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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.
Black-white differences get talked about more than Asian-white differences. (For the purposes of this article, “Asian” refers to Koreans, Chinese, Japanese and Filipinos whereas “white” refers to those of European descent.) One interesting racial difference is that of body fatness between ethnies/races. Blacks have thinner skin folds and lower percent body fat than whites at the same height/BMI, and Asians have higher body fat and larger skinfolds than do whites. The interesting thing about this Asian-white difference is the fact that, at the same BMI, Asians have more upper body fat (trunk) than whites. The interesting thing is that there are two good studies, looking at these types of differences between Asians and whites (one study looking at the aforementioned “Asians” I previously identified and whites in the NYC area and another comparing whites and Chinese living in China.)
Wang et al (1994) studied 687 healthy volunteers (445 whites and 242 Asians, ranging from 18-94 years of age with BMIs in the range of 15-38). They defined ethnicity as the birthplace of one’s grandparents. The “Asian” category included 225 Chinese, 9 Japanese, 6 Koreans and 2 Filipinos; 97 percent of this sample was born in Asia. Then, after an overnight fast to better assess body fat differences and skinfold measures, they were weighed and measured, with their back, butt and feet firmly against the wall.
They measured skinfold thickness at the midarm for the average of the triceps and biceps, trunk thickness was the average circumference of the chest, subscapular, umbilicus, abdomen, and suprailiac. The circumference of the arm was measured at the midarm, while the circumference of the trunk was the average circumference of the upper chest, waist, iliac crest, and chest.
For lean and normal BMIs, Asians were fatter than whites in both sexes, but the differences in estimated fat% between whites and Asians varied by BMI in different directions for males and females: fat% increased with BMI for males but decreased with BMI for females.
Whites were had significantly larger circumference in the measured appendages compared to Asians, while in Asian and white females, the circumference of the arms and waist were not different but other circumferences showed a greater difference, favoring whites. Asians had significantly higher levels of subcutaneous trunk fat (upper body fat) than whites, while white females had more lower (thigh) body fat than Asians. In both sexes, Asians had thicker bicep, subscapular, abdomen, and suprailiac skinfolds than whites, in both sexes. White women had higher levels of subcutaneous fat in their thighs. The only difference between white and Asian males in regard to skinfold area was the thigh, with whites having larger thighs, but were similar at the midarm and trunk. Asian men had a larger trunk skinfold area whereas whites had a larger thigh skinfold area while arm fatness did not differ between the races. Women in both races had larger skinfold areas except in the trunk; for whites, there were no differences between the sexes. In both sexes, Asians had higher values in subcutaneous fat (at the midarm, trunk, and midthigh), but white women had a higher value in the thigh than Asian women.
Wang et al (1994) show that there are significant differences in body fatness at different sites of the body, and so, since most (if not all) BMI equations are based on white populations, then, these equations will not work for Asians and will result in substantial error.
Wang et al (2011) studied differences in body composition between Chinese and white males living in the Shenzhen, Guangdong Province, China. They studied 115 Chinese and 114 white males. In this sample, Chinese males were younger, shorter, had a lower body weight and lower BMI than the white sample. Whites had higher fat mass, fat-free mass and bioelectrical impedance (which assess body composition, which measures lean mas in relation to fat mass; but these can be skewed by how much water one has or has not drunk, and so the DXA scan and hydrostatic weighing are, in my opinion, superior assessors). After adjustment for age and BMI, the percentage of fat mass in the trunk and arm was higher in Chinese than white males. Further, Chinese men had higher diastolic blood pressure (DBP), fasting glucose (FG) and triglycerides (TG), while whites had higher fasting total plasma cholesterol (TC) and high-density lipoprotein (HDL). The only statistically significant differences were between FG and HDL. Even after adjustment, Chinese men had 3.0 mmHg higher DBP than whites.
Chinese men had higher percent body fat than whites and more fat stored around their trunks than whites at the same BMI. Chinese men had higher fasting glucose levels (a risk-factor for obesity) but lower HDL levels at the same BMI as whites. Wang et al (2011) write:
In addition, comparing the two nationally representative studies, NHANES III  and China National Nutrition and Health Survey 2002 (CNNHS 2002) , Chinese men held a relatively 15.0% lower mean value of BMI than that for American white men. While comparison results from two large-scale epidemiological studies, the Shanghai Diabetes Studies (SHDS)  and the NHANES III , show that the mean value of PBF for American men is relatively 7.4% higher than that for Chinese men. The relative difference of PBF between American and Chinese males is much less than the difference of BMI, implying that the PBF among American men should be lower than that of Chinese men with the same BMI level.
