Bhash Mazumder sends along a paper (coauthored with Zachary Seeskin) which begins:
A growing body of literature has shown that environmental exposures in the period around conception can affect the sex ratio at birth through selective attrition that favors the survival of female conceptuses. Glucose availability is considered a key indicator of the fetal environment, and its absence as a result of meal skipping may inhibit male survival. We hypothesize that breakfast skipping during pregnancy may lead to a reduction in the fraction of male births. Using time use data from the United States we show that women with commute times of 90 minutes or longer are 20 percentage points more likely to skip breakfast. Using U.S. census data we show that women with commute times of 90 minutes or longer are 1.2 percentage points less likely to have a male child under the age of 2. Under some assumptions, this implies that routinely skipping breakfast around the time of conception leads to a 6 percentage point reduction in the probability of a male child.
Here are the key graphs. First, showing that people with long commute times are more likely to be skipping breakfast:
I have no idea how 110% of people are supposed to be skipping breakfast, but whatever.
And, second, showing that people with long commute times are less likely to have boy babies:
I have no idea what’s going on with these bars that start at 49.8%, but whatever. Maybe someone can tell these people that it’s ok to plot points, you don’t need big gray bars attached?
Anyway, what can I say . . . I don’t buy it. This second graph, in particular: everything looks too noisy to be useful.
Or, to put it another way: The general hypothesis seems reasonable, when the fetus gets less nourishment, it’s more likely the boy fetus doesn’t survive. But this all looks really really noisy. Also, the statistical significance filter. So the estimates they report, are overestimates.
To put it another way: Get a new data set, and I don’t expect to see the pattern repeat.
That said, there are papers in this literature that are a lot worse. For example, Mazumder and Seeskin cite a Mathews, Johnson, and Neil paper on correlation between maternal diet and sex ratio that had a sample size of only 740, which makes it absolutely useless for learning anything at all, given actual effect sizes on sex ratios. They could’ve just as well been publishing random numbers. But that was 2008, back before people know about these problems. We can only hope that the editors of “Proceedings of the Royal Society B: Biological Sciences” know better today.