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Causal inference in occupational epidemiology: accounting for the healthy worker effect by using structural nested models.

ABSTRACT: In a recent issue of the Journal, Kirkeleit et al. (Am J Epidemiol. 2013;177(11):1218-1224) provided empirical evidence for the potential of the healthy worker effect in a large cohort of Norwegian workers across a range of occupations. In this commentary, we provide some historical context, define the healthy worker effect by using causal diagrams, and use simulated data to illustrate how structural nested models can be used to estimate exposure effects while accounting for the healthy worker survivor effect in 4 simple steps. We provide technical details and annotated SAS software (SAS Institute, Inc., Cary, North Carolina) code corresponding to the example analysis in the Web Appendices, available at http://aje.oxfordjournals.org/.

SUBMITTER: Naimi AI

PROVIDER: S-EPMC3858107 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Causal inference in occupational epidemiology: accounting for the healthy worker effect by using structural nested models.

Naimi Ashley I AI Richardson David B DB Cole Stephen R SR

American journal of epidemiology 20130927 12

In a recent issue of the Journal, Kirkeleit et al. (Am J Epidemiol. 2013;177(11):1218-1224) provided empirical evidence for the potential of the healthy worker effect in a large cohort of Norwegian workers across a range of occupations. In this commentary, we provide some historical context, define the healthy worker effect by using causal diagrams, and use simulated data to illustrate how structural nested models can be used to estimate exposure effects while accounting for the healthy worker s ...[more]

PMID: 24077092

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