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JP Rushton

Richard Lynn

Linda Gottfredson

The Evolution of Human Skin Variation

4050 words

Human skin variation comes down to how much UV radiation a population is exposed to. Over time, this leads to changes in genetic expression. If that new genotype is advantageous in that environment, it will get selected for. To see how human skin variation evolved, we must first look to chimpanzees since they are our closest relative.

The evolution of black skin

Humans and chimps diverged around 6-12 mya. Since we share 99.8 percent of our genome with them, it’s safe to say that when we diverged, we had pale skin and a lot of fur on our bodies (Jablonski and Chaplin, 2000). After we lost the fur on our bodies, we were better able to thermoregulate, which then primed Erectus for running (Liberman, 2015). The advent of fur loss coincides with the appearance of sweat glands in Erectus, which would have been paramount for persistence hunting in the African savanna 1.9 mya, when a modern pelvis—and most likely a modern gluteus maximus—emerged in the fossil record (Lieberman et al, 2006). This sets the stage for one of the most important factors in regards to the ability to persistence hunt—mainly, the evolution of dark skin to protect against high amounts of UV radiation.

After Erectus lost his fur, the unforgiving UV radiation beamed down on him. Selection would have then occurred for darker skin, as darker skin protects against UV radiation. Dark skin in our genus also evolved between 1 and 2 mya. We know this since the melanocortin 1 receptor promoting black skin arose 1-2 mya, right around the time Erectus appeared and lost its fur (Lieberman, 2015).

However, other researchers reject Greaves’ explanation for skin cancer being a driver for skin color (Jablonksi and Chaplin, 2014). They cite Blum (1961) showing that skin cancer is acquired too late in life to have any kind of effect on reproductive success. Skin cancer rates in black Americans are low compared to white Americans in a survey from 1977-8 showing that 30 percent of blacks had basal cell carcinoma while 80 percent of whites did (Moon et al, 1987). This is some good evidence for Greaves’ hypothesis; that blacks have less of a rate of one type of skin cancer shows its adaptive benefits. Black skin evolved due to the need for protection from high levels of UVB radiation and skin cancers.

Highly melanized skin also protects against folate destruction (Jablonksi and Chaplin, 2000). As populations move away from high UV areas, the selective constraint to maintain high levels of folate by blocking high levels of UV is removed, whereas selection for less melanin prevails to allow enough radiation to synthesize vitamin D. Black skin is important near the equator to protect against folate deficiency. (Also see Nina Jablonski’s Ted Talk Skin color is an illusion.)

The evolution of white skin

The evolution of white skin, of course, is much debated as well. Theories range from sexual selection, to diet, to less UV radiation. All three have great explanatory power, and I believe that all of them did drive the evolution of white skin, but with different percentages.

The main driver of white skin is living in colder environments with fewer UV rays. The body needs to synthesize vitamin D, so the only way this would occur in areas with low UV rays.

White skin is a recent trait in humans, appearing only 8kya. A myriad of theories have been proposed to explain this, from sexual selection (Frost, 2007), which include better vitamin D synthesis to ensure more calcium for pregnancy and lactation (which would then benefit the intelligence of the babes) (Jablonski and Chaplin, 2000); others see light skin as the beginnings of more childlike traits such as smoother skin, a higher pitched voice and a more childlike face which would then facilitate less aggressiveness in men and more provisioning (Guthrie, 1970; from Frost, 2007); finally, van den Berghe and Frost (1986) proposed that selection for white skin involved unconscious selection by men for lighter-skinned women which is used “as a measure of hormonal status and thus childbearing potential” (Frost, 2007). The three aforementioned hypotheses have sexual selection for lighter skin as a proximate cause, but the ultimate cause is something completely different.

The hypothesis that white skin evolved to better facilitate vitamin D synthesis to ensure more calcium for pregnancy and lactation makes the most sense. Darker-skinned individuals have a myriad of health problems outside of their ancestral climate, one of which is higher rates of prostate cancer due to lack of vitamin D. If darker skin is a problem in cooler climates with fewer UV rays, then lighter skin, since it ensures better vitamin D synthesis, will be selected for. White skin ensures better and more vitamin D absorption in colder climates with fewer UV rays, therefore, the ultimate cause of the evolution of white skin is a lack of sunlight and therefore fewer UV rays. This is because white skin absorbs more UV rays which is better vitamin D synthesis.

Peter Frost believes that Europeans became white 11,000 years ago. However, as shown above, white skin evolved around 8kya. Further, contrary to popular belief, Europeans did not gain the alleles for white skin from Neanderthals (Beleza et al, 2012). European populations did not lose their dark skin immediately upon entering Europe—and Neanderthal interbreeding didn’t immediately confer the advantageous white skin alleles. There was interbreeding between AMH and Neanderthals (Sankararaman et al, 2014). So if interbreeding with Neanderthals didn’t infer white skin to proto-Europeans, then what did?

A few alleles spreading into Europe that only reached fixation a few thousand years ago. White skin is a relatively recent trait in Man (Beleza et al, 2012). People assume that white skin has been around for a long time, and that Europeans 40,000 ya are the ancestors of Europeans alive today. That, however, is not true. Modern-day European genetic history began about 6,500 ya. That is when the modern-day European phenotype arose—along with white skin.

Furthermore, Eurasians were still a single breeding population 40 kya, and only diverged recently, about 25,000 to 40,000 ya (Tateno et al, 2014). The alleles that code for light skin evolved after the Eurasian divergence. Polymorphisms in the genes ASIP and OCA2 may code for dark and light skin all throughout the world, whereas SLC24A5, MATP, and TYR have a predominant role in the evolution of light skin in Europeans but not East Asians, which suggests recent convergent evolution of a lighter pigmentation phenotype in European and East Asian populations (Norton et al, 2006). Since SLC24A5, MATP, and TYR are absent in East Asian populations, then that means that East Asians evolved light skin through completely different mechanisms than Europeans. So after the divergence of East Asians and Europeans from a single breeding population 25-40kya, there was convergent evolution for light pigmentation in both populations with the same selection pressure (low UV).

Some populations, such as Arctic peoples, don’t have the skin color one would predict they should have based on their ancestral environment. However, their diets are high in shellfish which is high in vitamin D, which means they can afford to remain darker-skinned in low UV areas. UV rays reflect off of the snow and ice in the summer and their dark skin protects them from UV light.

Black-white differences in UV absorption

If white skin evolved to better synthesize vitamin D with fewer (and less intense) UV rays, then those with blacker skin would need to spend a longer time in UV light to synthesize the same amount of vitamin D. Skin pigmentation, however, is negatively correlated with vitamin D synthesis (Libon, Cavalier, and Nikkels, 2013). Black skin is less capable of vitamin D synthesis. Furthermore, blacks’ skin color leads to an evolutionary environmental mismatch. Black skin in low UV areas is correlated with rickets (Holick, 2006), higher rates of prostate cancer due to lower levels of vitamin D (Gupta et al, 2009; vitamin D supplements may also keep low-grade prostate cancer at bay).

Libon, Cavalier, and Nikkels, (2013) looked at a few different phototypes (skin colors) of black and white subjects. The phototypes they looked at were II (n=19), III (n=1), and VI (n-11; whites and blacks respectively). Phototypes are shown in the image below.

skin-type-chart

fitzpatrick-color-chart

To avoid the influence of solar UVB exposure, this study was conducted in February. On day 0, both the black and white subjects were vitamin D deficient. The median levels of vitamin D in the white subjects was 11.9 ng/ml whereas for the black subjects it was 8.6 ng/ml—a non-statistically significant difference. On day two, however, concentrations of vitamin D in the blood rose from 11.9 to 13.3 ng/ml—a statistically significant difference. For the black cohort, however, there was no statistically significant difference in vitamin D levels. On day 6, levels in the white subjects rose from 11.6 to 14.3 ng/ml whereas for the black subjects it was 8.6 to 9.57 ng/ml. At the end of day 6, there was a statistically significant difference in circulating vitamin D levels between the white and black subjects (14.3 ng/ml compared to 9.57 ng/ml).

Different phototypes absorb different amounts of UV rays and, therefore, peoples with different skin color absorb different levels of vitamin D. Lighter-skinned people absorb more UV rays than darker-skinned people, showing that white skin’s primary cause is to synthesize vitamin D.

UVB exposure increases vitamin D production in white skin, but not in black skin. Pigmented skin, on the other hand, hinders the transformation of 7-dehydrocholesterol to vitamin D. This is why blacks have higher rates of prostate cancer—they are outside of their ancestral environment and what comes with being outside of one’s ancestral environment are evolutionary mismatches. We have now spread throughout the world, and people with certain skin colors may not be adapted for their current environment. This is what we see with black Americans as well as white Americans who spend too much time in climes that are not ancestral to them. Nevertheless, different-colored skin does synthesize vitamin D differently, and knowledge of this will increase the quality of life for everyone.

