(Article last update : January 2015)
A widely cited study (Eppig et al., 2010) has suggested that infectious disease is the most important determinant of national IQs, independently and above GDP, education and some evolutionary variables. But their analysis is just a hierarchical multiple regression. It does not tell us anything about the arrow of causality. It is plausible that it goes both ways. A less recognized fact is their analysis showing a non-trivial direct (i.e., independent) effect of winter and distance from EEA. When both effects are cumulated, they become close to the effect of DALY disease. Their results look like this :
The problem is in the method, as multiple regression does not estimate the full but the direct effect of the independent variables. The interesting fact, anyway, is that they have used Lynn and Vanhanen’s (LVE) as well as Wicherts et al. (WEAM) IQ estimates. They demonstrate that the results are not meaningfully different for DALY disease and the evolutionary variables, which suggests that L&V estimates are not as inaccurate as is usually said.
There had been direct answers against such reverse causality hypotheses. Christainsen (2013, p. 693, tables 3 & 4) cites some countries where living condition was better than countries with much higher IQ. This attenuates somewhat the wealth->IQ causality. More importantly, a multiple regression including malnutrition and a series of dummy (regional) variables shows that even after partialling out malnutrition, east asian countries outsmart african countries by 8.5+18.7=27.2 IQ points. Thus, whatever the effect of malnutrition could have been, the score rank-ordering and magnitude of the score difference is not much affected, excepted the 18.7 points separating the african and european countries, now much less than the 30 IQ point difference reported by Lynn & Vanhanen. As stated above, this is because malnutrition has been partialed out.
Returning to Eppig’s hypothesis, one could say that a cut finger will get infected in tropical jungle but perhaps not in the artic. But this kind of infection may not necessarily affect individuals randomly. Skillful and thoughtful persons, are more likely to have a higher IQ and more likely to be spared from those diseases. Infectious may be acting as a selector, eliminating people of low intelligence first. On top of that, the following passage from Eppig suggests a certain role for a genetic cause :
In an environment where there has consistently been a high metabolic cost associated with parasitic infection, selection would not favour the maintenance of a phenotypically plastic trait. That is, the conditional strategy of allocating more energy into brain development during periods of health would be lost, evolutionarily, if periods of health were rare. Peoples living in areas of consistently high prevalence of infectious disease over evolutionary time thus may possess adaptations that favour high obligatory investment in immune function at the expense of other metabolically expensive traits such as intelligence.
The authors consider it unlikely because they think that the Flynn Effect is not caused by evolutionary processes. Still, there is no proof yet that the secular gain is a real gain in intelligence. And they haven’t provided any piece of evidence that region-specific genetic adaptations do not play a significant role in those differences in national IQs. On the other hand, Wicherts et al. (2010) showed, using PC analysis, that national IQ and environmental variables have significant loadings on PC1 while at the same time the evolutionary variables (longitude and distance from Ethiopia) have significant loadings on PC2. However, the fact that the 2 other environmental variables (temperature and latitude) load on PC1 is sufficient to refute the authors’ preferred theory. Hassall & Sherratt (2011) however indicate that temperature could mediate the relationship between environmental variables (e.g., disease) and national IQs :
Given the strength of evidence for the physiological effects of disease, it may be that temperature is acting not through an impact on the environment but through an impact on the interaction between humans and their diseases. Temperature influences a number of disease-related parameters such as disease distribution (Guernier, Hochberg, & Guégan 2004), transmission seasons (e.g. malaria, Hay, Guerra, Tatem, Noor, & Snow 2004), the ability of insect vectors to transmit diseases (Cornel, Jupp, & Blackburn 1993) and the development and survival of parasites and host susceptibility (Harvell et al. 2002). It may be that temperature is having an effect on national mean IQ by mediating the response to infectious diseases rather than via environmental complexity.
If so, regression would have removed the indirect effect of winter and distance from EEA, biasing downwardly their regression coefficient. Even the problem with Eppig’s conclusion has been already dealt with long ago now. Carleton Putnam (1967, p. 57) said that the image of an Africa ravaged by diseases was exaggerated :
Driven from their conflicting defenses of isolation and lost ruins, some equalitarians finally retreated to the excuse of climate and disease, to the argument that tropical maladies and the heat were enough to account for the Negro’s condition. I knew of no scientists who advanced this argument, but it was frequently heard from laymen.
Here again one needed only to reply that, on the one hand, there were many parts of Africa where the climate was good and, on the other hand, other parts of the world which had produced great civilizations where the climate was bad. Moreover, for a hundred years the Negro had been free of both tropical diseases and the incubus of climate in the old ex-slave settlement at Chatham, Ontario. Yet his performance there on intelligence tests followed the standard pattern. In fact tropical diseases no longer could be blamed for the Negro’s relative performance in the Southern United States.
