Invited commentary: causation or "noitasuac"?

Am J Epidemiol. 2011 May 1;173(9):984-7; reply 988-9. doi: 10.1093/aje/kwq499. Epub 2011 Mar 23.

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.

Publication types

  • Comment

MeSH terms

  • Bias
  • Breast Feeding / epidemiology*
  • Data Interpretation, Statistical
  • Humans
  • Infant
  • Menarche / physiology
  • Models, Statistical
  • Research Design*
  • Time Factors