Andrea J Glenn1, Pablo Hernández-Alonso2, Cyril W C Kendall3, Miguel Ángel Martínez-González4, Dolores Corella5, Montserrat Fitó6, J Alfredo Martínez7, Ángel M Alonso-Gómez8, Julia Wärnberg9, Jesús Vioque10, Dora Romaguera11, José López-Miranda12, Ramon Estruch13, Francisco J Tinahones14, José Lapetra15, J Luís Serra-Majem16, Aurora Bueno-Cavanillas17, Josep A Tur18, Sofia Reguero Celada19, Xavier Pintó20, Miguel Delgado-Rodríguez21, Pilar Matía-Martín22, Josep Vidal23, Sebastian Mas-Fontao24, Lidia Daimiel25, Emilio Ros26, David J A Jenkins27, Estefania Toledo28, José V Sorlí5, Olga Castañer6, Itziar Abete29, Anai Moreno Rodriguez8, Olga Fernández Barceló30, Alejandro Oncina-Canovas31, Jadwiga Konieczna11, Antonio Garcia-Rios12, Rosa Casas13, Ana Maria Gómez-Pérez14, José Manuel Santos-Lozano15, Zenaida Vazquez-Ruiz28, Olga Portolés5, Helmut Schröder32, Maria A Zulet29, Sonia Eguaras33, Itziar Salaverria Lete8, María Dolores Zomeño34, John L Sievenpiper35, Jordi Salas-Salvadó36. 1. Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Toronto, Ontario, Canada; Toronto 3D Knowledge Synthesis and Clinical Trials Unit, St. Michael's Hospital, Toronto, Ontario, Canada. 2. Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició, Reus, Spain; University Hospital of Sant Joan de Reus, Nutrition Unit, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain. 3. Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Toronto, Ontario, Canada; Toronto 3D Knowledge Synthesis and Clinical Trials Unit, St. Michael's Hospital, Toronto, Ontario, Canada; College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. 4. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA, Pamplona, Spain; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 5. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine, University of Valencia, Valencia, Spain. 6. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d`Investigació Médica (IMIM), Barcelona, Spain. 7. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain; Nutritional Control of the Epigenome. IMDEA Food, CEI UAM + CSIC, Madrid, Spain. 8. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area; Osakidetza Basque Health Service, Araba University Hospital; University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain. 9. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Nursing. University of Málaga, Institute of Biomedical Research in Malaga (IBIMA), Málaga, Spain. 10. CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain; Instituto de Investigation Sanitaria y Biomédica de Alicante, ISABIAL-UMH, Alicante, Spain. 11. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; 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. 12. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain. 13. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain. 14. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Virgen de la Victoria Hospital, Department of Endocrinology, Instituto de Investigación Biomédica de Málaga (IBIMA). University of Málaga, Málaga, Spain. 15. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Sevilla, Spain. 16. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria & Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, Las Palmas de Gran Canaria, Spain. 17. CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain. 18. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Research Group on Community Nutrition & Oxidative Stress, University of Balearic Islands-IUNICS & IDISBA, Palma de Mallorca, Spain. 19. Institute of Biomedicine (IBIOMED), University of León, León, Spain. 20. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge, University of Barcelona, Hospitalet de Llobregat, Barcelona Spain. 21. CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain; Division of Preventive Medicine, Faculty of Medicine, University of Jaén, Jaén, Spain. 22. Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), Madrid, Spain. 23. CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Department of Endocrinology, Institut d` Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain. 24. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Department of Endocrinology and Nutrition, Hospital Fundación Jimenez Díaz. Instituto de Investigaciones Biomédicas IISFJD. University Autonoma, Madrid, Spain. 25. Nutritional Control of the Epigenome. IMDEA Food, CEI UAM + CSIC, Madrid, Spain. 26. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Lipid Clinic, Department of Endocrinology and Nutrition, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain. 27. Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Toronto, Ontario, Canada; Toronto 3D Knowledge Synthesis and Clinical Trials Unit, St. Michael's Hospital, Toronto, Ontario, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada; Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada. 28. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA, Pamplona, Spain. 29. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain. 30. Department of Nursing. University of Málaga, Institute of Biomedical Research in Malaga (IBIMA), Málaga, Spain. 31. Instituto de Investigation Sanitaria y Biomédica de Alicante, ISABIAL-UMH, Alicante, Spain. 32. Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d`Investigació Médica (IMIM), Barcelona, Spain; CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain. 33. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain; Servicio Navarro de Salud, Pamplona, Spain. 34. Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d`Investigació Médica (IMIM), Barcelona, Spain; Servicio Navarro de Salud, Pamplona, Spain. 35. Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Toronto, Ontario, Canada; Toronto 3D Knowledge Synthesis and Clinical Trials Unit, St. Michael's Hospital, Toronto, Ontario, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada; Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada. Electronic address: john.sievenpiper@utoronto.ca. 36. Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició, Reus, Spain; University Hospital of Sant Joan de Reus, Nutrition Unit, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain. Electronic address: jordi.salas@urv.cat.
