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Setting: 50kya in the Environment of Evolutionary Adaptedness
Imagine you and your band are being chased by a group of animals 50kya in the Savanna. You look back as the herd is almost at your band, about to rip them to pieces. When, suddenly, there is a bright, blinding flash and the animals stop in their tracks, giving your band enough time to escape.
Your band looks back about 200 feet away to see a man standing there with his bald head standing at the animals, directing a beam of UV rays at the group. The women stand there, lovestruck, as this man just saved the band.
This man—and men who looked like him—were then taken on many expeditions and the same thing happened whenever the band got into trouble out in the grasslands. A group of animals threatens the band? No problem, there is a bald man there, waiting to use his head to blind the back so the band can get away.
Women then started showing more affection to the bald men as they proved they can save the band, and without having to risk harm, at that. So women started mating more with them. Bald men then gained more power in the society, as the women of course continued to pick berries while the men hunted—bald men going with both groups to give protection.
Then, over time, genes the conferred a higher chance of becoming bald became fixated in the group as it conveyed a fitness benefit from which resulted from protecting the group by shining UV rays at a pack of animals to save the group resulting in women finding it attractive and so having more children with them.
Sound ridiculous? Well, searching for claims for bald heads being an adaptation, I discovered that someone said the same exact thing:
A well-polished bald male head was often used by tribes of cavemen to blind predators. As a result every cavemen hunting group of 8 had one bald member, and thus thousands of years later 1 in 8 men experience early on set of baldness. – Taz Boonsborg, London, UK
There are other similar adaptive stories for bald heads, such as a lather surface area to receive more vitamin D:
Loss of hair creates more skin area, which means more vitamin D can be absorbed from sunlight. This would provide a survival benefit for me, which would explain this trait being passed on.
While another person makes a similar claim:
I wonder if it can be linked to the time in evolution when Europeans lived in Central Asia before moving west to Europe. Vitamin D was a scarce necessity. I like to think of my bald head as sun ray receiver. I have noticed that women 30+ are a lot more likely to be attracted to me partially due to my baldness, sometimes very much so 😉
There are, thankfully, some commenters that say it has no adaptive value. When it comes to the existence of any trait, of course, one can construct a plausible evolutionary narrative to explain the survival of the trait into the current day.
A conversation about baldness should include a conversation about bearded-ness—as I have written about before. The story goes that beards are adaptive for men, since “beards may have been valuable as a threat signal during direct male-versus-male competition for dominance and resources“, while also stating for pattern baldness that “The senescence feature of male pattern baldness may be an advertisement of social maturity. Social maturity includes enhanced social status but decreased physical threat, increased approachability, and a propensity to nurture.” (Muscarella and Cunningham, 1996). They also discuss differing sexual selection theories for pattern baldness, such as “for an increase in the visual area for the intimidation display of reddening color during anger.” So to these authors, baldness signifies social status, and if one is bald or balding, they can then show their emotions more—especially if light-skinned. So baldness is a signal of senescence—biological aging.
Kabai (2008) hypothesizes (storytells) that androgenic alopecia—male pattern baldness (MPB)—is an adaptation. Each hair follicle has its own resistance to whether or not it will fall out. So, to Kabai (2008: 1039), MPB “evolved to elevate UV absorbance and thus to provide some protection against prostate cancer.” This is a classic just-so story. I have written a ton about the relationship between testosterone, prostate cancer (PCa), and vitamin D. Blacks have lower levels of vitamin D, and higher levels of prostate cancer. (It should be notes that Setty et al (1970) showed that MPB is four times less likely in blacks compared to whites.) So, in whites, baldness was adaptive in order to acquire more UV rays.
Unfortunately for Kabai (2008), the underlying logic of his hypothesis (that the more bald a head, the higher the vitamin D production) was tested. Bolland et al (2008: 675) “found no evidence to support the hypothesis that the degree of baldness in influences serum 25-OHD levels.” This could be, as the authors note, due to the fact that vitamin D is not produced in the scalp or that vitamin D is produced in the scalp but getting sunburned would modify a man’s behavior to spend less time in the sun and so, the so-called benefits of a bald head for vitamin D production would be limited. Bolland et al (2008) end up concluding that:
there is no accepted evolutionary explanation for the almost universal prevalence of hair loss in older men. We suggest that other hypotheses are required to determine why older men go bald and whether baldness serves any physiological purpose.
Why must baldness “serve a physiological purpose”? I like how the proposal of these hypotheses doesn’t consider the fact that hair just falls out at a certain rate in certain individuals with no evolutionary purpose behind it. Everything must have an adaptive purpose, it seems, and so, one creates these fantastic stories. It’s just like Rudyard Kipling’s stories, actually.
Lastly, Yanez (2004) proposes a cultural hypothesis for MPB. Yanez (2004: 982) states that the cause of MPB is “the detention in the sebum flow moving towards the root of hair.” Those who are more likely to suffer from baldness are those with thin hair who constantly cut their hair short, or hair that is straight or low-density. On the other hand, those with high hair density and thicker hair are less likely to go bald, even if they keep short hair. This, to Yanez (2004), the catalyst of balding is cultural but, of course, is driven by physiological factors (blocking the flow of sebum to the hair follicle).
Many kinds of stories have been crafted in order to explain how and why humans—mostly men—are bald. Though, this just speaks to the problem with adaptationist hypotheses—notice bald heads; bald heads are still around (obviously, since we are observing it); since we notice bald heads because they are still around then there must have been an evolutionary advantage for bald heads; *advantages noted above*; therefore baldness is an adaptation. This reasoning, though, is faulty—it’s a kind of rampant adaptationism, that if a trait exists today then it must, therefore, procure an advantage in an evolutionary context which was then therefore selected-for.
Of course, we can not—and should not—discard the hypothesis that bald men still exist because they could direct UV rays at oncoming predators trying to kill the band, the women seeing it, and it, therefore, becoming an attractive signal that the man can protect the family by directing UV rays at other men and animals. That’s a good hypothesis that’s worth investigating. (Sarcasm.)
What would you think if you heard about a new fortune-telling device that is touted to predict psychological traits like depression, schizophrenia and school achievement? What’s more, it can tell your fortune from the moment of your birth, it is completely reliable and unbiased — and it only costs £100.
This might sound like yet another pop-psychology claim about gimmicks that will change your life, but this one is in fact based on the best science of our times. The fortune teller is DNA. The ability of DNA to understand who we are, and predict who we will become has emerged in the last three years, thanks to the rise of personal genomics. We will see how the DNA revolution has made DNA personal by giving us the power to predict our psychological strengths and weaknesses from birth. This is a game-changer as it has far-reaching implications for psychology, for society and for each and every one of us.
This DNA fortune teller is the culmination of a century of genetic research investigating what makes us who we are. When psychology emerged as a science in the early twentieth century, it focused on environmental causes of behavior. Environmentalism — the view that we are what we learn — dominated psychology for decades. From Freud onwards, the family environment, or nurture, was assumed to be the key factor in determining who we are. (Plomin, 2018: 6, my emphasis)
The main premise of Plomin’s 2018 book Blueprint is that DNA is a fortune teller while personal genomics is a fortune-telling device. The fortune-telling device Plomin most discusses in the book is polygenic scores (PGS). PGSs are gleaned from GWA studies; SNP genotypes are then added up with scores of 0, 1, and 2. Then, the individual gets their PGS for trait T. Plomin’s claim—that DNA is a fortune teller—though, falls since DNA is not a blueprint—which is where the claim that “DNA is a fortune teller” is derived.
It’s funny that Plomin calls the measure “unbiased”, (he is talking about DNA, which is in effect “unbiased”), but PGS are anything BUT unbiased. For example, most GWAS/PGS are derived from European populations. But, for example, there are “biases and inaccuracies of polygenic risk scores (PRS) when predicting disease risk in individuals from populations other than those used in their derivation” (De La Vega and Bustamante, 2018). (PRSs are derived from statistical gene associations using GWAS; Janssens and Joyner, 2019.) Europeans make up more than 80 percent of GWAS studies. This is why, due to the large amount of GWASs on European populations, that “prediction accuracy [is] reduced by approximately 2- to 5-fold in East Asian and African American populations, respectively” (Martin et al, 2018). See for example Figure 1 from Martin et al (2018):
With the huge number of GWAS studies done on European populations, these scores cannot be used on non-European populations for ‘prediction’—even disregarding the other problems with PGS/GWAS.
By studying genetically informative cases like twins and adoptees, behavioural geneticists discovered some of the biggest findings in psychology because, for the first time, nature and nurture could be disentangled.
… DNA differences inherited from our parents at the moment of conception are the consistent, lifelong source of psychological individuality, the blueprint that makes us who we are. A blueprint is a plan. … A blueprint isn’t all that matters but it matters more than everything else put together in terms of the stable psychological traits that make us who we are. (Plomin, 2018: 6-8, my emphasis)
Nevermind the slew of problems with twin and adoption studies (Joseph, 2014; Joseph et al, 2015; Richardson, 2017a). I also refuted the notion that “A blueprint is a plan” last year, quoting numerous developmental systems theorists. The main thrust of Plomin’s book—that DNA is a blueprint and therefore can be seen as a fortune teller using the fortune-telling device to tell the fortunes of the people’s whose DNA are analyzed—is false, as DNA does not work how it does in Plomin’s mind.
These big findings were based on twin and adoption studies that indirectly assessed genetic impact. Twenty years ago the DNA revolution began with the sequencing of the human genome, which identified each of the 3 billion steps in the double helix of DNA. We are the same as every other human being for more than 99 percent of these DNA steps, which is the blueprint for human nature. The less than 1 per cent of difference of these DNA steps that differ between us is what makes us who we are as individuals — our mental illnesses, our personalities and our mental abilities. These inherited DNA differences are the blueprint for our individuality …
[DNA predictors] are unique in psychology because they do not change during our lives. This means that they can foretell our futures from our birth.
The applications and implications of DNA predictors will be controversial. Although we will examine some of these concerns, I am unabashedly a cheerleader for these changes. (Plomin, 2018: 8-10, my emphasis)
This quote further shows Plomin’s “blueprint” for the rest of his book—DNA can “foretell our futures from our birth”—and how it affects his conclusions gleaned from his work that he mostly discusses in his book. Yes, all scientists are biased (as Stephen Jay Gould noted), but Plomin outright claimed to be an unabashed cheerleader for his work. Plomin’s self-admission for being an “unabashed cheerleader”, though, does explain some of the conclusions he makes in Blueprint.
However, the problem with the mantra ‘nature and nurture’ is that it runs the risk of sliding back into the mistaken view that the effects of genes and environment cannot be disentangled.
Our future is DNA. (Plomin, 2018: 11-12)
The problem with the mantra “nature and nurture” is not that it “runs the risk of sliding back into the mistaken view that the effects of genes and environment cannot be disentangled”—though that is one problem. The problem is how Plomin assumes how DNA works. That DNA can be disentangled from the environment presumes that DNA is environment-independent. But as Moore shows in his book The Dependent Gene—and as Schneider (2007) shows—“the very concept of a gene requires the environment“. Moore notes that “The common belief that genes contain context-independent “information”—and so are analogous to “blueprints” or “recipes”—is simply false” (quoted in Schneider, 2007). Moore showed in The Dependent Gene that twin studies are flawed, as have numerous other authors.
Lewkowicz (2012) argues that “genes are embedded within organisms which, in turn, are embedded in external environments. As a result, even though genes are a critical part of developmental systems, they are only one part of such systems where interactions occur at all levels of organization during both ontogeny and phylogeny.” Plomin—although he does not explicitly state it—is a genetic reductionist. This type of thinking can be traced back, most popularly, to Richard Dawkins’ 1976 book The Selfish Gene. The genetic reductionists can, and do, make the claim that organisms can be reduced to their genes, while developmental systems theorists claim that holism, and not reductionism, better explains organismal development.
