Eva-Maria Navarrete-Muñoz1, Jesus Vioque2,3,4, Estefanía Toledo5,6, Alejando Oncina-Canovas7, Miguel Ángel Martínez-González5,6,8, Jordi Salas-Salvadó5,9,10,11, Dolores Corella5,12, Montserrat Fitó5,13, Dora Romaguera5,14, Ángel M Alonso-Gómez5,15, Julia Wärnberg5,16, J Alfredo Martínez5,17, Luís Serra-Majem5,18, Ramon Estruch5,19, Francisco J Tinahones5,20, José Lapetra5,21, Xavier Pintó5,22, Josep A Tur5,14,23, José López-Miranda5,24, Aurora Bueno-Cavanillas25,26, Pilar Matía-Martín27, Lidia Daimiel28, Vicente Martín Sánchez25,29, Josep Vidal30,31, Ana Isabel de Cos Blanco5,32, Emili Ros5,33, Javier Diez-Espino5,6,34, Nancy Babio5,9,10,11, Rebeca Fernandez-Carrion5,12, Olga Castañer5,13, Antoni Colom14, Laura Compañ-Gabucio7, Itziar Salaverria Lete15, Edelys Crespo-Oliva5,16, Itziar Abete5,17, Laura Tomaino5,18,35, Rosa Casas5,19, José Carlos Fernandez-Garcia5,20, José Manuel Santos-Lozano5,21, Iziar Sarasa22, José M Gámez5,14,23,36, José M Antonio Garcia-Rios5,24, Sandra Martín-Pelaez26, Miguel Ruiz-Canela5,6, Andrés Díaz-López5,9,10,11, Raul Martinez-Lacruz5,12, Maria Dolors Zomeño5,13, Elena Rayó14, Cristina Gisbert Sellés37, Silvia Canudas5,9,10,11, Albert Goday5,13, Manoli García-de-la-Hera25,7. 1. Grupo de Investigación en Terapia Ocupacional (InTeO), Department of Surgery and Pathology, Miguel Hernández University, 03550, Alicante, Spain. 2. CIBER de Epidemiología y Salud Pública (CIBERESP), Institute of Health Carlos III, Madrid, Spain. vioque@umh.es. 3. Nutritional Epidemiology Unit, Universidad Miguel Hernández, ISABIAL-UMH, Alicante, Spain. vioque@umh.es. 4. Departamento Salud Pública, Campus San Juan, Universidad Miguel Hernández, Ctra. Nacional 332 s/n, 03550, Sant Joan d'Alacant, Spain. vioque@umh.es. 5. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain. 6. Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain. 7. Nutritional Epidemiology Unit, Universidad Miguel Hernández, ISABIAL-UMH, Alicante, Spain. 8. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 9. Departament de Bioquímica i Biotecnologia, Unitat de Nutrició, Universitat Rovira i Virgili, Reus, Spain. 10. Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain. 11. Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. 12. Department of Preventive Medicine, University of Valencia, Valencia, Spain. 13. Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d'Investigació Médica (IMIM), Barcelona, Spain. 14. Health Research Institute of the Balearic Islands (IdISBa), University Hospital Son Espases, Palma de Mallorca, Spain. 15. Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain. 16. Department of Nursing, School of Health Sciences, University of Málaga-Institute of Biomedical Research in Malaga (IBIMA), Málaga, Spain. 17. Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, Pamplona, Spain. 18. Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria and Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, Las Palmas de Gran Canaria, Spain. 19. Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain. 20. Department of Endocrinology, Instituto de Investigación Biomédica de Málaga (IBIMA), Virgen de la Victoria Hospital, University of Málaga, Málaga, Spain. 21. Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Sevilla, Spain. 22. Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain. 23. Research Group on Community Nutrition and Oxidative Stress, University of Balearic Islands, Palma de Mallorca, Spain. 24. Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain. 25. CIBER de Epidemiología y Salud Pública (CIBERESP), Institute of Health Carlos III, Madrid, Spain. 26. Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain. 27. Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), Madrid, Spain. 28. Nutritional Control of the Epigenom Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain. 29. Institute of Biomedicine (IBIOMED), University of León, León, Spain. 30. CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. 31. Department of Endocrinology, Institut d'Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain. 32. Department of Endocrinology and Nutrition, Hospital Fundación Jimenez Díaz, Instituto de Investigaciones Biomédicas IISFJD, University Autonoma, Madrid, Spain. 33. Lipid Clinic, Department of Endocrinology and Nutrition, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain. 34. Gerencia de Atención Primaria, Servicio Navarro de Salud-Osasunbidea, Pamplona, Spain. 35. Department of Clinical and Community Health (DISCCO), Università degli Studi di Milano, Milan, Italy. 36. Department of Cardiology, Hospital Son Llàtzer, 07198, Palma de Mallorca, Spain. 37. Centro Salud San Vicente del Raspeig, Alicante, Spain.
