Quantitative threshold effects identification of urban green exposure on multidimensional human health – A case study in Xiamen City, China

Urban green spaces benefit health, and several cities have set specific greening targets or proposed guidelines to increase the presence of green spaces. However, the development of urban green spaces is restricted by the complex urban environment. The quantitative threshold effects of passive green exposure levels and human health are still not clear. Addressing this gap is crucial for effective urban planning, particularly in densely built environments with limited land resources, as it helps prevent uneven resource distribution and waste. This study explored a threshold effects identification framework related to human health based on quantifying passive green exposure, which characterizes the supply and service capacity of urban green spaces. A case study in Xiamen included a survey of 902 investigated individuals was conducted to collect self-reported health data. Their passive green exposure was quantified using open access geospatial data to quantify the individuals’ actual green visibility, availability and proximity. A generalized additive model (GAM) was employed to detect non-linear relationships and identify threshold effects by its derivative. The results showed significant non-linear relationships exist between green visibility and availability and physical health in Xiamen City, with threshold effects. At the individual level, achieving the green visibility thresholds (0.1 and 0.15) and availability thresholds (0.26 and 0.35) were associated with significant social health benefits. Future research should integrate both active and passive green exposure metrics and employ threshold effects identification in different urban contexts, providing more accurate guidance for healthier urban green spaces planning.