Global Inequity in Diabetes 3

Abstract

Type 2 diabetes disparities in the USA persist in both the prevalence of disease and diabetes-related complications. We conducted a literature review related to diabetes prevention, management, and complications across racial and ethnic groups in the USA. The objective of this review is to summarise the current understanding of diabetes disparities by examining differences between and within racial and ethnic groups and among young people (aged <18 years). We also examine the pathophysiology of diabetes as it relates to race and ethnic differences. We use a conceptual framework built on the socioecological model to categorise the causes of diabetes disparities across the lifespan looking at factors in five domains of health behaviours and social norms, public awareness, structural racism, economic development, and access to high-quality care. The range of disparities in diabetes prevalence and management in the USA calls for a community-engaged and multidisciplinary approach that must involve community partners, researchers, practitioners, health system administrators, and policy makers. We offer recommendations for each of these groups to help to promote equity in diabetes prevention and care in the USA.

Introduction

Type 2 diabetes is a highly prevalent, costly, chronic disease that poses a serious threat to both domestic and global health. The International Diabetes Federation reports that 10% of adults (aged 20–79 years) have type 2 diabetes worldwide, with North America reporting 51 million adults living with this disease.¹ In the USA specifically, an estimated 37·3 million (11·1% of the population) had type 2 diabetes in 2020.² Type 2 diabetes is currently one of the leading causes of death in the USA with a crude death rate of 26·7 per 100 000 people.² Type 2 diabetes prevalence varies between states in the USA, ranging from 3·3% (95% CI 2·2–4·5) in Teton County, WY, to 19·5% (17·2–22·0) in Oglala Lakota County, SD, in 2017.³ There is also 7-fold to 8-fold variation in incidence of age-standardised diagnosed diabetes across US counties.⁴ A common and potentially preventable disease, type 2 diabetes imposes substantial health and economic burdens in the USA, where the medical costs and lost work wages of people diagnosed with the disease total an estimated US$327 billion annually.⁵

The burden of type 2 diabetes in the USA is not shared equally between different racial and ethnic groups. Several reviews from the past 5 years have discussed disparities in the prevalence of diabetes and diabetes-related complications by racial and ethnic groups in the USA. For example, Cheng and colleagues’ 2019 review⁶ of the literature showed persistent disparity in the prevalence of diabetes in the USA with Hispanic American adults (aged ≥20 years) having the highest prevalence (22·1%) followed by non-Hispanic Black adults (20·4%), and non-Hispanic Asian American adults (19·1%) compared with the non-Hispanic White American adult population (12·1%). In their 2021 study, Wang and colleagues⁷ showed that there continues to be poor control of risk factors such as blood sugar levels, blood pressure, cholesterol concentrations, and smoking among individuals with type 2 diabetes. Moreover, non-Hispanic Black individuals were significantly less likely than non-Hispanic White adults to have these risk factors controlled.⁷ In 2021, Ezzatvar and colleagues⁸ described the persistent disparities in diabetes-related complications and all-cause mortality that are in part a consequence of poorly controlled risk factors. In 2022, El Hussein and colleagues⁹ described disparities in the prescribing of new diabetes medication (eg, GLP-1 receptor agonists, DPP-4 inhibitors, and SGLT2 inhibitors), with Black (hazard ratio 0·81, 95% CI 0·71–0·94) and American Indian and Native American individuals (0·51, 0·26–0·99) less likely to be prescribed these medications than White individuals.

The limitation of many of these reviews is that they analyse racial and ethnic groups as one homogeneous entity. However, there is growing realisation of the importance of examining within-group differences to address diabetes disparities.^10,11 Furthermore, focusing solely on adults with diabetes overlooks the degree to which child and adolescent onset type 2 diabetes is contributing to the growing burden of disease and worsening disparities. Not only has the prevalence of type 2 diabetes among young people (aged 10–19 years) nearly doubled in the past two decades (from 34 per 100 000 in 2001 to 67 per 100 000 in 2017), but the highest number of young people living with type 2 diabetes per 1000 individuals is seen among Black or American Indian populations.¹² The story of disparities in diabetes in the USA is, therefore, incomplete if not considering the whole lifespan.

Our objective in this Series paper is to compile and summarise key literature examining diabetes disparities across the lifespan and within racial and ethnic groups. We then provide a summary of more recent literature looking at the role of genetics and emerging views on pathophysiological basis of different diabetes phenotypes. Finally, we provide a framework to summarise the multilevel contributors to diabetes disparities in the USA. Leveraging this more informative view of disparities, we recommend a path forward to address knowledge gaps and an implementation and policy agenda to promote diabetes health equity.

Definition of racial and ethnic groups

We define racial and ethnic groups in this Series paper using the Office of Management and Budget Standards (OMB) definition.¹³ The racial groups are American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or other Pacific Islander, and White. The ethnic groups are Hispanic and non-Hispanic. From here on, we will refer to non-Hispanic Black as Black, and non-Hispanic White as White. American Indian or Alaska Native might also be referred to as Native American on the basis of study descriptions.

Conceptual framework

We consider the contributors to diabetes disparities across the lifespan, within, and between racial and ethnic groups using a modified version of the conceptual framework proposed by Agarwal and colleagues in this Series paper.¹⁴ We consider the domains of health behaviours and social norms, structural racism, access to high-quality care, economic development, and public awareness. We discuss how these domains differentially exert their influence at the individual, interpersonal, community, and societal levels across the lifespan (figure 1).

Figure 1: Conceptual framework for diabetes disparities in the USA (adapted from Agarwal et al¹⁴).

