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Dietary Pattern Analysis×NOVA Food Classification×
领域Food Agriculture StudiesFood Agriculture Studies
方法族Process / pipelineProcess / pipeline
起源年份20022019
提出者Frank B. Hu; P. K. Newby & Katherine L. TuckerCarlos A. Monteiro and colleagues (University of Sao Paulo)
类型Multivariate pipeline for deriving empirical dietary patterns from food intakeFood-processing classification pipeline for diet and food-system analysis
开创性文献Hu, F. B. (2002). Dietary pattern analysis: a new direction in nutritional epidemiology. Current Opinion in Lipidology, 13(1), 3-9. DOI ↗Monteiro, C. A., Cannon, G., Levy, R. B., Moubarac, J.-C., Louzada, M. L. C., Rauber, F., Khandpur, N., Cediel, G., Neri, D., Martinez-Steele, E., Baraldi, L. G., & Jaime, P. C. (2019). Ultra-processed foods: what they are and how to identify them. Public Health Nutrition, 22(5), 936-941. DOI ↗
别名Empirical Dietary Patterns, A Posteriori Dietary Patterns, Data-Driven Dietary Patterns, Eating Pattern AnalysisNOVA, NOVA classification, Ultra-Processed Food Classification, NOVA food processing classification
相关44
摘要Dietary pattern analysis is the nutritional-epidemiology application of multivariate statistics that identifies how foods are actually eaten together, summarizing the whole diet into a few empirical patterns rather than studying single nutrients in isolation. Introduced as a research direction by Frank Hu in his 2002 Current Opinion in Lipidology review and surveyed methodologically by Newby and Tucker in 2004, the approach takes a matrix of food-group intakes and applies factor (principal component) analysis, cluster analysis, or reduced-rank regression to extract a posteriori patterns such as a 'prudent' pattern rich in fruits, vegetables, and whole grains and a 'Western' pattern high in red meat and refined foods. While the underlying algebra is generic principal component or cluster analysis, what makes this a distinct method is its substantive construction: the input is the food-group intake matrix of the whole diet, and the output is interpretable eating patterns linked to disease.The NOVA classification groups foods not by their nutrient content but by the nature, extent, and purpose of the industrial processing they undergo, sorting all items into four groups: unprocessed or minimally processed foods, processed culinary ingredients, processed foods, and ultra-processed foods. Developed by Carlos Monteiro and colleagues at the University of Sao Paulo, NOVA introduced ultra-processed foods (UPF) as a category — industrial formulations made largely from substances extracted from foods plus additives — and argued that this processing dimension, rather than nutrient profile alone, is central to diet and health. The 2019 paper Ultra-processed foods: what they are and how to identify them gives the operational definitions, and the share of dietary energy from ultra-processed foods has become a widely used exposure in nutrition and food-system research.
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ScholarGate方法对比: Dietary Pattern Analysis · NOVA Food Classification. 于 2026-06-24 检索自 https://scholargate.app/zh/compare