Evidence map›Paper›PMID 38685072›Full record

ArticleLipids in health and disease2024

Chinese visceral adiposity index and its transition patterns: impact on cardiovascular and cerebrovascular diseases in a national cohort study.

Zhihan Lv, Yunxi Ji, Su Xu, Chenyi Li, Wenwei Cai

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Lipids in health and disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.6field-weighted citation impact, top 6% 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.

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

8 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Zhihan Lv *Department of General Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizaoju Road, Shanghai, 200011, China.
Yunxi Ji *Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Su XuDepartment of General Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizaoju Road, Shanghai, 200011, China.
Chenyi LiDepartment of General Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizaoju Road, Shanghai, 200011, China. sjtu.plum@outlook.com.
Wenwei CaiDepartment of General Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizaoju Road, Shanghai, 200011, China. 13564084838@139.com.
Shanghai Jiao Tong University · CNShanghai Ninth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObesity affects approximately 800 million people worldwide and may contribute to various diseases, especially cardiovascular and cerebrovascular conditions. Fat distribution and content represent two related yet distinct axes determining the impact of adipose tissue on health. Unlike traditional fat measurement indices, which often overlook fat distribution, the Chinese visceral adiposity index (CVAI) is a novel metric used to assess visceral fat accumulation and associated health risks. Our objective is to evaluate its association with the risk of cardiovascular and cerebrovascular diseases.

methodsA nationwide longitudinal study spanning 9 years was conducted to investigate both the effects of baseline CVAI levels (classified as low and high) and dynamic changes in CVAI over time, including maintenance of low CVAI, transition from low to high, transition from high to low, and maintenance of high CVAI. Continuous scales (restricted cubic spline curves) and categorical scales (Kaplan-Meier curves and multivariable Cox regression analyses) were utilized to evaluate the relationship between CVAI and cardiovascular and cerebrovascular diseases. Furthermore, subgroup analyses were conducted to investigate potential variations.

resultsTotally 1761 individuals (22.82%) experienced primary outcomes among 7717 participants. In the fully adjusted model, for each standard deviation increase in CVAI, there was a significant increase in the risk of primary outcomes [1.20 (95%CI: 1.14-1.27)], particularly pronounced in the high CVAI group [1.38 (95%CI: 1.25-1.54)] compared to low CVAI group. Regarding transition patterns, individuals who consistently maintained high CVAI demonstrated the highest risk ratio compared to those who consistently maintained low CVAI [1.51 (95%CI: 1.31-1.74)], followed by individuals transitioning from low to high CVAI [1.22 (95% CI: 1.01-1.47)]. Analysis of restricted cubic spline curves indicated a positive dose-response relationship between CVAI and risk of primary outcomes (p for non-linear = 0.596). Subgroup analyses results suggest that middle-aged individuals with high CVAI face a notably greater risk of cardiovascular and cerebrovascular diseases in contrast to elderly individuals [1.75 (95% CI: 1.53-1.99)].

conclusionThis study validates a significant association between baseline levels of CVAI and its dynamic changes with the risk of cardiovascular and cerebrovascular diseases. Vigilant monitoring and effective management of CVAI significantly contribute to early prevention and risk stratification of cardiovascular and cerebrovascular diseases.

Indexed as

AdiposityCardiovascular DiseasesCerebrovascular DisordersIntra-Abdominal FatAdultAgedChinaCohort StudiesEast Asian PeopleFemaleHumansLongitudinal StudiesMaleMiddle AgedObesity, AbdominalRisk FactorsCardiovascular and cerebrovascular diseasesChinese visceral adiposity indexLongitudinal transitionVisceral adipose tissue

Identifiers

PMID38685072
PMCPMC11057120
OpenAlexW4396222179

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.