ArticleBMJ open2018
Validation of a non-invasive method for the early detection of metabolic syndrome: a diagnostic accuracy test in a working population.
Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
- Waist to Height Ratio and Metabolic Syndrome as lung dysfunction predictors.Scientific reports · 2020Trial
- Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome.BMC public health · 2025Article
- Predictive Diagnostic Power of Anthropometric Indicators for Metabolic Syndrome: A Comparative Study in Korean Adults.Journal of clinical medicine · 2025Article
- Capturing metabolic syndrome in low-resource settings: a case study in urban Haiti.Frontiers in endocrinology · 2025Article
- Blood metabolome shows signatures of metabolic dysregulation in obese and overweight subjects that can be predicted by machine learning applied to heart rate variability.Frontiers in molecular biosciences · 2025Article
- Sex Differences in the Associations among Insulin Resistance Indexes with Metabolic Syndrome: A Large Cross-Sectional Study.International journal of endocrinology · 2024Article
- Estimating transformations for evaluating diagnostic tests with covariate adjustment.Statistical methods in medical research · 2023Article
- Remnant cholesterol can identify individuals at higher risk of metabolic syndrome in the general population.Scientific reports · 2023Article
- The Association of Retinal age gap with metabolic syndrome and inflammation.Journal of diabetes · 2023Article
- Article
- Alanine aminotransferase to aspartate aminotransferase ratio and hepatitis B virus on metabolic syndrome: a community-based study.Frontiers in endocrinology · 2022Article
- Diagnostic accuracy of the waist-to-height ratio and other anthropometric indices for metabolically healthy obesity in the working population.Frontiers in nutrition · 2022Article
- Association between serum low-density lipoprotein cholesterol and metabolic syndrome in a working population.Lipids in health and disease · 2021Article
- Waist Circumference and BMI Are Strongly Correlated with MRI-Derived Fat Compartments in Young Adults.Life (Basel, Switzerland) · 2021Article
- An Approach to Early Detection of Metabolic Syndrome through Non-Invasive Methods in Obese Children.Children (Basel, Switzerland) · 2020Article
- Threshold Effects in the Relationship Between Serum Non-High-Density Lipoprotein Cholesterol and Metabolic Syndrome.Diabetes, metabolic syndrome and obesity : targets and therapy · 2019Article
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9 authors.
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Abstract
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 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 χ
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.
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