dc.contributor.author | Martinez-Perez, Celia |
dc.contributor.author | Castañer, Olga |
dc.contributor.author | Lassale, Camille |
dc.contributor.author | Zomeño Fajardo, Maria Dolores |
dc.contributor.author | Muñoz-Martínez, Júlia |
dc.contributor.author | Daimiel, Lidia |
dc.date.accessioned | 2022-07-05T06:24:16Z |
dc.date.available | 2022-07-05T06:24:16Z |
dc.date.issued | 2021 |
dc.identifier.citation | Martinez-Perez C, San-Cristobal R, Guallar-Castillon P, Martínez-González MÁ, Salas-Salvadó J, Corella D, et al. 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). Nutrients. 2021 Jul 20; 13(7): 2471. DOI: 10.3390/nu13072471 |
dc.identifier.issn | 2072-6643 |
dc.identifier.uri | http://hdl.handle.net/10230/53676 |
dc.description.abstract | The 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.sponsorship | The PREDIMED-Plus trial was supported by the European Research Council (Advanced Research grant 2014–2019; agreement #340918; granted to M.Á.M.-G.); the official Spanish institutions for funding scientific biomedical research, CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN) and Instituto de Salud Carlos III (ISCIII) through the Fondo de Investigación para la Salud (FIS) which is co-funded by the European Regional Development Fund (coordinated FIS projects led by J.S-S. and J.V., including the following projects: 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, 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, PI17/00926, PI19/00957, PI19/00386, PI19/00309, PI19/01032, PI19/00576, PI19/00017, PI19/01226, PI19/00781, PI19/01560, PI19/01332), and the Especial Action Project “Implementación y evaluación de una intervención intensiva sobre la actividad física Cohorte PREDIMED-Plus” (J.S.-S.); the Recercaixa (grant number 2013ACUP00194) (J.S.-S.). Moreover, J.S-S. gratefully acknowledges the financial support by ICREA under the ICREA Academia program; the SEMERGEN grant; Department of Health of the Government of Navarra (61/2015), the Fundació La Marató de TV (Ref. 201630.10); the AstraZeneca Young Investigators Award in Category of Obesity and T2D 2017 (D.R.); grants from the Consejería de Salud de la Junta de Andalucía (PI0458/2013; PS0358/2016; PI0137/2018), the PROMETEO/2017/017 grant from the Generalitat Valenciana, the SEMERGEN grant; grant of support to research groups 35/2011 (Balearic Islands Government; FEDER funds) (J.A.T.). R.S.-C. acknowledges financial support from the Juan de la Cierva Program Training Grants of the Spanish State Research Agency of the Spanish Ministerio de Ciencia e Innovación y Ministerio de Universidades (FJC2018-038168- I). N.B.-T. acknowledges financial support from the Juan de la Cierva Formación Program Training Grants of the Spanish State Research Agency of the Spanish Ministerio de Ciencia e Innovación y Ministerio de Universidades (FJC2018-036016-I). M.R.B.-L. was supported by “Miguel Servet Type I” program (CP15/00028) from the ISCIII-Madrid (Spain), cofinanced by the Fondo Europeo de Desarrollo Regional-FEDER. S.K.N. acknowledges financial support from the Canadian Institute for Health Research, CIHR Fellowship. J.K. was supported by the ‘FOLIUM’ programme within the FUTURMed project from the Fundación Instituto de Investigación Sanitaria Illes Balears (financed by 2017 annual plan of the sustainable tourism tax and at 50% with charge to the ESF Operational Program 2014–2020 of the Balearic Islands. C.M.-P. was financially supported by a joint grant from the Community of Madrid and the European Social Fund (grant PEJD-2019-POST/SAL-15892). The METHYL-UP project was supported by the Spanish Ministry of Science and Innovation (RTI2018-095569-B-I00, Programa de Proyectos Orientados a los Retos de la Sociedad “Projects Toward Society Challenges Program”). |
dc.format.mimetype | application/pdf |
dc.language.iso | eng |
dc.publisher | MDPI |
dc.rights | Copyright © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0 |
dc.title | 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) |
dc.type | info:eu-repo/semantics/article |
dc.identifier.doi | http://dx.doi.org/10.3390/nu13072471 |
dc.subject.keyword | IARC |
dc.subject.keyword | IFIC |
dc.subject.keyword | NOVA |
dc.subject.keyword | PREDIMED-Plus |
dc.subject.keyword | UNC |
dc.subject.keyword | Cardiometabolic risk |
dc.subject.keyword | Classification systems |
dc.subject.keyword | Diet |
dc.subject.keyword | Food processing |
dc.subject.keyword | Ultra-processed food |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/FP7/340918 |
dc.rights.accessRights | info:eu-repo/semantics/openAccess |
dc.type.version | info:eu-repo/semantics/publishedVersion |