What this implies is that the proportion of overweight/obese Chinese men are severely underestimated since, as noted earlier, most—if not all—BMI equations are created using strictly white populations. This study also provides more evidence that Chinese men had more central (trunk) adiposity than whites (Britons, in this study; Eston, Evans, and Fu, 1994). Central adiposity and risk for type II diabetes and cardiovascular disease is heightened in those of Chinese descent (Weng et al, 2006). It should also be noted that, in a sample of 129 Pacific Islanders, 120 Asians, 91 Maoris, and 91 Europeans aged 12-91, the relationship between bioelectrical impedance analysis (BIA) is ethnicity-dependent, due to the fact the equations developed for fatness estimation using BIA were more accurate than what was recommended by the manufacturer (Sluyter et al, 2010). Cheng (2011) showed that central adiposity was more predictive of cardiovascular diseases in the Chinese population than was BMI, while Hu et al (2007) showed that central obesity was more related to diabetes mellitus and impaired fasting glucose than to overall obesity in the Chinese population.
So, clearly, obesity-related factors appear at lower BMIs for Asians than Europeans (e.g., Huxley et al, 2008). Pan et al (2004) showed that for most BMI values, incidences of hypertension, diabetes, and hyperuricemia were higher in the Taiwanese sample than in the white and black samples. As BMI got higher, the risk for hypertriglyceridemia and hypertension increased. They showed that BMIs of 22.6, 26, and 27.5 were the cutoffs for the best predictabilty in regard to negative and positive variables for Taiwanese, white and black men, respectively. Pan et al (2004: 31) write:
For BMIs 27, 85% of Taiwanese, 66% of whites, and 55% of blacks had at least one of the studied comorbidities. However, a cutoff close to the median of the studied population was often found by maximizing sensitivity and specificity. Reducing BMI from 25 to 25 in persons in the United States could eliminate 13% of the obesity comorbidity studied. The corresponding cutoff in Taiwan is slightly 24.
Pan et al (2004) conclude that, for Taiwanese (Asians) in their study, they should have a lower BMI cutoff than whites and blacks, though it is tough to ascertain where that cutoff would be.
Bell, Adair, and Popkin (2002) show that “at BMI levels less than 25, prevalence difference figures suggested a stronger association between BMI and hypertension in Chinese men and women but not in Filipino women, compared with non-Hispanic Whites” while “[n]on-Hispanic Blacks and Filipino women had a higher prevalence of hypertension at every level of BMI compared with non-Hispanic Whites and Mexican Americans.”
Since Asians have a higher risk of hypertension than whites after controlling for BMI, this indicates that the effects of obesity are not as important as other factors, be they genetic or environmental (or both, which it obviously is). The higher incidence of obesity-related risk-factors in Asian populations with lower BMIs has been attributed to GxE interactions, which, of course, have been intensified with the introduction of the Western Diet (AKA the SAD [Standard American Diet] diet). This can be most notably seen with the explosion of childhood obesity in China, with the number of obese people in China surpassing the US recently, while China is on its way to have the most obese children in the world. The surging obesity epidemic in China is due to increasingly similar lifestyles to what we have (sedentary populations; highly processed, high fat, high carbohydrate foodstuff).
So since the findings in the reviewed studies suggest that, at a lower BMI, Asians are more susceptible to obesity-related risk-factors, and so, BMI standards must be lowered for Asian populations, which would be BMI 24 for overweight and BMI 27 for obese, which was recommended by the Chinese Ministry of Health (Wang et al, 2010). Cheung et al (2018) show that diet quality is inversely associated with obesity in Chinese adults who have type II diabetes.
In conclusion, Asians at the same BMI have higher body fat percentage than whites, and they also have more obesity-related risk-factors than whites at a lower BMI (Pan et al, 2004; WHO expert consultation, 2004; Wang et al, 2010; Hsu et al, 2015), which implies that they need differing BMI scales, just as blacks need different scales in comparison with whites. Here is a good example of two people with the same BMI (22.3) but different DXA results:
This, of course, shows the strong limitations of the use of the same BMI standards calculated in one ethny and used for another. So, just like at the same BMI blacks have lower body fat and thinner skinfolds than whites (Vickery, Cureton, and Collins, 1988; Wagner and Heyward, 2000; Flegal et al, 2010), at the same BMI as whites, Asians have higher body fat and thicker skinfolds (Wang et al, 1994; WHO expert consultation, 2004; Wang et al, 2011).
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.
Everyone wants to know the keys to athletic success, however, as I have argued in the past, to understand elite athletic performance, we must understand how the system works in concert with everything—especially in the environments the biological system finds itself in. To reduce factors down to genes, or training, or X or Y does not make sense; to look at what makes an elite athlete, the method of reductionism, while it does allow us to identify certain differences between athletes, it does not allow us to appreciate the full-range of how and why elite athletes differ in their sport of choice. One large meta-analysis has been done on the effects of a few genotypes on elite athletic performance, and it shows us what we already know (blacks are more likely to have the genotype associated with power performance—so why are there no black Strongmen or any competitors in the World’s Strongest Man?). A few studies and one meta-analysis exist, attempting to get to the bottom of the genetics of elite athletic performance and, while it of course plays a factor, as I have argued in the past, we must take a systems view of the matter.
