From causal diagrams to birth weight-specific curves of infant mortality
- 26 January 2008
- journal article
- research article
- Published by Springer Nature in European Journal of Epidemiology
- Vol. 23 (3) , 163-166
- https://doi.org/10.1007/s10654-007-9220-4
Abstract
This report explores the low birth weight paradox using two graphical approaches: causal directed acyclic graphs (DAGs), and the empirical curves of the birth weight distribution and birth weight-specific mortality. The birth weight curves are able to represent the associations quantitatively, while the corresponding causal DAGs provide a set of plausible explanations for the findings. Taken together, these two approaches can facilitate discussion of underlying biological mechanisms.Keywords
This publication has 9 references indexed in Scilit:
- The Birth Weight "Paradox" Uncovered?American Journal of Epidemiology, 2006
- Birth Weight and Mortality: Causality or Confounding?American Journal of Epidemiology, 2006
- A Structural Approach to Selection BiasEpidemiology, 2004
- Fallibility in estimating direct effectsInternational Journal of Epidemiology, 2002
- Causal Knowledge as a Prerequisite for Confounding Evaluation: An Application to Birth Defects EpidemiologyAmerican Journal of Epidemiology, 2002
- On the importance—and the unimportance— of birthweightInternational Journal of Epidemiology, 2001
- Causal diagrams for empirical researchBiometrika, 1995
- Birth Weight and Perinatal Mortality: The Effect of Maternal SmokingAmerican Journal of Epidemiology, 1993
- Causation, Prediction, and SearchPublished by Springer Nature ,1993