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Revista Española de Nutrición Humana y Dietética

versión On-line ISSN 2174-5145versión impresa ISSN 2173-1292


ALCOCER OLACIREGUI, Adalgisa Esther; VARGAS MORANTH, Rusvelt Franklin  y  NAVARRO LECHUGA, Edgar. Area under the ROC curve of Body fat percentage to assess Metabolic syndrome in adults from Barranquilla, Colombia. Rev Esp Nutr Hum Diet [online]. 2017, vol.21, n.4, pp.351-359. ISSN 2174-5145.


The aim of the present work was to determine the relationship between body fat and Metabolic Syndrome (MS) in adults of a Colombian Caribbean locality using ROC curves.

Material and Methods:

A cross-sectional study was carried out with 552 adults aged 20 to 64 years, with complete information on: lipid profile, glycemia and anthropometric measurements: weight, height, blood pressure, waist circumference and skinfolds. Body fat percentage was calculated by means of Siri, Brozeck and Lean equations and the presence of MS was determined through 4 consensuses: AHA, ATP III, IDF and Harmonized. To compare body fat averages according to these, Student’s T and/or Mann Whitney U were used. ROC curve analysis was used to determine cut-off points of body fat to determine SM.


Body fat means were higher in subjects with MS regardless of the method used (p<0.05). The areas under the ROC curve ranged between 63% and 76.9%, with sensitivities between 50% and 85%, and specificities between 51% and 78%. The highest value of the area under the curve (0.77; cut-off point: 37.1, sensitivity: 60.8, specificity: 78.8%) was obtained by Lean-waist and the consensus of AHA and using Siri and the Harmonized consensus obtained the lowest value (0.63; cut-off point: 28.5, sensitivity: 80%, specificity: 42.5%).


The analysis of ROC curves allows identifying the relationship between body fat and metabolic syndrome. It could be used as a screening test, taking into account that the values of sensitivity and specificity depend on the anthropometric measurements and the equations used.

Palabras clave : Metabolic Syndrome; Adipose Tissue; ROC Curve; Mass Screening.

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