Razib Khan One-stop-shopping for all of my content

May 8, 2019

Going beyond the sex “grip strength” binary

Filed under: Sex Difference,Sex Differences — Razib Khan @ 11:20 pm

Jesse Singal brought this piece in Deadspin, She’s Got The Strength, But Who Has The Power?, to my attention.

Some very interesting sections:

When we shove the concept of athletic ability—strength, for instance—into the same black-and-white binary that we try to put gender into, we’re wrong. There is no stark line separating what men can do athletically and what women can. Some women, in fact, are bigger, faster, and stronger than some men. A large data set analyzed for a 2018 study looked at the body composition and endocrine profiles of 689 elite cisgender athletes in various sports. When it came to physical attributes there was complete overlap between the men and women analyzed, McKinnon pointed out. For instance, the shortest person in the data set was male, not female. The lightest male weighed the same as the lightest female. There were men athletes and women athletes who had testosterone levels that hit the top of the chart and the bottom. Simply put, the range of any physical characteristic within a sex, (like, for instance, the six feet of difference between the shortest man in the world and the tallest man) is far greater than the average difference in height between the average man and the average woman (five inches). And elite athletes tend to live at the far ends of these spectra anyway.

USA Powerlifting’s response to transgender athletes is head-spinning. The thing about all this talk equating hormone replacement therapy to doping, and the threat to “biological females,” and the “unfair advantages” of “male puberty,” is that it’s based entirely on social perceptions of gender.

“There’s absolutely no scientific evidence at all that supports their position,” said Rachel McKinnon, an expert on athletes’ rights and a professor of philosophy at the College of Charleston, and a world champion track cyclist to boot.

Recently a very successful person told me that mathematical intelligence is probably overrated in comparison to verbal intelligence. It is true that some women are bigger, faster, and stronger than some men, and therefore a lot of social policy follows from this truth? Well, empirically that seems to be the case today.

Despite the irrefutable sophistication of words, I decided to pull some data from the National Center for Health Statistics. These data are useful because they separate by sex and age (and in some cases race/ethnicity). Rather than focusing on ranges, I was curious about the distributions for two characteristics:

  • Height in males and females of a range of ages and between the sexes
  • Dominant hand grip strength in a range of ages and between the sexes

In some cases, there were age intervals, so I simply took the midpoint (e.g., 25-29 becomes 27). Also, they had an 80 and over category. I just left that as 80.

First, let’s look at the age. The figure below shows the distribution of height for males and females over the years, with intervals along with two standard deviations for each age.

Let’s zoom in on puberty.

None of the results should be surprising. I assume many of you remember age 12 when the girls were taller than the boys?

Now let’s look at the distribution at age 25.

You probably want to know the overlap. The shaded area is 51% of the total area under the union of the two curves.

Not a great surprise. Men are taller than women, on average. But there are many women taller than many men.

But what about grip strength? This is one of those standard metrics that’s used to measure health. People with illnesses tend to weak. So they measure this in many people to get epidemiological data.

Here is the plot by age and sex. Again, two standard deviations. Notice that the two curves are more distinct during adulthood than height. Men have stronger grips than women to a greater extent than their simple size difference.

Let’s zoom in on puberty. Here we can see a very large difference between males and females. The difference is more striking than with height. Between the ages of 12 and 13, males start to zoom away from females in grip strength. There’s basically no difference in grip strength for children of elementary school age, on average.

Now let’s look at the distribution at age 25. Again, it is more striking than that for height.

So finally, what’s the overlap? ~21% of the area under the curves overlaps. This means that are a substantial number of women who could pummel a substantial number of men. But, in these cases, it is the strongest of women and the weakest of men. I would say that that’s not sporting, to be frank.

In media, there is often a depiction of rather petite women taking on larger men in physical fights. Because film and television is fantasy, of course, the women, if they are on the “good” side, will come out victorious (just like the hobbits in Peter Jackson’s films). But reality would not be as pretty.

On the other hand, a large woman and a very small man seem like it would be a reasonably “fair” fight from these data. But I’m certainly glad that Red Sonja was not written and filmed in a more realistic manner, with the towering Brigitte Neilsen avoiding Arnold Schwarzenegger’s Lord Kalidor to only slay smaller fry.

