Meat is best for growing brains

(Emphasis ours)
“OBJECTIVE:
“This study was undertaken to assess the feasibility and effects of consuming either meat or iron-fortified infant cereal as the first complementary food.
“METHODS:
“Eighty-eight exclusively breastfed infants were enrolled at 4 months of age and randomized to receive either pureed beef or iron-fortified infant cereal as the first complementary food, starting after 5 months and continuing until 7 months. Dietary, anthropometric, and developmental data were obtained longitudinally until 12 months, and biomarkers of zinc and iron status were measured at 9 months.
“RESULTS:
“Mean (+/-SE) daily zinc intake from complementary foods at 7 months for infants in the meat group was 1.9 +/- 0.2 mg, whereas that of the cereal group was 0.6 +/- 0.1 mg, which is approximately 25% of the estimated average requirement. Tolerance and acceptance were comparable for the two intervention foods. Increase in head circumference from 7 to 12 months was greater for the meat group, and zinc and protein intakes were predictors of head growth. Biochemical status did not differ by feeding group, but approximately 20% of the infants had low (<60 microg/dL) plasma zinc concentrations, and 30% to 40% had low plasma ferritin concentrations (<12 microg/L). Motor and mental subscales did not differ between groups, but there was a trend for a higher behavior index at 12 months in the meat group.
“CONCLUSIONS:
“Introduction of meat as an early complementary food for exclusively breastfed infants is feasible and was associated with improved zinc intake and potential benefits. The high percentage of infants with biochemical evidence of marginal zinc and iron status suggests that additional investigations of optimal complementary feeding practices for breastfed infants in the United States are warranted.”

(Emphasis ours)
“Today the close correlation between head circumference growth and brain development in the last weeks of gestation and in the first two years of life is no longer disputed. A recently developed formula even allows for calculations of brain weight based upon head circumference data. Between the ages of 32 postmenstrual weeks and six months after expected date of delivery there is a period of very rapid brain growth in which the weight of the brain quadruples. During this growth spurt there exists an increased vulnerability by unfavorable environmental conditions, such as malnutrition and psychosocial deprivation. The erroneous belief still being prevalent that the brain of the fetus and young infant is spared by malnutrition, can be looked upon as disproved by new research results. Severe malnutrition during the brain growth spurt is thought to be a very important non-genetic factor influencing the development of the central nervous system (CNS) and therewith intellectual performance. In the past a permanent growth retardation of head circumference and a reduced intellectual capacity usually was observed in small-for-gestational age infants (SGA). Nowadays, however, there can be found also proofs of successful catch-up growth of head circumference and normal intellectual development after early and high-energy postnatal feeding of SGA infants. The development of SGA infants of even very low birth weight can be supported in such a way that it takes a normal course by providing good environmental conditions, such as appropriate nutrition – especially during the early growth period – and a stimulating environment with abundant attention by the mother.”

(Emphasis ours)
“OBJECTIVE:
“To quantify the relationship between brain volume and head circumference from early childhood to adulthood, and quantify how this relationship changes with age.
“METHODS:
“Whole-brain volume and head circumference measures were obtained from MR images of 76 healthy normal males aged 1.7 to 42 years.
“RESULTS:
“Across early childhood, brain volume and head circumference both increase, but from adolescence onward brain volume decreases while head circumference does not. Because of such changing relationships between brain volume and head circumference with age, a given head circumference was associated with a wide range of brain volumes. However, when grouped appropriately by age, head circumference was shown to accurately predict brain volume. Head circumference was an excellent prediction of brain volume in 1.7 to 6 years old children (r = 0.93), but only an adequate predictor in 7 to 42 year olds.
“CONCLUSIONS:
“To use head circumference as an accurate indication of abnormal brain volume in the clinic or research setting, the patient’s age must be taken into account. With knowledge of age-dependent head circumference-to-brain volume relationship, head circumference (particularly in young children) can be an accurate, rapid, and inexpensive indication of normalcy of brain size and growth in a clinical setting.

