Ben G in the comments points to COMMON GENETIC VARIANTS UNDERLYING COGNITIVE ABILITY, a dissertation. I don't have time to read the whole thing right now, but comments welcome.

Labels: Genomics

That's what Daniel is asking at Genetic Future, and he is soliciting the input of the economically informed. I've closed comments on this post so as to encourage you to leave comments there if you have something intelligent to say. Also, Dan posted last year. FWIW I am moderately skeptical of health benefits for the average person re: genomics as I recall several years back steakhouses were supposedly attributing their robust business to the ubiquity of statins. I suspect quantitative improvements in healthcare will have more relevance toward combining lifestyle choices with the current expectations of life expectancy and quality of life as opposed to pushing the longevity window outward much. The ubiquity of fatitude makes me skeptical that we're going in any direction aside from risking-pooling. BTW, Half Sigma has recently been promoting socialized medicine.

I assume most readers know about SNPedia, but I started noticing some traffic from it recently, so it must be gaining some traction.

Continuing my series of notes on Sewall Wright's population genetics, I come to the subject of migration. This is important in understanding the differences between Wright and R. A. Fisher on the role of genetic drift in evolution. Fisher and Wright both agreed that genetic drift would be too weak a process to be of evolutionary significance in large populations (above, say, 10,000 in effective size) . [Note 1] Equally, they agreed that it would be important in small populations, provided these remained sufficiently isolated over sufficiently long periods of time. Their disagreement was over the probability that the necessary degree of isolation would occur. This depends largely on the rate of migration between populations.



Fisher's views on the subject can be pieced together from scattered remarks, as I attempted here. It seems that from an early stage - at least from his 1921 review of the 'Hagedoorn Effect' - Fisher regarded small isolated populations as unimportant in evolution. If they stayed isolated for long, they would go extinct from occasional adverse conditions (epidemic disease, drought, etc). If they did not stay isolated, the flow of migrants from outside (whether in a steady small trickle, or occasional larger floods) would be sufficient to prevent their gene frequencies from drifting far from those of the general population of their species. But so far as I know, Fisher never made any formal quantitative estimate of the amount of migration necessary to offset genetic drift.

Sewall Wright, on the other hand, did make such estimates, and developed them in published works from 1931 onwards. It is known that a first draft of Wright's major 1931 paper on 'Evolution in Mendelian Populations') was written as long ago as 1925. In this he already took the view that genetic drift in small semi-isolated populations was an important evolutionary factor. This might suggest that by that time he had already considered the role of migration in depth. The draft of 1925 has not survived (Provine p. 237), but it seems that in fact it did not yet contain a detailed treatment of migration. The evidence for this is from Wright's correspondence with Fisher in 1929. Wright told Fisher that 'since I wrote [in August 1929, sending a copy of his draft] I have been trying to get a clearer idea of the effect of diffusion [i.e. migration] and I see, at least, that isolation in districts must be much more nearly complete than I realized at first, to permit random fixation of strains' [Provine p.256].

This conclusion is presented more formally in 'Evolution in Mendelian Populations' (at ESP pp.127-9). Here Wright develops an equation for the distribution of gene frequencies which incorporates a term for m, the rate of migration into a small semi-isolated population from a larger population with different gene frequencies. The exact meaning of this equation is difficult to interpret [see Note 2], but Wright's own conclusion is that 'Where m [the migration rate] is less than 1/2N [with N being the effective size of the receiving population] there is a tendency toward chance fixation of one or the other allelomorph [i.e. one of the alleles at a locus where there are two alleles in the population]. Greater migration prevents such fixation. How little interchange appears necessary to hold a large population together may be seen from the consideration that m = 1/2N means an interchange of only one individual every other generation, regardless of the size of the subgroup'.

This conclusion has been widely restated in the population genetics literature. Unfortunately I do not know of any clear and mathematically elementary proof. (John Maynard Smith [p. 158-60] presents a proof using only basic algebra, but it combines the treatment of migration and mutation, and involves various simplifying assumptions and approximations. There are also some confusing misprints or slips of the pen.)

