Use of Different Food Classification Systems to Assess the Association between Ultra-Processed Food Consumption and Cardiometabolic Health in an Elderly Population with Metabolic Syndrome (PREDIMED-Plus Cohort)

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dc.contributor.authorMartínez Pérez, Celia
dc.contributor.authorSan Cristobal, Rodrigo
dc.contributor.authorGuallar Castillon, Pilar
dc.contributor.authorMartínez González, Miguel Ángel
dc.contributor.authorSalas Salvadó, Jordi
dc.contributor.authorCorella, Dolores
dc.contributor.authorCastañer, Olga
dc.contributor.authorMartínez, José Alfredo
dc.contributor.authorAlonso Gómez, Ángel M.
dc.contributor.authorWärnberg, Julia
dc.contributor.authorVioque, Jesús
dc.contributor.authorRomaguera, Dora
dc.contributor.authorLópez Miranda, José
dc.contributor.authorEstruch, Ramon
dc.contributor.authorTinahones, Francisco J.
dc.contributor.authorLapetra, José
dc.contributor.authorSerra-Majem, Lluis
dc.contributor.authorBueno Cavanillas, Aurora
dc.contributor.authorTur, Josep A.
dc.contributor.authorSánchez, Vicente Martín
dc.contributor.authorPintó, Xavier
dc.contributor.authorGaforio, José J.
dc.contributor.authorMatía Martín, Pilar
dc.contributor.authorVidal, Josep
dc.contributor.authorVázquez, Clotilde
dc.contributor.authorRos, Emilio
dc.contributor.authorBes Rastrollo, Maira
dc.contributor.authorBabio, Nancy
dc.contributor.authorSorlí, Jose V.
dc.contributor.authorLassale, Camille
dc.contributor.authorPérez Sanz, Beatriz
dc.contributor.authorVaquero Luna, Jessica
dc.contributor.authorBazán, María Julia Ajejas
dc.contributor.authorBarceló Iglesias, María Concepción
dc.contributor.authorKonieczna, Jadwiga
dc.contributor.authorRíos, Antonio García
dc.contributor.authorBernal López, María Rosa
dc.contributor.authorSantos Lozano, José Manuel
dc.contributor.authorToledo, Estefanía
dc.contributor.authorBecerra Tomás, Nerea
dc.contributor.authorPortoles, Olga
dc.contributor.authorZomeño, María Dolores
dc.contributor.authorAbete, Itziar
dc.contributor.authorMoreno Rodríguez, Anai
dc.contributor.authorLecea Juarez, Oscar
dc.contributor.authorNishi, Stephanie K.
dc.contributor.authorMuñoz Martínez, Júlia
dc.contributor.authorOrdovás, José M.
dc.contributor.authorDaimiel, Lidia
dc.date.accessioned2023-06-16T14:21:55Z
dc.date.available2023-06-16T14:21:55Z
dc.date.issued2021-07-20
dc.description.abstractThe association between ultra-processed food (UPF) and risk of cardiometabolic disorders is an ongoing concern. Different food processing-based classification systems have originated discrepancies in the conclusions among studies. To test whether the association between UPF consumption and cardiometabolic markers changes with the classification system, we used baseline data from 5636 participants (48.5% female and 51.5% male, mean age 65.1 ± 4.9) of the PREDIMED-Plus (“PREvention with MEDiterranean DIet”) trial. Subjects presented with overweight or obesity and met at least three metabolic syndrome (MetS) criteria. Food consumption was classified using a 143-item food frequency questionnaire according to four food processing-based classifications: NOVA, International Agency for Research on Cancer (IARC), International Food Information Council (IFIC) and University of North Carolina (UNC). Mean changes in nutritional and cardiometabolic markers were assessed according to quintiles of UPF consumption for each system. The association between UPF consumption and cardiometabolic markers was assessed using linear regression analysis. The concordance of the different classifications was assessed with intra-class correlation coefficients (ICC3, overall = 0.51). The highest UPF consumption was obtained with the IARC classification (45.9%) and the lowest with NOVA (7.9%). Subjects with high UPF consumption showed a poor dietary profile. We detected a direct association between UPF consumption and BMI (p = 0.001) when using the NOVA system, and with systolic (p = 0.018) and diastolic (p = 0.042) blood pressure when using the UNC system. Food classification methodologies markedly influenced the association between UPF consumption and cardiometabolic risk markers.
