Interesting, but take with a grain of salt:
Another caveat is the composition of the sample. The Nurses' Health Study that the sample was drawn from is made up of overwhelmingly white women residing in the United States. "Since sex preferences and reproductive behaviors vary across cultures, religions, or countries … the sex ratio distribution pattern observed in our study may not apply to other societies," the researchers acknowledge.
That's true...
But applicable to almost all our medical information.
Like, the BMI scale was developed in the 1800s by a Belgian astronomer, based solely on European men of that time period.
But people are really fucking insistent we keep it, because in 6th grade a gym teacher said it was important.
Body types vary a lot, any simplified measurement can't account for much and shouldn't be used on its own. However, it is fast, easy, and gives a decent ballpark of weight related health for most people. That makes it useful. More accurate things like impedance or displacement or pinch tests require equipment, a mess and/or patient discomfort.
Yeah. But there's also the ponderial index, which still just uses height/weight and provides a much better result than BMI. Because when BMI was invented, a guy that was 5'8 was so tall they were statistically insignificant.
Like, there is a benefit from using a simple formula, but there's no reason to keep using an outdated one that we know has serious problems, when the medical community already made a better one...
https://en.m.wikipedia.org/wiki/Corpulence_index
Like, it's not perfect. Still has flaws...
But it's only 100 years old, compared to BMI at 200 years old.
And was invented by an actual medical.professional and not an astronomer.
So while you do have some good points, none of that is a reason to keep using BMI. Hell, pretty sure we can make an even better formula than Ponderal Index by now. And there's no reason not to.
Like math is a little harder, but why does that matter? Who's doing bmi by hand intead of plugging into a calculator on a webpage? Or just looking at a chart?
How hard the math is doesn't really matter.
To avoid bias from parents who stopped having children after reaching a preferred sex ratio, the researchers did not count each woman's final birth in the analysis.
Uhhhh, I'm no statistician, but doesn't that introduce a bias into the statistics? It means that you (potentially, depending on behaviour) have fewer examples of balanced-sex families.
Yeah, I can see the bias they are trying to account for, but fail to see how excluding a birth from the statistics helps combat this in any way. Just because you stopped having kids doesn't have any effect on the gender of your last kid.
It does, but that may not necessarily be a bad thing. It largely depends on what the overall dataset looks like.
It's not unusual to tweak your dataset in response to certain biases, especially if there is a known bias at play (for example, I've actually met plenty of parents who keep having kids hoping for a boy/girl, and then stop once they get what they initially wanted. As creepy and weird as that is to me, it's definitely a thing).
This does seem a bit blunt of an approach, however. I would've preferred a survey question as part of data collection where parents are asked if they were "trying" for one sex over another, if they wanted "one of each", etc etc., and then using that info to weight the data.
But without reading the article myself, my assumption is they just used a readily available dataset (such as medical records) rather than recruit participants directly. But I could be wrong, didn't read it after all.
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