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S.-Y. Li1,2,3,#, X.-Y. Xie1,2,3,#, D. Liu1,2,3,#, G.-R. Cheng1,2,3,#, F.-F. Hu1,2,3,#, D.-Y. Zeng1,2,3,#, X.-C. Chen5, L.-F. Jia6, Y.-J. Wang7, X.-L. Bu7, C. Qiu8, F. Gao8, J.-G. Gu8, M.-F. Liu8, Y. Li9, Y.-L. Zhou1,3, H.-J. Chang1,3, Y.-M. Ou1,3, L. Xu1,3, Z.-X. Wu10, J.-J. Zhang1,2,3, J.-Y. Wang1,2,3, L.-Y. Huang1,2,3, Y.-Y. Cui1,2,3, J. Zhou1,2,3, X.-C. Liu1,2,3, J. Liu1,2,3, Q.-Q. Nie1,2,3, D. Song1,2,3, C. Cai1,2,3, G.-B. Han1,2,3, X. Yang2, W. Tan2, J.-T. Yu4, Y. Zeng1,2,3


1. Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China; 2. Brain Science and Advanced Technology Institute, School of Medicine, Wuhan University of Science and Technology, Wuhan, China; 3. School of Public Health, Wuhan University of Science and Technology, Wuhan, China; 4. Department of Neurology and National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China; 5. Department of Neurology, Fujian Medical University Union Hospital, and Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, China; 6. Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China; 7. Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China; 8. Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China; 9. Department of Laboratory Medicine, Hubei Provincial Hospital of Integrated Chinese & Western Medicine, Wuhan, China; 10. Wuchang Hospital affiliated to Wuhan University of Science and Technology, Wuhan, China; #Joint first authors: Shi-Yue Li, Xin-Yan Xie, Dan Liu, Gui-Rong Cheng, Fei-Fei Hu, and De-Yang Zeng

Corresponding Author: Yan Zeng, Brain Science and Advanced Technology Institute, School of Medicine, Wuhan University of Science and Technology, West Huangjiahu Road, Hongshan District, Wuhan 430065, China. Email:; Jin-Tai Yu, Department of Neurology and National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Huashan Hospital, Shanghai Medical College, Fudan University, 12th Wulumuqi Zhong Road, Shanghai 200040, China. Email:; Wei Tan, Geriatric Hospital Affiliated to Wuhan University of Science and Technology, West Huangjiahu Road, Hongshan District, Wuhan 430065, China. Email:

J Prev Alz Dis 2024;3(11):589-600
Published online March 26, 2024,



BACKGROUND: Alzheimer’s disease (AD), the most common type of irreversible dementia, is predicted to affect 152 million people by 2050. Evidence from large-scale preventive randomized controlled trials (RCTs) on modifiable risk variables in Europe has shown that multi-domain lifestyle treatments for older persons at high risk of dementia may be practical and effective. Given the substantial differences between the Chinese and European populations in terms of demographics and living conditions, direct adoption of the European program in China remains unfeasible. Although a RCT has been conducted in China previously, its participants were mainly from rural areas in northern China and, thus, are not representative of the entire nation.There is an urgent need to establish cohorts that represent different economic, cultural, and geographical situations in order to explore implementation strategies and evaluate the effects of early multi-domain interventions more comprehensively and accurately.
MEDTODS: We developed an integrated intervention procedure implemented in urban neighborhood settings, namely China Initiative for Multi-Domain Intervention (CHINA-IN-MUDI). CHINA-IN-MUDI is a 2-year multicenter open-label cluster-randomised controlled trial centered around a Chinese-style multi-domain intervention to prevent cognitive decline. Participants aged 60–80 years were recruited from a nationally representative study, i.e. China Healthy Aging and Dementia Study cohort. An external harmonization process was carried out to preserve the original FINGER design. Subsequently, we standardized a series of Chinese-style intervention programs to align with cultural and socioeconomic status. Additionally, we expanded the secondary outcome list to include genomic and proteomic analyses. To enhance adherence and facilitate implementation, we leveraged an e-health application.
RESULTS: Screening commenced in July 2022. Currently, 1,965 participants have been randomized into lifestyle intervention (n = 772) and control groups (n = 1,193). Both the intervention and control groups exhibited similar baseline characteristics. Several lifestyle and vascular risk factors were present, indicating a potential window of opportunity for intervention. The intervention will be completed by 2025.
CONCLUSIONS: This project will contribute to the evaluation of the effectiveness and safety of intervention strategies in controlling AD risk and reducing clinical events, providing a basis for public health decision-making in China.

