Ismael Alvarez-Alvarez1, Estefanía Toledo1,2, Oscar Lecea1,3, Jordi Salas-Salvadó2,4, Dolores Corella2,5, Pilar Buil-Cosiales1,2,3, María Dolores Zomeño6,7, Jesús Vioque8,9, J Alfredo Martinez2,10,11, Jadwiga Konieczna2,12, Francisco J Barón-López13, José López-Miranda2,14, Ramon Estruch2,15, Aurora Bueno-Cavanillas8,16, Ángel M Alonso-Gómez2,17,18, Josep A Tur2,19, Francisco J Tinahones2,20, Lluís Serra-Majem2,21, Vicente Martín8,22, Manuel Ortega-Calvo2,23, Clotilde Vázquez2,24, Xavier Pintó2,25, Josep Vidal26,27, Lidia Daimiel11, Miguel Delgado-Rodríguez8,28, Pilar Matía29, José I González2,5, Andrés Díaz-López2,4, Indira Paz-Graniel4, Miguel A Muñoz30,31, Montse Fito2,6, Salvador Pertusa-Martinez9,32, Itziar Abete10, Antonio García-Ríos14, Emilio Ros2,33, Miguel Ruiz-Canela1,2, Miguel Á Martínez-González34,35,36. 1. Department of Preventive Medicine and Public Health, University of Navarra-IdiSNA, C/Irunlarrea 1, 31080, Pamplona, Navarra, Spain. 2. CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. 3. Atención Primaria, Osasunbidea-Servicio Navarro de Salud, Pamplona, Spain. 4. Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana IISPV, Hospital Universitari Sant Joan de Reus, Rovira i Virgili University, Reus, Spain. 5. Department of Preventive Medicine, University of Valencia, Valencia, Spain. 6. Cardiovascular Risk and Nutrition, IMIM-Hospital del Mar Medical Research Institute, Barcelona, Spain. 7. Blanquerna School of Life Sciences, Universitat Ramon Llull, Barcelona, Spain. 8. CIBER Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. 9. Nutritional Epidemiology Unit, Miguel Hernandez University, ISABIAL-FISABIO, Alicante, Spain. 10. Department of Nutrition, Food Sciences and Physiology, University of Navarra, Pamplona, Spain. 11. Nutritional Genomics and Epigenomics Group, IMDEA Food, CEI UAM + CSIC, Madrid, Spain. 12. Health Research Institute of the Balearic Islands (IdISBa), University Hospital Son Espases, Palma, Spain. 13. Department of Public Health, University of Malaga-IBIMA, Málaga, Spain. 14. Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Research Institute of Córdoba (IMIBIC), Reina Sofía University Hospital, University of Córdoba, Córdoba, Spain. 15. Department of Internal Medicine, IDIBAPS, Hospital Clinic, University of Barcelona, Barcelona, Spain. 16. Department of Preventive Medicine, University of Granada, Granada, Spain. 17. Department of Cardiology Organización Sanitaria Integrada (OSI) ARABA, University Hospital Araba, Vitoria-Gasteiz, Spain. 18. University of the Basque Country, UPV/EHU, Vitoria-Gasteiz, Spain. 19. Research Group on Community Nutrition & Oxidative Stress, University of Balearic Islands, Palma de Mallorca, Spain. 20. Department of Endocrinology, Hospital Virgen de la Victoria (IBIMA), University of Málaga, Málaga, Spain. 21. Institute for Biomedical Research, University of Las Palmas de Gran Canaria, Las Palmas, Spain. 22. Institute of Biomedicine (IBIOMED), University of León, León, Spain. 23. Department of Family Medicine, Healthcare centre Las Palmeritas, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain. 24. Department of Endocrinology, Fundación Jiménez-Díaz, Madrid, Spain. 25. Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain. 26. CIBER Diabetes y enfermedades metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. 27. Department of Endocrinology, IDIBAPS, Hospital Clinic, University of Barcelona, Barcelona, Spain. 28. Division of Preventive Medicine, University of Jaén, Jaén, Spain. 29. Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid, Spain. 30. Gerencia territorial de Barcelona, Institut Català de la Salut, Barcelona, Spain. 31. Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain. 32. Healthcare centre Cabo Huertas, Alicante, Spain. 33. Department of Endocrinology and Nutrition, Lipid Clinic, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain. 34. Department of Preventive Medicine and Public Health, University of Navarra-IdiSNA, C/Irunlarrea 1, 31080, Pamplona, Navarra, Spain. mamartinez@unav.es. 35. CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. mamartinez@unav.es. 36. Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, USA. mamartinez@unav.es.