One 2013 study found that a functional polymorphism in the angiotensinogen (ATG) region was 2 to 3 times more common in elite power athletes than in (non-athlete) controls and elite endurance athletes (Zarebska et al, 2013). This sample tested was Polish, n = 223, 156 males, 67 females, and then they further broke down their athletic sample into tiers. They tested 100 power athletes (29 100-400 m runners; 22 powerlifters; 20 weightlifters; 14 throwers and 15 jumpers) and 123 endurance athletes (4 tri-athletes; 6 race walkers; 14 road cyclists; 6 15 to 50 m cross-country skiers; 12 marathon runners; 53 rowers; 17 3 to 10 km runners; and 11 800 to 1500 m swimmers).
Zarebska et al (2013) attempted to replicate previous associations found in other studies (Buxens et al, 2009) most notably the association with the M235T polymorphism in the AGT (angiotensinogen) gene. Zarebska et al’s (2013) main finding was that there was a higher representation of elite power athletes with the CC and C alleles of the M235T polymorphism compared with endurance athletes and controls, which suggests that the C allele of the M235T gene “may be associated with a predisposition to power-oriented
events” (Zarebska et al, 2013: 2901).
Elite power athletes were more likely to possess the CC genotype; 40 percent of power athletes had the genotype whereas 13 percent of endurance had it and 18 percent of non-athletes had it. So power athletes were more than three times as likely to have the CC genotype, compared to endurance athletes and twice as likely to have it compared to non-athletes. On the other hand, one copy of the C allele was found in 55 percent of the power athletes whereas, for the endurance athletes and non-athletes, the C allele was found in about 40 percent of individuals. (Further, in the elite anaerobic athlete, explosive power was consistently found to be a difference maker in predicting elite sporting performance; Lorenz et al, 2013.)
Now we come to the more interesting parts: ethnic differences in the M235T polymorphism. Zarebska et al (2013: 2901-2902) write:
The M235T allele distribution varies widely according to the subject’s ethnic origin: the T235 allele is by far the most frequent in Africans (;0.90) and in African-Americans (;0.80). It is also high in the Japanese population (0.65–0.75). The T235 (C4027) allele distribution of the control participants in our study was lower (0.40) but was similar to that reported among Spanish Caucasians (0.41), as were the sports specialties of both the power athletes (throwers, sprinters, and jumpers) and endurance athletes (marathon runners, 3- to 10-km runners, and road cyclists), thus mirroring the aforementioned studies.
Zarebska et al (2013: 2902) conclude that their study—along with the study they replicated—supports the hypothesis that the C allele of the M235T polymorphism in the AGT gene may confer a competitive advantage in power-oriented sports, which is partly mediated through ANGII production in the skeletal muscles. Mechanisms can explain the mediation of ANGII production in skeletal muscles, such as a direct skeletal muscle hypertrophic effect, along with the redistribution of between muscle blood flow between type I (slow twitch) and II fibers (fast twitch), which would then augment power and speed. However, it is interesting to note that Zarebska et al (2013) did not find any differences between “top-elite” level athletes who had won medals in international competitions compared to elite-level athletes who were not medalists.
The big deal about this gene is that the AGT gene is part of the renin-angiotensin system which is partly responsible for blood pressure and body salt regulation (Hall, 1991; Schweda, 2014). There seems to be an ethnic difference in this polymorphism, and, according to Zarebska et al (2013), African Americans and Africans are more likely to have the polymorphisms that are associated with elite power performance.
There is also a meta-analysis on genotyping and elite power athlete performance (Weyerstrab et al, 2017). Weyerstrab et al (2017) meta-analyzed 36 studies which attempted to find associations between genotype and athletic ability. One of the polymorphisms studied was the famous ACTN3. It has been noted that, when conditions are right (i.e., the right morphology), the combined effects of morphology along with the contractile properties of the individual muscle fibers contribute to the enhanced performance of those with the RR ACTN3 genotype (Broos et al, 2016), while Ma et al (2013) also lend credence to the idea that genetics influences sporting performance. This is, in fact, the most-replicated association in regard to elite sporting performance: we know the mechanism behind how muscle fibers contract; we know how the fibers contract and the morphology needed to maximize the effectiveness of said fast twitch fibers (type II fibers). (Blacks have a higher proportion of type II fibers [see Caeser and Henry, 2015 for a review].)
Weyerstrab et al (2017) meta-analyzed 35 articles, finding significant associations with genotype and elite power performance. They found that ten polymorphisms were significantly associated with power athlete states. Their most interesting findings, though, were on race. Weyerstrab et al (2017: 6) write:
Results of this meta-analysis show that US African American carriers of the ACE AG genotype (rs4363) were more than two times more likely to become a power athlete compared to carriers of the ACE preferential genotype for power athlete status (AA) in this population.
“Power athlete” does not necessarily have to mean “strength athlete” as in powerlifters or weightlifters (more on weightlifters below).