“Head circumference is known to correlate closely with brain volume (Cooke et al., 1977; Wickett et al., 2000) and can therefore be used to measure brain growth, but a single measurement cannot provide a complete insight into neurological development. Different patterns of early brain growth may result in a similar head size. A child whose brain growth both pre‐ and postnatally followed the 50th centile might attain the same head size as a child whose brain growth was retarded in gestation but who later experienced a period of rapid growth. Different growth trajectories may reflect different experiences during sensitive periods of brain development and have different implications for later cognitive function.
“We have investigated whether brain growth during different periods of pre‐ and postnatal development influences later cognitive function in a group of children for whom serial measurements of head growth through foetal life, infancy and childhood were available.”
[…]
“We found no statistically significant associations between head circumference at 18 weeks’ gestation or head circumference at birth SDS and IQ at the age of 9 years.”
[…]
“In contrast, there were strong statistically significant associations between measures of postnatal head growth and IQ. After adjustment for sex, full‐scale IQ rose by 2.59 points (95% CI 0.87 to 4.32) for each SD increase in head circumference at 9 months of age, and by 3.85 points (95% CI 1.96 to 5.73) points for each SD increase in head circumference at 9 years; verbal IQ rose by 2.66 points (95% CI 0.49 to 4.83) for each SD increase in head circumference at 9 months of age, and by 3.76 points (95% CI 1.81 to 5.72) for each SD increase in head circumference at 9 years; performance IQ rose by 2.88 points (95% CI 0.659 to 5.11) for each SD increase in head circumference at 9 months of age, and by 3.16 points (95% CI 1.16 to 5.16) for each SD increase in head circumference at 9 years.”
[…]
“[W]e interpret these findings as evidence that postnatal brain growth is more important than prenatal brain growth in determining higher mental function. This interpretation is supported by the finding that head growth in the first 9 months of life and head growth between 9 months and 9 years of age are also related to cognitive function, regardless of head size at the beginning of these periods.”

“The total content of zinc in the adult human body averages almost 2 g. This is approximately half the total iron content and 10 to 15 times the total body copper. In the brain, zinc is with iron, the most concentrated metal. The highest levels of zinc are found in the hippocampus in synaptic vesicles, boutons, and mossy fibers. Zinc is also found in large concentrations in the choroid layer of the retina which is an extension of the brain. Zinc plays an important role in axonal and synaptic transmission and is necessary for nucleic acid metabolism and brain tubulin growth and phosphorylation. Lack of zinc has been implicated in impaired DNA, RNA, and protein synthesis during brain development. For these reasons, deficiency of zinc during pregnancy and lactation has been shown to be related to many congenital abnormalities of the nervous system in offspring. Furthermore, in children insufficient levels of zinc have been associated with lowered learning ability, apathy, lethargy, and mental retardation. Hyperactive children may be deficient in zinc and vitamin B-6 and have an excess of lead and copper. Alcoholism, schizophrenia, Wilson’s disease, and Pick’s disease are brain disorders dynamically related to zinc levels. Zinc has been employed with success to treat Wilson’s disease, achrodermatitis enteropathica, and specific types of schizophrenia.”

• Babies who were born early or small.
• Babies given cow’s milk before age 12 months.
• Breastfed babies who after age 6 months are not being given plain, iron-fortified cereals or another good source of iron from other foods.
• Formula-fed babies who do not get iron-fortified formulas.
• Children aged 1–5 years who get more than 24 ounces of cow, goat, or soymilk per day. Excess milk intake can decrease your child’s desire for food items with greater iron content, such as meat or iron fortified cereal.
• Children who have special health needs, for example, children with chronic infections or restricted diets.

