Heinz Freisling1, Pedro T Pisa2,3, Pietro Ferrari2, Graham Byrnes2, Aurelie Moskal2, Christina C Dahm4, Anne-Claire Vergnaud5, Marie-Christine Boutron-Ruault6,7,8, Guy Fagherazzi6,7,8, Claire Cadeau6,7,8, Tilman Kühn9, Jasmine Neamat-Allah9, Brian Buijsse10, Heiner Boeing10, Jytte Halkjær11, Anne Tjonneland11, Camilla P Hansen4, J Ramón Quirós12, Noémie Travier13, Esther Molina-Montes14,15, Pilar Amiano16,17, José M Huerta15,18, Aurelio Barricarte17,19, Kay-Tee Khaw20, Nicholas Wareham21, Tim J Key22, Dora Romaguera5,23, Yunxia Lu5, Camille M Lassale5, Androniki Naska24,25, Philippos Orfanos24,25, Antonia Trichopoulou24,25, Giovanna Masala26, Valeria Pala27, Franco Berrino27, Rosario Tumino28, Fulvio Ricceri29, Maria Santucci de Magistris30, H Bas Bueno-de-Mesquita5,31,32,33, Marga C Ocké31, Emily Sonestedt34, Ulrika Ericson35, Mattias Johansson2,36, Guri Skeie37, Elisabete Weiderpass37,38,39,40, Tonje Braaten37, Petra H M Peeters41, Nadia Slimani2. 1. International Agency for Research on Cancer (IARC-WHO), 150, Cours Albert Thomas, 69372, Lyon Cedex 08, France. freislingh@fellows.iarc.fr. 2. International Agency for Research on Cancer (IARC-WHO), 150, Cours Albert Thomas, 69372, Lyon Cedex 08, France. 3. Wits Reproductive Health and HIV Institute, University of the Witwatersrand, Johannesburg, South Africa. 4. Section of Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark. 5. Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK. 6. Centre for Research in Epidemiology and Population Health (CESP), Nutrition, Hormones and Women's Health Team, INSERM, Villejuif, France. 7. Université Paris Sud, Villejuif, France. 8. Institut Gustave Roussy, Villejuif, France. 9. Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany. 10. Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbruecke, Nuthetal, Germany. 11. Institute of Cancer Epidemiology, Danish Cancer Society, Copenhagen, Denmark. 12. Public Health Directorate, Asturias, Spain. 13. Unit of Nutrition and Cancer, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain. 14. Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs, Hospitales Universitarios de Granada, Universidad de Granada, Granada, Spain. 15. CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain. 16. Public Helath Division of Gipuzkoa, Basque Health Department, BioDonostia Research Institute, San Sebastián, Spain. 17. Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública-CIBERESP), Madrid, Spain. 18. Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain. 19. Navarre Public Health Institute, Pamplona, Spain. 20. Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge, Cambridge, UK. 21. Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK. 22. Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK. 23. Instituto de Investigación Sanitaria de Palma (IdISPa), CIBER Fisiopatología de la Obesidad y Nutrición (CIBER-OBN), Madrid, Spain. 24. Hellenic Health Foundation, Athens, Greece. 25. Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece. 26. Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute, ISPO, Florence, Italy. 27. Epidemiology and Prevention Unit, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy. 28. Cancer Registry, Azienda Ospedaliera "Civile M.P. Arezzo", Ragusa, Italy. 29. Unit of Cancer Epidemiology - CERMS, Department of Medical Sciences, University of Turin and Città della Salute e della Scienza Hospital, Turin, Italy. 30. Department of Clinical and Experimental Medicine, Frederico II University, Naples, Italy. 31. National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands. 32. Department of Gastroenterology and Hepatology, University Medical Centre Utrecht, Utrecht, The Netherlands. 33. Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia. 34. Department of Clinical Sciences, Lund University, Malmö, Sweden. 35. Diabetes and Cardiovascular Disease, Genetic Epidemiology, Department of Clinical Sciences, Lund University, Malmö, Sweden. 36. Department of Biobank Research, Umea University, Umeå, Sweden. 37. Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsö, Norway. 38. Cancer Registry of Norway, Oslo, Norway. 39. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. 40. Department of Genetic Epidemiology, Folkhälsan Research Center, Helsinki, Finland. 41. Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
Abstract
PURPOSE: Various food patterns have been associated with weight change in adults, but it is unknown which combinations of nutrients may account for such observations. We investigated associations between main nutrient patterns and prospective weight change in adults. METHODS: This study includes 235,880 participants, 25-70 years old, recruited between 1992 and 2000 in 10 European countries. Intakes of 23 nutrients were estimated from country-specific validated dietary questionnaires using the harmonized EPIC Nutrient DataBase. Four nutrient patterns, explaining 67 % of the total variance of nutrient intakes, were previously identified from principal component analysis. Body weight was measured at recruitment and self-reported 5 years later. The relationship between nutrient patterns and annual weight change was examined separately for men and women using linear mixed models with random effect according to center controlling for confounders. RESULTS: Mean weight gain was 460 g/year (SD 950) and 420 g/year (SD 940) for men and women, respectively. The annual differences in weight gain per one SD increase in the pattern scores were as follows: principal component (PC) 1, characterized by nutrients from plant food sources, was inversely associated with weight gain in men (-22 g/year; 95 % CI -33 to -10) and women (-18 g/year; 95 % CI -26 to -11). In contrast, PC4, characterized by protein, vitamin B2, phosphorus, and calcium, was associated with a weight gain of +41 g/year (95 % CI +2 to +80) and +88 g/year (95 % CI +36 to +140) in men and women, respectively. Associations with PC2, a pattern driven by many micro-nutrients, and with PC3, a pattern driven by vitamin D, were less consistent and/or non-significant. CONCLUSIONS: We identified two main nutrient patterns that are associated with moderate but significant long-term differences in weight gain in adults.
PURPOSE: Various food patterns have been associated with weight change in adults, but it is unknown which combinations of nutrients may account for such observations. We investigated associations between main nutrient patterns and prospective weight change in adults. METHODS: This study includes 235,880 participants, 25-70 years old, recruited between 1992 and 2000 in 10 European countries. Intakes of 23 nutrients were estimated from country-specific validated dietary questionnaires using the harmonized EPIC Nutrient DataBase. Four nutrient patterns, explaining 67 % of the total variance of nutrient intakes, were previously identified from principal component analysis. Body weight was measured at recruitment and self-reported 5 years later. The relationship between nutrient patterns and annual weight change was examined separately for men and women using linear mixed models with random effect according to center controlling for confounders. RESULTS: Mean weight gain was 460 g/year (SD 950) and 420 g/year (SD 940) for men and women, respectively. The annual differences in weight gain per one SD increase in the pattern scores were as follows: principal component (PC) 1, characterized by nutrients from plant food sources, was inversely associated with weight gain in men (-22 g/year; 95 % CI -33 to -10) and women (-18 g/year; 95 % CI -26 to -11). In contrast, PC4, characterized by protein, vitamin B2, phosphorus, and calcium, was associated with a weight gain of +41 g/year (95 % CI +2 to +80) and +88 g/year (95 % CI +36 to +140) in men and women, respectively. Associations with PC2, a pattern driven by many micro-nutrients, and with PC3, a pattern driven by vitamin D, were less consistent and/or non-significant. CONCLUSIONS: We identified two main nutrient patterns that are associated with moderate but significant long-term differences in weight gain in adults.
Entities:
Keywords:
Dietary patterns; Energy balance; Nutrients; Obesity; Public health; Weight gain
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