Studies that have compared HbA1c levels by race have consistently demonstrated higher HbA1c levels in African Americans than in whites. These racial differences in HbA1c have not been explained by measured differences in glycemia, sociodemographic factors, clinical factors, access to care, or quality of care. Recently, a number of nonglycemic factors and several genetic polymorphisms that operate through nonglycemic mechanisms have been associated with HbA1c. Their distributions across racial groups and their impact on hemoglobin glycation need to be systematically explored. Thus, on the basis of evidence for racial differences in HbA1c, current clinical guidelines from the American Diabetes Association state: “It is important to take…race/ethnicity…into consideration when using the A1C to diagnose diabetes.” However, it is not clear from the guidelines how this recommendation might be actualized. So, the critical question is not whether racial differences in HbA1c exist between African Americans and whites; the important question is whether the observed differences in HbA1c level are clinically meaningful. Therefore, given the current controversy, we provide a Point-Counterpoint debate on this issue. In the preceding point narrative, Dr. Herman provides his argument that the failure to acknowledge that HbA1c might be a biased measure of average glycemia and an unwillingness to rigorously investigate this hypothesis will slow scientific progress and has the potential to do great harm. In the counterpoint narrative below, Dr. Selvin argues that there is no compelling evidence for racial differences in the validity of HbA1c as a measure of hyperglycemia and that race is a poor surrogate for differences in underlying causes of disease risk.

—William T. Cefalu

Editor in Chief, Diabetes Care

In a major change to clinical practice guidelines, the International Expert Committee first recommended the use of hemoglobin A1c (HbA1c) for the diagnosis of diabetes in 2009 (1). This recommendation was codified in the American Diabetes Association’s Clinical Practice Recommendations in 2010 (2) and has been adopted by the World Health Organization and numerous other professional groups across the globe (3,4). Given the long-standing use of HbA1c for diabetes control and its strong link to complications, the use of HbA1c in diagnosis of diabetes seemed advisable and advantageous. Nevertheless, the 2009 recommendations for the use of HbA1c as a diagnostic test for diabetes were met with considerable controversy (5). Central to this controversy has been the interpretation of racial differences in HbA1c levels. The relevance of racial differences in HbA1c for its use in screening, diagnosis, and management of diabetes is the focus of this commentary.

In the U.S., racial and ethnic minority groups are disproportionately burdened by adverse social and economic conditions that can profoundly influence disease risk. Society-level factors such as social position, residence, material conditions (including wealth), social connections, environment, and food and physical insecurity are particularly important factors influencing risk of obesity and diabetes (6,7). There are well-documented racial disparities in the risk of diabetes, with African Americans approximately twice as likely to develop diabetes as compared with their white counterparts (8). Racial and ethnic minority groups are also disproportionately burdened by the complications of diabetes including retinopathy (9,10), chronic kidney disease (11), and lower-extremity peripheral vascular disease (12,13), with an especially high risk of amputation (14). Indeed, racial differences in end-stage renal disease represent one of the most striking racial disparities in health in the U.S. (15,16).

In numerous cohorts and in national data, it has been shown that blacks have higher HbA1c values than whites in both the presence and absence of diabetes (1721). Mexican Americans have values of HbA1c that are intermediate between blacks and whites (9,22). Comparisons of HbA1c in other racial/ethnic groups and non-U.S. populations are scarce but suggest higher nondiabetic levels of HbA1c in some groups, e.g., South Asians, black Brazilians, and Inuit populations, compared with whites or Caucasians (2325). It is unclear what factors might be driving these differences.

Racial differences in HbA1c have been widely cited as a potential shortcoming of HbA1c testing for diagnosis of diabetes (2629). On the basis of evidence for racial differences in HbA1c, current clinical guidelines from the American Diabetes Association state: “It is important to take…race/ethnicity…into consideration when using the A1C to diagnose diabetes” (29). However, it is not clear from the guidelines how this recommendation might be actualized. Some argue that racial differences are nonglycemic in nature, i.e., a result of factors that influence HbA1c via pathways independent of glucose or hyperglycemia, and have suggested that HbA1c is “invalid” or “misleading” as a diagnostic test in African Americans (30,31). Clearly this claim is not trivial: HbA1c is widely considered the gold standard measure of chronic hyperglycemia in diabetes care. Treatment and diagnostic decisions are routinely based on HbA1c levels. If the higher HbA1c in blacks compared with whites is primarily due to nonglycemic factors, then HbA1c is falsely high in blacks. If this claim is substantiated, it suggests potential disparities in diabetes care may not be real, efforts to reduce hyperglycemia in blacks may be unwarranted and could cause harm, and that we might need race-specific diagnostic and treatment thresholds.

The debate is not whether racial differences in HbA1c exist: they do. What is not clear is why levels of HbA1c are somewhat higher in blacks compared with whites.

Nonglycemic Factors

HbA1c is an indirect measure of hyperglycemia (3235), but it is well established that the primary determinant of HbA1c is circulating glucose level (33). It has been postulated that racial differences in HbA1c might be explained by differences in hemoglobin-related factors. Red cell turnover may be the most important unmeasured nonglycemic determinant of HbA1c (36), but there is currently no direct evidence of racial differences in red cell turnover that might explain racial differences in HbA1c. The impact of red cell turnover on HbA1c in the general population is not well understood because of major difficulties in its measurement (37). Certain conditions such as glucose-6-phosphate dehydrogenase deficiency and specific hemoglobin variants (e.g., sickle cell) are more common in African Americans than in whites. Glucose-6-phosphate dehydrogenase deficiency causes hemolysis and can result in a lowering of HbA1c, and sickle cell trait (and other hemoglobin variants) can falsely lower or raise HbA1c or may have no effect depending on the method of HbA1c measurement (38).