It may be surprising that the rate of migration sufficient to prevent populations drifting apart can be stated as a constant number of migrants, regardless of the size of the population. D. S. Falconer comments that 'This conclusion, which may at first seem paradoxical, may be understood by noting that a smaller population needs a higher rate of immigration than a larger one to be held at the same state of dispersion' [Falconer p.79]. We may put this point slightly more formally by noting that the effect of migration in offsetting drift may be expected to be proportional to the rate of migration. The rate can be expressed as n/N, where n is the number of migrants and N is the effective size of the receiving population. Since the effect of genetic drift has previously been shown to be proportional to 1/2N, we can therefore expect the migration rate required to neutralise drift to be n/N = k/2N, where k is some constant factor of proportionality. But it follows that in equilibrium we will have n = k/2, where k is a constant. Of course, this does not tell us the size of k, but it is plausible that it is of the order of 1, as is proved by Wright and others using more rigorous methods.

The conclusion that only around 1 migrant every other generation is sufficient to prevent sub-populations drifting apart might seem fatal to Wright's belief in the importance of genetic drift. As shown in his correspondence with Fisher, Wright does initially seem to have had his confidence shaken. But Wright (like Fisher) was not one to give up a cherished theory without a struggle. Immediately following the quoted passage from 'Evolution in Mendelian Populations', Wright continues: 'However, this estimate must be qualified by the consideration that the effective N [the population size] of the formula is in general much smaller than the actual size of the population or even than the breeding stock, and by the further consideration that qm ['m' is a subscript, indicating the frequency of the allele among the migrants] of the formula refers to the gene frequency of actual migrants and that a further factor must be included if qm is to refer to the species as a whole. Taking both of these into account, it would appear that an interchange of the order of thousands of individuals per generation between neighboring subgroups of a widely distributed species might well be insufficient to prevent a considerable random drifting apart in their genetic compositions' (ESP p.128).

Wright's first point, that effective N may be lower than the apparent size of the population, is either confused or confusing, since Wright has just proved that N, the effective size of the receiving population, is irrelevant to the number of immigrants required to neutralise drift. Perhaps Wright is thinking of the effective number of migrants, rather than of the receiving population, in which case the number who succeed in contributing to the gene pool may indeed be less than the total number. The second point is valid, but not well explained. Wright's formula contains a term mqm (with the second m a subscript), where qm is the frequency of the relevant allele among the migrants. But the underlying assumption is that this is the same as in the species generally. Wright's point (made more explicitly in later papers) is that the allele frequencies in neighbouring populations are likely to be more similar than in the species generally, so that mqm will actually be less than is assumed in the derivation of the result. To adjust for this we might stipulate that the 'effective' number of migrants is smaller than the actual number, even of those who successfully breed, just as the 'effective' population size may be smaller than the actual size. This approach is clearer in later papers, for example at ESP p.236: 'Cross breeding is, however, most likely to be with neighboring populations which differ but little in value of q. In this case the coefficient m is only a small fraction of the actual amount of change [i.e. the actual observed rate of migration]'. With this adjustment of mqm, the number of actual migrants required to neutralise drift might indeed be many more than 1 per generation.

This is valid as far at it goes, but it depends on the assumption that allele frequencies in neighbouring populations are likely to be relatively similar. This is perfectly plausible, but only because we tacitly assume that migration between neighbouring subpopulations is, or recently has been, sufficient to offset genetic drift. Wright therefore seems perilously close to sawing off the branch he is sitting on. Certainly, if the allele frequencies do drift 'considerably' apart (to use Wright's word in 'Evolution in Mendelian Populations'), the assumption of similar frequencies ceases to apply, and we can no longer rely on it. A further consideration is that on an evolutionary time scale (i.e. hundreds or thousands of generations) occasional larger influxes of migrants are almost bound to occur, and undo all the slow work of genetic drift. Even if an allele is lost or fixed in a subpopulation, it can be reintroduced at any time by migration from outside, so long as it persists somewhere in the species.

Wright continued to study the effect of migration after 1931, with his fullest treatment in the paper 'Isolation by Distance' in 1943 (ESP pp.401-425). Here Wright examines three different models for migration: the Island Model, in which migrants are derived at random from a number of semi-isolated subpopulations of the species, and therefore on average have the gene frequencies of the species as a whole; isolation by distance in a two-dimensional continuum, where the probability of cross-breeding is proportional to the distance between the birthplaces of the breeding individuals; and isolation by distance in a linear range such as a river-bank. Wright's conclusions from the Island Model are not very different from those in his 1931 paper based on the cruder assumption of random migration throughout the species. The conclusions from two-dimensional isolation by distance are only slightly more favourable. As he summarises it in 1943: 'It is apparent that there is a great deal of local differentiation if the random breeding unit is as small as 10, even within a territory the diameter of which is only ten times that of the unit. If the unit has an effective size of 100, differentiation becomes important only at much greater relative distances. If the effective size is 1000, there is only slight differentiation at enormous distances. If it is as large as 10,000 the situation is substantially the same as if there were panmixia [random mating] throughout any conceivable range' (ESP p.411). Only for the more special linear-range model is there substantial differentiation due to drift in populations of moderate size.

