Evidence map›Paper›PMID 30325976›Full record

ArticlePloS one2018

Impact of interactions among metabolic syndrome components on the development of cardiovascular disease among Kazakhs in Xinjiang.

Wenwen Yang, Xiang Gao, Xianghui Zhang, Yunhua Hu, Heng Guo, Kui Wang, Yizhong Yan, Jia He, Jingyu Zhang, Jiaolong Ma and 8 more

Abstract read
In one paragraph

Article in PloS one, 2018. 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

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

3 citing papers in PubMed.

  1. Trial
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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

18 authors.

Wenwen YangDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Xiang GaoDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Xianghui ZhangDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Yunhua HuDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Heng GuoDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Kui WangDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Yizhong YanDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Jia HeDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Jingyu ZhangDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Jiaolong MaDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Lei MaoDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Lati MuDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Jiaming LiuDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Shugang LiDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Yusong DingDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Mei ZhangDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Rulin MaDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Shuxia GuoDepartment of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China.ORCID 0000-0002-8139-2813

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFew prospective studies have explored the effect of interactions among metabolic syndrome (MS) components on the development of cardiovascular disease (CVD) in the Kazakh population in Xinjiang Province of China.

methodAs of December 2016, 2,644 participants who completed a baseline survey over a period of 5 years or more were included in the study. The multiplicative interactions among MS components were evaluated by incorporation of the product terms into a logistic regression model. The additive interactions among MS components were evaluated by calculating the additive interaction index. Logistic regression was used to construct a predictive model, and CVD risk level was divided according to the risk probability of the population that did not eventually have CVD.

resultsWhen we analyzed the independent risk of MS and its components on developing CVD, only blood pressure(BP) and waist circumference(WC) were associated with CVD. A linear association was found between the risk of CVD, BP/WC, and the number of other components (trend, P<0.001). The risk of developing CVD increased when BP and WC coexisted, or when combined BP/WC with MS (≥3 components except for BP and WC) was present; however, there were no significant interactions among MS components. After the CVD hazards were divided into four levels, it was showed that over 19.92% of the incidence probability was in the population under mediate-risk while over 35.24% of them was in the high-risk group, respectively.

conclusionsBP and WC were independent risk factors for CVD in the Kazakh population. The risk of CVD was greatly increased when BP and WC coexisted or when combined BP/WC with MS (≥3 components except for BP and WC) was present, but no significant interactions were found among MS components.

Indexed as

AdultBlood PressureCardiovascular DiseasesChinaFemaleHumansIncidenceKazakhstanLogistic ModelsMaleMetabolic SyndromeMiddle AgedRisk FactorsWaist Circumference

Identifiers

PMID30325976
PMCPMC6191126

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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.