You may have noticed that males are stronger than females when you correct for body size. Why? The average body fat percentage of a male (not overweight or obese, though not fit) is in the low 20s. The average body fat percentage of a similar woman is in the high 20s. In contrast, men have 40% more muscle mass in the upper body, and 33% in the lower body.

I’m just a simple geneticist. I don’t really know much biology. I don’t know what goes on physiologically and structurally beyond what I learned in high school and what I know from being a human being who went through puberty. But something happens that makes males and females quite distinct in their athletic abilities from what I can see in the data.

November 18, 2010

Sex differences in global atheism, part N

Filed under: atheism,Culture,Data Analysis,Religion,Sex Difference,WVS — Razib Khan @ 2:55 pm

Whenever I blog religion and atheism I brace for a bunch of uninformed comments. Everyone has an opinion, but few seem genuinely interested in digging for data, or reading about the history of religion, and the empirical realities of the phenomenon. If you are an exception to this trend, you’re awesome, and more power to you. Seeing the responses around the blogosphere to some of my posts it is immediately obvious that people don’t make recourse to the GSS, WVS, or The Religious Landscape Survey, let alone read books like In Gods We Trust or The Reformation. I could go on, but there are so many data sources, and proportionally so little interest in relation to the broader enthusiasm for opining on the topic.

As an aside, in my previous post I alluded to the fact that atheism is not a white thing. I didn’t lay it out explicitly, but far too much of commentary on power dynamics and human affairs is locked into the age of white supremacy. There are Chinese mining towns all over Africa, and we’re still fixated on the legacies of the mustachioed men of yore. Some new thought is needful.

In any case, whenever I post on atheism or religion the data comes calling to me, and begs me to revisit it. Questions, questions. I’m always curious if I can find something new, a twist, a novel inference. So I decided to look for patterns in the WVS wave 5 in regards to the well known phenomenon of male excess in the area of atheism. The data are country-by-country. Below are some plots. The asked was if one was a religious person, and I’m looking at those who asserted they were “convinced atheists.”

The first plots aren’t super interesting. What you’re seeing is that absolute differences in percentage of atheists by sex increase as the percentage of atheists increase. The variance of the latter explains 75% of the variance in the former. Rather, it is better to look at the ratio of males to females. That’s in the third plot. Comparing that to the percent of atheists in the fourth plot you see an interesting trend: the maximum ratio seems to be at low, but not trivial, levels of atheism. As atheism becomes more common in society the sex ratio abates, though it does not disappear. The last plot has a log-scale to show the pattern more clearly. Note that I had to remove some nations from the ratio list because there were basically no atheists, period.

Here are the raw data tables:

