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Is Obesity Caused by a Virus?

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I’ve recently taken a large interest in the human microbiome and parasites and their relationship with how we behave. There are certain parasites that can and do have an effect on human behavior, and they also reduce or increase certain microbes, some of which are important for normal functioning. What I’m going to write may seem weird and counter-intuitive to the CI/CO (calories in/calories out) model, but once you understand how the diversity in the human mirobiome matters for energy acquisiton, then you’ll begin to understand how the microbiome contributes to the exploding obesity rate in the first world.

One of the books I’ve been reading about the human microbiome is 10% Human: How Your Body’s Microbes Hold the Key to Health and Happiness. P.h.D. in evolutionary biology Alanna Collen outlines how the microbiome has an effect on our health and how we behave. Though one of the most intriquing things I’ve read in the book so far is how there is a relationship with microbiome diversity, obesity and a virus.

Collen (2014: 69) writes:

But before we get too excited about the potential for a cure for obesity, we need to know how it all works. What are these microbes doing that make us fat? Just as before, the microbiotas in Turnbaugh’s obese mice contained more Firmicutes and fewer Bacteroidetes, and they somehow seemed to enable the mice to extract more energy from their food. This detail undermines one of the core tenets of the obesity equation. Counting ‘calories-in’ is not as simple as keeping track of what a person eats. More accurately, it is the energy content of what a person absorbs. Turnbaugh calculated that the mice with the obese microbiota were collecting 2 per cent more calories from their food. For every 100 calories the lean mice extracted, the obese mice squeezed out 102.

Not much, perhaps, but over the course of a year or more, it adds up. Let’s take a woman of average height. 5 foot 4 inches, who weights 62 kg (9st 11 lb) and a healthy Body Mass Index (BMI: weight (kg) /(height (m)^2) of 23.5. She consumes 2000 calories per day, but with an ‘obese’ microbiota, her extra 2 per cent calorie extraction adds 40 more calories each day. Without expending extra energy, those further 40 calories per day should translate, in theory at least, to a 1.9 kg weight gain over a year. In ten years, that’s 19 kg, taking her weight to 81 kg (12 st 11 lb) and her BMI to an obese 30.7. All because of just 2 percent extra calories extracted from her food by her gut bacteria.

Turnbaugh et al (2006) showed that differing microbiota contributes to differing amounts of weight gain. The obese microbiome does have a greater capacity to extract more energy out of the same amount of food in comparison to the lean microbiome. This implies that obese people would extract more energy eating the same food as a lean person—even if the so-called true caloric value on the package from a caloriometer says otherwise. How much energy we absorb from the food we consume comes down to genes, but not the genes you get from your parents; it matters which genes are turned on or off. Our microbes also control some of our genes to suit their own needs—driving us to do things that would benefit them.

Gut microbiota does influence gene expression (Krautkramer et al, 2016). This is something that behavioral geneticists and psychologists need to look into when attempting to explain human behavior, but that’s for another day. Fact of the matter is, where the energy that’s broken down from the food by the microbiome goes is dictated by genes; the expression of which is controlled by the microbiome. Certain microbiota have the ability to turn up production in certain genes that encourage more energy to be stored inside of the adipocite (Collen, 2014: 72). So the ‘obese’ microbiota, mentioned previously, has the ability to upregulate genes that control fat storage, forcing the body to extract more energy out of what is eaten.

Indian doctor Nikhil Dhurandhar set out to find out why he couldn’t cure his patients of obesity, they kept coming back to him again and again uncured. At the time, an infectious virus was wiping out chickens in India. Dhurandhar had family and friends who were veteraniarians who told him that the infected chickens were fat—with enlarged livers, shrunken thymus glands and a lot of fat. Dhurandhar then took chickens and injected them with the virus that supposedly induced the weight gain in the infected chickens, and discovered that the chickens injected with the virus were fatter than the chickens who were not injected with it (Collen, 2014: 56).

Dhurandhar, though, couldn’t continue his research into other causes for obesity in India, so he decided to relocate his family to America, as well as studing the underlying science behinnd obesity. He couldn’t find work in any labs in order to test his hypothesis that a virus was responsible for obesity, but right before he was about to give up and go back home, nutrional scientist Richard Atkinson offered him a job in his lab. Though, of course, they were not allowed to ship the chicken virus to America “since it might cause obesity after all” (Collen, 2014: 75), so they had to experiment with another virus, and that virus was called adenovirus 36—Ad-36 (Dhurandhar et al, 1997Atkinson et al, 2005; Pasarica et al, 2006;  Gabbert et al, 2010Vander Wal et al, 2013;  Berger et al, 2014; Pontiero and Gnessi, 2015; Zamrazilova et al. 2015).

Atkinson and Dhurandhar injected one group of chickens with the virus and had one control group. The infected chickens did indeed grow fatter than the ones who were not infected. However, there was a problem. Atkinson and Dhurandhar could not outright infect humans with Ad-36 and test them, so they did the next best thing: they tested their blood for Ad-36 antibodies. 30 percent of obese testees ended up having Ad-36 antibodies whereas only 11 percent of the lean testees had it (Collen, 2014: 77).

