An enduring mystery (among many mysteries) is the existence of women exhibiting sexual attraction to other women. Unlike male homosexuality, where a likely explanation has been put forth (see Greg Cochran’s “Gay Germ” Hypothesis – An Exercise in the Power of Germs), female same-sex attraction remains the realm of speculation. My previous foray into the matter, The Evolution of Female Bisexuality, contains much of that speculation. I’ve learned quite a bit since then, so the time has come to revisit the matter. This time I will make use of one of the most powerful exploratory methods in social science, behavioral genetics.
The first thing to look at is the heritability. An analysis of large twin registry studies pegs the heritability of female same-sex attraction (SSA) as 33% (Whitehead, 2011). This is in contrast to the very low heritability of male SSA, 22%, as reported in the same study. However, these heritabilities were not significantly different.
Unfortunately, a key weakness here (as with virtually all sex research) is that this relies entirely on self-report – worse, with no form of corroboration from any other measurement. Hence, measurement error can be expected to be large.
Looking at the various studies examined by Whitehead, heritabilities were quite variable. A lot of this stems from the relative rarity of SSA, making samples of SSA individuals small even in large studies. (Another problem with that non-response was generally high in these studies, which may have biased heritabitlity estimates.) Only the largest population-based studies with good compliance can firmly pin down the heritability of SSA.
The low heritability and evolutionary contradiction of male homosexuality necessitates the pathogenic explanation. But, assuming the 0.33 heritability of female SSA is reliable, is an evolutionary explanation workable? It is quite possibly is.
A big component is the fitness impact of female SSA. It appears to be much more common than male non-heterosexuality (again, assuming self-reports are to be believed). A British survey (Mercer et al, 2013) finds that among the youngest cohorts of women (ages 16-34), as much as 19% claim to have sexual contact with another woman (the fraction maxes out at around 9-10% for men).
However, the racial composition of the sample changes considerably across age, going from 92% to only 82% White from the oldest to the youngest cohort. Hence it’s unclear how much demographic changes are driving this apparent generational change (more on that shortly).
Nonetheless, female SSA is quite common. Its historic fitness impact then would appear to be – at worst – not as deleterious male same sex attraction. According to the Add Health data (a nationally representative U.S. teen/young adult sample), the predominant (de facto) orientation of non-heterosexual women is some sort of bisexual, indeed “mostly heterosexual” (from Udry & Chantala, 2006):
(My own personal suspicion is that most of the men claiming to be “mostly heterosexual” are in fact gay.)
As a check, I looked at the General Social Survey (GSS) to see what the reported overall behavior of non-hetero woman was. I looked at women (all races) who reported 1 or more female sex partners. This is the number of male sex partners these women claim to have had:
As we can see, non-hetero women are apparently quite promiscuous; such women with no or only a few male sex partners are very much the exception. Indeed, a third or more have had more than eight male partners; ~15% or more claim to have had more than 20 male partners!
The second chart is the number of female sex partners women who report one or more female sex partners claim to have had (all races). As we see, the most common value is just the one. All these indicate that such women are indeed primarily attracted to men.
If this is representative of past potential inclination (not necessarily realized behavior]), then the fitness impact of female SSA couldn’t have been too negative, at worst. An interest in other women likely did not preclude marrying and having children for women historically, especially if they were primarily attracted to men.
Also, for the record, I checked the GSS to see if the apparently highish frequency of women reporting SSA was driven by racial differences in SSA. As we see, even when we look at Whites only, we see a noticeable generational rise in the fraction of women who report sexual experiences with other women. I also looked at racial differences, and the values are similar for other races, except for Hispanics, who have consistently reported a 10-13% female-female sex rate for all of these cohorts. Whites and Blacks have merely converged with the Hispanic rate as of late.
