JOURNAL ARTICLE

Effects of China's Clean Air Act on Frailty Levels Among Middle-Aged and Older Adults: A Population-Based Quasi-Experimental Study.

  • Published In: Journals of Gerontology Series A: Biological Sciences & Medical Sciences, 2024, v. 79, n. 4. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Guo, Yujia; Yang, Fan 3 of 3

Abstract

This article examines the impact of China’s Clean Air Action (CCAA), a national air pollution control policy implemented from 2013 to 2017, on frailty levels among Chinese adults aged 45 and older. Using data from the China Health and Retirement Longitudinal Study (CHARLS) and employing propensity score matching with difference-in-differences analysis, the study found that the CCAA significantly reduced frailty progression—measured by the Frailty Index (FI)—among individuals who were robust or prefrail before the policy, but showed no significant effect on those already classified as frail. Specifically, the CCAA lowered the risk of worsening from robust to prefrail or frail by 7.0% and from prefrail to frail by 3.9%, without facilitating recovery from frail or prefrail states. The policy’s benefits were consistent across subgroups defined by age, gender, Hukou status, education, and social participation, highlighting the value of proactive air quality improvements in mitigating frailty deterioration in midlife and older populations.

Additional Information

  • Source:Journals of Gerontology Series A: Biological Sciences & Medical Sciences. 2024/04, Vol. 79, Issue 4, p1
  • Document Type:Article
  • Subject Area:Environmental Sciences
  • Publication Date:2024
  • ISSN:1079-5006
  • DOI:10.1093/gerona/glae040
  • Accession Number:176469950
  • Copyright Statement:Copyright of Journals of Gerontology Series A: Biological Sciences & Medical Sciences is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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