Kroger J, Ferrari P, Jenab M, Bamia C, Touvier M, Bueno-de-Mesquita HB et al.. Specific food group combinations explaining the variation in intakes of nutrients and other important food components in the European Prospective Investigation into Cancer and Nutrition: an application of the reduced rank regression method. Eur J Clin Nutr 63(Suppl 4), S263-S274

Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbrücke, Germany.
European journal of clinical nutrition (Impact Factor: 2.71). 11/2009; 63 Suppl 4:S263-74. DOI: 10.1038/ejcn.2009.85
Source: PubMed


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 (

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    • "The reason for this could be the homogeneous character of the Zutphen Elderly population regarding energy intake, age and sex. After energy adjustment, Kröger et al. [34] found a decrease of about 15 percentage points in total explained nutrient variation by the first pattern derived from RRR. Our results for the percentage in explained CVD risk factor variation was similar before and after energy adjustment. "
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    ABSTRACT: Reduced rank regression (RRR) combines exploratory analysis with a-priori knowledge by including risk factors in the model. Dietary patterns, derived from RRR analysis, can be interpreted by the chosen risk factor profile and give an indication of positive or adverse health effects for a specific disease. Our aim was to assess the stability of dietary patterns derived by RRR over time. We used data from 467 men, aged 64-85 years, participating in the 1985 and 1990 examination rounds of the Zutphen Elderly Study. Backwards regression on risk factors and food groups was applied prior to the RRR analysis to exclude food groups with low predictability (from 36 to 19 food groups) for the chosen risk factor profile. For the final RRR analysis, dietary intake data from 19 food groups as predictor variables and 6 established risk factors for cardiovascular diseases (body mass index, systolic and diastolic blood pressure, high density lipoprotein and total cholesterol levels, and uric acid) were used. Three RRR dietary patterns were derived for both examination years: a "(low in) cereal fibre pattern", an "alcohol pattern" and an "inconsistent pattern". The "(low in) cereal fibre pattern" was most stable over time, with a correlation coefficient of 0.47 (95% CI: 0.38-0.53) between 1985 and 1990 measurements. Dietary patterns as measured by RRR, after backwards regression, are reasonably stable over a period of five years. Thus, RRR appears to be an attractive method to measure long-term dietary exposure for nutritional epidemiological studies, with one dietary measurement at baseline.
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    • "Our baseline data indicated that the usual intakes of study volunteers reflected overconsumption of E and SFA while underconsuming PUFA compared with study targets. The consequent macronutrient profile was associated with increased health risks [25] and allowed for significant dietary change to test the research hypothesis. "
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