admin Continuous glucose monitors were developed to solve a serious clinical problem: helping people with diabetes understand how glucose changes throughout the day and make better-informed treatment decisions.
Now the same technology is moving into a much broader consumer market.
In March 2024, the U.S. Food and Drug Administration cleared Dexcom’s Stelo as the first over-the-counter continuous glucose monitor in the United States. Abbott subsequently received FDA clearance for its Lingo and Libre Rio systems. In June 2026, the FDA expanded OTC access further by clearing Stelo for people as young as two years old who do not use insulin.
That regulatory shift matters because continuous glucose monitoring is no longer only a diabetes-management technology. It is also becoming a consumer interface for understanding metabolism.
The promise is easy to understand: eat something, watch what happens, learn from the response.
The harder question is whether that information leads to a better health decision.
That distinction will determine much of the value created around the next generation of metabolic-health products.
What Is a Continuous Glucose Monitor?
A continuous glucose monitor, or CGM, uses a small sensor placed under the skin to estimate glucose levels in the fluid between cells. The sensor collects readings repeatedly throughout the day and sends the information to a smartphone, receiver, insulin pump, or other connected system.
Unlike a traditional finger-stick measurement, which provides a snapshot, CGM produces a continuous pattern. Users can see glucose rise and fall across meals, activity, sleep, medication and everyday routines.
This makes CGM fundamentally different from many other consumer health measurements.
A laboratory test can tell someone what their glucose looked like at one moment.
A CGM can show the shape of a response.
That may include:
- How high glucose rises after a meal
- How quickly it returns toward baseline
- Differences between similar meals
- Changes associated with physical activity
- Overnight patterns
- Repeated periods of higher or lower glucose
- Variability across different days
For people managing diabetes, this longitudinal information already has substantial clinical value. Current diabetes standards have continued expanding recommended access to CGM, reflecting a growing evidence base across diabetes populations.
The question becomes more complicated when the user does not have diabetes.
Why CGMs Became Attractive to Consumers Without Diabetes
The appeal fits neatly into a larger shift already visible across health wearables.
Consumers increasingly expect health information to be:
- Continuous
- Personalized
- Immediate
- Visual
- Actionable
Glucose is especially compelling because the feedback can appear closely connected to behavior.
Eat lunch.
Watch the curve.
Take a walk.
See another curve.
Change breakfast.
Compare the result.
That feedback loop makes metabolism feel observable in a way that traditional nutrition advice rarely does.
It also fits naturally with the growth of personalized nutrition, where the relevant question is increasingly not simply whether a food is considered healthy, but how an individual responds to it.
Research has repeatedly found meaningful differences in glucose responses between individuals. CGM makes those differences visible outside a laboratory.
But visibility should not be confused with interpretation.
What CGMs Can Reveal
Individual Glucose Responses
Two meals containing similar amounts of carbohydrate can produce different glucose patterns in the same person.
The same meal may also produce different responses in different people.
CGM can therefore reveal patterns that would be invisible from food composition alone.
For someone working with a clinician or qualified nutrition professional, these patterns may provide useful additional context when evaluating meal timing, carbohydrate intake, exercise or other behaviors.
Patterns Rather Than Isolated Measurements
One of CGM’s most useful qualities is repetition.
A single elevated reading may mean little without context.
A recurring pattern across many days can be more informative.
This is one reason continuous data has become important in diabetes care: it allows clinicians and patients to examine concepts such as time in range, glucose variability and recurring periods of hyperglycemia rather than depending solely on occasional measurements.
Immediate Behavioral Feedback
CGM may also function as a behavior-change tool.
A 2024 systematic review and meta-analysis examining randomized controlled trials in populations with and without diabetes found favorable, although generally modest, effects from CGM-based feedback on glycemic and behavioral outcomes.
The mechanism is intuitively appealing.
Instead of being told that activity after a meal might be useful, someone can observe how their own glucose pattern changes.
Instead of receiving generic dietary advice, they can compare repeated experiences.
The technology can make an abstract recommendation more immediate.
But this does not mean every observed difference is medically meaningful.
What CGMs Do Not Tell You
Whether a Food Is “Good” or “Bad”
A glucose curve is not a nutritional quality score.
A meal can produce a relatively modest glucose response while still being poor in fiber, micronutrients or overall nutritional quality.
Another food may cause a larger short-term rise in glucose while providing valuable nutrients and fitting comfortably within a healthy dietary pattern.
Glucose is one dimension of metabolism.
It does not measure the complete nutritional value of a meal.
