Self Testing - Part I

 Those of you who know me will not be surprised that I love data.  Even noisy data can bring a picture into focus if there is enough of it.  I collect data on all sorts of things but find biometrics fun because it’s easy to collect and it can potentially give useful insights.

A couple of previous posts alluded to some obvious trends that I have observed.  To all those people who mocked me decades ago for starting a low carb diet, contrary to their predictions that I would gain weight, I shed 50 pounds by eating mostly fat with a bit of protein and as few carbs as possible.  In the process, my cholesterol also dropped to healthy levels (see http://unknownphysicist.blogspot.com/2011/10/eating-lots-of-fat-to-lose-weight.html).  I kept my weight down for a decade.

After a trip to Belgium and then to Italy, I adopted a Mediterranean diet, which was a gateway to me eating lots of carbs again, which produced an upward spiral in my weight.  Then in 2012, when I had almost regained all the weight that I had lost, I went on a strict low carb diet for a second time.  Again, it worked, but over the last two years, I have struggled with a small weight gain, whose source I have tried to identify using my vast stores of data.

In the interim, PSA (prostate specific antigen) data that I had been tracking took off, as I described in my post describing my ordeal with prostate cancer. (see http://unknownphysicist.blogspot.com/2021/01/can-major-surgery-cure-depression.html and http://unknownphysicist.blogspot.com/2020/06/i-was-relieved-i-had-cancer.html)

The graph below shows my weight as a function of time.  There are a series of drops each followed by a plateau.  Also plotted are my measurements of total cholesterol and LDL cholesterol along with error bars that reflect the accuracy of my instrument.  LDL is the bad cholesterol.  My triglycerides were always very low, so I was not so concerned about my cholesterol while it slowly fell over 4 years (1500 days).  Then, for no apparent reason, my cholesterol shot up even as I was losing more weight.

  

Both my doctor and I got concerned with the rise, so he prescribed the highest dose of atorvastatin – which scrubs serum cholesterol.  My cholesterol remained high for months while taking it, so he sent me to a cardiologist, who suggested I add ezetimibe, which prevents cholesterol from being absorbed through the intestines.  I was reluctant to take ezetimibe because I had had a bad experience with Vytorin, which combines atorvastatin with ezetimibe.  I hadn’t realized how much energy Vytorin was sopping away (and resulting in weight gain) until I accidentally stopped taking it for a week.  I then regained my usual vigor.  That’s when I stopped Vytorin and went back to my strict diet.

My cardiologist suggested that I take an ultralow dose of Ezetimibe, which I did at the time shown by the vertical gray line in the plot.  Indeed, it drastically decreased my serum cholesterol, as you can see in the plots, and I retained my energy levels within my ability to notice.  And my weight appeared to remain stable, as shown within the gray dashed box.

The plot below shows a magnified view of my weight after starting to take Ezetimibe.  The raw data (points) is quite noisy and can vary by as much as 6 pounds over a few days.  That variation is real.  There are days when I exercise vigorously and might also dehydrate, so I could easily lose a few pounds, which I regain when hydrating and remaining sedentary for a few days.

The raw weight data does not appear to show any trends.  However, a plot of 50 (dark curve) and 100 point smoothed data (gray curve) shows a different story.  My weight appears to be increasing and it also fluctuates over time.  The fluctuations might also be real due to seasonal variations in my diet and activity.  The gray vertical dashed line falls on the date that I started taking Ezetimibe and the pink dashed line when I had prostate surgery.  Each seems to have been responsible for some weight gain.

Next I fit the raw data to saturated exponentials starting at the time I began my Ezetimibe regimen (light blue curve) and then after prostate surgery (magenta curve).   The fit shows that the Ezetimibe resulted in almost a 3 pound weight gain (when averaged over a couple months).  This is consistent with the fact that I observed a huge weight increase when I was taking a larger dose.  I gained a little less than two pounds after my radical prostatectomy.  Though minor, I have noticed a little edema around the incision area, so this increase is also explainable.

The skeptic might complain that the pink curve start lower than the flat part of the blue curve.  A closer examination of the data right after my surgery shows that my weight dropped by 5 pounds from the previous baseline for a week right after surgery, so that biases the early parts of the fit.  However, all of the fits and the smoothed data nicely follow each other aside from seasonal variations.

I would not conclude form my data that ezetimibe results in weight gain nor that prostate surgery does so too.  However, the data is suggestive that this might be the case and my data is consistent with secondary observations.  I find it amazing how such small effects can be drawn from the data and gives a small level of confidence that it might be true.

In the meantime, I continue to take and analyze the data to see if any other correlations emerge that might signal an interesting underlying cause.  Apologies for typos and the like, but my Fitbit just informed me that I missed my 250 step goal this hour while writing.  So I have to get up and walk...