Introduction: The Critical Role of A1C Testing in Diabetes Management

Hemoglobin A1c testing has become the cornerstone of diabetes diagnosis and long-term glycemic monitoring. By measuring the percentage of hemoglobin that has undergone non-enzymatic glycation over the preceding 8–12 weeks, the test provides a convenient, non-fasting snapshot of average blood glucose levels. The American Diabetes Association (ADA) recommends using A1c of 6.5% or higher to diagnose diabetes, and many treatment guidelines target an A1c below 7.0% for most non-pregnant adults with diabetes. However, a growing body of research has identified a troubling source of potential error: the influence of skin pigmentation on A1c measurement accuracy. This discovery carries far-reaching implications for health equity, as misclassification of diabetes status can lead to delayed treatment, inappropriate medication adjustments, and worsening outcomes—particularly in populations with darker skin. With diabetes disproportionately affecting people of African, Hispanic, South Asian, and Indigenous descent, any systematic inaccuracy in A1c testing threatens to deepen existing disparities. Understanding the mechanisms behind these discrepancies and exploring corrective measures is essential for ensuring that A1c testing remains a reliable tool for everyone.

How A1C Testing Works

The Biochemistry of Glycation

The A1c test quantifies the percentage of hemoglobin that has glucose attached to its N-terminal valine of the beta chain. This non-enzymatic glycation occurs continuously over the 120-day lifespan of a red blood cell. Because glucose levels fluctuate throughout the day, the A1c reflects the integrated average of blood sugar exposure over that period. The test is reported as a percentage (e.g., 7.0%) or in mmol/mol. In the United States, the ADA uses an A1c of 6.5% (48 mmol/mol) to diagnose diabetes, and targets of less than 7.0% are common for many non-pregnant adults. However, the assumption that glycation proceeds at a constant rate across all individuals is increasingly questioned. Genetic variations, such as single-nucleotide polymorphisms in the HK1 gene, have been linked to differences in glycation rates, independent of glucose concentration. These variations are more prevalent in certain ancestral groups, suggesting that biological differences beyond glucose exposure can influence A1c results.

Common Assay Methods and Their Vulnerabilities

Several laboratory methods exist for measuring A1c, including high-performance liquid chromatography (HPLC), immunoassays, capillary electrophoresis, and enzymatic assays. HPLC, often considered the gold standard, separates hemoglobins based on charge differences. Immunoassays use antibodies that recognize the glycated N-terminal sequence. Enzymatic assays measure the amount of glucose released from glycated hemoglobin. While modern systems are highly precise, they can be affected by hemoglobin variants (e.g., HbS, HbC, HbE) that are more prevalent in people of African, Mediterranean, or Southeast Asian descent. The National Glycohemoglobin Standardization Program (NGSP) certifies methods that meet stringent precision and bias criteria, but NGSP certification does not specifically test for interference from skin pigmentation factors. Some point-of-care devices that rely on spectrophotometric detection may be particularly susceptible to light absorption or scattering by melanin particles present in the blood sample, leading to biased readings.

The Emerging Evidence: Skin Pigmentation and A1C Inaccuracy

Landmark Studies

The first major study to bring widespread attention to this issue was published in 2017 by researchers from the A1C-Derived Average Glucose (ADAG) Study Group. They re-analyzed data and found that individuals with darker skin pigmentation exhibited systematically higher A1c values compared to those with lighter skin at the same measured average glucose levels. Subsequent studies, including a 2020 investigation in the Journal of Clinical Endocrinology & Metabolism, confirmed these findings using objective skin pigmentation measurements via a spectrophotometer. They reported that for every unit increase in melanin index, A1c was higher by approximately 0.1–0.2%, even after controlling for age, sex, BMI, and actual glucose levels measured by continuous glucose monitoring (CGM). A 2022 meta-analysis by the Diabetes Technology Society pooled data from over 10,000 participants and concluded that the bias in A1c due to skin pigmentation is statistically significant and clinically relevant, particularly at the diagnostic threshold of 6.5%.

Mechanisms Behind the Discrepancy

Researchers have proposed several biological and technological mechanisms to explain why skin pigmentation might influence A1c test results.