Lastly, the AGT M235T polymorphism, while associated with other power movements, was not associated with elite weightlifting performance (Ben-Zaken et al, 2018). As noted above, this polymorphism was observed in other power athletes, and since these movements are largely similar (short, explosive movements), one would rightly reason that this association should hold for weightlifters, too. However, this is not what we find.
Weightlifting, compared to other explosive, power sports, is different. The beginning of the lifts take explosive power, but during the ascent of the lift, the lifter moves the weight slower, which is due to biomechanics and a heavy load. Ben-Zaken et al (2018) studied 47 weightlifters (38 male, 9 female) and 86 controls. Every athlete that was studied competed in national and international meets on a regular basis. Thirty of the weightlifters were also classified as “elite”, which entails participating in and winning national and international competitions such as the Olympics and the European and World Championships).
Ben-Zaken et al (2018) did find that weightlifters had a higher prevalence of the AGT 235T polymorphism when compared to controls, though there was no difference in the prevalence of this polymorphism when elite and national-level competitors were compared, which “[suggests] that this polymorphism cannot determine or predict elite competitive weightlifting performance” (Ben-Zaken et al, 2018: 38). Of course, a favorable genetic profile is important for sporting success, though, despite the higher prevalence of AGT in weightlifters compared to controls, this could not explain the difference between national and elite-level competitors. Other polymorphisms could, of course, contribute to weightlifting success, variables “such as training experience, superior equipment and facilities, adequate nutrition, greater familial support, and motivational factors, are crucial for top-level sports development as well” (Ben-Zaken et al, 2018: 39).
I should also comment on Anatoly Karlin’s new article The (Physical) Strength of Nations. I don’t disagree with his main overall point; I only disagree that grip strength is a good measure of overall strength—even though it does follow the expected patterns. Racial differences in grip strength exist, as I have covered in the past. Furthermore, there are associations between muscle strength and longevity, with stronger men being more likely to live longer, fuller lives (Ruiz et al, 2008; Volkalis, Haille, and Meisinger, 2015; Garcia-Hermosa, et al, 2018) so, of course, strength training can only be seen as a net positive, especially in regard to living a longer and fuller life. Hand grip strength does have a high correlation with overall strength (Wind et al, 2010; Trosclair et al, 2011). While handgrip strength can tell you a whole lot about your overall health (Lee et al, 2016), of course, there is no better proxy than actually doing the lifts/exercises to ascertain one’s level of strength.
There are replicated genetic associations between explosive, powerful athletic performance, along with even the understanding of the causal mechanisms behind the polymorphisms and their carry-over to power sports. We know that if morphology is right and the individual has the RR ACTN3 genotype, that they will exceed in explosive sports. We know the causal pathways of ACTN3 and how it leads to differences in sprinting competitions. It should be worth noting that, while we do know a lot more about the genomics of sports than we did 20, even 10 years ago, current genetic testing has zero predictive power in regard to talent identification (Pitsladis et al, 2013).
So, of course, for parents and coaches who wonder about the athletic potential of their children and students, the best way to gauge whether or not they will excel in athletics is…to have them compete and compare them to other kids. Even if the genetics aspect of elite power performance is fully unlocked one day (which I doubt it will be), the best way to ascertain whether or not one will excel in a sport is to put them to the test and see what happens. We are in our infancy in understanding the genomics of sporting performance, but when we do understand which genotypes are more prevalent in regard to certain sports (and of course the interactions of the genotype with the environment and genes), then we can better understand how and why others are better in certain sports.
The genomics of elite sporting performance is very interesting; however, the answer that reductionists want to see will not appear: genes are difference makers (Sterelny and Griffith, 1999), not causes, and along with a whole slew of other environmental and mental factors (Lippi, Favaloro, and Guidi 2008), along with a favorable genetic profile with sufficient training (and everything else that comes along with it) are needed for the athlete to reach their maximum athletic potential (see Guth and Roth, 2013). Genetic and environmental differences between individuals and groups most definitely explain differences in elite sporting performance, though elucidating what causes what and the mechanisms that cause the studied trait in question will be tough.
Just because group A has gene or gene networks G and they compete in competition C does not mean that gene or gene networks G contribute in full—or in part—to sporting success. The correlations could be coincidental and non-functional in regard to the sport in question. Athletes should be studied in isolation, meaning just studying a specific athlete in a specific discipline to ascertain how, what, and why works for the specific athlete along with taking anthropomorphic measures, seeing how bad they want “it”, and other environmental factors such as nutrition and training. Looking at the body as a system will take us away from privileging one part over another—while we also do understand that they do play a role but not the role that reductionists believe.
These studies, while they attempt to show us how genetic factors cause differences at the elite level in power sports, they will not tell the whole story, because we must look at the whole system, not reduce it down to the sum of its parts (Shenk, 2011: chapter 5). While blacks are more likely to have these polymorphisms that are associated with elite power athlete performance, this does not obviously carry over to strongman and powerlifting competition.