(Emphasis ours)
“Background: High intake of cow-milk protein in formula-fed infants is associated with higher weight gain and increased adiposity, which have led to recommendations to limit protein intake in later infancy. The impact of protein from meats for breastfed infants during complementary feeding may be different.
“Objective: We examined the effect of protein from meat as complementary foods on growths and metabolic profiles of breastfed infants.
“Design: This was a secondary analysis from a trial in which exclusively breastfed infants (5–6 mo old from the Denver, CO, metro area) were randomly assigned to receive commercially available pureed meats (MEAT group; n = 14) or infant cereal (CEREAL group; n = 28) as their primary complementary feedings for ∼5 mo. Anthropometric measures and diet records were collected monthly from 5 to 9 mo of age; intakes from complementary feeding and breast milk were assessed at 9 mo of age.
“Results: The MEAT group had significantly higher protein intake, whereas energy, carbohydrate, and fat intakes from complementary feeding did not differ by group over time. At 9 mo of age mean (± SEM), intakes of total (complementary feeding plus breast-milk) protein were 2.9 ± 0.6 and 1.4 ± 0.4 g ⋅ kg−1 ⋅ d−1, ∼17% and ∼9% of daily energy intake, for MEAT and CEREAL groups, respectively (P < 0.001). From 5 to 9 mo of age, the weight-for-age z score (WAZ) and length-for-age z score (LAZ) increased in the MEAT group (ΔWAZ: 0.24 ± 0.19; ΔLAZ: 0.14 ± 0.12) and decreased in the CEREAL group (ΔWAZ: −0.07 ± 0.17; ΔLAZ: −0.27 ± 0.24) (P-group by time < 0.05). The change in weight-for-length z score did not differ between groups. Total protein intake at 9 mo of age and baseline WAZ were important predictors of changes in the WAZ (R2 = 0.23, P = 0.01).
“Conclusion: In breastfed infants, higher protein intake from meats was associated with greater linear growth and weight gain but without excessive gain in adiposity, suggesting potential risks of high protein intake may differ between breastfed and formula-fed infants and by the source of protein.”

(The whole paper is worth reading, but these highlights serve our point.)
“Without routine access to ASF [animal source foods], it is highly unlikely that evolving humans could have achieved their unusually large and complex brain while simultaneously continuing their evolutionary trajectory as large, active and highly social primates. As human evolution progressed, young children in particular, with their rapidly expanding large brain and high metabolic and nutritional demands relative to adults would have benefited from volumetrically concentrated, high quality foods such as meat.”
[…]
“If the dietary trajectory described above was characteristic of human ancestors, the routine, that is, daily, inclusion of ASF in the diets of children seems mandatory as most wild plant foods would not be capable of supplying the protein and micronutrients children require for optimal development and growth, nor could the gut of the child likely provide enough space, in combination with the slow food turnover rate characteristic of the human species, to secure adequate nutrition from wild plant foods alone. Wild plant foods, though somewhat higher in protein and some vitamins and minerals than their cultivated counterparts (52), are also high in fiber and other indigestible components and most would have to be consumed in very large quantity to meet the nutritional and energetic demands of a growing and active child.”
[…]
“Given the postulated body and brain size of the earliest humans and the anatomy and kinetic pattern characteristics of the hominoid gut, turning increasingly to the intentional consumption of ASF on a routine rather than fortuitous basis seems the most expedient, indeed the only, dietary avenue open to the emerging human lineage (2,3,10,53).”
[…]
“Given the probable diet, gut form and pattern of digestive kinetics characteristic of prehuman ancestors, it is hypothesized that the routine inclusion of animal source foods in the diet was mandatory for emergence of the human lineage. As human evolution progressed, ASF likely achieved particular importance for small children due to the energetic demands of their rapidly expanding large brain and generally high metabolic and nutritional demands relative to adults.”

“Although some researchers have claimed that plant foods (e.g., roots and tubers) may have played an important role in human evolution (e.g., O’Connell et al., 1999; Wrangham et al., 1999; Conklin-Brittain et al., 2002), the low protein content of ‘‘starchy’’ plants, generally calculated as 2% of dry weight (see Kaplan et al., 2000: table 2), low calorie and fat content, yet high content of (largely) indigestible fiber (Schoeninger et al., 2001: 182) would render them far less than ideal weaning foods. Some plant species, moreover, would require cooking to improve their digestibility and, despite claims to the contrary (Wrangham et al., 1999), evidence of controlled fire has not yet been found at Plio-Pleistocene sites. Other plant foods, such as the nut of the baobab (Adansonia digitata), are high in protein, calories, and lipids and may have been exploited by hominoids in more open habitats (Schoeninger et al., 2001). However, such foods would be too seasonal or too rare on any particular landscape to have contributed significantly and consistently to the diet of early hominins. Moreover, while young baobab seeds are relatively soft and may be chewed, the hard, mature seeds require more processing. The Hadza pound these into flour (Schoeninger et al., 2001), which requires the use of both grinding stones and receptacles, equipment that may not have been known to early hominins. Meat, on the other hand, is relatively abundant and requires processing that was demonstrably within the technological capabilities of Plio-Pleistocene hominins. Meat, particularly organ tissues, as Bogin (1988, 1997) pointed out, would provide the ideal weaning food.”

