Alexander Persoskie1, Rebecca A Ferrer2. 1. Office of Science, FDA Center for Tobacco Products, Silver Spring, Maryland;. Electronic address: persoskie@gmail.com. 2. Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Rockville, Maryland.
Abstract
INTRODUCTION: The OR is one of the most commonly used measures of association in preventive medicine, and yet it is unintuitive and easily misinterpreted by journal authors and readers. METHODS: This article describes correct interpretations of ORs, explains how ORs are different from risk ratios (RRs), and notes potential supplements and alternatives to the presentation of ORs that may help readers avoid confusion about the strength of associations. RESULTS: ORs are often interpreted as though they have the same meaning as RRs (i.e., ratios of probabilities rather than ratios of odds), an interpretation that is incorrect in cross-sectional and longitudinal analyses. Without knowing the base rate of the outcome event in such analyses, it is impossible to evaluate the size of the absolute or relative change in risk associated with an OR, and misinterpreting the OR as an RR leads to the overestimation of the effect size when the outcome event is common rather than rare in the study sample. In case-control analyses, whether an OR can be interpreted as an RR depends on how the controls were selected. CONCLUSIONS: Education, peer reviewer vigilance, and journal reporting standards concerning ORs may improve the clarity and accuracy with which this common measure of association is described and understood in preventive medicine and public health research. Published by Elsevier Inc.
INTRODUCTION: The OR is one of the most commonly used measures of association in preventive medicine, and yet it is unintuitive and easily misinterpreted by journal authors and readers. METHODS: This article describes correct interpretations of ORs, explains how ORs are different from risk ratios (RRs), and notes potential supplements and alternatives to the presentation of ORs that may help readers avoid confusion about the strength of associations. RESULTS:ORs are often interpreted as though they have the same meaning as RRs (i.e., ratios of probabilities rather than ratios of odds), an interpretation that is incorrect in cross-sectional and longitudinal analyses. Without knowing the base rate of the outcome event in such analyses, it is impossible to evaluate the size of the absolute or relative change in risk associated with an OR, and misinterpreting the OR as an RR leads to the overestimation of the effect size when the outcome event is common rather than rare in the study sample. In case-control analyses, whether an OR can be interpreted as an RR depends on how the controls were selected. CONCLUSIONS: Education, peer reviewer vigilance, and journal reporting standards concerning ORs may improve the clarity and accuracy with which this common measure of association is described and understood in preventive medicine and public health research. Published by Elsevier Inc.
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