Evidence map›Paper›PMID 40395232›Full record

ArticleFrontiers in medicine2025

Muscle quality index correlates with arthritis: a cross-sectional study from NHANES 2011-2014.

Chao Wang, Haotai Xu, Lei Wang, Sidan Huang, Bingcheng Pan, Hui Pan, Haisheng Jia, Shujie Tang

Abstract read
In one paragraph

Article in Frontiers in medicine, 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

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

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

8 authors.

Chao Wang *School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
Haotai Xu *School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
Lei WangZhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Traditional Chinese Medicine, Zhongshan, China.
Sidan HuangSchool of Acupuncture-Moxibustion and Tuina, Hebei University of Chinese Medicine, Shijiazhuang, China.
Bingcheng PanSchool of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
Hui PanSchool of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
Haisheng JiaAffiliated Jiangmen Traditional Chinese Medicine Hospital of Jinan University, Jiangmen, Guangdong, China.
Shujie TangSchool of Traditional Chinese Medicine, Jinan University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aimed to investigate the association between Muscle Quality Index (MQI) and arthritis using data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014. Methods: A cross-sectional analysis was conducted using data from 4,558 participants aged 20-60 years. MQI was calculated using handgrip strength and appendicular skeletal muscle mass obtained through Dual-energy X-ray Absorptiometry (DXA) scans. Arthritis status was determined based on self-reported physician diagnoses. Multivariable logistic regression models were applied to examine the relationship between MQI and arthritis, adjusting for potential confounders, including demographic, socioeconomic, and lifestyle factors. Subgroup and sensitivity analyses were performed to evaluate heterogeneity. Results: Higher MQI was significantly associated with a lower risk of arthritis (adjusted OR = 0.73, 95% CI: 0.61-0.88, Conclusions: MQI is inversely associated with arthritis prevalence, suggesting that maintaining muscle quality may be a critical factor in arthritis prevention. These findings highlight the importance of muscle health in public health strategies for arthritis management.

Indexed as

arthritiscross-sectional researchmuscle quality indexNHANESpublic health

Identifiers

PMID40395232
PMCPMC12089042

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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.