Could the fitness impact of female SSA have been positive? That is, was it specifically selected for? I suspect not. While it is common, its nonetheless minority status would entail some sort of balancing selection to remain at its low level. The most plausible type, frequency-dependent selection, implies that female SSA is beneficial when it is rare. I can’t see how this would be the case (especially since it would be tough for such a girl who can’t find other women who are interested in her).
No, I don’t think female SSA is an adaptation at all. Rather, if it is actually genetic in nature, then the most likely explanation appears to be that it is some sort of side effect of something else. I suspect that it may be due to sexual antagonistic selection. That is, its existence may be driven by selection on alleles that have positive effects in men.
Key to this idea is the apparently near neutral past fitness impact of female SSA (its present impact is decidedly deleterious, as per the GSS). It was not rapidly selected out, unlike any alleles which would cause male homosexuality.
A clue here is the characteristics of non-hetero women. They are often masculinized relative to other women, with higher sex drives and, as we see, greater promiscuity.
Here again, twin studies are informative. One twin study (Burri, Spector, and Rahman, 2015) found that in female twins, masculinity (measured by childhood “gender non-conformity”) was genetically correlated both with female non-heterosexuality and number of sex partners, through a latent genetic factor. EDIT: added the genetic pathway image:
One idea that we can lay to rest here is the notion that female masculinization and SSA stem from prenatal exposure to male hormones. The way to test this idea is to look at females with a male fraternal twin (Fm) compared to women with female fraternal twins (Ff). If the Fm women were more masculine that Ff women, then it would imply prenatal hormones were at work. A massive review looking at such twin studies (Tapp, Maybery, and Whitehouse, 2011) found little support for this notion, particularly from the larger studies examined. Another recent twin study out of Denmark (Ahrenfeldt et al, 2015) found no such effect on women’s academic performance (Fm twins didn’t exhibit a more male-typical cognitive profile).
It also has been said that non-heterosexual women look different from straight women, the former appearing more masculine. Unfortunately, I haven’t been able to find much by way of good studies examining female appearance and sexual orientation. There are a few small and questionable ones, but nothing I’d take too seriously. That said, there’s another way to look indirectly at the matter.
Two twin studies by the same team (Mitchem et al, 2014 and Lee et al, 2014) looked at the heritability of facial attractiveness and facial masculinity-femininity in two sets of large and well-measured samples. They found that both are highly heritable (primarily driven by additive genetic factors), but what’s more, high facial masculinity in men led to high facial masculinity in their sisters, decreasing these women’s attractiveness.
This spillover of male traits on their female relatives can also be seen in “sociosexuality” (promiscuity). A largish twin study out of Australia (Baily et al, 2000) found sociosexuality in men predicted the same in their female co-twins. As well, there is the Zietsch et al (2008) study that found that masculinized women were more likely to be non-heterosexual, and that straight women with a non-heterosexual female twin reported somewhat more sexual partners.
Unfortunately, all these fall short of a more ideal of study, one that examines the morphological and psychological characteristics of women and their male relatives to pin down good familial predictors of female SSA.
Nevertheless, taken together, these point in the direction of masculinity being a distinct suite of traits and that appears related to female SSA. In terms of facial features, that masculinity is distinct from attractiveness in men is interesting. It speaks to perhaps a set of “masculinity promoting” genes that act somewhat orthogonal to those that lead to good looks. Research is mixed on the extent that women find masculine facial features attractive, but I’d say it’s safe to say that these alleles underwent positive selection in men. However, unfortunately, manly men beget manly daughters. Some of these alleles may serve to increase “gynephilia” (attraction to women), and they may have this effect in both sexes. This may be where SSA comes from in women. Unlike male SSA, female SSA appears to be continuously distributed – consistent with what we’d expect if it arose from the general load of various gynephilic alleles (resulting in pure lesbianism in the most extreme cases). The female SSA itself, being near selectively neutral, could reach high frequencies in women, just as masculinity in general has. However, the general suite of masculinized traits (e.g., sociosexuality, facial masculinity) was likely maladaptive in women, and was selected against, counteracting the positive selection in men. In other words, sexual antagonistic selection. A GWAS (Drabant et al, 2012) found no genetic hits to sexual orientation, indicating that female SSA – if primarily genetically driven – is caused by many genes of small effect, as we might expect.
