Educational note: causal decomposition of population health differences using Monte Carlo integration and the g-formula.

ABSTRACT: One key objective of the population health sciences is to understand why one social group has different levels of health and well-being compared with another. Whereas several methods have been developed in economics, sociology, demography, and epidemiology to answer these types of questions, a recent method introduced by Jackson and VanderWeele (2018) provided an update to decompositions by anchoring them within causal inference theory. In this paper, we demonstrate how to implement the causal decomposition using Monte Carlo integration and the parametric g-formula. Causal decomposition can help to identify the sources of differences across populations and provide researchers with a way to move beyond estimating inequalities to explaining them and determining what can be done to reduce hea

SUBMITTER: Sudharsanan N 

PROVIDER: S-EPMC8743135 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature