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Comparison of Three Adiposity Indexes and Cutoff Values to Predict Metabolic Syndrome among University Students

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dc.creatorCorrea-Bautista J.E.spa
dc.creatorGonzález-Ruíz K.spa
dc.creatorVivas A.spa
dc.creatorTriana-Reina H.R.spa
dc.creatorMartínez-Torres J.spa
dc.creatorPrieto-Benavides D.H.spa
dc.creatorCarrillo H.A.spa
dc.creatorRamos-Sepúlveda J.A.spa
dc.creatorAfanador-Rodríguez M.I.spa
dc.creatorVilla-González E.spa
dc.creatorGarcía-Hermoso A.spa
dc.creatorRamírez-Vélez R.spa
dc.date.accessioned2020-05-25T23:57:02Z
dc.date.available2020-05-25T23:57:02Z
dc.date.created2017spa
dc.description.abstractPurpose: Obesity and high body fat are related to diabetes and metabolic syndrome (MetS) in all ethnic groups. Based on the International Diabetes Federation (IDF) definition of MetS, the aim of the present study was to compare body adiposity indexes (BAIs) and to assess their various cutoff values for the prediction of MetS in university students from Colombia. Methods: A cross-sectional study was conducted on 886 volunteers (51.9% woman; age mean 21.4 years). Anthropometric characteristics (height, weight, waist circumference [WC], and hip circumference [HC]) were measured, and body composition was assessed by bioelectrical impedance analysis. MetS was defined as including ?3 of the metabolic abnormalities (WC, high-density lipoprotein cholesterol [HDL-C], triglycerides, fasting glucose, and systolic and diastolic blood pressure [BP]) in the definition provided by the IDF. The BAIs (i.e., BAI-HC [BAI], BAI-WC [BAI-w], and [BAI-p]) were calculated from formulas taking into account, height, weight, and WC, and for the visceral adiposity indexes, a formula, including WC, HDL-C, and triglycerides, was used. Results: The overall prevalence of MetS was 5.9%, higher in men than in women. The most prevalent components were low HDL-C, high triglyceride levels, WC, and BP levels. The receiver operating characteristic curves analysis showed that BAI, BAI-w, and BAI-p could be useful tools to predict MetS in this population. Conclusion: For women, the optimal MetS threshold was found to be 30.34 (area under curve [AUC] = 0.720-0.863), 19.10 (AUC = 0.799-0.925), and 29.68 (AUC = 0.779-0.901), for BAI, BAI-w, and BAI-p, respectively. For men, the optimal MetS threshold was found to be 27.83 (AUC = 0.726-0.873), 21.48 (AUC = 0.755-0.906), and 26.18 (AUC = 0.766-0.894), for BAI, BAI-w, and BAI-p, respectively. The three indexes can be useful tools to predict MetS according to the IDF criteria in university students from Colombia. Data on larger samples are needed. © Copyright 2017, Mary Ann Liebert, Inc. 2017.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1089/met.2017.0016
dc.identifier.issn15404196
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/22585
dc.language.isoengspa
dc.publisherMary Ann Liebert Inc.spa
dc.relation.citationEndPage370
dc.relation.citationIssueNo. 7
dc.relation.citationStartPage363
dc.relation.citationTitleMetabolic Syndrome and Related Disorders
dc.relation.citationVolumeVol. 15
dc.relation.ispartofMetabolic Syndrome and Related Disorders, ISSN:15404196, Vol.15, No.7 (2017); pp. 363-370spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85028577180&doi=10.1089%2fmet.2017.0016&partnerID=40&md5=b5f4d7f560832c514553cf63cde63d58spa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.keywordGlucosespa
dc.subject.keywordHigh density lipoprotein cholesterolspa
dc.subject.keywordLow density lipoprotein cholesterolspa
dc.subject.keywordTriacylglycerolspa
