ObjectiveTo investigate the relationship between different types of cardiovascular disease and transitions in cognitive frailty states.MethodsData from the 2010—2014 Health and Retirement Study (HRS) in the United States and the 2011-2015 China Health and Retirement Longitudinal Study(CHARLS) were selected as data sources. A multi-state Markov model was employed to examine the impact of cardiovascular disease on cognitive frailty transitions.ResultsAmong patients with cardiovascular disease,the incidence rates of cognitive frailty,frailty,and cognitive impairment were 2.5%,8.6%,and 16.2%,respectively.A total of 5 990 state transitions were observed,of which deteriorations accounted for 60.2% and improvements accounted for 39.8%.Patients with multimorbid cardiovascular disease were more likely to transition from a normal state to physical frailty and were less likely to recover from deteriorated states compared to those with a single condition.Hypertensive patients demonstrated a higher likelihood of recovery from deteriorated states.ConclusionsThe relationships between different types of cardiovascular disease and transitions in cognitive frailty states vary.Healthcare providers should pay attention to state transitions in patients with different cardiovascular conditions and provide timely,personalized interventions and care.

Depressive symptoms in older adults compromise physical and mental health, burdening individuals, families, and society. Sleep duration, self-rated health (SRH), and frailty are critical correlates. Sleep shapes older adults’ health evaluation, and poor SRH elevates frailty risk. However, the interconnections among these four variables are rarely explored. Therefore, this study aimed to examine the serial mediating effect of SRH and frailty in the relationship between sleep duration and depressive symptoms in older adults. We performed a cross-sectional study utilizing nationally representative data from the 2018 wave of the China Health and Retirement Longitudinal Study (CHARLS), including 5,111 participants aged ≥ 60 years. The SPSS PROCESS macro (Model 6) and Bootstrap were used to examine the serial mediating effect, with subgroup analyses stratified by sleep duration (≤ 6, 6–7, 7–8, > 8 h). Sleep duration had a direct effect on depressive symptoms [B= -0.548, 95

Social activity in older adults is often correlated with their depressive symptoms, and this correlation is stronger in older adults with multimorbidity than in those without. However, few studies have analyzed this longitudinal association over time. This study aimed to examine the bidirectional longitudinal associations between social activity and depressive symptoms in older adults with multimorbidity. Additionally, we examined subjective life expectancy’s (SLE) moderating association in this bidirectional longitudinal association. Data were obtained from Waves 3 and 4 survey of 1435 older adults with multimorbidity (≥ 60 years) enrolled in the China Health and Retirement Longitudinal Study. We used cross-lagged panel models and grouped regression models to analyze the bidirectional longitudinal association between social activity and depressive symptoms, as well as the moderating association of subjective life expectancy, among Chinese older adults with multimorbidity. T1 social activity was significantly negatively associated with T2 depressive symptoms (β=-0.054, P < 0.050), and T1 depressive symptoms were significantly negatively associated with T2 social activity (β=-0.112, P < 0.010). SLE significantly moderated the association between T1 social activity and T2 depressive symptoms. Further, among participants with high SLE, the absolute value of the regression coefficient for the negative association of T1 social activity with T2 depressive symptoms (β=-0.134, P < 0.010) was larger than that for the association of T1 depressive symptoms with T2 social activity (β=-0.114, P < 0.050), indicating a more pronounced negative association for the former. All reported standardized coefficients were relatively modest; nevertheless, these statistically significant longitudinal associations are clinically and public health-relevant in this high-risk cohort of older adults with multimorbidity, who are disproportionately vulnerable to depressive symptom progression and social disengagement. Reciprocal longitudinal associations between social activity and depressive symptoms were observed among Chinese older adults with multimorbidity, with the negative longitudinal association from baseline depressive symptoms to subsequent social activity being larger in magnitude than the reverse association. Additionally, subjective life expectancy (SLE) showed a significant moderating effect on the association from baseline social activity to subsequent depressive symptoms.

