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ORIGINAL RESEARCH article
Front. Public Health
Sec. Environmental Health and Exposome
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1541803
This article is part of the Research TopicClimate Change, Air Pollution, and Health Inequality: Vulnerability of Marginalized PopulationsView all 9 articles
Exploring association between ambient air pollution and glaucoma in China: A nationwide analysis with predictive modeling based on the China health and Retirement Longitudinal Study Author
Provisionally accepted- 1Eye Center, Xiamen University, Xiamen, China
- 2Department of Pharmacy, Shanghai Pudong Hospital, Shanghai, Shanghai Municipality, China
- 3Sun Yat-sen University Cancer Center (SYSUCC), Guangzhou, Guangdong Province, China
- 4Chongqing Three Gorges Medical College, Chongqing, China
- 5The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
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Background：Glaucoma, a leading global cause of blindness, has garnered increasing research attention in recent years concerning its potential association with environmental factors. This study investigates the influence of various environmental pollutants on glaucoma prevalence among middle-aged and elderly populations in China, a country with a high incidence of the disease. Methods ： Using data from 17,184 participants in the 2015 China Health and Retirement Longitudinal Study (CHARLS), individuals were grouped based on glaucoma diagnosis. Environmental pollutant exposure levels were derived from satellite-based spatiotemporal models. Standardized linear regression and restrictedcubic spline (RCS) analysis were applied to evaluate the impact of pollutants on glaucoma across different covariate-adjusted models, while logistic regression was used to assess significant variables for constructing and evaluating a predictive model.Results： After adjusting for covariates, six pollutants (PM2.5, PM10, PM1, NH4, Cl, and NO3) demonstrated significant associations with glaucoma incidence. Subsequent logistic regression revealed that the occurrence of glaucoma may be influenced by a combination of environmental pollutants (NH4 and NO3), regional categories, gender, age, educational level, and diabetes history.Conclusions：In conclusion, this study offers a novel perspective on glaucoma risk prediction by integrating environmental pollutants, potentially contributing to enhanced preventive strategies for this condition.
Keywords: Glaucoma, Air pollutant, CHARLS, machine learning, Middle-aged and older adults
Received: 08 Dec 2024; Accepted: 09 Apr 2025.
Copyright: © 2025 Li, Luo, Lei, Zhang, Jiafeng and Sun. 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:
Tang Jiafeng, Chongqing Three Gorges Medical College, Chongqing, 404120, China
Yiqing Sun, Chongqing Three Gorges Medical College, Chongqing, 404120, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.