Evidence map›Paper›PMID 42282460›Full record

ArticleSports medicine and health science2026

The decision support system for preventing non-elderly sarcopenia: Data from NHANES 2011-2018.

Qiao He, Jingwei Cao

Abstract read
In one paragraph

Article in Sports medicine and health science, 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

2 authors.

Qiao HeSchool of Strength and Conditioning Training, Beijing Sport University, 100084, Beijing, China.
Jingwei CaoSports Training Laboratory, China Institute of Sport Science, 100061, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sarcopenia is a syndrome characterized by a progressive loss of skeletal muscle mass, strength, and function. This study aimed to identify independent factors influencing sarcopenia in a non-elderly population. Methods: This cross-sectional study analyzed data from 17 883 participants in the 2011-2018 National Health and Nutrition Examination Survey (NHANES). After the exclusion of individuals with missing data, a final analytical cohort comprised 11 288 participants aged 18-60. This study examined variables including demographic characteristics (age, sex, race), body mass index (BMI), lifestyle factors (vigorous activity, moderate activity, and activity time), dietary habits, laboratory tests, and health status (including sarcopenia). Univariable and multivariable logistic regression analyses were performed to identify independent factors influencing sarcopenia in the non-elderly population. Results: Among the 11 288 participants, 5 596 (49.57%) were men and 5 692 (50.43%) were women. Univariable and multivariable logistic regression analyses identified several factors significantly influencing the occurrence of sarcopenia, including sex, age, race, BMI, total caloric intake (TKCAL), vigorous work activity, moderate work activity, and sedentary behavior. In the multivariable analysis, male ( Conclusion: In the non-elderly population, the prevention and management of sarcopenia should focus on key factors such as sex, BMI, dietary caloric intake, and physical activity. That maintaining a healthy weight, increasing high-intensity physical activity, and reducing sedentary time potentially could lower the risk of sarcopenia.

Indexed as

ExerciseHealthModerate activitySarcopeniaVigorous activity

Identifiers

PMID42282460
PMCPMC13250197

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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 OpenQuestion graph.