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Comparison of two statistical approaches to predict all-cause mortality by dietary patterns in German elderly subjects

Published online by Cambridge University Press:  08 March 2007

Kurt Hoffmann ,
Heiner Boeing ,
Paolo Boffetta ,
Gabriele Nagel ,
Philippos Orfanos ,
Pietro Ferrari  and
Christina Bamia
Kurt Hoffmann*
Affiliation:
Department of Epidemiology, German Institute of Human Nutrition, Arthur-Scheunert-Allee 114-116, 14558, Nuthetal, Germany
Heiner Boeing
Affiliation:
Department of Epidemiology, German Institute of Human Nutrition, Arthur-Scheunert-Allee 114-116, 14558, Nuthetal, Germany
Paolo Boffetta
Affiliation:
Division of Clinical Epidemiology, German Cancer Research Centre, Heidelberg, Germany
Gabriele Nagel
Affiliation:
Division of Clinical Epidemiology, German Cancer Research Centre, Heidelberg, Germany
Philippos Orfanos
Affiliation:
Department of Hygiene and Epidemiology, University of Athens Medical School, Athens, Greece
Pietro Ferrari
Affiliation:
Unit of Nutrition and Cancer, International Agency for Research on Cancer, Lyon, France
Christina Bamia
Affiliation:
Department of Hygiene and Epidemiology, University of Athens Medical School, Athens, Greece
*
*Corresponding author: Dr Kurt Hoffmann, fax +49 33200 88 721, email khoff@mail.dife.de
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Abstract

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Dietary patterns are comprehensive variables of dietary intake appropriate to model the complex exposure in nutritional research. The objectives of this study were to identify dietary patterns by applying two statistical methods, principal component analysis (PCA) and reduced rank regression (RRR), and to assess their ability to predict all-cause mortality. Motivated by previous studies we chose percentages of energy from different macronutrients as response variables in the RRR analysis. We used data from 9356 German elderly subject enrolled in the European Prospective Investigation into Cancer and Nutrition study. The first RRR pattern, subjects which explained 30·8 % of variation in energy sources and especially much variation in intake of saturated fat, monounsaturated fat and carbohydrates was a significant predictor of all-cause mortality. The pattern score had high positive loadings in all types of meat, butter, sauces and eggs, and was inversely associated with bread and fruits. After adjustment for other known risk factors, the relative risks from the lowest to highest quintiles of the first RRR pattern score were 1·0, 1·01, 0·96, 1·32, 1·61 (P for trend: 0·0004). In contrast, the first two PCA patterns explaining 19·7 % of food intake variation but only 7·0 % of variation in energy sources were not related to mortality. These results suggest that variation in macronutrients is meaningful for mortality and that the RRR method is more appropriate than the classic PCA method to identify dietary patterns relevant to mortality.

Keywords

NutritionMortalityDietary patternsStatistical methods
Type
Research Article
Information
British Journal of Nutrition , Volume 93 , Issue 5 , May 2005 , pp. 709 - 716
Copyright
Copyright © The Nutrition Society 2005

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