Evidence map›Paper›PMID 41243371›Full record

ArticleJournal of cachexia, sarcopenia and muscle2025

3D Body Scanning-Derived Normative Values of Appendicular Circumferences: A Novel Tool for Sarcopenia Screening in Chinese Adults.

Huijing He, Qiaolu Cheng, Zhiyue Zhang, Yaoda Hu, Zhiming Lu, Wei Han, Ji Tu, Ang Li, Zhen Song, Yawen Liu and 6 more

Abstract read
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

16 authors.

Huijing HeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
Qiaolu ChengDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
Zhiyue ZhangDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
Yaoda HuDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
Zhiming LuDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
Wei HanDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
Ji TuDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
Ang LiDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
Zhen SongState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Yawen LiuSchool of Public Health, Jilin University, Changchun, China.
Tan XuSchool of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou, China.
Qing ChangShengjing Hospital, China Medical University, Shenyang, China.
Qiong OuSleep Center, Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangdong Provincial Geriatrics Institute, Guangzhou, China.
Hui PanDepartment of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, Translation Medicine Centre, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Zichao WangDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
Guangliang ShanDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.ORCID 0000-0002-4535-8941

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAppendicular circumferences (ACs) are critical predictors of skeletal health, cardiovascular disease risk and mortality. Currently, comprehensive reference values and associated factors for thigh (TC), calf (CC), upper arm (UAC) and forearm (FC) circumferences remain unestablished in Chinese adults.

methodsThis community-based cross-sectional study (China National Health Survey, April 2023-November 2024) enrolled 8915 adults (≥20 years) for reference value development and 10 632 for association analysis. ACs were measured via 3D scanning, body composition via bioelectrical impedance analysis and handgrip strength using a Jamar dynamometer. Sex-specific centile curves (P2.5-P97.5) were generated using lambda-mu-sigma methods. Propensity score matching balanced age distributions for sex and menopause subgroup comparisons. Multivariate logistic regression was used to examine factors associated with low appendicular circumference (lowest 5th percentile).

resultsMedian (25th and 75th) values for men were TC: 59.27 cm (55.09, 64.18), CC: 39.20 cm (37.17, 41.59), UAC: 28.31 cm (26.75, 30.10) and FC: 27.02 cm (25.67, 28.29); for women, TC: 52.45 cm (49.50, 55.74), CC: 35.71 cm (33.95, 37.76), UAC: 27.71 cm (25.74, 30.10) and FC: 24.64 cm (23.33, 26.07). Age trajectories showed sex-specific patterns: TC, CC and UAC peaked at 20-29 years with subsequent decline, while FC peaked at 40-49 years. BMI-adjusted circumferences exhibited divergent aging trajectories by sex. Postmenopausal women had significantly lower appendicular skeletal muscle mass (ASM), appendicular skeletal muscle mass index (ASMI), handgrip strength and CC than age-matched premenopausal women (all p values < 0.05). All ACs strongly correlated with muscle mass, fat mass and muscle strength (all p values < 0.001), with UAC and FC showing the strongest ASM and ASMI correlations in men (correlation coefficient: 0.757 and 0.735). Factors associated with low ACs included rural residence, lower education, low BMI, elevated body fat (positively linked to low CC, especially ≥ 60 years) and cardiometabolic disorders (diabetes, hypertension, hyperuricemia, dyslipidemia).

conclusionsThis study establishes the first age- and sex-stratified percentile references for ACs in Chinese adults. These results reveal significant sex disparities in absolute and BMI-adjusted measures, providing essential tools for sarcopenia screening, lifestyle intervention evaluation and high-risk population identification.

Indexed as

Imaging, Three-DimensionalSarcopeniaAdultAgedBody CompositionChinaCross-Sectional StudiesEast Asian PeopleFemaleHand StrengthHumansMaleMiddle AgedReference ValuesYoung Adult3D scanappendicular circumferencesbody compositionmuscle healthreference valuessarcopenia

Identifiers

PMID41243371
PMCPMC12620412

What Socratic 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 Socratic graph.