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The ENA Theory: On Testosterone and Aggressive Behavior by Race/Ethnicity

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A commenter by the name of bbloggz alerted me to a new paper by Lee Ellis published this year titled Race/ethnicity and criminal behavior: Neurohormonal influences in which Ellis (2017) proposed his theory of ENA (evolutionary neuroandrogenic theory) and applied it to racial/ethnic differences in crime. On the face, his theory is solid and it has great explanatory power for the differences in crime rates between men and women, however, there are numerous holes in the application of the theory in regards to racial/ethnic differences in crime.

In part I, he talks about racial differences in crime. No one denies that, so on to part II.

In part II he talks about environmental causes for the racial discrepancies, that include economic racial disparities, racism and societal discrimination and subordination, a subculture of violence (I’ve been entertaining the honor culture hypothesis for a few months; Mazur (2016) drives a hard argument showing that similarly aged blacks with some college had lower levels of testosterone than blacks with less than high school education which fits the hypothesis of honor culture. Though Ellis’ ENA theory may account for this, I will address this below). However, if the environment that increases testosterone is ameliorated (i.e., honor culture environments), then there should be a subsequent decrease in testosterone and crime, although I do believe that testosterone has an extremely weak association with crime, nowhere near high enough to account for racial differences in crime, the culture of honor could explain a good amount of the crime gap between blacks and whites.

Ellis also speaks about the general stress/strain explanation, stating that blacks have higher rates of self-esteem and Asians the lowest, with that mirroring their crime rates. This could be seen as yet another case for the culture of honor in that blacks with a high self-esteem would feel the need to protect their ‘name’ or whatever the case may be and feel the need for physical altercation based on their culture.

In part III, Ellis then describes his ENA theory, which I don’t disagree with on its face as it’s a great theory with good explanatory power but there are some pretty large holes that he rightly addresses. He states that, as I have argued in the past, females selected men for higher rates of testosterone and that high rates of testosterone masculinize the brain, changing it from its ‘default feminine state’ and that the more androgens the brain is exposed to, the more likely it is for that individual to commit crime.

Strength

Ellis cites a study by Goodpaster et al (2006) in which he measured the races on the isokinetic dynamometry, pretty much a leg extension. However, one huge confound is that participants who did not return for follow-up were more likely to be black, obese and had more chronic disease (something that I have noted before in an article on racial grip strength). I really hate these study designs, but alas, it’s the best we have to go off of and there are a lot of holes in them that must be addressed. Though I applaud the researchers’ use of the DXA scan (regular readers may recall my criticisms on using calipers to assess body fat in the bench press study, which was highly flawed itself; Boyce et al, 2014) to assess body fat as it is the gold standard in the field.

Ellis (2017: 40) writes: “as brain exposure to testosterone surges at puberty, the prenatally-programmed motivation to strive for resources, status, and mating opportunities will begin to fully activate.” This is true on the face, however as I have noted the correlation between physical aggression and testosterone although positive is low at .14 (Archer, 1991; Book et al, 2001). Testosterone, as I have extensively documented, does cause social dominance and confidence which do not lead to aggression. However, when other factors are coupled with high testosterone (as noted by Mazur, 2016), high rates of crime may occur and this may explain why blacks commit crime; a mix of low IQ, high testosterone and low educational achievement making a life of crime ‘the smart way’ to live seeing as, as Ellis points out, and that intelligent individuals find legal ways to get resources while less intelligent individuals use illegal ways.

ENA theory may explain racial differences in crime

In part IV he attempts to show how his ENA theory may explain racial differences in crime—with testosterone sitting at the top of his pyramid. However, there are numerous erroneous assumptions and he does rightly point out that more research needs to be done on most of these variables and does not draw any conclusions that are not warranted based on the data he does cite. He cites one study in which testosterone levels were measured in the amniotic fluid of the fetus. The sample was 59 percent white and due to this, the researchers lumped blacks, ‘Hispanics’ and Native Americans together which showed no significant difference in prenatal testosterone levels (Martel and Roberts, 2014).

Umbilical cord and testosterone exposure

Ellis then talks about testosterone in the umbilical cord, and if the babe is exposed to higher levels of testosterone in vitro, then this should account for racial/ethnic differences in crime. However, the study he cited (Argus-Collins et al, 2012) showed no difference in testosterone in the umbilical cord while Rohrmann et al (2009) found no difference in testosterone between blacks and whites but found higher rates of SHBG (sex hormone-binding globulin) which binds to testosterone and makes it unable to leave the blood which largely makes testosterone unable to affect organ development. Thusly, if the finding of higher levels of SHBG in black babes is true, then they would be exposed to less androgenic hormones such as testosterone which, again, goes against the ENA theory.

He also cites two more studies showing that Asian babes have higher levels of umbilical cord testosterone than whites (Chinese babes were tested) (Lagiou et al, 2011; Troisi et al, 2008). This, again, goes against his theory as he rightly noted.

Circulating testosterone

Next he talks about circulating differences in testosterone between blacks and whites. He rightly notes that testosterone must be assayed in the morning within an hour after waking as that’s when levels will be highest, yet cites Ross et al (1986) where assay times were all over the place and thusly testosterone cannot be said to be higher in blacks and whites based on that study and should be discarded when talking about racial differences in testosterone due to assay time being between 10 am and 3 pm. He also cites his study on testosterone differences (Eliss and Nyborg, 1993), but, however, just as Ross et al (1986) did not have a control for WC (waist circumference) Ellis and Nyborg (1993) did not either, so just like the other study that gets cited to show that there is a racial difference in testosterone, they are pretty hugely flawed and should not be used in discussion when discussing racial differences in testosterone. Why do I not see these types of critiques for Ross et al (1986) in major papers? It troubles me…

He also seems to complain that Lopez et al (2013) controlled for physical activity (which increases testosterone) and percent body fat (which, at high levels, decreases testosterone). These variables, as I have noted, need to be controlled for. Testosterone varies and fluctuated by age; WC and BMI vary and fluctuate by age. So how does it make sense to control for one variable that has hormone levels fluctuate by age and not another? Ellis also cites studies showing that older East Asian men had higher levels of testosterone (Wu et al, 1995). Nevertheless, there is no consensus; some studies show Chinese babes have higher levels of testosterone than whites and some studies show that whites babes have higher levels of testosterone than Chinese babes. Indeed, this meta-analysis by Ethnicmuse shows that Asians have the highest levels, followed by Africans then Europeans, so this needs to be explained to save the theory that testosterone is the cause of black overrepresentation of violence (as well as what I showed that testosterone is important for vital functioning and is not the boogeyman the media makes it out to be).

Bone density and crime

Nevertheless, the next variable Ellis talks about is bone density and its relationship to crime. Some studies find that blacks are taller than whites while other show no difference. Whites are also substantially taller than Asian males. Blacks have greater bone density than the other three races, but according to Ellis, this measure has not been shown to have a relationship to crime as of yet.

Penis size, race and crime

Now on to penis size. In two articles, I have shown that there is no evidence for the assertion that blacks have larger penises than whites. However, states that penis length was associated with higher levels of testosterone in Egyptian babes. He states that self-reported penis size correlates with self-reports of violent delinquency (Ellis and Das, 2012). Ellis’ main citations for the claim that blacks have larger penises than other races comes from Nobile (1982), the Kinsey report, and Rushton and Boagert (1987) (see here for a critique of Rushton and Boagert, 1987), though he does cite a study stating that blacks had a longer penis than whites (blacks averaging 5.77 inches while whites averaged 5.53 inches). An HBDer may go “Ahah! Evidence for Rushton’s theory!”, yet they should note that the difference is not statistically significant; just because there is a small difference in one study also doesn’t mean anything for the totality of evidence on penis size and race—that there is no statistical difference!

He then cites Lynn’s (2013) paper which was based on an Internet survey and thus, self-reports are over-measured. He also cites Templer’s (2002) book Is Size Important?, which, of course, is on my list of books to read. Nevertheless, the ‘evidence’ that blacks average larger penises than whites is extremely dubious, it’s pretty conclusive that the races don’t differ in penis size. For further reading, read The Pseudoscience of Race Differences in Penis Sizeand read all of Ethnicmuses’ posts on penis size here. It’s conclusive that there is no statistical difference—if that—and any studies showing a difference are horribly flawed.

2d/4d ratio and race

Then he talks about 2d/4d ratio, which supposedly signifies higher levels of androgen exposure in vitro (Manning et al, 2008) however these results have been challenged and have not been replicated (Koehler, Simmons, and Rhodes, 2004; Yan et al, 2008, Medland et al, 2010). Even then, Ellis states that in a large analysis of 250,000 respondents, Asians had the lowest 2d/4d ratio, which if the hypothesis of in vitro hormones affecting digit length is to be believed, they have higher levels of testosterone than whites (the other samples had small ns, around 100).

Prostate-specific antigens, race, and prostate cancer

He then talks about PSA (prostate-specific antigen) rates between the races. Blacks are two times more likely to get prostate cancer, which has been blamed on testosterone. However, I’ve compiled good evidence that the difference comes down to the environment, i.e., diet. Even then, there is no evidence that testosterone causes prostate cancer as seen in two large meta-analyses (Stattin et al, 2003; Michaud, Billups, and Partin, 2015). Even then, rates of PCa (prostate cancer) are on the rise in East Asia (Kimura, 2012; Chen et al, 2015Zhu et al, 2015) which is due to the introduction of our Western diet. I will cover the increases in PCa rates in East Asia in a future article.

CAG repeats

He then reviews the evidence of CAG repeats. There is, however, no evidence that the number of CAG repeats influences sensitivity to testosterone. However, intra-racially, lower amounts of CAG repeats are associated with higher spermatozoa counts—but blacks don’t have higher levels of spermatozoa (Mendiola et al, 2011; Redmon et al, 2013). Blacks do have shorter CAG repeats, and this is consistent with the racial crime gap of blacks > whites > Asians. However, looking at the whole of the evidence, there is no good reason to assume that this has an effect on racial crime rates.

Intelligence and education

Next he talks about racial differences in intelligence and education, which have been well-established. Blacks did have higher rates of learning disabilities than whites who had higher levels of learning disabilities then Asians in a few studies, but other studies show whites and South Asians having different rates, for instance. He then talks about brain size and criminality, stating that the head size of males convicted for violent crimes did not differ from males who committed non-violent crimes (Ikaheimo et al, 2007). I won’t bore anyone with talking about what we know already: that the races differ in average brain size. However, a link between brain size and criminality—to the best of my knowledge—has yet to been discovered. IQ is implicated in crime, so I do assume that brain size is as well (no matter if the correlation is .24 or not; Pietschnig et al, 2015).

Prenatal androgen exposure

Now to wrap things up, the races don’t differ in prenatal androgen exposure, which is critical to the ENA theory; there is a small difference in the umbilical cord favoring blacks, and apparently, that predicts a high rate of crime. However, as noted, blacks have higher levels of SHBG at birth which inhibits the production of testosterone on the organs. Differences in post-pubertal testosterone are small/nonexistent and one should not talk about them when talking about differences in crime or disease acquisition such as PCa. DHT only shows a weak positive correlation with aggression—the same as testosterone (Christiansen and Winkler, 1992; however other studies show that DHT is negatively correlated with measures of physical aggression; Christiansen and Krussmann, 1987; further, DHT is not so evil after all).

Summing it all up

Blacks are not stronger than whites, indeed evidence from the races’ differing somatype, grip strength and leverages all have to do with muscular strength. Furthermore, the study that Ellis cites as ‘proof’ that blacks are stronger than whites is on one measure; an isokinetic dynamometry machine which is pretty much a leg extension. In true tests of strength, whites blow blacks away, which is seen in all major professional competitions all around the world. Blacks do have denser bones which is due to androgen production in vitro, but as of yet, there has been no research done into bone density and criminality.

The races don’t differ on penis size—and if they do it’s by tenths of an inch which is not statisitcally significant and I won’t waste my time addressing it. It seems that most HBDers will see a racial difference of .01 and say “SEE! Rushton’s Rule!” even when it’s just that, a small non-significant difference in said variable. That’s something I’ve encountered a lot in the past and it’s, frankly, a waste of time to converse about things that are not statistically significant. I’ve also rebutted the theory on 2d/4d ration as well. Finally, Asians had a similar level of androgen levels compared to blacks, with whites having the least amount. Along with a hole in the theory for racial differences in androgen causing crime, it’s yet another hole in the theory for racial differences in androgens causing racial differences in penis size and prostate cancer.

