Evidence map›Paper›PMID 32616490›Full record

ArticleBMJ open2020

Sex-specific association of serum uric acid dynamics with the incidence of metabolic syndrome in a health check-up Chinese population: a prospective cohort study.

Ying Liu, Yongjun Fan, Qigui Liu, Kehua Liu, Fangfang Chen, Xiao Tang, Guorong Li, Dongmei Hu, Guirong Song

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 19% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 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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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

9 authors at 1 institution in 1 country.

Ying Liu *The Physical Examination Centre of the Second Affiliated Hospital, Dalian Medical University, Dalian, Liaoning, China.
Yongjun Fan *Department of Health Statistics, School of Public Health, Dalian Medical University, Dalian, Liaoning, China.
Qigui Liu *Department of Health Statistics, School of Public Health, Dalian Medical University, Dalian, Liaoning, China.
Kehua LiuDepartment of Health Statistics, School of Public Health, Dalian Medical University, Dalian, Liaoning, China.
Fangfang ChenDepartment of Health Statistics, School of Public Health, Dalian Medical University, Dalian, Liaoning, China.
Xiao TangDepartment of Health Statistics, School of Public Health, Dalian Medical University, Dalian, Liaoning, China.
Guorong LiDepartment of Health Statistics, School of Public Health, Dalian Medical University, Dalian, Liaoning, China.
Dongmei HuDepartment of Health Statistics, School of Public Health, Dalian Medical University, Dalian, Liaoning, China.
Guirong SongDepartment of Health Statistics, School of Public Health, Dalian Medical University, Dalian, Liaoning, China songsara110@163.com.ORCID 0000-0001-6784-8805
Dalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveMany studies have demonstrated that elevated serum uric acid (SUA) level is linked with metabolic syndrome (MetS). However, whether there is a sex difference in the association between SUA and MetS has not been determined. This study aimed to accurately explore the impact of SUA longitudinal changes on MetS by sex.

designA prospective cohort study.

settingThe Health Check-up Centre of the Second Hospital affiliated with Dalian Medical University from 2010 to 2016.

participantsA health check-up cohort of 577 men and 1698 women aged 20-60 years who did not exhibit MetS or hyperuricaemia at baseline and underwent at least two physical examinations from 2010 to 2016. PRIMARY AND SECONDARY OUTCOME MEASURES: Weight, height, blood pressure and blood biochemistry parameters, including SUA, were measured. MetS was defined according to the Joint Interim Statement criteria.

methodsBased on longitudinal data, a linear mixed-effects model was constructed to explore the characteristics of SUA dynamic changes in males and females, and joint modelling of longitudinal and survival data was done to analyse the association between SUA dynamic changes and MetS occurrence.

resultsThe natural logarithm of SUA (LNSUA) in females exhibited a gradually increasing trend, and its annual growth rate in females who developed MetS was greater than that of the non-MetS females. The longitudinal growth of SUA in females was a risk factor for the onset of MetS, and the estimated HR was 13.2580 (95% CI 1.9106 to 91.9957) for each 1-unit rise in LNSUA longitudinally. An association between the longitudinal growth of LNSUA and MetS was not found in males.

conclusionsThe longitudinal increase in SUA in females could increase the risk of MetS, even if the SUA changes within the normal range. The longitudinal increase in SUA in males was not a predictor for MetS.

Indexed as

AdultAsian PeopleCohort StudiesFemaleHumansLinear ModelsLongitudinal StudiesMaleMetabolic SyndromeMiddle AgedProspective StudiesRisk FactorsSex FactorsUric AcidUric Acidepidemiologyrisk managementstatistics & research methods

Identifiers

PMID32616490
PMCPMC7333806
OpenAlexW3040203648

What OpenQuestion holds

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LicenceCC BY-NC
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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.