Key words: Alzheimer’s disease, preclinical stages, multi-domain behavioral intervention, multicenter, the Chinese Healthy Aging and Dementia Study, randomized controlled clinical trial.

Abbreviations: Aβ: Amyloid β; AD: Alzheimer’s disease; ADL: ability of daily living; AI: artificial intelligence; ApoE: apolipoprotein E; BMI: body mass index; CAIDE: Cardiovascular risk factors for aging and dementia; CRF: Case Report Form; CHINA-IN-MUDI: China initiative for multi-domain intervention; DNA: DeoxyriboNucleic Acid; EHR: electronic health records; ERP: event related potential; FINGER: Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability; HEAD: China HEalth Aging and Dementia Study; MCI: mild cognitive impairment; MIND-China: Multimodal INterventions to delay Dementia and disability in rural China; MMSE: Mini-Mental State Examination; MRI: magnetic resonance imaging; mITT: modified intention-to-treat; NIA-AA: National Institute on Aging-Alzheimer’s Association workgroup; NTB: neuropsychological test battery; PD: Parkinson disease; PET-CT: Positron Emission Tomography-Computed Tomography; PSG: polysomnography; QOL: quality of life; RCTs: randomized controlled trials; rsEEG: resting-state electroencephalogram; SD: standard deviation; SINGER: the SINgapore GERiatric intervention study; sMRI: structural Magnetic Resonance Imaging.



The burden of dementia continues to increase worldwide and is more noticeable in China. The number of people with Alzheimer’s disease (AD), the most common subtype of irreversible dementia, is expected to reach 152 million by 2050 (1). The prevalence of cognitive impairment in china experienced an initial increase from 2002 to 2008, followed by a subsequent decrease until 2018. Cognitive impairment and AD are complex clinical diseases that are influenced by factors such as aging and genetics, while also being affected by various modifying factors (2). Prevention suitable for each nation’s unique circumstances is the only viable approach to public health problems of this magnitude. In recent years, evidence from large-scale preventive randomized controlled trials (RCTs) on modifiable risk factors (3) has begun to emerge. Three pioneering multi-lifestyle intervention trials have been completed in Europe, namely, the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) (4), the Multi-domain Alzheimer Preventive Trial (5), and the Dutch Prevention of Dementia by Intensive Vascular Care (6). FINGER was the first extensive RCT study of multiple lifestyle interventions spanning two years and reported a positive interference effect. It led to the establishment of a global alliance (WW-FINGERS) to promote the implementation of the FINGER model in countries outside Finland, including China (7). To date, no remarkable results from similar trials in other countries have been published. Several cohort studies, including Moll vanCharante’s RCT of multiple vascular nursing interventions for prevention of dementia (6) and the Austrian Polyintervention Study to Prevent Cognitive Decline after Ischemic Stroke (8) did not show significant positive effects of multi-domain interventions on primary outcomes but showed positive intervention effects on specific sub-measures. In Singapore, the SINGER pilot RCT, designed to test the feasibility and acceptability of the FINGER model, provided valid evidence for the efficacy of a multivariate lifestyle intervention in preventing cognitive decline within the Asian population (9).
These studies suggest that multi-domain lifestyle interventions may be feasible and effective for older adults at high risk of dementia. However, the multi-domain intervention studies conducted to date appear to have complex and wide variations in the selection of target populations, intervention forms and intensity, control parameters, and outcome measures (10).
Given the substantial differences between the Chinese and European populations in terms of demographics and living conditions, direct adoption of the European program in China remains unfeasible. Thus, larger cohort studies are needed before drawing conclusions that can guide national public health policies in China. This is important given China’s higher prevalence of modifiable risk factors and its potentially greater dementia-prevention prospects than those reported worldwide (11). Although a randomized controlled Multimodal INterventions to delay Dementia and disability in rural China (MIND-China) based on the FINGER model has been conducted (12), its participants were mainly from rural areas in northern China and thus are not representative of the entire nation. There is an urgent need to establish cohorts that represent different economic, cultural, and geographical situations in order to explore implementation strategies and evaluate the effects of early multi-domain interventions more comprehensively and accurately. In response, Chinese scientists in the field of AD recently launched a nationally representative cohort known as the China Health Aging and Dementia Community Cohort Study (China HEAD), supported by the Science and Technology Innovation 2030 Major Projects (2022ZD0211600). We are actively planning collaborations and integrating efforts to initiate a project similar to the FINGER trial (4) with the objective of developing effective and sustainable approaches to dementia prevention and risk reduction. We have developed an integrated intervention procedure by unifying the most popular traditional components, such as the Eight Section Brocade (Ba Duan Jin), Tang poems, and popular songs, into the program and implementing the procedure in urban neighborhood settings. We also took advantage of the most recent insights into AD biomarkers to precisely evaluate the effectiveness of artificial intelligence (AI) technology in enhancing intervention adherence. This report presents an overview of the trial design and explores the different strategies and tools used in the China Initiative for Multi-Domain Intervention (CHINA-IN-MUDI).



