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Racial Differences in Somatype

1750 words

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

History of somatyping

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

Somatypes

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

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

Racial differences in somatype

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

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

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

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

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

Black-white differences in somatype

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

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

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

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

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

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

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

Conclusion

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

References

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

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

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

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

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

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

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

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

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

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

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

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

Possibly Retracting My Article on HBD and Baseball

700 words

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


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

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

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

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

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

* played 48 percent more games

* had 66 percent more major league hits

* hit 93 percent more triples

* hit 66 percent more home runs

* scored 69 percent more runs

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

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

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

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

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

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

1700 words

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

Muscle fiber typing by race

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

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

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

Disease and muscle fiber typing

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

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

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

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

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

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

Conclusion

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

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

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

References

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

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

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

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

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

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

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

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

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

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

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

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

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

Racial Differences in Muscle Fiber Typing Cause Differences in Elite Sporting Competition

1050 words

Blacks are, on average, better at sports than whites. Why? The answer is very simple: muscle fiber typing. Most individuals have an even proportion of muscle fibers, skewing about 5 to 10 percent less on type II fibers. However, when it comes to elite competition, race—and along with it muscle fiber typing—come into play more. Who is stronger? Why? Who is faster? Why? Who is better at endurance running? Why? The answers to these questions lie in muscle fiber typing, somatype, and, of course, grit and determination. Today I will provide yet more evidence for my argument that whites are stronger than blacks.

Muscle fiber typing by race

I’ll be quick here since I’ve covered this extensively.

Blacks have more type II muscle fibers in comparison to whites who have more type I muscle fibers. This difference in fiber typing causes differences in aerobic capacity which lead to higher rates of cardiorespiratory diseases such as type II diabetes, heart disease, and hypertension.

There are two types of muscle fibers with two divisions: Type I and Type II with the divisions being in the slow twitch fiber, further broken down into Type IIa and Type II x. Type I fibers fire slowly and possess greater aerobic metabolic capacity due to higher levels of lipid, myoglobin, mitochondrial and capillary content. Type II fibers, on the other hand, fire faster, have reduced aerobic capacity (and all that comes with it) and are better equipped for anaerobic activity (explosive sports). Type IIa possesses more aerobic potential than IIx, but less anaerobic potential than type I fibers. Some evidence exists showing that it’s possible to train type II fibers to have a similar aerobic capacity to type I, but I don’t really buy that. It is possible to make aerobic capacity similar to the aerobic capacity that type I fibers have, but type II will not be fully like them.

Blacks have more type II fibers while whites have more type I fibers. Type II fibers predispose people to a myriad of cardiometabolic diseases which are also associated with grip strength.

Differences in fiber typing in elite athletes

Now comes the fun part. How do muscle fibers differ between elite athletes? A few studies have been done but, as expected in physiology studies, they have a low n, but they still do show physiologic differences when compared to the control subjects, physiologic differences that were predicted due to what we know about muscle fiber typing.

Type IIa fibers possess more aerobic potential than IIx, therefore, power lifters have a higher proportion of IIa fibers compared to IIx fibers. It should also be noted that powerlifters have the same amount of type I fibers as the general population (Fry et al, 2003a), so knowing this fact, since blacks have a lower proportion of type I muscle fibers as noted in Caeser and Hunter (2015), this explains why there are very few black power lifters: they have the opposite type II fiber type while having less type I fiber.

Furthermore, Olympic lifters also use a higher percentage of type IIa fibers (Fry et al, 2003b). This also explains the lower amount of blacks in weight lifting as well. Fiber types don’t explain everything, but at elite levels, they do mean a lot and looking at the racial variation explains racial differences in elite sporting competition.

Explaining racial differences in sprinting competitions is easy as well. Type IIx fibers combined with the ACTN3 gene=elite human performance (Mills et al, 2001). The gene ACTN3 was discovered to explain explosive power, and it just so happened to vary by race. William Saletan writes:

the relative frequency of the X allele is 0.52 in Asians, 0.42 in whites, 0.27 in African-Americans, and 0.16 in Africans. If you break out the data further, the frequency of the XX genotype is 0.25 in Asians, 0.20 in European whites, 0.13 in African-Americans, and 0.01 in African Bantu. Conversely, the frequency of RR (the genotype for speed and power) is 0.25 in Asians, 0.36 in European whites, 0.60 in African-Americans, and 0.81 in African Bantu. Among Asians, you can expect to find one RR for every XX. Among whites, you can expect nearly two RRs for every XX. Among African-Americans, you can expect more than four RRs for every XX.

This allele is responsible for explosive power. Explosive power is needed to excel in events such as sprinting, football, basketball and other sports where power is needed in short bursts. However, where blacks have an advantage in explosive power sports, the advantage is lost once events like swimming, power lifting (described above), Olympic lifting (differing fiber type) etc.

Conclusion

Racial differences in elite sporting competition come down to a lot of genetic factors, largely influenced by hormones, genes, and muscle fiber typing. Population variation between known fiber typings/hormones/genes that affect certain types of athletic performance explains a lot of the variation within, and especially between populations. Due to anatomical differences, blacks excel at some sports and suffer at others. The same also holds for whites; there is considerable variation in somatype, some somatypes are better for strongman/powerlifting competitions than others. These differences affect the outcomes of elite sporting competition as well.

Blacks have a higher amount of type II fibers, which accounts for a lot of their disease acquisition (Caesar et al, 2015). Due to this physiologic difference, this is why blacks excel at some sports, and not others.

Once again: Blacks are not stronger than whites.

(Note: Click here for discussion on Kenyan distance running.)

References

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

Fry, A. C., Webber, J. M., Weiss, L. W., Harber, M. P., Vaczi, M., & Pattison, N. A. (2003). Muscle Fiber Characteristics of Competitive Power Lifters. The Journal of Strength and Conditioning Research,17(2), 402. doi:10.1519/1533-4287(2003)017<0402:mfcocp>2.0.co;2

Fry, A. C., Schilling, B. K., Staron, R. S., Hagerman, F. C., Hikida, R. S., & Thrush, J. T. (2003). Muscle Fiber Characteristics and Performance Correlates of Male Olympic-Style Weightlifters. Journal of Strength and Conditioning Research,17(4), 746-754. doi:10.1519/00124278-200311000-00020

Mills, M., Yang, N., Weinberger, R., Vander Woude, D., Beggs, A., Easteal, S., & North, K. (2001). Differential expression of the actin-binding proteins, alpha-actinin-2 and -3, in different species: implications for the evolution of functional redundancy. Human Molecular Genetics,10(13), 1335-1346. doi:10.1093/hmg/10.13.1335

Muscular Strength By Gender and Race

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It’s a known fact that men are stronger, but how much stronger are we really than women? Strength does vary by race as I have covered here extensively. However, I took another look at the only paper that I can find in the literature on black/white strength on the bench press and found one more data point that lends credence to my theory on racial differences in strength.

Strength and gender

Men are stronger than women. No one (sane) denies this. There are evolutionary reasons for this, main reason being, women selected us for higher levels of testosterone, along with differences in somatype. Now, what is not known by the general public is just how much stronger the average man is compared to the average woman.

Miller et al (2008) studied the fiber type and area and strength of the biceps brachii and vastus lateralis in 8 men and 8 women. They were told to do two voluntary tests of strength, using elbow flexion (think biceps curl) and knee extension. (Note: I am assuming they are exercises similar to biceps curls and knee extension, as the authors write that they had custom-made equipment from Global Gym.) They also measured motor unit size, number, and activation during both movements.

The women had 45 percent smaller muscle cross-section area (CSA) in the brachii, 41 percent in the total elbow flexor, 30 percent in the vastus laterus, and 25 percent smaller knee extensors. The last point makes sense, since women have stronger lower bodies compared to their upper bodies (as you can see).

Men were significantly stronger in both upper and lower body strength. In the knee extension, women was 62 and 59 percent of male 1RM and maximal voluntary isometric contraction (MVC) respectively. As for elbow strength, women were 52 percent as strong as men in both 1RM and MVC. Overall, women were 70 and 80 percent as strong as men in the arms and the legs. This is attributed to either men’s bigger fibers or men putting themselves into more physical situations to have bigger fibers to be stronger (…a biological explanation makes more sense). However, no statistical difference between muscle fibers was found between gender, lending credence to the hypothesis that men’s larger fibers are the cause for greater overall upper-body strength.

