Many people wearing an over-the-counter sensor ask the same thing: is my glucose normal? The honest answer is that normal has a range, and there is no official target for a CGM in people without diabetes.
Quick answer: In a multicenter study of healthy people without diabetes who wore CGMs, average glucose was about 98 to 99 mg/dL, and glucose sat between 70 and 140 mg/dL about 96 percent of the time. Brief rises above 140 after meals were part of normal life, and averaged only about 30 minutes a day. These are research findings, not a clinical standard, and individuals varied widely.
What the main study found
The most-cited reference is a 2019 multicenter study by Shah and colleagues, published in Diabetes Technology and Therapeutics: “Continuous Glucose Monitoring Profiles in Healthy Non-Diabetic Participants.” The researchers fitted 153 healthy people without diabetes, aged 7 to 80, with a blinded Dexcom G6 sensor for up to 10 days, and analyzed the readings. You can see the record on the Henry Ford Health repository.
| Measure | What the study reported |
|---|---|
| Participants | 153 healthy, non-diabetic people, aged 7 to 80 |
| Wear time | Up to 10 days, blinded Dexcom G6 sensor |
| Mean glucose | 98 to 99 mg/dL (5.4 to 5.5 mmol/L) in all age groups except those over 60 |
| Mean glucose, over 60 | About 104 mg/dL (5.8 mmol/L) |
| Time in 70 to 140 mg/dL | Median 96 percent (interquartile range 93 to 98 percent) |
| Time above 140 mg/dL | Median 2.1 percent, about 30 minutes a day |
| Variability (coefficient of variation) | Mean within-person CV about 17 percent (plus or minus 3) |
Two points stand out. First, healthy glucose is not constantly flat; people spent a small fraction of the day above 140, which is a measurable but short stretch. Second, the group was small and fairly healthy, with a non-obese body mass index as an inclusion criterion, so the numbers describe that group and not everyone.
What these numbers mean for your sensor
If you wear a Stelo or Lingo, your own numbers will not match the study’s exactly, and that is expected. A few comparisons are reasonable:
- Your average. An average in the high 90s to low 100s mg/dL fits what the study saw in healthy adults. An average somewhat higher than the study’s does not diagnose anything, but it is a reason to ask for lab testing.
- Time above 140. If your sensor shows you above 140 mg/dL for a large part of the day, that differs from the study’s median of about 2 percent. Context matters: a large meal, illness, poor sleep, or a sensor problem can explain it.
- Brief post-meal peaks. A rise after eating that returns to baseline within a couple of hours is the normal pattern.
Our guide to reading CGM data explains why patterns over many days say more than any single spike.
A worked example: comparing a 10-day report
Suppose a person’s sensor reports a 10-day average of 104 mg/dL and 3 percent of readings above 140 mg/dL. 3 percent of 24 hours is 0.03 × 1,440 minutes = about 43 minutes a day, compared with about 30 minutes a day for the study’s median of 2.1 percent. The person’s number is slightly higher but in the same neighborhood. Their average, at 104, sits close to the over-60 mean in the study. Nothing here is diagnostic, and it would be reasonable to wait for a lab test only if there are symptoms or if repeated readings are persistently higher.
Compare that with another person whose average is 125 mg/dL and whose time above 140 is 30 percent, which is about 432 minutes a day. That pattern is far from what the healthy study group showed, and it is worth discussing with a clinician and confirming with lab tests, rather than concluding anything from a sensor alone.
A side-by-side: study group versus your sensor
This table puts the study’s findings next to the questions to ask yourself. It is a reading aid, not a pass-or-fail chart.
| Sensor measure | Healthy-study reference | If yours looks different |
|---|---|---|
| Average glucose | About 98 to 99 mg/dL; about 104 over age 60 | Note the number and ask whether lab testing makes sense |
| Time in 70 to 140 mg/dL | Median 96 percent | Check sensor placement and wear time, meals, sleep, and illness first |
| Time above 140 mg/dL | Median 2.1 percent (about 30 minutes a day) | Look at which meals drive it; repeat the experiment on another day |
| Variability (CV) | About 17 percent | Compare several days, not one |
| Fasting reading | Close to the average | Confirm repeated high fasting readings with a lab test |
How to wear a sensor so the data is fair
Sensor data is only as comparable as the conditions behind it. A few habits make a 10 to 14-day report easier to interpret:
- Give a new sensor time to settle. Early readings after insertion can be less steady, so avoid drawing conclusions from the first day.
- Keep the sensor in the same relative conditions. Avoid sleeping on it where you can, because pressure can create false overnight lows.
- Log what you eat and do. A simple note of meals, workouts, and poor sleep explains many surprises.
- Repeat experiments. A food that looks bad once might look ordinary the next time. Two or three comparable trials say more than one.
