Validation of a non-invasive method for the early detection of metabolic syndrome: a diagnostic accuracy test in a working population

Manuel Romero-Saldaña, Pedro Tauler, Manuel Vaquero-Abellán, Angel-Arturo López-González, Francisco-José Fuentes-Jiménez, Antoni Aguiló, Carlos Álvarez-Fernández, Guillermo Molina-Recio, Miquel Bennasar-Veny
2018 BMJ Open  
ObjectivesA non-invasive method for the early detection of metabolic syndrome (NIM-MetS) using only waist-to-height ratio (WHtR) and blood pressure (BP) has recently been published, with fixed cut-off values for gender and age. The aim of this study was to validate this method in a large sample of Spanish workers.DesignA diagnostic test accuracy to assess the validity of the method was performed.SettingOccupational health services.ParticipantsThe studies were conducted in 2012–2016 on a sample
more » ... 2–2016 on a sample of 60 799 workers from the Balearic Islands (Spain).InterventionsThe NCEP-ATP III criteria were used as the gold standard. NIM-MetS has been devised using classification trees (the χ2 automatic interaction detection method).Main outcome measuresAnthropometric and biochemical variables to diagnose MetS. Sensitivity, specificity, validity index and Youden Index were determined to analyse the accuracy of the diagnostic test (NIM-MetS).ResultsWith regard to the validation of the method, sensitivity was 54.7%, specificity 94.9% and the Validity Index 91.2%. The cut-off value for WHtR was 0.54, ranging from 0.51 (lower age group) to 0.56 (higher age group). Variables more closely associated with MetS were WHtR (area under the curve (AUC)=0.85; 95% CI 0.84 to 0.86) and systolic BP (AUC=0.79; 95% CI 0.78 to 0.80)). The final cut-off values for the non-invasive method were WHtR ≥0.56 and BP ≥128/80 mm Hg, which includes four levels of MetS risk (very low, low, moderate and high).ConclusionsThe analysed method has shown a high validity index (higher than 91%) for the early detection of MetS. It is a non-invasive method that is easy to apply and interpret in any healthcare setting. This method provides a scale of MetS risk which allows more accurate detection and more effective intervention.
doi:10.1136/bmjopen-2017-020476 fatcat:e67oh7mtoja5li4ac3fi6lydgm