Even the great Darwin wrote about differences in human skin color. He didn’t touch human evolution in On the Origin of Species (Darwin, 1859), but he did in his book Descent of Man (Darwin, 1871). Darwin talks about the effects of climate on skin color and hair, writing:

It was formerly thought that the colour of the skin and the character of the hair were determined by light or heat; and although it can hardly be denied that some effect is thus produced, almost all observers now agree that the effect has been very small, even after exposure during many ages. (Darwin, 1871: 115-116)

Darwin, of course, championed sexual selection as the cause for human skin variation (Darwin, 1871: 241-250). Jared Diamond has the same view, believing that natural selection couldn’t account for hair loss, black skin and white skin weren’t products of natural selection, but female mate preference and sexual selection (Greaves, 2014).

Parental selection for white skin 

Judith Rich Harris, author of the book The Nurture Assumption: Why Kids Turn Out the Way They Do (Harris, 2009), posits another hypothesis for the evolution of light skin for those living in northern latitudes—parental selection. This hypothesis may be controversial to some, as it states that dark skin is not beautiful and that white skin is.

Harris posits that selection for lighter skin was driven by sexual selection, but states that parental selection for lighter skin further helped the fixation of the alleles for white skin in northern populations. Neanderthals were a furry population, as they had no clothes, so, logic dictates that if they didn’t have clothes then they must have had some sort of protection against the cold Ice Age climate, therefore they must have had fur.

Harris states that since lighter skin is seen as more beautiful than darker skin, then if a woman birthed a darker/furrier babe than the mother would have committed infanticide. Women who birth at younger ages are more likely to commit infanticide, as they still have about twenty years to birth a babe. On the other hand, infanticide rates for mothers decrease as she gets older—because it’s harder to have children the older you get.

Harris states that Erectus may have been furry up until 2 mya, however, as I’ve shown, Erectus was furless and had the ability to thermoregulate—something that a hairy hominin was not able to do (Lieberman, 2015).

There is a preference for lighter-skinned females all throughout the world, in Africa (Coetzee et al, 2012); China and India (Naidoo et al, 2016; Dixson et al, 2007); and Latin America and the Philipines (Kiang and Takeuchi, 2009). Light skin is seen as attractive all throughout the world. Thus, since light skin allows better synthesize of vitamin D in colder climes with fewer UV rays, then there would have been a myriad of selective pressures to push that along—parental selection for lighter-skinned babes being one of them. This isn’t talked about often, but infanticide and rape have both driven our evolution (more on both in the future).

Harris’ parental selection hypothesis is plausible, and she does use the right dates for fur loss which coincides with the endurance running of Erectus and how he was able to thermoregulate body heat due to lack of fur and more sweat glands. This is when black skin began to evolve. So with migration into more northerly climes,  lighter-skinned people would have more of an advantage than darker-skinned people. Infanticide is practiced all over the world, and is caused—partly—by a mother’s unconscious preferences.

Skin color and attractiveness

Lighter skin is seen as attractive all throughout the world. College-aged black women find lighter skin more attractive (Stephens and Thomas, 2012). It is no surprise that due to this, a lot of black women lighten their skin with chemicals.

In a sample of black men, lighter-skinned blacks were more likely to perceive discrimination than their darker-skinned counterparts (Uzogara et al, 2014). Further, in appraising skin color’s effect on in-group discrimination, medium-skinned black men perceived less discrimination than lighter- and darker-skinned black men. Lastly—as is the case with most studies—this effect was particularly pronounced for those in lower SES brackets. Speaking of SES, lighter-skinned blacks with higher income had lower blood pressure than darker-skinned blacks with higher income (Sweet et al, 2007). The authors conclude that a variety of psychosocial stress due to discrimination must be part of the reason why darker-skinned blacks with a high SES have worse blood pressure—but I think there is something else at work here. Darker skin on its own is associated with high blood pressure (Mosley et al, 2000). I don’t deny that (perceived) discrimination can and does heighten blood pressure—but the first thing that needs to be looked at is skin color.

Lighter-skinned women are seen as more attractive (Stephen et al, 2009). This is because it signals fertility, femininity, and youth. One more important thing it signals is the ability to carry a healthy child to term since lighter skin in women is associated with better vitamin D synthesis which is important for a growing babe.

Skin color and intelligence

There is a high negative correlation between skin color and intelligence, about –.92 (Templer and Arikawa, 2006). They used the data from Lynn and Vanhanen’s 2002 book IQ and the Wealth of Nations and found that there was an extremely strong negative correlation between skin color and IQ. However, data wasn’t collected for all countries tested and for half of the countries the IQs were ‘estimated’ from other surrounding countries’ IQs.

Jensen (2006) states that the main limitation in the study design of Arikawa and Templer (2006) is that “correlations obtained from this type of analysis are completely non-informative regarding any causal or functional connection between individual differences in skin pigmentation and individual differences in IQ, nor are they informative regarding the causal basis of the correlation, e.g., simple genetic association due to cross-assortative mating for skin color and IQ versus a pleiotropic correlation in which both of the phenotypically distinct but correlated traits are manifested by one and the same gene.”

Lynn (2002) purported to find a correlation of .14 in a representative sample of American blacks (n=430), concluding that the proportion of European genes in African Americans dictates how intelligent that individual black is. However, Hill (2002) showed that when controlling for childhood environmental factors such as SES, the correlation disappears and therefore, a genetic causality cannot be inferred from the data that Lynn (2002) used.

Since Lynn found a .14 correlation between skin color and IQ in black Americans, that means that only .0196 percent of the variation in IQ within black American adults can be explained by skin color. This is hardly anything to look at and keep in mind when thinking about racial differences in IQ.

However, other people have different ideas. Others may say that since animal studies find that lighter animals are less sexually active, are less aggressive, have a larger body mass, and greater stress resistance. So since this is seen in over 40 species of vertebrate, some fish species, and over 30 bird species (Rushton and Templer, 2012) that means that it should be a good predictor for human populations. Except it isn’t.

Razib Khan states:

we know the genetic architecture of pigmentation. that is, we know all the genes (~10, usually less than 6 in pairwise between population comparisons). skin color varies via a small number of large effect trait loci. in contrast, I.Q. varies by a huge number of small effect loci. so logically the correlation is obviously just a correlation. to give you an example, SLC45A2 explains 25-40% of the variance between africans and europeans.

long story short: it’s stupid to keep repeating the correlation between skin color and I.Q. as if it’s a novel genetic story. it’s not. i hope don’t have to keep repeating this for too many years.

Finally, variation in skin color between human populations are primarily due to mutations on the genes MC1RTYRMATP (Graf, Hodgson, and Daal, 2005), and SLC24A5 (also see Lopez and Alonso, 2014 for a review of genes that account for skin color) so human populations aren’t “expected to consistently exhibit the associations between melanin-based coloration and the physiological and behavioural traits reported in our study” (Ducrest, Keller, and Roulin, 2008). Talking about just correlations is useless until causality is established (if it ever is).

Conclusion

The evolution of human skin variation is complex and is driven by more than one variable, but some are stronger than others. The evolution of black skin evolved—in part—due to skin cancer after we lost our fur. White skin evolved due to sexual selection (proximate cause) and to better absorb UV rays for vitamin D synthesis in colder climes (the true need for light skin in cold climates). Eurasians split around 40kya, and after this split both evolved light skin pigmentation independently. As I’ve shown, the alleles that code for skin color between blacks and whites don’t account for differences in aggression, nor do they account for differences in IQ. The genes that control skin color (about a dozen) pale in comparison to the genes that control intelligence (thousands of genes with small effects). Some other hypotheses for the evolution of white skin are on par with being as controversial as the hypothesis that skin color and intelligence co-evolved—mainly that mothers would kill darker-skinned babies because they weren’t seen as beautiful as lighter-skinned babies.

The evolution of human skin variation is extremely interesting with many competing hypotheses, however, to draw wild conclusions based on just correlations in regards to human skin color and intelligence and aggression, you’re going to need more evidence than just correlations.

References

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Holick, M. F. (2006). Resurrection of vitamin D deficiency and rickets. Journal of Clinical Investigation,116(8), 2062-2072. doi:10.1172/jci29449

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Problems With Forensic Facial “Reconstruction”: Implications for the Facial “Reconstruction” of Ancient Hominin

1050 words

Forensic facial reconstruction is the process by which a face is reconstructed from a deceased individual’s “skeletal remains through an amalgamation of artistry, forensic science, anthropology, osteology, and anatomy.” This technique is used largely only when skeletal remains are the only evidence at the scene of a crime. Perhaps most famously, it was used in the facial reconstruction of Mitochondrial Eve—but just how accurate is forensic facial reconstruction?