Wright's theoretical conclusions might seem to imply that genetic drift in subpopulations would seldom be a major factor in evolution. It seems to require rather special circumstances to be effective: either very small populations, populations sparsely scattered with long distances between them, populations with a narrow linear range, or organisms that are very immobile at all stages of their life cycle. Wright nevertheless continued to insist throughout his career that drift in subpopulations was an important, if not essential, feature of evolution. The uncharitable view of this would be that Wright was simply stubborn. Having taken up his position on the importance of this factor, before having considered in depth the effects of migration, he was determined to defend it. come what may. (There would be a parallel here with the equally stubborn position of Fisher on the evolution of dominance.) A more charitable view would be that Wright was trying to find an explanation of something that was generally accepted by biologists when he began his career: namely, that the observable differences between subspecies, and even between species, are usually selectively neutral. Wright himself stresses this point in 'Evolution in Mendelian Populations': 'It appears, however, that the actual differences among natural geographical races and subspecies are to a large extent of the nonadaptive sort expected from random drifting apart. An interesting example, apparently nonadaptive, is the racial distribution of the 3 allelomorphs which determine human blood groups' (ESP p.128).

In the years and decades following 'Evolution in Mendelian Populations', the opinion of biologists turned away from the consensus view in 1931 (really no more than a superficial assumption) that subspecific differences are selectively neutral. Much of the relevant research was carried out by the students and collaborators of Wright and Fisher themselves, notably E. B. Ford in England and Theodosius Dobzhansky in the USA. The general outcome was that even apparently minor subspecific differences often had some selective value. Human blood groups, for example, were found to be correlated with resistance to different diseases, though it remains unclear whether all such differences have a selective basis.

The importance of genetic drift in subpopulations is of course an empirical matter. It is quite possible that some species are 'Wrightian' and some are 'Fisherian' in this respect. The observed amount of genetic diversity between subpopulations is usually quite modest (Maynard Smith p.160-161], suggesting that migration between them is usually sufficient to prevent them drifting far apart . There are theoretical reasons for expecting that 'Fisherian' species would be in a majority. Most species have adaptations for dispersal at some stage of their life. Plants, for example, have adaptations for spreading their seeds. Among animals, the juveniles of one or both sexes often disperse from their region of birth to find mates or territories. With a few exceptions, organisms that just stick to one spot are doomed to extinction within a fairly short period of evolutionary time, since the conditions of life seldom stay fixed for many generations. Even in species with relatively stable environments, there are theoretical reasons for expecting that a mixture of mobility and immobility would be adaptive (W. D. Hamilton, Narrow Roads of Gene Land, vol. 1, chapter 11). But it remains possible that 'Wrightian' processes are important in some cases. A particularly interesting case is the modern human species itself. After the dispersal of modern humans out of Africa, it is likely that human populations for most of the last 100,000 years were small and scattered, with little migration between different continental groups. These are good conditions for Wrightian genetic drift. Whether the observed differences in gene frequencies between continental populations are due to drift or selection remains an active area of research [see Jobling et al., passim].


Note 1. Neither Wright nor Fisher were very interested in genetic drift among genetic variants that are selectively entirely neutral, as expounded in Kimura's theory of neutral evolution at the molecular level. Fisher died before Kimura published his theory. Wright lived long enough to take account of it, and found it plausible enough with regard to neutral mutations of nucleotides, but considered it of no evolutionary interest (see Provine p.469-77).