The cause for less upper-body strength in women is due the distribution of women’s lean tissue being smaller. Women, as can be seen in the study, are stronger in terms of lower limb strength and get substantially weaker when upper-body strength is looked at.

Other studies have shown this stark difference between male and female strength. Men have, on average, 61 percent more total muscle mass than women, 75 percent more arm muscle mass, which translates approximately into a 90 percent greater upper body strength in men. 99.9 percent of females fall below the male mean, meaning that sex accounts for 70 percent of human variation in muscle mass and upper-body strength in humans (Lassek and Gaulin, 2009). Women select men for increased muscular size, which means increased testosterone, but this is hard to maintain so it gets naturally selected against. There is, obviously, a limit to muscle size and how many kcal you can intake and partition enough kcal to your growing muscles. However, women are more attracted to a muscular, mesomorphic phenotype (Dixson et al, 2009) so selection will occur by women for men to have a larger body type due to higher levels of testosterone.

Strength and race

The only study I know of comparing blacks and whites on a big three lift (bench pressing) is by Boyce et al (2014). They followed a sample of 13 white female officers, 17 black female officers, 41 black male officers and 238 white male officers for 12.5 years, assessing bench pressing strength at the beginning and the end of the study. The average age of the sample was 25.1 for the 41 black males and 24.5 for the 237 white males. The average age for the black women was 24.9 and the average for white women was 23.9. This is a longitudinal study, and the methodology is alright, but I see a few holes.

An untrained eye looking at the tables in the study would automatically think that blacks are stronger than whites at the end of the study. At the initial recruitment, the black mean weight was 187 pounds and they benched 210 pounds. They benched 1.2 times their body weight. Whites weighed 180 pounds and benched 185 pounds. They benched 1.02 times their body weight. Black women weighed 130 pounds at initial recruitment and benched 85 pounds, benching .654 times their body weight. White women weighed 127 pounds at initial recruitment and bench 82 pounds, benching .646 times their body weight. Right off the bat, you can see that the difference between black and white women is not significant, but the difference between blacks and whites is.

At the follow-up, the black sample weighed 224 pounds and benched 240 pounds while the whites weighed 205 pounds benching 215 pounds. Looking at this in terms of strength relative to body weight, we see that black males benched 1.07 times their body weight while whites benched 1.04 times their body weight. A very slight difference favoring black males. However, there were more than 5 times the amount of whites in comparison to blacks (41 compared to 238), so I can’t help but wonder if the smaller black sample compared to the white sample may have anything to do with it.

Black women weighed 150 pounds at the follow-up, benching 99 pounds while white women weighed 140 pounds benching 90 pounds. So black women benched .66 times their body weight while white women benched .642 times their body weight.

Another thing we have to look at is black body weight compared to bench press decreased in the 12 years while white body weight compared to bench press was diverging with the black bench press compared to body weight.

Furthermore, this study is anomalous as the both cohorts gained strength into their late 30s (testosterone begins to decline at a rate of 1-2 percent per year at age 25). It is well known in the literature that strength begins to decrease at right around 25 years of age (Keller and Englehardt, 2014).

Another pitfall is that, as they rightly point out, they used skin caliper measuring on the black cohort. It has been argued in the literature that blacks should have a different BMI scale due to differing levels of fat-free body mass (Vickery et al, 1988). Remember that black American men with more African ancestry are less likely to be obese, which is due to levels of fat-free body mass. Since fat-free mass is most likely skewed, I shouldn’t even look at the study. I do believe that black Americans should have their own BMI scale; they’re physiologically different enough from whites—though the differences are small—they lead to important medical outcomes. This is why race most definitely should be implemented into medical research. The authors rightly state that when further research is pursued the DXA scan should be used to assess fat-free body mass.

Unfortunately, the authors did not have access to the heights of the cohort due to an ongoing court case on the department for discrimination based on height. So, unfortunately, this is the only anthropometric value that could not be assessed and is an extremely important variable. Height can be used to infer somatype. Somatype can then be used to infer limb length. Longer limbs increase the ROM, in turn, decreaseing strength. The missing variable of height is a key factor in this study.

Finally, and perhaps most importantly, they assessed the strength of the cohort on a Smith Machine Bench Press.

  • The Smith Machine is set on a fixed range of motion; not all people have the same ROM, so assessing strength on a smith machine makes no sense.
  • To get into position for the Smith Machine, since the bar path is the same, you need to get in pretty much the same position as everyone else. I don’t need to explain the anatomical reasons why this is a problem in regards to testing a 1RM.
  • An Olympic bar weighs 45 pounds, but numerous Smith Machines decreases the weight by 10-20 pounds.
  • Since the individual is not able to stabilize the bar due to the machine, the chest, triceps, and biceps are less activated during the Smith Machine lift (Saeterbakken et al, 2011)

 

Due to all of these things wrong with the study, especially the Smith Machine bench press, it’s hard to actually gauge the true strength of the cohort. Depending on the brand, Smith Machines can decrease the load by 10-30 pounds. Combined with the unnatural, straight-line bar path of the movement, it’s not ideal for a true strength test.

Conclusion

Gender differences in strength have a biological basis (obviously) and are why women shouldn’t be able to serve in the military and transgendered people shouldn’t be able to compete with ‘the gender they feel that they are’ (coming in the future).

The more interesting topic is the one on racial differences in strength. The untrained eye may read that paper and walk away assuming that the average black person is somehow stronger than the average white person. However, this study is anomalous since the cohort gained strength into their 30s when the literature shows otherwise. The biggest problem with the study is the Smith Machine bench press. It is not a natural movement and decreases muscle activation in key areas of the chest and triceps which aid in power while doing a regular bench press. Due to this, and the other problems I pointed out, I can’t accept this study.

Of course, height not being noted is not the fault of the researchers, but more questions would be answered if we knew the heights of the officers—which is an extremely critical variable. White males also gained more lean mass over the course of the study compared to blacks—47 percent and 44 percent respectively—which, as I pointed out, is anomalous.

There is more to HBD than IQ differences. I contend that somatype differences between the races are much more interesting. I will be writing about that more in the future.

Furthermore, for anyone with any basic physiology and anatomy knowledge, they’d know that different leverages affect strength. The races differ in somatype on average and thusly have different leverages. This is one out of many reasons why there are racial differences in strength and elite sports. Leverages and muscle fiber typing.

My points on racial differences in strength still hold; the anthropmetric data backs me upelite sporting events back me up. My theory as a whole to racial differences in sports is sound, and this study does nothing to make me think twice about it. There are way too many confounds for me to even take it seriously when reevaluating my views on racial differences in strength. This study was garbage to assess absolutely strength due to the numerous things wrong with it. I await a more robust study with actual strength exercises, not one done on an assisted machine.

References

Boyce, R. W., Willett, T. K., Jones, G. R., & Boone, E. L. (2014). Racial Comparisons in Police Officer Bench Press Strength over 12.5 Years. Int J Exerc Sci 7 (2), 140-151.

Dixson, B. J., Dixson, A. F., Bishop, P. J., & Parish, A. (2009). Human Physique and Sexual Attractiveness in Men and Women: A New Zealand–U.S. Comparative Study. Archives of Sexual Behavior,39(3), 798-806. doi:10.1007/s10508-008-9441-y

Keller K, Engelhardt M. Strength and muscle mass loss with aging process. Age and strength loss. MLTJ. 2013;3(4):346–350.

Lassek, W. D., & Gaulin, S. J. (2009). Costs and benefits of fat-free muscle mass in men: relationship to mating success, dietary requirements, and native immunity. Evolution and Human Behavior,30(5), 322-328. doi:10.1016/j.evolhumbehav.2009.04.002

Miller, A. E., Macdougall, J. D., Tarnopolsky, M. A., & Sale, D. G. (1993). Gender differences in strength and muscle fiber characteristics. European Journal of Applied Physiology and Occupational Physiology,66(3), 254-262. doi:10.1007/bf00235103

Saeterbakken, A. H., Tillaar, R. V., & Fimland, M. S. (2011). A comparison of muscle activity and 1-RM strength of three chest-press exercises with different stability requirements. Journal of Sports Sciences,29(5), 533-538. doi:10.1080/02640414.2010.543916

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

Female Mate Preference and Somatypes

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PumpkinPerson’s most recent article Are muscular guys genetically inferior? is a joke. He makes huge assumptions and attempts to this ‘social experiment’ as evidence that women find ‘nerds’ more attractive. The logic here is that since East Asians are the ‘most evolved’ race and (in his world) they have the least testosterone along with the highest intelligence, that this is some kind of apex of human evolution. However the conclusions he makes off of this one video are very erroneous and I will explain why.