The burden of diabetes-related disparities in the USA

Differences in diabetes burden and diabetes-related complications by race or ethnicity in young people

Parallel to the growing epidemic of childhood obesity, prevalence and incidence of type 2 diabetes in children and adolescents has increased since the turn of the 21st century, with continued and persistent earlier onset of diagnosis, which has been exacerbated by the COVID-19 pandemic.¹⁵ The burden of type 1 and type 2 diabetes varies by race and ethnicity, as reported in the SEARCH for Diabetes in Youth Study (SEARCH; figure 1). Although this Series paper is focused on type 2 diabetes, type 1 diabetes continues to play an important role in diabetes in young people. We note here that data in young people are limited by racial and ethnic group differences and not within racial and ethnic groups; therefore, this topic will not be discussed in the young people section (figure 2).

Figure 2: Type 1 and type 2 diabetes incidence per 100 000 person-years (2014–15) and prevalence per 100 000 individuals (2017): results from the SEARCH for Diabetes in Youth Study12,16.

SEARCH has conducted diabetes surveillance in young people in the USA for nearly two decades. In 2001, 6379 individuals aged 0–19 years were identified with diabetes within a population of approximately 3·5 million, with Native American young people having the largest proportion (76%) of type 2 diabetes.¹⁷ Population projections from this study estimated roughly 154 000 young people aged 0–19 years were living with diabetes in the USA in 2001. Since 2001, diabetes prevalence in young people has increased among all racial and ethnic groups, with the largest increases among Asian and Pacific Islander (these groups were not separated in SEARCH), Black, and Hispanic children. Between 2009 and 2017, the estimated prevalence of diabetes in Black children increased by 7·1% (95% CI 4·8 to 9·4), compared with 7·3% (2·7 to 12·1) in Asian and Pacific Islander children, 4·8% (0·7 to 9·0) in American Indian children, 3·2% (1·4 to 5·0) in Hispanic children, and 1·4% (–1·2 to 4·1) in White children.^12,16 A separate study showed a pronounced increase in diabetes among American Indian and Alaska Native young people (aged 15–19 years), with a 68% increase in cases of diagnosed type 2 diabetes from 1994 to 2004.^12,18 The COVID-19 pandemic has been associated with a rise of incident paediatric diabetes cases, with one study finding incident type 2 diabetes cases decreasing moderately by 7·4% in the 2 years before the pandemic and increasing 182% during the pandemic (n=141; 1·45 cases per month; p<0·001). Type 2 diabetes cases increased by more in Black children (76·6%) than in White children (56·7%; p=0·001) and more in boys (58·9%) than in girls (40·4%; p=0·005).¹⁹ Among American Indian children and adolescents, metabolic abnormalities led to greater relative risk of diabetes in children (aged 5–11 years) compared with adolescents (aged 12–19 years).^20,21 With one in five adolescents in the USA having prediabetes, the problem of diabetes among young people will probably continue to grow.²²

Overall, adolescents have more rapid and complete onset of β-cell failure compared with adults, increasing urgency for the few available treatment options.²³ Furthermore, the onset of diabetes-related complications in specific racial and ethnic groups is accelerated in young people. The Pediatric Diabetes Consortium Registry reported significant race and ethnic differences in HbA_1c and C-peptide levels, with Black young people (aged <18 years) having higher HbA_1c and lower C-peptide than White young people. Black children are significantly more likely than White children (odds ratio [OR] 4·85, 95% CI 1·49–15·77) to have poor glycaemic control (HbA_1c >9·5%) at 1 year from time of diagnosis.²⁴ Non-alcoholic fatty liver disease was diagnosed in 9% of Hispanic children and 11% of White children, compared with 2% of Black children.²⁵ Similarly, Hispanic children have significantly elevated liver aminotransferases compared with Black children.²⁶

Differences in diabetes burden within racial and ethnic groups

Here, we describe within-group differences in diabetes prevalence, burden, and management among Hispanic, Black, and Asian individuals. Data on differences within White, American Indian, and Pacific Islander populations are scarce. White people are often viewed as one large, homogeneous group; however, many people who identify as White in the USA might represent different and culturally distinct subgroups, such as people born within the USA and those born overseas (eg, Europe or the Middle East), or religious subgroups. Although studies exploring these subgroups are scarce, differences in diabetes prevalence by rural versus urban residency have been found.^27,28 Additionally, demographic-adjusted models have shown increased diabetes risk among White populations based on residency in the so-called stroke belt of the southeastern USA (OR 1·22, 95% CI 1·09–1·36) and buckle of eastern North Carolina, South Carolina, and Georgia (1·26, 1·10–1·44), compared with residency in other parts of the USA.²⁹

Within the Hispanic population, the national diabetes statistic report of 2020 highlights differences in age-adjusted prevalence of diagnosed diabetes among Hispanic Americans, with Cuban Americans having the lowest prevalence at 6·5%, compared with 12·4% in Puerto Rican American and 13·4% in Mexican American adults.² These differences have been shown using different datasets as well, including the nationally representative NESARC-III study.²² The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) corroborates these findings with a population-based cohort. A longitudinal analysis from HCHS/SOL showed persistent differences in diabetes incidence within the Hispanic population with higher incidence among those with Puerto Rican and Mexican backgrounds.^30,31

US-born Black individuals and non-US born Black individuals of sub-Saharan African or Caribbean descent are often analysed as one racial group (Black) in the literature, although research disaggregating these groups has shown important differences in diabetes prevalence.³² Several studies have indicated the higher prevalence of diabetes among US-born versus African-born or Caribbean-born Black adults.^33,34 Ford and colleagues¹⁰ used National Health Interview Survey data to show that Black individuals born in Africa or the Caribbean had significantly lower odds of having diabetes (OR 0·75, 95% CI 0·62–0·89) compared with US-born Black individuals. Within the population of Black individuals born in Africa or the Caribbean, studies have shown little to no difference between those born in the Caribbean and those born in sub-Saharan Africa. Nevertheless, increasing time in the USA and higher levels of acculturation were associated with increased odds of diabetes diagnosis among foreign-born Black individuals.³³ This increase has highlighted the importance of furthering our understanding of the differences between Black people born within and outside of the USA, as a unique opportunity to examine genetic differences, sociocultural contexts, migration experience, and population characteristics.³⁵