Glycemic Factors

The racial differences we see in HbA1c levels across populations may reflect real differences in circulating average (nonfasting) glucose that are reflected in HbA1c but not (or not as much) in fasting glucose or 2-h glucose. Given the considerable black–white disparities in risk of diabetes and other major health conditions, perhaps it is not so surprising that there are racial differences in HbA1c even after adjusting for fasting glucose. A single measurement of fasting glucose or 2-h glucose does not fully reflect average glycemia and would not account for possible differences in true circulating average glucose between races. Differences in body composition, physical activity, diet, lifestyle, stress, and/or environmental and neighborhood-level factors might affect circulating nonfasting glucose levels and contribute to the racial differences in HbA1c. Such parameters may not be fully captured by standard assessments in large epidemiologic studies, leaving open the possibility that racial disparities in HbA1c are not artifactual but reflect black–white differences in true circulating nonfasting glucose.

Importantly, the higher levels of HbA1c are also seen for other biomarkers of chronic hyperglycemia, specifically fructosamine and glycated albumin (3942). Because fructosamine and glycated albumin are unaffected by the hematologic factors that might affect HbA1c, racial differences in erythrocyte turnover or hemoglobin glycation cannot explain racial differences in these hemoglobin-independent serum biomarkers of hyperglycemia. The racial differences in fructosamine and glycated albumin support a difference in glycemia itself.

Genetic Factors

Genetic differences undoubtedly contribute to both glycemic and nonglycemic variation in measures of hyperglycemia including HbA1c. The clinical significance of a nonglycemic genetic contribution is uncertain, particularly in persons without genetic hemoglobin abnormalities. We have previously shown that genetic ancestry does not contribute substantially (<1%) to variability in HbA1c among African Americans (43). Furthermore, no known genetic variants differ substantially enough between persons of African compared with Caucasian ancestry to explain racial differences in HbA1c in the general population (4446). Although the current evidence does not rule out the possibility of genetic nonglycemic determinants of HbA1c, there is no clear evidence that genetic differences contribute substantially to racial differences in HbA1c. Race is primarily a social construct (47,48), and the literature does suggest that we should not treat race like a biological factor that should be used to adjust HbA1c values.

The cause or causes of racial disparities in HbA1c are incompletely understood, and we cannot rule out a small but systematic nonglycemic difference. Research is needed to understand the full determinants of HbA1c, particularly the impact of red cell turnover on differences across population subgroups. Nonetheless, we should recognize that, in the diabetic range, the primary determinant of HbA1c is circulating ambient glucose; other factors are likely to have a relatively small influence.

Are there nonglycemic determinants of HbA1c? Certainly. Do these nonglycemic determinants play a large role at diagnostic or higher (diabetic) levels of HbA1c in most of the population? Probably not. Are there studies that provide direct evidence that nonglycemic factors explain racial differences in HbA1c? No. The question is then not whether there are racial differences in HbA1c as an accurate index of chronic hyperglycemia. The important question now is: Are the observed racial differences in HbA1c level clinically meaningful?

A major justification for using HbA1c as a diagnostic test for diabetes is the strong evidence linking it to future diabetes and major clinical complications in ethnically diverse populations (19,4954). If the observed systematically higher HbA1c levels in African Americans as compared with whites stem from racial differences not in glucose exposure but from nonglycemic factors, then HbA1c should be a weaker predictor of diabetic complications in African Americans, especially compared with fasting glucose. The current diabetes diagnostic cut point of HbA1c 6.5% is supported by epidemiologic evidence for a high prevalence of retinopathy beginning above this threshold (1,55,56), with key studies in multiethnic U.S. study populations (56,57), Malay adults in Singapore (58), and Australian (59), Pima Indian (60), Egyptian (55,61), Korean (62), Chinese (63), and Japanese (64,65) populations. In analyses of data from the National Health and Nutrition Examination Survey (NHANES), investigators have directly compared the prognostic value of clinical categories of HbA1c in populations of Mexican Americans, African Americans, and whites. These analyses found no evidence for racial/ethnic differences in the relative association of HbA1c with prevalent retinopathy, suggesting that current diabetes clinical cut points should be interpreted similarly in whites, African Americans, and Mexican Americans (9,10). Randomized clinical trials in persons with diabetes have further demonstrated that lowering HbA1c reduces the risk of microvascular disease, regardless of race/ethnicity (66).

For this report we conducted analyses of two population-based studies, the community-based Atherosclerosis Risk in Communities (ARIC) Study and the nationally representative NHANES, to compare associations of diagnostic categories of HbA1c and fasting glucose with major long-term diabetic complications in black, Mexican American, and white persons. We analyzed HbA1c and fasting glucose data from 11,018 participants aged 48–68 years with no history of cardiovascular disease who attended the second examination of the ARIC Study from 1990 to 1992. During a median of approximately 20 years of follow-up, there were 279 peripheral vascular disease events, 1,550 cases of chronic kidney disease, 2,205 cardiovascular (coronary heart disease or stroke) events, and 2,999 deaths. Comparing the hazard ratios across clinical categories of HbA1c and fasting glucose reveals that, in general, HbA1c is more strongly associated with future clinical outcomes as compared with fasting glucose and the relative risk associations appear similar in blacks and whites (Table 1). NHANES III, which is linked to national mortality data (but not nonfatal outcomes), also included measurements of HbA1c and fasting glucose in non-Hispanic black, non-Hispanic white, and Mexican American adults. Thus, similar analyses can be conducted in this nationally representative cohort. In an analysis of 12,722 NHANES III (1988–1994) participants aged 20 years or older with HbA1c measurements (and 5,676 with fasting glucose), there were 804 total deaths of which 363 were from cardiovascular causes during a median of approximately 19 years of follow-up. In NHANES III, clinical categories of HbA1c in non-Hispanic blacks were similarly or more strongly associated with cardiovascular and all-cause mortality as compared with non-Hispanic whites (Table 2).

