownership and tackling corruption. They required careful monitoring of particular ‘good governance’ indicators, such as GDP, inflation rate, and average life expectancy.

B. Metrics in justice and education

Within the domain of justice, it has become obvious that indicators exercise power in a variety of ways. They have, for example, been used to bring claims to individual human rights into closer relation with population-based discourses and management of international development, as economic indicators have increasingly been used for measuring and ranking human rights compliance (Merry 2011: 2016). Thus, economists at the World Bank, who have been pivotal for collecting and collating socioeconomic data throughout the world, have promoted the concept of ‘economic rights’, such as the right to an adequate standard of living or to social security, as central to the human rights agenda. Their success illustrates the power of certain indicators over others, based on the resources that they open up or close down. With the considerable economic and governing power behind it, the World Bank can prioritise which kinds of indicators it uses to direct its funding, or how much funding individual countries or organizations receive. It has the power to refine human rights indicators to prioritise the economic opportunities of individuals over other aspects of human life. These decisions affect not just what kind of funding countries may receive, but also how they measure human rights issues within their own borders.

Metrics often shape what is prioritised in our justice and education systems, but anthropologists have also shown that they must be understood in the context of other forms of evidence. Thus, qualitative narratives or other forms of evidence are part and parcel of numeric indicators themselves. Take the example of popular media rankings of quality for law schools. They impact the day-to-day occurrences within those schools by producing narratives that are just as important as the numbers themselves (Espeland 2015). When rankings are reorganised and some law schools are suddenly put ‘below’ others that law students and faculty had previously believed themselves to be superior to, they may provide narratives that try to temper and explain away the new hierarchy. For example, a law school dean may provide a narrative to his students about the ways that the rankings themselves were produced and the fact that they could be impacted, and changed quickly, by limiting class sizes the next year. In this way, rankings create narratives that ‘speak back’ to the numbers. Other examples also show that indicators are not simple and straightforward facts, but that they require qualitative interpretation, a perspective that some South African prosecutors studied by Muegler (2015) have taken. Thus ‘performance measurement systems’ measuring the ‘accountability’ of the justice system to the country’s population in South Africa must be analysed through how indicators and measurement are used in legal cases. The prosecutors’ ‘stat talk’ was always situated in larger understandings of practices of accountability, showing how indicators always must be understood in their larger context.

C. Metrics in health

The anthropology of metrics has traditionally had a strong focus on health. This is linked to the history of colonialism, where measurements of the body, of health, and of illness have been particularly pernicious in producing and maintaining oppressive theories of othering and racism (Arnold 1993; Anderson 2005). This history highlights how important it is that anthropologists continue to analyse the assumptions at the heart of health metrics. Further, techniques of measuring the body or sub-elements of the body have come to stand in for determining health in general, in ways that shape the lived experience of individuals as well as the institutions with which they interact.

In The mismeasure of man, evolutionary biologist Steven Jay Gould (1996) explains how complex human intelligence was systematically reduced to what could be measured with crude tools, such as IQ tests and skull size gauges, and how such unsuitable proxies were used to justify existing social hierarchies. The use of metrics of bodily weight and size to measure individuals’ health echoes this history (Yates-Doerr 2013). For example, obesity has come to be measured through various techniques including waist circumference, body mass index, and bioimpedance analysis. As part of this trend, ‘the public health community has become swept up with the idea that measurements can reveal the interior health of the body’ (Yates-Doerr 2013: 50). A major goal in public health is to find the best tool to provide a quantified value for body fat. In the process of finding more and more ‘accurate’ tools to do so, public health officials and clinicians easily forget the ‘representational quality of numbers’ and allow them to stand in for the concept of health itself. This standardised and metrics-based understanding of health stands in contrast to alternate ways of conceiving of fatness. In Guatemala, for example, where one individual’s corporeality is not necessarily commensurate with another’s, fatness and illness are not considered to be intrinsically linked as they so often are in the public health literature. Here, experiences and attitudes about fatness connote abundance and joy rather than illness or poor health. While numerical representations are not inherently bad, the power of numbers means that ‘other knowledges about bodies become harder to see, and though they certainly do not disappear, they become more difficult for scientists and public health worker to value’ (Yates-Doerr 2013: 64).

Metrics tend to impact those who use them, down to the level of their innermost subjectivity. Enumerative practices around the surveillance and prevention of HIV/AIDS in Miami, Florida, for example, have helped shape the identities – or ‘numerical subjectivities’ – of those living with the disease (Sangaramoorthy 2012: 292). Here, HIV/AIDS patients come to define themselves and how they understand wellness through their viral loads, or the number of viruses within a given amount of bodily fluid. They also define themselves through their CD4 counts, or the number of CD4+ T cells in a given amount of fluid, measuring individuals’ immunity levels. They tie changes in such numbers explicitly to external phenomena, arguing they might change for the better if a favourable health policy was passed. At the same time, statistics co-create how people see the world around them. Thus, the Center for Disease Control uses gathered surveillance data on Haitians living in Miami, classifying them as a ‘high risk’ population that requires extra HIV/AIDS surveillance. This is a legacy of the incorrect assumption that the presence of the disease in the US originated from Haiti (Farmer 1992), and Thurka Sangaramoorthy shows how Haitian-Miamians’ contemporary risk level is based on national statistical estimates on the disease. Previously-held assumptions about these populations being ‘high-risk heterosexual’ populations have made them particularly targeted for surveillance, and as a result of these categorizations, Haitians living with HIV/AIDS in Miami have internalised this externally imposed risk. In opposition to non-Haitians understanding their HIV/AIDS experience through ‘numerical subjectivity’, Haitians living with HIV/AIDS in Miami have been placed in a category of ‘high risk’ by outside forces – a category maintained through statistical surveillance – that has led them to reject these same practices of self-enumeration because of these legacies of discrimination. In this way, categorizations maintained by metrics are imposed externally, but there is always space for rejecting or manipulating them on the level of the individual.

Since global health metrics are powerful tools, they are always a tangle of contentions over epistemological definitions of disease, competition over limited funding from international organizations, and techniques of calculating and modelling proxies for disease. This has been shown in the example of maternal health in Malawi (Wendland 2016). Here, the officially-stated national progress on maternal health, based on a maternal mortality ratio (MMR), stood in painful disconnect to the experiences of physicians at the Queen Elizabeth Central Hospital in Blantyre. The MMR had been estimated in 2010 by the Seattle-based Institute for Health Metrics and Evaluation (IHME), which projected success in the country’s goals for maternal mortality. Yet local physicians observed the same frequency of funeral processions in the maternity wing of the hospital. An analysis of the way that IHME and the World Health Organization produce MMR estimates shows that the metric, in places where maternal mortality data collection is sparse, like Malawi, is, in fact, an estimation of estimations, which in this instance failed to capture reality and risked losing funding for maternal health programmes. At the same time, epidemiologists, statisticians, and demographers have been developing and advocating for better metrics to measure progress in maternal health, asserting that their current forms do not appropriately represent reality (Storeng & Béhague 2017). However, it may be that at the heart of this effort is not so much a desire to represent the world, but one to ‘sell’ maternal health as a priority over other health issues to global health donors. It may well be that health metrics are themselves marketing techniques in a world governed by indicators.

In a world where metrics proliferate but health inequalities persist, one may go so far as to ask whether metrics create value only for a select few (Erikson 2016: 148). Not only are numbers required to give value to past action, but they are also asked to produce ‘future actuarial worth’. Promoters of health interventions among the global health community in Seattle, or Washington D.C, for example, often package their work for investors by providing productions of ‘expected growth’ due to their interventions, providing them a return on their investment (Erikson 2016: 153). Metrics have evolved from being strictly an accountability tool to one to be used to attract and incentivise investment, which we can see in the example of the shift in how the Bill & Melinda Gates Foundation (BMGF) has approached the use of metrics. ‘“Tools of business’ will be the solution to bringing health and welfare to the world’, Bill Gates stated in his 2013 Annual Letter, showing how BMGF has fully embraced the use of metrics to govern global health like a business. These ‘incentivizing financial tools’ have been proliferating at a clip, using modelled and forecasted metrics as a means to show investors which medical commodities are the important ones to support.

One particularly elaborate incentivising financial tool of this sort is the World Bank’s Pandemic Emergency Financing Facility (PEF), which promised large interest rates to investors in the absence of a major pandemic within a three-year window (Erikson 2015; Stein & Sridhar 2017). Using medical expertise as well as that of multinational insurance companies, the PEF’s dispersal of funds for the support of lower- and middle-income country governments and global health agencies is determined by a series of metrics that some have argued are ill-fitting for many potential pandemics (Jonas 2019). This raises the question of whether metrics can be used to incentivise inaction, rather than action in global health. During the COVID-19 pandemic, the PEF was only triggered in late April 2020, when other non-metrics-based funding mechanisms had already been allocated. In addition to fostering inertia, and slowing down the disbursement of aid, metrics like those required by the PEF turn health itself into an object of investment for which actors obtain a financial return (Erikson 2016). This shifts the fundamental measure of success for health interventions from addressing health problems to whether an investor makes a profit, further deteriorating the concept of health as a public good.

Conclusions

This entry has focused on the anthropology of metrics, which analyses the effects of the increasing quantification of our institutions, communities, and selves. However, anthropology’s engagement with metrics as an object of study exists alongside the use of indices, indicators, and statistics for research. Anthropologists make use of or even help produce population-based statistics to provide context for ethnographic studies. At the same time, the UK’s Research Excellence Framework requires that anthropology departments produce performance indicators of the impact of their research, turning its members into both producers and researchers of metrics. Anthropologists sometimes assert that their research output is ‘a form of counterevidence to metrics’, which produces a tension between ‘stories and numbers’ (Moats 2016: 596). They will need to bridge the chasm between qualitative and quantitative ways of representing the world, which exist alongside and in tension with each other (Benton 2012). Rather than arguing against metrics, which is a dangerous thing to do in our ‘post-truth’ world, anthropologists may want to argue for better metrics and the simultaneous use of multiple modes of evidence. Analysing the practices that create metrics, and interrogating their effects, does not stand in for an argument against their use. Instead, it indicates the importance of couching metrics and quantified data within other forms of evidence, in a way that ensures that the assumptions, data sources, and estimations that were used to create them remain clear.

We may today be reaching a point at which the production and consumption of evaluative metrics has reached its peak (Kelly & McGoey 2018). At the same time, our trust in the systems that produce and consume them is at a historic low. In a time where nuance seems to be mostly absent from political debate, debating the validity of metrics feels like a dangerous game. And yet, those who design and implement metrics, and those whose lives are impacted by them, must understand how the dominant categories and measurements affect social life. Based on this understanding, they may be able to decide where measurement is needed and where unmeasured life should continue.

Acknowledgements

This entry is part of a project that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme, under Grant agreement No 715125 METRO (ERC-2016-StG) (“International Organisations and the Rise of a Global Metrological Field”, 2017–2022, PI: Sotiria Grek). It was also supported by Wellcome Trust [106635/Z/14/Z].

References

Adams, V. 2016. Metrics: what counts in global health. Durham, N.C.: Duke University Press.

Anders, G. 2015. The normativity of numbers: World Bank and IMF conditionality. PoLAR: Political and Legal Anthropology Review 31(2), 187-202.

Anderson, W. 2005. The cultivation of whiteness: science, health and racial destiny in Australia. Melbourne: University Press.

Appadurai, A. 1993. Number in the colonial imagination. In Orientalism and the postcolonial predicament: perspectives on South Asia (eds) C.A. Breckenridge & P. van der Veer, 314-40. Philadelphia: University of Pennsylvania Press.

Arnold, D. 1993. Colonizing the body: state medicine and epidemic disease in nineteenth-century India. Berkeley: University of California Press.

Bemme, D. 2019. Finding “what works”: theory of change, contingent universals, and virtuous failure in global mental health. Culture, Medicine, and Psychiatry 43, 574-595.

