Why Are Humans Cognitively Superior to Other Animals?
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The past few articles I have written touched on the fact that the human brain isn’t special and is just a scaled-up primate brain, bipedalism, tools, fire, cooking and meat eating had the largest effect on hominin brain evolution, and that, despite seeing a so-called ‘upward trend’ in the evolution of primate brain size, the reverse was occurring. So what makes us cognitively superior to other animals?
The most oft-cited reason why humans are cognitively superior to other animals is that we have the largest EQ compared to other animals. Ours is 7.5, meaning that we have a brain that’s 7.5 times larger than a mammal for our size but only 3.4 times as larger than expected for an anthropoid primate of its body mass (Azevedo et al, 2009). However, in stark contrast to the view of the people who view EQ as the reason why we are cognitively superior to other animals, what separates us in terms of cognitive ability is the difference in cortical neurons compared to other primates.
We humans have the most cortical neurons in our cerebral and prefrontal cortexes, relatively high neuron packing density (NPD), and much more cortical neurons of mammals of the same brain size (Roth and Dicke, 2012). Differences in intelligence across primate taxa best correlate with differences in number of cortical neurons, information processing speed, and synapses. Though, the human brain stands out having a “large cortical volume with a relatively NPD, high conduction velocity and high cortical parcellation.” This is why we are much more intelligent than other primates, due to the amount of cortical neurons we have as well as higher neuron packing density (keep this in mind for later). Encephalization quotient doesn’t explain intelligence differences within species, hence there being a problem with the use of encephalization to as the reason for human cognitive superiority, our Human Advantage, if you will.
Harry Jerison, the originator of the encephalization quotient, came to the conclusion that “human evolution … had been all about an advancement of encephalization quotients culminating in man.” (Herculano-Houzel, 2016: 15) What a conclusion. Just because EQ increased throughout hominin evolution, that means that it was all an advancement of EQs culminating to man. That’s circular logic.
Moreover, the “circular assumption” that higher EQ mean superior cognitive abilities in humans wasn’t founded on “tried-and-true correlations with actual measures of cognitive capacity.” (Herculano-Houzel, 2016: 15)
In second place on the EQ chart is the capuchin monkey coming in with an EQ of 2, which is more than double that of great apes who fall way below 1. That would imply that capuchin monkeys are more intelligent than great apes and outsmart great apes, right? Wrong. Great apes are. Total brain size predicts cognitive abilities in non-human primates better than EQ (Deaner et al, 2007).
Great apes significantly outperform other lineages. (Deaner, Schaik, and Johnson, 2006) Yet they have smaller EQs compared to other less intelligent primates. This is one of the largest problems with the EQ: total brain size is a better predictor of cognitive ability in non-human primates (Herculano-Houzel, 2011). She proposes that the absolute number of neurons, irrespective of brain size or body weight, is a better predictor of cognitive ability than is EQ.
Another problem with the EQ is that it assumes that all brains are made the same, and they aren’t. They scale differently between species. That’s one pretty huge flaw. Scaling is not the same across species, only within certain species. This one fatal flaw in EQ comparing different species of humans is why there is a problem with EQ in assessing cognitive abilities and why total brain size predicts cognitive abilities in non-human primates better than EQ.
Absolute brain size is a much better indicator of intelligence than the encephalization quotient.
So what exactly explains human cognitive superiority over other animals if the most often-used metric—the EQ—is flawed? An enlarged frontal cortex? No, the prefrontal areas in a human brain occupy 29 percent of the mass of the cerebral cortex. Moreover, the prefrontal cortex of humans, bonobos, chimpanzees, gorillas, and orangutans occupies the same 35-37 percent of all cortical volume (Semendeferei et al, 2002). (See also Herculano-Houzel, 2016: 119 and Gorillas Agree: Human Frontal Cortex is Nothing Special). Just because our frontal cortexes are all the same size, doesn’t mean that we don’t have a higher neuron packing density (NPD) than other primates. However, the human brain has the amount of neurons expected for its grey matter volume and total number of neurons remaining in the cerebral cortex; it has the white matter volume expected for amount of neurons; and the white matter volume and number of neurons expected for the number and volume of neurons in the “nonprefrontal subcortical white matter” (Herculano-Houzel, Watson, and Paxinos, 2013). The human prefrontal cortex is no larger than it ‘should’ be.
However, there seems to be a problem with Herculano-Houzel’s (2011) theory that absolute number of neurons predicts cognitive superiority (Mortenson et al, 2014). The long-finned pilot whale has 37,200,000 neurons in its cerebral cortex, more than double that of humans (16 billion). Does this call into question Herculano-Houzel’s (2011) theory on absolute number of neurons being the best case of human cognitive superiority over other animals?
In short, no. Neuron density is higher in humans than in the pilot whale. We have more neurons packed into our cerebral cortex. Their higher cell count is due only to their larger brains. And where it matters: pilot whales have a higher than expected amount of neocortical neurons relative to body weight, although not higher than humans. Herculano-Houzel’s (2011) theory is still in play here. They have big brains and in turn large amounts of glial cells to counter heat loss. So even then, this doesn’t counter Herculano-Houzel’s theory that the absolute amount of neurons dictates overall cognitive superiority.
Moreover, there is the same amount of cortical neurons in mice brains and human brains, with both mice and humans housing 8 percent of their total neurons in the prefrontal cortex. So what accounts for human cognitive superiority in humans compared to other primates? Most likely, the connectivity of the brain.
The connectivity in the brain of humans is not different from other species. The density of gray matter within species is fairly constant within mammalian species (Herculano-Houzel, 2016: 122). If true, then human prefrontal cortex, being nowhere near the largest, wouldn’t have the most synapses in our prefrontal cortex or anywhere else in the brain, and thus these wouldn’t be the largest. So, what does explain the cognitive superiority of humans over other animals in the animal kingdom?
All though all mammals use 8 percent of their total neurons in their prefrontal cortex, there is a differing distribution due to the amount of total neurons in each brain (remember, all brains aren’t made the same. It doesn’t hold for humans, and it especially doesn’t hold across phyla). We have 1.3 billion cortical neurons in our prefrontal cortex, baboons have 230 million, the macaque has 137 million and the marmoset has 20 million (Herculano-Houzel, 2016: 122). Prefrontal neurons are able to add complexity and flexibility, among other associative functions, to behavior while making planning for the future possible. All of these capabilities would increase with the more neurons a prefrontal cortex has (remember back to my article that the seat of intelligence (g) is the prefrontal cortex). So this seems to confirm the past studies showing the seat of intelligence to be the frontal cortex, due to the large amount of cortical neurons it has.
Herculano-Houzel writes the best definition of intelligence she’s ever heard, from MIT physicist Alex Wissner-Gross, which I believe is a great definition of intelligence:
The ability to plan for the future, a significant function of prefrontal regions of the cortex, may be key indeed. According to the best definition I have come across so far, put forward by MIT physicist Alex Wissner-Gross, intelligence is the ability to make decisions that maximize future freedom of action—that is, decisions that keep most doors open for the future. (Herculano-Houzel, 2016: 122-123)
All of the above are the direct result of more neurons in our frontal cortexes compared to other primates, which is why she finds it is the best definition of intelligence she’s ever heard.
Our ‘Human Advantage’ over other species comes down to the number of cortical neurons we have in our prefrontal cortex compared to other primates as well as the most neurons along with the highest NPD in the animal kingdom—which will be matched by no animal. The encephalization quotient has a lot of problems, with overall brain weight being a much better predictor of intelligence (Herculano-Houzel, 2011). Human cognitive superiority comes down to the total amount of neurons in our frontal cortex (1.3 billion neurons—where we will not be beaten) and our cerebral cortexes (16 billion neurons [long-finned pilot whales beat us out by more than double the amount, but we have more neurons packed into our cerebral cortex signifying our higher cognitive abilities). Within primates, total brain size predicts cognitive abilities better than EQ (Deaner et al, 2007).
Human cognitive superiority, contrary to popular belief, is not due to the EQ. It’s due to our NPD and amount of neurons in our frontal and cerebral cortexes that no other animal has–and we will not find another animal like this. This only would have been possible with the advent of bipedalism, tool-making, fire, cooking and meat eating. That’s what drives the evolution of brain size—and our evolution as a whole. Energy. Energy to reproduce, which then produce mutations which eventually coalesce new species.
Is There Progress in Hominin Brain Evolution?
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Tl;dr: The ‘trend’ in the evolution of hominin brain size is only due to diet quality and abundance. If there is any scarcity of food or a decrease in nutritional quality, there will be a subsequent decrease in brain size, as seen with H. floresiensis. Brain size, contrary to popular belief, has been decreasing for the past 20,000 years and has accelerated in the past 10,000. This trend is noticed all over the world with multiple hypotheses put out to explain the phenomenon. Despite this, people still deny that a decrease is occurring. Is it? Yes, it is. It’s due to a decrease in diet quality along with higher population density. If the human diet were to decrease in quality and caloric amount, our brains—along with our bodies—would become smaller over time.
Is there progress in hominin brain evolution? Many people may say yes. Over the past 7 million years, the human brain has tripled in size with most of this change occurring within the past 2 million years. This perfectly coincides with the advent of bipedalism, tool-making, fire, cooking and meat eating. Knowing the causal mechanisms behind the increase in hominin (primate) brain size, is there ‘progress’ to brain size in hominin evolution?
Looking at the evolution of hominin brain size in the past 7 million years, one can rightfully make the case that there is an evolutionary trend with the brain size increase. I don’t deny there is an increase, but first, before one says there is ‘progress’ to this phenomenon, you must look at it from both sides.
Montgomeroy et al (2010) reconstructed the ‘ups and downs’ of primate brain size evolution, and of course, decreases in hominin brain size can’t be talked about without bringing up H. floresiensis and his small brain and body mass, which they discuss as well. They come to the conclusion that “brain expansion began early in primate evolution”, also showing that there have been brain size increases in all clades of primates. Humans only show a bigger increase in absolute mass, with rate of proportional change in mass and relative brain size “having greater episodes of expansion elsewhere on the primate phylogeny”. Decreases in brain size also occurred in all of the major primate clades studied, they conclude that “while selection has acted to enlarge primate brains, in some lineages this trend has been reversed.” The selection can only occur in the presence of adequate kcal, keeping everyone sated and nourished enough to provide for the family, ensuring a woman gets adequate kcal and nutrients during pregnancy and finally ensuring that the baby gets the proper amount of energy for growth during infancy and childhood.
