Alcohol, Carbs and Your CGM: What the Flat Line Is Really Telling You — The Fasting Method Podcast

A flat CGM line isn't always good news.

Episode #267
🎙️ In this Metabolic Troubleshooting episode, Coach Lisa Chance explains what really happens when alcohol and carbohydrates collide—and why your CGM may not be telling the whole story.

Using practical examples like pizza and wine, Lisa explores how alcohol changes the way your liver regulates blood sugar, why glucose readings can appear deceptively stable, and what that means for anyone using a Continuous Glucose Monitor (CGM) to better understand their metabolic health.

Whether you're experimenting with different foods, wearing a CGM for the first time, or simply curious about how alcohol affects your metabolism, this episode will help you interpret your glucose data with greater confidence.

👉 What you'll learn:

Why alcohol can make your CGM readings misleading
What a "flat" glucose line really means after drinking
How alcohol affects blood sugar, insulin, and liver function
Why food experiments should be done on alcohol-free nights
How carbs and alcohol interact metabolically
Which types of alcohol are the least disruptive to glucose regulation
Why beer, wine, and spirits affect your metabolism differently
How to use your CGM as a feedback tool—not a moral scorecard

📝 Transcript

The transcript for this episode is available on our website:
👉 https://www.thefastingmethod.com/podcasts/

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⏱️ Timestamps

00:00 — Pizza, wine, and the misleading flat CGM line
00:24 — Why alcohol changes how to interpret CGM data
02:40 — Blood glucose basics and understanding your CGM
05:57 — How alcohol affects liver glucose production
09:23 — Why alcohol can disrupt blood sugar for up to 24 hours
12:27 — Alcohol, insulin, and hidden metabolic effects
14:37 — Why carbs and alcohol create misleading CGM data
18:01 — Beer, wine, and spirits: what's the metabolic difference?
21:24 — Choosing lower-impact alcoholic drinks
24:00 — What metabolic healing looks like on a CGM
27:00 — Key takeaways for interpreting your glucose data

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