How should runners use CGM data?

Quick Answer

Best CGM Patterns for Runners is best understood as a timing problem: exercise can shift glucose immediately, hours later, or both.

What Exercise Studies Suggest

Evidence shows activity type and intensity shape CGM trajectories differently, and delayed effects are clinically meaningful. Immediate in-session readings alone can miss the most relevant risk period for some users.

Interpretation quality improves when users couple trend data with session metadata. This creates actionable patterns instead of anecdotal impressions.

Practical Decision Framework

Keep the framework simple: identify response class, test one adjustment, and re-check across multiple sessions. Complexity beyond that often reduces adherence and consistency.

If recurrent unexpected lows/highs persist, move from self-experimentation to clinician-guided adjustment. The goal is sustainable performance and safety, not perfect single-session curves.

Clinical Caveats

Exercise effects can be immediate or delayed; both windows matter. Risk management should include post-session monitoring, not only in-session trend checks.

Action Checklist

Use this short checklist as your implementation layer so evidence can be translated into consistent daily decisions.

Monitor pre-, during-, and delayed post-exercise windows.
Separate aerobic, interval, and resistance sessions in your analysis.
Recheck patterns across multiple sessions before changing dosing/fueling strategy.

References

Medical Disclaimer

This content is for informational purposes only and does not constitute medical advice. Always consult your healthcare provider before making decisions about your diabetes management or CGM device selection.