The average person may believe that forensic facial reconstruction is successful and a good proxy for what an individual may have looked like. This is bolstered by the fact that people hear of stories in which facial reconstruction are successful, never hearing of the countless number of cases in which the “reconstruction” fails to identify anyone.

Numerous papers in the literature, though, do show that forensic facial reconstruction does have a high success rate. For instance, Lee et al (2011) and Wilkinson et al (2006) show that this method has a considerable chance of getting facial morphology in the ballpark of how they look. However, this was done on live subjects and is of no use for Mitochondrial Eve/deceased individuals. Facial reconstructions of the deceased are, for the purpose of this article, what we need to look at, not studies looking at live people. (There are also hurdles for facial recognition systems.)

One of the biggest hurdles for the accuracy of forensic facial reconstruction is that average facial tissue thickness cannot be inferred (most importantly, the lips, cartilage, skin and fat). Due to this, with no prior information to look at, the look of the skull will be subjective with the “reconstruction” looking somewhat similar due to chance. Further, the main facial features are largely determined by the shape of the skull.

Now to the fun part: Is this what Mitochondrial Eve really looked like?

mitochondrial-eve2

There are a number of features that are problematic to infer from these facial reconstructions. Lips, ears, skin, craniofacial muscles—all are extremely hard, or next to impossible, to predict if the only thing we had was a skeleton. Further, since there are few tested relationships between soft and hard tissue for modern humans “it is clear that the use of facial approximation techniques on ancestral skulls of modern Homo are fundamentally flawed, as previously reported by Montagu” (Stephan, 2003). Since soft tissue quickly decays, it is left up to artistic interpretation. Further, attempting to map ape morphology since we diverged a few million years before is misleading, due to the fact that hard and soft tissue relationships are not likely to be the same for apes and our hominin ancestors.

Now that we know the so-called “reconstruction” of Mitochondrial Eve is not what she really looked like, there are a few more problems with this method I’d like to go over.

Forensic facial reconstruction is used when the remains of an unidentified individual are discovered. If the bones of the deceased are all that forensic artists have to go off of, the finished product may be extremely subjective/biased. People who believe that forensic facial reconstruction truly works may say “It works all the time. If it didn’t, how would it be able to solve crimes?” Success rates for the identification of individuals ranges from 50 to 100 percent (Stephan, 2003: 196), and so, the belief that “reconstructions” are largely accurate continue to persist.

However, like with the case of the famous stereotype threat with a modicum of unpublished studies, the “success” of forensic facial reconstruction is also skewed by non-reporting of unsuccessful cases

It is also rare for forensic facial approximation to be to be better than chance, with 403 incorrect facial identifications out of 592 identification scenarios in one study (Stephan and Henneberg, 2001). Facial reconstruction has the greatest accuracy if there is any knowledge of past injuries for the individual,  a photo, and soft tissue. Obviously, in the case of Mitochondrial Eve, we don’t have a photo nor do we have soft tissue and knowledge of past injuries are a non-factor. So it seems that if some people claim to know what the first AMH looked like, it’s probably “just a guess”, and a pretty bad one at that due to the no knowledge of hard and soft facial tissue in the hominin lineage.

The hardest part about facial reconstruction is reconstructing soft tissues accurately since they quickly decompose. This is even more of a problem for people who lived hundreds of thousands of years ago. We’ve never seen any alive so we don’t know what they may have looked like to be able to infer what Mitochondrial Eve would have looked like. Things like lips/mouth, skin, hair, and ears are largely up to artistic interpretation, which are subjective in nature. Craniofacial morphology has also changed in the past 200 thousand years, which may be due to a decrease in testosterone/androgen receptors.

If we can’t identify humans with facial recognition better than chance, what makes anyone think that we can even have the slightest idea of how Mitochondrial Eve looked—when some of the most important parts of the phenotype aren’t around to observe and thus subjectivity then comes into play. Any “reconstructions” you come across, you should take with a grain of salt. It’s next to impossible to know what ancient hominins may have looked like due to the absence of soft tissue, and so any phenotype that a so-called “reconstruction” may give is, largely, up to the interpretation of the individual artist.

With our current technology, it’s next to impossible to ascertain what Mitochondrial Eve—or any other ancient hominin for that matter—may have looked like.

References

Lee, W., Wilkinson, C. M., & Hwang, H. (2011). An Accuracy Assessment of Forensic Computerized Facial Reconstruction Employing Cone-Beam Computed Tomography from Live Subjects. Journal of Forensic Sciences,57(2), 318-327. doi:10.1111/j.1556-4029.2011.01971.x

Stephan, C. (2003). Anthropological facial ‘reconstruction’ – recognizing the fallacies, ‘unembracing’ the errors, and realizing method limits. Science & Justice,43(4), 193-200. doi:10.1016/s1355-0306(03)71776-6

Stephan, C. N., & Henneberg, M. (2001). Building Faces from Dry Skulls: Are They Recognized Above Chance Rates? Journal of Forensic Sciences,46(3). doi:10.1520/jfs14993j

Wilkinson, C., Rynn, C., Peters, H., Taister, M., Kau, C. H., & Richmond, S. (2006). A Blind Accuracy Assessment of Computer-Modeled Forensic Facial Reconstruction Using Computed Tomography Data From Live Subjects. Forensic Science, Medicine and Pathology,2(3), 179-188. doi:10.1385/fsmp:2:3:179

Wilkinson, C. (2010). Facial reconstruction—anatomical art or artistic anatomy? Journal of Anatomy,216(2), 235-250. doi:10.1111/j.1469-7580.2009.01182.x

Reading Wrongthought Books In Public

750 words.

How many of you have read wrongthought books in public? Books like Race, Evolution, and Behavior, The Blank Slate, The Nurture Assumption, or any other kind of wrongthought literature? I’ve had two specific run-ins this week reading a wrongthought book in public, both people giving me the expected reaction “Why are you reading that?” I bring a few books with me in my daily travels, one of them being Taboo: Why Black Athletes Dominate Sports and Why We’re Afraid To Talk About It.

I was in the bookstore the other day reading Taboo while drinking some coffee and someone came up to me and said, “Why are you reading that?” I responded, “Because I’m interested in the material, why else why I read it?” The person scowled at me and walked away. I don’t understand why you need to ask dumb questions like that. Clearly, if I’m reading something I find an interest in it. People are clearly scared of acknowledging any kind of racial differences in public—even if they cheer for their favorite sports teams a few times a week, not realizing that they’re cheering on people who have inherent genetic advantages due to their morphology. Ironically enough, the book I was reading was talking about how and why blacks dominate sports. That’s ‘racist’ though, so people don’t want to talk about it specifically in public, but they know the truth unconsciously.

As I wrote the other day, people are scared of talking about things that are “natural” in human populations. Because the admission of one population being inherently better, on average than another would then open the gates to talking about other more uncomfortable things, such as racial differences in intelligence. I bet seeing someone read a book like Taboo in public without having knowledge of population differences is pretty jarring for someone who is not privy to the information. However, as we all know, reality isn’t based on how we wish it to be. These taboo subjects that people are scared to approach don’t go away if they don’t acknowledge them.

I had another run-in the other day while drinking some coffee, reading the same wrongthought book. The person asked me “Why are you reading that in public?” with a surprised look on his face. I laughed and said, “Because I can,” and sipped my coffee. People don’t want their preconceived notions challenged (the notion of ‘equality’ of human races). To see someone reading a wrongthought book in public is heresy, and people will always give you an odd look if you’re reading one in public.

I also saw someone reading Outliers by Malcolm Gladwell the other day and I just had to tell them that Gladwell is wrong in his contention that practicing something for 10,000 hours is something that Gladwell has been rebutted on and continues to perpetuate. People should always know there are two sides to every story, whether they want to hear it or not.

People change their minds through reading. So if people who’ve not been exposed to wrongthought books see others reading them, they may be compelled to look into it themselves. That’s the best part about reading those types of books in public. A person may look into it themselves and change their views. I’ve personally found it much easier to change my views on something when I’ve read it myself in comparison to if I’m debating someone.

There is a cognitive bias known as the ‘backfire effect’, where correcting someone actually increases their misperceptions. Engaging people’s beliefs, in the end, just makes them hold onto them more strongly and has them search for evidence to confirm their beliefs. So by people being exposed to wrongthought books they can see them and look into it for themselves and weigh both sides on their own without the possibility of the backfire effect.

So just by exposing others to the covers of these wrongthought books may have them look into something themselves and, possibly, someone else will accept genetic causes for human differences. If you do read a wrongthought book in public and someone attempts to engage you due to what you’re reading, remember the backfire effect. This is why debating people doesn’t change their views because showing people they are wrong (with scholarly sources) has them hold onto their views more strongly. To avoid this, just read a wrongthought book in public so people can see it and look into it themselves.