So, clearly, Ad-36 meddles with the body’s energy storage system. But we currently don’t know how much this virus contributes to the epidemic. This throws the CI/CO theory of obesity into dissarray, proving that stating that obesity is a ‘lifestyle disease’ is extremely reductionist and that other factors strongly influence the disease.

On the mechanisms of exactly how Ad-36 influences obesity:

The mechanism in which Ad-36 induces obesity is understood to be due to the viral gene, E4orf1, which infects the nucleus of host cells. E4orf1 turns on lipogenic (fat producing) enzymes and differentiation factors that cause increased triglyceride storage and differentiation of new adipocytes (fat cells) from pre-existing stem cells in fat tissue.

We can see that there is a large variation in how much energy is absorbed by looking at one overfeeding study. Bouchard et al (1990) fed 12 pairs of identical twins 1000 kcal a day over their TDEE, 6 days per week for 100 days. Each man ate about 84,000 kcal more than their bodies needed to maintain their previous weight. This should have translated over to exactly 24 pounds for each individual man in the study, but this did not turn out to be the case. Quoting Collen (2014: 78):

For starters, even the average amount the men gained was far less than maths dictates that it should have been, at 18 lb. But the individual gains betray the real failings of applying a mathematical rule to weight loss. The man who gained the least managed only 9 lb — just over a third of the predicted amount. And the twin who gained the most put on 29 lb — even more than expected. These values aren’t ’24 lb, more or less’, they are so far wide of the mark that using it even as a guide is purposeless.

This shows that, obviously, the composition of the individual microbiome contributes to how much energy is broken down in the food after it is consumed.

One of the most prominent microbes that shows a lean/obese difference is one called Akkermansia micinphilia. The less Akkermensia one has, the more likely they are to be obese. Akkermansia comprise about 4 percent of the whole microbiome in lean people, but they’re almost no where to be found in obese people. Akkermansia lives on the mucus lining of the stomach, which prevents the Akkermansia from crossing over into the blood. Further, people with a low amount of this bacterium are also more likely to have a thinner mucus layer in the gut and more lipopolysaccharides in the blood (Schneeberger et al, 2015). This one species of microbiota is responsible for dialing up gene activity which prevents LPS from crossing into the blood along with more mucus to live on. This is one example of the trillions of the bacteria in our microbiome’s ability to upregulate the expression of genes for their own benefit.

Everard et al (2013) showed that by supplementing the diets of a group of mice with Akkermensia, LPS levels dropped, their fat cells began creating new cells and their weight dropped. They conclude that the cause of the weight gain in the mice was due to increased LPS production which forced the fat cell to intake more energy and not use it.

There is evidence that obesity spreads in the same way that an epidemic does. Christakis and Fowler (2007) followed over 12000 people from 1971 to 2003. Their main conclusion was that the main predictor of weight gain for an individual was whether or not their closest loved one had become obese. One’s chance of becoming obese increased by a staggering 171 percent if they had a close friend who had become obese in the 32 year time period, whereas among twins, if one twin became obese there was a 40 percent chance that the co-twin would become obese and if one spouse became obese, the chance the other would become obese was 37 percent. This effect also did not hold for neighbors, so something else must be going in (i.e., it’s not the quality of the food in the neighborhood). Of course when obesogenic environments are spoken of, the main culprits are the spread of fast food restaurants and the like. But in regards to this study, that doesn’t seem to explain the shockingly high chance that people have to become obese if their closest loved ones did. What does?

There are, of course, the same old explanations such as sharing food, but by looking at it from a microbiome point of view, it can be seen that the microbiome can and does contribute to adult obesity—due in part to the effect on different viruses’ effects on our energy storage system, as described above. But I believe that introducing the hypothesis that we share microbes with eachother, which also drive obesity, should be an alternate or complimentary explanation.

As you can see, the closer one is with another person who becomes obese, the higher chance they have of also becoming obese. Close friends (and obviously couples) spend a lot of time around each other, in the same house, eating the same foods, using the same bathrooms, etc. Is it really an ‘out there’ to suggest that something like this may also contribute to the obesity epidemic? When taking into account some of the evidence reviewed here, I don’t think that such a hypothesis should be so easily discarded.

In sum, reducing obesity just to CI/CO is clearly erroneous, as it leaves out a whole slew of other explanatory theories/factors. Clearly, our microbiome has an effect on how much energy we extract from our food after we consume it. Certain viruses—such as Ad-36, an avian virus—influence the body’s energy storage, forcing the body to create no new fat cells as well as overcrowding the fat cells currently in the body with fat. That viruses and our diet can influence our microbiome—along with our microbiome influencing our diet—definitely needs to be studied more.

