Evidence map›Paper›PMID 36839381›Full record

ArticleNutrients2023

Association of Chinese Visceral Adiposity Index and Carotid Atherosclerosis in Steelworkers: A Cross-Sectional Study.

Xuelin Wang, Zhikang Si, Hui Wang, Rui Meng, Haipeng Lu, Zekun Zhao, Jiaqi Hu, Huan Wang, Jiaqi Chen, Yizhan Zheng and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 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

17 authors.

Xuelin WangDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Zhikang SiDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Hui WangDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Rui MengDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Haipeng LuDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Zekun ZhaoDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Jiaqi HuDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Huan WangDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Jiaqi ChenDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Yizhan ZhengDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Ziwei ZhengDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.ORCID 0000-0002-1762-3285
Yuanyu ChenDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Yongzhong YangDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Xiaoming LiDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Ling XueDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Jian SunDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.
Jianhui WuKey Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan 063210, China.ORCID 0000-0002-8440-1404

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Chinese Visceral Adiposity Index (CVAI) is an indicator of visceral adiposity dysfunction used to evaluate the metabolic health of the Chinese population. Steelworkers are more likely to be obese due to their exposure to special occupational factors, and have a higher prevalence of carotid atherosclerosis (CAS). This study aimed to analyze the special relationship between CVAI and CAS among steelworkers. A total of 4075 subjects from a northern steel company were involved in the cross-sectional study. Four logistic regression models were developed to analyze the correlation between CVAI and CAS. In addition, the restricted cubic spline was applied to fit the dose-response association between CVAI and CAS risk. In the study, the prevalence of CAS was approximately 25.94%. After adjustment for potential confounders, we observed a positive correlation between CVAI and CAS risk. Compared to the first CVAI quartile, the effect value odds ratio (OR) and 95% CI in the second, third, and fourth CVAI quartile were 1.523 (1.159-2.000), 2.708 (2.076-3.533), and 4.101 (3.131-5.372), respectively. Additionally, this positive correlation was stable in all subgroups except for female. Furthermore, we also found a non-linear relationship between CVAI and CAS risk (

Indexed as

AdiposityCarotid Artery DiseasesChinaCross-Sectional StudiesEast Asian PeopleFemaleHumansObesityObesity, AbdominalRisk Factorscarotid atherosclerosiscross-sectional studyCVAIsteelworkers

Identifiers

PMID36839381
PMCPMC9964603

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