Benefits of clean air for school children's vision health

Myopia has become a significant public health concern among school-aged children in East Asia. A growing body of evidence acknowledges the multifactorial nature of myopia, including genetic susceptibility, lifestyle habits, and environmental influences. However, the specific role of air quality on vision remains poorly understood due to many confounding variables. Here, we applied an explainable machine learning framework with a large multifactorial cohort to identify key drivers of uncorrected visual acuity and to quantify the potential vision benefits of cleaner air in nearly 30,000 school-aged children. We show that, after controlling for potential confounders, lower ambient nitrogen dioxide and fine particles levels are independently associated with better vision. Primary school students and children with mild-to-moderate myopia benefit more from cleaner air than highly myopic or senior school students. These findings reinforce the emerging view that air pollution plays a significant and modifiable role in visual development. Importantly, our results uniquely indicate that early interventions to reduce air pollution exposure for younger children could yield greater benefits.

Authors

Institutions

Publication Details

Journal
PNAS Nexus
Published
2025-08-30
DOI
https://doi.org/10.1093/pnasnexus/pgaf279
Citations
1
Primary Topic
Ophthalmology and Visual Impairment Studies
Type
article
Field-Weighted Citation Impact
1.35

Funders

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

Benefits of clean air for school children's vision health

Bei Du, Congchao Lu, A. R. MacKenzie, Yuqing Dai et al.
1 citations
PNAS Nexus
Ophthalmology and Visual Impairment Studies
1.35
article

Benefits of clean air for school children's vision health

Bei Du, Congchao Lu, A. R. MacKenzie, Yuqing Dai, Xi Chen, Naijun Tang, Ruihua Wei, Zongbo Shi, Hua Yan
article en
1 citations

Abstract

Myopia has become a significant public health concern among school-aged children in East Asia. A growing body of evidence acknowledges the multifactorial nature of myopia, including genetic susceptibility, lifestyle habits, and environmental influences. However, the specific role of air quality on vision remains poorly understood due to many confounding variables. Here, we applied an explainable machine learning framework with a large multifactorial cohort to identify key drivers of uncorrected visual acuity and to quantify the potential vision benefits of cleaner air in nearly 30,000 school-aged children. We show that, after controlling for potential confounders, lower ambient nitrogen dioxide and fine particles levels are independently associated with better vision. Primary school students and children with mild-to-moderate myopia benefit more from cleaner air than highly myopic or senior school students. These findings reinforce the emerging view that air pollution plays a significant and modifiable role in visual development. Importantly, our results uniquely indicate that early interventions to reduce air pollution exposure for younger children could yield greater benefits.

PNAS NexusVol. 4(9)
Tianjin Medical University Eye Hospital (CN), Tianjin Medical University (CN), University of Birmingham (GB)
Wellcome Trust, National Natural Science Foundation of China, Natural Science Foundation of Tianjin City, Tianjin Medical University, Tianjin Municipal Education Commission, National Science and Technology Major Project, Tianjin Medical University Eye Hospital
Openalex Percentile: Top 15%
Ophthalmology and Visual Impairment Studies
1.35
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.