Table 1

Adjusted hazard ratios (95% CI)* of peripheral vascular disease, chronic kidney disease, cardiovascular disease, and all-cause mortality according to categories of HbA1c and fasting glucose at baseline in blacks and whites without diagnosed diabetes, the ARIC Study (1990–1992), N = 11,018

HbA1c <5.0%HbA1c 5.0–5.6%HbA1c 5.7–6.5%HbA1c ≥6.5%
Peripheral vascular disease, n = 279 events     
 White 1.25 (0.70–2.23) 1 (ref) 1.63 (1.20–2.22) 3.22 (1.93–5.38) 
 Black 2.06 (0.74–5.69) 1 (ref) 1.24 (0.66–2.33) 2.73 (1.24–6.02) 
Chronic kidney disease, n = 1,550 events     
 White 0.97 (0.76–1.22) 1 (ref) 1.30 (1.13–1.49) 1.84 (1.41–2.42) 
 Black 2.15 (1.40–3.30) 1 (ref) 1.56 (1.22–2.01) 1.82 (1.28–2.60) 
Cardiovascular disease, n = 2,205 events     
 White 0.99 (0.81–1.20) 1 (ref) 1.51 (1.35–1.69) 1.94 (1.55–2.44) 
 Black 0.78 (0.47–1.29) 1 (ref) 1.36 (1.09–1.70) 2.28 (1.68–3.08) 
All-cause mortality, n = 2,999 deaths     
 White 1.19 (1.01–1.40) 1 (ref) 1.37 (1.24–1.50) 1.72 (1.39–2.12) 
 Black 1.41 (1.03–1.93) 1 (ref) 1.14 (0.96–1.36) 1.36 (1.05–1.78) 
 Fasting glucose <90 mg/dL Fasting glucose 90–99 mg/dL Fasting glucose 100–125 mg/dL Fasting glucose ≥126 mg/dL 
Peripheral vascular disease, n = 279 events     
 White 0.79 (0.42–1.51) 1 (ref) 0.99 (0.72–1.35) 1.26 (0.74–2.17) 
 Black 0.71 (0.21–2.45) 1 (ref) 0.68 (0.37–1.25) 1.55 (0.72–3.33) 
Chronic kidney disease, n = 1,550 events     
 White 1.07 (0.84–1.36) 1 (ref) 1.04 (0.91–1.18) 1.25 (0.98–1.59) 
 Black 1.14 (0.71–1.84) 1 (ref) 1.16 (0.90–1.50) 1.61 (1.14–2.27) 
Cardiovascular disease, n = 2,205 events     
 White 1.27 (1.04–1.55) 1 (ref) 1.12 (1.00–1.25) 1.40 (1.15–1.71) 
 Black 0.88 (0.57–1.35) 1 (ref) 0.89 (0.71–1.11) 1.38 (1.01–1.87) 
All-cause mortality, n = 2,999 deaths     
 White 1.01 (0.85–1.21) 1 (ref) 1.10 (1.00–1.21) 1.54 (1.29–1.83) 
 Black 1.17 (0.87–1.59) 1 (ref) 0.89 (0.75–1.07) 1.06 (0.81–1.38) 
HbA1c <5.0%HbA1c 5.0–5.6%HbA1c 5.7–6.5%HbA1c ≥6.5%
Peripheral vascular disease, n = 279 events     
 White 1.25 (0.70–2.23) 1 (ref) 1.63 (1.20–2.22) 3.22 (1.93–5.38) 
 Black 2.06 (0.74–5.69) 1 (ref) 1.24 (0.66–2.33) 2.73 (1.24–6.02) 
Chronic kidney disease, n = 1,550 events     
 White 0.97 (0.76–1.22) 1 (ref) 1.30 (1.13–1.49) 1.84 (1.41–2.42) 
 Black 2.15 (1.40–3.30) 1 (ref) 1.56 (1.22–2.01) 1.82 (1.28–2.60) 
Cardiovascular disease, n = 2,205 events     
 White 0.99 (0.81–1.20) 1 (ref) 1.51 (1.35–1.69) 1.94 (1.55–2.44) 
 Black 0.78 (0.47–1.29) 1 (ref) 1.36 (1.09–1.70) 2.28 (1.68–3.08) 
All-cause mortality, n = 2,999 deaths     
 White 1.19 (1.01–1.40) 1 (ref) 1.37 (1.24–1.50) 1.72 (1.39–2.12) 
 Black 1.41 (1.03–1.93) 1 (ref) 1.14 (0.96–1.36) 1.36 (1.05–1.78) 
 Fasting glucose <90 mg/dL Fasting glucose 90–99 mg/dL Fasting glucose 100–125 mg/dL Fasting glucose ≥126 mg/dL 
Peripheral vascular disease, n = 279 events     
 White 0.79 (0.42–1.51) 1 (ref) 0.99 (0.72–1.35) 1.26 (0.74–2.17) 
 Black 0.71 (0.21–2.45) 1 (ref) 0.68 (0.37–1.25) 1.55 (0.72–3.33) 
Chronic kidney disease, n = 1,550 events     
 White 1.07 (0.84–1.36) 1 (ref) 1.04 (0.91–1.18) 1.25 (0.98–1.59) 
 Black 1.14 (0.71–1.84) 1 (ref) 1.16 (0.90–1.50) 1.61 (1.14–2.27) 
Cardiovascular disease, n = 2,205 events     
 White 1.27 (1.04–1.55) 1 (ref) 1.12 (1.00–1.25) 1.40 (1.15–1.71) 
 Black 0.88 (0.57–1.35) 1 (ref) 0.89 (0.71–1.11) 1.38 (1.01–1.87) 
All-cause mortality, n = 2,999 deaths     
 White 1.01 (0.85–1.21) 1 (ref) 1.10 (1.00–1.21) 1.54 (1.29–1.83) 
 Black 1.17 (0.87–1.59) 1 (ref) 0.89 (0.75–1.07) 1.06 (0.81–1.38) 
*

Adjusted for age, sex, LDL cholesterol, HDL cholesterol, log-transformed triglycerides, BMI, waist-to-hip ratio, hypertension, family history of diabetes, education, drinking status, cigarette smoking status, and physical activity index.

