Evidence map›Paper›PMID 39434052›Full record

SynthesisBMC public health2024

The epidemiology of asthma in Mainland China: a systematic review and meta-analysis.

Jiarui Yu, Liang Xu, Azhu Han, Maomao Xie

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Jiarui Yu *First Affiliated Hospital of Bengbu Medical University, Bengbu, Anhui, 233004, China.
Liang Xu *Hospital 902, Joint Logistics Support Force, Bengbu, Anhui, 233000, China.
Azhu Han *School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China.
Maomao XieFirst Affiliated Hospital of Bengbu Medical University, Bengbu, Anhui, 233004, China. maomao123@bbmc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReliable estimates of asthma prevalence are essential for developing effective public health policies. However, discrepancies in published results have posed challenges for public health planning in China. To address this issue, we conducted this study to provide a comprehensive assessment of the epidemiology of asthma prevalence in China.

methodsWe conducted a thorough systematic review across multiple databases including PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data, and Weipu database. The search was limited to studies published in either Chinese or English up to August 31, 2023, that reported on asthma prevalence in China. We extracted relevant study characteristics and performed meta-analyses. The study protocol was registered with PROSPERO (CRD42023397949).

resultsA literature search yielded 192 studies that met the inclusion criteria out of 17,152 articles. The overall prevalence of asthma in Mainland China was found to be 2.20% (95% confidence interval, CI: 1.96-2.47%; I

conclusionsAsthma remains less prevalent in China than in western countries, however its prevalence has been gradually increasing over the past thirty years. The disease burden shows notable variations based on sex, age, and geographic regions, indicating significant demographic and regional disparities. To guide decision-making priorities and direct future research, conducting high-quality epidemiological studies on asthma is crucial.

Indexed as

AsthmaChinaHumansPrevalenceAsthmaChinaEpidemiologyMeta-analysisPrevalence

Identifiers

PMID39434052
PMCPMC11492516

What OpenQuestion holds

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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.