That distinction is particularly important as consumer apps increasingly translate biological measurements into simplified scores.
Simple interfaces can make data easier to use.
They can also give individual metrics more authority than the science supports.
A Glucose Spike Is Not Automatically a Health Event
The phrase glucose spike has become common in consumer wellness content.
It often carries an implicit assumption that any visible rise after eating is harmful.
That conclusion goes beyond the current evidence.
Glucose normally rises after carbohydrate-containing meals. What matters clinically depends on factors including magnitude, duration, frequency, baseline metabolic health and the broader physiological context.
A 2025 scoping review comparing medical research with consumer-facing discussion of glucose spikes found an important gap between the two. The authors concluded that potential health effects in people without diabetes are more plausibly associated with repeated long-term patterns than with isolated acute glucose rises, while noting that evidence in healthy populations remains limited.
In other words, a visible curve should not automatically become a diagnosis—or a reason to fear a food.
CGM Is Not Currently a Standalone Diabetes Screening Test
This boundary matters.
The American Diabetes Association’s 2026 Standards of Care state that evidence is currently insufficient to support CGM as a screening or diagnostic method for prediabetes or diabetes.
CGM can reveal unusual patterns.
Those patterns may justify further discussion or clinical testing.
But a consumer should not infer a diagnosis simply because an app displays a glucose response they do not like.
This is a useful example of a broader principle explored in Evidence vs. Hype in Wellness:
measurement and medical meaning are not the same thing.
Sensor Data Is Still an Estimate
CGMs do not continuously sample blood directly.
They estimate glucose in interstitial fluid—the fluid between cells—which closely reflects blood glucose but is a distinct measurement environment. NIDDK also notes that users may sometimes need to compare CGM readings with a standard blood glucose meter when readings appear inconsistent or when clinical decisions require confirmation.
That does not make the technology unreliable.
It means the number on the screen should be understood as a measurement produced by a sensor system rather than as perfect access to the body’s underlying state.
A 2025 randomized crossover study in healthy adults also found that CGM measurements could differ from capillary measurements in ways that varied by meal and individual, reinforcing the need for caution when interpreting small differences as meaningful biological discoveries.
The Evidence Is Stronger for Diabetes Than for Metabolic Optimization
This may be the most important distinction in the category.
CGM has a well-established role in diabetes management. That evidence cannot simply be transferred to every consumer seeking better metabolic health.
A 2026 systematic review and meta-analysis examining CGM in populations without diabetes found evidence that CGM-based interventions may improve some glucose measures and support adherence to lifestyle interventions. However, the authors also identified substantial variation across studies and noted that evidence for broader outcomes remains limited.
That is encouraging.
It is not the same as demonstrating that every healthy person benefits from continuously monitoring glucose.
The evidence supports further exploration more strongly than it supports universal use.
The Commercial Opportunity Is Moving Beyond the Sensor
The first phase of CGM innovation solved measurement.
The emerging consumer problem is interpretation.
That creates a useful way to think about the category.
The CGM Decision Value Chain
| Layer | What it provides | Where value can break down |
|---|---|---|
| Sensor | Continuous glucose measurements | Accuracy, context and measurement limitations |
| Context | Meals, activity, sleep, medication and timing | Incomplete or inconsistent inputs |
| Interpretation | Patterns, comparisons and personalized insights | Oversimplified algorithms or unsupported conclusions |
| Decision | A useful behavioral or clinical action | Data that produces anxiety, confusion or unnecessary restriction |
The sensor creates data.
The commercial value increasingly depends on what happens after the data arrives.
This has implications for companies building:
- Metabolic-health platforms
- Personalized nutrition programs
- Digital coaching
- Food recommendation systems
- Preventive-health services
- Employer health programs
- Weight-management products
- Clinical decision-support tools
The differentiating question is unlikely to remain who can show consumers a glucose curve?
Multiple companies can do that.
A more defensible question is:
Who can help a specific user understand when that curve matters?
From Measurement to Decision Quality
This is the same transition occurring throughout consumer health.
Wearables have made heart rate, sleep, recovery, temperature and movement easier to measure.
Consumer diagnostics are making more biomarkers accessible.
Artificial intelligence is making interpretation cheaper and faster.
The bottleneck is gradually moving.
The problem is no longer simply obtaining data.
It is deciding what deserves attention.
A useful CGM experience should therefore help distinguish among at least three situations:
Interesting: the user notices an individual response worth understanding.
Actionable: repeated evidence supports a sensible behavioral adjustment.