Table 2

Adjusted hazard ratios (95% CI)* of cardiovascular and all-cause mortality according to categories of HbA1c and fasting glucose at baseline in persons without diagnosed diabetes, by race/ethnicity group, U.S. adults aged 18 years or older (NHANES III, 1988–1994), N = 12,722

HbA1c <5.0%HbA1c 5.0–5.6%HbA1c 5.7–6.5%HbA1c ≥6.5%
Cardiovascular mortality, n = 804 deaths     
 Non-Hispanic white 0.74 (0.38–1.41) 1 (ref) 1.13 (0.83–1.53) 1.39 (0.77–2.51) 
 Non-Hispanic black 0.94 (0.45–1.96) 1 (ref) 1.10 (0.78–1.56) 2.25 (0.89–5.64) 
 Mexican American 0.60 (0.18–1.98) 1 (ref) 1.15 (0.63–2.10) 3.90 (1.86–8.17) 
All-cause mortality, n = 3,415 deaths     
 Non-Hispanic white 1.18 (0.91–1.54) 1 (ref) 1.12 (0.96–1.32) 1.50 (1.09–2.05) 
 Non-Hispanic black 1.27 (0.88–1.81) 1 (ref) 1.14 (0.98–1.32) 2.00 (1.40–2.85) 
 Mexican American 0.99 (0.60–1.63) 1 (ref) 1.15 (0.84–1.58) 1.74 (1.13–2.67) 
 Fasting glucose <90 mg/dL Fasting glucose 90–99 mg/dL Fasting glucose 100–125 mg/dL Fasting glucose ≥126 mg/dL 
Cardiovascular mortality, n = 363 deaths     
 Non-Hispanic white 0.96 (0.51–1.80) 1 (ref) 1.43 (0.87–2.35) 1.82 (0.98–3.36) 
 Non-Hispanic black 0.77 (0.29–2.05) 1 (ref) 0.97 (0.45–2.07) 1.60 (0.42–6.13) 
 Mexican American 1.96 (0.86–4.47) 1 (ref) 1.11 (0.55–2.24) 1.22 (0.39–3.84) 
All-cause mortality, n = 1,536 deaths     
 Non-Hispanic white 0.96 (0.76–1.21) 1 (ref) 1.16 (0.97–1.38) 1.47 (1.04–2.08) 
 Non-Hispanic black 1.09 (0.71–1.66) 1 (ref) 1.16 (0.85–1.59) 2.40 (1.50–3.84) 
 Mexican American 0.84 (0.46–1.53) 1 (ref) 0.97 (0.61–1.52) 1.48 (0.69–3.17) 
HbA1c <5.0%HbA1c 5.0–5.6%HbA1c 5.7–6.5%HbA1c ≥6.5%
Cardiovascular mortality, n = 804 deaths     
 Non-Hispanic white 0.74 (0.38–1.41) 1 (ref) 1.13 (0.83–1.53) 1.39 (0.77–2.51) 
 Non-Hispanic black 0.94 (0.45–1.96) 1 (ref) 1.10 (0.78–1.56) 2.25 (0.89–5.64) 
 Mexican American 0.60 (0.18–1.98) 1 (ref) 1.15 (0.63–2.10) 3.90 (1.86–8.17) 
All-cause mortality, n = 3,415 deaths     
 Non-Hispanic white 1.18 (0.91–1.54) 1 (ref) 1.12 (0.96–1.32) 1.50 (1.09–2.05) 
 Non-Hispanic black 1.27 (0.88–1.81) 1 (ref) 1.14 (0.98–1.32) 2.00 (1.40–2.85) 
 Mexican American 0.99 (0.60–1.63) 1 (ref) 1.15 (0.84–1.58) 1.74 (1.13–2.67) 
 Fasting glucose <90 mg/dL Fasting glucose 90–99 mg/dL Fasting glucose 100–125 mg/dL Fasting glucose ≥126 mg/dL 
Cardiovascular mortality, n = 363 deaths     
 Non-Hispanic white 0.96 (0.51–1.80) 1 (ref) 1.43 (0.87–2.35) 1.82 (0.98–3.36) 
 Non-Hispanic black 0.77 (0.29–2.05) 1 (ref) 0.97 (0.45–2.07) 1.60 (0.42–6.13) 
 Mexican American 1.96 (0.86–4.47) 1 (ref) 1.11 (0.55–2.24) 1.22 (0.39–3.84) 
All-cause mortality, n = 1,536 deaths     
 Non-Hispanic white 0.96 (0.76–1.21) 1 (ref) 1.16 (0.97–1.38) 1.47 (1.04–2.08) 
 Non-Hispanic black 1.09 (0.71–1.66) 1 (ref) 1.16 (0.85–1.59) 2.40 (1.50–3.84) 
 Mexican American 0.84 (0.46–1.53) 1 (ref) 0.97 (0.61–1.52) 1.48 (0.69–3.17) 
*

Adjusted for age, sex, lipids, BMI, waist-to-hip ratio, education, smoking status, hypertension, and physical activity;

Subsample of 5,676 participants who attended the morning examination and had measurements of fasting plasma glucose.

