My data: seven months of readings

Seven months, one sensor, no medication. This page shows how my readings changed — with the reports from the app, exactly as they appear there.

What this is and what it is not

A single-case record. I show what happened to me, not what will happen to you. What I changed — food, movement, sleep — worked in my situation. Whether it works in yours is a question for your medical team.

Seven months in figures

146

The percentages in this article are calculated from the raw sensor export, not read off the app screens. The app uses the configured target range of 70 to 160 mg/dl and therefore shows different shares.

mg/dl · January

Monthly average at the start

119

mg/dl · July

Monthly average at the end

-27

mg/dl · change

Difference over seven months

99 %

in range 70–160

July, up from 81 per cent in January

Calculated from the raw sensor export — not read off the app screens.

Fig.: Monthly average from 7 months of continuous measurement. Each point is based on between 6,864 and 8,895 individual readings.

January 2026

February 2026

March 2026

April 2026

May 2026

June 2026

July 2026

What changed during this time

Three things I kept up: a twenty-minute walk after larger meals, fewer carbohydrates at dinner, and regular training — steady endurance work plus strength sessions.

What I did not do: skip meals, go hungry, or treat supplements as a substitute.

How to read this

These reports show a development over seven months. They do not show which single measure contributed how much — separating the influences is not possible in everyday life. Season, stress and sleep play their part too.

Key points

Seven months of continuous measurement with the same type of sensor.
Time in range increased noticeably over this period.
What changed: movement after meals, the composition of dinner, and training.
A single observation — no reliable proof that it works the same way for others.

Single-case record, not a study.

🔍 How I read this data

The values in this article come from my own sensor (FreeStyle Libre 3) and are a single-case observation (n = 1) – they show a pattern in me, not a rule for you. Every statement is labelled as established, plausible or open, and proximity in time never counts as proof of a cause. How I handle time windows, sensor lag, influencing factors and approval is collected on one page. Read the methodology

Sources

This entry is based on my own sensor readings. Where studies are mentioned, they are linked in the text. Continuous glucose monitoring: FreeStyle Libre 3.

Recalculated from the complete CSV export

Actual monthly values from 89,488 continuous glucose readings. July ends on 24 July 2026.

The earlier image selection included daily screenshots that could be mistaken for monthly summaries. This graph uses only the CSV export. Calculated GMI is a CGM estimate, not a laboratory HbA1c.