(Emphasis ours)
“We studied the western lowland gorilla diet as a possible model for human nutrient requirements with implications for colonic function. Gorillas in the Central African Republic were identified as consuming over 200 species and varieties of plants and 100 species and varieties of fruit. Thirty-one of the most commonly consumed foods were collected and dried locally before shipping for macronutrient and fiber analysis. The mean macronutrient concentrations were (mean ± SD, g/100 g dry basis) fat 0.5 ± 0.4, protein 11.8 ± 8.2, available carbohydrate 7.7 ± 6.3 and dietary fiber 74.0 ± 12.9. Assuming that the macronutrient profile of these foods was reflective of the whole gorilla diet and that dietary fiber contributed 6.28 kJ/g (1.5 kcal/g), then the gorilla diet would provide 810 kJ (194 kcal) metabolizable energy per 100 g dry weight. The macronutrient profile of this diet would be as follows: 2.5% energy as fat, 24.3% protein, 15.8% available carbohydrate, with potentially 57.3% of metabolizable energy from short-chain fatty acids (SCFA) derived from colonic fermentation of fiber. Gorillas would therefore obtain considerable energy through fiber fermentation. We suggest that humans also evolved consuming similar high foliage, high fiber diets, which were low in fat and dietary cholesterol. The macronutrient and fiber profile of the gorilla diet is one in which the colon is likely to play a major role in overall nutrition. Both the nutrient and fiber components of such a diet and the functional capacity of the hominoid colon may have important dietary implications for contemporary human health.”
We disagree, of course, with the authors’ suggested interpretation that humans, too, could make good use of the same dietary strategy, as we haven’t the colons for it.

“The value of 6-10% for humans (Table 3) was calculated on the basis of a typical British diet where 50-60 g of carbohydrate (15 g fiber and 35-50 g sugar and starch) are fermented per day (209). It is pointed out, however, that dietary fiber intakes in Africa or the Third World are up to seven times higher than in the United Kingdom (55). It is likely, therefore, that much of this increased fiber intake is fermented to VFA and even greater amounts of energy are made available by large intestinal fermentation.”
However, it should not be concluded that SCFA production could rise to 70% of energy requirements!
For one thing, as a back-of-the-envelope calculation, you can get up to about 2 kcal worth of SCFA per gram of fermentable carbohydrate.
That would come from soluble plant fiber, resistant starch and regular starch that escapes digestion.
To get 70% of calories this way on a 2000 kcal/day diet, you’d need to ingest 700g of fibre.
Even if you achieved this, it is unlikely you could absorb it all, and in the process of trying, you would experience gastrointestinal distress, including cramping, diarrhea or constipation, gas, and perhaps worse.
Indeed, this would probably happen even at 100g/d, which would provide about 10% of energy in a 2000 kcal/d diet.
Moreover, it would interfere with mineral absorption, rendering it an unviable evolutionary strategy.
Even the ADA, which extols the virtues of fiber, cautions against exceeding their recommendations of 20-35g. See Position of the American Dietetic Association: health implications of dietary fiber.

“As the mathematical models now seem quite plausible and the patterns of survivors versus extinct species seem inexplicable by climate change and easily explicable by hunting (7,11), it is worth considering comparisons to other systems. Barnosky et al. note that on islands, humans cause extinctions through multiple synergistic effects, including predation and sitzkrieg, and “only rarely have island megafauna been demonstrated to go extinct because of environmental change without human involvement,” while acknowledging that the extrapolation from islands to continents is often disputed (7). The case for human contribution to extinction is now much better supported by chronology (both radiometric and based on trace fossils like fungal spores), mathematical simulations, paleoclimatology, paleontology, archaeology, and the traits of extinct species when compared with survivors than when Meltzer and Beck rejected it in the 1990s, although the blitzkrieg model which assumes Clovis-first can be thoroughly rejected by confirmation of pre-Clovis sites. Grayson and Meltzer (12) argue that the overkill hypothesis has become irrefutable, but the patterns by which organisms went extinct (7,11), the timing of megafauna population reductions and human arrival when compared with climate change (5), and the assumptions necessary to make paleoecologically informed mathematical models for the extinctions to make accurate predictions all provide opportunities to refute the overkill hypothesis, or at least make it appear unlikely. However, all of these indicate human involvement in megafauna extinctions as not only plausible, but likely.”

