Low-volume alcohol consumption has no impact on longevity

This study does not mean you should chug a bunch of those little airplane travel bottles of your favorite booze.

A study published in JAMA Network Open and conducted by scientists in Canada and the UK shows that people who drink a little are no more or less likely to die than someone who never does. Both are less likely than people who have three or more drinks daily.

So it doesn't necessarily mean you shouldn't chug those airplane bottles, either. As in all things, act responsibly.


Overall, they reviewed over 100 studies that analyzed mortality risk and alcohol, which collectively involved nearly 5 million people. Notably, they also tried to adjust for factors that could have affected the results of previous studies. It's known that many people who currently abstain from alcohol, for instance, have stopped drinking because they're in poorer health or perhaps even because of their earlier drinking—a phenomenon called the "sick quitter effect." Including these sick quitters in the same group as lifetime abstainers and then comparing them to light and moderate drinkers can bias the analysis in a way that makes alcohol seem healthier than it truly is.

As expected, heavier drinking (more than three drinks a day on average) was linked to a noticeably higher risk of dying earlier. But in the team's adjusted model, there was no statistically significant effect on mortality—either good or bad—linked to light or moderate drinking. Women also appeared to generally be worse off, since their higher risk of dying began at lower levels of alcohol consumption than it did for men.

"This updated meta-analysis did not find significantly reduced risk of all-cause mortality associated with low-volume alcohol consumption after adjusting for potential confounding effects of influential study characteristics," the review authors wrote. They also argue that occasional drinkers should be used as the baseline comparison group for future alcohol-related studies from now on, given how hard it can be to account for the sick quitter effect and other biases.