Montgomery et al write:
The branch with the highest rate of change in absolute brain mass is the terminal human branch (140,000 mg/million years). However for rate of proportional change in absolute brain mass the human branch comes only fourth, below the branches between the last common ancestor of Macaques and other Papionini, and the last common ancestor of baboons, mangabeys and mandrills (48 to 49), the ancestral primate and ancestral haplorhine (38 to 39) and the branch between the last common ancestor of Cebinae, Aotinae and Callitrichidae, and the ancestral Cebinae (58 to 60). The rate of change in relative brain mass along the human branch (0.068/million years) is also exceeded by the branch between the last common ancestor of Alouatta, Ateles and Lagothrix with the last common ancestor of Ateles and Lagothrix (branch 55 to 56; 0.73), the branch connecting the last common ancestor of Cebinae, Aotinae and Callitrichidae, and the ancestral Cebinae (branch 58 to 60; 0.074/million years) and the branch connecting the last common ancestor of the Papionini with the last common ancestor of Papio, Mandrillus and Cercocebus (branch 48 to 49; 0.084). We therefore conclude that only in terms of absolute mass and the rate of change in absolute mass has the increase in brain size been exceptional along the terminal branch leading to humans. Once scaling effects with body mass have been accounted for the rate of increase in relative brain mass remains high but is not exceptional.
“Remains high but is not exceptional”, ie, expected for a primate of our size (Azevedo et al, 2009). Of course, since evolution is not progressive, then finding any so-called ‘anomalies’ that ‘deviate’ from the ‘progress’ in brain size evolution makes sense. They conclude that floresiensis’ brain size and body mass decrease fell within the expected range of Argue et al’s (2009) proposed phylogenetic scenario. Though, only if he evolved from habilis or Dmansi hominins if the insular dwarfism hypothesis was taken into account (which is a viable explanation for the decrease).
The effects of food scarcity and its effect on hominin brain size is hardly ever spoken about. However, as I’ve been documenting here recently, caloric quality and amount dictate brain size. Montgomeory et al (2010) write:
Although many studies have investigated the possible selective advantages and disadvantages of increased brain size in primates [5, 17, 18, 19, 20, 21], few consider how frequently brain size has reduced. Periods of primate evolution which show decreases in brain size are of great interest as they may yield insights into the selective pressures and developmental constraints acting on brain size. Bauchot & Stephan [22] noted the evolution of reduced brain size in the dwarf Old World monkey Miopithecus talapoin and Martin [23] suggested relative brain size in great apes may have undergone a reduction based on the cranial capacity of the extinct hominoid Proconsul africanus. Taylor & van Schaik [24]reported a reduced cranial capacity in Pongo pygmaeus morio compared to other Orang-utan populations and hypothesise this reduction is selected for as a result of scarcity of food. Finally, Henneberg [25] has shown that during the late Pleistocene human absolute brain size has decreased by 10%, accompanied by a parallel decrease in body size.
[…]
These authors suggest this reduction is associated with an increase in periods of food scarcity resulting in selection to minimise brain tissue which is metabolically expensive [17]. Food scarcity is also believed to have played a role in the decrease in brain size in the island bovid Myotragus [12]. Taylor & van Schaik [24] therefore propose that H. floresiensis may have experienced similar selective pressures as Myotragus and Pongo p. morio.
Nice empirical vindication for me, if I don’t say so myself. This lends further credence to my scenario of an asteroid impact on earth halting food production leading to a scarcity in food. It’s hypothesized that floresiensis went from eating (if evolved from erectus) 1800 kcal per day and 2500 while nursing to 1200 per day and 1400 while nursing (Lieberman, 2013: 125). This, again, is proof that big brains need adequate energy and that cooking meat was what specifically drove this facet of our evolution.
Montgomeroy et al (2010) conclude:
Finally, our analyses add to the growing number of studies that conclude that the evolution of the human brain size has not been anomalous when compared to general primate brain evolution [59, 61, 91, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94].
In other words, humans are not ‘special’ in terms of brain size. While there is a ‘trend’ in the increase in brain size, this ‘trend’ is only possible with the advent of fire, cooking, and meat eating. Without that causal mechanism, big brains would not be metabolically viable.
A big brain (large amounts of neurons) can only evolve with enough energy, mainly the advent of cooking meat (Herculano-Houzel, 2009). Primates have much higher neuronal densities than other mammals (Herculano-Houzel, Manger, and Kaas, 2014). Since the amount of energy the brain needs per day depends on how many total neurons it has (Azevedo and Herculano-Houzel, 2012), quality calories are needed to power such a metabolically expensive organ. Only with the advent of fire could we consume enough high-quality energy to evolve such big brains.
Mammalian brains that have 100 million neurons require .6 kcal, brains with 1 billion neurons use 6 kcal per day, and brains with 100 billion neurons use 600 kcal per day (humans with 86 billion neurons use 519 kcal, coming out to 6 kcal per neuron) regardless of the volumes of the brains (Herculano-Houzel, 2011). Knowing that the amount of neurons a brain has is directly related to how much energy it needs, it doesn’t seem so crazy now that, like with the example of floresiensis, a brain could decrease in size even when noticing this ‘upward trend’ in hominin brain size. This is simply because how big a brain is directly related to amount of energy available in an area as well as the most important variable: quality of the food.
If floresiensis is descended from habilis (and there is evidence that habilis was a meat eater, so along with a low amount of energy for floresiensis on Flora as well as there being no large predators on the island, a smaller size would have been advantageous to floresiensis), then this shows that what I’ve been saying for a few months is true: the diet quality as well as amount of energy dictates whether an organism evolves to be big or small. Energy is what ‘drives’ evolution in a sense and energy comes from kcal. The highest quality energy is from meat, and that fuels our ‘big brains’ with our high neuron count.
Imagine this scenario: an asteroid hits the earth and destroys the world power grid. All throughout the world, people cannot consume enough food. The sun is blocked by dust clouds for, say, 5000 years. The humans that survive this asteroid collision would evolve a smaller brain and body as well as better eyesight to see in an environment with low light, among other traits. Natural selection can only occur on the heritable variants already in the population, so whatever traits that would increase fitness in this scenario would multiply and flourish in the population, leading to a different, smaller-brained and smaller-bodied human due to the effects of the environment.
While on the subject of the decrease in human brain size, something that’s troubling to those who champion the ‘increase in hominin brain size’ as the ‘pinnacle of evolution’: our brains have been decreasing in size for at least the past 20,000 years according to John Hawks associate professor of anthropology at the University of Wisconsin-Madison. Keep in mind, this is someone that Pumpkin Person brings up saying that our brains have been increasing for the past 10,000 years. He has also said that the increase in better nutrition has allowed us to gain back the brain size of our hunter-gatherer ancestors (with no reference), which is not true. Because what John Hawks actually wrote on his blog about this says a different story:
The available skeletal samples show a reduction in endocranial volume or vault dimensions in Europe, southern Africa, China, and Australia during the Holocene. This reduction cannot be explained as an allometric consequence of reductions of body mass or stature in these populations. The large population numbers in these Holocene populations, particularly in post-agricultural Europe and China, rule out genetic drift as an explanation for smaller endocranial volume. This is likely to be true of African and Australian populations also, although the demographic information is less secure. Therefore, smaller endocranial volume was correlated with higher fitness during the recent evolution of these populations. Several hypotheses may explain the reduction of brain size in Holocene populations, and further work will be necessary to uncover the developmental and functional consequences of smaller brains.
In fact, from the Discover article on decreasing brain size, John Hawks says:
Hawks spent last summer measuring skulls of Europeans dating from the Bronze Age, 4,000 years ago, to medieval times. Over that period the land became even more densely packed with people and, just as the Missouri team’s model predicts, the brain shrank more quickly than did overall body size, causing EQ values to fall. In short, Hawks documented the same trend as Geary and Bailey did in their older sample of fossils; in fact, the pattern he detected is even more pronounced. “Since the Bronze Age, the brain shrank a lot more than you would expect based on the decrease in body size,” Hawks reports. “For a brain as small as that found in the average European male today, the body would have to shrink to the size of a pygmy” to maintain proportional scaling.
This is in stark contrast to what PP claims he says about the evolution of human brain size over the past 10,000 years, especially Europeans who he claims Hawks has said there has been an increase in European brain size. An increase in brain size over the past 100 years doesn’t mean a trend is occurring upward, since all other data on human brain size says otherwise.
Our brains have begun to decrease in size, which is due to the effects of overnutrition and diseases of civilization brought on by processed foods and the agricultural revolution. Another proposed cause for this is that population density tracks with brain size, with brain size increasing with a smaller population and decreasing with a bigger population. In a way, this makes sense. A bigger brain should have more neurons than a smaller brain, which would aid in cognitive tasks and have that one hominin survive better giving it a better chance to pass on its genes, so if you think about it, when the population increases when social trust forms, you can piggyback off of others and they wouldn’t have to do things on their own. As population size increased from sparse to dense, brain size decreased with it.
On this notion of ‘progress’ in brain size, some people may assume that this puts us at the ‘pinnacle’ of evolution due to our superior cognitive ability (which is due to the remarkably large amount of neurons in our cerebral cortex [Hercualno-Houzel, 2016: 102]), Herculano-Houzel writes on page 91 of her book The Human Advantage: A New Understanding of How Our Brains Became Remarkable:
We have long deemed ourselves to be at the pinnacle of cognitive abilities among animals. But that is different than being at the pinnacle of evolution in a number of important ways. As Mark Twain pointed out in 1903, to presume that evolution has been a long path leading to humans as its crowning achievement is just as preposterous as presuming that the whole purpose of building the Eiffel Tower was to put the final coat of paint on its tip. Moreover, evolution is not synonmous with progress, but simply change over time. And humans aren’t even the youngest, most recently evolved species. For example, more than 500 new species of cichlid fish in Lake Victoria, the youngest of the great African Lakes, have appeared since it filled with water some 14,500 years ago.
Using PP’s logic, the cichlid fishes of Lake Victoria are ‘more highly evolved’ than we are since they’re a ‘newer species’. Using that line of logic makes no sense now, putting it in that way.
