“This is the very first public presentation of my data,” I began, “and I’m excited because I get to start it off with a bang.”
I was standing before the Ketogains Seminar audience on October 9th, 2016 in Las Vegas, and I planned to make that day just a little extra special. The first slide I showed included a picture of me smiling as my blood was taken, with the heading, “October 7th, 2016 – Two days ago”. I then explained I expect my cholesterol on that day will be very high.
I follow with a second slide. It has the same picture but I’m a silhouette with a question mark inside. The heading reads, “October 10th, 2016 – Tomorrow”
Finally, I present a third slide that includes both images and my predictions together, the second reading plainly, “Cholesterol Plummets in 3 Days”.
“How am I doing this?” I asked. “A super powerful statin? High dose of Niacin? Some new, special exercise?… No… just food.”
I’d be lying if I didn’t confess at this point that my heart was pounding. I’m no stranger to public speaking, with one of my very first jobs being the M.C. of a dive show and working my way through college as a D.J. No, my nervousness stemmed from the fact that I was trusting all my research to date and taking this to the next level of publicly predicting an outcome. And not just any outcome… the outcome a thirty billion dollar prescription industry tries to provide.
So what happened? Quite a lot actually. Let me break it down into small pieces…
Sure enough, my Total Cholesterol dropped 66 points. But the real star of the show is LDL-C, the so called “Bad Cholesterol” which dropped a whopping 73 points in just three days — that’s nearly a 30% drop!!!
If I could put these results in a drug, I’d be a multibillionaire right now. Bayer and Pfizer would be pounding down my door offering a slice of the world to package this magic in a bottle.
But what about the actual LDL particles which show on the NMR labs as LDL-P? Or for that matter, the “Small” LDL-P that gets the credit as being the most dangerous of all?
LDL-P is nearly cut in half! This was even more impact than I had predicted. While it is true my LDL-P continued to drop into the 5th day (to be covered in an upcoming post), the shift in just 72 hours was really impressive.
Even more strikingly, Small LDL-P drops from 442 into the unreadably small “<90” range. Like LDL-P above, this runs very counter to the endless articles I’ve read about clearance with LDL receptors, which has been one of the chief suspects as to why LDL gets “backed up” in the bloodstream. Over and over, my data keeps providing a very different story.
HDL-C and Triglycerides both shifted in different directions, each one considered more favorable.
HDL-C bumped up 18 to 68, which is likewise consistent with my data.
Triglycerides are still a little more mysterious to me as they have the lowest correlation of the bunch over my research span, but are still negatively correlated with dietary fat. In this case, I was excited to see it dropped to nearly half of its earlier reading.
Food. Just Food
Unless you’re just now joining us, you already know how I pulled this off. More fat.
On one hand, if this is the first blog post of mine you’ve ever read, you might think I mistyped the above sentence. I most certainly didn’t. As with the last eleven months of my life, I carefully logged my food in MyFitnessPal to track it closely. I likewise took pictures of everything I ate. Everything.
On the five days prior to the Oct 7th blood test that gave me the high cholesterol, I had brought my total diet down to an average of 748 calories per day. This wasn’t pleasant given I’m a 6’3 male who gets semi-regular exercise. (Not to be confused with “athletic”)
Moreover, I didn’t want to stay too low on the calories for very long given I’m also very lean and would actually prefer to weigh a little more. I know this has me on the other side of most people in a low carb lifestyle, but actually aligned well with many at Ketogains.
By the time Friday was rolling around, I was excited to finally move to the next phase and ramp up the total food to full throttle. But unlike my Intentional Outlier experiment that I describe in Part I, I planned to exceed everything and shoot for the gold: 5,000 calories per day for five days.
The first day was pretty easy, most likely due to having been so low cal for the previous five. Each meal I had to double or even triple my portions. But eventually I figured out it was just better to spread it out over the day. By the last day I could barely stand it. It’s incredibly difficult to eat very high calories on such a satiating diet. I kept telling my wife, “ugh, I can’t ever do this again,” to which she rolled her eyes knowing my variety of experiments before it and said, “yeah, we’ll see.”
Thus, many at the Ketogains Seminar noticed I was constantly pulling food out of my backpack in various forms: Adapt bars, peanut butter, and hot dogs I kept in a small cooler to name a few. This was especially annoying given the conference was catered with several amazing Keto-friendly buffet delights. But I couldn’t partake, given I needed to be certain of the exact macros and general ingredients I was consuming.
One particularly funny moment happened near the end of Sunday where I was sitting with other presenters at a Q&A and I realized I was still 1,200 calories short for my 5k goal which I had to meet by 7PM in order to have the proper 14 hour gap for the blood test at 9PM the following morning. I left my chair to go get a block of cheese and munched on it for the remaining 15 minutes of discussion.
Having said all that, let’s revisit our final version of the chart where we’ll include the food as well:
I’ll concede I’m still pretty awestruck. Even as I write these words and post this data, I keep rereading the labs and checking back over my logs. But there’s no doubting it now – the experiment delivered. The Dietary Inversion is very much real and yet almost no one knows about it.
Maybe this will move that needle just a little more.
This Part I is meant to be more layman, less geeky. In Part II I’ll be expanding on the data including the test before Oct 7 and after Oct 10th and how all of it compares to my current correlation timeline.