PP writes:

They are simply genetically inferior because the muscular body type branched off the evolutionary tree pre-maturely.

…No idea what he’s talking about. No source that the ‘muscular body type branched off the evolutionary tree prematurely.’ This is just an assumption because Africans supposedly have higher testosterone than both Europeans and East Asians, except East Asians have the highest testosterone out of all of all three traditional races, not Africans.

After watching this video I feel like starving my muscles off (not that I recommend that).

Good luck with that.

I realize not everyone agrees with the progressive model of evolution, but real scientists do. For example, check out this phys.org article:

This article has nothing to do with progressive evolution at all. In fact, this article is basically a summary of Full House (Gould, 1996) in which Gould argues that since life began at the left wall of complexity—where no organism can get simpler—that a right-tail distribution of complexity was inevitable. I have covered this here.  This is not evidence for progressive evolution. It is, in fact, the opposite. He’s never read Gould’s books so he wouldn’t know that.

Now, PP’s contention that women find nerds more attractive has no basis. When I think of a ‘nerd’, I think of a scrawny pencil-neck, buck teeth, person with thick-rimmed black glasses. This, obviously, isn’t true. If it were, then why do East Asians—Japan specifically—have the lowest birthrates? Of course, social factors have a lot to do with it—birthrates decline in developed countries (Nargund, 2009; Sinding, 2009), as well as genetic ones (Harris and Nielson, 2016). So, clearly, the more intelligent, more developed countries don’t have more children, which then, of course implies that either higher IQ people are less desirable from a reproductive point of view (plausible), or they forgo having children until around 28 years of age (Lange, Rinderu and Bushman, 2016). Whatever the case may be, those with higher IQs do not conceive as many children as those with lower IQs, signifying something about their fitness aspects.

Further, women, evolutionarily speaking, sexually selected men for high levels of testosterone, which leads to bigger muscles, more defined facial features, higher levels of aggression (good for protecting genetic interests) and so on. The fact that some people may think that nerds have better prospects than non-nerds, evolutionarily speaking, had no basis in reality and for one to believe as much, it has to be driven by ideology.

Dixson et al (2010) showed that women prefer men with the mesomorphic somatype and ‘average’ body type, then prefer ectomorphs (a skinnier body type) and finally endomorph (a heavier build) ranging from most attractive to least. This study shows that, at least when it comes to European females, they prefer mesomorphic somatypes, which, more often than not, one who is over 6 feet tall will have. Does that seem like a ‘nerd’ to you? I don’t think so. Someone who has the potential ability to control a room with his presence doesn’t seem like a nerd to me. These are the same people who are CEOs.

Journalist Malcolm Gladwell showed that on average, CEOs averaged just under 6 foot tall. Since the average American is 5 foot 9, the average CEO has a three-inch height advantage over the average man in America. However, when looking at those who are 6 feet tall and up, for average Joe the percentage is a paltry 3.9 percent while, in Gladwell’s sample, 30 percent were over 6’2″. So, Gladwell states, the lack of minorities and women in high positions has a plausible explanation: height. Men are, on average taller than women. Tall men earn more money than their shorter counterparts. Taller children also perform better on cognitive tests, taller men earn more money in Mexico, and taller children do better on learning tests in India (Lawson and Spears, 2016).

Women want taller men more than men want taller women (Stulp, Buunk, and Pollet, 2012). Tall men are also more likely to have a mesomorphic somatype. Those somatypes are seen as the most attractive. Does that seem like a nerd somatype to you? An athletic somatype? On the other hand, women aren’t attracted to short men (Nettle, 2002). East Asians—the so-called ‘most evolved race’—are the shortest race. Doesn’t look too good for them.

Furthermore, while East Asian men see themselves as attractive and dateable, they don’t believe society sees it that way. Forty-six percent of the sample said they could recall one instance where they hear someone state that they do not date Asian men, while eleven percent of Asian men have heard it at least six times. For Okcupid’s 2009 race/dating data, 18 percent of Asian women (3,381 yes) would date someone of their own background/skin color while 82 percent (17,227) wouldn’t! So much for the ‘most evolved’ race having dating prospects in their own race. East Asian men said yes to the question at a rate of 24 percent (7,965 yes) and no 76 percent of the time (25,358).

To further put this into perspective, white women would said yes to the question at a rate of 54 percent (154,595) and no at a rate of 46 percent (132,497) while white men said yes at a 40/60 yes/no rate (183,360/277,827 respectively). In total, 45 percent of whites would prefer to date someone of their skin color/ethnicity while 55 percent wouldn’t (337,955/410,324) while non-whites said yes to the question 20 percent of the time while they said no 80 percent of the time (56,080/222,484).

A 2014 follow-up found the same thing, however with Asian women showing some positive ratings toward Asian males (while all races of men didn’t find black women particularly attractive). However, Asian men were seen as the least attractive throughout the whole sample. Asian males are also seen as less attractive than males of other races (Fisman et al, 2008). In their sample, they found even after running regressions that Asian women found white, black, and ‘Hispanic’ men. They also show that even Asian men find white, black and ‘Hispanic’ females more attractive than Asian females.

In sum, PP’s contentions and reaches in his article are wrong. ‘Nerds’ (in the way I’m defining the word) are not more successful than the alpha CEOs who are over 6’2”. PP seems to have an aversion to testosterone (believes that it is the cause for racial differences in prostate cancer differences, but vitamin D deficiencies are a more likely culprit). East Asian men—the so-called ‘most evolved’ men of the ‘most evolved’ race do not fair well in terms of physical attractiveness, and this may be a reason why the Japanese birthrate is declining, with the average Japanese woman having only one child during her lifetime (Nomura and Koizumi, 2016). PP’s theory makes no sense, because women favor mesomorphic somatypes. Mesomorphs are more likely to be CEOs of 500 companies, more likely to be more cognitively adept and make more money than their shorter counterparts. Making evolutionary theories off of one (obviously fake) ‘social experiment’ is ridiculous. East Asian men, the so-called ‘most evolved man’ fall short in the dating game, due to being seen as less attractive.

References

Dixson, B. J., Dixson, A. F., Bishop, P. J., & Parish, A. (2009). Human Physique and Sexual Attractiveness in Men and Women: A New Zealand–U.S. Comparative Study. Archives of Sexual Behavior,39(3), 798-806. doi:10.1007/s10508-008-9441-y

Fisman, R. J., Iyengar, S. S., Kamenica, E., & Simonson, I. (2008) (n.d.). Racial Preferences in Dating: Evidence from a Speed Dating Experiment. SSRN Electronic Journal. doi:10.2139/ssrn.610589

Gould, S. J. (1996). Full house: The Spread of Excellence from Plato to Darwin. New York: Harmony Books.

Harris, K., & Nielsen, R. (2016). The Genetic Cost of Neanderthal Introgression. Genetics, 2016 doi:10.1101/030387

Lange, P. A., Rinderu, M. I., & Bushman, B. J. (2016). Aggression and Violence Around the World: A Model of CLimate, Aggression, and Self-control in Humans (CLASH). Behavioral and Brain Sciences, 1-63. doi:10.1017/s0140525x16000406

Nargund G. (2009) Declining birth rate in Developed Countries: A radical policy re-think is required. F.V & V in ObGyn. 2009;1:191-3

Nettle, D. (2002). Women’s height, reproductive success and the evolution of sexual dimorphism in modern humans. Proceedings of the Royal Society B: Biological Sciences,269(1503), 1919-1923. doi:10.1098/rspb.2002.2111

Nomura, K., & Koizumi, A. (2016). Strategy against aging society with declining birthrate in Japan. Industrial Health INDUSTRIAL HEALTH,54(6), 477-479. doi:10.2486/indhealth.54-477

Sinding S.(2009) Population, poverty and economic development. Phil. Trans. R. Soc. B 364.

