Long-term exposure to PM2.5 and NO2 and risk of myopia in Chinese school-aged children: a cross-sectional study

Abstract Objective To explore the link between long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) and myopia prevalence in Chinese school-aged children. Methods Conducted from September 2023 to June 2024, this cross-sectional study included 23,983 school-aged children from six cities across China. Myopia was defined using non-cycloplegic refraction (SE < -0.50 D) combined with visual acuity testing. Three-year average concentrations of pollutants were sourced from the China High Air Pollutants (CHAP) dataset. We employed adjusted mixed-effects models to evaluate the relationship between exposure to air pollutants and the risk of myopia. Results In adjusted linear models, each interquartile range (IQR) increase in long-term PM2.5 exposure was associated with significantly higher odds of myopia (odds ratio [OR] = 1.63; 95% confidence interval [CI]: 1.14–2.33). However, non-linear modeling identified a pronounced departure from linearity (P for non-linearity < 0.001), characterized by a steep risk increase at lower concentrations followed by a plateau at higher levels. Consistent with this pattern, categorical analyses showed that children in PM2.5 exposure quartiles Q2-Q4 had substantially elevated odds of myopia compared with Q1 (OR range: 3.30–3.59).For NO2, the per-IQR association was not statistically significant (OR = 0.96; 95% CI: 0.84–1.09), yet exposure quartiles Q2-Q4 were all associated with significantly increased myopia risk relative to Q1 (OR range: 1.30–1.58). Subgroup analyses suggested variability across sex, grade level, and parental education, but no consistent pattern was observed. Results were robust after adjusting for ozone and using alternative exposure windows. Conclusion Our results provide clear evidence that ambient PM2.5 is an important environmental risk factor for childhood myopia, with a dose-response pattern indicating heightened vulnerability at commonly encountered exposure levels. The consistent risk associated with higher NO2 exposure further supports the role of air pollution. Mitigating myopia burden may therefore require integrating air quality criteria into public health strategies for children’s visual health.

Authors

Institutions

Publication Details

Journal
BMC Ophthalmology
Published
2026-01-29
DOI
https://doi.org/10.1186/s12886-025-04587-7
Primary Topic
Ophthalmology and Visual Impairment Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Long-term exposure to PM2.5 and NO2 and risk of myopia in Chinese school-aged children: a cross-sectional study

H.H. Kuang, Xin Guo, Keke Liu, Boran E et al.
BMC Ophthalmology
Ophthalmology and Visual Impairment Studies
article

Long-term exposure to PM2.5 and NO2 and risk of myopia in Chinese school-aged children: a cross-sectional study

H.H. Kuang, Xin Guo, Keke Liu, Boran E, Chenyu Zhang, Huijuan Luo
article en

Abstract

Abstract Objective To explore the link between long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) and myopia prevalence in Chinese school-aged children. Methods Conducted from September 2023 to June 2024, this cross-sectional study included 23,983 school-aged children from six cities across China. Myopia was defined using non-cycloplegic refraction (SE < -0.50 D) combined with visual acuity testing. Three-year average concentrations of pollutants were sourced from the China High Air Pollutants (CHAP) dataset. We employed adjusted mixed-effects models to evaluate the relationship between exposure to air pollutants and the risk of myopia. Results In adjusted linear models, each interquartile range (IQR) increase in long-term PM2.5 exposure was associated with significantly higher odds of myopia (odds ratio [OR] = 1.63; 95% confidence interval [CI]: 1.14–2.33). However, non-linear modeling identified a pronounced departure from linearity (P for non-linearity < 0.001), characterized by a steep risk increase at lower concentrations followed by a plateau at higher levels. Consistent with this pattern, categorical analyses showed that children in PM2.5 exposure quartiles Q2-Q4 had substantially elevated odds of myopia compared with Q1 (OR range: 3.30–3.59).For NO2, the per-IQR association was not statistically significant (OR = 0.96; 95% CI: 0.84–1.09), yet exposure quartiles Q2-Q4 were all associated with significantly increased myopia risk relative to Q1 (OR range: 1.30–1.58). Subgroup analyses suggested variability across sex, grade level, and parental education, but no consistent pattern was observed. Results were robust after adjusting for ozone and using alternative exposure windows. Conclusion Our results provide clear evidence that ambient PM2.5 is an important environmental risk factor for childhood myopia, with a dose-response pattern indicating heightened vulnerability at commonly encountered exposure levels. The consistent risk associated with higher NO2 exposure further supports the role of air pollution. Mitigating myopia burden may therefore require integrating air quality criteria into public health strategies for children’s visual health.

BMC OphthalmologyVol. 26(1)
Capital Medical University (CN), Chinese Center For Disease Control and Prevention (CN), Beijing Center for Disease Prevention and Control (CN)
Ministry of Science and Technology of the People's Republic of China, Beijing Municipal Health Commission, National Key Research and Development Program of China
Openalex Percentile: Top 73%
Ophthalmology and Visual Impairment Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.