One good correlate of the microbiomes’/virsuses’ role in human obesity is that the closer one is to one who becomes obese, the more likely it is that the other person in the relationship will become obese. And since the chance increases the closer one is to who became obese, the explanation of gut microbes and how they break down our food and store energy becomes even more relevant. The trillions of bacteria in our guts may control our appetites (Norris, Molina, and Gewirtz, 2013; Alcock, Maley, and Atkipis, 2014), and do control our social behaviors (Foster, 2013; Galland, 2014).

So, clearly, to understand human behavior we must understand the gut microbiome and how it interacts with the brain and out behaviors and how and why it leads to obesity. Ad-36 is a great start with quite a bit of research into it; I await more research into how our microbiome and parasites/viruses control our behavior because the study of human behavior should now include the microbiome and parasites/viruses, since they  have such a huge effect on eachother and us—their hosts—as a whole.

Racial Differences in Jock Behavior: Implications for STI Prevalence and Deviance

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The Merriam-Webster dictionary defines jock asa school or college athlete” and “a person devoted to a single pursuit or interest“. This term, as I previously wrote about, holds a lot of predictive power in terms of life success. What kind of racial differences can be found here? Like with a lot of life outcomes/predictors, there are racial differences and they are robust.

Male jocks get more sex, after controlling for age, race, SES and family cohesion. Being involved in sports is known to decrease sexual promiscuity, however, this effect did not hold for black American jocks, with the jock label being associated with higher levels of sexual promiscuity (Miller et al, 2005). Black American jocks reported significantly higher levels of sexual activity than non-black jocks, but they did not find that white jocks too fewer risks than their non-jock counterparts.

Black Americans do have a higher rate of STDs compathe average population (Laumann et al, 1999Cavanaugh et al, 2010; CDC, 2015). Black females who are enrolled in, or have graduated from college had a higher STI (sexually transmitted infection) rate (12.4 percent self-reported; 13.4 percent assayed) than white women with less than a high school diploma (6.4 percent self-reported; 2.3 percent assayed) (Annang et al, 2010). I would assume that these black women would be more attracted to black male jocks and thusly would be more likely to acquire STIs since black males who self-identify as jocks are more sexually promiscuous. It seems that since black male jocks—both in high school and college—are more likely to be sexually promiscuous, this then has an effect on even the college-educated black females, since higher educational status has one less likely to acquire STIs.

Whites use the ‘jock identity’ in a sports context whereas blacks use the identity in terms of the body. Black jocks are more promiscuous and have more sex than white jocks, and I’d bet that black jocks have more STDs than white jocks since they are more likely to have sex than white jocks. Jock identity—but not athletic activity and school athlete status—was a better predictor of juvenile delinquency in a sample of 600 Western New York students, which was robust across gender and race (Miller et al, 2007a). Though, surprisingly, the ‘jock effect’ on crime was not as you would expect it: “The hypothesis that effects would be stronger for black adolescents than for their white counterparts, derived from the work of Stark et al. 1987 and Hughes and Coakley (1991), was not supported. In fact, the only clear race difference that did emerge showed a stronger effect of jock identity on major deviance for whites than for blacks” (Miller et al, 2007a).

Miller et al (2007b) found that the term jock means something different to black and white athletes. For whites, the term was associated with athletic ability and competition, whereas for blacks the term was associated with physical qualities. Whites, though, were more likely to self-identify with the label of jock than blacks (37 percent and 22 percent respectively). They also found that binge drinking predicted violence amongst family members, but in non-jocks only. The jock identity, for whites and not blacks, was also associated with more non-family violence while whites were more likely to use the aggression from sports in a non-sport context in comparison to blacks.

For black American boys, the jock label was a predictor of promiscuity but not for dating. For white American jocks, dating meant more than the jock label. Miller et al (2005) write:

We suggest that White male jocks may be more likely to be involved in a range of extracurricular status-building activities that translate into greater popularity overall, as indicated by more frequent dating; whereas African American male jocks may be “jocks” in a more narrow sense that does not translate as directly into overall dating popularity. Furthermore, it may be that White teens interpret being a “jock” in a sport context, whereas African American teens see it more in terms of relation to body (being strong, fit, or able to handle oneself physically). If so, then for Whites, being a jock would involve a degree of commitment to the “jock” risk-taking ethos, but also a degree of commitment to the conventionally approved norms with sanctioned sports involvement; whereas for African Americans, the latter commitment need not be adjunct to a jock identity.

It’s interesting to speculate on why whites would be more prone to risk-taking behavior than blacks. I would guess that it has something to do with their perception of themselves as athletes, leading to more aggressive behavior. Though certain personalities would be more likely to be athletic and thusly refer to themselves as a jock. The same would hold true for somatype as well.

So the term jock seems to mean different things for whites and blacks, and for whites, leads to more aggressive behavior in a non-sport context.

Black and females who self-identified as jocks reported lower grades whereas white females who self-identified as jocks reported higher grades than white females who did not self-report as jocks (Miller et al, 2006). Jocks also reported more misconduct such as skipping school, cutting class, being sent to the principals office, and parents having to go to the school for a disciplinary manner compared to non-jocks. Boys were more likely to engage in actions that required disciplinary intervention in comparison to girls, while boys were also more likely to skip school, have someone called from home and be sent to the principal’s office. Blacks, of course, reported lower grades than whites but there was no significant difference in misconduct by race. However, blacks reported fewer absences but more disciplinary action than whites, while blacks were less likely to cut class, but more likely to have someone called from home and slightly more likely to be sent to the principal’s office (Miller et al, 2006).

This study shows that the relationship between athletic ability and good outcomes is not as robust as believed. Athletes and jocks are also different; athletes are held in high regard in the eyes of the general public while jocks are seen as dumb and slow while also only being good at a particular sport and nothing else. Miller et al (2006) also state that this so-called ‘toxic jock effect‘ (Miller, 2009Miller, 2011) is strongest for white boys. Some of these ‘effects’ are binge drinking and heavy drinking, bullying and violence, and sexual risk-taking. Though Miller et al (2006) say that, for this sample at least, “It may be that where academic performance is concerned, the jock label constitutes less of a departure from the norm for white boys than it does for female or black adolescents, thus weakening its negative impact on their educational outcomes.

The correlation between athletic ability and jock identity was only .31, but significant for whites and not blacks (Miller et al, 2007b). They also found, contrary to other studies, that involvement in athletic programs did not deter minor and major adolescent crime. They also falsified the hypothesis that the ‘toxic jock effect’ (Miller, 2009; Miller, 2011) would be stronger for blacks than whites, since whites who self-identified as jocks were more likely to engage in delinquent behavior.

In sum, there are racial differences in ‘jock’ behavior, with blacks being more likely to be promiscuous while whites are more likely to engage in deviant behavior. Black women are more likely to have higher rates of STIs, and part of the reason is sexual activity with black males who self-identify as jocks, as they are more promiscuous than non-jocks. This could explain part of the difference in STI acquisition between blacks and whites. Miller et al argue to discontinue the use of the term ‘jock’ and they believe that if this occurs, deviant behavior will be curbed in white male populations that refer to themselves as ‘jocks’. I don’t know if that will be the case, but I don’t think there should be ‘word policing’, since people will end up using the term more anyway. Nevertheless, there are differences between race in terms of those that self-identify as jocks which will be explored more in the future.

Nerds vs. Jocks: Different Life History Strategies?

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I was alerted to a NEEPS (Northeastern Evolutionary Psychology Society) conference paper, and one of the short abstracts of a talk had a bit about ‘nerds’, ‘jocks’, and differing life history strategies. Surprisingly, the results did not line up with current stereotypes about life outcomes for the two groups.

The Life History of the Nerd and Jock: Reproductive Implications of High School Labels

The present research sought to explore whether labels such as “nerd” and “jock” represent different life history strategies. We hypothesized that self-identified nerds would seek to maximize future reproductive success while the jock strategy would be aimed at maximizing current reproductive success. We also empirically tested Belsky’s (1997) theory of attachment style and life history. A mixed student/community sample was used (n=312, average age = 31) and completed multiple questionnaires on Survey Monkey. Dispelling stereotypes, nerds in high school had a lower income and did not demonstrate a future orientation in regards to reproductive success, although they did have less offspring. Being a jock in high school was related to a more secure attachment style, higher income, and higher perceived dominance. (NEEPS, 2017: 11)

This goes against all conventional wisdom; how could ‘jocks’ have better life outcomes than ‘nerds’, if the stereotype about the blubbering idiot jock is supposedly true?

Future orientation is The degree to which a collectivity encourages and rewards future-oriented behaviors such as planning and delaying gratification (House et al, 2004,p. 282). So the fact that self-reported nerds did not show future orientation in regards to reproductive success is a blow to some hypotheses, yet they did have fewer children.

However, there are other possibilities that could explain why so-called nerds have fewer children, for instance, they could be seen as less attractive and desirable; could be seen as anti-social due to being, more often than not, introverted; or they could just be focusing on other things, and not worrying about procreating/talking to women so they end up have fewer children as result. Nevertheless, the fact that nerds ended up having lower income than jocks is pretty telling (and obvious).

There are, of course, numerous reasons why a student should join a sport. One of the biggest is that the skills that are taught in team sports are most definitely translatable to the real world. Most notably, one who plays sports in high school may be a better leader and command attention in a room, and this would then translate over to success in the post-college/high school world. The results of this aren’t too shocking—to people who don’t have any biases, anyway.

Why may nerds in high school have had lower income in adulthood? One reason could be that the social awkwardness did not translate into dollar signs after high school/college graduation, or chose a bad major, or just didn’t know how to translate their thoughts into real-world success. Athletes, on the other hand, have the confidence that comes from playing sports and they know how to work together with others as a cohesive unit in comparison to nerds, who are more introverted and shy away from being around a lot of people.

