Evidence map›Paper›PMID 41353457›Full record

ArticleScientific reports2025

Association between changes in Chinese visceral adiposity index and cardiovascular disease among middle-aged and older Chinese adults.

Li-Hua Huang, Kun-Peng Kang

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

2 authors.

Li-Hua HuangDepartment of Clinical Laboratory, The Second Affiliated Hospital of Gannan Medical University, Ganzhou, 341600, Jiangxi, China.
Kun-Peng KangDepartment of Cardiovascular Medicine, The First Affiliated Hospital of Gannan Medical University, Ganzhou, 341000, Jiangxi, China. gydkangkunpeng@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies have established visceral adiposity as a risk factor for cardiovascular disease (CVD), but the relationship between longitudinal changes in Chinese Visceral Adiposity Index (CVAI) and CVD risk has not been thoroughly investigated. This study aimed to investigate the longitudinal association between CVAI changes and CVD risk in Chinese middle-aged and older adults. A total of 3,805 CVD-free participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study (CHARLS) were followed from 2015 until 2020 (median follow-up: 4.9 years) to detect incident CVD. Participants were categorized based on CVAI changes using K-means clustering. During follow-up, 375 participants (9.86%) developed CVD. Multivariable-adjusted Cox proportional hazards regression and restricted cubic spline regression models were used for data analysis. Compared with the low-increasing CVAI group, the hazard ratios (HR) were 1.25 (95% confidence interval [CI], 0.89 to 1.74) for moderate-increasing, 1.56 (95% CI, 1.09 to 2.24) for moderate high-increasing, and 1.87 (95% CI, 1.21 to 2.89) for high-increasing CVAI groups (P for trend = 0.002). Each standard deviation increase in cumulative CVAI was associated with a 20% increased CVD risk (HR 1.20, 95% CI, 1.06 to 1.37). The relationship was linear (P for nonlinearity = 0.998). Cumulative CVAI showed modest predictive performance (area under the curve 0.598), slightly better than body mass index, waist circumference, and Visceral Adiposity Index. These findings suggest CVAI changes may provide additional information for comprehensive CVD risk assessment, though further validation is needed given the modest predictive accuracy.

Indexed as

AdiposityCardiovascular DiseasesIntra-Abdominal FatObesity, AbdominalAgedBody Mass IndexChinaEast Asian PeopleFemaleHumansLongitudinal StudiesMaleMiddle AgedProportional Hazards ModelsRisk FactorsWaist CircumferenceCardiovascular diseasesChinese populationLongitudinal studiesRisk assessmentVisceral adiposity

Identifiers

PMID41353457
PMCPMC12796186

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.