Asian Americans are a large and diverse population, although they are often grouped into one large racial and ethnic group.³⁶ South Asian Americans have higher age-adjusted prevalence of diabetes and gestational diabetes than other Asian American subgroups.³⁷ Filipino American and Korean American adults have the next highest prevalence of diabetes among Asian Americans;^38,39 prevalence of diabetes among Korean Americans was 10% in New York City and 11·9% in California,^40,41 with Korean Americans having very low rates of physical activity compared with other Asian subgroups.^42,43 Of all Asian American subgroups, Chinese Americans continue to have the lowest rates of diabetes.⁴⁴

Factoring in within-group differences will allow us to better understand trends in diabetes prevalence epidemiologically. We can better target resources and interventions if we look at subgroups within racial and ethnic groups whose rising rates might be otherwise masked. These described differences within racial and ethnic groups are crucial considerations when designing interventions for diabetes prevention or management.

Disparities in diabetes complications

Disparities in diabetes prevalence are compounded by disparities in diabetes-related complications. Although disparities in diabetes-related complications in young people have been described, there are scarce data on differences in complications within racial and ethnic groups. Diabetes-related microvascular complications include chronic kidney disease, retinopathy, and amputations. Among US adults with diabetes, 39·2% were reported to have chronic kidney disease (stages 1–4). This prevalence was higher among Black adults, with 23·1% having chronic kidney disease stage 3–4, compared with 17·2% of White adults and 8·9% of Hispanic adults with diabetes.⁴⁵ Diabetes is now the leading cause of new cases of blindness among adults in the USA.⁴⁶ Diabetic retinopathy is more prevalent in Black individuals (38·8%) than in Hispanic individuals (31·0%) and White individuals (26·4%). Black and Hispanic individuals with diabetic retinopathy are much more likely to progress to visual impairment and blindness than White individuals.^46–48 Odds for major amputation were significantly greater in Black (OR 1·44, 95% CI 1·36–1·53), Hispanic (1·33, 1·25–1·41), and Native American (1·47, 1·2–1·8) patients with diabetic foot infections than in White patients.⁴⁹ Asian patients had a 64% lower rate of major amputation in cases of diabetic foot infections compared with White patients.⁵⁰

Cardiovascular and cerebrovascular disease are the major macrovascular complications of diabetes. To prevent these complications, individuals with diabetes should meet the recommended ABC metrics for cardiovascular disease risk reduction—ie, HbA_1c <7%, blood pressure <130/80 mm Hg, LDL cholesterol <100 mg/dL. Multiple studies have shown that Black Americans and Mexican Americans are less likely to meet all three ABC goals than White individuals.⁵¹ Cardiovascular disease is the leading cause of mortality among people with diabetes in the USA.⁵² Although overall cardiovascular death in the USA decreased significantly between 1988 and 2015, gaps in mortality between racial and ethnic groups have persisted.⁵²

Disparities in diabetes management

Disparities between racial and ethnic groups for diabetes management have received little attention in the past; however, there are important differences between these groups—eg, geographical location (ie, rural and urban), income, and insurance status. Disparities can be seen at the level of diabetes screening as well as management. Large disparities exist in the diagnosis of diabetes with all racial and minority ethnic populations (eg, Black, Hispanic, and Asian) being more likely to have undiagnosed diabetes than White individuals in the USA.⁵³ For screening of diabetes-related complications in the USA, only 33–68% of adults with diabetes obtain an annual dilated eye exam; however, these screening rates are even lower in Black individuals and Latino individuals.⁴⁸ A 2008 qualitative review of various minority groups, including Black, American Indian, and Latino, reported substantially decreased rates of eye examinations in these populations.⁵⁴ New modalities for efficient screening using artificial intelligence, machine learning, and telehealth have the potential to increase access to retinopathy screening for minority populations; however, data on their reach and uptake are not yet available. Similarly, data on reach and uptake of new modalities to treat diabetic retinopathy including intravitreal anti-VEGF injections, which present opportunities to prevent blindness, are not yet available.

Diabetes management also refers to medication and equipment that is prescribed. A 2021 review looked at access to GLP-1 receptor agonists and found that Asian, Black, and Hispanic individuals and those with low incomes were less likely to receive treatment with GLP-1 receptor agonists than White individuals and those with better incomes.⁵⁵ This disparity is important to recognise given the known cardiovascular benefits of GLP-1 receptor agonists. Further disparity can be seen in access to new technology. Data show that for continuous glucose monitoring (CGM), for example, Black individuals have the lowest rates of access across age groups, health insurance coverage, and location.^56,57

Pathophysiology of diabetes and diabetes disparities

Increased diabetes risk at low BMI in minority race and ethnic populations

Overweight and obesity are well established risk factors for diabetes. However, evidence suggests that the relationship between bodyweight and diabetes is not linear, and that diabetes at low BMI is considerably more prevalent in minority race and ethnic populations.⁵⁸ A study from 2022 of diabetes prevalence in US Asian adults by weight found an increased burden of diabetes risk among south Asian Americans and Filipino Americans who had a BMI within a healthy range compared with White Americans and Chinese Americans.⁵⁹ Additionally, a study examining the prevalence of diabetes by BMI status and place of birth found that the prevalence of diabetes in immigrants with a healthy weight from India and Africa was higher than the prevalence of diabetes in immigrants with obesity from Europe.⁶⁰ A 2019 study examining racial and ethnic disparities in the prevalence of diabetes by BMI category in six racial and ethnic groups in the USA found that in those with a healthy weight, the prevalence of diabetes was 5·0% in White participants, 10·1% in Asian participants, 9.6% in American Indian and Alaskan Native participants, 13·0% in Hispanic participants, 13·5% in Black participants, and 18·0% in Hawaiian and Pacific Islander participants.⁶¹ Furthermore, when examining the relative risks for diabetes for each BMI category across all racial and ethnic groups, White participants showed the greatest sensitivity to changes in BMI followed by Asian, American Indian and Alaskan Native, Hispanic, Hawaiian and Pacific Islander, and Black participants.⁶¹ These results do not indicate greater sensitivity to excess adiposity in non-White populations, rather they suggest that factors other than BMI are driving the disproportionate burden of diabetes in non-White populations, both in the USA and globally. Additionally, these data have implications for screening and prevention. Elevated BMI should not necessarily be the first criterion to consider when screening for diabetes in minority race and ethnic populations as it could result in a substantial number of at-risk individuals being missed. Furthermore, prevention strategies that target weight loss could be less effective in minority racial and ethnic groups when diabetes in individuals with a healthy weight is prevalent.

Differences in the contributions of insulin secretion by racial and ethnic group

Traditionally, diabetes pathogenesis has been described as obesity-driven insulin resistance followed by a subsequent decline in insulin secretion, eventually leading to overt type 2 diabetes.⁶² However, evidence suggests that some racial and ethnic groups might also exhibit early declines in insulin secretion, which can contribute to excess diabetes risk in the absence of obesity. A study comparing the prevalence and associated risk factors of diabetes in four racial and ethnic groups in the USA found that south Asian Americans, Black Americans, Hispanic Americans, and Chinese Americans all had a diabetes prevalence that was at least two-times, if not three-times, higher than that of White Americans.³⁷ Furthermore, these same groups all had worse insulin secretion than the White Americans. Additionally, a 2004 study by Torréns and colleagues⁶³ assessed differences in insulin sensitivity and β-cell function between non-diabetic premenopausal or early perimenopausal non-Hispanic White women and African American, Chinese American, Japanese American, and non-Mexican-American Latino women. Torréns and colleagues found that Japanese American and Chinese American women had worse insulin secretion than non-Hispanic White women, whereas African American women had higher insulin secretion than non-Hispanic White women, and insulin secretion was similar between non-Mexican-American Latino women and non-Hispanic White women, after correcting for confounders.⁶³

The role of ectopic fat in diabetes development

Although obesity is a well known risk factor in diabetes pathogenesis, the pattern and placement of fat deposition is also important as several organs including the muscle, liver, and pancreas are all highly involved in glucose metabolism.⁶² Notably, hepatic fat content, independent of BMI has been associated with metabolic disturbances even in individuals with a healthy weight and normoglycaemia.^64,65 Furthermore, pancreatic fat content has been associated with poor insulin secretion in individuals without diabetes.^66,67 Therefore, increased fat deposition in the liver and pancreas could lead to early metabolic disturbances and subsequent diabetes risk. Studies have pointed to large differences in ectopic fat deposition by racial and ethnic group.^68,69 There has not been an exploration of how these differences change across the lifespan and if there are any differences within racial and ethnic groups.

The aforementioned studies related to ectopic fat suggest that increased susceptibility to diabetes in some racial and ethnic groups such as Asian American individuals could be associated with ectopic fat deposition contributing to increased insulin resistance and worse insulin secretion. However, in other groups such as Black Americans, the increased risk of diabetes persists despite normal rates of ectopic, particularly hepatic, fat deposition. The combined contributions of hepatic and pancreatic fat to insulin resistance and insulin secretion in various ethnic groups has not been well studied, and could provide target mechanisms for treatment and prevention across populations.

Diabetes subgroups and race and ethnic risk factor burden

Type 2 diabetes risk is multifaceted and there is a need to better classify the heterogeneity in diabetes development as there might be differences in underlying disease aetiology and progression, particularly among different race and ethnic populations. Studies categorising diabetes subgroups have found variations in the distribution of cohort membership by racial and ethnic group. For example, a study seeking to characterise potential diabetes subgroups among race and ethnic populations in the USA identified five distinct subgroups—ie, older age at diabetes onset (mean age 66·8 years [SD 8·3]), severe hyperglycaemia (mean HbA_1c 8·3% [1·8]), severe obesity (mean BMI 35·4 kg/m² [6·2]), younger age (mean age 23·8 years [7·7]) at diabetes onset, and insulin use.⁷⁰ In 2022, a systematic review of 18 studies characterising novel diabetes clusters based on clinical variables found that in Asian populations, the cluster of severe insulin deficiency was more common than severe insulin resistance whereas the cluster of severe insulin resistance was more common in populations with European ancestry.⁷¹ Given the differences in diabetes pathophysiology among ethnic groups, there is a need for more targeted diagnosis, prevention, and treatment, as methods traditionally applied to one population might not be applicable to all.

The role of polygenic scores

During the past decade, there have been substantial advances in our understanding of the genetic basis for type 2 diabetes.⁷² Identified individual genetic variants can only provide a modest effect on risk, but when combined into a polygenic risk score, they provide information on disease predisposition and could be useful for guiding clinical management. These polygenic risk scores are determined using ever-growing genome-wide association studies. Polygenic risk scores have been used to identify subtypes of diabetes, predict risk for type 2 diabetes, and predict effectiveness of interventions. In a diabetes prevention programme post-hoc analysis, polygenic risk scores identified subgroups at high risk for whom successful lifestyle modification was associated with an improved absolute reduction in the risk of incident diabetes.⁷³ As polygenic risk scores become more widely available, it is important to remember that genetics represent only one contributor to individual disease risk and profile.73 Additionally, there is a need to ensure that the benefits of these risk scores are equitably available to all. Equitable access to polygenic risk scores is especially important as much of the genome-wide association studies and sequence data are derived from individuals of European descent. As such, there is an urgency to build a repository for other ethnic groups as well.

Contributors to diabetes disparities in the USA

The factors within domains and across levels of influence that could contribute to diabetes disparities are summarised in the table.

Contributors to diabetes disparities between racial and ethnic groups

The complex interplay of factors across all five domains and all levels of influence contribute to disparities between racial and ethnic groups. Structural racism play a prominent role at all levels. Past policies, laws, and economies contribute to where people live, their access to sufficient and healthy food, and their access to health-care services.^{106,110,111,113,115} For example, redlining and predatory lending affected where and what type of housing was available to Black individuals, forcing them to live in less healthy and worse resourced neighbourhoods compared with other racial and ethnic groups. Furthermore, these same areas received fewer government and private sector investments, leading to fewer facilities, such as health facilities and food access points.^161,162 These factors, stemming largely from structural racism and discrimination, play an important role in driving racial and ethnic inequities in diabetes and diabetes-related complications.¹⁶³ At the community level, neighbourhoods with primarily Black and Hispanic individuals tend to have little space for physical activity, more food deserts (ie, neighbourhoods of 5000–15 000 people served by two or fewer big supermarkets), and restricted access to health care compared with other neighbourhoods. These factors have been linked to physical inactivity, poor diet quality, and reduced use of health-care services, which in turn have been found to contribute to the development of diabetes and poor diabetes management.¹¹² Additionally, neighbourhoods with Black and Hispanic individuals have higher levels of toxic environmental exposures than other neighbourhoods, and a growing body of evidence indicates that these exposures are associated with the development of diabetes.¹¹² The interpersonal level reflects relationships between individuals in a family, within a social network, or with health-care professionals. The many forms of interpersonal racism and discrimination can play an important role in health disparities including in those with diabetes. For example, perceived racism has been associated with increased incidence of diabetes in Black women.¹⁵² This association is hypothesised to be through biological mechanisms including increase in chronic stress. These interpersonal relationships in turn affect the gut microbiome, lifestyle behaviours, mental health, and access to care.¹⁵⁶ The determinants are all inter-related and overlapping. The factors within the structural racism domain overlap with the economic development domain and the access to high-quality care domain as outlined.

Native Americans have the highest age-adjusted prevalence of diabetes compared with all other racial and ethnic groups in the USA. Native Americans have 2·0 times higher diabetes prevalence and 1·9 times higher diabetes-related mortality than White Americans.¹⁶⁴ The disproportionate prevalence and disease burden of diabetes has been associated with factors in the economic development domain with social disadvantages faced by American Indian and other Native American communities, including high rates of neighbourhood poverty, inadequate access to health services, and long-standing economic adversity. These factors in turn are related to the health behaviours and social norms domain, where they facilitate unhealthy day-to-day living practices that ultimately contribute to disease, and subsequently hinder optimal management of chronic illnesses. The structural racism domain is also relevant in this case as discrimination has been associated with increased prevalence of diabetes among American Indians and other Native Americans. Some findings have shown that microaggressions experienced by American Indians and other Native Americans with diabetes in health-care settings were associated with greater reports of worse physical and mental health, including increased hospitalisations and depressive symptoms within the previous year.¹⁵⁶

Although pathophysiology of diabetes is important to consider, and there might be a role of genome-wide association studies, it is important to recognise that biological factors are not a cause of disparities. There is a growing body of evidence on biological and epigenetic differences that contribute to the risk of developing diabetes.¹⁶⁵ However, race is a socially constructed variable, not a biologically constructed one.¹⁶⁶ Existing literature suggests that acknowledging the admixture of multiple ethnic groups is crucial in efforts to further define any genetic predisposition to diabetes.¹⁶⁷ Admixture is also an important consideration when looking at the performance of diagnostic tests such as HbA_1c in different racial and ethnic groups.^168,169

Contributors to diabetes disparities within racial and ethnic groups

Using the modified framework proposed by Agarwal and colleagues,¹⁴ we can see that factors at the individual, interpersonal, community, and societal levels together contribute to differences within racial and ethnic groups (table). The health behaviours and social norms domain plays an important role as a contributor to diabetes disparities. Diversity within racial and ethnic groups in cultural practices, knowledge, and beliefs can contribute to differences in dietary and lifestyle habits that in turn can drive within racial and ethnic group differences.¹⁷⁰ Cultural practices, knowledge, and beliefs can also contribute to different relationships with the health-care profession, which might lead to different levels of trust and adherence to medical advice.^132–135 Economic development is also important. Previous studies have consistently found that people with lower socioeconomic status are more likely to develop diabetes and experience more diabetes-related complications compared with those with higher socioeconomic status.⁹⁸ There is also a rural and urban divide that can help explain disparities within groups given rural counties have the highest diabetes-related mortality.¹⁷¹ Examining trends in diabetes-related mortality in urban and rural areas in the USA between 1999 and 2018, Kobo and colleagues found that diabetes-related age-adjusted mortality rates of both Black and White adults decreased in urban but not rural areas.¹⁷² The socioeconomic and built environment can also contribute to disparities within racial and ethnic groups. In 2014, Gaskin and colleagues described the “nexus of race, poverty, and place” and showed that both individual poverty and living in a poor neighbourhood increased the odds of having diabetes for Black and White adults.¹⁷³ In 2019, a systematic review and meta-analysis of longitudinal studies found strong evidence for relationships between neighbourhood walkability and diabetes outcomes.¹⁷⁴ Results from an analysis of nationally representative county-level data showed that counties with higher rates of unemployment and poverty had higher incidence rates of diabetes compared with counties with lower levels of unemployment and poverty, whereas counties with greater access to healthy food and more opportunities for exercise had fewer cases of diabetes.⁴

Table: Contributors (ie, levels of influence and domains of influence over the life course) to diabetes using Agarwal and colleagues’ framework14.

	Individual	Interpersonal	Community	Societal
Health behaviours and social norms	Health behaviours and coping strategies: smoking and sedentary lifestyle; sociodemographic; cultural identity; response to discrimination; cultural beliefs;* stigma;* acculturation; body image perceptions;* poor English proficiency;* and comorbid health conditions:74 depression,*75 hypertension,* heart disease,* and autoimmune conditions*	Family functioning: parental modelling;† and caregiver–child interaction: gestational diabetes,†76–78 intrauterine exposure to diabetes,†21,79 and preterm birth†80,81	Community functioning: food eating practices of a community (eg, type of food and communal eating),82,83 acculturation,84 fear of Western medical practices, scarcity of preventive health seeking behaviour,85 social dietary temptations and overcoming temptations,84 apathy (ie, the inevitability of diabetes in the community),86,87 and weight perception88	Policies and laws: reducing stress exposure via policy,89 association between food prices and insulin resistance,90 mandating diabetes education through policy,91 social norms, societal structural discrimination, smoking as a norm in American Indian and other Native American communities,†92 machismo (ie, masculine ideologies) as driver of health neglect in Mexican men,*93 cultural traditions as a challenge to immigrants managing chronic illness,*94 effect of colonisation on diabetes risk factors in Indigenous communities,95 and education discrimination*96
Economic development	Personal environment:97 income, employment status and job stability, and education level	Household environment: household food insecurity,98 homelessness,*99 housing instability,*100 and energy insecurity;*101 school or work environment; and stress at work102	Community environment,98 neighbourhood walkability,*103 exposure to greenspace,†104 community resources, poor access to affordable diabetes-friendly food compared with relatively easy access to unhealthy food,105–107 and area deprivation index (housing, income, employment, education)108	Societal structure: neighbourhood discrimination,106,109 neighbourhood disadvantage contributes to disproportionate diabetes burden,110–112 and food insecurity113–115
Public awareness	Diabetes knowledge and distress,116 diabetes-related knowledge,* and diabetes self-management knowledge*	Social networks, parental and familial modelling,†117 social support;118 family and peer norms and traditional gender roles:†118 familial social interactions;†118 and social norms*119,120	Community norms; local structural discrimination; diabetes-related social stigma;*121,122 and young adults: community expectations of self-independence, employment, and care of siblings123	..
Access to high-quality care	Insurance coverage, health literacy, and treatment preferences; regional variation;*124 health literacy and numeracy;*125,126 fear of medications and insulin medication adherence;*127 and cost*128	Patient–clinician relationship: perceived discrimination,129 communication,*130–133 lack of trust,*132,134,135 physicians’ empathy,*136 medical decision-making, not enough shared decision-making,*132,137 non-adherence labelling,*138,139 discriminatory health-care practices,140,141 and variations in phenotypes not targeted†70,142	Health-care access, subspecialty care (endocrinologist),*143 safetynet clinics and hospitals,* mental health services,* diabetes self-management education,*144 and transition services for young adults from the paediatrician to adult provider*123	Health-care affordability and quality, differential access to technology for diabetes management (including telehealth and continous glucose monitoring),145 differential access to new anti-diabetic medication,146 and differential access to subspecialty care147
Structural racism	Sociodemographic, cultural identity, response to discrimination, stigma,* acculturation, poor English proficiency,* chronic stress,148 poor sleep, and obesity149	Interpersonal discrimination, major experiences of discrimination,†150,151 perceived everyday racism,†152 lifetime racism,†152 racial discrimination,*153–155 and microaggressions*156	Community environment,98 neighbourhood walkability,*103 exposure to greenspace,†104 community resources, restricted access to affordable diabetes-friendly food compared with relatively easy access to unhealthy food,105–107 area deprivation index (housing, income, employment, education),108 and environmental exposures: air pollution,†157 heat exposure,*158 and endocrine-disrupting chemicals†159	Societal structure: neighbourhood discrimination,106,109 neighbourhood disadvantage contributes to disproportionate diabetes burden,110–112 and food insecurity;113–115 and exposure: climate-induced extreme weather events (heat, cold, natural disasters);160 and sanitation

^*Disparities in diabetes management and control only.

^†Disparities in diabetes incidence only.

The association between social determinants of health and diabetes differs by ethnicity within the Black population. For example, the association of health insurance, income, and education with diabetes was different among African Americans, African immigrants, and African Caribbeans.³⁴ The differences described within the Hispanic population are most likely multifactorial but are still not fully understood.³⁰ Finally, within the Asian American population, we described how south Asians have the highest prevalence of diabetes. The causes of this are multifactorial and are likely due to not only patterns of immigration and sociodemographic characteristics, but also might be related to distinct cardiometabolic phenotypes that increase the risk of diabetes among south Asians.¹⁷⁵

Contributors to diabetes disparities among children and adolescents

Risk factors for type 2 diabetes in children and adolescents (aged <18 years) are similar to those of adults. Studies have found that intergenerational factors, malnutrition, little physical exercise, obesity, family history, and low or very high birthweight elevate diabetes risk in children.¹⁷⁶ Poor sleep has also been linked to diabetes risk among both adults and children, with one multiethnic study in the UK finding that children aged 9–10 years had reduced risk of type 2 diabetes for every additional hour of sleep duration.¹⁷⁷