Looking at the ‘trend’ in human brain size over the past 7 million years, and its acceleration in the past 2 million, without thinking about what jumpstarted it (bipedalism, tools, fire, meat eating) is foolish. Moreover, any change to our environment that decreases our energy input would, over time, lead to a decrease in our overall brain size perhaps more rapidly, showing that this ‘trend’ in the increase in brain size is directly related to the quality and amount of food in the area. This is why floresiensis’ brain and body shrunk, and why certain primate lineages show increases in brain size: because they have a higher-quality diet. But it comes at a cost. Since primates largely eat a plant-based diet, they have to eat upwards of 10 hours a day to get enough energy to power either their brains or their bodies. If their bodies are large, their brains are small and vice versa. A plant-based diet cannot power a large brain with a high neuron count like we have, it’s only possible with meat eating (Azevedo and Herculano-Houzel, 2012). This is one reason why floresiensis’ brain shrunk along with not enough kcal to sustain their larger brain and body mass that their ancestor they evolved from previously had.
Our brains are not particularly special, and in a way, you can thank fire and cooking meat for everything that’s occurred since erectus first controlled fire. For without a quality diet in our evolution, this so-called ‘trend’ (which is based on the environment due to food quality and scarcity/abundance which fluctuate) would not have occurred. In sum, this ‘progress’ will halt and ‘reverse’ if the amount of energy consumed decreases or diet quality decreases.
What Caused Human Brain Size to Increase?
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People talk a lot about intelligence and brain size. Something that’s most always brought up is how the human brain increased in size the past 4 million years. According to PP, the trend for bigger brains in hominins is proof that evolution is “progressive”. However, people never talk about a major event in human history that caused our brains to suddenly increase: the advent of fire. When our ancestors mastered fire, it was then possible for the brain to get important nutrients that influenced growth. People say that “Intelligence is the precursor to tools”, but what if fire itself is the main cause for the increase in brain size in hominins the past 4 million or so years? If this is the case, then fire is, in effect, the ultimate cause of everything that occurred after its use.
The human brain consumes 20-25 percent of our daily caloric intake. How could such a metabolically expensive organ have evolved? The first hominin to master fire was H. erectus. There is evidence of this occurring 1-1.5 mya. Not coincidentally, brain size began to tick upward after the advent of fire by H. erectus. Erectus was now able to consume more kcal, which in turn led to a bigger brain and the beginnings of a decrease in body size. The mastery and use of fire drove our evolution as a species, keeping us warm and allowing us to cook our food, which made eating and digestion easier. Erectus’s ability to use fire allowed for the biggest, in my opinion, most important event in human history: cooking.
With control of fire, Erectus could now cook its foods. Along with pulverizing plants, it was possible for erectus to get better nutrition by ‘pre-digesting’ the food outside of the body so it’s easier to digest. The advent of cooking allowed for a bigger brain and with it, more neurons to power the brain and the body. However, looking at other primates you see that they either have brains that are bigger than their bodies, or bodies that are bigger than their brains, why is this? One reason: there is a trade-off between brain size and body size and the type of diet the primate consumes. Thinking about this from an evolutionary perspective along with what differing primates eat and how they prepare (if they do) their food will show whether or not they have big brains or big bodies. How big an organism’s brain gets is directly correlated with the amount and quality of the energy consumed.
There is a metabolic limitation that results from the number of hours available to feed and the low caloric yield of raw foods which then impose a trade-off between the body size and number of neurons which explains why great apes have small brains in comparison to their bodies. Metabolically speaking, a body can only handle one or the other: a big brain or a big body. This metabolic disadvantage is why great apes did increase their brain size, because their raw-food diet is not enough, nutritionally speaking, to cause an increase in brain size (Azevedo and Herculano-Houzel, 2016). Can you imagine spending what amounts to one work day eating just to power the brain you currently have? I can’t.
Energy availability and quality dictates brain size. A brain can only reach maximum size if adequate kcal and nutrients are available for it.
Total brain metabolism scales linearly with the number of neurons (Herculano-Houzel, 2011). The absolute number of neurons, not brain size, dictates a “metabolic constraint on human evolution”, since people with more neurons need to sustain them, which calls for eating more kcal. Mammals with more neurons need to eat more kcal per day just to power those brains. For instance, the human brain needs 519 kcal to run, which comes out to 6 kcal per neuron. The brain is hugely metabolically expensive, and only the highest quality nutrients can sustain such an organ. The advent of fire and along with it cooking is one of, if not the most important reason why our brains are large (compared to our bodies) and why we have so many neurons compared to other species. It allowed us to power the neurons we have, 86 billion in all (with 16 billion in the cerebral cortex which is why we are more intelligent than other animals, number of neurons, of course being lower for our ancestors) which power human thought.
The Expensive Tissue Hypothesis (ETA) explains the metabolic trade-off between brain and gut, showing that the stomach is dependent on body size as well as the quality of the diet (Aiello, 1996). As noted above, there is good evidence that erectus began cooking, which coincides with the increase in brain size. As Man began to consume meat around 1.5 million years ago, this allowed for the gut to get smaller in response. If you think about it, it makes sense. A large stomach would be needed if you’re eating a plant-based diet, but as a species begins to eat meat, they don’t need to eat as much to get the adequate amount of kcal to fuel bodily functions. This lead to the stomach getting smaller, and along with it so did our jaws.
So brain tissue is metabolically expensive but there is no significant correlation between brain size and BMR in humans or any other encephalized mammal, the metabolic requirements of relatively large brains are offset by a corresponding gut reduction (Aiello and Wheeler, 1995). This is the cause for the low, insignificant correlation between BMR and our (relatively large brains, which correlates to the amount of neurons we have since our brains are just linearly scaled-up primate brains).
Evidence for the ETA can be seen in nature as well. Tsuboi et al (2015) tested the hypothesis in the cichlid fished of Lake Victoria. After they controlled for the effect of shared ancestry and other ecological variables, they noted that brain size was inversely correlated with gut size. Perhaps more interestingly, they also noticed that when the fish’s’ brain size increased, increased investment and paternal care occurred. Moreover, more evidence for the ETA was found by Liao et al (2015) who found a negative correlation between brain mass and the length of the digestive tract within 30 species of Anurans. They also found, just like Tsuboi et al (2015), that brain size increase accompanied an increase in female reproductive investment into egg size.
Moreover, another cause for the increase in brain size is our jaw size decreasing. This mutation occurred around 2.4 million years ago, right around the time frame that erectus discovered fire and began cooking. This is also consistent with, of course, the rapid increase in brain size which was occurring around that time. The room has to come from somewhere, and with the advent of cooking and meat eating, the jaw was, therefore, able to get smaller along with the stomach which increased brain size due to the trade-off between gut size and brain size. Morphological changes occurred exactly at the same time changes in brain size occurred which coincides with the advent of fire, cooking, and meat eating. Coincidence? I think the evidence strongly points that this is the case, the rapid increase in brain size was driven by fire, cooking, and meat eating.
The rise of bipedalism also coincided with the brain size increase and nutritional changes. Bipedalism freed the hands so tools could be made and used which eventually led to the control of fire. Lending more credence to the hypothesis of bipedalism/tools/brain size is the fact that there is evidence that the first signs of bipedalism occurred in Lucy, our Australopithecine ancestor who had pelvic architecture that showed she was clearly on the way to bipedalism. There is more evidence for bipedalism in fossilized footprints of australopithecines around 3 mya, coinciding with Lucy, tool use and eventually the advent and use of fire as a tool to cook and ward off predators. Ancient hominids could then better protect their kin, have higher quality food to eat and use the fire to scare off predators with.
The nutritional aspect of evolution and how it co-evolved with us driving our evolution in brain size which eventually led to us is extremely interesting. Without proper nutrients, it’s not metabolically viable to have such a large brain, as whatever kcal you do eat will need to go towards other bodily functions. Moreover, diet quality is highly correlated with brain size. Great apes can never get to the brain size that we humans have, and their diet is the main cause. The discovery and control of fire, the advent of cooking and then meat eating was what mainly drove the rapid increase of brain size starting 4 mya.
In a way, you can think of the passing down of the skill of fire-making to kin as one of the first acts of cultural transference to kin. It’s one of the first means of Lamarckian cultural transference in our history. Useful skills for survival will get passed down to the next generation, and fire is arguably the most useful skill we’ve ever come across since it’s had so many future implications for our evolution. The ability to create and control fire is one of the most important skills as it can ward off predators, cook meat, be used to keep warm, etc. When you think about how much time was freed up upon the advent of cooking, you can see the huge effect the control of fire first had for our species. Then think about how we could only control fire if our hands were freed. Then human evolution begins to make a lot more sense when put into this point of view.
When thinking about brain size evolution as well as the rapid expansion of brain size evolution, nutrition should be right up there with it. People may talk about things like the cold winter hypothesis and intelligence ad nauseam (which I don’t doubt plays a part, but I believe other factors are more important), but meat-eating along with a low waist-to-hip ratio, which bipedalism is needed for all are much more interesting when talking about the evolution of brain size than cold winters. All of this wouldn’t be possible without bipedalism, without it, we’d still be monkey-like eating plant-based diets. We’d have bigger bodies but smaller brains due to the metabolic cost of the plant-based diet since we wouldn’t have fire to cook and tools to use as we would have still been quadrupeds. The evolution of hominin intelligence is much more interesting from a musculoskeletal, physiological and nutritional point of view than any simplistic cold winter theory.
What caused human brain size to increase is simple: bipedalism, tools, fire, cooking, meat eating which then led to big brains. The first sign of big brains were noticed right around the time erectus had control of fire. This is no coincidence.
Bipedalism, cooking, and food drove the evolution of the human brain. Climate only has an effect on it insofar as certain foods will be available at certain latitudes. These three events in human history were the most important for the evolution of our brains. When thinking about what was happening physiologically and nutritionally around that time, the rebuttal to the statement of “Intelligence requires tools” is tools require bipedalism and further tools require bigger brains as human brains may have evolved to increase expertise capacity and not IQ (more on that in the future), which coincides with the three events outlined here. Whatever the case may be, the evolution of human intelligence is extremely interesting and is most definitely multifaceted.
The Human Brain Is Not Particularly Special: A New Way of Looking At the Human Brain
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What if I told you that, neuronally speaking, the human brain was not particularly special? That, despite its size in comparison to our bodies, we are not particularly special in comparison to other primates or mammals. The encephalization quotient supposedly shows how “unique” and “special” humans are in terms of brain size compared to body size. We have a brain that’s seven times bigger than would be expected for our body size, and that’s what supposedly makes us unique compared to the rest of the animals kingdom.
