Biological variation of homeostasis model assessment-derived insulin resistance in type 2 diabetes

Vijay Jayagopal, Eric S. Kilpatrick, Paul E. Jennings, David A. Hepburn, Stephen Atkin

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OBJECTIVE - Individuals with type 2 diabetes are particularly vulnerable to cardiovascular disease. Insulin resistance is a major determinant of this increased risk and is a potential therapeutic target. This study was undertaken to establish the natural biological variation of insulin resistance in individuals with type 2 diabetes. RESEARCH DESIGN AND METHODS - The biological variation of insulin resistance was assessed by measuring insulin resistance at 4-day intervals on 10 consecutive occasions in 12 postmenopausal women with diet-controlled type 2 diabetes and in 11 weight- and age-matched postmenopausal women without type 2 diabetes. Insulin resistance was derived using the homeostasis model assessment for insulin resistance (HOMA-IR) method. RESULTS - The distribution of HOMA-IR was log Gaussian in the type 2 diabetic study group and Gaussian in the control group. The HOMA-IR in the type 2 diabetic group was significantly greater than that of the control group (mean ± SD: 4.33 ± 2.3 vs. 2.11 ± 0.79 units, P = 0.001). After accounting for analytical variation, the mean intraindividual variation was also substantially greater in the type 2 diabetic group than in the control group (mean 1.05 vs. 0.15, P = 0.001). Consequently, at any level of HOMA-IR, a subsequent sample must increase by >90% or decrease by >47% to be considered significantly different from the first. CONCLUSIONS - HOMA-IR is significantly greater and more variable for individuals with type 2 diabetes. Therefore, this inherent variability needs to be accounted for in studies evaluating therapeutic reduction of HOMA-IR in this group.

Original languageEnglish
Pages (from-to)2022-2025
Number of pages4
JournalDiabetes Care
Issue number11
Publication statusPublished - Nov 2002
Externally publishedYes


ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism

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