Evidence map›Paper›PMID 30132261›Full record

ArticleEndocrine2019

Analysis of risk factors of metabolic syndrome using a structural equation model: a cohort study.

Zhimin Ma, Ditian Li, Siyan Zhan, Feng Sun, Chaonan Xu, Yunfeng Wang, Xinghua Yang

Abstract read
PubMed Publisher
In one paragraph

Article in Endocrine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Role of Mast Cells and Their Mediators in Chronic Kidney Diseases.International journal of molecular sciences · 2025
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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

7 authors at 3 institutions in 2 countries.

Zhimin MaSchool of Public Health, Capital Medical University, Beijing, China.
Ditian LiMailman School of Public Health, Columbia University, New York, NY, USA.
Siyan ZhanDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Feng SunDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Chaonan XuSchool of Public Health, Capital Medical University, Beijing, China.
Yunfeng WangSchool of Public Health, Capital Medical University, Beijing, China.
Xinghua YangSchool of Public Health, Capital Medical University, Beijing, China. xinghuay@sina.com.
Capital Medical University · CNPeking University · CNColumbia University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe aimed to use a structural equation model (SEM) to determine the interrelations between various risk factors, including latent variables, involved in the development of metabolic syndrome(MetS).

methodsThis study used data derived from the MJ Longitudinal Health Check-up Population Database for participants aged 20 to 70 years, who were asymptomatic for MetS at enrollment and were followed up for 5 years. A SEM was applied to investigate the attributions of MetS and the interrelations between different risk factors.

resultsSocioeconomic status (SES), living habits, components of metabolic syndrome (COMetS), and blood pressure had a diverse impact on the onset of MetS, directly and (or) indirectly. When investigating the latent risk factors and the interrelations between different risk factors. The standardized total effect (the sum of the direct and indirect effects, β

conclusionsThese results demonstrate that individuals with a higher level of SES are susceptible to high blood pressure and are at increased risk for MetS. Additionally, there is a decrease in exercise and an increase in smoking and consumption of alcohol corresponded to an increase in metabolic risk factors.

Indexed as

AlgorithmsAdultAgedAlcohol DrinkingBlood PressureCohort StudiesDatabases, FactualFemaleHumansLife StyleLongitudinal StudiesMaleMetabolic SyndromeMiddle AgedModels, TheoreticalRisk FactorsMetabolic syndromeRisk factorsSocioeconomic statusStructural equation model

Identifiers

PMID30132261
OpenAlexW2888193759

What OpenQuestion holds

Textmetadata
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.