Nevertheless, this flew in the faces of the stereotypes of nerds having greater success after college while the jocks—who (supposedly) don’t have anything beyond their so-called ‘primitive’ athletic ability—had greater success and more money. This flies in the face of what others have written in the past about how nerds don’t have greater success relative to the average population, well this new presentation says otherwise. Thinking about the traits that jocks have in comparison to nerds, it doesn’t seem so weird that jocks would have greater life outcomes in comparison to nerds.

Self-reported nerds, clearly, don’t don’t have the confidence to make the stratospheric amounts of cash that people would assume that they should make because they are knowledgeable in a few areas, on the contrary. Those who could use their body’s athletic ability had more children as well as had greater life success than nerds, which of course flew in the face of stereotypes. Certain stereotypes need to go, because sometimes stereotypes do not tell the truth about some things; it’s just what people believe ‘sounds good’ in their head.

If you think about what it would take, on average, to make more money and have great success in life after high school and college, you’ll need to know how to talk to people and how to network, which the jocks would know how to do. Nerds, on the other hand, who are more ‘socially isolated’ due to their introverted personality, would not know too much about how to network and how to work together with a team as a cohesive unit. This, in my opinion, is one reason why this was noticed in this sample. You need to know how to talk to people in social settings and nerds wouldn’t have that ability—relative to jocks anyway.

Jocks, of course, would have higher perceived dominance since athletes have higher levels of testosterone both at rest and exhaustion (Cinar et al, 2009). Athletes, of course, would have higher levels of testosterone since 1) testosterone levels rise during conflict (which is all sports really are, simulated conflict) and 2) dominant behavior increases testosterone levels (Booth et al, 2006). So it’s not out of the ordinary that jocks were seen as more dominant than their meek counterparts. In these types of situations, higher levels of testosterone are needed to help prime the body for what it believes is going to occur—competition. Coupled with the fact that jocks are constantly in situations where dominance is required; engage in more physical activity than the average person; and need to keep their diet on point in order to maximize athletic performance, it’s no surprise that jocks showed higher dominance, as they do everything right to keep testosterone levels as high as possible for as long as possible.

I hope there are videos of these presentations because they all seem pretty interesting, but I’m most interested in locating the video for this specific one. I will update on this if/when I find a video for this (and the other presentations listed). It seems that these labels do have ‘differing life history strategies’, and, despite what others have argued in the past about nerds having greater success than jocks, the nerds get the short end of the stick.

Why Are People Afraid of Testosterone?

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The answer to the question of why people are afraid of testosterone is very simple: they do not understand the hormone. People complain about birth rates and spermatogenesis, yet they believe that having high testosterone makes one a ‘savage’ who ‘cannot control their impulses’. However, if you knew anything about the hormone and how it’s vital to normal functioning then you would not say that.

I’ve covered why testosterone does not cause crime by looking at the diurnal variation in the hormone, showing that testosterone levels are highest at 8 am and lowest at 8 pm, while children commit the most crimes at 3 pm and adults at 10 pm. The diurnal variation is key: if testosterone truly did cause crime then rates of crime would be higher in both children and adults in the morning; yet, as can be seen with children, there are increases in amounts of violence committed when they enter school, go to recess, and exit school. This shows why those times are related to the spike in crime in children.

I have wrote a previous article citing a paper by Book et al (2001) in which they meta-analyzed testosterone studies and found that the correlation between testosterone and aggression was .14. However, that estimate is too high since they included 15 studies that should have not been included in the analysis. The true correlation is .08 (Archer, Graham-Kevan, and Davies, 2004). So, clearly, along with the fact that the diurnal variation in testosterone does not correlate with crime spikes, it shows that testosterone has no relationship to the cause of crime; it’s just always at the scene because it prepares the body to deal with a threat. That does not mean that testosterone itself causes crime.

One main reason people fear testosterone and believe that it causes crime and by extension aggressive behavior is because of racial crime disparities. According to the FBI, black Americans by and large commit the most crime, despite being 13 percent of the US population. And since it has been reported that blacks have higher levels of testosterone (Ross et al, 1986; Lynn, 1992; Rushton, 1997; Ellis, 2017), people believe that the supposed higher levels of testosterone that blacks, on average, have circulating in their blood is the ultimate cause of the crime disparities in America between races. Though see above to see why this is not the ultimate cause.

Blacks, contrary to popular belief, don’t have higher levels of testosterone (Gasper et al, 2006; Rohrrman et al, 2007; Lopez et al, 2013; Richard et al, 2014). Even if they did have higher levels, say the 13 percent that is often cited, it would not be the cause of higher rates of crime, nor the cause of higher rates of prostate cancer in blacks compared to whites. What does cause part of the crime differential, in my opinion, is honor culture (Mazur, 2016). The blacks-have-higher-testosterone canard was pushed by Rushton and Lynn to explain both higher rates of prostate cancer and crime in black Americans, however I have shown that high levels of testosterone do not cause prostate cancer (Stattin et al, 2003; Michaud, Billups, and Partin, 2015). Looking to testosterone as a ‘master switch’ as Rushton called it is the wrong thing to research because, clearly, the theories of Lynn, Rushton, and Ellis have been rebutted.

