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arXiv · 2404.14915

A novel mathematical model for predicting the benefits of physical activity on type 2 diabetes progression

Pierluigi Francesco De Paola·Alessandro Borri·Fabrizio Dabbene·Karim Keshavjee·Pasquale Palumbo·Alessia Paglialonga
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Abstract

Despite the well-acknowledged benefits of physical activity for type 2 diabetes (T2D) prevention, the literature surprisingly lacks validated models able to predict the long-term benefits of exercise on T2D progression and 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-term glucose-insulin dynamics to predict the benefits of regular exercise on T2D progression. 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. These results are encouraging and can be the basis for future development of decision support tools able to assist patients and clinicians in tailoring preventive lifestyle interventions.

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Pierluigi Francesco De Paola, Alessandro Borri, Fabrizio Dabbene, Karim Keshavjee, Pasquale Palumbo, Alessia Paglialonga. 2024-04-23. A novel mathematical model for predicting the benefits of physical activity on type 2 diabetes progression. https://arxiv.org/abs/2404.14915

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