Revisiting sequential attributable fractions.

ABSTRACT:

Background

In 1995, Eide and Gefeller introduced the concepts of sequential and average attributable fractions as methods to partition the risk of disease among differing exposures. In particular, sequential attributable fractions are interpreted in terms of an incremental reduction in disease prevalence associated with removing a particular risk factor from the population, having removed other risk factors. Clearly, both concepts are causal entities, but are not usually estimated within a causal inference framework.

Methods

We propose causal definitions of sequential and average attributable fractions using the potential outcomes framework. To estimate these quantities in practice, we model exposure-exposure and exposure-disease interrelationships using a causal Bayesian ne

SUBMITTER: Ferguson J 

PROVIDER: S-EPMC7374857 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature