Evidence map›Paper›PMID 36936175›Full record

ArticleFrontiers in endocrinology2023

The role of obesity in sarcopenia and the optimal body composition to prevent against sarcopenia and obesity.

Chaoran Liu, Keith Yu-Kin Cheng, Xin Tong, Wing-Hoi Cheung, Simon Kwoon-Ho Chow, Sheung Wai Law, Ronald Man Yeung Wong

Registry-linked trialOpen access · goldFull text read
In one paragraph

Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06298825 (Effect of Sarcopenia on Prognosis of Patients With Acute Decompensated Heart Failure), which is not on this map. Cited by 54 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 2 pooled it
13.7field-weighted citation impact, top 1% of its field
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.

NCT06298825 unknown statusnot on this mapstarted 2024, after this paper: background citation

Effect of Sarcopenia on Prognosis of Patients With Acute Decompensated Heart Failure: a Prospective, Multi-center, Observational Cohort Study

TypeobservationalSponsorGuangdong Provincial People's HospitalRan2024 to 2026Enrolled500ConditionsAcute Decompensated Heart Failure
3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 2 syntheses or guidelines pooled it, 78 citations in OpenAlex.

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  19. Sarcopenic Obesity Phenotype Index (SOPi): A Population-Based Study.Journal of cachexia, sarcopenia and muscle · 2025
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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

7 authors at 1 institution in 1 country.

Chaoran LiuDepartment of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Keith Yu-Kin ChengDepartment of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Xin TongDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Wing-Hoi CheungDepartment of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Simon Kwoon-Ho ChowDepartment of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Sheung Wai LawDepartment of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Ronald Man Yeung WongDepartment of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Chinese University of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Elderly people with low lean and high fat mass, are diagnosed with sarcopenic obesity (SO), and often have poor clinical outcomes. This study aimed to explore the relationship between obesity and sarcopenia, and the optimal proportion of fat and muscle for old individuals. Methods: Participants aged 60 years or above were instructed to perform bioelectrical impedance analysis to obtain the muscle and fat indicators, and handgrip strength was also performed. Sarcopenia was diagnosed according to predicted appendicular skeletal muscle mass and function. Body mass index (BMI) and body fat percentage (BF%) were used to define obesity. The association of muscle and fat indicators were analyzed by Pearson's correlation coefficient. Pearson Chi-Square test was utilized to estimate odds ratios (OR) and 95% confidence intervals (CI) on the risk of sarcopenia according to obesity status. Results: 1637 old subjects (74.8 ± 7.8 years) participated in this study. Not only fat mass, but also muscle indicators were positively correlated to BMI and body weight (p < 0.05). Absolute muscle and fat mass in different positions had positive associations (p < 0.05). Muscle mass and strength were negatively related to appendicular fat mass percentage (p < 0.05). When defined by BMI (OR = 0.69, 95% CI [0.56, 0.86]; p = 0.001), obesity was a protective factor for sarcopenia, whilst it was a risk factor when using BF% (OR = 1.38, 95% CI [1.13, 1.69]; p = 0.002) as the definition. The risk of sarcopenia reduced with the increase of BMI in both genders. It was increased with raised BF% in males but displayed a U-shaped curve for females. BF% 26.0-34.6% in old females and lower than 23.9% in old males are recommended for sarcopenia and obesity prevention. Conclusion: Skeletal muscle mass had strong positive relationship with absolute fat mass but negative associations with the percentage of appendicular fat mass. Obesity was a risk factor of sarcopenia when defined by BF% instead of BMI. The management of BF% can accurately help elderly people prevent against both sarcopenia and obesity.

Indexed as

Body CompositionObesitySarcopeniaAgedBody Mass IndexBody WeightFemaleHand StrengthHumansMaleagingbody fat percentagebody mass indexfatmusclesarcopenic obesity

Identifiers

PMID36936175
PMCPMC10016224
OpenAlexW4323309635

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read187
Read underepoch 390

Registered trials

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.