In Part I, we focused on the three day gap where I arranged a massive shift around the first public presentation of my data. There’s quite a bit more to the story, though, which we’ll dig into here…
Knowing I’d be presenting on October 9th made it immediately clear I needed to test on the Friday before (7th) and the Monday following (10th). This should reflect the shift in LDL-C and HDL-C, given they both follow that three day window immediately before a blood test.
But what about LDL-P, and for that matter, small LDL-P (smLDL-P)? Since these follow a three day window, but with a two day gap in between, I needed to be sure I captured all five days before Oct 7th and the five days following. So in short, I’d be on the “low calorie diet” on October 2nd, 3rd, 4th, 5th, 6th until the morning of the 7th (Sunday, Monday, Tuesday, Wednesday, Thursday). I’d then take the blood test and ramp up the food intake to a “high calorie diet” for the rest of the 7th, then the 8th, 9th, 10th, and 11th (Friday, Saturday, Sunday, Monday, Tuesday) up to the morning of the 12th.
Below, in each graph, I mark the blood test associated with these four tests over the ten days in red, which will always be at the right of the graph.
So let’s start by looking at our old friend, LDL-C.
For those of you who regularly read my blog, this is a familiar graph. In this case the blue solid line represents the LDL cholesterol that resulted from the blood test. The dashed orange line represents the dietary fat I ate in the three days just before the blood test was taken.
At the far right end you’ll see a solid red line replacing the blue. Those four data points took place October 5th, 7th, 10th, and 12th. You can also see the dashed orange lines showing my extreme low, followed by the extreme high in dietary fat.
Let’s invert the axis on the left side of the graph (the Three Day Dietary Fat) so that we can compare these trends visually.
Sure enough — I “broke” my own correlation given how quickly I shifted from one extreme to the other. Given our correlation on the left side of the graph, you’d expect my extreme low on dietary fat of 63g would theoretically push my LDL-C up to around 348.
However, I did manage to bring the LDL-C down to 155 which did match the expected position relative to the diet. Yet this completed on the 12th, not the 10th. Again, this was probably due to the degree of shift, but we’d need to do more testing to know.
How about LDL-P?
Same thing. Purple is pre-conference, red on the right is during. Let’s invert again…
Like LDL-C above, the massive shifts seem to surpass my metabolism’s attempt to catch up.
Now let’s look at HDL-C.
As you can see from the green line on the right side, we have a long established coupling in the positive between dietary fat and HDL-C. But this too is broken by the experiment as shown on the right.
Other Interesting Markers
I had a number of things change, but there are two specific ones I wanted to call attention to in this post.
Glucose vs Insulin
Now I don’t want to blow your mind too much, so prepare yourself… here comes fasting glucose vs insulin…
Whoa — really?!? As my fasting glucose went up, so too did my insulin? No way!
Okay, kidding aside, it’s difficult to tease out the impact of each macronutrient on my fasting glucose to see what the primary drivers of the increased insulin were. Since all of my macros went up, this could’ve been from higher carbs or protein — or possibly just overall caloric load.
What is interesting is that even after 5 days at 5000 calories, my peak insulin was still at the bottom third of the reference range, at 8.3. Incredible!
Calories vs Weight
Easily one of the most hotly debated subjects in low carb communities. I’m firmly in the camp that says Hormone Balance Matters Most, But Calories Are Still Energy. Is that a side? If so, should we start a website for hbmmbcase.com?
I’m 6’3″ (190.5 cm) and thus feel a bit underweight at my running average of around 176 lbs (79.8 kg). My typical average calories right now are around 3,100. So what happens when I drop it to 750-ish for five days, then ramp up to 5,000+ for five days?
Clearly the massive drop, then rise, in calories had a very acute effect on my weight. Over this span of time, I was careful to keep my water intake roughly the same for both low and high periods, although my non-water beverages were a little higher on the last half.
I’m now at the point of being so sure about the dynamism of the lipid system that this is becoming almost comical. Getting to this point took a lot of money, time, and blood (literally). I was fortunate to have this experiment wrapped into my first presentation. Doing the demonstration was a no-brainer. Why only show the data if you can display its predictive power as well?
There’s actually a lot more data I couldn’t get to due to the balancing act I’m now performing between this, contract work, interviews, and helping others to gather N=1 data as well (upcoming).
Personally, I wish I could work on this research 100% of the time, but I do have to pay the bills…