BMJ Open · 2018 · 27 citations · 23 references
MedicineInternal MedicineClinical Classification SystemsClinical EpidemiologyEarly DetectionMetabolic EvaluationMetabolic HealthMetabolic SyndromeBlood PressureDiagnostic Accuracy StudiesDiagnostic Test Accuracy AppraisalDiagnostic Testing AccuracyMetabolic Disease ScreeningMetabolic Disorder ScreeningMetabolic Syndrome ScreeningNon-invasive Examination
OBJECTIVES: A 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. DESIGN: A diagnostic test accuracy to assess the validity of the method was performed. SETTING: Occupational health services. PARTICIPANTS: The studies were conducted in 2012-2016 on a sample of 60 799 workers from the Balearic Islands (Spain). INTERVENTIONS: automatic interaction detection method). MAIN OUTCOME MEASURES: Anthropometric 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). RESULTS: With 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). CONCLUSIONS: The 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.
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