Abstract
BACKGROUND & AIMS: The Portfolio and Dietary Approaches to Stop Hypertension (DASH) diets have been shown to lower cardiometabolic risk factors in randomized controlled trials (RCTs). However, the Portfolio diet has only been assessed in RCTs of hyperlipidemic patients. Therefore, to assess the Portfolio diet in a population with metabolic syndrome (MetS), we conducted a longitudinal analysis of one-year data of changes in the Portfolio and DASH diet scores and their association with cardiometabolic risk factors in Prevención con Dieta Mediterránea (PREDIMED)-Plus trial. METHODS: PREDIMED-Plus is an ongoing clinical trial (Trial registration: ISRCTN89898) conducted in Spain that includes 6874 older participants (mean age 65 y, 48% women) with overweight/obesity fulfilling at least three criteria for MetS. Data for this analysis were collected at baseline, six months and one year. Adherence to the Portfolio and DASH diet scores were derived from a validated 143-item food frequency questionnaire. We used linear mixed models to examine the associations of 1-SD increase and quartile changes in the diet scores with concomitant changes in cardiometabolic risk factors. RESULTS: After adjusting for several potential confounders, a 1-SD increase in the Portfolio diet score was significantly associated with lower HbA1c (β [95% CI]: -0.02% [-0.02, -0.01], P < 0.001), fasting glucose (-0.47 mg/dL [-0.83, -0.11], P = 0.01), triglycerides (-1.29 mg/dL [-2.31, -0.28], P = 0.01), waist circumference (WC) (-0.51 cm [-0.59, -0.43], P < 0.001), and body mass index (BMI) (-0.17 kg/m2 [-0.19, -0.15], P < 0.001). A 1-SD increase in the DASH diet score was significantly associated with lower HbA1c (-0.03% [-0.04, -0.02], P < 0.001), glucose (-0.84 mg/dL [-1.18, -0.51], P < 0.001), triglycerides (-3.38 mg/dL [-4.37, -2.38], P < 0.001), non-HDL-cholesterol (-0.47 mg/dL [-0.91, -0.04], P = 0.03), WC (-0.69 cm [-0.76, -0.60 cm], P < 0.001), BMI (-0.25 kg/m2 [-0.28, -0.26 kg/m2], P < 0.001), systolic blood pressure (-0.57 mmHg [-0.81, -0.32 mmHg], P < 0.001), diastolic blood pressure (-0.15 mmHg [-0.29, -0.01 mmHg], P = 0.03), and with higher HDL-cholesterol (0.21 mg/dL [0.09, 0.34 mg/dL, P = 0.001]). Similar associations were seen when both diet scores were assessed as quartiles, comparing extreme categories of adherence. CONCLUSIONS: Among older adults at high cardiovascular risk with MetS, greater adherence to the Portfolio and DASH diets showed significant favourable prospective associations with several clinically relevant cardiometabolic risk factors. Both diets are likely beneficial for cardiometabolic risk reduction.