Stockholm 5000 BC

by Scott Jameson

350 words

Stockholm Syndrome is when you identify with people who capture and, in some cases, abuse you. I’ve heard two pretty good explanations for this phenomenon. One is that female mammals like powerful male mammals. Makes sense. The other is that abducted people are attempting to maximize their own chances of survival, and perhaps those of any children they already have. Also makes sense. Let me present a third.

Intra-female competition. Imagine that a woman from tribe B is forcibly inducted into tribe A. The women from tribe A know all of the customs of tribe A, speak the language and so on, and they have known the men from tribe A since childhood. All else equal, what does the woman from tribe B have going for her- novelty, perhaps? That’ll wear off pretty quick, likely faster than it takes for her to get familiarized with her new culture. How can she possibly compensate? How can she compete with the women from tribe A for quantity and social status of offspring?

Lots and lots of asabiyah. If she were that much more devoted to her captors, to their religion, and so on, the men may admire her, or perhaps begin to consider her truly one of “their own,” thereby reducing the disadvantage by comparison to the women from tribe A.

All of these line up with the common belief- which I cannot seem to find strong evidence for or against, but here’s a study that mentions a sample of 21 Stockholm cases wherein 18 were women– that women tend to “suffer” from Stockholm Syndrome more often than men.

It’s not a disease in the Darwinian sense, it’s a behavioral response mechanism. The more accurate term is Capture Bonding.

Any one of these three hypotheses may explain it, or perhaps any combination of the three, or maybe something else. You would have to determine selective pressures operating on women currently in a situation wherein capture bonding is common, for example determining which behaviors enabled one war bride to have more children than another. Anybody up for some field work with Boko Haram?

The “N” Word

1300 words

Numerous academics have been looked at as pariahs for uttering this word. This word has a pretty long history offending people. The word I’m talking about is natural. This “N” word—especially today—is extremely divisive in today’s society. If you say that something is ‘natural‘, are you taking away any accomplishments that one has done, all because it’s ‘natural‘?

Take what I’ve been writing about for the past three weeks: athletics. If you say that one is a “natural” at athletic competition, are you taking away the hard work it took for that specific athlete to accomplish his goal? No way. You’re acknowledging that that specific individual has something special that sets him apart from the average person. That’s not to say that hard work, determination, and confidence don’t matter; on the contrary. They DO matter. However, like I said with the Kalenjin Kenyan distance runners (who do have anatomical/physiologic advantages in regards to sprinting): you can take someone with elite genetics who has done elite training and put him up against someone who has subpar genetics (in terms of the athletic event) with elite training—the same training as the athlete with elite genetics—and the athlete with elite genetics/muscle fibers/physiology will constantly blow away the individual who is less genetically gifted.

People readily admit that certain races excel at certain physical activities whereas other races don’t fare as well. As I’ve extensively covered (and provided more than enough evidence/arguments for), the races differ in the number of muscle fibers which cause higher rates of obesity in blacks; this causes strength differences which then correlate with mortality. Finally, somatype is extremely important when speaking about athletics. Blacks have a mesomorphic somatype, which, along with their fiber typing and physiologic differences on average compared to whites, cause blacks to dominate most sporting events. However, when you say that certain races are “naturally more intelligent than others“, people all of a sudden have a bone to pick.

This “N” word when it comes to athletics is perfectly fine to use in our vocabulary, yet when we begin talking about intelligence differences—between races and individuals—all of a sudden we think that everyone is the same and that all brains are made the same. We believe that, although humans evolved genetically isolated for thousands of years and have incurred anatomic/physiologic differences, that one organ—the brain—is somehow exempt from the forces of natural selection. I can think of no traits that WON’T get selected for/against, and so I can think of no reason why the brain wouldn’t be under different selective pressures in Siberia/Northern Europe/the Americas/Africa/PNG/Australia.

However, as far as I can tell, we have not found any alleles that differ between populations. It was proposed in 2005 that the genes ASPM and Microcephalin influenced brain growth (Evans et al, 2005; Mekel-Brobov et al, 2005). However, two years later, Rushton, Vernon and Ann Bons (2007) showed that there was no evidence that Microcephalin and ASPM were associated with general mental ability (GMA), head circumference or altruism. Peter Frost cites Woodley et al, (2014) showing that the correlation between microcephalin and IQ is .79, whereas the correlation with ASPM and IQ was .254. Woodley et al (2014) also show there is a correlation between Disability Adjusted Life Years (DALY) and Microcephalin. The reasoning is that Microcephalin may improve the body’s immune response to viral infections, enabling humans to live in larger societies and thus get selected for higher IQ. Since the allele seems to give better disease resistance, then, over time, selection for higher intelligence can be selected for since fewer people are dying from disease due to increased resistance.

Nevertheless, the debate is still out on this allele. However, the data does look good in that we may have found certain polymorphisms that differ between populations which may explain some racial differences in intelligence. (For more information on IQ alleles, see Race and IQ: the Case for Genes).

Now, we are beginning to have some good evidence pile up showing that there are population differences in these alleles, and that they do predict intelligence. Racial differences in intelligence aren’t accepted by mainstream science and the public at large (obviously) like physiologic/anatomic differences are between human populations. Populations are split for thousands of years. They evolve different anatomy/physiology based on the environment. So, then, why wouldn’t psychological differences appear between the races of Man, when other, physical changes occurred from the OoA migration? It literally makes no sense.

People readily admit that athleticism is largely “natural“, yet when someone says that differences in intelligence are largely due to genes they get shouted down and called a ‘racist’, as if that adds anything to the dialogue. People readily admit that individuals/races are “naturally” leaner/stronger/faster/have quicker reflexes. But if one just even hints at thinking about “natural” differences between populations when it comes to general mental ability, they will be shouted down and their careers will be ruined.

Why? Why are people so scared of the “N” word? Because people want to believe that what they do or do not accomplish comes down to them as an individual and only them. They don’t want to think about the complex interaction between genes x environment and how that shapes an individual’s life path. They only think about environment, and not any possible genetic factors. Certain people—mostly social science majors—deny that evolution had ANY impact on human behavior. The “N” word, especially in today’s society, is a completely divisive word. State that you hold hereditarian views (in terms of mental ability) in regards to differences between populations and athletic events and no one will bat an eye.

“Didn’t you see Usain Bolt blow away the competition and set a new world record in the 100m dash at 9.58 seconds?!”

“He’s naturally good, he was born a gifted athlete.”

No one will bat an eye if you say this. This is where the tables will be flipped if you say:

“Don’t you know that differences in intelligence are largely genetic in nature and no matter how much you ‘train the brain’ you’ll stay at that intelligence level?”

“Man, that’s racist. That shouldn’t be looked at. We are all the same and equal. Except when it comes to certain athletic events, then we are not equal and some populations have natural predispositions that help them win. Evolution stopped at the neck 100kya; the only parts of the body under selective pressure over the past 100kya is below the neck!”

People who say this need to explain exactly what shields the brain from selection pressures. Man originated in Africa, the descendants of the soon-to-be coalesced races spent tens of thousands of years in differing environments. You need to do different things to survive in different environments. Just as the races differ physically, they differ mentally as well. Evolution did not stop at the neck. Significant changes in the brain have occurred in the past 10,000 years. There was a trade-off with agriculture, in that it was responsible for the population explosion which was responsible for mutations that affect intelligence and thus get selected for.

The “N” word is not a scary word. It is, in fact, it’s just common sense. People need to realize that by accepting genetic explanations for black domination in sports, that they would then, logically, have to accept racial differences in intelligence. It makes no sense to accept evolutionary theories (even if you don’t know it) in regards to athletics and not accept the same evolutionary theories for racial differences in the brain. There are real differences between populations, in both anatomy/physiology and our mental faculties and brain organization. If you accept one, you have to accept the other.

Diet Or Socializing—What Caused Primate Brain Size To Increase?

1100 words

The social brain hypothesis argues that the human brain did not increase in size to solve increasingly complex problems, but as a means of surviving and reproducing in complex social groups (Dunbar, 2009). The social brain hypothesis is one of the most largely held views when it comes to explaining primate encephalization. However, an analysis of new phylogeny and more primate samples shows that differences in human and non-human primate brain evolution come down to diet, not sociality.

Diet is one of the most important factors in regards to brain and body size. The more high-quality food an animal has, the bigger its brain and body will be. Using a larger sample (3 times as large, 140 primates), more recent phylogenies (which show inferred evolutionary relationships amongst species, not which species is ‘more evolved’ than another), and updated statistical techniques, Decasien, Williams, and Higham (2017) show that diet best predicts brain size in primates, not social factors after controlling for body size and phylogeny (humans were not used because we are an outlier).

