Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology.
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.
Hernán
Miguel A
MA
Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA. miguel_hernan@post.harvard.edu
Hernández-Díaz
Sonia
S
Werler
Martha M
MM
Mitchell
Allen A
AA
D015982:Bias; D015984:Causality; D015986:Confounding Factors, Epidemiologic; D004812:Epidemiologic Methods; D005260:Female; D005492:Folic Acid / Q000627:therapeutic use*; D006801:Humans; D007231:Infant, Newborn; D011939:Mental Recall; D009436:Neural Tube Defects / Q000453:epidemiology* / Q000517:prevention & control*; D009864:Ontario / Q000453:epidemiology; D011247:Pregnancy; D014481:United States / Q000453:epidemiology
D005492:Folic Acid