What Training with a Continuous Glucose Monitor Taught Me: The FreeStyle Libre 2

[@normwachholz7221]

Mike, interesting video. My first question is, what were you looking for in the data to help you? Second is, were you looking to fine tune your nutrition protocol, or have a device that would yield useful info during a race? It seems to me that there are many variables that would influence blood glucose level like what's still digesting in your gut, the rate of absorption which is a function of physical stress, temperature, the type of carb you're fuel with during the event, etc. I imagine that to get any useful information, you'd need to run a bunch of controlled experiments like not fueling to determine at which point your liver starts releasing glucose into the blood stream. My suspicion is that the information can be useful to tune one's nutritional protocol, but this requires an intimate knowledge of how to interpret the data in a useful way. Perhaps AI will come to the rescue. I think there are likely many other areas that one can spend money and time to improve performance.

[@bikesbymike]

Hey, Norm. Thanks for watching. The main thing I wanted to get from the data was to show me unexpected spikes, or dips, in my glucose levels, which I thought may be indictors that I’m doing something wrong (i.e. not taking in the right fuel, not fuelling enough, fuelling too much, or not fuelling at the right time). So if I was getting frequent “above normal” spikes in my glucose while riding, maybe I was taking in the wrong type of carbs or too much carbs. If my glucose was dipping too low, I was probably fuelling too little and risked bonking. If my glucose peaked and then it’s crashing down, I’ve probably started a ride too soon after eating. The data didn’t really help me identify if I was taking in too little or not enough carbs during a ride. I kind of knew I was taking in enough to prevent bonking, but did’t know how topped up my glycogen stores were as that is not what the device is measuring. Yes, when I deliberately took in fewer carbs than I thought I needed, I could induce a bonk and confirmed that this zone is somewhere below 4.0 mmol/L. But by that time, I already felt the bonk and having a score to confirm it didn’t help me much. One of the concepts Supersapiens promotes, is that everyone has an “optimal” glucose range where they perform at their best. Another is to keep glucose levels flat and stable. Their app helps you track trends and identify this personalized performance zone. There is science to back up the idea that there are unhealthy and dangerous zones, but little, if any, scientific research to say if optimal performance zones exist or if flattening the curve is desirable. That’s a big gap in the science. An ER doctor can tell you that if your blood glucose level drops below around 3.5 mmol/L, you’ll likely pass out or worse. But for non-diabetics, it’s the performance zone that’s more interesting. If a “performance zone” does exist, it’s likely such a wide zone that one could probably stay within it just by doing simple things like fuelling often, but in smaller doses. I will say that the data did show me a few really big spikes while fuelling during a ride, which did remind me that I should take in carbs more regularly, but maybe in smaller doses. You’re dead-on about there being lots of factors in play that impact blood glucose levels. And that’s the complication that researchers have raised. Your liver will release glucose into the blood in simple anticipation of the work that expected to come, for example, irrespective of other factors. Supersapiens was plugging their app as a good tool to interpret the data, but I’m not so convinced. For example, their premise that spikes are bad is hotly contested. What seems to be more important (within reason) is how quickly glucose returns to baseline, not the magnitude of the spike.

[@marcusmatthews8255]

Good video. But you should look at the research from the Ohio State professor Dr. Jeff Volek on carbs for endurance athletes

[@bikesbymike]

Interesting. I see he has a few articles and research papers on keto-adaptation and the benefits of a low-carb diet. And certainly, you see this among elite athletes that have peak fat oxidation rates at very high VO2 max levels. That’s a winning formula; someone that has great fat oxidation but is able to use carbs at super high intensities when it’s necessary. Being a non-researcher, I find it difficult to decipher the science on metabolic adaptations. The research paper that came out in January of this year and published in Nutrients certainly got a lot of press. It looked at whether restricting carbs during training would improve athletic performance. The researchers concluded that the high carb and low carb periodization groups improved equally well, with no difference between the two groups in terms of fat or carb oxidation rates at max lactate steady state. It would have been interesting if they also included a permanently low carb / keto group in their study.