Advanced search
1 file | 182.32 KB

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

Author
Organization
Abstract
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 (<= 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 (<= 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.
Keywords
food component intakes, nutrient intakes, food group combinations, reduced rank regression, EPIC, 24-h dietary recall, DIETARY PATTERNS, EPIC PROJECT, CALIBRATION, EPIDEMIOLOGY

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 182.32 KB

Citation

Please use this url to cite or link to this publication:

Chicago
Kroger, J, P Ferrari, M Jenab, C Bamia, M Touvier, HB Bueno-de-Mesquita, MT Fahey, et al. 2009. “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.” European Journal of Clinical Nutrition 63: S263–S274.
APA
Kroger, J., Ferrari, P., Jenab, M., Bamia, C., Touvier, M., Bueno-de-Mesquita, H., Fahey, M., et al. (2009). 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. EUROPEAN JOURNAL OF CLINICAL NUTRITION, 63, S263–S274.
Vancouver
1.
Kroger J, Ferrari P, Jenab M, Bamia C, Touvier M, Bueno-de-Mesquita H, 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. EUROPEAN JOURNAL OF CLINICAL NUTRITION. 2009;63:S263–S274.
MLA
Kroger, J, P Ferrari, M Jenab, 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.” EUROPEAN JOURNAL OF CLINICAL NUTRITION 63 (2009): S263–S274. Print.
@article{1177659,
  abstract     = {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 (<= 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 (<= 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.},
  author       = {Kroger, J and Ferrari, P and Jenab, M and Bamia, C and Touvier, M and Bueno-de-Mesquita, HB and Fahey, MT and Benetou, V and Schulz, M and Wirfalt, E and Boeing, H and Hoffmann, K and Schulze, MB and Orfanos, P and Oikonomou, E and Huybrechts, Inge and Rohrmann, S and Pischon, T and Manjer, J and Agren, A and Navarro, C and Jakszyn, P and Boutron-Ruault, MC and Niravong, M and Khaw, KT and Crowe, F and Ocke, MC and van der Schouw, YT and Mattiello, A and Bellegotti, M and Engeset, D and Hjartaker, A and Egeberg, R and Overvad, K and Riboli, E and Bingham, S and Slimani, N},
  issn         = {0954-3007},
  journal      = {EUROPEAN JOURNAL OF CLINICAL NUTRITION},
  keywords     = {food component intakes,nutrient intakes,food group combinations,reduced rank regression,EPIC,24-h dietary recall,DIETARY PATTERNS,EPIC PROJECT,CALIBRATION,EPIDEMIOLOGY},
  language     = {eng},
  pages        = {S263--S274},
  title        = {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},
  url          = {http://dx.doi.org/10.1038/ejcn.2009.85},
  volume       = {63},
  year         = {2009},
}

Altmetric
View in Altmetric
Web of Science
Times cited: