A Geographically Weighted Random Forest Analysis of Spatial Non-Stationarity Association of Street View Environmental, Socioeconomic, and Lifestyle Factors with Type-2 Diabetes Prevalence in Toronto

Background Numerous studies have shown that the environment can affect the prevalence of Type-2 Diabetes Mellitus (T2DM) by encouraging healthy lifestyle behaviours. Alongside traditional medical prevention strategies, social determinants have also been prioritized as a top consideration in T2DM clinical treatment and care. However, limited research has explored the association between neighbourhood perceptions of aesthetics and safety and T2DM prevalence, potentially through indirect pathways influencing behavioural response. Combining the effects, this research has two main objectives: (1) to identify the relationships between street view environmental, socioeconomic, and lifestyle factors with T2DM prevalence rates and (2) to determine how these associations vary spatially across different regions of Toronto. Methods This study applied a Geographically Weighted Random Forest regression to analyze the spatial non-stationarity associations and account for potential confounding factors in the relationship between 27 variables with T2DM prevalence across Toronto’s 3,800 Dissemination Areas. After modelling, the study examined local variations in feature effects using partial dependency plots and permutation-based feature importance maps to assess how variable associations on T2DM prevalence various around Toronto. Results The model achieved an R ² of 77%. Having regular healthcare, age, smoking rate, and obesity prevalence have the strongest positive correlation with T2DM prevalence. Beauty and safety perception, NDVI, and mental issues have a weak positive association with T2DM prevalence. In the downtown financial districts, immigration rates and drinking rates were identified as negatively associated with T2DM prevalence. Meanwhile, marital status, obesity, life dissatisfaction, and commuting by walking or cycling were found to have positive or negative spatial non-stationary associations across different geographical regions in Toronto. Conclusions Street view-derived environmental perceptions show spatially non-stationary associations with the prevalence of T2DM in Toronto. Higher T2DM rates are observed in dissemination areas with better street-view environments and access to healthcare providers. This may reflect underdiagnosis in areas with poorer perceived environments and less frequent access to healthcare providers. Residents living in better-perceived environments may not necessarily engage in more physical activity or active transportation. The findings offer valuable insights to assist government and public health authorities design targeted prevention and intervention programs in Toronto.