Of course, much of this info comes from WEIRD countries (i.e., NW European and offshoots). As with much of social science in general, these investigations should be repeated with large samples from non-Western societies.
As for the male interest in girl-girl sex (*guilty*), I still suspect it’s a simple matter being able to have multiple women. Even men from highly conservative cultures may not express interest, but often such men harbor rather “colorful” sexual proclivities. Further research needed.
Now, is all of this compatible with a pathogenic source for female SSA? Absolutely, especially if the true heritability turns out to be truly low. See Peter Frost (Yes, Demons Do Exist). Perhaps the recent trend towards more women displaying SSA is due to the spread of a new pathogen. Time will tell. However, unlike male homosexuality, I don’t think we can retire the pure genetic explanation, yet.
The obvious theme song for this post:
One of the greatest pieces of evidence demonstrating that the family/rearing environment has no effect on eventual outcomes is the absence of birth order effects. Birth order is an excellent test for these effects: it is something that systematically differs between siblings and is bona fide non-genetic (mostly). Hence, it’s a great way to see if childhood environment leaves any sort of mark on people.
And it turns out that it does not. The study of birth order has been marred with poor research – faulty because it relies on the Standard Social Science Method:
This has prevented us from separating any putative causal effects of birth order from genetic confounds – most notably, the tendency of less intelligent/educated parents to have larger families. However, some decent research has been conducted demonstrating the absence of these birth order effects. One is an adoption study (Beer & Horn, 2000), which goes into good detail on the problems with birth order research and ways around these problems. They looked at adoptees from the Texas Adoption Project and the Colorado Adoption Project and found only tiny and statistically insignificant effects of birth order on personality traits. Another (tiny, N = 69 pairs) study looked within sibships for birth order effects on personality and found none (Blesk-Rechek & Kelly, 2015). A big review of the claims of Frank Sulloway (a major proponent of birth order effects) by Frederic Townsend (2000) also found no birth order effects on personality or on “rebellious” actions (as claimed by Sulloway).
But, perhaps better than these is a whole-population study out of Norway (Black, Devereux, & Salvanes, 2005). Unfortunately, this is a SSSM study, but its enormous size makes it invaluable for evaluating potential birth order effects. They performed an analysis of birth order controlling for family size as well as a within-family analysis of the effects of birth order on educational attainment. They did find modest but significant effects on educational attainment, with later-borns achieving less than earlier-borns – but I will return to this point. However, this study is useful because in addition to education, they looked at various real world outcomes, like income and likelihood of teenage pregnancy. Here, they found statistically significant but extremely small effects of birth order, with the birth order correlations of -0.04 or even closer to 0. This means birth order would explain less than 2 X 10^-5 worth of the variance – and this is without controlling for family size.
So we don’t see birth order effects on personality or important life outcomes. But some recent studies claimed to find a birth order effect on IQ of all things.
One large study of Norweigan conscripts (Bjerkedal et al, 2007) claimed to find a birth order effect on IQ within families between brothers. Younger brothers scored lower than their older brothers. The effect was small (less than 4 IQ points), but owing to the very large sample, significant.
It gets better. Another very recent study (Barclay, 2015) claimed to find a birth order effect on education with a large sample (N > 6000) of adoptees in Sweden. Again, the effects were small, and even with this large sample, only just barely statistically significant.
So there you have it. Have we found real birth order effects after all? An environmental one at that, as some have suggested? Well, if you’ve been following this blog, you’ll know I’m going to say not so fast.
