At Odds: Concerns Raised by Using Odds Ratios for Continuous or Common Dichotomous Outcomes in Research on Physical Activity and Obesity
Gina S. Lovasi*, Lindsay J. Underhill, Darby Jack, Catherine Richards, Christopher Weiss, Andrew Rundle
Identifiers and Pagination:Year: 2012
First Page: 13
Last Page: 17
Publisher Id: TOEPIJ-5-13
Article History:Received Date: 30/11/2011
Revision Received Date: 29/03/2012
Acceptance Date: 30/03/2012
Electronic publication date: 4/5/2012
Collection year: 2012
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Purpose: Research on obesity and the built environment has often featured logistic regression and the corresponding parameter, the odds ratio. Use of odds ratios for common outcomes such obesity may unnecessarily hinder the validity, interpretation, and communication of research findings. Methods: We identified three key issues raised by the use of odds ratios, illustrating them with data on walkability and body mass index from a study of 13,102 New York City residents. Results: First, dichotomization of continuous measures such as body mass index discards theoretically relevant information, reduces statistical power, and amplifies measurement error. Second, odds ratios are systematically higher (further from the null) than prevalence ratios; this inflation is trivial for rare outcomes, but substantial for common outcomes like obesity. Third, odds ratios can lead to incorrect conclusions during tests of interactions. The odds ratio in a particular subgroup might higher simply because the outcome is more common (and the odds ratio inflated) compared with other subgroups. Conclusion: Our recommendations are to take full advantage of continuous outcome data when feasible and to use prevalence ratios in place of odds ratios for common dichotomous outcomes. When odds ratios must be used, authors should document outcome prevalence across exposure groups.