American Journal of Epidemiology Vol. 155, No. 2 : 176-184
Copyright © 2002 by The Johns Hopkins University School of Hygiene and Public Health
PRACTICE OF EPIDEMIOLOGY |
Causal Knowledge as a Prerequisite for Confounding Evaluation: An Application to Birth Defects Epidemiology
1 Department of Epidemiology, Harvard School of Public Health, Boston, MA.
2 Slone Epidemiology Unit, Boston University School of Public Health, Brookline, MA.
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.
abnormalities; causality; confounding factors (epidemiology); inference; selection bias
Abbreviations: CI, confidence interval; DAG, directed acyclic graph; OR, odds ratio; RR, risk ratio
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