Suzana Herculano-Houzel, the new Associate Professor of Psychology at Vanderbilt University (former Associate Professor at the Federal University of Rio de Janeiro), is a neuroscientist who challenges these notions that humans are supposedly unique in our brain size when compared to other mammals and primates. She pioneered a technique of turning brains into soup with a machine called the isotropic fractionator, which turns it into a “soup of a known volume” that contain the free cell nuclei to be colored and counted under a microscope. Using this technique, Azevedo et al (2009) showed that “with regard to numbers of neuronal and nonneuronal cells, the human brain is an isometrically scaled-up primate brain.” Every cell in the soup contains one nucleus, so counting is easy. Using this technique, they discovered that using the brain scaling of rats, a brain of 100 billion neurons would weigh 45 kg and body mass would be 109 tons. While using the primate scaling, a brain of 100 billion neurons would weigh 1.45 kg and belong to a body weighing 74 kg, suspiciously what humans are…. The human brain is constructed with the same rules as other primate’s brains. We are no different.
This is in direct opposition to brain size fetishists, who champion the fact that the human brain is some so-called ‘pinnacle of evolution’, as if all of the events that preceded us was setting the stage for our eventual arrival.
Of course, speaking in terms of body size, humans have the largest brains. However, the amount of neurons a brain has seems to be correlated to how cognitively complex the organism is. Humans have the most neurons for their brain size, however, that is one of the only things that sets us apart from other mammals/primates.
Azevedo et al (2009) write:
Our notion that the human brain is a linearly scaled-up primate brain in its cellular composition is in clear opposition to the traditional view that the human brain is 7.0 times larger than expected for a mammal and 3.4 times larger than expected for an anthropoid primate of its body mass (Marino, 1998). However, such large encephalization is found only when body-brain allometric rules that apply to nonprimates are used, as stated above, or when great apes are included in the calculation of expected brain size for a primate of a given body size.
Humans aren’t special in terms of neuronal and nonneuronal cells, our brains are just scaled-up versions of primate brains. There is nothing ‘weird’ or ‘unique’ about our brains; our brains follow the same ‘laws’ as other primates. Great apes such as the orangutans and gorillas are the ones who have brains that are smaller than their bodies. Their bodies are much larger than expected for primates of their brain size. That is where the outlier exists; not us.
The reason for our higher cognition is the 16 or so billion neurons in our cerebral cortex. For instance, the astounding human brain size in relation to body size is often touted, however, elephant’s brains are bigger, and they also have more neurons than we do. What sets us apart from elephants is that our cerebral cortex has about three times the amount of neurons compared to the elephant whose cerebral cortex is two times larger. The density of the neurons in our cerebral cortex seems to be the cause of our unique intelligence in the animal kingdom. Herculano-Houzel writes in her book The Human Advantage: A New Understanding of How Our Brains Became Remarkable (2016: 102):
The superior cognitive abilities of the human brain over the elephant brain can simply—and only—be attributed to the remarkably large number of neurons in its cerebral cortex.
Moreover, the absolute expansion of the cerebral cortex and its relative increase over the rest of the brain have been particularly fast in primate evolution (Herculano-Houzel, 2016: 110). I will return to the cause for this later.
She also noticed that in all of the papers that she read about the brain that the constant number quoted for the amount of neurons in the human brain was 100 billion. She continuously searched for the original citation and couldn’t find it. It wasn’t until she used her isotropic fractionator to get the true amount of neurons in the human brain—86 billion, which coincided with another stereological estimate.
Human brains are normally thought of as the ‘pinnacle of evolution’. Some people believe that everything preceding us was just setting the stage for the eventual Dawn of Man. This couldn’t be further from the truth. She writes on page 112:
And at the pinnacle of evolution, supposedly, is the human cerebral cortex, with the largest relative size compared to the brain. That, however, is only to be expected, both because we are primates and because, among primates, we have the largest brain and cerebral cortex, not because we are special.
Moreover, what I hardly see discussed is the fact that the brain is the most metabolically expensive organ the body has. Our brain weighs in at 2 percent of our body weight, yet takes 500 kcal—or 25 percent of our daily energy needs—to power. Further, 500 kcals per day translates to 24 watts of power, slightly more than half the amount of energy it takes to power a 40 watt light bulb and just over one-third of the power it takes to power a 60-watt laptop. Our muscles, in comparison, generate over 3 times the amount of energy (75 watts) and even more in short bursts (think Type II muscle fibers). Amazingly, the amount of energy the brain uses stays constant at 24 watts. This is attributed to some parts of the brain being more active while some are less active. However, the redistribution of blood flow from the less active to more active parts of the brain explains how the brain can use a constant amount of energy and never go above its daily requirements (Herculano-Houzel, 2016: 174).
When thinking about the overall brain size of a species, the amount of caloric energy that organ needs daily has to be taken into account. For instance, as noted previously, the human brain needs 129 grams of glucose or 519 kcal to run per day. Consuming the amount of kcal we need to keep our brains running efficiently is easy in the modern-day world: one cup of sugar contains the amount of kcal needed to power the brain all day. There is a trade-off between body size and number of neurons. Thinking about this from a metabolic point of view, there are metabolic limitations on how big a brain can get in comparison to how many kcal the primate in question consumes.
In her Ted Talk (starting at 10 minutes in), she talks about how there is a trade-off between body and brain size. She says that a primate that eats 8 hours per day would have 53 billion neurons if it weighed 25 kg, 45 billion neurons if it weighed 50 kg, if it had 30 billion neurons it would weigh 75 kg, if it had 12 billion neurons it would weigh 100 kg and the amount of neurons would not be viable if it weighed 150 kg. Keep in mind that primates eat 8-9 hours per day—which seems to be the upper limit on the amount of time they can spend eating. So you can clearly see there is a trade-off between brain size and body size—the bigger the body gets for a primate, the brain gets smaller. And, obviously, we humans got around that—but how?
Neurons are extremely expensive from a caloric point of view. Using our brains in the previous comparison, for a brain with 86 billion neurons in a body weighing g 60-70 kg, we should have to eat for over 9 hours to attain the caloric energy needed to power our huge (in terms of neurons) brains. And, obviously, eating for over 9 hours per day just to power our neurons isn’t viable. So how did we get so many neurons if they are so dependent on adequate kcal to power? The thing is, the energy availability in a raw diet never would have powered brains as big as ours (Azevedo and Herculano-Houzel, 2012).
Let’s talk about what we know so far: as detailed above, our brains cost just as much energy as it should and we can’t eat for over 9 hours a day to attain the amount of kcal in order to power and sustain our huge brains, how did our brains get so big?
There is a ‘simple’ way of getting around these energy restraints: cooking. Cooking allowed us to ‘pre-digest’ food, so to speak, before we ingested it. PumpkinPerson always talks about the ‘radical behavioral change’ that occurred, well it occurred with the advent of cooking allowing us to extract nutrients quicker from our food to power our big brain with 86 billion neurons. Without one of the most important events in human history, everything you see around you today would not exist. The best evidence we have is that our ancestors starting with the australopithecines and going to habilis and erectus, was that there was a huge increase in brain size and the only thing that could possibly explain such an increase was the advent of cooking. Our ancestors 1.5 million years ago showed the first signs of cooking, which led to the increase in brain size in our species. Fire played a huge role in our evolution and it could be argued that, without fire, we wouldn’t be here today (or, at least with our current cognitive ability). Our ancestors who were alive around that time did have the capability to make tools, so the digestion process could have begun outside the body by grinding and mashing food before it was eaten.
In sum, the human brain is not special. It follows the same laws as all other primate brains. It has the amount of neurons that are expected for a brain its size in a primate. We can either take ‘brains’ or ‘brawn’, meaning our brains will get smaller as our bodies get bigger and vice versa (in primates anyway). The size of our brains is completely predicated on the amount of caloric energy we intake. Human evolution was driven by fire when our first ancestors started to use it to cook to pre-digest food before eating it. That’s what drove the evolution of our bigger brains which started around 1-1.5 million years ago, and without the ability to consume quality calories with the right amount of nutrients for brain growth, human evolution never would have occurred how it did—especially for the evolution of our brains. Moreover, without the rise of bipedalism, our hands would have never been free to make tools, to use fire and cook food to get our bigger brains because, as shown above, the amount of hours we would need to eat would not be feasible to sustain the brain that we have.
The human brain is just a linearly scaled-up primate brain (Herculano-Houzel, 2009) and has the amount of neurons that a brain our size that an organism of our size would be expected to have. What sets us apart is the amount of neurons that are crowded into our cerebral cortex—16 billion in total—which is responsible for our cognitive superiority over other species on earth. Our overall brain size is not responsible for our domination and conquest of earth, it was the amount of neurons in our cerebral cortex that allowed for our cognitive sophistication over other animals on earth. What sustained our big brains with energy-demanding neurons was the advent of fire and cooking, which allowed us to consume the amount of kcal needed in order to carry around such big brains. The real “Human Advantage” is cooking which led to bigger brains and more cognitive sophistication due to the amount of neurons in our cerebral cortex, not our overall brain size.
The Threat of Increasing Diversity: Why Many White Americans Supported Trump in the 2016 Presidential Election
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Tl;dr: White Americans exposed to more diversity are more likely to support Trump, anti-PC speech and anti-immigration policies while showing less support and positivity towards Democratic candidates. In the racial shift group, whites with low racial identity, ethnic replacement didn’t seem to care about ethnic replacement and showed stronger support for Democratic candidates. To wake up more whites to anti-immigration sentiments and white identity politics, you need to show them the effects of diversity in the social context as well as what a demographic replacement will mean in the next two decades.
Why did so many white Americans support Donald Trump’s Presidency? The reasons are numerous, though there are some key reasons why he won. To look at the exact reasons why, we need to look at some evolutionary psychology as well as political psychology. I came across a paper today titled The threat of increasing diversity: Why many White Americans support Trump in the 2016 presidential election, it has many thought provoking things in it and pretty much confirms what the altright says about an increase in white identity occurring. An ‘ethnic awakening’ if you will. The authors state that white Americans high in racial identity will be more likely to derogate out-groups when white Americans realize they are becoming replaced in their own country.
