Yong Xin

Many literature and research indicate that health rates frequently follow a distinguishing socio-economic gradient, where health is influenced by an individual’s socioeconomic status (SES) and those of lower SES are more at risk to illness. The purpose of this research was to assess (within a bivariate and spatial context) how sociodemographic profiles influence asthma, diabetes, and high blood pressure rates in the City of Toronto. The objectives of this study were summed up in two questions; (1) “is there a spatial pattern to the rates of diabetes, asthma, and high blood pressure at the neighbourhood level in Toronto?” and (2) “are any socio-economic variables that can explain the patterns observed? And if so, which ones?”. Toronto health rate variables were obtained from the OCHPP while sociodemographic variables were acquired from open-source data archives for the year 2016. The analysis was multi-step where the initial steps (bivariate regression and PCA) were for data reduction. The third step – measures of spatial autocorrelation (i.e. Moran’s I) were tested on dependent variables to explore whether any broad spatial patterns existed. The final multivariate analysis modeled relationships between health measures and the SES measures. The first question was found to be true, where the Moran’s I test and tests for spatial dependency indicated the presence of spatial autocorrelation and spatial dependence. However, the second question had somewhat mixed results as there was a lack of spatial significance regarding the correlation of the sociodemographic variables and health rates. Future research should rely less on socioeconomic variables being the main indicator of health rates and assess other causations such as lifestyle variables or geographic factors.