Wellness

A1C to blood glucose conversion: chart, formula, and examples

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Sheenam Midha · Health writer

Published Aug 3, 2026 7 min read
An A1C laboratory result converting into estimated average glucose values beside a glucose meter

A1C to blood glucose conversion turns a laboratory percentage into estimated average glucose, or eAG, in the same units used by many glucose meters. It is a translation, not a reconstruction of every reading from the previous three months.

Use the A1C calculator for an instant result. The formula is based on the international ADAG study relationship summarized by the NGSP.

Why convert A1C to estimated average glucose?

A result such as 7.0% can feel abstract. An eAG near 154 mg/dL uses the same scale as a meter, making the long-term result easier to discuss. The conversion also helps explain why a normal-looking fasting value does not always mean the full-day average is in range.

Do not compare eAG with one reading. Compare it with a pattern of readings or a sufficiently complete CGM period.

How the A1C to blood glucose conversion works

For milligrams per deciliter:

eAG (mg/dL) = 28.7 × A1C − 46.7

Blood sample and red blood cells flowing through a visual bridge to a blank glucose meter
The A1C-to-eAG equation translates a laboratory percentage into the units used by glucose meters.

For millimoles per liter:

eAG (mmol/L) = eAG (mg/dL) ÷ 18

Example for A1C 7.0%:

  • 28.7 × 7.0 = 200.9
  • 200.9 − 46.7 = 154.2 mg/dL
  • 154.2 ÷ 18 = 8.6 mmol/L

A1C to blood glucose conversion chart

A1CEstimated average glucoseEstimated average glucose
5.0%97 mg/dL5.4 mmol/L
5.5%111 mg/dL6.2 mmol/L
6.0%126 mg/dL7.0 mmol/L
6.5%140 mg/dL7.8 mmol/L
7.0%154 mg/dL8.6 mmol/L
8.0%183 mg/dL10.2 mmol/L
9.0%212 mg/dL11.8 mmol/L
10.0%240 mg/dL13.3 mmol/L
11.0%269 mg/dL14.9 mmol/L
12.0%298 mg/dL16.6 mmol/L

Values are rounded. They describe the average relationship in the study population, not an exact personal equivalence.

Why eAG may not match your meter or CGM

Red blood cell stream branching toward a calendar, glucose meter, kidney, and blood-loss symbols
Red blood cell turnover and testing patterns can make measured glucose differ from the converted estimate.

Meters are often used at selected times, such as before breakfast. A1C includes exposure after meals and overnight. CGM captures far more data, but sensor gaps, compression lows, and the period selected can still change its mean.

A1C also depends on red blood cells. Anemia, kidney disease, recent bleeding, transfusion, pregnancy, and some hemoglobin variants can change the result independently of glucose. The NIDDK describes these limitations in detail.

How to use the conversion responsibly

Use eAG to translate a confirmed laboratory result, compare broad trends, and prepare questions for your next visit. Do not use it to calculate an insulin dose or decide that a single high or low reading is harmless.

For diagnostic cutoffs and common monitoring targets, see our blood-sugar chart by age. If the A1C is above your agreed goal, start with safe, evidence-based ways to lower A1C rather than a quick-fix promise.

The bottom line

The conversion makes A1C easier to understand, but the result remains an estimate. Your laboratory A1C, meter or CGM pattern, symptoms, medicines, and medical history belong in the same conversation.

Evidence and review

How this article was checked

Formula and interpretation checked against NGSP, CDC, and NIDDK materials. This article has not been independently medically reviewed. Evidence last reviewed Aug 3, 2026.

FAQ

Frequently asked

Answers

Frequently asked questions

  1. What is the formula for converting A1C to average glucose?

    Estimated average glucose in mg/dL is 28.7 multiplied by A1C, minus 46.7. Divide mg/dL by 18 to estimate mmol/L.

  2. Does eAG equal my fasting glucose?

    No. eAG estimates an average across day and night, including after-meal periods. A fasting test is one measurement under specific conditions.

  3. Why is my CGM average different from A1C-derived eAG?

    The formula describes an average relationship across study participants. Red-cell lifespan, missing CGM data, sensor differences, recent changes, and medical conditions can create a personal mismatch.

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