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PLoS One. 2014 Jun 5;9(6):e98647. doi: 10.1371/journal.pone.0098647. eCollection 2014.

Nutrient patterns and their food sources in an International Study Setting: report from the EPIC study.

Author information

1
Dietary Exposure Assessment Group, International Agency for Research on Cancer, Lyon, France.
2
Nutritional Epidemiology Group, International Agency for Research on Cancer, Lyon, France.
3
Biostatistics Group, International Agency for Research on Cancer, Lyon, France.
4
Center for research in Epidemiology and Population Health, Nutrition, Hormones and Women's Health, INSERM U1018, Villejuif, France; Université Paris Sud, UMRS 1018, Villejuif, France; Institut Gustave-Roussy, Villejuif, France.
5
Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.
6
Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbruecke, Germany.
7
Danish Cancer Society Research Center, Diet, Genes and Environment, Copenhagen, Denmark.
8
Section for Epidemiology, Institute of Public Health, Aarhus University, Aarhus, Denmark.
9
Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America; Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America.
10
Public Health and Health Planning Directorate, Asturias, Spain.
11
Unit of Nutrition, Environment and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology, Barcelona, Spain.
12
Andalusian School of Public Health, Granada, Spain.
13
Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública-CIBERESP), Madrid, Spain; Public Health Division of Gipuzkoa, BIODonostia Research Institute, San Sebastian, Spain.
14
Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública-CIBERESP), Madrid, Spain; Department of Epidemiology, Murcia Regional Health Council, Murcia, Spain.
15
Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública-CIBERESP), Madrid, Spain; Navarre Public Health Institute, Pamplona, Spain.
16
Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
17
Cancer Epidemiology Unit, University of Oxford, Oxford, United Kingdom.
18
Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; CIBER Fisiopatología de la Obesidad y Nutrición, Madrid, Spain.
19
Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.
20
WHO Collaborating Center for Food and Nutrition Policies, Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece; Hellenic Health Foundation, Athens, Greece.
21
Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute ISPO, Florence, Italy.
22
Nutritional Epidemiology Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
23
Cancer Registry and Histopathology Unit, "Civile - M.P. Arezzo" Hospital, Ragusa, Italy.
24
HuGeF Foundation and Center for Cancer Prevention CPO-Piemonte, Torino, Italy.
25
Department of Clinical and Experimental Medicine, Federico II University, Naples, Italy.
26
The National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands; Department of Gastroenterology and Hepatology, University Medical Center, Utrecht, The Netherlands.
27
The National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
28
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
29
Diabetes and Cardiovascular Disease, Genetic Epidemiology, Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden.
30
Department of Clinical Sciences in Malmö, Research Group in Nutritional Epidemiology, Lund University, Malmö, Sweden.
31
Department of Public Health and Clinical Medicine, Nutrition Research, Umeå University, Umeå, Sweden.
32
Department of Internal Medicine and Clinical Nutrition, University of Gothenburg, Gothenburg, Sweden.
33
Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway; Department of Research, Cancer Registry of Norway, Oslo, Norway; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Samfundet Folkhälsan, Helsinki, Finland.
34
Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.

Abstract

BACKGROUND:

Compared 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 FINDINGS:

We 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/SIGNIFICANCE:

The 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.

PMID:
24901309
PMCID:
PMC4047062
DOI:
10.1371/journal.pone.0098647
[Indexed for MEDLINE]
Free PMC Article

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