Evidence map›Paper›PMID 42260836›Full record

ArticleMedicine2026

Systemic inflammatory biomarkers and their partial role in the association between diabetes and sarcopenia: A population-based study using NHANES data.

Jingqian Qin, Xue Qiu, Bin Liang, Yongyu Chen, Tao Jiang

Abstract read
In one paragraph

Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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

5 authors.

Jingqian QinDepartment of Nutrition, The First Affiliated Hospital of Guangxi University of Traditional Chinese Medicine, Nanning, Guangxi, China.ORCID 0009-0008-1510-1011
Xue QiuDepartment of Cardiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Bin LiangDepartment of Gastroenterology, Minzu Hospital of Guangxi Medical University, Nanning, China.
Yongyu ChenDepartment of Hematology, Minzu Hospital of Guangxi Medical University, Nanning, China.
Tao JiangDepartment of Nutrition, The First Affiliated Hospital of Guangxi University of Traditional Chinese Medicine, Nanning, Guangxi, China.ORCID 0009-0002-8984-9360

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mediating role of inflammatory biomarkers in the association between diabetes and sarcopenia remains poorly quantified in general populations. This study aims to investigate this relationship and quantify the mediating effects of systemic inflammatory indicators. This cross-sectional study included 11,190 adults from the National Health and Nutrition Examination Survey 2011 to 2018. Weighted logistic regression and subgroup analyses were used to assess the association between diabetes and sarcopenia, defined by the Foundation for the National Institutes of Health criteria (appendicular skeletal muscle mass/body mass index). Mediation analysis with bootstrapping was performed to evaluate the mediating roles of white blood cells, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, and Systemic Immune-Inflammation Index. Diabetes was significantly associated with an increased risk of sarcopenia (odds ratio = 1.48, 95% confidence interval: 1.03-2.13, P = .042) after full adjustment. Mediation analysis revealed that white blood cells, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, and Systemic Immune-Inflammation Index mediated 28.48%, 26.58%, 7.36%, 6.54%, and 10.17% of this association, respectively (all P < .05). Diabetes is positively associated with sarcopenia risk, partially mediated by systemic inflammation. Readily available inflammatory biomarkers may aid in identifying high-risk diabetic patients for sarcopenia prevention.

Indexed as

BiomarkersDiabetes MellitusInflammationSarcopeniaAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedNeutrophilsNutrition SurveysRisk FactorsBiomarkersdiabetesinflammationinflammatory biomarkersmediation analysisNHANESsarcopenia

Identifiers

PMID42260836
PMCPMC13246112

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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.