Study design

The CHINA-IN-MUDI study was designed as a two-year-multicenter, multi-domain lifestyle intervention RCT. The trial is registered on (2300075181). We recruited participants from the China HEAD study, which enrolled at least 20,000 older adults from four major cities in China (Wuhan, Beijing, Shanghai, and Fuzhou). The primary objective of China’s HEAD study is to establish a national dementia prevention research platform by creating nationally integrated and standardized cohorts across various regions of China. These cohorts were collected using a standardized case report form (CRF) (shown in Supplementary Materials). Cluster sampling of 16 neighborhoods covered by the China HEAD was conducted to select locations for the CHINA-IN-MUDI intervention (intensive multi-domain intervention) or control (regular health advice) sites. The clinical sites include Wuhan Science and Technology University, Huashan Hospital, Fudan University, Fujian Medical University Union Hospital, Fujian Medical University, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Daping Hospital, Third Military Medical University.
The interventions focus on exercise, cognitive stimulation, diet, and cardiovascular risk reduction. Outcomes assessments are completed at baseline and months 6, 12, 24, 48, and 84, and the primary outcome is a global cognition composite score. After baseline assessment, computer-generated allocations were performed in 16 neighborhoods (covered by HEAD project) by the researchers. Participants were grouped according to their neighborhoods, maintaining homogeneity within each group. All enrolled older adults within the same neighborhood received the same treatment to minimize the impact of contamination on intervention effectiveness. The grouping information was not disclosed to the participants and was concealed by the evaluators. Each site was led by an experienced subgroup leader and operated by a skilled team. The monitoring committee ensured that the protocol for each intervention domain was carefully followed at each study site.


Inclusion and exclusion criteria

The CHINA-IN-MUDI recruits individuals aged 60–80 years. Because the participants of the China HEAD were prescreened using the Cardiovascular Risk Factors for Aging and Dementia (CAIDE) (calculated based on sex, age, education, body mass index (BMI), systolic blood pressure, total cholesterol, and level of physical activity, with a total score of 0-15) (13) and a neuropsychological test battery (NTB) when enrolled in the cohort, the baseline characteristics served as the reference for recruiting participants into the intervention program.
The inclusion criteria were as follows: (1) aged 60 to 80 years at the time of baseline investigation; (2) from China HEAD cohort; (3) living in a sampling neighborhood; (4) having CAIDE score which is in the upper quartile of the cohort (values above 75%); (5) meting at least one of the following criteria: A) MMSE (z score) between 0 and −1.0, B) learning task (z score) <0, and C) delayed recall (z score) <0; meeting any item of A-D: A) carriers of ApoE ε4 allele, B) first-degree family history of significant memory impairment, C) having one of the Aβ (Aβ42/40) and Tau (p-Tau 181, p-Tau 217, and p-Tau 231) pathological markers in blood but lacking clinical signs and symptoms of AD (typical or atypical phenotype), and D) olfactory abnormalities; (7) no traveling for 4 or more consecutive weeks during the study period; (8) willing to complete all study-related activities for 24 months and provide written informed consent.
Participants have been excluded if they experience one of the following conditions: (1) prior diagnosis or self-report of AD dementia and other dementia; (2) diagnosis or self-report of a major psychiatric illness (e.g., major depression, schizophrenia); (3) history of severe alcohol or drug abuse; (4) hearing or language impairment, and other conditions that prevent cooperation; (5) a need to limit physical activity and/or diet due to functional decline, which include a history of chemotherapy for bone or joint disease, renal failure, ischemic heart disease, or cardiopulmonary disease, diagnosed or self-reported neurodegenerative diseases other than AD (e.g., Parkinson disease and Parkinson disease-related diseases, Huntington’s disease); (6) an inability to complete an magnetic resonance imaging and Positron Emission Tomography-Computed Tomography or a cognitive test; (7) participated in another clinical research trial. Table 1 shows an overview of the inclusion and exclusion criteria for CHINA-IN-MUDI and a comparison with FINGER and MIND-China.