Clinical: a pattern may warrant discussion with a qualified healthcare professional.
Collapsing those three categories into one “good” or “bad” score may make a product easier to understand, but it can reduce the quality of the decision that follows.
The Next Phase of Consumer Metabolic Health
OTC access has already lowered one barrier to CGM adoption in the United States. FDA clearances for Stelo, Lingo and Libre Rio moved the technology outside a prescription-only model for eligible users, and the 2026 pediatric Stelo clearance expanded that access further.
The next question is less regulatory than behavioral and commercial.
What should consumers do with all this information?
The companies that answer that question responsibly have a meaningful opportunity.
They will need to combine good sensors with evidence, context, understandable recommendations and appropriate boundaries between wellness information and medical care.
CGM makes metabolism more visible.
Visibility is useful.
But the value of the technology ultimately depends on whether seeing more helps people decide better.
Building a metabolic-health, nutrition or wearable product where the data is easier to explain than the customer value? We help teams test demand, positioning and the path to adoption before more money goes into launch or growth. Email Us.
Sources
All links below were checked during preparation of this article.
- U.S. Food and Drug Administration — First OTC Continuous Glucose Monitor
FDA Clears First Over-the-Counter Continuous Glucose Monitor - U.S. Food and Drug Administration — 2026 Pediatric OTC Clearance
FDA Clears First Over-the-Counter Continuous Glucose Monitor for Children - National Institute of Diabetes and Digestive and Kidney Diseases — CGM Overview
Continuous Glucose Monitoring - FDA — Abbott Lingo Clearance
Lingo Glucose System — 510(k) Premarket Notification - FDA — Abbott Libre Rio Clearance
Libre Rio Continuous Glucose Monitoring System — 510(k) Premarket Notification - Richardson et al., International Journal of Behavioral Nutrition and Physical Activity, 2024
The efficacy of using continuous glucose monitoring as a behaviour change tool in populations with and without diabetes - Liao et al., European Journal of Medical Research, 2026
Continuous glucose monitoring in non-diabetic populations: a systematic review of observational and interventional studies with meta-analysis - Avner et al., Clinical Medicine Insights: Endocrinology and Diabetes, 2025
A Scoping Review of Glucose Spikes in People Without Diabetes - American Diabetes Association — Standards of Care in Diabetes 2026
Diabetes Technology: Standards of Care in Diabetes—2026 - American Diabetes Association — Diagnosis and Classification, 2026
Diagnosis and Classification of Diabetes: Standards of Care in Diabetes—2026
Frequently Asked Questions
What does a continuous glucose monitor measure?
A CGM uses a sensor under the skin to estimate glucose levels in interstitial fluid and tracks how those levels change throughout the day.
Are continuous glucose monitors only for people with diabetes?
No. Some CGMs are now cleared for over-the-counter use by eligible people who do not use insulin, including people without diabetes who want to understand glucose responses to diet and activity. Their clinical value remains much better established for diabetes management.
Can a CGM tell you which foods are healthy?
No. A CGM shows one aspect of metabolic response. It cannot determine a food’s complete nutritional quality, which also depends on factors such as fiber, protein, micronutrients, overall dietary pattern and individual health needs.
Are glucose spikes unhealthy?
Glucose normally rises after eating carbohydrate-containing foods. Current evidence does not support treating every temporary glucose rise in a person without diabetes as harmful. Frequency, magnitude, duration and overall metabolic context matter.
Can a CGM diagnose prediabetes?
Current American Diabetes Association guidance says evidence is insufficient to use CGM alone for screening or diagnosing prediabetes or diabetes.
Can CGM help with personalized nutrition?
It can provide additional information about individual glucose responses to meals and activity. That information may be useful when interpreted alongside broader nutritional, behavioral and medical context.
Are CGM readings the same as blood glucose readings?
Not exactly. CGMs estimate glucose in interstitial fluid rather than continuously measuring glucose directly from blood.
Do healthy people benefit from CGMs?
Research in people without diabetes is growing. Some studies suggest CGM feedback may support behavior change and modest improvements in glucose-related outcomes, but evidence for broader long-term health benefits remains limited.
Why are CGMs becoming more popular?
Smaller sensors, smartphone integration and over-the-counter access have made continuous glucose data easier for consumers to obtain. Interest in personalized nutrition and metabolic health has expanded the audience beyond traditional diabetes care.
What is the biggest opportunity in consumer CGM products?
The larger opportunity may lie in interpretation rather than measurement alone: helping users understand which patterns matter and translating data into appropriate, evidence-based decisions.
