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. 2012 Nov;29(11):1390-4.
doi: 10.1111/j.1464-5491.2012.03723.x.

Associations between surrogate measures of insulin resistance and waist circumference, cardiovascular risk and the metabolic syndrome across Hispanic and non-Hispanic white populations

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Associations between surrogate measures of insulin resistance and waist circumference, cardiovascular risk and the metabolic syndrome across Hispanic and non-Hispanic white populations

M T Martínez-Larrad et al. Diabet Med. 2012 Nov.

Abstract

Aims: We evaluated the relations between surrogate indices of insulin resistance and waist circumference, metabolic syndrome and coronary heart disease risk across Hispanic and non-Hispanic white populations.

Methods: The study was a cross-sectional analysis of participants without diabetes in the San Antonio Heart Study, Mexico City Diabetes Study and Spanish Insulin Resistance Study. We evaluated commonly used indices of insulin resistance, including homeostasis model assessment, McAuley's index, Gutt's insulin sensitivity index, Avignon's insulin sensitivity index and the Stumvoll index with and without demographics, the modified Matsuda index and the product of the triglycerides and glucose index. The metabolic syndrome was defined by American Heart Association/National Heart, Lung, and Blood Institute criteria and coronary heart disease risk by Framingham risk scores.

Results: The Stumvoll index with demographics and the Avignon's insulin sensitivity index had the strongest correlations with waist circumference across populations. The triglycerides and glucose and McAuley's indices had the most robust correlations with Framingham risk score. The triglycerides and glucose index had the greatest ability to detect individuals with the metabolic syndrome and ≥ 10% coronary heart disease risk. Some indices display significant variability in the strength of the relationship with adiposity and coronary heart disease risk across populations.

Conclusions: There are significant differences between insulin resistance indices regarding the ability to detect the metabolic syndrome and coronary heart disease risk across populations. Studies may need to consider the index of insulin resistance that best suits the objectives.

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