Cited by 198Nutritional Studies and DietNutrition, Genetics, and DiseaseNutrition, Health and Food Behavior

Dietary patterns and their association with food and nutrient intake in the European Prospective Investigation into Cancer and Nutrition (EPIC)–Potsdam study

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Schulze, Matthias B., Hoffmann, Kurt, Kroke, Anja, Boeing, Heiner·2001·British Journal Of Nutrition

Abstract

Dietary pattern analysis has recently received growing attention, as it might be more appropriate in studies of diet-disease associations than the single food or nutrient approach that has dominated past epidemiological research. Factor analysis is a technique which is commonly used to identify dietary patterns within study populations. However, the ability of factor solutions to account for variance of food and nutrient intake has so far remained unclear. The present study therefore explored the statistical properties of dietary patterns with regard to the explained variance. Food intake of 8975 men and 13 379 women, assessed by a food-frequency questionnaire, was aggregated into forty-seven separate food groups. Dietary patterns were identified by principal component analysis and subsequent varimax rotation. Seven factors were retained for both men and women, which accounted for about 31 % of the total variance. The explained variance was relatively high (>40 %) for cooked vegetables, sauce, meat, dessert, cake, bread other than wholemeal, raw vegetables, processed meat, high-fat cheese, butter and margarine. Factor scores were used to investigate associations between the factors and nutrient intake. The patterns accounted for relatively large proportions of variance of energy and macronutrient intake, but for less variance of alcohol and micronutrient intake, especially of retinol, beta-carotene, vitamin E, Ca and ascorbic acid. In addition, factors were related to age, BMI, physical activity, education, smoking and vitamin and mineral supplement use.

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  • Potential confounders were a priori selected based on the literature on red meat intake and diabetes risk and prior investigations in EPIC-Potsdam.

    “Potential confounders to be included as covariates were a priori selected based on the literature on the association between red meat intake and diabetes risk (2, 3) and prior investigations in EPIC-Potsdam regarding risk factors of type 2 diabetes (5), dietary patterns (27), and determinants of metabolic profiles (28,29).”

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References 30 · Cited by 198

Research works printed but not linked: 1

  1. Bohlscheid-Thomas S, Hoting I, Boeing H & Wahrendorf J (1997b) Reproducibility and relative validity of food energy and macronutrient intake of a food frequency questionnaire developed for the German part of the EPIC project. Interna- tional Journal of Epidemiology 26, Suppl. 1, S71±S81. Federal Institute for Health Protection of Consumers and Veterinary Medicine (1998) The German Food Code and Nutrient Database, BLS 2.1. Berlin: BgVV-Journal 2.

Authors
Schulze, M. B., Hoffmann, K., Kroke, A., & Boeing, H.
Affiliations
German Institute of Human Nutrition (DE)
Corresponding author
Schulze, Matthias B.
Venue
British Journal Of Nutrition
Published
2001-03
Volume
85
Issue
3
Pages
363-373
ISSN
  • 0007-1145 (ISSN-L)
  • 1475-2662
OpenAlex
W1989715709
Cited by
198
References
30
Citations by year
2026: 1 · 2025: 1 · 2024: 4 · 2023: 3 · 2022: 5 · 2021: 5 · 2020: 3 · 2019: 6 · 2018: 6 · 2017: 5 · 2016: 8 · 2015: 15 · 2014: 8 · 2013: 11 · 2012: 11
FWCI
8.91
Type
journal article
Language
en
Open access
Locations
  • British Journal Of Nutrition (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Deutsche Forschungsgemeinschaft
  • Deutsche Krebshilfe (70–2488-Ha I, 70-2488-Ha, SOC 95 201408 05F02)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
  • Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
Keywords
dietary habits, explained variance, dietary intake, nutrient intake, factor analysis, principal component analysis, varimax rotation, cooked vegetables, meat consumption, processed meat, dairy products, energy intake, macronutrient intake, micronutrient intake, alcohol consumption, EPIC-Potsdam cohort, diet-disease association
MeSH terms
Adult, Energy Intake, Diet, Diet Surveys, Europe, Factor Analysis, Statistical, Feeding Behavior, Female, Food, Humans, Male, Middle Aged, Neoplasms, Nutritional Physiological Phenomena, Prospective Studies, Surveys and Questionnaires

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