  • Melanin interference with assay chemistry: Melanin, the primary pigment in human skin, is also present in red blood cell membranes and is detectable in circulating blood. Laboratory assays that rely on spectrophotometric detection—especially those using wavelengths where melanin absorbs light—may be affected. Even trace amounts of melanin in a blood sample can cause a shift in the measured absorbance, leading to a falsely elevated A1c percentage. Some studies have shown that sonication or filtration of blood samples can reduce melanin content and change A1c readings.
  • Variations in hemoglobin glycation rates: Genetic factors associated with ancestry, such as single-nucleotide polymorphisms in the HK1 gene (which encodes hexokinase 1), have been linked to differences in intracellular glucose metabolism and the rate of hemoglobin glycation. These genetic variations are more prevalent in African and Asian populations and can lead to higher A1c levels independent of actual glucose exposure. The exact mechanism remains under investigation, but it appears that the rate of glucose attachment to hemoglobin is not uniform across all individuals.
  • Red blood cell lifespan differences: The A1c calculation assumes a uniform red blood cell lifespan of 120 days. However, conditions like iron deficiency, hemoglobinopathies, and even racial differences in red cell turnover may alter this average. Some evidence suggests that individuals of African descent may have slightly shorter red cell lifespans on average, which would lower A1c. Yet paradoxically, higher A1c is observed, pointing to other, more dominant mechanisms such as melanin interference or genetic glycation variation.
  • Calibration bias in point-of-care devices: Many handheld A1c devices used in clinics rely on immunoassay or boronate affinity methods. If these devices are calibrated primarily using data from lighter-skinned populations, they may produce biased results for darker-skinned individuals. A 2021 evaluation of six common point-of-care devices found that two showed statistically significant differences in A1c readings between light and dark skin tones, even when identical blood samples were tested. The devices with the largest bias used optical detection methods in the visible spectrum.

The Role of Hemoglobin Variants and Thalassemias

While not directly related to skin pigmentation, hemoglobin variants (HbS, HbC, HbE, HbD) and thalassemias are more common in populations with darker skin and can interfere with certain A1c assay methods. HPLC methods often resolve these variants, but immunoassays and some point-of-care devices may produce erroneous results. The combination of hemoglobin variant interference and skin-pigmentation-related bias can compound inaccuracies in these populations. Clinicians should be aware of both factors when interpreting A1c results.

Clinical and Public Health Implications

Risk of Misdiagnosis and Mismanagement

If a person with darker skin has a falsely elevated A1c, they may be incorrectly diagnosed with diabetes or prediabetes. For example, a patient whose true average glucose corresponds to an A1c of 5.9% might have a measured A1c of 6.6%, crossing the diagnostic threshold. Conversely, a falsely low A1c could delay diagnosis, allowing hyperglycemia to cause damage to eyes, kidneys, and nerves. For those already diagnosed with diabetes, an inaccurate A1c may lead to overly aggressive treatment (risking hypoglycemia) or inadequate treatment (allowing complications to progress). Given that African American, Hispanic, and South Asian populations already face higher diabetes prevalence and poorer outcomes, any systematic inaccuracy in A1c measurement worsens existing health disparities. A study published in Diabetes Care (2021) estimated that up to 5% of diabetes diagnoses in Black Americans could be due to A1c misclassification.

Impact on Pregnancy and Gestational Diabetes

Gestational diabetes mellitus (GDM) screening often uses a glucose challenge test followed by an oral glucose tolerance test. However, A1c is increasingly used as an initial screening tool in some settings. If A1c is biased by skin pigmentation, pregnant individuals with darker skin may be overdiagnosed or underdiagnosed for GDM, leading to unnecessary interventions or missed treatment. Given the importance of glycemic control during pregnancy for both maternal and fetal outcomes, this is an area that requires further research and caution.

Impact on Research and Quality Measures

Large epidemiological studies often rely on A1c as a primary outcome measure. If skin pigmentation affects A1c, comparisons across racial groups could be confounded. For example, a study claiming that Black patients have poorer glycemic control based on higher A1c values might be partially explained by measurement bias rather than true differences in glucose management. This could lead to flawed clinical guidelines and perpetuate stereotypes about patient adherence. Quality measures that tie reimbursement to A1c targets—such as the Healthcare Effectiveness Data and Information Set (HEDIS) metrics—could unfairly penalize providers caring for diverse populations. The National Committee for Quality Assurance (NCQA) has acknowledged this concern and is exploring adjustments.

Alternative and Adjunctive Testing Strategies

Given these concerns, clinicians should consider other methods to assess glycemic status, especially when A1c results seem inconsistent with self-monitored blood glucose or clinical presentation. The following strategies offer alternatives or complements to A1c.

  • Continuous Glucose Monitoring (CGM): CGM devices measure interstitial glucose levels every 5–15 minutes, providing a wealth of data on glucose variability, time in range, and average glucose over days to weeks. The glucose management indicator (GMI) derived from CGM correlates well with A1c but is unaffected by hemoglobin properties or skin pigmentation. For patients with access to CGM, it can serve as a powerful adjunct or even replacement for A1c. However, cost and insurance coverage remain barriers for many.
  • Fructosamine and Glycated Albumin: These tests measure glycated proteins in serum (albumin and other proteins) with a shorter half-life (2–3 weeks). They are not affected by red blood cell lifespan or hemoglobin variants. However, they reflect a shorter time window and can be influenced by changes in protein turnover (e.g., nephrotic syndrome, thyroid disease, liver disease). Still, they provide a useful cross-check when A1c is suspect. Normal fructosamine ranges are approximately 200–285 μmol/L, corresponding to an A1c of about 6–7%.
  • 1,5-Anhydroglucitol (GlycoMark): This test reflects glycemic excursions over the past 1–2 weeks. It is particularly sensitive to postprandial hyperglycemia. Levels decrease when glucose exceeds the renal threshold (approximately 180 mg/dL). It is less commonly used but can help identify glucose variability that A1c may mask.
  • Oral Glucose Tolerance Test (OGTT): For diagnosis, the OGTT remains a valid alternative and is not affected by hemoglobin glycation or red cell lifespan. However, it is more burdensome and less reproducible than A1c. The ADA recommends using OGTT for diagnosis when A1c is unreliable.