The social scheme they used consisted of solitary, pair-living, harem polygyny (one or two males, “a number of females” and offspring), and polygynandry (males and females have multiple breeding partners during the mating season). The diet scheme they used consisted of folivore (leaf-eater), frugivore-folivore (fruit and leaf eater), frugivore (fruit-eater) and omnivore (meat- and plant-eaters).

None of the sociality measures used in the study showed a relative increase in primate brain size variation, whereas diet did. Omnivores have bigger brains than frugivores. Frugivores had bigger brains than folivores. This is because animal protein/fruit contains higher quality energy when compared to leaves. Bigger brains can only evolve if there is sufficient and high-quality energy being consumed. The predicted difference in neurons between frugivores and folivores as predicted by Herculano-Houzel’s neuronal scaling rules was 1.08 billion.

The authors conclude that frugivorous primates have larger brains due to the cognitive demands of “(1) necessity of spatial information storage and retrieval; (2) cognitive demands of ‘extractive foraging’ of fruits and seeds; and (3) higher energy turnover and enhanced diet quality for energy needed during fetal brain growth.” (Decasien, Williams, and Higham, 2017). Clearly, frugivory provided some selection pressures, and, of course, the energy needed to power a larger brain.

The key here is the ability to overcome metabolic constraints. Without that, as seen with the primates that consumed a lower-quality diet, brain size—and therefore neuronal count—was relatively smaller/lower in those primates. Overall brain size best predicts cognitive ability across non-human primates—not encephalization quotient (Deaner et al, 2007). Primate brains increase approximately isometrically as a function of neuron number and its overall size with no change in neuronal density or neuronal/glial cell ratio with increasing brain size (in contrast to rodent brains) (Herculano-Houzel, 2007). If brain size best predicts cognitive ability across human primates and primate brain size increases isometrically as a function of neuron number with no change in neuronal density with increasing brain size, then primates with larger brains would need to have a higher quality diet to afford more neurons.

The results from DeCasien, Williams, and Higham (2017) call into question the social brain hypothesis. The recent expansion of the cerebellum co-evolved with tool-use (Vandervert, 2016), suggesting that our ability to use technology (to crush and mash foods, for instance) was at least as important as sociality throughout our evolution.

The authors conclude that both human and non-human primate brain evolution was driven by increased foraging capability which then may have provided the “scaffolding” for the development of social skills. Increased caloric consumption can afford larger brains with more neurons and more efficient metabolisms. It’s no surprise that frugivorous primates had larger brains than folivorous primates. Just as Fonseca-Azevedo and Herculano-Houzel (2012) observed, primates that consumed a higher quality diet had larger brains.

In sum, this points in the opposite direction of the social brain hypothesis. This is evidence for differing cognitive demands placed on getting foods. Those who could easily get food (folivores) had smaller brains than those who had to work for it (frugivores, omnivores). However, to power a bigger brain the primate needs the energy from the food that takes the complex behavior—and thus larger brain—to obtain. This lends credence to Lieberman’s (2013) hypothesis that bipedalism arose after we came out of the trees and needed to forage for fruit to survive.

Brain size in non-human primates is predicted by diet, not social factors, after controlling for body size and phylogeny. Diet is the most important factor in the evolution of species. With a lower quality diet, larger brains with more neurons (in primates, 1 billion neurons takes 6 kcal per day to power) would not evolve. Brain size is predicated on a high-quality diet, and without it, primates—including us—would not be here today. Diet needs to be talked about a lot more when it comes to primate evolution. If we would have continued to eat leaves and not adopt cooking, we would still have smaller brains and many of the things that immediately came after cooking would not have occurred.

Since we are primates we have the right morphology to manipulate our environment and forage for higher quality foods. But those primates with access to foods with higher quality have larger brains and are thus more intelligent (however, there are instances where primate brain size increases and decreases and it comes back to, of course, diet). Sociality comes AFTER having larger brains driven by nutritional factors—and would not be possible without that. Social factors drove our evolution—no doubt about it. But the importance of diet throughout hominin evolution cannot be understated. Without our high-quality diet, we’d still be like our hominin ancestors such as Lucy and her predecessors. Higher quality diet—not sociality, drives primate brain size.

References

DeCasien, A. R., Williams, S. A. & Higham, J. P. Primate brain size is predicted by diet but not sociality. Nat. Ecol. Evol. 1, 0112 (2017).

Deaner, R. O., Isler, K., Burkart, J., & Schaik, C. V. (2007). Overall Brain Size, and Not Encephalization Quotient, Best Predicts Cognitive Ability across Non-Human Primates. Brain, Behavior and Evolution,70(2), 115-124. doi:10.1159/000102973

Dunbar, R. (2009). The social brain hypothesis and its implications for social evolution. Annals of Human Biology,36(5), 562-572.

Fonseca-Azevedo, K., & Herculano-Houzel, S. (2012). Metabolic constraint imposes tradeoff between body size and number of brain neurons in human evolution. Proceedings of the National Academy of Sciences,109(45), 18571-18576. doi:10.1073/pnas.1206390109

Herculano-Houzel, S. (2007). Encephalization, neuronal excess, and neuronal index in rodents. Anat. Rec. 290, 1280–1287.

Lieberman, D. (2013). The story of the human body: evolution, health and disease. London: Penguin Books.

Vandervert, L. (2016). The prominent role of the cerebellum in the learning, origin and advancement of culture. Cerebellum & Ataxias,3(1). doi:10.1186/s40673-016-0049-z

Evolution and IQ Linkfest III

1050 words

What the octopus tells us about human intelligence (Mammals are ‘brain heavy’, the cephalopod nervous system is more distributed across its limbs. Some people believe they have minds with consciousness. Interesting read.)

A brewing debate on evolution theory picks up in India (Great look at the niche construction theory—which states that an organism modifies its environment which in turn decreases or increases fitness. Two great examples of NC are lactase consumption 6500 ya that led to most European populations having the ability to digest lactase and an African farmer digging some irrigation holes could cause mosquitoes to live in the still water. Over time, the people would get malaria. They then would evolve sickle cell anemia to battle the malaria virus. For more information on niche construction, read this paper: Conceptual Barriers to Progress Within Evolutionary Biology and Niche Construction Theory and Archaeology.)

Human evolution: why we’re more than great apes (Culture and our brains set us apart from the animal kingdom, and thus, some researchers argue, that humans shouldn’t be called Great Apes. Both humans and Great Apes are a part of the Hominidae family. Sure we’re ‘more than Great Apes’. However, due to the chromosomal fusion some 6mya, this is why we speciated.)

4qheo

Dramatic evolution within human genome may have been caused by malaria parasite (The most recent common ancestor that possessed the DARC gene, which shuts off a protein receptor on the surface of the red blood cells that the parasite needs to gain entry, lived around 42 kya. By 8000 ya, 99 percent of the population had the DARC gene. The author estimates that for every 100 people that were born without the DARC gene, 105 would have been born with it. The gene has pretty much has hit fixation in this population. Of course, since humans evolved to fight the parasite, the parasite itself evolved adaptations to continue living. See the Red Queen Hypothesis.)

Climate may have shaped the evolution of the human nose: Nature’s nose job (Nose shape is linked to climate, which is then shaped by natural selection. Africans and their descendants have wider, shorter, flatter noses due to living in more moist, drier environments. A larger mucous area is needed to moisten dry air. Peoples who evolved in cooler climes, however, evolved longer, thinner noses due to living in colder climes. Read the paper here: Investigating the case of human nose shape and climate adaptation.)

Human skull evolved along with two-legged walking, study confirms (No surprise here. This is some good evidence for my “Man the Athlete” hypothesis. Our athleticism was paramount in our evolutionary history, which released important hormones to aid in our brain growth over time. The foramen magnum is forward-shifter in many bipedal species. That is the hole in which the spinal column goes into.)

Stone tools not always deliberate, research finds (Capuchin monkeys of South America can flake tools similar to that of early hominins. Pretty much, if we find tools that are similar to this, we cannot assume that a human ancestor made them. Flaking alone is not enough, it may have been by a non-hominin so other measures are needed.)

MD Debunks Myth that Humans Evolved to Eat Meat (This deserves a full-length article. The MD says that humans eating meat are like dogs eating chocolate since we are closely related to chimpanzees who eat a plant-based diet. This reasoning…. makes no sense! There are genetic changes from cooking that appeared between 265 to 800kya and the ONLY explanation is the introduction of cooked foods! I will cover this article in the future.)

Tooth be told: Millions of years of evolutionary history mark those molars (Anthropologists can see what type of diet an animal ate, to how long their childhood was due to the layers of tooth enamel. Looking at the teeth of hominins/chimps also show that humans have a longer childhood, which is important for motor development at a young age.)

Microbes evolved to colonize different parts of the human body (The microbiota in our body evolved especially for the place it found itself it. Each species of bacteria serves a pertinent function in the body. These bacteria also drive part of our metabolism, so having them was extremely beneficial in our evolution.)

