Prevalence Trends and Influencing Factors for Post-Stroke Cognitive Impairment in China: A Meta-Analysis

ZHAO Xuejiao¹², LI Juan¹*, LI Yujie², LU Ting², XIAN Lihong³, YAN Huan³

¹Department of Nursing, Guizhou Provincial People's Hospital, Guiyang 550002, China
²School of Nursing, Guizhou University of Traditional Chinese Medicine, Guiyang 550002, China
³School of Nursing, Zunyi Medical University, Zunyi 563000, China

Corresponding author: LI Juan, Professor of Nursing; E-mail: 694807055@qq.com

Abstract

Background: Post-stroke cognitive impairment (PSCI) is a common sequela of stroke that severely impacts patients' quality of life and is often overlooked. The high incidence, subtle symptoms, and substantial social burden of PSCI make it a research priority. Understanding the prevalence and associated factors of PSCI is crucial for improving stroke prevention and treatment strategies.

Objective: To systematically evaluate the prevalence and trends of PSCI in China from 2014 to 2024 and summarize the related risk and protective factors.

Methods: Relevant studies on the prevalence and influencing factors of PSCI in China were retrieved from PubMed, Web of Science, Embase, CNKI, Wanfang Data, VIP, and CBM, covering the period from November 2014 to November 2024. Stata 16.0 and SPSS 26.0 software were used to analyze the current status and trends of PSCI, and RevMan 5.4 software was employed to analyze related factors.

Results: A total of 59 studies were included in this analysis, revealing that the overall prevalence of PSCI in China was 51% (95%CI=48%-55%). The prevalence of PSCI among males and females was 50% (95%CI=46%-54%) and 56% (95%CI=51%-60%), respectively. Patients aged under 60 years and those aged 60 years and above exhibited prevalence rates of 47% (95%CI=40%-55%) and 59% (95%CI=50%-67%), respectively. The prevalence in East China, South China, North China, Central China, Northeast China, Northwest China and Southwest China was 49% (95%CI=42%-56%), 48% (95%CI=36%-61%), 53% (95%CI=44%-62%), 48% (95%CI=40%-56%), 57% (95%CI=54%-60%), 42% (95%CI=32%-52%) and 51% (95%CI=43%-59%), respectively. Furthermore, the prevalence of hemorrhagic and ischemic stroke was 54% (95%CI=41%-67%) and 52% (95%CI=48%-56%), respectively. At different time points (≤ 2 weeks, 2 weeks~3 months, 3~6 months, >6 months), the prevalence rates were 52% (95%CI=45%-58%), 52% (95%CI=45%-58%), 40% (95%CI=35%-44%) and 56% (95%CI=43%-70%) respectively. The highest prevalence rate of 63% (95%CI=55%-71%) was observed in individuals with lower education levels (primary school and below). Additionally, the prevalence among married and unmarried individuals was 57% (95%CI=46%-68%) and 64% (95%CI=52%-75%), respectively. The prevalence among employed and unemployed individuals was 64% (95%CI=44%-84%) and 71% (95%CI=56%-87%), respectively. Finally, the prevalence among mental workers and manual workers was 48% (95%CI=33%-64%) and 53% (95%CI=30%-76%), respectively, while those living with family members and living alone exhibited prevalence rates of 62% (95%CI=43%-82%) and 71% (95%CI=62%-81%), respectively.

The prevalence of PSCI in China increased with age (χ²=73.805, P<0.01), and was notably higher among individuals with lower education levels (χ² trend=164.711, P<0.01). There were significant differences among different regions (χ²=74.701, P<0.01). With the extension of assessment periods, the prevalence showed an upward trend (χ² trend=186.504, P<0.05). Although a significant difference in prevalence rates was observed across different periods (χ² trend=325.964, P<0.01), no linear correlation was identified (P=0.259). Factors such as age, female gender, hypertension, diabetes, hyperlipidemia, a history of stroke, carotid plaque, hyperhomocysteinemia, C-reactive protein levels, smoking, drinking and NIHSS score were identified as risk factors for PSCI in China, whereas education level and physical exercise emerged as protective factors.

