Dynamic network analysis of air pollution-related health vulnerability: Implications for policy synergy

Air pollution impacts exhibit dynamic associations that cascade between natural ecosystems and socioeconomic networks over time. However, the current analysis of air pollution-related health vulnerability largely fails to account for dynamic interactions among contributing indicators. Addressing this gap is critical, as static strategies can underestimate the long-term health burden of chronic exposure. This, in turn, may lead to the allocation of insufficient or a low amount of resources. Using a nationally representative eight-year cohort dataset, a dynamic directed network among indicators was constructed to assess air pollution-related health vulnerability. Our analysis suggested the following: (1) A dynamic directed network in which air pollution exposure was directly associated with and indirectly linked to (via adaptive capacity) health sensitivity. These connections occurred both within the same time period and across subsequent intervals. (2) Vulnerability was greater in northern China than in southern China. Although the vulnerability rankings were generally consistent between the dynamic and static analyses for most cities, Tianjin and Beijing were exceptions. Both cities exhibited improved performance rankings in the dynamic analysis. This likely reflects progressive health gains that coincide with the implementation of clean-air policies. (3) Integrated mitigation and adaptation efforts appeared to be associated with health benefits.