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Sources of confounding in life course epidemiology

Published online by Cambridge University Press:  16 August 2018

S. Santos*
The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
D. Zugna
Department of Medical Sciences, Cancer Epidemiology Unit, University of Turin and CPO-Piemonte, Turin, Italy
C. Pizzi
Department of Medical Sciences, Cancer Epidemiology Unit, University of Turin and CPO-Piemonte, Turin, Italy
L. Richiardi
Department of Medical Sciences, Cancer Epidemiology Unit, University of Turin and CPO-Piemonte, Turin, Italy
*Address for correspondence: S. Santos, The Generation R Study Group, Room Na-2908, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands E-mail:


In epidemiologic analytical studies, the primary goal is to obtain a valid and precise estimate of the effect of the exposure of interest on a given outcome in the population under study. A crucial source of violation of the internal validity of a study involves bias arising from confounding, which is always a challenge in observational research, including life course epidemiology. The increasingly popular approach of meta-analyzing individual participant data from several observational studies also brings up to discussion the problem of confounding when combining data from different populations. In this study, we review and discuss the most common sources of confounding in life course epidemiology: (i) confounding by indication, (ii) impact of baseline selection on confounding, (iii) time-varying confounding and (iv) mediator–outcome confounding. We also discuss the issue of addressing confounding in the context of an individual participant data meta-analysis.

© Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2018 

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