Diagnosing insulin resistance in the general population.

OBJECTIVE: Difficulties in measuring insulin sensitivity prevent the identification of insulin-resistant individuals in the general population. Therefore, we compared fasting insulin, homeostasis model assessment (HOMA), insulin-to-glucose ratio, Bennett index, and a score based on weighted combinations of fasting insulin, BMI, and fasting triglycerides with the euglycemic insulin clamp to determine the most appropriate method for assessing insulin resistance in the general population. RESEARCH DESIGN AND METHODS: Family history of diabetes, BMI, blood pressure, waist and hip circumference, fasting lipids, glucose, insulin, liver enzymes, and insulin sensitivity index (ISI) using the euglycemic insulin clamp were obtained for 178 normoglycemic individuals aged 25-68 years. Product-moment correlations were used to examine the association between ISI and various surrogate measurements of insulin sensitivity. Regression models were used to devise weights for each variable and to identify cutoff points for individual components of the score. A bootstrap procedure was used to identify the most useful predictors of ISI.
RESULTS: Correlation coefficients between ISI and fasting insulin, HOMA, insulin-to-glucose ratio, and the Bennett index were similar in magnitude. The variables that best predicted insulin sensitivity were fasting insulin and fasting triglycerides. The use of a score based on Mffm/I = exp[2.63 - 0.28ln(insulin) - 0.31ln(TAG)] rather than the use of fasting insulin alone resulted in a higher sensitivity and a maintained specificity when predicting insulin sensitivity.
CONCLUSIONS: A weighted combination of two routine laboratory measurements, i.e., fasting insulin and triglycerides, provides a simple means of screening for insulin resistance in the general population.