Multimethod geospatial modeling of life expectancy determinants in China

Introduction Although China has achieved sustained growth in life expectancy, significant spatial disparities persist across regions, necessitating investigation into their underlying determinants. Methods This study systematically examines provincial-level life expectancy patterns in 2020 using multiple analytical approaches, including multiple linear regression (MLR), spatial lag model (SLM), geographically weighted regression (GWR), multiscale geographically weighted regression (MGWR), and Geodetector. The analysis incorporates comprehensive datasets covering socioeconomic indicators, education levels, healthcare resources, and environmental factors. Results The findings reveal a pronounced east–west gradient, with coastal provinces exhibiting significantly higher life expectancy than inland regions. Spatial analysis identified distinct clustering patterns (Global Moran’s I = 0.5339, p 0.001), with high-high clusters in eastern areas and low-low clusters in western regions. MGWR demonstrated superior performance by accounting for spatial variations in factor influences. Education level emerged as a fundamental determinant (PD = 0.850, p = 0.012), showing particularly strong effects in western China. Economic development also showed substantial explanatory power (PD = 0.661, p = 0.030), with greater influence in western provinces. Household consumption expenditure per capita (PD = 0.586, p = 0.027) and urbanization rate (PD = 0.633, p = 0.036) were additionally identified as significant factors. Household size showed a negative association exclusively in certain western regions. Notably, healthcare resource allocation demonstrated no significant effect (PD = 0.344, p = 1.000), while PM 2.5 also lacked statistical significance (PD = 0.344, p = 1.000). Furthermore, Geodetector interaction analysis revealed that economic development and education level exhibited particularly strong synergistic effects (interaction PD = 0.944). Conclusion The findings provide a scientific basis for formulating region-specific health policies and offer valuable insights for advancing the Healthy China initiative.