A few weeks ago I decided to get the Abbott Libre 3, Continuous Glucose Monitor (CGM) and it was super insightful in gaining a deeper understanding of how various foods affected me [Box 1]. But I knew I could get more out of it especially combining it with the data from my Ultrahuman Ring Air, Smart Ring. Here are some of the insights I gained by combining these two data modalities.
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**It is super important to mention that what you’re going to see are just trends and one cannot establish a causal relationship since the data size is really low and moreover it’s just N=1.
So take it with a grain of salt!**
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With that said……
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Box 1: We all know that some foods cause bigger blood sugar spikes than others, but it's not that simple. Everyone reacts differently, even to the same foods. That’s why using a CGM can be super helpful.
To know more, check out this paper: https://www.cell.com/fulltext/S0092-8674(15)01481-6
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I first started looking into my sleep data cause that’s where the Ring AIR truly excels at and naturally the first metric I looked at was the Sleep Score. The Sleep Score is a cumulative metric that takes into account various aspect of your sleep (consistency, efficiency, resting heart rate (RHR), heart rate variability (HRV), etc.) to give you a score between 0 and 100, where 100 is optimal sleep.
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Coefficient of Variation (CV): CV of glucose measures how much your blood sugar levels fluctuate relative to your average glucose. If you experience frequent or large glucose spikes after meals, your glucose variability (the ups and downs) increases, leading to a higher CV. And lower CV would mean fewer spikes throughout the day.
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So, I looked into the Mean Glucose Level and CV of Glucose during sleep and compared it to the Sleep Score during that sleep session. And what I see is a negative correlation between for both (Mean: r=-0.40 | CV: r=-0.58). Not surprising, since it’s quit well know that sleep greatly affects glucose metabolism (Ref), but over here it’s rather difficult to know what the direction of effect is, does bad sleep cause cause bad glucose control or vice versa? or maybe both?.
| RHR vs | Person’s Correlation (r) |
|---|---|
| Mean | 0.10 |
| CV | 0.51 |
| HRV vs | Person’s Correlation (r) |
|---|---|
| Mean | -0.02 |
| CV | -0.31 |
| Recovery Score vs | Person’s Correlation (r) |
|---|---|
| Mean | -0.01 |
| CV | -0.31 |
This was an interesting relationship, where the Resting Heart Rate (RHR) and Heart Rate Variability (HRV) during sleep was only correlated with CV of glucose and not the Mean levels. In other words, if your glucose is steady (low CV), it leads to a lower RHR and higher HRV, thereby higher parasympathetic activity, thereby better recovery from sleep. I couldn’t find a lot of papers that looked into this specific relationship (will update here incase I find something).
There are several studies that show deep sleep improves next day insulin sensitivity (Ref) and it’s nice to see that same trend with my data as well (Mean: r=-0.46 | CV: r=-0.46).
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AUC (Area Under the Curve) of glucose: is a way to measure your total blood sugar exposure over a period of time.
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| Stress Score vs | Person’s Correlation (r) |
|---|---|
| AUC | -0.43 |
| Mean | 0.13 |
| CV | 0.01 |
| Stress Score vs | Person’s Correlation (r) |
|---|---|
| AUC | -0.43 |
| Mean | 0.13 |
| CV | 0.01 |
This is an interesting but rather tricky one, the total glucose exposure during sleep is negatively correlated with my next day Stress Score. It’s an interesting trend, but it does have several confounders to it and can be hypothesized from a few different lenses: