A1C ↔ eAG
Converter

What A1C actually measures.

Hemoglobin A1C — also called HbA1c or glycated hemoglobin — is the percentage of hemoglobin in your red blood cells that has a glucose molecule permanently attached to it. Glucose binds to hemoglobin in a slow, non-enzymatic process called glycation; the higher your average blood glucose, the faster the reaction proceeds. Because red blood cells live approximately 120 days before being broken down and recycled, an A1C measurement effectively reflects your average blood glucose over the preceding two to three months — weighted toward the most recent four to six weeks.

A single blood draw, no fasting required, yields a number that no individual fingerstick or continuous sensor reading can provide: a long, slow average that is largely immune to the hour-to-hour swings that consume so much attention in daily diabetes management. That stability is both the strength and the limitation of the test.

The ADAG study — where this formula comes from.

In 2008, Nathan et al. published the A1C-Derived Average Glucose (ADAG) study in Diabetes Care, the flagship journal of the American Diabetes Association. The study enrolled 507 participants — spanning Type 1 diabetes, Type 2 diabetes, and non-diabetic controls — drawn from six ethnic groups across ten international centers, including cohorts from the United States, Europe, Africa, and South Asia. Each participant wore a continuous glucose monitor for approximately 12 weeks while also having eight-point daily fingerstick profiles and laboratory A1C measurements drawn simultaneously.

The regression analysis of those 507 datasets yielded the formula used by this calculator: eAG (mg/dL) = 28.7 × A1C − 46.7. The correlation was high (r = 0.92), and the formula was subsequently endorsed by the American Diabetes Association and the American Association for Clinical Chemistry. To convert to mmol/L, divide the mg/dL result by 18.0182. The reverse — working from eAG to an implied A1C — is simply A1C = (eAG mg/dL + 46.7) ÷ 28.7.

One important caveat from the authors themselves: the 95% confidence interval around any individual prediction spans roughly ±15 mg/dL. Two people with identical A1C values can have meaningfully different true average glucose levels depending on their red blood cell kinetics, hemoglobin variants, and glucose variability patterns.

eAG vs your fingerstick or CGM average — why they often differ by 20–30 mg/dL.

Most patients who check their CGM or glucometer average against the eAG on their lab report find a frustrating discrepancy. The gap is not an error — it reflects three genuine differences in what each number measures.

First, sampling windows differ. A1C is weighted toward the last 4–6 weeks because that is when the most recently formed red blood cells were glycated. A 14-day CGM average is an unweighted mean of 14 days. A 90-day CGM average is an unweighted mean of 90 days. None of these windows are identical.

Second, CGM measures interstitial fluid, not plasma glucose. The ADAG formula was derived from plasma glucose readings. Interstitial glucose lags blood glucose by 5–15 minutes and can differ by 10–15 mg/dL during rapid glucose excursions — which, if frequent, will shift the CGM mean relative to the equivalent plasma mean.

Third, time-of-day sampling bias. Fingerstick averages skew toward pre-meal and post-meal checks — the times people are most likely to test. CGM captures the overnight lows that self-testers often miss. Those overnight lows tend to pull the CGM average down relative to the A1C-weighted figure.

The ADA acknowledges this discordance explicitly in its Standards of Medical Care and advises clinicians not to expect numeric agreement between CGM-derived averages and laboratory A1C. If the two are consistently 40+ mg/dL apart, it is worth discussing with your endocrinologist — that magnitude of discordance can occasionally signal a condition affecting red blood cell lifespan.

ADA classification and glycemic targets.

The American Diabetes Association classifies glycemic status by A1C as follows: Normal is below 5.7% (eAG below 117 mg/dL); Prediabetes is 5.7–6.4% (eAG 117–137 mg/dL); Diabetes is 6.5% or above (eAG 140 mg/dL or above). Diagnosis requires two separate abnormal results on different days unless symptoms are present.

Source: ADA Standards of Medical Care in Diabetes 2024 — Section 6, Glycemic Targets.

When the A1C-eAG conversion is unreliable.

The ADAG formula is only as good as the A1C value it receives as input. Several conditions systematically distort A1C in ways that make the eAG output misleading:

• Sickle cell disease and sickle cell trait. Hemoglobin S has different glycation kinetics than hemoglobin A, and sickle red blood cells are destroyed faster than normal — typically 70–90 days instead of 120. The result is a falsely low A1C that understates average glucose. In these patients, fructosamine or a 2,3-DPG-corrected hemoglobin assay is preferred.
• Beta-thalassemia and other hemoglobinopathies. Structural variants that alter RBC lifespan or hemoglobin solubility change glycation rates. HbA2-dominant variants can also interfere with the HPLC assay used in most labs, producing artifactually high or low readings depending on the assay method.
• Iron-deficiency anemia. Iron-deficient erythrocytes live longer than normal, extending the glycation window and falsely elevating A1C. Treatment of the iron deficiency often reveals a lower "true" A1C within one to two months.
• B12 and folate deficiency. Similar mechanism: macrocytes live longer, accumulate more glycation, and push A1C upward. Replacement therapy normalizes the reading.
• Recent blood transfusion. Donor red blood cells of unknown age dilute the patient's glycated hemoglobin pool. Depending on the transfusion volume and timing, A1C can shift substantially in either direction. Most guidelines recommend waiting at least 60 days after a transfusion before interpreting A1C.
• Late pregnancy (third trimester). Increased red cell turnover and plasma volume expansion in the third trimester consistently lower A1C by 0.5–1.0 percentage points relative to the true glycemic state. The ADA recommends fructosamine or CGM-based monitoring as adjuncts in pregnancy.

