Using Multiscale Geographically Weighted Regression (MGWR) to explore spatial varying relationships of urban built environments and socioeconomic factors with suicide rate in Hong Kong

Keywords: Suicide; Built environment; Socioeconomic factors; Multiscale Geographically Weighted Regression (MGWR)
Abstract Type: Poster Abstract

Abstract

Suicide is a critical public health issue with complex, multi-dimensional causes. While previous studies have examined socio-economic and built environmental influences, they often neglect their impacts across spaces, which are crucial for targeted prevention strategies. To address the gap, this study focused on Hong Kong, utilizing Multiscale Geographically Weighted Regression (MGWR) to analyze the 2021 suicide death dataset at the TPU level. Results indicate significant spatial variations in the impacts. First, four significant socio-economic influences were identified: the male-to-female ratio positively correlates with suicide rates, with its impact diminishing from northwest to southeast; the local and working population ratios show a shift from negative correlation in the northwest to positive in the southeast; and higher levels of occupational mixing correlate negatively with suicide rates, with increasing strength from southeast to northwest. Second, two built environment factors are significantly related to suicide rates. The positive influence of building shape complexity diminishes from northern to southern areas. The negative impact of land-use mix levels decreases from urban areas to rural areas, for both new and old towns in Hong Kong. These findings suggest that urban planning strategies for suicide prevention, such as land resource allocation, urban function configuration, and job opportunity allocation, should be tailored to local conditions.