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Disease Attribution to Multiple Exposures Using Aggregate Data
論文ID: JE20210084
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論文ID: JE20210084
Introduction. 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. By 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.
Conclusions. The calculation is simple and straightforward; therefore, it is recommended for use in studies on disease burden.
