Percentage of body fat and fat mass index as a screening tool for metabolic syndrome prediction in colombian university students

dc.contributor.authorRamírez Vélez, Robinson
dc.contributor.authorCorrea Bautista, Jorge Enrique
dc.contributor.authorSanders-Tordecilla, Alejandra
dc.contributor.authorOjeda Pardo, Mónica Liliana
dc.contributor.authorCobo-Mejía, Elisa Andrea
dc.contributor.authorCastellanos-Vega, Rocío del Pilar
dc.contributor.authorGarcía Hermoso, Antonio
dc.contributor.authorGonzález-Jiménez, Emilio
dc.contributor.authorSchmidt Río-Valle, Jacqueline
dc.contributor.authorGonzález Ruiz, Katherine
dc.contributor.departmentCiencias de la Saludes_ES
dc.contributor.departmentOsasun Zientziakeu
dc.date.accessioned2024-10-01T07:58:25Z
dc.date.available2024-10-01T07:58:25Z
dc.date.issued2017
dc.date.updated2024-10-01T07:47:59Z
dc.description.abstractHigh body fat is related to metabolic syndrome (MetS) in all ethnic groups. Based on the International Diabetes Federation (IDF) definition of MetS, the aim of this study was to explore thresholds of body fat percentage (BF%) and fat mass index (FMI) for the prediction of MetS among Colombian University students. A cross-sectional study was conducted on 1687 volunteers (63.4% women, mean age = 20.6 years). Weight, waist circumference, serum lipids indices, blood pressure, and fasting plasma glucose were measured. Body composition was measured by bioelectrical impedance analysis (BIA) and FMI was calculated. MetS was defined as including more than or equal to three of the metabolic abnormalities according to the IDF definition. Receiver operating curve (ROC) analysis was used to determine optimal cut-off points for BF% and FMI in relation to the area under the curve (AUC), sensitivity, and specificity in both sexes. The overall prevalence of MetS was found to be 7.7%, higher in men than women (11.1% vs. 5.3%; p < 0.001). BF% and FMI were positively correlated to MetS components (p < 0.05). ROC analysis indicated that BF% and FMI can be used with moderate accuracy to identify MetS in university-aged students. BF% and FMI thresholds of 25.55% and 6.97 kg/m2 in men, and 38.95% and 11.86 kg/m2 in women, were found to be indicative of high MetS risk. Based on the IDF criteria, both indexes¿ thresholds seem to be good tools to identify university students with unfavorable metabolic profiles.en
dc.description.sponsorshipThis study was part of the project entitled 'Body Adiposity Index and Biomarkers of Endothelial and Cardiovascular Health in Adults', which was funded by Centre for Studies on Measurement of Physical Activity, School of Medicine and Health Sciences, Universidad del Rosario (Code Nº FIUR DN-BG001), and Universidad de Boyacá (Code Nº RECT 60). The funder had no role in the study design, data collection, data analysis and interpretation, the preparation of the manuscript, or the decision to publish.
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRamírez-Vélez, R., Correa-Bautista, J. E., Sanders-Tordecilla, A., Ojeda-Pardo, M. L., Cobo-Mejía, E. A., Castellanos-Vega, R. D. P., García-Hermoso, A., González-Jiménez, E., Schmidt-RioValle, J., González-Ruíz, K. (2017) Percentage of body fat and fat mass index as a screening tool for metabolic syndrome prediction in colombian university students. Nutrients, 9(9), 1-13. https://doi.org/10.3390/nu9091009
dc.identifier.doi10.3390/nu9091009
dc.identifier.issn2072-6643
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/51897
dc.language.isoeng
dc.publisherMDPI
dc.relation.ispartofNutrients, 9(9), 1-13
dc.relation.publisherversionhttps://doi.org/10.3390/nu9091009
dc.rights© 2017 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)
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectAdiposityen
dc.subjectFat massen
dc.subjectMetabolic syndromeen
dc.subjectObesityen
dc.titlePercentage of body fat and fat mass index as a screening tool for metabolic syndrome prediction in colombian university studentsen
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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