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Blacks have higher BP on average than whites. Why? One popular explanation is the Slavery Hypertension Hypothesis (SHH). The SHH is a hypothesis which posits 2 things: (1) that those living in the African climate were subject to limited water and salt, and dehydration so, a higher sodium-retention mechanism evolved in those populations to retain salt, which also leads to hypertension; and (2) during the Middle Passage there were high amounts of vomiting, diarrhea, heat, and little salt and so surviving slaves were “selected for” salt conserving water and salt. Then, when they reached the plantations, due to low water, copious sweating, and intense work, there were additional selective pressures which “selected for” water and salt conservation.
This hypothesis is so popular, that it was even pushed by Oprah, when Dr. Mehmet Oz asked Oprah why blacks have higher BP than whites. Lujan and DiCarlo (2018) write:
During a May 2007 Oprah show, Dr. Mehmet Oz asked Oprah, “Do you know why African-Americans have high blood pressure?” Oprah promptly replied that Africans who survived the slave trade’s Middle Passage “were those who could hold more salt in their bodies.” To which Dr. Oz exclaimed, “That’s perfect!” (64, 71). According to Dr. Oz and Oprah, African-Americans today are afflicted by hypertension at higher rate than whites because of genes passed on by their ancestors, genes that favored salt retention and that, in turn, cause high blood pressure (Fig. 1) (71). [They are implying that genetic ancestry is associated with BP; see below.]
Lujan and DiCarlo (2018) state that when individuals were “salt-loaded”, normal salt-resistant individuals retained just as much sodium in their bodies as salt-sensitive individuals. Salt-resistant individuals retain as much salt as salt-sensitive individuals—but they did not develop hypertension.
Furthermore, available evidence suggests that the difference in salt-sensitivity between African-Americans and Caucasians (European-Americans) is significantly smaller than what the Slavery Hypertension Hypothesis suggests. In fact, Chrysant and colleagues (14) were unable to find differences in the blood pressure response to salt by race, age, sex, or body weight. Thus salt sensitivity is not a racial problem, but rather a human problem, and the generalization that blacks are salt sensitive and whites are not should be discarded (14). It is important to note that measurements of salt retention in humans have come into serious question (50).
The hypothesis, as explained above, explains the data it purports to explain and only the data it purports to explain and is, therefore, a just-so story. Using the definition from Sterelny and Griffiths (1999: 61), a just-so story is “an adaptive scenario, a hypothesis about what a trait’s selective history might have been and hence what its function may be.”
So, the just-so story goes, that Africans in Africa—and those who survived the Middle Passage—had genes which favored better salt retention, and so, they were “selected for” which lead to an increased chance of survival in the low-salt, low-water, high-heat environment. The hypothesis is clearly ad hoc – notice that African-descended people have higher rates of blood pressure and then work backward. What in their recent or past history, could have lead to these high rates of hypertension in today’s societies.
This method is the usual EP reverse engineering method—strongly criticized by philosophers of science Robert Richardson (2007) and David Buller (2005)—which is “the inference from function to cause” (Richardson, 2007: 51). The just-so storytellers then work backward from a data point and “reason” how the trait became fixated in a particular population. So the formulators of the SHH wanted to infer function from cause—what the function of higher African BP was.
So the just-so story in question was formulated, which leads to genetic essentialist and determinist views—that genes are “causing” and were “selected for”—to explain the data they wanted to explain. But it makes no testable predictions, so it’s a just-so story. The hypothesis is inherently ad hoc—the “justification” for the hypothesis was reasoned backward from a fact we know today—that blacks have higher BP—and the “speculation” was provided as if it were true—which has permeated into the media, as can be seen above.
There are more sensible explanations for differences in hypertension between blacks and whites (I use those terms since they are socialraces). Genetic determinists would always go to the genes as an explanation for differences in any trait X. However, there is no reason to posit genetic differences between population groups as evidence for the differences in the causes of the trait in question. There are more sensible explanations for the BP disparity between blacks and whites.
Williams (1992) cites social factors as much more important than genetic factors in the etiology of hypertension – stress, social support, coping patterns, health behavior, sodium, calcium, and potassium consumption, alcohol consumption, and obesity. Citing these environmental factors that raise BP is critical—the human body’s physiology is adaptive and so, it can adapt to differing environments based on the reactions of the individual in that environment. This, of course, holds for nutrition as well. Nutrition most definitely affects BP – nutrition also affects rates of obesity (obviously). Blacks are more likely to be lower SES. Since blacks are more likely to be lower SES, they have higher rates of obesity which lead to higher rates of BP, too.
But one of the most important factors here is education. If people don’t know something, then they won’t do it. If they are taught ways to reduce symptom X, there is a higher chance of them reducing symptom X because they are better-armed with the knowledge against it. Knowing that all of these different environmental factors influence BP, then this points to a main culprit: education. Non, Gravlee, and Mulligan (2012) argue that it’s not ancestry that explains hypertension, but differences in education.
Non, Gravlee, and Mulligan (2012) analyzed both environmental and genetic factors which lead to hypertension. Thy found that in the black sample, systolic BP and mean arterial pressure (MAP) were higher among those who had a HS diploma or lower, but found no differences by education in the white sample.
So black men were predicted to have a higher SBP, then white men, black women and finally white women, across all levels of education. SBP declined most sharply in black men and women compared to white men and women.
Genetic ancestry was not associated with BP among black Americans, but there was a significant association between education and BP. Education is, of course, not too good a measure of the social environment. Even using this measure, significant reductions in BP were found. Genetic ancestry is supposed to be associated BP in virtue of the ancestral environment of black Americans, along with supposed selection pressures which occurred on the Middle Passage. So if genetic ancestry isn’t associated, then the hypothesis is discarded.
Non, Gravlee, and Mulligan’s (2012) results support the “minority poverty hypothesis” because “the worst blood pressures were predicted for people who faced the double burden of being less educated and identifying as African American.” The minority poverty hypothesis is “The idea is that black people who live in poverty are uniquely disadvantaged in attaining good health because of the combination of poverty and race” (Hall, Humphreys, and Ruseski, 2015: 5).
Because genetic ancestry was estimated from only 294 loci, and a large set of populations across Africa, which may not be best for representing the West African ancestry of black Americans (Note how this is the population in question in the theory we are discussing). So an analysis focusing just on West African populations may change the relationship. Education was their only measure of the social environment, but other measures of the social environment, like “residential segregation, psychosocial stress, and everyday discrimination” may fully account for higher levels of BP in black Americans. Of course, further there needs to be further study to see whether it is the education per se that causes the differences in BP or if education serves only as a marker for other aspects of the social environment.
The evidence that education accounts for a lot of the variation in differences in BP between blacks and whites is strong. If it is other aspects of the social environment, and not education per se, then there is something in that environment that does not elicit the physiological response that leads to higher BP. We can also, of course, liken this to the Mazur’s (2016) honor culture hypothesis—the hypothesis “that young men’s participation in the honor culture of poor black neighborhoods has the effect of elevating T.” This is due to the adaptiveness of our physiological systems and how it adapts to the environment based on environmental cues.
There was one recent study where they found that “Among black male barbershop patrons with uncontrolled hypertension, health promotion by barbers resulted in larger blood-pressure reduction when coupled with medication management in barbershops by specialty-trained pharmacists” (Victor et al, 2018). This, of course, makes sense. If one is made aware of anything wrong with them, then they will be more likely to seek help for their ailments.
Victor et al (2018) write:
Because black men with hypertension often have multiple cardiovascular risk factors,37 marked reductions in blood pressure — if sustained with the use of our approach and then initiated more widely — might reduce the high rates of hypertension-related disability and death among black men with hypertension in the United States.11
Since three out of four black men have high blood pressure by the time they are 55, then if this can and does hold for the long-term, then this would help many individuals.
Seventy-eight barber shops enrolled in the program. The n was 319 men who had a SBP of 140 mm or higher from 52 black-owned barber shops. The intervention increased doctor visits and anti-hypertensive medications (which I disagree with). Pharmacists were placed in the shop and checked the BP of black men who entered (barbers were also trained to measure BP). Reductions of 21.6 and 14.9 SBP and DBP respectively were seen. 63 percent of those who participated achieved a normal BP whereas 12 percent of those in the control group did so. This, clearly, is another way in which education can lower BP in this population.
This is a great idea—and if further study confirms that this works, it should begin to be implemented elsewhere. The most important factor is outreach—getting the information to people and teaching them how to reduce it on their own through lifestyle modifications. And since outreach is related to educating people on a certain topic, then this, too, falls under the—somewhat large—umbrella of “education.”
In sum, the SHH is a just-so story and doesn’t explain why blacks have higher rates of BP than whites. Genetic ancestry seems to not explain hypertension rates between blacks and whites. Social environment changes and outreach can lower BP disparities between populations. If one understands the intricacies of physiology, then they would understand the physiological responses to different environmental/social stimuli.
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.
To be a realist about race is to hold that racial categories pick out real kinds in nature. (Smith, 2015: 43; Nature, Human Nature, and Human Difference Race in Early Modern Philosophy)
Claims from biological racial realists are simple: Racial categories pick out real kinds in nature. If racial categories pick out real kinds in nature, then race surely exists.
Racial groups—or groups taken to be racial groups—characterize three conditions from Hardimon (2017): C1: they are distinguished from other groups by patterns of visible physical features; C2: the members are linked by common ancestry which is peculiar to that group; and C3: they derive from a distinct geographic location.
Justifying C1 is simple: groups taken to be ‘racial’ are distinguished from other groups on the basis of physical characters. Someone from Europe looks different than someone from Africa; someone from Africa looks different than someone from Asia; someone from Asia looks different than someone from the Pacific Islands; someone from the Pacific Islands looks different than the Natives of America. Groups taken to be ‘racial’ have different facial features; they have different morphology. Thus, since there are heritable differences between groups taken to be ‘racial’, then this is evidence that race does indeed exist.
It’s important to also discuss what C1 does not demand: it does not demand that racial groups be distinguished by each of their visible physical features; it does not demand that each visible physical features of members of a race be identical; it allows skin color to vary just as much within race as it does between race; finally, it also allows great variation in hair color, skull morphology and skin color. Thus, since Hardimon’s concept is ‘vague’, then one might be able to say that it is “clinal” (that is, these differences vary by geography). But “Physical anthropologist Frank Livingstone’s well-known adage “There are no races, only clines” overlooks the possibility that, logically speaking, races might be clines” (Hardimon, 2017: 38). The claim “There are no races, only clines” is one that is oft-repeated against the reality of biological races.
C2, very simply, shows that differences in visible physical features are not the only things that delineate race: race is also defined in terms of ancestry and is therefore essential to the concept of race (I’d argue that ancestry is essential to any argument that attempts to establish races as biologically real). Races are, clearly, morphologically demarcated ancestry groups. The justification for C2 is thus: it is intuitive. Examples of race articulated in the past also bore this very basic concept: Linneus’ europeaus, asiaticus, afer, and americanus; Blumenbach’s Mongoloid, Caucasoid, Ethiopian, Malay and American; UNESCO’s Negroid, Mongoloid, and Caucasoid (deployed most famously by JP Rushton); and the Office of Management and Budget’s American Indian (or Alaskan native), black, Asian, whites, native Hawaiians (Pacific Islanders) (see Spencer, 2014 for a treatment of the OMB’s views on race and his ‘radical solution to the race problem’).
Now, finally, C3: the condition that groups taken to be ‘racial’ must derive from a distinct geographic location. Race, and the names used to refer to race, and so “The use of typonyms in the naming of racial groups suggests that the thinkers who chose these names were thinking of race as a geographical grouping” (Hardimon, 2017: 50). So, C1 and C2 have been established. This leaves us with C3. Races differ in patterns of visible physical features; these differences are explained by differences in geographic location. If race R1 derives from geographic location G1, and G1 is distinct from G2 which race R2 inhabits, then races R1 and R2 will look physically different.
Thus the groups that we think of when we think about race are groups that genetically transmit heritable characters to their offspring which then correspond to differences in geographic ancestry. So groups that satisfy C1-C3 are ‘races’, in the normal sense of the word. Groups that satisfy C1-C3 are articulated in Hardimon’s (2017) populationist race concept using Rosenberg et al’s (2002) data, and these are, largely, the same groups that Blumenbach pointed out centuries ago (Spencer, 2014).
The Visible Physical Features of Minimalist Race Are Racial
The visible physical features of minimalist race that correspond to geographical ancestry count as “racial” because they are defining features of minimalist races. They no more need to be correlated with normatively important features to be properly counted as racial then minimalist races need to be characterized by normatively important features to be properly counted as races. Just as the concept of minimalist race deflates the concept of RACE, so too it deflates the concept of RACIAL. Visible physical features that correspond to geographical ancestry are eo ipso racial. (Hardimon, 2017: 52)
Hardimon (2017: 99) also articulates one of the best definitions of race I have come across:
A race is a subdivision of Homo sapiens—a group of populations that exhibits a distinctive pattern of genetically transmitted phenotypic characters that corresponds to the group’s geographic ancestry and belongs to a biological line of descent initiated by a geographically separated and reproductively isolated founding population.
Since Hardimon’s views are new (published in 2017), there are no replies to his argument—excpet one, by Spencer (2018). Spencer doesn’t take to two of Hardimon’s claims: that (1) that the minimalist concept of race is the ordinary concept of race and (2) that minimalist races are biologically real. He grants (1) until Hardimon provides evidence that the minimalist concept of race is the ordinary concept of race. (2), on the other hand, Spencer attacks.
His objection to (2) comes down to the simple fact that 13/17 of the different conceptions of racial groups discussed by Linnaeus, Blumenbach, the OMB, and UNESCO do not fit C1-C3 (Blumenbach’s races do fit C1-C3). Spencer (2018) states that “there’s no ancestor that Eurasians share that’s not also shared by East Asians, Oceanians, and Native Americans […] there’s no ancestor that East Asians share that’s not also shared by Oceanians and Native Americans.” (See Duda and Zrzavy, 2016.) We need to be clear on what Hardimon means by “ancestry.” The dictionary definition of “ancestry” is thus: “one’s family or ethnic descent.” On this definition of “ancestry”, groups taken to be races do have “distinct ancestry“, so defined, and so, Hardimon’s (2017) C2 does indeed hold.
Biological racial realism “should” mean “race is a geniuine kind in biology.” Take the argument from Spencer (2011: 24):
(1) The meaning of ‘biological racial realism’ in the race debate should be a metaphysically minimal interpretation of important scientific kindhood that also does the most justice to what counts as an important scientific kind.
(2) A “metaphysically minimal” interpretation of important scientific kindhood is one that does not adopt unnecessary and contentious metaphysical assumptions.
(3) The interpretation of important scientific kindhood that does the most justice to what counts as an important scientific kind is the one that best captures epistemically important scientific kinds—or ‘EIS kinds’ for short.
(4) The candidates for important scientific kindhood in the race debate are natural kinds, naturali kinds, naturalu kinds, naturalp kinds, realp biological kinds, reali biological kinds, and geniuine kinds.
(5) No kind of kind in the race debate is both metaphysically minimal and does a better job of capturing EIS kindhood than genuine kinds.
(6) Therefore, the meaning of ‘biological racial realism’ in the race debate should be ‘race is a genuine kind in biology’.
Spencer has good critiques of Hardimon’s minimalist/populationist race view, but it does not hold.
Even if we allow Spencer’s views on Hardimon’s arguments for the existence of race to hold, Spencer himself has articulated a sound argument for the existence of race. In his 2014 paper A Radical Solution to the Race Problem, Spencer (2014) shows that Americans defer to the US Census on matters of race; the US Census defers to the OMB; the OMB refers to “sets of” populations—blacks, whites, Asians, Native Americans and Pacific Islanders; these “sets of” populations are not kinds (like what Hardimon argues his racial classifications are); therefore, races are not ‘kinds’, the term ‘race’ refers to sets of population groups. Thus, according to Spencer (2014), race refers to “proper names” for population groups, not “kinds”.
Both of Hardimon’s and Spencer’s arguments show that race is a biological reality; they both show that biological racial realism is true. Their concepts pick out real kinds in nature (Smith, 2016: 43).
Philosopher Justin Smith, in his book 2015 book Nature, Human Nature, and Human Difference Race in Early Modern Philosophy articulates a Hardimonian argument for the existence our habits of distinguishing between human populations:
Now if scientific taxonomy builds on folk taxonomy, and if racial classification builds on this in turn, there might be some basis for supposing that something about the modern habit of distinguishing between human groups on racial grounds is more deep-seated than we have acknowledged it to be. (Smith, 2015: 47)
The reason why there “might be some basis for supposing that something about the modern habit [which is not truly modern; Sarich and Miele, 2004; which I am sure that Smith knows due to the content of his book] of distinguishing between human groups on racial grounds is more deep-seated” than we have acknowledged because we are picking out real kinds that exist in nature.
Race, as a concept, is biologically real. Racial categories pick out real kinds in nature, as argued by Spencer (2014) and Hardimon (2017). Criticisms on Hardimon from Spencer or Spencer from Hardimon do not take away from this one fact: that race exists and is biologically real. Groups taken to be ‘racial’ look different from each other; they look different from each other due to their geographic locations and their ancestry (C1-C3). Since this is true, then race exists. We can argue this view simply:
P1. If groups of people look different from each other depending on where their ancestors evolved, then race exists.
P2. Groups of people look different from each other depending on where their ancestors evolved.
C. Therefore, race exists since people look different depending on where their ancestors evolved (modus ponens, P1, P2).
Biological racial realism is true.
Like abortion, preimplantation genetic diagnosis (PGD) is feared. This is due, in part, to fears of eugenics coming back through a “backdoor” with the advent of new technology such as CRISPR/CAS9 and other types of tools we can use to genetically modify ourselves. The case of PGD—just like abortion—has been heavily debated in recent times, more so due to the recent strides in genomics we have made since the advent of the Human Genome Project.
PGD offers us a method to identify embryos with genetic diseases. Understandably, this has raised caution with some, due to the strong link with eugenic thinking/policies. See The Ethical Implications of Preimplantation Genetic Diagnosis. Thus, by scanning the genomes of fetuses, we can then see if they have a higher chance of acquiring any disease and select fetuses which have a lower to nonexistent chance of acquiring said disease.
An argument against PGD
In his paper Just diagnosis? Preimplantation genetic diagnosis and injustices to disabled people, Peterson (2005) presents one slippery slope argument against PGD (Freeman, 1996) (and later provides a refutation). The argument that Peterson (2005) presents is a “slippery slope” argument—that is, it’s an argument which argues that if we allow X, then since we allowed X, then horrible thing Y can and will follow. Peterson (2005) articulates the argument thus:
As situation A (the use of PGD to select against severe genetic diseases) is refined, “it will be difficult, if not impossible, to contain the uses of such research”. A will therefore bring about situation B, where PGD will be used to select against mild or perhaps non-medical conditions.
Besides the refinement of A, B will be brought about because “There will likely be an increasing pressure … on people to take advantage of these techniques, and not bring even a mildly disabled child into the world …”.
Finally, we could reach a morally abhorrent outcome Z, which is disturbingly close to eugenics, where our notion of the moral equality of all human beings, including those with disabilities, is undermined.
Z is so morally bad, that it outweighs the benefits of undertaking A.
Therefore, A should not be undertaken.
This argument, in my view, seems to be appealing to emotion by saying that since we can reach morally abhorrent outcome Z (a type of eugenics), then we should not continue with this practice. However, others argue that this discriminates against people with disabilities (see Katthab, 2009). Peterson (2005) argues that Freeman’s (1996) argument “lacks empirical support” and so it makes the conclusion difficult to assess; technology can and will be regulated which would quell any fears of possible use of this technology for any eugenic ideals; and, through using PGD, we can use it to “fight the obvious causes of discrimination, such as intolerance and egoism“, which would, in turn, reduce discrimination. Lastly, addressing Freeman’s (1996) concerns that PGD would lead to the discrimination of currently disabled persons, Peterson (2005) claims that “even if we accept that PGD will generate discrimination against disabled people, it is far from obvious that this is sufficient to warrant its moral condemnation.” Thus, Peterson (2005) concludes that Freeman’s (1996) argument is not sufficient to end the use of PGD technology. (Also see Robertson, 2003 for the view that “except for sex selection of the first child, most current extensions of PGD are ethically acceptable“.)
Many arguments against PGD rely on the concept of a fetus as a person and terminating any fetus with any prospective disease is paramount to killing a person. Others, of course, hinge on the fact that PGD does help reduce the risk of a babe being born with deleterious diseases, it does not completely ameliorate any generic risk for disease and so the fetus must be monitored through conception up until pregnancy to be sure that no disease appears during conception. And, of course, certain diseases that may hamper one’s quality of life may not appear until one reaches adolescence, adulthood, middle or old age. This is another fact against PGD: that even selecting embryos that apparently have no risk for disease, they may acquire diseases in older age which would not be seen since some diseases only generate symptoms at certain stages of life.
One final objection to PGD is also moral: it could, and will, send a message to any individuals currently alive that their lives are somehow “less” than others, since individuals with a chance to acquire said disease are selected against, as McConachy (2010) argues.
Lastly, Richardson (2017: 155-157) argues that the selection of embryos with so-called “potential” is ill-founded since they talk about vague concepts such as “egg quality”. Differences in potential lie, supposedly, in the “genetic blueprint” (see my article DNA Is not a Blueprint for arguments against that notion), though “That view implies that differences in individuals in important functions are largely due to differences in genes. As we have seen, though, things are far from being so simple” (Richardson, 2017: 156).
An argument for PGD
PGD can be used for many things; most importantly, screening the genome of a perspective fetus before IVF. Though, this has led some to worry that this could be a way in which eugenics can “sneak in through the backdoor” by virtue of making people with diseases more likely to be discriminated against since “disabled phenotypes” would slowly be phased out by PGD. One argument for could be:
Parents have rights; if parents have rights, then they have the right to do what they want with their children, and they want to do what is best for their children; therefore a parent should have the right to use PGD to select the best-possible embryo for implantation.
This is where we think of the implications of aborting a fetus, or not implanting a fetus that has a higher chance of acquiring any disease. There are, of course, certain people who would willingly select embryos which have a high chance to be disabled, because they themselves are disabled or they believe they “should be” disabled themselves and so want disabled children. Since parents have rights, as can be seen in the reasoning chain above, then parents should be able to choose the status of their babe. But if the babe’s quality of life is low, then is it ethical for that person to select an embryo with a high chance of acquiring a disease?
Another argument “for” PGD can be:
Humans should not suffer; if we can prevent human suffering with our current technology, then we have a moral imperative to do whatever is in our power to do so; if we can prevent low qualities of life for any embryo E, then we should do so; therefore, we should screen embryos for diseases that can and will lower their qualities of life and select against these embryos.
One may argue that a fetus may not have a “moral right” to life (see Tooley, 1972), though, if we know that a fetus has a high chance to have such a debilitating disease such that it lowers its quality of life, then it should be aborted/not implanted in the womb. Religious views, of course, come into play here but I am not worried about them; I am worried only about sound arguments for them. (See Fasoulioutis and Schenker, 1997 for these views.)
PGD may, of course, prevent abortions of said fetus since we know that the fetus in question may have a higher chance of acquiring a certain disease, so if one is against abortion, then they may be for the use of PGD to screen the fetuses’ genome to scan for any readily apparent problems in their genome in regard to the acquiring of certain genetic diseases.
Arguments for PGD hinge on parents wanting the best possible lives for the children they conceive and the arguments really rely on parental autonomy, the parent’s want to choose how their kid is born, if their chance for disease is high or not (which also would turn to “designer babies”; an argument against “designer babies” will be erected soon. If parents can do what’s best for an unborn child then, most would argue they have a moral imperative to give the babe the best possible life and so they should abort/select against certain embryos which have a high chance of acquiring diseases.
There do not seem to be as many strong arguments against PGD compared to abortion. Though one can use the basic blueprint of the argument against abortion and liken it to PGD. The PGD debate is similar to the abortion debate. One can use similar arguments against abortion to argue against PGD.
These debates are both ethical scientific: we have the ability to now do X which would stop suffering Y in embryo E. Just because we can do something, does that mean we should do so? Like with the editing of the germline, we don’t know what types of consequences would occur since we have, pretty much, no experience in editing the germline/genes of humans in a large-scale way.
Abortion is a touchy subject for many people. There are many different arguments for and against abortion, including, but not limited to, the woman’s right to do what she wants with her body on the pro-abortion side, to the right of a fetus to live a good life if there is little chance of the fetus developing a serious disease. In this article, I will provide two arguments: one for and one against abortion. The abortion debate is an ethical, not scientific, one, and so, we must use argumentation to see the best way to move forward in this debate.
An argument for abortion
Michael Tooley, in his paper Abortion and Infanticide, provides an argument not only for the abortion of fetuses, but the killing of infants and animals since they cannot conceive of continuing their selves. He argues that an organism only has a right o life of they can conceive of that right to life. His conclusion is that it should be morally permissible to end a baby’s life shortly after birth since it cannot conceive of wanting to live. The conclusion of the argument also includes—quite controversially, in fact—young infants and (nonhuman) animals. Ben Saunders articulates Tooley’s argument in Just the Arguments: 100 of the Most Important Arguments in Western Philosophy (2011: 284-286):
P1. If A has a morally serious right to X, then A must be able to want X.
P2. If A is able to want X, then A must be able to conceive if X.
C1. If A has a morally serious right to X, then A must be able to conceive of X (hypothetical syllogism, P1, P2).
P3. Fetuses, young infants, and animals cannot conceive of their continuing as subjects of mental states.
C2. Fetuses, young infants, and animals cannot want their continuance as subjects of mental states (modus tollens, P2, P3).
C3. Fetuses, young infants, and animals do not have morally serious rights to continue as subjects of mental states (modus tollens, P1, C2).
P4. If something does not have a morally serious right to life, then it is not morally wrong to kill it painlessly.
C4. It is not wrong to kill fetuses, young infants, or animals painlessly (modus ponens, C3, P4).
Of course, most people would seriously disagree with C4, since a babe’s life is one of the most precious things in the world— the protection of said babes is how we continue our species. However, the argument is deductively valid, and so one must show which premise is wrong and why. This argument—along with the one that will be presented below against abortion (of healthy fetuses)—is very strong. Thus, if a woman so pleases (along with her autonomy), she can choose to abort her fetus since it is not wrong to kill a fetus painlessly. (I am not aware if fetuses can feel pain or not, however. If they can, then the conclusion of this argument does not hold.)
Tooley’s argument regarding the killing of infants is similar to an argument made by Gibiulini and Minerva (2013) who argue that since fetuses and newborns don’t have the same moral status as actual persons, fetuses and infants can eventually become persons, and since adoption is not always in the best interests 9f people, then “‘after-birth abortion’ (killing a newborn) should be permissible in all the cases where abortion is, including cases where the newborn is not disabled” (Giubilini and Minerva, 2013).
