Type 2 Diabetes in Rural Bangladesh: Leveraging Machine Learning to Identify Determinants of Glycaemic Control, Comorbidities, and Complications

Effective diabetes care is vital to control diabetes and prevent complications. Data is limited on diabetes outcome in rural Bangladesh. This thesis shows that many adults with type-2 diabetes have inadequate blood sugar control and high blood pressure, along with a considerable burden of heart disease, stroke, and diabetic foot, and reduced physical and mental well-being. Using advanced data analysis, the study identified key risk factors, including older age, longer disease duration, unhealthy lifestyles, medication nonadherence, and diabetes-related distress. These findings highlight the need for targeted community-based interventions to improve diabetes care and reduce preventable complications in rural, resource-limited settings.