The main thrust of Plomin’s Blueprint rests on (1) GWA studies and (2) PGSs/PRSs derived from the GWA studies. Ken Richardson (2017b) has shown that “some cryptic but functionally irrelevant genetic stratification in human populations, which, quite likely, will covary with social stratification or social class.” Richardson’s (2017b) argument is simple: Societies are genetically stratified; social stratification maintains genetic stratification; social stratification creates—and maintains—cognitive differentiation; “cognitive” tests reflect prior social stratification. This “cryptic but functionally irrelevant genetic stratification in human populations” is what GWA studies pick up. Richardson and Jones (2019) extend the argument and argue that spurious correlations can arise from genetic population structure that GWA studies cannot account for—even though GWA study authors claim that this population stratification is accounted for, social class is defined solely on the basis of SES (socioeconomic status) and therefore, does not capture all of what “social class” itself captures (Richardson, 2002: 298-299).
Plomin also heavily relies on the results of twin and adoption studies—a lot of it being his own work—to attempt to buttress his arguments. However, as Moore and Shenk (2016) show—and as I have summarized in Behavior Genetics and the Fallacy of Nature vs Nurture—heritability estimates for humans are highly flawed since there cannot be a fully controlled environment. Moore and Shenk (2016: 6) write:
Heritability statistics do remain useful in some limited circumstances, including selective breeding programs in which developmental environments can be strictly controlled. But in environments that are not controlled, these statistics do not tell us much. In light of this, numerous theorists have concluded that ‘the term “heritability,” which carries a strong conviction or connotation of something “[in]heritable” in the everyday sense, is no longer suitable for use in human genetics, and its use should be discontinued.’ 31 Reviewing the evidence, we come to the same conclusion.
Heritability estimates assume that nature (genes) can be separated from nurture (environment), but “the very concept of a gene requires the environment” (Schneider, 2007) so it seems that attempting to partition genetic and environmental causation of any trait T is a fool’s—reductionist—errand. If the concept of gene depends on and requires the environment, then how does it make any sense to attempt to partition one from the other if they need each other?
Let’s face it: Plomin, in this book Blueprint is speaking like a biological reductionist, though he may deny the claim. The claims from those who push PRS and how it can be used for precision medicine are unfounded, as there are numerous problems with the concept. Precision medicine and personalized medicine are similar concepts, though Joyner and Paneth (2015) are skeptical of its use and have seven questions for personalized medicine. Furthermore, Joyner, Boros and Fink (2018) argue that “redundant and degenerate mechanisms operating at the physiological level limit both the general utility of this assumption and the specific utility of the precision medicine narrative.” Joyner (2015: 5) also argues that “Neo-Darwinism has failed clinical medicine. By adopting a broader perspective, systems biology does not have to.”
Janssens and Joyner (2019) write that “Most [SNP] hits have no demonstrated mechanistic linkage to the biological property of interest.” Researchers can show correlations between disease phenotypes and genes, but they cannot show causation—which would be mechanistic relations between the proposed genes and the disease phenotype. Though, as Kampourakis (2017: 19), genes do not cause diseases on their own, they only contribute to its variation.
GPS are unique predictors in the behavioural sciences. They are an exception to the rule that correlations do not imply causation in the sense that there can be no backward causation when GPS are correlated with traits. That is, nothing in our brains, behaviour or environment changes inherited differences in DNA sequence. A related advantage of GPS as predictors is that they are exceptionally stable throughout the life span because they index inherited differences in DNA sequence. Although mutations can accrue in the cells used to obtain DNA, like any cells in the body these mutations would not be expected to change systematically the thousands of inherited SNPs that contribute to a GPS.
Turkheimer goes on to say that this (false) assumption by Plomin and Stumm (2018) assumes that there is no top-down causation—i.e., that phenotypes don’t cause genes, or there is no causation from the top to the bottom. (See the special issue of Interface Focus for a slew of articles on top-down causation.) Downward causation exists in biological systems (Noble, 2012, 2017), as does top-down. The very claim that “nothing in our brains, behaviour or environment changes inherited differences in DNA sequence” is ridiculous! This is something that, of course, Plomin did not discuss in Blueprint. But in a book that, supposedly, shows “how DNA makes us who we are”, why not discuss epigenetics? Plomin is confused, because DNA methylation impacts behavior and behavior impacts DNA methylation (Lerner and Overton, 2017: 114). Lerner and Overtone (2017: 145) write that:
… it should no longer be possible for any scientist to undertake the procedure of splitting of nature and nurture and, through reductionist procedures, come to conclusions that the one or the other plays a more important role in behavior and development.
Plomin’s reductionist takes, therefore again, fail. Plomin’s “reluctance” to discuss “tangential topics” to “inherited DNA differences” included epigenetics (Plomin, 2018: 12). But it seems that his “reluctance” to discuss epigenetics was a downfall in his book as epigenetic mechanisms can and do make a difference to “inherited DNA differences” (see for example, Baedke, 2018, Above the Gene, Beyond Biology: Toward a Philosophy of Epigenetics and Meloni, 2019, Impressionable Biologies: From the Archaeology of Plasticity to the Sociology of Epigenetics see also Meloni, 2018). The genome can and does “react” to what occurs to the organism in the environment, so it is false that “nothing in our brains, behaviour or environment changes inherited differences in DNA sequence” (Plomin and Stumm, 2018), since our behavior and actions can and do methylate our DNA (Meloni, 2014) which falsifies Plomin’s claim and which is why he should have discussed epigenetics in Blueprint. End Edit
So the main premise of Plomin’s Blueprint is his two claims: (1) that DNA is a fortune teller and (2) that personal genomics is a fortune-telling device. He draws these big claims from PGS/PRS studies. However, over 80 percent of GWA studies have been done on European populations. And, knowing that we cannot use these datasets on other, non-European datasets, greatly hampers the uses of PGS/PRS in other populations—although the PGS/PRS are not that useful in and of itself for European populations. Plomin’s whole book is a reductionist screed—“Sure, other factors matter, but DNA matters more” is one of his main claims. Though, a priori, since there is no privileged level of causation, one cannot privilege DNA over any other developmental variables (Noble, 2012). To understand disease, we must understand the whole system and how when one part of the system becomes dysfunctional how it affects other parts of the system and how it runs. The PGS/PRS hunts are reductionist in nature, and the only answer to these reductionist paradigms are new paradigms from systems biology—one of holism.
Plomin’s assertions in his book are gleaned from highly confounded GWA studies. Plomin also assumes that we can disentangle nature and nurture—like all reductionists. Nature and nurture interact—without genes, there would be an environment, but without an environment, there would be no genes as gene expression is predicated on the environment and what occurs in it. So Plomin’s reductionist claim that “Our future is DNA” is false—our future is studying the interactive developmental system, not reducing it to a sum of its parts. Holistic biology—systems biology—beats reductionist biology—the Neo-Darwinian Modern Synthesis.
DNA is not a blueprint nor is it a fortune teller and personal genomics is not a fortune-telling device. The claim that DNA is a blueprint/fortune teller and personal genomics is a fortune-telling device come from Plomin and are derived from highly flawed GWA studies and, further, PGS/PRS. Therefore Plomin’s claim that DNA is a blueprint/fortune teller and personal genomics is a fortune-telling device are false.
(Also read Erick Turkheimer’s 2019 review of Plomin’s book The Social Science Blues, along with Steve Pitteli’s review Biogenetic Overreach for an overview and critiques of Plomin’s ideas. And read Ken Richardson’s article It’s the End of the Gene As We Know It for a critique of the concept of the gene.)
The association between muscle fiber typing obesity and race is striking. It is well-established that blacks have a higher proportion of type II skeletal muscle fibers than whites and these higher proportions of these specific types of muscle fibers lead to physiological differences between the two races which then lead to differing health outcomes between them—along with differences in athletic competition. Racial differences in health are no doubt complex, but there are certain differences between the races that we can look at and say that there is a relationship here that warrants further scrutiny.
Why is there an association between negative health outcomes and muscle phsyiology? The answer is very simple if one knows the basics of muscle physiology and how and why muscles contract (it is worth noting that out of a slew of anatomic and phsyiologic factors, movement is the only thing we can consciously control, compare to menstration and other similar physiologic processes which are beyond our control). In this article, I will describe what muscles do, how they are controlled, muscle physiology, the differences in fiber typing between the races and what it means for health outcomes between them.
Muscle anatomy and physiology
Muscle fiber number is determined by the second trimester. Bell (1980) noted that skeletal muscle fiber in 6 year olds is not different from normal adult tissue, and so, we can say that between the time in the womb and age 6, muscle fiber type is set and cannot be changed (though training can change how certain fibers respond, see below).
Muscle anatomy and physiology is interesting because it shows us how and why we move the way we do. Tendons attach muscle to bone. Attached to the tendon is the muscle belly. The muscle belly is made up of facsicles and the fascicles are made up of muscle fibers. Muscle fibers are made up of myofibrils and myofibrils are made up of myofilaments. Finally, myofilaments are made up of proteins—specifically actin and myosin, this is what makes up our muscles.
(Image from here.)
Muscle fibers are encased by sarcolemma which contains cell components such as sarcoplasm, nuclei, and mitochondria. They also have other cells called myofibrils which contain myofilaments which are then made up of actin (thin filaments) and mysoin (thick filaments). These two types of filaments form numerous repeating sections within a myofibril and each repeating section is known as a sarcomere. Sarcomeres are the “functional” unit of the muscle, like the neuron is for the nervous system. Each ‘z-line’ denotes another sarcomere across a myofibril (Franzini-Armstrong, 1973; Luther, 2009).
Other than actin and myosin, there are two more proteins important for muscle contraction: tropomyosin and troponin. Tropomyosin is found on the actin filament and it blocks myosin binding sites which are located on the actin filament, and so it keeps myosin from attaching to muscle while it is in a relaxed state. On the other hand, troponin is also located on the actin filament but troponin’s job is to provide binding sites for calcium and tropomyosin when a muscle needs to contract.
So the structure of skeletal muscle can be broken down like so: epymyseum > muscle belly > perimyseum > fascicle > endomyseum > muscle fibers > myofibrils > myofilaments > myosin and actin. Note diagram (C) from above; the sarcomere is the smallest contractile unit in the myofibril. According to sliding filament theory (see Cook, 2004 for a review), a sarcomere shortens as a result of the ‘z-lines’ moving closer together. The reason these ‘z-lines’ converge is because myosin heads attach to the actin filament which asynchronistically pulls the actin filament across the myosin, which then results in the shortening of the muscle fiber. Sarcomeres are the basic unit controlling changes in muscle length, so the faster or slower they fire depends on the majority type of fiber in that specific area.
But the skeletal muscle will not contract unless the skeletal muscles are stimulated. The nervous system and the muscular system communicate, which is called neural activiation—defined as the contraction of muscle generated by neural stimulation. We have what are called “motor neurons”—neurons located in the CNS (central nervous system) which can send impulses to muscles to move them. This is done through a special synapse called the neuromuscular junction. A motor neuron that connects with muscle fibers is called a motor unit and the point where the muscle fiber and motor unit meet is callled the neuromuscular junction. It is a small gap between the nerve and muscle fiber called a synapse. Action potentials (electrical impulses) are sent down the axon of the motor neuron from the CNS and when the action potential reaches the end of the axon, hormones called neurotransmitters are then released. Neurotransmitters transport the electrical signal from the nerve to the muscle.
Muscle fiber types
The two main categories of muscle fiber are type I and type II—‘slow’ and ‘fast’ twitch, respectively. Type I fibers contain more blood cappilaries, higher levels of mitochondria (which transforms food into ATP) and myoglobin which allows for an improved delivery of oxygen. Since myoglobin is similar to hemoglobin (the red pigment which is found in red blood cells), type I fibers are also known as ‘red fibers.’ Type I fibers are also smaller in diameter and slower to produce maximal tension, but are also the most fatigue-resistant type of fiber.
