I've been thinking a lot about continuos health parameter monitoring lately. For the last 100 days or so I have been running a personal health experiment and collecting multiple data points during the process. I guess some use the term "bio-hacking", not sure if it applies.
The experiment has included multiple fasting periods, with a maximum of 7 days as well as changing one variable at a time in categories such as diet and exercise. The results have been very interesting and I intend to continue on this path until at least the end of the year.
As part of the data collection I have been taking my blood pressure a minimum of twice a day, sometimes more. Also blood glucose, ketones and (consumer) EKG.
The first thing that jumped at me was the inaccuracy or variability of these measurements. I even got a Dexcom continuous glucose monitor. Interesting but useless for my purposes. The thing produced 20% error with respect to finger poke measurements. And, then again, when I got a calibration kit to check my finger poke meter, the calibration range is approximately +/- 18%. In other words, unless you hit extremes it feels like these measurements are almost useless. You can kind of tell you are going up or down, yet don't really know where you are.
The same, of course, has been true of blood pressure measurements. I went through three consumer machines. I can't say any of it is accurate because there are too many variables. I have run multiple experiments with regards to where and how to measure BP. All I can determine are relative changes by effectively measuring under as close to the same conditions as possible twice a day, morning and evening (both before meals).
During the last month or so I have been using a protocol I learned from one of Andrew Huberman's presentations (can't remember which one or I would post a link). I believe he was interviewing a researcher who explained the process they use during their studies. In simple terms, they take three measurements and then average. The first is after 15 minutes sitting, feet on the ground, back supported, no movement, no speaking, no activity. The second and third are at 5 minute intervals under the same conditions. In other words, the entire process takes at least 25 minutes.
After adopting this approach I have been seeing wildly different numbers with respect to the single measurement protocol I had been using for two months. In addition to that, the standard deviation of the computed values are much tighter now.
This experience, so far, has made me wonder about just how many people might be misdiagnosed and put on medication every year because of bad data. I can see the value in having more data, of course. Yet, continuous data is only good if it is accurate to within a reasonable margin.
> how many people might be misdiagnosed and put on medication every year because of bad data
Another variable that causes this is the patient. They don't like the medication or don't take it properly but tell their prescriber that they are taking the medication correctly (age, culture, dementia etc). The prescriber then adjusts the dose.
The experiment has included multiple fasting periods, with a maximum of 7 days as well as changing one variable at a time in categories such as diet and exercise. The results have been very interesting and I intend to continue on this path until at least the end of the year.
As part of the data collection I have been taking my blood pressure a minimum of twice a day, sometimes more. Also blood glucose, ketones and (consumer) EKG.
The first thing that jumped at me was the inaccuracy or variability of these measurements. I even got a Dexcom continuous glucose monitor. Interesting but useless for my purposes. The thing produced 20% error with respect to finger poke measurements. And, then again, when I got a calibration kit to check my finger poke meter, the calibration range is approximately +/- 18%. In other words, unless you hit extremes it feels like these measurements are almost useless. You can kind of tell you are going up or down, yet don't really know where you are.
The same, of course, has been true of blood pressure measurements. I went through three consumer machines. I can't say any of it is accurate because there are too many variables. I have run multiple experiments with regards to where and how to measure BP. All I can determine are relative changes by effectively measuring under as close to the same conditions as possible twice a day, morning and evening (both before meals).
During the last month or so I have been using a protocol I learned from one of Andrew Huberman's presentations (can't remember which one or I would post a link). I believe he was interviewing a researcher who explained the process they use during their studies. In simple terms, they take three measurements and then average. The first is after 15 minutes sitting, feet on the ground, back supported, no movement, no speaking, no activity. The second and third are at 5 minute intervals under the same conditions. In other words, the entire process takes at least 25 minutes.
After adopting this approach I have been seeing wildly different numbers with respect to the single measurement protocol I had been using for two months. In addition to that, the standard deviation of the computed values are much tighter now.
This experience, so far, has made me wonder about just how many people might be misdiagnosed and put on medication every year because of bad data. I can see the value in having more data, of course. Yet, continuous data is only good if it is accurate to within a reasonable margin.