Introduction: Alzheimer's disease (AD) is imposing an increasing public health and socioeconomic burden. In China, rapid population ageing is sharply increasing disease burden. Previous studies have shown that AD-related costs are mainly driven by long-term informal care. However, evidence in China remains limited by an incomplete cost framework, and insufficient consideration of caregivers' burden and indirect costs. Notably, the National Dementia Action Plan (2024-2030), issued by the Chinese government, marks a major shift to early detection and comprehensive care of AD, highlighting the urgent need for nationally representative economic evidence to support policy implementation. This study aims to evaluate the economic burden and quality of life of AD patients and their caregivers in mainland China, and is the first nationwide study to include individuals with amnestic mild cognitive impairment (aMCI), providing foundational data for future health technology assessment (HTA) of early AD interventions. Methods and analysis: Baseline characteristics will be presented and compared using t-tests or chi-square tests. Economic burden will be estimated by calculating the per capita cost and weighted national total based on provincial numbers of AD patients. Indirect costs will be assessed using locally adapted replacement cost approach and forgone wages approach. The analysis will be stratified by disease severity and age. Future burden will be projected by linking data from China Statistical Yearbook 2025 and the United Nations World Population Prospects 2024. Unmet care needs, AD-related catastrophic health expenditure (CHE), and AD dependency ratio (ADDR) will also be assessed. Ethics and dissemination: Ethics approval was obtained from the Ethics Committee of Xuanwu Hospital, Capital Medical University. The study has been registered at ClinicalTrials.gov and the Chinese Clinical Trial Registry (ChiCTR). The results from this study will be actively disseminated through research articles and conference presentations. Trial registration number: [NCT05995418][1]; ChiCTR2300074723. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Trial NCT05995418; ChiCTR2300074723 ### Funding Statement This work is supported by Noncommunicable Chronic Diseases-National Science and Technology Major Project (2025ZD0546200), Beijing Outstanding Young Scientist Program (JWZQ20240101023). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The original protocol received approval from the Ethics Committee of Xuanwu Hospital, Capital Medical University, Beijing, China. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Study data are collected using an electronic data capture system and will be available from the corresponding author upon reasonable request, subject to ethical and institutional requirements. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT05995418&atom=%2Fmedrxiv%2Fearly%2F2026%2F05%2F01%2F2026.04.30.26352138.atom

Background: The gamma-glutamyl transferase to high-density lipoprotein cholesterol (GGT/HDL-C) ratio has been reported to be associated with various metabolic diseases, but its relationship with cognitive dysfunction remains limited. This study aimed to investigate the relationship between the GGT/HDL-C ratio and cognitive dysfunction in older adults. Methods and Results: This cross-sectional study included 2,769 participants and used data from the National Health and Nutrition Examination Survey (NHANES) database (2011 similar to 2014). Natural logarithmic (ln) transformation was performed on GGT/HDL-C before analysis. After adjusting for various covariates, logistic regression models showed that the association between ln(GGT/ HDL-C) and cognitive dysfunction assessed by total-CF and AFT remained significant [OR (95% CI): 1.374 (1.126 similar to 1.676), 1.220 (1.030 similar to 1.444)], whereas no significant correlation was found with CERAD W-L or DSST (P>0.05). Then, restricted cubic spline (RCS) regression and threshold effect analyses were conducted, and we observed nonlinear associations between ln(GGT/HDL-C) and cognitive dysfunction measured by total-CF, CERAD W-L and DSST (all P-nonlinear<0.05). Subgroup analyses were performed based on multiple variables, including age, gender, BMI, race, education level, DM, sleep problems, hypertension, drinking, and smoking status. The results suggested that the association between ln(GGT/HDL-C) and cognitive dysfunction was comparable across most subgroups. Conclusion: Our study suggested that higher levels of ln(GGT/HDL-C) might be associated with an increased risk of cognitive dysfunction in older adults.

As global population aging accelerates, the number of older adults with ischemic stroke (IS) continues to rise. Cognitive frailty (CF), a geriatric syndrome, exhibits relatively high prevalence in this population and is associated with substantially elevated risks of disability, mortality, and poor prognosis. This review summarizes the epidemiological characteristics, underlying pathological mechanisms, and key influencing factors of CF in older patients with IS, and proposes a personalized prevention and management framework guided by digital and intelligent technologies through multidisciplinary collaboration. The aim is to provide a robust theoretical foundation and practical guidance for early identification and precise intervention targeting CF in older adults with IS. With the caveat that current evidence is constrained by regional concentration and heterogeneity in CF definitions and assessment tools, pending prospective validation through standardized protocols.

