Evidence map›Paper›PMID 37272170›Full record

ArticleZhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics2023

[Relationship between skeletal muscle mass index and metabolic phenotypes of obesity in adolescents].

Ling-Ling Tong, Xiao-Yan Ma, Mei Tian, Wen-Qing Ding

Open access · greenAbstract readEnglish Abstract
In one paragraph

Article in Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

4 authors at 1 institution in 1 country.

Ling-Ling TongSchool of Public Health and Management, Ningxia Medical University, Yinchuan 750004.
Xiao-Yan MaSchool of Public Health and Management, Ningxia Medical University, Yinchuan 750004.
Mei TianSchool of Public Health and Management, Ningxia Medical University, Yinchuan 750004.
Wen-Qing DingSchool of Public Health and Management, Ningxia Medical University, Yinchuan 750004.
Ningxia University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo study the relationship between skeletal muscle mass index (SMI) and metabolic phenotypes of obesity in adolescents, and to provide a basis for the prevention and control of adolescent obesity and related metabolic diseases.

methodsA total of 1 352 adolescents aged 12 to 18 years were randomly selected by stratified cluster sampling in Yinchuan City from October 2017 to September 2020, and they were surveyed using questionnaires, physical measurements, body composition measurements, and laboratory tests. According to the diagnostic criteria for metabolic abnormalities and the definition of obesity based on the body mass index, the subjects were divided into four metabolic phenotypes: metabolically healthy normal weight, metabolically healthy obesity, metabolically unhealthy normal weight, and metabolically unhealthy obesity. The association between SMI and the metabolic phenotypes was analyzed using multivariate logistic regression.

resultsThe SMI level in the metabolically unhealthy normal weight, metabolically healthy obesity, and metabolically unhealthy obesity groups was lower than that in the metabolically healthy normal weight group (

conclusionsIncreasing SMI can reduce the risk of the development of metabolic unhealthy/obesity.

Indexed as

Metabolic SyndromeObesity, Metabolically BenignPediatric ObesityAdolescentBody Mass IndexChildHumansMuscle, SkeletalPhenotypeRisk FactorsAdolescentMetabolic phenotypeObesitySkeletal mass index

Identifiers

PMID37272170
PMCPMC10247192
OpenAlexW4379375480

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.