title: Invited commentary: causation or "noitasuac"?
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.
authors: Epidemiology Branch, Division of Epidemiology, Statistics, and Prevention Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland 20854, USA. schistee@mail.nih.gov
authors: Enrique
authors: E
authors: Schisterman
authors: Brian
authors: B
authors: Whitcomb
authors: Katherine
authors: K
authors: Bowers
mesh_terms: D015982:Bias; D001942:Breast Feeding / Q000453:epidemiology*; D003627:Data Interpretation, Statistical; D006801:Humans; D007223:Infant; D008572:Menarche / Q000502:physiology; D015233:Models, Statistical; D012107:Research Design; D013997:Time Factors