Waist-to-weight ratios in pictures: The John Stone transformation

John Stone is a bodybuilder and founder of a bodybuilding and fitness web site (). There he has provided pictures and stats of his remarkable transformation, which were used to prepare the montage below.



John’s height is reported as 5' 11.5". Below the photos are the months in which they were taken, the waist circumferences in inches, the weights in lbs, and the waist-to-weight ratios (WWRs). Abhi was kind enough to provide a more detailed plot of John Stone’s WWRs ().

Assuming that minimizing one’s WWR is healthy, an idea whose rationale was explained here before (), we could say that John was at his most unhealthy in the photo on the left.

The second photo from the left shows a slightly more healthy state, at a reported 8 percent body fat (his lowest). The two photos on the right represent states in which John’s WWR is at its lowest, namely 0.1544. That is, in these two photos John minimized his WWR; at a reported 14 and 13.8 percent body fat, respectively.

When we look at the WWRs in these photos, it seems that he is only marginally healthier in the second photo from the left than in the leftmost photo. In the two photos on the right, the WWRs are much lower (they are the same), suggesting that he was significantly healthier in those photos.

Interestingly, in both photos on the right John reported to have been at the end of bulking periods. Whenever he entered a cutting period his WWR started going up. This suggests that his ratio of lean body mass to total mass started decreasing just as soon as he started cutting. I suspect the same would happen if he continued gaining weight.

Which of the two photos on the right represents the best state? Assuming that both states are sustainable, over the long run I would argue that the best state is the one where the WWR was minimized with the lowest weight. There whole-day joint stress is lower. This corresponds to the photo at the far right.

By sustainable states I mean states that are not reached through approaches that are unhealthy in the long term; e.g., approaches that place organs under such an abnormal stress that they are damaged over time. This kind of damage is essentially what happens when we become obese – i.e., too fat. One can also become too muscular for his or her own good.

Is Refined Carbohydrate Addictive?

[Note: in previous versions, I mixed up "LGI" and "HGI" terms in a couple of spots.  These are now corrected.  Thanks to readers for pointing them out.]

Recently, a new study was published that triggered an avalanche of media reports suggesting that refined carbohydrate may be addictive:

Refined Carbs May Trigger Food Addiction
Refined Carbs May Trigger Food Addictions
Can You be Addicted to Carbs?
etc.

This makes for attention-grabbing headlines, but in fact the study had virtually nothing to do with food addiction.  The study made no attempt to measure addictive behavior related to refined carbohydrate or any other food, nor did it aim to do so.

So what did the study actually find, why is it being extrapolated to food addiction, and is this a reasonable extrapolation?  Answering these questions dredges up a number of interesting scientific points, some of which undermine popular notions of what determines eating behavior.

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More Thoughts on Cold Training: Biology Chimes In

Now that the concept of cold training for cold adaptation and fat loss has received scientific support, I've been thinking more about how to apply it.  A number of people have been practicing cold training for a long time, using various methods, most of which haven't been scientifically validated.  That doesn't mean the methods don't work (some of them probably do), but I don't know how far we can generalize individual results prior to seeing controlled studies.

The studies that were published two weeks ago used prolonged, mild cold exposure (60-63 F air) to achieve cold adaptation and fat loss (1, 2).  We still don't know whether or not we would see the same outcome from short, intense cold exposure such as a cold shower or brief cold water plunge.  Also, the fat loss that occurred was modest (5%), and the subjects started off lean rather than overweight.  Normally, overweight people lose more fat than lean people given the same fat loss intervention, but this possibility remains untested.  So the current research leaves a lot of stones unturned, some of which are directly relevant to popular cold training concepts.

In my last post on brown fat, I mentioned that we already know a lot about how brown fat activity is regulated, and I touched briefly on a few key points.  As is often the case, understanding the underlying biology provides clues that may help us train more effectively.  Let's see what the biology has to say.

Biology of Temperature Regulation

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Could we have evolved traits that are detrimental to our survival?

Let us assume that we collected data on the presence or absence of a trait (e.g., propensity toward risky behavior) in a population of individuals, as well as on intermediate effects of the trait, downstream effects on mating and survival success, and ultimately on reproductive success (a.k.a. “fitness”, in evolutionary biology).