Note 2. As I understand it, Wright's conception of the distribution of gene frequencies is broadly is follows. We assume that two populations have evolved separately, and are fixed for different alleles at one or more loci. (For simplicity it is assumed that there are no more than two alleles at each locus.) The two populations are then combined and interbreed freely. Assuming that the populations are of equal size, the frequencies of the alleles at each locus in the combined population will initially all be 50%. The combined population then evolves in isolation. As a result of random genetic drift, the allele frequencies will tend to drift away from 50%. Over a large number of loci (or over a large number of hypothetical populations) we can ask, what is the probability that an allele will have any particular frequency after any specified number of generations? The total of such probabilities over all possible allele frequencies, from 0 to 1, will of course add up to 1, and will have an approximately smooth (continuous) distribution, which (on the given assumptions) will be symmetrical around a frequency of 50%. Initially the probability distribution will be clumped closely around 50%, but as time goes on it will spread out. Eventually, some alleles will begin to be lost or fixed, with a probability of 1/2N per generation. Wright now assumes that beyond a certain number of generations the shape of the probability distribution of frequencies for the remaining alleles will be approximately constant, apart from the continuing occasional loss and fixation of alleles, which will affect all the remaining alleles equally. The problem is to find this constant distribution under various assumptions about mutation, migration, and selection. Much of Wright's work in the 1930s was devoted to this problem. I cannot claim to have followed Wright's derivations in detail, as his explanations are obscure even by his usual standards. The problem is not just that the mathematics is advanced (though it does involve more calculus than in most of Wright's work) but that he makes various simplifying assumptions and approximations which are not self-evidently justified. I can only take it on trust that the conclusions are correct, and that if they were not (as Dobzhansky put it) 'some mathematician would have found it out'.

References:

[Provine] William B. Provine: Sewall Wright and Evolutionary Biology, 1986.

[ESP] Sewall Wright: Evolution: Selected Papers, edited and with Introductory Materials by William B. Provine, 1986.

D. S. Falconer: Introduction to Quantitative Genetics, 3rd edn., 1989.

M. Jobling, M. Hurles, and C. Tyler-Smith: Human Evolutionary Genetics, 2004.

John Maynard Smith: Evolutionary Genetics, 1989.

More religious demographics from Pew: Conservative blacks and Mitt Flanders.

In discussions of nature vs. nurture a common assumption is that if it is in the genes then we can't fix it. Or we can only change it by eugenics or bioengineering babies. I wish to suggest a different approach.

The following links provide background:
Bioengineered Stem Cells Rejuvenate Muscles In Mice

Stem Cell Review Series: Aging of the skeletal muscle stem cell niche

Stem Cell Review Series: Regulating highly potent stem cells in aging: environmental influences on plasticity

Autism-spectrum disorder reversed in mice


Essentially all tissues turn-over with time. Some tissues such as the gut lining are replaced every three days, other tissues such as bone and fat are replaced over decades. (Proven by tracking green florescent cell markers over time.) In the adult brain, neurons are seldom replaced but new neurons are continually produced and some repair occurs. I believe it will eventually be shown that all tissues contain stem cells that have the potential to rebuild that tissue. Pluripotent hematopoietic stem cells from bone marrow can, with the proper differentiation signals, produce every cell type in the body. Stem cells make up less than 1/10,000 of the cells in tissue. (Adipose tissue may have a higher frequency of stem cells. Satellite cells in muscle tissue may also be relatively common. I welcome correction if I'm wrong about other tissue types.) If scientists could replace that small stem cell fraction and increase the rate of cell turn-over then eventually most of the body cells would become the new type.

Each day a few hundred stem cells in the bone marrow mobilize, circulate in the blood, and either migrate to specific tissue sites, resettle into other bone marrow niches, or die. (This has been observed in mice by florescent labeling of transplanted stem cells.) By injecting a few thousand stem cells each day, a person's original bone marrow stem cells could be gradually replaced. The process would be accelerated if stem cell mobilizing drugs were used. Or if the old stem cells were selectively targeted for destruction.

By itself, transplants using young stem cells don't significantly repair damage or rejuvenate tissue. Proper signals are needed to mobilize the stem cells to the desired site, to cause the stem cells to divide, to cause the stem cells to differentiate into the right cells, and to cause those cells to integrate into the existing tissue. This is what happens when our body successfully heals a wound. For rejuvenation scientists also need to kill senescent cells and remodel the extracellular matrix. This isn't easy but significant progress is being made.

Imagine that in ten years the technology existed to completely replace the stem cells in one mouse with stem cells from a different mouse. And that the tissue turn-over rate was increased so that most of the mouse body cells derived from the second mouse. How much remodeling of body and brain would occur? Some body structures would have been largely fixed during development but much would change due to the new cell DNA. Potentially, a sick or dull mouse could be made healthy or smart by such a full body stem cell makeover.

