N Babio1, M A Martínez-González2, R Estruch3, J Wärnberg4, J Recondo5, M Ortega-Calvo6, L Serra-Majem7, D Corella8, M Fitó9, E Ros10, N Becerra-Tomás11, J Basora12, J Salas-Salvadó13. 1. Human Nutrition Unit, Hospital Universitari de Sant Joan de Reus, Faculty of Medicine and Health Sciences, IISPV (Institut d'Investigació Sanitària Pere Virgili), Department of Biochemistry and Biotechnology, Universitat Rovira i Virgili, Reus, Spain; CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain. Electronic address: nancy.babio@urv.cat. 2. CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain; Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain. 3. CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain; Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, University of Barcelona, Barcelona, Spain. 4. CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain; Department of Preventive Medicine, University of Malaga, Malaga, Spain. 5. CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain; Department of Cardiology, University Hospital Txagorritxu, Vitoria, Spain. 6. CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain; Department of Family Medicine, Primary Care Division of Seville, San Pablo Health Center, Seville, Spain. 7. CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain; Research Institute of Biomedical and Health Sciences, University of Las Palmas de Gran Canaria, Las Palmas, Spain. 8. CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain; Department of Preventive Medicine, University of Valencia, València, Spain. 9. CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain; Cardiovascular Risk and Nutrition Research Group, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona Biomedical Research Park, Barcelona, Spain. 10. CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain; Lipid Clinic, Endocrinology and Nutrition Service, IDIBAPS, Hospital Clinic, University of Barcelona, Barcelona, Spain. 11. Human Nutrition Unit, Hospital Universitari de Sant Joan de Reus, Faculty of Medicine and Health Sciences, IISPV (Institut d'Investigació Sanitària Pere Virgili), Department of Biochemistry and Biotechnology, Universitat Rovira i Virgili, Reus, Spain; CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain. 12. Human Nutrition Unit, Hospital Universitari de Sant Joan de Reus, Faculty of Medicine and Health Sciences, IISPV (Institut d'Investigació Sanitària Pere Virgili), Department of Biochemistry and Biotechnology, Universitat Rovira i Virgili, Reus, Spain; CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain; Institut Català de la Salut, IDIAP Jordi Gol i Gurina, Barcelona, Spain. 13. Human Nutrition Unit, Hospital Universitari de Sant Joan de Reus, Faculty of Medicine and Health Sciences, IISPV (Institut d'Investigació Sanitària Pere Virgili), Department of Biochemistry and Biotechnology, Universitat Rovira i Virgili, Reus, Spain; CIBERobn (Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición), Institute of Health Carlos III, Madrid, Spain. Electronic address: jordi.salas@urv.cat.
Abstract
BACKGROUND AND AIMS: Several studies have demonstrated a relationship between increased serum uric acid (SUA) concentrations and the prevalence of metabolic syndrome (MetS) in the oriental population. However, to the best of our knowledge, the association between SUA and MetS has never been investigated in elderly European individuals at high cardiovascular risk. The aim of this study was to conduct a cross-sectional and prospective evaluation of the associations between SUA concentrations and the MetS in elderly individuals at high cardiovascular risk. METHODS AND RESULTS: Men and women (55-80 years of age) from different PREDIMED (Prevención con DIeta MEDiterránea) recruiting centers were studied. Baseline cross-sectional (n = 4417) and prospective assessments (n = 1511) were performed. MetS was defined in accordance with the updated harmonized criteria. Anthropometric measurements and biochemical determinations were assessed at baseline and yearly during follow-up. Unadjusted and adjusted regression models were fitted to assess the risk of MetS and its components according to the levels of baseline SUA. Participants in the highest baseline sex-adjusted SUA quartile showed an increased prevalence of MetS than those in the lowest quartile, even after adjusting for potential confounders (odd ratio (OR): 2.3 (95% confidence interval (CI), 1.8-2.8); P < 0.001). Participants in the highest baseline sex-adjusted SUA quartile presented a higher incidence of new-onset MetS than those in the lowest quartile (hazard ratios (HR): 1.4 (95% CI, 1.1-1.9); P < 0.001). Participants initially free at baseline of hypertriglyceridemia (HR: 1.9 (1.6-2.4); P < 0.001), low high-density lipoprotein (HDL)-cholesterol (HR: 1.4 (1.1-1.7); P = 0.002), and hypertension components of MetS (HR: 2.0 (1.2-3.3); P = 0.008) and who were in the upper quartile of SUA had a significantly higher risk of developing these MetS components during follow-up. CONCLUSIONS: Elevated SUA concentrations are significantly associated with the development of MetS.