‘No Valid Conclusions’: Omega-3 trade body fires back over prenatal DHA supplementation findings (A new RCT (Randomized Controlled Trial) just came out stating that DHA supplements that mothers take while pregnant doesn’t increase IQ. Women were randomized to receive a placebo or 800 mg of DHA. They found no difference in cognitive, language or motor development by 18 months. At four years of age, they reported no effect of DHA on the children’s cognitive, language or motor development, noting possibly that DHA consumption had a negative effect on parent-rated behavior. Of the eligible children, 85 percent (543 children) took part in the follow-up. IQ did not differ in the DHA group (98.31) or for the placebo group (97.32). Perceptual reasoning was slightly higher in the DHA group, but the parent-rated behavior was worse. There are some problems with the study design, however. The experimental design didn’t test blood levels of omega-3s in the mothers or the offspring. It’s also unknown if they were receiving the correct amount of DHA since they weren’t tested. Of course, post-pregnancy diets of the mothers while breastfeeding AND that of the children would skew levels of DHA in the blood. Omega-3s are paramount for brain health at all ages—most importantly in the womb and the first few years of a child’s life. In fact, telling women and children NOT to consume fish oil/omega-3s is the WORST thing you can do!)

How a Western diet leads to overeating and obesity (Chronic overconsumption of Western diets high in sugar and fat is a major cause of the obesity epidemic. However, researchers have found that a chronic overconsumption of the Western diet leads to obesity “due to elevations in ‘peripheral endocannabinoid signaling.'” The endocannabinoid system regulates energy balance, reward, and food intake. Elevations of endocannabinoids in the body lead to hyperphagia (an abnormal appetite for food). I await future looks into this research. We may be able to curb the epidemic by identifying certain pathways that lead to hyperphagia and other eating disorders and prevent them.)

Racial Differences in Somatype

1750 words

One’s somatype is, really, the first thing they notice. Somatypes are broken down into three categories: ectomorph (skinny build), endomorph (rounder, fatter build) and mesomorph (taller, more muscular build). Like numerous other traits, different races and ethnies fall somewhere in between these three soma categories. Africans are meso, while Europeans are endo, while East Asians are more endo than Europeans. Differences in somatype, too, lead to the expected racial differences in sports due to differing anatomy and fat mass.

History of somatyping

The somatype classification was developed by psychiatrist William Sheldon in the 1940s, while releasing a book in 1954 titled Atlas of Men: Somatotyping the Adult Male At All AgesHe theorized that one’s somatype could predict their behavior, intelligence, and where they place socially. Using nude posture photos from his Ivy League students, he grouped people into three categories based on body measurements and ratios—mesomorph, endomorph, and ectomorph. Clearly, his theory is not backed by modern psychology, but I’m not really interested in that. I’m interested in the somatyping.

Somatypes

The three somatypes are endomorph, mesomorph, and ectomorph. Each type has different leverages and body fat distribution. Endomorphs are rounder, with short limbs, a large trunk, carry more fat in the abdomen and lower body, large chest, wide hips, and has hardly any muscular definition, yet gain strength easily. Ectomorphs, on the other hand, are taller, lankier with longer limbs, a narrow chest, thin body, short trunk and has little muscle.

There are further subdivisions within the three main types, mesomorphic-endomorph (meso-dominant), mesomorph-endomorph (both types are equal with less ectomorphy), ectomorphic-mesomorph, endomorphic-mesomorph, endomorph-ectomorph, and ectomorphic-endomorph. This can be denoted as “7-1-1”, which would indicate pure endomorph, “1-7-1” would indicate pure mesomorph and “1-1-7” would be a pure ectomorph. Further breakdowns can be made such as “1.6-2.7-6.4”, indicating the somatype is ecto-dominant. On the scale, 1 is extremely low while 7 is extremely high. The races, however, fall along racial lines as well.

Racial differences in somatype

West Africans and their descendants are the most mesomorphic. They also have the highest amount of type II muscle fibers which is a leading cause of their success in sporting events which call for short bursts of speed. Due to having longer limbs, they have a longer stride and can generate more speed. West Africans also have the narrowest hips out of all of the races (Rushton, 1997: 163) which further leads to their domination in sprinting competitions and events that take quick bursts of speed and power. However much success their morphology lends them in these types of competitions, their somatype hampers them when it comes to swimming. The first black American qualified for the Olympic swimming team in the year 2000. This is due to a narrower chest cavity and denser, heavier bones.

East Africans are most ectomorphic which you can see by their longer limbs and skinnier body. They have an average BMI of 21.6, one of the lowest in the world. Their low BMI, ectomorphic somatype and abundance of slow twitch muscle fibers are why they dominate in distance running events. Many explanations have been proposed to explain why East Africans (specifically Kenyans and Ethiopians) dominate distance running. The main factor is their somatype (ectomorphic) (Wilbur and Pitsiladis, 2012). The authors, however, downplay other, in my opinion, more important physiologic characteristics such as muscle fiber typing, and differences in physiology. Of course their somatype matters for why they dominate, but other important physiologic characteristics do matter. They clearly evolved together so you cannot separate them.

Europeans are more endo than East Africans and West Africans but less so than East Asians. Europeans have a strong upper body, broad shoulders, longer and thicker trunk and shorter extremities along with 41 percent slow twitch fibers compared to blacks’ 33 percent slow twitch fibers. This is why Europeans dominate power sports such as powerlifting and the World’s Strongest Man. Eighty to 100 percent of the differences in total variation in height, weight, and BMI between East Asians and Europeans are associated with genetic differences (Hur et al, 2008). If the variation between East Asians and Europeans on height, weight and BMI are largely attributed to genetic factors, then the same, I assume, should be true for Africans and Europeans/East Asians.

East Asians are the most endomorphic race and have lighter skeletons and more body fat. They have short arms and legs with a large trunk, which is a benefit when it comes to certain types of lifting movements (such as Olympic lifting, where East Asians shine) but hampers them when it comes to sprinting and distance running (although they have higher rates of type I fibers). East Asians also have more body fat at a lower BMI which is further evidence for the endomorphic somatype. This is also known as ‘TOFI’, ‘Thin on the Outside, Fat on the Inside’. Chinese and Thai children had a higher waist circumference and higher trunk fat deposits than Malay and Lebanese children (Liu et al, 2011). This is a classic description of the endomorphic individual.

Human hands and feet are also affected by climate. Climatic variation played a role in shaping the racial somatic differences we see today. The differences seen in hands and feet “might be due to the presence of evolutionary constraints on the foot to maintain efficient bipedal locomotion” (Betti et al, 2015).

Black-white differences in somatype

Fifty percent of the variability in lean mass is due to genetic factors (Arden and Specter, 1997) with the heritability of stature 85 percent in a meta-analysis (Peeters et al, 2009). Racial differences in somatype are also seen at a young age (Malina, 1969). Blacks had better muscular development and less fat-free mass at an early age. Vickery et al (1988) argued that since blacks have thinner skin folds that caliper measurements testing differences in body fat would be skewed. Malina (1969) also reports the same. Note that Malina’s paper was written in 1969, literally right before it got pushed on the American populace that fat was bad and carbohydrates were good.

Looking at the two tables cited by Malina (1969) on somatype we can see the difference between blacks and whites.

Data from Malina, (1969: 438) n Mesomorph Ectomorph Endomorph
Blacks 65 5.14 2.99 2.92
Whites 199 4.29 2.89 3.86
Data from Malina (1969: 438) Blacks Whites
Thin-build body type 8.93 5.90
Submedium fatty development 48.31 29.39
Medium fleshiness 33.69 43.63
Fat and very fat categories 9.09 21.06

Since this data was collected literally before we went down the wrong path and wrongly demonized fat and (wrongly) championed carbohydrates, this is an outstanding look at somatype/fat mass before the obesity epidemic. There is a clear trend, with blacks being more likely to have lower levels of fat-free body mass while also more likely to be mesomorphic. This has a ton of implications for racial differences in sports.

Somatype is predicated on lean mass, stature, bone density and fat-free body mass. Since racial differences appear in somatype at an early age, there is a great chance that the differences in somatype are genetic in nature.

College (American) football players are more likely to be endo-mesomorphs while high-school football players were more likely to be mesomorphs (Bale et al, 1994). This partly explains black over representation in football. Further, basketball, handball, and soccer players in Nigeria were taller, heavier, and had lower percent body fat than other athletic groups (Mazur, Toriola, and Igobokwe, 1985). Somatic differences have a lot to do with domination in sports competition.

Somatic differences are also seen in boxing. Elite boxers are more likely to have a mesomorphic somatype compared to non-athletes. Higher weight divisions were also more likely to be mesomorphic and endomorphic than the lower weight divisions which skewed ectomorphic (Noh et al, 2014). Blacks do well in boxing since they have a more mesomorphic somatype. Due to their higher levels of type II fibers, they can be quicker and throw more forceful punches which translates to boxing success.