First of all, these putative effects – where they’re found at all – are all tiny. That itself is a red flag – one that demands we subject it to closer scrutiny. Now, there’s nothing saying that extremely tiny effects can’t exist, but it is suspicious. But these findings come from very large samples, so we can’t dismiss them off-hand.
So what else could be going on here? It has been said that these birth order effects could be the result of the Flynn effect. This would mean that there’s no real change in intelligence by birth order, merely systematic variation in test scores, along what whatever it is that drives the Flynn effect. Indeed, one study seem to show exactly that.
Sudet et al 2010 looked at those Norwegian conscripts and studied the trends in the Flynn effect in Norway at the time. The Flynn effect wasn’t undergoing a monotonic increase but rather stalled at times and as of late has been reversing.
Notice the pattern? Birth order effects track the direction of the Flynn effect in Norway during this time. When the Flynn effect tracked upward, the difference between brothers decreased with increasing years between their births. When the Flynn effect reversed, we see the opposite pattern. And we see no change with years separation during neutral Flynn effect times. What does this mean? Well, this, coupled with research showing whatever the Flynn effect is, it is “hollow” with respect to g, show that a big part of this observed pattern is just testing variability from cohort to cohort.
But is that everything? I don’t think so. There exists another factor that could be behind this result. One birth order study (Barclay and Myrskylä, 2010) out of Norway describes this:
A substantial proportion of children in Sweden experience family complexity in one form or another as they growup. Amongst those borns in the 1960s, 23% of individuals have at least one half-sibling, and for those born in the 1970s the corresponding figure is 25%
Many of these brother pairs do not share a father (since they are matched by mothers in most of these studies). If we assume that people with children tend to “marry down” so-to-speak – that is, pair off with a mate less intelligent than their previous one, then that could easily explain the small apparent birth order effects. Re-analysis of these data excluding “blended families” could serve to address this issue.
(Indeed, the Barclay and Myrskylä study itself found small birth order effects in physical fitness – however, upon analysis with “non-blended” families these effects were greatly attenuated.)
Confounding stemming from half-siblings demonstrates a key weakness with paying too much attention to small effects. That, and (especially) the apparent role of the Flynn effect in these birth order findings show the importance of cohort effects (i.e., secular changes) which can confound even within-family designs. These two factors likely explain another study out of Norway that claimed to find a birth order effect on IQ (Kristensen & Bjerkedal, 2007). Their analysis didn’t even look within sibships. EDIT: [
Their effect went away when they controlled for family size, as usual. In their sample, those families where one sibling died seem to oddly score higher than the those that did not. (See the table here.) I don’t trust that result for a second. I’d like to see an ethnic breakdown of this sample as well as control for “blended families.”]
But is that all? What about the effect on education? Surely that’s not a Flynn effect? (Or is it?) Well, for one the Barcley 2015 study did look at adoptees, but those adoptees weren’t ethnic Swedes; they were in fact almost entirely foreign-born. What’s more, they were largely non-European. They found, as Emil Kirkegaard had, EDIT: [See also Heiner Rindermann and James Thompson] they these foreign adoptees performance varied according to their region of origin. Who’s to say that these adoptive families got both of their adoptees from the same country? I wouldn’t be surprised if they had to “go cheap” for their second adoption.
And, even going beyond that, showing an “environmental” effect on educational attainment wouldn’t be too meaningful, because, as described in my post The Son Becomes The Father, there is a shared environment on education, but one that doesn’t translate to later outcomes. “Family/rearing environment” does impact educational attainment. Hence, finding an effect of family dynamic on educational attainment isn’t unexpected. (For the record, the shared environment captures all the effects of rearing environment – a nonzero shared environment – beyond what we can ascribe to assortative mating – indicates the presence of such an effect, and likewise, for reasons described previously, its absence indicates no such effect.)
None the less, this whole enterprise on these latest supposed birth order effects has been the baby of a certain subset of researchers who are ardent “half-slatists.” This is the “nature AND nurture” crew. That is, these individuals acknowledge the role of heredity in human traits and outcomes, but seem to find ways to slip “nurture” in with reliance on questionable research and unduly unskeptical attitudes. Well, I’ve been around here long enough to learn a good rule of thumb:
If your research shows some “environmental” effect (one we can’t pin down to pathogens or developmental noise, isn’t incredibly superficial, or isn’t a secular change), it’s probably wrong.
This topic will lead into my next post, where I intend to finally lay it down on the “environment.”
This will likely be my final post of 2014. As such, Merry Christmas and Happy New Year to you all! To those of you who have donated, thank you. However, I am sad to report that my wife’s grandfather has passed away. As such, I dedicate this post to him, my wife, and her family.
I’ve added a new page, which covers many of the key facts about obesity – facts which are conveniently ignored or misunderstood in the many emotionally charged discussion of the matter. See:
I’ve made this a page rather than a post because I anticipate updating it fairly frequently, as more information becomes available. I link to all the relevant papers on the matter there. From the heritability of obesity, to the ineffectiveness of all obesity treatments, to the overblown case for its inherent dangers, I cover it all.
Posting will be light around here. As I am nearing my 200th post, I intend to make infrequent but comprehensive posts in the coming weeks and months. If there’s something you think I need to address, now is the time to speak up…
Please direct all relevant comments on the topic of the page on the page, not here. Thanks.
There are many comments I get that, while not necessarily being disrespectful or mean-spirited, nonetheless add little value, are egregiously wrong and ignorant, and would waste a lot of my time and energy to address. Fortunately, many of them are by first-time commenters and get caught by the moderation filter. I have deliberately left many of those comments there. While I’m not certain whether or not that’s fair or wise, it has been expedient. For now, I will continue to do so, and institute a de facto policy of denying hopelessly stupid comments from getting through. If you have a comment that’s been sitting in moderation for a long time, that’s why.
I would like input on this. What do you think? Is this a fair practice? Suggestions?
With that, I announce that I have returned! Comment moderation has been lifted, and things are back to the previous policy of requiring approval only for brand new commenters.
I’ll be away for the next week. Have fun everyone! I’ve temporarily enabled comment moderation for all comments. Hope everyone is enjoying their summer.
I’ll be completely incommunicado, so I hope everyone out there in the world behaves. Try not to destroy too much while I’m away. :)
Post updated, 10/21/14. See below!
It’s general trope in the HBD community: people are getting dumber. The low IQ are outbreeding the high IQ, leading to a slow decline in genetic intellectual potential in the population. Indeed, my own analyses seem to have shown that there was a fair fertility advantage among the lower IQ over the higher IQ (seen most recently in my post Who’s Having the Babies?):
The key limitation is that most of these analyses left off in 1950s cohorts – the people who had their children in the 70s and 80s. This was my parents’ generation! We don’t know what people born later did. Does the apparent dysgenic pattern continue right up to the present day? I decided it was time to take a look:
These are average number of children had by White Americans aged 42 and older born during the 1960s, from the GSS (drawn from all GSS years, with those two parameters established), by WORDSUM score, a proxy for IQ. 95% confidence intervals shown, which should give an idea of sample sizes. I’ve collapsed the 0-3 score to make the distribution symmetrical on both sides in terms of number of subjects (there appears to be a significant rightward skew in the WORDSUM data).
Now this is interesting; unlike previous cohorts, fertility among the 1960s cohorts doesn’t look dysgenic for IQ. If anything, it looks slightly eugenic.
Let’s see further what’s going on, by looking at the sexes separately:
Here is fertility by WORDSUM for White males and females separately. Previously, we’ve seen that fertility is eugenic for men and dysgenic for women. For the 1960s cohorts, this appears to be case. But the eugenic fertility for men is strong enough to outweigh the dysgenic fertility for women, so the net effect is slightly eugenic (things were probably a bit more eugenic when you consider childhood mortality is more concentrated on the low end).