Walking for leisure is a key contributor to healthy ageing, yet participation remains uneven across older populations. Addressing these inequalities requires approaches that capture how physical and social environments jointly shape opportunities for walking. Integrating the COM-B (Capability, Opportunity, Motivation-Behavior) model’s emphasis on behavioral opportunity, this study examines how the combinations of geographic and social domains intersect to shape walking in later life. Conceptually grounded in the geosocial framework, which posits that territories (e.g., parks, walkways, libraries), social networks (e.g., social trust and bonds), and social categories (e.g., age and gender) intertwine to shape health and well-being, multilevel models were analyzed to examine the association between interlocking geosocial environments and walking using data from the National Health Interview Survey for adults aged 55 or older (n = 14,149). Collectively the three geosocial domains were interdependent, while individually territorial characteristics showed the strongest associations with walking for leisure, followed by social network and categorical characteristics. By integrating the geographic and social opportunity domains of the COM-B model through the geosocial framework, this study quantitatively operationalizes the built, network, and categorical domains as interacting structures at a fine level of granularity to inform precisely targeted physical activity interventions among older populations.

Background: Type 2 diabetes (T2DM) is an independent risk factor for accelerated cognitive decline, creating a need for non-invasive biomarkers to diagnose T2DM-related mild cognitive impairment (T2DM-MCI). Circular RNAs (circRNAs), known to regulate T2DM pathophysiology, represent promising candidate biomarkers.Objective We aimed to assess the relationship between circRNAs levels and cognitive decline in T2DM patients. Method: This study included 64 patients with T2DM-MCI and 75 patients with T2DM and normal cognition (T2DM-NC). All T2DM-MCI participants completed a 1.5-year follow-up period. Neuropsychological assessments were performed for all participants. Blood levels of circRNA were quantified using real-time quantitative polymerase chain reaction. Results: (1) Whole-blood expression of hsa_circ_0015335 was significantly reduced in T2DM-MCI patients compared to T2DM-NC controls. (2) Receiver operating characteristic (ROC) curve analysis demonstrated that hsa_circ_0015335 could differentiate T2DM-MCI from T2DM-NC with an Area Under ROC Curve of 0.722. (3) Lower hsa_circ_0015335 levels showed significant negative correlations with global cognitive function, episodic memory, and executive function scores in T2DM-MCI patients. (4) A significant interaction was observed between reduced hsa_circ_0015335 expression and elevated triglyceride glucose (TyG) index, collectively contributing to global cognitive impairment in T2DM-MCI patients. (5) Mediation analysis revealed that the TyG index significantly mediated the association between baseline hsa_circ_0015335 levels and the rate of global cognitive decline during follow-up. Conclusions: Peripheral blood hsa_circ_0015335 shows potential as a biomarker for T2DM-MCI identification and cognitive decline progression in affected patients. This circRNA may contribute to cognitive impairment pathogenesis in T2DM, potentially through mechanisms involving glucose metabolism dysregulation.

Epidemiological studies have suggested that exposure to particulate matter (PM) may increase the risk of developing metabolic syndrome (MetS). However, evidence on the long-term effects of PM exposure on the incidence of individual MetS's components remain limited and inconsistent. This knowledge gap highlights the need for further research to clarify the potential role of PM in the development and progression of MetS over extended periods. Follow-up data collected from a cohort in Eastern China, encompassing 44,720 individuals between 2014 and 2021, were utilized. Residential exposures to fine particles (PM2.5) and inhalable particles (PM10) for each participant were estimated using a random forest model with a spatial resolution of 1 x 1 km. The generalized estimating equations (GEE) model was employed to assess the associations of long-term PM exposures with incident MetS and its components, as well as with continuous metabolic indicators related to MetS. For each 10 mu g/m3 increase in annual average concentration of PM2.5, there were significant increases in the incidence of MetS (Relative risk: 1.17, 1.10-1.26), elevated triglycerides (TG) (1.17, 1.10-1.24), decreased high-density lipoprotein cholesterol (HDL-C) (1.18, 1.11-1.27), elevated fasting blood glucose (FBG) (2.05, 1.94-2.16), and elevated blood pressure (BP) (1.30, 1.17-1.44). The RR associated with PM10 were smaller compared to PM2.5 but still statistically significant. The analyses of continuous metabolic indicators indicated that long-term exposure to PM was positively associated with FBG and systolic BP, and inversely associated with HDL-C. This cohort study provides valuable evidence of the increased risk of MetS and its components associated with long-term PM exposure in areas with high pollution levels.

BACKGROUND:Determining a non-invasive, serum-based diagnostic panel for early diagnosis of AD will play a significant role in the prevention and treatment of the disease. METHODS:We performed standardized clinical assessments and neuroimaging measurements in 45 patients with AD and an equal number of sex - and age-matched controls. 48 target peptides of 14 identified target proteins were quantitatively analyzed by PRM. RESULTS:8 protein markers were screened, including SAA4, PPBP, PF4, APOA4, F10, CPB2, C1S and IGHM. An diagnosis panel including 8 proteins and demographic characteristics markers respectively was found to be the robust with a AUC of 92.3%. CONCLUSIONS:Our study developed a new panel including protein and demographic characteristics that could be used to distinguish AD from control candidates.

Limited studies investigated the effects of long-term ozone exposure on cardiometabolic health. We aimed to examine the association of long-term ozone exposure with a range of cardiometabolic diseases, as well as the subclinical indicators in Eastern China. The study included 202,042 adults living in 11 prefecture-level areas in Zhejiang Province between 2014 and 2021. Using a satellite-based model with a 1 x 1 km spatial resolution, we estimated residential 5-year average ozone exposures for each subject. Mixed-effects logistic and linear regression models were applied to explore the associations of ozone exposure with cardiometabolic diseases and subclinical indicators, respectively. We found that a 9% [95% confidence interval (95% CI): 7-12%] higher in odds of cardiometabolic disease per 10 & mu;g/m3 increase in ozone exposure. Specifically, we also found higher prevalence of cardiovascular diseases (15%), stroke (19%), hypertension (7%), dyslipidemia (15%), and hypertriglyceridemia (9%) associated with ozone exposure. However, we did not find significant associations between ozone exposure and coronary heart disease, myocardial infarction, or diabetes mellitus. Long-term ozone exposures were also significantly associated with adverse changes in systolic blood pressure, diastolic blood pressure, total serum cholesterol, triglyceride, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, glucose concentration, and body mass index. Our results showed that people with lower education levels, those over 50 years old, and those who were overweight or obese were more susceptible to the effects of ozone on cardiometabolic diseases. Our findings demonstrated the detrimental effects of long-term ozone exposure on cardiometabolic health, emphasizing the need for ozone control strategies to reduce the burden of cardiometabolic diseases.

INTRODUCTION:Alzheimer's disease (AD) is a disease caused by many factors including occupational and environmental factors. Secondhand smoke (SHS) can affect cognitive function. However, there is limited recent epidemiological research on how SHS and occupational factors affect AD in Zhejiang province.METHODS:We established a cohort of an AD high-risk population. In 2018, a cohort of 1742 elderly aged ≥60 years was established. In 2020, the cohort was followed up, and a total of 1545 people participated in the two surveys. Data collection included demographic and economic information such as age, gender, occupation, education level etc., and relative health behavior information such as smoking, drinking and tea drinking, etc. Basic physical examination data included height, weight, blood pressure, etc. At the same time, related cognitive status was assessed. Cox proportional hazards regression models, both unadjusted and adjusted models, were used to determine associations between cohort characteristics and AD.RESULTS:The results showed that SHS exposure and occupational characteristics were associated with an increased risk of cognitive impairments in seniors. Subgroups who used to work as blue-collar workers, who never worked, who kept standing for most of the time at work, and who were engaged in hard physical labor prior to retirement, had high incidence rates of AD.CONCLUSIONS:It was revealed that SHS, standing for most of the time and hard physical labor were associated risk factors of AD among seniors, compared with white-collar work. We recommend that the government establish a community supervisory mechanism to persuade smokers to quit or control smoking.

Background: With the accelerating aging process, the number of participants with Alzheimer’s disease (AD) is rising sharply, causing a huge economic burden. Objective: This study aimed to identify blood protein and metabolic biomarkers and explore the diagnostic model for AD among elderly in southeast China. Methods: We established a cohort among population with high risk AD in Zhejiang Province in 2018. Case and control groups each consisting of 45 subjects, matched for gender and age, were randomly selected from the cohort. Based on bioinformatics research, PRM/MRM technology was used to detect candidate biomarkers. Ensemble-based feature selection and machine learning methods was used to screen important variables as risk indicators for AD. Based on the risk biomarkers, the risk diagnostic model of AD in the elderly was constructed and evaluated. Results: Cystine and CPB2 were evaluated as biomarkers. The diagnostic model is constructed using logistic regression algorithm with the best cutoff value, sensitivity, specificity, and accuracy of 0.554, 0.895, 0.976, and 0.938, respectively, which determined by Youden’s index. The results showed that the model with protein and metabolite had a high efficiency. Conclusion: It showed that the diagnostic model constructed by Cystine and CPB2 had a good performance on sample classification. This study was of great significance for the early screening and diagnosis of AD, timely intervention, control and delay the development of dementia in southeast China.