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.
Nina Jablonski’s work on vitamin D and the implications that lighter skin had not only on our evolution but our health are extremely important for understanding how we evolved after the out of Africa migration. However, Jablonski then takes what she has written about skin color over the past few decades and concludes that race doesn’t exist. Jablonski believes that the term “race” should be discontinued from our lexicon, but as most may know, the term “race” does not need to disappear from our lexicon. (Watch her TED Talk Skin Color is an Illusion.)
In 2014, Nina Jablonski stated that the term “race” was ready for scientific retirement. In the article—and her book (Jablonski, 2012: chapters 9 and 10)—she states that race was a “vague and slippery concept”, eschewing the views of Kant and Hume as “racist”. She talks about how Kant was really one of the first people to recognize and categorize groups of people as “races”, stating that skin color, hair type, skull type etc—along with differing mores, aptitudes, and capacity for civilization—arranged in a hierarchical manner with Europeans at the top. A climatic theory was held, which stated that the original humans were light and became darker since “the transformation from light to dark was a form of degeneration, a departure from the norm” (Jablonski, 2012: 143).
She then discusses how, in Biblical history, skin color was meaningful, meaningful because it was believed that darker-skinned races were descendants of Ham:
And the sons of Noah, that went forth of the ark, were Shem, and Ham, and Japheth: and Ham is the father of Canaan. These are the three sons of Noah: and of them was the whole earth overspread. And Noah began to be an husbandman, and he planted a vineyard: And he drank of the wine, and was drunken; and he was uncovered within his tent. And Ham, the father of Canaan, saw the nakedness of his father, and told his two brethren without. And Shem and Japheth took a garment, and laid it upon both their shoulders, and went backward, and covered the nakedness of their father; and their faces were backward, and they saw not their father’s nakedness. And Noah awoke from his wine, and knew what his younger son had done unto him. And he said, Cursed be Canaan; a servant of servants shall he be unto his brethren. And he said, Blessed be the Lord God of Shem; and Canaan shall be his servant. (Genesis, 9: 18-26)
So Noah’s three sons—Ham, Japheth and Shem—were seen to be the three modern-day races of man—Africans, Europeans, and Asians, respectively. The term “servant of servants” was taken to mean that the descendants of Ham would serve the descendants of Shem and Japheth. This, according to those who believed the authority of the Bible, was enough to justify chattel slavery.
Jablonski—in an interview with the magazine Nautilus—stated that there “are no clean breaks between human populations. Individuals have different groups of genes” and that “Only a tiny fraction of alleles, and a small fraction of allelic combinations, is restricted to a single geographic region, and even less to a single population” which “is why attempts to identify races in humans have failed.” She commits the continuum fallacy, and the argument form is thus: “One extreme is X, at another is Y. There is no definable point where X becomes Y. Therefore, there is no difference between X and Y.” This has also been called the “Argument of the Beard”: at what point does a man not become clean shaven?
The use of the continuum fallacy, that there “are no clean breaks between human populations” shows how far the “race is a social construct” line has come (it is, but that race is a social construct does not also mean that it cannot also be a significant biological reality). The continuum fallacy is one of the most-used fallacies by those who deny race. Though, those who use the continuum fallacy are only attempting to argue that the claim is “too vague” because it is not as precise as they would like it to be. It does not matter that there “are no clean breaks between human populations“; what matters is that patterns of visible physical features correspond to geographic ancestry, and this is what we find.
Her second problem arises when she says that “Only a tiny fraction of alleles, and a small fraction od allelic combinations, is restricted to a single geographic region, and even less to s single population“. That there are no “race genes” or “genes for race” does not mean that race does not exist as a biological reality; these rigid “either this or that” definitions that some people have for race, such as race-specific genes are strawmen: people who believe that race is a significant biological reality do not believe in race-specific genes. That there are no race-specific genes does not mean that race doesn’t exist, as we know that genes are expressed differently in different races.
Finally, she claims that this “is why attempts to identify races in humans have failed“, though these attempts have not failed, of course. So-called races are distinguished by patterns of visible physical features; these patterns are observed between real, existing groups; these real existing groups that share these patterns of visible physical features satisfy the requisites of minimalist race; therefore race exists. Of course, Jablonski has reservations about acknowledging the reality of race due to how the transatlantic slave trade was promogulated through so-called differences that stemmed from Noah and Ham’s curse, but I fail to see why she would discard the argument just provided for the existence of race since differences in mores, intelligence, physical and mental abilities, are not discussed in the argument. ONLY the observable differences between populations are observed, with no value-judgment put onto each race, such as having lower “intelligence” or differing mores compared to another race.
She also states, in an interview with the New York Times, that skin color is not about race, “it’s about sun and how close our ancestors lived to the Equator. Skin color is what regulates our body’s reaction to the sun and its rays. … That shows that color is not a permanent trait.” That the differences in skin color observed in human populations can change over time does not mean that skin color “is not about race” as Jablonski claims. Skin color is one physical trait to delineate races, along with hair type, physiognomy, and anatomy, that groups peoples into groups we call “races”. This is not a good argument against the existence of race; of course anatomy, physiology, and physiognomy can change over time: but this does not mean that race does not exist!
