Prediction of homeostasis model assessment of insulin resistance in Japanese subjects.

OBJECTIVE In our previous study, multivariate analysis showed that body mass index (BMI), triglycerides (TG) levels, and systolic blood pressure (SBP), in addition to fasting plasma glucose (FPG) levels, significantly correlated with homeostasis model assessment of insulin resistance (HOMA-IR). Our aim was to develop a predictive tool for HOMA-IR using tests of the specific health examinations. METHODS We enrolled 7,248 Japanese adults (3,793 men, and 3,455 women) in this cross-sectional study. A multiple regression model for predicting HOMA-IR was created using laboratory tests and lifestyle habits in the specific health examination. RESULTS HOMA-IR prediction index was developed using routinely measured parameters (BMI; levels of FPG, TG, and high-density lipoprotein cholesterol; BP; exercise; and physical activity), and did not require measurement of immunoreactive insulin levels. The prediction accuracy of the model was considered good, as indicated by R2 values (men, 0.465; women, 0.405). CONCLUSION The predictive tool for HOMA-IR using specific health examination tests allows healthcare professionals to estimate an individual's overall risk of metabolic syndrome (MetS). We propose that this tool can be used as an aid in health guidance for MetS.