Modeling the cumulative benefits of regular physical activity on type 2 diabetes progression

Despite the well-acknowledged benefits of physical activity for type 2 diabetes (T2D) prevention, the literature lacks validated models able to predict the long-term benefits of exercise on T2D progression and that could be used to support personalized risk prediction and prevention. To bridge this gap, we developed a novel mathematical model that formalizes the link between exercise and short- and long-termglucose-insulin dynamics to predict the benefits of regular exercise on T2D progression. Specifically, we combine a well-known T2D progression model that describes a fast dynamics of physical activity with a slow dynamics that accounts for the cumulative effects of regular physical activity on pancreatic beta-cell mass and on individual insulin sensitivity, mediated by the integral effect of interleukin-6 produced during exercise. The model was used to estimate the benefits of physical activity in four conditions: (i) regular exercise of varying intensity; (ii) regular exercise following the World Health Organization (WHO) recommendations for chronic disease prevention; (iii) discontinuation of a regular exercise program; and (iv) assessment of the inter-individual variability in a wide range of simulated scenarios. These results are encouraging and can set the basis for future development of decision support tools able to assist patients and clinicians in tailoring preventive lifestyle interventions. Results showed that the model quantitatively captured the dose-response relationship (larger benefits with increasing intensity and/or duration of exercise), it consistently reproduced the benefits of clinical guidelines for diabetes prevention, and it accurately predicted persistent benefits following interruption of physical activity, in line with real-world evidence from the literature.