In addition there will be progress in restructuring damaged parts of the brain. This may require putting the tissues back in an earlier developmental state so as to rebuild a functional structure, e.g., regrow a nerve fiber connection. Memories stored in the original brain tissue structure would be lost but functionality would be regained after training. Even developmentally fixed traits might be altered by selective rebuilding of body structures.

The stem cell donors might be world class athletes, handsome, musically gifted, with IQ's over 160. By expanding a cell line in culture, one donor could supply an unlimited number of recipients. Modest genetic engineering might improve the cell line. Even the germ cells would be replaced so future offspring would not be genetically related to the original person.

Would you choose to undergo such a metamorphosis? Externally you might change in just a couple of years. Your parents and friends might not recognize you. Internally you should have pretty much the same memories. However, your internal processing might be different and your personality might change. I think you would feel like the same person but you would also know that you were different. Like remembering how it felt to be depressed...you were you then and you are you now but you aren't the same you. Hopefully your spouse would like the new you. This would be a little like massive cosmetic surgery.

This is a potential solution to the unfair distribution of good genetic traits. It could be a win-win for all groups. Defeat old age, class divisions, and racial strife in one stroke. I would do it to myself and would support having the government offer free treatment to everyone. It might even be offered as an alternative to execution or long term imprisonment.

Labels: life hacking, Stem cells

Recent advances in genotyping have made genome-wide association studies the standard way to study the genetics of a phenotype in humans (model organisms, for various reasons, are suddenly lagging behind). In terms of simply identifying loci underlying disease, this approach has led to a number of notable successes, but there's been a nagging concern that identifying loci of small effect doesn't help much with diagnostics--even with 30 loci now know to impact height, genetics is able to account for something like 3% of the total variance in the phenotype despite the fact that the heritability of the trait is something like 90%.

Different traits have different genetic architectures, of course, so the recent publication of 30 loci involved in Crohn's disease has led to vastly different results:

To advance gene discovery further, we combined data from three studies on Crohn's disease (a total of 3,230 cases and 4,829 controls) and carried out replication in 3,664 independent cases with a mixture of population-based and family-based controls. The results strongly confirm 11 previously reported loci and provide genome-wide significant evidence for 21 additional loci, including the regions containing STAT3, JAK2, ICOSLG, CDKAL1 and ITLN1.

So with the same number of loci, how much of the variance are these authors able to explain? It's 10%, a modest number, but larger than that currently mapped for most (any?) other complex trait. And keeping in mind that the heritability of Crohn's disease is estimated at 50%, they've accounted for something like a fifth of the total genetic variance. I'm not sure exactly what threshold makes genetics clinically useful, but surely this is approaching it.

Labels: Genetics

Trait-Like Brain Activity during Adolescence Predicts Anxious Temperament in Primates. ScienceDaily summary:

We all know people who are tense and nervous and can't relax. They may have been wired differently since childhood.

....

"We're looking for better ways to diagnose and treat mental illness," explains Kalin, about his ongoing work at HealthEmotions. "We're trying to understand how the brain influences mood, reactions to stress and physical health."

PLoS stays afloat with bulk publishing: Science-publishing firm struggles to make ends meet with open-access model. In Nature News.

When The Inductivist observed that the unchurched tend more toward criminality, I asked whether social matrix would be a major factor here. In other words, in an area where church going is a major signal of social conformity antisocial oddballs would be far more likely to break the the norm. With a follow up The Inductivist says:

My next step was to estimate the association between arrest and attendance for each of the nine divisions: I did this with logistic regression (sample sizes ranged between 460 and 2,306). I then calculated the Pearson correlation between these logit coefficients and the mean attendance scores displayed above. It is .44. This means that the connection between arrest and never going to church is stronger in areas where churchgoing is most common. So Razib might be right that in religious areas many of the well-adjusted folks feel like they should go to church, leaving a high percentage of antisocial people among the ranks of non-attenders.

A meta-point here (and obvious one to many of you no doubt) is that religion can not be understood simply as a relationship between an individual and their faith in an atomic manner. The social dimension in critical to mass religion.

Related: Good Without God, But Better With God?

Pardis Sabeti on The Future of Genomics (video). Via Sandy.

