Publication:
Muscle strength cut-offs for the detection of metabolic syndrome in a nonrepresentative sample of collegiate students from Colombia

dc.contributor.authorGarcía Hermoso, Antonio
dc.contributor.authorTordecilla Sanders, Alejandra
dc.contributor.authorCorrea Bautista, Jorge Enrique
dc.contributor.authorPeterson, Mark Dean
dc.contributor.authorIzquierdo Redín, Mikel
dc.contributor.authorQuino Ávila, Aura Cristina
dc.contributor.authorSandoval Cuellar, Carolina
dc.contributor.authorGonzález Ruiz, Katherine
dc.contributor.authorRamírez Vélez, Robinson
dc.contributor.departmentCiencias de la Saludes_ES
dc.contributor.departmentOsasun Zientziakeu
dc.date.accessioned2019-08-14T11:21:26Z
dc.date.available2019-08-14T11:21:26Z
dc.date.issued2018
dc.description.abstractBackground: Evidence shows an association between grip strength and health; however, grip strength cut-offs for the detection of metabolic syndrome (MetS) in Latin American populations are scarce. The purpose of this study was to determine cut-offs of normalized grip strength (NGS) for the detection of MetS in a large nonrepresentative sample of a collegiate student population from Colombia. Methods: A total of 1795 volunteers (61.4% female, age = 20.68 ± 3.10 years, mean ± SD), ranging between 18 and 30 years of age participated in the study. Strength was estimated using a handheld dynamometer and normalized to body mass (handgrip strength (kg)/body mass (kg)). Anthropometrics, serum lipids indices, blood pressure, and fasting plasma glucose were measured. Body composition was measured by bioelectrical impedance analysis. MetS was defined as including ≥3 of the 5 metabolic abnormalities according to the International Diabetes Federation definition. A metabolic risk score was computed from the following components: waist circumference, triglycerides, high-density lipoprotein cholesterol, glucose, and systolic and diastolic blood pressure. Results: Receiver operating curve analysis showed significant discriminatory accuracy of NGS in identifying the thresholds and risk categories. Lower strength was associated with increased prevalence of MetS. In males, weak, intermediate, and strong NGS values at these points were <0.466, 0.466–0.615, >0.615, respectively. In females, these cut-off points were <0.332, 0.332–0.437, >0.437, respectively. Conclusion: Our sex-specific cut-offs of NGS could be incorporated into a clinical setting for identifying college students at cardiometabolic disease risk.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 the Centre for Studies on Measurement of Physical Activity, School of Medicine and Health Sciences, Universidad del Rosario (Code N. FIUR DN-BG001) and Universidad de Boyacá (Code N. RECT 60).en
dc.format.extent8 p.
dc.format.mimetypeapplication/pdfen
dc.identifier.doi10.1016/j.jshs.2018.09.004
dc.identifier.issn2095-2546
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/34338
dc.language.isoengen
dc.publisherElsevieren
dc.relation.ispartofJournal of Sport and Health Scienceen
dc.relation.publisherversionhttps://doi.org/10.1016/j.jshs.2018.09.004
dc.rights© 2018. This is an open access article under the CC BY-NC-ND license.en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCardiometabolic risken
dc.subjectMuscular fitnessen
dc.subjectReceiver operating characteristic curveen
dc.subjectThresholdsen
dc.titleMuscle strength cut-offs for the detection of metabolic syndrome in a nonrepresentative sample of collegiate students from Colombiaen
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.type.versionVersión publicada / Argitaratu den bertsioaes
dspace.entity.typePublication
relation.isAuthorOfPublicationef73585d-4750-4f56-9d4f-0d759232dbca
relation.isAuthorOfPublicationd0c2c11e-01d0-46ff-93b4-36b11beaf269
relation.isAuthorOfPublication.latestForDiscoveryef73585d-4750-4f56-9d4f-0d759232dbca

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