Table 1. Comparison between CHINA-IN-MUDI with MIND-China and FINGER

Abbreviations: Aβ Amyloid β, AD Alzheimer’s disease, ApoE apolipoprotein E,CAIDE Cardiovascular risk factors for aging and dementia, CHINA-IN-MUDI China initiative for multi-domain intervention, FINGER Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability, HEAD China HEalth Aging and Dementia Study, MCI mild cognitive impairment, MIND-China Multimodal INterventions to delay Dementia and disability in rural China, MMSE Mini-Mental State Examination, MRI magnetic resonance imaging, PD Parkinson disease, PET-CT Positron Emission Tomography-Computed Tomography.



To ensure comprehensive representation in our intervention program, we implemented a sequential multi-step screening process for participant recruitment. Leveraging electronic health records (EHR) specifically designed for individuals aged 65 years and above in China, we identified potential candidates who could actively participate in interventions within 16 sampled neighborhoods. The recruitment process consisted of three distinct phases, which are outlined below.
Screening 1: Initial Contact. In order to identify potential participants within the sampled neighborhoods, we employed a two-pronged approach. Firstly, we utilized EHR from local health centers to identify individuals who met the preliminary inclusion criteria for the study. Concurrently, we implemented an extensive outreach strategy that encompassed widespread social media platforms. In addition, we conducted grassroots efforts and involved forging community partnerships to maximize our reach and ensure diverse representation among the recruited participants.
Screening 2: Assessment of Eligibility. Following the initial contact in Phase 1, participants who responded to the screening were provided with comprehensive details regarding the study. To evaluate their eligibility, CRF was employed to gather extensive information encompassing a wide array of topics. These topics included individual and familial background, lifestyle and economic circumstances, physical and mental well-being, social and psychological factors, behavioral patterns, and biological aspects. The data collected through the CRF allowed for a thorough assessment of each participant’s eligibility for the study.
Screening 3: Face-to-face Cognitive Screening. For screening 2-eligible candidates, a face-to-face cognitive screening was conducted by experienced neurologists. These professionals utilized NTB that encompassed various domains, including global cognition, executive functioning/attention, language, spatial functioning, and memory. To optimize efficiency and minimize waiting time between the baseline assessment and intervention initiation, participants were grouped into batches based on their availability to join the next scheduled intervention program. Factors such as time, date, and location were taken into consideration when assigning participants to specific batches, ensuring a streamlined and timely progression into the intervention phase.

Sample size calculations

The sample size was calculated based on previous studies of mild AD and multi-domain interventions (4, 14). A decrease of approximately -0.21 Z score with a standard deviation (SD) of 0.5 was estimated in the control group over two years. Based on a significance level of 5% and 90% power, the estimated sample size required was approximately 500 participants per group. Considering an annual loss-to-follow-up rate of 10%, the minimum number of participants was 600.

Chinese style intervention design

The interventions were modeled on FINGER and adapted for Chinese culture and delivery in the community—in collaboration with doctors and public health workers from local community servece centers. Participants in the intervention group visit the senior center within their neighborhood every week for an integrated multi-domain on-site intervention program (Figure 1). These senior centers are conveniently located within neighborhoods, enabling easy access for older persons without additional public transportation. The six components of the intervention include a 5-minute finger exercise; a 20-minute Eight Section Brocade exercise; a 20-minute Tang poem learning, memorization, and recitation session; a 20-minute popular song learning and rehearsing session; a 20-minute lecture on nutrition balance and risk factors of cardiovascular diseases; and a 15-minute session for anthropometric measurements (weight, blood pressure, glucose, hip and waist circumference, heart rate, and blood oxygen) and cardiovascular and metabolic condition monitoring (hypertension, diabetes, and hyperlipidemia) (Figure 2). These six components are initiated gradually to facilitate adherence to each component. Multiple classes are designed for each neighborhood based on the number of recruits, with 30 participants per class. A researcher serves as a class coordinator, and a family doctor from the community health service center co-directs the intervention project. Participants are encouraged to perform at least five weekly sessions at home, with a minimum of 20 min per session.

Figure 1. Trial summary showing key aspects of recruitment, interventions timeline, and outcomes

NTB, neuropsychological test battery; CAIDE, Cardiovascular Risk Factors for Aging and Dementia.