In any of these scenarios, the eAG produced by this calculator should be treated as an approximation only, and clinical decisions should incorporate additional markers such as fructosamine, glucose tolerance testing, or continuous glucose monitoring data.

GMI — the CGM-derived alternative to eAG.

In 2018, Bergenstal et al. published the Glucose Management Indicator (GMI) in Diabetes Care. GMI addresses a specific frustration: patients and clinicians who tried to convert a CGM-derived mean glucose to an "equivalent A1C" using the ADAG formula consistently found the result misaligned with their laboratory A1C. The reason, as discussed above, is that CGM measures interstitial glucose, not plasma glucose, and the sampling window differs from the A1C-weighted lookback.

GMI uses a new regression built specifically on CGM data: GMI (%) = 3.31 + 0.02392 × mean glucose (mg/dL). Unlike the ADAG formula, GMI is not intended to predict a patient's next laboratory A1C — it is intended to give a CGM-native "glycemic summary" expressed on the familiar A1C percentage scale. In well-controlled patients, GMI tends to run about 0.3–0.5 percentage points higher than their measured A1C. In poorly controlled patients the difference narrows.

Both eAG and GMI are useful. eAG translates a laboratory A1C into a number that patients find more intuitive — "my blood sugar averaged 154 mg/dL over the past three months" is more actionable than "my A1C is 7.0%." GMI gives a daily glycemic summary from a CGM that clinicians can monitor without waiting 90 days for the next blood draw. They are complementary, not competing, metrics.

What to do if your eAG is high.

An eAG above 154 mg/dL (A1C ≥ 7.0%) in a patient with diagnosed diabetes indicates that glycemic targets are not being met, and the appropriate response depends on the clinical context. A few evidence-based starting points:

• Pattern identification before medication changes. A single A1C result does not tell you where in the day glucose is highest. Before adjusting medications, use a CGM or structured 8-point fingerstick profile to identify whether the excess comes from fasting, post-meal, or overnight glucose. The intervention differs for each pattern.
• Dietary composition matters more than calorie counting. Post-meal glucose spikes are driven primarily by carbohydrate quantity and glycemic index, not total calories. Apps like CalEye that provide glycemic load per meal give you a more actionable number than a calorie tally.
• Physical activity lowers A1C independently of weight loss. Both aerobic exercise (150 min/week moderate intensity) and resistance training reduce A1C by approximately 0.5–0.7 percentage points on average, with greater reductions in less-controlled patients.
• Medication review. If lifestyle adjustments have been optimized, a medication review with your endocrinologist is warranted. Current ADA guidelines prioritize agents with proven cardiovascular and renal benefits (GLP-1 receptor agonists, SGLT-2 inhibitors) in patients with established cardiovascular disease or high risk.
• Recheck in 3 months. Any medication or significant lifestyle change takes 8–12 weeks to show its full effect on A1C. Rechecking at 3 months gives enough time to see a signal without waiting so long that a poor response goes undetected.

A1C to eAG — full reference table.

Pre-computed values for common A1C milestones. All values calculated using the ADAG formula (Nathan et al. 2008).

Related reading.

• What your A1C actually means — a plain-language explainer
• A1C to eAG conversion examples — worked clinical cases
• CGM vs A1C for clinical decisions — when each metric wins
• CalEye for diabetes — AI carb counter, glycemic load tracking

Frequently asked questions.

What is the difference between A1C and a CGM average glucose?

A1C reflects glycation of hemoglobin over the 120-day lifespan of a red blood cell — a weighted average skewed toward the most recent weeks. A CGM average captures every interstitial glucose reading during the sensor wear period. Because CGM measures interstitial fluid (not blood), and the sampling windows differ, CGM averages and eAG derived from A1C routinely diverge by 20–30 mg/dL even in the same patient over the same period.

Which conditions distort the A1C reading?

Sickle cell disease and beta-thalassemia shorten RBC lifespan, falsely lowering A1C. Iron-deficiency anemia, B12/folate deficiency, and late pregnancy extend RBC lifespan, falsely raising it. Recent blood transfusions can shift A1C in either direction. In these cases, fructosamine or CGM-derived GMI are more reliable glycemic markers.

Why does my CGM average differ from the eAG the calculator shows?

The ADAG formula converts laboratory A1C — which reflects plasma glucose — to eAG. CGM measures interstitial fluid glucose, which lags plasma glucose by 5–15 minutes and can differ by 10–15 mg/dL during rapid excursions. Sampling window differences compound the gap. Expect 20–30 mg/dL discordance; above 40 mg/dL is worth discussing with your endocrinologist.

What is GMI and how does it differ from eAG?

GMI (Glucose Management Indicator) is a CGM-native metric from Bergenstal et al. (Diabetes Care 2018): GMI = 3.31 + 0.02392 × mean CGM glucose. It expresses a CGM period's average on the A1C scale, and tends to run 0.3–0.5 percentage points higher than a concurrent lab A1C. eAG converts a lab A1C to an average glucose; GMI converts a CGM mean to an A1C-equivalent. They answer different questions.

How often should A1C be rechecked?

ADA 2024 recommends twice yearly for stable patients at goal, four times yearly (every 3 months) after any treatment change or if targets are not met. Checking more frequently than every 3 months yields little new information because A1C changes slowly — it represents a 90-day biological average, not an instantaneous measure.