Use a continuous glucose monitor (CGM) to discover your personal glycemic responses

A two-week CGM trial reveals which specific foods and combinations spike your blood sugar — results that often defy standard glycemic index tables.

Why it works

Zeevi and Segal’s 2015 Cell paper showed that the same meal produces glucose responses that vary two- to fivefold between individuals, driven by microbiome composition, meal context, sleep, stress, and metabolic health. Personalized glycemic responses mean that population-based advice about which foods are "safe" or "high GI" is often wrong for specific individuals. A CGM makes this invisible variation visible, allowing evidence-based personal food choices rather than rule-following.

How to do it

1. Obtain a consumer CGM (e.g., Libre or similar) for a two-week observation period.
2. Eat your normal diet for the first week to establish your baseline response patterns.
3. In week two, test specific foods and meals you are uncertain about.
4. Record meal composition, timing, sleep quality, and stress level alongside glucose data for correlation.

Evidence

Zeevi et al. demonstrated high inter-individual variability in postprandial glycemic response and that microbiome-informed personalized diet recommendations outperformed standard glycemic index guidance. (rct)

CGMs are designed for clinical monitoring; consumer use is off-label. Sensor accuracy has variation. A two-week snapshot may not represent all conditions. This is an observational tool, not a treatment.

Sources

• Zeevi et al. (2015), Personalized Nutrition by Prediction of Glycemic Responses, Cell

Common mistake

Using CGM data to optimize glucose without also tracking sleep, stress, and exercise — glucose is an output of many inputs simultaneously, and isolating food effects requires consistent non-food variables.