Land M, Vogel C, Gefeller O
Department of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander-University of Erlangen-Nuremberg, Germany.
Stat Methods Med Res. 2001 Jun;10(3):217-30. doi: 10.1177/096228020101000304.
The epidemiological problem of risk attribution in the framework of multiple exposures has been the subject of intensive research activities in the last decade. In particular, partitioning methods have been developed to define new multidimensional measures of attributable risk putting the task of quantifying a proportion of disease events in a population that can be ascribed to the adverse health effects of certain risk factors into a multifactorial perspective. The parameters generalize the concept of attributable risk to different multifactorial frameworks in which multiple exposures might be arranged in hierarchically ordered classes or in equally ranking groups. Partitioning methods are reviewed and differences between the multifactorial variants of attributable risk are illustrated by a component causes model.
在过去十年中，多重暴露框架下风险归因的流行病学问题一直是深入研究的主题。特别是，已经开发了划分方法来定义新的多维归因风险度量，将量化人群中可归因于某些风险因素对健康的不利影响的疾病事件比例的任务置于多因素视角。这些参数将归因风险的概念推广到不同的多因素框架，在这些框架中，多重暴露可能按层次排序类别或同等排名组进行排列。本文回顾了划分方法，并通过一个成分病因模型说明了归因风险多因素变体之间的差异。