These data from ARIC and NHANES demonstrate that HbA1c ≥6.5% is a risk factor for future development of peripheral vascular disease, kidney disease, cardiovascular disease, and death across racial/ethnic groups. We see patterns of association of HbA1c diagnostic categories that are generally similar or stronger than those for fasting glucose; our results do not support the contention that HbA1c is a weaker predictor of outcomes compared with fasting glucose in African Americans compared with whites. These results extend and update prior publications (18,19,53,6769), and, taken as a whole, the current literature demonstrates that race-specific HbA1c cut points for diagnosis of diabetes would not be consistent with long-term risk associations.

In other studies in ARIC, we also observed that associations of nontraditional biomarkers of hyperglycemia (fructosamine and glycated albumin) with clinical outcomes were also similar in blacks and whites (39). Ultimately, the literature suggests that HbA1c is a similarly valid diagnostic and prognostic tool in persons of different races/ethnicities and supports recommendations for using the same HbA1c diagnostic cut points across racial/ethnic groups (10,70). To quote a saying commonly attributed to Gertrude Stein: “A difference, to be a difference, must make a difference.”

As with any clinical test, the strength and limitations of HbA1c need to be understood and communicated. Each HbA1c test result needs to be interpreted in the context of the individual patient. Although population-level evidence is critical to guide individual decision-making, diabetes clinical practice guidelines have increasingly recognized the need for individualization of diabetes treatment (7173). To most effectively address the diabetes epidemic, we need to improve our approaches to preventing and treating diabetes and tailor these approaches to each individual.

The evidence from population-based studies suggests that HbA1c is a useful and valid test of hyperglycemia across racial/ethnic groups. Indeed, studies using modern HbA1c assays have now shown that HbA1c is more strongly associated with outcomes as compared with fasting glucose or 2-h postprandial glucose (19,54). There is robust evidence that HbA1c is associated with microvascular and macrovascular outcomes in diverse populations. There is no compelling evidence that the validity of HbA1c as a measure of hyperglycemia and the prognostic value of clinical categories of HbA1c differ substantially according to race.

Certainly more work needs to be done to understand the causes of racial differences in HbA1c and the contribution of nonglycemic factors. But race is a poor surrogate for differences in underlying causes of disease risk, and suggestions for racially based medical decisions are disquieting. If anything, we need less emphasis on using race to define health and guide medical decision making. With respect to HbA1c, we need to understand what might be causing disparities lest we inappropriately withhold a useful and prognostic test from a subgroup of the population known to be at high risk for diabetes and its complications. There is no evidence that HbA1c testing will lead to “overdiagnosis” of diabetes in African Americans. There is, however, a real concern that recommendations to avoid or interpret HbA1c results differently in racial/ethnic minority populations may actually increase health disparities.

Acknowledgments. E.S. is indebted to Drs. Larry Appel and Morgan Grams, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, for their valuable comments on an early draft of this article and to the staff and participants of the ARIC Study for their important contributions to this work. E.S. also thanks Yuan Chen, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, for assistance with statistical analyses.

Funding. This work is supported by National Institutes of Health National Institute of Diabetes and Digestive and Kidney Diseases grants 2R01-DK-089174 and K24-DK-106414 to E.S. The ARIC Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C).

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

See accompanying articles, pp. 1299 and 1458.