People are scared of testosterone because they do not understand the hormone. Indeed, people complain about lower birth rates and lower sperm counts, yet believe that having high testosterone will cause one to be a high T savage. This is seen in the misconception that injecting anabolic steroids causes higher levels of aggression. One study looked at the criminal histories of men who self-reported drug use and steroid use Lundholm et al (2014) who conclude: “We found a strong association between self-reported lifetime AAS use and violent offending in a population-based sample of more than 10,000 men aged 20-47 years. However, the association decreased substantially and lost statistical significance after adjusting for other substance abuse. This supports the notion that AAS use in the general population occurs as a component of polysubstance abuse, but argues against its purported role as a primary risk factor for interpersonal violence. Further, adjusting for potential individual-level confounders initially attenuated the association, but did not contribute to any substantial change after controlling for polysubstance abuse.

The National Institute of Health (NIH) writes: “In summary, the extent to which steroid abuse contributes to violence and behavioral disorders is unknown. As with the health complications of steroid abuse, the prevalence of extreme cases of violence and behavioral disorders seems to be low, but it may be underreported or underrecognized.” We don’t know whether steroids cause aggression or more aggressive athletes are more likely to use the substance (Freberg, 2009: 424). Clearly, the claims of steroids causing aggressive behavior and crime are overblown and there has yet to be a scientific consensus on the matter. A great documentary on the matter is Bigger, Stronger, Faster, which goes through the myths of testosterone while chronicling the use of illicit drugs in bodybuilding and powerlifting.

People are scared of the hormone testosterone—and by extent anabolic steroids—because they believe the myths of the hulking, high T aggressive man that will fight at the drop of the hat. However, reality is much more nuanced than this simple view and psychosocial factors must also be taken into account. Testosterone is not the ‘master switch’ for crime, nor prostate cancer. This is very simply seen with the diurnal variation of the hormone as well as the peak hours for crime in adolescent and adult populations. The extremely low correlation with aggression and testosterone (.08) shows that aggression is mediated by numerous other variables other than testosterone, and that testosterone alone does not cause aggression, and by extension crime.

People fear things they don’t understand and if people were to truly understand the hormone, I’m sure that these myths pushed by people who are scared of the hormone will no longer persist. Low levels of testosterone are part of the cause of our fertility problems in the West. So does it seem logical to imply that high testosterone is for ‘savages’, when, clearly, high levels of testosterone are needed for spermatogenesis which, in turn, would mean a higher birth rate? Anyone who believes that testosterone causes aggression and crime and that the injection of anabolic steroids causes ‘roid rage’ should do some reading on how the production of the hormone in the body as well as the literature on anabolic steroids. If one wants birth rates to increase in the West, then they must also want testosterone levels to increase as well, since they are intimately linked.

Testosterone does not cause crime and there is no reason to fear the hormone.

Diet and Exercise: Don’t Do It? Part II

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In part II, we will look at the mental gymnastics of someone who is clueless to the data and uses whatever mental gymnastics possible in order to deny the data. Well, shit doesn’t work like that, JayMan. I will review yet more studies on sitting, walking and dieting on mortality as well as behavioral therapy (BT) in regards to obesity. JayMan has removed two of my comments so I assume the discussion is over. Good thing I have a blog so I can respond here; censorship is never cool. JayMan pushes very dangerous things and they need to be nipped in the bud before someone takes this ‘advice’ who could really benefit from lifestyle alterations. Stop giving nutrition advice without credentials! It’s that simple.

JayMan published a new article on ‘The Five Laws of Behavioral Genetics‘ with this little blip:

Indeed, we see this with health and lifestyle: people who exercise more have fewer/later health problems and live longer, so naturally conventional wisdom interprets this to mean that exercise leads to health and longer life, when in reality healthy people are driven to exercise and have better health due to their genes.

So, in JayMan’s world diet and exercise have no substantial impact on health, quality of life and longevity? Too bad the data says otherwise. Take this example:

Take two twins. Lock both of them in a metabolic chamber. Monitor them over their lives and they do not leave the chamber. They are fed different diets (one has a high-carb diet full of processed foods, the other a healthy diet for whatever activity he does); one exercises vigorously/strength trains (not on the same day though!) while the other does nothing and the twin who exercises and eats well doesn’t sit as often as the twin who eats a garbage diet and doesn’t exercise. What will happen?

Jayman then shows me Bouchard et al, (1990) in which a dozen pairs of twins were overfed for three months with each set of twins showing different gains in weight despite being fed the same amount of kcal. He also links to Bouchard et al, 1996 (can’t find the paper; the link on his site is dead) which shows that the twins returned to their pre-experiment weight almost effortlessly. This, of course, I do not deny.

