Back in July of this year (2023) I wrote a blog post about a recent fat loss journey I went on since the beginning of the year ultimately culminating in making a weight cut for a grip competition I was planning on competing in.
Since writing that post I have been in “maintenance mode” from a body weight point of view. My primary focus after cutting weight for the grip competition was to focus more on some obstacle course races I had planned for the remainder of the summer and into the fall. While I was not making an effort to gain/lose any weight (I certainly didn’t want to lose any more) I just fell into a comfortable eating pattern that kept me full and satisfied while maintaining my weight.
For the most part I maintained my weight pretty much within the 146-150 range up until the writing of this blog post in November of 2023.
With my obstacle course racing season over at the beginning of November and winter around the corner, it was time to think of some offseason goals. After discussing things with my coach we decided it would be a good time to focus on adding muscle mass.
Being the health and data nerd I am, I want to have some metrics to go along with changes I was about to embark on over the next several months.
So over the past few weeks I had 3 tests done:
- A DEXA scan to assess how much fat and muscle I currently have.
- A comprehensive blood panel to check on different health markers.
- A resting metabolic rate test to see where my metabolism is at.
What I saw in the results of these tests were not surprising to me. The reason I want to share the results with you is because it illustrates some of the things we hear that are associated with fat loss and the cost of trying to be lean. I also want to use it to dispel myths around fat loss and what is and is not possible. While this is my own personal experience, it only applies to me and my unique body. I thought it would be informative to see how other people approach fat loss, the cost of losing body fat, and give you some hope in your own fat loss journey.
With all that said, let’s dive into some of the data…time to get nerdy!
First I want to start off with some of the data from my blood work. For context I include results from blood work I had in January of 2023. On the day I had my blood drawn in January I weighed 163 pounds eating roughly 3000+ calories a day. My macros were 141 grams of protein, 350-400 grams of carbs, and the rest of the calories in fat. That was near my peak caloric intake during my last lean mass gaining phase from the winter of 2022-2023.
On the day I had my blood drawn in October 2023 I weighed 148 pounds eating roughly 2000+ calories a day. My macros were 141 grams of protein, 150-200 grams of carbs and the rest of the calories in fat.
I was down around 15 pounds and consuming roughly 1000 less calories a day between these two blood draws.
With that context in mind let’s look at some of my blood work.
Despite consuming close to 400 grams of carbs a day in January my blood sugar markers were all within the optimal ranges. As you would expect they were a little higher in January but still within normal ranges so it is no surprise that in October they still looked good.
Next let’s jump to my thyroid markers. Here is where you can really start to see a change due to my caloric deficit. I have measured these same thyroid markers for years now, and they are always notoriously low. However in January they looked the best they have ever looked. I was pumped to see those numbers! I knew it actually had to do with the amount of food I was eating at the time. I was clearly in a surplus of calories (on purpose) and my body was relatively happy from a thyroid point of view.
Going into my blood draw in October I was ready to see those numbers fall back outside the optimal ranges…and sure enough that is what I saw.
Another set of markers that is often affected by diet is your lipid markers. My total cholesterol is always over 200 (the conventional cutoff for high cholesterol) and my LDL is always “high” as well. Of course in the conventional sense most medical professionals would be alarmed at this and I can’t blame them. However at the same time they don’t see “high cholesterol” numbers and then also see low blood sugar markers, low inflammation, low triglycerides and high HDL (“the good cholesterol”) like I do.
We know high cholesterol, high inflammation, out of control blood sugar numbers, high triglycerides, and low HDL is asking for trouble from a cardiovascular point of view. What is not clear is whether high cholesterol without the other markers out of range is bad?
This topic is super complex, and I don’t know the right answer. However the one thing I know is that my 289 total cholesterol I had in October is partly due to the downstream effects of my lower thyroid hormones. Thyroid hormones are responsible for clearing cholesterol (Effects of Thyroid Dysfunction on Lipid Profile, n.d.). A 289 cholesterol number is higher than I would like, but I know it would be lower if my thyroid numbers were also better.
Also note the lower triglyceride number. In January having a triglyceride level of 93 was “high” for me, but that was driven by the caloric surplus I was in. It was still optimal but approaching 100 shows how I was pushing the calories. The drop down to 71 is more “normal” triglyceride number for me.
Overall though these numbers from October are not or less in line with my “norms”.
These next few markers, white and red blood cells, hemoglobin and hematocrit are somewhat interesting. Like my thyroid numbers they are also generally low, but they look OK in January at a higher calorie intake. Like my thyroid markers, in my October blood draw they all fell outside the optimal ranges.
As an athlete, these numbers are especially concerning because your red blood cells are responsible for carrying nutrients to your muscles to fuel exercise. Hemoglobin is part of the red blood cell and is responsible for carrying oxygen to the muscle. Having low red blood cells and low hemoglobin is probably negatively affecting my athletic performance.
So why are these numbers lower? I think the red blood cell count (and therefore the hemoglobin and hematocrit numbers) also have to do with the lower thyroid numbers. Thyroid hormones play a crucial role in blood cell production (Mohammed, 2020).
https://www.hindawi.com/journals/ije/2015/292574/fig1/
I don’t really have a good explanation for the low white blood cell numbers, someone smarter than me might be able to figure that out, but I have yet to come up with an answer.
Finally we have my testosterone numbers. While the testosterone is not bad in October, it is lower than it was back in January. Again this is likely due to the lack of calories (Long-Term Effects of Calorie Restriction on Serum Sex Hormone Concentrations in Men, 2010).
So at a high level what is happening here?
In my opinion this is an example of what is called low energy availability (LEA). I have written about LEA in the past. Essentially you can think of LEA as a state in which the body is not given enough energy to maintain everything it needs to run optimally. To dive into this low energy availability state in more detail involves a longer discussion around my exercise, metabolic rate, and the food I was eating. That deserves its own blog post so I will cover all of that in my next blog post. To be the first to know when it is published be sure to sign up for my newsletter using the form below and I will email you as soon as it is available. In the meantime if you have any questions or comments on my blood work please leave them in the comments below.
References
Effects of Thyroid Dysfunction on Lipid Profile. (n.d.). NCBI. Retrieved November 6, 2023, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3109527/
Long-term effects of calorie restriction on serum sex hormone concentrations in men. (2010, January 20). NCBI. Retrieved November 8, 2023, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3569090/
Mohammed, A. A. (2020, July 11). Effects of thyroid dysfunction on hematological parameters: Case controlled study. NCBI. Retrieved November 8, 2023, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374177/
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