An argument against abortion
One strong argument against abortion exists: Marquis’ (1989) argument in his paper Why Abortion Is Immoral. Women may want an abortion for many reasons: such as not wanting to carry a babe to term, to finding out that the babe has a serious genetic disorder. Though, what matters to this argument is not the latter, but the former: the mother wanting an abortion of a healthy fetus. Marquis’ argument is simple: killing is wrong; killing is wrong since killing ends one’s life, and ending one’s life means they won’t experience anything anymore, they won’t be happy anymore, they won’t be able to accomplish things, and this is one of the greatest losses that can be suffered; abortions of a healthy fetus cause the loss of experiences, activities, and enjoyment to the fetus; thus, the abortion of a healthy fetus is not only ethically wrong, but seriously wrong. Marquis’ (1989) argument is put succinctly by Leslie Burkholder in the book Just the Arguments: 100 of the Most Important Arguments in Western Philosophy (2011: 282-283):
P1. Killing this particular adult human being or child would be seriously wrong.
P2. What makes it so wrong is that it causes the loss of this individual’s future experiences, activities, projects, and enjoyments, and this loss is one of the greatest losses that can be suffered.
C1. Killing this adult human being or child would be seriously wrong, and what makes it so wrong is that it causes the loss of this individual’s future experiences, activities, projects, and enjoyments, and this loss is one of the greatest losses that can be suffered (conjunction, P1, P2).
P3. If killing this particular adult human being or child would be seriously wrong and what makes it so wrong is that it causes the loss of all this individual’s experiences, activities, projects, and enjoyments, and this loss is one of the greatest losses that can be suffered, then anything that causes to any individual the loss of all future experiences, activities, projects, and enjoyments is seriously wrong.
C2. Anything that causes to any individual the loss of all future experiences, activities, projects, and enjoyments is seriously wrong (modus ponens, C1, P3).
P4. All aborting of any healthy fetus would cause the loss to that individual of all its future experiences, activities, projects, and enjoyments.
C3. If A causes to individual F the loss of all future experiences, activities, projects, and enjoyments, then A is seriously wrong (particular instantiation, C2).
C4. If A is an abortion of healthy fetus F, then A causes to individual F the loss of all future experiences, activities, projects, and enjoyments (particular instantiation, P4).
C5. If A is an abortion of a healthy fetus F, then A is seriously wrong (hypothetical syllogism, C3, C4).
C6. All aborting of any healthy fetus is seriously wrong (universal generalization, C5).
In this case, the argument is about abortion in regard to healthy fetuses. This argument, like the one for abortion, is also deductively valid. (Arguments for and against the abortion of unhealthy fetuses will be covered in the future.) Thus, if a fetus is healthy then it should not be aborted since doing so would cause the individual to lose their future experiences, enjoyments, activities, and projects. Thus, the abortion of a healthy fetus is seriously and morally wrong. This argument clearly establishes the fetuses’ right to life if it is healthy.
Both of these arguments for and against abortion are strong; on the “for” side, we have the apparent facts that fetuses, infants, and (nonhuman) animals cannot want their continuance of their mental states since they cannot conceive of their continuance and want of mental states, so if they cannot want their continuance of their mental states they do not have a morally serious right to life and it is, therefore, morally right to kill them painlessly. On the “against” side, we have the facts that aborting healthy fetuses will cause the loss of all future experiences, enjoyments, activities, and projects, and so, the abortion of these healthy fetuses is both seriously and morally wrong.
I will cover these types of arguments—and more—in the future. However, if one is against genetic modification, embryo selection, preimplantation genetic diagnosis (PGD) and ‘eugenics’, then one must, logically, be against the abortion of healthy fetuses as well. These two arguments, of course, have implications for any looming eugenic policies as well, which I will cover in the future.
(I, personally, lean toward the “against” side in this debate; though, of course, the argument presented in this article on the “for” side is strong as well.)
Rational people can just look at people of different ancestries and see that there is something to what we call “race.” We notice that others look different based on where their ancestors came from and we classify people into different races on the basis of their physical appearance. Anti-biological racial realists may point to the fact that there is more variation within races than between them (Lewontin, 1972; Rosenberg et al, 2002; Witherspoon et al, 2007; Hunley, Cabana, and Long, 2016; Hardimon, 2017). While this is true, this does not mean that race is “just a social construct” (a phrase used to deflate the meaning of “race”); it is both a social construct and a biological reality.
The definition of race is simple—a group of populations which genetically transmit heritable characteristics which correspond to that group’s geographic ancestry who also belong to a biological line of descent which was initiated by a geographically isolated and reproductively isolated founding populations (Hardimon, 2017). Note how this definition says nothing about differences in allele frequencies between populations between populations—because, for these purposes, they’re irrelevant for the argument being made. The fact of the matter is, the reality of race hinges on two things: (1) the heritable differences between population groups which were geographically/reproductively isolated and (2) our ability to discern these population groups by their phenotype.
A great book on the history of race, its meaning and how the term was used over the ages is Race: The Reality of Human Differences by Sarich and Miele (2004). For the purposes of this piece, the first two chapters are the most important, since they touch on aspects of race that I have in the past—mainly the fact that we only need phenotype to discern one’s race. People from Europe look phenotypically different from people from Africa who look phenotypically different from people from Asia etc. These differences between these groups are evidence that race exists—these racial differences in phenotype are due, in part, to the climate they evolved in while geographically and reproductively isolated (two conditions for racehood).
Sarich and Miele (2004: 29) write:
Vince [Sarich; one of the authors of the book] naively asked for the legal definition of “race” and was told there wasn’t one.
As we began working on this book, we discussed the issue of the legal definition of “race” … He informed us that there is still no legal definition of “race”; nor, as far as we know, does it appear that the legal system feels the need for one. Thus, it appears that the most adversarial part of our complex society, the legal system, not only continues to accept the existence of “race” but also relies on the ability of the average individual to sort people into races. Our legal system treats “racial identification” as self-evident …
The courts have come to accept the commonsense definition of race, and it is this commonsense view that, as we show, best conforms to reality. A look at two recent (2000) cases is illustrative. In both Rice v. Office of Hawaiian Affairs and in Hank v. Rochester School District, neither side raised any questions about the existence of human races or the ability of the average citizen to make valid judgements as to who belongs to which race (even if the racial categories are euphemistically termed “peoples” or “populations”). No special expertise was assumed or granted in defining or recognizing race other than the everyday commonsense usage, as given in the Oxford English Dictionary, that a race is “a group of persons connected by common descent” or “a tribe, nation, or people, regarded as common stock.” The courts and the contending parties, in effect, accepted the existence of race and the ability of the ordinary person to distinguish between races based on a set of physical features.
In Rice v. Office of Hawaiian Affairs, Rice challenged the state of Hawaii since they did not allow him to vote—on the basis that he was not a native Hawaiian, and that the electoral system of Hawaii is for the benefit of Hawaiians and Hawaiians only. Everyone agreed that Rice was a Hawaiian citizen—but he did not have Hawaiian ancestry, so he could not be recognized as “Hawaiian” under state law. However, the SCOTUS overturned the ruling (that Rice should not be allowed to vote on the basis of not having Hawaiian ancestry) 7-2, citing the 15th amendment: “The right of the citizens of the United States to vote shall not be denied or abridged by the United States or any State on account of race, color, or previous condition of servitude.” Sarich and Miele (2004: 31) write “The 15th amendment is explicit—race means what the average person thinks it means—and the majority of the Supreme Court read it that way.” (Also see Hong, 2008 for an overview of the case.)
On the other hand, in Haak v. Rochester School District, the Second Circuit Court of Appeals ruled that a white fourth-grade student named Jessica Haak could transfer from her current district to another district (full of whites) since the transfer program was initiated with the idea of lessening the racial isolation of the adjoining districts. Jessica’s mother cited the 14th amendement, and a district court ruled in their favor but the Second Circuit Court of Appeals overturned the decision. “A “minority pupil” was defined as “a pupil who is of Black or Hispanic origin or is a member of another minority group that historically has been the subject of discrimination” (Sarich and Miele, 2004: 31).
The critical points here are that in both Rice and Haak, neither side raised any questions about the existence of human races or the ability of the average citizen to make valid judgements as to who belongs to which race. No special expertise was assumed or granted in defining or recognizing race other than the everyday usage of the term. In Rice, the court, in effect, took judicial notice of the commonsense definition of race. In Haak, the court accepted physical appearance as a valid means by which the average citizen can recognize races and distinguish among them.
In short, the courts accepted the existence of race, even if the legislature was afraid to use the offending word.
Despite the fact that Sarich and Miele (2004) claim that there is no legal definition of race, Cornell Law School has one definition stating that “the term “racial group” means a set of individuals whose identity as such is distinctive in terms of physical characteristics or biological descent.” While the Law Dictionary, citing the 15th amendment writes that race is “A tribe, people, or nation, belonging or supposed to belong to the same stock or lineage. “Race, color, or previous condition of servitude.” Const U. S., Am. XV.” (Also see Hoffman, 2004 who argues that “race” should not be used in the legal system.)
Notice how Sarich and Miele’s (2004) description of “race” and what “race” is almost—word-for-word—like Spencer’s Blumenbachian partitions (Spencer, 2014). Americans defer to the US Census Bureau on matters of race; the US Census Bureau defers to the Office of Management and Budget (OMB) who speak of sets of populations; these sets of populations correspond to geographic clusters who have distinct phenotypes based on their geographic ancestry, which the average American can discern; therefore race exists. Spencer states that when Americans refer to “race” that Americans refer to both a social construct and a biological reality—that is, Americans socially construct race (think of how Hardimon’s minimalist concept of race is related to the concept of socialrace) but these social constructs do have biological underpinnings which can be discerned in two ways: (1) just observation of phenotypes and (2) looking into the genomes of genetically related individuals who make up these population groups.
