Researchers have debated the causes of earlier menarche among Western adolescents for decades. Fatness (as distinct from BMI, it should be noted), environmental factors, and stress have all been implicated in the shift, but the evidence for each remains relatively weak and the interplay between them difficult to sort out.

A new study in the Journal of Adolescent Health seeks to quantify the impact of an absent biological father on thelarche (breast development) and pubarche (pubic hair development). These were taken to be more sensitive and earlier markers of pubertal maturation than menarche. The researchers found that earlier pubertal development was only correlated with father absence in higher-income families and was not related to BMI: “Findings indicated that father absence in higher-income, but not lower-income families resulted in girls exhibiting earlier pubertal onset than those from father-present homes. Despite the evidence that the secular trend in pubertal timing among girls in United States is largely influenced by body weight, our results show that BMI neither accounted for all the variance in pubertal onset nor operated as a mechanism in the causal path between father absence and puberty.”

The study, while an interesting and important document, highlights the deficits in our present understanding of reproductive physiology. Online reports and their argument-rich comment sections prove this point. As the paper itself states, “Our research fell short of identifying a potentially modifiable mechanism that might explain the relationship between father absence and puberty.” But, of course, when the findings — however iffy — are taken out of context, they prompt commentators, even informed reporters, to run amok drawing conclusions and spewing analyses.

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While this study may be the “state of the science,” what it reveals is that the state of the science is, truth be told, not all that advanced. The researchers, with the best of intentions, strove to find readily interpretable, measurable data. These types of data, of course, are the easiest to parse. So, BMI in this analysis stands in for fatness, physical activity, and types of foods consumed. Income stands in for economic stress, type of school attended, and amount of supervised leisure time. Any of these may be more useful parameters and, in all likelihood, the combination of them would be most telling. But hindered as we are by present research tactics, we don’t really know.

This isn’t a call for scrapping the great work done by Deardorff’s group and others like them. It’s just a reminder that the conclusions we can draw from studies like these are decidedly limited. As the researchers themselves note, many intriguing paths for future research are still open. 

Tempting as it may be to sensationalize these findings, it’s important to remember that research can only answer the questions we ask it to. And sometimes, not even those.