Evidence map›Paper›PMID 40970420›Full record

ArticleAnnals of medicine2025

Incidence and prevalence of gout in Eastern China from 2011 to 2021: a retrospective population-based study.

Ke Liu, Ding Ye, Hao Lin, Yexiang Sun, Peng Shen, Jianbing Wang, Zhiqin Jiang, Yingying Mao, Kun Chen

Abstract read
In one paragraph

Article in Annals of medicine, 2025. 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. Article
  2. Article
  3. Article
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.

Ke LiuDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China.
Ding YeDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China.ORCID 0000-0001-6654-7832
Hao LinDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China.
Yexiang SunDepartment of Chronic Disease and Health Promotion, Yinzhou District Center for Disease Control and Prevention, Ningbo, China.
Peng ShenDepartment of Chronic Disease and Health Promotion, Yinzhou District Center for Disease Control and Prevention, Ningbo, China.
Jianbing WangDepartment of Public Health, and Department of Endocrinology of the Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Zhiqin JiangDepartment of Chronic Disease and Health Promotion, Yinzhou District Center for Disease Control and Prevention, Ningbo, China.
Yingying MaoDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China.
Kun ChenDepartment of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo characterize the burden of gout by estimating the temporal trends in prevalence and incidence, and assessing age- and gender-specific patterns in Yinzhou, Ningbo, China (2011-2021).

methodsA population-based retrospective study was conducted using the Yinzhou Regional Health Information Platform. Poisson regression estimated the 95% confidence intervals (CIs) for prevalence and incidence rates, and relative risks for both rates across subgroups. Age-standardized incidence (ASIR) and prevalence rates (ASPR) were calculated based on China's 2020 census. The average annual percent changes (AAPCs) of standardized rates were calculated to estimate the secular trends using joinpoint regression analysis.

resultsOf the over 1.1 million resident adults, 23,967 gout cases were identified over an eleven-year period. The total incidence and prevalence rates from 2011 to 2021 were 211.29 (95% CI: 208.28-214.33)/100,000 person-years and 2.16% (95% CI: 2.13% to 2.19%), respectively. The incidence and prevalence rates of gout was more than twice as heavy in men than women, and exhibited a rising tendency with advancing age, particularly for elderly men. Additionally, lower education attainment, obesity, and unfavorable lifestyle contributed significantly to the burden of gout. ASIR (AAPC: 5.37, 95% CI: 0.30-10.70) and ASPR (AAPC: 7.75, 95% CI: 6.29-9.23) increased significantly over the 11-year period, though ASIR in women remained stable.

conclusionsThe incidence and prevalence of gout increased over time, showing age- and gender-specific patterns. The healthcare authorities need to focus on the burden of gout and guide targeted prevention and treatment strategies for gout.

Indexed as

GoutAdolescentAdultAgedAged, 80 and overAge DistributionAge FactorsChinaFemaleHumansIncidenceMaleMiddle AgedPrevalenceRetrospective StudiesRisk FactorsEpidemiologygoutincidenceprevalencetrend

Identifiers

PMID40970420
PMCPMC12451967

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.