Even the ancients distinguished races and sorted them on the basis of hair color/type, skin color, physiognomy etc. “[The Egyptians, Greeks, Romans, Indians, and Chinese] sorted [broad racial groups] based upon the same set of characteristics—skin color, hair form, and head shape” while “it is evident that they relied upon a set of observable features (skin color and form, body build, facial features) quite similar to those used in the commonsense notion of race and the racial classifications of nineteenth-century anthropology to sort the many diverse groups they encountered into a smaller number of categories” (Sarcih and Miele, 2004: 42).
It is very clear that, ever since antiquity at the very least, we have been classifying racial groups on the basis of phenotype—and, come to find out, this is one of the best ways to sort people—and you don’t even need to look at genetic differences between groups. Phenotype is clearly enough to delineate racial groupings, you don’t need genes to delineate race. We only need to recognize that (1) people look different on the basis of where they (or their ancestors) came from; (2) observe that these physical differences between people who come from different places are between real and existing groups; (3) people have common ancestry with others; (4) people derive from distinct geographic locations; so (5) we can infer that race exists.
Race is very clearly a reality—both biologically and socially. At least three sound arguments exist for the existence of race (Sarich and Miele, 2004; Spencer, 2014; Hardimon, 2017; see Hardimon’s and Spencer’s arguments at length). Even those in antiquity delineated races on the basis of physical features—exactly what has been argued by Spencer and Hardimon. Race is physically real—people look different from each other individually, ethnically, and racially.
Biological racial realism is true, and if biological racial realism is true then race exists.
(1) If groups of people look different from each other depending on where their ancestors evolved, then race exists.
(2) Groups of people look different from each other depending on where their ancestors evolved.
(3) Therefore, race exists since people look different depending on where their ancestors evolved.
On Twitter, JayMan wrote: “Not talked about much by fitness buffs (a world that’s full of BS anyway): a fair fraction of people respond little to even *negatively* to exercise“. This is the same person that thinks behavior genetics is a science, and that is a field “that’s full of BS anyway”, too. Anyway, the article that JayMan cited was from the website Stronger by Science, titled Hardgainers? What We Know About Non-Responders by Greg Nuckols.
First off, JayMan’s comment that “a fair fraction of people respond … *negatively* to exercise” is, on its face, already false. Most everyone in the study referenced by Nuckols (There Are No Nonresponders to Resistance-Type Training in Older Men and Women; Churchward-Venne et al, 2015) gained strength, but some people’s muscle fibers did not grow, and some apparently shrank (that is, their muscle cross-section area; CSA). But the important thing to note is that ALL gained strength, which implies physiologic adaptation to the stressor placed on the body (something that is overlooked).
Though, even if some people do not respond to certain programs or weight/rep schemes, does not mean that they are “non-responders”. All that needs to be done is to change the program if one “does not respond” to the program created. All exercise programs should be tailored to the individual and their own specific goals. There is no “one-size-fits-all” exercise program, as can be seen from these studies on so-called “hardgainers.”
The best study for this matter, though, is the HERITAGE (HEalth, RIsk factors, exercise, Training, And GEnetics) study, carried out by five universities in Canada and the US, who enlisted 98 two-generation families and then subject each member to five months of the same stationary bike training regimen—three workouts per week with increasing intensity. Each of the 482 individuals in the study was assayed, and so we would also see which genes would play a role in how fit one person would be in comparison to another.
David Epstein, author of The Sports Gene, writes (pg 85):
Despite the fact that every member of the study was on an identical exercise program, all four sites saw a vast and similar spectrum of aerobic capacity improvement, from about 15 percent of participants who showed little or no gain whatsoever after five months of training all the way up to 15 percent of participants who improved dramatically, increasing the amount of oxygen their bodies could use by 50 percent or more.
Amazingly, the amount of improvement that any one person experienced had nothing to do with how good they were to start. In some cases, the poor got relatively poorer (people who started with a low aerobic capacity and improved little); in others, the oxygen rich got richer (people who started with high aerobic capacity and improved rapidly); with all manner of variation in between—exercisers with a high baseline aerobic capacity and little improvement and others with meager starting aerobic capaacity whose bodies transformed drastically.
Though, contrary to JayMan’s claims, “Fortunately, every single HERITAGE subject experienced health benefits from exercise. Even those who did not improve at all in aerobic capacity improved in some other health parameter, like blood pressure, cholesterol, or insulin sensitivity” (Epstein, 2014: 88).
Epstein also writes about another study, undertaken at the University of Alabama-Birmingham’s Core Muscle and Research Laboratory, writing:
Sixty-six people of varying ages were put on a four-month strength training plan—squats, leg press, and leg lifts—all matched for effort level as a percentage of the meximinum they could lift. (A typical set was eleven reps at 75 percent of the maxmimum that could be lifted for a single rep.) At the end of the trainin, the sibjects fell rather neatly into three groups: those whose thigh muscle fibers grew 50 percent in size; those whose fibers grew 25 percent; and those who had no increased in muscle size at all.
Seventeen weight lifters were “extreme responders” who added muscle furiously; thirty-two were moderate responders, who had decent gains; and seventeen were nonresponders, whose muscle fibers did not grow.* (pg 110)
* “It’s important to keep in mind that the harder the training, the less likely there are to be “nonresponders.” The harder the work, the more likely a subject will get at least some response, even if it is less than her peers” (pg 376).
Those who responded the most to the regimen had the most satellite cells in their quads which were waiting to be activated by training. When one becomes stronger from hypertrophy, the muscle thickness correlates to muscle CSA (Franchi et al, 2018). When one performs a repetition, the muscle fibers break down—this leads to trauma of the cellular proteins in the muscles which must then go under repair. Numerous growth factors influence the growth of skeletal muscle, such as GH (growth hormone), testosterone, protein and carb intake. Skeletal muscle adapts almost immediately after a bout of exercise, but the apparent changes to the muscle (both in the mirror and seeing large gains in strength on any particular movement) will take weeks and months.
There’s one thing about the claims of “exercise nonresponders” that really gets me: everyone responds positively to exercise, even if it’s not the same exact response to another individual doing the same—or different—exercise! I don’t know who made the claim that “people respond the same to any exercise program”, but that’s a claim that hbdchick made, writing “plenty of the “fitness buffs” do [make the claim that everyone would respond the same to the same exercise regimen]. I then asked her, and JayMan, to name three people who made this outrageous claim: but, of course, I got no answer.
Not to mention that Nuckols ended the article writing:
… there were way fewer nonresponders when people were put on personalized training programs instead of one-size-fits-all standardized programs. This study was primarily looking at aerobic fitness, but it also examined strength measures (bench press and leg press 5RM). It found that all the subjects on personalized programs got stronger, while only 64.3% of the subjects on standardized programs got stronger. This gives us more evidence that “nonresponders” in scientific studies aren’t necessarily “true” nonresponders.
Take two people who have similar measures and, say, start at the same weight on one exercise. In 6 months, all else being equal with regard to lifestyle, there will be a difference in strength gained on that particular exercise. However, an increase from t he baseline from when both individuals began, to the 6-month point, shows that they did, indeed, respond to the exercise program at least in some way (see above quotes from Epstein). Thus, the claim that “there are nonresponders to exercise” makes no sense, on the basis that people necessarily respond physiologically to the stressors placed on them, and so, if they do more (and they will) than they did previously from their baseline, then they did adapt to the protocol, implying that they are not “nonresponders” to exercise. It does not matter if Person B does not catch up to Person A on all variables: the fact that there was a difference in each individual from the baseline all the way to 6 months on a specific regimen implies adaptation to the stressors—which implies that there is no such thing “nonresponders”.
JayMan also has views similar to this, which I have responded to last year in the articles Diet and Exercise: Don’t Do It? and Diet and Exercise: Don’t Do It? Part II. Eating well and exercising—although benefits are not the same for each individual (and I do not know who made the claim this was the case)—does ameliorate numerous diseases and can extend lifespan, contrary to the results of certain studies (e.g., the Look AHEAD study; Annuzzi et al 2014).
Claims from people like JayMan who do not know the first thing about dieting and exercise are dangerous—though, all one has to do is have a basic understanding of physiology to understand that the claim “a fair fraction of people respond little to even *negatively* to exercise” is false, since everyone who does something for the first few times will ALWAYS be better in the months after learning the specific movement, implying that there are no nonresponders to exercise.
Of course everyone does not respond the same to exercise regimen A. Other studies found that increasing the frequency, reps, and set scheme lead to changes in the so-called “nonresponders.” Different individuals respond differently to different training programs [be it, strength, conditioning, cardio, plyometrics, balance, and stabilization etc. But it must be stressed that, although not everyone has the same potential for muscle-building/strength-gaining as, say, the IFBB pros or strongmen/powerlifters, everyone can and does benefit from NOT being sedentary, that much is most definitely clear. These studies that show “nonresponders” run people through the same exercise regimen. Anyone with an iota of experience in this industry knows that people do not respond the same to any and every exercise regimen and, so, the program must be tailored to that specific individual. Though, people like JayMan read this stuff and, without understanding what they’re talking about, jump to brash conclusions that are not supported by reality.
