Research on the Impact of PM2.5 Pollution and Climate Change on Respiratory Diseases in Chinese Children Based on XGBoost-SHAP

Abstract

Children are among the most sensitive groups to air pollution. This study focuses on Chinese children aged 0–16 years, integrating six waves of tracking data from the China Family Panel Studies (CFPS, 2012–2022), the ChinaHighAirPollutants (CHAP) dataset, and MOD11A1 land surface temperature (LST) data, covering 20,241 samples across 25 provinces. Using the eXtreme Gradient Boosting–SHapley Additive exPlanations (XGBoost-SHAP) framework, we quantified the relative contributions of fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and climate factors to children’s respiratory disease risk. The overall area under curve (AUC) was 0.6765, with urban and rural sub-models achieving 0.6576 and 0.6864, respectively. SHAP analysis revealed that the temporal variable ranked first, reflecting population-level improvements from 2012 to 2022; age ranked second, with a 70.1% prevalence in the 0–6 age group. Rural PM2.5 contribution was approximately 1.68 times that of urban areas; the O3 effect showed opposite directions between urban (risk) and rural (protective association) settings; solid fuel contribution in rural areas was approximately 2.25 times the urban level. Regional clustering analysis identified differentiated environmental drivers across five geographic types. These findings provide a quantitative basis for differentiated regional prevention strategies.