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Cited by 660

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Application of a New Statistical Method to Derive Dietary Patterns in Nutritional Epidemiology

Hoffmann, K.·2004·American Journal of Epidemiology

Abstract

Because foods are consumed in combination, it is difficult in observational studies to separate the effects of single foods on the development of diseases. A possible way to examine the combined effect of food intakes is to derive dietary patterns by using appropriate statistical methods. The objective of this study was to apply a new statistical method, reduced rank regression (RRR), that is more flexible and powerful than the classic principal component analysis. RRR can be used efficiently in nutritional epidemiology by choosing disease-specific response variables and determining combinations of food intake that explain as much response variation as possible. The authors applied RRR to extract dietary patterns from 49 food groups, specifying four diabetes-related nutrients and nutrient ratios as responses. Data were derived from a nested German case-control study within the European Prospective Investigation into Cancer and Nutrition-Potsdam study consisting of 193 cases with incident type 2 diabetes identified until 2001 and 385 controls. The four factors extracted by RRR explained 93.1% of response variation, whereas the first four factors obtained by principal component analysis accounted for only 41.9%. In contrast to principal component analysis and other methods, the new RRR method extracted a significant risk factor for diabetes.

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Metadata

Authors
Hoffmann, K.
Venue
American Journal of Epidemiology
Published
2004-05-15
Volume
159
Issue
10
Pages
935-944
ISSN
0002-9262 (ISSN-L)
OpenAlex
W2112779575
Cited by
660
References
8
FWCI
12.13
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Application of a New Statistical Method to Derive Dietary Patterns in Nutritional Epidemiology. https://app.cochat.ai/papers/10.1093/aje/kwh134
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Hoffmann, K. (2004). Application of a New Statistical Method to Derive Dietary Patterns in Nutritional Epidemiology. American Journal of Epidemiology. https://doi.org/10.1093/aje/kwh134

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.