This actually replicates a study done on prisoners in a Vermont prison (Salans, Horton, and Sims, 1971). “The astonishing overeating paradox” is something that’s well worth a look in to. Salans et al had prisoners overeat and also limited their physical activity. They started eating 4000 kcal per day and by the end of the study they were eating about 10000 kcal per day. But something weird happened: their metabolisms revved up by 50 percent in an attempt to get rid of the excess weight. After the study, the prisoners effortlessly returned to their pre-experiment weight—just like the twins in Bouchard et al’s studies.

The finding is nothing new but it’s nice to have replication (on top of the replication that it already had), but that’s not what I was talking about. Of course, being sedentary, eating like shit and not exercising will lead to deleterious health outcomes. The fact of the matter is, the twin in my thought experiment that did not exercise, sat around all day and ate whatever would die way sooner, have a lower quality of life, and more deleterious disease due to the shitty diet while his co-twin would have less since he ate right, exercised and spent less time sitting.

JayMan says, in regards to studies that show that obese people that even do light physical activity show lower all-cause mortality, that “That’s not what large RCTs show.” I know the study that he’s speaking of—the Look AHEAD study (Action for Health and Diabetes) (The Look AHEAD Research Group, 2009). The research group studied the effects of lifestyle interventions in type II diabetics. For one of the groups they gave intensive diet and exercise information, the other they gave only the standard advice. However, the study ended early at 9.3 years because there was no difference between both groups (Pi-Sunyer, 2015). JayMan uses this study as evidence that diet and exercise have no effect on the mortality of type II diabetics; however, in actuality, the results are much more nuanced.

Annuzzi et al (2014) write in their article The results of Look AHEAD do not row against the implementation of lifestyle changes in patients with type 2 diabetes:

The intervention aimed at weight loss by reducing fat calories, and using meal replacements and, eventually, orlistat, likely underemphasizing dietary composition. There is suggestive evidence, in fact, that qualitative changes in dietary composition aiming at higher consumption of foods rich in fiber and with a high vegetable/animal fat ratio favorably influence CV risk in T2D patients.

In conclusion, the Look AHEAD showed substantial health benefits of lifestyle modifications. Prevention of CV events may need higher attention to dietary composition, contributing to stricter control of CV risk factors. As a better health-related quality of life in people with diabetes is an important driver of our clinical decisions, efforts on early implementation of behavioral changes through a multifactorial approach are strongly justified.

They reduced far calories and used meal replacements. This is the trial JayMan is hedging his assertion on. Type II diabetics need a higher fat diet and don’t need the carbs as it will spike their insulin. Eating a higher fat diet will also lower the rate of CVD as well. This trial wasn’t too vigorous in terms of macronutrient composition. This is one of many reasons why type II diabetics discard dieting and exercise just yet.

Even modest weight loss of 5 to 10 percent is associated with significant improvements in cardiovascular disease (CVD) after one year, with larger weight loss showing better improvement (Wing et al, 2011). (Also read the article The Spinning of Look AHEAD.)

Telling diabetics not to eat right and exercise is, clearly, a recipe for disaster. This canard that dieting/exercise doesn’t work to decrease all-cause mortality—especially for diabetics and others who need the lifestyle interventions—is dangerous and a recipe for disaster.

Intentional weight loss needs to be separated from intentional weight loss as to better study the effects of both variables. Kritchevsky et al (2015) meta-analyzed 15 RCTs that “reported mortality data either as an endpoint or as an adverse event, including study designs where participants were randomized to weight loss or non-weight loss, or weight loss plus a co-intervention (e.g. weight loss plus exercise) or the weight stable co-intervention (i.e. exercise alone).” They conclude that the risk for all-cause mortality in obese people who intentionally lose weight is 15 percent lower than people not assigned to lose weight.

This study replicates a meta-analysis by Harrington, Gibson, and Cottrell (2009) on the benefits of weight loss and all-cause mortality. They noted that in unhealthy adults, weight loss accounted for a 13 percent decrease in all-cause mortality increase while in the obese this accounted for a 16 percent decrease. Of course, since the weights were self-reported and there are problems with self-reports of weight (Mann et al, 2007), then that is something that a skeptic can rightfully bring up. However, it would not be a problem since this would imply that they weighed the same/gained more weight yet had a decrease in all-cause mortality.

Even light physical activity is associated with a decrease in all-cause mortality. People who go from light activity, 2.5 hours a week of moderate physical intensity compared to no activity, show a 19 percent decrease in all-cause mortality while people who did 7 hours a week of moderate activity showed a 24 percent decrease in all-cause mortality (Woodcock et al, 2011). Even something as simple as walking is associated with lower incidence of all-cause mortality, with the largest effect being seen in individuals who went from no activity to light walking. Walking is inversely associated with disease incidence (Harner and Chida, 2008) but their analysis indicated publication bias so further study is needed. Nevertheless, the results line up with what is already known—that low-to-moderate exercise is associated with lower all-cause mortality (as seen in Woodcock et al, 2011).

