Evidence map›Paper›PMID 40492984›Full record

ArticleInvestigative ophthalmology & visual science2025

Prevalence of Myopia and Axial Length Distribution in China: The Wuhu Children and Adolescents Eye Study.

Li Dong, Wen-Da Zhou, Ya-Bin Hu, Li Wei, Wei Cao, Ning-Hong Chen, Di Liu, Cheng Zhen, Yu-Chun Zheng, Jost B Jonas and 1 more

Abstract read
In one paragraph

Article in Investigative ophthalmology & visual science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Trend of Myopia Incidence Among Adolescents (2018-2025) in Senior High School: An 8-Year Retrospective Study in Multi-Regions of China, With Projections to 2030.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Li DongBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Wen-Da ZhouBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Ya-Bin HuBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Li WeiMingsii Co., Ltd, Beijing, China.
Wei CaoWuhu Center for Disease Control and Prevention, Wuhu, Anhui Province, China.
Ning-Hong ChenDepartment of Ophthalmology and Optometry, Ophthalmic Hospital of Wuhu, Wuhu, Anhui Province, China.
Di LiuNational Digital Health Center of China Top Think Tanks, Beijing Normal University, Beijing, China.
Cheng ZhenAIFuture Lab, Beijing, China.
Yu-Chun ZhengAIFuture Lab, Beijing, China.
Jost B JonasRothschild Foundation Hospital, Institut Français de Myopie, Paris, France.
Wen-Bin WeiBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To re-assess myopia prevalence, update the database of ocular biometric parameters, and assess the prevalence of fundus abnormalities in schoolchildren and adolescents in Wuhu, Anhui Province, China. Methods: The Wuhu Children and Adolescents Eye Study (WCAES) is a longitudinal population-based cohort study, and the cross-sectional analysis results of the baseline assessment are reported here. It included 315,569 out of 330,173 eligible children and adolescents (95.6%), ages 2 to 19 years, from 513 schools with measurements of presenting distance visual acuity (PDVA) and uncorrected distance visual acuity (UDVA), non-cycloplegic autorefractometry, ocular biometry, and color fundus photography. Fundus abnormalities were assessed by an artificial intelligence-based system. Results: Prevalences of likely myopia (-1.00 D < refractive error ≤ -0.50 D), myopia (refractive error ≤-1.00 D), low myopia (-3.00 D < refractive error ≤ -1.00 D), moderate myopia (-6.00 D < refractive error ≤ -3.00 D), and high myopia (refractive error ≤ -6.00 D) were 13.58% (95% confidence interval [CI], 13.46-13.70), 56.92% (95% CI, 56.74-57.10), 32.87% (95% CI, 32.70-33.04), 19.74% (95% CI, 19.60-19.88), and 4.31% (95% CI, 4.24-4.38), respectively. Among high-school students, myopia prevalence was 92.18% (95% CI, 91.68-92.68). High myopia prevalence rates in kindergarten, elementary, middle, and high schools were 0.30% (95% CI, 0.18-0.43), 1.53% (95% CI, 1.48-1.59), 9.05% (95% CI, 8.86-9.24), and 18.57% (95% CI, 17.84-19.29), respectively. Higher prevalence of overall myopia and high myopia was associated (all P < 0.001) with female sex (odds ratio [OR] = 0.81 and OR = 0.91, respectively), older age (OR = 1.45 and OR = 1.48, respectively), longer axial length (OR = 3.71 and OR = 5.89, respectively), and higher prevalence of fundus tessellation (OR = 1.10 and OR = 1.21, respectively.). The percentage of myopic individuals using vision correction and the prevalence of an age-dependent defined suboptimal PDVA in the myopic population were 48.05% (95% CI, 47.81-48.28) and 65.84% (95% CI, 65.51-66.16), respectively. Conclusions: Compared with previous studies, the present investigation suggests a further rise in the prevalence of myopia, particularly high myopia, in the younger generations in China.

Indexed as

Axial Length, EyeMyopiaAdolescentBiometryChildChild, PreschoolChinaCross-Sectional StudiesFemaleHumansMalePrevalenceRefraction, OcularVisual AcuityYoung Adult

Identifiers

PMID40492984
PMCPMC12165258

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