On intelligence scores, no one denies that blacks have scored about 1 SD lower than whites for 100 years, no one denies that blacks have a lower educational attainment. In regards to learning disabilities, blacks seem to have the highest rates, followed by Native Americans, than non-Hispanic whites, East Asians and the lowest rates found in South Asians. He states only one study links brain size to criminal behavior and it showed a significant inverse relationship with crime but not other types of offenses.

This is a really good article and I like the theory, but it’s full of huge holes. Most of the variables described by Ellis have been shown to not vary at all or much between the races (re: penis size, testosterone, strength [whites are stronger] prostate cancer caused mainly by diet, 2d/4d ratio [no evidence of it showing a digit ratio difference], and bone density not being studied). Nevertheless, a few of his statements do await testing so I await future studies on the matter. He says that androgen exposure ‘differs by race and ethnicity’, yet the totality of evidence shows ‘not really’ so that cannot be the cause of higher amounts of crime. Ellis talks about a lot of correlates with testosterone, but they do not pass the smell test. Most of it has been rebutted. In fact, one of the central tenets of the ENA theory is that the races should differ in 2d/4d ratio due to exposure of differing levels of the hormone in vitro. Alas, the evidence to date has not shown this—it has in fact shown the opposite.

ENA theory is good in thought, but it really leaves a lot to be desired in regards to explaining racial differences in crime. More research needs to be looked into in regards to intelligence and education and its effect on crime. We can say that low IQ people are more likely to drop out of school and that is why education is related to crime. However, in Mazur (2016) shows that blacks matched for age had lower levels of testosterone if they had some college under their belt. This seems to point in the direction of the ENA theory, however then all of the above problems with the theory still need to be explained away—and they can’t! Furthermore, one of the nails in the coffin should be this: East Asian males are found to have higher levels of testosterone than white males, often enough, and East Asian males actually have the lowest rate of crime in the worle!

This seems to point in the direction of the ENA theory, however then all of the above problems with the theory still need to be explained away—and they can’t! Furthermore, one of the nails in the coffin should be this: East Asian males are found to have higher levels of testosterone than white males, often enough, and East Asian males actually have some of the lowest rate of crime in the world (Rushton, 1995)! So this is something that needs to be explained if it is to be shown that testosterone facilitates aggression and therefore, crime.

Conclusion

I’ve shown—extensively—that there is a low positive correlation between testosterone and physical aggression, why testosterone does not cause crime, and have definitively shown that, by showing how flawed the other studies are that purport to show blacks have higher testosterone levels than whites, along with citing large-scale meta-analyses, that whites and blacks either do not differ or the differences is small to explain any so-called differences in disease acquisition or crime. One final statement on the CAG repeats, they are effect by obesity, men who had shorter CAG repeats were more likely to be overweight, which would skew readings (Gustafsen, Wen, and Koppanati, 2003). So depending on the study—and in most of the studies I cite whites have a higher BMI than blacks—BMI and WC should be controlled for due to the depression of testosterone.

It’s pretty conclusive that testosterone itself does not cause crime. Most of the examples cited by Ellis have been definitively refuted, and his other claims lack evidence at the moment. Even then, his theory rests on the 2d/4d ratio and how blacks may have a lower 2d/4d ratio than whites. However, I’ve shown that there is no significant relationship between 2d/4d ratio and traits mediated by testosterone (Kohler, Simmons, and Rhodes, 2004) so that should be enough to put the theory to bed for good.

Rebutting Heartiste on the Twinkie Diet

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Nutritional myths run amok everywhere. One of the most persistent is that ‘a calorie is a calorie’, that is, every macronutrient will be processed the same by the body. Another assumption is that the body doesn’t ‘care’ about where the calories come from—they can come from fat, protein, or carbs and the response will be the same: bodyweight will be reduced until one reaches their goal. However, it’s not as simple as that. He also has the assumption that “diets work”, when the best meta-analysis I know of on the matter shows the opposite (Mann et al, 2007, see especially table 1). They control for studies where weight was self-reported. They conclude that dieting does not work. This is what, as Heartiste says, “iScience!” says on the matter, so he should believe everything I state in this article, which is backed by “iScience!”.

Chateau Heartiste published an article back in 2010 titled The Twinkies Diet Proves Fatty Fats Are Fat Because They Eat Too Much. He is referring to professor of human nutrition Mark Haub and his success on ‘the twinkies diet’, where 2/3rds of his caloric intake came from junk food such as Twinkies. He lost 27 pounds in a two month period while his LDL cholesterol decreased by 20 percent and his HDL cholesterol increased by 20 percent. His level of triglycerides also decreased by 37 percent, with his body fat decreasing from 33.4 to 24.9 percent. So he ate 1800 kcal per day—2/3rds of it being junk food—for two months and lost 27 pounds. Case closed, right? Eat junk food at a deficit and lose weight? A calorie is a calorie? There are a few problems with this contention which will be addressed below.

Heartiste writes:

Big bottom line: Being fat itself is bad for your health. “Fat and fit” is a myth. The change that counts the most is losing the weight, which can only be done by PUSHING AWAY FROM THE TABLE.

Except fit and overweight and obese individuals have similar mortality rates than their normal weight counterparts (Barry et al, 2014). However, more recently a study was published purporting that overweight and obese individuals being healthy despite excess weight is a myth. The researchers state that in a sample of millions of Britons that overweight and obese individuals had a higher risk of heart disease than their normal-weight counterparts. Unfortunately, I cannot locate the study since it wasn’t published in a journal (and thusly not peer reviewed). I wonder if variables such as diet, smoking and other lifestyle factors were taken into account. Nevertheless, the debate on fitness and fatness continues.

Another large meta-analysis shows that grade 1 obesity (BMI 30->35) had the same mortality risk as normal-weight individuals with grade 2 obese (BMI +35) having a significantly higher risk of death (Flegal, Kit, and Orpana, 2013).

Heartiste claims that ‘a calorie is a calorie’. This is a common fallacy. This suggests that the body will process all foods the same way—that is, processing them the same metabolically. This, however, is not the case. Haub himself is a sample size of 1. If Heartiste can use a sample size of 1 to make a claim, then I can too.

Sam Feltham ate +5,000 kcal per day for 21 days and only gained 1.3 kg when he should have gained 7.3 kg based on the amount of kcal he ate. A calorie is a calorie, right? This is a fallacious statement. The statement “a calorie is a calorie” violates the second law of thermodynamics (Feinman and Fine, 2004). Heartiste writes:

That first law of thermodynamics looms large over everything.

The first law of thermodynamics is irrelevant to human physiology. It only states that an organism gets bigger if it consumes more energy; it doesn’t state why this occurs, which is due to the hormone insulin which causes weight gain.

He does rightly state that an omega 3/6 imbalance is part of the reason but then handwaves it away. Western-like high-fat diets (i.e., diets with an imbalance of linoleic acids (LA; and n-6 fatty acid) with n-3) are sufficient enough to induce gradual enhancement in fat mass across the generations (Massiera et al, 2010). This obviously includes the average 55 percent carbohydrate diet that the AHA recommends (Eckel et al, 2014). The Standard American Diet (aptly named the “SAD diet”) has the n-3/n-6 imbalance along with being high in carbohydrates which spike insulin which impedes fat being unlocked from the adipocyte.

Heartiste doesn’t understand that if you reduce the ‘in’, the ‘out’ also decreases. This was noted in the famous starvation experiment headed by Ancel Keys. They took 36 healthy men who ate normally for three months while being their behavior and personality was monitored. In the next six months, they were reduced to eating half of their initial intake (they started at 2000 kcal and dropped to 1000 kcal; some individuals going lower than that) and their metabolic rate decreased by 40 percent (Keys et al, 1945). This is proof for the contention that the body decreases its metabolic rate due to what is ingested. A similar study was done on Vermont prisoners, except they were told to gorge on food. Since they were in a controlled setting, the prisoners could be monitored to ensure they ate all of the food.

At the end of the study, their metabolic rates had increased by 50 percent. This is evidence that the body was trying to get back to its original weight. In six months, the prisoners went back to their normal weight as they ate normally (Salas, Horton, and Sims, 1971) One man only gained ten pounds eating all of those calories. Clearly, the body was resisting weight gain and when they were allowed to eat normally, they effortlessly regained their normal weights.

Finally, on the topic of Haub, Big Food shill, I will address a few things about him and his ‘research’ that recently came to light.

Intermittent fasting and obesity expert Dr. Jason Fung showed that in 2016 after Coca-Cola released their funding reports after criticisms of transparency, Mark Haub was found to be one of the many researchers that were backed by Coca-Cola. This is an attempt to show that ‘a calorie is a calorie’ and that ‘all calories are created equal’. This has been rebutted above.

In 2016—six years after his ‘experiment—it was revealed that he was funded by Coca-Cola. No doubt in order to ‘prove’ that ‘a calorie is a calorie’ and have people continue to gorge on high carbohydrate/insulinogenic foods. However, the human body is a lot more complex than to just reduce it to simply calories in and calories out—which I have written about in depth.

People like Heartiste need to get an actual understanding of the literature and what Coca-Cola has been trying to do for years, which is to make eating junk food ‘OK’ because ‘it doesn’t cause obesity’. Children consume 45 percent more food when exposed to advertisements (Harris, Bargh, and Brownell, 2009). So to begin to curb obesity rates we don’t need to ‘eat junk food’, we need to not eat junk food and eat a diet more ancestral to us—that is, one lower in processed carbs and higher in animal fat and protein. Big Food shills like Haub need to be exposed for what they are—people who do ‘research’ for a quick buck, i.e., not furthering our understanding of a complex issue as he would like you to believe. Exercise also doesn’t induce weight loss. So the claims of ‘eat less and move more’ (eat less according to the 55 percent carbohydrate recommendations) is bound to fail.

If Heartiste can make a claim using one man as an example then so can I. Read the above article by Sam Feltham in which he writes about hs experience eating 5,000 kcal per day for 21 days while only gaining 1.3 kg. I can use this example to say that eating low carb and high fat at 5,000 kcal per day will lead to negligible weight gain, however, I don’t use n=1 sample sizes to make claims and no one else should either.

Between-group Differences in Obesity Rates

By Scott Jameson

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I’ve been active in the blogosphere for around 24 hours now and I’ve already gotten a negative response from someone who happens to be wrong. That’s a win in my book.
The argument we’re having is, as best I can tell, why some populations out there just don’t have obesity as an observed phenotype amongst their members. TL;DR: Pumpkin Person and Robert Lindsay believe that genetics explain why there are no obese New Guineans. But it ain’t so.

The original context is an old Pumpkin Person post. Much of what he’s saying here doesn’t seem too off-base; for example he says that behavioral genetics may explain much of the differences in BMI between individuals within the same population. True. It is possible that some people are genetically inclined to eat more or unhealthier foods, rather than simply being genetically inclined to putting on weight regardless of what they do.

As an aside, genotypes that affect how you digest things also probably explain part of the BMI gap between skinny folks and fat folks within the first world. The APOA2 gene for example has a recessive allele that is associated with higher BMI in people who eat more saturated fats. The interactions between genes and environment which determine BMI are complicated and not yet fully understood, but I’m willing to bet that being genetically worse at processing certain nutrients is a part of the problem, and that being genetically inclined to stuff your face is a part of the problem as well. PP is probably right about that issue.

Where he and Lindsay get it wrong is using examples of people from Podunk, New Guinea as evidence for obesity “being genetic” (relative term). Obesity is a gene-environment interaction such that, without certain environmental inputs, you simply won’t get the phenotype. History tells us that that input is processed carbohydrates.

There was a time when people could have used Australian Aboriginals or Inuit or Pima Indians as examples of groups of people who just don’t have obese folks amongst their numbers, just as Lindsay did with a few populations. Homo sans lardicus. Then the White Devils showed up with their refined Einkorn wheat products and their firewater and so on. Now those populations have fat people in them.

There’s an ongoing debate as to whether some populations are more resistant to the fattening effects of processed carbs or not. My guess is, the answer’s yes (and you’d look at Europeans and East Asians to see the more carb-resistant people, in theory) but that topic would merit its own post. That being said, every population in the world will almost assuredly have obese people in it after you introduce processed carbs. All of the populations that were introduced to this diet, now have fat people in them.

Heritability of BMI is high within the first world because the relevant environmental input is pretty uniform: everybody has access to potatoes, everybody has access to broccoli. As PP points out, which you’re likely to eat and how much you’re likely to eat likely depends on your genetics. As I point out, how your body processes the nutrients also has a likely genetic component. But the environmental contribution to our within-population differences in BMI is low (~20%) because we all have access to roughly the same stuff.

Rural New Guineans, lacking a bunch of processed carbs, could hardly get fat if they tried their best to. That’s a big between-population, nonheritable cause for a phenotypic difference; this means that environment probably explains most of the BMI gap between them and us. If I wanted evidence to refute Lindsay’s assertion that New Guineans are skinnier thanks to genetics, I’d find a population of urbanized New Guineans somewhere with higher average BMI. Such a group would have New Guinean genetics but a “developed” environment vaguely similar to ours; if they were fatter than their rural ken, then Lindsay’s hypothesis that New Guineans are just genetically obesity-free would be falsified.

If only such research existed!

Is Obesity Genetic? A Reply to PumpkinPerson and Robert Lindsay

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I come across a lot of ridiculous articles from PumpkinPerson, but this has to be one of the most ridiculous. He writes:

Identical twin studies show that obesity has a heritability of almost 80%. Although I generally lean towards nature in most nature-nurture debates, I’ve always had a problem with the idea that obesity is highly genetic, and thus enjoyed this epic rant by blogger Robert Lindsay:

It is 80% genetic[?]

That is why you have whole tribes in South America where not one person has ever been fat.

That is why you have whole towns in Melanesia with 1000’s of people where not one person is fat.

There are fat people in the cities of Solomon Islands. In the study I read, the only man who was fat was one who had gone off to the city for a while and ate salt and processed, packaged food. Do you realize that if you did a genetic study of the fatties in Melanesia, you would find that wonderful 80% “genetic” link you guys are shouting about?

That is why the fatness and obesity rate has exploded in the US and much of the rest of the world. Because it’s 80% genetic!

I do not believe that fatsos act just like the rest of us. Ever known a blimp who ate like a bird? Me either.

I dunno about you, but I have never seen a fat person who wasn’t stuffing their face all the time with lousy food. They are always in restaurants. Always going out to eat. If you go to a restaurant, look around at all the fat people. Those people are fat because fat people like to eat out all the time and restaurant food is fattening. Fat people love to eat. Have you ever noticed that?

It’s 80 percent heritable in first world countries. Obviously the heritability will be lower in the third world. Clearly in first-world countries we have an overabundance of food. We don’t know what to do with it. So instead of having the opposite problem (not enough food) we now have too much food and this is what caused weight to increase (along with added sugars processed carbs).

Look at Melanesia—they still eat an ancestral diet. I can’t tell if Lindsay is being serious or not. He’s comparing people who still eat their ancestral diet to people who live in first-world countries and eat a Western diet. There’s no comparison there. If you want to see why people aren’t fat nor have the same diseases at the same rates (they are low to nonexistent in places like that) read Agriculture and Diseases of Civilization

This is the study that’s being referred to Elks et al 2012. The heritability of BMI is between .75 and .82. Again: this is in first-world countries.

PP then says:

In fact just the other day, I was at the home of someone who was so incredibly fat I thought “it must be genetic.” And then just as I was leaving his house, I noticed a huge empty box of pizza in the kitchen.

Binge eating and obesity both have a heritable component (Bulk, Sullivan and Kendler, 2003). Further, to quote Gary Taubes from Why We Get Fat and What to Do About It:

“So maybe the answers to be found are in the integration of factors – starting with the physiological, metabolic, and genetic ones and letting them lead us to the environmental triggers. Because the one thing we know for sure is that the laws of thermodynamics, true as they always are, tell us nothing about why we get fat or why we take in more calories than we expend while it’s happening. (emphasis mine) (Taubes, 2011: pg 74, excerpt from Why We Get Fat and What to Do About It)

PP says:

The fatness itself or the tendency to engage in behaviors that cause fatness such as ordering large pizzas? So while obesity might technically be nearly 80% genetic, the statistic is misleading because it’s not directly genetic in the same was as height is.

If you don’t eat enough, nor get the right nutrients, you don’t hit your genetic height. If you don’t eat enough you don’t hit your genetic weight.

I don’t get why studies like this get generalized to the whole population. This study was done in first-world countries and so this only applies to first-world countries. You’d think that people who think they know science would know that studies are only applicable for the cohort and people they are done on. Guess not.

Of course I don’t deny obesity has some direct genetic component. Some people gain weight a lot easier than others and for some people, it’s virtually impossible to lose weight no matter how well they eat, though this is rare.

Of course some people gain weight easier than others. Some people lose weight easier than others. Much of the biological opposition to sustained weight loss is due to the hormone leptin (Rosenbaum et al, 2010). The more fat you have in your body, the more leptin you have. Moreover, the longer you are at a certain weight, the more likely it is that is your bodyweight set-point and thus you can only move up or down at around a range of 10 to 15 pounds. Also see this quote from neuroscientist Sandra Aamodt’s book Why Diets Make Us Fat (see her Ted Talk here):

Like nearsightedness, environmental influences on weight also mostly affect the genetically vulnerable, although we understand the details of the process in only rare cases. Fitness gains on a standardized exercise program vary from one person to another largely because of differences in their genes. When identical twins, men in their early twenties, were fed an extra thousand calories per day for about three months, each pair showed similar weight gains . In contrast, the gain varied across twin pairs, ranging from nine to twenty-nine pounds, even though the caloric imbalance was the same for everyone. An individual’s genes also influence weight loss. When another group of identical twins burned a thousand more calories per day through exercise while maintaining a stable food intake in an in-patient facility, their losses ranged from two to eighteen pounds and were even more similar within twin pairs than weight gain. (Aamodt, 2016 pg. 138)

The cold, hard truth is that dieting doesn’t have a good track record. See Mann et al (2007) here. People don’t understand the bodies’ biological processes and assume something is easy while being ignorant to how the body reacts under caloric deprivation. This wouldn’t happen if people actually had some knowledge of human physiology. Something that PP and RL lack. They are speaking about a complex problem than they’re too ignorant to really know about.  

PP then says:

“Now I have no doubt that if that person has an identical twin raised apart, he too is extremely fat, and thus fatness technically has a high heritability, but what exactly is genetic here?”

Would the identical twin be raised in an obesogenic environment? If so, there’s a high chance that, yes he’d be fat too.

It’s also true that most people who lose weight end up gaining it back, but that’s because they end up returning to their compulsive eating habits.

Most people do end up gaining it back but it has to do with biological and physiological processes; obesity has nothing to do with willpower. You can’t willpower your way to extra weight loss.

People should read a few papers and books to see some data and facts before they write what “sounds good” in their head. These two clearly have no idea what they’re talking about and clearly talking from emotion and what sounds good.

Also read Are There Genetic Causes for Obesity?

An Evolutionary Look At Obesity

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Diet is the main driver of our evolution. Without adequate energy, we wouldn’t be able to able to have a brain as large as we do that has the number of neurons we have due to how calorically expensive each neuron is (6 kcal per billion neurons). However, as I’m sure everyone can see, our current diets and environment has caused the current obesity crisis in the world. What is the cause of this? Our genomes are adapted for a paleolithic diet and not our modern environment with processed foodstuffs along with an overabundance of energy. With an overabundance of novel food items and situations due to our obesogenic environments, it is easier for a higher IQ person to stay thinner than it is for a lower IQ person. Tonight I will talk about the causes for this, how and what we evolved to eat and, of course, how to reverse this phenomenon.

“Gourmet Sapiens” arose around 1-1.5 mya with the advent of cooking by Homo erectus. Even before then, when we became bipedal our hands were freed which then allowed us to make tools. With these tools, we could mash and cut food which was a sort of pre-digestion outside the body (exactly what cooking is). Over time, our guts shrank (Aiello, 1997) and we became adapted for a certain diet (Eaton, 2006). Over time, we evolved to eat a certain way—that is, we had times of feast and famine. Due to this, eating three meals a day is abnormal from an evolutionary perspective (Mattson et al, 2014). This sets the stage for the acquisition of diseases of civilization along with the explosion of obesity rates.

When looking for the causes—and not symptoms—of the rise of obesity rates, the first thing we should do is look at our current environment. How is it constructed? What type of foodstuffs are in it? What kinds of foods get advertised to us and how does this have an effect on our psyche and what we eventually buy? All three of these questions are extremely important to think of when talking about why we are so obese as a society. First-world environments are obesogenic (Galgani and Ravussin, 2008) due to being evolutionarily novel. Our genomes are adapted to a paleolithic diet, and so the introduction of the neolithic diet and agriculture reduced our quality of life, with a marked decrease in the quality of skeletal remains discovered after the advent of agriculture. However, agriculture is obviously responsible for the population boom that allowed us to become the apes the took over the world, cause being the population boom that followed the agricultural revolution (Richards, 2002).

Evolutionary mismatches occur when the rate of cultural or technological change is far faster than the genome can change to adapt to the new pressure. These dietary mismatches occur when cultural and technological change which can vastly outstrip biological evolution. The two big events that occurred in human history that have vastly outstripped biological evolution are the agricultural and Industrial Revolution. Contrary to Ryan Faulk’s belief, East Asians are not ‘less sensitive to carbohydrates’ and he did not “solve Gary Taubes’ race problem” in regards to diabesity rates. The rate of cultural and technological change has had large deleterious effects on our quality of life, and our increasing obesity rates have a lot to do with it.

Cofnas (2016) showed that mice taken off of their ancestral diet lead to worse healthy outcomes. The results of Lamont et al (2016) show that we, as animals, are adapted for ancestral diets, not the diets of the environment we have currently made for ourselves. This is a big point to take home from this. All organisms are adapted/evolved for what occurred in the ancestral past, not any possible future events. Therefore, to be as healthy as possible, it stands to reason you should eat a diet that’s closer to the ones your ancestors ate, especially since it can reverse type II diabetes and reverse bad blood markers (Klonoff, 2009). Even a short-term switch to a paleo diet “improves BP and glucose tolerance, decreases insulin secretion, increases insulin sensitivity and improves lipid profiles without weight loss in healthy sedentary humans.” (Frassetto et al, 2009) Since we evolved for a past environment and not any possible future ones, then eating a diet that’s as close as possible to our paleolithic ancestors looks like a smart way to beat the evolutionary mismatch in terms of our new, current obesogenic environment.

In one extremely interesting study, O’dea (1984) took ten middle-aged Australian Aborigines with type 2 diabetes and had them return to their ancestral hunter-gatherer lifestyle. With seven weeks of an ancestral diet and exercise, the diabetes had almost completely reversed! Clearly, when the Aborigines were taken off of our Western diet and put back in their ancestral environment with their ancestral diet, their diabetes disappeared. If we went back to a more ancestral eating pattern, the same would happen with us. This one small study lends credence to my claim that we need to eat a diet that’s more ancestral to us for us to ameliorate diseases of civilization (Eaton, 2006).

Further, looking at obesity from an evolutionary perspective can and will help us understand the disease of obesity (Ofei, 2005) better. Speakman (2009) reviewed three different explanations of the current obesity epidemic and assessed their usefulness in explaining the epidemic. The thrifty gene hypothesis states that obesity is an adaptive trait, that people who carry so-called ‘thrifty genes’ would be at an adaptive advantage. And since we have an explosion of obesity today from the 70s to today, this must explain a large part of the variance, right? There is evidence pointing in this direction, however (Southam et al, 2009). The second cause that Speakman looks at is the adaptive viewpoint—that obesity may have never been advantageous in our history, but genes that ultimately predispose us to obesity become “selected as a by-product of selection on some other trait that is advantageous.” (Speakman, 2009) The third and final perspective he proposes is that it’s due to random genetic drift, called ‘drifty genes’, predisposing some—and not others—to obesity. Whatever the case may be, there is some truth to their being genetic factors involved in the acquisition of fat storage. Though drifty genes and the adaptive viewpoint on obesity make more sense than any thrifty gene hypothesis.

For there to be any changes in the rate of obesity in the world, we need to begin to change our obesogenic environments to environments that are more like our ancestral one in terms of what foods are available. Once we alter our obesogenic environment into one that is more ancestrally ‘normal’ (since we are adapted for our past environments and not any possible future ones) then and only then will we see a reduction in obesity around the world. We are surrounded and bombarded with ads since we are children, which then effects our choices later in life; children consume 45 percent more when exposed to advertising (Harris et al, 2009). Clearly, advertisements can have one eat more, and the whole environmental mismatch in regards to being surrounded by foodstuffs not ancestral to us causes the rate of obesity to rise.