Abstract
PURPOSE: Cardiovascular disease remains the global leading cause of death. We evaluated at baseline the association between the adherence to eight a priori high-quality dietary scores and the prevalence of individual and clustered cardiovascular risk factors (CVRF) in the PREDIMED-Plus cohort. METHODS: All PREDIMED-Plus participants (6874 men and women aged 55-75 years, with overweight/obesity and metabolic syndrome) were assessed. The prevalence of 4 CVRF (hypertension, obesity, diabetes, and dyslipidaemia), using standard diagnoses criteria, were considered as outcomes. The adherence to eight a priori-defined dietary indexes was calculated. Multivariable models were fitted to estimate differences in mean values of factors and prevalence ratios for individual and clustered CVRF. RESULTS: Highest conformity to any dietary pattern did not show inverse associations with hypertension. The modified Mediterranean Diet Score (PR = 0.95; 95% CI 0.90-0.99), Mediterranean Diet Adherence Score (MEDAS) (PR = 0.94; 95% CI 0.89-0.98), the pro-vegetarian dietary pattern (PR = 0.95; 95% CI 0.90-0.99) and the Alternate Healthy Eating Index 2010 (PR = 0.92; 95% CI 0.87-0.96) were inversely associated with prevalence of obesity. We identified significant inverse trend among participants who better adhered to the MEDAS and the Prime Diet Quality Score (PDQS) in the mean number of CVRF across categories of adherence. Better adherence to several high-quality dietary indexes was associated with better blood lipid profiles and anthropometric measures. CONCLUSIONS:Highest adherence to dietary quality indexes, especially Mediterranean-style and PDQS scores, showed marginal associations with lower prevalence of individual and clustered CVRF among elderly adults with metabolic syndrome at high risk of cardiovascular disease.
RCT Entities:
PURPOSE:Cardiovascular disease remains the global leading cause of death. We evaluated at baseline the association between the adherence to eight a priori high-quality dietary scores and the prevalence of individual and clustered cardiovascular risk factors (CVRF) in the PREDIMED-Plus cohort. METHODS: All PREDIMED-Plus participants (6874 men and women aged 55-75 years, with overweight/obesity and metabolic syndrome) were assessed. The prevalence of 4 CVRF (hypertension, obesity, diabetes, and dyslipidaemia), using standard diagnoses criteria, were considered as outcomes. The adherence to eight a priori-defined dietary indexes was calculated. Multivariable models were fitted to estimate differences in mean values of factors and prevalence ratios for individual and clustered CVRF. RESULTS: Highest conformity to any dietary pattern did not show inverse associations with hypertension. The modified Mediterranean Diet Score (PR = 0.95; 95% CI 0.90-0.99), Mediterranean Diet Adherence Score (MEDAS) (PR = 0.94; 95% CI 0.89-0.98), the pro-vegetarian dietary pattern (PR = 0.95; 95% CI 0.90-0.99) and the Alternate Healthy Eating Index 2010 (PR = 0.92; 95% CI 0.87-0.96) were inversely associated with prevalence of obesity. We identified significant inverse trend among participants who better adhered to the MEDAS and the Prime Diet Quality Score (PDQS) in the mean number of CVRF across categories of adherence. Better adherence to several high-quality dietary indexes was associated with better blood lipid profiles and anthropometric measures. CONCLUSIONS: Highest adherence to dietary quality indexes, especially Mediterranean-style and PDQS scores, showed marginal associations with lower prevalence of individual and clustered CVRF among elderly adults with metabolic syndrome at high risk of cardiovascular disease.
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