1. Obesity is increasing in the population, so it can’t be genetic.
Well, average height is also increasing in the population. Does that mean that you could be as tall as me, if you weren’t too lazy to grow?
Twin studies and adoptive studies show that the overwhelming determinant of your weight is not your willpower; it’s your genes. The heritability of weight is between .75 and .85. The heritability of height is between .9 and .95. And the older you are, the more heritable weight is.
I think the analogy between obesity and height is weakened by likely differences in the effect on the variance of the traits due to environmental changes. First, remember that the term “genetic” is very broad, while the term “heritable” is very specific. Heritability is the proportion of trait variance within the population explainable by variance of genes. The said traits are usually thought of as quantitative traits, like height, weight or IQ, which exhibit a normal distribution. To say that a trait is .95 heritable does not mean that it is caused 95% by genes, that’s not even wrong. Rather, it is to say that 95% of the variance within the population can be accounted for by the variance of genes within the population. But heritable traits are also usually affected by environment; if you starve someone they will be short, but retain five fingers. The number of fingers you have on your hand is not heritable, because there’s no real variance within the population of the trait. It’s genetically specified, but not heritable.
In this study, genotypes from Human Genome Diversity Panel populations were used to further evaluate a 93 SNP AIM panel, a subset of the 128 AIMS set, for distinguishing continental origins. Using both model-based and relatively model-independent methods, we here confirm the ability of this AIM set to distinguish diverse population groups that were not previously evaluated. This study included multiple population groups from Oceana, South Asia, East Asia, Sub-Saharan Africa, North and South America, and Europe. In addition, the 93 AIM set provides population substructure information that can, for example, distinguish Arab and Ashkenazi from Northern European population groups and Pygmy from other Sub-Saharan African population groups.
These data provide additional support for using the 93 AIM set to efficiently identify continental subject groups for genetic studies, to identify study population outliers, and to control for admixture in association studies.
AIM = ancestrally informative markers. You are probably aware of the fact that most variance on any given gene is found within populations, and not between. Therefore, the chestnut of conventional wisdom that 85% of variance is within races, and 15% is between races. But not all genes are created equal. For example, on SLC24A5 almost all the variance among Europeans and Africans is between the races; if you know the state of SLC24A5, then you can establish with a high degree of certainty whether the person is African or European in origin if these are your only two options (Asians and Africans cluster on SLC245, though if you find the “European” variant you can be assured of an individual’s provenance, at least partially, from North Africa or Western Eurasia). The logic then is that a small number of highly population informative markers (i.e., those markers which are good at distinguishing between populations) can allow one to discern population stratification within medical studies. If, for example, you are looking for disease susceptibility alleles and different populations have different disease susceptibilities, then naturally those alleles which are correlated with particular populations will show up on an association (though the “causal” connection is population identity in terms of both disease and allele). This is why Ashkenazi Jewish genetics are of more than genealogical interest, if Jews have a unique suite of genetic diseases (this is true) then it might best to exclude them from studies using other Europeans. Sniffing out of this sort of “cryptic” structure isn’t that hard, in the early 2000s Neil Risch et al. pointed out that as few as 20 AIMs may be sufficient to distinguish continental populations.
This study uses 93 markers to distinguish HGDP groups, along with a few other supplemental populations which were not well represented in HGDP sample. For example, since the government of India was rather restrictive of genetic research when the HGDP population samples were being collected the “South Asians” are generally from Pakistan. A study which surveyed Indian Americans (that is, Americans whose family are of Indian origin) provided the data to “plug” that whole. Clusters were displayed through two primary methods, Structure and principal component analysis charts.
Matt Yglesias pointed to this Forbes list of best cities for singles. Shouldn’t one observe that the best city for men might not be the best city for women, and vice versa??? (sex ratio differences) Below the fold is the famous “singles map” from a few years back….
A quick follow up to the post below, I was curious as to the increased profile of Google in The New York Times (Google trends doesn’t seem to be available to the public before 2004) around the turn of the century. In particular, I curious as to Google’s prominence in the “Technology” section of the paper. So I looked it up. There were 78 mentions between July 1999 and December 2001. Mentions of Google increase at a rapid clip throughout this whole period. Below is a histogram of this period, illustrating the consistent rise in frequency of mention.
