Six-way decomposition of causal effects: Unifying mediation and mechanistic interaction.

The sufficient component cause (SCC) model and counterfactual model are two common methods for causal inference, each with their own advantages: the SCC model allows the mechanistic interaction to be detailed, whereas the counterfactual model features a systemic framework for quantifying causal effects. Hence, integrating the SCC and counterfactual models may facilitate the conceptualization of causation. Based on the marginal SCC (mSCC) model, we propose a novel counterfactual mSCC framework that includes the steps of definition, identification, and estimation. We further propose a six-way effect decomposition for assessing mediation and the mechanistic interaction. The results demonstrate that when all variables are binary, the six-way decomposition is an extension of four-way decomposition and that without agonism, the six-way decomposition is reduced to four-way decomposition. To illustrate the utility of the proposed decomposition, we apply it to a Taiwanese cohort to examine the mechanism of hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC) with liver inflammation measured by alanine aminotransferase (ALT) as a mediator. Among the HCV-induced HCC cases, 62.27% are not explained by either mediation or interaction in relation to ALT; 9.32% are purely mediated by ALT; 16.53% are caused by the synergistic effect of HCV and ALT; and 9.31% are due to the mediated synergistic effect of HCV and ALT. In summary, we introduce an SCC model framework based on counterfactual theory and detail the required identification assumptions and estimation procedures; we also propose a six-way effect decomposition to unify mediation and mechanistic interaction analyses.

Mediation analysis for new recognition criteria, working hours and overwork-related disease: a nationwide ecological study using 11-year follow-up data in Taiwan.

OBJECTIVES: Taiwan revised its criteria for overwork-related cerebrovascular and cardiovascular disease (CCVD) in 2010. A new definition of overwork increased the number of recognised cases. Meanwhile, actual average working hours decreased. We estimated the effects of the revised criteria on the number of overwork-related CCVD cases and the mediation effect through reduced working hours. METHODS: From the Labor Insurance of Taiwan, we collected data on the total number of overwork-related CCVD cases from 2006 to 2016 and average monthly working hours for 13 industry groups. We conducted causal mediation analysis to investigate the mechanism of the effect of new criteria on CCVD mediated by working hours. RESULTS: From 2006 to 2016, 594 overwork-related cases of CCVD were recognised across 13 industry groups. After introducing the new criteria, overwork-related CCVD increased by 8.40 cases (per one million person-years) (95% CI 4.53 to 15.05), which resulted from a decrease of 1.54 (95% CI 0.22 to 3.82) cases due to reduced working hours (mediation effect) and an increase of 9.93 (95% CI 5.24 to 18.17) cases related to the effect of the criteria change and other covariates excluding working hours (alternative effect). CONCLUSIONS: Working hours are an important mediator of the effect of policy on the rate of overwork-related CCVD. Introducing new criteria for recognising overwork-related disease might raise awareness and prompt reductions in working hours, which also help to reduce CCVD. Our findings suggest that understanding mediation effects is important to evaluating national health policies.