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From causal diagrams to birth weight-specific curves of infant mortality

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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.

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References

  1. Wilcox A. On the importance—and the unimportance—of birthweight. Int J Epidemiol 2001;30:1233–41.

    Article  PubMed  CAS  Google Scholar 

  2. Wilcox A. Birth weight and perinatal mortality: the effect of maternal smoking. Am J Epidemiol 1993;137:1098–104.

    PubMed  CAS  Google Scholar 

  3. Basso O, Wilcox A, Weinberg CR. Birth weight and mortality: causality or confounding? Am J Epidemiol 2006;164:303–11.

    Article  PubMed  Google Scholar 

  4. Hernández-Díaz S, Schisterman EF, Hernán MA. The birth weight “paradox” uncovered? Am J Epidemiol 2006.doi 10.1093/aje/kwj275

  5. Pearl J. Causal diagrams for empirical research. Biometrika 1995;82:669–710.

    Article  Google Scholar 

  6. Spirtes P, Glymour C, Scheines R. Causation, prediction, and search. Lecture notes in statistics 81. New York: Springer-Verlag; 1993.

    Google Scholar 

  7. Cole SR, Hernán MA. Fallibility in estimating direct effects. Int J Epidemiol 2002;31(1):163–5.

    Article  PubMed  Google Scholar 

  8. Hernán MA, Hernández-Díaz S, Robins JM. A structural approach to selection bias. Epidemiology 2004;15(5):615–25.

    Article  PubMed  Google Scholar 

  9. Hernán MA, Hernández-Díaz S, Werler MM, Mitchell AA. Causal knowledge as a prerequisite for confounding evaluation. An application to birth defects epidemiology. Am J Epidemiol 2002;155:176–84.

    Article  PubMed  Google Scholar 

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Acknowledgments

This work was supported in part by NIH grant R01-HL080644, and by the Intramural Research Program of the National Institute of Environmental Health Sciences, NIH.

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Authors and Affiliations

  1. Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA

    Sonia Hernández-Díaz & Miguel A. Hernán

  2. Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA

    Allen J. Wilcox

  3. Epidemiology Branch, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA

    Enrique F. Schisterman

Authors
  1. Sonia Hernández-Díaz
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  2. Allen J. Wilcox
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  3. Enrique F. Schisterman
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  4. Miguel A. Hernán
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Correspondence to Sonia Hernández-Díaz.

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Hernández-Díaz, S., Wilcox, A.J., Schisterman, E.F. et al. From causal diagrams to birth weight-specific curves of infant mortality. Eur J Epidemiol 23, 163–166 (2008). https://doi.org/10.1007/s10654-007-9220-4

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  • DOI: https://doi.org/10.1007/s10654-007-9220-4

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