Abstract
PURPOSE: We examined the association between dietary folate intake and a score of MetS (metabolic syndrome) and its components among older adults at higher cardiometabolic risk participating in the PREDIMED-Plus trial. METHODS: A cross-sectional analysis with 6633 with overweight/obesity participants with MetS was conducted. Folate intake (per 100 mcg/day and in quintiles) was estimated using a validated food frequency questionnaire. We calculated a MetS score using the standardized values as shown in the formula: [(body mass index + waist-to-height ratio)/2] + [(systolic blood pressure + diastolic blood pressure)/2] + plasma fasting glucose-HDL cholesterol + plasma triglycerides. The MetS score as continuous variable and its seven components were the outcome variables. Multiple robust linear regression using MM-type estimator was performed to evaluate the association adjusting for potential confounders. RESULTS: We observed that an increase in energy-adjusted folate intake was associated with a reduction of MetS score (β for 100 mcg/day = - 0.12; 95% CI: - 0.19 to - 0.05), and plasma fasting glucose (β = - 0.03; 95% CI: - 0.05 to - 0.02) independently of the adherence to Mediterranean diet and other potential confounders. We also found a positive association with HDL-cholesterol (β = 0.07; 95% CI: 0.04-0.10). These associations were also observed when quintiles of energy-adjusted folate intake were used instead. CONCLUSION: This study suggests that a higher folate intake may be associated with a lower MetS score in older adults, a lower plasma fasting glucose, and a greater HDL cholesterol in high-risk cardio-metabolic subjects.
PURPOSE: We examined the association between dietary folate intake and a score of MetS (metabolic syndrome) and its components among older adults at higher cardiometabolic risk participating in the PREDIMED-Plus trial. METHODS: A cross-sectional analysis with 6633 with overweight/obesityparticipants with MetS was conducted. Folate intake (per 100 mcg/day and in quintiles) was estimated using a validated food frequency questionnaire. We calculated a MetS score using the standardized values as shown in the formula: [(body mass index + waist-to-height ratio)/2] + [(systolic blood pressure + diastolic blood pressure)/2] + plasma fasting glucose-HDL cholesterol + plasma triglycerides. The MetS score as continuous variable and its seven components were the outcome variables. Multiple robust linear regression using MM-type estimator was performed to evaluate the association adjusting for potential confounders. RESULTS: We observed that an increase in energy-adjusted folate intake was associated with a reduction of MetS score (β for 100 mcg/day = - 0.12; 95% CI: - 0.19 to - 0.05), and plasma fasting glucose (β = - 0.03; 95% CI: - 0.05 to - 0.02) independently of the adherence to Mediterranean diet and other potential confounders. We also found a positive association with HDL-cholesterol (β = 0.07; 95% CI: 0.04-0.10). These associations were also observed when quintiles of energy-adjusted folate intake were used instead. CONCLUSION: This study suggests that a higher folate intake may be associated with a lower MetS score in older adults, a lower plasma fasting glucose, and a greater HDL cholesterol in high-risk cardio-metabolic subjects.
Authors: Camille M Mba; Albert Koulman; Nita G Forouhi; Fumiaki Imamura; Felix Assah; Jean Claude Mbanya; Nick J Wareham Journal: Nutrients Date: 2021-12-30 Impact factor: 5.717
Authors: Ana Nogal; Panayiotis Louca; Xinyuan Zhang; Philippa M Wells; Claire J Steves; Tim D Spector; Mario Falchi; Ana M Valdes; Cristina Menni Journal: Front Microbiol Date: 2021-07-15 Impact factor: 5.640