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Carb Counting Type 1 Diabetes

The Carb Counting Myth: Why 50% of Diabetics Rely on "Gut Feeling“

Bo Frese
4 min read

Why the gold standard of diabetes management doesn't work in real life

Table of Contents

You're sitting at the dinner table, trying to figure out how many carbs are in your portion. 75 grams of pasta? Or was it 90? And that sauce—how much sugar is in it? You take your best guess, adjust your insulin, and cross your fingers.

If this sounds familiar, you're not alone.

What People With Diabetes Actually Do

I recently asked 662 people with diabetes a simple question:
"How do you decide how much insulin to take?"

The results were eye-opening:

  • 50% rely on "experience" and gut feeling
  • 33% use rough estimates in their head
  • Only 17% use any systematic approach

This isn't because people are lazy or irresponsible. It's because reality is more complex than the formulas suggest. Carb counting is too cumbersome and too imprecise in practice for most people to actually use it consistently.

When the Math Fails

On paper, it sounds logical: The more precisely you can count carbs, the better you can hit the right insulin dose. But research tells a different story.

In a study of children with type 1 diabetes, only 67% of meals were counted within 20% accuracy—even after extensive training. In adults, the average error was 20 grams per meal—enough to cause significant blood sugar swings.

And even when carb counting was accurate, blood sugars were still often out of range due to other factors.

The Bigger Picture: Everything Else That Affects Your Blood Sugar

Protein: 50+ grams of protein can raise blood sugar 2-4 hours later. Most people ignore this completely. On a keto diet, protein becomes a major factor.

Fat: High-fat meals slow carb absorption. The "pizza effect" means blood sugar rises slowly over up to 6 hours, while your rapid-acting insulin peaks too early.

Meal order: Eating protein first and carbs last? That gives better blood sugar readings than the reverse.

Exercise: Working out before a meal means lower insulin needs. Exercise after eating changes absorption patterns. And yesterday's run affects today.

Stress and sleep: Poor sleep can mean 25% higher insulin requirements. Stress hormones interfere with insulin action. For women, menstrual cycles change needs.

Processing: A whole apple vs. apple juice = completely different blood sugar responses, even with the same carb content.

The Memory Problem

Our brains are terrible at remembering complex patterns:

  • Most people can't accurately recall what they ate yesterday
  • Linking food choices to blood sugar outcomes hours later
  • Tracking multiple variables over time
  • Recognizing patterns across weeks or months

That's why "experience" works for many—but it can work even better when built systematically.

Your Personal Logbook

Here's the key: A simple logbook that captures context.

You don't need to weigh or calculate down to the gram. Think of it more like a food journal:

What you ate: "Homemade lasagna, large portion" is precise enough.

What you did: How much insulin? Blood sugar before and after?

The context—this is crucial: Had you exercised? Were you stressed? Did you sleep poorly? This is the difference between success and guesswork.

Next time you eat lasagna, you can look back and see the last 5 times. You'll spot patterns:

  • "After a run: 4 units was enough"
  • "When I had a cold: needed 8 units"
  • "Late dinner means high morning blood sugar"

This is your reality with your body—not a standard formula.

Make It Easy

The best logbook is one you'll actually use:

Choose your tool. App or paper—whatever works for you. But it needs to be something you always have with you and can quickly note things in.

Make it searchable. You need to be able to quickly find previous experiences with the same meal.

Keep it brief:

  • "Homemade lasagna, large portion"
  • "6 units NovoRapid at 6:30 PM"
  • "BG before: 112, after: 164"
  • "Note: Had run 5K"

Why Most Diabetes Apps Fail

Most apps focus on:

  • Precise carb calculations
  • Perfect insulin ratios
  • Complicated databases

What they miss:

  • How meals affect each other
  • Daily patterns and trends
  • Easy overview of the whole day's context
  • Your individual learning

Try a Different Approach

Glysimi App (for iPhone) was built specifically with this philosophy in mind. Not another complicated carb calculator, but an app that focuses on what matters:

  • Your notes and readings in context
  • Overview of entire days, not just isolated readings
  • Easy search across your own data
  • Spot patterns in how your body reacts

Simple. Practical. Built to help you develop the experience that actually works.

Learn more here...

The Bottom Line

Research shows what those 662 people with diabetes already knew: Experience often works better than math.

But experience only becomes reliable when it's systematically documented. Your logbook gradually becomes your personal guide—filled with patterns and insights that no standard formula can provide.

This doesn't mean precision is never important. But it means that daily life with diabetes is about learning to know yourself, not slavishly following formulas.

Sometimes the best strategy is admitting that the "perfect" strategy doesn't work in real life.

Your body is your best teacher. Listen to it. Document what it tells you. And build the experience that makes life with diabetes easier.

References

  1. Shimin Fu, Linjun Li, Shuhua Deng, Liping Zan, Zhiping Liu. (2016). "Effectiveness of advanced carbohydrate counting in type 1 diabetes mellitus: a systematic review and meta-analysis". Scientific Reports, 6(1), 1-8. https://doi.org/10.1038/srep37067.
  2. Kirstine J Bell, Carmel E Smart, Garry M Steil, Jennie C Brand-Miller, Howard A Wolpert. (2015). "Impact of Fat, Protein, and Glycemic Index on Postprandial Glucose Control in Type 1 Diabetes: Implications for Intensive Diabetes Management in the Continuous Glucose Monitoring Era.". Diabetes Care, 38(6), 1008-1015.
  3. Deeb, A., et al. (2017). Accurate carbohydrate counting is an important determinant of postprandial glycemia in children and adolescents with type 1 diabetes. Journal of Diabetes Science and Technology, 11(4), 753-758.
  4. Brazeau, A. S., et al. (2013). Carbohydrate counting accuracy and blood glucose variability in adults with type 1 diabetes. Diabetes Research and Clinical Practice, 99(1), 19-23.
  5. Smart, C. E., et al. (2009). The effect of including protein and fat in carbohydrate counting on postprandial glycaemia in children with type 1 diabetes. Diabetic Medicine, 26(4), 354-361. 6.
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