Aim: With the intensification of population aging, the public health challenges posed by multimorbidity have become increasingly severe. This study employs bibliometric analysis to elucidate research hotspots and trends in the field of multimorbidity against the backdrop of global aging. The immediate aim is to systematically map the intellectual landscape and evolving patterns in multimorbidity research. The ultimate long-term aim is to provide a scientific basis for optimizing chronic disease prevention systems and guiding future research directions. Methods: The study adopted the descriptive research method and employed a bibliometric approach, analyzing 8129 publications related to multimorbidity from the Web of Science Core Collection. Using CiteSpace, we constructed and visualized several knowledge structures, including collaboration networks, keyword co-occurrence networks, burst detection maps, and co-citation networks within the multimorbidity research domain. Results: The analysis included 8129 articles from 2004 to 2024, published across 1042 journals, with contributions from 740 countries/regions, 33,931 institutions, and 40,788 authors. The five most frequently occurring keywords were prevalence, health, older adult, mortality, and risk. The top five contributing countries globally were the United States, the United Kingdom, Germany, China, and Spain. Five pivotal research trajectories delineate the intellectual architecture of this field: ① Evolution of Disease Cluster Management: Initial investigations (2013–2014) prioritized disease cluster coordination within general practice settings, particularly cardiovascular comorbidity management through primary care protocols and self-management strategies. ② Paradigm Shifts in Health Impact Assessment: Multimorbidity outcome research demonstrated sequential transitions—from physical disability evaluation (2013) to mental health consequences like depression (2016), culminating in current emphasis on holistic health indicators including frailty syndromes (2015–2019). ③ Expansion of Risk Factor Exploration: Analytical frameworks evolved from singular physical activity metrics (2014) toward comprehensive lifestyle-related determinants encompassing behavioral and environmental dimensions (2021). ④ Emergence of Polypharmacy Scholarship: Medication optimization studies emerged as a distinct research stream since 2016, addressing therapeutic complexities in multimorbidity management. ⑤ Frontier Investigations: Cutting-edge directions (2019–2021) feature cardiometabolic multimorbidity patterns and their dementia correlations, signaling novel interdisciplinary interfaces. Conclusions: The prevalence of multimorbidity is on the rise globally, particularly in older populations. Therefore, it is essential to prioritize the prevention of cardiometabolic conditions in older adults and to provide them with appropriate and effective health services, including disease risk monitoring and community-based chronic disease care.

Background: As the global population ages, there is an increasing prevalence of mild cognitive impairment and dementia. Protecting and preserving cognitive function in older adults has become a critical public health concern. Methods: This study utilized data from four phases of the Chinese Longitudinal Healthy Longevity Survey conducted from 2008 to 2018, encompassing a total of 2454 participants. Latent growth curve modeling was employed to analyze the trajectory and role of protein intake frequency and cognitive function. Results: The frequency of protein intake among older adults tends to rise, with individuals exhibiting higher initial levels experiencing smaller subsequent increases. Conversely, cognitive function generally declines, with those starting at higher levels experiencing more pronounced decreases. Notably, the initial frequency of protein intake is positively correlated with the initial level of cognitive function (β = 0.227, 95% CI: 0.156 to 0.299, p < 0.001), but does not significantly influence the rate of change in cognitive function (β = −0.030, 95% CI: −0.068 to 0.009, p = 0.128). The rate of change in protein intake frequency is positively associated with the rate of change in cognitive function (β = 0.152, 95% CI: 0.023 to 0.280, p = 0.020). Conclusions: The alterations in protein intake frequency are linked to alterations in cognitive function among older adults. Maintaining a stable high frequency of protein intake or increasing the frequency of protein intake may contribute to stabilizing cognitive function as well as reducing the risk of cognitive impairment and dementia in older adults.

