In defense of standardized regression coefficients

Abstract

The association between a risk factor and a disease can be expressed as a standardized regression coefficient derived from a logistic model. When exponentiated, this standardized coefficient equals the odds ratio associated with a one-standard-deviation change in the risk factor. Some epidemiologists have recently recommended that standardized regression coefficients not be used in epidemiologic research. We disagree and provide examples that demonstrate that, when a risk factor is continuous, standardized regression coefficients may be helpful for comparing variables measured in different units. Standardized regression coefficients may also be helpful for comparing the effect of the same risk factor in different populations. Misinterpretations can be avoided if the standard deviations of the variables of interest are also provided. There is no reason to abandon the use of standardized regression coefficients in epidemiologic analyses. © 1991 Epidemiology Resources Inc.