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

Título de la revista
Correa-Bautista J.E.
González-Ruíz K.
Vivas A.
Triana-Reina H.R.
Martínez-Torres J.
Prieto-Benavides D.H.
Carrillo H.A.
Ramos-Sepúlveda J.A.
Afanador-Rodríguez M.I.
Villa-González E.



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Título del volumen
Mary Ann Liebert Inc.


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Purpose: 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.
Palabras clave
Glucose , High density lipoprotein cholesterol , Low density lipoprotein cholesterol , Triacylglycerol , High density lipoprotein cholesterol , Triacylglycerol , Adult , Analysis , Anthropometric parameters , Anthropometry , Bioelectrical impedance analysis , Body adiposity index , Body composition , Body height , Body mass , Body weight , Cholesterol blood level , Cohort analysis , Colombia , Colombian , Comparative effectiveness , Controlled study , Correlation coefficient , Cross-sectional study , Diagnostic accuracy , Diagnostic test accuracy study , Diastolic blood pressure , Disease association , Female , Glucose blood level , Hip circumference , Human , Major clinical study , Male , Metabolic syndrome x , Normal value , Obesity , Predictive value , Prevalence , Priority journal , Review , Sensitivity and specificity , Sex difference , Systolic blood pressure , Triacylglycerol level , University student , Visceral adiposity index , Waist circumference , Waist hip ratio , Waist to height ratio , Adolescent , Area under the curve , Blood , Comparative study , Diastole , Inflammation , Intra-abdominal fat , Metabolic syndrome x , Pathology , Questionnaire , Receiver operating characteristic , Student , Systole , University , Waist circumference , Young adult , Adiposity , Adolescent , Adult , Anthropometry , Area under curve , Blood glucose , Body composition , Cholesterol, hdl , Colombia , Cross-sectional studies , Diastole , Female , Humans , Inflammation , Intra-abdominal fat , Male , Metabolic syndrome , Obesity , Roc curve , Students , Surveys and questionnaires , Systole , Triglycerides , Universities , Waist circumference , Waist-hip ratio , Young adult , Dyslipidemia , Metabolic syndrome , Obesity