Abstract

The glycemic response to the consumption of food is important in managing healthy metabolism and preventing diet-related diseases. The glycemic response is the trend of changes in the concentration of blood glucose following the intake of food, especially of carbohydrate-rich meals. The simplistic measures of traditional nutritional assessment of the effect of diets on blood glucose levels are often the Glycemic Index (GI) and the Glycemic Load (GL), which mainly study how carbohydrate-rich diets influence blood glucose levels. However, these measurements assume a more or less linear connection between carbohydrate consumption and glucose reaction, which is unverified due to the complex physiological interactions that occur in the human body. In the real sense, the glycemic control depends on diverse factors, such as macronutrient content, digestion, hormonal reactions, and individual metabolic diversity. This paper examines how non-linear modelling methods can be used to examine the glycemic response of healthy adults in relation to macronutrient composition, as it relates to the change in carbohydrates, proteins and fats. It attempts to give a mathematical and computer model in which it could explain non-linear and dynamic relationships between dietary intake and glucose regulation in the blood. The postprandial glucose concentration was determined on healthy adult participants who had taken food of different macronutrient formulations. Time profile of glucose changes is obtained through the measurement of blood glucose at certain intervals subsequent meals. The relationship between the nutritional intake and the glycemic response is predicted by the non-linear modelling techniques which include the non-linear regression functions, logistic growth model and the glucose-insulin interaction model using the differential equations. These models are able to pick the non-linear trends including delayed glucose peaks, saturation effects, and rounded responses because of the existence of proteins and fats in mixed diets. The results indicate that the interactions between macronutrients influence the shape and size of the glycemic curves significantly, which means that carbohydrate content cannot be trusted to predict blood glucose response.