Identifying the main economic-social influencing factors of health risks of PM_2.5 pollution is significant for the development of environmental quality management and health risk prevention. Through spatial correlation analysis of PM2.5 pollution in the Yangtze River Delta (YRD) region, significant positive spatial dependence of PM2.5 pollution is observed. Given the spatial proximity and temporal trend effects of regional air pollution, and the limitations of the existing grey incidence models in integrating different dimensions trend characteristics of panel data, this paper proposes a grey dihedral angle incidence model (GDAIM) to identify the main influencing factors of regional PM_2.5 pollution health risk. By constructing the three-dimensional data matrix network structures and studying the angle relationship between two network planes, a difference-measure method is developed, and the modeling steps of the GDAIM are given. Focusing on the ‘high-high’ clustering area of PM_2.5 pollution in the YRD, the GDAIM is used to examine the association between PM_2.5 health risk and the economic-social factors. Results show that particulate matter and sulfur dioxide emissions are the main factors, followed by rural population and nitrogen oxide emissions. The findings can provide theoretical support for joint prevention and control of air pollution.