Zhao Junkang, Li Zhiyao, Gao Qian, Zhao Haifeng, Chen Shuting, Huang Lun, Wang Wenjie, Wang Tong
Department of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, 030001, Shanxi province, China.
Department of Nutrition & Food Hygiene, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, 030001, Shanxi province, China.
Nutr J. 2021 Apr 19;20(1):37. doi: 10.1186/s12937-021-00692-7.
Dietary pattern analysis is a promising approach to understanding the complex relationship between diet and health. While many statistical methods exist, the literature predominantly focuses on classical methods such as dietary quality scores, principal component analysis, factor analysis, clustering analysis, and reduced rank regression. There are some emerging methods that have rarely or never been reviewed or discussed adequately.
This paper presents a landscape review of the existing statistical methods used to derive dietary patterns, especially the finite mixture model, treelet transform, data mining, least absolute shrinkage and selection operator and compositional data analysis, in terms of their underlying concepts, advantages and disadvantages, and available software and packages for implementation.
While all statistical methods for dietary pattern analysis have unique features and serve distinct purposes, emerging methods warrant more attention. However, future research is needed to evaluate these emerging methods' performance in terms of reproducibility, validity, and ability to predict different outcomes.
Selection of the most appropriate method mainly depends on the research questions. As an evolving subject, there is always scope for deriving dietary patterns through new analytic methodologies.
饮食模式分析是理解饮食与健康之间复杂关系的一种很有前景的方法。虽然存在许多统计方法，但文献主要集中在经典方法上，如饮食质量评分、主成分分析、因子分析、聚类分析和降秩回归。有一些新兴方法很少或从未得到充分的综述或讨论。
本文对用于推导饮食模式的现有统计方法进行了全景综述，特别是有限混合模型、小波变换、数据挖掘、最小绝对收缩和选择算子以及成分数据分析，涉及它们的基本概念、优缺点以及可用于实现的软件和程序包。
虽然所有饮食模式分析的统计方法都有独特的特点并服务于不同的目的，但新兴方法值得更多关注。然而，未来需要开展研究以评估这些新兴方法在可重复性、有效性以及预测不同结果的能力方面的表现。
选择最合适的方法主要取决于研究问题。作为一个不断发展的主题，总是有通过新的分析方法推导饮食模式的空间。