The data would have been collected over several generations. Let us also assume that we conducted a multivariate analysis on this data, of the same type as the analyses employing WarpPLS that were discussed here in previous posts (). The results are summarized through the graph below.



Each of the numbers next to the arrows in the graph below represents the strength of a cause-effect relationship. The number .244 linking “a” and “y” means that a one standard deviation variation in “a” causes a .244 standard deviation increase in “y”. It also means that a one standard deviation variation in “a” causes a 24.4 percent increase in “y” considering the average “y” as the baseline.

This type of mathematical view of evolution may look simplistic. This is an illusion. It is very general, and encompasses evolution in all living organisms, including humans. It also applies to theoretical organisms where multiple (e.g., 5, 6 etc.) sexes could exist. It even applies to non-biological organisms, as long as these organisms replicate - e.g., replicating robots.

So the trait measured by “a” has a positive effect on the intermediate effect “y”. This variable, “y” in turn has a negative effect on survival success (“s”), and a strong one at that: -.518. Examples: “a” = propensity toward risky behavior, measured as 0 (low) and 1 (high); and “y” = hunting success, measured in the same way. (That is, “a” and “y” are correlated, but “a”=1 does not always mean “y”=1.) Here the trait “a” has a negative effect on survival via its intermediate effect on “y”. If I calculate the total effect of “a” on “w” via the 9 paths that connect these two variables, I will find that it is .161.

The total effect on reproductive success is positive, which means that the trait will tend to spread in the population. In other words, the trait will evolve in the population, even though it has a negative effect on survival. This type of trait is what has been referred to as a “costly” trait ().

Say what? Do you mean to say that we have evolved traits that are unhealthy for us? Yes, I mean exactly that. Is this a “death to paleo” post? No, it is not. I discussed this topic here before, several years ago (). But the existence of costly traits is one of the main reasons why I don’t think that mimicking our evolutionary past is necessarily healthy. For example, many of our male ancestors were warriors, and they died early because of that.

What type of trait will present this evolutionary pattern – i.e., be a costly trait? One answer is: a trait that is found to be attractive by members of the other sex, and that is not very healthy. For example, a behavior that is perceived as “sexy”, but that is also associated with increased mortality. This would likely be a behavior prominently displayed by males, since in most species, including humans, sexual selection pressure is much more strongly applied by females than by males.

Examples would be aggressiveness and propensity toward risky behavior, especially in high-stress situations such as hunting and intergroup conflict (e.g., a war between two tribes) where being aggressive is likely to benefit an individual’s group. In warrior societies, both aggressiveness and propensity toward risky behavior are associated with higher social status and a greater ability to procure mates. These traits are usually seen as male traits in these societies.

Here is something interesting. Judging from our knowledge of various warrior societies, including American plains Indians societies, the main currency of warrior societies were counts of risky acts, not battle effectiveness. Slapping a fierce enemy warrior on the face and living to tell the story would be more valuable, in terms of “counting coup”, than killing a few inexperienced enemy warriors in an ambush.

Greater propensity toward risky behavior among men is widespread and well documented, and is very likely the result of evolutionary forces, operating on costly traits. Genetic traits evolved primarily by pressure on one sex are often present in the other (e.g., men have nipples). There are different grades of risky behavior today. At the high end of the scale would be things that can kill suddenly like race car driving and free solo climbing (, ). (If you'd like to know the source of the awesome background song of the second video linked, here it is: Radical Face's "Welcome Home".)

One interesting link between risky behavior and diet refers to the consumption of omega-6 and omega-3 fats. Risky behavior may be connected with aggressive behavior, which may in turn be encouraged by greater consumption of foods rich in omega-6 fats and avoidance of foods rich in omega-3 fats (, ). This may be behind our apparent preference for foods rich in omega-6 fats, even though tipping the balance toward more foods rich in omega-3 fats would be beneficial for survival. We would be "calmer" though - not a high priority among most men, particularly young men.

This evolved preference may also be behind the appeal of industrial foods that are very rich in omega-6 fats. These foods seem to be particularly bad for us in the long term. But when the sources of omega-6 fats are unprocessed foods, the negative effects seem to become "invisible" to statistical tests.

