Abstract:
Metabolic syndrome (MS) is a complex clinical condition in which several parameters, when associated with central obesity, increase the risk of cardiovascular disease, insulin resistance and their complications. Given the global epidemic of overweight, identifying these individuals early and with the greatest possible accuracy is a public health issue. However, traditional anthropometric measures have not been shown to be effective in this screening and fail to take into account different body compositions, requiring that more appropriate tools for determining central adiposity and patients with MS be established.
A descriptive, cross-sectional study was conducted with patients treated in the endocrinology department of a tertiary hospital. They underwent sociodemographic and anthropometric assessment, including neck circumference (NC), waist circumference (WC), and hip circumference (HC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and body mass index (BMI), in addition to biochemical evaluation of the last 3 months and blood pressure measurement. MS was defined based on the criteria adopted by the International Diabetes Federation. Logistic regression analyses were used to correlate MS and its components with anthropometric measurements. The Receiver Operator Characteristic (ROC) curve was constructed to assess the accuracy of anthropometric measurements in establishing MS in men and women, and the Youden index was used to determine the cutoff point for each measurement evaluated. Cardiovascular risk using the Framingham score was assessed in groups above and below the cutoff points for NC.
The study concluded that CP, WHR and RCA proved useful in detecting MS, with good accuracy and established cutoff points, being valid alternatives for identification of these patients. Its low cost and easy measurement are relevant for clinical practice.