Type II fibers have two subdivisions—IIa and IIx—based on their mechanical and chemical properties. Type II fibers are in many ways the opposite of type I fibers—they contain far fewer blood cappilaries, mitochondria and myoglobin. Since they have less myoglobin, they are not red, but white, which is why they are known as ‘white fibers.’ IIx fibers have a lower oxidative capacity and thusly tire out quicker. IIa, on the other hand, have a higher oxidative capacity and fatigue slower than IIx fibers (Herbison, Jaweed, and Ditunno, 1982; Tellis et al, 2012). IIa fibers are also known as intermediate fast twitch fibers since they can use both anarobic and aerobic metabolism equally to produce energy. So IIx fibers are a combo of I and II fibers. Type II fibers are bigger, quicker to produce maximal tension, and tire out quicker.
Now, when it comes to fiber typing between the races, blacks have a higher proportion of type II fibers compared to whites who have a higher proportion of type I fibers (Ama et al, 1986; Ceaser and Hunter, 2015; see Entine, 2000 and Epstein, 2014 for reviews). Higher proportions of type I fibers are associated with lower chance of cardiovascular events, whereas type II fibers are associated with a higher risk. Thus, “Skeletal muscle fibre composition may be a mediator of the protective effects of exercise against cardiovascular disease” (Andersen et al, 2015).
Now that the basics of muscle anatomy and physiology are apparent, hopefully the hows and whys of muscle contraction and what different muscle fibers do are becoming clear, because these different fibers are distributed between the races in uneven frequencies, which then leads to differences in sporting performance but also differents in health outcomes.
Muscle fibers and health outcomes
We now know the physiology and anatomy of muscle and muscle fiber typing. We also know the differences between each type of skeletal muscle fiber. Since the two races do indeed differ in the percentage of skeletal muscle fiber possessed on average, we then should find stark differences in health outcomes, part of the reason being these differences in muscle fiber typing.
While blacks on average have a higher proportion of type II muscle fibers, whites have a higher proportion of type I muscle fibers. Noting what I wrote above about the differences between the fiber types, and knowing what we know about racial differences in disease outcomes, we can draw some inferences on how differences in muscle fiber typing between races/individuals can then affect disease seriousness/acquisition.
In their review of black-white differences in muscle fiber typing, Ceaser and Hunter (2015) write that “The longitudinal data regarding the rise in obesity indicates obesity rates have been highest among non-Hispanic Black women and Hispanic women.” And so, knowing what we know about fiber type differences between races and how these fibers act when they fire, we can see how muscle fiber typing would contribute to differences in disease acquisition between groups.
Tanner et al (2001) studied 53 women (n=28, lean women; and n=25, obese women) who were undergoing an elective abdominal surgery (either a hysterectomy or gastric bypass). Their physiologic/anatomic measures were taken and they were divided into races: blacks and whites, along with their obesity status. Tanner et al found that the lean subjects had a higher proportion of type I fibers and a lower proportion of type IIx fibers whereas those who were obese were more likely to have a higher proportion of type IIb muscle fibers.
Like other analyses on this matter, Tanner et al (2001) showed that the black subjects had a higher proportion of type II fibers in comparison to whites who had a higher proportion of type I fibers (adiposity was not taken into account). Fifty-one percent of the fiber typing from whites was type I whereas for blacks it was 43.7 pervent. Blacks had a higher proportion of type IIx fibers than whites (16.3 percent for whites and 23.4 for blacks). Lean blacks and lean whites, though, had a similar percentage of type IIx fibers (13.8 percent for whites and 15 percent for blacks). It is interesting to note that there was no difference in type I fibers between lean whites and blacks (55.1 percent for whites and 54.1 percent for blacks), though muscle fibers from obese blacks contained far fewer type I fibers compared to their white counterparts (48.6 percent for whites and 34.5 for blacks). Obese blacks’ muscle fiber had a higher proportion of type IIx fibers than obese whites’ fiber typing (19.2 percent for whites and 31 percent for blacks). Lean blacks and lean whites had a higher proportion of type I fibers than obese blacks and obese whites. Obese whites and obese blacks had more type IIx fibers than lean whites and lean blacks.
So, since type II fibers are insulin resistant (Jensen et al, 2007), then they should be related to glucose intloerance—type II diabetes—and blacks with ancestry from West Africa should be most affected. Fung (2016, 2018) shows that obesity is a disease of insulin resistance, and so, we can bring that same rationale to racial differences in obesity. Indeed, Nielsen and Christensen (2011) hypothesize that the higher prevalence of glucose intolerance in blacks is related to their lower percentage of type I fibers and their higher percentage of type II fibers.
Nielsen and Christensen (2011) hypothesize that since blacks have a lower percentage of type I fibers (the oxidative type), this explains the lower fat oxidation along with lower resting metabolic rate, sleeping metabolic rate, resting energy expenditure and Vo2 max in comparison to whites. Since type I fibers are more oxidative over the glycolitic type II fibers, the lower oxidative capacity in these fibers “may cause a higher fat storage at lower levels of energy intake than in individuals with a higher oxidative capacity” (Nielsen and Christensen, 2011: 611). Though the ratio of IIx and IIa fibers are extremely plastic and affected by lifestyle, Nielsen and Christensen do note that individuals with different fiber typings had similar oxidative capacity if they engaged in physical activity. Recall back to Caesar and Hunter (2015) who note that blacks have a lower maximal aerobic capacity and higher proportion of type II fibers. They note that lack of physical activity exacerbates the negative effects that a majority type II fibers has over majority type I. And so, some of these differences can be ameliorated between these two racial groups.
The point is, individuals/groups with a higher percentage of type II fibers who do not engage in physical activity have an even higher risk of lower oxidative capacity. Furthermore, a higher proportion of type II fibers implies a higher percentage of IIx fibers, “which are the least oxidative fibres and are positively associated with T2D and obesity” (Nielsen and Christensen, 2011: 612). They also note that this may explain the rural-urban difference in diabetes prevalance, with urban populations having a higher proportion of type II diabetics. They also note that this may explain the difference in type II diabetes in US blacks and West African natives—but the reverse is true for West Africans in the US. There is a higher rate of modernization and, with that, a higher chance to be less physically active and if the individual in question is less physically active and has a higher proportion of type II fibers then they will have a higher chance of acquiring metabolic diseases (obesity is also a metabolic disease). Since whites have a higher proportion of type I fibers, they can increase their fat intake—and with it, their fat oxidation—but this does not hold for blacks who “may not adjust well to changes in fat intake” (Nielsen and Christensen, 2011: 612).
Nielsen and Christensen end their paper writing:
Thus, Blacks of West African ancestry might be genetically predisposed to T2D because of an inherited lower amount of skeletal muscle fibre type I, whereby the oxidative capacity and fat oxidation is reduced, causing increased muscular tissue fat accumulation. This might induce skeletal muscle insulin resistance followed by an induced stress on the insulin-producing beta cells. Together with higher beta-cell dysfunction in the West African Diaspora compared to Whites, this will eventually lead to T2D (an overview of the ‘skeletal muscle distribution hypothesis’ can be seen in Figure 2).
Lambernd et al (2012) show that muscle contractions eliminated insuin resistance by blocking pro-inflammatory signalling pathways: this is the mechanism by which physical activity decreases glucose intolerance and thusly improves health outcomes—especially for those with a higher proportion of type II fibers. Thus, it is important for individuals with type II fibers to exercise, since sedentariness is associated with an age-related insulin resistance due to impaired GLUT4 utilization (Bunprajun et al, 2013).
(Also see Morrison and Cooper’s (2006) hypothesis that “reduced oxygen-carrying capacity induced a shift to more explosive muscle properties” (Epstein, 2014: 179). Epstein notes that the only science there is on this hypothesis is one mouse and rat study showing that low hemoglobin can “induce a switch to more explosive muscle fibers” (Epstein, 2014: 178), but this has not been tested on humans to see if it would hold. If this is tested on humans and if it does hold, then that would lend credence to Morrison’s and Cooper’s (2006) hypothesis.)
Knowing what we know about muscle anatomy and physiology and how muscles act we can understand the influence the different muscle types have on disease and how they contribute to disease variation between race, sex and the individual level. Especially knowing how type II fibers act when the individual in question is insulin resistant is extremely important—though it has been noted that individuals who participate in aerobic exercise decrease their risk for cardiometabolic diseases and can change the fiber distribution difference between IIx and IIa fibers, lowering their risk for acquiring cardiometabolic diseases (Ceaser and Hunter, 2015).
Thinking back to sarcomeres (the smallest contractile unit in the muscle) and how they would act in type II fibers: they would obviously contract much faster in type II muscles over type I muscles; they would then obviously tear faster than type I muscles; since type II muscles are more likely to be insulin resistant, then those with a higher proportion of type II fibers need to focus more on aerobic activity to “balance out” type IIx and IIa fibers and decrease the risk of cardiometabolic disease due to more muscle contractions (Lambernd et al, 2012). Since blacks have a higher proportion of type II fibers and are more likely to be sedentary than whites, and since those who have a higher proportion of type II fibers are more likely to be obese, then it is clear that exercise can and will ameliorate some of the disparity in cardiometabolic diseases between blacks and whites.
Racial differences in body fat are clear to the naked eye: black women are more likely to carry more body fat than white women; Mexican American women are more likely to carry more body fat than white women, too. Different races/ethnies/genders of these races/ethnies have different formulas to assess body fat through the use of skin-folds. The sites to grasp the skin is different based on gender and race.
Body mass index (BMI) and waist circumference is overestimated in blacks, which means that they need different formulas to assess their BMI and adiposity/lean mass. Race-specific formulas/methods are needed to assess body fat and, along with it, disease risk, since blacks are more likely to be obese (black women, at least, it’s different with black American men with more African ancestry, see below). The fact of the matter is, when matched on a slew of variables, blacks had lower total and abdominal fat mass than whites.
This is even noted in Asian, black and white prepubertal children. He et al (2002) show that sex differences in body fat distribution are present in children who have yet to reach puberty and the differences in body fat in Asians is different than that from blacks and whites which also varies by sex. Asian girls had greater gynoid fat by DXA scan only, with girls having greater gynoid fat than boys. Asian girls had lower adjusted extremity fat and gynoid fat compared to white and black girls. Though, Asian boys had a lower adjusted extremity by fat as shown by DXA (a gold standard in body fat measurement) when compared to whites, but greater gynoid fat than whites and blacks.
Vickery, Cureton, and Collins, (1988), Wagner and Heyward (2000), and Robson, Bazin, and Soderstrom (1971) show that there are considerable body composition differences between blacks and whites. These differences in body composition come down to diet, of course, but there is also a genetic/physiologic component there as well. Combining the known fact that skin-fold testing is not conducive to a good estimate, black American men with more African ancestry are less likely to be obese.
Vickery, Cureton, and Collins (1988) argue that, if accurate estimates of body fat percentages are to be obtained, race-specific formulas need to be developed and used as independent variables to assess racial differences in body fat percentage. Differences in muscularity don’t seem to account for these skinfold differences, nor does greater mesomorphy. One possible explanation for differences in skinfold thickness is that blacks may store most of their body fat subcutaneously. (See Wagner and Heyward, 2000 for a review on fat patterning and body composition in blacks and whites.)
The often-used Durnin-Womersley formula which is used to predict body fat just from skin folds. However, “The 1974 DW equations did not predict %BF(DXA) uniformly in all races or ethnicities” (Davidson et al, 2011). Truesdale et al (2016) even show that numerous formulas used to estimate percent body fat are flawed, even some formulas used on different races. Most of the equations tested showed starkly different conclusions. But, this is based on NHANES data and the only data they provide regarding skin-folds is the tricep and subscapular skinfold so there may still be more problems with all of the equations used to assess body fat percentage between races. (Also see Cooper, 2010.)
Klimentidis et al (2016) show that black men—but not black women—seem to be protected against obesity and central adiposity (fat gain around the midsection) and that race negatively correlated with adiposity. The combo of male gender and West African ancestry predicted low levels of adiposity compared to black Americans with less African ancestry. Furthermore, since black men and women have—theoretically—the same SES, then cultural/social factors would not play as large a role as genetic factors in explaining the differences in adiposity between black men and black women. Black men with more African ancestry had a lower WHR and less central adiposity than black men with less African ancestry. If we assume that they had similar levels of SES and lived in similar neighborhoods, there is only one reason why this would be the case.