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).
Is there one (or, one with slight modifications) diet that all humans should be eating? I’m skeptical of such claims. Though both vegans (one who does not eat or use animal products) and carnivores (one who eats only animal products), in my opinion, have some warped views on diet and human evolution. Both are extreme views; both have wrong ideas about diet throughout our evolution; both get some things right. Though, both are extreme views with little to no support. While it is hard to pinpoint what the “human diet” is, clearly, there were certain things that we ate through our evolutionary niches in our ancestral Africa that we “should” be eating today (in good quantities).
Although it is difficult to reconstruct the diet of early hominids due to lack of specimens (Luca, Perry, and Rienzo, 2014), by studying the eating behavior of our closest evolutionary relatives—the chimpanzees—we can get an idea of what our LCA ate and its eating behavior (Ulijaszek, Mann, and Elton, 2013). Humans have been throughout most every niche we could possibly been in and, therefore, have come across the most common foods in each ecology. If animal A is in ecosystem E with foods X, Y, and Z, then animal A eats foods X, Y, and Z, since animals consume what is in their ecosystem. Knowing this much, the niches our ancestors lived in in the past had to have a mix of both game and plants, therefore that was our diet (in differing amounts, obviously). But it is more complicated than that.
So, knowing this, according to Ulijaszek, Mann, and Elton, (2013: 35) “Mammalian comparisons may be more useful than ‘Stone Age’ perspectives, as many of the attributes of hominin diets and the behaviour associated with obtaining them were probably established well before the Pleistocene, the time stone agers were around (Foley 1995; Ulijaszek 2002; Elton 2008a).” Humans eat monocots (various flowering plants with one seed), which is not common our order. The advent of farming was us “expanding our dietary niche”, which began “the widespread adoption of agriculture [which] is an obvious point of transition to a ‘monocot world’” (Ulijaszek, Mann, and Elton, 2013). Although these foodstuffs dominate our diet, there is seasonality in what types of those foods we consume.
So since humans tend to not pick at things to eat, but have discrete meals (it is worth noting that one should have “three square meals a day” is a myth; see Mattson et al, 2014), we need to eat a lot in the times we do eat. Therefore, since we are large-bodied primates and our energy needs are much higher (due to our large brains that consume 20 percent of our daily caloric consumption), we need higher quality energy. The overall quality and energy density of our diets are due to meat-eating—which folivorous/frugivorous primates do not consume. We have a shorter gut tract which is “often attributed to the greater reliance of faunivory in humans“, though “humans are not confined to ‘browse’ vegetation … and make extensive use of grasses and their animal consumers” (Ulijaszek, Mann, and Elton, 2013: 58). Due to this, we show amazing dietary flexibility and adaptability due to our ability to eat a wide range of foodstuffs in most any environment we find ourselves in.
So “It is difficult to pinpoint what the human diet actually is … Nonetheless, humans are frequently described as omnivores” (Ulijaszek, Mann, and Elton, 2013: 59). Omnivores normally feed at two or more trophic levels, though others define it as just consuming plants and animals (Chubaty et al, 2014). Trophic level one is taken up by plants; level two is taken up by herbivores—primary consumers; level three is taken up by predators—who feed on the herbivores; level four or five is taken up by apex predators or carnivores; while the last level is also taken up by detrivores—those who feed on waste. Though, of course, “omnivory” is a continuum and not a category in and of itself. Humans eat primary producers (plants) and primary consumers (herbivores) and some secondary consumers (like fish), “although human omnivory may only be possible because of technological processing” (Ulijaszek, Mann, and Elton, 2013: 59). Other animals described as “omnivorous” eat only foods from one trophic level and only consume food from another level when needed.
Humans—as a species—rely on meat consumption. Fonseca-Azevedo and Herculano-Houzel (2012) showed that the energetic cost of a brain is directly related to the number of neurons in the brain. So, there were metabolic limitations in regard to brain and body size. The number of hours available to feed along with the low caloric yield of plant foods explains why great apes have such large bodies and small brains—which was probably overcome by erectus, who probably started cooking food around 1.5 mya. If we consumed only a diet of raw foods, then it would have taken us around 9 h/day to consume the calories we would need to power our brains—which is just not feasible. So it is unlikely that erectus—who was the first to have the human body plan and therefore the ability to run, which implies he would have needed higher quality energy—would have survived on a diet of raw plant foods since it would take so many hours to consume enough food to power their growing brains.
We can see that we are adapted to eating meat by looking at our intestines. Our small intestines are relatively long, whereas our long intestines are relatively short, which indicates that we became adapted to eating meat. Our “ability to eat significant quantities of meat and fish is a significant departure from the dietary norm of the haplorhine primates, especially for animals in the larger size classes.” Though “Humans share many features of their gut morphology with other primates, particularly the great apes, and have a gut structure that reflects their evolutionary heritage as plant, specifically ripe fruit, eaters” (Ulijaszek, Mann, and Elton, 2013: 63). Chimpanzees are not physiologically adapted to meat eating, which can be seen in the development of hypercholesterolemia along with vascular disease, even when controlled diets in captivity (Ford and Stanford, 2004).
When consuming a lot of protein, though, “rabbit starvation” needs to be kept in mind. Rabbit starvation is a type of malnutrition that arises from eating little to no fat and high amounts of protein. Since protein intake is physiologically demanding (it takes the most energy to process out of the three macros), Ben-Dor et al (2011) suggest a caloric ceiling of about 35 percent of kcal coming from protein. So erectus’ protein ceiling was 3.9 g/bw per day whereas for Homo sapiens it was 4.0 g/bw per day. Ben-Dor et al (2011) show that erectus’ DEE (daily energy expenditure) was about 2704 kcal, with “a maximum long-term plant protein ceiling of 1014 calories“, implying that erectus was, indeed, an omnivore. So, of course, the consumption of protein and raw plants are physiologically limited. Since erectus’ ceiling on protein intake was 947 kcal and his ceiling on raw plant intake was 1014 kcal, then, according to the model proposed by Ben-Dor et al (2011), erectus would have needed to consume about 744 kcal from fat, which is about 27 percent of his overall caloric intake and 44 percent of animal product intake.
Neanderthals would have consumed between 74-85 percent of their daily caloric energy during glacial winters from fat, with the rest coming from protein (Ben-Dor, Gopher, and Barkai, 2016), while consuming between 3,360 to 4,480 kcal per day (Steegman, Cerny, and Holliday, 2002). (See more on Neanderthal diet here.) Neanderthals consumed a large amount of protein, about 292 grams per day (Ben-Dor, Gopher, and Barkai, 2016: 370). Since our close evolutionary cousins (Neanderthals and erectus) ate large amounts of protein and fat, they were well-acclimated, physiologically speaking, to their high-protein diets. Though, their diets were not too high in protein to where rabbit starvation would occur—fat was consumed in sufficient amounts in the animals that Neanderthals hunted and killed, so rabbit starvation was not a problem for them. But since rabbit starvation is a huge problem for our species, “It is therefore unlikely that humans could be true carnivores in the way felids are” (Ulijaszek, Mann, and Elton, 2013: 66).
We consume a diet that is both omnivorous and eclectic, which is determined by our phylogeny through the form of our guts; we have nutritional diversity in our evolutionary history. We needed to colonize new lands and, since animals can only consume what is in their ecosystem, the foods that are edible in said ecosystem will be what is consumed by that animal. Being eclectic feeders made the migration out of Africa possible.
But humans are not true carnivores, contrary to some claims. “Meat-eating has allowed humans to colonize high latitudes and very open landscapes. However, bearing in mind the phylogenetic constraints that prevent humans from being true carnivores, such expansion was probably not accomplished through meat-eating alone. Instead, humans have used their ability to technologically harvest, produce, and consume a very wide range of foods to help exploit all major biomes” (Ulijaszek, Mann, and Elton, 2013: 67).
Humans, though, lack the gut specialization and dentition to process grasses efficiently. This means that our ancestors ate animals that ate these things, and therefore the C4 they consumed elevated the levels in the fossils we discovered. Information like this implies that our ancestors ate across a wide variety of trophic levels and had substantial dietary diversity throughout evolutionary history.
“Hominins lack the specialized dentition found in carnivorans (the group of animals that includes the cat and dog families) and other habitual meat and bone eaters, so must have pre-processed at least some of the meat in their diet” (Ulijaszek, Mann, and Elton, 2013: 81). This is where stone tools come into play (Zink and Lieberman, 2016). “Processing” food can be anything from taking out nutrients to changing how the food looks. We can look at “food processing” as a form of pre-digestion before consumption. The use of stone tools, and cooking, was imperative for us to begin the processing of meat and other foods. This gave us the ability to “pre-digest” our food before consumption, which increases the available energy in any food that is cooked/processed. For example, cooking denatures protein strands and breaks down the cell walls which gelatinizes the collagen in the meat which allows for easier chewing and digestion. Carmody et al (2016) showed that adaptation to a cooked diet began around 275 kya.