The truth of the matter was that whatever influence climate and disease may indeed have had upon the Negro over tens of thousands of years, the result had by now become innate through evolutionary processes. I could paraphrase Nathaniel Weyl and state that “the fundamental barrier is less the action of climate and disease on the living generation than its cumulative action, over an immense time span, in forming the race.”
And it is not even certain how to make sense of the fact that India, for which the IQ is 82 (Lynn & Vanhanen, 2012, pp. 400-401), has 49% of preschool children suffering from malnourishment, compared to the 31% of the sub-Saharan Africa (Bamji, 2003). As Bamji suggests, infant mortality has probably eliminated the more malnourished children from the statistics. Thus, if africans were more likely to die, it must result in improved IQ. It was also revealed that the % of low birth weight was over 30% in South Asia, 15% in Africa, and less than 10% in countries like East Asia-Pacific and Latin America.
John R. Baker, in “Race” (1974), substantiates the argument and provides a large body of evidence that many parts of Africa were free from such diseases and the climate favorable enough to the development of a civilization :
Schweinfurth remarks of the countryside at the border of Dinka (Ni), Dyoor (Ni), and Bongo (Pan 3) territory, ‘The extreme productiveness of the luxuriant tropics is well exemplified in these fields, which for thirteen years have undergone continual tillage without once lying fallow and with no other manuring but what is afforded by the uprooted weeds.’ The land of the Mittu (Pan 3) ‘… is very productive. … On account of its fertility the land requires little labour in its culture.’ ‘The Monbuttoo [Pan 3] land greets us as an Eden upon earth.’ In some districts of the Azande ‘… the exuberance is unsurpassed. … the cultivation of the soil is supremely easy. The entire land is pre-eminently rich in many spontaneous products, animal and vegetable alike, that conduce to the direct maintenance of human life.’ Baker says of the country in what is now the borderland between Sudan and Uganda, ‘… we were in a beautiful open country, naturally drained by its undulating character, and abounding in most beautiful low pasturage’. He describes Shooa (Ladwong) in Acholi (Ni) territory, as ‘… “flowing with milk and honey”; fowls, butter, goats, were in abundance and ridiculously cheap’. […]
… he [Livingstone] writes, ‘To one who has observed the hard toil of the poor in old civilized countries, the state in which the inhabitants here live is one of glorious ease. … Food abounds, and very little labour is required for its cultivation; the soil is so rich that no manure is required’. […]
It is questionable, however, whether the inhabitants of the secluded area were in a worse situation, in respect of illness, than those of comparable tropical and subtropical countries elsewhere, in some of which, especially India, great advances in intellectual life had been made from remote times onwards. … The explorers certainly do not present a picture of universal sickness among the inhabitants of the inland parts of Africa. Du Chaillu says of the Ashira (Pan 1), ‘The natives are generally tolerably healthy. I have seen cases of what I judge the leprosy, but they have little fever among them, or other dangerous diseases.’ … Galton says of Ovamboland that ‘There are no diseases in these parts except slight fever, frequent ophthalmia, and stomach complaints.’ … he [Schweinfurth] remarks that ‘My health was by no means impaired, but, on the contrary, I gained fresh vigour in the pure air of the southern highlands.’ … he [Livingstone] remarked that the hilly ridges of this region ‘may even be recommended as a sanatorium for those whose enterprise leads them on to Africa. … they afford a prospect to Europeans, of situations superior in point of salubrity to any of those on the coast’. He says also that ‘… they resemble that most healthy of all healthy climates, the interior of South Africa, near and adjacent to the [Kalahari] Desert’.
Like Putnam, Baker does not believe that environment is the best explanation that accounts for race differences in achievements, far from it. Therefore, in the last chapter of his book, he made the following point :
It would be wrong to suppose that civilization developed wherever the environment was genial, and failed to do so where it was not. … It has been pointed out by an authority on the Maya that their culture reached its climax in that particular part of their extensive territory in which the environment was least favourable, and in reporting this fact he mentions the belief that ‘civilizations, like individuals, respond to challenge’.  … The Sumerians found no Garden of Eden awaiting them in Mesopotamia and the adjoining territory at the head of the Persian Gulf, but literally made their environment out of unpromising material by constructing an elaborate system of canals for the drainage and watering of their lands. A very large number of Aztecs and members of several other Middle American tribes lived and made their gardens on artificial islands that they themselves constructed with their hands.
