Evidence map›Paper›PMID 42591222›Full record

SynthesisFrontiers in nutrition2026

Abdominal obesity among Chinese children and adolescents: a systematic review and meta-analysis of prevalence and study-level heterogeneity.

Bo Chen, Xufeng Xu, Zisheng Li, Jiaqing Dou

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Bo Chen *Department of Nuclear Medicine, The Fourth Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Xufeng Xu *Department of Traditional Chinese Medicine (TCM) Surgery, The Fourth Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Zisheng Li *Department of Nuclear Medicine, The Fourth Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Jiaqing DouDepartment of Endocrinology, The Fourth Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Abdominal obesity in youth is a nutrition-related public health concern and may capture cardiometabolic risk beyond BMI. We aimed to estimate the pooled prevalence of abdominal obesity among Chinese children and adolescents and explore study-level heterogeneity. Methods: PubMed, Web of Science, Embase, CNKI, WanFang, and VIP were searched from inception to December 31, 2025. Eligible studies reported abdominal obesity prevalence among children and adolescents in China. Random-effects meta-analysis of proportions was performed. Subgroup analyses and exploratory meta-regression assessed variation by survey year, sex, urban-rural setting, diagnostic criterion, and study quality. Results: Twenty-eight studies contributing 30 prevalence estimates were included. The pooled prevalence was 20.0% (95% CI: 19.0-22.0%; 95% prediction interval: 11.9-31.3%), with very high heterogeneity (I Conclusion: Standardized waist-based surveillance, alongside BMI, is needed to improve comparability across studies and to support school- and community-based prevention strategies targeting central adiposity in Chinese youth. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251053503, identifier PROSPERO (CRD420251053503).

Indexed as

abdominal obesitychildren and adolescentsChinaMeta-analysisnutritional epidemiologyprevalencesystematic review

Identifiers

PMID42591222
PMCPMC13461509

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.