Percentage of body fat and fat mass as screening tool in prediction metabolic syndrome in Colombian University Students
Metadatos
Mostrar el registro completo del ítemAutor
Ramírez Vélez, Robinson; Correa-Bautista, Jorge Enrique; Sanders-Tordecilla, Alejandra; Ojeda-Pardo, Mónica Liliana; Cobo-Mejía, Elisa Andrea; Castellanos-Vega, Rocío del Pilar; Schmidt Río Valle, Jacqueline; González-Ruiz, KatherineEditorial
MDPI
Materia
Obesity Adiposity Fat mass Metabolic syndrome Students Colombia
Fecha
2017-09-13Referencia bibliográfica
Ramírez-Vélez, R.; et al. Percentage of body fat and fat mass as screening tool in prediction metabolic syndrome in Colombian University Students. Nutrients, 9(9): 1009 (2017). [http://hdl.handle.net/10481/47557]
Patrocinador
This 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 N° FIUR DN-BG001), and Universidad de Boyacá (Code N° RECT 60).Resumen
High 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.