Blood Sugar Average and Variability Calculator

Calculate mean glucose, standard deviation, and coefficient of variation from a set of readings, plus estimated A1C — measures that together describe control far better than an average alone.

📊 Lab Value📐 CV = (SD / mean) × 100; eA1C = (mean + 46.7) / 28.7🏥 Health
Units
Glucose readings (comma separated)
Please enter valid values.

Formula & Reference

VariableSymbolFormulaUnits
Blood Sugar Average and Variability Calculator—CV = (SD / mean) × 100; eA1C = (mean + 46.7) / 28.7mg/dL and %

Step-by-Step Examples

Example 1
Stable Control

Readings: 110, 118, 105, 124, 112, 120 mg/dL.

  • Mean = 114.8 mg/dL
  • SD ≈ 7.0 mg/dL
  • CV = 7.0 / 114.8 = 6.1% — very stable
  • Estimated A1C = (114.8 + 46.7) / 28.7 = 5.6%
✓ Mean 115, CV 6.1% — stable
Example 2
Same Average, High Variability

Readings: 62, 185, 78, 168, 95, 179 mg/dL.

  • Mean = 127.8 mg/dL — similar in magnitude
  • SD ≈ 53.4 mg/dL
  • CV = 41.8% — well above the 36% threshold
  • The average conceals both hypoglycaemia and marked excursions
✓ Mean 128, CV 41.8% — high variability
Example 3
Elevated but Stable

Readings: 172, 181, 165, 190, 176, 184 mg/dL.

  • Mean = 178 mg/dL
  • SD ≈ 8.6 mg/dL, CV = 4.8%
  • Estimated A1C = 7.8%
  • Consistently high but with little variability
✓ Mean 178, estimated A1C 7.8%

Real-World Applications

📊
Beyond the Average
Two people with identical mean glucose can have very different risk profiles depending on variability.
📉
Hypoglycaemia Risk
High glucose variability is independently associated with increased hypoglycaemia risk, which the average alone conceals.
📈
Time in Range
Continuous glucose monitoring shifted the focus toward time in range as a complement to A1C.
🗣️
Clinical Discussion
Bringing variability and time-in-range data to an appointment gives a far richer picture than a single A1C.

Common Mistakes to Avoid

⚠️
Judging control by the average alone

A mean of 130 mg/dL can reflect stable readings or a pattern swinging between 60 and 200. The clinical implications differ substantially.

⚠️
Comparing fingerstick and CGM statistics directly

Fingerstick readings are taken at chosen moments and typically undersample overnight and post-meal periods, so their statistics are not equivalent to CGM-derived values.

⚠️
Using too few readings

Standard deviation and coefficient of variation become unstable with small samples. A meaningful picture generally needs at least a couple of weeks of data.

Frequently Asked Questions

What is glucose coefficient of variation? ▾
Standard deviation divided by mean glucose, expressed as a percentage. A CV under 36% is commonly cited as the threshold for stable glucose.
Why does glucose variability matter? ▾
High variability is associated with increased hypoglycaemia risk and, in some research, with complications independently of average glucose.
What is time in range? ▾
The percentage of readings falling between 70 and 180 mg/dL. Consensus guidance commonly suggests aiming for above 70% for many adults with diabetes.
Can I estimate A1C from my meter average? ▾
Approximately, using the ADAG regression — but meter averages typically undersample overnight and post-meal glucose, so the estimate often differs from the laboratory value.
How many readings do I need for meaningful statistics? ▾
More is better. Standard deviation and CV are unreliable with only a handful of readings, and at least two weeks of consistent data is a common minimum.

Related Health Calculators

🍬 A1C to Glucose🍬 A1C Target💊 Insulin Sensitivity Factor💊 Insulin:Carb Ratio🍬 Glycemic Load