Stulp, G., Buunk, A. P., & Pollet, T. V. (2013). Women want taller men more than men want shorter women. Personality and Individual Differences,54(8), 877-883. doi:10.1016/j.paid.2012.12.019

Psychology, Anti-Hereditarianism, and HBD

3800 words

Abstract

The denial of human nature is extremely prevalent, most noticeably in our institutions of higher learning. To most academics, the fact that there could be population differences that are genetic in nature is troubling for many people. However, denying genetic/biological causes for racial differences is 1) intellectually dishonest; 2) will lead to negative health outcomes for populations due to the assumption that all human populations are the same; and 3) the ‘lie of equality’ will not allow all human populations to reach their ‘potential’ to be as good as they can be due to the fact that implicit assumption that all human populations are the same. Anti-hereditarians fully deny any and all genetic explanations for human differences, believing that human brain evolution somehow halted around 50-100 kya. Numerous studies show that race is a biological reality; it doesn’t matter what we call the clusters as those are the social constructs. The contention is that ‘all brains are the same color’ (Nisbett, 2007; for comment see my article Refuting Richard Nisbett), and that evolution in differing parts of the world for the past 50,000 years was not enough for any meaningful population differences between people. But to accept that means you must accept the fact that the brain is the only organ that is immune to natural selection. Does that make any sense? I will show that these differences do exist and should be studied, as free of any bias as possible, with every possible hypothesis being looked at and not discarded.

Evolution is true. It’s not ‘only a theory’ (as some anti-evolutionists contend). Anti-evolutionists do not understand the definition of the word ‘theory’. Richard Dawkins (2009) wrote that a theory is a scheme or system of ideas or statements held as an explanation or account of a group of facts or phenomena. This is in stark contrast to the layperson’s definition of the word theory, which means ‘just a guess’. Evolution is a fact. What biologists argue with each other about is the mechanisms behind evolution, for any quote-mining Creationists out there.

We know that evolution is a fact and it is the only game in town (Dawkins, 2009) to explain the wide diversity and variation we see on our planet. However, numerous scholars deny the effect of evolution on human behavior (most residing in the social sciences, but other prominent biologists have denied (or implied there were no differences between us and our ancestors) the effect of human evolution on behavior and cognition; Gould 1981, 1996, for a review of Gould 1996, see my article Complexity, Walls, 0.400 Hitting and Evolutionary “Progress” and Stephen Jay Gould and Anti-Hereditarianism; Mayr 1963; see Cochran and Harpending 2009). A prominent neuroscientist, who I have written about here, Herculano-Houzel, implied that Neanderthals and Antecessor may have been just as intelligent as we are due to a neuronal count in a similar range to ours (Herculano-Houzel 2013). This raises an interesting question (which I have tackled here and will return to in the future): did our recent hominin ancestors at least have the capacity for similar intellect to ours (Villa and Roebroeks, 2014; Herculano-Houzel and Kaas, 2011)? It is interesting that neuronal scaling rules hold for our extinct ancestors, and this question is most definitely worth looking into.

Whatever the case may be in regards to recent human evolution and our extinct hominin ancestors, human evolution has increased in the past 10,000 years (Cochran and Harpending, 2009; Wade, 2014). This is due to the dispersal of Anatomical Modern Humans (AMH) OoA around 70 kya; and with this geographical isolation, populations began to diverge with no interbreeding with each other. However, this is noticed most in ‘Native’ Americans, who show no gene flow with other populations due to being genetically isolated (Villena et al, 2000). Who’s to say that evolution stops at the neck, and no further evolution occurs on the brain? Is the brain itself exempt from the laws of natural selection? We know that there is no/hardly any gene flow between populations before the advent of modern-day technology and vehicles; we know that humans differ on morphological and anatomical traits, why are genetic differences out of the question, especially when genetic differences may explain, in part, some of the variation between populations?

We know that evolution is true, without a reasonable doubt. So why, do some researchers contend, is the human brain exempt from such selective pressures?

A theoretical article by Winegard, Winegard, and Boutwell (2017) was just released on January 17th. In the article, they argue that social scientists should integrate HBD into their models. Social scientists do not integrate genetics into their models, and the longer one studies social sciences, the more likely it is they will deny human nature, regardless of political leaning (Perry and Mace, 2010). This poses a problem. By completely ignoring a huge variable (possible genetic differences), this has the potential to harm people’s health, as race is a very informative marker when discussing diseases acquisition as well as whether certain drugs will work on two individuals of different races (Risch et al, 2002; Tang et al, 2005; Wade, 2014). People who deny the usefulness of race, even in a medical context, endanger the lives of individuals from different races/ethnies since they assume that all humans are the same inside, despite ‘superficial differences’ between populations.

The notion that all human populations—genetic isolation and evolution in differing ecosystems/climates/geographic locales be damned—is preposterous to anyone who has a true understanding of evolution. Why should man’s brain be the only organ on earth exempt from the forces of natural selection? Why do egalitarians assume that all humans are the same and have the same psychological faculties compared to other humans, despite the fact that rapid evolution has occurred within the human species within the last 10,000 years?

To see some of the most obvious ways to see natural selection in action in human populations, one should look to the Inuits (Fumagalli, 2015; Daanen and Lichtenbelt, 2016; NIH, 2015; Cardona et al, 2014; Tishkoff, 2015; Ford, McDowell, and Pierce, 2015; Galloway, Young, and Bjerregaard, 2012; Harper, 2015). Global warming is troubling to some researchers, with many researchers suggesting that global warming will have negative effects on the health and food security of the Inuit (Ford et al, 2014, 2016; Ford, 2012, 2009; Wesche, 2010; Furgal and Seguin, 2006; McClymont and Myers, 2012; Petrasek et al, 2015; Rosol, Powell-Hellyer, and Chan, 2016; Petrasek, 2014; WHO, 2003). I could go on and on citing journal articles for both claims, but you get the point already. The main point is this: we know the Inuit have evolved for their climate, and a (possible) climate change would then have a negative effect on their quality of life due to their adaptations to the cold weather climate. However, egalitarians still contend, with these examples and numerous others I could cite, that any and all differences within and between human populations can be explained by socio-cultural factors and not any genetic ones.

One of the best examples of genetic isolation in a geographic locale that is the complete opposite from the environment of evolutionary adaptedness (EEA; Kanazawa, 2004), the African savanna in which we evolved in. I did entertain the idea of the Savanna hypothesis, and while I do believe that it could explain a lot of the variance in IQ between countries (Kanazawa, 2007), his hypothesis doesn’t make sense with what we know about human evolution over the past 10,000 years.

The most obvious differences we can see between populations is differences in skin color. Skin color does not signify race, per se, but it is a good indicator. Skin color is an adaptation to UV radiation (Jablonski and Chaplin, 20102000; Juzenienne et al, 2009; Jeong and Rienzo, 2015; Hancock, et al, 2010; Kita and Fraser, 2016; Scheinfeldt and Tishkoff, 2013), and is therefor and adaptation based on climate. Dark skin is a protectant from skin cancer (Brenner and Hearing, 2008; D’Orazio et al, 2010; Bradford, 2009). Skin cancer is a possible selective force in black pigmentation of the skin in early hominin evolution (Greaves, 2014). With these adaptations in skin color between genetically and geographically isolated populations, are changes in the brain, however small, really out of the question?

A better population to bring up in regards to geographic isolation having an effect on human evolution is the Tibetans. For instance, Tibetans have higher total lung capacities in comparison to the Han Chinese (Droma et al, 1991). There are even differences in lung capacity between Tibetans and Han Chinese who live at the same altitude (Yangzong et al, 2013), with the same thing noticed for peoples living in the Andean mountains (Beall, 2007). Tibetans evolved in a higher elevation than the Han Chinese who lived closer to sea level, so it makes sense that they would be selected for the ability to take deeper inhales They also have a larger chest circumference and greater capacity than the Han Chinese who live at lower altitudes (Gilbert-Kawai et al, 2014).

Admittedly, the acceptance of the usefulness of race in regards to human differences is a touchy subject. So much so, that social scientists do not take genetics into account in their models. However, researchers in the relevant fields accept the usefulness of race (Risch et al, 2002; Tang et al, 2005; Wade, 2014; Sesardic, 2010), so the fact that social scientists do not is to be ignored. Race is a social construct, yes. But no matter what we call these clusters, clines, demes, races, ethnies—whatever name you want to use to describe them—this does not change the fact that race is a useful category in biomedical research. Race is an issue when talking about bone marrow transplants, so by treating all populations as the same with no variation between them, people are pretty much saying that differences between people in a biomedical context do not exist, with there being other explanatory factors behind population differences, in this case, bone marrow transplants. Ignoring heritable human variation will lead to disparate health outcomes for all human populations with the assumption that all humans are the same. Is that what we want? Is that what race-deniers want?