“Humans are well-documented optimal foragers, and in general, large prey (ungulates) are highly ranked because of the greater return for a given foraging effort. A survey of the association between mammal body size and the current threat of human hunting showed that large-bodied mammals are hunted significantly more than small-bodied species (Lyons et al. 2004). Studies of Amazonian Indians (Alvard 1993) and Holocene Native American populations in California (Broughton 2002, Grayson 2001) show a clear preference for large prey that is not mitigated by declines in their abundance. After studying California archaeological sites spanning the last 3.5 thousand years, Grayson (2001) reported a change in relative abundance of large mammals consistent with optimal foraging theory: The human hunters switched from large mammal prey (highly ranked prey) to small mammal prey (lower-ranked prey) over this time period (figure 7). Grayson (2001) stated that there were no changes in climate that correlate with the nearly unilinear decline in the abundance of large mammals. Looking further back in time, Stiner and colleagues (1999) described a shift from slow-moving, easily caught prey (e.g., tortoises) to more agile, difficult-to-catch prey (e.g., birds) in Mediterranean Pleistocene archaeological sites, presumably as a result of declines in the availability of preferred prey.”

“The disappearance of elephants from the diet of H. erectus in the Levant by the end of the Acheulian had two effects that interacted with each other, further aggravating the potential of H. erectus to contend with the new dietary requirements:
“The absence of elephants, weighing five times the weight of Hippopotami and more than eighty times the weight of Fallow deer (Kob in Table 3), from the diet would have meant that hunters had to hunt a much higher number of smaller animals to obtain the same amount of calories previously gained by having elephants on the menu.
“Additionally, hunters would have had to hunt what large (high fat content) animals that were still available, in order to maintain the obligatory fat percentage (44% in our model) since they would have lost the beneficial fat contribution of the relatively fat (49% fat) elephant. This ‘large animal’ constraint would have further increased the energetic cost of foraging.”
[…]
“Comparing the average calories per animal at GBY and Qesem Cave might lead to the conclusion that Qesem Cave dwellers had to hunt only twice as many animals than GBY dwellers. This, however, is misleading as obligatory fat consumption complicates the calculation of animals required. With the obligatory faunal fat requirement amounting to 49% of the calories expected to be supplied by the animal, Fallow deer with their caloric fat percentage of 31% (Kob in Table 3) would not have supplied enough fat to be consumed exclusively. Under dietary constraints and to lift their average fat consumption, the Qesem Cave dwellers would have been forced to hunt aurochs and horses whose caloric fat ratio amounts to 49% (the equivalent of buffalo in Table 3). The habitual use of fire at Qesem Cave, aimed at roasting meat [23], [45], may have reduced the amount of energy required for the digestion of protein, contributing to further reduction in DEE. The fact that the faunal assemblage at Qesem Cave shows significantly high proportions of burnt and fractured bones, typical of marrow extraction, is highly pertinent to the point. In addition, the over-representation of fallow deer skulls found at the site [9], [45] might imply a tendency to consume the brain of these prey animals at the cave. Combined, these data indicate a continuous fat-oriented use of prey at the site throughout the Acheulo-Yabrudian (400-200 kyr).
“However, the average caloric fat percentage attributed to the animals at Qesem Cave – 40% – is still lower than the predicted obligatory fat requirements of faunal calories for H. sapiens in our model, amounting to 49% (Table 2). This discrepancy may have disappeared should we have considered in our calculations in Table 3 the previously mentioned preference for prime-age animals that is apparent at Qesem Cave [9], [45]. The analysis of Cordain’s Caribou fat data ([124]: Figure 5) shows that as a strategy the selective hunting of prime-age bulls or females, depending on the season, could, theoretically, result in the increase of fat content as the percentage of liveweight by 76% from 6.4% to 11.3%, thus raising the caloric percentage of fat from animal sources at Qesem Cave. Citing ethnographic sources, Brink ([125]:42) writes about the American Indians hunters: “Not only did the hunters know the natural patterns the bison followed; they also learned how to spot fat animals in a herd. An experienced hunter would pick out the pronounced curves of the body and eye the sheen of the coat that indicated a fat animal”. While the choice of hunting a particular elephant would not necessarily be significant regarding the amount of fat obtained, this was clearly not the case with the smaller game. It is apparent that the selection of fat adults would have been a paying strategy that required high cognitive capabilities and learning skills.”