Concepts and pitfalls in measuring and interpreting attributable fractions, prevented fractions, and causation probabilities

Ann Epidemiol. 2015 Mar;25(3):155-61. doi: 10.1016/j.annepidem.2014.11.005. Epub 2014 Nov 14.

Abstract

Measures of causal attribution and preventive potential appear deceptively simple to define, yet have many subtle variations and are subject to numerous pitfalls in conceptualization, interpretation, and application. This article reviews basic concepts, measures, and problems to serve as an introduction to more detailed literature. Allowing for validity and generalization (projection) issues, epidemiologic attribution measures can serve as useful policy inputs for contrasting expected caseloads or survival times under different well-defined interventions. Nonetheless, their application in these settings requires attention to effects of the interventions besides those on the study outcome. Their use as estimates of etiologic attribution requires assumptions beyond the usual validity and statistical assumptions; these further assumptions will usually have little support or plausibility when the mechanisms of action are unknown.

Keywords: Attributable fraction; Attributable risk; Causation; Etiologic fraction; Excess fraction; Preventable fraction; Prevented fraction; Public health; Years of life lost.

Publication types

  • Review

MeSH terms

  • Causality*
  • Data Interpretation, Statistical*
  • Epidemiologic Methods*
  • Humans
  • Models, Theoretical
  • Probability*