- Do not recalibrate on impulse. If your device offers calibration or a comparison to a fingerstick, follow its instructions rather than adjusting settings to make a number look right.
If you are still deciding whether to buy a sensor, our guide to whether you need a CGM with prediabetes and the comparison of Stelo and Lingo cover the practical questions.
Why the study’s age range matters
The participants ranged from 7 to 80 years, and the report noted a higher average glucose in those over 60. That fits a broader pattern that glucose regulation changes with age, but the abstract does not test why, and the group was small. If you are older, your own normal may sit a little higher than a younger person’s, which is another reason to interpret your numbers with a clinician who knows your health.
How this connects to A1C
People often try to translate a sensor average into an A1C. Take the study’s mean of about 98.5 mg/dL. The ADAG equation inverted, (98.5 + 46.7) ÷ 28.7, gives about 5.1 percent, while the GMI equation, 3.31 + 0.02392 × 98.5, gives about 5.7 percent. Those two answers differ by more than half a percentage point because they are different equations built from different data. That is a useful reminder that conversions are estimates, and that a lab A1C remains the standard test. Our A1C to average glucose chart shows the first conversion in full.
What is not established
There is no consensus that keeping glucose below a particular peak prevents disease in people without diabetes. Studies of healthy volunteers describe what is typical, not what is optimal. Sensor accuracy is lowest at the extremes, and overnight dips can be artifacts from lying on the sensor. Over-the-counter sensors are cleared for general wellness, not diagnosis. The Stelo and Lingo comparison explains how the two main options differ: Stelo vs Lingo.
Why individual variation is so large
Even among healthy people, the same meal can produce different responses. Contributors include how quickly the stomach empties, gut and food factors, body composition, sleep, stress, recent activity, and the previous meal. The same person can also respond differently on different days. This is why a fair comparison of foods requires repeating them under similar conditions, which the Post-Meal Glucose Experiment Tracker is designed for. A single dramatic spike after a particular food is an anecdote, not a rule.
When to see a clinician
- Fasting readings that are regularly high.
- Readings that stay elevated for hours after meals.
- Symptoms such as unusual thirst, frequent urination, or blurred vision.
- A family history of diabetes combined with elevated readings.
In those cases, ask for lab testing rather than rely on a sensor. The standard tests are explained in the comparison of A1C, fasting glucose, and OGTT and the complete guide to A1C and glucose, and the A1C to average glucose chart shows how an average glucose relates to A1C. For whether a sensor is worthwhile at all, see do I need a CGM with prediabetes.
Common mistakes
- Treating one post-meal spike as a sign of disease.
- Treating a study of healthy volunteers as a target to hit every day.
- Restricting foods heavily in response to normal post-meal rises.
- Ignoring symptoms because the sensor looks fine.
- Using a sensor to diagnose yourself.
Low blood sugar warning: if you take insulin, a sulfonylurea, or another glucose-lowering medicine, diet experiments can push glucose too low. Symptoms include shakiness, sweating, confusion, and a fast heartbeat. Talk to your prescriber first.
Questions to bring to your appointment
- Do my sensor patterns suggest I need lab testing?
- What fasting and post-meal range would you consider normal for me?
- Should I keep wearing a sensor, and for what purpose?
- Is my family history or weight relevant to how we interpret these numbers?
Frequently asked questions
What is a normal fasting glucose on a CGM?
The study of healthy people reported mean glucose of about 98 to 99 mg/dL across the day. Fasting values are typically in that region, with variation between people. Diagnostic fasting thresholds come from lab tests, not sensors.
Is a spike to 150 after a meal abnormal?
A brief rise above 140 was part of the normal pattern in the study, where people spent a median of about 2 percent of the day above 140. A single brief rise is not a diagnosis.
Why is the average a bit higher in people over 60?
The study reported a mean of about 104 mg/dL in those over 60, compared with 98 to 99 in other groups. The abstract does not explain why, and the group was small.
Does a CGM replace an A1C test?
No. A1C and fasting glucose are standard lab tests. A sensor adds detail about patterns, but over-the-counter sensors are not cleared for diagnosis.
Can I trust the readings at the low end?
Sensor accuracy is lowest at the extremes, and overnight lows can be false from lying on the sensor. Confirm unexpected lows with a fingerstick if you feel unwell.
Should I try to keep my glucose under 140 at all times?
There is no evidence-based rule that says so for people without diabetes. Chasing a flat line can cause unnecessary food restriction. Ask your clinician what is appropriate for you.
About the author: Charles Kirkland is the founder of Metabolic Clarity Labs and author of The Journey Back. He is not a physician. This is general education, not a medically reviewed treatment plan.
Sources checked October 31, 2026. Discuss personal decisions with a qualified clinician. Do not start, stop, or change prescribed treatment based on this article.
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