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ORIGINAL RESEARCH article
Front. Public Health
Sec. Environmental Health and Exposome
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1565744
This article is part of the Research Topic Mapping the Unseen: Advancements and Innovations in Spatial Epidemiology for Disease Dynamics and Public Health Interventions View all 8 articles
A study on the spatial distribution of life expectancy and its air pollution factors in China based on geographically weighted regression
Provisionally accepted- 1 Xiamen Haicang Hospital, Xiamen, China
- 2 Fuwai Central China Cardiovascular Hospital, Zhengzhou, Henan Province, China
- 3 QianDongNanZhou Center for Disease Control and Prevention, QianDongNanZhou, China
- 4 Nanjing Lishui Dongping Street Health Center, Nanjing, China
Background: Life expectancy in China has demonstrated a consistent upward trend, yet significant disparities persist across provinces. Addressing these regional imbalances necessitates a comprehensive investigation into the determinants of life expectancy. Previous research has largely overlooked the critical role of spatial heterogeneity, which is essential for understanding the underlying mechanisms driving these disparities. By incorporating spatial analysis, this study aims to identify and address the factors contributing to the uneven distribution of life expectancy across China, thereby providing a more nuanced understanding of regional health inequalities. Methods: Therefore, this study investigated the spatial distribution patterns of life expectancy across 31 provinces in China in 2020 by conducting descriptive and spatial autocorrelation analyses, utilizing life expectancy data alongside key air pollution indicators(PM2.5, SO2, NO2, and PM10). To address spatial heterogeneity, the geographically weighted regression (GWR) model was applied to assess the regional variations in the impact of air pollutants on life expectancy. This approach allows for the incorporation of geographic coordinates into the regression coefficients, capturing localized effects and providing a more nuanced understanding of the relationship between air pollution and life expectancy across different regions.Results: The findings revealed that in 2020, China exhibited a distinct spatial autocorrelation in life expectancy, predominantly characterized by two aggregation patterns: high-high and low-low clusters. The analysis demonstrated that air pollutants, including SO2, NO2, and PM10, exerted significant influences on life expectancy, albeit with regional variations. Specifically, SO2 exhibited a more pronounced negative impact on life expectancy in southern cities, while NO2 demonstrated a stronger effect in northwestern regions. Notably, PM10 showed a significant influence limited to Yunnan Province, highlighting the spatial heterogeneity in the relationship between air pollution and life expectancy across China. Conclusions: These findings highlight the imperative for local governments to develop and implement region-specific air pollution control measures, taking into account the unique environmental and socio-economic conditions of their respective areas.
Keywords: Life Expectancy, Air Pollution, Spatial heterogeneity, spatial autocorrelation, Geographically weighted regression
Received: 27 Jan 2025; Accepted: 20 Mar 2025.
Copyright: © 2025 Hu, Yu, Yang and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xing Zhang, Nanjing Lishui Dongping Street Health Center, Nanjing, China
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