Question Did preterm births increase among Latina women who were pregnant during the 2016 US presidential election?
Findings This population-based study used an interrupted time series design to assess 32.9 million live births and found that the number of preterm births among Latina women increased above expected levels after the election.
Meaning The 2016 presidential election may have been associated with adverse health outcomes of Latina women and their newborns.
Hmmm, the research article says “may have been associated” but then ups that to “appears to have been associated.”
On one hand, I find it admirable that JAMA will publish a paper with such an uncertain conclusion. On the other hand, the conclusions got stronger once they made their way into news reports. In the above-linked article, “may have been associated” becomes “an association was found” and then “We think there are very few alternative explanations for these results.”
There’s also a selection issue. It’s fine to report maybes, but then why this particular maybe? There are lots and lots of associations that may be happening, right?
Let’s look at the data
In any case, they did an interrupted time series analysis, so let’s see the time series:
I don’t think the paper’s claim, “In the 9-month period beginning with November 2016, an additional 1342 male (95% CI, 795-1889) and 995 female (95% CI, 554-1436) preterm births to Latina women were found above the expected number of preterm births had the election not occurred,” is at all well supported by these data. But you can make your own judgement here.
Also, I’m surprised they are analyzing raw numbers of pre-term births rather than rates.
Look. Don’t get me wrong. This topic is important. We’d like to minimize preterm births, and graphs such as shown above (ideally using rates, not counts, I think) should be a key part of a monitoring system that will allow us to notice problems. It should be possible to look at such time series without pulling out one factor and wrapping this sort of story around it. I think this is a problem with scientific publication, that journals and the news media want to publish big splashy claims.