In his book Catching Fire, Wrangham (2009: 17-18) writes:
Raw-foodists are dedicated to eating 100 percent of their diets raw, or as close to 100 percent as they can manage. There are only three studies of their body weight, and all find that people who eat raw tend to be thin. The most extensive is the Giessen Raw Food study, conducted by nutritionist Corinna Koebnick and her colleagues in Germany, who used questionnaires to study 513 raw-foodists who ate from 70 to 100 percent of their diet raw. They chose to eat raw to be healthy, to prevent illness, to have a long life, or to live naturally. Raw food included not only uncooked vegetables and occasional meat, but also cold-pressed oil and honey, and some items were lightly heated such as dried fruits, dried meat, and dried fish. Body mass index (BMI), which measures weight in relation to the square of the height, was used as a measure of fatness. As the proportion of food eaten raw rose, BMI fell. The average weight loss when shifting from a cooked to a raw food diet was 26.5 pounds (12 kilograms) for women and 21.8 pounds (9.9 kilograms) for men. Among those eating a purely raw diet (31 percent), the body weights of almost a third indicated chronic energy deficiency. The scientists’ conclusion was unambiguous: “a strict raw food diet cannot guarantee an adequate energy supply.”
Also, vegetarians and meat-eaters who cooked their food have similar body weights. This implies that cooking food—no matter the type—gives more caloric energy to use for the body and that raw-foodists are fighting a losing battle with biology, consuming raw foods at such a high quantity that our guts are not used for. As can be seen above in the citation from Fonseca-Azevedo and Herculano-Houzel (2012), great apes who eat nothing but raw food have large guts and bodies which are needed to consume the raw plant foods they eat but we cannot thrive on such a diet because it is not calorically nor nutritionally viable for us—most importantly due to the size of our brains and its caloric requirements.
Carmody, Weintraub, and Wrangham (2011) show that modern raw-foodists who subsist on raw meat and plants have nutrient deficiencies and chronic energy deficiencies, even though they process their foods (cooking is a form of processing, as is cutting, mashing, pounding, etc) in different manners, while females experience low fecundity. Thus, the cooking of food seems to be needed for normal biological functioning; we have clearly evolved past consuming all raw foods. So it is clear that cooking—along with meat-eating—was imperative to our evolution. (Which does not mean that humans only ate meat and that eating meat and only meat is part of our evolutionary history.) Cooking food lead to it gelatinizing which denatured the protein, leading to easier mastication of the food, which meant less force since the food was not as hard after cooking. This then led to smaller teeth, over time, which was seen in erectus (Zink and Lieberman, 2016). This was due to cooking along with tool-use: the tool-use lead to smaller particles leading to less force per bite, which eventually led to smaller teeth in our lineage.
Finally, humans are said to be “facultative carnivores.” A facultative carnivore is an animal that does best on a carnivorous diet but can survive—not thrive—on other foodstuffs when meat is not available. This, though, doesn’t make sense. Humans are eclectic feeders—omnivorous in nature. Yes, we began cooking about 1.5 mya; yes meat-eating (and the cooking of said meat) is huge in the evolution of our species; yes without meat and cooking we would not have had the energy requirements to split off from chimpanzees/great apes. But this does not mean that we do “best” on a carnivorous diet. There are about 7,105 ethnic groups in the world (Spencer, 2014: 1029), and so to say that all of these ethnies would do the same or similar, physiologically speaking, on an all-meat diet is crazy talk. The claims that we subsisted on one type of food over the other throughout our evolutionary history is a bold claim—with no basis in evolutionary history.
Marlene Zuk (2013: 103-104), author of Paleofantasy writes:
Another implication of the importance Marlowe attaches to bow hunting is that, rather than starting out as exclusively carnivorous and then adding starches and other plant material to the diet, ancient humans have been able to increase the proportion of meat only after newer technology had come about, a mere 30,000 years ago. Other anthropologists concur that the amount of meat in the human diet grew as we diverged from our other primate ancestors. All of this means that, first, contrary to the claims of many paleo-diet proponents, the earliest humans did not have an exclusively meat-based diet that we are best adapted to eat; and second, our ancestors’ diets clearly changed dramatically and repeatedly over the last tens, not to mention hundreds, thousands of years, even before the advent of agriculture.
The assumption that we were fully (or even mostly) carnivorous and then added plant foods/carbs is clearly false. “Fantasies” like this are “just-so stories”; they are nice-sounding stories, but reality is clearly more nuanced than people’s evolutionary and Stone Age imaginations. This makes sense, though. Since we evolved from an LCA (last common ancestor) with chimpanzees some 6.3 mya (Patterson et al, 2006). So why would it make sense that we would then, ultimately, only subsist on an all-meat diet, if our LCA with chimpanzees was most likely a forager who lived in the trees (Lieberman, 2013).
One thing, though, I’m sure that everyone agrees with is that the environments we have constructed for ourselves in the first world are maladaptive—what is termed an “evolutionary mismatch” (Lieberman, 2013; Genne-Bacon, 2014). The mismatch arises from the high-carb food environments we have constructed, with cheap foodstuffs that is loaded with sugar, salt, and fat which is much more addictive than on their own (see Kessler, 2010). This makes food more palatable and people then want to eat it more. Foods like this, obviously, were not in our OEE (original evolutionary environment), and therefore cause us huge problems in our modern-day environments. Evolutionary mismatches occur when technological advancement increases faster than the genome can adapt. This can clearly be seen in our societies and the explosion of obesity over the past few decades (Fung, 2016, 2018).
We did not evolve eating highly processed carbohydrates loaded with salt and sugar. That much everyone can agree on.
It is clear that both claims from vegans/vegetarians and carnivores are false: there is no one “human diet” that we “should” be eating. Individual variation in different physiologic processes implies that there is no one “human diet”, no matter what type of food is being pushed as “what we should be” eating. Humans are eclectic feeders; we will eat anything since “Humans show remarkable dietary flexibility and adaptability“. Furthermore, we also “have a relatively unspecialized gut, with a colon that is shorter relative to overall size than in other apes; this is often attributed to the greater reliance on faunivory in humans (Chivers and Langer 1994)” (Ulijaszek, Mann, and Elton, 2013: 58). Our dietary eclectism can be traced back to our Australopithecine ancestors. The claim that we are either “vegetarian/vegan or carnivore” throughout our evolution is false.
Humans aren’t “natural carnivores” or “natural vegans/vegetarians.” Humans are eclectic feeders. Animals eat whatever is in their ecosystem. Ergo humans are omnivores, though we can’t pinpoint what the “human diet” is since there is great variability in it due to culture/ecology, we know one thing: we did not subsist on mainly only one food; we had a large variety of food, especially with fallback foods, to consume throughout our evolutionary history. So claims that we evolved to eat a certain way (as vegans/vegetarians and carnivores claim) is false. (Note I am not saying that high carb diets are good; I’ve railed hard on them.)
In 2012, biologist Hippokratis Kiaris published a book titled Genes, Polymorphisms, and the Making of Societies: How Genetic Behavioral Traits Influence Human Cultures. His main point is that “the presence of different genes in the corresponding people has actually dictated the acquisition of these distinct cultural and historical lines, and that an alternative outcome might be unlikely” (Kiaris, 2012: 9). This is a book that I have not seen discussed in any HBD blog, and based on the premise of the book (how it purports to explain behavioral/societal outcomes between Eastern and Western society) you would think it would be. The book is short, and he speaks with a lot of determinist language. (It’s worth noting he does not discuss IQ at all.)
In the book, he discusses how genes “affect” and “dictate” behavior which then affects “collective decisions and actions” while also stating that it is “conceivable” that history, and what affects human decision-making and reactions, are also “affected by the genetic identity of the people involved” (Kiaris, 2012: 11). Kiaris argues that genetic differences between Easterners and Westerners are driven by “specific environmental conditions that apparently drove the selection of specific alleles in certain populations, which in turn developed particular cultural attitudes and norms” (Kiaris, 2012: 91).
Kiaris attempts to explain the societal differences between the peoples who adopted Platonic thought and those who adopted Confucian thought. He argues that differences between Eastern and Western societies “are not random and stochastic” but are “dictated—or if this is too strong an argument, they are influenced considerably—by the genes that these people carry.” So, Kiaris says, “what we view as a choice is rather the complex and collective outcome of the influence of people’s specific genes combined with the effects of their specific environment … [which] makes the probability for rendering a certain choice distinct between different populations” (Kiaris, 2012: 50).
The first thing that Kiaris discusses (behavior wise) is DRD4. This allele has been associated with miles migrated from Africa (with a correlation of .85) along with novelty-seeking and hyperactivity (which may cause the association found with DRD4 frequency and miles migrated from Africa (Chen et al, 1999). Kiaris notes, of course, that the DRD4 alleles are unevenly distributed across the globe, with people who have migrated further from Africa having a higher frequency of these alleles. Europeans were more likely to have the “novelty-seeking” DRD7 compared to Asian populations (Chang et al, 1996). But, Kiaris (2012: 68) wisely writes (emphasis mine):
Whether these differences [in DRD alleles] represent the collective and cumulative result of selective pressure or they are due to founder effects related to the genetic composition of the early populations that inhabited the corresponding areas remains elusive and is actually impossible to prove or disprove with certainty.
