A mathematical model of adiponectin resistance

•Adiponectin is often associated with obesity.•We propose a mathematical model of the adiponectin − adiponectin receptors framework.•We take different parameters and their default values for simulation process.•We apply the rough set as secretion of adiponectin is uncertain with time. Adiponectin is often associated with obesity. The obese body displays a significant decrease in adiponectin expression and plasma levels. Higher adiponectin also results in lower expression of pro-inflammatory cytokine TNF-α from adipose tissue. Low adiponectin levels show to exist significantly in the case of insulin resistance. Adiponectin levels are found to be significantly lower in people with type 2 diabetes. In this paper, we proposed a mathematical model of the adiponectin − adiponectin receptors framework, based on the assumption that the secretion of adiponectin is inversely proportional to fat mass. Here, we show that an increase in obesity or adiposity results in a decrease in the adiponectin plasma level, which contributes to the development of adiponectin resistance. In this model, we have used different parameters and their default values, to perform a simulation based on the model. Further, experimentally, the plasma adiponectin concentration is ( ≈ 0.015) significantly lowered in the diabetic group compared to the non-diabetic group. In this model, we have obtained the plasma adiponectin concentration level ( ≈ 0.014) in the simulation process. So this model is only differing from 1 × 10−3 significant digits. We have achieved the degree of accuracy of adiponectin resistance is 93.33%. Therefore, these advances offer novel insights into the mathematical approach.