Klimentidis et al (2016) write:
One interpretation is that AAs are exposed to environmental and/or cultural factors that predispose them to greater obesity than EAs. Possibly, some of the genes that are inherited as part of their West-African ancestry are protective against obesity, thereby “canceling out” the obesifying effects of environment/culture, but only in men. Another interpretation is that genetic protection is afforded to all individuals of African descent, but this protection is overwhelmed by cultural and/or other factors in women.
Black men do, as is popularly believed, prefer bigger women over smaller women. For example, Freedman et al (2004) showed that black American men were more likely to prefer bigger women. Black American men “are more willing to idealize a woman
of a heavier body size, with more curves, than do their White American counterparts” (Freedman et al, 2004: 197). It is then hypothesized that black American men find these figures attractive (figures with “more curves” (Freedman et al, 2004: 197)) to protect against eating pathologies, such as anorexia and bulimia. So, it has been established that black men have thinner skin folds than whites which leads to skewed lean mass/body fat readings and black men with more African ancestry are less likely to be obese. These average differences between races, of course, contribute to differing disease acquisition.
I have covered differences in body fat in a few Asian ethnies and have come to the obvious conclusion: Asians, at the same height, weight etc as whites and blacks, will have more adipose tissue on their bodies. They, too, like blacks and whites, have different areas that need to be assessed for skin folds to estimate body fat.
Henriques (2016: 29) has a table on the equations for calculating estimated body density from skin fold measures from various populations. Of interest are the ones on blacks or ‘Hispanics‘, blacks or athletes and blacks and whites. (The table is provided from NSCA, 2008 so the references are not in the back of the text.)
For black and ‘Hispanic’ women aged 18-55 years, the sites to use for skin-folds are the chest, abdomen, triceps, subscapular, suprailiac, midaxillary, and the thigh. For blacks or athletes aged 18-61 years, the sites to use are the same as before (but a different equation is used for body fat estimation). For white women or anorexic women aged 18-55, the sites used are just triceps, suprailiac and the thigh. For black and white boys aged 6-17, only the triceps and the calf is used. It is the same for black and white girls, but, again, a different formula is used to assess body fat (Henriques, 2016: 29).
Morrison et al (2012) showed that white girls had a higher percent body fat when compared to black girls at ages 9-12 but every age after, black girls had higher percent body fat (which is related to earlier menarche in black girls since they have higher levels of body fat which means earlier puberty; Kaplowitz, 2008). Black girls, though, had higher levels of fat in their subscapular skin folds than white girls at all ages.
So, it seems, there are population-/race-specific formulas that need to be created to better assess body fat percentage in different races/ethnies and not assume that one formula/way of assessing body fat should be used for all racial/ethnic groups. According to the literature (some reviewed here and in Wagner and Heyward, 2000), these types of formulas are sorely needed to better assess health markers in certain populations. These differences in body fat percentage and distribution then have real health consequences for the races/ethnies in question.
Leading behavior geneticist Robert Plomin is publishing “Blueprint: How DNA Makes Us Who We Are” in October of 2018. I, of course, have not read the book yet. But if the main thesis of the book is that DNA is a “code”, “recipe”, or “blueprint”, then that is already wrong. This is because presuming that DNA is any of the three aforementioned things marries one to certain ideas, even if they themselves do not explicitly state them. Nevertheless, Robert Plomin is what one would term a “hereditarian”, meaning that he believes that genes—more than environment—shape an individual’s psychological and other traits. (That’s a false dichotomy, though.) In the preview for the book at MIT Press, they write:
In Blueprint, behavioral geneticist Robert Plomin describes how the DNA revolution has made DNA personal by giving us the power to predict our psychological strengths and weaknesses from birth. A century of genetic research shows that DNA differences inherited from our parents are the consistent life-long sources of our psychological individuality—the blueprint that makes us who we are. This, says Plomin, is a game-changer. It calls for a radical rethinking of what makes us who were are.
Genetics accounts for fifty percent of psychological differences—not just mental health and school achievement, but all psychological traits, from personality to intellectual abilities. Nature defeats nurture by a landslide.
Plomin explores the implications of this, drawing some provocative conclusions—among them that parenting styles don’t really affect children’s outcomes once genetics is taken into effect. Neither tiger mothers nor attachment parenting affects children’s ability to get into Harvard. After describing why DNA matters, Plomin explains what DNA does, offering readers a unique insider’s view of the exciting synergies that came from combining genetics and psychology.
I won’t get into most of these things today (I will wait until I read the book for that), but this will be just an article showing that DNA is, in fact, not a blueprint, and DNA is not a “code” or “recipe” for the organism.
It’s funny that the little blurb says that “Nature defeats nurture by a landslide“, because, as I have argued at length, nature vs nurture is a false dichotomy (See Oyama, 1985, 2000, 1999; Moore, 2002; Schneider, 2007; Moore, 2017). Nature vs nurture is the battleground that the false dichotomy of genes vs environment is fought on. However, it makes no sense to partition heritability estimates if it is indeed true that genes interact with environment—that is, if nature interacts with nurture.
DNA is also called “the book of life”. For example, in her book The Epigenetics Revolution: How Modern Biology Is Rewriting Our Understanding of Genetics, Disease, and Inheritance, Nessa Carey writes that “There’s no debate that the DNA blueprint is a starting point” (pg 16). This, though, can be contested. “But the promise of a peep into the ‘book of life’ leading to a cure for all diseases was a mistake” (Noble, 2017: 161).
Developmental psychologist and cognitive scientist David S. Moore concurs. In his book The Developing Genome: An Introduction to Behavioral Epigenetics, he writes (pg 45):
So, although I will talk about genes repeatedly in this book, it is only because there is no other convenient way to communicate about contemporary ideas in molecular biology. And when I refer to gebe, I will be talking about a segment or segments of DNA containing sequence information that is used to help construct a protein (or some other product that performs a biological function). But it is worth remembering that contemporary biologists do not mean any one thing when they talk about “genes”; the gene remains a fundementally hypothetical concept to this day. The common belief that there are things inside of us that constitute a set of instructions for building bodies and minds—things that are analogous to “blueprings” or “recipes”—is undoubedtly false. Instead, DNA segements often contain information that is ambiguous, and that must be edited or arranged in context-dependent ways before it can be used.
Still, other may use terms like “genes for” trait T. This, too, is incorrect. In his outstanding book Making Sense of Genes, Kostas Kamporakis writes (pg 19):
I also explain why the notion of “genes for,” in the vernacular sense, is not only misleading but also entirely inaccurate and scientifcally illegitamate.
First, I show that genes “operate” in the context of development only. This means that genes are impllicated in the development of characters but do not determine them. Second, I explain why single genes do not alone produce characters or disease but contribute to their variation. This means that genes can account for variation in characters but cannot alone explain their origin. Third, I show that genes are not the masters of the game but are subject to complex regulatory processes.
Genes can only be seen as passive templates, not ultimate causes (Noble, 2011), and they cannot explain the origin of different characters but can account for variation in physical characters. Genes only “do” something in the context of development; they are inert molecules and thusly cannot “cause” anything on their own.
Genes are not ‘for’ traits, but they are difference-makers for traits. Sterelny and Griffiths (1999: 102), in their book Sex and Death: An Introduction to Philosophy of Biology write:
Sterelny and Griffiths (1988) responded to the idea that genes are invisible to selection by treating genes as difference makers, and as visible to selection by virtue of the differences they make. In doing so, they provided a formal reconstruction of the “gene for” locution. The details are complex, but the basic intent of the reconstruction is simple. A certain allele in humans is an “allele for brown eyes” because, in standard environments, having that allele rather than alternatives typically available in the population means that your eyes will be brown rather than blue. This is the concpet of a gene as a difference maker. It is very important to note, however, that genes are context-sensitive difference makers. Their effects depend on the genetic, cellular, and other features of their environment.
(Genes can be difference makers for physical traits, but not for psychological traits because no psychophysical laws exist, but I’ll get to that in the future.)
Note how the terms “context-sensitive” and “context-dependent” continue to appear. The DNA-as-blueprint statement presumes that DNA is context-independent, but we cannot divorce genes—whatever they are—from their context, since genes and environment, nature and nurture, are intertwined. (And it is even questioned if ‘genes’ are truly units of inheritance, see Fogle, 1990. Fogle, 2000 also argues to dispense with the concept of “gene” and that biologists should be using terms like intron, promoter region, and exon. Nevertheless, there is a huge disconnect with the term “gene” in molecular biology and classical genetics. Keller 2000 argues that there are still uses for the term “gene” and that we should not dispense with the term. I believe we should dispense with it.)
Susan Oyama (2000: 77) writes in her book The Ontogeny of Information:
“Though a plan implies action, it does not itself act, so if the genes are a blueprint, something else is the constructor-construction worker. Though blueprints are usually contrasted with building materials, the genes are quite easily conceptualized as templates for building tools and materials; once so utilized, of course, they enter the developmental process and influence its course. The point of the blueprint analogy, though, does not seem to be to illuminate developmental processes, but rather to assume them and, in celebrating their regularity, to impute cognitive functions to genes. How these functions are exercised is left unclear in this type of metaphor, except that the genetic plan is seen in some peculiar way to carry itself out, generating all the necessary steps in the necessary sequence. No light is shed on multiple developmental possibilities, species-typical or atypical.“
The Modern Synthesis is one of the causes for the genes-as-blueprints thinking; the Modern Synthesis has causation in biology wrong. Genes are not active causes, but they are passive templates, as argued by many authors. They, thus, cannot “cause” anything on their own.
In his 2017 book Dance to the Tune of Life: Biological Relativity, Denis Noble writes (pg 157):
As we saw earlier in this chapter, these triplet sequences are formed from any combination of the four bases U, C, A and G in RNA and T, C, A and G in DNA. They are often described as a genetic ‘code’, but it is important to understand that this usage of the word ‘code’ carries overtones that can be confusing.
A code was originally an intentional encryption used by humans to communicate. The genetic ‘code’ is not intentional in that sense. The word ‘code’ has unfortunately reinforced the idea that genes are active and even complete causes, in much the same was as a computer is caused to follow the instructions of a computer program. The more nuetral word ‘template’ would be better. Templates are used only when required (activated); they are not themselves active causes. The active causes lie within the cells themselves since they determine the expression patterns for the different cell types and states. These patterns are comminicated to the DNA by transcrption factors, by methylation patterns and by binding to the tails of histones, all of which influence the pattern and speed of transcription of different parts of the genome. If the word ‘instruction’ is useful here at all, it is rather that the cell instructs the genome. As Barbara McClintock wrote in 1984 after receiving her Nobel Prize, the genome is an ‘organ of the cell’, not the other way around.
Realising that DNA is under the control of the system has been reinforced by the discovery that cells use different start, stop and splice sites for producing different messenger RNAs from a single DNA sequence. This enables the same sequence to code different proteins in different cell types and under different conditions [here’s where context-dependency comes into play again].
Representing the direction of causality in biology the wrong way round is therefore confusing and has far-reaching conseqeunces. The causality is circular, acting both ways: passive causality by DNA sequences acting as otherwise inert templates, and active causality by the functional networks of interactions that determine how the genome is activated.
This takes care of the idea that DNA is a ‘code’. But what about DNA being a ‘blueprint’, that all of the information is contained in the DNA of the organism before conception? DNA is clearly not a ‘program’, in the sense that all of the information to construct the organism exists already in DNA. The complete cell is also needed, and its “complex structures are inherited by self-templating” (Noble, 2017: 161). Thus, the “blueprint” is the whole cell, not just the genome itself (remember that the genome is an organ of the cell).
Lastly, GWA studies have been all the rage recently. However, there is only so much we can learn just from association studies, before we need to turn to the physiological sciences for functional analyses. Indeed, Denis Noble (2018) writes in a new editorial:
As with the results of GWAS (genome-wide association studies) generally, the associations at the genome sequence level are remarkably weak and, with the exception of certain rare genetic diseases, may even be meaningless (13, 21). The reason is that if you gather a sufficiently large data set, it is a mathematical necessity that you will find correlations, even if the data set was generated randomly so that the correlations must be spurious. The bigger the data set, the more spurious correlations will be found (3).
