Evidence map›Paper›PMID 40889799›Full record

SynthesisStroke and vascular neurology2026

Incidence and prevalence of vascular cognitive impairment in China: a systematic review and meta-analysis.

Su Zhen Liang, Shenyu Li, Ao Guan, Ruijia Xu, Mingxia Wei, Yingzhe Wang, Weiwei Shen, Yanfeng Jiang, Tiejun Zhang, Mei Cui

Abstract readSystematic ReviewMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Stroke and vascular neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

10 authors.

Su Zhen Liang *Department of Neurology, Huashan Hospital Fudan University, Shanghai, China.ORCID 0009-0002-3671-3080
Shenyu Li *Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China.ORCID 0009-0006-6161-5238
Ao Guan *Department of Neurology, Huashan Hospital Fudan University, Shanghai, China.ORCID 0009-0001-8869-1066
Ruijia XuDepartment of Neurology, Huashan Hospital Fudan University, Shanghai, China.ORCID 0009-0009-0406-3934
Mingxia WeiDepartment of Neurology, Huashan Hospital Fudan University, Shanghai, China.ORCID 0009-0005-4402-1254
Yingzhe WangDepartment of Neurology, Huashan Hospital Fudan University, Shanghai, China.ORCID 0000-0002-8401-2644
Weiwei ShenDepartment of Neurology, Huashan Hospital Fudan University, Shanghai, China.
Yanfeng JiangHuman Phenome Institute, Research and Innovation Center,Shanghai Pudong Hospital, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China cuimei@fudan.edu.cn tjzhang@shmu.edu.cn yanfengjiang@fudan.edu.cn.ORCID 0000-0003-4976-6333
Tiejun ZhangDepartment of Epidemiology, School of Public Health, Fudan University, Shanghai, China cuimei@fudan.edu.cn tjzhang@shmu.edu.cn yanfengjiang@fudan.edu.cn.
Mei CuiDepartment of Neurology, Huashan Hospital Fudan University, Shanghai, China cuimei@fudan.edu.cn tjzhang@shmu.edu.cn yanfengjiang@fudan.edu.cn.ORCID 0000-0002-6449-8106

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveGiven China's rapid population ageing and substantial stroke burden, understanding the epidemiology of vascular cognitive impairment (VCI) is critical. This study aimed to systematically evaluate VCI prevalence and incidence in China from 1980 to 2023, and explore demographic and geographic disparities.

methodsA systematic review and meta-analysis of 81 observational studies (73 on prevalence, 10 on incidence) was conducted, analysing data from 784 846 participants for prevalence. Data were extracted from multiple databases, and studies were selected based on predefined inclusion criteria. Meta-analysis was performed using random-effects models due to high heterogeneity (I²>90%). Machine learning models (including gradient boosting machine, random forest) were employed to assess associations between demographic factors and VCI prevalence, with SHapley Additive exPlanations analysis for interpretability.

resultsOverall pooled prevalence was estimated at 1.54% (95% CI: 1.14% to 1.93%), varying significantly with age, education and region, peaking at 2.91% in those ≥80 years. Temporal trends revealed increasing prevalence from 1980 to 2023, while incidence was estimated at 0.29 per 100 person-years (95% CI: 0.21% to 0.41%), with regional disparities. Machine learning identified age, sex and survey period as key determinants of prevalence, aligning with meta-regression findings.

conclusionsVCI poses a growing burden in China, particularly among older and less-educated populations. This analysis provides the most comprehensive assessment of VCI in China to date, underscoring demographic and regional variations. These findings highlight the need for targeted public health strategies, improved diagnostics and lifestyle interventions to address the growing burden of VCI, particularly amidst China's ageing population. Future longitudinal research integrating clinical data, biomarkers and potentially neuroimaging is warranted to better understand VCI progression and refine intervention efficacy.

Indexed as

CognitionCognitive DysfunctionDementia, VascularAgedAged, 80 and overAge DistributionAge FactorsChinaFemaleHealth Status DisparitiesHumansIncidenceMaleMiddle AgedObservational Studies as TopicPrevalenceCognitive DysfunctionMeta-AnalysisSystematic Review

Identifiers

PMID40889799
PMCPMC13151871

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.