BACKGROUND:Depression and cognitive impairment are prevalent mental health issues. Older adults in China exhibits a higher prevalence of multimorbidity, which is linked to an increased risk of depression and cognitive impairment. This study aims to investigate association between depressive symptoms and cognitive impairment in older adults with multimorbidity using network analysis, and to identify important bridge symptoms as potential intervention targets. METHOD:The study included 5729 individuals aged 60 years and above with multimorbidity, drawn from the China Health and Retirement Longitudinal Survey (CHARLS) dataset. Depressive symptoms and cognitive performance were assessed utilizing the CESD-10 (10-item Center for Epidemiologic Studies Depression) and MMSE (Mini Mental State Examination) scales, respectively. We constructed a network structure of depressive symptoms and cognitive performance, and calculated index of strength and bridge strength for each symptom. Furthermore, a comparative analysis of the network structure across gender and age groups were conducted. RESULTS:D3 (Felt depressed), C1 (Orientation), and D10 (Could not get going) were identified as the central symptoms of the depressive symptoms - cognitive performance network. C1 (Orientation), C5 (Linguistic skills), and D10 (Could not get going) were bridge symptoms connecting the two illnesses. Moreover, significant differences in edge weights were observed across gender and age groups. CONCLUSIONS:The central symptoms and bridge symptoms in the network may represent the most effective intervention pathway for addressing cognitive impairment and depression in older adults with multimorbidity. Clinical interventions should properly focus on gender and age differences in symptom presentation.

The global population ageing presents new challenges in older adult care. To elevate the quality of life of older adults, it is essential to explore their intrinsic capacity over time. Engaging in leisure activities may exert a positive impact, which is crucial for promoting healthy ageing. This study used longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS). Group-based trajectory modeling was applied to identify the trajectories of intrinsic capacity, and respondents were categorized accordingly. Leisure activities were assessed based on their intellectual and social components. The impact of social and intellectual activities on intrinsic capacity trajectories was analyzed through multinomial logistic regression, with odds ratios (OR) and 95

BACKGROUND:Improving the mental health and digital divide issues is crucial for promoting active aging. This study aimed to examine the bidirectional relationship and intricate mechanisms between social participation, social media use, and depressive symptoms among a nationwide sample of Chinese older adults. METHODS:We utilized data from two waves (2018, 2020) of the China Health and Retirement Longitudinal Survey, which included 4928 older adults aged 60 years and above. We Used a cross-lagged model to examine the bidirectional relationship between social participation, social media use, and depressive symptoms. RESULTS:In two years, social media use competency and social participation frequency can be predicted bidirectionally, and social media use competency and depressive symptoms can also be predicted bidirectionally. However, there is no cross-temporal bidirectional relationship between social participation frequency and depressive symptoms. Depressive symptoms can predict social participation frequency two years later, while social participation frequency cannot directly predict depressive symptoms. The mediation analysis indicated that social media use competency played a complete mediating role between social participation frequency and depressive symptoms. CONCLUSIONS:Continuous social participation may enhance social media use competency and alleviate depressive symptoms in older adults. Social media use may alleviate the decrease in social participation frequency and increase in depressive symptoms in older adults. Therefore, social media can be an effective tool to promote the integration of the older adults into society and alleviate negative emotions.

This study aims to examine the personality trait patterns of older adults, investigate the influence of personality traits on their mental health, and explore the mediating role of social support in the relationship among personality trait patterns, personality traits and mental health. This study utilized a cross-sectional design, with 4,197 participants from the psychology and behavior investigation of Chinese residents in 2022 (PBICR2022). Latent profile analysis (LPA) was conducted to identify distinct personality profiles, and multiple linear regression and mediation analyses were performed to examine the relationships among personality trait patterns, personality traits, social support, and mental health. The LPA identified four distinct personality profiles among older adults. Multiple linear regression revealed that Extraversion, Agreeableness, Conscientiousness, and Openness were positively associated with better mental health, whereas Neuroticism was negatively associated with mental health. Social support was found to partially mediate the effects of Extraversion, Agreeableness, Conscientiousness, Neuroticism, Agreeable-Conscientious Personality and Extraverted-Low Neuroticism Personality on mental health and to fully mediate the effect of Openness and Extraverted-Conscientious Personality. The study’s cross-sectional design limits the ability to draw causal inferences about the relationships among personality traits, social support, and mental health. Additionally, the reliance on self-reported measures may introduce bias. This study demonstrated that personality traits and social support are crucial determinants of mental health in older adults. Social support plays a significant mediating role, suggesting that interventions aimed at enhancing social networks could be particularly effective in improving mental health for older adults.