What is needed to change habits/behavior is behavioral therapy (BT) (Jacob and Isaac, 2012; Buttren, Webb, and Waddren, 2012; Wilfley, Kolko, and Kaas, 2012; ). BT can also be used to increase adherence to exercise (Grave et al, 2011). BT has been shown to have great outcomes in the behaviors of obese people, and even if no weight loss/5-10 percent weight loss is seen (from Wing and Hill, 2001), better habits can be developed, and along with ‘training’ hunger hormones with lifestyle changes such as fasting, people can achieve better health and longevity—despite what naysayers may say. Though I am aware that outside of clinics/facilities, BT does not have a good track record (Foster, Makris, and Bailer, 2005). However, BT is the most studied and effective intervention in managing obesity at present (Levy et al, 2007). This is why people need to join gyms and exercise around people—they will get encouragement and can talk to others about their difficulties. Though, people like JayMan who have no personal experience doing this would not understand this.

In regards to dieting, the effect of macronutrient composition on blood markers is well known. Type II diabetics need to eat a certain diet to manage their insulin/blood sugar, and doing the opposite of those recommendations will lead to disaster.

Low-carb ketogenic diets are best for type II diabetics. There are benefits to having ketones circulating in the blood, which include (but are not limited to): weight loss, improved HbA1c levels, reduced rate of kidney disease/damage, cardiac benefits, reversing non-alcoholic fatty liver, elevated insulin, and abnormal levels of cholesterol in the blood (Westman et al, 2008Azar, Beydoun, and Albadri, 2016Noakes and Windt, 2016Saslow et al, 2017). These benefits, of course, carry over to the general non-diabetic population as well.

Of course, JayMan has reservations about these studies wanting to see follow-ups—but the fact of the matter is this: dieting and eating right is associated with good blood markers, exactly what type II diabetics want. In regards to food cravings, read this relevant article by Dr. Jason Fung: Food CravingsContrary to JayMan’s beliefs, it’s 100 percent possible to manage food cravings and hunger. The hormone ghrelin mediates hunger. There are variations in ghrelin every day (Natalucci et al, 2005) and so if you’re feeling hungry if you wait a bit it will pass. This study lines up with most people’s personal experience in regards to hunger. One would have to have an understanding of how the brain regulates appetite to know this, though.

JayMan also cannot answer simple yes or no questions such as: Are you saying that people should not watch what they eat and should not make an effort to eat higher-quality foods? I don’t know why he is so anti-physical activity. As if it’s so bad to get up, stop sitting so much and do some exercise! People with more muscle mass and higher strength levels live longer (Ruiz et al, 2008). This anti-physical activity crusade makes absolutely no sense at all given the data. If I were to stop eating well and strength training, along with becoming a couch potato, would my chance of dying early from a slew of maladies decrease? Anyone who uses basic logic would be able to infer that the answer is yes.

I also need to address JayMan’s last comment to me which he censored:

No intervention shows that lifestyle changes extend life – or even improve health. Even if they did, their generalizability would depend on their actual prescription. In any case, the point is moot, since they don’t even show such improvements in the first place.

You’re only saying that because you’re literally hand waving away data. It’s clear that going from no exercise to some exercise will decrease all-cause mortality. I’m sorry that you have a problem reading and understanding things that you don’t agree with, but this is reality. You don’t get to construct your own reality using cherry-picked studies that don’t mean what you think they mean (like Look AHEAD; Dr. Sharma states that we may never know if weight reduction can save lives in type II diabetics, however the three studies on low-carb diets cited above lend credence to the idea that we can).

Please see my previously linked Obesity Facts page for more. Once you’ve read that, get back to me. Until then, I’m putting the brakes on this discussion.

Of course, you’re putting the brakes on this discussion, you have substantial replies other than your one-liners. You need to censor people when you have no substantial response, that’s not intellectually honest.

All in all, JayMan is giving very dangerous ‘advice’, when the literature says otherwise in regards to lifestyle interventions and all-cause mortality. You can talk about genes for this or that all you want; you’re just appealing to genes. Light physical exercise shows that mortality risk can be decreased; that’s not too hard for most people.

I know JayMan talks about genes for this and that, yet he does not understand that obesogenic environments drive this epidemic (Lake and Townshend, 2006; Powell, Spears, and Rebori, 2011;  Fisberg et al, 2016). He doesn’t seem to know about the food reward hypothesis of obesity either. Think about obesogenic environments and food reward and how our brains change when we eat sugar and then things will begin to become clearer.

JayMan is giving out deadly ‘advice’, again, without the correct credentials. Clearly, as seen in both of my responses to him, taking that ‘advice’ will lead to lower quality of life and lower life expectancy. But I’m sure my readers are smart enough to not listen to such ‘advice’.

(Note: Diet and exercise under Doctor’s supervision only)