Use of Anthropometric Variables, Lipid Profile and Serum Insulin as Predictors of Insulin Resistance in Metabolic Syndrome Subjects

Metabolic syndrome is a combination of medical disorders that increase the risk of developing cardiovascular disease and diabetes. It affects one in five people, and prevalence increases with age.

A total of 120 subjects were studied, comprising of 60 healthy controls and 60 metabolic syndrome subjects. Anthropometric measurements (waist circumference, waist-hip ratio, BMI Prime), fasting glucose, triglycerides, total cholesterol, HDLc, LDLc were estimated by enzymatic method and fasting insulin by ELISA. HOMA-2 indices (updated homeostasis model assessment) were calculated using Microsoft Excel based HOMA-2 calculator.

The optimal cut-off values for identification of insulin resistance in overweight individuals were: 144 mg/dL for triglycerides (sensitivity-66%; specificity-83%), 3.4 for TG/HDLc ratio (sensitivity 68%; specificity-90%), and 17μU/mL for fasting insulin (sensitivity-74%; specificity-100%). Linear regression analysis showed a significant linear relationship between HOMA2-IR and waist circumference, serum triglycerides, TG:HDL ratio and fasting insulin (p < 0.001).

Waist circumference and BMI can be used as screening tools in the diagnosis of insulin resistance with minimal cost and manpower requirement. Fasting triglyceride levels, TG/HDLc ratio and insulin levels are practical methods for quantifying insulin resistance among metabolic syndrome subjects. In the absence of a standardized insulin assay, the most practical approach to identify insulin resistance is to use the cut-off values for either triglyceride concentration or the TG/HDLc ratio.