The collaboration between Yahoo! and Microsoft is spawning a lot of articles about the coming duopoly in search (since the Yahoo! Microsoft deal is for 10 years, we’re talking 10 year horizon times). But this got me to thinking: when did people realize Google was something big? I realized Google was something big (for me personally since I’m a data junkie) after being pointed to it from this article in Salon in December of 1998. I became a Google evangelist. Initially most people thought my enthusiasm was a bit strange, at that point there were a dozen search engines, and all of them were pretty much crap. Of course once anyone used Google they never touched anything else again (to be fair, it took a little while for Google’s indexing to overtake all other search engines, so there was some utility in checking the others for a bit).
But when did Google hit the media radar? It seems that The New York Times didn’t see fit to mention it until July of 1999, I Link, Therefore I Am: a Web Intellectual’s Diary:
Hang around long enough on Lemonyellow.com and you’ll feel the power and depth of the Web in a way that is very different from, say, a day spent bidding on old comic books at Ebay or managing a stock portfolio at E*Trade. The links on Lemonyellow.com go to very few commercial sites, with the exception of Amazon.com, which is the link for the site’s many book titles. To find just the right link, Ms. Halpert uses a search engine — usually Google, her favorite.
Update: The author of the paper clears up confusions.
Follow up to the post yesterday, here’s the paper, Physical attractiveness and reproductive success in humans: evidence from the late 20th century United States:
Physical attractiveness has been associated with mating behavior, but its role in reproductive success of contemporary humans has received surprisingly little attention. In the Wisconsin Longitudinal Study (1244 women, 997 men born between 1937 and 1940), we examined whether attractiveness assessed from photographs taken at age ∼18 years predicted the number of biological children at age 53-56 years. In women, attractiveness predicted higher reproductive success in a nonlinear fashion, so that attractive (second highest quartile) women had 16% and very attractive (highest quartile) women 6% more children than their less attractive counterparts. In men, there was a threshold effect so that men in the lowest attractiveness quartile had 13% fewer children than others who did not differ from each other in the average number of children. These associations were partly but not completely accounted for by attractive participants’ increased marriage probability. A linear regression analysis indicated relatively weak directional selection gradient for attractiveness (β=0.06 in women, β=0.07 in men). These findings indicate that physical attractiveness may be associated with reproductive success in humans living in industrialized settings.
I don’t see a point in commenting further at this point. Since Satoshi Kanazawa is a fan of Ann Coulter (H/T Jezebel), I think it would be appropriate to refer to him as the “Ann Coulter of Evolutionary Psychology.” His genius for self-promotion is equivalent.
Short article in PLoS Biology, Charles Darwin’s Reception in Germany and What Followed.
In the post below I wanted to have an attractive female headshot, so I naturally looked for something from Megan Fox. A few years ago I probably would have used someone like Jessica Alba. In fact, I did use Alba as an “illustration” a few times in this blog’s history. But 3 years is a long time, and Fox is the new thang in the air. But I wanted to make a bit more precise my subjective impression, so I thought Google Trends might be helpful. I think it can be argued that Jessica Alba’s “peak” was the mid-2000s, and the trend data goes back to 2004. And so below, the results….
It’s rather clear. Fox has eclipsed Alba. At least among the set who use search engines to find more “data” on young starlets. How does Megan Fox relate to other celebrities? Below are comparisons with Paris Hilton and Britney Spears.
Update: The author of the paper clears up confusions.
Update: Here’s the paper. End Update
The British media is abuzz with another paper from Satoshi Kanazawa, the evolutionary psychologist who has great marketing savvy. I can’t find the study online anyway, so here is the Times Online:
In a study released last week, Markus Jokela, a researcher at the University of Helsinki, found beautiful women had up to 16% more children than their plainer counterparts. He used data gathered in America, in which 1,244 women and 997 men were followed through four decades of life. Their attractiveness was assessed from photographs taken during the study, which also collected data on the number of children they had.