So there are anatomical and physiological differences between human populations (Wagner and Hayward, 2000), with black Americans having a different morphology and lower fat-free body mass on average in comparison to white Americans. This, then, is one of the variables that dictates racial differences in sports, along with muscle fiber explaining a large portion of the variance, in my opinion. No one denies that blacks and whites differ at elite levels in baseballfootballswimming and jumping, and bodybuilding and strength sports. Though, accepting the fact that these morphological and anatomical differences between the races come down to evolution, one would then have to accept the fact that different races/ethnies differ in the brain, thusly destroying their egalitarian fantasy in their head of all genetically isolated human populations being the same in the brain. Wade (2014) writes on page 106:

“… brain genes do not lie in some special category exempt from natural selection. They are as much under evolutionary pressure as any other category of gene”

This is a hard pill to swallow for race-deniers, especially those who emphatically deny any type of selection pressure on the human brain within the past 10,000 to 100,000 years.

Winegard, Winegard, and Boutwell (2017) write:

Consider an analogy that might make this clear while simultaneously illuminating the explanatory importance of population differences. Most cars are designed from the same basic blueprint and consist of similar parts—an internal combustion engine, a gas tank, a chassis, tires, bearings, spark plugs, et cetera. Cars as distinct as a Honda Civic and a Subaru Outback are built from the same basic blueprint and comprised of the same parts; so, in this sense, there is a “universal car nature” (Newton 1999). However, precise, correlated changes in these parts can dramatically change the characteristics of a car.

Humans, like cars, are built from the same basic body plan. They all have livers, lungs, kidneys, brains, arms, and legs. And these structures are built from the same basic building blocks, tissues, which are built of proteins, which are built of amino acids, et cetera. However, small changes in the structures of these building blocks can lead to important and scientifically meaningful differences in function.

Put in this context, yes, there is a ‘universal human nature’, but the application of that human nature will differ depending on what a population has to do to survive in that climate/ecosystem. And, over time, populations will diverge away from each other, both physically and mentally. The authors also argue that societal differences between Eurasians (Europeans and East Asian) can be explained partly by genetic differences. Indeed, the races do differ on the Big Five Personality traits, with heritable components explaining 40 to 60 percent of the variation (Power and Pluess, 2015). So some of the cultural differences between European and East Asians must come down to some biological variation.

One of the easiest ways to see the effects of cultural/environmental selective pressures in humans is to look at Ashkenazi Jews (Cochran et al, 2006). Due to Ashkenazi Jews being barred from numerous occupations, they were confined to a few cognitively demanding occupations. Over time, only the Jews that could handle these occupations would prosper, further selecting for higher intelligence due to the cognitive demands of the jobs they were able to acquire. Thus, Ashkenazi Jews who could handle the few occupations they were allowed to do would breed more and pass on variants for higher intelligence to their offspring, whereas those Jews who couldn’t handle the cognitive demands of the occupation were selected out of the gene pool. This is one situation in which natural selection worked swiftly, and is why Ashkenazi Jews are so overrepresented in the fields of academia today—along with nepotism.

Winegard, Winegard, and Boutwell (2017) lay out six basic principles for a new Darwinian paradigm, as follows:

  1. Variation is the grist for the mill of natural selection and is ubiquitous within and among human populations.
  2. Evolution by natural selection has not stopped acting on human traits and has significantly shaped at least some human traits in the past 50,000 years.
  3. Current hunter-gatherer groups might be slightly different from other modern human populations because of culture and evolution by natural selection acting to influence the relative presence, or absence, of trait-relevant alleles in those groups. Therefore, using extant hunter-gatherers as a template for a panhuman nature is problematic.
  4. It is probably more accurate to say that, while much of human nature is universal, there may have been selective tuning on various aspects of human nature as our species left Africa and settled various regions of the planet (Frost 2011).
  5. The human brain is subject to selective forces in the same way that other organ systems are. Natural selection does not discriminate between genes for the body and genes for the brain (Wade 2014).
  6. The concept of a Pleistocene-based environment of evolutionary adaptedness (EEA) is likely unhelpful (Zuk 2013). Individual traits should be explored phylogenetically and historically. Some human traits were sculpted in the Pleistocene (or before) and have remained substantially unaltered; some, however, have been further shaped in the past 10,000 years, and some probably quite recently (Clark 2007). It remains imperative to describe what selection pressures might have been actively shaping human nature moving forward from the Pleistocene epoch, and how those ecological pressures might have differed for different human populations.

No stone should be left unturned when attempting to explain population differences between geographically isolated peoples, and these six principles are a great start, which all social scientists should introduce into their models.

As I brought up earlier, Kanazawa’s (2004b) hypothesis doesn’t make sense in regards to what we know about the evolution of human psychology. Thus, any type of proposed evolutionary mismatch in regards to our societies do not make much sense. However, one mismatch that does need to be looked into is the negative mismatch we have with our modern-day Western diets. Agriculture was both a gift and a negative event in human history. Yes, without the advent of agriculture 10,000 years ago we would not have the societies we have today. However, on the other hand, we have higher rates of disease compared to our hunter-gatherer ancestors. This is one evolutionary mismatch that cannot and should not go ignored as it has devastating effects on our populations that consume a Western diet—which we did not evolve to eat.

Winegart, Winegart, and Boutwell (2017) then discuss how their new Darwinian paradigm could be used by researchers: 1) look for differences among human populations; 2) after population differences are found, causal analyses should be approached neutrally; 3) researchers should consider a broad range of data to consider whether or not the trait or traits in question are heritable; and 4) researchers should test the posited biological cause more indepth. Without understanding—and using—biological differences between human populations, the quality of life for some populations will be diminished, all for the false notion of ‘equality’ between human races.

There are huge barriers in place to studying human differences, however. Hayden (2013) documents differing taboos in genetics, with intelligence having a high taboo rating. Of course, we HBDers know that intelligence is a highly heritable trait, largely genetic in nature, and so studying these differences between human populations may lead to some uncomfortable truths for some people. On the 200th anniversary of Darwin’s On the Origin of Species, Ceci and Williams (2009) said that “the scientific truth must be pursued” and that researchers must study race and IQ, much to the chagrin of anti-hereditarians (Horgan, 2013). He does write something very troubling in regards to this research, and free speech in our country as a whole:

Some readers may wonder what I mean by “ban,” so let me spell it out. I envision a federal prohibition against speech or publications supporting racial theories of intelligence. All papers, books and other documents advocating such theories will be burned, deleted or otherwise destroyed. Those who continue espousing such theories either publicly or privately (as determined by monitoring of email, phone calls or other communications) will be detained indefinitely in Guantanamo until or unless a secret tribunal overseen by me says they have expressed sufficient remorse and can be released.

Whether he’s joking or not, that’s besides the point. The point is, is that these topics are extremely sensitive to the lay public, and with these articles being printed in popular publications, the reader will get an extremely biased look into the debate and their mind will already be made up for them. This is the definition of intellectual dishonesty, attempting to sway a lay-readers’ opinion on a subject they are ignorant of with an appeal to emotion. Shouldn’t all things be studied scientifically, without any ideological biases?

Speaking about the ethics of putting this information out to the general public, Winegard, Winegard, and Boutwell (2017) write:

If researchers do not responsibly study and discuss population differences, then they leave an abyss that is likely to be filled by the most extreme and hateful writings on population differences. So, although it is understandable to have concerns about the dangers of speaking and writing frankly about potential population differences, it is also important to understand the likely dangers of not doing so. It is not possible to hide the reality of human variation from the world, not possible to propagate a noble lie about human equality, and the attempt to do so leaves a vacancy for extremists to fill.

This is my favorite quote in the whole paper. It is NOT possible to hide the reality of HBD from the world; anyone with eyes can see that humans do differ. Attempting to continue the feel-good liberal lie of human equality will lead to devastating effects in all countries/populations due to the implicit assumption that all human groups are the same in their cognitive and mental faculties.

The denial of genetic human differences, could, as brought up earlier in this article, lead to negative effects in regards to health outcomes between populations. Black Americans have higher rates of hypertension than white Americans (Fuchs, 2011; Ferdinand, 2007; Ortega, Sedki, and Nayer, 2015; Nesbitt, 2009; Wright et al, 2005). To overlook possible genetic differences as a causal factor in regards to racial differences will mean the deaths of many people since people truly believe that people are the same and that all differences come down to the environment. This, however, is not true and believing so is extremely dangerous to the health of all populations in the world.