TotalMaleFemale
CountryAtheistReligiousNot ReligiousAtheistReligiousNot ReligiousAtheistPercent differenceRatio
Romania0.6%90.5%8.4%1.1%95.9%4.0%0.1%1.0%11.00
Guatemala0.8%68.5%30.0%1.5%75.7%24.1%0.2%1.3%7.50
Poland1.4%92.5%4.9%2.6%96.4%3.2%0.4%2.2%6.50
Ethiopia0.4%78.9%20.6%0.6%83.4%16.5%0.1%0.5%6.00
Chile3.2%56.2%38.1%5.6%72.4%26.5%1.1%4.5%5.09
United States3.6%65.1%28.9%6.0%78.6%20.1%1.2%4.8%5.00
Indonesia0.3%82.5%17.1%0.4%86.9%13.0%0.1%0.3%4.00
Trinidad0.5%81.3%18.0%0.7%86.9%12.9%0.2%0.5%3.50
Italy2.7%82.8%13.0%4.1%93.1%5.7%1.2%2.9%3.42
Spain7.4%36.6%51.8%11.6%53.9%42.5%3.6%8.0%3.22
Peru1.4%77.4%20.4%2.2%86.4%12.9%0.7%1.5%3.14
Ukraine3.0%71.5%23.7%4.8%88.0%10.4%1.6%3.2%3.00
Uruguay7.6%45.0%43.2%11.8%65.4%30.3%4.3%7.5%2.74
Turkey0.5%79.6%19.6%0.8%85.5%14.2%0.3%0.5%2.67
Colombia0.5%75.5%23.7%0.8%84.4%15.3%0.3%0.5%2.67
Cyprus2.1%49.7%47.1%3.1%71.7%27.0%1.3%1.8%2.38
Argentina2.3%72.5%24.2%3.2%88.8%9.8%1.4%1.8%2.29
South Africa1.2%73.1%25.2%1.6%89.4%9.9%0.7%0.9%2.29
Bulgaria5.3%57.1%35.5%7.5%69.4%27.3%3.3%4.2%2.27
Finland3.1%51.3%44.4%4.3%68.3%29.8%1.9%2.4%2.26
Japan13.7%21.6%59.2%19.3%26.4%64.6%9.0%10.3%2.14
Malaysia2.3%87.4%9.4%3.2%90.7%7.8%1.5%1.7%2.13
Serbia4.0%83.3%11.4%5.3%87.7%9.8%2.6%2.7%2.04
Russia4.4%61.6%32.3%6.1%83.2%13.8%3.0%3.1%2.03
Iran0.1%80.7%19.1%0.2%86.6%13.3%0.1%0.1%2.00
Norway6.8%30.5%60.5%9.0%52.3%43.1%4.6%4.4%1.96
Netherlands7.5%50.8%39.2%9.9%62.9%32.0%5.1%4.8%1.94
Slovenia9.8%66.2%20.5%13.3%77.8%15.2%7.0%6.3%1.90
Canada6.6%60.8%30.5%8.7%72.1%23.3%4.6%4.1%1.89
Moldova1.0%75.8%23.0%1.3%91.4%7.8%0.7%0.6%1.86
Hong Kong5.4%19.8%73.2%7.0%34.1%62.1%3.8%3.2%1.84
France17.1%42.0%35.6%22.3%51.5%36.3%12.3%10.0%1.81
Andorra14.2%40.1%42.0%18.0%56.9%32.9%10.1%7.9%1.78
Sweden17.2%26.4%52.0%21.6%40.6%46.6%12.8%8.8%1.69
South Korea28.6%23.0%41.4%35.6%37.1%41.3%21.7%13.9%1.64
New Zealand7.0%43.3%48.2%8.5%55.1%39.7%5.2%3.3%1.63
Germany19.2%36.7%39.5%23.7%48.6%36.5%14.9%8.8%1.59
Iraq2.7%54.3%42.5%3.2%55.1%42.8%2.1%1.1%1.52
Burkina Faso1.6%90.8%7.3%1.9%92.2%6.6%1.3%0.6%1.46
Mexico2.9%70.6%26.0%3.4%80.0%17.6%2.4%1.0%1.42
Viet Nam23.6%32.2%40.7%27.1%46.6%33.6%19.8%7.3%1.37
Taiwan16.8%40.1%40.5%19.4%40.4%45.4%14.2%5.2%1.37
China17.9%20.7%58.7%20.7%22.8%61.7%15.6%5.1%1.33
Switzerland7.9%59.8%31.2%9.0%69.0%24.0%7.0%2.0%1.29
Great Britain10.4%42.4%46.0%11.6%54.5%36.3%9.3%2.3%1.25
Australia9.9%46.8%42.8%10.4%56.2%34.4%9.5%0.9%1.09
Mali0.4%97.5%2.1%0.4%97.8%1.8%0.4%0.0%1.00
India2.5%74.4%23.2%2.4%82.7%14.6%2.7%-0.3%0.89
Brazil1.2%84.7%14.2%1.1%91.1%7.6%1.3%-0.2%0.85
Thailand0.2%35.4%64.5%0.1%35.5%64.3%0.3%-0.2%0.33
Rwanda0.1%93.5%6.5%0.0%94.9%5.0%0.1%-0.1%0.00
Egypt0.0%90.1%9.9%0.0%95.1%4.9%0.0%0.0%#DIV/0!
Morocco0.0%91.3%8.7%0.0%92.3%7.7%0.0%0.0%#DIV/0!
Jordan0.1%88.7%11.1%0.2%95.6%4.4%0.0%0.2%#DIV/0!
Georgia0.3%94.3%5.1%0.6%98.6%1.4%0.0%0.6%#DIV/0!
Ghana0.5%91.3%7.7%1.0%91.8%8.2%0.0%1.0%#DIV/0!
Zambia0.5%88.0%11.0%1.0%91.1%8.9%0.0%1.0%#DIV/0!

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