Major, Blojorn and Blascovich (2016) state that reminding white Americans who are ‘high in ethnic identification’ (i.e., a white identitarian, an altrighters) that non-white populations will soon outnumber whites caused them to be more concerned about the future of whites in America, pushing them towards Trump and his anti-immigration policies. This also led to an increase in being politically incorrect. Moreover, whites low in ethnic identification (say, a progressive leftist) showed no greater chance in voting for Trump nor his anti-immigration policies. This did, however, decrease positivity towards Trump as well as decreased their opposition towards political correctness. The authors write:
The U.S. Census Bureau (2012) projects that the national population of non-White racial groups will exceed that of Whites before the middle of this century. Many White Americans in the US view race relations as “zero-sum,” in which status gains for minorities means status loss for Whites (Wilkins & Kaiser, 2014) and less bias against minorities means more bias against Whites (Norton & Sommers, 2011). The belief that Whites are losing out to ethnic minorities is particularly prevalent among Trump supporters (De Jonge, 2016).
This is noticed, anecdotally speaking and you can follow the citations to get more information. From an evolutionary perspective, this does make sense. Competition for resources between groups trigger evolutionary instincts. More non-whites in America will decrease the white population who has the lowest birth rate by ethnicity in the country and this will trigger more anti-immigration sentiments in whites high in ethnic identification. This ‘zero-sum game’, the ‘if your ethnic group has more than mine has less’ game will start to take hold in America in the next coming years if this paper is any indication of the future. The one particularly interesting point the authors bring up is that if there is “less ‘bias against minorities, there will be more minorities against whites”, and that, in turn, increased anti-immigration sentiments as well as drove people towards Trump and his anti-immigration views.
The more minorities that come into the country, the more whites in America will start to band together for their own ethnic genetic interests, move towards more conservative policies and begin to show more derogation towards the out-group.
The authors use the term ‘group status threat’, which is when one “worries that his group’s status, influence, and position in the hierarchy is under threat.” This threat then predicts out-group derogation. I wonder if oxytocin (a brain peptide that increases out-group derogation) increases when diversity occurs in the social context. I’d like to see that looked into one day.
There is also ‘integrated threat theory’ where increased diversity poses a threat to white Americans’ resources and American values. They also state, using social cognition theory, that increases in diversity will be ‘frightening’ and ‘confusing’ to whites, causing “uncertainty and fear”, which then drove whites towards more conservative anti-immigration policies.
When whites high in ethnic identification were shown a newspaper article stating that whites would be a minority by 2042, it led whites to be more concerned about whites’ social status in the country, leading them towards more conservative views and policies. It’s important to note that their views changed along with their policy recommendations.
In this study, the authors tested experimentally whether reminding white Americans that of the increasing diversity in the US affects their political leanings, whether or not group status is the cause of the political leanings when one hears about ethnic replacements, and whether or not ethnic identification or political alignment moderated the effects. They expected that reminding whites of ethnic replacement will cause them to lean towards conservative views and politicians (Trump, Kasich, Cruz) while decreasing support for Democrats (Clinton and Sanders).
People who experience ‘group status threat’ will be more likely to vote for Trump since he has more anti-immigration, antidiversity views than all politicians who ran for President. This, the researchers hypothesized, would come to fruition in their study. They also predicted that reminding white Americans of ethnic replacement would cause them to support more anti-immigration policies and be more resistant to political correctness, i.e., they would be more likely to be against positive policies for the out-group. They would become intolerant towards the out-group upon exposure to the reality of ethnic replacement in the country.
We also tested ethnic identification and political affiliation as potential moderators of the predicted effect of condition.1 Drawing on social identity theory (Tajfel & Turner, 1986), we expected that reminders of increasing ethnic diversity would be especially threatening to Whites whose race/ethnicity is a central aspect of their identity. Thus we expected them to report greater support for Republican candidates, anti-immigrant policies, and opposition to political correctness in response to reminders of the racial shift compared to Whites low in ethnic identification. In contrast, based on Craig and Richeson’s (2014b) finding that reminders of the racial shift increased support for conservative ideology irrespective of political leanings, we did not expect political affiliation to moderate effects.
Whites whose ‘race/ethnicity is a central aspect of their identity’, i.e. altrighters were predicted to be especially threatened at the reminder of ethnic replacement in their country of birth. However, as expected and what is seen in anecdotal accounts, whites low in ethnic identification, i.e., progressive leftists, antifas, etc, showed the opposite.
The researchers had a sample consisting of 450 white Americans with the following political beliefs: 262 Democrats, 114 Republicans, 50 Independents and 24 ‘other’. After removing the Independents and ‘others’ from the sample they had 376 white American participants (51.1 percent female).
They were given articles and were given two minutes to read them. One was an article talking about the ethnic replacement of whites and whites’ minority status in America that’s projected to occur by 2042 (aptly called ‘racial shift’) while the other article used “similar language to indicate geographic mobility is increasing (control condition).” It’s interesting to note that it seems like the only difference between the two articles is the wording. After reading the articles, they then completed tasks assessing group status threat, support for the current candidates running for office, anti-immigration sentiments, ethnic identification, and opposition to political correctness. After the completion of the tasks, they were then told the reason for the study and compensated their one dollar.
White Americans exposed to ‘racial shift condition’ reported greater group status threat than those in the control condition. This shows that white Americans who live in a diverse neighborhood will be more likely to be affected by the ‘racial shift condition’, leading them towards anti-immigration sentiment, a strong feeling towards white identity, and be more likely to hold more right-wing views. Whites high in ethnic identification showed greater group status threat than the control (.29) in the racial shift condition while whites low in ethnic identification did not. So, white identitarians showed a greater feeling of threat towards the group than did progressive leftists and antifas. Can’t say I’m too surprised. I did theorize in my article on the rise of the altright that either leftists have less oxytocin and altrighters have more, or that since political beliefs are heritable that high amounts of oxytocin will have one gravitate towards using their altruistic tendencies for the out-group or the in-group. This seems to be some evidence for my theory. For both right-wingers and left-wingers, ethnic identification was positively related to group status threat, but it was stronger in right-wingers. Even more evidence for my oxytocin/political beliefs theory.
White identitarians (whites high in ethnic identification) reported moderately greater positivity towards Trump as well as an even greater chance of voting for him in the racial shift scenario compared to the geographic movement scenario. Conversely, whites low in ethnic identification (progressive leftists, antifas, etc) showed less positivity towards Trump in the racial shift condition than in the geographic movement (control) condition,. However, in the racial shift condition, when one had high ethnic identification it led to increased positivity and a higher chance of voting for Trump. However, in the geographic condition, ethnic identification was unrelated to positivity towards Trump as well as voting for him.
Whites who showed less identification showed somewhat less support towards Sanders, being somewhat less likely to vote for him in the racial shift condition than in the geographic movement condition. In whites low in ethnic identity, neither condition (racial shift or geographic movement) had any effect on voting for Sanders or positivity towards him. Now here’s the good part: in the racial shift condition, whites high in ethnic identity showed somewhat less support and positivity towards Sanders in the racial shift condition compared to the geographic shift condition. Moreover, in the racial shift condition, ethnic identification was negatively correlated with positivity and chance of voting for Sanders, whereas in the control condition ethnic identification showed no effect.
In the racial shift condition, white identitarians were more supportive of anti-immigration policies than progressive leftists, while whites low in ethnic identification showed no difference, regardless of the condition. Ethnic identification was related to anti-immigration policies in both the racial shift and geographic movement conditions, but it was stronger in the racial shift condition.
White identitarians did not differ in outlook on political correctness by condition, while whites who show less ethnic identity reported less opposition to political correctness. Ethnic identification and anti-PC views were positively related in the racial shift condition but unrelated in the geographic shift condition.
Exposure to the racial shift condition vs. the geographic movement condition elicits different responses based on one’s political alignment and ethnic identification. Exposure to the racial shift condition increased group status threat, support for Trump and support for anti-immigration policies while somewhat decreasing support for Sanders, but only among whites high in ethnic identification. Conversely, for whites low in ethnic identification in exposure to the racial shift, there was no effect on group status threat, support for Sanders or anti-immigration sentiments and actually led to a decrease in positivity for Trump. That’s pretty powerful right there.
The support and election of Donald Trump is showing a paradigm shift in this country as ethnies in America start voting on racial lines. As diversity continues to increase and as more white Americans begin to realize the ethnic replacement will begin to impede on how many resources they have access to as well as the ‘racism being flipped on them’ with ‘less bias on minorities being more bias towards whites’, more and more whites will start voting not on party lines, but ethnic lines like all other ethnies in this country do. In the racial shift group, whites high in ethnic identification showed increased support for Trump and anti-immigration policies, increased opposition towards political correctness and decreased Sanders support through group status threat. Conversely, in the racial shift group, reminders of ethnic replacement in whites low in ethnic identification showed decreased Trump support and his policies and did not lead to group status threat. This can be termed ‘ethnic suicide’. Clearly, increased diversity is a threat to some but not all white Americans.
What boggles my mind is that when whites low in ethnic identification were reminded of the projected ethnic replacement by 2042, they decreased support for Trump and increased support for anti-immigration policies and their support for norms that prohibit bias in hate speech, which was not mediated by the group status threat. The authors put forth one theory why this may be the case. They say that whites low in ethnic identification were thinking of the changing racial demographics on the country as a whole, not just on their own ethnic group which may have led them to support a candidate who is tolerant of diversity and antibias norms. Reminding Americans high in racial identity of ethnic replacement increasingly shifted support to Trump and away from Sanders. Though this effect was not seen in relation to other candidates, the authors attributed this to Trump’s stance on immigration and political correctness relative to the other Republican candidates. To those white Americans with a high racial identity who experience group status threat, they would be drawn to Trump and his anti-immigration, anti-PC speech. The authors state:
Of all of the candidates, Trump has been most vocal in his opposition to “outsiders” such as Muslims and illegal immigrants from Latin America, and most openly critical of “political correctness” in both his rhetoric and his behavior. Trump’s rhetoric and policies thus appear to hold special appeal for White Americans highly in racial/ethnic identification who are concerned about the declining position of Whites in American society and who often perceive reverse discrimination as prevalent. In contrast, Sanders may have been perceived as the most inclusive candidate and thus most likely to exacerbate threats to White’s status as a group.