The results of GWAS do not reveal the secrets of life, nor have they delivered the many cures for complex diseases that society badly needs. The reason is that association studies do not reveal biological mechanisms. Physiology does. Worse still, “the more data, the more arbitrary, meaningless and useless (for future action) correlations will be found in them” is a necessary mathematical statement (3).
Nor does applying a highly restricted DNA sequence-based interpretation of evolutionary biology, and its latest manifestation in GWAS, to the social sciences augur well for society.
It is further worth noting that there is no privileged level of causation in biological systems (Noble, 2012)—a priori, there is no justification to privilege one system over another in regard to causation, so saying that one level of the organism is “higher” than another (for instance, saying that genes are, and should be, privileged over the environment or any other system in the organism regarding causation) is clearly false, since there is upwards and downwards causation, influencing all levels of the system.
In sum, it is highly misleading to refer to DNA as “blueprints”, a “code”, or a “recipe.” Referring to DNA in this way means that one presumes that DNA can be divorced from its context—that it does not work together with the environment. As I have argued in the past, association studies will not elucidate genetic mechanisms, nor will heritability estimates (Richardson, 2012). We need physiological testing for these functional analyses, and association studies like GWAS and even heritability estimates don’t tell us this type of information (Panofsky, 2014). So, it seems, that what Plomin et al are looking for that they assume are “in the genes”, are not there, because they use a false model of the gene (Burt, 2015; Richardson, 2017). Genes are resources—templates to be used by and for the system—not causes of traits and development. They can account for differences in variation, but cannot be said to be the origin of trait differences. Genes can be said to be difference makers, but knowing whether or not they are difference makers for behavior, in my opinion, cannot be known.
(For further information on genes and what they do, reach Chapters Four and Five of Ken Richardson’s book Genes, Brains, and Human Potential: The Science and Ideology of Intelligence. Plomin himself seems to be a reductionist, and Richardson took care of that paradigm in his book. Lickliter (2018) has a good review of the book, along with critiques of the reductionist paradigm that Plomin et al follow.)
In the 1940s, psychologist William Sheldon created a system of body measures known as “somatotyping”, then took his somatotypes and attempted to classify each soma (endomorph, ectomorph, or mesomorph) to differing personality types. It was even said that “constitutional psychology can guide a eugenics program and save the modern world from itself.”
Sheldon attempted to correlate different personality dimensions to different somas. But his somas fell out of favor before being revived by two of his disciples—without the “we-can-guess-your-personality-from-your-body-type” canard that Sheldon used. Somatotyping, while of course being put to use in a different way today compared to what it was originally created for, it gives us reliable dimensions for human appendages and from there we can ascertain what a given individual would excel at in regard to sporting events (obviously this is just on the basis of physical measures and does not measure the mind one needs to excel in sports).
The somatotyping system is straightforward: You have three values, say at 1-1-7; the first refers to endomorphy, the second refers to mesomorphy and the third refers to ectomorphy, therefore a 1-1-7 would be an extreme ectomorph. However, few people are at the extreme end of each soma, and most people have a combination of two or even all three of the somas.
According to Carter (2002): “The somatotype is defined as the quantification of the present shape and composition of the human body.” So, obviously, somas can change over time. However, it should be noted that the somatotype is, largely, based on one’s musculoskeletal system. This is where the appendages come in, along with body fat, wide and narrow clavicles and chest etc. This is why the typing system, although it began as a now-discredited method, should still be used today since we do not use the pseudoscientific personality measures with somatotyping.
Ectomorphs are long and lean, lanky, you could say. They have a smaller, narrower chest and shoulders, along with longer arms and legs, and have a hard time gaining weight, and a short upper body (I’d say they have a harder time gaining weight due to a slightly faster metabolism, in the variation of the normal range of metabolism, of course). Put simply, ectomorphs are just skinny and lanky with less body fat than mesos and endos. Human races that fit this soma are East Africans and South Asians (see Dutton and Lynn, 2015; one of my favorite papers from Lynn for obvious reasons).
Endomorphs are stockier, shorter and have wider hips, along with short limbs, a wider trunk, more body fat and can gain muscular strength easier than the other somas. Thus, endos, being shorter than ectos and mesos, have a lower center of gravity, along with shorter arms. Thus, we should see that these somas dominate strongman competitions and this is what we see. Pure strength competitions are perfect for this type, such as Strongman competitions and powerlifting. Races that generally conform to this type are East Asians, Europeans, and Pacific Islanders (see Dutton and Lynn, 2015).
Finally, we have mesomorphs (the “king” of all of the types). Mesos are more muscular on average than the two others, they have less body fat than endos but more body fat than ectos; they have wider shoulders, chest and hips, a short trunk and long limbs. The most mesomorphic races are West Africans (Malina, 1969), and due to their somatotype they can dominate sprinting competitions; they also have thinner skin folds (Vickery, Cureton, and Collins, 1988; Wagner and Heyward, 2000), and so they would have an easier time excelling at running competitions but not at weightlifting, powerlifting, or Strongman (see Dutton and Lynn, 2015).
These anatomic differences between the races of man are due to climatic adaptations. The somatypic differences Neanderthals and Homo sapiens mirror the somatotype difference between blacks and whites; since Neanderthals were cold-adapted, they were shorter, had wider pelves and could thusly generate more power than the heat-adapted Homo sapiens who had long limbs and narrow pelvis to better dissipate heat. Either way, we can look at the differences in somatotype between races that evolved in Europe and Africa to ascertain the somatotype of Neanderthals—and we also have fossil evidence for these claims, too (see e.g., Weaver and Hublin, 2009; Gruss and Schmitt, 2016)
Now, just because somatotyping, during its conception, was mixed with pseudoscientific views about differing somas having differing psychological types, does not mean that these differences in body type do not have any bearing on sporting performance. We can chuck the “constitutional psychology” aspect of somatotyping and just keep the anthropometric measures, and, along with the knowledge of human biomechanics, we can then discuss, in a scientific manner, why one soma would excel in sport X or why one soma would not excel in sport X. Attempting to argue that since somatotyping began as some crank psuedoscience does not mean that it is not useful today, since we do not ascribe inherent psychological differences to these somas (I’d claim that saying that this soma has a harder time gaining weight compared to that soma is not ascribing a psychological difference to the soma; it is taking physiologically and on average we can see that different somas have different propensities for weight gain).
In her book Straightening the Bell Curve: How Stereotypes about Black Masculinity Drive Research about Race and Intelligence, Hilliard (2012: 21) discusses the pitfalls of somatotyping and how Sheldon attempted to correlate personality measures with his newfound somatotypes:
As a young graduate student, he [Richard Herrnstein] had fallen under the spell of Harvard professor S. S. Stevens, who had coauthored with William Sheldon a book called The Varieties of Temperament: A Psychology of Constitutional Differences, which popularized the concept of “somatotyping,” first articulated by William Sheldon. This theory sought, through the precise measurement and analysis of human body types, to establish correlations comparing intelligence, temperament, sexual proclivities, and the moral worth of individuals. Thus, criminals were perceived to be shorter and heavier and more muscular than morally upstanding citizens. Black males were reported to rank higher on the “masculine component” scale than white males did, but lower in intelligence. Somatotyping lured the impressionable young Herrnstein into a world promising precision and human predictability based on the measuring of body parts.
Though constitutional psychology is now discredited, there may have been something to some of Sheldon’s theories. Ikeda et al (2018: 3) conclude in their paper, Re-evaluating classical body type theories: genetic correlation between psychiatric disorders and body mass index, that “a trans-ancestry meta-analysis of the genetic correlation between psychiatric disorders and BMI indicated that the negative correlation with SCZ supported classical body type theories proposed in the last century, but found a negative correlation between BD and BMI, opposite to what would have been predicted.” (Though it should be noted that SCZ is a, largely if not fully, environmentally-induced disorder, see Joseph, 2017.)
These different types (i.e., the differing limb lengths/body proportions) have implications for sporting performance. Asfaw and A (2018) found that Ethiopian women high jumpers had the highest ectomorph values whereas long and triple jumpers were found to be more mesomorphic. Sports good for ectos are distance running due to their light frame, tennis etc—anything that the individual can use their light frame as an advantage. Since they have longer limbs and a lighter frame, they can gain more speed in the run up to the jump, compared to endos and mesos (who are heavier). This shows why ectos have a biomechanical advantage when it comes to high jumping.
As for mesomorphs, the sports they excel at are weightlifting, powerlifting, strongman, football, rugby etc. Any sport where the individual can use their power and heavier bone mass will they excel in. Gutnik et al (2017) even concluded that “These results suggest with high probability that there is a developmental tendency of change in different aspects of morphometric phenotypes of selected kinds of sport athletes. These phenomena may be explained by the effects of continuous intensive training and achievement of highly sport-defined shapes.” While also writing that mesomorphy could be used to predict sporting ability.
Finally, for endomorphs, they too would excel in weightlifting, powerlifting, and strongman, but do on average better since they have different levers (i.e., shorter appendages so they can more weight and a shorter amount of time in comparison to those with longer limbs like ectos).
Thus, different somatotypes excel in different sports. Different races and ethnies have differing somatotypes (Dutton and Lynn, 2015), so these different bodies that the races have, on average, is part of the cause for differences in sporting ability. That somatotyping began as a pseudoscientific endeavor 70 years ago does not mean that it does not have a use in today’s world—because it clearly does due to the sheer amount of papers on the usefulness of somatotyping and relating differences in sporting performance due to somatotyping. For example, blacks have thinner skin folds (Vickery, Cureton, and Collins, 1988; Wagner and Heyward, 2000) which is due to their somatotype, which is then due to the climate their ancestors evolved in.
Somatotyping can show us the anthropometric reasons for how and why certain individuals, ethnies, and races far-and-away dominate certain sporting events. It is completely irrelevant that somatotyping began as a psychological pseudoscience (what isn’t in psychology, am I right?). Understanding anthropometric differences between individuals and groups will help us better understand the evolution of these somas along with how and why these somas lead to increased sporting performance in certain domains. Somatotyping has absolutely nothing to do with “intelligence” nor how morally upstanding one is. I would claim that somatotyping does have an effect on one’s perception of masculinity, and thus more masculine people/races would tend to be more mesomorphic, which would explain what Hilliard (2012) discussed when talking about somatotyping and the attempts to correlate differing psychological tendencies to each type.
Due to evolving in different climates, the different races of Man have differing anatomy and physiology. This, then, leads to differences in sports performance—certain races do better than others in certain bouts of athletic prowess, and this is due to, in large part, heritable biological/physical differences between blacks and whites. Some of these differences are differences in somatotype, which bring a considerable advantage for, say, runners (an ecto-meso, for instance, would do very well in sprinting or distance running depending on fiber typing). This article will discuss differences in racial anatomy and physiology (again) and how it leads to disparities in certain sports performance.
Kerr (2010) argues that racial superiority in sport is a myth. (Read my rebuttal here.) In his article, Kerr (2010) attempts to rebut Entine’s (2000) book Taboo: Why Black Athletes Dominate Sports and Why We’re Afraid to Talk About It. In a nutshell, Kerr (2010) argues that race is not a valid category; that other, nongenetic factors play a role other than genetics (I don’t know if anyone has ever argued if it was just genetics). Race is a legitimate biological category, contrary to Kerr’s assertions. Kerr, in my view, strawman’s Entine (2002) by saying he’s a “genetic determinist”, but while he does discuss biological/genetic factors more than environmental ones, Entine is in no way a genetic determinist (at least that’s what I get from my reading of his book, other opinions may differ). Average physical differences between races are enough to delineate racial categories and then it’s only logical to infer that these average physical/physiological differences between the races (that will be reviewed below) would infer an advantage in certain sports over others, while the ultimate cause was the environment that said race’s ancestors evolved in (causing differences in somatotype and physiology).