It is still possible however that environments were more important in determining wealth than it would be today (Daniele, 2013). But until now, we have only reviewed the between-country studies. Fortunately, Eppig et al. (2011) has conducted a similar study but inside the United States. They say (p. 157) that in the South of the U.S. there is a larger percentage of blacks and that infectious diseases are more prevalent in the Southern states. That may be true, but they should have said that southern US blacks have less white admixture (e.g., Lynn, 2002a, 2002b, p. 217). The IQ of southern blacks is around 80 (Jensen, 1980, pp. 98-99).
Hierarchical regression was used to predict average state IQ using parasite stress, wealth, percent of teachers highly qualified, and student/teacher ratio (Table 2). Parasite stress was added in the first iteration of the model, resulting in a change in R² of 0.445. Wealth was added in the second iteration of the model, resulting in a change in R² of 0.075. Both education variables were added simultaneously in the third iteration of the model because they both measure the same theoretical construct, resulting in a change in R² of 0.133. While these variables were added into the model in order of presumed causal priority, adding these variables in a different order did not appreciably change the additive R² of each iteration. In the final model, parasite stress (Std Beta = −0.62, variance inflation factor (VIF) = 1.02, and p < 0.0001), wealth (Std Beta = 0.30, VIF = 1.00, and p = 0.0006), percent of teachers highly qualified (Std Beta = 0.29, VIF = 1.16, and p = 0.0019), and student/teacher ratio (Std Beta = −0.22, VIF = 1.15, and p = 0.015) (Table 3) were all significant predictors of average state IQ. The whole model R² was 0.698 (p < 0.0001). The VIF was well below 2 for all variables in all models, indicating that multicolinearity did not introduce significant error into these models, and that the standardized beta coefficients are interpretable (Fox, 1991).
Again, it has the same problem with the previous study. The arrow of causality and the role of disease-related mortality as a selector. As Jensen (1973, p. 338) indicated, environmental depression causing higher death rates will act as a selector, enhancing the IQs of the targeted population :
One might even hypothesize that the net effect of extreme nutritional depression in a population (not for an individual) might actually be to raise the IQ due to increased fetal loss and infant mortality along with natural selection favoring those who are genetically better endowed physically and mentally.
Another common claim for explaining the Black-White IQ gap is that prenatal exposure to pollutants is likely to reduce the IQ of american blacks on the grounds that they usually live in unsanitary neighborhoods. According to this theory, blacks are far more likely than other ethnic groups to be exposed to such environmental hazards. The problem comes from the fact that, as SES increases, the Black-White difference in IQ increases as well, which clearly contradicts the environmental theory. The Black-White difference can also increase with SES levels. Currie (2005, pp. 124-127) exposes the weaknesses of the environmental hypothesis :
Although some studies have found that increasing blood lead levels from 10 to 20 microg/dl reduces IQ scores by as much as 7 points (where one standard deviation is about 15 points), two reviews of many studies of blood lead levels conclude that such an increase would reduce IQ by about 2 points. … But because lead exposure is increasingly strongly correlated with minority status, poverty, and residence in decaying older neighborhoods, it is possible that at least some of the observed correlations between lead levels and negative outcomes reflect omitted third factors. These estimates of the effects of low-level lead exposure should thus be regarded as upper bounds.
… The prevalence of high lead exposure is 8.7 percent among blacks and 2 percent among whites.
Given a mean score of 50 in school readiness for whites and the above figures, the independent effect of lead exposure, with regard to the black-white readiness differences, would be : [(0.98*50) + (0.02*48)] – [(0.913*50) + (0.087*48)] = (49+0.96) – (45.65+4.17) = 49.96 – 49.82 = 00.14. Currie uses a mean score of 50, but we could have used a mean of 100 instead, but the result would be unaffected : [(0.98*100) + (0.02*96)] – [(0.913*100) + (0.087*96)] = (98+1.92) – (91.30+8.35) = 99.92 – 99.65 = 00.27. This factor, thus, explains very little, if nothing at all, of the black-white test score gap. And the same thing goes for ADHD (Attention Deficit-Hyperactivity Disorder) :
How much of the racial gap in school readiness might be accounted for by ADHD? Suppose that a generic test has a mean of 50 and a standard deviation of 15 and that black children tend to score at least a half a standard deviation (8 points) lower than white children on this test. The studies discussed above suggest that ADHD lowers test scores by about a third of a standard deviation (5 points) and that about 4 percent of whites have the disorder, compared with 6 percent of blacks.
The independent contribution of ADHD to the BW score gap would be [(0.96*50) + (0.04*45)] – [(0.94*50) + (0.06*45)] = (48+1.8) – (47+2.7) = 49.8 – 49.7 = 00.1. Or, a near-zero effect. And what about poverty line ? Currie gives the following numbers :
With 37.5 percent of black children under five and 15.5 percent of white children in that same age group living in poverty, the socioeconomic gap in the incidence of maternal depression noted above — 28 percent among the poor, 17 percent among the nonpoor — means that maternal depression will affect some 11 percent of black preschool children but only 3 percent of white preschool children. These differing exposures to maternal depression could account for a half a point of the assumed eight-point gap in our generic average test score.