BACKGROUND AND AIMS: Several studies have demonstrated a relationship between increased serum uric acid (SUA) concentrations and the prevalence of metabolic syndrome (MetS) in the oriental population. However, to the best of our knowledge, the association between SUA and MetS has never been investigated in elderly European individuals at high cardiovascular risk. The aim of this study was to conduct a cross-sectional and prospective evaluation of the associations between SUA concentrations and the MetS in elderly individuals at high cardiovascular risk. METHODS AND RESULTS:Men and women (55-80 years of age) from different PREDIMED (Prevención con DIeta MEDiterránea) recruiting centers were studied. Baseline cross-sectional (n = 4417) and prospective assessments (n = 1511) were performed. MetS was defined in accordance with the updated harmonized criteria. Anthropometric measurements and biochemical determinations were assessed at baseline and yearly during follow-up. Unadjusted and adjusted regression models were fitted to assess the risk of MetS and its components according to the levels of baseline SUA. Participants in the highest baseline sex-adjusted SUA quartile showed an increased prevalence of MetS than those in the lowest quartile, even after adjusting for potential confounders (odd ratio (OR): 2.3 (95% confidence interval (CI), 1.8-2.8); P < 0.001). Participants in the highest baseline sex-adjusted SUA quartile presented a higher incidence of new-onset MetS than those in the lowest quartile (hazard ratios (HR): 1.4 (95% CI, 1.1-1.9); P < 0.001). Participants initially free at baseline of hypertriglyceridemia (HR: 1.9 (1.6-2.4); P < 0.001), low high-density lipoprotein (HDL)-cholesterol (HR: 1.4 (1.1-1.7); P = 0.002), and hypertension components of MetS (HR: 2.0 (1.2-3.3); P = 0.008) and who were in the upper quartile of SUA had a significantly higher risk of developing these MetS components during follow-up. CONCLUSIONS: Elevated SUA concentrations are significantly associated with the development of MetS.
Authors: Jenna L Riis; Crystal I Bryce; Marla J Matin; John L Stebbins; Olga Kornienko; Lauren van Huisstede; Douglas A Granger Journal: Biomark Med Date: 2018-06-06 Impact factor: 2.851
Authors: Nerea Becerra-Tomás; Guillermo Mena-Sánchez; Andrés Díaz-López; Miguel Ángel Martínez-González; Nancy Babio; Dolores Corella; Gala Freixer; Dora Romaguera; Jesús Vioque; Ángel M Alonso-Gómez; Julia Wärnberg; J Alfredo Martínez; Lluís Serra-Majem; Ramon Estruch; José Carlos Fernández-García; José Lapetra; Xavier Pintó; Josep A Tur; José López-Miranda; Aurora Bueno-Cavanillas; José Juan Gaforio; Pilar Matía-Martín; Lidia Daimiel; Vicente Martín-Sánchez; Josep Vidal; Clotilde Vázquez; Emili Ros; Cristina Razquin; Iván Abellán Cano; Jose V Sorli; Laura Torres; Marga Morey; Eva Mª Navarrete-Muñoz; Lucas Tojal Sierra; Edelys Crespo-Oliva; M Ángeles Zulet; Almudena Sanchez-Villegas; Rosa Casas; M Rosa Bernal-Lopez; José Manuel Santos-Lozano; Emili Corbella; Maria Del Mar Bibiloni; Miguel Ruiz-Canela; Rebeca Fernández-Carrión; Mireia Quifer; Rafel M Prieto; Noelia Fernandez-Brufal; Itziar Salaverria Lete; Juan Carlos Cenoz; Regina Llimona; Jordi Salas-Salvadó Journal: Eur J Nutr Date: 2019-08-05 Impact factor: 5.614