Resistance Training Experiment – Findings

As discussed earlier, this experiment is near and dear to me. And I must say, it did not disappoint…

Below I have expandable sections with the text from the prior posts that detail this experiment.

Design Amendment to Add an Extra Phase

The Face of Tired

As if this writing (Thursday night, Sept 13th), my cholesterol is below the baseline of the washout period (August 29st-Sept 5th). The mean average of TC and LDL-C during this run-up period are 382 and 314 respectively. [Note: these levels are higher due to the baseline diet being around 500 calories lower than my typical, ad libitum keto diet.]

I’m awaiting the baseline to return to this roughly this level before “triggering” another intervention of another intense workout. I figure a 3% offset should be sufficient. Thus, if either the TC comes to or above 370 (97% of 382) or LDL-C comes to or above 305 (97% of 315) for the 10am reading, then I’ll initiate the intervention on the following day.

Change to Intended Exercise Regime

While I had set up my vibration plate machine for exercise in the hopes I could fully quantify it for perfect replication, I quickly found out that I couldn’t easily do a full upper body workout to the degree I was seeking and that it was taking a bit of time working with the operation of it. Thus I altered the intervention phases as follows:

Intervention Phase I: Completed four exercises on the vibration plate for 20 minutes. Completed half of a free exercise video on YouTube for 15 minutes. Played 20 minutes of Knockout League for PSVR (Lots of rapid arm swinging, variety of motion), one lap around my block with a 500ml water bottle in each hand.

Intervention Phase II: Went to a nearby gym and had 5 minutes of warmup cardio, then 45 minutes on various upper body weights with extra emphasis on the arms and chest. I did another 15 minutes on the vibration plate afterward.

Change to Diet to Add More Salt

As many who follow me already know, I consume a lot of salt in my normal keto diet, usually targeting about 10g a day (no, that’s not a typo). At the beginning of the washout phase, I was consuming roughly 5g with my meals on top of a Sports Salts supplement of 1.5 servings at the 10am meal.

Alas, this was not enough. I began experiencing leg cramps a couple days in and so added an additional teaspoon (6g) of pink salt to water each day and this resolved the issues.

Staying Consistent Throughout

Here’s a straightforward graphic to illustrate my every day food… (additional water not shown)

A sample of my walking records are here on the right…

But so you know, this is actually wrong. I didn’t average 4.5 miles of walking each day, not even close. However, I don’t mind if the iOS devices are wrong so long as it is consistent in its magnitude of overestimation so I can at least see if my pattern is proving stable.

I did find myself getting anxious for the walk each day. As tedious constants go from one moment to the next, this was always the activity I most looked forward to each day. There were a number of times I wanted to tack on another mile or two.

Sleep Activity

I do want to make note that I haven’t slept for a typical length in a long time, usually averaging five to six hours a night for the last half a year or so. This was true throughout this experiment as well. The only exception was the very last night when it was over and I managed to knock out seven hours. (Probably not a coincidence)

Total and LDL Cholesterol Dropped Following Intervention

First, let’s look at 10am readings and the corresponding pattern shown:

This was taken just before my 10am “feeding” each morning.

These markers mostly represent a single data point. But on “key” days, opted to do several in a row for additional redundancy (such as on the morning following each intervention day) and averaged the result together.

NOTE: In the interest of full disclosure, there was one data point which was excluded due to a poor release from the capillary tube which unsurprisingly resulted in an oddly super low reading relative to the others. However, I’ll be including it anyway in the final raw data spreadsheet for reference which I’ll be releasing in a later post (probably Part II)

As it happened, on the day of the first intervention and thereafter, I decided to add lipid readings from my CardioChek following my other post-wake up measurements (glucose, BHB, weight/composition, and BP). I’ll include those here:

And finally, I decided to do one more chart where I averaged both the morning and 10am readings:

Needless to say, I really, really love these graphs! All that robotic, tedious living from day-to-day really paid off in a big way.

Of course, both Interventions have an almost perfect curvature downward, then upward. I joked to my wife, “these actually look too good. They’re going to think it is fake!” (Of course, I literally have every picture of every CardioChek screen timestamped and in the cloud, so feel free to audit me. 🙂 )

A Morning Triglyceride Spike

If you look closely at triglycerides from both time periods (the morning/wake up vs the 10am readings), you’ll notice an interesting bump. Let’s isolate the morning readings in yellow and the 10am readings in orange:

As you can see, my TGs following that 9/9 intervention was especially high when I woke up, but dropped substantially back to baseline by 10am.

When did I wake up? Well, I always try to make it a rule to take my readings within a half hour of being “fully awake”. Pretty much it’s the first thing I do when I get up — but I’ll concede I often check my phone for a little bit before leaving the bed itself. So the CC times taken each of those mornings were 6:41am, 6:55am, and 6:56am, respectively. Thus, I had about a 3 hour gap between the morning and 10am readings those days.

I’ve had two other occasions where I observed both a morning and 10am reading: The Capstone and Added Sugar Experiments. But this temporary spike was not observed in either one. In fact, my triglycerides very, very rarely climb into the triple digits in the first place, particularly on a very low carb, ketogenic diet.

As my second intervention led to more and longer-lasting soreness given I took to the weights and hammered it out at a gym, I expected a bit more intensive repair. More repair => more LDL needed => more VLDL secretion => more overall TG detected… and cleared rapidly?

This is some good stuff!

Glucose vs Ketones

Here we break the numbers out to a chart:

So my ketones hovered between 1.2 to 1.5 fairly reliably until I hit the first intervention and boom — 2.1 to 2.5 until the 14th, right about when my LDL started to come back up from it’s low of the second intervention.

Not-Quite-Final Thoughts

Without question, this experiment has been very challenging to execute, as all very long experiments typically are. That said, this certainly one of my favorites of all time.

For one, I had been putting off all resistance training for “the next few months” for over two years as I suspected it would impact my lipids. So it was a can I kept kicking down the road while focusing on the set of experiments at hand. Yes, I already had hints I might be right from my marathon training, but how sure could I be?

Moreover, this gives considerable evidence to the pattern I’ve speculated on this entire time as to why many keto bodybuilders will have lower LDL-C/-P than their runner/yoga/cardio counterparts. Can I be sure this is mostly muscle tissue endocytosis? Certainly not. But for me, this is the best evidence I’ve been able to generate to date to demonstrate that possibility.