Background Studies showed that PM 2.5 might be associated with various neurogenic diseases such as Alzheimer’s Disease (AD). However, this topic had been little studied in Zhejiang province of China. Methods In 2018, we established a cohort of AD high-risk population with 1,742 elderly aged 60 and above. In 2020, the cohort was followed up, a total of 1,545 people participated the 2 surveys. Data collection included questionnaires and basic physical examinations. The average residential exposure to PM 2.5 for each participant, that in a 5-years period prior to the first survey, was estimated using a satellite-based spatial statistical model. We determined the association between PM 2.5 and AD prevalence by cox proportional hazards regression model. Results This study showed that an increase in the PM 2.5 level was an important associated risk factor that contributed to AD. The average PM 2.5 exposure levels among the study population ranged from 32.69 μg/m 3 to 39.67 μg/m 3 from 2013 to 2017, which were much higher than 5 μg/m 3 that specified in the WHO air quality guidelines. There was an association between PM 2.5 exposure and AD, and the correlations between PM 2.5 and Mini-Mental State Examination, Montreal cognitive assessment scale scores were statistically significant. An increase in the PM 2.5 level by 10 μg/m 3 elevated the risk of AD among residents by 2%-5% (HR model 2-model 4 = 1.02 to 1.05, CI model 2-model 4 = 1.01–1.10). The subgroups of male, with old age, with low education levels, used to work as farmers or blue-collar workers before retirement, overweight and obese were associated with a higher effect of PM 2.5 . Conclusions Reducing PM 2.5 exposure might be a good way to prevent AD.

Aims: We conducted a multi-sectoral comprehensive intervention for elderly Alzheimer Disease patients and their caregivers to improve their quality of life. Design: Randomized controlled trial. Methods: From June to June in 2019, 150 Alzheimer Disease patients were randomly selected from a nursing home in Zhejiang province of China, they were randomly divided into the intervention group and the control group. And they were given comprehensive and routine interventions respectively for six months. We used mixed models in our analyses to see how outcomes changed over time and how they were affected by the intervention, which could also solve the problems of missing values and data correlation. Results: After six months, compared with the control group, the communication ability, housework handling ability, self-care ability and life quality of the patients in the intervention group were improved, and the quality of life and caring ability of their caregivers were also significantly improved. Conclusion: The multi-sectoral collaborative care model proposed in this study integrated resources from several departments, effectively improved the quality of life of patients and their caregivers, and provided a way of care services for patients with Alzheimer Disease. Impact: Multi-sectoral comprehensive intervention would improve the life quality of elderly patients with Alzheimer Disease and their caregivers.

Background: Globally and across China, dementia is a major disability and a public and economic health burden. Evidence suggests dementia prevalence in China is inconsistent and has probably been underestimated by previous studies. Methods: We conducted a population-based cross-sectional study from May 2019 to December 2019, which included 20438 participants who were ≥ 65 years old, from 36 communities and 52 villages from 14 selected centers. Dementia epidemiology and risk factors were then investigated and analyzed. Findings: Our data indicated the overall crude dementia prevalence in this population was 9·1%. The overall sex- and age-standardized prevalence was 8·8%. After stratifying by sex, age, education, location, marital status, and social activity, the prevalence was higher in females in rural areas; it not only increased significantly with increasing age, but it decreased with increased education levels. None-married and less socially active populations had a higher dementia prevalence. Not only being female, older age, rural living, lower education levels, and history of stroke were risk factors, but marital status and social activities were also probable risk factors. Interpretation: Our study indicated that dementia prevalence in China was higher in individuals aged ≥ 65 years. These findings will help policy-makers and practitioners improve treatment and management strategies to reduce dementia risk. Funding: This work was supported by the National Natural Science Foundation of China (grant number: 81571057). Declaration of Interest: None to declare Ethical Approval: The study protocol was approved by the ethics committee of Tianjin Huanhu Hospital (2019-40). Written informed consent was obtained from participants or their guardians.