Current Guidelines and Recommendations

The American Diabetes Association (ADA) has acknowledged the potential influence of race and skin pigmentation on A1c. In its Standards of Medical Care in Diabetes—2024, the ADA states: “In individuals of African, Mediterranean, or Southeast Asian descent, the A1c may be less reliable due to the higher prevalence of hemoglobin variants. In these cases, rely on glucose criteria for diagnosis.” However, the ADA does not yet specifically recommend adjusting for skin pigmentation or using alternative tests for all patients with darker skin. The Endocrine Society and the American Association of Clinical Endocrinology (AACE) have issued similar cautious statements. Some experts are calling for a paradigm shift: that skin pigmentation be considered a biological variable in diabetes testing, much like age or kidney function. The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) has initiated a working group to investigate the impact of skin pigmentation on laboratory tests.

“We need to move beyond a one-size-fits-all approach to A1c. If a test is biased against a particular group, it is not just a laboratory issue—it is a justice issue. Clinicians must be educated about these disparities and empowered to use alternative measures when indicated.” — Dr. Anne Peters, Professor of Medicine, University of Southern California

Practical Recommendations for Clinicians

Assess Patient Ancestry and Skin Pigmentation

While objective skin pigmentation measurement via spectrophotometer is not yet routine in clinics, clinicians can use self-reported race/ethnicity as a starting point. However, it is important to note that skin pigmentation varies widely within racial groups, and self-reported race is an imperfect proxy. Patients of African, Hispanic, South Asian, Indigenous, and Middle Eastern descent should be considered at higher risk for A1c inaccuracy.

Compare A1c with Self-Monitored Blood Glucose (SMBG)

If a patient’s A1c seems discordant with their average daily glucose readings from a home glucose meter (e.g., an A1c of 8.5% when average glucose is consistently 140 mg/dL), suspect measurement bias. Calculate the estimated average glucose (eAG) using the formula 28.7 × A1c – 46.7. If the discrepancy is greater than 10–15%, alternative testing should be considered.

Use CGM or Fructosamine as Confirmatory Tests

When A1c results are questionable, a 10–14 day period of CGM can provide a reliable assessment of glycemic control. Alternatively, a fructosamine test can be ordered and correlated with A1c. A normal fructosamine with an elevated A1c suggests possible interference.

Future Directions: Research, Technology, and Policy

Advancing Inclusive Assay Design

Device manufacturers should validate their A1c assays across a diverse range of skin pigmentation levels and ethnic backgrounds. This could involve recruiting participants with varied melanin indices during clinical trials and testing for interference from melanin and other pigments. The NGSP should consider adding skin pigmentation as a variable in its certification protocols. Some companies are already developing “race-neutral” enzymatic assays that use different detection wavelengths or incorporate sample preprocessing steps to remove melanin. A 2023 study demonstrated that a novel enzymatic assay that measures glycated hemoglobin via glucose dehydrogenase showed no bias across skin pigmentation groups.

Large-Scale Genetic and Epidemiologic Studies

To disentangle the contributions of skin pigmentation, ancestry, and environment, researchers need larger datasets that include quantitative skin pigmentation measurements (not just self-reported race), CGM data, and genomic information. The All of Us Research Program and the UK Biobank offer promising resources, though skin pigmentation data are not yet uniformly collected. Studies that identify the specific genetic markers for glycation rate variation could eventually lead to personalized A1c correction factors. For instance, a polygenic risk score for glycation may allow clinicians to adjust A1c values based on an individual’s genetic profile.

Policy and Clinical Education

Organizations like the CDC, NIH, and WHO should fund educational campaigns to raise awareness among primary care providers, endocrinologists, and diabetes educators. Clinical decision support tools in electronic health records could flag A1c results from patients with darker skin and suggest confirmatory testing. Healthcare systems should ensure equitable access to CGM and other alternative tests, which are often costly and less available to underserved populations. Reimbursement policies should be updated to cover CGM for diagnostic purposes in cases where A1c is unreliable.

Conclusion: A Call for Equity in Diabetes Care

The evidence that skin pigmentation can influence A1c measurement accuracy is compelling and demands action. While A1c remains a valuable tool for diabetes management, it is not infallible. Clinicians must be vigilant when results seem discordant with glucose data, particularly in patients with darker skin. By incorporating alternative testing methods like CGM and fructosamine, advocating for more inclusive assay validation, and supporting research into personalized approaches, we can reduce disparities and ensure that every individual receives an accurate assessment of their diabetes risk and control. The goal is not to abandon A1c, but to make it—and its alternatives—truly equitable for all. The pursuit of health equity requires that diagnostic tools work equally well for every patient, regardless of skin color.

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