PZ Myers outlines synteny. RPM says he's kind of wrong. Check out the definition in Wikipedia. Since RPM came down on me for confusion on this term I knew he would bring this up. I don't really care much about which definition is "correct," but I thought I'd point interested readers to the debate.....

Labels: Genetics

Remember that better time when college coeds frolicked on the quad lawn, safe from the eyes of older males, who were drawn instead to the allure of a mature woman? Indeed, doesn't it seem like nowadays, in our Girls Gone Wild culture, we shove females into the sexual spotlight at ever younger ages? That's what you'd conclude from the 50,000 alarmist results that a Google search for "+sexualizing +young" returns, in particular the recent panic over 15 year-old Miley Cyrus posing semi-topless for Vanity Fair. The cropped picture to the left is of Elizabeth Ann Roberts, who was 16 when she was photographed nude as Playboy Playmate of the Month -- of January 1958.

On an intuitive level, though, we know that the culture must be more hostile than before to sexualizing young females -- there would be no hysteria if it were acceptable. Plus, suburban housewives and city-dwelling cougars have never hogged so much of our attention. Still, let's turn to three datasets that show the trend is, if anything, toward sexualizing increasingly older females in popular culture. We will look at data across the decades on beauty pageant winners, girls featured in nude magazines, and hardcore porn actresses.

First, take the winners of the Miss America beauty pageant, a competition determined mostly by how closely the contestant fits the ideal look of the time. A writer for the website Seduction Labs has already done an extensive analysis, so I took the age data from his work. Here is how Miss America's age has changed over the decades:



It sure looks like Miss America is getting older -- the ones from before 1940 are quite young -- and this is true: Kendall's tau for the correlation between year and age is +0.50 (p = 3 x 10^(-10), two-tailed). Admittedly, estimating the youth-obsession of each year with only one data-point -- the winner from that year -- is less desirable than averaging all contestants' ages for that year, but the data are hard enough to come by that this is the best we can do.

Next, consider the Playboy Playmates of the Month, averaged for a given year. While the 1950s had fewer data, each year still had at least 7 data-points. Using 12 data-points to estimate each year should make us more confident in the results, shown here:



Again, the average Playboy Playmate is getting older: Kendall's tau for the correlation between year and age is +0.44 (p = 3 x 10^(-6), two-tailed). The trend is clearly not linear, though, since there was a decrease in age at least from the mid-1950s, when the data begin, throughout the 1960s.

In response to a criticism brought up in the comments to the post showing that the popularity of blonds is recent, I've also calculated Kendall's tau based on the raw month-by-month data-points, rather than yearly averages: it is +0.18 (p = 1 x 10^(-10), two-tailed). As I mentioned to the commenter, I think it's more instructive to look at the year's average since the Playboy people likely have a target girl in mind for the year's subscription, based on the perceived demand. That is, the Playmates within a given year are comparable to the Miss America contestants for a given year -- they are chosen to fill out a year's run, and Miss April could just as well have been Miss December. Still, even by this perhaps overly stringent standard, the trend is positive and significant.

Finally, we look at actresses in hardcore porn movies. Collecting a representative sample of active females in a given year would be incredibly arduous, so instead I took famous actresses and determined how old they were when they made their first movie, and entered this as a data-point for the year in which they started making movies.

The lists I used are the AVN Hall of Fame, the XRCO Hall of Fame (which barely added anyone else), and a list of female porn stars by decade drawn up by the porn geeks at Wikipedia. I required each year to have at least 5 data-points; if there were too few, I merged that year's data with an adjacent year (whichever had fewer data-points than the other choice), so that the data-sparse year is excluded and the beefed-up year is included. This mostly affects the 1970s and early 1980s. Here are the ages of first-time porn stars by year of their first movie:



There is no increase or decrease over time: Kendall's tau for the correlation between year and age is nowhere near significance. There are several apparent upward and downward trends, though. This might be the only example of the 1980s and early 1990s showing greater progress by the declinists' standards. I recently analyzed a large, representative sample of porn stars and found that their average age is 23, for what it's worth. Again, that's what we really want to see: the age of the typical actress for a given year.

Maybe girls enter at earlier ages in recent times but don't reach their peak in popularity until they are in their early 20s. Another drawback of looking at age at first movie is that it ignores the recent popularity of "MILF" actresses -- maybe it's just that the variance in age is increasing. Admittedly, these pornstar data are not ideal.