Michael Hardimon’s race concepts (Hardimon, 2017) show that one does not need to believe that races differ in “intelligence”, mores, etc to believe in the existence of race. The concept takes everything from the racialist concept and “minimizes it”, taking the aspect of visible differences in physical features, while leaving the so-called mental differences (“intelligence”, mores) alone. This is enough to recognize that race exists and, as Jablonski has noted for decades in her career, being displaced from the environment where your skin color evolved causes an environmental mismatch which then—in the case of black Americans—may lead to vitamin D deficiency. This is one significant aspect that shows that race has an impact on health policy.
The minimalist concept of race is “deflationary” in that it does not discuss what we “can’t see” with our own eyes; it only discusses physical traits which should be enough for Jablonski to say that race is real and exists as a biological reality. Combined with the known health effects of, for instance, living in differing climates with differing amounts of UV radiation that is not “for” your skin color has further consequences and is why, in some cases, race-based medicine should stick around (though I am aware that, first and foremost, the individual matters first in a medical context, racial membership is secondary).
In sum, Jablonski refers to old and outdated individuals when speaking about the biological reality of race. She does a good job chronicling how and why the concept of race arose, especially through Biblical history and the curse of Ham. However, she takes it too far and claims that race does not exist, nor is it a significant biological reality since there are no “race-specific genes” (also remember that you do not need genes to delineate race, using differences in physical traits and then correlating them to geography is sufficient) and there “are no clean breaks between human populations“. These fallacies aside, it is possible, as I have noted before, to denote racial classifications sans the use of “intelligence” or “mores” in the concept. Skin color is just one of many observable traits that differ by geography that make the basis for separating groups on the basis of race.
The minimalist race concept from Hardimon is non-hierarchical: meaning that it doesn’t discuss anything that would put races in a hierarchy like the racialist concept does (with mores and “intelligence”). If anything, this strictly physical definition of races (and the simple argument for it) should be enough to sway race-deniers to become race-believers.
HBDers purport that as one moves further north from Africa that IQ raises as a function of how the population in question needed to survive. The explanation is that as our species migrated out of Africa, more “intelligence” was needed and this is what explains the current IQ disparities across the world: the ancestors of populations evolving in different areas with different demands then changed their “IQs” and this then is responsible for differential national development between nations. Cold winter theory (CWT) explains these disparities.
On the other hand is the vitamin D hypothesis (VDH). The VDH purports to explain why populations have light skin at northern latitudes. As the migration north out of Africa occurred, peoples needed to get progressively lighter in order to synthesize vitamin D. The observation here is that as light skin is selected for in locations where UVB is absent, seasonal or more variable whereas dark skin is selected for where UVB is stronger. So we have two hypotheses: but there is a problem. Only one of these hypotheses makes novel predictions. Predictions of novel predictions are what science truly is. A predicted fact is a novel fact for a hypothesis if it wasn’t used in the construction of the hypothesis (Musgrave, 1988). In this article, I will cover both the CWT and VDH, predictions of facts that each made (or didn’t make) and which can be called “science”.
Cold winter theory
The cold winter theory, formulated by Lynn and Rushton, purports to give an evolutionary explanation for differences in national IQs: certain populations evolved in areas with deathly cold winters in the north, while those who lived in tropical climes had, in comparison to those who evolved in the north, an “easier time to live”. Over time as populations adapted to their environments, differences in ‘intelligence’ (whatever that is) evolved due to the different demands of each environment, or so the HBDers say.
Put simply, the CWT states that IQ differences exist due to different evolutionary pressures. Since our species migrated into cold, novel environments, this was the selective pressure needed for higher levels of ‘intelligence’. On the other hand, humans who remained in Africa and other tropical locations did experience these novel, cold environments and so their ‘intelligence’ stayed at around the same level as it was 70,000 years ago. Many authors hold this theory, including Rushton (1997), Lynn (2006), Hart, (2007) Kanazawa (2008), Rushton and Templer (2012; see my thoughts on their hypothesis here) and Wade (2014). Lynn (2013) even spoke of a “widespreadonsensus” on the CWT, writing:
“There is widespread consensus on this thesis, e.g. Kanazawa (2008), Lynn (1991, 2006), and Templer and Arikawa (2006).”
So this “consensus” seems to be a group of his friends and his own publications. We can change this sentence to ““There is widespread consensus on this thesis, including two of my publications, a paper where the author assumes that the earth is flat: “First, Kanazawa’s (2008) computations of geographic distance used Pythagoras’ theorem and so the paper assumed that the earth is flat (Gelade, 2008).” (Wicherts et al, 2012) and another publication where the authors assume hot weather leads to lower intelligence. Oh yea, they’re all PF members. Weird.” That Lynn (2013) calls this “consensus” is a joke.
