Does the quality of street greenspace matter? Examining the associations between multiple greenspace exposures and chronic health conditions of urban residents in a rapidly urbanising Chinese city

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: Diabetes; Greenspace exposure; Hypertension; Machine learning; Streetscape.