Finally, one thing we need to look at is the n-3 to n-6 ratio of our diets. As I covered last month, the n-6/n-3 is directly related to cognitive ability (Lassek and Gaulin, 2011). Our obesogenic environments cause our n-3/n-6 levels to be thrown out of whack. Our hunter-gatherer ancestors had a 1:1 level of n-3 and n-6 (Kris-Etherton, 2000). However, today, our diets contain 14 to 25 times more n-6 than n-3!! Still wondering why we are getting stupider and fatter? Further,  Western-like diets (high in linolic acid; an n-6 fatty acid) induces a general fat mass enhancement, which is in line with the observation of increasing obesity in humans (Massiera et al, 2010). There is extreme relevance to the n-3/n-6 ratio on human health (Griffin, 2008), so to curb obesity and illness rates, we need to construct environments that promote a healthy n-3/n-6 ratio, as that will at least curb the intergenerational transmission of obesity. Lands (2015) has good advice: “A useful concept for preventive nutrition is to NIX the 6 while you EAT the 3.” Here is a good list to help balance n-6 to n-3 levels.

In sum, obesity rates are a direct product of obesogenic environments. These environments cause obesity since we are surrounded by evolutionary novel situations and food. The two events in human history that contribute to this is the agricultural and Industrial Revolution. We have paleolithic genomes in a modern-day world, which causes a mismatch between our genomes and environment. This mismatch can be ameliorated if we construct differing environments—ones that are less obesogenic with less advertisement of garbage food—and we should see rates of obesity begin to decline as our environment becomes more and more similar to our ancestral one (Genné-Bacon, 2014).

The study on mice showed that for them to be healthy they need to eat a diet that is ancestral to them. We humans are no different.The evidence from the study on Australian Aborigines and the positive things that occur after going on a paleo diet for humans—even for sedentary people—shows that for us to be as healthy as possible in these obesogenic environments that we’ve made for ourselves, we need to eat a diet that matches with our paleolithic genome. This is how we can begin to fight these diseases of civilization and heighten our quality of life.

Note: Diet and exercise only under Doctor’s supervision, of course

References

Aiello, L. C. (1997). Brains and guts in human evolution: The Expensive Tissue Hypothesis. Brazilian Journal of Genetics,20(1). doi:10.1590/s0100-84551997000100023

Cofnas, N. (2016). Methodological problems with the test of the Paleo diet by Lamont et al. (2016). Nutrition & Diabetes,6(6). doi:10.1038/nutd.2016.22

Eaton, S. B. (2006). The ancestral human diet: what was it and should it be a paradigm for contemporary nutrition? Proceedings of the Nutrition Society,65(01), 1-6. doi:10.1079/pns2005471

Frassetto, L. A., Schloetter, M., Mietus-Synder, M., Morris, R. C., & Sebastian, A. (2009). Metabolic and physiologic improvements from consuming a paleolithic, hunter-gatherer type diet. European Journal of Clinical Nutrition,63(8), 947-955. doi:10.1038/ejcn.2009.4

Galgani, J., & Ravussin, E. (2008). Energy metabolism, fuel selection and body weight regulation. International Journal of Obesity,32. doi:10.1038/ijo.2008.246

Genné-Bacon EA, Thinking evolutionarily about obesity. Yale J Biol Med 87: 99112, 2014

Griffin, B. A. (2008). How relevant is the ratio of dietary n-6 to n-3 polyunsaturated fatty acids to cardiovascular disease risk? Evidence from the OPTILIP study. Current Opinion in Lipidology,19(1), 57-62. doi:10.1097/mol.0b013e3282f2e2a8

Harris, J. L., Bargh, J. A., & Brownell, K. D. (2009). Priming effects of television food advertising on eating behavior. Health Psychology,28(4), 404-413. doi:10.1037/a0014399

Klonoff, D. C. (2009). The Beneficial Effects of a Paleolithic Diet on Type 2 Diabetes and other Risk Factors for Cardiovascular Disease. Journal of Diabetes Science and Technology,3(6), 1229-1232. doi:10.1177/193229680900300601

Kris-Etherton PM, Taylor DS,  Yu-Poth S, et al. Polyunsaturated fatty acids in the food chain in the United States.  Am J Clin Nutr, 2000, vol. 71 suppl(pg. 179S-88S)

Lamont, B. J., Waters, M. F., & Andrikopoulos, S. (2016). A low-carbohydrate high-fat diet increases weight gain and does not improve glucose tolerance, insulin secretion or β-cell mass in NZO mice. Nutrition & Diabetes,6(2). doi:10.1038/nutd.2016.

Lands, B. (2015). Choosing foods to balance competing n-3 and n-6 HUFA and their actions. Ocl,23(1). doi:10.1051/ocl/2015017

Lassek, W. D., & Gaulin, S. J. (2011). Sex Differences in the Relationship of Dietary Fatty Acids to Cognitive Measures in American Children. Frontiers in Evolutionary Neuroscience,3. doi:10.3389/fnevo.2011.00005

Massiera, F., Barbry, P., Guesnet, P., Joly, A., Luquet, S., Moreilhon-Brest, C., . . . Ailhaud, G. (2010). A Western-like fat diet is sufficient to induce a gradual enhancement in fat mass over generations. The Journal of Lipid Research,51(8), 2352-2361. doi:10.1194/jlr.m006866

Mattson, M. P., Allison, D. B., Fontana, L., Harvie, M., Longo, V. D., Malaisse, W. J., . . . Panda, S. (2014). Meal frequency and timing in health and disease. Proceedings of the National Academy of Sciences,111(47), 16647-16653. doi:10.1073/pnas.1413965111

O’dea, K. (1984). Marked improvement in carbohydrate and lipid metabolism in diabetic Australian aborigines after temporary reversion to traditional lifestyle. Diabetes,33(6), 596-603. doi:10.2337/diabetes.33.6.596

Ofei F. Obesity- a preventable disease. Ghana Med J 2005;39: 98-101

Richards, M. P. (2002). A brief review of the archaeological evidence for Palaeolithic and Neolithic subsistence. European Journal of Clinical Nutrition,56(12), 1270-1278. doi:10.1038/sj.ejcn.1601646

Southam, L., Soranzo, N., Montgomery, S. B., Frayling, T. M., Mccarthy, M. I., Barroso, I., & Zeggini, E. (2009). Is the thrifty genotype hypothesis supported by evidence based on confirmed type 2 diabetes- and obesity-susceptibility variants? Diabetologia,52(9), 1846-1851. doi:10.1007/s00125-009-1419-3

Speakman, J. R. (2013). Evolutionary Perspectives on the Obesity Epidemic: Adaptive, Maladaptive, and Neutral Viewpoints. Annual Review of Nutrition,33(1), 289-317. doi:10.1146/annurev-nutr-071811-150711

Exercise, Longetivity, and Cognitive Ability

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The relationship between exercise and cognitive ability is important, but often not spoken about. Exercise releases many endorphins (Harber and Sutton, 1984) that help to further positive mood, have one better handle stress since sensitivity to stress is reduced after exercise; and after exercise, depression, and anxiety also decrease (Salmon, 2001). Clearly, if you’re attempting to maximize your cognition, you want to exercise. However, a majority of Americans don’t exercise (49 percent of Americans over the age of 18 do aerobic exercise whereas only 20 percent of Americans do both aerobic and muscle-strengthening exercise). The fact that we do not exercise as a country is proof enough that our life expectancy is declining (Olshansky et al, 2005), and we need to exercise—as a country—to reverse the trend.

Regular readers may know of my coverage of obesity on this blog. Understandably, a super majority of people will disregard my views on obesity and its causes as ‘pseudoscience’ or ‘SJW-ness’, that however says nothing to the data (and if anyone would like to discuss this, they can comment on the relevant articles). Since the average American hardly gets any exercise, this can lead to a decrease in cognitive functioning as less blood flows to the brain. Thus, everyone—especially the obese—needs to exercise to reach maximum genetic brain performance, lest they degenerate in cognitive function due a low-quality diet, such as a diet high in n-6 (the SAD diet), which is correlated with decreased cognition. Further, contrary to popular belief, the obese have lower IQs since around age three; obesity does not itself lower genotypic IQ, their IQ is ALREADY LOW which leads to obesity later in life due to a non-ability to delay gratification. Clearly, exercise education needs to be targeted at those with lower IQs since they have a higher chance of becoming obese in comparison to those with lower IQs (Kanazawa, 2013; 2014).

Clearly not eating well and not exercising can have negative effects on cognition. But what are the positives?

As mentioned previously, exercise releases endorphins that cause good mood and block pain. However, the importance of exercise does not stop there. Exercise also leads to faster reaction times on memory tasks and “increased levels of high-arousal positive affect (HAP) and decreased levels of low-arousal positive affect (LAP).” Exercise has important effects on people of all age groups (Hogan, Mata and Carstensen, 2013; Chodzko-Zajko et al, 2009). Further, physical exercise protects against age-related diseases and cognitive decline in the elderly by modifying “metabolic, structural, and functional dimensions of the brain that preserve cognitive performance in older adults.” (Kirk-Sanchez and McGough, 2014). Exercise is, clearly, a brain protectant during both adolsence and old age, so no matter your age if you want a high QoL living the best life possible, you need to supplement an already healthy lifestyle with strength training/cardio (of course, under doctor’s supervision).

Another important benefit to exercise is that it increases blood flow to the brain (Querido and Steele, 2007; Willie and Ainslie, 2011); however, changes in cerebral blood flow (CBF) during exercise are not associated with higher cognition (Ogoh et al, 2014). During prolonged exercise, cognition was improved when blood flow to the middle cerebral artery (MCA) was decreased. Thusly, exercise-induced changes in CBF do not preserve cognitive performance. Exercise to get blood to the brain is imperative for proper brain functioning. Our brains are vampiric, so we need to ‘feed it’ with blood and what’s the best way to ‘feed’ the brain in this context? Exercise!

Exercise also protects against cognitive degeneration in the elderly (Bherer, Erikson and Lie-Ambrose, 2013; Carvalho et al, 2014; Paillard, 2015). Further, longitudinal studies show an association between exercise and a decrease in dementia (Blondell, Hammersley-Mather and Veerman, 2014). The evidence is currently piling up showing that exercise at all ages is good cognitively, reduces mortality as well as a whole slew of other age-related cognitive diseases. The positive benefits of exercise need to be shown to elderly populations since exercise—mainly strength training—reduces the chance of osteoporosis (Layne and Nelson, 1999; Gray, Brezzo, and Fort, 2013). Moreover, elderly people who exercise live longer (Gremeaux et al, 2012). Now, if you don’t exercise, now’s looking like a pretty good time to start, right?

Finally, lack of exercise causes a myriad of deleterious diseases (Booth, Roberts, and Laye, 2014). This is due, in large part to our evolutionary novel environment (Kanazawa, 2004) which leads to evolutionary mismatches. An evolutionary mismatch, in this instance, is our obesogenic environment (Lake and Townshend, 2006). In terms of our current environment, it is evolutionary novel in comparison to our ancestral land (the Savanna; re: Kanazawa, 2004). Modern-day society is ‘evolutionarily novel’. In this case, we haven’t fully adapted (genetically) to our new lifestyles as, Gould said in Full House, our rate of cultural change has vastly exceeded Darwinian selection. Thusly, our environments that we have made for ourselves (and that we assume that heighten our QoL) actually cause the reverse, all the while top researchers are scratching their heads to figure out the answer, the problem while it’s staring them right in the face.

Our obesogenic environments have literally created a mismatch with our current eating habits and our ancestral one (Krebs, 2009). Moreover, dietary mismatches occur when cultural and technological change vastly outstrip biological evolution (Logan and Jacka, 2009). Clearly, we need to lessen the impact of our obesogenic environment we have made for ourselves so that we can live as long as possible, as well as be as cognitively sharp as possible. Thusly, if our environment causes a mismatch with our genome which in turn causes obesity, then by changing our environment to one that matches our genome, so to speak, levels of obesity should decline as our environment becomes less obesogenic while becoming like our ancestral environment (Genne-Bacon, 2014).

In sum, the evidence for the positive benefits for exercise is ever-mounting (not like you need Pubmed studies to know that exercise is beneficial). However, due to our obesogenic environments, this makes it hard for people with higher time preference to resist their urges and the result is what you see around you today. The evidence is clear: exercise leads to increased blood flow to our vampiric brains; thus it will have positive effects on memory and other cognitive faculties. So, in order to live to a ripe, old age as a healthy man/woman, hit the gym and treadmill and try staying away from evolutionarily novel things as much as possible (i.e., like processed food). When we, as a country recognize this, we can then be smarter, healthier and, above all else, have a high QoL while living a longer life. Is that not what we all want? Well hit the gym, start exercising and change your diet to one that matches our ancestors. Don’t be that guy/gal (we all know who that guy is) that jumps on the exercise train late and misses out on these cognitive and lifestyle benefits!

