Suburban neighborhood environments and depression: A case study of Guangzhou, China

Abstract

Background: Research on neighbourhood environments and depression has concentrated on public health in developed countries. This study aims to enrich the discourse on geographic characteristics and depression by providing new evidence of direct and indirect associations between suburban neighbourhood environments and depression in urban China.

Methods: Panyu in Guangzhou, a suburban district restructured by the speedy expansion of private housing, was selected as the case study area. Given the wide variety of influential factors of neighbourhood environments on depression, multivariate statistical analysis was performed using a two-stage model: 1) Binary Logistic Regression to evaluate the direct associations between neighbourhood environmental factors and depression; 2) Path Analysis to assess the indirect relationships between neighbourhood environmental attributes, physical activity and depression.

Results: We found that population density, sufficiency of public space, land use mix level and street connectivity had direct impacts on depressive symptoms. Land use mix, street connectivity and destination accessibility had indirect effects on depressive symptoms through influencing time spent on public transport and driving time. However, no significant effect of social capital on depression was found.

Conclusion: Environmental factors and mechanisms negatively affecting depressive symptoms in the specific suburban context of Guangzhou, China, are found to be the unsatisfactory public space and community facility provision, and land use mix. This study particularly identifies the mediation effect of time spent on public transit and driving time on depressive symptoms, enriching the debates in the extant literature on mediating effects of utilitarian physical activity in suburban China. It was also ascertained that interventions that create comfortable, convenient, appropriate, and active built environment can reduce depression symptoms.