Epigenetic signatures of ethnicity may be biomarkers for shared cultural experiences. Seventy-six percent of the genetic alteration between Mexicans and Puerto Ricans in this study was due to DNA methylation—which is an epigenetic mechanism used by cells to control gene expression. Therefore, 24 percent of the effect is due to an unknown factor, probably regarding environmental, social, and cultural differences between the two ethnies (Galanter et al, 2017). This is but one of many effects that culture can have on the genome, leading to differences between two populations, and is good evidence for the contention that the different races/ethnies evolved different psychological mechanisms due to genetic isolation in different environments.

We must now ask the question: what if the hereditarian hypothesis is true (Gottfredson, 2005)? If the hereditarian hypothesis is true, Gottfredson argues, special consideration should be given to those found to have a lower IQ, with better training and schooling that specifically target those individuals at risk to be less able due to their lower intelligence. This is one way the hereditarian hypothesis can help race relations in the country: people will (hopefully) accept intrinsic differences between the races. What Gottfredson argues in her paper will hopefully then pacify anti-hereditarians, as less able people of all races/ethnicities will still get the extra help they need in regards to finding work and getting schooling/training/jobs that accommodate their intelligence.

Conclusion

People accept genetic causes for racial differences in sports, yet emphatically deny that human races/ethnies differ in the brain. The denial of human nature—racially and ethnically—is the next hurdle for us to jump over. Once we accept that these differences in populations can, in part, be explained by genetic factors, we can then look to other avenues to see how and why these differences exist between populations occur and if anything can be done to ameliorate them. However, ironically, anti-hereditarians do not realize that their policies and philosophy is actively hindering their goals, and by accepting biological causes—if only to see them researched and held against other explanations—will lead to further inequality, while they scratch their heads without realizing that the cause is the one variable that they have discarded: genetics. Still, however, I see this won’t happen in the future and the same non-answers will be given in response to findings on how the human races differ psychologically (Gottfredson, 2012). The races do differ in biologically meaningful ways, and denying or disregarding the truth will not make these differences disappear. Social scientists must take these differences into account in their models, and seriously entertain them like any other hypothesis, or else they will never fully understand human nature.

Why Are Men Attracted To Low Waist-to-Hip Ratios?

3050 words

Why are men attracted to low waist-to-hip ratios (WHR)? Like with a lot of our preferences, there is an evolutionary reason why men are attracted to low WHR. I came across a paper the other day by M.D. William Lassek, “Assistant Professor of Epidemiology and Research Associate in the department of Anthropology at the University of California, Santa Barbara” and co-author P.h.D. Steven Gaulin, Professor of Anthropology with specific research interests in “evolutionary psychology, cognitive adaptations, the human voice, sexual selection, evolution of sex differences, lipid metabolism and brain evolution.” This paper fascinates me because it talks about the evolution of human intelligence through a lens of nutrition and micronutrients, something that I’m well-read on due to my career. First, I will discuss the benefits of fish oil and the main reason for taking them: omega-3 fatty acids and DHA. Then I will discuss the WHR/intelligence theory.

Fish Oils, DPA/EPA, and Omega-3 Fatty Acids

Misinformation about fish oils is rampant, specifically in the HBD-sphere, specifically with Steve Sailer’s article HBD and Diet AdviceThe study he cites (with no reference)  I assume is this study by Yano et al (1978) in which they found that Japanese men who ate more carbohydrates had less of a chance to die of cardiovascular heart disease (CHD). He says that the first generation ate mostly rice and no fat while the second generation “ate cheeseburgers and had higher rates of coronary disease than their parents.” He then says that these diet recommendations (low-fat, high-carb) were put onto all populations with no proven efficacy for all ethnies/racial groups. These diet recommendations began around two decades before the 80s, however.

He then quotes an article by the NYT science write, Carl Zimmer, talking about how the Inuit study has “added a new twist to the omega-3 fatty acid story”. Now, I read papers on nutrition every day due to my career, I don’t know what kind of literature they read on the subject, but fish oil, more specifically DPA/EPA and omega-3s are hugely important for optimal brain growth, health, and function.

Controlled studies clearly show that omega-3 consumption had a positive influence on n-3 (fatty acid) intake. N-3 has also been recognized as a modulator of inflammation as well as the fact that omega-3 fatty acids down-regulate genes involved in chronic inflammation, which show that n-3 is may be good for atherosclerosis.

An increase in omega-3 consumption leads to decreased damage from heart attacks.

Omega-3 may also reduce damage after a stroke.

Dietary epidemiology has also shown a link between n-3 and mental disorders such as Alzheimers and depression. N-3 intake is also linked to intelligence, vision and mood. Infants who don’t get enough n-3 prenatally are at risk for developing vision and nerve problems. Other studies have shown n-3’s effects on tumors, in particular, breast, colon and prostate cancer.

Omega-3’s are also great for muscle growth. Omega-3 intake in obese individuals along with exercise show a speed up in fat-loss for that individual.

Where do these people get their information from? Not only are omega-3’s good for damage reduction after a stroke and a heart attack, they’re also good for muscle growth, breast, colon and prostate tumor reduction, infants deficient in omega-3 prenatally are at risk for developing nerve and vision problems. Increase in omega-3 consumption is also linked to increases in cognition, reduces chronic inflammation and is linked to lower instances of depression.

Clearly, fish oils have a place in everyone’s diet, not only Inuits’.

This also reminds me of The Alternative Hypothesis’s argument that there are differing CHO metabolisms based on geographic origin (not true, to the best of my knowledge).

WHR and Intelligence

Most of the theories of the increase in brain size and intelligence have to do with climate, in one way or another, along with sexual selection. Though recently, I’ve been rethinking my position on cold winters having that big of an effect on intelligence due to some new information I’ve come across. The paper titled Waist-hip ratio and cognitive ability: is gluteofemoral fat a privileged store of neurodevelopmental resources? by Lassek and Gaudin (2008) posits a very sensible theory about the evolution of human intelligence: mainly that men prefer hour-glass figures due to an evolutionary adaptation.

Why may this be the case? One of the most important reasons I can think of is that women with high WHR have a higher chance of rate of death. The Nurses Health Study followed 44,000 women for 16 years and found that women who had waists bigger than 35 inches had a two times higher risk of dying from heart disease when compared to women with the lowest waist size of less than 28 inches. Clearly, men prefer women with low WHR since they will live longer, conceive more children and be around longer to take care of said children. So while a low WHR is not correlated with fertility per se, it is correlated with longevity, so the woman can have more children to spread more of her genes.

Lassek and Gaulin also bring up the ‘thrifty gene hypothesis’, which states that these genes evolved in populations that experienced nutritional stress, i.e., famines. I’ve read a lot of books on nutrition and human evolution (I highly recommend The Story of the Human Body: Evolution, Health, and Diseaseover the years and most of them discredit the idea of the thrifty gene hypothesis. However, recent research has shown the existence of these ‘thrifty genes’ in populations such as the Samoans and ‘Native’ Americans. It’s simple, really. Stop eating carbohydrates and the problems will fade away. (Hunter-gatherers don’t have these disease rates that we do in the West; it’s clear that the only difference is our diet and lifestyle. I will cover this in a future post titled “Diseases of Civilization”.)

Lassek and Gaulin pursued the hypothesis that gluteofemoral fat (fat stored in the thighs and buttocks) was the cause for the difference in the availability of neurodevelopmental nutrients available to a fetus. If correct, this could show why men prefer women with a low WHR and could show why we underwent such rapid brain growth: due to the availability of neurodevelopmental nutrients in the mother’s fat stores. Gluteofemoral body fat is the main source of long-chain polyunsaturated fatty acids (LPUFA) for children, along with another pertinent nutrient for fetal development: DHA. Lassek and Gaulin also state that 10 to 20 percent of the fat stored by a young woman during puberty is gluteofemoral fat, obviously priming her for childbearing. Even with caloric restriction, the gluteofemoral fat is not tapped utilized until late pregnancy/lactation when the baby needs nutrients such as DPA/EPA and omega-3s.

