Understanding My Blood Glucose
Bob Troia was interested in his blood glucose. After learning he had an elevated risk for contracting Type 2 Diabetes, he wanted to see if he could lower his fasting glucose levels. He started a long-term tracking experiment where he tested his blood glucose and began to explore the effects of supplementation and lifestyle factors. In this talk, Bob talks about his experiment and what he learned from analyzing his data.
Blood glucose monitor | Statwing
So there’s some general guidelines about glucose levels and the American diabetes Association will say you should be somewhere between 70 and 130 mg/dl. But when you look at organizations focused on anti-aging research they have it actually down to 70 to 85mg/dl.
My last round of blood work before starting my experiment was was at 85 which is okay but it’s not optimal or ideal and I want to be ideal. Also my 23andmedata showed I was at an elevated risk for Type 2 diabetes so I want to do anything I could take to control it and keep it to a minimum.
I came across a supplement called oxaloacetate at a biohacking conference. It’s been shown to lower and control fasting glucose levels. Actually scientists has given this to animals, from worms to mice to rats and it actually extended their lives by over 40%.
So what did I do? I took some daily fasting readings over a period of seven months. How did I do it? You’ve probably seen a blood glucose monitor before. You prick your finger, draw a drop of blood, touch a test strip from the meter to the blood and I would get a reading. Then you put the values into a spreadsheet. Actually the meter is pretty inexpensive as well and probable under €10 for one of those.
When I first started I wanted to get all sorts of values. I wanted to get my weight gain, pulse rate, and combine it with blood pressure and all these values of glucose. Before each meal, two hours after each meal but I just realized quickly that it was too unwieldy. There was no way I was going to track it all so I had to simplify things and I focused just on my glucose.
This is a baseline of my first 30 days. The y-axis is the glucose value, x-axis is the day number of my experiment, and you can see the values go from about 77 up to about 104, and so there’s a bit of jumping around there. I then started taking oxaloacetate right at that orange line and you can see quickly it went down and the value later stabilized. The orange line is a seven day of moving average of values.
So green just means I was taking oxaloacetate and there’s a few points there when I wasn’t. but I want to understand my glucose even better, and what really affects me and what factors will affect it. This is a seven day or an average of each day, and you can see Monday’s a rather high and it kind of goes down towards Thursday. And when you get to the weekend it’s at a low point.
To verify it I uploaded the data into a statistical analysis tool called Statwing and it proves that yes there’s a statistically significant relationship between day of week and glucose value.
I then took my data from steps and move and figured hay, maybe I took more steps in those days and that affected it, but I found there was no significant relationship in either case between the number of steps I took each day and the values. And I was like really kind of confused, like why isn’t there a relationship there. You would think that affected it. Well I play soccer a few night of the week. That’s me without a beard, and when I’m on the field I can’t wear my Basis band. The referee will not let me wear it. Also I don’t have my iPhone in my pocket so Moves can’t track me, so there’s a lot of unreported data going on there.
So what I did was I noted the days where I played soccer and then compared it to my fasting glucose values the next day. And bam, you can see right there, there’s a nine point difference in values on days where I played soccer and days where I didn’t so there’s clearly something going on there.
And as you can see most of my league matches are on Wednesday and Fridays, and you’ll see the Thursdays and Saturday results of exercising at night, intense interval type exercise on those days of the week.
I then tried to repeat the experiment. So we started back in September and we’re later in the fall here and I failed. The results and the trendline don’t actually jump back down again and actually stayed pretty consistent and even went up and I couldn’t figure out what was really going on there. You know I was kind of scratching my head because I thought it would have mimicked the first round of results.
Well, I was in New York city and we had a pretty nasty winter this winter, and I play soccer outside all year round. But that’s what our field looked like from about November to maybe March so I was actually not playing so much soccer this winter.
On top of that I had stopped commuting into the office everyday so I was really spending my time sitting down in my home and I wasn’t walking around and walking in the office, and walking around in meetings. And then when I looked at my steps from Basis and Moves you can confirm that there’s a negative trendline there so my activity is indeed going down.
But I think there may be other things that play there. Maybe I’m sitting more now and not standing, so that can have an effect on my glucose levels. And what’s interesting is that the data from Moves and Basis is never the same. Obviously my phone might be down on the ground or I might be charging my other device, but for me it shows even though the values are different you can still get the general trends off of it.
And this is how my data looks now going out until March and I haven’t been taking oxaloacetate for some time, but you’ll see there’s a slight peak as you go up towards he right of the chart.
So I went back into my calendar and I looked for days where I travel, and you’ll see I went on a trip to Jackson Hole snowboarding and I was in Austin Texas and San Francisco and those were cases where I had spikes in my values. And it was interesting to see if the effects were related to altitude change or travelling West bound versus East bound, but it definitely seemed to have an effect on me even for a few days. So travel has an effect on my glucose levels.
I then looked at the effects of alcohol. I actually track my consumption of caffeine and alcohol as much as I can remember on the alcohol side. And you would think it has an effect, but actually it did not. And what’s interesting is that the days where I consumed the most beverages were the days I played soccer. You go out after matches for a drink so it was interesting.
So what did I learn? I learned that oxaloacetate works but only in conjunction with intense interval exercise like soccer. Based on my stress levels of the week, Mondays suck, weekends are awesome. Alcohol didn’t have an effect. Travel seems to negatively affect things.
As we saw devices are never going to be 100% accurate or even 95%, so we shouldn’t get to worried about that. So long as you can identify the trends, and it helps you out, and you gain insights from it it’s great.
And lastly failure equals fails, so my experiment failed at one point, but it does give you some valuable data that you can use and perhaps change and look at your data in other ways.
And what am I going to do next? I’m looking at other ways of collecting some of this glucose data. They have continuous monitors that will collect data 24/7 so then I can see effects related to other aspects of my life. I want to look at sitting versus standing and how that relates to glucose. I want to look at other supplements other than oxaloacetate that have effects, or have been known to have some effects on glucose levels. And I also want to look at environmental impact, for example air quality indoors or outdoors or being outside more have an effect on my glucose.
So I’m still very much in the throes of this experiment and I hope to continue with it and this time if you have any questions, comments, feedback I would love to hear them.