{
  "abstract": "Objective Given 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.Methods A 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.Results Overall 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.Conclusions VCI 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.",
  "authors": [
    {
      "affiliations": [
        "Department of Neurology, Huashan Hospital Fudan University, Shanghai, China"
      ],
      "name": "Su Zhen Liang"
    },
    {
      "affiliations": [
        "Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China"
      ],
      "name": "Shenyu Li"
    },
    {
      "affiliations": [
        "Department of Neurology, Huashan Hospital Fudan University, Shanghai, China"
      ],
      "name": "Ao Guan"
    },
    {
      "affiliations": [
        "Department of Neurology, Huashan Hospital Fudan University, Shanghai, China"
      ],
      "name": "Ruijia Xu"
    },
    {
      "affiliations": [
        "Department of Neurology, Huashan Hospital Fudan University, Shanghai, China"
      ],
      "name": "Mingxia Wei"
    },
    {
      "affiliations": [
        "Department of Neurology, Huashan Hospital Fudan University, Shanghai, China"
      ],
      "name": "Yingzhe Wang"
    },
    {
      "affiliations": [
        "Department of Neurology, Huashan Hospital Fudan University, Shanghai, China"
      ],
      "name": "Weiwei Shen"
    },
    {
      "affiliations": [
        "Human Phenome Institute, Research and Innovation Center,Shanghai Pudong Hospital, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China",
        "Taizhou Institute of Health Sciences, Fudan University, Taizhou, China"
      ],
      "name": "Yanfeng Jiang"
    },
    {
      "affiliations": [
        "Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China"
      ],
      "name": "Tiejun Zhang"
    },
    {
      "affiliations": [
        "Department of Neurology, Huashan Hospital Fudan University, Shanghai, China",
        "Department of Neurology, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Huashan Hospital Fudan University, Shanghai, China"
      ],
      "name": "Mei Cui"
    }
  ],
  "title": "Incidence and prevalence of vascular cognitive impairment in China: a systematic review and meta-analysis",
  "uid": "18baaa1c-67ab-5b21-bf34-6982f25f7907"
}