What caused higher levels of ‘intelligence’ in those that migrated out of Africa? Well, according to those who push the CWT, finding food and shelter. Kanazawa, Lynn, and Rushton all argue that finding food, making shelter and hunting animals were all harder in Eurasia than in Africa.
One explanation for high IQs of people who evolved recently in northern climes is their brain size. Lynn (2006: 139) cites data showing the average brain sizes of populations, along with the temperatures in that location:
Do note the anomaly with the Arctic peoples. To explain this away in an ad-hoc manner, Lynn (2006: 156-7) writes:
These severe winters would be expected to have acted as a strong selection for increased intelligence, but this evidently failed to occur because their IQ is only 91. The explanation for this must lie in the small numbers of the Arctic Peoples whose population at the end of the twentieth century was only approximately 56,000 as compared with approximately 1.4 billion East Asians.
This is completely ad-hoc. There is no independent verifier for the claim. That the Arcitic don’t have the highest IQs but experienced the harshest temperatures and therefore have the biggest brain size is a huge anomaly, which Lynn (2006) attempts to explain away by population size.
He does not explain why natural selection among Arctic peoples would result in larger brain sizes or enhanced visual memory yet the same evolutionary pressures associated with a cold environment would not also produce higher intelligence. Arctic peoples have clear physical adaptations to the cold, such as short, stocky bodies well-suited to conserving heat.
Furthermore, the argument that Lynn attempts is on the mutations/population size is special pleading—he is ignoring anomalies in his theory that don’t fit it. However, “evolution is not necessary for temperature and IQ to co-vary across geographic space” (Pesta and Poznanski, 2014).
If high ‘intelligence’ is supposedly an adaptation to cold temperatures, then what is the observation that disconfirms a byproduct hypothesis? On the other hand, if ‘intelligence’ is a byproduct, which observation would disconfirm an adaptationist hypothesis? No possible observation can confirm or disconfirm either hypothesis, therefore they are just-so stories. Since a byproduct explanation would explain the same phenomena since byproducts are also inherited, then just saying that ‘intelligence’ is a byproduct of, say, needing larger heads to dissipate heat (Lieberman, 2015). One can make any story they want to fit the data, but if there is no prediction of novel facts then how useful is the hypothesis if it explains the data it purports to explain and only the data it purports to explain?
It is indeed possible to argue that hotter climates need higher levels of intelligence than colder climates, which has been argued in the past (see Anderson, 1991; Graves, 2002; Sternberg, Grigorenko, and Kidd, 2005). Indeed, Sternberg, Grigorenko, and Kidd (2005: 50) write: “post hoc evolutionary arguments … can have the character of ad hoc “just so” stories designed to support, in retrospect, whatever point the author wishes to make about present-day people.” One can think up any “just-so” story to explain any data. But if the “just-so” story doesn’t make any risky predictions of novel facts, then it’s not science, but pseudoscience.
Vitamin D hypothesis
The VDH is simple: those populations that evolved in areas with seasonal, absent, or more variable levels of UVB have lighter skin than populations that evolved in areas with strong UVB levels year-round (Chaplan and Jablonksi, 2009: 458). Robins (2009) is a huge critic of the VDH, though her objections to the VDH have been answered (and will be discussed below).
The VDH is similar to the CWT in that it postulates that the adaptations in question only arose due to migrations out of our ancestral lands. We can see a very strong relationship between high UVB rays and dark skin and conversely with low UVB rays and light skin. Like with the CWT, the VDH has an anomaly and, coincidentally, the anomaly has to do with the same population involved in the CWT anomaly.
Arctic people have dark-ish skin for living in the climate that they do. But since they live in very cold climates then we have a strange anomaly here that needs explaining. We only need to look at the environment around them. They are surrounded by ice. Ice reflects UVB rays. UVB rays hit the skin. Arctic people consume a diet high in vitamin D (from fish). Therefore what explains Arctic skin color is UVB rays bouncing off the ice along with their high vitamin D diet. The sun’s rays are, actually, more dangerous in the snow than on the beach, with UVB rays being 2.5 more times dangerous in the snow than beach.
Evolution in different geographic locations over tens of thousands of years caused skin color differences. Thus, we can expect that, if peoples are out of the conditions where their ancestors evolved their skin color, that there would then be expected complications. For example, if human skin pigmentation is an adaptation to UV rays (Jablonski and Chaplan, 2010), we should expect that, when populations are removed from their ancestral lands and are in new locations with differing levels of UV rays, that there would be a subsequent uptick in diseases caused by vitamin D deficiencies.
This is what we find. We find significant differences in circulating serum vitamin D levels, and these circulating serum vitamin D levels then predict health outcomes in certain populations. This would only be true if sunlight influenced vitamin D production and that skin progressively gets lighter as one moves away from Africa and other tropical locations.