Black athletic superiority has been discussed for decades. The reasons are numerous and of course, this has even been noticed by the general public. In 1991, half of the respondents of a poll on black vs. whites in sports “agreed with the idea that “blacks have more natural physical ability,“” (Hoberman, 1997: 207). Hoberman (1997) of course denies that there is any evidence that blacks have an advantage over whites in certain sports that come down to heritable biological factors (which he spends the whole book arguing). However, many blacks and whites do, in fact, believe in black athletic superiority and that physiologic and anatomic differences between the races do indeed cause racial differences in sporting performance (Wiggins, 1989). Though Wiggins (1989: 184) writes:
The anthropometric differences found between racial groups are usually nothing more than central tendencies and, in addition, do not take into account wide variations within these groups or the overlap among members of different races. This fact not only negates any reliable physiological comparisons of athletes along racial lines, but makes the whole notion of racially distinctive physiological abilities a moot point.
This is horribly wrong, as will be seen throughout this article.
|Data from Malina, (1969: 438)||n||Mesomorph||Ectomorph||Endomorph|
|Data from Malina (1969: 438)||Blacks||Whites|
|Thin-build body type||8.93||5.90|
|Submedium fatty development||48.31||29.39|
|Fat and very fat categories||9.09||21.06|
This was in blacks and whites aged 6 to 11. Even at these young ages, it is clear that there are considerable anatomic differences between blacks and whites which then lead to differences in sports performance, contra Wiggins (1989). A basic understanding of anatomy and how the human body works is needed in order to understand how and why blacks dominate certain sports over whites (and vice versa). Somatotype is, of course, predicated on lean mass, fat mass, bone density, stature, etc, which are heritable biological traits, thus, contrary to popular belief that somatotyping holds no explanatory power in sports today (see Hilliard, 2012).
One variable that makes up somatotype is fat-free body mass. There are, of course, racial differences in fat mass, too (Vickery, Cureton, and Collins, 1988; Wagner and Heyward, 2000). Lower fat mass would, of course, impede black excellence in swimming, and this is what we see (Rushton, 1997; Entine, 2000). Wagner and Heyward (2000) write:
Our review unequivocally shows that the FFB of blacks and whites differs significantly. It has been shown from cadaver and in vivo analyses that blacks have a greater BMC and BMD than do whites. These racial differences could substantially affect measures of body density and %BF. According to Lohman (63), a 2% change in the BMC of the body at a given body density could, theoretically, result in an 8% error in the estimation of %BF. Thus, the BMC and BMD of blacks must be considered when %BF is estimated.
While Vickery, Cureton, and Collins (1988) found that blacks had thinner skin folds than whites, however, in this sample, somatotype did not explain racial differences in bone density, like other studies (Malina, 1969), Vickery, Cureton, and Collins (1988) found that blacks were also more likely to be mesomorphic (which would then express itself in racial differences in sports).
Hallinan (1994) surveyed 32 sports science, exercise physiology, biomechanics, motor development, motor learning, and measurement evaluation textbooks to see what they said racial differences in sporting performance and how they explained them. Out of these 32 textbooks, according to Wikipedia, these “textbooks found that seven [textbooks] suggested that there are biophysical differences due to race that might explain differences in sports performance, one [textbook] expressed caution with the idea, and the other 24 [textbooks] did not mention the issue.” Furthermore, Strklaj and Solyali (2010), in their paper “Human Biological Variation in Anatomy Textbooks: The Role of Ancestry” write that their “results suggest that this type of human variation is either not accounted for or approached only superficially and in an outdated manner.”
It’s patently ridiculous that most textbooks on the anatomy and physiology of the human body do not talk about the anatomic and physiologic differences between racial and ethnic groups. Hoberman (1997) also argues the same, that there is no evidence to confirm the existence of black athletic superiority. Of course, many hypotheses have been proposed to explain how and why blacks are at an inherent advantage in sport. Hoberman (1997: 269) discusses one, writing (quoting world record Olympian in the 400-meter dash, Lee Evans):
“We were bred for it [athletic dominance] … Certainly the black people who survived in the slave ships must have contained the highest proportion of the strongest. Then, on the plantations, a strong black man was mated with a strong black woman. We were simply bred for physical qualities.”
While Hoberman (1997: 270-1) also notes:
Finally, by arguing for a cultural rather than a biological interpretation of “race,” Edwards proposed that black athletic superiority results from “a complex of societal conditions” that channels a disproporitionate number of talented blacks into athletic careers.
The fact that blacks were “bred for” athletic dominance is something that gets brought up often but has little (if any) empirical support (aside from just-so stories about white slavemasters breeding their best, biggest and strongest black slaves). The notion that “a complex of societal conditions” (Edwards, 1971: 39) explains black dominance in sports, while it has some explanatory power in regard to how well blacks do in sporting competition, it, of course, does not tell the whole story. Edwards (1978: 39) argues that these complex societal conditions “instill a heightened motivation among black male youths to achieve success in sports; thus, they channel a proportionately greater number of talented black people than whites into sports participation.” While this may, in fact, be true, this does nothing to rebut the point that differences in anatomic and physiologic factors are a driving force in racial differences in sporting performance. However, while these types of environmental/sociological arguments do show us why blacks are over-represented in some sports (because of course motivation to do well in the sport of choice does matter), they do not even discuss differences in anatomy or physiology which would also be affecting the relationship.
For example, one can have all of the athletic gifts in the world, one can be endowed with the best body type and physiology to do well in any type of sport you can imagine. However, if he does not have a strong mind, he will not succeed in the sport. Lippi, Favaloro, and Guidi (2008) write:
An advantageous physical genotype is not enough to build a top-class athlete, a champion capable of breaking Olympic records, if endurance elite performances (maximal rate of oxygen uptake, economy of movement, lactate/ventilatory threshold and, potentially, oxygen uptake kinetics) (Williams & Folland, 2008) are not supported by a strong mental background.
Any athlete—no matter their race—needs a strong mental background, for if they don’t, they can have all of the physical gifts in the world, they will not become top-tier athletes in the sport of their choice; advantageous physical factors are imperative for success in differing sports, though myriad variables work in concert to produce the desired effect so you cannot have one without the other. On the other side, one can have a strong mental background and not have the requisite anatomy or physiology needed to succeed in the sport in question, but if he has a stronger mind than the individual with the requisite morphology, then he probably will win in a head-to-head competition. Either way, a strong mind is needed for strong performance in anything we do in life, and sport is no different.
Echoing what Hoberman (1997) writes, that “racist” thoughts of black superiority in part cause their success in sport, Sheldon, Jayaratne, and Petty (2007) predicted that white Americans’ beliefs in black athletic superiority would coincide with prejudice and negative stereotyping of black’s “intelligence” and work ethic. They studied 600 white men and women to ascertain their beliefs on black athletic superiority and the causes for it. Sheldon, Jayaratne, and Petty (2007: 45) discuss how it was believed by many, that there is a “ perceived inverse relationship between athleticism and intelligence (and hard work).” (JP Rushton was a big proponent of this hypothesis; see Rushton, 1997. It should also be noted that both Rushton, 1997 and Entine, 2000 believe that blacks’ higher rate of testosterone—3 to 15 percent— [Ross et al, 1986; Ellis and Nyborg, 1992; see rebuttal of both papers] causes their superior athletic performance, I have convincingly shown that they do not have higher levels of testosterone than other races, and if they do the difference is negligible.) However, in his book The Sports Gene: Inside the Science of Extraordinary Athletic Performance, Epstein (2014) writes:
With that stigma in mind [that there is an inverse relationship between “intelligence” and athletic performance], perhaps the most important writing Cooper did in Black Superman was his methodological evisceration of any supposed inverse link between physical and mental prowess. “The concept that physical superiority could somehow be a symptom of intellectual superiority became associated with African Americans … That association did not begin until about 1936.”
What Cooper (2004) implied is that there was no “inverse relationship” with intelligence and athletic ability until Jesse Owens blew away the competition at the 1936 Olympics in Berlin, Germany. In fact, the relationship between “intelligence” and athletic ability is positive (Heppe et al, 2016). Cooper is also a co-author of a paper Some Bio-Medical Mechanisms in Athletic Prowess with Morrison (Morrison and Cooper, 2006) where they argue—convincingly—that the “mutation appears to have triggered a series of physiological adjustments, which have had favourable athletic consequences.”
Thus, the hypothesis claims that differences in glucose conversion rates between West African blacks and her descendants began, but did not end with the sickling of the hemoglobin molecule, where valine is substituted for glutamic acid, which is the sixth amino acid of the beta chain of the hemoglobin molecule. Marlin et al (2007: 624) showed that male athletes who were inflicted with the sickle cell trait (SCT) “are able to perform sprints and brief exercises at the highest levels.” This is more evidence for Morrison and Cooper’s (2006) hypothesis on the evolution of muscle fiber typing in West African blacks.
Bejan, Jones, and Charles (2010) explain that the phenomenon of whites being faster swimmers in comparison to blacks being faster runners can be accounted for by physics. Since locomotion is a “falling-forward cycle“, body mass falls forward and then rises again, so mass that falls from a higher altitude falls faster and forward. The altitude is set by the position of center of mass above the ground for running, while for swimming it is set by the body rising out of the water. Blacks have a center of gravity that is about 3 percent higher than whites, which implies that blacks have a 1.5 percent speed advantage in running whereas whites have a 1.5 percent speed advantage in swimming. In the case of Asians, when all races were matched for height, Asians fared even better, than whites in swimming, but they do not set world records because they are not as tall as whites (Bejan, Jones, and Charles, 2010).
It has been proposed that stereotype threat is part of the reasons for East African running success (Baker and Horton, 2003). They state that many theories have been proposed to explain black African running success—from genetic theories to environmental determinism (the notion that physiologic adaptations to climate, too, drive differences in sporting competition). Baker and Horton (2003) note that “that young athletes have internalised these stereotypes and are choosing sport participation accordingly. He speculates that this is the reason why white running times in certain events have actually decreased over the past few years; whites are opting out of some sports based on perceived genetic inferiority.” While this may be true, this wouldn’t matter, as people gravitate toward what they are naturally good at—and what dictates that is their mind, anatomy, and physiology. They pretty much argue that stereotype threat is a cause of East African running performance on the basis of two assertions: (1) that East African runners are so good that it’s pointless to attempt to win if you are not East African and (2) since East Africans are so good, fewer people will try out and will continue the illusion that East Africans would dominate in middle- and long-distance running. However, while this view is plausible, there is little data to back the arguments.
To explain African running success, we must do it through a systems view—not one of reductionism (i.e., gene-finding). We need to see how the systems in question interact with every part. So while Jamaicans, Kenyans, and Ethiopians (and American blacks) do dominate in running competitions, attempting to “find genes” that account for success n these sports seems like a moot point—since the whole system is what matters, not what we can reduce the system in question to.
However, there are some competitions that blacks do not do so well in, and it is hardly discussed—if at all—by any author that I have read on this matter. Blacks are highly under-represented in strength sports and strongman competitions. Why? My explanation is simple: the causes for their superiority in sprinting and distance running (along with what makes them successful at baseball, football, and basketball) impedes them from doing well in strength and strongman competitions. It’s worth noting that no black man has ever won the World’s Strongest Man competition (indeed the only African country to even place—Rhodesia—was won by a white man) and the causes for these disparities come down to racial differences in anatomy and physiology.
I discussed racial differences in the big four lifts and how racial differences in anatomy and physiology would contribute to how well said race performed on the lift in question. I concluded that Europeans and Asians had more of an advantage over blacks in these lifts, and the reasons were due to inherent differences in anatomy and physiology. One major cause is also the differing muscle fiber typing distribution between the races (Alma et al, 1986; Tanner et al, 2002; Caesar and Henry, 2015 while blacks’ fiber typing helps them in short-distance sprinting (Zierath and Hawley, 2003). Muscle fiber typing is a huge cause of black athletic dominance (and non-dominance). Blacks are not stronger than whites, contrary to popular belief.
I also argued that Neanderthals were stronger than Homo sapiens, which then had implications for racial differences in strength (and sports). Neanderthals had a wider pelvis than our species since they evolved in colder climes (at the time) (Gruss and Schmidt, 2016). With a wider pelvis and shorter body than Homo sapiens, they were able to generate more power. I then implied that the current differences in strength and running we see between blacks and whites can be used for Neanderthals and Homo sapiens, thusly, evolution in differing climates lead to differences in somatotype, which eventually then lead to differences in sporting competition (what Baker and Horton, 2003 term “environmental determinism” which I will discuss in the context of racial differences in sports in the future).
