Stay calm: There’s more to know about latest alcohol study
The New York Times
Last week a paper was published in The Lancet that claimed to be the definitive study on the benefits and dangers of drinking. The news was not good for those who enjoy alcoholic beverages. It was covered in the news media with headlines like: “There’s No Safe Amount of Alcohol.”
The truth is much less newsy and much more measured.
Limitations of the study
It’s important to note that this study, like most major studies of alcohol, wasn’t a new trial. It was a meta-analysis, or a merging of data, from many observational studies. It was probably the largest meta-analysis ever done to estimate the risks from drinking for 23 different alcohol-related health problems.
The researchers also combined almost 700 sources to estimate the most accurate levels of alcohol consumption worldwide, even trying to find drinking that might otherwise be missed (from tourism, for instance). They then combined all this data into mathematical models to predict the harm from alcohol worldwide.
They found that, overall, harms increased with each additional drink per day, and that the overall harms were lowest at zero. That’s how you get the headlines.
But, and this is a big but, there are limitations here that warrant consideration. Observational data can be very confounded, meaning that unmeasured factors might be the actual cause of the harm. Perhaps people who drink also smoke tobacco. Perhaps people who drink are also poorer. Perhaps there are genetic differences, health differences or other factors that might be the real cause.
There are techniques to analyze observational data in a more causal fashion, but none of them could be used here, because this analysis aggregated past studies — and those studies didn’t use them.
We don’t know if confounders are coming into play because this meta-analysis could only really control, overall, for age, sex and location. That’s not the researchers’ fault. That’s probably all they could do with the data they had, and they could still model population-level effects without them.