Comparar métodos

	Chains-of-Risk Model	Four-Way Decomposition
Campo	Social Epidemiology	Social Epidemiology
Familia	Process / pipeline	Process / pipeline
Año de origen	2003	2014
Autor original	Diana Kuh & Yoav Ben-Shlomo (life-course glossary and conceptual models)	Tyler J. VanderWeele
Tipo	Sequential-mediation model of linked life-course exposures	Counterfactual decomposition pipeline for total effects
Fuente seminal	Kuh, D., Ben-Shlomo, Y., Lynch, J., Hallqvist, J., & Power, C. (2003). Life course epidemiology. Journal of Epidemiology & Community Health, 57(10), 778-783.	VanderWeele, T. J. (2014). A unification of mediation and interaction: a four-way decomposition. Epidemiology, 25(5), 749-761.
Alias	Chain of Risk Model, Accumulation of Risk Model, Risk Chains, Additive vs Trigger Chains	4-Way Decomposition, VanderWeele Four-Way Decomposition, Mediation-Interaction Decomposition, Unification of Mediation and Interaction
Relacionados	3	3
Resumen	The chains-of-risk model is the specific life-course mechanism in which adverse exposures are linked in a sequence over time, so that one exposure raises the probability of the next, and the cumulative or final link bears on disease. Set out in Ben-Shlomo and Kuh's 2002 conceptual paper and defined in the Kuh, Ben-Shlomo, Lynch, Hallqvist, and Power 2003 life-course glossary, it models how early disadvantage can cascade — poor early circumstances leading to limited education, then to hazardous work or health behaviors, and finally to disease. Its signature analytic distinction is between an additive chain, in which each link independently adds to risk, and a trigger chain, in which the early links matter only because they lead to a final exposure that is the true cause. Chains-of-risk modeling thus treats the life course as a causal pathway to be decomposed, not a list of independent risk factors.	The four-way decomposition, introduced by Tyler VanderWeele in 2014, unifies the two great themes of effect analysis — mediation and interaction — into a single, exhaustive partition of a total causal effect. Any total effect of an exposure on an outcome can be split into exactly four pieces: a controlled direct effect (neither mediation nor interaction), a reference interaction (interaction but no mediation), a mediated interaction (both mediation and interaction at once), and a pure indirect effect (mediation but no interaction). These four components are mutually exclusive and add up to the total effect, and they nest the familiar two-way and three-way decompositions as special cases. Formalized in counterfactual notation and developed at book length in VanderWeele's 2015 Explanation in Causal Inference, the method gives social epidemiologists a precise vocabulary for asking how much of an exposure's effect runs through a mediator, how much depends on the exposure and mediator acting together, and how much is direct.