Benton, A. 2012. Exceptional suffering? Enumeration and vernacular accounting in the HIV-positive experience. Medical Anthropology 31(4), 310-28.

Biehl, J., B. Good & A. Kleinman 2007. Subjectivity: ethnographic investigations. Berkeley: University of California Press.

Bowker, G.C. & S.L. Star 2000. Sorting things out: classification and its consequences. Cambridge: MIT Press.

Crump, T. 1992. The anthropology of numbers. Cambridge: University Press.

Davis, S.L.M. 2017. The uncounted: politics of data and visibility in global health. The International Journal of Human Rights 21(8), 1-20.

Daston, L. 1992. Objectivity and the escape from perspective. Social Studies of Science 22(4), 597-618.

Day, S., C. Lury & N. Wakeford 2014. Number ecologies: numbers and numbering practices. Distinktion: Journal of Social Theory 15(2), 123-54.

Desrosières, A. 1998. The politics of large numbers: a history of statistical reasoning. Cambridge, Mass.: Harvard University Press.

Erikson, S.L. 2015. The financialization of ebola, 11 November. Somatosphere (available on-line: http://somatosphere.net/2015/the-financialization-of-ebola.html/). Accessed 28 July 2019.

−−−−− 2016. Metrics and market logics in global health. In Metrics: what counts in global health (ed.) V. Adams, 147-62. Durham, N.C.: Duke University Press.

Espeland, W.N. & M. Sauder 2007. Rankings and reactivity: how public measures recreate social worlds. American Journal of Sociology 113(1), 1-40.

Farmer, P. 1992. AIDS and accusation: Haiti and the geography of blame. Berkeley: University of California Press.

Fioramonti, L. 2014. The world’s most powerful number: an assessment of 80 years of GDP ideology. Royal Anthropological Institute 30(2), 12-15.

Foucault, M. 1978. The history of sexuality, vol. 1: an introduction. New York: Vintage Books.

−−−−− 2001. The order of things: archaeology of the human sciences. London: Routledge.

Fukuda‐Parr, S & D. McNeill 2019. Knowledge and politics in setting and measuring the SDGs: introduction to special issue. Global Policy 10(S1), 5-15.

Haraway, D. 1988. Situated knowledges: the science question in feminism and the privilege of partial perspective. Feminist Studies 14(3), 575-99.

Hulme, D. 2007. The making of the Millennium Development Goals: human development meets results-based management in an imperfect world. SSRN Scholarly Paper. Rochester, NY: Social Science Research Network.

Gould, S.J. 1996 [1981]. The mismeasure of man. New York: W.W. Norton & Company.

Jerven, M. 2013. Poor numbers: how we are misled by African development statistics and what to do about it. Ithaca: Cornell University Press.

Jonas, O. 2019. Pandemic bonds: designed to fail in ebola. Nature 572(7769), 285.

Kelly, A.H. & L. McGoey 2018. Facts, power and global evidence: a new empire of truth. Economy and Society 47(1), 1-26.

Luhrmann, T.M. 2006. Subjectivity. Anthropological Theory 6(3), 345-61.

McKittrick, K. 2014. Mathematics black life. The Black Scholar 44(2), 16-28.

Merry, S.E. 2011. Measuring the world: indicators, human rights, and global governance. Current Anthropology 52(S3), S83-S95.

−−−−− 2016. The seductions of quantification: measuring human rights, gender violence, and sex trafficking. Chicago: University Press.

Moats, D. 2016. Of stories and numbers: rethinking the settlement between anthropology and metrics in global health. Science as Culture 25(4), 594-9.

Moore, P.V. 2017. The quantified self in precarity: work, technology and what counts. New York: Routledge.

Mugler, J. 2015. By their own account: (quantitative) accountability, numerical reflexivity and the National Prosecuting Authority in South Africa. In The world of indicators (eds) R. Rottenburg, S.E. Merry, S.J. Park & J. Mugler, 76-101. Cambridge: University Press.

Porter, T.M. 1992. Quantification and the accounting ideal in science. Social Studies of Science 22(4), 633-51.

