Data-Driven Decisions in Type 2 Diabetes Management in Daily Life Monitoring
Niala den Braber is a PhD student in the Department Biomedical Signals and Systems. Promotors are prof.dr. M.M.R. Hutten and prof.dr. G.D. Laverman from the Faculty of Electrical Engineering, Mathematics and Computer Science.
The global increase in persons with type 2 diabetes mellitus (T2DM) poses a significant public health challenge, closely linked to unhealthy lifestyles, including insufficient physical activity, and poor dietary habits. Addressing T2DM effectively requires a holistic approach, with continuous glucose and lifestyle monitoring playing a critical role. This dissertation explored methods to utilize the growing amount of continuous glucose and lifestyle data for improved glucose control and behavioural change, aiming to develop a patient-centred decision support tool.
In Chapter 2, the dissertation began with exploring the requirements for designing a personalized diabetes management application. It examined how diet, physical activity, and glucose levels can be integrated into a (mobile) application and highlights the challenges of reliably and efficiently recording and integrating these data. Chapter 3 investigated the impact of data loss on glucose measurements obtained via continuous glucose monitoring (CGM), emphasizing how data loss can affect clinical decisions and underscoring the importance of complete and accurate data collection for reliable interpretations and treatment decisions. Real-life factors such as connectivity issues and sensor errors are discussed, and the potential deviations in glucose measurements due to data loss are analysed.
Chapter 4 continued with an analysis of glucose control beyond HbA1c levels in insulin-treated T2DM patients, using real-world data measured with a CGM device. This chapter highlighted the limitations of traditional methods such as HbA1c, which do not account for glucose variability and hypoglycaemic episodes. The value of CGM data for more detailed and accurate glucose management is emphasized, and the discrepancies between time in range (TIR) and HbA1c categories were explored.
Chapter 5 examined which objectively measured physical activity metrics are most important to assess using accelerometers and determines the activity profiles of individuals with T2DM to explore opportunities for tailored lifestyle interventions. The study identified five crucial parameters and three patient activity profiles, classified as inactive, moderately active, and active. Notably, the moderately active and inactive groups exhibited insufficient moderate to vigorous physical activity (MVPA) and prolonged sedentary behaviour, highlighting the need for interventions to increase physical activity and reduce sedentary behaviour. Chapter 6 examined the association between physical activity, muscle mass, and protein intake in individuals with T2DM. The study showed that low physical activity and insufficient protein intake are related to reduced muscle mass and poorer clinical outcomes, emphasizing the need for adequate protein intake and physical activity to maintain muscle mass and improve overall health in these patients.
Chapter 7 evaluated the contribution of postprandial glucose levels to the hyperglycaemic burden in T2DM. It provided insights for personalized treatment strategies by focusing on the differences between fasting plasma glucose (FPG) and postprandial plasma glucose (PPG). By analysing the impact of different meals on glucose levels, it demonstrated how dietary interventions can be optimized to improve both FPG and PPG.
In the final chapter, the discussion, the findings from the various studies were evaluated. It identified the essential parameters for effective monitoring, utilizing real-life data on glucose levels, physical activity, and diet. This chapter also addressed the challenges and importance of a holistic approach to these parameters for improved glycaemic control and reduced patient burden. Additionally, this chapter laid the foundation for developing a holistic, patient-centred decision support tool that provides personalized and action-oriented insights to support sustainable lifestyle changes and improved clinical outcomes in T2DM management.