Finally, blacks dominate the sport of bodybuilding, with Phil Heath dominating the competition for the past 7 years. Blacks dominate bodybuilding because, as noted above, blacks have thinner skin folds than whites, so their striations in their muscles would be more prevalent, on average, at the same exact %BF. Bodybuilders and weightlifters were similar in mesomorphy, but the bodybuilders showed more musculature than the bodybuilders whereas the weightlifters showed higher levels of body fat with a significant difference observed between bodybuilders and weightlifters in regard to endomorphy and ectomorphy (weightlifters skewing endo, bodybuilders skewing ecto, as I have argued in the past; Imran et al, 2011).
To conclude, blacks do dominate American sporting competition, and while much ink has been spilled arguing that cultural and social—not genetic or biologic—factors can explain black athletic superiority, they clearly work in concert with a strong mind to produce the athletic phenotype, no one factor has prominence over the other; though, above all, if one does not have the right mindset for the sport in question, they will not succeed. A complex array of factors is the cause of black athletic dominance, including muscle fibers, the type of mindset, anatomy, overall physiology and fat mass (among other variables) explain the hows and whys of black athletic superiority. Cultural and social explanations—on their own—do not tell the whole story, just as genetic/biologic explanations on their own would not either. Every aspect—including the historical—needs to be looked at when discussing the dominance (or lack thereof) in certain sports along with genetic and nongenetic factors to see how and why certain races and ethnies excel in certain sports.
I’ve been chronicling the VDH recently since it has great explanatory—and predictive—power. Light skin is a clear adaptation to low UVR, while dark skin is a clear adaptation to high UVR. Dark, highly melanized skin confers advantages in high UVR environments, such as protection against DNA damage, and also absorbs sufficient UV for vitamin D production while also protecting against folate depletion. However, when our ancestors migrated out of Africa, dark skin would not cut it in temperate environments with highly variable UV rays. This is where our highly adaptive physiology came into play, ensuring that we survived in highly variable environments. Light skin was important in low UVR environments in order to synthesize ample vitamin D, however, that synthesized vitamin D then conferred numerous other physiological advantages to the cold.
Eighty to ninety percent of the vitamin D required for humans comes from the sun, whereas ten to twenty percent comes from the diet, such as fatty fish, eggs, and dairy products (fortified with vitamin D, of course) (Ajabshir, Asif, and Nayer, 2014). Humans need to rely on high amounts of UV rays for vitamin D synthesis (Carlberg, 2014) other than Arctic peoples. Since dark skin does not synthesize vitamin D as well as light skin, skin gradually lightened as our ancestors migrated out of Africa (Juzeniene et al, 2009). This was then imperative to the physiologic adaptations that then occurred as our physiology had to adapt to novel, colder environments with fewer UV rays.
Sufficient amounts of vitamin D are highly important for the human musculoskeletal system (Wintermeyer et al, 2016), which is extremely important for birthing mothers. Along with the increased vitamin D synthesis in low UV environments, the heightened production of vitamin D conferred numerous other physiologic benefits which then helped humans adapt to colder environments with more varying UVR.
Vasoconstriction occurs when the blood vessels constrict which leads to heightened blood pressure, whereas vasodilation is the dilation of blood vessels which decreases blood pressure. So evolutionarily speaking, we had to have adaptive physiology in order to be able to “switch” back and forth between vasoconstriction and vasodilation, depending on what the current environment needed. Vasodilation, though, most likely had no advantage in high UV environments, and thus must have been an advantage in low UV environments, where it was more likely to be colder and so, when the blood vessels constrict, blood pressure increases and thus, heat loss could be considerably slowed in these environments due to these physiologic adaptations.
The races also differ, along with many other physiologic abilities, in nitric oxide-mediated vasodilation. Vasodilation is the dilation of blood vessels, which increases blood pressure. Mata-Greenwood and Chen (2008) reviewed the relevant literature regarding black/white differences in nitric oxide-dependent vasorelaxation and concluded that nitric oxide vasodilation is reduced in darker-skinned populations. Thus, we can infer that in lighter-skinned populations nitric oxide vasodilation is increased in lighter-skinned populations, which would have conferred a great physiological advantage when it came to colonizing environments with lower UV rays.
VDR and vitamin D metabolizing enzymes are present in adipose tissue. Tetrahydrobiopterin; which acts as a cofactor in the synthesis of nitric oxide and its primary function is as a vasodilator in the blood vessels (meaning that blood pressure is increased, to keep more heat in the cold) (Chalupsky and Cai, 2005). Since vasodilation is the body’s primary response to heat stress, blood flow increases which allows heat to leave the body. Therefore, the human body’s ability regarding vasodilation and vasoconstriction mechanisms were important in surviving areas with varying UVR.
One function of our adipose tissue is the storage of vitamin D, while vitamin D metabolizing enzymes and VDR are also expressed in the adipocyte (Abbas, 2017). With these known actions of vitamin D on adipose tissue, we can speculate that since vitamin D and the VDR are expressed in adipose tissue, it may have exerted a role in the adipose tissue which may have been important for surviving in cold, low UV environments (see below).
Furthermore, since these mechanisms are brought on by short-term changes, we can infer that it would hardly be of any use in high UVR environments and would be critical in temperate environments. So, vasodilation and vasoconstriction have little to no benefit in high UVR environments but seem to be imperative in temperate environments where UVR varies. It’s also likely that vitamin D influences vasodilation by influential nitric oxide synthesis (see Andrukhova et al, 2014) and vasoconstriction by influencing the renin-angiotensin system (Ajabshir, Asig, and Nayer, 2014).
This would have conferred great benefit to our ancestors as they migrated into more temperate and colder climates. You can read this for information on how adaptive our physiology is and why it’s like that. Because we went into numerous new environments and natural selection couldn’t act quickly enough, therefore the human body’s physiology is extremely adaptive.
What this suggests is that as skin lightened and adapted to low UV, the increased synthesis in vitamin D influenced vasodilation by a strong influence on nitric oxide synthase, along with vasoconstriction, implies that it would have been easier to survive in novel environments due to adaptive physiology and skin color, along with body fat reserves and the physiologic effects of vitamin D on adipose tissue. These physiologic adaptations would have been of no to little use in Africa. Thus, they must have been useful after we migrated out of Africa and experienced wildly varying environments—the whole reason why our physiology evolved (Richardson, 2017: chapter 5).
When the human body is exposed to cold, a few things occur: cutaneous vasoconstriction, shivering (Castellani and Young, 2016), “behavioral thermoregulation” (Young, Sawka, and Pandolf, 1996), while the human body can adapt physiologically to the cold (Young, 1994). The physiologic functions that vitamin D and folate in regard to vasodilation and vasoconstriction, there is a great chance that these effects were important in maintaining energy homeostasis in colder climates.
In sum, the evolution of light skin conferred a great survival advantage to our ancestors. This then upped the production of vitamin D synthesis in the body, which where then of utmost importance in regard to the adaptation of the human physiology to colder, lower-UV environments. Without our adaptive physiological systems, we would not have been able to leave Africa into novel environments. We need both behavioral thermoregulation as well as adaptive physiology to be able to survive in novel environments. Thus, the importance of skin lightening in our evolution becomes clearer:
As humans migrated out of Africa, lighter skin was needed to synthesize vitamin D. This was especially important to women, who needed higher amounts of vitamin D, in order to produce enough calcium for lactation and pregnancy—so the babe had enough calcium to grow its skeleton in the womb. With the uptake in vitamin D synthesis, this then allowed more adaptive physiologic changes that occurred due to the cold, and along with vasodilation and vasoconstriction, along with shivering and adapting behaviorally to the new environments, were our ancestors able to survive. Dark skin cannot synthesize vitamin D as well as light skin in low UV environments; this also can be seen with the lowered production of nitric oxide-dependent vasodilation in dark-skinned populations. Thus, vasoconstriction conferred no physiologic benefit in high UV environments, but almost certainly conferred a physiologic benefit in low UV environments.
Skin color differences between the sexes are always discussed in terms of women being lighter than men, but never men being darker than women. This is seen in numerous animal studies (some reviewed by Rushton and Templer, 2012; read rebuttal here; also see Ducrest, Keller, and Roulin, 2008). Though, the colors that evolved on the animal’s fur due to whatever mate choices are irrelevant to the survival capabilities that the fur, feathers etc give to the organism in question. So, when we look at humans, we lost our protective body hair millions of years ago (Lieberman, 2015), and with that, we could then sweat. So since furlessness evolved in the lineage Homo, there was little flexibility in what could occur due to environmental pressures on skin color in Africa. It should be further noted that, as Nina Jablonski writes in her book Living Color: The Biological and Social Meaning of Skin Color (2012, pg 74)
No researchers, by the way, have explored the opposite possibility, that women deliberately selected darker men!
One hypothesis proposes that lighter skin in women first arose as a byproduct due to the actions of differing levels of hormones in the sexes—with men obviously having higher levels of testosterone, making them darker them women. So according to this hypothesis, light-skinned women evolved since men could tell high-quality from low-quality mates as well as measure hormonal status and childbearing potential, which was much easier to do with lighter- than darker-skinned women.
Another hypothesis put forth is that further from the equator, sexual competition between women would have increased for mates since mates were depleted, and so light skin evolved since men found it more beautiful. Thus, women living at higher latitudes were lighter than women living at lower latitudes because men had to go further to hunt which meant they were more likely to die which caused even greater competition between females, lightening their skin even more. And another, related, argument, proposed that light skin in women evolved due to a complex of childlike traits which includes a higher voice, smoother skin and childlike facial features, which then reduced male competition and aggressiveness. But women did not stay around waiting to be provisioned and they got out and gathered, and hunted sometimes, too.
Harris (2005) proposes that light skin evolved due to parental selection—mothers choosing the lightest daughters to survive, killing off the darker ones. All babies are born pale—or at least lacking the amount of pigment they have later in life. So how would parental—mostly maternal—selection have caused selection for lighter skin in girls as Harris (2005) proposes? It’d be a pretty large guessing game.
The role of sexual selection in regard to human skin color, though, has been tested and falsified. Madrigal and Kelly (2007a) tested the hypothesis that skin reflectance should be positively correlated with distance from the equator. It was proposed by other authors that as our ancestors migrated out of Africa, environmental selection relaxed and sexual selection took over. Their data did not lend credence to the hypothesis and falsified it.
Madrigal and Kelly (2007a: 475) write (emphasis mine):
We tested the hypothesis that human sexual dimorphism in skin color should be positively correlated with distance from the equator, a proposal generated by the sexual selection hypothesis. We found no support for that proposition. Before this paper was written, the sexual selection hypothesis was based on stated male preference data in a number of human groups. Here, we focused on the actual pattern of sexual dimorphism. We report that the distribution of human sexual dimorphism in relation to latitude is not that which is predicted by the sexual selection hypothesis. According to that hypothesis, in areas of low solar radiation, there should be greater sexual dimorphism, because sexual selection for lighter females is not counterbalanced by natural selection for dark skin. Our data analysis does not support this prediction.
Though Frost (2007) replied, stating that Madrigal and Kelly (2007a) presumed that sexual selection was equal in all areas. Madrigal and Kelly (2007b) responded, stating that they tested one specific hypothesis regarding sexual selection and found it to be false. Frost (2007) proposed two hypotheses in order to test his version, but, again, no one has proposed that women select darker men, which could be a cause of lighter-skinned women (though sexual selection does not—and cannot—explain the observed gradation in skin color between men and women).
Skin color differences between men and women first arose to ensure women enough calcium for lactation and pregnancies. Since skin pigmentation protects against UVR but also must generate vitamin D, it must be light or dark enough to ensure ample vitamin D production in that certain climate, along with protecting against the UVR in that climate. So women needed sufficient vitamin D, which meant they needed sufficient calcium to ensure a strong skeleton for the fetus, for breastfeeding and for the mother’s own overall health.
