Evidence map›Paper›PMID 37171445›Full record

ArticleSingapore medical journal2025

Association between visual impairment and body mass index in students from rural China.

Hongyu Guan, Zhijie Wang, Yuxiu Ding, Yunyun Zhang, Kang Du, Yaojiang Shi

Open access · diamondAbstract read
In one paragraph

Article in Singapore medical journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 51% of its field
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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. Article
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

6 authors at 1 institution in 1 country.

Hongyu GuanCenter for Experimental Economics in Education, Shaanxi Normal University, Xi'an, China.
Zhijie Wang
Yuxiu Ding
Yunyun Zhang
Kang Du
Yaojiang Shi
Shaanxi Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionVisual impairment and obesity remain the major public health issues among school-age students in rural areas of China. Obesity is an underlying risk of vision problems. This study aimed to assess the association between visual impairment and body mass index (BMI) among school-age students in rural northwest China.

methodsThis study included 39,385 students from the 4 th to 9 th grade in rural northwest China. From 2018 to 2020, students underwent an assessment of visual acuity (VA) and completed a questionnaire on family demographics, and height and weight measurements. Multiple logistic regression analyses were used to analyse the data.

resultsThe association between visual impairment and BMI groups was significant in the study population ( P = 0.002) and in different groups (at the different educational, provincial and national levels) ( P < 0.001, separately). Multiple logistic regression analyses revealed a positive relationship between visual impairment and obesity in the study population, including those attending primary school, Han students and the residents of Ningxia autonomous region.

conclusionThe association between visual impairment and obesity was significant among school-age students in rural northwest China. There should be implementation of policies to address the problem about visual impairment and obesity among school-age students in rural areas.

Indexed as

Body Mass IndexObesityVision DisordersAdolescentChildChinaCross-Sectional StudiesFemaleHumansLogistic ModelsMaleRural PopulationStudentsSurveys and QuestionnairesVisual AcuityBMIrural Chinaschool-age studentsvisual impairment

Identifiers

PMID37171445
PMCPMC12364395
OpenAlexW4376224606

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

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.