Skip to main content
Erschienen in: European Journal of Epidemiology 10/2015

01.10.2015 | METHODS

From bad to worse: collider stratification amplifies confounding bias in the “obesity paradox”

verfasst von: Hailey R. Banack, Jay S. Kaufman

Erschienen in: European Journal of Epidemiology | Ausgabe 10/2015

Einloggen, um Zugang zu erhalten

Abstract

Smoking is often identified as a confounder of the obesity–mortality relationship. Selection bias can amplify the magnitude of an existing confounding bias. The objective of the present report is to demonstrate how confounding bias due to cigarette smoking is increased in the presence of collider stratification bias using an empirical example and directed acyclic graphs. The empirical example uses data from the Atherosclerosis Risk in Communities (ARIC) study, a prospective cohort study of 15,792 men and women in the United States. Poisson regression models were used to examine the confounding effect of smoking. In the total ARIC study population, smoking produced a confounding bias of <3 percentage points. This result was obtained by comparing the incidence rate ratio (IRR) for obesity from a model adjusted for smoking was 1.07 (95 % CI 1.00, 1.15) with one that did not adjust for smoking was 1.10 (95 % CI 1.03, 1.18). However, among smokers with CVD, the obesity IRR was 0.89 (95 % CI 0.81, 0.99), while among non-smokers with CVD the obesity IRR was 1.20 (95 % CI 1.03, 1.41). The empirical and graphical explanations presented suggest that the magnitude of the confounding bias induced by smoking is greater in the presence of collider stratification bias.
Literatur
1.
Zurück zum Zitat Glymour MM, Greenland S. Causal Diagrams. In: Rothman KJ, Greenland S, Lash T, editors. Modern epidemiology. 3rd ed. Philadelphia: Lippincott Williams Wilkins; 2008. p. 183–212. Glymour MM, Greenland S. Causal Diagrams. In: Rothman KJ, Greenland S, Lash T, editors. Modern epidemiology. 3rd ed. Philadelphia: Lippincott Williams Wilkins; 2008. p. 183–212.
2.
Zurück zum Zitat Hernán MA, Hernández-Díaz S, Robins JM. A structural approach to selection bias. Epidemiology. 2004;15(5):615–25.CrossRefPubMed Hernán MA, Hernández-Díaz S, Robins JM. A structural approach to selection bias. Epidemiology. 2004;15(5):615–25.CrossRefPubMed
3.
Zurück zum Zitat Banack HR, Kaufman JS. The obesity paradox: understanding the effect of obesity on mortality among individuals with cardiovascular disease. Prev Med. 2014;62:96–102.CrossRefPubMed Banack HR, Kaufman JS. The obesity paradox: understanding the effect of obesity on mortality among individuals with cardiovascular disease. Prev Med. 2014;62:96–102.CrossRefPubMed
4.
Zurück zum Zitat Preston SH, Stokes A. Obesity paradox: conditioning on disease enhances biases in estimating the mortality risks of obesity. Epidemiology. 2014;25(3):454–61.PubMedCentralCrossRefPubMed Preston SH, Stokes A. Obesity paradox: conditioning on disease enhances biases in estimating the mortality risks of obesity. Epidemiology. 2014;25(3):454–61.PubMedCentralCrossRefPubMed
5.
Zurück zum Zitat Flanders DW, Eldridge RC, McClellan W. A nearly unavoidable mechanism for collider bias in the obesity-end-stage-renal-disease-mortality and similar studies. Epidemiology. 2014;25(5):762–4.CrossRefPubMed Flanders DW, Eldridge RC, McClellan W. A nearly unavoidable mechanism for collider bias in the obesity-end-stage-renal-disease-mortality and similar studies. Epidemiology. 2014;25(5):762–4.CrossRefPubMed
6.
Zurück zum Zitat The BMI in Diverse Populations Collaborative Group. Effect of Smoking on the body mass index-mortality relation: empirical evidence from 15 studies. Am J Epidemiol. 1999;150(12):1297–308.CrossRef The BMI in Diverse Populations Collaborative Group. Effect of Smoking on the body mass index-mortality relation: empirical evidence from 15 studies. Am J Epidemiol. 1999;150(12):1297–308.CrossRef
7.
Zurück zum Zitat Chiolero A, Faeh D, Paccaud F, Cornuz J. Consequences of smoking for body weight, body fat distribution, and insulin resistance. Am J Clin Nutr. 2008;87(4):801–9.PubMed Chiolero A, Faeh D, Paccaud F, Cornuz J. Consequences of smoking for body weight, body fat distribution, and insulin resistance. Am J Clin Nutr. 2008;87(4):801–9.PubMed
8.
Zurück zum Zitat Durazo-Arvizu RA, Cooper RS. Issues related to modeling the body mass index-mortality association: the shape of the association and the effects of smoking status. Int J Obes. 2008;32(S3):S52–5.CrossRef Durazo-Arvizu RA, Cooper RS. Issues related to modeling the body mass index-mortality association: the shape of the association and the effects of smoking status. Int J Obes. 2008;32(S3):S52–5.CrossRef
9.
Zurück zum Zitat Mehio-Sibai A, Feinleib M, Sibai TA, Armenian HK. a positive or a negative confounding variable? A simple teaching aid for clinicians and students. Ann Epidemiol. 2005;15(6):421–3.CrossRefPubMed Mehio-Sibai A, Feinleib M, Sibai TA, Armenian HK. a positive or a negative confounding variable? A simple teaching aid for clinicians and students. Ann Epidemiol. 2005;15(6):421–3.CrossRefPubMed
10.
Zurück zum Zitat VanderWeele TJ, Robins JM. Signed directed acyclic graphs for causal inference. J R Stat Soc Ser B Stat Methodol. 2010;72(1):111–27.CrossRef VanderWeele TJ, Robins JM. Signed directed acyclic graphs for causal inference. J R Stat Soc Ser B Stat Methodol. 2010;72(1):111–27.CrossRef
11.
Zurück zum Zitat de Gonzalez Berrington, et al. Body-mass index and mortality among 1.46 million white adults. N Engl J Med. 2010;363(23):2211–9.PubMedCentralCrossRef de Gonzalez Berrington, et al. Body-mass index and mortality among 1.46 million white adults. N Engl J Med. 2010;363(23):2211–9.PubMedCentralCrossRef
Metadaten
Titel
From bad to worse: collider stratification amplifies confounding bias in the “obesity paradox”
verfasst von
Hailey R. Banack
Jay S. Kaufman
Publikationsdatum
01.10.2015
Verlag
Springer Netherlands
Erschienen in
European Journal of Epidemiology / Ausgabe 10/2015
Print ISSN: 0393-2990
Elektronische ISSN: 1573-7284
DOI
https://doi.org/10.1007/s10654-015-0069-7

Weitere Artikel der Ausgabe 10/2015

European Journal of Epidemiology 10/2015 Zur Ausgabe