1.
The International Expert Committee
.
International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes
.
Diabetes Care
2009
;
32
:
1327
1334
2.
American Diabetes Association
.
Standards of medical care in diabetes—2010
.
Diabetes Care
2010
;
33
(
Suppl. 1
):
S11
S61
3.
World Health Organization
. Use of glycated haemoglobin (HbA1c) in the diagnosis of diabetes mellitus: abbreviated report of a WHO consultation [Internet],
2011
. World Health Organization. Available from http://www.who.int/diabetes/publications/report-hba1c_2011.pdf. Accessed 26 May 2016
4.
International Diabetes Federation Clinical Guidelines Task Force
. Global guideline for type 2 diabetes [Internet],
2012
. International Diabetes Federation. Available from http://www.idf.org/sites/default/files/IDF-Guideline-for-Type-2-Diabetes.pdf. Accessed 26 May 2016
5.
Sacks
DB
.
Hemoglobin A1c in diabetes: panacea or pointless?
Diabetes
2013
;
62
:
41
43
6.
Jack
L
,
Jack
NH
,
Hayes
SC
.
Social determinants of health in minority populations: a call for multidisciplinary approaches to eliminate diabetes-related health disparities
.
Diabetes Spectr
2012
;
25
:
9
13
7.
Agardh
E
,
Allebeck
P
,
Hallqvist
J
,
Moradi
T
,
Sidorchuk
A
.
Type 2 diabetes incidence and socio-economic position: a systematic review and meta-analysis
.
Int J Epidemiol
2011
;
40
:
804
818
8.
Brancati
FL
,
Kao
WHL
,
Folsom
AR
,
Watson
RL
,
Szklo
M
.
Incident type 2 diabetes mellitus in African American and white adults: the Atherosclerosis Risk in Communities Study
.
JAMA
2000
;
283
:
2253
2259
9.
Bower
JK
,
Brancati
FL
,
Selvin
E
.
No ethnic differences in the association of glycated hemoglobin with retinopathy: the National Health and Nutrition Examination Survey 2005–2008
.
Diabetes Care
2013
;
36
:
569
573
10.
Tsugawa
Y
,
Mukamal
KJ
,
Davis
RB
,
Taylor
WC
,
Wee
CC
.
Should the hemoglobin A1c diagnostic cutoff differ between blacks and whites? A cross-sectional study
.
Ann Intern Med
2012
;
157
:
153
159
11.
Crews
DC
,
Pfaff
T
,
Powe
NR
.
Socioeconomic factors and racial disparities in kidney disease outcomes
.
Semin Nephrol
2013
;
33
:
468
475
12.
Selvin
E
,
Erlinger
TP
.
Prevalence of and risk factors for peripheral arterial disease in the United States: results from the National Health and Nutrition Examination Survey, 1999-2000
.
Circulation
2004
;
110
:
738
743
13.
Gregg
EW
,
Sorlie
P
,
Paulose-Ram
R
, et al.;
1999-2000 National Health and Nutrition Examination Survey
.
Prevalence of lower-extremity disease in the U.S. adult population >=40 years of age with and without diabetes: 1999-2000 National Health and Nutrition Examination Survey
.
Diabetes Care
2004
;
27
:
1591
1597
14.
Goodney
PPDN
,
Goodman
DC
,
Bronner
KK
. Variation in the Care of Surgical Conditions: Diabetes and Peripheral Arterial Disease: A Dartmouth Atlas of Health Care Series,
2014
. Available from http://www.dartmouthatlas.org/downloads/reports/Diabetes_report_10_14_14.pdf. Accessed 26 May 2016
15.
Tarver-Carr
ME
,
Powe
NR
,
Eberhardt
MS
, et al
.
Excess risk of chronic kidney disease among African-American versus white subjects in the United States: a population-based study of potential explanatory factors
.
J Am Soc Nephrol
2002
;
13
:
2363
2370
16.
Parsa
A
,
Kao
WHL
,
Xie
D
, et al.;
AASK Study Investigators
;
CRIC Study Investigators
.
APOL1 risk variants, race, and progression of chronic kidney disease
.
N Engl J Med
2013
;
369
:
2183
2196
17.
Harris
MI
,
Eastman
RC
,
Cowie
CC
,
Flegal
KM
,
Eberhardt
MS
.
Racial and ethnic differences in glycemic control of adults with type 2 diabetes
.
Diabetes Care
1999
;
22
:
403
408
18.
Selvin
E
,
Rawlings
AM
,
Bergenstal
RM
,
Coresh
J
,
Brancati
FL
.
No racial differences in the association of glycated hemoglobin with kidney disease and cardiovascular outcomes
.
Diabetes Care
2013
;
36
:
2995
3001
19.
Selvin
E
,
Steffes
MW
,
Zhu
H
, et al
.
Glycated hemoglobin, diabetes, and cardiovascular risk in nondiabetic adults
.
N Engl J Med
2010
;
362
:
800
811
20.
Kirk
JK
,
D’Agostino
RB
 Jr
,
Bell
RA
, et al
.
Disparities in HbA1c levels between African-American and non-Hispanic white adults with diabetes: a meta-analysis
.
Diabetes Care
2006
;
29
:
2130
2136
21.
Saaddine
JB
,
Fagot-Campagna
A
,
Rolka
D
, et al
.
Distribution of HbA(1c) levels for children and young adults in the U.S.: Third National Health and Nutrition Examination Survey
.
Diabetes Care
2002
;
25
:
1326
1330
22.
Menke
A
,
Rust
KF
,
Savage
PJ
,
Cowie
CC
.
Hemoglobin A1c, fasting plasma glucose, and 2-hour plasma glucose distributions in U.S. population subgroups: NHANES 2005-2010
.
Ann Epidemiol
2014
;
24
:
83
89
23.
Shipman
KE
,
Jawad
M
,
Sullivan
KM
,
Ford
C
,
Gama
R
.
Ethnic/racial determinants of glycemic markers in a UK sample
.
Acta Diabetol
2015
;
52
:
687
692
24.
de Miranda
VA
,
Cruz Filho
RA
,
de Oliveira
TS
, et al
.
Racial differences in HbA1c: a cross-sectional analysis of a Brazilian public primary care population
.
Prim Care Diabetes
2013
;
7
:
135
141
25.
Jørgensen
ME
,
Bjerregaard
