The exposome puzzle: advanced statistical methods for investigating the contextual determinants of cardiometabolic diseases

Abstract

Obesity is a chronic condition that leads to a range of other non-communicable diseases, including type 2 diabetes (T2D). In recent decades, the incidence rates of obesity and T2D have risen alarmingly, posing a significant threat to global health. The rise in these conditions may be linked to changes in our surrounding environments. Environmental factors can influence obesity and T2D risks directly (e.g., pollutants, toxins) or indirectly by affecting behaviour. Studies have shown that our built environment, walkability, transportation, and other factors can influence obesity through physical activity levels. The local food environment, air pollution, and noise have also been linked to obesity and particularly to T2D risk. Furthermore, in high-income countries, individuals with lower income and education are generally more likely to experience higher rates of obesity and T2D. However, the results remain heterogeneous and vary across different countries and regions. Despite substantial research, a few studies examined the joint exposure to various factors. In real life we are exposed to various environmental stressors simultaneously, forming our exposome. Therefore, it is important to study their joint effects. Most earlier research focused on single exposures, potentially neglecting complex interrelations among these components. In this doctoral thesis, I applied discovery-based approaches to investigate a large set of environmental drivers of obesity and T2D in adults. I employed advanced statistical methods to comprehensively study the exposome factors as parts of one complex system. The results showed that neighbourhood-level social and economic factors, walkability, temperature, loneliness were associated with obesity and T2D risk.