Obesity and insulin resistance in children portends an increased risk of developing diabetes. There is now good evidence to show that stress, obesity, and hyperglycaemia in lactating mothers is associated with increased rates of obesity and insulin resistance in their offspring.¹⁷⁸ Additionally, overnutrition as a consequence of an infant being born small for gestational age, as well as early weaning from breastmilk are associated with obesity and insulin resistance.¹⁷⁸ Lastly, on the other end of the spectrum, a combination of early-life undernutrition and later development of obesity is associated with increased risk of type 2 diabetes in adulthood.¹⁷⁹

Economic development also has a role for racial and ethnic disparities in young people. For example, lower socioeconomic status and living in poor areas are associated with higher diabetes risk, a 34% increased likelihood of developing obesity, and a 60% increased likelihood of developing diabetes, when compared with living in high income areas.^180,181 Additionally, compared with White women, Asian and Hispanic women have a higher prevalence of gestational diabetes, which has been associated with increased risk in offspring of developing type 2 diabetes later in life.^182,183

Diabetes disparities are now evident across the lifespan with the emerging concept of intergenerational risk of developing diabetes.¹⁸⁴ Young people who identify as Native American, American Indian, or Alaska Native; Black; and Hispanic have an increased burden of diabetes and obesity. This burden is in part due to social determinants of health within the structural racism domain that are “systemic, population-based, cyclical, and intergenerational.”¹⁸⁵ These same social determinants of health are rooted in racism that is internalised, or at the interpersonal, institutional, and societal levels. These factors are experienced by the family (including children) and not only the adult. Additionally, intergenerational poverty makes it harder for children to find a way out of the cycle of intergenerational risk. Although socioeconomic status is complex and multidimensional, all indicators are strongly patterned by racial and ethnic group: “for every dollar of wealth that Whites have, Asian households have 83 cents, Black households have 6 cents, and Hispanic households have 7 cents”.¹⁸⁶

Recommendations and future directions

We have provided an overview of the literature from the past decade on disparities in diabetes between and within racial and ethnic groups in the USA across the lifespan. This overview provides a US-focused framing that adds to the other two papers in this Series^14,187 and The Lancet Commission on Diabetes.¹⁸⁸ This Series paper highlights the importance of considering the complexity of disparities in diabetes and diabetes-related complications beyond racial and ethnic groups to consider within-group differences, how disparities differ in children and adolescents, and the complex pathophysiology. Using a comprehensive framework, this Series paper also emphasises that these disparities arise from many multilevel factors. With these key points in mind, we propose a path forward for providers, researchers, funders, and policy makers to address diabetes disparities (figure 2, panel).

Generate a community-engaged and multidisciplinary research agenda that adopts a life course approach and addresses pathophysiological and multilevel causes of diabetes disparities

This Series paper has thus far highlighted the complexity and multifaceted nature of diabetes disparities. Solutions must, therefore, meet this complexity by ensuring a multidisciplinary approach that carefully engages affected communities in an equitable manner. Increased attention to more detailed diabetes phenotypic structures (see previous sections) is important to guide tailored prevention and management strategies. Understanding diabetes phenotypes and the resulting tailored management strategies can provide the health-care community with the needed information to move towards effective and equitable precision medicine in diabetes care. As we give the pathophysiology of diabetes more attention, researchers should be sure not to confuse social constructs such as race with biological factors such as genetics.¹⁸⁹ As we promote ideas around precision medicine for diabetes care, it is crucial to curb any misconceptions of this idea and ensure emergent technologies and advancements overcome current inequities in access. Community-engaged and community-based participatory research is essential for designing acceptable and feasible strategies of promoting uptake of diabetes treatment interventions among disadvantaged groups. These strategies will need to be tailored to groups across the lifespan (strategies related to young people [aged <18 years] will differ from those targeting older people [aged >65 years]). These strategies will also need to be tailored across and within racial and ethnic groups given much of the social and behavioural norms that differ between these groups. To do this well, research needs to continue to disaggregate the large groupings of Black, Asian, and Hispanic individuals.

As we see the growth of the fields of environmental justice, climate, and health, we must pay attention to their effects on diabetes prevalence, management, and thereby disparities. We need more community-engaged research to document the attribution of environmental factors on diabetes risk and management. Moreover, we need community-engaged research to co-design strategies with communities to mitigate the effects of environmental hazardous exposures and climate change on health. Researchers need to apply a health equity lens to ensure that novel therapeutics and diagnostics are implemented without worsening disparities.

The field of implementation science increasingly offers approaches to integrating health equity into intervention design and implementation and should be embraced along with equitable partner and community engagement as the field moves to develop, implement, and scale evidence-based interventions to reduce diabetes disparities.^190,191

Principles of equitable, sustainable, and cost-effective research that addresses the multilevel and multidisciplinary behavioural, social, and structural determinants of diabetes disparities must be embraced by the funding community

Funders of community or clinic-based diabetes research should require a health equity plan for all phases of diabetes research—ie, a statement on how the research will promote health equity or at the very least not increase disparities. To achieve this goal, principles of implementation science should be considered even at the effectiveness and clinical trial stages of research to ensure an understanding of how to promote equity as the research progresses. Practically speaking this means evaluating key implementation outcomes such as reach, acceptability, appropriateness, feasibility, and adoption early on. Studying implementation outcomes enables investigators to start to identify early on potential barriers for equitable implementation in the real world. Defining implementation outcomes also provides an opportunity to tailor implementation strategies to age groups and differences within racial and ethnic groups.

Upon review of the multilevel causes of diabetes disparities across the lifespan, it becomes apparent that multilevel and multidisciplinary approaches are crucial to solving the problem of diabetes disparities. Funders should recognise this importance and provide opportunities for multidisciplinary teams to address this need in collaboration with communities. To promote community-based participatory research that addresses these multilevel factors, funders should invest in strengthening capacity among early stage investigators in the intersection of diabetes and health equity with a focus on trainees from under-represented groups. Moreover, given the value of implementation science in improving equity in health service delivery, training, and funding for early-stage investigators to conduct health-equity focused implementation science research could accelerate the implementation and dissemination of evidence-based interventions in routine practice.¹⁸⁹ Furthermore, there is a need to provide training opportunities for more experienced scientists to embrace and incorporate principles of community engagement and health equity into existing research programmes.

Practitioners on the front lines of diabetes prevention and management need to know and understand the multilevel factors contributing to diabetes disparities including those at the provider, community, and health-system levels

Front-line providers play an important role in addressing disparities through their one-on-one interaction with patients, through institutional change, and through community engagement. At an individual level, the role of health-care providers’ implicit bias has long been studied and the effect of training on reducing disparities examined.¹⁹² Continued attention to implicit bias with focus on understanding gaps in translational effectiveness is important.¹⁹³ At an institutional level, front-line practitioners have a role in addressing structural barriers to access to care for their patients. It is crucial to develop evidence-based approaches to address structural barriers to health-care access such as inadequacies of language services, variable dependence on technology, transportation challenges, and financial constraints. Lastly, engaging with community members to actively understand the challenges faced by patients and develop equitable solutions is essential.^194–196 We need participatory action research engaging community partners in prioritising and developing approaches for overcoming these health system barriers. This participatory action research provides an opportunity for health providers to understand differences across the lifespan as well as tailoring approaches to within group differences.

In their approach to counselling and management of patients, health providers must learn to recognise differences in phenotypic presentation of diabetes to tailor therapy. Recognising the structural and environmental factors that contribute to diabetes and poor management of diabetes in some communities is imperative as we design therapies, set policy, and provide advice. Training providers on the role of social and environmental determinants of health is crucial to ensuring future practitioners overcome their own and their institution’s contribution to health disparities.

Policy makers must recognise their role in health disparities both based on historical policy decisions as well as current ones to make necessary policy changes to reduce disparities

In this Series paper, we summarised the various ways in which policy decisions now (eg, scarcity of policies to drive investment in disadvantaged neighbourhoods) and in the past (eg, redlining), differentially affect the health of minority race and ethnic communities and, therefore, drive health disparities. Addressing social determinants of health holds great potential for progress towards reducing diabetes disparities.^98,197 As health-care quality improvement efforts to address diabetes care advance, there is a need for rigorous studies to design and test delivery models that integrate social care into medical care; for example, through screening of individuals’ social risks and assets and strategies to address or mitigate the adverse effects of social adversity on diabetes management.¹⁹⁸ In addition to addressing social determinants of diabetes within the health-care system, there are opportunities to fill gaps in evidence on the effectiveness of large-scale policies and programmes such as food and agricultural policies and programmes in promoting healthy eating and physical activity and thereby contributing to the prevention of diabetes and diabetes-related complications, including their effect on diabetes disparities.¹⁹⁹

Recognising the role of institutional racism on existing policies is crucial to revising and developing evidence-based solutions to policy change that can overcome these barriers to care. Further research is needed to inform policies that can address some of the structural and social determinants of health that are the root causes of health disparities, both between and within racial and ethnic groups.²⁰⁰ To achieve this goal, policy and programme monitoring should integrate health equity indicators so that the differential effect of policies can be documented and thus the impact of policy change reported on health disparities. This type of attention would help promote accountability and generate data needed to inform change.

Conclusions

Disparities in the prevalence and management of diabetes in the USA persist today due to multilevel and multidisciplinary factors from the individual level to the systems level. Disparities should be examined beyond differences between racial and ethnic groups to include differences within race and ethnic groups and across the lifespan. Our Review systematically outlines those differences and their drivers and offers actionable recommendations at the researcher, practitioner and health-system, and policy levels to promote health equity in diabetes moving forward.

Panel: Recommendations for addressing disparities in diabetes.

Generate a community-engaged and multidisciplinary research agenda that adopts a life course approach and addresses pathophysiological and multilevel causes of diabetes disparities

• Community-based participatory research to guide precision medicine approaches

• Incorporation of environmental and climate justice principles

• Equitable partnerships

Principles of equitable, sustainable, and cost-effective research that addresses the multilevel and multidisciplinary behavioural, social, and structural determinants of diabetes disparities must be embraced by the funding community

• Funders should require a health equity plan

• Multilevel and multidisciplinary approaches

• Strengthening capacity among diverse early-stage investigators

Practitioners on the front lines of diabetes prevention and management need to know and understand the multilevel factors contributing to diabetes disparities including those at the provider, community, and health-system levels

• Awareness of implicit bias

• Addressing barriers to accessing quality health care

• Tailoring therapy to diabetes phenotypes

Policy makers must recognise their role in health disparities both based on historical policy decisions and current ones to make necessary policy changes to reduce disparities

• Models of care that integrate social care into medical care

• Policies to address social determinants of health within the health-care system

• Addressing institutional racism

Search strategy and selection criteria.

We identified references for this Series paper through searches of PubMed for articles published between Jan 1, 2012, and Jan 31, 2022, to reflect the past decade of innovation and discovery in the diabetes disparities literature. Additional articles published before Jan 1, 2012, and after Jan 31, 2022, were included when relevant and important to this Series paper. Our search was designed to identify relevant literature across three main themes: diabetes disparities across the lifespan, diabetes disparities within racial and ethnic groups, and diabetes phenotypes. As this is a narrative review, our objective was to use this search to provide key articles that together could yield a more nuanced understanding of diabetes disparities. A full description of our methods can be found in the appendix.