BACKGROUND & AIMS: The Portfolio and Dietary Approaches to Stop Hypertension (DASH) diets have been shown to lower cardiometabolic risk factors in randomized controlled trials (RCTs). However, the Portfolio diet has only been assessed in RCTs of hyperlipidemic patients. Therefore, to assess the Portfolio diet in a population with metabolic syndrome (MetS), we conducted a longitudinal analysis of one-year data of changes in the Portfolio and DASH diet scores and their association with cardiometabolic risk factors in Prevención con Dieta Mediterránea (PREDIMED)-Plus trial. METHODS: PREDIMED-Plus is an ongoing clinical trial (Trial registration: ISRCTN89898) conducted in Spain that includes 6874 older participants (mean age 65 y, 48% women) with overweight/obesity fulfilling at least three criteria for MetS. Data for this analysis were collected at baseline, six months and one year. Adherence to the Portfolio and DASH diet scores were derived from a validated 143-item food frequency questionnaire. We used linear mixed models to examine the associations of 1-SD increase and quartile changes in the diet scores with concomitant changes in cardiometabolic risk factors. RESULTS: After adjusting for several potential confounders, a 1-SD increase in the Portfolio diet score was significantly associated with lower HbA1c (β [95% CI]: -0.02% [-0.02, -0.01], P < 0.001), fasting glucose (-0.47 mg/dL [-0.83, -0.11], P = 0.01), triglycerides (-1.29 mg/dL [-2.31, -0.28], P = 0.01), waist circumference (WC) (-0.51 cm [-0.59, -0.43], P < 0.001), and body mass index (BMI) (-0.17 kg/m2 [-0.19, -0.15], P < 0.001). A 1-SD increase in the DASH diet score was significantly associated with lower HbA1c (-0.03% [-0.04, -0.02], P < 0.001), glucose (-0.84 mg/dL [-1.18, -0.51], P < 0.001), triglycerides (-3.38 mg/dL [-4.37, -2.38], P < 0.001), non-HDL-cholesterol (-0.47 mg/dL [-0.91, -0.04], P = 0.03), WC (-0.69 cm [-0.76, -0.60 cm], P < 0.001), BMI (-0.25 kg/m2 [-0.28, -0.26 kg/m2], P < 0.001), systolic blood pressure (-0.57 mmHg [-0.81, -0.32 mmHg], P < 0.001), diastolic blood pressure (-0.15 mmHg [-0.29, -0.01 mmHg], P = 0.03), and with higher HDL-cholesterol (0.21 mg/dL [0.09, 0.34 mg/dL, P = 0.001]). Similar associations were seen when both diet scores were assessed as quartiles, comparing extreme categories of adherence. CONCLUSIONS: Among older adults at high cardiovascular risk with MetS, greater adherence to the Portfolio and DASH diets showed significant favourable prospective associations with several clinically relevant cardiometabolic risk factors. Both diets are likely beneficial for cardiometabolic risk reduction.
Authors: Paraskevi Massara; Andreea Zurbau; Andrea J Glenn; Laura Chiavaroli; Tauseef A Khan; Effie Viguiliouk; Sonia Blanco Mejia; Elena M Comelli; Victoria Chen; Ursula Schwab; Ulf Risérus; Matti Uusitupa; Anne-Marie Aas; Kjeld Hermansen; Inga Thorsdottir; Dario Rahelić; Hana Kahleová; Jordi Salas-Salvadó; Cyril W C Kendall; John L Sievenpiper Journal: Diabetologia Date: 2022-08-26 Impact factor: 10.460
Authors: Kenneth Lo; Andrea J Glenn; Suey Yeung; Cyril W C Kendall; John L Sievenpiper; David J A Jenkins; Jean Woo Journal: Nutrients Date: 2021-12-03 Impact factor: 5.717