Partitioning the population attributable fraction for a sequential chain of effects.

ABSTRACT:

Background

While the population attributable fraction (PAF) provides potentially valuable information regarding the community-level effect of risk factors, significant limitations exist with current strategies for estimating a PAF in multiple risk factor models. These strategies can result in paradoxical or ambiguous measures of effect, or require unrealistic assumptions regarding variables in the model. A method is proposed in which an overall or total PAF across multiple risk factors is partitioned into components based upon a sequential ordering of effects. This method is applied to several hypothetical data sets in order to demonstrate its application and interpretation in diverse analytic situations.

Results

The proposed method is demonstrated to provide clear and inter

SUBMITTER: Mason CA 

PROVIDER: S-EPMC2572052 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature