Causal Inference in Occupational Epidemiology: Accounting for the Healthy Worker Effect by Using Structural Nested Models
Author(s) -
Ashley I. Naimi,
David B. Richardson,
Stephen R. Cole
Publication year - 2013
Publication title -
american journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.33
H-Index - 256
eISSN - 1476-6256
pISSN - 0002-9262
DOI - 10.1093/aje/kwt215
Subject(s) - causal inference , inference , occupational exposure , epidemiology , medicine , occupational medicine , econometrics , environmental health , computer science , mathematics , artificial intelligence
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/.
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