To confirm that net White fertility was eugenic, I ran the correlation between WORDSUM and average number of children (for all individuals 42 and older at time of survey):
|Cohorts||Total fertility-IQ correlation||Males only||Females only|
This is a fascinating finding. A big point of alarm in the HBD world (even noted by myself previously) is that people are getting slowly dumber with each generation. Aside from the fact that this process is, at best, very slow (see Greg Cochran here and here), as far as we’re concerned, it doesn’t even appear to continuing! At least for one period, it reversed somewhat. This seriously calls into question the practice of projecting fertility trends into the future on the assumptions current patterns will hold.
So why did dysgenic fertility halt for the 1960s cohort? That’s currently not clear. These were people born in the tail end of the Baby Boom, who would have been having children in the ’80s and ’90s. Economic conditions (which, as we’ve previous seen, can strongly affect fertility – see Another Tale of Two Maps and A Tale of Three Maps) – while clearly being not as good as during the Baby Boom – were not particularly bad, nor particularly good. This was during the “Rust Belt” epoch – “deindustrialization”– where many manufacturing jobs across the Midlands and Greater New England left the region for other parts of the country and overseas. The erosion of earning ability for low-ability males may have stymied their child-bearing prospects compared to earlier decades. I will return to this point shortly.
What about the 1970s cohorts? Well, this is a bit harder to call at the moment, because that generation is still having children (I should know). Here is a look at fertility for 1970s White Americans:
These are only individuals age 38 and over. I didn’t bother with error bars, because sample sizes are all really small here. I collapsed score 0-4 and 9-10 to make the distribution symmetrical. Sample sizes were too small for me to look at the sexes separately. But, at first look, it would seem fertility appears to have returned to a dysgenic pattern.
Though before we go too far with that conclusion, let me show you something else:
This is average age of having the first child for the marked cohorts, for White Americans, from all GSS years. To ensure every respondent had a chance to contribute their likely lifetime datum, I included only individuals age 48 and older at the time of the survey. As we see, there is a fairly consistent pattern for smarter individuals to have their first child systematically later than dumber individuals. The pattern reverses a bit at the lowest IQ levels, it appears (note: this doesn’t appear to an artifact of small sample size).
Here are males and females separately:
For the 1970s (and younger) cohorts, the smartest individuals are likely not done having children, due to the high average age of first child, which is in the 30s for these folks. Indeed, see here [Edit, 10/21/14: I’ve inserted a chart that includes all sampled individuals from the 1970s cohorts, to increase the sample size. The samples are still pretty small
(age 38 and older) –forewarned: samples are tiny, sometimes in the single digits]:
For the record, I did look at other races. Sample sizes are much smaller here, so charts would have much less value. For Blacks, fertility is generally much more strongly dysgenic throughout, increasing with time. The correlation between fertility and WORDSUM is remains in -0.19 to -0.25 range. However, the correlations are smaller in magnitude for the oldest cohorts, though it has to be expected that this is partly due to attrition through death at these ages. While samples are small, preliminarily for the 1970s cohort, the correlation is -0.30. The male-female difference was present, but small (see also Dysgenic Fertility Among Blacks? Apparently, Yes).
Samples sizes for Hispanics were too small to do anything useful.
Edit, 10/21/14: [On the advice of Greg Cochran, I also looked at whether the above pattern was just an artifact of unreliable WORDSUM scores by looking at fertility by education. Here at the results:
This is average number of children had by non-Hispanic Whites, age 44 or older, 95% confidence intervals shown. Here again we what looks like a neutral to perhaps very slightly negative relationship between education and fertility for the 1960s cohorts.
Here are males and females separately:
We see the classic pattern: fertility appears to be eugenic for men and dysgenic for women. Indeed, a look at the correlation between education and number of children shows very near neutral total fertility for the 1960s cohorts:
|Cohorts||Total fertility-Education correlation||Males only||Females only|
(Indeed, the correlation for the 1960s people becomes positive, r = 0.02, if I set the cutoff at age 48. This is driven by an increase in the correlation for men, from 0.14 to 0.20. This indicates that older fathers may be driving the relationship.)