This sums up the 2016 election in one paragraph. White Americans high in racial identity showed a greater chance to vote for Trump, greater opposition to political correctness and were more likely to espouse anti-immigration sentiments.
Political leaning affiliation had a large and expected effect on candidate choice as well as policy preferences. Compared to Dems, Republicans reported much stronger support for Republican candidates than Democratic candidates while being more supportive of anti-immigration and “more un-PC attitudes”. However, when reminded of ethnic replacement, both Democrats and Republicans who showed high racial identification were more likely to lean right and vote Trump. This study shows important implications about group identity and intergroup process to voting preferences. In whites high in racial identity, increased racial diversity affects voting preferences amongst whites, with the strength of the racial/ethnic identity moderating the effect. I.e., the stronger a racial identity one has the more likely they are to support Trump and anti-immigration policies, irrespective of political leaning. Due to this study, psychologists and political scientists need to begin to pay attention to the increasing concerns of whites high in racial identification, while traditionally thinking that white Americans’ politics weren’t driven by white identity, deeming them to be unimportant to whites’ political outlooks. For example, one study showed that “racial identification, perceptions of discrimination, and linked fate were only weak predictors of White Americans’ attitudes on policies related to race and immigration. This led them to conclude that “Whites’ whiteness is usually likely to be no more noteworthy to them than is breathing the air around them” (Sears and Savelli, 2006, p. 901).
However, the current political climate shows that this no longer is the case. As more non-whites immigrate into America, whites who have high racial identity, irrespective of political leaning, will become more open to supporting Trump (or people like him) as well as anti-immigration policies. As the white majority in America shrinks, more and more white Americans will be open to white identity politics to get back their rightful resources in the country as well as the demographic majority. Eventually, with more and more unchecked immigration, white identity will start to become a central part in white American politics and voting blocks. White Americans who regard their identity as ‘white’ and an important part of their identity, future white American political preferences will be molded by group status threat as well as opposition to diversity. Trump has ‘tapped into’ the demographic of white Americans who feel looked down on in their own home country from mass immigration from the South (and soon from MENA countries). White Americans who feel that their numerical advantage is threatened are more likely to vote for Trump and support anti-immigration policies that will begin to benefit American whites.
It is, however, important to note that Trump may not be who he says he is (like most politicians). On election night last month I blogged on Donald Trump and Ethnic Genetic Interests. I showed that contrary to the average perception of him, his interests lie with Israel, not with his own racial group (due to his children marrying Jews). Moreover, he has already reneged on his wall, deporting illegals and his supposed moratorium on Muslim immigration into the US from threat countries. If anything, Trump is just a stepping stone towards more nationalistic attitudes in the US for whites. With the increased diversity, whites will start to see that they are becoming replaced by other ethnies and in whites with high racial identity, it will trigger nationalistic attitudes and responses to the impending threat on their unique genetic code. This will help to foster the awakening of more whites to identity politics, voting in their own ethnic interests and not for the interest of other ethnies.
I personally hope this leads to a renaissance of race-realism in America, but I may be aiming the bar too high. The conclusion of this study is hopeful for the status of whites in America, however. The more whites that get exposed to diversity AND have high racial identity will then lean more towards Trumpian policies. As whites decrease in number in the US, more and more whites will begin to vote for themselves and, in my opinion, once these nationalistic attitudes appear in the white consciousness in America, this demographic replacement can begin to be reversed. If it were not for the increased immigration, however, this would not have happened. The increased immigration is a main driver of these feelings towards political correctness and anti-immigration. The more anti-white sentiment that is heard in America, the more whites high in racial identity will move towards the right while leftists will continue to commit ‘ethnic suicide’.
The takeaway from this paper is this: Whites exposed to the racial shift high in racial identity were more likely to support Trump, anti-immigration policies and be anti-PC. Whites in the racial shift condition who showed low racial identity showed the opposite and were more likely to vote for Democratic candidates. This paper shows good news in the future for whites in America and voting in their interests. Whites in America are beginning to vote for their ethnic genetic interests and this is largely due to genetic similarity theory as immigration from MENA countries and South of the border increase into America. Moreover, with Trump’s allegiance to Israel, Trump is just a man to awaken more people to the realities of immigration. So Trump himself won’t do anything, but his anti-immigration rhetoric is having people notice the realities of immigration and ethnic replacement in America.
Oprah, Weight Watchers, and Big Food Shilling
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The stock of Weight Watchers rose 19 percent after Oprah endorsed their ‘diet system, claiming to have lost 40 pounds. Keep in mind that Oprah has a history of ‘eating bread’ to lose weight. Oprah, ‘the most powerful black woman in the world’, according to Pumpkin Person. She does all of these good things, so she’s such a good person! Well, I don’t think a ‘good person’ would shill for Big Food at the expense of the health and metabolisms of the people she supposedly cares about so much.
One reason why this (usual) endorsement by Oprah for Weight Watchers is that, to be frank, Weight Watchers is a garbage company who wants nothing other than their clients’ money and not for them to ‘succeed’ in their goals. Because to them, a repeat customer is a good customer. They don’t want to keep a revolving door of clientele, all they want to do is keep the same suckers and fool them into spending more money on magic diet secret #494949228742874827482….. This, however, is where Oprah, Big Food Shill comes in.
The stock for Weight Watchers soared in recent weeks, when it was announced that Oprah had lost 40 pounds eating “pasta and tacos” (I’ll return to that later). Last October, Pumpkin Person reported that Oprah stood to make 100 million dollars in 36 hours due to the stocks she bought in WW, not even thinking about how horrible of a company WW is.
Oprah has said herself that she’ll “never quit Weight Watchers“, but if you had a stake in Weight Watchers worth 77 million dollars, wouldn’t you say that you would ‘never quit Weight Watchers’? Notice how she’ll be ‘counting points’ the rest of her life and she said absolutely nothing about the quality of the food. She claims she ate ‘tacos and pasta’ to lose weight, and if that’s any indication of how she did it, she’ll be back up sooner rather than later.
Oprah herself has a long history of yo-yo dieting. Though studies are mixed, in some large-scale studies there is a relationship between yo-yo dieting (weight fluctuations) and increased mortality and cardiovascular disease. I lean towards there being a considerable shift in metabolism, slowing the metabolism. Because if you diet our of the set-point, your metabolism slows down as seen in The Biggest Loser study.
At the start of the show the average RMR was 2,607 +/-649 kcal per day, falling to 1,996 +/- 358 kcal per day at the end of the 30-week competition. Only one maintained weight loss after the 6 years and l regained weight as well as more fat that they bad previously (shocking, I know). The mean rate dropped to 1,996 +/- 358 per day with the researchers noticing that those who lost the greatest amount of weight had the biggest metabolic slow down. Despite then regaining their weight, their metabolic rate was 1,903 +/- 466 kcal per day.
Based on individual weights, the researchers concluded they were burning around 500 kcal less than would be expected of people that size. The one who lost the most weight, Danny Cahill, was burning 800 less kcal than a man his size who has never been obese.
This is not the only study showing this. Numerous other studies show that the body matches metabolism to how much one is ingesting. This is what the hawks at WW don’t tell you.
Put simply, Oprah has no idea how to diet nor has she ever tried a true low-carb diet. Oprah herself admittingly says that she only has ever tried the CAD (Carbohydrate Addicts Diet) with no success. The CAD diet is where one eats no carbs all day long until the end of the day where they’re allowed to consume carbohydrates for one hour. People assume this is a low-carb diet, but it’s really not. According to Dr. Micahael Eades, Oprah tried the CAD diet, the only ‘low-carb’ diet she’s ever tried, and she asked the authors of the book for the CAD diet if she can eat macaroni and cheese in her one-hour carb window (Dr. Oz, another Big Food shill pushes nutrition myths). The authors told her she most definitely could, and that she should toss in some apple pie while she’s at it. Dr. Eades says she was probably eating somewhere in the range of 300 kcal, which is why he so-called ‘low-carb diet’ didn’t work. She eats low-fat diets, complaining of hunger. She’s obviously ignorant to the fact that fat is a filling macro, and a very important one.
All of these advertisements and ad campaigns are to line her and Weight Watchers’ pockets even more. If someone like Oprah is pushing something, it’s best not to buy into it because it’ll probably largely be bullshit, especially if it’s for a multi-billion dollar company who stands to gain a ton from the publicity. Of course, Oprah does as well which is why she’d doing it, a company that she has a 77 million dollar stake in.
Big Food shills are rampant today. From Oprah to Mark Haub who pushed the twinkies diet who claims to have lost 27 pounds while eating 66 percent of his diet from junk food. But it recently came out that Haub was paid by Coca-Cola who, of course, had a vested interest in seeing a ‘positive’ result. Coca-Cola released a list of researchers who took funds from them in 2016 due to pushes for transparency by the public. His name was one of the names on the list.
If Haub’s claims are to be taken on the fact that it ‘worked for him’, then why don’t we take this n=1 claim? Scott Feltham didn’t gain any weight eating 5000 kcal a day for 21 days. Fact of the matter is, look into who funds what. Big Food (Coca-Cola) funds studies and people pushing questionable things? Look into it. Oprah is running shill advertisements for Weight Watchers despite being a yo-yo dieter her whole life? Look into her claims as well.
Here’s the truth about dieting: it doesn’t work. Table 1 shows 9 studies in which there were self-reported weights in comparison to a lab weighing. Table 1 also shows that the studies that had the highest percent n in follow-ups had the lower mean weight loss. This obviously suggest that study participants who don’t show a difference in weight don’t show up to follow-ups.
Also looking at table 1 we can see that for the studies with the most significant weight loss, they were 100 percent self-reported. They showed their analysis of 2 studies that fit their criteria; people would underestimate by 4.5 pounds, a statistically significant result that would skew results.
Also the average weight loss over those 5 years, is that something to celebrate? Six pounds? Self-report reports for weight are not good measurements for aj honest assessment of any possible weight lost. Low follow-up rates seriously hamper these studies, because if all people returned to them, the difference would be even worse.
The fact that there are Big Food shills such as Haub or Oprah are telling. They want to prey on the ignorance of the average American person who doesn’t know anything about dieting. The claim that diet quality does not matter is incorrect. People will vehemently deny that kcal quality is meaningless over kcal quantity. Traditional diets do not work. But that doesn’t stop Big Food shills like Oprah and Haub from pushing their garbage. This is where they know that the average person won’t take a look beyond what these highly embellished news stories write about sample sizes of one. They also believe anything Oprah says, like the low information people they are relying on the word of a woman who has never “succeeded” in the game of dieting because, as shown, they do not work.
