This study aimed to investigate whether body mass index (BMI), waist circumference (WC), or waist to hip ratio (WHR) could be a better predictor of metabolic syndrome and, if so, what would be the cutoff points for these surrogates to appropriately differentiate metabolic syndrome in different age and sex subgroups. Methods. The present cross-sectional study was conducted on a sample of Isfahan Cohort Study (ICS). In total, 468 individuals (194 with and 274 subjects without metabolic syndrome) according to the National Cholesterol Education Program’s Adult Treatment Panel III (ATP-III) criteria were selected. Anthropometric indices were measured and plotted using receiver-operating characteristic (ROC) curves. Results. According to ROC curve analysis, WC and WHR parameters were better indicators of metabolic syndrome compared to BMI in women, whereas in men WHR had a lower discriminating value compared to the other two parameters. Among these three anthropometric parameters, BMI had a lower sensitivity and WC and WHR both had a higher sensitivity for predicting metabolic syndrome in women compared with in men. The cut points for WC were nearly equal in men and women, 90.3 versus 90.0, respectively. Women had higher cut points for BMI (28.5？kg/m2) compared to men (26.0？kg/m2). Our results showed the highest sensitivity and specificity for WC cut points specially in women. To predict metabolic syndrome, we looked into optimal age-specific cut points for BMI, WC, and WHR. The results indicated that WC had the highest discriminating value compared to other indicators in the different age subgroups. The optimal cut points for all three parameters gradually increased with age. Conclusion. Our results demonstrated that regardless of gender and age variables, WC could be a preferred parameter for predicting metabolic syndrome compared to BMI and WHR in Iranian population. 1. Introduction Metabolic syndrome is known to be a cluster of variety of cardiac and metabolic-related factors such as obesity, elevated blood pressure, glucose metabolism disturbances, and raised lipid levels leading to increased risk of mortality and morbidity [1–4]. From all these risk factors, existing diagnostic criteria emphasize the importance of body fat [5]. It has been suggested that central obesity as an indicator of body fat can be easily and cost-effectively estimated by measuring body mass index (BMI) and waist circumference (WC) which might discriminate metabolic syndrome from nonmetabolic syndrome status [6, 7]. To diagnose metabolic syndrome, different cutoff points for these
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