Long-term Exposure to Fine Particulate Matter and Its Constituents Is Related to Self-reported Visual Impairment Among Middle-aged and Older Adults - a Longitudinal Study in China

Sep 28, 2026

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Visual impairment creates a growing global health burden, but whether long-term exposure to fine particulate matter (PM2.5) constituents increases risk remains unclear. This longitudinal study evaluates associations between multi-year PM2.5 exposure and specific chemical constituents and the incidence of self-reported fair or poor vision among adults aged 45+ in China (2011–2018). Time-dependent Cox models and sensitivity analyses assess nonlinear and subgroup effects.

LanguageEnglish

CategoryHealthcare

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Pages10

Reading Time25 min

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Abstract

Introduction

Visual impairment as a global public health issue

Links between air pollution and ocular diseases

Methods

Results

Conclusion

Wang et al. BMC Public Health (2025) 25:4397 BMC Public Health [https://doi.org/10.1186/s12889-025-25648-y](https://doi.org/10.1186/s12889-025-25648-y) RESEARCH Open Access Long-term exposure to fine particulate matter and its constituents is related to self-reported visual impairment among middle-aged and older adults: a longitudinal study in China Songtao Wang 1†, Xueying Li2†, Xiufen Liu 1, Yibo Wang 1, Dandan Zhou3* and Chengwei Lu 1* Abstract Background Visual impairment (VI) poses an increasing global health burden, yet the long-term effects of fine particulate matter (PM2.5) constituents on VI remain unclear. This study aimed to evaluate associations between longterm exposure to PM2.5 and its constituents and the risk of VI. Methods We used data from the nationally representative China Health and Retirement Longitudinal Study (CHARLS, 2011–2018) including adults aged ≥ 45 years. Long-term exposure to PM2.5 and its constituents (SO42–, NO3–, NH4+, organic matter (OM), and black carbon (BC)) was obtained from the Tracking Air Pollution in China dataset and linked to participants’ residential cities. The 3-year moving average concentration was used as the primary exposure metric to capture cumulative effects, while the 1-year average concentration was applied for sensitivity analysis. VI was defined as self-reported fair or poor vision. Associations were estimated using time-dependent Cox models, with restricted cubic spline (RCS), stratified and interaction analyses to assess nonlinear and subgroup effects. Results Over 27,443 person-years of follow-up, 3,736 participants developed VI. Per interquartile range (IQR) increase in 3-year moving average concentrations, higher risks of VI were observed for PM2.5 (HR = 1.09, 95% CI: 1.03–1.15), SO42–(HR = 1 . 13, 95% CI: 1 .05–1. 22), NO3–(HR = 1 . 06, 95% CI: 1 .00–1. 13), NH4+ (HR = 1 . 09, 95% CI: 1.02–1. 17), OM (HR = 95% CI: 1. 15, 1.07–1. 24), and BC (HR = 1 . 24, 95% CI: 1.14–1. 34) . RCS analysis revealed non-linear associations for PM2.5, NO3–, NH4+, and OM, whereas SO42– and BC showed approximately linear trends. Associations were more pronounced among older adults (> 60 years old), smokers, and those with hypertension. Conclusion Long-term exposure to PM2.5 and its constituents significantly increases the risk of VI among middleaged and older adults in China, highlighting the need for targeted environmental health policies. Keywords Black carbon, Fine particulate matter, Time-dependent Cox models, Visual impairment †Songtao Wang and Xueying Li were contributed equally to this work. *Correspondence: Dandan Zhou [zhoudan0928@jlu.edu.cn](zhoudan0928@jlu.edu.cn)[ ](zhoudan0928@jlu.edu.cn)Chengwei Lu[lcwchina800@jlu.edu.cn](lcwchina800@jlu.edu.cn) 1Department of Ophthalmology, the First Hospital of Jilin University, No. 1 Xinmin St., Changchun, Jilin 130021, China 2Department of Neonatology, Children’s Medical Center, the First Hospital of Jilin University, No. 1 Xinmin St., Changchun, Jilin 130021, China 3Department of Radiology, the First Hospital of Jilin University, No. 1 Xinmin St., Changchun, Jilin 130021, China © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by stat

FAQs

What exposure and outcomes are studied in this longitudinal analysis?

The study assesses long-term exposure to PM2.5 and constituents (SO42-, NO3-, NH4+, organic matter, and black carbon) linked to participants’ residential cities. Visual impairment is defined as self-reported fair or poor vision.

How is long-term exposure measured and modeled?

The primary exposure metric is the 3-year moving average concentration to capture cumulative effects, with the 1-year average used for sensitivity analysis. Associations are estimated using time-dependent Cox models, including restricted cubic splines for nonlinear relationships.

What key results show about the relationship between PM2.5 constituents and visual impairment?

Per interquartile range increase in 3-year moving average concentrations, higher risks of visual impairment were observed for PM2.5 and multiple constituents (including SO42-, NO3-, NH4+, organic matter, and black carbon). Nonlinear associations were detected for PM2.5, NO3-, NH4+, and organic matter, while SO42- and black carbon were approximately linear.

Sep 28, 2026

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