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Background <p>Previous studies have thoroughly evaluated the association between long-term exposure to PM2.5 and mortality, but the effect of socioeconomic status on the association remains controversial.</p> Methods <p>We utilized the data of all-cause mortality per year, concentration of PM2.5, socioeconomic and demographic characteristics for 345 cities in China from 2000-2019. We applied the Poisson generalized estimating equations (Poisson GEE) model to explore the association between PM2.5 and mortality in cities with different quartiles of demographic and socioeconomic characteristics.</p> Results <p>Overall, every 10 µg/m ³ increase in PM2.5, the RR was 1.082 (95% CI:1.058-1.106) for all-cause mortality, with residents of the Northeast and Southwest regions having a higher risk of death. Cities with the highest quartiles of gender ratio, age, dependency rate, and migration rate had relative risks of 1.110 (95%&#xa0;CI: 1.020-1.208), 1.075 (95% CI: 1.018-1.135), 1.101 (95% CI: 1.068-1.135), and 1.108 (95% CI: 1.053-1.165), respectively. Stratified analyses showed that the exposure-mortality associations were strongest in cities with both the lowest and highest socioeconomic status (SES) quartiles.</p> Conclusion <p>The association between PM2.5 and mortality varied by socioeconomic status, demonstrating a U-shaped pattern with the highest mortality risk observed among residents in cities with both the lowest and highest socioeconomic levels.</p>

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Study of socioeconomic differences of long-term PM2.5 exposure and population mortality risk - based on 345 cities from 2000 to 2019 in China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月6日

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  • Surong Zhao,
  • Xingyu Zhang,
  • Ronghang Liu,
  • Junyan Liu,
  • Xiaoqian Shao,
  • Wanru Zhao,
  • Jiu Wang,
  • Yang Zhao,
  • Chunlei Han

摘要

Background

Previous studies have thoroughly evaluated the association between long-term exposure to PM2.5 and mortality, but the effect of socioeconomic status on the association remains controversial.

Methods

We utilized the data of all-cause mortality per year, concentration of PM2.5, socioeconomic and demographic characteristics for 345 cities in China from 2000-2019. We applied the Poisson generalized estimating equations (Poisson GEE) model to explore the association between PM2.5 and mortality in cities with different quartiles of demographic and socioeconomic characteristics.

Results

Overall, every 10 µg/m ³ increase in PM2.5, the RR was 1.082 (95% CI:1.058-1.106) for all-cause mortality, with residents of the Northeast and Southwest regions having a higher risk of death. Cities with the highest quartiles of gender ratio, age, dependency rate, and migration rate had relative risks of 1.110 (95% CI: 1.020-1.208), 1.075 (95% CI: 1.018-1.135), 1.101 (95% CI: 1.068-1.135), and 1.108 (95% CI: 1.053-1.165), respectively. Stratified analyses showed that the exposure-mortality associations were strongest in cities with both the lowest and highest socioeconomic status (SES) quartiles.

Conclusion

The association between PM2.5 and mortality varied by socioeconomic status, demonstrating a U-shaped pattern with the highest mortality risk observed among residents in cities with both the lowest and highest socioeconomic levels.