Again, the operation would be : [(0.03*45) + (0.97*50)] – [(0.11*45) + (0.89*50)] = (1.35+48.5) – (4.95+44.5) = 49.85 – 49.45 = 00.40. The effect is insignificant. Moreover, the effect of all these environmental variables cannot be added because there is certainly a non-trivial correlation between them, meaning that those environmental factors are not independent of each other.
Probably the most used argument is undernutrition. But undernutrition, especially at an early age, increases the differences in mental and physical characteristics between siblings. If nutritional deficiencies were the causes of IQ differences between blacks and whites, the correlations (expressed as r) and absolute differences (expressed in d) between siblings in height and cognitive/achievement tests should be different between the black population and white population, with lower correlations for blacks. No evidence of this was reported by Jensen (1973, pp. 110-113, 339-340). There is also no evidence that sibling correlations differ between blacks and whites (Jensen, 1998, pp. 366, 447). The fact that siblings of blacks (matched for IQ with whites) regress to a lower cognitive mean is another problem for environmental hypotheses.
Undernutrition (e.g., protein deficiency) retards the ossification of cartilage and results in depressed performance in infant tests of sensori-motor development and impairment of memory ability; yet black infants have been found to be advanced over whites in ossification and sensori-motor development tests, and show no deficit in rote memory (Jensen, 1973, pp. 333, 338-339).
Jason Malloy (May 26, 2013) compiled data (35 studies) and showed that the BW IQ gap at age 3 is almost the same as the IQ gap at adulthood. Obviously, an environmental theory usually argues that the IQ gap keeps increasing with age. As Malloy pointed out, a counter-argument would be that the BW gap shrinks after age 3, and then starts again to grow in adulthood, but this is not compelling at all. This finding, on the other hand, annihilates the black cognitive cumulative deficit. However, it could be said that cross-sectional studies are sub-optimal for examining longitudinal changes. And yet Jensen (1973, pp. 97-102; 1974, pp. 998, 1000) reviewed some longitudinal studies, generally not supportive of the cumulative deficit hypothesis, although one sibling study by Jensen (1977) is supportive of the cumulative deficit hypothesis. More recently, Farkas & Beron (2004) examine the PPVT in the CNLSY79 and find that the BW IQ gap does not widen after age 3 (through age 12).
Even when there was a sign of poor nutrition among some families, Jensen tells us (1973, pp. 331-332), usually not all the children in the same family will show signs of poor nutrition. When there was no evidence of poor nutrition among low-IQ children, it has been once hypothesized that this was due, in part, to the children’s mother, or grandmother, having suffered from poor nutrition. But Jensen (1973, p. 334) said :
Stein and Kassab (1970, p. 109) summarize the present state of knowledge on this point: ‘There are no studies in human societies which can be held to support a cumulative generational effect of dietary restriction. Certainly any such effect was not sufficiently widespread, after countless generations of rural poverty, to prevent the emergence during the past century of the technological societies of Europe and North America.’
Even if we suppose, for the sake of the argument, that under-nutrition is alone responsible for a depression of 20 IQ points among US blacks, Jensen tells us, it would cause a loss of only 2 points in the black population :
I asked Dr Herbert Birch, a leading researcher in this field, for a rough estimate of the percentage of our population that might suffer a degree of malnutrition sufficient to affect IQ. He said he would guess ‘Not more than about 1 percent’ (personal communication, 19 April 1971). … Assume that all of the 1 percent of malnutrition in the U.S. population occurs within the Negro population; this would mean that approximately 9 percent of the Negro population suffers from malnutrition. Assume further that all 9 percent of this group afflicted by malnutrition has thereby had its IQ lowered by 20 points (which is the difference between severely malnourished and adequately nourished groups in South Africa – the most extreme IQ difference reported in the nutrition literature). Assuming the present Negro mean IQ in the U.S. to be 85, what then would be the mean if the 20 points of IQ were restored to the hypothetical 9 percent who had suffered from intellectually stunting malnutrition? It would be 86.70, or a gain of less than 2 IQ points as an outer-bound estimate.
The calculation would be : 100 – [(0.09*80) + (0.91*100)] = 100 – (7.2 + 91) = 100 – 98.2 = 1.8. This outcome is expected, because even blacks in advanced societies usually do not suffer from nutritional deficiency. Needless to say, Jensen provides perhaps one of the most compelling collection of arguments against environmentalists in Educability and Group Differences (1973).
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