BMC Public Health (Jul 2022)

The superposition effects of air pollution on government health expenditure in China— spatial evidence from GeoDetector

  • Qi Xia,
  • Xiyu Zhang,
  • Yanmin Hu,
  • Wanxin Tian,
  • Wenqing Miao,
  • Bing Wu,
  • Yongqiang Lai,
  • Jia Meng,
  • Zhixin Fan,
  • Chenxi Zhang,
  • Ling Xin,
  • Jingying Miao,
  • Qunhong Wu,
  • Mingli Jiao,
  • Linghan Shan,
  • Nianshi Wang,
  • Baoguo Shi,
  • Ye Li

DOI
https://doi.org/10.1186/s12889-022-13702-y
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 15

Abstract

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Abstract Background As the fifth-largest global mortality risk factor, air pollution has caused nearly one-tenth of the world’s deaths, with a death toll of 5 million. 21% of China’s disease burden was related to environmental pollution, which is 8% higher than the US. Air pollution will increase the demand and utilisation of Chinese residents’ health services, thereby placing a greater economic burden on the government. This study reveals the spatial impact of socioeconomic, health, policy and population factors combined with environmental factors on government health expenditure. Methods Spearman’s correlation coefficient and GeoDetector were used to identify the determinants of government health expenditure. The GeoDetector consist of four detectors: factor detection, interaction detection, risk detection, and ecological detection. One hundred sixty-nine prefecture-level cities in China are studied. The data sources are the 2017 data from China’s Economic and Social Big Data Research Platform and WorldPOP gridded population datasets. Results It is found that industrial sulfur dioxide attributed to government health expenditure, whose q value (explanatory power of X to Y) is 0.5283. The interaction between air pollution factors and other factors will increase the impact on government health expenditure, the interaction value (explanatory power of × 1∩× 2 to Y) of GDP and industrial sulfur dioxide the largest, whose values is 0.9593. There are 96 simple high-risk areas in these 169 areas, but there are still high-risk areas affected by multiple factors. Conclusion First, multiple factors influence the spatial heterogeneity of government health expenditure. Second, health and socio-economic factors are still the dominant factors leading to increased government health expenditure. Third, air pollution does have an important impact on government health expenditure. As a catalytic factor, combining with other factors, it will strengthen their impact on government health expenditure. Finally, an integrated approach should be adopted to synergisticly governance the high-risk areas with multi-risk factors.

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