Invited commentary: Causation or noitasuaC

Enrique Schisterman, Brian Whitcomb, Katherine Bowers

Research output: Contribution to journalArticlepeer-review

Abstract

Longitudinal studies are often viewed as the "gold standard" of observational epidemiologic research. Establishing a temporal association is a necessary criterion to identify causal relations. However, when covariates in the causal system vary over time, a temporal association is not straightforward. Appropriate analytical methods may be necessary to avoid confounding and reverse causality. These issues come to light in 2 studies of breastfeeding described in the articles by Al-Sahab et al. (Am J Epidemiol. 2011;173(9):971-977) and Kramer et al. (Am J Epidemiol. 2011;173(9):978-983) in this issue of the Journal. Breastfeeding has multiple time points and is a behavior that is affected by multiple factors, many of which themselves vary over time. This creates a complex causal system that requires careful scrutiny. The methods presented here may be applicable to a wide range of studies that involve time-varying exposures and time-varying confounders.

Original languageEnglish (US)
Pages (from-to)984-987
Number of pages4
JournalAmerican Journal of Epidemiology
Volume173
Issue number9
DOIs
StatePublished - May 1 2011
Externally publishedYes

Keywords

  • breast feeding
  • causality
  • confounding

ASJC Scopus subject areas

  • Epidemiology

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