P
,
Borch-Johnsen
K
,
Witte
D
.
New diagnostic criteria for diabetes: is the change from glucose to HbA1c possible in all populations?
J Clin Endocrinol Metab
2010
;
95
:
E333
E336
26.
Inzucchi
SE
.
Clinical practice. Diagnosis of diabetes
.
N Engl J Med
2012
;
367
:
542
550
27.
Sacks
DB
.
A1C versus glucose testing: a comparison
.
Diabetes Care
2011
;
34
:
518
523
28.
Davidson
MB
.
Diagnosing diabetes with glucose criteria: worshiping a false God
.
Diabetes Care
2011
;
34
:
524
526
29.
American Diabetes Association
.
Classification and diagnosis of diabetes. Sec. 2. In Standards of Medical Care in Diabetes—2016
.
Diabetes Care
2016
;
39
(
Suppl. 1
):
S13
S22
30.
Dagogo-Jack
S
.
Pitfalls in the use of HbA₁(c) as a diagnostic test: the ethnic conundrum
.
Nat Rev Endocrinol
2010
;
6
:
589
593
31.
Herman
WH
,
Ma
Y
,
Uwaifo
G
, et al.;
Diabetes Prevention Program Research Group
.
Differences in A1C by race and ethnicity among patients with impaired glucose tolerance in the Diabetes Prevention Program
.
Diabetes Care
2007
;
30
:
2453
2457
32.
Bunn
HF
,
Haney
DN
,
Kamin
S
,
Gabbay
KH
,
Gallop
PM
.
The biosynthesis of human hemoglobin A1c. Slow glycosylation of hemoglobin in vivo
.
J Clin Invest
1976
;
57
:
1652
1659
33.
Nathan
DM
,
Kuenen
J
,
Borg
R
,
Zheng
H
,
Schoenfeld
D
,
Heine
RJ
;
A1c-Derived Average Glucose Study Group
.
Translating the A1C assay into estimated average glucose values
.
Diabetes Care
2008
;
31
:
1473
1478
34.
Koenig
RJ
,
Peterson
CM
,
Kilo
C
,
Cerami
A
,
Williamson
JR
.
Hemoglobin A1c as an indicator of the degree of glucose intolerance in diabetes
.
Diabetes
1976
;
25
:
230
232
35.
Nathan
DM
,
Singer
DE
,
Hurxthal
K
,
Goodson
JD
.
The clinical information value of the glycosylated hemoglobin assay
.
N Engl J Med
1984
;
310
:
341
346
36.
Mortensen
HB
,
Christophersen
C
.
Glucosylation of human haemoglobin a in red blood cells studied in vitro. Kinetics of the formation and dissociation of haemoglobin A1c
.
Clin Chim Acta
1983
;
134
:
317
326
37.
Franco
RS
.
The measurement and importance of red cell survival
.
Am J Hematol
2009
;
84
:
109
114
38.
Bry
L
,
Chen
PC
,
Sacks
DB
.
Effects of hemoglobin variants and chemically modified derivatives on assays for glycohemoglobin
.
Clin Chem
2001
;
47
:
153
163
39.
Parrinello
CM
,
Sharrett
AR
,
Maruthur
NM
,
Bergenstal
RM
,
Grams
ME
,
Coresh
J
, et al
.
Racial differences in and prognostic value of biomarkers of hyperglycemia
.
Diabetes Care
. 17 December 2015 [Epub ahead of print]
40.
Selvin
E
,
Steffes
MW
,
Ballantyne
CM
,
Hoogeveen
RC
,
Coresh
J
,
Brancati
FL
.
Racial differences in glycemic markers: a cross-sectional analysis of community-based data
.
Ann Intern Med
2011
;
154
:
303
309
41.
Kohzuma
T
,
Yamamoto
T
,
Uematsu
Y
,
Shihabi
ZK
,
Freedman
BI
.
Basic performance of an enzymatic method for glycated albumin and reference range determination
.
J Diabetes Sci Technol
2011
;
5
:
1455
1462
42.
Shafi
T
,
Sozio
SM
,
Plantinga
LC
, et al
.
Serum fructosamine and glycated albumin and risk of mortality and clinical outcomes in hemodialysis patients
.
Diabetes Care
2013
;
36
:
1522
1533
43.
Maruthur
NM
,
Kao
WH
,
Clark
JM
, et al
.
Does genetic ancestry explain higher values of glycated hemoglobin in African Americans?
Diabetes
2011
;
60
:
2434
2438
44.
Soranzo
N
,
Sanna
S
,
Wheeler
E
, et al.;
WTCCC
.
Common variants at 10 genomic loci influence hemoglobin A₁(C) levels via glycemic and nonglycemic pathways
.
Diabetes
2010
;
59
:
3229
3239
45.
Soranzo
N
.
Genetic determinants of variability in glycated hemoglobin (HbA(1c)) in humans: review of recent progress and prospects for use in diabetes care
.
Curr Diab Rep
2011
;
11
:
562
569
46.
An
P
,
Miljkovic
I
,
Thyagarajan
B
, et al
.
Genome-wide association study identifies common loci influencing circulating glycated hemoglobin (HbA1c) levels in non-diabetic subjects: the Long Life Family Study (LLFS)
.
Metabolism
2014
;
63
:
461
468
47.
Havranek
EP
,
Mujahid
MS
,
Barr
DA
, et al.;
American Heart Association Council on Quality of Care and Outcomes Research, Council on Epidemiology and Prevention, Council on Cardiovascular and Stroke Nursing, Council on Lifestyle and Cardiometabolic Health, and Stroke Council
.
Social determinants of risk and outcomes for cardiovascular disease: a scientific statement from the American Heart Association
.
Circulation
2015
;
132
:
873
898
48.
Collins
FS
.
What we do and don’t know about ‘race’, ‘ethnicity’, genetics and health at the dawn of the genome era
.
Nat Genet
2004
;
36
(
Suppl.
):
S13
S15
49.
Heianza
Y
,
Hara
S
,
Arase
Y
, et al
.
HbA1c 5.7-6.4% and impaired fasting plasma glucose for diagnosis of prediabetes and risk of progression to diabetes in Japan (TOPICS 3): a longitudinal cohort study
.
Lancet
2011
;
378
:
147
155
50.
Droumaguet
C
,
Balkau
B
,
Simon
D
, et al.;
DESIR Study Group
.
Use of HbA1c in predicting progression to diabetes in French men and women: data from an Epidemiological Study on the Insulin Resistance Syndrome (DESIR)
.
Diabetes Care
2006
;
29
:
1619
1625
51.
Khaw
KT
,
Wareham
N
,
Bingham
S
,
Luben
R
,
Welch
A
,
Day
N
.
Association of hemoglobin A1c with cardiovascular disease and mortality in adults: the European prospective investigation into cancer in Norfolk
.
Ann Intern Med
2004
;
141
:
413
420
52.
Matsushita
K
,
Blecker
S
,
Pazin-Filho
A
, et al
.
The association of hemoglobin a1c with incident heart failure among people without diabetes: the atherosclerosis risk in communities study
.
Diabetes
2010
;
59
:
2020
2026
53.
Selvin
E
,
Ning
Y
,
Steffes
MW
, et al
.
Glycated hemoglobin and the risk of kidney disease and retinopathy in adults with and without diabetes
.
Diabetes
2011
;
60
:
298
305
54.
Di Angelantonio
E
,
Gao
P
,
Khan
H
, et al.;
Emerging Risk Factors Collaboration
.
Glycated hemoglobin measurement and prediction of cardiovascular disease
.
JAMA
2014
;
311
:
1225
1233
55.
Colagiuri
S
,
Lee
CM
,
Wong
TY
,
Balkau
B
,
Shaw
JE
,
Borch-Johnsen
K
;
DETECT-2 Collaboration Writing Group
.
Glycemic thresholds for diabetes-specific retinopathy: implications for diagnostic criteria for diabetes
.
Diabetes Care
2011
;
34
:
145
150
56.
Cheng
YJ
,
Gregg
EW
,
Geiss
LS
, et al
.
Association of A1C and fasting plasma glucose levels with diabetic retinopathy prevalence in the U.S. population: Implications for diabetes diagnostic thresholds
.
Diabetes Care
2009
;
32
:
2027
2032
57.
Wong
TY
,
Liew
G
,
Tapp
RJ
, et al
.
Relation between fasting glucose and retinopathy for diagnosis of diabetes: three population-based cross-sectional studies
.
Lancet
2008
;
371
:
736
743
58.
Jeganathan
VS
,
Cheung
N
,
Tay
WT
,
Wang
JJ
,
Mitchell
P
,
Wong
TY
.
Prevalence and risk factors of retinopathy in an Asian population without diabetes: the Singapore Malay Eye Study
.
Arch Ophthalmol
2010
;
128
:
40
45
59.
Tapp
RJ
,
Zimmet
PZ
,
Harper
CA
, et al.;
AusDiab Study Group
.
Diagnostic thresholds for diabetes: the association of retinopathy and albuminuria with glycaemia
.
Diabetes Res Clin Pract
2006
;
73
:
315
321
60.
McCance
DR
,
Hanson
RL
,
Charles
MA
, et al
.
Comparison of tests for glycated haemoglobin and fasting and two hour plasma glucose concentrations as diagnostic methods for diabetes
.
BMJ
1994
;
308
:
1323
1328
61.
Engelgau
MM
,
Thompson
TJ
,
Herman
WH
, et al
.
Comparison of fasting and 2-hour glucose and HbA1c levels for diagnosing diabetes. Diagnostic criteria and performance revisited
.
Diabetes Care
1997
;
20
:
785
791
62.
Park
YM
,
Ko
SH
,
Lee
JM
, et al.;
Committee of Clinical Practice Guideline, Korean Diabetes Association
.
Glycaemic and haemoglobin A1c thresholds for detecting diabetic retinopathy: the fifth Korea National Health and Nutrition Examination Survey (2011)
.
Diabetes Res Clin Pract
2014
;
104
:
435
442
63.
Xin
Z
,
Yuan
MX
,
Li
HX
, et al
.
Evaluation for fasting and 2-hour glucose and HbA1c for diagnosing diabetes based on prevalence of retinopathy in a Chinese population
.
PLoS One
2012
;
7
:
e40610
64.
Tsugawa
Y
,
Takahashi
O
,
Meigs
JB
, et al
.
New diabetes diagnostic threshold of hemoglobin A(1c) and the 3-year incidence of retinopathy
.
Diabetes
2012
;
61
:
3280
3284
65.
Fukushima
S
,
Nakagami
T
,
Suto
C
,
Hirose
A
,
Uchigata
Y
.
Prevalence of retinopathy and its risk factors in a Japanese population
.
J Diabetes Investig
2013
;
4
:
349
354
66.
Gerstein
HC
,
Miller
ME
,
Byington
RP
, et al.;
Action to Control Cardiovascular Risk in Diabetes Study Group
.
Effects of intensive glucose lowering in type 2 diabetes
.
N Engl J Med
2008
;
358
:
2545
2559
67.
Selvin
E
,
Coresh
J
,
Shahar
E
,
Zhang
L
,
Steffes
M
,
Sharrett
AR
.
Glycaemia (haemoglobin A1c) and incident ischaemic stroke: the Atherosclerosis Risk in Communities (ARIC) Study
.
Lancet Neurol
2005
;
4
:
821
826
68.
Saydah
S
,
Tao
M
,
Imperatore
G
,
Gregg
E
.
GHb level and subsequent mortality among adults in the U.S
.
Diabetes Care
2009
;
32
:
1440
1446
69.
Selvin
E
,
Wattanakit
K
,
Steffes
MW
,
Coresh
J
,
Sharrett
AR
.
HbA1c and peripheral arterial disease in diabetes: the Atherosclerosis Risk in Communities Study
.
Diabetes Care
2006
;
29
:
877
882
70.
Sabanayagam
C
,
Khoo
EY
,
Lye
WK
, et al
.
Diagnosis of diabetes mellitus using HbA1c in Asians: relationship between HbA1c and retinopathy in a multiethnic Asian population
.
J Clin Endocrinol Metab
2015
;
100
:
689
696
71.
Inzucchi
SE
,
Bergenstal
RM
,
Buse
JB
, et al.;
American Diabetes Association (ADA)
;
European Association for the Study of Diabetes (EASD)
.
Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)
.
Diabetes Care
2012
;
35
:
1364
1379
72.
National Guideline Clearinghouse
. VA/DoD clinical practice guideline for the management of diabetes mellitus [Internet], 2012. Rockville, MD, Agency for Healthcare Research and Quality (AHRQ). Available from http://www.healthquality.va.gov/guidelines/CD/diabetes/AboutDM.asp. Accessed 26 May 2016
73.
American Diabetes Association
.
Strategies for improving care. Sec. 1. In Standards of Medical Care in Diabetes—2016
.
Diabetes Care
2016
;
39
(
Suppl. 1
):
S6
S12