The use of attributable fraction in the design and interpretation of epidemiologic studies

Abstract

Because of the etiologic heterogeneity present in many diseases and the interaction among causal factors in the development of disease, relative risks relating any one exposure to a disease may be low, especially in the presence of common exposures. Nevertheless, in the design of epidemiologic studies, arbitrary values of relative risks are often used to determine the sample size required to detect an association between a particular exposure and a disease outcome. Such an approach may not yield adequate statistical power to detect an association. In this commentary, the authors point out the value of using the attributable fraction to determine an appropriate value of relative risk to use for sample size calculations. The approach is particularly useful in cluster investigations where the magnitude of the expected attributable fraction can be readily estimated from the observed and expected rates of disease. Specification of an attributable fraction is also useful in the design of case-control studies of etiologically heterogeneous diseases, especially when common exposures are suspected. Finally, the relationship among attributable fraction, relative risk and exposure frequency is valuable in interpreting results of an epidemiologic study and gaining insight into the differences in relative risk estimates found in various studies.