Reflections on the 2013 Ancestral Health Symposium

I just returned from the 2013 Ancestral Health Symposium in Atlanta.  Despite a few challenges with the audio/visual setup, I think it went well.

I arrived on Thursday evening, and so I missed a few talks that would have been interesting to attend, by Mel Konner, Nassim Taleb, Gad Saad, and Hamilton Stapell.  Dr. Konner is one of the progenitors of the modern Paleo movement.  Dr. Saad does interesting work on consummatory behavior, reward, and its possible evolutionary basis.  Dr. Stapell is a historian with an interest in the modern Paleo movement.  He got some heat for suggesting that the movement is unlikely to go truly mainstream, which I agree with.  I had the opportunity to spend quite a bit of time with him and found him to be an interesting person.

On Friday, Chris Kresser gave a nice talk about the potential hidden costs of eradicating our intestinal parasites and inadvertently altering our gut flora.  Unfortunately it was concurrent with Chris Masterjohn so I'll have to watch his talk on fat-soluble vitamins when it's posted.  I spent most of the rest of the day practicing my talk.

On Saturday morning, I gave my talk "Insulin and Obesity: Reconciling Conflicting Evidence".  I think it went well, and the feedback overall was very positive, both on the content and the delivery.  The conference is fairly low-carb-centric and I know some people disagree with my perspective on insulin, and that's OK.   The-question-and-answer session after the talk was also productive, with some comments/questions from Andreas Eenfeldt and others.  With the completion of this talk, I've addressed the topic to my satisfaction and I don't expect to spend much more time on it unless important new data emerge.  The talk will be freely available online at some point, and I expect it to become a valuable resource for people who want to learn more about the relationship between insulin and obesity.  It should be accessible to anyone with a little bit of background in the subject, but it will also be informative to most researchers.

After my talk, I attended several other good presentations.  Dan Pardi gave a nice talk on the importance of sleep and the circadian rhythm, how it works, how the modern world disrupts it, and how to fix it.  The relationship between sleep and health is a very hot area of research right now, it fits seamlessly with the evolutionary perspective, and Pardi showed off his high level of expertise in the subject.  He included the results of an interesting sleep study he conducted as part of his doctoral work at Stanford, showing that sleep restriction makes us more likely to choose foods we perceive as unhealthy.

Sleep and the circadian rhythm was a recurrent theme at AHS13.  A lot of interesting research is emerging on sleep, body weight, and health, and the ancestral community has been quick to embrace this research and integrate it into the ancestral health template.  I think it's a big piece of the puzzle.

Jeff Rothschild gave a nice summary of the research on time-restricted feeding, body weight and health in animal models and humans.  Research in this area is expanding and the results are pretty interesting, suggesting that when you restrict a rodent's feeding window to the time of day when it would naturally consume food (rather than giving constant access during both day and night), it becomes more resistant to obesity even when exposed to a fattening diet.  Rothschild tied this concept together with circadian regulation in a compelling way.  Since food is one of the stimuli that sets the circadian clock, Rothschild proposes to eat when the sun is up, and not when it's down, synchronizing eating behavior with the natural seasonal light rhythm.  I think it's a great idea, although it wouldn't be practical for me to implement it currently.  Maybe someday if I have a more flexible schedule.  Rothschild is about to publish a review paper on this topic as part of his master's degree training, so keep your eyes peeled.

Kevin Boyd gave a very compelling talk about malocclusion (underdeveloped jaws and crowded teeth) and breathing problems, particularly those occurring during sleep.  Malocclusion is a modern epidemic with major health implications, as Dr. Boyd showed by his analysis of ancient vs. modern skulls.  The differences in palate development between our recent ancestors (less than 200 years ago) and modern humans are consistent and striking, as Weston Price also noted a century ago.  Dr. Boyd believes that changing infant feeding practices (primarily the replacement of breast feeding with bottle feeding) is the main responsible factor, due to the different mechanical stimulation it provides, and he's proposing to test that hypothesis using the tools of modern research.  He's presented his research at prestigious organizations and in high-impact scientific journals, so I think this idea may really be gaining traction.  Very exciting.