Here are the 1970s cohorts (included only those age 40 or over) – sample sizes are very small, so I forwent the confidence intervals (0-1 = high school and below; 2 = some college; 3 = bachelors; 4 = graduate):
This suggests a return to a dysgenic pattern, as seen from the correlations. However, the as seen before, the small samples and the possible age effect makes this hard to call.
Either by the IQ (as gauged by the WORDSUM) or by reported education, the GSS data shows that dysgenic breeding seems to have significantly stalled or even reversed for those born in the 1960. For what it’s worth, Audacious Epigone has noted a decreasing correlation between the WORDSUM score and reported education in the GSS:
the correlation between wordsum scores and educational attainment by decade of birth among all native-born Americans who have participated in the GSS:
Born prior to 1950: .536
Born in the 1950s: .507
Born in the 1960s: .469
Born in the 1970s: .419
Born in the 1980s: .373
One serious issue would be this: the current neutral to slightly eugenic fertility reported in the GSS stems from a serious sex difference: eugenic for men and dysgenic for women. This leads one to suspect that low-IQ men may just be systematically underreporting the number of children they have, perhaps unwittingly so. To check for this, I looked at the total average number of children for men and women separately. I did find a slight difference (1.88 for men vs 1.96 for women), however it’s not statistically significant. ***End Edit***]
Looking at total fertility rates over time and age of first child underscores a pattern I found earlier (as noted in my post Some guys get all the babes – not exactly). Specifically, the Baby Boom was a brief period (at least during the past 100 years or so) where the total fraction of individuals who contributed to the gene pool increased:
In the era before the Baby Boom (the people who gave birth during the Great Depression), ~20% of individuals, male and female, had no children. That fraction fell to less than 10% during the Boom. It has since returned to its pre-Baby Boom size of ~20-25% (higher for males). During the Baby Boom, all sorts of individuals (about 10% more of the population) were having children who previously wouldn’t have. Since we see that in the pre-1900 cohorts, the fraction of the childless was about the same as it was for the people born at the start of the 20th century (~20%), this doesn’t appear to be solely a product of the generation trough during the Great Depression.
This may explain something noticed by blogger “Agnostic“: homeless individuals, who are very often mentally ill (especially schizophrenic) appear to be disproportionately Baby Boomers. If a certain segment of the population who, in earlier epochs, normally didn’t reproduce as much, suddenly increased their fertility due to a time of easy living, then you would expect an uptick of those sort of individuals in the following generation. If that 10% of people who bred more during the Boom were in the top 10% of those with genetic load, say, then the following era would witness a significant increase, at especially at the extreme ends of the distribution – which schizophrenia, for example, may represent.
These generational effects in fertility, with boom and bust cycles, represent the effects of the population cycle as described by Peter Turchin (see here for a good description of the process). Population growth sows the seeds of its undoing, by decreasing the share of resources (be it food, land, or these days, well-paying jobs) available to the up-and-coming generation. In short, the more people, the smaller slice of the pie each individual gets. The fewer people, the larger piece of the resource pie each family can acquire, typically boosting fertility. Immigration exacerbates these trends (see Turchin on it here). The whole process represents one of the most reliable “environmental” effects I have examined.
Coupled with the good times during the Baby Boom, we see that age of first child fell a bit (though it was fairly low before), as you’d expect. Afterwards, it rose significantly, especially for smarter women. The smartest individuals (WORDSUM 10 – roughly IQ 120+) now typically have their first child after their 30th birthday.