Conclusion

Racial differences in somatype are another key to the puzzle to figure out why the races differ in elite sporting competition. The races evolved in different geographic locations which then led to differences in somatype. West African sports dominance is explained by their somatype, muscle fiber type, and physiology. The same can be said for Europeans in strength sports/powerlifting sports, and East Asians with ping-pong and some strength sports (though, due to lower muscle mass they are the least athletic of the races). I am not, of course, denying the impact of determination to succeed or training of any kind. What one must realize, however, is that one with the right genetic makeup/somatype and elite training will, way more often than not, outperform an individual with the wrong genetic makeup/somatype and elite training. These inherent differences between races explain the disparities in elite sporting competitions.

References

Arden, N. K., & Spector, T. D. (1997). Genetic Influences on Muscle Strength, Lean Body Mass, and Bone Mineral Density: A Twin Study. Journal of Bone and Mineral Research,12(12), 2076-2081. doi:10.1359/jbmr.1997.12.12.2076

Bale P, Colley E, Mayhew JL, et al. Anthropometric and somatotype variables related to strength in American football players. J Sports Med Phys Fitness 1994;34:383–9

Betti, L., Lycett, S. J., Cramon-Taubadel, N. V., & Pearson, O. M. (2015). Are human hands and feet affected by climate? A test of Allen’s rule. American Journal of Physical Anthropology,158(1), 132-140. doi:10.1002/ajpa.22774

Hur, Y., Kaprio, J., Iacono, W. G., Boomsma, D. I., Mcgue, M., Silventoinen, K., . . . Mitchell, K. (2008). Genetic influences on the difference in variability of height, weight and body mass index between Caucasian and East Asian adolescent twins. International Journal of Obesity,32(10), 1455-1467. doi:10.1038/ijo.2008.144

Liu, A., Byrne, N. M., Kagawa, M., Ma, G., Kijboonchoo, K., Nasreddine, L., . . . Hills, A. P. (2011). Ethnic differences in body fat distribution among Asian pre-pubertal children: A cross-sectional multicenter study. BMC Public Health,11(1). doi:10.1186/1471-2458-11-500

Malina, R. M. (1969). Growth and Physical Performance of American Negro and White Children: A Comparative Survey of Differences in Body Size, Proportions and Composition, Skeletal Maturation, and Various Motor Performances. Clinical Pediatrics,8(8), 476-483. doi:10.1177/000992286900800812

Mathur, D. N., Toriola, A. L., & Igbokwe, N. U. (1985). Somatotypes of Nigerian athletes of several sports. British Journal of Sports Medicine,19(4), 219-220. doi:10.1136/bjsm.19.4.219

Noh, J., Kim, J., Kim, M., Lee, J., Lee, L., Park, B., . . . Kim, J. (2014). Somatotype Analysis of Elite Boxing Athletes Compared with Nonathletes for Sports Physiotherapy. Journal of Physical Therapy Science,26(8), 1231-1235. doi:10.1589/jpts.26.1231

Peeters, M., Thomis, M., Beunen, G., & Malina, R. (2009). Genetics and Sports: An Overview of the Pre-Molecular Biology Era. Genetics and Sports Medicine and Sport Science, 28-42. doi:10.1159/000235695

Rushton J P (1997). Race, Evolution, and Behavior. A Life History Perspective (Transaction, New Brunswick, London).

Vickery SR, Cureton KJ, Collins MA. Prediction of body density from skinfolds in black and white young men. Hum Biol 1988;60:135–49.

Wilber, R. L., & Pitsiladis, Y. P. (2012). Kenyan and Ethiopian Distance Runners: What Makes Them so Good? International Journal of Sports Physiology and Performance,7(2), 92-102. doi:10.1123/ijspp.7.2.92

Possibly Retracting My Article on HBD and Baseball

700 words

I am currently reading Taboo: Why Black Athletes Dominate Sports and Why We’re Afraid To Talk About It and came across a small section in the beginning of the book talking about black-white differences in baseball. It appears I am horribly, horribly wrong and it looks like I may need to retract my article HBD and Sports: Baseball. However, I don’t take second-hand accounts as gospel, so I will be purchasing the book that Entine cites, The Bill James Baseball Abstract 1987 to look into it myself and I may even do my own analysis on modern-day players to see if this still holds. Nevertheless, at the moment disregard the article I wrote last year until I look into this myself.


Excerpt from Taboo: Why Black Athletes Dominate Sports and Why We’re Afraid To Talk About It:

Baseball historian Bill James, author of dozens of books on the statistical twists of his favorite sport believes this trend [black domination in baseball] is not a fluke. In an intriguing study conducted in 1987, he compared the careers of hundreds of rookies to figure out what qualities best predict who would develop into stars. He noted many intangible factors, such as whether a player stays fit or is just plain lucky. The best predictors of long-term career success included the age of the rookie, his defensive position as a determinant in future hitting success (e.g., catchers fare worse than outfielders), speed, and the quality of the player’s team. But all of these factors paled when compared to the color of the player’s skin.

“Nobody likes to write about race,” James noted apologetically. “I thought I would do a [statistical] run of black players against white players, fully expecting that it would show nothing in particular or nothing beyond the outside range of chance, and I would file it away and never mention that I had looked at the issue at all.

James first compared fifty-four white rookies against the same number of black first-year players who had comparable statistics. “The results were astonishing,” James wrote. The black players:

* went on to have better major-league careers in 44 out of 54 cases

* played 48 percent more games

* had 66 percent more major league hits

* hit 93 percent more triples

* hit 66 percent more home runs

* scored 69 percent more runs

* stole 400 more bases (Entine, 2000: 22-23)

Flabbergasted at what he found, James ran a second study using forty-nine black/white comparisons. Again, blacks proved more durable, retained their speed longer, and were consistently better hitters. For example, he compared Ernie Banks, a power hitting shortstop for the Chicago Cubs, and Bernie Allen who broke in with Minnesota. They both reached the majors when they were twenty-three years old, were the same height and weight, and were considered equally fast. Over time, Allen bombed and Banks landed in the Hall of Fame. (Entine, 2000: 24)

In an attempt to correct for possible bias, James compared players with comparable speed statistics such as the number of doubles, triples, and stolen bases. He ran a study focused on players who had little speed. He analyzed for “position bias” and made sure that players in the same eras were being compared. Yet every time he crunched the numbers, the results broke down across racial lines. When comparing home runs, runs scored, RBIs or stolen bases, black players held an advantage a startling 80 percent of the time. “And I could identify absolutely no bias to help explain why this should happen,” James said in disbelief.

James also compared white Hispanic rookies whom he assumed faced an uphill battle similar to that for blacks, with comparable groups of white and black players. The blacks dominated the white Latinos by even more than they did white North Americans, besting them in 19 of the 26 comparisons. Blacks played 62 percent more games, hit 192 more home runs, drove in 125 percent more runs, and stole 30 percent more bases.

So why have blacks become the stars of baseball far out of proportion to their relative numbers? James eventually concluded that there were two possible explanations: “Blacks are better athletes because they are born better athletes, which is to say that it is genetic, or that they are born equal and become better athletes. (Entine, 2000: 24-25)

Black-White Differences in Muscle Fiber and Its Role In Disease and Obesity

1700 words

How do whites and blacks differ by muscle fiber and what does it mean for certain health outcomes? This is something I’ve touched on in the past, albeit briefly, and decided to go in depth on it today. The characteristics of skeletal muscle fibers dictate whether one has a higher or lower chance of being affected by cardiometabolic disease/cancer. Those with more type I fibers have less of a chance of acquiring diabetes while those with type II fibers have a higher chance of acquiring debilitating diseases. This has direct implications for health disparities between the two races.

Muscle fiber typing by race

Racial differences in muscle fiber typing explain differences in strength and mortality. I have, without a shadow of a doubt, proven this. So since blacks have higher rates of type II fibers while whites have higher rates of type I fibers (41 percent type I for white Americans, 33 percent type I for black Americans, Ama et al, 1985) while West Africans have 75 percent fast twitch and East Africans have 25 percent fast twitch (Hobchachka, 1988). Further, East and West Africans differ in typing composition, 75 percent fast for WAs and 25 percent fast for EAs, which has to do with what type of environment they evolved in (Hochhachka, 1998). What Hochhachka (1998) also shows is that high latitude populations (Quechua, Aymara, Sherpa, Tibetan and Kenyan) “show numerous similarities in physiological hypoxia defence mechanisms.” Clearly, slow-twitch fibers co-evolved here.