Finally, we examine the popularity of beauty pageants specifically for teenage contestants. While I don't have datasets to analyze, such as the annual TV ratings, there is enough information on them to get a rough picture. First, there is Miss Teen USA, the adolescent version of Miss Universe. It was created in 1983, reached its peak for ratings in 1988, and has declined in popularity afterward, to the point where it may not even be televised anymore. And second, there is Miss Teenage America, which was created in 1962 and was last televised in 1977. Judging by its corporate sponsorship and celebrity hosts, it must have been somewhat popular. There are other beauty pageants for teenagers, but they are not even televised, and so do not count as evidence of an obsession with youth. Rather, we see a shift away from throwing young girls into the purely sexual spotlight.

Since there are no huge long-term swings up and down in these data, as opposed to the cases of sluttiness and violence, all generations can say that they've improved over previous generations, or at least done no worse. If any generation is to be accused of sexualizing younger girls in popular culture, though, it is surely the older ones. It is true that the current culture does not value women over 30, but that has never been the case -- just the opposite.

As with sluttiness, part of the declinists' misperception may be due to fashion trends, such as even prepubescent girls wearing adult-inspired clothing. That's hardly evidence of their being sexualized, though -- no guy is actually looking at them as a sex object, and dressing like an adult doesn't make you behave like one sexually. While it may be a bizarre fashion trend -- though more bizarre than when pre-pubescents started wearing two-piece bathing suits? -- it doesn't reflect a sexualization of the young.

What's causing this trend toward older sex symbols? Oh, I don't know, but I'm sure we'll get a bunch of half-baked ideas in the comments, so I'll get the goofball ball rolling. Women are having their first kid later, if at all, so there's a wider age range of females who haven't ruined their figure by giving birth. Still, according to the analysis of Miss America winners at Seduction Labs, there are other trends: starting around 1960, winners became taller, less buxom, and less hourglass in shape, in addition to older. In short, the feminine ideal in popular culture has been worn down by the march of the masculine minxes. It's a mistake to blame this on the women's movement of the 1970s, though, since most of these trends began in the early-to-mid-1960s. Radical feminists were just jumping on the bandwagon and trying to steal credit for it.

Though it's harder to measure, the manliness of these sex symbols' faces has surely increased -- go back and look at some of the Playboy Playmates from the late 1950s through the late 1960s. They look like girls, not butch transvestites (NSFW, obviously). I see this as a form of cultural decline, of course, but the declinists who decry our obsession with youth could not be more wrong.

Labels: babes and hunks, previous generations were more depraved

Doubling Of Sexually Transmitted Infections Among Over-45s In Under A Decade. Dare we say an "epidemic???" If you want to push the envelope of course, She was 82. He was 95. They had dementia. They fell in love. And then they started having sex. In any case:

While the numbers of infections identified in younger age groups rose 97% during the period of the study, those identified in the over 45s rose 127%.
...
"Indeed, it may be argued that older people are more susceptible [to sexually transmitted infections] as they are less likely to use condoms than younger people," they say, adding that as successive waves of people with more liberal sexual attitudes and behaviours age, the problem is likely to worsen.

I guess the "safe sex" message just isn't getting through to the less young.

Related: Your generation was sluttier.

Labels: sex

Long-time readers know that one of my beliefs that I'll stop at nothing to prove is that blond women are not sexier than brunettes, whatever other appeal they obviously have for many men. Point-estimates of the current popularity of blond hair neglect the fact that standards of beauty can change over time -- within boundaries, to be sure, but still. Perhaps we only live in a blond-obsessed world today, while brunettes may have ruled in the past. Indeed, I will show just that. Furthermore, the shift toward blonds parallels several other shifts toward a more masculine ideal of female beauty since the early / mid-1960s.

The data come from Playboy Playmates of the Month ("Playmates") from 1954 to 2007. We need to look at sources that pander to popular demand in sexual tastes, which excludes runway fashion magazines (not used by males for fantasy purposes) as well as data on high-ranking Hollywood actresses (who are esteemed only in part based on their looks). We also need comparable data that stretch over decades, and that provide us with many data-points for each year -- in a worst case scenario, we might look at something like Miss Universe winners, but estimating the value of blond-obsession for a given year with only a single data-point is hardly ideal. Playmates, though, yield 12 data-points per year.