Further, 10 to 20 percent of the dry weight of the brain is made up of LCPUFA, which shows how important this one nutrient is for proper brain development in-vitro as well as the first few years of life. Lassek and Gaulin state:

A recent meta-analysis estimates that a child’s IQ increases by 0.13 point for every 100-mg increase in daily maternal prenatal intake of DHA (Cohen, Bellinger, Connor, & Shaywitz, 2005), and a recent study in England shows a similar positive relationship between a mother’s prenatal consumption of seafood (high in DHA) and her child’s verbal IQ (Hibbeln et al., 2007).

Along with what I cited above about these nutrients and their effects on our bodies while we’re in our adolescence and even adulthood, this is yet another huge reason WHY we should be consuming more fish oils, not only for the future intelligence of our offspring, but for our own brain health as a whole. Lassek and Gaulin state on pg. 3:

Each cycle of pregnancy and lactation draws down the gluteofemoral fat store deposited in early life; in many poorly nourished populations, this fat is not replaced, and women become progressively thinner with each pregnancy, which is termed “maternal depletion” (Lassek & Gaulin, 2006). We have recently shown that even well-nourished American women experience a relative loss of gluteofemoral fat with parity (Lassek & Gaulin, 2006). In parallel, parity is inversely related to the amount of DHA in the blood of mothers and neonates (Al, van Houwelingen, & Hornstra, 1997).

That critical fatty acids are depleted with parity is also consistent with studies showing that cognitive functioning is impaired with parity. IQ is negatively correlated with birth order (Downey, 2001), and twins have decreased DHA (McFadyen, Farquharson, & Cockburn, 2001) and compromised neurodevelopment compared to singletons (Ronalds, De Stavola, & Leon, 2005). The mother’s brain also typically decreases in size during pregnancy (Oatridge et al., 2002).

This also could explain why first born children are more intelligent than their siblings: because they have first dibs on the neurodevelopmental nutrients from the gluteofemoral fat, which aids in their brain growth and intelligence. What also lends credence to the theory is how the mother’s brain size typically decreases during pregnancy, due to the neurodevelopmental nutrients going to the child. (I also can’t help but wonder if this has any effect on Chinese IQ, since they had a nice increase in intelligence due to the Flynn Effect from 1982 to 2012. I will cover that in the future.)

“This hypothesis,” the authors write, “thus unites two derived (evolutionarily novel) features of Homo sapiens: sexually dimorphic fat distributions and large brains. On this view, a low WHR signals the availability of critical brain-building resources and should therefore have consequences for cognitive performance.”

The authors put forth three predictions for their study: 1) that a woman’s WHR should be negatively correlated with the cognitive ability of her offspring, 2) a woman’s WHR should be negatively correlated with her own intelligence since a woman passes on DPA as well as her own genes for low WHR to female offspring and 3) “cognitive development should be impaired in women whose first birth occurred early as well as in her future offspring, but lower WHRs, which indicate large stores of LCPUFA should be significantly protective for both” the mother and the child.

Lassek and Gaulin used data from the NHANES (National Health and Nutrition Examination Survey) III which included over 16,000 females with a mean age of 29.9 years. Measurements were taken on waist and hip circumference, WHR, BMI, and body fat as measured from bioelectrical impedance.*

For 752 “nulligravidas” (medical term for a woman who has never been pregnant), WHR explained 23 percent of the variance in total body fat estimated from the bioelectrical impedance (ugh, such a horrible measure). Moreover, “controlling for age and race/ethnicity” showed an increase of “0.01 in WHR increases total body fat by .83 kg” (1.82 pounds in freedom units). They also discovered that WHR explains 28 percent of the variance in BMI, with an increase of .47 kg per square meter, increasing the WHR by 0.01. BMI also explained 89 percent of the variance in body fat (garbage ‘body fat measuring instrument’ aside) with an increase of 1 kg per square meter increasing fat by 1.8 kg (close to 4 pounds in freedom units), but when added to the regression model, WHR made no additional contribution.

Lassek and Gaulin’s first hypothesis was corroborated when they found that the mother’s WHR was negatively correlated with the child’s intelligence on 4 cognitive tests. WHR accounted for 2.7 percent of the variation in test scores, “with a decrease of 0.01 in the mother’s current WHR increasing the child’s mean cognitive score by 0.061 points”. In the first subsample, they controlled for mother’s age, parental education, family income and race/ethnicity. Even when these variables were controlled for, WHR was still negatively correlated with the cognitive score. When these variables were controlled for, a decrease of 0.01 in WHR increased the average score by 0.024 points.

Their second hypothesis was also confirmed: that women with lower WHR would be more intelligent than women with higher WHRs. In girls aged 14-16, the WHR accounted for 3.6 percent of the variance in the average of the four cognitive tests. Also discovered was that in women aged 18 to 49, WHR accounted for 7 percent of the variance in years of education and 6 percent of the variance in two tests of cognitive ability. Even when controlling for age, parity, family income, age at first birth, and race/ethnicity, the negative correlation was still seen in 14 to 16-year-old girls.

There is also competition neurodevelopmental resources between mother and child. As I showed earlier in this article, a woman’s brain size decreases during pregnancy. This decrease in brain size during pregnancy is due to the babe getting more of the neurodevelopmental nutrients for brain growth from the mother. Clearly, as the mother’s stores of brain-growing nutrients become depleted, so does her brain size as te nutrients from her stored fat goes to developing the fetuses’ brain.

Lassek and Gaulin confirmed their hypothesis that a woman with a lower WHR would be more intelligent as well as have more intelligent children. WHR predicts the cognitive ability of the offspring while BMI does not. However, controlling for family income and parental education decreases the effect of WHR on the child’s intelligence, the effect still remains giving strong support to the hypothesis that women with low WHR pass on genes for low WHR as well as nutrients needed for neurodevelopment. Further, controlling for parental cognitive ability may mask the effects of the WHR. It’s well known that the mother’s intelligence is the best predictor for her offspring’s intelligence, which is due to the mother and grandmother passing on genes that augment the effect of LCPUFAs, along with the genes for lower WHR.

Women with a lower WHR were found to be more intelligent, and a lower WHR helps to protect cognitive resources (neurodevelopmental nutrients) for the mother and child. The mother’s body has a dilemma, though: it has to store nutrients for the mother’s own cognition; store resources for future pregnancies; and provide nutrients for their growing fetus. Obviously, especially in young mothers, this poses a problem as there is a conflict for what the brain should do with the nutrients the mother ingests. Children born to teenaged mothers have lower cognitive test scores, but, they are protected from this fate if the mother has a low WHR. This shows, definitively, that young mothers who are still growing will show no negative effects on their growth when pregnant if they have a low WHR which signals they have a large amount of LCPUFAs and other essential neurodevelopmental nutrients for the baby’s brain growth.

LCPUFAs are scarce in human diets. Thusly, an evolutionary preference for low WHR evolved for men so their children can have optimal nutrients while growing in the mother’s womb. The study confirmed that large brains, and along with it higher intelligence, and sexually dimorphic fat distribution have a strong link. Clearly, if a mother doesn’t have adequate levels of LCPUFAs, neurodevelopment will be impeded since the babe will not be getting the optimal nutrients for brain growth. Moreover, diets low in omega-3s should have consequences for intelligence and brain size of a baby, since when a baby is in the womb that is the most important time for it to get optimal brain nutrients. Is there any type of environment we can make ourselves and lifestyle choices we can take for ourselves, spouses and children to foster higher intelligence in them? I will cover that in the future.

Men love hour-glass figures, a low WHR. As I’ve shown in this article, there is an evolutionary reason for this. Men were asked to rate women who had surgery to move fat to their buttocks. Body weight stayed the same, but the fat was redistributed. It was found in brain scans of the men that the same parts of the brain related to reward lit up, including regions associated with drugs and alcohol. (more information here)

Conclusion

I’ve long known of the tons of positive benefits of omega-3 fatty acids and fish oil on human brain development. Fish oils and the nutrients in them are imperative for a healthy and growing brain. Without it, brain development will suffer. As a man, I can say firsthand that a low WHR is the most attractive. Now I understand the evolutionary reason behind it: fostering high intelligence due to the mothers lower-body fat stores. Omega-3s and LCPUFA are extremely important for optimal fetal brain growth. Moreover, the current American diet is low in omega-3s, while high in omega-6s. There is evidence of high omega-6 intake being related to obesity, metabolic syndromes, a progressive increase in body fat over the generationsThe omega-6 and -3 ratios in the body also play a role in obesity, with a lower omega-3 ratio and higher omega-6 ratio being related to obesity. This is due to adipogenesis, browning of the fat tissue, lipid homeostasis, and systemic inflammation. Clearly, as shown in this article, it’s imperative to have a balance of omega-3 and omega-6 fatty acids. This could also have to do with the hyperactivity of the cannabinoid system (which we all know what that’s involved with: eating more) and that could also be a cause for obesity with out-of-whack omega-6 to -3 fatty acid levels in the body. That’s for another day, though.

