Fat-to-muscle ratio: a new anthropometric indicator as a screening tool for metabolic syndrome in young Colombian people

dc.contributor.authorRamírez Vélez, Robinson
dc.contributor.authorCarrillo Arango, Hugo Alejandro
dc.contributor.authorCorrea Bautista, Jorge Enrique
dc.contributor.authorSchmidt Río-Valle, Jacqueline
dc.contributor.authorGonzález Jiménez, Emilio
dc.contributor.authorCorrea Rodríguez, María
dc.contributor.authorGonzález Ruiz, Katherine
dc.contributor.authorGarcía Hermoso, Antonio
dc.contributor.departmentCiencias de la Saludes_ES
dc.contributor.departmentOsasun Zientziakeu
dc.date.accessioned2024-10-01T09:53:28Z
dc.date.available2024-10-01T09:53:28Z
dc.date.issued2018
dc.date.updated2024-10-01T09:48:26Z
dc.description.abstractFat-to-muscle ratio has been proposed as an alternative approach for assessing body fat. The objective of this study was to explore fat-to-muscle ratio thresholds in metabolic syndrome (MetS) diagnosis; it was hypothesised that the fat-to-muscle ratio is a good predictive indicator of MetS in a large population of young Colombian adults. For this purpose, a cross-sectional study was conducted on 1416 subjects (66.6% female), aged from 18.1 to 25.1. As part of the study, measurements of the subjects' anthropometric indicators, serum lipid indices, blood pressure, and fasting plasma glucose were taken. Body composition was measured through bioelectrical impedance analysis (BIA). A new variable (ratio of fat mass to muscle mass, in kg) was calculated. Following the International Diabetes Federation (IDF) definition, MetS includes three or more metabolic abnormalities. Receiver operating characteristic (ROC) curves and logistic regression determined the discriminatory ability of the fat-to-muscle ratio to predict MetS. According to the IDF, the best fat-to-muscle ratio cut-off point for detecting MetS in men was 0.225 kg, with an area under the curve (AUC) of 0.83, sensitivity of 80%, and specificity of 70%. For women, the fat-to-muscle ratio cut-off point was 0.495 kg, the AUC was 0.88, and the sensitivity and specificity were 82% and 80%, respectively. In conclusion, our results showed that the fat-to-muscle ratio cut-off points from ROC analyses demonstrate good discriminatory power for detecting MetS in young Colombian adults.en
dc.description.sponsorshipThis research was funded by the Centre for Studies on Measurement of Physical Activity, School of Medicine and Health Sciences, Universidad del Rosario grant number [Code Nº FIUR DN-BG001].
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRamírez-Vélez, R., Carrillo, H. A., Correa-Bautista, J. E., Schmidt-RioValle, J., González-Jiménez, E., Correa-Rodríguez, M., González-Ruíz, K., García-Hermoso, A. (2018) Fat-to-muscle ratio: a new anthropometric indicator as a screening tool for metabolic syndrome in young colombian people. Nutrients, 10(8), 1-11. https://doi.org/10.3390/nu10081027
dc.identifier.doi10.3390/nu10081027
dc.identifier.issn2072-6643
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/51911
dc.language.isoeng
dc.publisherMDPI
dc.relation.ispartofNutrients, 10(8), 1-11
dc.relation.publisherversionhttps://doi.org/10.3390/nu10081027
dc.rights© 2018 by the authors. License MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectFat massen
dc.subjectLatin-americansen
dc.subjectMetabolic syndromeen
dc.subjectMuscle massen
dc.subjectYoung adultsen
dc.titleFat-to-muscle ratio: a new anthropometric indicator as a screening tool for metabolic syndrome in young Colombian peopleen
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication
relation.isAuthorOfPublicationd0c2c11e-01d0-46ff-93b4-36b11beaf269
relation.isAuthorOfPublicatione84ae68a-fa4a-4e00-be27-bedfffc8612e
relation.isAuthorOfPublication.latestForDiscoveryd0c2c11e-01d0-46ff-93b4-36b11beaf269

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