Note: Only with Doctor supervision, of course

References

Bherer, L., Erickson, K. I., & Liu-Ambrose, T. (2013). A Review of the Effects of Physical Activity and Exercise on Cognitive and Brain Functions in Older Adults. Journal of Aging Research,2013, 1-8. doi:10.1155/2013/657508

Blondell, S. J., Hammersley-Mather, R., & Veerman, J. L. (2014). Does physical activity prevent cognitive decline and dementia?: A systematic review and meta-analysis of longitudinal studies. BMC Public Health,14(1). doi:10.1186/1471-2458-14-510

Booth, F. W., Roberts, C. K., & Laye, M. J. (2013). Lack of Exercise Is a Major Cause of Chronic Diseases. Comprehensive Physiology. doi:10.1002/cphy.c110025

Carvalho, A., Cusack, B., Rea, I. M., & Parimon, T.,. (2014). Physical activity and cognitive function in individuals over 60 years of age: a systematic review. Clinical Interventions in Aging, 661. doi:10.2147/cia.s55520

Chodzko-Zajko WJ, Proctor DN, Fiatarone Singh MA, Minson CT, Nigg CR, Salem GJ, Skinner JS: American College of Sports Medicine position stand. Exercise and physical activity for older adults. Med Sci Sports Exerc. 2009, 41: 1510-1530. 10.1249/MSS.0b013e3181a0c95c.

Gray M., Di Brezzo R., I.L. Fort (2013) The effects of power and strength training on bone mineral density in premenopausal women. J Sports Med Phys Fitness, 53, pp. 428–436

Genné-Bacon EA, Thinking evolutionarily about obesity. Yale J Biol Med 87: 99112, 2014

Gremeaux V, Gayda M, Lepers R, Sosner P, Juneau M, Nigam A. Exercise and longevity. Maturitas. 2012;73(4):312–7.

Harber VJ, Sutton JR. (1984) Endorphins and exercise. Sports Medicine 1: 154–174, 1984

Hogan, C. L., Mata, J., & Carstensen, L. L. (2013). Exercise holds immediate benefits for affect and cognition in younger and older adults. Psychology and Aging,28(2), 587-594. doi:10.1037/a0032634

Kanazawa, S. (2004). The Savanna Principle. Managerial and Decision Economics,25(1), 41-54. doi:10.1002/mde.1130

Kanazawa, S. (2013). Childhood intelligence and adult obesity. Obesity,21(3), 434-440. doi:10.1002/oby.20018

Kanazawa, S. (2014). Intelligence and obesity. Current Opinion in Endocrinology & Diabetes and Obesity,21(5), 339-344. doi:10.1097/med.0000000000000091

Krebs, J. R. (2009). The gourmet ape: evolution and human food preferences. American Journal of Clinical Nutrition,90(3). doi:10.3945/ajcn.2009.27462b

Lake, A., & Townshend, T. (2006). Obesogenic environments: exploring the built and food environments. The Journal of the Royal Society for the Promotion of Health,126(6), 262-267. doi:10.1177/1466424006070487

Layne, J. E., & Nelson, M. E. (1999). The effects of progressive resistance training on bone density: a review. Medicine & Science in Sports & Exercise,31(1), 25-30. doi:10.1097/00005768-199901000-00006

Kirk-Sanchez, N., & Mcgough, E. (2014). Physical exercise and cognitive performance in the elderly: current perspectives. Clinical Interventions in Aging, 51. doi:10.2147/cia.s39506

 Ogoh, S., Tsukamoto, H., Hirasawa, A., Hasegawa, H., Hirose, N., & Hashimoto, T. (2014). The effect of changes in cerebral blood flow on cognitive function during exercise. Physiological Reports,2(9). doi:10.14814/phy2.12163

Olshansky, S. J., Passaro, D. J., Hershow, R. C., Layden, J., Carnes, B. A., Brody, J., . . . Ludwig, D. S. (2005). A Potential Decline in Life Expectancy in the United States in the 21st Century. New England Journal of Medicine,352(11), 1138-1145. doi:10.1056/nejmsr043743

Paillard, T. (2015). Preventive effects of regular physical exercise against cognitive decline and the risk of dementia with age advancement. Sports Medicine – Open,1(1). doi:10.1186/s40798-015-0016-x

Querido, J. S., & Sheel, A. W. (2007). Regulation of Cerebral Blood Flow During Exercise. Sports Medicine,37(9), 765-782. doi:10.2165/00007256-200737090-00002

Salmon, P. (2001). Effects of physical exercise on anxiety, depression, and sensitivity to stress. Clinical Psychology Review,21(1), 33-61. doi:10.1016/s0272-7358(99)00032-x

Willie, C. K., & Ainslie, P. N. (2011). Cool head, hot brain: cerebral blood flow distribution during exercise. The Journal of Physiology,589(11), 2657-2658. doi:10.1113/jphysiol.2011.209668

Agriculture and Diseases of Civilization

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It is assumed that since the advent of agriculture that we’ve been better nourished than our hunter-gatherer ancestors. This assumption stems from the past 130 years since the advent of the Industrial Revolution and the increase in the quality of life of those who had the benefit of the Revolution. However, over a longer period of time, the advent of agriculture is linked to poorer health, vectors of disease and lower quality of life (in terms of intractable disease). Despite what I have claimed in the past about hunter-gatherer societies, they do have lower or nonexistent rates of the diseases that currently plague our first-world societies. Why do we have such extremely high rates of disease that they don’t?

Contrary to popular belief, agriculture has caused decreases in many facets of our lives. These diseases, more aptly termed ‘diseases of civilization‘ are directly caused by agricultural and societal ways of living. This increases disease rates as it’s easier for diseases to spread faster through bigger populations. Moreover, we haven’t had time to evolve to the current diet we now eat in first-world countries which has lead to what is termed an ‘evolutionary mismatch‘ between genes and environment. We evolved to eat a certain diet and the introduction of easily digestible carbohydrates which spike insulin the highest. Since insulin causes weight gain, and carbohydrate intake has dramatically increased since the 70s, obesity has increased as a result as countries begin to industrialize and more processed foods are available to the populace.

However, since the Industrial Revolution, height has increased along with IQ. Researchers argue that in first-world countries, high rates of obesity are not preventable due to the excess amounts of highly refined and processed foods. There is data for this theory. In first-world countries, the heritability of BMI is between .76 and .85. Since first-world countries are industrialized, we would expect them to hit their ‘genetic height and weight’ along with having the ability to reach their IQ potential. However, with the excess amount of highly processed and refined foods, this would also, in theory, have the population hit their ‘genetic weights’. This is what we see in first-world countries.

To see how first-world, industrialized societies cause these gene-environment mismatches, we can compare the disease acquisition rate—or lack thereof—to that of Europeans eating an industrialized, first-world diet (high in carbohydrates).

In his 2013 book The Story of the Human Body: Evolution, Health, and DiseasePaleoanthropologist Daniel Lieberman talks at length about evolutionary mismatches. The easiest way to think about this is to think about how one evolved to their environment and think how the processes that alter the environment. A perfect example is African farmers. They may dig a trench to divert water to better irrigate their crops, but this then would cause a higher rate of mosquitoes due to the increase in still water and then selection for genes that protect against malaria would be selected for. This is one example of an evolutionary mismatch turning into an advantage for a population. Most mismatch diseases are caused by changes in the environment which change how the body functions. In other words, the current first-world diet is correlated very highly with diseases of civilization and drive most of the mismatch diseases. Most likely, you will die from one of these mismatch diseases.

If you’re born in a hotter environment, you will have more sweat glands than if you were born in a cooler environment. If you grow up eating soft, processed food, your face will be smaller than if you ate harder foods. These are two ways in which ‘cultural evolution’ (cultural change) have an effect on how the human body grows and adapts to certain stimuli based on the environment around it.

The largest cause of the higher disease rate between industrialized peoples and those in hunter-gatherer societies is shifts in life history. As our life spans increased through modernization, so to did our chance of acquiring more diseases. Of course living longer affects how many children you have but it also raises your chances of acquiring an evolutionary mismatch and your chances of dying from one.

Daniel Lieberman writes on page 190 of his book The Story of the Human Body:

A typical hunter-gatherer adult female will manage to collect 2,000 calories a day and a male can hunt between 3,000 and 6,000 calories a day. (24) A hunter-gatherer groups combined efforts yield just enough food to feed small families. In contrast, a household of early Neolithic farmers from Europe using solely manual labor before the invention of the plow could produce an average if 12,800 calories per day over the course of a year, enough to feed families of six. (25) In other words, the first farmers could double their family size.

Thusly, you can see how evolutionary mismatches would occur with the advent of an agricultural diet that we didn’t evolve to be accustomed to. This is one of the biggest examples of the negative effects of agriculture, our inability to adapt quickly to our new diets which then accelerated after the Industrial Revolution. Further, hunter-gatherers will eat anything edible while agricultural societies will largely eat only what they grow. This would have huge implications for farmers if a few pests ruined their crops since they relied on a few crops to survive.

The thing about farming is that as the Agricultural Revolution began, this increased the population size as well as making that population pretty much stable in terms of migrating. This, then, led to higher rates of disease as larger populations foster new kinds of infectious diseases. Large populations didn’t happen until the advent of farming, and with it came the first plagues. The first farming villages were small, but “as the Reverend Malthus pointed out in 1798, even modest increases in a population’s birthrate will cause rapid increases in overall population size in just a few generations.” (Lieberman, 2013: 197) So as even small increases in population size would cause a boom in future generations, which along with it would drive disease acquisition and plagues in that new and stationary society.

Lieberman further writes on pages 199-200:

Not surprisingly, farming ushered in an era of epidemics, including tuberculosis, leprosy, syphilis, plague, smallpox and influenza. (44) This is not to say that hunter-gatherers did not get sick, but before farming, human societies primarily suffered from parasites such as lice, pinworms they acquired from contaminated food, and viruses or bacteria, such as herpes simplex, which they got from contact with mammals. (45) Diseases such as malaria and yaws (the nonvenereal precursor of syphilis) were probably also present among hunter-gatherers, but at much lower rates than in farmers. In fact, epidemics could not exist prior to the Neolithic because hunter-gatherer populations are below one person per square kilometer, which is below the threshold necessary for virulent diseases to spread. Smallpox, for example, is an ancient viral disease that humans apparently acquired from monkeys or rodents (the disease’s origins are unresolved) that was able to spread appreciably until the growth of large, dense settlements. (46)

Moreover, another evolutionary mismatch is the lack of sanitation that comes with stationary societies. Hunter-gatherers could just go and defecate in a bush, whereas with the advent of civilization, waste and refuse began to pile up in the area. As noted above, when farmers clear space for irrigation to plant crops, this introduces mosquitoes into the area which then causes more disease. Furthermore, we have also acquired about 50 diseases from living near animals (Lieberman, 2013: 201). There are more than 100 evolutionary mismatch diseases that agriculture has brought to humanity.

We can compare disease rates of people in industrialized societies and people in modern-day hunter-gatherer societies. In his 2008 book Good Calories, Bad CaloriesGary Taubes documents numerous instances of hunter-gatherer societies that have no to low rates of the same modern diseases that we have:

In 1914, Hoffman himself had surveyed physicians working for the Bureau of Indian Affairs. “Among some 63,000 Indians of all tribes,” he reported, “there occurred only 2 deaths from cancer as medically observed from the year 1914.” (Taubes, 2008: 92)

“There are no known reasons why cancer should not occasionally occur among any race of people, even though it be below the lowest degree of savagery and barbarism,” Hoffman wrote. (Taubes, 2008: 92)

“Granting the practical difficulties of determining with accuracy the causes of death among the non-civilized races, it is nevertheless a safe assumption that the large number of medical missionaries and other trained medical observers, living for years among native races throughout the world, would long ago have provided a substantial basis of fact regarding the frequency of malignant disease among the so-called “uncivilized” races, if cancer were met with among them to anything like the degree common to practically all civilized countries. Quite the contrary, the negative evidence is convincing that in the opinion of qualified medical observers cancer is exceptionally rare among the primitive peoples.” (Taubes, 2008: 92)

These reports, often published in the British Medical Journal, The Lancet or local journals like the East African Medical Journal, would typically include the length of service the author had undergone among the natives, the size of the local native population served by the hospital in question, the size of the local European population, and the number of cancers involved in both. F.P. Fouch, for instance, district surgeon of the Orange Free State in South Africa, reported to the BMJ in 1923 that he had spent six years at a hospital that served fourteen thousand natives. “I never saw a single case of gastric or duodenal ulcer, colitis, appendicitis, or cancer in any form in a native, although these diseases were frequently seen among the white or European population.” (Taubes, 2008: 92)

As a result of these modern processed foods, noted Hoffman, “far-reaching changes in bodily functioning and metabolism are introduced which, extending over many years, are the causes or conditions predisposing to the development of malignant new growths, and in part at least explain the observed increase in cancer death rate of practically all civilized and highly urbanized countries.” (Taubes, 2008: 96)

The preponderance of evidence shows that these people have low rates of disease that are endemic to our societies due to the advent of agriculture. There is one large difference between hunter-gatherer societies and industrialized ones: the type and amount of food we eat.

