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使用核k均值聚类的时间饮食模式

Temporal Dietary Patterns Using Kernel k-Means Clustering.

作者信息

Khanna Nitin, Eicher-Miller Heather A, Boushey Carol J, Gelfand Saul B, Delp Edward J

机构信息

School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana, USA.

Department of Nutrition Science, Purdue University, West Lafayette, Indiana, USA.

出版信息

ISM. 2011;2011:375-380. doi: 10.1109/ISM.2011.68.

Abstract

Chronic diseases, such as heart disease, diabetes, and obesity, have been linked with diet. Nutrient intake is also associated with diet. However, much of the research completed to elucidate these associations has not incorporated the concept of time. This paper introduces the concept of temporal dietary patterns and demonstrates a novel construct of 24-hour temporal dietary patterns for energy intake, present in a sample of the adult U.S. population 20 years and older (NHANES 1999-2004 dataset). An appropriate distance metric is proposed for comparing 24-hour diet records and is used with kernel k-means clustering to identify the temporal dietary patterns.

摘要

心脏病、糖尿病和肥胖症等慢性病与饮食有关。营养摄入也与饮食相关。然而,为阐明这些关联而完成的许多研究并未纳入时间概念。本文介绍了时间饮食模式的概念,并展示了一种针对能量摄入的24小时时间饮食模式的新颖构建,该模式存在于20岁及以上的美国成年人群样本中(1999 - 2004年国家健康与营养检查调查数据集)。提出了一种用于比较24小时饮食记录的合适距离度量,并将其与核k均值聚类一起用于识别时间饮食模式。

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