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- M Solans
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- G Coenders
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- R Marcos-Gragera
- Research Group on Statistics, Econometrics and Health (GRECS), Universitat de Girona, Girona, Spain
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- A Castelló
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- E Gràcia-Lavedan
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- Y Benavente
- Unit of molecular and genetic epidemiology in infections and cancer, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain
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- V Moreno
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- B Pérez-Gómez
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- P Amiano
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- T Fernández-Villa
- Instituto de Biomedicina, Universidad de León, León, Spain
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- M Guevara
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- I Gómez-Acebo
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- G Fernández-Tardón
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- M Vanaclocha-Espi
- Cancer and Public Health Area, FISABIO – Public Health, Valencia, Spain
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- MD Chirlaque
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- R Capelo
- Centro de Investigación en Recursos Naturales, Salud y medio Ambiente (RENSMA), Universidad de Huelva, Huelva, Spain
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- R Barrios
- Departamento de Medicina Preventiva y Salud Pública, Facultad de Medicina, Universidad de Granada, Granada, Spain
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- N Aragonés
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- A Molinuevo
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- F Vitelli-Storelli
- Instituto de Biomedicina, Universidad de León, León, Spain
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- J Castilla
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- T Dierssen-Sotos
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- G Castaño-Vinyals
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- M Kogevinas
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- M Pollán
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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- M Saez
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
抄録
<jats:p> Instead of looking at individual nutrients or foods, dietary pattern analysis has emerged as a promising approach to examine the relationship between diet and health outcomes. Despite dietary patterns being compositional (i.e. usually a higher intake of some foods implies that less of other foods are being consumed), compositional data analysis has not yet been applied in this setting. We describe three compositional data analysis approaches (compositional principal component analysis, balances and principal balances) that enable the extraction of dietary patterns by using control subjects from the Spanish multicase-control (MCC-Spain) study. In particular, principal balances overcome the limitations of purely data-driven or investigator-driven methods and present dietary patterns as trade-offs between eating more of some foods and less of others. </jats:p>
収録刊行物
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- Statistical Methods in Medical Research
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Statistical Methods in Medical Research 28 (9), 2834-2847, 2018-07-26
SAGE Publications