Fixing The Symptom, As If It Will Help

Someone asked me why I tend not to gain body fat, even when I eat way too much food and take time off from working out. I don’t know why, it’s a complicated question. I have a fast metabolic rate, my body temperature tends to stay stable although I get colder in the winter than many of my peers and my blood levels tend to be in the nominal range. These are observations, not reasons. They are symptoms of something that may be the reason why, but they are NOT the reason why.

This is a silly example of a major challenge in health, wellness, medicine, any field that relies of research to prove that things work or don’t.

Let’s unpack some more. IF someone was to look at my blood levels and make the assumption that all people who have levels similar to mine will get the same results I get, they may progress this line of thinking and make the call that lowering LDL and raising HDH cholesterol will create an internal environment that makes one resistant to fat gain. It’s an easy leap to make because human beings have evolved to see patterns even when a pattern doesn’t exist. It also feels like it could correct and when we look at the cholesterol levels of lean or skinny people, and obese people, there is a trend for the levels to fall within a range for the lean / skinny people and outside of that range for obese people. And the obesity problem has been solved! If we’re able to get an obese persons cholesterol levels into the nominal range they will become lean / skinny.

Except it is bullsh!t. Changing ones cholesterol levels through medication does nothing to their level of body fat and it may not do much of anything other than lower their cholesterol level. This example is simply used as an illustration and I am not implying that taking medication to lower cholesterol will directly impact body fat levels.

The problem with using a change in a biological marker as an indication that something will have a real world outcome (other than just a change in the biological marker) is that is relies on correlation vs. causation. There are 1000’s of things that cause changes in biological markers but have no impact on the thing they are trying to impact. Imagine, for example, the notion that insulin sensitivity is inversely correlated to increases in fat storage. While it may be true that some people who are obese have lower insulin sensitivity than people who are not obese, any intervention that improves insulin sensitivity will not necessarily lower ones body fat level. Adding body fat and losing body fat are a lot more complicated than just altering insulin sensitivity and altering levels of body fat is, for most people, very challenging in one direction or the other.

I have a tough time gaining body fat and little difficulty dropping it. But I also don’t really enjoy eating a lot of the things that help people gain fat. I don’t feel very good when I eat a lot of sugar and I am prone to chest pains when I overeat in general. All you can eat restaurants are no longer the source of gluttonous joy that they were when I was younger.

The opposite is true as well. I have worked with many people who have no difficulty gaining body fat because they have no trouble eating large amounts of the foods that promote fat storage. They don’t experience the negative side effects of eating too much of these foods that I do.

I have little doubt however that if I was to spend a year not moving much while force feeding myself, or they were to spend a year eating and doing the things that have been shown to burn off extra body fat, we would switch places.

So what am I getting at and what should you take our of this post?

Biological markers or surrogate endpoints are useful in researching things that you cannot ethically control for. It would be unethical and immoral to perform a study that used death as the measure of the effectiveness or ineffectiveness of an intervention. In these cases, biological markers / surrogate endpoints are used when strong correlations have been demonstrated between the marker and the real world outcome that is being investigated. Imagine creating a double blind randomized placebo control group designed study to measure the effects of alcohol and driving deaths. While the study would be very simple to design and could yield high quality data, it wouldn’t be ethical, moral or legal to get people drunk and let them drive their cars around. In this case, the surrogate endpoint that is used is reaction time in a task that is performed while sitting down given the correlation between slowed reaction time and car accidents. This way no one is put at unnecessary or unreasonable risk.

Biological markers have a place in research and are not necessarily bad or indicative of a poorly designed or performed study. BUT if they are unnecessary, if the real life outcome can be measured without undo harm and a surrogate endpoint was used, be weary of the conclusions that are drawn. More importantly, be cautions of how these studies are used as evidence that product / compound / molecule X is effective at causing an impact on something. A good example is antioxidant supplementation as a way reduce cancer risk. It is true that people who have a diet that is high in vegetables tend to have lower incidents of cancer and that vegetables are high in antioxidants. But the studies testing the effectiveness of antioxidant pills indicate that they are not helpful and in some instances increase the incidences of cancer.

By treating the symptom, low levels of antioxidant consumption, you achieve nothing. It may be the whole food that is helpful, it could be another lifestyle factor entirely, but most likely it is a complex combination of things that make the difference. Consume the science directly or with a more critical mind, and do not accept someone else’s interpretation of the conclusions, particularly if they sell the solution.