I was honored when Dr. Boyd told me that my 9-part series on malocclusion is what got him interested in this problem (1, 2, 3, 4, 5, 6, 7, 8, 9).  His research has of course taken it further than I did, and as a dentist his understanding of malocclusion is deeper than mine.  He's a middle-aged man who is going back to school to do this research, and his enthusiasm is palpable.  Robert Corruccini, a quality anthropology researcher and notable proponent of the idea that malocclusion is a "disease of civilization" and not purely inherited, is one of his advisers.

There were a number of excellent talks, and others that didn't meet my standards for information quality.  Overall, an interesting conference with seemingly less drama than in previous years.

AHS Talk This Saturday

For those who are attending the Ancestral Health Symposium this year, my talk will be at 9:00 AM on Saturday.  The title is "Insulin and Obesity: Reconciling Conflicting Evidence", and it will focus on the following two questions:

1. Does elevated insulin cause obesity; does obesity cause elevated insulin; or both?
2. Is there a unifying hypothesis that's able to explain all of the seemingly conflicting evidence cited by each side of the debate?

I'll approach the matter in true scientific fashion: stating hypotheses, making rational predictions based on those hypotheses, and seeing how well the evidence matches the predictions.  I'll explore the evidence in a way that has never been done before (to my knowledge), even on this blog.

Why am I giving this talk?  Two reasons.  First, it's an important question that has implications for the prevention and treatment of obesity, and it has received a lot of interest in the ancestral health community and to some extent among obesity researchers.  Second, I study the mechanisms of obesity professionally, I'm wrapping up a postdoc in a lab that has focused on the role of insulin in body fatness (lab of Dr. Michael W. Schwartz), and I've thought about this question a lot over the years-- so I'm in a good position to speak about it.

The talk will be accessible and informative to almost all knowledge levels, including researchers, physicians, and anyone who knows a little bit about insulin.  I'll cover most of the basics as we go.  I guarantee you'll learn something, whatever your knowledge level.

We share an ancestor who probably lived no more than 640 years ago

This post is a revised version of a previous post. The original post has been or will be deleted, with the comments preserved. Typically this is done with posts that attract many visits at the time they are published, and whose topics become particularly relevant or need to be re-addressed at a later date.

***

We all evolved from one single-celled organism that lived billions of years ago. I don’t see why this is so hard for some people to believe, given that all of us also developed from a single fertilized cell in just 9 months.

However, our most recent common ancestor is not that first single-celled organism, nor is it the first Homo sapiens, or even the first Cro-Magnon.

The majority of the people who read this blog probably share a common ancestor who lived no more than 640 years ago. Genealogical records often reveal interesting connections - the figure below has been cropped from a larger one from Pinterest.

You and I, whoever you are, have each two parents. Each of our parents have (or had) two parents, who themselves had two parents. And so on.

If we keep going back in time, and assume that you and I do not share a common ancestor, there will be a point where the theoretical world population would have to be impossibly large.

Assuming a new generation coming up every 20 years, and going backwards in time, we get a theoretical population chart like the one below. The theoretical population grows in an exponential, or geometric, fashion.

As we move back in time the bars go up in size. Beyond a certain point their sizes go up so fast that you have to segment the chart. Otherwise the bars on the left side of the chart disappear in comparison to the ones on the right side (as several did on the chart above). Below is the section of the chart going back to the year 1371.

The year 1371 is a mere 640 years ago. And what is the theoretical population in that year if we assume that you and I have no common ancestors? The answer is: more than 8.5 billion people. We know that is not true.

Admittedly this is a somewhat simplistic view of this phenomenon, used here primarily to make a point. For example, it is possible that a population of humans became isolated 15 thousand years ago, remained isolated to the present day, and that one of their descendants just happened to be around reading this blog today.

Perhaps the most widely cited article discussing this idea is this one by Joseph T. Chang, published in the journal Advances in Applied Probability. For a more accessible introduction to the idea, see this article by Joe Kissell.

Estimates vary based on the portion of the population considered. There are also assumptions that have to be made based on migration and mating patterns, as well as the time for each generation to emerge and the stability of that number over time.

Still, most people alive today share a common ancestor who lived a lot more recently than they think. In most cases that common ancestor probably lived less than 640 years ago.

And who was that common ancestor? That person was probably a man who, due to a high perceived social status, had many consorts, who gave birth to many children. Someone like Genghis Khan.