−−−−− 1995. Trust in numbers: the pursuit of objectivity in science and public life. Princeton: University Press.

Power, M. 1994. The audit explosion. London: Demos.

−−−−− 1999. The audit society: rituals of verification. Oxford: University Press.

Rottenburg, R. 2000. Accountability for development aid. In Facts and figures: economic representations and practices(eds) H. Kalthoff, R. Rottenburg & H.J. Wagener, 143-73. Marburg: Metropolis-Verlag.

−−−−− & S.E. Merry 2015. A world of indicators: the making of governmental knowledge through quantification. In The world of indicators (eds) R. Rottenburg, S.E. Merry, S.J. Park & J. Mugler, 1–33. Cambridge: University Press.

Said, E. 1978. Orientalism. New York: Pantheon Books.

Sangaramoorthy, T. 2012. Treating the numbers: HIV/AIDS surveillance, subjectivity, and risk. Medical Anthropology31(4), 292–309.

Scott, J.C. 1998. Seeing like a state: how certain schemes to improve the human condition have failed. New Haven: Yale University Press.

Shore, C. & S. Wright 2015. Governing by numbers: audit culture, rankings and the new world order. Social Anthropology 23(1), 22–8.

Stein, F. 2018. Anthropology’s “impact”: a comment on audit and the unmeasurable nature of critique. Journal of the Royal Anthropological Institute 24(1), 10–29.

Stein, F. & D. Sridhar 2017. Health as a “global public good”: creating a market for pandemic risk. BMJ 358(August), j3397.

Storeng, K.T. & D.P. Béhague 2017. “Guilty until proven innocent”: the contested use of maternal mortality indicators in global health. Critical Public Health 27(2), 163-76.

Strathern, M. 1992. Reproducing the future: essays on anthropology, kinship and the new reproductive technologies. Manchester: University Press.

−−−−− 2000. Audit cultures: anthropological studies in accountability, ethics and the academy. New York: Routledge.

Suh, S. 2019. Metrics of survival: post-abortion care and reproductive rights in Senegal. Medical Anthropology 38(2), 152-66.

Tichenor, M. & D. Sridhar 2020. Metric partnerships: global burden of disease estimates within the World Bank, the World Health Organisation and the Institute for Health Metrics and Evaluation. Wellcome Open Research 4.

Wendland, C. 2016. Estimating death: a close reading of maternal mortality metrics in Malawi. In Metrics: what counts in global health (ed) V. Adams, 57-81. Durham, N.C.: Duke University Press.

Yates-Doerr, E. 2013. The mismeasure of obesity. In Reconstructing obesity: the meaning of measures and the measure of meanings (eds) M. McGullough & J. Hardin, 49-70. Oxford: Berghahn Books.

Note on contributor

Marlee Tichenor is a research fellow in the Social Policy Department at the University of Edinburgh and received her PhD from UC Berkeley and UC San Francisco. She is a medical anthropologist interested in the politics of evidence and data in global health policy and intervention.

Marlee Tichenor, Social Policy Department, University of Edinburgh, Chrystal Macmillan Building, 15A George Square, Edinburgh EH8 9LD. marlee.tichenor@ed.ac.uk

[1] In anthropology, ‘subjectivity’ is used to mean many things, including personhood, the ‘emotional life of a political subject’ (Luhrmann 2006: 345), and the processes by which a ‘modern subject’ is made (Biehl, Good & Kleinman 2007: 1). The concept is used to interrogate the ways by which individuals understand themselves and how this is influenced by social processes and conditions around them.

[2] Along with other feminist anthropologists of science, Donna Haraway has argued that the objectivity touted by natural scientists over the centuries is not a ‘view from nowhere’. She holds that evidence, research designs, and theories have historically been produced from a Western, masculine perspective, and that all production of knowledge must be thus understood to be ‘situated’ (Haraway 1988: 575). Social anthropologists, particularly since the field’s representational turn in the 1980s, have tended to assert the importance of acknowledging the positionality of the ethnographer in the knowledge they produce about different communities.