Evidence map›Paper›PMID 40369042›Full record

ArticleScientific reports2025

Relationship between atherosclerotic burden and sarcopenia in U.S. adults: A cross-sectional study based on the NHANES database.

Jing Li, Zeli Tang, Xia Zhang, Yanling Zheng, Jie Yv

Abstract read
In one paragraph

Article in Scientific reports, 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

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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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Jing LiPeople's Hospital of Honghuagang District, Zunyi, 563000, China.
Zeli TangPeople's Hospital of Honghuagang District, Zunyi, 563000, China. 15085446137@163.com.
Xia ZhangPeople's Hospital of Honghuagang District, Zunyi, 563000, China.
Yanling ZhengPeople's Hospital of Honghuagang District, Zunyi, 563000, China.
Jie YvGuizhou Hospital The First Affiliared Hospital of Sun Yat-Sen Univeruity, Guiyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sarcopenia, characterized by the progressive loss of skeletal muscle mass and strength, significantly impacts the people, leading to increased frailty and mortality. The atherogenic index of plasma (AIP), a biomarker for lipid imbalance, may be linked to sarcopenia due to shared pathways of inflammation and metabolic dysregulation. Data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles were analyzed. The AIP was calculated as the logarithm of the ratio of triglycerides to High density lipoprotein cholesterol. Sarcopenia was defined using the appendicular skeletal muscle mass index (ASMBMI) adjusted for body mass index (BMI). Multivariable linear regression and logistic regression models were employed to assess the association between AIP and ASMBMI, as well as sarcopenia. Restrictive cubic spline curves were utilized to analyze potential nonlinear associations between AIP and outcome indicators. Additionally, subgroup analyses and intergroup interaction tests were performed. Elevated AIP levels were associated with decreased ASMBMI and an increased risk of sarcopenia. After adjusting for confounding factors, the association between AIP and ASMBMI remained significant (Beta [95% CI] = -0.02 [-0.03, -0.01], P < 0.001). AIP was significantly associated with sarcopenia (OR [95% CI] = 2.6 [1.78, 3.81], P = < 0.001). AIP is significantly associated with reduced muscle mass and potentially with sarcopenia, suggesting that lipid metabolism plays a critical role in muscle health. Identifying AIP as a modifiable risk factor could have important public health implications for managing sarcopenia.

Indexed as

AtherosclerosisSarcopeniaAdultAgedBiomarkersBody Mass IndexCholesterol, HDLCross-Sectional StudiesFemaleHumansMaleMiddle AgedMuscle, SkeletalNutrition SurveysRisk FactorsTriglyceridesBiomarkersCholesterol, HDLTriglyceridesA cross-sectional studyAtherosclerotic index of plasma (AIP)NHANESSarcopenia

Identifiers

PMID40369042
PMCPMC12078528

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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.