dc.description.facultyFac. de Enfermería, Fisioterapia y Podología
dc.description.refereedTRUE
dc.description.sponsorshipUnión Europea. FP7
dc.description.sponsorshipMinisterio de Ciencia e Innovación (MICINN)
dc.description.sponsorshipInstituto de Salud Carlos III (ISCIII)/CIBEROBN/FEDER
dc.description.sponsorshipInstituto de Salud Carlos III (ISCIII)/CIBEROBN/FEDER
dc.description.sponsorshipInstituto de Salud Carlos III (ISCIII)/CIBEROBN/FEDER
dc.description.sponsorshipComunidad de Madrid/FEDER
dc.description.sponsorshipRecercaixa
dc.description.sponsorshipJunta de Andalucía
dc.description.sponsorshipGeneralitat Valenciana
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/71657
dc.identifier.doi10.3390/nu13072471
dc.identifier.issn2072-6643
dc.identifier.officialurlhttps://doi.org/10.3390/nu13072471
dc.identifier.relatedurlhttps://www.mdpi.com/2072-6643/13/7/2471/htm
dc.identifier.urihttps://hdl.handle.net/20.500.14352/4830
dc.issue.number7
dc.journal.titleNutrients
dc.language.isoeng
dc.page.initial2471
dc.publisherMPDI
dc.relation.projectIDPREDIMED PLUS (340918)
dc.relation.projectIDMETHYL-UP (RTI2018-095569-B-I00); (FJC2018-038168- I; FJC2018-036016-I)
dc.relation.projectID(PI13/00673, PI13/00492, PI13/00272, PI13/01123, PI13/00462, PI13/00233, PI13/02184, PI13/00728, PI13/01090, PI13/01056, PI14/01722, PI14/00636, PI14/00618, PI14/00696, PI14/01206, PI14/01919, PI14/00853, PI14/01374, PI14/00972, PI14/00728, PI14/01471)
dc.relation.projectID(PI16/00473, PI16/00662, PI16/01873, PI16/01094, PI16/00501, PI16/00533, PI16/00381, PI16/00366, PI16/01522, PI16/01120, PI17/00764, PI17/01183, PI17/00855, PI17/01347, PI17/00525, PI17/01827, PI17/00532, PI17/00215, PI17/01441, PI17/00508, PI17/01732)
dc.relation.projectID(PI17/00926, PI19/00957, PI19/00386, PI19/00309, PI19/01032, PI19/00576, PI19/00017, PI19/01226, PI19/00781, PI19/01560, PI19/01332)
dc.relation.projectID(PEJD-2019- POST/SAL-15892)
dc.relation.projectID(grant number 2013ACUP00194)
dc.relation.projectID(PI0458/2013; PS0358/2016; PI0137/2018)
dc.relation.projectIDPROMETEO/2017/017
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/es/
dc.subject.keywordcardiometabolic risk
dc.subject.keywordclassification systems
dc.subject.keyworddiet
dc.subject.keywordfood processing
dc.subject.keywordIARC
dc.subject.keywordIFIC
dc.subject.keywordNOVA
dc.subject.keywordPREDIMED-Plus
dc.subject.keywordultra-processed food
dc.subject.keywordUNC
dc.subject.ucmDietética y nutrición (Medicina)
dc.subject.ucmEndocrinología
dc.subject.ucmNutrición
dc.subject.unesco3206 Ciencias de la Nutrición
dc.subject.unesco3205.02 Endocrinología
dc.subject.unesco3206 Ciencias de la Nutrición
dc.titleUse of Different Food Classification Systems to Assess the Association between Ultra-Processed Food Consumption and Cardiometabolic Health in an Elderly Population with Metabolic Syndrome (PREDIMED-Plus Cohort)
dc.typejournal article
dc.volume.number13
dspace.entity.typePublication
relation.isAuthorOfPublication066f66b1-aba0-451a-91f0-7e34a3b92cee
relation.isAuthorOfPublication.latestForDiscovery066f66b1-aba0-451a-91f0-7e34a3b92cee
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