OBJECTIVE: To identify combinations of food groups that explain as much variation in absolute intakes of 23 key nutrients and food components as possible within the country-specific populations of the European Prospective Investigation into Cancer and Nutrition (EPIC). SUBJECTS/ METHODS: The analysis covered single 24-h dietary recalls (24-HDR) from 36,034 subjects (13,025 men and 23,009 women), aged 35-74 years, from all 10 countries participating in the EPIC study. In a set of 39 food groups, reduced rank regression (RRR) was used to identify those combinations (RRR factors) that explain the largest proportion of variation in intake of 23 key nutrients and food components, namely, proteins, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, cholesterol, sugars (sum of mono- and disaccharides), starch, fibre, alcohol, calcium, iron, potassium, phosphorus, magnesium, vitamin D, beta-carotene, retinol and vitamins E, B1, B2, B6, B12 and C (RRR responses). Analyses were performed at the country level and for all countries combined. RESULTS: In the country-specific analyses, the first RRR factor explained a considerable proportion of the total nutrient intake variation in all 10 countries (27.4-37.1%). The subsequent RRR factors were much less important in explaining the variation (<or=6%). Strong similarities were observed for the first country-specific RRR factor between the individual countries, largely characterized by consumption of bread, vegetable oils, red meat, milk, cheese, potatoes, margarine and processed meat. The highest explained variation was seen for protein, potassium, phosphorus and magnesium (50-70%), whereas sugars, beta-carotene, retinol and alcohol were only marginally explained (<or=5%). The explained proportion of the other nutrients ranged between these extremes. CONCLUSIONS: A combination of food groups was identified that explained a considerable proportion of the nutrient intake variation in 24-HDRs in every country-specific EPIC population in a similar manner. This indicates that, despite the large variability in food and nutrient intakes reported in the EPIC, the variance of intake of important nutrients is explained, to a large extent, by similar food group combinations across countries.
OBJECTIVE: To identify combinations of food groups that explain as much variation in absolute intakes of 23 key nutrients and food components as possible within the country-specific populations of the European Prospective Investigation into Cancer and Nutrition (EPIC). SUBJECTS/ METHODS: The analysis covered single 24-h dietary recalls (24-HDR) from 36,034 subjects (13,025 men and 23,009 women), aged 35-74 years, from all 10 countries participating in the EPIC study. In a set of 39 food groups, reduced rank regression (RRR) was used to identify those combinations (RRR factors) that explain the largest proportion of variation in intake of 23 key nutrients and food components, namely, proteins, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, cholesterol, sugars (sum of mono- and disaccharides), starch, fibre, alcohol, calcium, iron, potassium, phosphorus, magnesium, vitamin D, beta-carotene, retinol and vitamins E, B1, B2, B6, B12 and C (RRR responses). Analyses were performed at the country level and for all countries combined. RESULTS: In the country-specific analyses, the first RRR factor explained a considerable proportion of the total nutrient intake variation in all 10 countries (27.4-37.1%). The subsequent RRR factors were much less important in explaining the variation (<or=6%). Strong similarities were observed for the first country-specific RRR factor between the individual countries, largely characterized by consumption of bread, vegetable oils, red meat, milk, cheese, potatoes, margarine and processed meat. The highest explained variation was seen for protein, potassium, phosphorus and magnesium (50-70%), whereas sugars, beta-carotene, retinol and alcohol were only marginally explained (<or=5%). The explained proportion of the other nutrients ranged between these extremes. CONCLUSIONS: A combination of food groups was identified that explained a considerable proportion of the nutrient intake variation in 24-HDRs in every country-specific EPIC population in a similar manner. This indicates that, despite the large variability in food and nutrient intakes reported in the EPIC, the variance of intake of important nutrients is explained, to a large extent, by similar food group combinations across countries.
Authors: Krishna Vyncke; Inge Huybrechts; Myriam Van Winckel; Magdalena Cuenca Garcia; Idoia Labayen; Frederic Gottrand; Kurt Widhalm; Catherine Leclercq; Lars Libuda; Yannis Manios; Michael Sjostrom; Denes Molnar; Luis A Moreno; Marcela Gonzalez-Gross; André Spinneker; Fatima Perez de Heredia; Maria Plada; Stefaan De Henauw Journal: Lipids Date: 2014-08-14 Impact factor: 1.880
Authors: Laura K Frank; Franziska Jannasch; Janine Kröger; George Bedu-Addo; Frank P Mockenhaupt; Matthias B Schulze; Ina Danquah Journal: Nutrients Date: 2015-07-07 Impact factor: 5.717
Authors: K Iqbal; L Schwingshackl; M Gottschald; S Knüppel; M Stelmach-Mardas; K Aleksandrova; H Boeing Journal: Eur J Clin Nutr Date: 2017-07-26 Impact factor: 4.016
Authors: Iris Trefflich; Hanns-Ulrich Marschall; Romina di Giuseppe; Marcus Ståhlman; Andreas Michalsen; Alfonso Lampen; Klaus Abraham; Cornelia Weikert Journal: Nutrients Date: 2019-12-23 Impact factor: 5.717