Wednesday, 8 June 2022

Analysis of insulin resistance using the non-linear homeostatic model assessment index in overweight canines

Research (Published online: 08-06-2022)
2. Analysis of insulin resistance using the non-linear homeostatic model assessment index in overweight canines
Franco Gonzlez-Villar and Francisco Pérez-Bravo
Veterinary World, 15(6): 1408-1412

ABSTRACT

Background and Aim: Diabetes mellitus is a carbohydrate metabolism disorder produced mainly by a deficit in insulin production or insulin resistance. The homeostatic model assessment (HOMA) is a broad method for estimating insulin resistance and β-cell function. This study aimed to evaluate the stages of insulin resistance using non-linear HOMA index analysis in normoglycemic normal weight and obese canines.

Materials and Methods: Insulin resistance was evaluated using the mathematical HOMA non-linear model in canines with different body and glycemic conditions. Forty canines were studied, including 20 normoglycemic normal weight canines and 20 normoglycemic obese canines. Chi-square statistical test was applied, in which the body condition and HOMA non-linear index were evaluated. The Spearman correlation test was conducted to evaluate the glycemic and insulin variables in both types of canines.

Results: The Spearman correlation presented a correlation between increased blood glucose levels and insulin in obese canines, with a correlation of 0.79, while no significant changes in insulin were found in normal weight canines with different blood glucose levels, with a correlation of –0.11. The analysis of the non-linear HOMA index showed significant differences between non-linear HOMA insulin resistance in normal weight and obese canines, with a Chi-square statistic of 16.9424 and p = 0.000039. Canine with increased HOMA 2 showed higher levels of insulin with increasing blood glucose compared to those with normal HOMA 2.

Conclusion: The HOMA 2 is a marker for evaluating increased insulin resistance in obese dogs and can be used to determine patients at risk for glycemic alterations.

Keywords: diabetes, glycemia, insulin resistance, overweight.



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