Kiaris then discusses differences between Eastern and Western societies and how we might understand these differences between societies as regards novelty-seeking and the DRD4-7 distribution across the globe. Westerners are more individualistic and this concept of individuality is actually a cornerstone of Western civilization. The “increased excitability and attraction to extravagance” of Westerners, according to Kiaris, is linked to this novelty-seeking behavior which is also related to individualism “and the tendency to constantly seek for means to obtain satisfaction” (Kiaris, 2012: 68). We know that Westerners do not shy away from exploration; after all, the West discovered the East and not vice versa.
Easterners, on the other hand, are more passive and have “an attitude that reflects a certain degree of stoicism and makes life within larger—and likely collectivistic—groups of people more convenient“. Easterners, compared to Westerners, take things “the way they are” which “probably reflects their belief that there is not much one can or should do to change them. This is probably the reason that these people appear rigid against life and loyal, a fact that is also reflected historically in their relatively high political stability” (Kiaris, 2012: 68-69).
Kiaris describes DRD4 as a “prototype Westerner’s gene” (pg 83), stating that the 7R allele of this gene is found more frequently in Europeans compares to Asians. The gene has been associated with increased novelty-seeking, exploratory activity and human migrations, along with liberal ideology. These, of course, are cornerstones of Western civilization and thought, and so, Kiaris argues that the higher frequency of this allele in Europeans—in part—explains certain societal differences between the East and West. Kiaris (2012: 83) then makes a bold claim:
All these features [novelty-seeking, exploratory activity and migration] indeed tend to characterize Westerners and the culutral norms they developed, posing the intriguing possibility that DRD4 can actually represent a single gene that can “predispose” for what we understand as the stereotypic Western-type behavior. Thus, we could imagine that an individual beating the 7-repeat allele functions more efficiently in Western society while the one without this allele would probably be better suited to a society with Eastern-like structure. Alternatively, we could propose that a society with more individuals bearing the 7-repeat allele is more likely to have followed historical lines and choices more typical of a Western society, while a population with a lower number (or deficient as it is the actual case with Easterners) of individuals with the 7-repeat allele would more likely attend to the collective historical outcome of Eaasterners.
Kiaris (2012: 84) is, importantly, skeptical that having a high number of “novelty-seekers” and “explorers” would lead to higher scientific achievement. This is because “attempts to extrapolate from individual characteristics to those of a group of people and societies possess certain dangers and conceptual limitations.”
Kiaris (2012: 86) says that “collectivistic behavior … is related to the activity of serotonin.” He then goes on to cite a few instances of other polymorphisms which are associated with collective behavior as well. Goldman et al (2010) show ethnic differences in the l and s alleles (from Kiaris, 2012: 86):
It should also be noted that populations (Easterners) that had a higher frequency of the s allele had a lower prevalence of depression than Westerners. So Western societies are more likely to “suffer more frequently from various manifestations of depression and general mood disorders than those of Eastern cultures (Chiao & Blizinsky, 2010)” (Kiaris, 2012: 89).
As can be seen from the table above, Westerners are more likely to have the l allele than Easterners, which should subsequently predict higher levels of happiness in Western compared to Eastern populations. However, “happiness” is, in many ways, subjective; so how would one find an objective way to measure “happiness” cross-culturally? However, Kiaris (2012: 94) writes: “Intuitively speaking, though, I have to admit that I would rather expect Asians to be happier, in general, than Westerners. I cannot support this by specific arguments, but I think the reason for that is related to the individualistic approach of life that the people possess in Western societies: By operating under individualistic norms, it is unavoidably stressful, a condition that operates at the expense of the perception of individuals’ happiness.”
Kiaris discusses catechol-O-methyltransferase (COMT), which is an enzyme responsible for the inactivation of catecholamines. Catecholamines are the hormones dopamine, adrenaline, and noradrenaline. These hormones regulate the “fight or flight” function (Goldstein, 2011). So since catecholamines play a regulatory role in the “fight or flight” mechanism, increased COMT activity results in lower dopamine levels, which is then associated with better performance.
“Warriors” and “worriers” are intrinsically linked to the “fight or flight” mechanism. A “warrior” is someone who performs better under stress, achieves maximal performance despite threat and pain, and is more likely to act efficiently in a threatening environment. A “worrier” is “someone that has an advantage in memory and attention tasks, is more exploratory and efficient in complex environments, but who exhibits worse performance under stressful conditions (Stein et al., 2006)” (Kiaris, 2012: 102).
Kiaris (2012: 107) states that “at the level of society, it can be argued that the specific Met-bearing COMT allele contributes to the buildup of Western individualism. Opposed to this, Easterners’ increased frequency of the Val-bearing “altruistic” allele fits quite well with the construction of a collectivistic society: You have to be an altruist at some degree in order to understand the benefits of collectivism. By being a pure individualist, you only understand “good” as defined and reflected by your sole existence.”
So, Kiaris’ whole point is thus: there are differences in polymorphic genes between Easterners and Westerners (and are unevenly distributed) and that differences in these polymorphisms (DRD4, HTT, MAOA, and COMT) explain behavioral differences between behaviors in Eastern and Western societies. So the genetic polymorphisms associated with “Western behavior” (DRD4) are associated with increased novelty-seeking, tendency for financial risk-taking, distance of OoA migration, and liberal ideology. Numerous different MAOA and 5-HTT polymorphisms are associated with collectivism (e.g., Way and Lieberman, 2006 for MAOA and collectivism). The polymorphism in COMT more likely to be found in Westerners predisposes for “worrier’s behavior”. Furthermore, certain polymorphisms of the CHRNB3 gene are more common in all of the populations that migrated out of Africa, which predisposed for leaders—and not follower—behavior.
|Novelty seeking||DRD4||7-repeat novelty seeking allele more common in the West|
|Migration||DRD4||7-repeat allele is associated with distance from Africa migration|
|Nomads/settlers||DRD4||7-repeat allele is associated with nomadic life|
|Political ideology||DRD4||7-repeat allele is more common in liberals|
|Financial risk taking||DRD4||7-repeat allele is more common in risk takers|
|Individualism/Collectivism||HTT||s allele (collectivistic) of 5-HTT is more common in the East|
|Happiness||HTT||l allele has higher prevalence in individuals happy with their life|
|Individualism/Collectivism||MAOA||3-repeat allele (collectivistic) more common in the East)|
|Warrior/Worrier||COMT||A-allele (worrier) more common in the West|
|Altruism||COMT||G-allele (warrior) associated with altruism|
|Leader/Follower||CHRBN3||A-allele (leader) more common in populations Out-of-Africa|
The table above is from Kiaris (2012: 117) who lays out the genes/polymorphisms discussed in his book—what supposedly shows how and why Eastern and Western societies are so different.
Kiaris (2012: 141) then makes a bold claim: “Since we know now that at least a fraction (and likely more than that) of our behavior is due to our genes“, actually “we” don’t “know” this “now”.
The takeaways from the book are: (1) populations differ genetically; (2) since populations differ genetically, then genetic differences correlated with behavior should show frequency differences between populations; (3) since these populations show both behavioral/societal differences and they also differ in genetic polymorphisms which are then associated with that behavior, then those polymorphisms are, in part, a cause of that society and the behavior found in it; (4) therefore, differences in Eastern and Western societies are explained by (some) of these polymorphisms discussed.
Now for a simple rebuttal of the book:
“B iff G” (behavior B is possible if and only if a specific genotype G is instantiated) or “if G, then necessarily B” (genotype G is a sufficient cause for behavior B). Both claims are false; genes are neither a sufficient or necessary cause for any behavior. Genes are, of course, a necessary pre-condition for behavior, but they are not needed for a specific behavior to be instantiated; genes can be said to be difference makers (Sterelny and Kitcher, 1988) (but see Godfrey-Smith and Lewontin, 1993 for a response). These claims cannot be substantiated; therefore, the claims that “if G, then necessarily B” and “B iff G” are false, it cannot be shown that genes are difference makers in regard to behavior, nor can it be shown that particular genes or whatnot.
I’m surprised that I have not come across a book like this sooner; you would expect that there would be a lot more written on this. This book is short, it discusses some good resources, but the conclusions that Kiaris draws, in my opinion, will not come to pass because genes are not neccesary nor sufficient cause of any type of behavior, nor can it be shown that genes are causes of any behavior B. Behavioral differences between Eastern and Western societies, logically, cannot come down to differences in genes, since they are neither necessary nor sufficient causes of behavior (genes are neccessary pre-conditions for behavior, since without genes there is no organism, but genes cannot explain behavior).
Kiaris attempts to show how and why Eastern and Western societies became so different, how and why Western societies are dominated by “Aristotle’s reason and logic”, while Eastern lines of thought “has been dominated by Confucious’s harmony, collectivism, and context dependency” (Kiaris, 2012: 9). While the book is well-written and researched (he talks about nothing new if you’re familiar with the literature), Kiaris fails to prove his ultimate point: that differences in genetic polymorphisms between individuals in different societies explain how and why the societies in question are so different. Though, it is not logically possible for genes to be a necessary nor sufficient cause for any behavior. Kiaris talks like a determinist, since he says that “the presence of different genes in the corresponding people has actually dictated the acquisition of these distinct cultural and historical lines, and that an alternative outcome might be unlikely” (Kiaris, 2012: 9), though that is just wishful thinking: if we were able to start history over again, things would occur differently, “the presence of different genes in the corresponding people” be dammed, since genes do not cause behavior.