Literature DB >> 21430191

Invited commentary: causation or "noitasuac"?

Enrique Schisterman1, Brian Whitcomb, Katherine Bowers.   

Abstract

Longitudinal studies are often viewed as the "gold standard" of observational epidemiologic research. Establishing a temporal association is a necessary criterion to identify causal relations. However, when covariates in the causal system vary over time, a temporal association is not straightforward. Appropriate analytical methods may be necessary to avoid confounding and reverse causality. These issues come to light in 2 studies of breastfeeding described in the articles by Al-Sahab et al. (Am J Epidemiol. 2011;173(9):971-977) and Kramer et al. (Am J Epidemiol. 2011;173(9):978-983) in this issue of the Journal. Breastfeeding has multiple time points and is a behavior that is affected by multiple factors, many of which themselves vary over time. This creates a complex causal system that requires careful scrutiny. The methods presented here may be applicable to a wide range of studies that involve time-varying exposures and time-varying confounders.

Mesh:

Year:  2011        PMID: 21430191      PMCID: PMC3121226          DOI: 10.1093/aje/kwq499

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  11 in total

1.  Marginal structural models and causal inference in epidemiology.

Authors:  J M Robins; M A Hernán; B Brumback
Journal:  Epidemiology       Date:  2000-09       Impact factor: 4.822

2.  THE ENVIRONMENT AND DISEASE: ASSOCIATION OR CAUSATION?

Authors:  A B HILL
Journal:  Proc R Soc Med       Date:  1965-05

3.  Toward optimal health: the maternal benefits of breastfeeding.

Authors:  Jodi R Godfrey; Ruth A Lawrence
Journal:  J Womens Health (Larchmt)       Date:  2010-09       Impact factor: 2.681

4.  Illustrating bias due to conditioning on a collider.

Authors:  Stephen R Cole; Robert W Platt; Enrique F Schisterman; Haitao Chu; Daniel Westreich; David Richardson; Charles Poole
Journal:  Int J Epidemiol       Date:  2009-11-19       Impact factor: 7.196

5.  Impact of breastfeeding duration on age at menarche.

Authors:  Ban Al-Sahab; Linda Adair; Mazen J Hamadeh; Chris I Ardern; Hala Tamim
Journal:  Am J Epidemiol       Date:  2011-03-23       Impact factor: 4.897

6.  Association between infant breastfeeding and overweight in young children.

Authors:  M L Hediger; M D Overpeck; R J Kuczmarski; W J Ruan
Journal:  JAMA       Date:  2001-05-16       Impact factor: 56.272

7.  Breastfeeding and infant size: evidence of reverse causality.

Authors:  Michael S Kramer; Erica E M Moodie; Mourad Dahhou; Robert W Platt
Journal:  Am J Epidemiol       Date:  2011-03-23       Impact factor: 4.897

8.  Adjusting for reverse causality in the relationship between obesity and mortality.

Authors:  W D Flanders; L B Augestad
Journal:  Int J Obes (Lond)       Date:  2008-08       Impact factor: 5.095

9.  Causal models for estimating the effects of weight gain on mortality.

Authors:  J M Robins
Journal:  Int J Obes (Lond)       Date:  2008-08       Impact factor: 5.095

10.  Overadjustment bias and unnecessary adjustment in epidemiologic studies.

Authors:  Enrique F Schisterman; Stephen R Cole; Robert W Platt
Journal:  Epidemiology       Date:  2009-07       Impact factor: 4.822

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  1 in total

Review 1.  Life-course origins of the ages at menarche and menopause.

Authors:  Michele R Forman; Lauren D Mangini; Rosenie Thelus-Jean; Mark D Hayward
Journal:  Adolesc Health Med Ther       Date:  2013-01-18
  1 in total

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