Spatial scale analysis for the relationships between the built environment and cardiovascular disease based on multi-source data

作者：Jiwei Xu, Ying Jing, Xinkun Xu, Xinyi Zhang, Yanfang Liu, Yanfang Liu, Huagui He, Fei Chen, Yaolin Liu, Yaolin Liu · 发表于：Health & Place · 年份：2023 · DOI：10.1016/j.healthplace.2023.103048 · 被引用次数：22 · 研究领域：Urban Transport and Accessibility、Noise Effects and Management、Urban Green Space and Health

To examine what built environment characteristics improve the health outcomes of human beings is always a hot issue. While a growing literature has analyzed the link between the built environment and health, few studies have investigated this relationship across different spatial scales. In this study, eighteen variables were selected from multi-source data and reduced to eight built environment attributes using principal component analysis. These attributes included socioeconomic deprivation, urban density, street walkability, land-use diversity, blue-green space, transportation convenience, ageing, and street insecurity. Multiscale geographically weighted regression was then employed to clarify how these attributes relate to cardiovascular disease at different scales. The results indicated that: (1) multiscale geographically weighted regression showed a better fit of the association between the built environment and cardiovascular diseases than other models (e.g., ordinary least squares and geographically weighted regression), and is thus an effective approach for multiscale analysis of the built environment and health associations; (2) built environment variables related to cardiovascular diseases can be divided into global variables with large scales (e.g., socioeconomic deprivation, street walkability, land-use diversity, blue-green space, transportation convenience, and ageing) and local variables with small scales (e.g., urban density and street insecurity); and (3) at...