However, breastfeeding new babes is demanding on the mother’s body (calcium reserves are depleted four times quicker), and the calcium the babe needs to grow its skeleton comes directly from the mother’s bones. Even a mother deficient in vitamin D will still give calcium to the babe at the expense of her own health. But she then needs to increase her reserves of calcium in order to ensure future pregnancies aren’t fatal for her or her offspring.
Though, at the moment to the best of my knowledge, there are no studies on calcium absorption, vitamin D levels and the recovery of the female skeleton after breastfeeding. (Though n3 fatty acids are paramount as well, and so a mother must have sufficient fat stores; see Lassek and Gaulin, 2008.) Thus, light-skinned women are most likely at an advantage when it comes to vitamin D production: The lighter they are, the more vitamin D and calcium they can produce for more pregnancies. Since light skin synthesizes vitamin D more efficiently, the body could then synthesize and use calcium more efficiently. The body cannot use and absorb calcium unless vitamin D is present. Since the fetus takes calcium from the mother’s skeleton, ample amounts of vitamin D must be present. For ample amounts of vitamin D to be present, the skin must be light enough to ensure vitamin D synthesis which would be needed for calcium absorption (Cashman, 2007; Gallagher, Yalamanchili, and Smith, 2012; Aloia et al, 2013).
Nina Jablonski writes in her book (2012, 77):
Women who are chronically deficient in vitamin D because of successive pregnancies and periods of breastfeeding experience a form of bone degeneration called osteomalacia. This has serious consequences for infants born of later pregnancies and for mothers themselves, who are at greater risk of breaking bones. It makes sense that protection of female health during the reproductive years would be a top evolutionary priority, so we are now investigating whether, in fact, slightly lighter skin in women might be a fairly simple way of ensuring that women get enough vitamin D after pregnancy and breastfeeding to enable their bodies to recover quickly. The need for maintaining strong female skeletons through multiple pregnancies may have been the ultimate evolutionary reason for the origin of differences in skin color between men and women.
While Jablonski and Chaplin (2000: 78) write:
We suggest that lighter pigmentation in human females began as a trait directly tied to increased fitness and was subsequently reinforced and enhanced in many human populations by sexual selection.
It is obvious that skin color in women represents a complex balancing act between giving the body the ability to synthesize ample vitamin D and protect from UVR. Skin coloration in humans is very clearly highly adaptive to UVR, and so, with differing average levels of UVR in certain geographic locales, skin color would have evolved to accommodate the human body to whichever climate it found itself in—because human physiology is perhaps the ultimate adaptation.
Sexual selection for skin color played a secondary, not primary role (Jablonski, 2004: 609) in the evolution of skin color differences between men and women. There is a delicate balancing act between skin color, vitamin D synthesis, and UVR protection. Women need to produce enough vitamin D in order to ensure enough calcium and its absorption to the baby and then ensure there are ample amounts to replace what the baby took while in the womb in order for future pregnancies to be successful. Sexual selection cannot explain the observed gradation in skin color between the races and ethnies of the human race. In my opinion, the only explanation for the observed explanation is the fact that skin color evolved due to climatic demands, while independent justification exists for the hypothesis as a whole (Jablonski and Chaplin, 2010).
I don’t see any way that sexual selection can explain the observed gradation in skin color around the world. Skin color is very clearly an adaptation to climate, though of course, cultural customs could widen the skin color differences between the sexes, and make women lighter over time. Nevertheless, what explains the observed skin gradation is adaptation to climate to ensure vitamin D synthesis among a slew of other factors (Jones et al, 2018). Sexual selection, while it may explain small differences between the sexes, cannot explain the differences noted between the native human races.
Vitamin D is an important “vitamin” (it is really a steroid hormone). It is produced when the skin (the largest organ in the body) is exposed to the sun’s UVB rays (Nair and Maseeh, 2012). So this is one of the only ways to get natural levels of UVB. We can then think that, if a population is outside of its natural evolutionary habitat (the habitat where that skin color evolved), then we should note numerous problems caused by the lack of vitamin D in whichever population is studied outside of a location that doesn’t get the correct amount of UVB rays from the sun.
Black Americans are more likely than other ethnies to be deficient in vitamin D (Harris, 2006; Cosman et al, 2007; Nair, 2012; Forest and Stuhldreher, 2014; Taksler et al, 2014). But, paradoxically, low vitamin D levels don’t cause weaker bones in black Americans (O’Conner et al, 2014). However, like with all hypotheses, there are naysayers. For example. Powe et al (2013) argue that vitamin D tests misdiagnose blacks, that blacks have a form of the vitamin that cells can use called 25-hydroxyvitamin D. They conclude: “Community-dwelling black Americans, as compared with whites, had low levels of total 25-hydroxyvitamin D and vitamin D–binding protein, resulting in similar concentrations of estimated bioavailable 25-hydroxyvitamin D. Racial differences in the prevalence of common genetic polymorphisms provide a likely explanation for this observation.” Though there are a whole host of problems here.
The limitations of Powe et al (2013) striking: it was cross-sectional and observational (like most nutrition studies) so they were unable to predict effects of vitamin-D binding protein on bone fractures; no data on the consumption of vitamin D supplements; measurement of bone turnover markers, urinary calcium excretion and levels of 1,25-dihydroxyvitamin D may explain the effect of VDBP (vitamin D-binding protein) on mineral metabolism; and they relied on a calculation, rather than a measurement of 25-hydroxyvitamin D levels.
Powe et al’s (2013) findings, though, have been disputed. Using different measurement tools from Powe et al (2013), Henderson et al (2015) conclude that “Counter to prior observations by immunoassay, VDBG concentrations did not vary by race.” While Bouillon (2014) writes: In our view, black Americans, as compared with white Americans, have lower levels of not only total 25-hydroxyvitamin D but also free or bioavailable 25-hydroxyvitamin D.” And finally, Hollis and Bikle (2014) write: “Specifically, for any given physically measured level of bio-available 25-hydroxyvitamin D, the authors are overestimating bio-available 25-hydroxyvitamin D by 2 to 2.5 times owing to underestimation of vitamin D–binding protein in blacks.”
Either way, even if what Powe et al (2013) conclude is true, that would not mean that black Americans should not supplement with vitamin D, since many diseases and health problems are associated with low vitamin D intake in blacks, including osteoporosis, cardiovascular disease, cancer, diabetes, and other serious conditions (Harris, 2006). An indirect relationship between low levels of vitamin D and hypertension is also noted (Mehta and Agarwal, 2017). Since there is an indirect relationship between vitamin D levels and hypertension, then we should keep an eye on this because black Americans have some of the highest levels of hypertension in the world (Ferdinand and Armani, 2007; see also Fuchs, 2011).
Vitamin D is, of course, important for skeletal and nonskeletal health (Kennel et al, 2010). So if vitamin D is important for skeletal and nonskeletal health, we should see more diseases in black Americans that imply a lack of this steroid in the body. Although blacks have stronger bones even when deficient in vitamin D, it is still observed that black children who break their forearms have less vitamin D circulating in their blood (Ryan et al, 2011). This observation is borne out by the data, since black children are more likely to be deficient in vitamin D compared to other ethnies (Moore, Murphy, and Hollick, 2005). Since black skin predicts vitamin D deficiency (Thomas and Demay, 2000), it seems logical to give vitamin D supplements to children, especially black children, on the basis that it would help lower incidences of bone fractures, even though blacks have stronger bones than whites.
Furthermore, physiologically “normal” levels of vitamin D differ in blacks compared to whites (Wright et al, 2012). They showed that it is indeed a strong possibility that both whites and blacks have different levels of optimum vitamin D. Wright et al (2012) showed that there is a relationship between 25(OH)D levels and intact parathyroid hormone (iPth); for blacks, the threshold in which there was no change was 20 ng/ml whereas for whites it was 30 ng/ml which suggests that there are different levels of optimal vitamin D for each race, and the cause is due to skin color. Thus, physiologically “normal” levels of vitamin D differ for blacks and whites.
There is also a high prevalence of vitamin D deficiency/insufficiency and asthma in black inner-city youth in Washington DC (Freishtat et al, 2010). We can clearly see that, even though black Americans have stronger bones than white Americans and vitamin D predicts bone strength, the fact that blacks have stronger bones than whites even while being deficient in vitamin D on average does not mean that black Americans should not supplement with vitamin D, since it would ameliorate many other problems they have that are related to vitamin D deficiency.
There are also racial differences in prostate cancer (PCa) acquisition too, and vitamin D deficiency may also explain this disparity (Khan and Partin, 2004; Bhardwaj et al, 2017). I have heavily criticized the explanations that testosterone influences PCa, while having indicated that environmental factors such as diet and vitamin D deficiency may explain a large amount of the gap (Batai et al, 2017; but see Stranaland et al, 2017 for a contrary view). Since low vitamin D is related to prostate cancer, by supplementing with vitamin D, it is possible that levels of PCa may decrease. Kristal et al (2014) show that both high and low levels of vitamin D are associated with PCa.
Evidence also exists that vitamin D levels and hypertension are related. Rostand (2010) proposes a unified hypothesis: an important role exists in vitamin D deficiency and the pathogenesis and maintenance of hypertension in blacks (Rostand, 2010).
(From Rostand, 2010)
Since black Americans are no longer near the equator, their ability to synthesize vitamin D from UVB rays is diminished. This then probably leads the RAS (renin-angiotensin system) and inflammatory cytokine activation which then leads to vascular endothelial dysfunction along with structural changes to the microvasculature, which have been linked to vascular (arterial) stiffness along with increased vascular resistance, and these changes are shown to precede hypertension, which also occurs early in life. So since blacks are deficient in vitamin D, which even starts in the womb (Bodnar et al, 2007; Dawodu and Wagner, 2007; Lee et al, 2007; Khalessi et al, 2015; Seto et al, 2016), and this vitamin D deficiency most likely produces changes in large and small arteries and arterials, this could be the explanation for higher hypertension in black Americans (Rostand, 2010: 1701).
This would be a large environmental mismatch: since the population is displaced from its ancestral homeland, then this causes problems since it is not the environment where their ancestors evolved. So in this case, since black Americans are concentrated in the southeast corner of the United States, this may explain the high rates of vitamin D deficiency and hypertension in the black American community.
People whose ancestors evolved in locations with fewer UVB rays have lighter skin, whereas people whose ancestors evolved in locations with more UVB rays have darker skin. Thus, by placing populations in their opposite evolutionary environment, we can see how and why deleterious effects would occur in the population that is in the mismatched environment. For whites, skin cancer would occur, whereas for blacks, higher rates of hypertension and low birth weights occur.
Looking at levels of vitamin D deficiency in races is a great way to understand the evolution of certain populations. Because if the vitamin D hypothesis is correct, if skin color is an adaptation to UVB rays, with light skin being an adaptation to low UVB while dark skin is an adaptation to high UVB, then we can safely hypothesize about certain problems that would arise in races that are outside of their natural habitats. We have confirmed these hypotheses—black Americans who are outside of the location that their ancestors evolved in are more likely to have deleterious symptoms, and the symptoms are due to differences in vitamin D production, which come down to differences in skin color and how the skin synthesizes vitamin D in low-light environments.
Even though blacks have stronger bones than whites, this does not mean that they do not experience fractures at a high rate—especially children—and since the association was noticed, then by supplementing with vitamin D, this may lower the disparity of these types of injuries.
Since black Americans, compared to their evolutionary history, live in low-light environments, this then explains the how and why of vitamin D deficiency and why blacks need to supplement with vitamin D; no matter if certain studies show that blacks are ‘healthy’ even though they have low levels of vitamin D. If true (which I strongly doubt), that does not mean that black Americans should not supplement with vitamin D, because numerous other maladies are associated with vitamin D intake. This is one aspect where understanding the evolution of our species and the different races in it would lead to better medical care for individuals and ancestral groups that may need special treatment.
It is clear that race and geography should inform vitamin D intake, for if we do this, many diseases that arise can be ameliorated and quality of life can increase for everyone.