ArticleThe Journal of international medical research2024
Predictive ability of anthropometric indices for risk of developing metabolic syndrome: a cross-sectional study.
Article in The Journal of international medical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Predicting metabolic syndrome in Iranian adults using artificial neural networks: a comparative analysis with logistic regression based on demographic, lifestyle, and clinical indicators.BMC research notes · 2026Article
- Gender-Specific Predictive Utility of Twelve Anthropometric Indices for Metabolic Syndrome in Chinese Lahu Adults with Dyslipidemia.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Article
- Obesity indices as predictors of metabolic syndrome: 1-year findings from a Peruvian cohort of private educational institution workers.Therapeutic advances in endocrinology and metabolism · 2026Article
- Predictors of Metabolic Syndrome in Polish Women-The Role of Body Composition and Sociodemographic Factors.Journal of clinical medicine · 2025Article
- A comment on "The impact of metabolic heterogeneity of obesity and transitions on cardiovascular disease incidence in Chinese middle-aged and elderly population: a nationwide prospective cohort study".Journal of translational medicine · 2025Article
- Association of Relative Fat Mass and Conicity Index with the Risk of Hyperuricemia in Obese Women with PCOS: A Cross-Sectional Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- Association between relative fat mass and colorectal cancer: a cross-sectional study.Frontiers in nutrition · 2025Article
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Authors and funding
5 authors.
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Abstract
objectiveTo determine the discriminatory ability of different anthropometric indicators of body fat percentage for diagnosing metabolic syndrome (MetS) in a Peruvian sample.
methodsThis was a cross-sectional, non-experimental, diagnostic accuracy study. Anthropometric and biochemical data for 948 participants were analyzed. Waist circumference (WC), body mass index, relative fat mass (RFM), conicity index, body roundness index (BRI), waist-to-height ratio (WHtR), and A Body Shape Index were assessed for their MetS discriminatory ability. The National Cholesterol Education Program's Adult Treatment Panel III criteria were used to diagnose MetS. Receiver operating characteristic curves and area under the curve (AUC) were used to determine the predictive power of each anthropometric measurement to diagnose MetS.
resultsIn both sexes, RFM, BRI, and WHtR showed the same predictive ability to diagnose MetS. In women, indicators incorporating WC showed high discriminatory ability: RFM, BRI, and WHtR (all AUC: 0.869, 95% confidence interval [CI]: 0.828-0.910). In men, WC had the highest AUC (0.829, 95% CI: 0.793-0.866).
conclusionsIn both sexes, RFM, WC, BRI, and WHtR were the best predictors of MetS diagnosis. This is the first study to identify RFM as a potentially useful clinical predictor of MetS in a Peruvian sample of educational workers.
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