Evidence map›Paper›PMID 39964957›Full record

ArticleJMIR public health and surveillance2025

Investigating the Trajectories of Poor Vision in Children and Adolescents in Wuhan, China From 2016 to 2019: Prospective Cohort Study.

Lijuan Xu, Hanjia Li, Fang Li, Tinghui Zhang, Jingyan Yan, Hong Yan, Lu He, Bin Yu

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

8 authors.

Lijuan Xu *Physical Examination Center, Renmin Hospital of Wuhan University, Wuhan, China.ORCID 0000-0003-1374-4343
Hanjia Li *Department of Epidemiology and Health Statistics, School of Public Health, Wuhan University, 115 Donghu Rd, Wuchang District, Wuhan, 430071, China, 86 13797095040.ORCID 0009-0006-6041-0329
Fang Li *Wuhan Center for Disease Control and Prevention, Wuhan, China.ORCID 0009-0005-6587-7916
Tinghui ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Wuhan University, 115 Donghu Rd, Wuchang District, Wuhan, 430071, China, 86 13797095040.ORCID 0009-0002-2523-6661
Jingyan YanDepartment of Epidemiology and Health Statistics, School of Public Health, Wuhan University, 115 Donghu Rd, Wuchang District, Wuhan, 430071, China, 86 13797095040.ORCID 0009-0007-6256-912X
Hong YanDepartment of Epidemiology and Health Statistics, School of Public Health, Wuhan University, 115 Donghu Rd, Wuchang District, Wuhan, 430071, China, 86 13797095040.ORCID 0000-0001-7031-6455
Lu HePhysical Examination Center, Renmin Hospital of Wuhan University, Wuhan, China.ORCID 0009-0005-0348-1019
Bin YuDepartment of Epidemiology and Health Statistics, School of Public Health, Wuhan University, 115 Donghu Rd, Wuchang District, Wuhan, 430071, China, 86 13797095040.ORCID 0000-0001-6941-8083

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Poor vision is a challenging public health problem among children and adolescents globally and in China. It is well-recognized that early onset of poor vision and progressing to moderate and severe poor vision will increase the risk of irreversible blinding complications. To achieve the national goal of poor vision control and prevention, it is essential to investigate and understand the development of poor vision among children and adolescents in China. Objective: This study aims to investigate the progression of poor vision among children and adolescents in Wuhan, China, based on a prospective cohort and to provide scientific evidence for the development and implementation of effective poor vision prevention and control programs. Methods: Data were derived from a 4-year prospective cohort (2016-2019) of primary and middle school students (N=108,585) in Wuhan, China. Vision condition was measured using the standard logarithmic visual acuity charts. A group-based trajectory model was used to identify trajectories of poor vision overall and by gender and region. Results: The mean age of the study subjects was 11.13 (SD 3.33) years, 200,110 (53.91%) were male and the majority (354404, 95.48%) were from urban areas. The prevalence of poor vision was 58.51% in 2016, 58.95% in 2017, 53.83% in 2018, and 54.79% in 2019. Group-based trajectory model identified 3 groups, including normal vision group (NVG) (27.4%), vision decline group (VDG) (17.8%), and moderate poor vision group (MPVG) (54.8%). A higher proportion of girls (57.8%) were in the MPV group compared to boys (50.5%), and the VDG showed greater changes in girls compared to boys. Furthermore, urban students (55.3%) had a higher proportion of MPV compared to rural students (47.5%), while urban students (17.2%) had a smaller proportion in the VDG compared to rural students (24%). Further analyses showed that as age increased, the likelihood of being categorized in the NVG decreased (β=-.417, P<.001), while the likelihood of being in the VDG (β=.058, P<.001) increased. Compared with boys, girls were more likely to be categorized in the VDG (β=.597, P<.001) and MPV group (β=.362, P<.001). Rural students were less likely than urban students to be categorized in the VDG (β=-.311, P<.001). Conclusions: The prevalence of poor vision among children and adolescents in Wuhan has remained high over the years, with a slight decrease in recent years. The study identified three groups: normal vision, vision decline, and moderate poor vision. Girls and students from urban areas were more likely to have moderate poor vision, while boys and rural students had a higher proportion of vision decline. These findings provide valuable information for implementing poor vision prevention and control policies in the region.

Indexed as

Vision DisordersVision, LowAdolescentChildChinaCohort StudiesDisease ProgressionFemaleHumansMalePrevalenceProspective Studieschildren and adolescentsChinagender differencegroup-based trajectory modelmoderate poor vision groupmyopianormal vision grouppoor visionprevalencevision decline group

Identifiers

PMID39964957
PMCPMC11855164

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.