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...
