College of Landscape Architecture, Nanjing Forestry University, Nanjing, 210037, China.
College of Landscape Architecture, Nanjing Forestry University, Nanjing, 210037, China.
Environ Res. 2023 Apr 1;222:115344. doi: 10.1016/j.envres.2023.115344. Epub 2023 Jan 21.
Numerous studies have demonstrated that greenspace(GS) exposure is associated with health improvements in individuals with hypertension and diabetes. However, studies examining the associations between multiple GS exposures and chronic health conditions in developing countries are limited.
Geospatial data and spatial analysis were employed to objectively measure the total neighbourhood vegetative cover (mean value of normalised difference vegetation index [NDVI] within specific buffer zone) and proximity to park-based GS (network distance from home to the entrance of park-based GS). Street view imagery and machine learning techniques were used to measure the subjective perceptions of street GS quality. A multiple linear regression model was applied to examine the associations between multiple GS exposures and the prevalence of hypertension and diabetes in neighbourhoods located in Qingdao, China.
The model explained 29.8% and 28.2% of the prevalence of hypertension and diabetes, respectively. The results suggested that: 1) the total vegetative cover of the neighbourhood was inversely correlated with the prevalence of hypertension (β = -0.272, p = 0.013, 95% confidence interval (CI): [-1.332, -0.162]) and diabetes (β = -0.230, p = 0.037, 95% CI: [-0.720, -0.008]). 2) The street GS quality was negatively correlated with the prevalence of hypertension (β = -0.303, p = 0.007, 95% CI: [-2.981, -0.491]) and diabetes (β = -0.309, p = 0.006, 95% CI: [-1.839, -0.314]). 3) Proximity to park-based GS and the prevalence of hypertension and diabetes mellitus were not significantly correlated.
This study used subjective and objective methods to comprehensively assess the greenspace exposure from overhead to eye level, from quantity, proximity to quality. The results demonstrated the beneficial relationships between street GS quality, total vegetative cover, and chronic health in a rapidly urbanising Chinese city. Furthermore. the effect of street GS quality was more pronounced in potentially mitigating chronic health problems, and improving the quality of street GS might be an efficient and effective intervention pathway for addressing chronic health issues in densely populated cities.
大量研究表明,绿地(GS)暴露与高血压和糖尿病患者的健康改善有关。然而,研究发展中国家多种 GS 暴露与慢性健康状况之间的关系的研究有限。
采用地理空间数据和空间分析客观测量邻里植被总覆盖率(特定缓冲区归一化差异植被指数 [NDVI] 的平均值)和接近基于公园的 GS(从家到基于公园的 GS 入口的网络距离)。使用街景图像和机器学习技术来衡量对街道 GS 质量的主观感知。应用多元线性回归模型来检验中国青岛市社区中多种 GS 暴露与高血压和糖尿病患病率之间的关系。
该模型分别解释了高血压和糖尿病患病率的 29.8%和 28.2%。结果表明:1)社区的总植被覆盖率与高血压患病率呈负相关(β=-0.272,p=0.013,95%置信区间 [CI]:[-1.332,-0.162])和糖尿病(β=-0.230,p=0.037,95% CI:[-0.720,-0.008])。2)街道 GS 质量与高血压患病率呈负相关(β=-0.303,p=0.007,95% CI:[-2.981,-0.491])和糖尿病(β=-0.309,p=0.006,95% CI:[-1.839,-0.314])。3)接近基于公园的 GS 与高血压和糖尿病患病率无显著相关性。
本研究使用主观和客观方法全面评估了从头顶到视线高度、从数量、接近到质量的绿地暴露情况。研究结果表明,在中国快速城市化的城市中,街道 GS 质量、总植被覆盖率与慢性健康之间存在有益关系。此外,街道 GS 质量的影响在减轻慢性健康问题方面更为明显,改善街道 GS 的质量可能是解决人口密集城市慢性健康问题的有效干预途径。