Figure 2. Intervention components used in China Initiative for Multi-Domain Intervention

Physical intervention

The physical intervention includes a group of sessions (5-minute finger exercises and 20-minute Eight Section Brocade). Finger exercises, which are aerobics, can activate cerebral cortex function in multiple brain regions, thereby improving cognitive function and delaying the progress of neurodegeneration (15). These exercises have been widely used for intellectual development in young children and the physical health care of older adults. Some studies have found that finger exercises are preventive against AD (15). The Eight Section Brocade, a traditional qigong exercise with a long history in China, consists of eight smooth and graceful movements resembling silk brocade. Practicing the Eight Section Brocade has excellent fitness effects, is suitable for people of all ages, and is well received by the public. The project also offers two other exercise programs, namely, Twenty-Four Simplified Tai Chi and Jiamusi Happy Dance Fitness, to enhance enjoyment and diversity. Similar to the Eight-Section-Brocade, these two programs are popular among older Chinese individuals.

Cognitive intervention

The cognitive intervention includes learning Chinese Tang poetry and rehearsing popular songs. The Tang poetry-300 selected for this program represents the essence of Chinese culture, with approximately 100 of them being essential content in primary and secondary school language curricula in China and enjoying high popularity in Chinese and world poetry history (16). The visual and auditory effects of Chinese characters in Tang poetry have been well investigated (17). The participants are required to recite and understand poems, developing their ability to feel, imagine, and understand the deeper meanings of these pieces. The enjoyable and rhythmic nature of these poems makes them effective cognitive intervention materials that cover various aspects of cognitive training, including attention, executive function, memorization, vocabulary skills, and writing. Compared with fragmented memory, attention, and executive function training, Tang poems have higher participant compliance (17).
In addition to Tang poetry-300, we select 60 popular songs beloved by Chinese people aged 60-80 years for cognitive training. Long-term, rigorous musical training promotes various aspects of spoken language processing and facilitates speech tone, vowel processing and other aspects of spoken language processing (18). Evidence suggests that music affects various brain regions and may contribute to strengthening brain networks and pathways associated with sensory and motor processes, emotions, perception, and memory (19).

Nutritional intervention

Nutritional intervention is mainly conducted through lectures and Q&A sessions.
Researchers assess each participant’s nutritional status and dietary problems, set personal goals, and propose dietary adjustments following the Dietary Guidelines for Chinese Residents (2022 Edition) (20). These adjustments include increasing the consumption of fruits, vegetables, whole grains, plant fats, and fish while reducing oil, salt, sugar, and alcohol consumption. The participants are asked to monitor their weight and record their daily nutritional profiles to track goal achievement. Researchers consider each participant’s BMI, health status, age, and eating habits and encourage personalized dietary interventions.

Medical monitoring intervention

This session mainly monitor hypertension, diabetes (characterized by hyperglycemia), and dyslipidemia (mainly manifested as elevated serum cholesterol or triglyceride levels). The first step is to measure blood pressure and glucose level every week, with hemoglobin A1c and blood lipid measurements conducted every three months, to identify individuals with hypertension, diabetes, and dyslipidemia and to determine whether blood pressure, hyperglycemia, and dyslipidemia coexist. General practitioners at community health service centers conduct medical monitoring. Then, overall cardiovascular risk is evaluated and stratified, and suitable targets for blood pressure, blood sugar, and/or lipid control are established. Finally, comprehensive health management is carried out for the following contents: (1) Recommending a non-hypertension diet or a Chinese heart-healthy diet; (2) Reducing sodium intake and limiting daily salt intake to 5 grams; (3) Increasing physical activity, reducing sedentary lifestyles such as prolonged sitting, and engaging in moderate-intensity physical activity for at least 150 minutes per week; (4) Controlling weight to achieve a BMI of <24 kg/m² and abdominal circumference <90 cm for males, <85 cm for females; (5) Encouraging smoking cessation, and avoiding passive smoking; (6) Restricting alcohol consumption; (7) Reducing mental stress and maintaining psychological balance; (8) Promoting healthy sleep, habits, aiming for 7-8 hours per day.

Follow-up and outcome measurements

The cognitive battery and primary outcome were selected to permit head-to-head comparisons with FINGER and MIND-CHINA. All participants meet with the study researchers at baseline and months 6, 12, 24, 48, and 84, and the study physician at screening and month 24 for general health evaluation. A psychologist assesses the cognitive status of each participant, and information on health status, socioeconomic factors, and lifestyle is gathered at baseline and 12 and 24 months. Details on outcome selection and definitions are presented in Section Table 2.

