Pathways from street network design to symptoms of depression among emerging adults in China

Abstract

Streets comprise over 80% of all urban public space, while previous studies associated street network attributes with traffic and transport model choice, they did not examine network design in conjunction with symptoms of depression. This paper developed a path analysis model to examine the direct and indirect effects of street network designs on symptoms of depression among undergraduates. Road network density, road intersection density and public transit density were measured within 1 km buffers centered on university campuses. A survey that included the 9-item patient health questionnaire (PHQ9) addressed these effects and measured the incidence of symptoms of depression among a random sample of 22,060 Chinese undergraduates. After controlling for individual- and campus-level covariates, the results revealed that exposure to PM2.5, poor sleep quality and unhealthy dietary pattern (excluding transport-related physical activity) mediated the relationship between specific street network attributes and symptoms of depression. Higher road density was found to alleviate symptoms of depression by increasing exposure to PM2.5. Greater road connectivity tended to alleviate symptoms of depression by reducing exposure to PM2.5 but to exacerbate symptoms of depression by worsening sleep quality and increasing the incidence of unhealthy dietary patterns. Better access to public transit inclined to ameliorate symptoms of depression by improving sleep quality but to exacerbate symptoms by increasing PM2.5 exposure. These findings emphasize the need for strategies aimed at improving street network designs to include assessments of the aggregate effects on campus environs and the associated impacts on undergraduate mental health.