Disease Attribution to Multiple Exposures Using Aggregate Data

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...

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Detalles Bibliográficos
Autores principales: Lee, Wen-Chung, Wu, Yun-Chun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japan Epidemiological Association 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10319529/
https://www.ncbi.nlm.nih.gov/pubmed/35283399
http://dx.doi.org/10.2188/jea.JE20210084
Descripción
Sumario: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.

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