Along with the boom of agriculture, we see a slight decrease in height the longer people live in these types of societies. As the Neolithic began 11,500 years ago, height increased about 1.5 inches for males and slightly less for females. But around 7,500 years ago, stature began to decrease and we began noticing evidence of nutritional stress and skeletal markers of disease. There is evidence that as maize was introduced into eastern Tennessee about 1,000 years ago, a decrease of .87 inches in men and 2.4 inches in women were seen. Further, the height of early farmers in China and Japan decreased by 3.1 inches as rice farming progressed, with similar height decreases being seen in Mesoamerica in men (2.2 inches) and women (3.1 inches).

Anti-hereditarian Jared Diamond asks the question “Was farming worth it?” in which he writes:

With agriculture came the gross social and sexual inequality, the disease and despotism, that curse our existence.

The first two things he brings up are pretty Marxist in nature, though they are true. He implies that agriculture causes so-called ‘sexual inequalities’ in which women are made ‘beasts of burden’, made to do the work while men walk by ’empty handed’. This seems to be one negative to a society that is, supposedly, smarter than Europeans.

Regular readers may remember me criticizing Andrew Anglin and his stance on the paleo diet—with how it’s ‘how European man evolved to eat’. However, I am a data-driven person and I try to not let any bias get involved in my thought processes. I know do believe that we should eat a diet that closely mimics our hunter-gatherer ancestors, though we shouldn’t go overboard like certain people in the paleo community, we should be mindful of the quality of food we do it as we will greatly increase our life expectancy along with our quality of life. Indeed, researchers have proposed that we should adopt diets that are close in composition to what our hunter-gatherer ancestors ate in order to battle diseases of civilization. Based on what I’ve read over the past few months, I am inclined to agree. Indeed, evidence for this is seen in a sample of ten Australian Aborigines who were introduced back to their traditional lifestyle (O’Dea, 1984). In a 7 week period, they showed improvement in carbohydrate and lipid metabolism, effectively becoming diabetes-free in almost 2 months.

In sum, there were obviously both positive and negative effects on human life due to the advent of agriculture (leaning more towards negative). These range from diseases to increased population size, to ‘social inequalities’ to higher rates of obesity (this evolutionary mismatch will be extensively covered in the future) to a whole myriad of other diseases. These then lower the quality of life of the individual inflicted. However, the rates of these diseases are low to non-existent in hunter-gatherer societies due to them being nomadic and eating more plentiful foods. Agricultural societies become dependent on a few staple crops so when an endemic occurs, there is mass death since they do not know how to subsist on anything but what they have become accustomed to. The advent of agriculture leads to a decrease in stature as well as brain size. Further, agriculture and the processed foods that came with it caused us to become more susceptible to obesity, which was further exacerbated by the industrial revolutions and the ‘nutritional guidelines’ of the 60s and 70s that led to higher rates of coronary heart disease. It is the lifestyle change from agriculture that we have not adapted to yet that causes disease these diseases of civilization that shorten our life expectancies. I do now believe that all people should eat a diet as close to hunter-gatherer diet as possible, as that’s what the preponderance of evidence shows.

By the way, to my knowledge, contrary to what The Alternative Hypothesis says, there are no differences in carbohydrate metabolism between races (save for a few populations such as the Pima).

Agriculture and Evolution: A Reply to The Alternative Hypothesis

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I love nutrition science. So much so that I read a new book on it every week. The Alternative Hypothesis has a pretty old video on agriculture and evolution. I strongly disagree with his main thesis. I strongly disagree with his denigration of Gary Taubes. Most of all, I strongly disagree with what he says about the East Asian rice eaters because since that video has been made, the carbohydrate/insulin hypothesis of obesity has changed to the insulin hypothesis of obesity.

In the very beginning of the video he brings up Gary Taubes’s research on low-carb diets and how people tend to be healthier than those who eat higher carb diets. He brings up the East Asians who eat a lot of rice. However, it’s clear he doesn’t know that the percent of carbohydrate intake is nowhere near as important as the absolute amount of carbohydrate consumed:

  1. They consume a fraction of the sugar we do.  More sugar consumption leads to greater insulin resistance, more fat creation, less fat breakdown, and more fat accumulation.
  2. They consume less total glucose, AND the glucose they consume is accompanied by less sugar (and less omega-6 PUFA, if it matters).
  3. They consume a ratio of omega-6 to omega-3 PUFA that is much lower than we do.  This mayfurther reduce any insulin resistance brought on by the glucose they do consume (in smaller doses and with less sugar).

The fact that East Asians didn’t have high rates of diabesity (diabetes and obesity) was a big blow to the carbohydrate insulin hypothesis. However, the East Asian rice paradox is simply explained by low, if non-existent, consumption of refined carbohydrates. Those populations actually consume fewer total carbohydrates than Western diets, and have lower levels of glycemic load as a result. To quote Mark Sisson:

Before recently, Asians ate less refined sugar and used animal fats for cooking. Sugar intake is rising now, of course, and cooking oils made from corn and soybean have largely replaced lard and tallow, but rice in the context of a low-sugar, no-HFCS (remember, the oft-cited 55/45 fructose/glucose breakdown for HFCS is highly misleading and actually quite often incorrect), low-vegetable oil, nose-to-tail nutrient-dense diet is (or was) acceptable. You can’t reduce a food down to its constituent parts and focus on, say, the bit of fructose in a blueberry and then condemn the entire berry because of it. Similarly, you can’t reduce a diet down to a single constituent food and condemn – or praise – it based on that single food. You have to look at the entire picture, and the Asian diet is largely a nutritious one.

These paradoxes where one population seems to disprove a certain hypothesis are pretty easily explainable with the existing data. There are numerous reasons why East Asian rice eaters have lower rates of diabesity. Dr. Jason Fung also explains why:

Wheat, particularly in the modern iteration may be particularly fattening for numerous reasons.  The high level of amylopectin means that most of the starch contained in flour is efficiently converted to glucose.  This deadly combination of wheat and sugar has been introduced into the Chinese diet.  The result is a Chinese diabetes catastrophe.  The prevalence of diabetes in China has now even outstripped the USA.

This is the answer to the paradox of the Asian Rice eater puzzle.  Why didn’t the Chinese have a diabetes epidemic in 1990 with all their white rice?  Well, because they didn’t eat any sugar (fructose), they were not developing insulin resistance.  Because they were not snacking all the time, they had periods of low insulin level that helped prevent the development of insulin resistance.  So the high rice intake by itself was not enough to cause either of diabetes or obesity.

Then he says that whites intake more total carbs in comparison to blacks and ‘Hispanics’ (1:32 in the video). This is wrong.

Diaz et al (2005) showed that minority populations are more likely to be affected by diabetes mellitus which may be due to less healthy diets and/or genetic factors. Using the National Health and Nutrition Survey for 1999-2000, they analyzed overweight, healthy adults, calculating dietary intake variables and insulin sensitivity by ethnicity. They characterized insulin resistance with fasted insulin, as those who are more likely to become insulin resistant have higher fasted insulin levels (levels taken after waking, with the subject being told not to eat the night before as to get a better reading of fasted insulin levels). Non-‘Hispanic’ whites had higher energy and fat intake while ‘Hispanics’ had higher carb intake with blacks having lower fiber intake.  Blacks and ‘Hispanics’ were more likely to have lower insulin sensitivity. However, ‘Hispanics’ were more likely to have lower insulin sensitivity even after controlling for diet, showing that metabolic differences exist between ethnicities that affect carbohydrate metabolism which leads to higher rates of diabetes in those populations.

Diaz et al state in the results of the study:

Dietary differences are seen by ethnicity, with non-Hispanic whites having higher
energy, saturated fat and total fat intake, while Hispanics had higher carbohydrate intake and African-Americans had lower fibre intake.Both African-Americans and Hispanics had higher levels of fasting insulin, demonstrating lower insulin sensitivity in comparison with non-Hispanic whites.
Non-‘Hispanic’ whites have higher overall energy and fat intake. This means that carbohydrates are less of a percent of the overall diet. In comparison, blacks had lower fiber intake. This means that they eat more processed foods. The same with ‘Hispanics’. Since they constantly spike their insulin with refined carbs, they have higher rates of fasted insulin and thus, have lower insulin sensitivity which is a risk factor for pre-diabetes.
Moreover, from my own personal work with people’s diets, whites eat less refined carbs than blacks or ‘Hispanics’, and while an anecdote, I’ve worked with hundreds of people.
Table 2 of the study shows that whites have a higher total kcal intake in comparison to blacks and ‘Hispanics’, ‘Hispanics’ have a statistically significant higher carb consumption, and blacks eat less fiber. Since whites eat more dietary fat and have a higher fiber intake, that protects them against higher rates of the *average population* that will be obese. Blacks consume less fiber. Dietary fiber actually protects against obesity, so the fact that blacks don’t eat more fiber shows that they eat more refined foods (it’s easily explainable why ‘Hispanics’ eat more fiber. They consume more beans and other fibrous, whole foods). However, since ‘Hispanics’ are more likely to be poor (correlated with low intelligence), they then cannot afford higher quality foods.
Drewnowski and Specter (2004) showed that 1) the highest rates of obesity are found in populations with the lowest incomes and education (correlated with IQ); 2) an inverse relationship between energy density and energy cost; 3) sweets and fats have higher energy density and are more palatable (food scientists work feverishly in labs to find out different combinations of foods to make them more palatable so we will eat more of them); and 4) poverty and food insecurity are associated with lower food expenditures, lower fruit and vegetable intake, and lower-quality diet. All of these data points show that those who are poor are more likely to be obese due to more energy-dense food being cheaper and fats and sugars being more palatable. it’s worth noting that dietary fat combined with carbohydrates and the subsequent insulin spike stores the dietary fat as body fat as well as the insulin telling the body to not burn fat.

I’ve written more on this here and here.

So now that I’ve established that blacks and ‘Hispanics’ consume more total carbohydrates from refined foods, now I’ll show the physiologic effects of insulin.

Insulin inhibits the breakdown of fat in the adipose tissue by inhibiting the lipase that hydrolyzes (the chemical breakdown of a compound due to a reaction with water) the fat out of the cell. Since insulin facilitates the entry of glucose into the cell, when this occurs, the glucose is synthesized into glycerol. Along with the fatty acids in the liver, they both are synthesized into triglycerides in the liver. Due to these mechanisms, insulin is directly involved with the shuttling of more fat into the adipocyte. Since insulin has this effect on fat metabolism in the body, it has a fat-sparing effect. Insulin drives most cells to prefer carbohydrates for energy. Putting it all together, insulin indirectly stimulates the accumulation of fat into the adipose tissue.

Do you see why blacks and ‘Hispanics’ are more susceptible to obesity?

Another glaring error he commits is not separating refined carb consumption with natural carb consumption. Refined carbs spike insulin much more than those foods with natural carbohydrates. East Asians do not have a “higher carbohydrate tolerance than Europeans” (2:06 in the video). This one huge error he commits completely discredits his hypothesis.

He then goes on to talk about India’s diabetes rates. But why is it increasing? Because of Western diets. It’s not about a “lower carbohydrate tolerance” as he says at 3:07, it’s about consuming more refined carbohydrates.

Then at 5:05, he says that he’s “solved Gary Taubes’s race problem in regards to diet”. He did nothing of the sort.

I, of course, have no problem with his IQ data. I have a problem with the conclusions he jumps to in regards to carbohydrates and diabetes. He clearly didn’t look at other factors that would explain why East Asians have lower rates of diabesity (which is increasing as they adopt a Western lifestyle… Weird…). The same thing explains it with the Australian Aborigines.

