Evidence map›Paper›PMID 22682157›Full record

ArticleBMC public health2012

A longitudinal cohort based association study between uric acid level and metabolic syndrome in Chinese Han urban male population.

Qian Zhang, Chengqi Zhang, Xinhong Song, Haiyan Lin, Dongzhi Zhang, Wenjia Meng, Yongyuan Zhang, Zhenxin Zhu, Fang Tang, Longjian Liu and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 3 pooled it
3.6field-weighted citation impact, top 7% 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

32 citing papers in PubMed, 3 syntheses or guidelines pooled it, 71 citations in OpenAlex.

  1. Can biomarkers be used to improve diagnosis and prediction of metabolic syndrome in childhood cancer survivors? A systematic review.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2021
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  18. The Associations of Serum Uric Acid with Obesity-RelatedInternational journal of endocrinology · 2017
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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

12 authors at 4 institutions in 2 countries.

Qian ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Shandong University, PO Box 100, Jinan, 250012, China.
Chengqi Zhang
Xinhong Song
Haiyan Lin
Dongzhi Zhang
Wenjia Meng
Yongyuan Zhang
Zhenxin Zhu
Fang Tang
Longjian Liu
Xiaowei Yang
Fuzhong Xue
Shandong University · CNShandong Provincial QianFoShan Hospital · CNDrexel University · USUniversity of California, Davis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt has been recently demonstrated that serum uric acid (UA) is associated with metabolic syndrome (MetS) or its related clinical indications based on cross-sectional or prospective cohort studies. Nonetheless, due to the fact that UA level constantly fluctuates from time to time even for the person, using a single measure of UA level at baseline of those studies may not be sufficient for estimating the UA-Mets association.

methodsTo further estimate this time-dependent association, we fitted a generalized estimating equation (GEE) regression model with data from a large-scale 6-year longitudinal study, which included 2222 participants aged > =25 years with an average of 3.5 repeated measures of UA per person in the Health Management Center of Shandong Provincial Hospital, Shandong, China.

resultsAfter adjusting for other potential confounding factors (i.e., total cholesterol, low-density lipoprotein), it was verified that time-dependent UA level was an independent risk factor for MetS (OR = 1.6920, p < 0.0001). It was found that UA level was positively associated with obesity, hypertension, and dyslipidemia, but was inversely associated with hyperglycemia.

conclusionsSerum UA level may serve as an important risk factor of MetS. Additionally, our study suggested that UA level be an independent risk factor to obesity, hypertension and dyslipidemia, but a protective factor to hyperglycemia. These findings are concordant with results from other studies on Asian populations, and jointly provide a basis to further develop a risk assessment model for predicting MetS using UA levels and other factors in China.

Indexed as

AdultAgedAged, 80 and overAsian PeopleBiomarkersChinaHumansLongitudinal StudiesMaleMetabolic SyndromeMiddle AgedRisk FactorsUrban PopulationUric AcidBiomarkersUric Acid

Identifiers

PMID22682157
PMCPMC3416673
OpenAlexW1988016170

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.