Table 2. Outcomes selection and definitions

Abbreviations: BMI body mass index, NIA-AA National Institute on Aging-Alzheimer’s Association workgroup, ADL ability of daily living, DNA DeoxyriboNucleic Acid, sMRI structural Magnetic Resonance Imaging, PSG polysomnography, QOL quality of life, rsEEG resting-state electroencephalogram, ERP event related potential

Quality control

The project has established unified quality standards, including the inclusion and exclusion of participants, data and biological sample collection, and primary and secondary outcome observations. Blood, urine, and fecal samples are uniformly coded, collected, processed, and stored according to quality control standards and procedures.
To enhance implementation, we have developed a versatile App called “East Brain Health Valle” that can be accessed on mobile phones, computers, and mobile PADs. This App detects motion variables such as walking speed and step count and records medical indicators such as respiration, heart rate, pulse, blood pressure, and fingertip oxygen saturation. These variables serve as vital signs for tracking the participant’s physical status. Additionally, the App recognizes facial and voice features and analyzes Tang poem learning and popular song-singing performances for intelligent diagnosis and multiple interventions. Experts can then provide recommendations based on the collected data and system analyses, including dietary components, nutritional profiles, and exercise levels. As 95% of our participants use smartphones, researchers could use the App to evaluate shifts in dietary patterns and monitor goal attainment, promoting positive dietary changes.

Statistical analyses

Baseline characteristics are described using frequencies and percentages for categorical variables and means and SD for continuous variables. Comparisons of demographic variables between the two groups are performed using Student’s t-test or the chi-square test. Linear regression models are used for cognitive outcome variables following a linear assumption. For cognitive function scores exhibiting skewed distributions, we apply a zero-skewness log transformation to the skewed components. Z-scores for the tests at each time point are standardized to the mean and SD at baseline. We employ mixed-effects regression models with maximum likelihood estimation to analyze changes in cognitive scores, considering factors of randomization group, time, and group × time interactions.
The primary efficacy analysis is based on a modified intention-to-treat (mITT) population, which includes all randomly assigned participants with at least one post-baseline observation. Secondary and sensitivity analyses are conducted using intention-to-treat analyses, including all randomly assigned participants, even those without post-baseline observations. Multiple imputations are conducted using the chained equations approach with 20 repetitions. Furthermore, analyses are conducted on a subset of randomly assigned participants who completed all cognitive evaluations. Finally, binary logistic regression analyses are performed, with the outcomes defined as cognitive decline, improvement, or no change between the assessments at baseline and 24 months.
We analyze the other secondary and exploratory outcomes shown in Table 2 in the mITT population using mixed-effects regression models with maximum likelihood estimation for all endpoints. For categorical variables, we calculate the changes in percentage units between baseline and 24 months using multinomial logistic models. All analyses are adjusted for age, sex, education level, study region, marital status, systolic blood pressure, total cholesterol level, and baseline BMI. A significance level of less than 5% is used for all analyses. R v3.2.5 software is used for all calculations.

Data management process

We coordinated a standard data dictionary capturing critical aspects of data collection. The data are collected and sent to CHINA-IN-MUDI without personal identifying information, using number-coded stickers that are unique to each visit. The link between the participant, visit, and code is maintained in the logistics system of CHINA-IN-MUDI. Data are analyzed (laboratory samples) or recorded (forms) and stored in an analysis database, where all changes can be tracked.



Study progress

Starting in July 2022 and as of September 1, 2022, 3,713 individuals from the China HEAD project were invited to participate in the CHINA-IN-MUDI screening examination. Among them, 1,965 participants (52.9%) were randomly assigned to either the intervention (n = 772) or the control group (n = 1,193). All four intervention domains were initiated according to the schedule for each wave of intervention groups, and this 2-year intervention period will end in 2025. Electronic data entry and processing are currently ongoing.
Both the intervention and control groups exhibited similar baseline characteristics (Table 3). The mean (SD) age in the intervention group was 69.88 (4.39) years, and their Mini-Mental State Examination (MMSE) score was 28.82 (1.53) points. Individuals in the intervention group had fewer years of education (10.70 ± 2.96) than those in the control group (11.39 ± 3.06). The control and the intervention groups showed slight differences in five specific cognitive domains: memory (Auditory Verbal Learning Test with long-delayed recognition, P = 0.045), language (30-item Boston Naming Test, P = 0.045), visuospatial functioning (Clock Drawing Task, P = 0.001), executive functions (Trail Making Test B, P = 0.027), and attention (Digit Span, P = 0.009). The CAIDE scores were similar between the two groups, with the intervention group scoring (4.89 ± 2.60) and the control group scoring (4.81 ± 2.47). Several vascular and lifestyle risk factors were present, indicating a potential window of opportunity for intervention. Approximately 25% of individuals reported engaging in smoking and alcohol consumption, with over half of the population suffering from hypertension and one-third experiencing hyperlipidemia. Nearly 30% of participants had a systolic blood pressure > 140 mmHg. Furthermore, the serum total cholesterol level was > 5.0 mmol/L in 42.9% of the participants, the high-density lipoprotein level was < 1 mmol/L in 9.1%, and the low-density lipoprotein level was > 3 mmol/L in 44.3%.

Table 3. Some initial characteristics based on the first 1965 randomized participants

Note: *Data are n, n/N (%), or mean (SD). †CAIDE, which was calculated based on sex, age, education, body-mass index, systolic blood pressure, total cholesterol, and level of physical activity, with a total score 0-15; AVLT, Auditory Verbal Learning Test.

Figure 3. Representative images of the “East Brain Health Valle” mobile application

(a) App homepage; (b) Health data monitoring page; (c) Popular song learning effectiveness scoring page; (d) Eight Section Brocade learning effectiveness scoring page.



It is estimated that AD patients worldwide will increase from 57.4 million in 2019 to 152.8 million by 2050 (21). More than 11 million family members and other unpaid caregivers provided an estimated 18 billion hours of care to people with Alzheimer’s or other dementias in 2022 (22). With the acceleration of population aging, the total number of Alzheimer’s disease patients in China will continue to grow (21). The costs of medical care, care costs, and progressive loss of ability to perform activities of daily living in patients with AD will impose a significant economic and human burden on families and society. Based on previous global initiatives to prevent dementia and promote brain health (4-6), it is suggested that multi-domain intervention may be feasible and effective for elderly high-risk population, however this needs to be supported by evidence from the Chinese population. The CHINA-IN-MUDI study, a multicenter, 2-year endeavor based on the Chinese HEAD project, was designed to identify interventions that can reduce the risk of cognitive decline and prevent or delay cognitive impairment in older individuals. The CHINA-IN-MUDI study, a multicenter, 2-year endeavor based on the Chinese HEAD project, was designed to identify interventions that can reduce the risk of cognitive decline and prevent or delay cognitive impairment in older individuals. The biggest breakthrough of this study is the formulation of an intervention program in line with China’s national conditions, encompassing living arrangements, physical exercise preferences, attitudes toward cognitive activities, and health education of the older population in cities. This project also established high-quality standards, including data collection, homogenization management, standardized follow-up procedures, quality control for biological samples, unified image interpretation, and event adjudication. Furthermore, it established several electronic data management platforms and biobank support structures.
We have compiled a summary of cognitive-related prevention trials conducted in China and major Chinese populations in the world (Table S1). For further clarification, we made comparisons between China HEAD, MIND-China and FINGER, as shown in Table 1. The current project design shares similarities with Finland’s earlier multi-domain intervention projects in terms of sample population selection (targeting community high-risk individuals), intervention duration (2 years), and intervention modalities (exercise, cognitive training, nutrition, and vascular risk monitoring) (4). However, there are some differences: the intervention frequency in this design is higher, with sessions conducted once a week. The evaluation approach is more comprehensive, incorporating multidimensional biological biomarkers, and the design involves a nationwide multicenter project with the largest number of participants in an intervention study to date.
This study had several advantages. First, based on preliminary research, intervention components widely enjoyed by Chinese seniors were selected. Although these activities have broad appeal, they have not yet been endorsed nationally, requiring sufficient scientific evidence to validate their effectiveness in increasing cognitive reserves, slowing cognitive decline, and establishing biological foundations. Second, whether finger exercises, the Eight Section Brocade, Twenty-Four Simplified Tai Chi, Jiamusi Happy Dance Fitness Routine, Tang poetry, or Chinese patriotic songs, each activity was easy to learn, aesthetically pleasing, and enjoyable. Moreover, these projects are easy to standardize as intervention modules. Third, due to the high acceptance of the chosen intervention components, implementing interventions once a week is highly feasible. Although older adults may not be interested in learning the dry theory or theoretical basis of a healthy lifestyle, this project links knowledge of dietary management, lifestyle management, and proactive health with quantifiable improvements in physical metrics such as blood pressure, blood sugar, lipid levels, and weight. This increased the feasibility of nutritional interventions and the intensive management of vascular risk factors. Importantly, the study seamlessly combines six modules, integrating dynamic and static elements, balancing intensity, combining learning with practice, and integrating lifestyle adjustments with medical examination results, thus pioneering a distinctive Chinese-style intervention approach. Fourth, the project incorporates a more comprehensive evaluation of intervention effects beyond cognitive outcomes, including improvements in physical abilities, such as daily life skills and exercise capabilities, lifestyle evaluations, lifestyle quality improvements, cardiovascular risk factors, health economics, and frailty, which are commonly observed in older adults.
Additionally, the project evaluates the knowledge, attitudes, and behavioral changes among participants in cognitive and physical training through assessments by on-site researchers and AI. Fifth, with significant funding support in the early stages of the project, it became feasible to objectively evaluate the effects of CHINA-IN-MUDI using various biomarkers, such as PET scans, proteomics, whole-genome sequencing, transcriptomics, and DNA methylation. This allows for the exploration of the underlying biological basis for these intervention effects. Lastly, considering the living arrangements and habits of Chinese seniors, organizing activities at the neighborhood level is the most suitable approach for promotion in China, given that urban residents have neighborhood-based senior activity centers and grassroots social management organizations within walking distance. Each neighborhood has a health service station typically staffed by a family doctor and a nurse, making neighborhood-level activities ideal for promoting interventions in China.
There are several limitations to address in this study. Firstly, our study population consists of participants from urban communities, which may lead to an underrepresentation of the entire Chinese population. It is important to acknowledge that participants from urban communities were more likely to have higher education levels, be more accepting of interventions, and possess better organizational skills. After exploring the strategy and verifying the results in urban areas, we will gradually carry out the adaptation and improved intervention in the rural areas of central China to wipe off this limitation. Secondly, our results might be biased by various factors, such as economy, geography, and educational level. Thirdly, the decreasing of vision and hearing, and the ability of coordination in some older adults may make using electronic devices difficult for them. In addition, uploading personal information to digital apps may cause concerns of misuse or disclosure of private data. The program has issued all this concerns and provided corresponding solutions. For example, the implementation of comprehensive training and education programs was facilitated by program committees to increase awareness and promote adoption, which may help to tackle this challenge. Moreover, we streamlined the operational procedures of the app to make it elderly friendly.