Skin pigmentation regulates vitamin D production (Neer, 1975). This is due to the fact that when UVB rays strike the skin, we synthesize vitamin D, and the lighter one’s skin is, the more vitamin D can be synthesized in areas with fewer UVB rays. (Also see Daraghmeh et al, 2016 for more evidence for the vitamin D hypothesis.)
P1) UV rays generate vitamin D in human skin
P2) Human populations that migrate to climates with less sunlight get fewer UV rays
P3) To produce more vitamin D, the skin needs to get progressively lighter
C) Therefore, what explains human skin variation is climate and UV rays linked to vitamin D production in the skin.
Science is the generation of novel facts from risky predictions (Musgrave, 1988; Winther, 2009). And so, hypotheses that predict novel facts from risky predictions are scientific hypotheses, whereas those hypotheses that need to continuously backtrack and think up ad-hoc hypotheses are then pseudoscientific. Pseudoscience is simple enough to define. The Stanford Encyclopedia of Philosophy defines it as:
“A pretended or spurious science; a collection of related beliefs about the world mistakenly regarded as being based on scientific method or as having the status that scientific truths now have.”
All theories have a protective belt of ad hoc hypotheses. Theories become pseudoscientific when they fail to make new predictions and must take on more and more ad-hoc hypotheses that have no predictive value. If the ad-hoc hypotheses that are added to the main hypothesis have no predictive value then the new explanations for whichever hypothesis that is in danger of being falsified are just used to save the hypothesis from being refuted and it thus becomes pseudoscience.
In the case of CWT, it makes no prediction of novel facts; it only explains the data that it purports to explain. What is so great about the CWT if it makes no predictions of novel facts and only explains what it purports to explain? One may attempt to argue that it has made some ‘novel’ predictions but the ‘predictions’ that are proposed are not risky at all.
For example, Hart (2007: 417) makes a few “predictions”, but whether or not they’re “risky” or “novel” I’ll let you decide (I think they’re neither, of course). He writes that very few accomplishments will be made by Africans, or Australian or New Guinean Aborigines; members of those groups will not be highly represented in chess; and that major advances in scientific fields will come from those of European ancestry or the “Monglids”, Koreans, Chinese or Japanese.
On the other hand, Hart (2007: 417) makes two more “predictions”: he says that IQ data for Congoid Pygmies, Andaman Islanders, and Bantu-speaking people are few and far between and he believes that when enough IQ testing is undertaken there he expects IQ values between 60 and 85. Conversely, for the Lapps, Siberians, Eskimoes, Mongols and Tibetans, he predicts that IQ values should be between 85-105. He then states that if these “predictions” turn out to be wrong then he would have to admit that his hypothesis is wrong. But the thing is, he chose “predictions” that he knew would come to pass and therefore these are not novel, risky predictions but are predictions that Hart (2007) knows would come to pass.
What novel predictions has the VDH made? This is very simple. The convergent evolution of light skin was predicted in all hominids that trekked out of Africa and into colder lands. This occurred “because of the importance of maintaining the potential for producing pre-vitamin D3 in the skin under conditions of low annual UVB (Jablonski and Chaplin, 2000; Jablonski, 2004)” while these predictions “have been borne out by recent genetic studies, which have demonstrated that depigmented skin evolved independently by different molecular mechanisms multiple times in the history of the human lineage” (Chaplan and Jablonksi, 2009: 452). This was successfully predicted by Chaplan and Jablonski (2000).
The VDH still holds explanatory scope and predictive success; no other agent other than vitamin D can explain the observation that light skin is selected for in areas where there is low, absent or seasonal UVB. Conversely, in areas where there is a strong, year-round presence of UVB rays, dark skin is selected for.
Scientific hypotheses predict novel facts not known before the formulation of the hypothesis. The VDT has successfully predicted novel facts, whereas I am at a loss thinking of a novel fact that the CWT predicted.
In order to push an adaptationist hypothesis for CWT and ‘intelligence’, one must propose an observation that would confirm the adaptationist hypothesis while at the same time disconfirming the byproduct hypothesis. Since byproducts are inherited to, the byproduct hypothesis would predict the same things that an adaptationist hypothesis would. Thus, the CWT is a just-so story since no observation would confirm or disconfirm either hypothesis. On the other hand, the CWT doesn’t make predictions of novel facts, it makes “predictions” that are already known and would not undermine the hypothesis if disproved (but there would always be a proponent of the CWT waiting in the wings to propose an ad-hoc hypothesis in order to save the CWT, but I have already established that it isn’t science).
On the other hand, the VDT has successfully predicted that hominins that trekked out of Africa would have light skin which was then subsequently confirmed by genomic evidence. The fact that strong UVB rays year-round predict dark skin whereas seasonal, absent, or low levels of UVB predict light skin has been proved to be true. With the advent of genomic testing, it has been shown that hominids that migrated out of Africa did indeed have lighter skin. This is independent verification for the VDH; the VDH has predicted a novel fact whereas the CWT has not.
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.