Journal of Metabolic Health (Oct 2017)

Assessing the test–retest repeatability of insulin resistance measures: Homeostasis model assessment 2 and oral glucose insulin sensitivity

  • Catherine A.P. Crofts,
  • Mark C. Wheldon,
  • Caryn Zinn,
  • Xiaomiao Lan-Pidhainy,
  • Thomas M.S. Wolever,
  • Grant Schofield

DOI
https://doi.org/10.4102/jir.v2i1.27
Journal volume & issue
Vol. 2, no. 1
pp. e1 – e9

Abstract

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Background: Insulin resistance is commonly assessed using the homeostasis model assessment (HOMA) variants. HOMA is potentially insensitive to change because of its high coefficient of variation. The repeatability coefficient is an alternative means of assessing test repeatability. To be confident of clinical change, rather than biological variation, a subsequent test needs to differ from the former by more than the repeatability coefficient using the equation. Test 1 = Test 2 ± repeatability coefficient. The repeatability coefficients for measures of insulin resistance are unknown. Aim: To compare the repeatability coefficient of HOMA2 variants (Beta-cell function [%B], insulin sensitivity [%S], insulin resistance [IR]) to a dynamic measure of insulin resistance, and the oral glucose insulin sensitivity (OGIS) test. Setting: The raw data from a previously used data set were reanalysed. Methods: Glycaemic and insulinaemic tests were performed on 32 men and women both with (n = 10) and without type 2 diabetes (n = 22). From these data, eight fasting tests and three 50-g oral glucose tolerance tests were used to calculate HOMA2 and OGIS. The methods of Bland and Altman assessed repeatability. Results: Repeatability coefficients for all participants for the HOMA2 %B, %S and IR variants were 72.91, 189.75 and 0.9, which equates to 89%, 135% and 89% of their respective grand means. By contrast, OGIS had a repeatability coefficient of 87.13, which equates to 21% of the grand mean. Conclusion: Because of the high repeatability coefficient relative to the grand mean, use of HOMA2 measures for assessing insulin resistance in small population studies should be reconsidered.

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