One finding was that women were generally regarded by both sexes as more aesthetically appealing than men. The other was that the most attractive parents were 26% less likely to have sons.
Kanazawa said: “Physical attractiveness is a highly heritable trait, which disproportionately increases the reproductive success of daughters much more than that of sons.
“If more attractive parents have more daughters and if physical attractiveness is heritable, it logically follows that women over many generations gradually become more physically attractive on average than men.”
The Daily Mail has more numbers:
If you are a regular reader of ScienceBlogs you will have already stumbled upon several reviews of Unscientific America: How Scientific Illiteracy Threatens our Future. Janet Stemwedel of Ethnics & Science probably has the most thorough reviews, while P. Z. Myers’ ‘exchange’ with the authors, Sheril Kirshenbaum & Chris Mooney, had the most ‘spirit.’ Chard Orzel of Uncertain Principles put up a short & sweet positive impression which covers the major points in Unscientific America very well, as well as the overall thrust of the book.
Of course as Chad noted If you read Sheril & Chris’ weblog, The Intersection, the narrative will seem rather familiar, as filaments of their overall brief can be found strewn across many of their blog posts these past two years. It is important to reiterate that this is a book that should not be judged by the cover, in particular, the title. It’s not a conventional rehashing of the fact that most Americans, and most humans, are illiterate in terms of the nuts & bolts of science fact. Median human stupidity is such a banal background condition of the universe so as to not be worthy of any interest. Rather Sheril & Chris sketch out the multivalent relationships between the media, government, religion and science, and how these distinct institutions relate to each other and the populace at large. The authors draw heavily upon their own diverse personal experiences. It is perhaps not a trivial fact that Chris Mooney’s fiance worked for the Writer’s Guild of America, and so he had some firsthand media connections which allowed him to easily communicate the mindset of those in the entertainment industry. After all they were his friends and acquaintances. Sheril was at one point a staffer at Congress. The funniest anecdote in Unscientific America for me was that Vern Ehlers, a physicist who represents a district in Michigan, had to rush to the floor to make it clear to his colleagues that funding for “game theory” did not mean funding for the scientific research of sports games!
So, in a frankly insane healthcare reform effort, he restricted the public’s access to care by replacing up to 15,000 doctors and nurses with unqualified military conscripts. The next year, he ordered hospitals and clinics outside of the capital, Ashgabat, to close — even though the vast proportion of Turkmenistan’s population lives in rural areas. The BBC quoted him as saying, “Why do we need such hospitals? If people are ill, they can come to Ashgabat.” He also implemented fees and created an “unofficial” ban on the diagnosis of certain communicable diseases, like hepatitis.
For Mozilla and Google, Group Hugs Get Tricky. To some extent it seems that the story is going to be relevant in a few years when Chrome will presumably be more of a full-featured browser. Right now it seems a non-issue since Chrome’s penetration is rather low. But this part was pretty weird:
“Mozilla performed a really good service, but you have to wonder what their relevance is going to be going forward,” says Matt Rosoff, an analyst at Directions on Microsoft, an independent firm that tracks the company. “They keep Microsoft honest. But if Google is pushing innovation in its own browser, it can play that role.”
It seems bizarre to insert a quote in from a firm whose bread is buttered by Microsoft. One would suspect that such a company would have a good sense of how Microsoft might respond to competition, but be less cognizant about the specific details of said competition. I’m not a Richard Stallman type fanatic, but it seems a no-brainer that perhaps there might be some benefit from an organization whose strength is leveraging its credibility with the open source programming community. The original “browser wars” were between Netscape and Microsoft when Netscape was still dominated by a start-up culture. The Mozilla Foundation is obviously not a conventional corporation. We really don’t know what a full-blown browser war between two public corporations, a duopoly if you will, would look like. I assume that corporate competition would see predictable gains in efficiency, productivity, and continuous incremental additions to functionality. But the open source movement, or a start-up, would be more likely to “think outside the box” and take risks, and flip-paradigms. After all, the browser technology was dead in the water for years after the vanquishing of Netscape by IE. No established tech company saw any market opportunity to challenge Microsoft. The Mozilla Foundation created an opportunity by disrupting IE’s de facto monopoly in what seemed like a quixotic attempt at the time. Sometimes society may profit from those who act in a manner which may not maximize their personal short-term profit.