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 Advice. The 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 Disease) over 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 generations. The 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.)
Science Proves It: Fat-Shaming Causes Weight Regain
950 words
Back in July, I refuted Milo Yiannopoulos’s article stating that fat-shaming leads to weight loss. I showed that fat-shaming exacerbates the problem and makes weight problems worse (ironic, because fat-shamers believe what they’re doing causes weight loss. Not according to any published study I’ve encountered), BMI categories need changing since the BMI with the lowest rate of death is one with BMI 27, and that, contrary to popular belief, metabolically healthy obese people do indeed exist (Bluher, 2012). Now the studies on weight-discrimination are from questionnaires, and one who objects could rightfully say “Well, fat people may think that anything is weight discrimination because they’re so self-conscious.” That is an extremely good point to bring up about these studies.
What do we know about weight discrimination? Those who perceive weight discrimination are more likely to either keep weight on or gain more weight over a long period of time. When one is shamed for their weight, cortisol levels should increase, which then increase insulin. Insulin causes obesity, so we can now see what occurs when cortisol is released in the body due to fat-shaming.
Just this past October, a paper was published in the journal Obesity called Perceived weight discrimination and chronic biochemical stress: A population-based study using cortisol in scalp hair. They took data from 563 non-smoking individuals from the English Longitudinal Study of Ageing. The participants in the study reported whether or not they have ever felt discriminated against in a questionnaire. Hair cortisol concentrations “were determined from the scalp-nearest 2-cm hair segment”. Height and weight were objectively determined. The following variables were controlled for: “age, sex, ethnicity, socioeconomic status, and BMI.”
What they discovered proves that fat-shaming makes the problem worse: the mean hair cortisol concentrations were 33 percent higher in those who had experienced weight discrimination than those who hadn’t! Moreover, the relationship between weight discrimination and elevated hair cortisol was worse for people who were classified severely obese (class II [30 to 34.9 BMI] and class III [BMI equal to or greater than 40]).
The authors conclude that weight discrimination is associated with the experience of stress at the biological level. I will repeat again for anyone who still believes that fat-shaming does anything: weight discrimination is associated with the experience of stress at the biological level. Chronic exposure to elevated levels of cortisol may play a role in exacerbating the abhorrent cycle of obesity and fat-shaming, causing further health problems. I’d love to see how people who believe that fat-shaming works would respond to this paper. It’s plainly written clear as day that fat-shaming causes stress at the biological level.
Cortisol is an essential hormone we secrete during times of stress. Cortisol is secreted in response to a stressor, in order to help you cope with that stressor efficiently. Exercise (hunting for our ancestors), disrupts homeostasis because of the stressors that are put on the body. The stressors then require an adaptive response, which is cortisol. Most anything our ancestors did disrupted homeostasis, causing cortisol to be secreted. Because of increased cortisol levels during times of need, you can push through certain things than if you didn’t have that cortisol increase due to the stressor that made your body secrete the extra cortisol.
Cortisol is secreted as a response to stressors. Basically, we secrete cortisol so we can better deal with stress. Clearly, fat-shaming is stressful; which is seen in hair cortisol concentration. There is now biological evidence that fat-shaming leads to cortisol secretion.
During times of stress, the hormones cortisol and insulin rise together, sending a strong signal to the body to store fat. Now think of this from an evolutionary viewpoint. For our ancestors, times of stress included but were not limited to: running from predators, chasing prey, times of famine, etc. When food was scarce for our ancestors, cortisol was secreted and what little food our ancestors did eat was more easily stored as body fat. Knowing the biological reasons WHY cortisol is associated with the storage of body fat and weight gain is imperative for our understanding of this phenomenon.
With the rising rates of obesity in the first-world, we need to discover the hormonal causes of obesity. Since CICO is irrelevant to human physiology, current research should be directed to discovering which hormones exacerbate obesity and how we can curb these problems.
It’s clear that fat-shaming doesn’t work. Idiots like Milo who either a) only read ‘what they agree with’ or b) read a paper they DON’T agree with while cherry-picking from the paper what supports their claim. It’s clear that fat-shaming doesn’t work; it’s clear that fat-shaming causes biochemical stressors that exacerbate weight gain and further make the problem worse. Whoever truly believes that fat-shaming works, do me a favor. Do a bit of reading into the literature on this subject and let me know what you think. Let me know if you discover a study showing that fat-shaming works. I’ll make it easy for you: you won’t discover a study like that because they do not exist (save whatever studies Milo spun to ‘prove his point’).
Fat-shaming exacerbates the problem of obesity and, contrary to fat-shamers, it makes the problem worse. If one truly believes that fat-shaming works to ‘help’ people lose weight, they should then find other, actual ways to help cull the 70 percent obesity rate in America at the moment. One more thing: your friend who got made fun of and lost weight and kept it off (a double rarity) does not refute this data, so you’ll have to address what is written in this article if you would like to prove me wrong. N=1 doesn’t say anything to what is written in this article.
Are Caesarian Sections Affecting Human Evolution?
1100 words
Our brains are the most metabolically demanding organ we have, sapping 5-600 kcal per day (25 percent of our daily energy needs). Due to how cost-efficient the brain is, it only would have evolved if it gave us a bigger fitness advantage (which it obviously did). In the news a couple of days ago, it broke that C-sections may be affecting our evolution. But in all of the articles I read about it I didn’t see any one of them talking about how C-sections may affect human evolution in America between race. Clearly, if C-sections are having this effect on the country as a whole, there must be racial differences as well. Could this have an effect on brain size between race in America?
C-sections have increased in frequency since 1996. Clearly, if there is any selection it’s for more narrow-hipped women and bigger-brained babies. The regular use of C-sections has led to an evolutionary increase of fetopelvic disproportion rates by 10 to 20%. (Mitteroecker et al, 2016) Fetopelvic disproportion is the inability of a babe’s head to pass through the mother’s birth canal. This is because the head—and along with it the brain—is too big, leading to emergency C-sections. Mitteroecker et al (2016) also say (which slightly amused me):
Mitteroecker et al (2016) also say (which slightly amused me):
Neonatal size and maternal pelvic dimensions influence fitness (i.e., reproductive success) of the newborn and the mother in multiple ways. Undoubtedly, relative brain size had increased during human evolution in response to directional selection. Recently, it has also been suggested that the large human brain may be the result of runaway selection for the childcare of infants that are born prematurely because of their large brain (12). It is unclear whether any of this selection still persists after the slight decrease of brain size in the late Pleistocene. However, birth weight, which correlates with brain size at birth, is strongly positively associated with infant survival rate (13) and has also been reported to correlate negatively with the risk of multiple diseases (14). Reducing neonatal brain size by shortening gestation length seems to be equally disadvantageous: Delivery before term clearly increases the likelihood of impaired cognitive function in later life (15, 16).
Brain size is decreasing. Associate professor of anthropology at the University of Wisconsin John Hawks also states in his blog post, Selection for smaller brains in Holocene human evolution, where he says (contrary to Pumpkin Person’s assertion) that human brain size has gotten smaller in the past 10,000 years:
The available skeletal samples show a reduction in endocranial volume or vault dimensions in Europe, southern Africa, China, and Australia during the Holocene. This reduction cannot be explained as an allometric consequence of reductions of body mass or stature in these populations. The large population numbers in these Holocene populations, particularly in post-agricultural Europe and China, rule out genetic drift as an explanation for smaller endocranial volume. This is likely to be true of African and Australian populations also, although the demographic information is less secure. Therefore, smaller endocranial volume was correlated with higher fitness during the recent evolution of these populations. Several hypotheses may explain the reduction of brain size in Holocene populations, and further work will be necessary to uncover the developmental and functional consequences of smaller brains.
The reduction in brain size began around 28 kya and accelerated around 10 kya after the dawn of agriculture. The planet getting warmer also played a part in the decrease in brain size, which also allowed for the beginning of agriculture. Anyway, I’m sidetracking, I will return to this point in the future.
Large brains were also selected for since we needed to care for helpless babies. Natural selection for large brains led to more premature births which itself selected for even larger brains.
One-hundred years ago, a narrow-hipped mother who was pregnant with a big-headed baby would have died. Narrow-hipped women with big-headed babies can now survive, transmitting genes for both big brains and narrower pelvises. This is natural selection currently at work as we speak.
One thing that I obviously didn’t see in any article I’ve read on this matter is how will this affect racial differences in brain size? Which race has the most C-sections and will that select for bigger heads and smaller pelvises in that population?
Black women are substantially more likely to deliver by C-section than are white women (pg. 4). Though, one reason that C-sections occur is due to obesity. Black women are the most likely to be obese, which is part of the reason why they have more C-sections. If this trend continues, I could see a slight uptick in black brain size, as even smaller hips get selected for in black women, along with an increase in brain size. That’s one reason why Africans have smaller heads and brains than East Asians and Europeans: they have narrower hips which allows for better athleticism. Conversely, Europeans and East Asians have wider hips which allows for bigger-brained children but hampers athletic ability.
While on the topic of race and C-sections, Asian female-European Male couples have higher rates of C-sections. The obvious explanation is that the Asian woman’s pelvis is too narrow to birth bigger babies. In the study, Asian female-white male couples had babies that had a median weight of 8 pounds, while Asian-Asian couples had babies that had a median weight of 7.1 pounds and finally Asian male-white female couples’ babies had a median weight of 7.3 pounds. However, Asian female-white male couples had an increased rate of C-section deliveries, proving that a significant differences exist between sex of the parent (whether the father or mother is Asian or white influences birth weight) which leads to increased C-section rates due to the white father passing clearly influencing the birth weight more, thusly making it difficult for his Asian partner to birth the baby. There are 100 deaths per 100,000 live births per year in the U.S., a rate of .1 percent. Clearly, though the death rate is low, C-sections lead to maternal mortality and since Asian females are more likely to have a C-section when the father is white due to the baby being bigger, the mortality rate is slightly increased when this interracial pairing occurs.
