Evidence map›Paper›PMID 41388515›Full record

ArticleBMC geriatrics2025

Dynamic sarcopenia transitions in older Chinese: physical activity and cognitive insights.

Yutao Li, Yuxin Tang, Weifeng Pan, Hengguo Song

Abstract read
In one paragraph

Article in BMC geriatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

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.

Yutao Li *School of Physical Education and Sports Science, South China Normal University, No.55, West of Zhongshan Avenue, Tianhe District, Guangzhou City, 510631, China.
Yuxin Tang *School of Physical Education and Sports Science, South China Normal University, No.55, West of Zhongshan Avenue, Tianhe District, Guangzhou City, 510631, China.
Weifeng PanSchool of Physical Education and Sports Science, South China Normal University, No.55, West of Zhongshan Avenue, Tianhe District, Guangzhou City, 510631, China. weifengpan@m.scnu.edu.cn.
Hengguo SongSchool of Physical Education and Sports Science, South China Normal University, No.55, West of Zhongshan Avenue, Tianhe District, Guangzhou City, 510631, China. tiyuxuey@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate sarcopenia state transitions (non-sarcopenia, possible sarcopenia, and sarcopenia) and their determinants among older Chinese adults, emphasizing the roles of physical activity, cognitive status, and other risk factors.

methodsA longitudinal study utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011–2015, integrating Multi-State Markov (MSM) models and Transformer-based deep learning approaches. We examined 5,756 participants (including 3,373 for deep learning) across three waves, with a mean age of 67.9 years (SD = 6.5). MSM models estimated transition intensities and probabilities between sarcopenia states. Deep learning with SHAP analysis identified key determinants of transitions and mortality. Covariates included age, sex, BMI, smoking, physical activity, mild cognitive impairment (MCI), and functional disability.

resultsMSM models indicated a high transition rate from non-sarcopenia to possible sarcopenia (intensity: 0.383, 95% CI: 0.355–0.411) and a 38.6% five-year recovery probability from possible sarcopenia to non-sarcopenia. Physical activity reduced deterioration risk (HR: 0.916, 95% CI: 0.842–0.997) and mortality in possible sarcopenia (HR: 0.565, 95% CI: 0.339–0.944). MCI increased deterioration risk (HR: 1.724, 95% CI: 1.268–2.346). Age > 80 significantly elevated deterioration (HR: 3.007, 95% CI: 1.992–4.538) and mortality risks (HR: 7.400, 95% CI: 2.542–21.544). Sex, BMI, smoking, and functional disability also influenced transitions.

conclusionsSarcopenia exhibits bidirectional progression, with physical activity serving as a key protective factor. MCI attenuates this benefit, highlighting the need for tailored interventions that address cognitive status and other risk factors in older adults.

Indexed as

CognitionExerciseSarcopeniaAgedChinaCognitive DysfunctionFemaleHumansLongitudinal StudiesMaleMiddle AgedRisk FactorsAgingCHARLSDeep learningMild cognitive impairmentMulti-State markov modelPhysical activitySarcopenia

Identifiers

PMID41388515
PMCPMC12817442

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.