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首页> 外文期刊>Annals of epidemiology >Patterns of cleaning product exposures using a novel clustering approach for data with correlated variables
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Patterns of cleaning product exposures using a novel clustering approach for data with correlated variables

机译：使用具有相关变量的数据的新型聚类方法清洁产品曝光的模式

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PurposeClustering methods may be useful in epidemiology to better characterize exposures and account for their multidimensional aspects. In this context, application of clustering models allowing for highly dependent variables is of particular interest. We aimed to characterize patterns of domestic exposure to cleaning products using a novel clustering model allowing for highly dependent variables. MethodsTo identify domestic cleaning patterns in a large population of French women, we used a mixture model of dependency blocks. This novel approach specifically models within-class dependencies, and is an alternative to the latent class model, which assumes conditional independence. Analyses were conducted in 19,398 participants of the E3N study (women aged 61–88?years) who completed a questionnaire regarding household cleaning habits. ResultsSeven classes were identified, which differed with the frequency of cleaning tasks (e.g., dusting/sweeping/hoovering) and use of specific products (e.g., bleach, sprays). The model also grouped the variables into conditionally independent blocks, providing a summary of the main dependencies among the variables. ConclusionsThe mixture model of dependency blocks, a useful alternative to the latent class model, may have broader application in epidemiology, in particular, in the context of exposome research and growing need for data-reduction methods.
机译：purposeClustering方法可用于流行病学，以更好地表征曝光和占多维方面的曝光。在这种情况下，允许高度依赖变量的聚类模型的应用特别感兴趣。我们旨在使用新型聚类模型来表征国内暴露于清洁产品的模式，允许高度依赖变量。方法识别大量法国女性中的国内清洁模式，我们使用了依赖块的混合模型。这种新颖方法专门在课堂内依赖性模型，并且是潜在类模型的替代方法，它假设有条件独立性。分析是在19,398名参与者的E3N学习参与者（61-88岁的女性）进行，他在家庭清洁习惯完成了调查问卷。确定结果，与清洁任务的频率不同（例如，除尘/扫描/呼吸）和使用特定产品（例如，漂白剂，喷雾）的频率不同。该模型还将变量分组成有条件独立的块，从而提供变量中的主要依赖项的摘要。结论依赖性块的混合物模型，潜在阶级模型的有用替代品，可能在流行病学中具有更广泛的应用，特别是在曝光的研究和日益增长的数据减少方法的背景下。

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