Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology

Am J Epidemiol. 2002 Jan 15;155(2):176-84. doi: 10.1093/aje/155.2.176.


Common strategies to decide whether a variable is a confounder that should be adjusted for in the analysis rely mostly on statistical criteria. The authors present findings from the Slone Epidemiology Unit Birth Defects Study, 1992-1997, a case-control study on folic acid supplementation and risk of neural tube defects. When statistical strategies for confounding evaluation are used, the adjusted odds ratio is 0.80 (95% confidence interval: 0.62, 1.21). However, the consideration of a priori causal knowledge suggests that the crude odds ratio of 0.65 (95% confidence interval: 0.46, 0.94) should be used because the adjusted odds ratio is invalid. Causal diagrams are used to encode qualitative a priori subject matter knowledge.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Bias
  • Causality
  • Confounding Factors, Epidemiologic
  • Epidemiologic Methods*
  • Female
  • Folic Acid / therapeutic use*
  • Humans
  • Infant, Newborn
  • Mental Recall
  • Neural Tube Defects / epidemiology*
  • Neural Tube Defects / prevention & control*
  • Ontario / epidemiology
  • Pregnancy
  • United States / epidemiology


  • Folic Acid