In conclusion, this report describes the CHINA-IN-MUDI study design based on a nationally representative multicenter cohort in China. Notably, China is home to a population of older people, and dementia cases account for over 25% of the world’s total. This study compares the strategies and tools used by two similar intervention programs in China and Finland.
This design underscores the implementation of CHINA-IN-MUDI within neighborhood settings through a series of Chinese programs. This project contributes to the evaluation of the effectiveness and safety of intervention strategies in delaying the rate of cognitive decline, controlling AD risk, and reducing clinical events, such as mild cognitive impairment and dementia, providing a basis for public health decision-making in China. Moreover, this study will also provide a way to validate and optimize intervention programs for large-scale populations.


Ethics approval and consent to participate: China Initiative for Multi-Domain Intervention (CHINA-IN-MUDI) (ChiCTR,; Registration number: ChiCTR2300075181) was approved by the ethics committee of the Wuhan University of Science and Technology (protocol code: 2023035), Wuhan, China. This study has been performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments. Written informed consents were obtained from all participants, or in the case of illiteracy and inability to write, from a proxy (usually a guardian or a family member), and were kept in the CHINA-IN-MUDI study administrative office.

Consent for publication: Not applicable.

Availability of data and materials: The datasets during the current study are not publicly available due to privacy and ethical restrictions but are available from the corresponding author on reasonable request.

Competing interests: The authors declare that they have no competing interests.

Funding: This study was supported by the Science and Technology Innovation 2030 Major Projects (2022ZD0211600) and the National Natural Science Foundation of China (82171491).

Author contribution: Clinical sites. 1. School of Medicine, Wuhan University of Science and Technology, PI: Yan Zeng (MD/ PhD), and Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Co-PI: Wei Tan (MD/ PhD). 2. Huashan Hospital, Shanghai Medical College, Fudan University, PI: Jin-Tai Yu (MD/ PhD). 3. Fujian Medical University Union Hospital, and Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, PI: Xiao-Chun Chen (MD/ PhD). 4. Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, PI: Long-Fei Jia (MD/ PhD). 5. Daping Hospital, Third Military Medical University, PI: Yan-Jiang Wang (MD/ PhD). YZ, GC, DL, WT, JY, XC, LJ, YW conceptualized and designed the study; SL, XX, FH, DZ, XB, YL, YZ, HC, MO, LX, ZW, JZ, JW, LH, YC, JZ, CL, JL, QN, DS, CC, GH, and XX acquired, analysed, or interpreted of data; XX conducted statistical analysis; SL, XX, and YZ drafted and critically revised the manuscript; CQ, FG, JG, and LM carried out the development of app. All authors read and approved the final manuscript.

Acknowledgements: We thank all participants for their willingness to participate in the study and the time they devoted to the study.





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