articleAmerican Journal of EpidemiologyJan 15, 2002BRONZE OA

Causal Knowledge as a Prerequisite for Confounding Evaluation: An Application to Birth Defects Epidemiology

Harvard University

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Abstract

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…

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Topics & keywords

Keywords
  • Confounding
  • Odds ratio
  • Confidence interval
  • Epidemiology
  • Medicine
  • Odds
  • Causality (physics)
  • Statistics
UN Sustainable Development Goals
  • Good health and well-being
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