Rocío Zamanillo-Campos1, Alice Chaplin2, Dora Romaguera3, Itziar Abete4, Jordi Salas-Salvadó5, Vicente Martín6, Ramón Estruch7, Josep Vidal8, Miguel Ruiz-Canela9, Nancy Babio5, Francisca Fiol10, José Antonio de Paz11, Rosa Casas7, Romina Olbeyra12, Miguel A Martínez-González9, Jesús F García-Gavilán5, Albert Goday13, Cesar I Fernandez-Lazaro14, J Alfredo Martínez15, Frank B Hu16, Jadwiga Konieczna2. 1. Research Group on Preventive Activities and Promotion Illes Balears (GRAPP-caIB), Health Research Institute of the Balearic Islands (IdISBa), Primary Care Research Unit of Mallorca (IB-Salut), Palma de Mallorca, Spain. 2. Research Group on Nutritional Epidemiology & Cardiovascular Physiopathology (NUTRECOR), Health Research Institute of the Balearic Islands (IdISBa), University Hospital Son Espases (HUSE), Palma de Mallorca, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. 3. Research Group on Nutritional Epidemiology & Cardiovascular Physiopathology (NUTRECOR), Health Research Institute of the Balearic Islands (IdISBa), University Hospital Son Espases (HUSE), Palma de Mallorca, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. Electronic address: mariaadoracion.romaguera@ssib.es. 4. Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, Pamplona, University of Navarra, Navarra Institute for Health Research (IdiSNA), Pamplona, Spain. 5. Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Pere Virgili (IISPV), Reus, Spain. 6. CIBER Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Institute of Biomedicine (IBIOMED), University of León, León, Spain. 7. Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Department of Internal Medicine, IDIBAPS, Hospital Clinic, University of Barcelona, Barcelona, Spain. 8. CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; Department of Endocrinology, Institut d'Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain. 9. Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Department of Preventive Medicine and Public Health, IdiSNA, University of Navarra, Pamplona, Spain. 10. Atención Primaria Mallorca, Centro de Salud Son Serra de la Vileta, Palma de Mallorca, Spain. 11. Institute of Biomedicine (IBIOMED), University of León, León, Spain. 12. Institut d'Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Barcelona, Spain. 13. Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Medical Research Institute (IMIM), Department of Medicine, University of Barcelona, Barcelona, Spain; Departament de Medicina, Universitat Autonoma de Barcelona, Barcelona, Spain. 14. Department of Preventive Medicine and Public Health, IdiSNA, University of Navarra, Pamplona, Spain. 15. Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, Pamplona, University of Navarra, Navarra Institute for Health Research (IdiSNA), Pamplona, Spain; Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain. 16. Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA.
Abstract
BACKGROUND & AIMS: The quality of dietary carbohydrates rather than total carbohydrate intake may determine the accumulation of visceral fat; however, to date, few studies have examined the impact of diet on adiposity using specific imaging techniques. Thus, the aim of this prospective study was to investigate the association between concurrent changes in carbohydrate quality index (CQI) and objectively-quantified adiposity distribution over a year. METHODS: We analyzed a cohort of 1476 participants aged 55-75 years with overweight/obesity and metabolic syndrome (MetS) from the PREDIMED-Plus randomized controlled trial. Dietary intake information was obtained at baseline, 6- and 12-months from a validated 143-item semi-quantitative food-frequency questionnaire, and CQI (range: 4 to 20) was calculated based on four dietary criteria: total dietary fibre, glycemic index, wholegrain/total grain carbohydrate ratio, and solid/total carbohydrate ratio. Overall and regional adiposity (total body fat, visceral fat and android-to-gynoid fat ratio) was quantified using dual-energy X-ray absorptiometry at all three time points. Multiple adjusted linear mixed-effects models were used to assess associations between concurrent changes in repeatedly measured CQI and adiposity over time. RESULTS: After controlling for potential confounding factors, a 3-point increment in CQI over 12-month follow-up was associated with a decrease in visceral fat (β -0.067 z-score, 95% CI -0.088; -0.046, p < 0.001), android-to-gynoid fat ratio (-0.038, -0.059; -0.017, p < 0.001), and total fat (-0.064, -0.080; -0.047, p < 0.001). Fibre intake and the ratio of wholegrain/total grain showed the strongest inverse associations with all adiposity indicators. CONCLUSIONS: In this prospective cohort of older adults with overweight/obesity and MetS, we found that improvements in dietary carbohydrate quality over a year were associated with concurrent favorable changes in visceral and overall fat deposition. These associations were mostly driven by dietary fibre and the wholegrain/total grain ratio. TRIAL REGISTRATION: The trial was registered at the International Standard Randomized. CONTROLLED TRIAL: (ISRCTN: http://www.isrctn.com/ISRCTN89898870) with number 89898870 and registration date of 24 July 2014, retrospectively registered.
BACKGROUND & AIMS: The quality of dietary carbohydrates rather than total carbohydrate intake may determine the accumulation of visceral fat; however, to date, few studies have examined the impact of diet on adiposity using specific imaging techniques. Thus, the aim of this prospective study was to investigate the association between concurrent changes in carbohydrate quality index (CQI) and objectively-quantified adiposity distribution over a year. METHODS: We analyzed a cohort of 1476 participants aged 55-75 years with overweight/obesity and metabolic syndrome (MetS) from the PREDIMED-Plus randomized controlled trial. Dietary intake information was obtained at baseline, 6- and 12-months from a validated 143-item semi-quantitative food-frequency questionnaire, and CQI (range: 4 to 20) was calculated based on four dietary criteria: total dietary fibre, glycemic index, wholegrain/total grain carbohydrate ratio, and solid/total carbohydrate ratio. Overall and regional adiposity (total body fat, visceral fat and android-to-gynoid fat ratio) was quantified using dual-energy X-ray absorptiometry at all three time points. Multiple adjusted linear mixed-effects models were used to assess associations between concurrent changes in repeatedly measured CQI and adiposity over time. RESULTS: After controlling for potential confounding factors, a 3-point increment in CQI over 12-month follow-up was associated with a decrease in visceral fat (β -0.067 z-score, 95% CI -0.088; -0.046, p < 0.001), android-to-gynoid fat ratio (-0.038, -0.059; -0.017, p < 0.001), and total fat (-0.064, -0.080; -0.047, p < 0.001). Fibre intake and the ratio of wholegrain/total grain showed the strongest inverse associations with all adiposity indicators. CONCLUSIONS: In this prospective cohort of older adults with overweight/obesity and MetS, we found that improvements in dietary carbohydrate quality over a year were associated with concurrent favorable changes in visceral and overall fat deposition. These associations were mostly driven by dietary fibre and the wholegrain/total grain ratio. TRIAL REGISTRATION: The trial was registered at the International Standard Randomized. CONTROLLED TRIAL: (ISRCTN: http://www.isrctn.com/ISRCTN89898870) with number 89898870 and registration date of 24 July 2014, retrospectively registered.
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Authors: Helmut Schröder; Gabriela Cárdenas-Fuentes; Miguel Angel Martínez-González; Dolores Corella; Jesús Vioque; Dora Romaguera; J Alfredo Martínez; Francisco J Tinahones; José López Miranda; Ramon Estruch; Aurora Bueno-Cavanillas; Fernando Arós; Ascensión Marcos; Josep A Tur; Julia Warnberg; Lluis Serra-Majem; Vicente Martín; Clotilde Vázquez; José Lapetra; Xavier Pintó; Josep Vidal; Lidia Daimiel; José Juan Gaforio; Pilar Matía-Martín; Emilio Ros; Olga Castañer; Camille Lassale; Miguel Ruiz-Canela; Eva M Asensio; Josep Basora; Laura Torres-Collado; Antonio Garcia-Rios; Itziar Abete; Estefania Toledo; Pilar Buil-Cosiales; Mònica Bullo; Albert Goday; Montserrat Fitó; Jordi Salas-Salvadó Journal: Int J Behav Nutr Phys Act Date: 2018-11-13 Impact factor: 6.457