Invited Commentary Invited Commentary: Pushing the Mediation Envelope

The very insightful and clear paper by VanderWeele and Vansteelandt in this issue of the Journal (Am J Epidemiol. 2010;172(12):1339–1348) bridges the gap between biostatistics methodologists focusing on causal methods for mediation analyses and the practitioners of mediational analyses to the benefit of both groups. In an effort to continue the bridging of this gap, this invited commentary relates the important issue of ‘‘natural direct effects’ ’ to the well-known epidemiologic method of direct standardization. Additionally, attention is paid to the importance of temporal sequencing to help substantiate the mediation relations among the exposure, mediation, and outcome. A crucial mathematical distortion under the logistics model, called ‘‘absence of collapsibility,’ ’ is noted in motivating VanderWeele and Vansteelandt’s use of the log-linear model for comparing the effect of exposure adjusted for the mediator with the effect of exposure unadjusted for the mediator. It is also noted that this issue applies to one approach to assessing confounding. Finally, some issues are raised for consideration when testing the interaction between the exposure and mediator before assessing mediation. collapsibility; confounding; epidemiologic methods; logistic regression; log-linear models; standardization Drs. VanderWeele and Vansteelandt (1) have covered much ground in presenting mediation analyses for binary outcomes in the context of case-control and cohort studies