Key result
Anthropometric indices linked to ~14% higher odds of metabolic syndrome.
Why the study?
Do anthropometric indices predict metabolic syndrome in college students?
Cross-Sectional (n=330)
No
Do anthropometric indices predict metabolic syndrome in college students?
Odds Ratio: 1.14
p-value: p=<0.001
Simple anthropometric measurements like waist circumference and waist-to-height ratio serve as practical, low-cost surrogate markers for early cardiometabolic risk stratification.
Early identification of cardiometabolic risk and metabolic dysregulation is essential for effective prevention, particularly in populations with limited access to biochemical testing. Anthropometric indices represent practical, low-cost tools for preliminary risk stratification; however, population-specific thresholds remain insufficiently defined. This study aimed to establish sex-specific cut-off points for selected anthropometric indices as surrogate markers of metabolic syndrome and to evaluate their diagnostic performance in a college student population. A cross-sectional study was conducted on 330 college students (138 males, 192 females) aged 18–59 years. Anthropometric measurements (body mass, height, and waist circumference) were used to calculate a body shape index (ABSI), body roundness index (BRI), waist circumference (WC), and waist-to-height ratio (WHtR). Metabolic parameters, including fasting glucose, total cholesterol, HDL-C, LDL-C, triglycerides, and blood pressure, were assessed. Receiver operating characteristic (ROC) curve analysis was applied to determine optimal cut-off values based on sensitivity and specificity. Logistic regression models were used to evaluate the discriminatory ability of anthropometric indices for detecting metabolic syndrome. Sex-specific thresholds were identified for all indices. In females, optimal cut-off values were ABSI > 0.073, BRI > 1.81, WC > 87.8 cm, and WHtR > 0.52, while in males they were ABSI > 0.079, BRI > 3.42, WC > 90 cm, and WHtR > 0.50. Anthropometric indices showed a significant association with metabolic syndrome (total sample: χ 2 = 70.7, R 2 = 0.410, OR = 1.14; females: χ 2 = 44.1, R 2 = 0.457, OR = 1.15; males: χ 2 = 28.1, R 2 = 0.371, OR = 1.13; all p < 0.001). Among the evaluated indices, WC demonstrated the highest diagnostic performance in both sexes, but this should be observed with great caution, as WC acted as both a test and outcome variable, potentially generating significant bias. BRI showed superior performance in females, whereas WHtR performed better in males. ABSI exhibited limited discriminatory ability. Overall, indices reflecting central adiposity were more strongly associated with adverse metabolic profiles. Anthropometric indices serve as reliable surrogate markers of metabolic syndrome and effective tools for cardiometabolic risk stratification in college students. The proposed sex-specific cut-off values enhance the accuracy of early detection and support the use of simple anthropometric measures as a first-line screening approach before biochemical assessment. These findings have important implications for large-scale public health screening, especially in resource-limited settings.
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Sousa et al. (2026) conducted a cross-sectional in Metabolic syndrome (n=330). Anthropometric indices (ABSI, BRI, WC, WHtR) was evaluated on Metabolic syndrome (OR 1.14, p=<0.001). Anthropometric indices were significantly associated with the presence of metabolic syndrome (OR 1.14, p<0.001).
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