Evidence map›Paper›PMID 40969368›Full record

ArticleFrontiers in endocrinology2025

Analysis of prevalence and associated biomarkers of sarcopenia in older adults living in rural community in Wuhan, China.

Yun Zhou, Kemeng Zhang, Yanling Zhang, Ping He, Zhaohui Wang

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2025. 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

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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.

  1. 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

5 authors.

Yun ZhouDepartment of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Kemeng ZhangDepartment of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yanling ZhangDepartment of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ping HeDepartment of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhaohui WangDepartment of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sarcopenia is a disease of loss of muscle mass and decreased skeletal muscle function with impaired ability in the activities of daily life. Exploring potential biomarkers for sarcopenia may lead to early screening and intervention for sarcopenia.This study investigated the prevalence and potential biomarkers of sarcopenia in older adults living in rural community in Wuhan,China. Methods: This cross-sectional study involved 236 older participants (age ≥65 years) who received a health examination that included body composition and 23 circulating biomarkers. Sarcopenia was defined by the Asian Working Group for Sarcopenia revised in 2019 (AWGS2019). We divided the participants into a non-sarcopenia group and a sarcopenia group. The correlation between biomarkers and sarcopenia was analyzed by independent sample Results: Among the 236 participants, 61% were females, with a mean age of 70.6 ± 4.4years. The prevalence of sarcopenia in rural community was 25.4%(men 20.7%, women 28.5%). Analyses were conducted using binary logistic regression, growth differentiation factor 11(GDF11), was an independent risk factor for sarcopenia [Exp (B) 1.031, 95% CI: 1.010-1.052, Conclusions: About a quarter of older adults in rural Chinese communities are at risk of sarcopenia. Lower BMI, lower serum ALB, FGF19, TNF-α, and higher circulating GDF11 are associated with sarcopenia.

Indexed as

BiomarkersRural PopulationSarcopeniaAgedAged, 80 and overBody CompositionChinaCross-Sectional StudiesFemaleHumansMalePrevalenceRisk FactorsBiomarkersbiomarkersdisease incidenceolder adultsrural communitysarcopenia

Identifiers

PMID40969368
PMCPMC12440784

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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.