RT Journal Article
T1 Nutrient patterns and their food sources in an International Study Setting: report from the EPIC study.
A1 Moskal, Aurelie
A1 Pisa, Pedro T
A1 Ferrari, Pietro
A1 Byrnes, Graham
A1 Freisling, Heinz
A1 Boutron-Ruault, Marie-Christine
A1 Cadeau, Claire
A1 Nailler, Laura
A1 Wendt, Andrea
A1 Kühn, Tilman
A1 Boeing, Heiner
A1 Buijsse, Brian
A1 Tjønneland, Anne
A1 Halkjær, Jytte
A1 Dahm, Christina C
A1 Chiuve, Stephanie E
A1 Quirós, Jose R
A1 Buckland, Genevieve
A1 Molina-Montes, Esther
A1 Amiano, Pilar
A1 Huerta Castaño, José M
A1 Barricarte Gurrea, Aurelio
A1 Khaw, Kay-Tee
A1 Lentjes, Marleen A
A1 Key, Timothy J
A1 Romaguera, Dora
A1 Vergnaud, Anne-Claire
A1 Trichopoulou, Antonia
A1 Bamia, Christina
A1 Orfanos, Philippos
A1 Palli, Domenico
A1 Pala, Valeria
A1 Tumino, Rosario
A1 Sacerdote, Carlotta
A1 Santucci de Magistris, Maria
A1 Bueno-de-Mesquita, H Bas
A1 Ocké, Marga C
A1 Beulens, Joline W J
A1 Ericson, Ulrika
A1 Drake, Isabel
A1 Nilsson, Lena M
A1 Winkvist, Anna
A1 Weiderpass, Elisabete
A1 Hjartåker, Anette
A1 Riboli, Elio
A1 Slimani, Nadia
K1 Cuestionarios
K1 Alimentos
K1 Investigación
K1 Europa
K1 Hábitos alimenticios
K1 Estilo de vida
K1 Evaluación nutricional
K1 Estudios prospectivos
K1 Vigilancia en salud pública
K1 Factores socioeconómicos
AB BACKGROUNDCompared to food patterns, nutrient patterns have been rarely used particularly at international level. We studied, in the context of a multi-center study with heterogeneous data, the methodological challenges regarding pattern analyses.METHODOLOGY/PRINCIPAL FINDINGSWe identified nutrient patterns from food frequency questionnaires (FFQ) in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study and used 24-hour dietary recall (24-HDR) data to validate and describe the nutrient patterns and their related food sources. Associations between lifestyle factors and the nutrient patterns were also examined. Principal component analysis (PCA) was applied on 23 nutrients derived from country-specific FFQ combining data from all EPIC centers (N = 477,312). Harmonized 24-HDRs available for a representative sample of the EPIC populations (N = 34,436) provided accurate mean group estimates of nutrients and foods by quintiles of pattern scores, presented graphically. An overall PCA combining all data captured a good proportion of the variance explained in each EPIC center. Four nutrient patterns were identified explaining 67% of the total variance: Principle component (PC) 1 was characterized by a high contribution of nutrients from plant food sources and a low contribution of nutrients from animal food sources; PC2 by a high contribution of micro-nutrients and proteins; PC3 was characterized by polyunsaturated fatty acids and vitamin D; PC4 was characterized by calcium, proteins, riboflavin, and phosphorus. The nutrients with high loadings on a particular pattern as derived from country-specific FFQ also showed high deviations in their mean EPIC intakes by quintiles of pattern scores when estimated from 24-HDR. Center and energy intake explained most of the variability in pattern scores.CONCLUSION/SIGNIFICANCEThe use of 24-HDR enabled internal validation and facilitated the interpretation of the nutrient patterns derived from FFQs in term of food sources. These outcomes open research opportunities and perspectives of using nutrient patterns in future studies particularly at international level.
PB Public Library of Science
YR 2014
FD 2014-06-05
LK http://hdl.handle.net/10668/1972
UL http://hdl.handle.net/10668/1972
LA en
NO Moskal A, Pisa PT, Ferrari P, Byrnes G, Freisling H, Boutron-Ruault MC, et al. Nutrient patterns and their food sources in an International Study Setting: report from the EPIC study. PLoS ONE 2014; 9(6):e98647
NO Journal Article; Research Support, Non-U.S. Gov't;
DS RISalud
RD Apr 17, 2025