I Wore a CGM for 30 Days: What My Average Glucose Really Means for A1c

I'm not diabetic. My last A1c was 5.3%—solidly normal. But I wanted to know what's really happening with my blood sugar throughout the day. So I wore a continuous glucose monitor for 30 days straight, tracked every meal, and analyzed the data obsessively.

What I learned completely changed how I think about food, exercise, and metabolic health. Here's what a month of real-time glucose data taught me—and what your average glucose actually means for your A1c.

The Setup: My Baseline Numbers

Before I started, I got a lab A1c test: 5.3%, which converts to an average glucose of about 105 mg/dL. That's the number I'd be comparing my CGM data against.

I used an over-the-counter CGM (no prescription needed anymore—welcome to 2026). The sensor sits on your arm, reads glucose every few minutes, and syncs to an app. I ate normally, exercised my usual amount, and watched what happened.

Week 1: The Shocking Reality

Average glucose: 112 mg/dL
Estimated A1c (GMI): 5.4%
Time in Range (70-180 mg/dL): 91%

The first week was eye-opening. My fasting glucose was consistently 85-95 mg/dL—exactly what I expected. But here's what shocked me:

Oatmeal spiked me to 165 mg/dL. I'd been eating steel-cut oats for breakfast for years, thinking it was the healthiest option. Nope. My glucose shot up within 30 minutes and stayed elevated for 2+ hours.
White rice hit 175 mg/dL. Dinner with white rice sent my glucose soaring, even though I felt fine and had no symptoms.
Late-night snacking kept me elevated. Eating after 8 PM meant my glucose stayed above 120 mg/dL until midnight, even for "healthy" snacks like fruit.

The kicker? If I hadn't been wearing the CGM, I'd have no idea any of this was happening. I felt completely normal while my glucose was hitting 165+.

Week 2: Experimenting with Meal Composition

Average glucose: 107 mg/dL
Estimated A1c (GMI): 5.3%
Time in Range: 94%

Week two was all about testing what worked. I made targeted changes based on week one data:

Swapped oatmeal for eggs + avocado

Peak glucose: 115 mg/dL (down from 165). My mornings became much more stable, and I felt less hungry by 11 AM.

Added protein and fat to carb-heavy meals

White rice with chicken thighs and olive oil: peak 140 mg/dL instead of 175. The fat and protein slowed glucose absorption significantly.

Walked after dinner

A 15-minute walk after meals dropped my post-meal peaks by 15-25 mg/dL. This was the single most effective intervention I tested.

Stopped eating after 7 PM

My overnight glucose dropped to 75-85 mg/dL consistently. Better sleep, too.

These changes dropped my average glucose by 5 mg/dL and improved my time in range by 3%. Small tweaks, significant impact.

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Week 3-4: Consistency and Patterns

Final average glucose: 104 mg/dL
Final estimated A1c (GMI): 5.2%
Final time in range: 96%

By week three, I'd settled into a routine that kept my glucose remarkably stable. The biggest lessons from the final two weeks:

Sleep Quality Matters

After a bad night's sleep (less than 6 hours), my fasting glucose was 10-15 mg/dL higher than normal. My insulin sensitivity tanked. One night of poor sleep had measurable metabolic consequences that lasted all day.

Stress Spikes Glucose

During a particularly stressful work week, my fasting glucose climbed to 100-105 mg/dL (normally 85-90). No dietary changes—just stress hormones driving glucose up. Cortisol is real.

Exercise Timing Is Everything

Morning fasted cardio dropped my glucose into the 60s (felt fine, not dangerous). Heavy lifting in the evening spiked my glucose to 130+ from adrenaline/cortisol—but it came back down within an hour. Exercise affects glucose in complex ways depending on intensity and timing.

Individual Foods Matter More Than Macros

Bananas spiked me hard (165 mg/dL). Apples barely moved the needle (125 mg/dL). Both are "fruit" with similar carb counts, but my body responded completely differently. Sweet potatoes were fine; white potatoes were terrible. You can't predict your personal response without testing.

The Final Verdict: How My CGM Data Matched My A1c

After 30 days, my CGM data showed:

Average glucose: 104 mg/dL
Estimated A1c (GMI): 5.2%
Time in Range: 96%
Coefficient of variation: 18% (low variability—very stable)

I got another lab A1c test at the end of the experiment: 5.2%. Spot on. My CGM-estimated A1c was accurate within 0.1%.

But here's the thing: the A1c alone doesn't tell the full story. My time in range and glucose variability were arguably more important than the single A1c number. An A1c of 5.2% with wild swings (60 mg/dL to 180 mg/dL daily) would be metabolically worse than an A1c of 5.5% with rock-solid stability.

What I'd Tell Someone Starting a CGM Experiment

Key Takeaways:

Don't obsess over single spikes. One meal at 170 mg/dL won't ruin your A1c. Focus on patterns, not individual data points.
Test your personal food responses. What spikes me might not spike you. Experiment with different foods and track what works.
Post-meal walks are magic. 15 minutes of movement after eating can drop your glucose by 20-30 mg/dL. Easiest intervention, biggest impact.
Sleep and stress matter more than you think. Poor sleep and chronic stress will sabotage your glucose control no matter how perfectly you eat.
Time in range > A1c. An A1c of 5.5% with 95% time in range is better than an A1c of 5.2% with 80% time in range and wild variability.
Use the data to build habits, not to stress. CGM is a tool for learning, not for anxiety. Once you know your triggers, you don't need to wear it forever.

Should You Try a CGM?

You don't need to be diabetic to benefit from a CGM. Here's who should consider it:

Prediabetic (A1c 5.7-6.4%): Absolutely yes. See exactly which foods and habits are driving your glucose up.
Family history of diabetes: Proactive monitoring can catch early metabolic dysfunction before your A1c crosses into prediabetes.
Unexplained fatigue or brain fog: Glucose swings could be the culprit. See if stabilizing your levels helps.
Athletes or biohackers: Optimize performance and recovery by understanding fuel utilization and glycogen management.
Anyone curious about metabolic health: Even if your A1c is "normal," you might have hidden glucose variability worth addressing.

CGMs are now available over-the-counter (no prescription) from brands like Stelo and Lingo. They're not cheap (~$100-150 for a two-week sensor), but the data you get is worth it if you're serious about understanding your metabolism.

The Bottom Line

Wearing a CGM for 30 days taught me more about my metabolic health than years of annual bloodwork. My average glucose of 104 mg/dL translated to an A1c of 5.2%—exactly what the lab test confirmed. But the real value wasn't the A1c number. It was learning which foods spike me, how exercise affects my glucose, and how sleep and stress sabotage my control.

If you're on the fence about trying a CGM, do it. Two weeks of data will teach you more about your body than any article or study ever could. Your glucose response is unique to you—stop guessing and start measuring.

References

Battelino, T., et al. (2019). Clinical Targets for Continuous Glucose Monitoring Data Interpretation. Diabetes Care, 42(8), 1593-1603.
Beck, R. W., et al. (2019). Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials. Diabetes Care, 42(3), 400-405.
Hall, H., et al. (2018). Glucotypes reveal new patterns of glucose dysregulation. PLOS Biology, 16(7), e2005143.
Zeevi, D., et al. (2015). Personalized Nutrition by Prediction of Glycemic Responses. Cell, 163(5), 1079-1094.

Medical Disclaimer

This article describes a personal experiment and is for informational purposes only. It does not constitute medical advice. Always consult with a qualified healthcare provider before making changes to your diet, exercise, or diabetes management plan. CGM data should be interpreted with medical guidance.