Last updated on November 6, 2018
A few months ago, The Lancet Public Health published a much-ballyhooed article by Seidelmann et al. linking dietary carbohydrate consumption that is either too low or too high with an increased risk of mortality.
I first heard about that article when I saw an article about it on CNN.com which, as is often the case with popular-press pieces about splashy public health findings, played fast and loose with the passage from correlation to causation.
When I read the CNN article, I didn’t think much of it, but my Allegheny College colleague Amelia Finaret got in touch with me asking me if I’d be interested in writing a short piece commenting on the Seidelmann et al. study for submission to The Lancet, the gist of which would be about the difficulty posed by making causal inference from observational data.
After a few days of iterating on our manuscript, we submitted it to The Lancet. I was happy to see that it was published yesterday, alongside several other comments on the Seidelmann et al. study. Best of all is the fact that our comment is open-access, meaning anyone with an Internet connection can read it. (Thank goodness for the fact that the publication costs for comments are cross-subsidized by the authors of original research articles!)
Here is a link to the .pdf of our comment; here is a link to the web version. The gist of our argument is that because of the presence of unobserved confounders, one cannot make a causal statement about the relationship between carbohydrate consumption and mortality. In other words, not all that glitters is gold.