Tag Archives: Intelligence

Intelligence Predicts Health and Longevity, but Why?

Intelligence Predicts Health and Longevity, but Why?

Large epidemiological studies of almost an entire population in Scotland have found that intelligence (as measured by an IQ-type test) in childhood predicts substantial differences in adult morbidity and mortality, including deaths from cancers and cardiovascular diseases. These relations remain significant after controlling for socioeconomic variables. One possible, partial explanation of these results is that intelligence enhances individuals’ care of their own health because it represents learning, reasoning, and problem-solving skills useful in preventing chronic disease and accidental injury and in adhering to complex treatment regimens.

A Gottfredson pdf just full of useful bits of information about the influence of IQ on mortality. A few of the most interesting bits…

a drop of 1 standard deviation in IQ was associated with a 27% increase in cancer deaths among men and a 40% increase in cancer deaths among women (Deary, Whalley, & Starr, 2003). The effect was especially pronounced for stomach and lung cancers, which are specifically associated with low socioeconomic status (SES) in childhood.

For each standard deviation increase in IQ, there was a 33% increased rate of quitting smoking. Adjusting for social class reduced this rate only mildly, to 25%. Thus, childhood IQ was not associated with starting smoking (mostly in the 1930s, when the public were not aware of health risks), but was associated with giving up smoking as health risks became evident.

When all other variables were statistically controlled, each additional IQ point predicted a 1% decrease in risk of death. Also, IQ was the best predictor of the major cause of death, motor vehicle accidents. Vehicular death rates doubled and then tripled at successively lower IQ ranges (100–115, 85–100, 80–85; O’Toole, 1990).

A low IQ increases the risk of heart attack

Does IQ predict cardiovascular disease mortality as strongly as established risk factors? Comparison of effect estimates using the West of Scotland Twenty-07 cohort study

To compare the strength of the association between intelligence quotient (IQ) and cardiovascular disease (CVD) mortality with the predictive power for established risk factors.

Population-based cohort study of 1145 men and women with IQ test scores, a range of established risk factors, and 20-year mortality surveillance.

When CVD mortality was the outcome of interest, the relative index of inequality (sex-adjusted hazard ratio, 95% confidence interval) for the most disadvantaged relative to the advantaged persons was (in descending order of magnitude for the top five risk factors): 5.58 (2.89, 10.8) for cigarette smoking; 3.76 (2.14, 6.61) for IQ; 3.20 (1.85, 5.54) for income; 2.61 (1.49, 4.57) for systolic blood pressure and 2.06 (1.07, 3.99) for physical activity. Mutual adjustment led to some attenuation of these relationships. Similar observations were made in the analyses featuring all deaths where, again, IQ was the second most powerful predictor of mortality risk.

In this cohort, lower intelligence scores were associated with increased rates of CVD and total mortality at a level of magnitude greater than most established risk factors.

There’s also a paper from 2008 by the same man that comes to a similar conclusion after studying  4,166 US soldiers. This one concluded

The main finding was that, in age-adjusted analyses, lower IQ scores in both early adulthood and middle age were related to total and CVD mortality at a level of magnitude greater than many traditional risk indices.

What I did find amusing was reading through what the media had to say on this recently, trying to tell people that they could boost IQ with education (hasn’t been done with any lasting effect yet, and many have tried).

 Higher IQ has been associated with better outcome for disease in other studies, with explanations from following a healthier lifestyle (smokers have a much lower average IQ, 7.5 points lower) and being better able to manage medical conditions and medication.

Genetic Influences on the Overlap Between Low IQ and Antisocial Behavior in Young Children

Genetic Influences on the Overlap Between Low IQ and Antisocial Behavior in Young Children

The well-documented relation between the phenotypes of low IQ and childhood antisocial behavior could be explained by either common genetic influences or environmental influences. These competing explanations were examined through use of the Environmental Risk Longitudinal Twin Study 1994–1995 cohort (Moffitt & the E-Risk Study Team, 2002) of 1,116 twin pairs and their families. Children’s IQ was assessed via individual testing at age 5 years. Mothers and teachers reported on children’s antisocial behavior at ages 5 and 7 years. Low IQ was related to antisocial behavior at age 5 years and predicted relatively higher antisocial behavior scores at age 7 years when antisocial behavior at age 5 years was controlled. This association was significantly stronger among boys than among girls. Genetic influences common to both phenotypes explained 100% of the low IQ–antisocial behavior relation in boys. Findings suggest that specific candidate genes and neurobiological processes should be tested in relation to both phenotypes.

Remembering the outrage the last time I posted material of this nature, I shall stick to snipping the more interesting bits of text out and not add my own comments.

The exclusion of children who received a diagnosis of ADHD had no effect on our findings regarding the gender difference in the strength of the association between low IQ and antisocial behavior.

 Furthermore, it is important to note that once children with ADHD diagnoses were excluded from the sample, the low IQ–antisocial behavior correlation in girls was attenuated to almost nonsignificance. These findings suggest that the low IQ–antisocial behavior relation in girls is largely an artifact of comorbid ADHD.

The population prevalence of early-onset antisocial behavior that is life-course persistent is low (5% among men, less than 1% among women); however, these individuals account for more than their share of crime (Robins, 1966). Low IQ predicts the chronicity of antisocial behavior (Lahey et al., 1995); therefore, the children in our study who are boys, have low IQs, and have high levels of early antisocial behavior are at high risk for becoming life-course persistent antisocial individuals. This antisocial subtype is at the highest risk for myriad negative outcomes in adulthood, including mental health problems, substance dependence, financial problems, drug-related violent crime, and violence against women and children (Moffitt, Caspi, Harrington, & Milne, 2002). Genetic influences on IQ and antisocial behavior suggest that the parents of these vulnerable children are also likely to have low IQ and to be antisocial. Such parents are at risk for creating family environments that aggravate rather than ameliorate their children’s vulnerabilities. Thus, the families of young boys with low IQ who exhibit high levels of antisocial behavior should be targeted for early intervention.

One of the pieces of info I picked up from this was that … The prevalence of this research diagnosis of ADHD was 8% (70% boys; 30% girls). Also that the genders scored the same for IQ. I can’t help wondering if the abscence of these lower IQ antisocial boys from school during their teen years might not be part of the reason for the occasional finds of slightly higher IQ’s in the boys- the misssing lower IQ males boost the male average (tucked away in specialist schools, or just absent due to truancy or abandoning school at an early age.

IQ Population Genetics: It’s not as Simple as You Think

IQ Population Genetics: It’s not as Simple as You Think

A paper I came across while blog surfing. While the IQ stuff is interesting, what really caught my attention was the section on the out of Africa date.

Both genetic evidence (Ingman et al., 2000; Underhill et al., 2001; Zhivotovsky et al., 2003) and the fossil record (White et al., 2003) point to Africa as the likely homeland of our species. According to the most widely accepted scenario, one or more subgroups of early modern humans left Africa between 120,000 and 100,000 years ago to become the ancestors of the non- African populations

Which makes a pleasant change after reading an idiot paper earlier today that was hitting the 40k date. Again.

 And something I didn’t know..

Genes, like drugs, have many side effects. This is called pleiotropy. For example, the average IQ of nearsighted people is 6 to 8 points higher than the average for normal-sighted people.

Although I am familiar with a medical condition called torsion dystonia that raises the IQ of the sufferer by an average of 10 points. An interesting read.

Brain size, relative intelligence, sex and fat.

After re-reading the ludicrous (and I’ll explain why it’s ludicrous) assertion that women have an average IQ five points lower than the male claims from Lynn, I thought I’d dig up some of the facts and figures surrounding this flawed work.

First of all I’m going to put a link to this paper on relative brain size and intelligence by Tom Schoenemann, a professor whose specialist field is the evolution of the human brain. It has several numbers relevant to this subject:

Male:          (55.5 kg body weight, 1361 g brain weight)
Female:    (51.5 kg body weight, 1228 g brain weight)

As you can see, the human male appears to have a brain size proportionally slightly larger than the female. However, one thing  routinely ignored in all these measurements is fat. The average human male  (Western) carries a body fat of about 16%, women carry about 22%. Which means you need to calculate the relative brain size compared to non-fat mass, as fat is a null factor and as far as anyone can tell requires no processing power to control. My IQ at nine stone would be exactly the same if I weighed ten stone, although my relative brain size would have decreased due to the extra fat I now carried. This does not apply to long-term obesity which affects the brain, but the mere gaining of a few pounds has no known effect on IQ.

So from the numbers above the  you would have 25.52 g of brain per kg of body mass (male) vs 23.84 g (female). The female comes out as 93.4% the relative size of the male from this.

Factoring in the difference in body fat… 

 male       55.5- 8.88 (16% fat)  =  46.62  for 1361g, or 29.19g/kg

female    51.5 – 11.33 (22% fat) = 40.17 for 1228g, or  30.57g/kg

And all of a sudden the ‘large relative difference’ (16.6% here) between male and female brain size does a vanishing act. Here women actually seem to have a slightly larger relative brain size, although this may well be from the body fat percentages I used here being slightly askew. I’m not claiming that the percentage for body fat is 100% accurate, and if anyone reading this can link me to a study with the exact figures I’d be grateful, but you get the ballpark idea here.

In the Lynn study he comments how women seem to be doing better than men in spite of having a lower IQ; which suggests to me that the tests he and his colleagues were using were hinky. One of the main uses for IQ tests is to predict academic ability, and really all that Lynn’s test did was establish that his did not measure academic ability well in women or men, which pretty much proved it was slightly biased in favour of the male, and therefore not an accurate measure of intelligence. Gender biasing an IQ test is easy to do if you put in a few extra maths questions and remove a few language questions (in favour of the male). Something similar happened in the early days of IQ testing when a series of IQ tests found women to have a notably higher IQ, until they ‘balanced’ the test out.

This really goes towards ‘what are IQ tests and do they measure general intellegence’ debate. So far (poll a few psychologists) the consensus is that IQ tests are a real indicator of your general intelligence level and are a good predictor of your life outcome. If they weren’t relevant to real life/academic success, the only thing an IQ test would indicate would be how good you are at IQ tests, and your score wouldn’t be even remotely related to how smart you are (see earlier point about the tests Lynn used).

Going back to the Schoenemann paper, he makes it very clear that so far relative brain size and IQ are very strongly correlated:

“It is quite simply a myth that brain size and  IQ are empirically unrelated in modern populations.”

So far all the studies I’ve seen show a correlation between general brain size and IQ of about .4, which is statistically significant. I’m wondering if a more focused MRI/IQ brain size study vs non-fat body mass would reveal a much higher correlation for humans than this.

But essentially, functionally identical relative brain size (when fat is factored in) for male and female makes Lynn’s claims for a 5 point difference extremely hard to support, even more so when he admits that the tests used did not accurately predict academic outcome for the women who took them. In fact, he himself has commented on how racial difference in IQ are supported by the difference in relative brain mass. So how, with no quantitive difference between sexes in relative brain mass, can his claims for a lower average female IQ be correct?

It can’t.

Shame on you for bad science, Dr Lynn.

Intelligence and birth order in boys and girls

Intelligence and birth order in boys and girls

 The relation between intelligence and birth order was shown in a recent publication [Bjerkedal, T., Kristensen, P., Skjeret, G. A. & Brevik, J. I. (2007). Intelligence test scores and birth order among young Norwegian men (conscripts) analyzed within and between families. Intelligence, 35, 503–514] to be negative. Subjects in this and in an influential earlier study [Belmont, L. & Marolla F. A. (1973). Birth order, family size, and intelligence. Science, 182, 1096–1101] were all men. We tested if the association of IQ and birth order is the same in men and women. Longitudinal IQ data were available from 626 Dutch twin pairs at ages 5, 12 and 18 years. The number of older siblings in these twin families was between zero and five, and was recoded into 3 categories (0, 1 and 2, or more). IQ data were analyzed with a model in which age cohort, number of older sibs, sex and all interactions were included as fixed effects. The dependency between twins was modeled as a function of additive genetic effects (A) and common environment (C) shared by children from the same family. Effects of A, C and unique environment (E) were allowed to differ as a function of age. The correlation across time between IQ scores was modeled a function of genetic and environmental factors. The test for the effect of N of older sibs was significant [F(2,827)=6.51 (p=0.0016)], while the interaction of N of older sibs with sex was not significant [F(2,933)=1.93, p=0.15]. Heritability for IQ was estimated at 37% at age 5 (C explained 34% of the variance). At ages 12 and 18 heritability for IQ was 81% and 82%, respectively. At these ages C did not contribute to IQ variation. We conclude that the dependency of IQ scores on birth order does not differ for boys and girls. We discuss these results in the context of the general findings of the absence of common environmental influences on IQ scores in the genetic analyses of adolescent and adult twin data.

On the quite I’m quite interested in IQ testing and studies. This has some information on the Hereditability on IQ with age; 37% at age 5, 82% at age 18. And as I recall it gets higher the older you get, in the 90% once you are a full adult living your own life. Which makes a lot of the IQ studies that have been carried out on children pretty much pointless, as their IQ’s are so plastic at that age.

ASPM and MCPH1 and intelligence not linked.

The ongoing adaptive evolution of ASPM and Microcephalin is not explained by increased intelligence.

Mekel-Bobrov N, Posthuma D, Gilbert SL, Lind P, Gosso MF, Luciano M, Harris SE, Bates TC, Polderman TJ, Whalley LJ, Fox H, Starr JM, Evans PD, Montgomery GW, Fernandes C, Heutink P, Martin NG, Boomsma DI, Deary IJ, Wright MJ, de Geus EJ, Lahn BT.

Department of Human Genetics, Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA.

Recent studies have made great strides towards identifying putative genetic events underlying the evolution of the human brain and its emergent cognitive capacities. One of the most intriguing findings is the recurrent identification of adaptive evolution in genes associated with primary microcephaly, a developmental disorder characterized by severe reduction in brain size and intelligence, reminiscent of the early hominid condition. This has led to the hypothesis that the adaptive evolution of these genes has contributed to the emergence of modern human cognition. As with other candidate loci, however, this hypothesis remains speculative due to the current lack of methodologies for characterizing the evolutionary function of these genes in humans. Two primary microcephaly genes, ASPM and Microcephalin, have been implicated not only in the adaptive evolution of the lineage leading to humans, but in ongoing selective sweeps in modern humans as well. The presence of both the putatively adaptive and neutral alleles at these loci provides a unique opportunity for using normal trait variation within humans to test the hypothesis that the recent selective sweeps are driven by an advantage in cognitive abilities. Here, we report a large-scale association study between the adaptive alleles of these genes and normal variation in several measures of IQ. Five independent samples were used, totaling 2393 subjects, including both family-based and population-based datasets. Our overall findings do not support a detectable association between the recent adaptive evolution of either ASPM or Microcephalin and changes in IQ. As we enter the post-genomic era, with the number of candidate loci underlying human evolution growing rapidly, our findings highlight the importance of direct experimental validation in elucidating their evolutionary role in shaping the human phenotype.