dc.subject.keywordHigh density lipoprotein cholesterolspa
dc.subject.keywordTriacylglycerolspa
dc.subject.keywordAdultspa
dc.subject.keywordAnalysisspa
dc.subject.keywordAnthropometric parametersspa
dc.subject.keywordAnthropometryspa
dc.subject.keywordBioelectrical impedance analysisspa
dc.subject.keywordBody adiposity indexspa
dc.subject.keywordBody compositionspa
dc.subject.keywordBody heightspa
dc.subject.keywordBody massspa
dc.subject.keywordBody weightspa
dc.subject.keywordCholesterol blood levelspa
dc.subject.keywordCohort analysisspa
dc.subject.keywordColombiaspa
dc.subject.keywordColombianspa
dc.subject.keywordComparative effectivenessspa
dc.subject.keywordControlled studyspa
dc.subject.keywordCorrelation coefficientspa
dc.subject.keywordCross-sectional studyspa
dc.subject.keywordDiagnostic accuracyspa
dc.subject.keywordDiagnostic test accuracy studyspa
dc.subject.keywordDiastolic blood pressurespa
dc.subject.keywordDisease associationspa
dc.subject.keywordFemalespa
dc.subject.keywordGlucose blood levelspa
dc.subject.keywordHip circumferencespa
dc.subject.keywordHumanspa
dc.subject.keywordMajor clinical studyspa
dc.subject.keywordMalespa
dc.subject.keywordMetabolic syndrome xspa
dc.subject.keywordNormal valuespa
dc.subject.keywordObesityspa
dc.subject.keywordPredictive valuespa
dc.subject.keywordPrevalencespa
dc.subject.keywordPriority journalspa
dc.subject.keywordReviewspa
dc.subject.keywordSensitivity and specificityspa
dc.subject.keywordSex differencespa
dc.subject.keywordSystolic blood pressurespa
dc.subject.keywordTriacylglycerol levelspa
dc.subject.keywordUniversity studentspa
dc.subject.keywordVisceral adiposity indexspa
dc.subject.keywordWaist circumferencespa
dc.subject.keywordWaist hip ratiospa
dc.subject.keywordWaist to height ratiospa
dc.subject.keywordAdolescentspa
dc.subject.keywordArea under the curvespa
dc.subject.keywordBloodspa
dc.subject.keywordComparative studyspa
dc.subject.keywordDiastolespa
dc.subject.keywordInflammationspa
dc.subject.keywordIntra-abdominal fatspa
dc.subject.keywordMetabolic syndrome xspa
dc.subject.keywordPathologyspa
dc.subject.keywordQuestionnairespa
dc.subject.keywordReceiver operating characteristicspa
dc.subject.keywordStudentspa
dc.subject.keywordSystolespa
dc.subject.keywordUniversityspa
dc.subject.keywordWaist circumferencespa
dc.subject.keywordYoung adultspa
dc.subject.keywordAdiposityspa
dc.subject.keywordAdolescentspa
dc.subject.keywordAdultspa
dc.subject.keywordAnthropometryspa
dc.subject.keywordArea under curvespa
dc.subject.keywordBlood glucosespa
dc.subject.keywordBody compositionspa
dc.subject.keywordCholesterol, hdlspa
dc.subject.keywordColombiaspa
dc.subject.keywordCross-sectional studiesspa
dc.subject.keywordDiastolespa
dc.subject.keywordFemalespa
dc.subject.keywordHumansspa
dc.subject.keywordInflammationspa
dc.subject.keywordIntra-abdominal fatspa
dc.subject.keywordMalespa
dc.subject.keywordMetabolic syndromespa
dc.subject.keywordObesityspa
dc.subject.keywordRoc curvespa
dc.subject.keywordStudentsspa
dc.subject.keywordSurveys and questionnairesspa
dc.subject.keywordSystolespa
dc.subject.keywordTriglyceridesspa
dc.subject.keywordUniversitiesspa
dc.subject.keywordWaist circumferencespa
dc.subject.keywordWaist-hip ratiospa
dc.subject.keywordYoung adultspa
dc.subject.keywordDyslipidemiaspa
dc.subject.keywordMetabolic syndromespa
dc.subject.keywordObesityspa
dc.titleComparison of Three Adiposity Indexes and Cutoff Values to Predict Metabolic Syndrome among University Studentsspa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaArtículospa
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