I have absolutely no problem with the second half of his video. My problem is the first half of it–his denigration of Taubes, non-understanding of insulin spikes in comparison to the quality of carbohydrate ingested and not controlling for refined carbs– as it’s clear he didn’t do extensive research into these populations (which Taubes and others have) to show why they don’t have higher rates of diabesity.

What he doesn’t touch on are “obesogenic environments” which is defined as “the sum of influences that the surroundings, opportunities, or conditions of life have on promoting obesity in individuals or populations”. What a huge coincidence that most of the populations he cited today with higher rates of diabesity live in first-world nations, otherwise known as obesogenic environments.

He should have spoken about the Pima Indians and their rates of diabesity. They didn’t have rates of diabesity as high 100 years ago. Why? The introduction of the obesogenic environment. Prisancho (2003) in his study on the Pima and reduced fat oxidation in first-world countries showed how the Pima preferentially burn carbs and not body fat for energy. Fat-burning would account for 9 kcal lost and CHO for 4. Since they preferentially burn carbs for energy and not fat, this shows why they have higher rates of diabesity. It’s not that it’s a genetic susceptibility to burn CHO for energy over fat (there may be a small genetic component, but it doesn’t override the effects of the actual diet). I’ve shown insulin’s role in fat storage above, do you see why the Pima have this diabesity epidemic after the introduction of refined carbohydrates and the obesogenic environment?

Added sugars and salts in foods causes us to want more of those foods. As I alluded to above, food scientists continuously work to find out which combinations of sugar, salt and fat will be more hyperpalatable to us and make us eat them more. Whites nor East Asians have a ‘higher carb tolerance’, they just eat different types of carbs (mostly unrefined, in comparison to blacks and ‘Hispanics’ anyway). If any individual were to overeat on high carb foods they would become diabetic and obese. Whites nor East Asians are exempt from that.

In sum, he didn’t look at where the carbs came from, only total carb intake. Refined carbs and unrefined carbs do different things in the body. The whiter a processed food is, the more it is refined. The more a food is processed, the more its natural nutrients such as fiber are taken out. These low-fat refined foods are one cause of obesity. However, it’s way too complicated to say that only refined carbohydrates cause diabesity.

I strongly recommend he read Taubes’s and Fung’s books. If he did, he wouldn’t have said what he said about Taubes’s theory and completely disregard the absolute total amount of carb intake and not the total amount of carbohydrates ingested.

Ethnic Differences in Sleep, Obesity, and Metabolic Syndromes

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Ethnic differences in the prevalence of obesity occur, majorly in part due to differences in the rates of metabolic syndrome (which is actually a few variables including high blood pressure, high blood sugar which leads to insulin resistance, excess visceral fat around the waist which is the ‘skinny fat‘ phenomenon, and abnormal blood pressure levels) and obesity. Ethnic differences in these variables do, in part, show how the three ethnies differ in rates of obesity. I will discuss the differences between each ethny in regards to metabolic syndrome and sleep and how it leads to the differences in ethnic obesity rates.

Sleep Differences

There is a ‘missing hour of sleep‘ when comparing blacks and whites. On average, blacks get 6.05 hours of sleep while whites get 6.85 hours of sleep. Of course, the same old racism argument comes up, which, if one ‘percieves’ discrimination, I wouldn’t doubt that it would have an effect on sleep due to a rise in cortisol, which affects sleep due to the raised levels making you restless and not able to fall asleepInsulin levels then rise due to the rise in cortisol, which is the cause of obesity.

Some studies may try to say that racism and other forms of discrimination are a factor, without even thinking of genetic factors. Another study that Frost cites says that duration of deep sleep and duration of stage 2 (light sleep) is correlated correlated in African Americans with perceived discrimination. The authors defined ‘perceived discrimination’ as the extent to which one believes that their ethnic group have been discriminated against by society. Still even when controlling for discrimination, there were still marked differences between blacks and whites and how long they slept.

Frost then talks about how sleep patterns are heritable and cites studies done on Africans in Africa. One study found that there was an hour sleep difference between Ghanaians and Norwegians on the week days and between a quarter to half hour less on weekends. He shows another study showing that Nigerian college students sleep 6.2 hours a day while getting 70-minute naps in the afternoon.

Frost concludes that the African sleep patterns is normal on Africa. Africans are more active during the cooler times of the day and sleep during the bitter periods. Frost says those who evolved in more northerly climes are particularly adapted to a certain sleep pattern with the same holding true for Africans.

However, these sleep patterns in first world countries have negative effects on metabolism and rates of obesity.

Here are some more studies showing that blacks sleep less than whites:

The sleep of African Americans: a comparative review: The researchers found that blacks take longer to fall asleep than whites, report poorer sleep quality, have more light and less deep sleep, and nap more often and longer. This is a huge recipe for risk factors for obesity, and it shows in their demographics.

Unfair Treatment is associated with Poor Sleep in African American and Caucasian Adults: Pittsburgh SleepSCORE Project: This is one of the studies spoken about above that show that discrimination leads to less sleep. Though, it holds for both black and white adults. The researchers conclude:

Taken together, the confluence of perceived unfair treatment as a chronic stressor and poor sleep and the interplay between the two may have critical roles in long-term health problems.

African Genetic Ancestry is Associated with Sleep Depth in Older African Americans: The researchers hypothesized that “racial differences in sleep phenotypes would show an association with objectively measured individual genetic ancestry in AAs.” They conclude that the slow wave sleep may have genetic underpinnings.

Mexican Americans sleep less than do Mexican immigrants. US-born Mexicans are 40 percent more likely to be short sleepers. This is attenuated by environmental factors such as smoking and stress, which shorten the duration of sleep (smoking decreases the Body Set Weight, whereas cortisol along with insulin in tandem increase it).

Also, in this study by Roane et al (2014) looked at the link between sleep disturbances and stress in Mexican Americans (average age 55) and non-‘Hispanic’ whites (average age 66). Mexicans reported higher levels of sleep disturbance (25 percent) compared to whites (17 percent). They conclude that disturbed sleep was positively correlated with depression.

So both blacks and Mexicans sleep less than whites. These differences in sleep between these three ethnies also affect the prevalence of obesity in these populations.

Obesity and Sleep

It’s long been known that poor sleep habits make people fat. This is due to the effects of insulin and cortisol. Increased insulin comes before increased cortisol–increased insulin is the cause for obesity. Sleeping less is linked to obesity. Since, as described above, the three ethnies differ in sleep patterns, the same also holds true for obesity rates (Ogden at al, 2014). The trends are as follows: 67.3% for whites, 75.6% for blacks, and 77.9% for Hispanics. Though, sleep is only one factor involved with obesity.

Getting adequate sleep is extremely important. Not doing so can lead to a myriad of negative health implications:

Sleep is an important modulator of neuroendocrine function and glucose metabolism and sleep loss has been shown to result in metabolic and endocrine alterations, including decreased glucose tolerance, decreased insulin sensitivity, increased evening concentrations of cortisol, increased levels of ghrelin, decreased levels of leptin, and increased hunger and appetite. Recent epidemiological and laboratory evidence confirm previous findings of an association between sleep loss and increased risk of obesity.

So a lack of sleep leads to an increase in ghrelin levels, decreased levels of leptin (the same effects as caloric restriction over time), increased appetite and hunger, increased evening cortisol (which insulin spikes then follow), decreased insulin sensitivity (the cortisol brings it back up and most people are insulin resistant independent of diet), decreased glucose tolerance, etc. We can see that these ethnic differences in sleep, which are partly genetic in nature, can and would have great effects on metabolism, contributing to the ethnic differences in obesity rates.

And from Harvard:

For example, in the Nurses’ Health Study, researchers followed roughly 60,000 women for 16 years, asking them about their weight, sleep habits, diet, and other aspects of their lifestyle. (2) At the start of the study, all of the women were healthy, and none were obese; 16 years later,women who slept 5 hours or less per night had a 15 percent higher risk of becoming obese, compared to women who slept 7 hours per night. Short sleepers also had 30 percent higher risk of gaining 30 pounds over the course of the study, compared to women who got 7 hours of sleep per night.

Damn!! This, pretty much, mirrors the black-white difference. I’d love to see a racial breakdown of this cohort and will keep an eye out for one, but in the meantime, those who were short sleepers had a 30 percent higher risk of gaining 30 pounds over the course of the study in comparison to women who got 7 hours of sleep per night. Blacks are the most likely group to be overweight and obese in the US, and this data from the Nurses Health Study (which tons of data can be drawn from this study) shows one reason why, however the driver is cortisol > insulin > processed carbs > increased insulin > insulin resistance > increased insulin > vicious cycle > obesity. These differences in sleep almost perfectly mirror the ethnic differences in obesity.

There are several possible ways that sleep deprivation could increase the chances of becoming obese. (1) Sleep-deprived people may be too tired to exercise, decreasing the “calories burned” side of the weight-change equation. Or people who don’t get enough sleep may take in more calories than those who do, simply because they are awake longer and have more opportunities to eat; lack of sleep also disrupts the balance of key hormones that control appetite, so sleep-deprived people may be hungrier than those who get enough rest each night.

Ah the old ‘exercise to increase the Calories Out part of the equation’. however, Calories Out does not stay constant. This also rebuts the ‘Eat Less and Move More’ CICO (Calories In/Calories Out) model of obesity, showing that because it doesn’t take insulin into account, it’s doomed to fail.

Speaking of insulin, it’s about time I focused on metabolic syndrome.

Metabolic Syndrome

As I discussed in a previous post, Race, Obesity, Poverty, and IQ, metabolic differences exist between race/ethnicity. ‘Hispanics’ metabolize carbohydrates differently, blacks have a lower fiber intake (increased fiber protects against obesity, another correlate) while whites have a more high fat diet. Contrary to popular belief, dietary fat doesn’t make you fat as it’s the macro that spikes your insulin the least.

Diaz et al (2005) showed that minority populations are more likely to be affected by diabetes mellitus which may be due to less healthy diets and/or genetic factors. Using the National Health and Nutrition Survey for 1999-2000, they analyzed overweight, healthy adults, calculating dietary intake variables and insulin sensitivity by ethnicity. They characterized insulin resistance with fasted insulin, as those who are more likely to become insulin resistant have higher fasted insulin levels (levels taken after waking, with the subject being told not to eat the night before as to get a better reading of fasted insulin levels). Non-‘Hispanic’ whites had higher energy and fat intake while ‘Hispanics’ had higher carb intake with blacks having lower fiber intake.  Blacks and ‘Hispanics’ were more likely to have lower insulin sensitivity. However, ‘Hispanics’ were more likely to have lower insulin sensitivity even after controlling for diet, showing that metabolic differences exist between ethnicities that affect carbohydrate metabolism which leads to higher rates of diabetes in those populations.

In ‘Hispanics’, several loci were discovered that play a role in hepatic (relating to the liver) fat content. Along with showing that ‘Hispanics’ have lower insulin (which due to low insulin, blood glucose builds up in the blood stream leading to diabetes) and showing that they metabolize glucose in the liver differently due to differing loci leading to more cases of fatty liver, this shows how and why ‘Hispanics’ have higher rates of Type II Diabetes Mellitus (TIIDM).

Since TIIDM affects Mexican Americans more, better measures to address their differences in carbohydrate metabolism need to be taken. Racial and ethnic differences in TIIDM are as follows:

7.6% of non-Hispanic whites

9.0% of Asian Americans

12.8% of Hispanics

13.2% of non-Hispanic blacks

15.9% of American Indians/Alaskan Natives

Whites eat a higher fat diet, which means a decrease in carbs. Asians eat white rice which spikes blood glucose eliciting a high insulin response leading to TIIDM, ‘Hispanics’, non-‘Hispanic’ blacks, and Indians and Alaskan Natives (I wish they separated Indians and Alaskan Natives as I’m almost positive that Alaskan natives have a lower rate) all eat high carb, low fat, low protein diets. Carbohydrates are a main staple, and since they spike insulin the most, they are the cause for obesity and TIIDM rates in these populations.

Turning my attention over to metabolic syndrome and blacks and whites, we can see that black women with PCOS have an increased risk for cardiovascular disease and metabolic syndrome in comparison to white women with PCOS. The researchers say that after controlling for age and body mass index (BMI) “black women with PCOS had a significantly increased prevalence of low high-density lipoprotein and high glucose. The general CVD risk was significantly increased in black adults with PCOS.” Though, a longitudinal study needs to be carried out to assess the independent impact of race and PCOS with CVD (Cardiovascular Disease).

Blacks have a higher chance to be diagnosed with metabolic syndrome since they are also at increased risk to have elevated blood pressure (hypertension), become obese, and be diabetic. This is due to their diet, which is due to their low IQ (obesity is correlated with intelligence), and different metabolism in comparison to whites.

