Scholarlink

<p>China’s aging population and the rising public health burden from cognitive impairment are pressing concerns. Using mixed-effects models, we analyzed the association between particulate matter and its components with cognitive function using 20,115 observations from 123 Chinese cities and assessed economic costs under various socioeconomic scenarios. The single-pollutant model showed cognitive scores decrease with higher pollutant concentrations: PM<sub>1</sub> (−0.53 points/0.1 µg/m<sup>3</sup>), PM<sub>2.5</sub> (−0.30), PM<sub>10</sub> (−0.14), organic matter (−1.44), ammonium (−1.55), sulfate (−1.70), and black carbon (−7.23). Nitrate showed no statistical association. In the multi-pollutant model, PM₁, PM₂.₅, organic matter, sulfate, and black carbon exhibited a statistically negative association with cognitive scores. Sustainable strategies reducing particulate matter levels could mitigate aging impacts and lower economic costs by $19.35 billion by 2050, offering significant health and financial benefits.</p><p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Sustainable development reduces particulate matter emissions and mitigates aging’s cognitive impact

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月9日

查看全文
  • Guiming Zhu,
  • Yanchao Wen,
  • Rule Du,
  • Kexin Cao,
  • Rong Zhang,
  • Xiangfeng Lu,
  • Jie Liang,
  • Qian Gao,
  • Tong Wang

摘要

China’s aging population and the rising public health burden from cognitive impairment are pressing concerns. Using mixed-effects models, we analyzed the association between particulate matter and its components with cognitive function using 20,115 observations from 123 Chinese cities and assessed economic costs under various socioeconomic scenarios. The single-pollutant model showed cognitive scores decrease with higher pollutant concentrations: PM1 (−0.53 points/0.1 µg/m3), PM2.5 (−0.30), PM10 (−0.14), organic matter (−1.44), ammonium (−1.55), sulfate (−1.70), and black carbon (−7.23). Nitrate showed no statistical association. In the multi-pollutant model, PM₁, PM₂.₅, organic matter, sulfate, and black carbon exhibited a statistically negative association with cognitive scores. Sustainable strategies reducing particulate matter levels could mitigate aging impacts and lower economic costs by $19.35 billion by 2050, offering significant health and financial benefits.