[Use of causal diagrams in Epidemiology: application to a situation with confounding].

Abstract:

:Epidemiological research still rarely uses causal diagrams, despite growing recognition of their explanatory potential. One possible reason is that many research programs involve themes in which there is a certain degree of uncertainty as to mechanisms in the processes that generate the data. In this study, the relationship between occupational stress and obesity is used as an example of the application of causal diagrams to questions related to confounding. The article presents the selection stages for variables in statistical adjustment and the derivation of a causal diagram's statistical implications. The main advantage of causal diagrams is that they explicitly reveal the respective model's underlying hypotheses, allowing critical analysis of the implications and thereby facilitating identification of sources of bias and uncertainty in the epidemiological study's results.

journal_name

Cad Saude Publica

authors

Cortes TR,Faerstein E,Struchiner CJ

doi

10.1590/0102-311X00103115

subject

Has Abstract

pub_date

2016-08-08 00:00:00

pages

e00103115

issue

8

eissn

0102-311X

issn

1678-4464

pii

S0102-311X2016000804001

journal_volume

32

pub_type

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