Background: It has been proposed that some risk factors of cardiovascular disease (CVD) are associated with and contribute to the development of all cause of dementia. Our aim was to examine the short trends and associated factors of cognitive impairment among a eastern Chinese population at high risk of CVD. Methods: We used a convenience sampling strategy to select 7 subdistricts in Zhejiang province, which was a part of China Patient-Centered Evaluative Assessment of Cardiac Events (PEACE) project. Participants in 2018 (n=3089) and in 2020 (n=3082) at high risk of CVD in Zhejiang province with registry for the PEACE Project. Participants completed 3+ neuropsychological evaluations including of Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Hospital Anxiety and Depression Scale (HAD) tests. Age-, gender- standardized prevalence rates were calculated based on the sixth population census for population of China. Cox proportional hazards regression models to estimate hazard ratios (HR) for the associations between the risk for all-cause dementia. Trial registration number was NCT02536456. Results: There was an increase prevalence of dementia and MCI among the individuals at high risk of CVD between 2018 and 2020. It showed that older age, lower education levels, having a medical history of hypertension, stroke and diabetes, having the family history of hypertension, heavy drinking, depression, and obesity were associated with dementia, while female might be a protective factor for dementia. Conclusion : More population-based strategies should be focusing on modifiable risk factors of dementia, such as CVD risk factors.

Background China has a large population of older people, but has not yet undertaken a comprehensive study on the prevalence, risk factors, and management of both dementia and mild cognitive impairment (MCI). Methods For this national cross-sectional study, 46 011 adults aged 60 years or older were recruited between March 10, 2015, and Dec 26, 2018, using a multistage, stratified, cluster-sampling method, which considered geographical region, degree of urbanisation, economic development status, and sex and age distribution. 96 sites were randomly selected in 12 provinces and municipalities representative of all socioeconomic and geographical regions in China. Participants were interviewed to obtain data on sociodemographic characteristics, lifestyle, medical history, current medications, and family history, and then completed a neuropsychological testing battery administered by a psychological evaluator. The prevalence of dementia (Alzheimer's disease, vascular dementia, and other dementias) and MCI were calculated and the risk factors for different groups were examined using multivariable-adjusted analyses. Findings Overall age-adjusted and sex-adjusted prevalence was estimated to be 60% (95% CI 58-63) for dementia, 39% (38-41) for Alzheimer's disease, 16% (15-17) for vascular dementia, and 05% (05-06) for other dementias. We estimated that 1507 million (95% CI 1453-1562) people aged 60 years or older in China have dementia: 983 million (939-1029) with Alzheimer's disease, 392 million (364-422) with vascular dementia, and 132 million (116-150) with other dementias. Overall MCI prevalence was estimated to be 155% (152-159), representing 3877 million (3795-3962) people in China. Dementia and MCI shared similar risk factors including old age (dementia: odds ratios ranging from 269 [95% CI 243-298] to 660 [524-832]; MCI: from 189 [177-200] to 470 [377-587]); female sex (dementia: 143 [131-156]; MCI: 151 [143-159]); parental history of dementia (dementia: 720 [568-912]; MCI:191 [148-246]); rural residence (dementia:116 [106-127]; MCI:145 [138-154]); fewer years of education (dementia: from 117 [106-129] to 155 [138-173]; MCI: from 148 [139-158] to 348 [325-373]); being widowed, divorced, or living alone (dementia: from 259 [230-290] to 266 [229-310]; MCI: from 158 [144-173] to 174 [156-195]); smoking (dementia: 185 [167-204]; MCI: 127 [119-136]), hypertension (dementia: 186 [170-203]; MCI: 162 [154-171] for MCI), hyperlipidaemia (dementia: 187 [171-205]; MCI: 129 [121-137]), diabetes (dementia: 214 [196-234]; MCI: 144 [135-153]), heart disease (dementia: 198 [173-226]; MCI: 117 [106-130]), and cerebrovascular disease (dementia: 544 [495-597]; MCI: 149 [136-162]). Nine of these risk factors are modifiable. Interpretation Dementia and MCI are highly prevalent in China and share similar risk factors. A prevention strategy should be developed to target the identified risk factors in the MCI population to thwart or slow down disease progression. It is also crucial to optimise the management of dementia and MCI as an important part of China's public health system.

Cardiovascular factors increased the risk of dementia. We investigated the associations between such factors, and tested that if a population with a high level of cardiovascular risk would have a higher prevalence of cognitive impairment. Participants (n=3082; ages=55+; 46.4% female) at high risk of CVD in Zhejiang province Registry for PEACE Million Persons Project, completed 3+ neuropsychological evaluations. Age-, gender- standardized prevalence rates were calculated based on the sixth population census for population of China. Adjusted logistic regression models were used to ascertain the risk factors of dementia. Trial registration number: NCT02536456. There was a high prevalence of cognitive Impairment, coupled with the fact that stroke, diabetes, hypertension and depression were significant risk factors. Cognitive impairment are highly prevalent among elderly at high risk of CVD in Zhejiang province. More population-based strategies, including preventing CVD and reducing cardiovascular risk factors would be an effective way to reduce the dementia burden.