Evidence map›Paper›PMID 25961739›Full record

ArticlePloS one2015

Comparisons of different metabolic syndrome definitions and associations with coronary heart disease, stroke, and peripheral arterial disease in a rural Chinese population.

Jiangping Wen, Jingang Yang, Yujie Shi, Yuanbo Liang, Fenghua Wang, Xinrong Duan, Xilin Lu, Qiushan Tao, Xinxin Lu, Yaping Tian and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
2.0field-weighted citation impact, top 13% 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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 62 citations in OpenAlex.

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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

11 authors at 7 institutions in 1 country.

Jiangping WenDepartment of Clinical Biochemistry, Chinese PLA General Hospital, Beijing, China; Department of Laboratory Medicine, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Jingang YangState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yujie ShiCardiovascular Disease Institute, Beijing Military Area Command General Hospital, Beijing, China.
Yuanbo LiangClinical and Epidemiological Research Center, the Affiliated Eye Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.
Fenghua WangBeijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Laboratory, Beijing, China.
Xinrong DuanBeijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Laboratory, Beijing, China.
Xilin LuDepartment of Laboratory Medicine, Handan 3rd Hospital, Handan, Hebei Province, China.
Qiushan TaoSchool of Public Health, Peking University, Beijing, China.
Xinxin LuDepartment of Laboratory Medicine, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Yaping TianDepartment of Clinical Biochemistry, Chinese PLA General Hospital, Beijing, China.
Ningli WangBeijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Laboratory, Beijing, China.
Beijing Tongren Hospital · CNCapital Medical University · CNAffiliated Eye Hospital of Wenzhou Medical College · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNChinese PLA General Hospital · CNPeking University · CNThe Military General Hospital of Beijing PLA · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesWe estimated the prevalence of metabolic syndrome (MetS) and compared associations of different MetS definitions with coronary heart disease (CHD), stroke, and peripheral arterial disease (PAD) in a rural Chinese population.

methodsAmong 4,748 residents (2,145 men and 2,603 women) aged 30+ years in rural China from 2006 to 2007, the prevalence of MetS was estimated by using five different definitions: modified World Health Organization (WHO), Chinese Diabetes Society (CDS), the updated National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) for Asian-Americans, International Diabetes Federation (IDF), and Joint Interim Statement (JIS). Multivariable logistic regression analyses were implemented to estimate the association between MetS and the prevalence of CHD, stroke and PAD, respectively.

resultsPrevalence of MetS in men was 11.5% (WHO), 14.8% (CDS), 32.4% (NCEP-ATP III), 27.5% (IDF) and 39.7% (JIS) and in women was 15.7% (WHO), 20.7% (CDS), 54.2% (NCEP-ATP III), 51.5% (IDF) and 54.2% (JIS), respectively. Respective ORs (95% CI) for associating MetS with CHD in men were 1.79 (1.02-3.17), 1.25 (0.69-2.26), 1.61 (1.01-2.58), 1.84 (1.14-2.96), and 1.53 (0.96-2.43). Corresponding ORs (95% CI) for stroke in men were 2.18 (95% CI 1.20 to 3.97), 2.20 (95% CI 1.25 to 3.89), 1.71 (95% CI 1.02 to 2.84), 1.30 (95% CI 0.77 to 2.23), and 1.61 (95% CI 0.97 to 2.68), respectively. In women, CHD and stroke were significantly associated with MetS using all five definitions of MetS. In addition, PAD was associated with all five MetS definitions in men, but not in women. Only hyperglycemia and BMI were significantly associated with PAD in women.

conclusionsIn this rural Chinese population, the JIS, IDF and CDS criteria may not be more suitable than WHO and updated NCEP-ATPIII definitions for screening high-risk individuals and estimating the risk of CHD and stroke from MetS, especially in men.

Indexed as

Rural PopulationAdultChinaCoronary Artery DiseaseCross-Sectional StudiesFemaleHumansMaleMetabolic SyndromeMiddle AgedPeripheral Arterial DiseasePopulation SurveillancePrevalenceRisk FactorsStroke

Identifiers

PMID25961739
PMCPMC4427409
OpenAlexW276316426

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.