In the name of scientific discovery, I looked at pictures of every Playmate [1], and coded her hair color as either 1 for blond or 0 for non-blond. Dark blonds counted as blond, light browns as non-blond. Redheads counted as blond if they had very fair, strawberry blond hair, and as non-blond otherwise. The point is not to measure the popularity of the full spectrum of hair colors -- just blondness. A small handful of Playmates had several hair colors within the single issue they appeared in. I coded these as 0.5 because their pictures were split pretty evenly between blond and non-blond hair -- maybe due to wigs, I don't know.

I then took the fraction of blonds in a given year and plotted these over time. Here is the raw scatter-plot, together with 3-year and 7-year moving averages that smooth it out:



The scatter-plot suggests an increasing trend, and this is true: Kendall's tau for the correlation between year and percent blond is +0.27 (p = 0.01, two-tailed). [2] However, because each year's value can only take on roughly 12 values (1 / 12, 2 / 12, etc.), there are a lot of tied years, which may underestimate the true correlation. Kendall's tau for the correlation between year and the 3-year moving average of percent blond is +0.47 (p = 2 x 10^(-6), two-tailed), and is +0.64 (p = 2 x 10^(-10), two-tailed) when the 7-year moving averages are used. Using a moving average gives us a better idea since they can take on far many more values, and so produce fewer ties.

Whichever one we choose, it is clear that blonds have increased quite a bit in popularity over the decades. At the same time, the trend is clearly not linear: there is a decrease in blond-obsession at least from the mid-1950s, when the data begin, to the early / mid-1960s. There follows an increase, and an apparent reversal since the turn of the millennium -- please god, let it be so. This looks periodic, like a fashion cycle.

In trying to account for this trend, we should try to be as general as possible. What other trends in female beauty show an increase after the early 1960s? I didn't look at other aspects of the Playmates, but someone else has tabulated data on Playmates of the Year from 1960 to 2006 -- again, estimating the popularity of some trait in a given year based on a single data-point is worst-case, but I'm relying on it here because I've already spent enough time collecting hair color data. The links in footnote 1 provide all the anthropometric data, though, so if you want to collect an analyze it, we will link to your analysis.

I calculated the Waist-to-Hip Ratio and BMI of Playmates of the Year from the above data, and Kendall's tau for the correlation between year and WHR is +0.53 (p = 4 x 10^(-7), two-tailed), while between year and BMI it is -0.24 (p = 0.02, two-tailed). So, these sex symbols are increasingly losing their feminine hourglass shape and fatty softness -- nearly all BMI points are below 20, so it's not like they used to be fat but are now healthy. They are also getting taller: Kendall's tau is +0.31 (p = 0.004); and smaller in the chest: Kendall's tau is -0.35 (p = 0.001).

Someone else has also done an analysis of Miss America winners, and the exact same trends emerge there as well (see his graphs).

The common factor of all these trends is that the ideal of female beauty has become increasingly masculinized. Recall that males are more likely to be blond, so the hair color trend is part of the larger masculinizing trend. I didn't look at eye color, but if it's part of the overall trend, the earlier Playmates should be less blue-eyed than later ones, as blue eyes are also more typical of males. Skin color would be tougher to analyze; if it's part of the same trend, it should get darker over time. Anecdotally, these two guesses seem to be true, but someone should look at the data to check.

It therefore appears that a preference for blonds should also correlate with a preference for taller and less curvy women. Again, someone else can look that up in the psychology literature and post in the comments. But the words "tall," "thin," and "blond" usually co-occur, don't they? Whatever appeal such women have, raw sex appeal is unlikely to be among the top reasons. Blond hair correlates with something like introversion, and that makes sense since men on average are more introverted than women. So, maybe guys start digging blonds when they become more marriage-minded, or if they are inveterate monogamists. A blond will be less likely to be bouncing off the walls and being constantly out and about in search of social stimulation.

Bang a brunette, bank on a blond? It would fit with the trend toward lower sluttiness in recent times, which we expect to weed out the sex kitten types from popular culture. This suggests that dark hair is part of that highly sexualized image -- something that was always obvious to everyone but the blond-lovers.

[1] For years 1954 to 1992, I used this source that contains the full shoot for each Playmate, and for 1993 to 2007, Playboy's official website (if the single picture available on the Playboy site was ambiguous, I did a Google image search to get a better idea).

[2] You can easily calculate Kendall's tau with this website, which I used here.

Labels: babes and hunks