Amid escalating adult mental distress in urban areas, urban green space (UGS) is increasingly recognized as an environmental feature for mitigating distress burden and associated environmental stressors. Effective and equitable UGS planning requires a nuanced understanding of the associations between UGS types and frequent mental distress (FMD), as well as their heterogeneity across racial and ethnic neighborhoods. Using spatial regressions within a Piecewise Structural Equation Modeling (PSEM) framework, this study investigates both direct associations between two UGS types (e.g., trees and grass) and FMD, as well as indirect pathways through land surface temperature (LST), air pollution (PM2.5), and anthropogenic noise. Findings reveal that UGS types have distinct, and often opposing, non-linear associations with FMD and its environmental mediators. Tree canopy exhibits a direct negative association with FMD, with diminishing marginal effects as canopy cover increases, and a U-shaped association with PM2.5, while grass shows positive associations with FMD and PM2.5 concentrations. Although both UGS types are negatively associated with LST and noise levels, trees show a significantly stronger association with temperatures. We also identify significant racial and ethnic heterogeneity in these associations. The overall negative marginal effect of tree canopy on FMD is significant in communities of color but statistically insignificant in predominantly White tracts. This disparity is driven by both direct association with FMD and indirect pathways through LST mitigation, which are significant only in communities of color. These findings challenge one-size-fits-all greening narratives and provide evidence for context-specific, equity-oriented UGS planning aiming at mitigating urban mental distress and advancing restorative environmental justice.
扫码关注我们
求助内容:
应助结果提醒方式:
