• HOMA-IR;
  • Insulin resistance;
  • Metabolic syndrome


Aims/Introduction:  It is important to identify individuals at risk of metabolic syndrome (MetS), namely those with insulin resistance. Therefore, the aim of the present study was to find anthropometric and metabolic parameters that can better predict insulin resistance.

Subjects and Methods:  We selected 3899 individuals (2058 men and 1841 women), excluding those with fasting plasma glucose (FPG) ≥126 mg/dL, on medication for hypertension, dyslipidemia or diabetes, and those with a history of advanced macrovascular disease. Using multivariate analyses, we selected components for obesity, lipids, and blood pressure based on the strength of their association with the homeostasis model assessment of insulin resistance (HOMA-IR).

Results:  In multiple linear regression analysis, body mass index (BMI), waist circumference (WC), triglycerides (TG), high-density lipoprotein–cholesterol (HDL-C), and systolic blood pressure (SBP) were selected in men and women, and the effect of BMI on HOMA-IR outweighed that of WC. In multiple logistic regression analysis, BMI, TG, and SBP were significantly associated with HOMA-IR ≥2.5 in both genders, but WC and HDL-C were only selected in men. Combinations of BMI, TG, SBP, and FPG showed higher HOMA-IR values than those of the existing MetS components, considered useful for the identification of individual with higher insulin resistance.

Conclusions:  Body mass index, TG and SBP were selected as components significantly related to insulin resistance. The selected components were fundamentally adherent to the existing MetS criteria, the only difference being the measure of obesity, in which a stronger association with insulin resistance was observed for BMI than WC. (J Diabetes Invest, doi: 10.1111/j.2040-1124.2011.00162.x, 2011)