These and other factors makes many individuals (you know who you are) want to return us to the Baby Boom-like era, where labor was scare, and anyone who wanted a well-paying (though often gungy) job could have one. Restricting immigration, as Turchin discusses, is most likely to trend things in that direction. But it’s starting to look more and more questionable that the Baby Boom was an unadulterated good. Sure, the living was easy for those during the Boom, but its products haven’t necessarily been the best.
Fertility rose among everybody, even the smartest were breeding well over replacement then. However, the dumbest were breeding much more, more than they otherwise would, apparently. Perhaps excessive good times aren’t really all that great in the long run.
But, the following period appears to have given us an epoch of eugenic breeding, if ever slightly. Regardless, the important thing this demonstrates is that, at least in the U.S. anyway, we can forestall the coming of the supposedly inevitable idiocracy. We had a long way to go to get there anyway, but even that required a sustained dysgenic trend, and it’s unclear if that can be taken as a given. Razib Khan was right; population projections 50 years into the future are fantasy. Demographic trends have a nasty habit of changing quite a bit over time, enough to mess with the predictions of the most enlightened prophet.
Can be quite substantial. Jump off the Empire State Building and see for yourself. But, beyond that, the question remains how much of the variation in health outcomes and longevity can be explained by behavioral variation? Well, we don’t quite know. But we do have evidence which indicates that – at least in the developed world – that fraction is quite small.
On the matter of the attenuation of the association of IQ/simple reaction time with health/longevity, I’ll quote a few passages on that from relevant papers:
From Ian J. Deary & Geoff Der (2005) Reaction Time Explains IQ’s Association With Death:
After AH4 scores and each of the reaction time measures were adjusted for sex, smoking status, social class, and years of education, all effects remained significant, and the hazard ratios were only slightly attenuated (Table 1). Thus, the relation between IQ and mortality in this sample was not substantially mediated by social class, education, or smoking. Nor was the relation between reaction times and mortality substantially mediated by these variables.
we adjusted for a range of physiological, behavioural, psychological and social risk factors that can be considered as mediating variables in the IQ–mortality relation. The influence of controlling for these factors can be broadly divided into three strata. In the first, despite being associated with both IQ and mortality, adjusting individually for marital status, alcohol consumption, systolic and diastolic blood pressure, pulse rate, blood glucose, body mass index and psychiatric and somatic illness at medical examination had very little, if any, impact on the age-adjusted IQ–death relation (<10% attenuation in risk)
From Hagger-Johnson, Deary, Batty, et al (2014) Reaction Time and Mortality from the Major Causes of Death: The NHANES-III Study:
In fully adjusted models which also adjusted for educational attainment, occupational grade, poverty/income ratio, health behaviors and CVD risk factors, the association was attenuated but remained statistically significant for all-cause mortality (HR = 1.15, 95% CI 1.02,1.29; 37% attenuation), and CVD mortality (HR = 1.22, 95% CI 1.15,1.29; 36% attenuation).
The 2014 study found some attenuation when “health behaviors,” among other things, were factored in. Nonetheless, the association remained. A key problem, however, is that “health behaviors” were gauged via self-report. This has been demonstrated to be highly (though by no means completely) inaccurate. The effect of the measurement error in assessing behaviors in the study is unknown; it could bias the attenuation either upwards or downwards. Another similar study by Deary et al (2008) found that the association between simple reaction time and deaths from cardiovascular disease (and stroke in particular) unaffected by adjusting for covariants (they did however find that the association between reaction time and IQ and deaths from coronary artery disease in particular become non-significant when “health behaviors” were factored in). However, these health behaviors were also assessed by self-report. Yet another study by Shipley, Der, & Deary et al (2006) looked at a British sample (N ~7,400) found the association with simple reaction time and all cause mortality. The effect was also mediated by variables. These results call for a meta-analysis.
I also threw out this idea today:
The idea is that some ailments do appear to be heritable (e.g., heart disease), however, may have pathogenic involvement. A (heritable) weaker immune response or otherwise compromised defensive capacity might then at least partly explain observed heritability of these diseases.