Control of Confounding and Reporting of Results in Causal Inference Studies. Guidance for Authors from Editors of Respiratory, Sleep, and Critical Care Journals - Lederer, David J.; Bell, Scott C.; Branson, Richard D.; Chalmers, James D.; Marshall, Rachel; Maslove, David M.; Ost, David E.; Punjabi, Naresh M.; Schatz, Michael; Smyth, Alan R.; Stewart, Paul W.; Suissa, Samy; et al. (Annals of the American Thoracic Society, 2019)
[...]we urge authors to consider using causal models when testing causal associations. [...]all other methods of controlling for confounding involve implicit assumptions about causal effects, which are not transparent to the reader. The observed associations between these covariates and the outcome have not been subject to the same approach to control of confounding as the exposure. [...]residual confounding and other biases often heavily influence these associations. [...]we recommend that P values only rarely be presented in isolation (exceptions may include "omics" studies and tests for interaction).