Unplanned regional socioeconomic development contributes to PM2.5 pollution, which severely infringes on human well-being and even lives. Facing the spillover and migration of pollution, the cross-regional issue of environmental health inequalities implied in trade networks requires accurate recognition and research. In this research, a city-level PM2.5-related health impact complex network model (PHCNM) is developed. The Community Detection Algorithm (CDA) and the Stochastic Approach for Weighted Link-Structure Algorithm (SAWLSA) are optimized and applied to deconstruct the structures, hierarchies, and characteristics of PHCNM to assess the interactions of environmental health inequalities across regions and cities. At the urban layer, the empirical results suggest that the top 5 cities (i.e., Chongqing, Shanghai, Chengdu, Beijing, and Tianjin) have premature mortality of more than 25000 people each year, which is about 27% of the total. The demographic surge and PM2.5 pollution deterioration are responsible for the worsening health burden of cities. Chengdu, Suzhou, Shanghai, and Hangzhou are identified as development-driven critical cities; Shijiazhuang, Tangshan, Cangzhou, and Handan are recognized as pollution-driven critical cities. Thus, city-specific management and treatment of PM2.5 are possible depending on the characteristics of their environmental health inequalities. While at the regional layer, the urban agglomerations of Yangtze River Delta (YRD-UA) and Pearl River Delta (PRD-UA) transfer pollution and health threats through commercial interaction among cities, leaving the urban agglomerations of Beijing-Tianjin-Hebei (BTH-UA) and Chengdu-Chongqing (CC-UA) as victims of their environmental and health development. And the regional inequalities index elevates from 0.770 to 0.780, reflecting the easing of regional health inequalities. The research reveals that health inequalities significantly reside in communal or regional boundaries; therefore, the internalities and externalities of communal structures can offer insights into the regionalized and communalized development patterns of urban agglomerations.