Tyler Cowen linked to a Time article on the phenomenon of Southern Americans being relatively overweight vis-a-vis Americans from other regions of the country. Several reasons are offered, from the lower per capita income of Southern states, to the fact that Southern food tends to be fried and less healthful. But the article doesn’t mention one very salient fact: black Americans are heavier than white Americans, and are disproportionately concentrated in Southern states. What is a regional disparity could be accounted for by underlying differences in the distribution of races.
State Health Facts reports that 70% of African Americans are overweight, vs. 60% of white Americans. Using state-by-state data one can see how accurate assessments of interregional variation are when you control for race. The chart below shows the relationship between the proportion of whites who are overweight to the total population in each state*.
Nisan didn’t mean to fall in love with Nemutan. Their first encounter — at a comic-book convention that Nisan’s gaming friends dragged him to in Tokyo — was serendipitous. Nisan was wandering aimlessly around the crowded exhibition hall when he suddenly found himself staring into Nemutan’s bright blue eyes. In the beginning, they were just friends. Then, when Nisan got his driver’s license a few months later, he invited Nemutan for a ride around town in his beat-up Toyota. They went to a beach, not far from the home he shares with his parents in a suburb of Tokyo. It was the first of many road trips they would take together. As they got to know each other, they traveled hundreds of miles west — to Kyoto, Osaka and Nara, sleeping in his car or crashing on friends’ couches to save money. They took touristy pictures under cherry trees, frolicked like children on merry-go-rounds and slurped noodles on street corners. Now, after three years together, they are virtually inseparable. “I’ve experienced so many amazing things because of her,” Nisan told me, rubbing Nemutan’s leg warmly. “She has really changed my life.”
Nemutan doesn’t really have a leg. She’s a stuffed pillowcase — a 2-D depiction of a character, Nemu, from an X-rated version of a PC video game called Da Capo, printed on synthetic fabric. In the game, which is less a game than an interactive visual novel about a schoolyard romance, Nemu is the loudmouthed little sister of the main character, whom she calls nisan, or “big brother,” a nickname Nisan adopted as his own when he met Nemu. When I joined the couple for lunch at their favorite all-you-can-eat salad bar in the Tokyo suburb of Hachioji, he insisted on being called only by this new nickname, addressing his body-pillow girlfriend using the suffix “tan” to show how much he adored her. Nemutan is 10, maybe 12 years old and wears a little blue bikini and gold ribbons in her hair. Nisan knows she’s not real, but that hasn’t stopped him from loving her just the same. “Of course she’s my girlfriend,” he said, widening his eyes as if shocked by the question. “I have real feelings for her.”
H/T Talk Islam
Officials in Shanghai are urging parents to have a second child, the first time in decades the government has actively encouraged procreation.
A public information campaign has been launched to highlight exemptions to the country’s one-child policy.
With the whole Henry Louis Gates affair there has been some talk about how racist Boston is. This is a joke. I am aware that the North has a checkered history, from busing in Boston in the 1970s to Bensonhurst in the 1980s. But calling Boston the Alabama of the North is an insult to our intelligence. Part of the issue here I think is that it is easy to show how racist the North is, and how far the South as come, by using as a counterpoint a cartoon model of race relations as a function of geography which never existed. It is a fact that in much of the North blacks were excluded from settlement either de jure or de facto (several “Free States” attempted to ban black migration explicitly by law). But Boston was also the scene of riots when escaped slaves were caught and dragged off in chains by the law. Southern politeness is such that whites no doubt did not, nor do not, always behave like cretins to colored people.
But I was curious, how different are the North and the South on social issues? I used the GSS and combined some of the regional categories so that there were two classes, North and South. The distinction was based on Census Divisions, so one could quibble on the margins. I also limited the sample to whites, since blacks and whites may have very divergent views, especially in the South. Finally, I plotted the attitudes as a function of time to see if the two classes were tracking each other, diverging or converging.