C-sections are causing natural selection, favoring for bigger heads and narrower hips. This helped us, evolutionarily speaking, as human bipedalism is promoted by a narrow pelvis. C-sections could possibly select for bigger-brained African Americans. Though brain size has decreased in the past 10,000 years, our brain size will slightly increase over time due to this selection pressure. Asian women and white male couples have C-sections more often. Pretty good case against race-mixing, if I don’t say so myself.
Social Sciences and the Denial of the Evolution of Human Behavior
1900 words
What causes people to deny the evolution of human behavior? The denial of evolution’s effect on human behavior got a kickstart from E.O. Wilson’s book that attempted to unify the social sciences—Sociobiology: A New Synthesis—and there was a heated debate about Wilson’s thoughts on where the study of sociobiology would go. Sociobiology was almost immediately rejected by social scientists upon its release, while Wilson and others believed that by providing a model of underlying evolutionary influences on humans, if integrated into their models, would cause a unification of the social sciences. if integrated with social scientists’ and cultural anthropologists’ study of the effects of culture on human behavior,would unify them. The social science have been seen as incompatible with sociobiology, due to focusing on how culture shapes behavior, while disregarding any evolutionary explanations in behavior. I will discuss the study in the paper The Lack of Acceptance to Evolutionary Approaches to Human Behavior, which discusses the history of sociobiology, the sociobiology wars, a questionnaire given to UK university students on the evolution of human behaviors. The main aim of the study was “to evaluate whether there is evidence that studying certain academic disciplines, specifically the social sciences and sociocultural anthropology, correlates with rejection of the relevance of evolution to human behaviour.”
Darwin’s cousin, Sir Francis Galton, coined the term eugenics in the late 1800s. Galton was interested in Darwin’s idea of heritable behavioral characteristics, but entered soon to be muddy waters when he suggested that only positive traits be selected for while attempting to weed out deleterious ones. The authors of the paper, Perry and Mace, say that Darwinian and Galtonian ideas were used to “to justify right-wing capitalist ideology and racist immigration policy (ROSE and ROSE 2000; LALAND and BROWN 2002).” This is describing what occurred in the early 1900s with the acceptance of eugenics in the West. They bring up so-called “culturally biased IQ tests” that were regarded as proof for innate differences between the races (they aren’t biased) which the lead to immigration restrictions for certain races and ethnicities in the 1924 immigration act.
They then bring up how Social Darwinists believe that evolution is progressive and whites were the “most evolved race” (yawn). They believed in evolutionary progress and a unilinear track to evolution.
They then bring up the infamous Franz Boas who stated that differences between societies were purely cultural which regarded behavior as shaped by culture, shifting the burden of proof from nurture to nature.
E.O. Wilson’s book Sociobiology was the first attempt to fuse animal and human studies “using neo-Darwinian evolutionary approaches to understanding social behaviour. . .” Why should mankind be swayed from studying himself, thought Wilson. Wilson wrote that evolutionary history has resulted in selection for certain genetic predispositions for in modern behavior. Hamilton’s kin selection and inclusive fitness theories (also the base for genetic similarity theory/ethnic genetic interests) were a backbone to Wilson’s new approach, using them to explain interactions between individuals. Other important ideas for the new synthesis was Dawkins’s selfish gene theory, which uses the metaphor of bodies being vehicles for genes (the replicator) and the idea of reciprocal altruism from Trivers, which accounted for cooperation amongst unrelated individuals (also integrated into Rushton’s genetic similarity theory). Perry and Mace write on page 109:
Behavioural traits, like physical traits, can be genetic adaptations, and genes influencing phenotypic traits which result in higher inclusive fitness for the organism will be selected for and will propagate in future generations. Using this basic principle of natural selection, WILSON (1975; 1978) claimed that many human behaviours, for example male promiscuity, incest avoidance and hostility to strangers, are genetic adaptations (BATESON 2008).
Typically enough, Sociobiology was hated by the left and had good reception from biologists. At the forfront of the discontent for the book were the usual suspects: Gould, Lewontin (these two led a “Sociobiology book club”), Rose, Kamin and others. The group accused Wilson of being a eugenicist, supposedly linking it with racism, biological determinism and Nazi policies. Wilson denied these accusations, not knowing what had occurred due research such as this. (pg 110).
On page 113, Perry and Mace write:
From an evolutionary perspective, culture has a biological basis and is expressed as socially transmitted information grounded in psychological capacities for symbolic thought, language and learning (RICHERSON and BOYD 2005; CRONK 1995; GINTIS 2007; MESOUDI, WHITEN and LALAND 2006).
Eloquently stated. Culture is passed down from generation to generation as a sort of phenotypic matching for genetically similar others. Culture survives each generation and is passed down from parents to siblings, grandparents to siblings, and so on. Whichever culture provides a society the best chance to survive and pass on its genes will be one that prospers in a society. A people (most likely) will not adopt a culture that’s the opposite of what is good for them fitness-wise. Of course culture that’s transmitted from generation to generation can be Darwinian if it has an impact on fitness. So the question is really this: What is the evolutionary basis for that people’s behaviors and their cultural norms? What happened in that people’s evolutionary history for them to pick up these customs that theoretically increased their fitness?
An online questionnaire was given to students and faculty at the UCL and UK universities over the summer of 2007. The questionnaire was made to gather information on the student’s attitudes towards science, evolution along with their application to human behavior, religious belief and education. The final sample was 7621 individuals after the removal of faculty.
Perry and Mace put forth three hypotheses:
a) A social science background will decrease acceptance of the relevance of evolution to human behaviour. Conversely, a biological / scientific background will increase acceptance.
b) Greater knowledge of evolution will increase acceptance of evolutionary approaches to human behaviour.
c) Religious belief will decrease acceptance of the relevance of evolutionary theory applied to human behaviour.
Below are some questions from the questionnaire and their factor loadings:
a) Component Variables – Acceptance of the Relevance of Evolution to Human Behaviour
The evolutionary history of humans is relevant in studying human behaviour (q. 39) .659
Human behaviour can be explained in the same way as that of other animal species (q. 32) .587
Humans are a species of animal, related to other species (q. 29) .430
I am interested in the theory of evolution (q. 20) .416
The social sciences provide a greater understanding of humans and their behaviour than evolutionary theory (reverse) (q. 40) –.727
b) Component Variables – Religiosity
Would you describe yourself as religious? (q. 12) .880 Were you brought up with religious views? (q. 13) .776
A spiritual / supernatural influence can explain the nature of life and the world (q. 19) .766
Table 2 of the study shows that current discipline is the best predictor, explaining 9.1 percent of the variance in Acceptance of the Relevance of Evolution to Human Behavior. In that particular percentage of variance, the most important significantly negative predictor of Acceptance of the Relevance of Evolution to Human Behavior ” is studying social sciences (compared to disciplines unrelated to science and human behaviour).” What this indicates is that social scientists are more likely to reject evolutionary explanations for human behavior, followed by religious studies and sociocultural anthropology. Though, of course, biological science, biological anthropology, and psychology had the strongest positive relationship with the Acceptance of the relevance of evolution to human behavior. Not too shocking.
Also discovered was that as religiosity increased, acceptance for evolutionary explanations for human behavior decreased. Those with stronger religious beliefs are more likely to reject evolutionary explanations for human behavior.
Surprisingly, Perry and Mace write:
Holding left-wing political views has a positive relationship with Acceptance of the Relevance of Evolution to Human Behaviour. This result does not support the commonly held assumption that individuals in favour of evolutionary approaches to human behaviour have a right-wing bias.
They also discovered that, within the social sciences, knowledge of evolution was the most important predictor of the acceptance of the relevance of evolution to human behavior. How much exposure one is given to evolutionary theory strongly predicts whether or not they believe if it shaped human behavior? This can be remedied by better teaching the theory of evolution to our youth.
The number of years studying social science has a significant negative relationship with accepting that evolution has shaped human behaviors. The Boasian belief that only culture dictates behavior still permeates our universities today. These results, Perry and Mace write, may show that these beliefs are culturally transmitted themselves. Bias against evolutionary beliefs in human behaviors increases the longer one studies social science.
The results of this questionnaire show that exposure to evolutionary theory needs to occur at a younger age, as knowledge of evolution is low which is one variable that leads to the non-belief of evolution on human behavior. Moreover, what the study showed was that it wasn’t the beliefs of those individuals that had them select the courses, suggesting that it was a bias towards sociobiology was transmitted to them culturally. This shows how left-wing biases run high, at least in certain UK universities, which then clouds an individual’s judgement due to getting an adequate education about evolution and growing up in an environment that explicitly denies evolution for religious reasons. Religion showed a negative relationship with believing that evolution has shaped human behavior. Religious people are very likely to deny evolution, due to being ignorant of evolution’s processes or outright denying it because it contradicts the Bible.
Sadly enough, only 62 percent of Americans believe humans evolved over time, with 33 percent of them believed that humans and other living things evolved solely due to natural processes. Twenty-five percent of US adults believe that evolution was guided by a supreme being while 34 percent of Americans reject evolution entirely and believe that humans and animals have existed in their present form since the beginning of time. Fifty-seven percent of evangelicals believe that Man has always existed in his present form with half of Mormons and about 75 percent of Jehovah’s Witnesses rejecting evolution. Fifty-eight percent of Southern Baptists and sixty-seven percent of the Seventh Day Advent Church denied that humans evolved over time. Conversely, 30 percent of protestants, 29 percent of Catholics, 16 percent of Jews and 15 percent who don’t affiliate with a religion share the same view. This Pew Poll shows that evolution denial correlates strongly with religious affiliation.
Whatever the case may be, teaching evolution at a younger age can increase knowledge of evolution among people who may choose these majors, and may even persuade them from not choosing them since they will learn that biology is a better explanation for human behavior, with human culture largely coming from biology (there is a Lamarckian aspect to human culture). Evolution clearly caused differences in human behavior, and the denial of this reality has impeded our understanding of human evolution and human nature as a whole. Once people are more educated in evolutionary theory they can stop clinging to full-on cultural explanations for behavior and embrace the reality that evolution is the cause for human behavior and sociocultural differences. The social sciences, specifically cultural anthropology, is at the forfront of the denial of evolution in human behavior, and once the public as a whole has a better understanding of evolution.
People need to stop denying scientific truths: that man is the product of natural forces. Once our societies become better educated as a whole in evolutionary theory, we will then see a reduction of religious behavior as well as enrollment in cultural anthropology and sociocultural anthropology—at the very least radically changing the base of those disciplines.
NotPoliticallyCorrect 