Levels Study Background

This article explains why traditional glucose tests can miss early metabolic changes, and why continuous glucose monitoring (CGM) is useful for studying glucose patterns in everyday life. References are listed in the Bibliography section.

Standard glucose testing

Metabolic health has historically been evaluated using fasting blood glucose (BG), the oral glucose tolerance test (OGTT), and glycated hemoglobin (HbA1c). These tests are useful for screening and diagnosis under standardized conditions, but they can miss early changes in real-world glucose patterns.

Fasting blood glucose (BG)

A single time point measurement used to classify normal, pre-diabetic, and diabetic status.
Because it is typically repeated annually (or less often) in people without diabetes, it leaves most day-to-day glycemia unmeasured.
Fasting BG may not rise until metabolic dysfunction is more established, which can narrow the window for earlier intervention.

Oral glucose tolerance test (OGTT)

Measures response to a standardized oral glucose load (up to ~100 g).
Captures glucose dynamics relevant to insulin resistance and beta-cell function, but has limitations:

It assumes adaptation to a high-carbohydrate diet.
Low-carbohydrate diets can reduce reliance on glucose and increase fat oxidation.
Even one low-carbohydrate day (or a lack of a single high-carbohydrate meal) before testing may negatively affect results.
Impaired tolerance under these conditions may reflect physiologic adaptation rather than poor metabolic health.

Like fasting BG, the OGTT provides a limited snapshot and does not capture typical daily behaviors and responses.

HbA1c

Reflects hemoglobin glycation associated with average glucose exposure over ~3 to 4 months (the lifespan of red blood cells).
A gold standard for diabetes risk and management, but may not align with fasting BG or OGTT in all individuals.
Can be confounded by iron and vitamin B-12 levels, as well as genetic variants.
Limitations have driven alternative tests (for example, fructosamine), reinforcing the need for more individualized tools.

Continuous glucose monitors

Continuous glucose monitors (CGMs) measure glucose at 5-minute resolution, 24 hours per day. They use an enzymatic reaction to estimate glucose in interstitial fluid, which tracks blood glucose with a short delay.

Compared to single time point or short-window testing, CGM data can capture:

Daily glucose dynamics.
Circadian rhythms.
Post-meal responses.

This higher-resolution view has contributed to a shift toward CGM-based metrics for assessing glycemic control in diabetes care.

Study justification

Improvements in CGM functionality, form factor, and cost have increased adoption among people with diabetes. This use is associated with benefits such as reduced diabetes-related distress, improved glycemia, and reduced management burden.

Potential benefits extend beyond diabetes care. CGM paired with insight-driven software can provide feedback on how everyday choices, such as food, activity, sleep, and stress, relate to glucose patterns.

Researchers have begun characterizing continuous glucose dynamics in healthy participants. However:

Few studies (fewer than 20) have evaluated CGM in heterogeneous populations.
None have observed very large populations (n > 10,000) of people without diabetes to generate reference values, patterns, and usage analyses.
Prior work often used small cohorts or early-generation devices with lower accuracy.
Many studies rely on controlled tests and interventions that influence glycemia.

Why studying real-world CGM use matters

Free-living CGM use, outside controlled settings, is a rapidly emerging use case that has not been studied at scale. Studying these patterns may:

Reveal population-wide patterns of glucose dynamics.
Help evaluate whether CGM plus software supports metabolic education and behavior change.
Enable evaluation of associations between CGM use patterns and health outcomes.

CGM-based feedback may support healthier choices by linking lifestyle behaviors with glycemic responses. While long-term outcomes have not been demonstrated at scale, short-term studies suggest:

Agreement with traditional screening for metabolic risk.
Detection of pre-diabetic and diabetic glucose levels in people without diabetes.
Meal composition effects on post-meal glucose.
High user acceptability.
Minimal adverse effects.

Over longer periods, real-time feedback from a guided CGM experience could inform and motivate changes in nutrition, sleep, and exercise. Studies have reported improvements in post-meal glucose and variability with adjustments in macronutrient composition and food order. CGM has also been used to explore exercise timing effects on postprandial responses.

As CGM use expands, large anonymized datasets could improve understanding of full-spectrum glycemia, clarify reference ranges for “healthy” glucose regulation, and support research on the onset and progression of metabolic dysfunction.

What the proposed study enables

The proposed study (and follow-on research) will be novel in scale and can enable:

Reference glucose ranges in general-population adults using unblinded CGM and associated software in free-living conditions.
A foundational dataset for generating hypotheses about CGM use beyond diabetes management.
A large resource for assessing adverse metabolic events in the general population.
Safety and effectiveness evidence for CGM use in the general population.
Analyses of how demographic, anthropometric, and lifestyle factors relate to glucose patterns using Levels’ remote monitoring software.