Background: Previous study has identified a connection between intimate partner violence (IPV) and depressive symptoms. However, the underlying mechanisms of this connection have not yet been well understood. The aim of this study was to investigate the roles of big five personality traits and perceived social support on the association between IPV and depressive symptoms among Chinese college students. Methods: A cross-sectional questionnaire survey was conducted among college students in 23 provinces, 5 autonomous regions, and 4 municipalities in China from June to August 2022. Intimate Partner Violence Questionnaire was used to measure the frequency of exposure to IPV. The big five personality traits were measured by 10-item Big Five Inventory, Perceptive Social Support Scale-3 items was used to estimate the degree of perceived social support and the data on depressive symptoms were collected by Patient Health Questionnaire-9 items. We used data from the "Psychology and Behavior Investigation of Chinese Residents in 2022", which includes 6686 valid questionnaires of college students. The PROCESS macro developed by Hayes was utilized to perform moderated mediation analysis. Results: Among college students, IPV had a significant direct impact on depressive symptoms. Extroversion, agreeableness, conscientiousness and neuroticism mediated the association between IPV and depressive symptoms (beta = -0.08, P < 0.001; beta = -0.08, P < 0.001; beta = -0.14, P < 0.001; beta = 0.20, P < 0.001). Perceived social support significantly moderated the mediating role of the big five personality traits between IPV and depressive symptoms. Furthermore, perceived social support moderated the direct relationship between IPV and depressive symptoms (beta = 0.34, P < 0.001), as well as the indirect path of extroversion, agreeableness, neuroticism and the first half of the mediating role of conscientiousness. Moreover, perceived social support was one of the preventive factors that could effectively mitigate the harmful effects of IPV, neuroticism and depressive symptoms. Limitations: As this was a cross-sectional study, we were unable to investigate causal relationships between variables. The prevalence of IPV and depressive symptoms were self-reported by the college students, and there may be reporting bias. Additionally, this study only explored the influence and mechanism from the integrated dimension of IPV and PSSS, due to spatial constraints. Conclusions: The findings contribute to the existing understanding by clarifying the fundamental mechanisms linking IPV and depressive symptoms. These results may serve as a valuable reference for the Chinese government to improve mental health among college students.

AimsTo investigate the independent and combined effects of physical activity (PA) and depressive symptoms on the risk of frailty in community-dwelling older adults.BackgroundOlder adults face a high risk of frailty which is commonly used to predict adverse health outcomes in older patients. Engaging in PA and without depressive symptoms are crucial factors to prevent frailty. It is essential to investigate the independent and combined effects of these two variables on the risk of frailty.MethodsWe included 3392 community-dwelling older adults. The FRAIL Scale was used to assess older adults' frail status (robust, prefrail and frail). Multiple logistic regression was utilized to examine the independent and combined effects of PA and depressive symptoms on the risk of prefrailty and frailty. The combined effects were visualized by marginal plots.ResultsThe prevalence of prefrailty and frailty in older adults were 42.16% and 10.58%. Compared with the group of "Light physical activity and With depressive symptoms", "Vigorous physical activity and Without depressive symptoms" had the lowest risk of prefrailty and frailty.ConclusionsOlder adults who do not engage in PA or have depressive symptoms increased the risk of frailty, but older adults with depressive symptoms could lower the risk of frailty through PA.Relevance to Clinical PracticeIt is effective to reduce the risk of frailty by directing older adults to do moderate physical activity, although they have depressive symptoms. The focus should also be on older adults with depressive symptoms, who have at least more than twice and fourfold risk of prefrailty and frailty compared to those without.ImpactThis study offers insights for future interventions aimed at preventing frailty in older adults.Reporting MethodThis study adhered to the STROBE checklist.Patient or Public ContributionsOlder adults participated in this study and completed questionnaires.

