Evidence map›Paper›PMID 30413948›Full record

ArticleFrontiers of medicine2018

Analyzing the distinguishing factors that affect childhood obesity in South Korea.

So Jung Yang, Hun-Sung Kim, Kun-Ho Yoon

Abstract read
PubMed Publisher
In one paragraph

Article in Frontiers of medicine, 2018. 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 34% 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, 4 citations in OpenAlex.

  1. Review
  2. Review
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

3 authors at 1 institution in 1 country.

So Jung YangDepartment of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, 06591, Republic of Korea.
Hun-Sung KimDepartment of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, 06591, Republic of Korea.
Kun-Ho YoonDepartment of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, 06591, Republic of Korea. yoonk@catholic.ac.kr.
Catholic University of Korea · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding obesity in children is crucial because it can lead to adulthood obesity and result in fatal chronic diseases. Distinctive factors associated with obesity in adults have been described, but distinctive factors related to children remain unclear. We analyzed the correlation between the percentage of body mass index and lifestyle habits by conducting surveys on physical, nutritional, and psychological factors, and we used annual physical examination data to compare different traits among elementary school students (n = 197) and middle school students (n = 461). Our study revealed that the computing hours in elementary school students with overweight and obesity were significantly correlated with the percentage of body mass index (r = 0.29 on school days and r = 0.35 on days off, all P < 0.05). No statistically significant difference was found (all P > 0.05) in the computing hours of middle school students with overweight and obesity. Childhood obesity can cause depression and reduce children's quality of life because of their distorted body perception. In conclusion, physical factors directly affecting childhood obesity and psychological and environmental factors surrounding a child should be considered.

Indexed as

Body Mass IndexAdolescentChildDietExerciseFeeding BehaviorFemaleHumansMalePediatric ObesityPhysical ExaminationQuality of LifeRepublic of KoreaStudentsSurveys and Questionnaireschildhood obesityeating habitspercentage of body mass indexquality of lifescreen time

Identifiers

PMID30413948
OpenAlexW2899886230

What OpenQuestion holds

Textmetadata
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.