The totality of evidence is clear. If you want healthy children, choose a mate with a low WHR. She and her offspring will be more likely to be more intelligent. Clearly, if you’re reading this, you’re interested in intelligence as well as having the best possible life and life outcomes for your children. Well, choose a woman with a low WHR and you’ll be more likely to have more intelligent children!

* I have one problem with this study. They assessed body fat with bioelectrical impedance. The machine sends a light electrical current through the body and measures the degree of resistance to the flow of the current, which body fat can then be estimated. Problems with measuring body fat this way are as follows: it depends on how hydrated you are, whether you exercised that day, when you last ate, even whether your feet are calloused. Most importantly, they vary depending on the machine as well. Two differing machines will give two differing estimates. This is my only problem with the study. I would like if, in a follow-up study, they would use the DXA scan or hydrostatic weighing. These two techniques would be much better than using bioelectrical impedance, as the variables that prevent bioelectrical impedance from being a good way to measure body fat don’t exist with the DXA scan or hydrostatic weighing.

(Also see Eternal Curves by the Lassek and Gaulin and their book Why Women Need Fat for more information.)

What’s the Cause of the Cucking of Europe?

1500 words

We all wonder, why are most European men allowing what’s happening at the moment in Europe. Why, for instance, did hundreds of men not intervene during the sexual assaults in Cologne on New Years? There are both genetic and social reasons for these phenomena that are currently happening in the European Homeland. Causes include genetic pacification, the Bystander Effect, BPA in plastics and of course, the media and propaganda towards people.

Genetic Pacification

From this paper by Frost and Harpending (2015), we see that between the 5th and 11th centuries, genetic pacification was impeded by the nature of law enforcement, the beliefs in a man’s right to settle personal disputes as he saw fit, and the Church’s opposition to the death penalty.

The impediments on genetic pacification began to dissolve by the 11th century when the Church and State decided that the wicked should be punished so that the good may live in peace. By the late Middle Ages, Courts were imposing the death penalty on .5 to 1 percent of men each generation, with just as many dying at the scene of the crime or in prison awaiting trial.

The murder rate plummeted between the 14th and 20th centuries. Most murders during that time were committed due to jealousy, intoxication or stress. The decline is attributed to longer punishments and the effects of cultural conditioning, but may also be caused by the new cultural environment selecting against propensities for violence.

I theorize that due to the culling of .5 to 1 percent of the violent European men up to the late Middle Ages is the cause of the people with ‘no fight in them’, so to speak. By culling the part of the population that has propensities for violence, you’re only left with those with low testosterone, therefore, less propensity to act when situations arise (such as Cologne). Due to the culling of part of the violent population, this caused the murder rate to drop from the 14th to 20th centuries, as well as leaving most that were left, unable to act under certain circumstances.

Clearly, without the culling of those individuals with a propensity for violence, we are left with what we have in Europe today: men with no heart, no fight in them to protect their women against invading peoples. But there are more reasons for this other than genetic pacification.

BPA in Plastics

Being hugely interested in nutrition, I also know of this nice little tidbit about plastics. The chemical BPA was discovered to act as an artificial estrogen in the 1930s. Since BPA has been in our plastics for over 100 years, this, along with genetic pacification, also explains another part of this puzzle on why Europe is so cucked.

The consumption of fluids in plastics with the chemical BPA shows a decrease in testosterone for men. In a study from China, men who worked in a chemical plant showed lower levels of testosterone than men who worked in a tap water plant.  What was noted, was that those men who worked in a chemical plant had lower levels of free testosterone, which this form of test is thought to have the greatest effect on the body (most test is not free, but bound to a protein in the body).

Testosterone does begin to decline at around age 30 at around 1 percent per year (I have read other sources that say that it begins to decline at around age 25 at a rate of 2 percent per year), but this does not explain the cause of low testosterone in males. The effects of BPA do, though. It’s been noted that the past 20 years have seen a decrease in male testosterone.

I advise all of you (women included, there are many deleterious effects of BPA on the mother as well as the baby prenatally), to discontinue use of plastics with BPA in them.

The Bystander Effect

I have seen many people wonder “why did so many men in Cologne just stand around and watch women get sexually assaulted and not intervene?”

The cause is simply answered with some basic psychology.

Rushton (1978), noted that those in rural areas gave help more often than those in more urban areas. He noted that as helping behavior decreased, the urban population increased. He goes in depth in his book Altruism, Socialization and Society on this subject, with numerous examples.

One example I remember from the book is that they had subjects in a room. The room then started filling with smoke. Those who were in there alone almost immediately phoned 911. Those who were in the room with more than themselves waited until the whole room was filled with smoke to act. When an event happens and there are more than a few individuals present, they start thinking “oh he will do something, I’ll just watch”. This effect is then seen in others who think the same things. There is an inverse relationship between the number of people in any given situation and the help they will give. The fewer people there are, the more likely one is to help. The more people there are, the less likely one is to help due to them thinking the next person will.

The bystander effect was first discovered in 1964 by social psychologists Bibb Latané and John Darley. A woman named Kitty Genovese was murdered outside of her apartment. Bystanders who witnessed the event did not do anything to help her. Latané and Darley attributed the effect to diffusion of responsibility and social influences. In the case of Genovese’s murder, each bystander concluded by the inaction of others witnessing the event that their own help was not needed.

There were thousands upon thousands of people who witnessed the events of Cologne. Along with genetic pacification, along with BPA in plastics combined with the bystander effect, all of these variables made it so that there would be no action, due largely in part to this bystander effect.

Socialization from Media

Finally, we have the media’s involvement with the cucking of Europe.

The media can be a very powerful tool to influence behavior in the populace. To quote Rushton from the paper Effects of Prosocial Television and Film Material on The Behavior of Viewers

The chapter includes that television’s strongest effects result from altering (a) a person’s internalized norms of appropriate behavior or (b) a person’s direct emotional response to stimuli. These two concepts are elaborated and each of the four prosocial categories (altruism, friendliness, self-control, and diminishing fears) is presented in the chapter. In this chapter, it is indicated that television has the power to affect the social behavior of viewers in a positive, prosocial direction.

If television has that much effect on people’s behavior and emotional response in prosocial behaviors, of course, the reverse will have the opposite effect. Constantly telling European men that “all whites are evil, and some only ‘less bad than others'”, has yet another effect on the psyche of the European male. Being told you’re constantly worthless and the cause of all of the problems in the world will lead to men beginning to think that, which is in and of itself a self-fulfilling prophecy.

Through the use of predictive programming, they can alter one’s perception of the world by putting in what seems to be innocent things, but subconsciously affect the mind in a negative way. Those exposed constantly to the effects of predictive programming by the media will then begin to believe what they say due to being bombarded with its messages of worthlessness every day.

It’s noted in the discussion of this paper that:

First, the mass media can attract and direct attention to problems, or in ways which can favor those people in power, and correlatively, divert attention from rival individuals or groups. Second, the mass media can confer status and confirm legitimacy. Third, in some circumstances, the media can be a channel for persuasion and mobilization. Fourth, the mass media can help to bring certain kinds of publics into being and maintain them. Fifth, the media is a vehicle for psychic rewards and gratifications. They can divert and amuse and they can flatter. In general, mass media are very cost effective as a means of communication in society; they are also fast, flexible and easy to control.

The causes of the problems happening right now in Europe are due to both social and genetic factors. The reason for the cucking of Europe is due to the culling of the most aggressive men in the late Middle Ages, BPA in plastic, along with the bystander effect and finally, the anti-white media who tells European men they are useless.

I wonder, what if anything can be done to solve this problem and get Europe their fire back to protect the homeland from invasion. To stop drinking from plastics with BPA in them is a good start. To stop watching anti-white media that tells you’re worthless is a great start. To actually act when you see an event go down and not assume that the next man will intervene is a good start.

I wonder what it will take for Europe to finally get its fire back?