Disease Attribution to Multiple Exposures Using Aggregate Data

J Epidemiol. 2023 Aug 5;33(8):405-409. doi: 10.2188/jea.JE20210084. Epub 2022 May 21.

Abstract

Background: Identifying which exposures cause disease and quantifying their impacts is essential in promoting and monitoring public health. When multiple exposures are involved, measuring individual contributions becomes challenging.

Methods: The authors propose a disease attribution method based on aggregate data or summary statistics of individual-level data, possibly from multiple data sources.

Results: Using the proposed method, the burden of disease is apportioned to the independent and interaction effects of each of its major risk factors and all the other factors as a whole. This scheme guarantees that 100% is the total share of the burden.

Conclusion: The calculation is simple and straightforward; therefore, it is recommended for use in studies on disease burden.

Keywords: attributable fraction; burden of disease; causal pie model; disease attribution; interaction.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Causality
  • Cost of Illness*
  • Disease Attributes*
  • Humans
  • Japan
  • Public Health