The authors of the present paper compared studies included in a recent meta-analysis on alcohol consumption and the risk of coronary heart disease (CHD) for the number of potential confounding variables included in the analysis for each paper. While they found that most studies included adjustments for smoking, age, BMI, height and weight, physical activity, and education, many studies included adjustments for a multitude of other factors. They reach the conclusion that the large variation between studies in adjusting for confounding makes it impossible to accept the finding of a J-shaped curve between alcohol consumption and CHD (despite the consistency of such results).
Forum members agree that evaluating confounders in epidemiologic studies is extremely important. However, standardizing environmental confounders is not possible as there are so many, and so many yet undefined, and these confounders would be expected to vary in their influence among different populations. The authors did not focus on the key factor: the potential impact of each potential confounder. Limited research suggests that any “unknown confounder” would need to be extremely powerful to negate the reported protective effect of light-to-moderate consumption of alcohol, especially of wine, on the risk of CHD.
In addition, the authors were perturbed that many individual studies did not state specifically in their discussion that “residual confounding may be present in our results” or that “results of individual studies must be interpreted with caution.” Forum members assume that most readers of scientific reports realize that there should always be caution in making conclusions from a single study, especially observational studies, without the authors pointing in out in their paper. It may be analogous to stating that “further research is needed,” which should be assumed for any scientific paper.
Members of the Forum acknowledge that confounding makes it a difficult process to judge causality from observational studies, but point out that potential confounders in one study may be insignificant in another. It is not possible to generate a list of potential confounders that would apply to all epidemiologic studies. However, the consistency of the J-shaped curve between alcohol intake and risk of CHD in almost all epidemiologic studies, with support from a multitude of experimental studies, strongly supports the validity of such a relation.
Reference: Wallach JD, Serghiou S, Chu L, Egilman AC, Vasiliou V, Ross JS, Ioannidis JPA. Evaluation of confounding in epidemiologic studies assessing alcohol consumption on the risk of ischemic heart disease. BMC Medical Research Methodology 2020;20:64