Conclusion: The overall prevalence of PSCI in China is notably high, exhibiting significant regional and provincial variations, as well as a dynamic trend over time. The prevalence is particularly elevated among females, the elderly, and individuals with lower educational attainment. Additionally, hypertension, diabetes, and hyperlipidemia are identified as risk factors for PSCI. It is imperative for medical institutions at all levels to prioritize these high-risk groups, and expedite the development and implementation of comprehensive prevention and control strategies for PSCI to alleviate the social care burden and economic strain in China.

Keywords: Stroke; Cognitive impairment; Prevalence; Root cause analysis; Meta-analysis

1. Materials and Methods

This study followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines.

1.1 Search Strategy

Using a combination of MeSH terms and free-text terms, we systematically searched PubMed, Web of Science, Embase, CNKI, Wanfang Data, VIP, and CBM for studies on the prevalence and risk factors of PSCI in China, with the search period from November 2014 to November 2024. We also manually reviewed the reference lists of included studies using a "snowballing" approach to identify additional relevant literature. English search terms included: Stroke, Cerebrovascular Accident, Apoplexy, Cognitive Dysfunction, Cognitive Deficit, Cognitive Decline, Cognitive Disorder, Cognitive Impairment, Morbidity, Epidemi, Prevalence, Incidence, Influencing Factor, Affecting Factor, Risk Factor, China, Inner Mongolia, Sinkiang, Chinese, Hong Kong, Macao, Taiwan, etc. Chinese search terms included: stroke, stroke, cerebral infarction, cerebrovascular accident, cognitive impairment, cognitive dysfunction, cognitive decline, cognitive damage, cognitive decline, cognitive impairment, incidence, prevalence, epidemiology, current status, current situation, risk factors, influencing factors, related factors, etc. The specific PubMed search strategy is shown in Table 1 [TABLE:1].

1.2 Inclusion Criteria

Studies were included if they met the following criteria: (1) study subjects were Chinese patients aged ≥ 18 years who met diagnostic criteria for stroke; (2) study designs included cross-sectional, case-control, and cohort studies; (3) cognitive function was screened using the Mini-Mental State Examination (MMSE) or Montreal Cognitive Assessment (MoCA); (4) outcome measures were PSCI prevalence and/or its influencing factors; (5) only Chinese and English literature was included.

1.3 Exclusion Criteria

Studies were excluded if they were: (1) abstracts, conference papers, reviews, or study protocols; (2) unable to provide valid data or had incomplete data; (3) unable to obtain full text; (4) sample size < 150 cases; (5) animal experiments; (6) had unreasonable study design, poor literature quality, or statistical errors; (7) did not exclude pre-stroke cognitive impairment; or (8) duplicate data.

1.4 Literature Screening and Data Extraction

Two researchers independently screened literature, extracted data, and cross-checked results, with disagreements resolved through discussion or consultation with a third party. Extracted data included: (1) basic information: first author, publication year, study location, etc.; (2) study subject characteristics: stroke type, sample size, age, education level, etc.; (3) outcome measures: assessment time, tools, number of cases, influencing factors, etc. Supplementary data were obtained from authors via email when necessary.

1.5 Risk of Bias Assessment

Two researchers independently assessed the risk of bias in included studies and cross-checked results, with disagreements resolved through discussion or with third-party assistance. Cross-sectional studies were evaluated using the Agency for Healthcare Research and Quality (AHRQ) recommended tool, consisting of 11 items scored as 1 point for "yes" and 0 points for "no" or "unclear," with total scores of 8-11 indicating high quality, 4-7 indicating moderate quality, and 0-3 indicating low quality. Case-control and cohort studies were evaluated using the Newcastle-Ottawa Scale (NOS), with scores of 1-3 indicating low quality, 4-6 indicating moderate quality, and 7-9 indicating high quality.

1.6 Statistical Analysis

Stata 16.0 was used to analyze prevalence and trends, while RevMan 5.4 was used to analyze influencing factors. Pooled effect sizes were expressed as odds ratios (OR) with 95% confidence intervals (95%CI). Heterogeneity was analyzed using χ² tests (α=0.1) and I² tests. A fixed-effects model was used when I²<50% and P≥0.1; when I²≥50% and P<0.1, a random-effects model was employed with sensitivity or subgroup analyses conducted. Publication bias was assessed using funnel plots and Egger's test. Comparisons of PSCI prevalence across different subgroups used χ² tests, while trend analysis was performed using SPSS 26.0 software for trend χ² tests. P<0.05 was considered statistically significant.

2. Results

2.1 Literature Screening Results

The initial search yielded 10,819 relevant articles. After systematic screening, 59 studies were ultimately included, covering 24 provinces/autonomous regions/municipalities in China, with a total sample size of 21,704 cases, including 11,000 PSCI patients. The literature screening process is shown in Figure 1 [FIGURE:1].

2.2 Characteristics of Included Studies

The basic characteristics of included studies are presented in Table 2 [TABLE:2]. Among them, 32 cross-sectional studies had AHRQ scores of 7-11; 21 cohort studies had NOS scores of 6-9; and 6 case-control studies had NOS scores of 8-9.

2.3 Meta-Analysis Results of PSCI Prevalence

2.3.1 Overall PSCI Prevalence

Significant heterogeneity was observed among the 59 studies (I²=97.4%, P<0.001). Using a random-effects model, the meta-analysis revealed that the overall prevalence of PSCI in China was 51% (95%CI=48%-55%), as shown in Figure 2 [FIGURE:2].

2.3.2 Subgroup Analysis

Subgroup analyses were conducted by gender, age, geographic region, stroke type, assessment time, assessment tool, education level, marital status, employment status, occupation type, and living situation. The results showed that PSCI prevalence was 50% in males and 56% in females; 47% in patients <60 years and 59% in those ≥60 years; 49%, 48%, 53%, 48%, 57%, 42%, and 51% in East China, South China, North China, Central China, Northeast China, Northwest China, and Southwest China, respectively; 54% in hemorrhagic stroke and 52% in ischemic stroke; 52%, 52%, 40%, and 56% at assessment time points of ≤2 weeks, 2 weeks-3 months, 3-6 months, and >6 months, respectively; 46% using MMSE alone, 55% using MoCA alone, and 49% using both; 63%, 50%, and 42% for primary school and below, middle/high school, and college and above education levels, respectively; 57% in married and 64% in unmarried individuals; 64% in employed and 71% in unemployed individuals; 48% in mental workers and 53% in manual workers; and 62% in those living with family and 71% in those living alone. Detailed results are presented in Table 3 [TABLE:3].

2.3.3 Trend Analysis

Comprehensive trend analysis of PSCI prevalence in China revealed several key patterns. From an age perspective, PSCI prevalence increased significantly with age (χ²=73.805, P<0.01). Regarding education, higher educational attainment was associated with lower PSCI prevalence (χ² trend=164.711, P<0.01). Spatial distribution analysis showed significant differences across China's seven geographic regions (χ²=74.701, P<0.01), with prevalence ranging from 42% to 57%, and across provincial-level administrative regions (χ²=495.373, P<0.01), with prevalence ranging from 26% to 80%. Regarding assessment timing, prevalence showed a linear upward trend with extended assessment periods (χ² trend=186.504, P<0.05). Analysis by publication time showed significant differences in prevalence across years from January 2014 to November 2024 (χ² trend=325.964, P<0.01), but no linear correlation was found (linear association=1.272, P=0.259), precluding determination of a consistent year-over-year increasing trend.

2.3.4 Sensitivity Analysis

Sensitivity analysis indicated no significant change in effect size, suggesting robust study results.

2.3.5 Publication Bias

Funnel plots for PSCI prevalence in China showed roughly symmetrical distribution, as shown in Figure 5 [FIGURE:5]. Combined with Egger's test (t=-1.04, P=0.304), these results indicated no significant risk of publication bias.

