Table 2.

Rationale and measures of effect estimated and reported for Causal Mediation Analysis

References	Reasona	Measures discussed or reported	Motivation for applicationb
Randomized controlled trials
D’Amelio et al. [27]	Mediation	Natural direct and natural indirect effects Emphasized direct effect	Improve understanding to show that above and beyond how the treatment works through the mediator, there is an independent effect
Freeman et al. [28]	Mediation	Direct and indirect effectsc Proportion mediated by various factors	Improve understanding of mechanisms
Cohort studies
Banack et al. [26]	Mediation	Similar to controlled direct effect (with caveat that no manipulation of obesity could actually occur)	Refute/confirm that selection bias drives the obesity paradox in cardiovascular disease
Jackson et al. [29]	Mediation	Natural direct and indirect effects Proportion mediated by each medical event	Improve understanding of mechanisms
Kositsawat et al. [30]	Mediation	Not identified	Not clear
Louwies et al. [31]	Mediation	Direct and indirect effectc	Improve understanding of mechanisms
Lu et al. [32]	Mediation	Natural direct and natural indirect effect Percent excess risk mediated Natural indirect effect emphasized	Improve understanding of mechanisms
Mendola et al. [33]	Mediation	Controlled direct effect	Improve understanding
Messerlian et al. [34]	Mediation	Controlled direct effect	Improve understanding
Raghavan et al. [35]	Mediation	Direct and indirect effects but only indirect effects reportedc Proportion of risk mediated through genetic and metabolic factors	Improve understanding of what mediators might be ripe for intervention
Case control studies
Rao et al. [36]	Mediation	Controlled direct effect	Improve understanding
Song et al. [37]	Mediation	Effect not mediated mediated effectc Proportion mediated through various biomarkers	Improve understanding of mechanisms
Xie et al. [38]	Mediation	Direct and indirect effectc Proportion of effect mediated through testosterone	Improve understanding

^aReason for applying causal mediation analysis: Mediation, Interaction, or Interference

^bMotivation for each application of causal mediation analysis. For mediation (1) improve understanding; (2) confirm/refute theory; (3) intervention refinement. For interaction (1) help allocate resources better; (2) identifying groups in which treatments may be harmful or beneficial (qualitative or cross-over interactions); (3) understand mechanisms; (4) increase statistical power of main effect analysis, and (5) understand which mediator to intervene upon to eliminate most of the effect of primary exposure. For interference (1) quantify spillover effects for cost-effectiveness studies; (2) understand what proportion must be treated to attain population outcomes desired; (3) create knowledge for intervention development and refinement

^c“Natural” was not specifically used in the article but appeared to have counterfactual framework and appropriate references