GIS-based assessment of spatial and temporal disparities of urban health index in Shenzhen, China

• Main Authors: Duan Yongheng (Author), Xie Shan (Author), Liu Fei (Author), Tang Jinglin (Author), Gong Liyue (Author), Liu Xiaoying (Author), Wen Tingxiao (Author), Wang Hongrui (Author)
• Format: Book
• Published: Frontiers Media S.A., 2024-09-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2296-2565; 10.3389/fpubh.2024.1429143
• Keywords: urban health index; health inequalities; spatial autocorrelation analysis; highincome city; geographic in information system (GIS); Moran's I; Public aspects of medicine; RA1-1270
• Source: Frontiers in Public Health, Vol 12 (2024)

PurposeTo explore the inter-regional health index at the city level to contribute to the reduction of health inequalities.MethodsEmployed the health determinant model to select indicators for the urban health index of Shenzhen City. Utilized principal component analysis, the weights of these indicators are determined to construct the said health index. Subsequently, the global Moran's index and local Moran's index are utilized to investigate the geographical spatial distribution of the urban health index across various administrative districts within Shenzhen.ResultsThe level of urban health index in Shenzhen exhibits spatial clustering and demonstrates a positive spatial correlation (2017, Moran's I = 0.237; 2019, Moran's I = 0.226; 2021, Moran's I = 0.217). However, it is noted that this clustering displays a relatively low probability (90% confidence interval). Over the period from 2017 to 2019, this spatial clustering gradually diminishes, suggesting a narrowing of health inequality within economically developed urban areas.ConclusionOur study reveals the urban health index in a relatively high-income (Shenzhen) in a developing country. Certain spatially correlated areas in Shenzhen present opportunities for the government to address health disparities through regional connectivity.