2.4 Meta-Analysis Results of PSCI Influencing Factors

Meta-analysis of 46 studies examining influencing factors revealed that advanced age (OR=1.08), female gender (OR=1.65), hypertension (OR=2.01), diabetes (OR=2.03), hyperlipidemia (OR=1.55), stroke history (OR=2.56), carotid plaque (OR=1.76), hyperhomocysteinemia (OR=1.10), elevated C-reactive protein (OR=1.14), smoking (OR=1.63), alcohol consumption (OR=2.11), and high NIHSS score (OR=1.20) were risk factors for cognitive impairment in Chinese stroke patients (P<0.05), while higher education level (OR=0.71) and physical exercise (OR=0.71) were protective factors (P<0.05). Detailed results are presented in Table 6 [TABLE:6].

3. Discussion

3.1 High PSCI Prevalence Requires Enhanced Early Screening and Prevention

This meta-analysis of 59 studies (32 cross-sectional, 21 cohort, and 6 case-control studies) found that the overall prevalence of PSCI in China was 51%, consistent with previous research. Subgroup analyses revealed several important patterns:

Gender and Age: Female PSCI prevalence (56%) was higher than male (50%), and patients ≥60 years showed higher prevalence (59%) compared to those <60 years (47%). These findings align with our influencing factor analysis, identifying females and older adults as high-risk populations. The higher risk in females may be attributed to elevated follicle-stimulating hormone (FSH) levels, which activate the C/EBPβ/AEP pathway, promoting Aβ and Tau pathology and increasing cognitive impairment risk. Clinicians should pay special attention to cognitive changes in female stroke patients, conduct early screening and assessment, and strengthen health education to monitor and delay cognitive decline.

Education Level: Individuals with primary school education or below had the highest PSCI prevalence (63%), followed by those with middle/high school education (50%), while those with college education or above had the lowest (42%). Higher education appears protective, likely because education increases cerebral blood flow in temporoparietal regions, reduces neuronal damage from toxins and oxidative stress, and enhances cognitive reserve, strengthening neuronal activity and synaptic connections. Conversely, lower education levels result in insufficient brain stimulation, making sensitive neurons more vulnerable to degeneration. Clinical practice should therefore intensify cognitive screening and intervention among less-educated populations.

Stroke Type: Hemorrhagic stroke patients showed slightly higher PSCI prevalence (54%) than ischemic stroke patients (52%), possibly related to differences in brain injury severity, genetic factors, and accompanying symptoms. Future large-scale multicenter studies are needed to explore these differences further.

Assessment Timing: PSCI prevalence was 52% at both ≤2 weeks and 2 weeks-3 months post-stroke, decreased to 40% at 3-6 months, then increased again to 56% at >6 months. While some studies suggest PSCI prevalence increases over time post-stroke, others show different patterns. A 2-year longitudinal study found cognitive function changes fastest and is most unstable within 3-6 months post-stroke, with highest incidence at 3 months and lowest at 6 months. This highlights the dynamic nature of PSCI and the importance of early screening after patient stabilization and long-term follow-up mechanisms. The 3-month post-stroke time point is widely used because neurological deficits have typically stabilized while cognitive dysfunction becomes apparent.

Marital Status and Living Situation: Unmarried individuals showed higher PSCI prevalence (64%) than married individuals (57%), possibly due to lack of family support. Family support is crucial for stroke patients' health outcomes and recovery, while long-term solitary living increases risks of loneliness, depression, and cognitive impairment. Healthcare providers should emphasize the importance of family involvement in rehabilitation.

Assessment Tools: PSCI prevalence was higher when assessed with MoCA alone (55%) compared to MMSE alone (46%) or both tools combined (49%). While both MoCA and MMSE have good screening value for PSCI, MMSE has relatively lower sensitivity for mild cognitive impairment. MoCA demonstrates higher sensitivity and specificity for detecting mild impairment, and clinical practice often recommends using both tools together.

Geographic Distribution: Significant regional variations existed, with Northeast China showing the highest prevalence (57%) and Inner Mongolia reaching 80%. These differences likely relate to regional variations in economic development, healthcare levels, dietary habits, and cultural backgrounds. PSCI high-prevalence regions warrant targeted attention with early screening, treatment, and region-specific prevention strategies.

Temporal Trends: From 2014-2016, PSCI prevalence increased from 42% to 58%, then remained relatively stable (54%-58%) for the next four years except for a dip to 40% in 2017. After a slight decline in 2020-2021, prevalence rose again to 2016 levels by 2021-2024. However, no linear temporal trend was identified. Regardless of trends, the overall high prevalence necessitates continued strengthening of stroke prevention education and steady advancement of control efforts.

3.2 PSCI Is Influenced by Multiple Factors

This study identified advanced age, female gender, hypertension, diabetes, hyperlipidemia, stroke history, carotid plaque, hyperhomocysteinemia, elevated C-reactive protein, smoking, alcohol consumption, and high NIHSS score as risk factors, while higher education and physical exercise were protective.

Hypertension causes vascular narrowing, reduced compliance, and endothelial damage, promoting atherosclerosis and reducing cerebral blood flow, thereby affecting cognitive function. Maintaining blood pressure below 140/90 mmHg helps preserve cerebral perfusion and prevent dementia. Diabetes reduces hippocampal neuron density, disrupts neural information transmission, decreases neuroprotective Aβ while increasing neurotoxic Aβ release, and creates a chronic inflammatory state that exacerbates neuronal and endothelial damage. Hyperlipidemia promotes atherosclerosis, affects brain perfusion, and increases neuronal fiber tangles and amyloid accumulation. Stroke history leads to cumulative brain damage, with recurrent stroke patients showing significantly higher cognitive impairment rates (30%) compared to first-time stroke patients (10%). Carotid plaque causes vascular stenosis, cerebral hypoperfusion, and promotes capillary malformation and amyloid plaque formation, while unstable plaques can embolize and worsen cerebral ischemia.

Hyperhomocysteinemia increases Alzheimer's disease risk by 15% for every 5 μmol/L elevation, exacerbating oxidative stress, endothelial dysfunction, and arterial smooth muscle proliferation. It correlates with white matter damage and may cause micro-arteriosclerosis and neurotoxic reactions. C-reactive protein, while protective acutely, can promote LDL-C uptake by macrophages, form foam cells, damage endothelial function, and accelerate atherosclerosis when chronically elevated. Smoking stimulates vascular endocrine pathways, increases adrenaline and angiotensin secretion, raises blood pressure, and induces oxidative stress. Alcohol consumption damages neurons and exacerbates inflammatory factor expression during acute cerebral infarction. High NIHSS scores indicate severe neurological deficits, often involving critical brain regions that disrupt cognitive information networks.

Physical exercise is a protective factor that improves mental activity, mood, and reduces cerebrovascular perfusion stress. A 12-month randomized controlled trial demonstrated that exercise improves cognitive function in chronic stroke patients.

In conclusion, PSCI prevalence in China is high with significant regional variations and dynamic temporal patterns. High-risk groups include females, the elderly, and those with lower education. Key modifiable risk factors include hypertension, diabetes, hyperlipidemia, and lifestyle factors. Healthcare institutions should prioritize these high-risk populations and implement comprehensive prevention strategies including blood pressure and glucose control, smoking cessation, alcohol moderation, and promotion of physical exercise to reduce cognitive impairment burden.

Author Contributions: ZHAO Xuejiao was responsible for conceptualization, data collection, manuscript writing and revision; LI Yujie, LU Ting, and YAN Huan conducted literature search, data extraction, quality assessment, and data analysis; LI Juan supervised manuscript review, quality control, and funding acquisition.

Conflict of Interest: None declared.

Funding: National Natural Science Foundation of China (72364005); Guizhou Provincial Health Commission Fund (gzwkj2024-263); Guizhou Provincial Administration of Traditional Chinese Medicine Science and Technology Research Project (QZYY-2025-165)

Citation: ZHAO XJ, LI J, LI YJ, et al. Prevalence trends and influencing factors for post-stroke cognitive impairment in China: a meta-analysis [J]. Chinese General Practice, 2025. DOI: 10.12114/j.issn.1007-9572.2025.0073. [Epub ahead of print]

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Received: March 3, 2025; Revised: May 18, 2025
Edited by: JIA Mengmeng