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A comparison of confounding adjustment methods with an application to early life determinants of childhood obesity

Published online by Cambridge University Press:  29 August 2014

L. Li ,
K. Kleinman  and
M. W. Gillman
L. Li*
Affiliation:
Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
K. Kleinman
Affiliation:
Department of Population Medicine, Obesity Prevention Program, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
M. W. Gillman
Affiliation:
Department of Population Medicine, Obesity Prevention Program, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
*
*Address for correspondence: L. Li, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 133 Brookline Avenue, 6th floor, Boston, MA 02215, USA.(Email [email protected])
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Abstract

We implemented six confounding adjustment methods: (1) covariate-adjusted regression, (2) propensity score (PS) regression, (3) PS stratification, (4) PS matching with two calipers, (5) inverse probability weighting and (6) doubly robust estimation to examine the associations between the body mass index (BMI) z-score at 3 years and two separate dichotomous exposure measures: exclusive breastfeeding v. formula only (n=437) and cesarean section v. vaginal delivery (n=1236). Data were drawn from a prospective pre-birth cohort study, Project Viva. The goal is to demonstrate the necessity and usefulness, and approaches for multiple confounding adjustment methods to analyze observational data. Unadjusted (univariate) and covariate-adjusted linear regression associations of breastfeeding with BMI z-score were −0.33 (95% CI −0.53, −0.13) and −0.24 (−0.46, −0.02), respectively. The other approaches resulted in smaller n (204–276) because of poor overlap of covariates, but CIs were of similar width except for inverse probability weighting (75% wider) and PS matching with a wider caliper (76% wider). Point estimates ranged widely, however, from −0.01 to −0.38. For cesarean section, because of better covariate overlap, the covariate-adjusted regression estimate (0.20) was remarkably robust to all adjustment methods, and the widths of the 95% CIs differed less than in the breastfeeding example. Choice of covariate adjustment method can matter. Lack of overlap in covariate structure between exposed and unexposed participants in observational studies can lead to erroneous covariate-adjusted estimates and confidence intervals. We recommend inspecting covariate overlap and using multiple confounding adjustment methods. Similar results bring reassurance. Contradictory results suggest issues with either the data or the analytic method.

Keywords

breastfeedingcesarean sectionconfounding adjustmentobesitypropensity score
Type
Original Article
Information
Journal of Developmental Origins of Health and Disease , Volume 5 , Supplement 6 , December 2014 , pp. 435 - 447
Copyright
© Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2014 

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