Assessment of the influence of chewing pattern on glucose homeostasis through linear regression model

Abstract

Objective: Maintaining plasma glucose homeostasis is vital for mammalian survival, but the masticatory function, which influences glucose regulation, has, to our knowledge, been overlooked.

Research methods and procedures: In this study, we investigated the relationship between the glycemic response curve and chewing performance in a group of 8 individuals who consumed 80 g of apple. A device called "Chewing" utilizing electromyographic (EMG) technology quantitatively assesses chewing pattern, while glycemic response is analyzed using continuous glucose monitoring. We assessed chewing pattern characterizing chewing time (t_chew), number of bites (n_chew), work (w), power (wr), and chewing cycles (t_cyc). Moreover, we measured the principal features of the glycemic response curve, including the area under the curve (α) and the mean time to reach the glycemic peak (t_mean). We used linear regression models to examine the correlations between these variables.

Results: t_chew, n_chew, and wr were correlated with α (R² = 0.44, P < 0.05 for t_chew and n_chew, P < 0.001 for wr), and t_mean was correlated with t_chew (R² = 0.25, P < 0.05). These findings suggest that increasing chewing time and power, while reducing the number of chews, resulted in a wider glycemic curve and an earlier attainment of the glycemic peak.

Conclusions: These results emphasize the influence of proper chewing techniques on blood sugar levels. Implementing correct chewing habits could serve as an additional approach to managing the glycemic curve, particularly for individuals with diabetes.

Keywords: Chewing profile; EMG device; Glycemia; Glycemic curve; Linear regression models; Mastication.