There are also metabolic differences between race and sex. Fat oxidation is lower in black than white men and in African American men/women and white men/women, they have a lower metabolic rate!!! 24-hour energy expenditure is lower in black women in comparison to white women, whereas physical activity energy expenditure (PAEE) is the same as whites. Contrasted with women, black men had higher PAEE than white men. The authors conclude:

In conclusion, this comparative study of 24-h energy metabolism in African Americans and whites with use of a respiratory chamber not only confirms the previous findings from ventilated-hood studies of a lower resting metabolic rate, but also suggests a lower 24EE in African American women than in white women. Although only marginal ethnic differences in metabolic rate were found in men, African American men seem to have a lower rate of fat oxidation than do white men. The underlying mechanisms for these sex differences and the significance of these findings with respect to the development and maintenance of obesity remains to be investigated in longitudinal studies.

Metabolic Syndrome and Obesity

Seeing how the body acts when it has a lower metabolic rate due to the numerous confounders speaks for itself in regards to obesity. Metabolic syndrome does precede obesity a lot of the time. With insulin being one of the main drivers of metabolic syndrome, and with poor sleep being linked to metabolic syndrome, we can see how these factors combine to affect the health of the populations in question.
Conclusion
Sleep is a huge part of health, as it is important for brain activity among numerous other important factors. Not getting enough sleep causes the body to release hormones to make you eat more, hold more weight around your midsection (that’s one thing that cortisol does), have a decreased metabolism, and eventually leads to TIIDM. The fact that ethnies in America differ in metabolic syndrome and hours of sleep gotten per night shows that some of the obesity epidemic, both within and between race/ethnicity is genetic in origin due to carbohydrate metabolism and low insulin sensitivity independant of diet which raises insulin which then leads to obesity.

 

Race, Obesity, Poverty, and IQ

2100 words

America has a current and ongoing obesity epidemic. Some ethnicities are more likely to be obese or overweight than others due to lower intelligence which means a lack of ability to delay gratification, lack of ability to think into the future, lower funds which translates to eating more refined carbohydrates which means more blood glucose spikes which then leads to obesity as I will show. Insulin has a causal relationship with obesity so those who lack funds to buy healthier food then turn to refined foods high in carbohydrates as they are cheaper and more abundant in low-income neighborhoods.

Adult obesity rate by State (top 5) is: 1) Louisiana (36.2 percent), 2) Alabama (35.6), West Virginia (35.6), and Mississippi (35.6), and 5) Kentucky (34.6) with the 5 least obese States being 51) Colorado (20.2), 49) Hawaii (20.7), 48) Montana (23.6), 47) California (23.2), and 46) Massachusetts (24.3). Notice how the States with higher rates of obesity are in the South and the States with the lower rates are in the North, give or take. The average IQ for these States as follows: Lousiana: 95.3, Alabama: 95.7, West Virginia 98.7, Mississippi 94.2 (lowest IQ State in the country, largest black population at 37 percent), and Kentucky at 99.4. The average IQ for those States is 96.66. The average IQs for the States with the lowest obesity rates are: Colorado 101.6, Hawaii 95.6, Montana 103.4, California 95.5, and Massachusets 104.3 (highest IQ State). The average for these States being 100.08. So there is a 4 point IQ difference between the top 5 States with the highest and lowest percentage of obese people, which goes with the North/South gradient of higher IQ people living in the North and lower IQ people living in the South. Back in 2014, a California real estate group took 500,000 Tweets using a computer algorithm and estimated intelligence based on spelling, grammar, and word choice and found a difference in State by State intelligence. Notice how the further North you go the higher the average intelligence is, which is then correlated with the obesity levels in that State.

With poverty rates by State, we can see how the States in the South have less intelligent people in them which then correlates to the amount of obesity in the State. Though, there are some anomalies. West Virginia and Kentucky have a super majority of whites. This is easily explained by the fact that less intelligent whites live in those States, and since both the poverty rates and obesity rates are high, it follows that the State will be less intelligent than States that have more intelligent people and less obesity.

It is known that intelligence is correlated with obesity at around -.25 (Kanazawa, 2014). The negative correlation between intelligence and obesity means that they are inversely related so, on average, one with higher intelligence has less of a chance of being obese than one with lower intelligence. The States with the lowest IQ people having those with the highest BMIs corroborates this. In America, obesity rates by ethnicity are as follows: 67.3% for whites, 75.6% for blacks, and 77.9% for ‘Hispanics’.

Now that we know the average intelligence rates by State, the percentage of obese by State and the demographics by State, we can get into why obesity rates correlate with intelligence and race.

Diaz et al (2005) showed that minority populations are more likely to be affected by diabetes mellitus which may be due to less healthy diets and/or genetic factors. Using the National Health and Nutrition Survey for 1999-2000, they analyzed overweight, healthy adults, calculating dietary intake variables and insulin sensitivity by ethnicity. They characterized insulin resistance with fasted insulin, as those who are more likely to become insulin resistant have higher fasted insulin levels (levels taken after waking, with the subject being told not to eat the night before as to get a better reading of fasted insulin levels). Non-‘Hispanic’ whites had higher energy and fat intake while ‘Hispanics’ had higher carb intake with blacks having lower fiber intake.  Blacks and ‘Hispanics’ were more likely to have lower insulin sensitivity. However, ‘Hispanics’ were more likely to have lower insulin sensitivity even after controlling for diet, showing that metabolic differences exist between ethnicities that affect carbohydrate metabolism which leads to higher rates of diabetes in those populations.

Drewnowski and Specter (2004) showed that 1) the highest rates of obesity are found in populations with the lowest incomes and education (correlated with IQ), 2) an inverse relationship between energy density and energy cost, 3) sweets and fats have higher energy density and are more palatable (food scientists work feverishly in labs to find out different combinations of foods to make them more palatable so we will eat more of them), and 4) poverty and food insecurity are associated with lower food expenditures, lower fruit and vegetable intake, and lower-quality diet. All of these data points show that those who are poor are more likely to be obese due to more energy-dense food being cheaper and fats and sugars being more palatable.

Now that I’ve shown the relationship between race and IQ by state, obesity rates by state, insulin sensitivity by race, and that those in poverty are more likely to be obese, I can now talk about the actual CAUSE of obesity: insulin.

The conventional wisdom is that if you consume more kcal than you expend, you will gain weight, whereas if you consume less than your daily needs you will lose weight. This has been unchallenged for 50 years. Also known as Calories In and Calories Out (CICO), this mantra “eat less and move more!!!” has been bleated over and over with horrendous results. The CICO model only concerns itself with calories and not insulin which is a causal factor in obesity

In this study, participants in the basal insulin group which received the lowest average insulin dose gained the least average amount of weight at 4.2 pounds. Those on prandial insulin gained the most weight at 12.5 pounds. The intermediate group gained 10.3 pounds. More insulin, more weight gain. Moderate insulin, moderate weight gain. Low insulin, low weight gain.

Researchers compared a standard dose of insulin to tightly control blood sugars in type 1 diabetic patients. At the end of the 6 years, the study proved that intensive control of blood sugars resulted in fewer complications for those patients.

Though, in the high dose group, they gained on average 9.8 pounds more than those in the standard group.

More than 30 percent experienced major weight gain! Prior to the study, both groups were equal in weight. But the only difference was the amount of insulin administered. Were the ones given high levels of insulin all of a sudden more lazy? Were those who gained weight suddenly lacking in willpower? Were they lazier before the study? We’re they more gluttonous? No, no, and no!!

delprato_24

(source)

Finally, Henry et al (1993) took Type II diabetics and started them off with no insulin. They went from 0 units of insulin a day to 100 units at 6 months. As higher rates of insulin were administered, weight rose in the subjects. Insulin was given, people gained weight. A direct causal relationship (see figure above). However, what’s interesting about this study is that the researchers measured the amount of kcal ingested, the number of kcal ingested was reduced to 300 per day. Even as they took in less kcal, they gained 20 pounds! What’s going on here? Well, insulin is being administered and if you know anything about insulin it’s one of the hormones in the body that tells the body to either store fat or not burn it for energy. So what is occurring is the body is ramping down its metabolism in order for the subject to store more fat due to the exogenous insulin administered. Their TDEE dropped to about 1400 kcal, while they should have been losing weight on 1700 kcal! The CICO model predicts they should have lost weight, however, adaptive thermogenesis, better known as metabolic slow down, occurred which dropped the TDEE in order for the body to gain fat, as insulin directly causes obesity by signaling the body to store fat, so the body drops its metabolism in an attempt to do so. 

Putting this all together, blacks and ‘Hispanics’ are more likely to be in poverty, have lower intelligence, and have higher rates of obesity and diabetes. Furthermore, blacks are more likely to have metabolic diseases (adaptive thermogenesis aka metabolic slowdown is a metabolic disease) which are related with obesity due to their muscle fiber typing which leads to lower maximal aerobic capacity (less blood and oxygen get around the body). Type II skeletal muscle fibers’ metabolic profile contributes to lower average aerobic capacity in blacks. It also is related to cardiometabolic diseases, in my opinion because they don’t have the muscle fiber typing to run long distances, thus increasing their aerobic capacity and VO2 max.

Due to the diets they consume, which, due to being in poverty and having lower intelligence, they consume more carbohydrates than whites, which jacks their blood glucose levels up and the body then releases insulin to drive the levels glucose in the body down. As insulin levels are spiked, the body becomes insulin resistant due to the low-quality diet. Over time, even a change in diet won’t fix the insulin resistance in the body. This is because since the body is insulin resistant it created more insulin which causes insulin resistance, a vicious cycle.

Poverty, intelligence and race both correlate with obesity, with the main factor being lower intelligence. Since those with lower IQs have a lack of foresight into the future, as well as a lower ability to delay gratification which also correlates with obesity, they cannot resist low-quality, high-carb food the same way one with a higher IQ can. This is seen with the Diaz et al study I linked, showing that whites have higher levels of fat intake, which means lower levels of carbohydrate intake in comparison to blacks and ‘Hispanics’. As I’ve shown, those in poverty (code word for low intelligence) ingest more refined carbohydrates, they have higher levels of obesity due to the constant spiking of their insulin, as I have shown with the 3 aforementioned studies. Since blacks and ‘Hispanics’ have lower levels of intelligence, they have lower levels of income which they then can only afford cheap, refined carbs. This leads to insulin being constantly spiked, and with how Americans eat nowadays (6 times a day, 3 meals and snacks in between), insulin is being spiked constantly with it only dipping down as the body goes into the fasted state while sleeping. This is why these populations are more likely to be obese, because they spike their insulin more. The main factor here, of course, is intelligence.

Another non-CICO cause for obesity is exposure to BPA in the womb. Researchers carried out BPA testing in three differing subjects: 375 babies invitro, (3rd trimester) children aged 3 (n=408) and aged 5 (n=518) (Hoepner, et al, 2016). They measured the children’s bodies as well as measuring body fat levels with bioelectrical impedance scales.Prenatal urinary BPA was positively associated with waist circumference as well as fat mass index, which was sex-specific. When analyzed separately, it was found that there were no associated outcomes in body fat for boys (however it does have an effect on testosterone), but there was for girls (this has to do with early onset puberty as well). They found that after controlling for SES and other environmental factors there was a positive correlation with fat mass index – a measure of body fat mass adjusted for height, body fat percentage and waist circumference. The researchers say that since there was no correlation between BPA and increased obesity, that prenatal exposure to BPA indicates greater vulnerability in that period. The sample was of blacks and Dominicans from New York City. Whites drink less bottled water, which has higher levels of BPA. Blacks and ‘Hispanics’ consume more, and thus have higher levels of obesity.

In conclusion, blacks and ‘Hispanics’ are more likely to be in poverty, have lower intelligence, higher rates of obesity and lower incomes. Due to lower incomes, cheap, refined carbohydrates is what they can afford in bulk as that’s mostly what’s around poor neighborhoods. Ingesting refined carbohydrates more often consistently jacks up blood glucose which the body then releases insulin to lower the levels. Over time, insulin resistance occurs, which then leads to obesity. As I’ve shown, there is a direct causal relationship between the amount of insulin administered and weight gain. With the aforementioned factors with these two populations, we can see how the hormonal theory of obesity fits in perfectly with what we know about these ethnic groups and the obesity rates within them. Since people in poverty gravitate more towards cheap and refined carbohydrates, they’re constantly spiking their insulin which, over time, leads to insulin resistance and obesity.