Clearly, slow-twitch fibers co-evolved with hypoxia. Since hypoxia is the deficiency in the amount of oxygen that reaches the tissues, populations in higher elevations will evolve hypoxia defense mechanisms, and with it, the ability to use the oxygen they do get more efficiently. This plays a critical role in the fiber typing of these populations. Since they can use oxygen more efficiently, they then can become more efficient runners. Of course, these populations have evolved to be great distance runners and their morphology followed suit.

Caesar and Henry (2015) also show that whites have more type I fibers than blacks who have more type II fibers. When coupled with physical inactivity, this causes higher rates of cancer and cardiometabolic disease. Indeed, blacks have higher rates of cancer and mortality than whites (American Cancer Society, 2016), both of which are due, in part, to muscle fiber typing. This could explain a lot of the variation in disease acquisition in America between blacks and whites. Physiologic differences between the races clearly need to be better studied. But we first must acknowledge physical differences between the races.

Disease and muscle fiber typing

Now that we know the distribution of fiber types by race, we need to see what type of evidence there is that differing muscle fiber typing causes differences in disease acquisition.

Those with fast twitch fibers are more likely to acquire type II diabetes and COPD (Hagiwara, 2013); cardiometabolic disease and cancer (Caesar and Henry, 2015); a higher risk of cardiovascular events (Andersen et al, 2015, Hernelahti et al, 2006); high blood pressure, high heart rate, and unfavorable left ventricle geometry leading to higher heart disease rates and obesity (Karjalainen et al, 2006) etc. Knowing what we know about muscle fiber typing and its role in disease, it makes sense that we should take this knowledge and acknowledge physical racial differences. However, once that is done then we would need to acknowledge more uncomfortable truths, such as the black-white IQ gap.

One hypothesis for why fast twitch fibers are correlated with higher disease acquisition is as follows: fast twitch fibers fire faster, so due to mechanical stress from rapid and forceful contraction, this leads the fibers to be more susceptible to damage and thus the individual will have higher rates of disease. Once this simple physiologic fact is acknowledged by the general public, better measures can be taken for disease prevention.

Due to differences in fiber typing, both whites and blacks must do differing types of cardio to stay healthy. Due to whites’ abundance of slow twitch fibers, aerobic training is best (not too intense). However, on the other hand, due to blacks’ abundance of fast twitch fibers, they should do more anaerobic type exercises to attempt to mitigate the diseases that they are more susceptible due to their fiber typing.

Black men with more type II fibers and less type I fibers are more likely to be obese than ‘Caucasian‘ men are to be obese (Tanner et al, 2001). More amazingly, Tanner et al showed that there was a positive correlation (.72) between weight loss and percentage of type I fibers in obese patients. This has important implications for African-American obesity rates, as they are the most obese ethny in America (Ogden et al, 2016) and have higher rates of metabolic syndrome (a lot of the variation in obesity does come down food insecurity, however). Leaner subjects had higher proportions of type I fibers compared to type II. Blacks have a lower amount of type I fibers compared to whites without adiposity even being taken into account. Not surprisingly, when the amount of type I fibers was compared by ethnicity, there was a “significant interaction” with ethnicity and obesity status when type I fibers were compared (Tanner et al, 2001). Since we know that blacks have a lower amount of type I fibers, they are more likely to be obese.

In Tanner et al’s sample, both lean blacks and whites had a similar amount of type I fibers, whereas the lean blacks possessed more type I fibers than the obese black sample. Just like there was a “significant interaction” between ethnicity, obesity, and type I fibers, the same was found for type IIb fibers (which, as I’ve covered, black Americans have more of these fibers). There was, again, no difference between lean black and whites in terms of type I fibers. However, there was a difference in type IIb fibers when obese blacks and lean blacks were compared, with obese blacks having more IIb fibers. Obese whites also had more type IIb fibers than lean whites. Put simply (and I know people here don’t want to hear this), it is easier for people with type I fibers to lose weight than those with type II fibers. This data is some of the best out there showing the relationship between muscle fiber typing and obesity—and it also has great explanatory power for black American obesity rates.

Conclusion

Muscle fiber differences between blacks and whites explain disease acquisition rates, mortality rates (Araujo et al, 2010), and differences in elite sporting competition between the races. I’ve proven that whites are stronger than blacks based on the available scientific data/strength competitions (click here for an in-depth discussion). One of the most surprising things that muscle fibers dictate is weight loss/obesity acquisition. Clearly, we need to acknowledge these differences and have differing physical activity protocols for each racial group based on their muscle fiber typing. However, I can’t help but think about the correlation between strength and mortality now. This obesity/fiber type study puts it into a whole new perspective. Those with type I fibers are more likely to be physically stronger, which is a cardioprotectant, which then protects against all-cause mortality in men (Ruiz et al, 2008; Volaklis, Halle, and Meisenger, 2015). So the fact that black Americans have a lower life expectancy as well as lower physical strength and more tpe II fibers than type I fibers shows why blacks are more obese, why blacks are not represented in strength competitions, and why blacks have higher rates of disease than other populations.The study by Tanner et al (2001) shows that there obese people are more likely to have type II fibers, no matter the race. Since we know that blacks have more type II fibers on average, this explains a part of the variance in the black American obesity rates and further disease acquisition/mortality.

The study by Tanner et al (2001) shows that there obese people are more likely to have type II fibers, no matter the race. Since we know that blacks have more type II fibers on average, this explains a part of the variance in the black American obesity rates and further disease acquisition/mortality.

Differences in muscle fiber typing do not explain all of the variance in disease acquisition/strength differences, however, understanding what the differing fiber typings do, metabolically speaking, along with how they affect disease acquisition will only lead to higher qualities of life for everyone involved.

References

Araujo, A. B., Chiu, G. R., Kupelian, V., Hall, S. A., Williams, R. E., Clark, R. V., & Mckinlay, J. B. (2010). Lean mass, muscle strength, and physical function in a diverse population of men: a population-based cross-sectional study. BMC Public Health,10(1). doi:10.1186/1471-2458-10-508

Andersen K, Lind L, Ingelsson E, Amlov J, Byberg L, Miachelsson K, Sundstrom J. Skeletal muscle morphology and risk of cardiovascular disease in elderly men. Eur J Prev Cardiol 2013.

Ama PFM, Simoneau JA, Boulay MR, Serresse Q Thériault G, Bouchard C. Skeletal muscle characteristics in sedentary Black and Caucasian males. J Appl Physiol 1986: 6l:1758-1761.

American Cancer Society. Cancer Facts & Figures for African Americans 2016-2018. Atlanta: American Cancer Society, 2016.

Ceaser, T., & Hunter, G. (2015). Black and White Race Differences in Aerobic Capacity, Muscle Fiber Type, and Their Influence on Metabolic Processes. Sports Medicine,45(5), 615-623. doi:10.1007/s40279-015-0318-7

Hagiwara N. Muscle fibre types: their role in health, disease and as therapeutic targets. OA Biology 2013 Nov 01;1(1):2.

Hernelahti, M., Tikkanen, H. O., Karjalainen, J., & Kujala, U. M. (2005). Muscle Fiber-Type Distribution as a Predictor of Blood Pressure: A 19-Year Follow-Up Study. Hypertension,45(5), 1019-1023. doi:10.1161/01.hyp.0000165023.09921.34

Hochachka, P.W. (1998) Mechanism and evolution of hypoxia-tolerance in humans. J. Exp. Biol. 201, 1243–1254

Karjalainen, J., Tikkanen, H., Hernelahti, M., & Kujala, U. M. (2006). Muscle fiber-type distribution predicts weight gain and unfavorable left ventricular geometry: a 19 year follow-up study. BMC Cardiovascular Disorders,6(1). doi:10.1186/1471-2261-6-2

Ogden C. L., Carroll, M. D., Lawman, H. G., Fryar, C. D., Kruszon-Moran, D., Kit, B.K., & Flegal K. M. (2016). Trends in obesity prevalence among children and adolescents in the United States, 1988-1994 through 2013-2014. JAMA, 315(21), 2292-2299.

Ruiz, J. R., Sui, X., Lobelo, F., Morrow, J. R., Jackson, A. W., Sjostrom, M., & Blair, S. N. (2008). Association between muscular strength and mortality in men: prospective cohort study. Bmj,337(Jul01 2). doi:10.1136/bmj.a439

Tanner, C. J., Barakat, H. A., Dohm, G. L., Pories, W. J., Macdonald, K. G., Cunningham, P. R., . . . Houmard, J. A. (2001). Muscle fiber type is associated with obesity and weight loss. American Journal of Physiology – Endocrinology And Metabolism,282(6). doi:10.1152/ajpendo.00416.2001

Volaklis, K. A., Halle, M., & Meisinger, C. (2015). Muscular strength as a strong predictor of mortality: A narrative review. European Journal of Internal Medicine,26(5), 303-310. doi:10.1016/j.ejim.2015.04.013

Charles Murray

Arthur Jensen

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