Socioeconomic status (SES) is associated with both depression and activities of daily living (ADL and IADL). However, the role of ADL as a biological mechanism in the relationship between SES and late-life depression, examined through longitudinal data, remains understudied. This study explored the longitudinal mediation effects of basic ADL or IADL on the SES-depression link in older adults. Data from the China Health and Retirement Longitudinal Study (N = 4104) were utilized. Mediation analysis was performed using parallel process latent growth curve modeling. The average age of participants was 57.76 years, and 55.7

Background In recent years, in the context of global aging, the number of patients with chronic diseases in China has increased significantly, and the the coexistence of multiple diseases has become more and more common, which seriously threatens the life safety and quality of life of the older adults in China. Objective To investigate the status of multimorbidity of older adults, and explore the relationship and pathways of action between sleep, physical activity, social network and multimorbidity of older adults, providing ideas for the effective prevention of multimorbidity and health improvement of older adults. Methods Elderly people aged≥60 years in the Community Health and Behavior of the Elderly Panel Study (CHBEPS) established by our team in 2021 were selected as the subjects of the survey, a questionnaire was used to investigate the study population, the research objects were investigated by questionnaire, and the general situation was collected by self-designed basic information collection form, IPAQ-S-C, LSNS-6 and PSQI were used to assess the physical activity, social network and sleep of the subjects. AMOS 28.0 statistical software was used to set up the structural equation model. Results A total of 3 392 valid questionnaires were collected from 3 531 people over 60 years old, with an effective recovery rate of 96.06%. The average score of physical activity was 2 426.42 (495.00, 3 060.00) MET-min/w, the average score of social network was (15.91±6.43), and the average score of sleep was (5.49±3.53). There were 788 (23.23%) older adults with insufficient social network and 353 (10.41%) older adults with fair or very poor sleep quality. The prevalence of multimorbidity among the survey respondents was 41.13% (1 395/3 392). The results of correlation analysis showed that social network was negatively correlated with sleep level (rs=-0.113, P<0.01) and multimorbidity (rs=-0.049, P<0.01), and was positively correlated with physical activity (rs=0.073, P<0.01). Multivariate Logistic regression analysis showed that physical activity of 0-600 MET-min/w (OR=0.576, 95%CI=0.342-0.970) and good sleep quality (OR=0.409, 95%CI=0.209-0.803) were protective factors for multimorbidity (P<0.05). The results of structural equation modeling showed that social networks could affect physical activity and sleep quality (standardized path coefficient=0.096, t=4.982, P<0.001; standardized path coefficient=-0.043, t=-5.981, P<0.001), physical activity and sleep quality could affect multimorbidity (standardized path coefficient=0.023, t=5.280, P<0.001; standardized path coefficient=0.111, t=9.409, P<0.001). Social network had no direct effect on multimorbidity, but an indirect effect on it through two mediators of physical activity and sleep. The indirect effect of social network on multimorbidity through physical activity accounted for 10% of the total effect, and the indirect effect of social network on multimorbidity through sleep accounted for 36.5% of the total effect. Conclusion The prevalence of multimorbidity is high in the older adults (41.13%). The social network of the elderly group should be appropriately expanded to encourage them to maintain a moderate amount of physical activity and a good quality of sleep, alleviate and prevent the occurrence of multimorbidity.

Multimorbidity has become an important characteristic of chronic diseases,jeopardizing the health of middle-aged and older adults,and posing new challenges to health management of chronic disease.There is a lack of guidelines and intervention programs for multimorbidity in China.In this study,we initially formulated a health management service pathway for multimorbidity among middle-aged and older adults in the community through the literature research method and focus group discussion method.Then,the constructed service pathway was evaluated and revised through the expert consultation method.Finally,a health management service pathway for the multimorbidity of middle-aged and older adults in the community with behavioral change techniques as the core.The pathway optimizes the implementation of multimorbidity health management,and standardizes its health monitoring,assessment and intervention process,providing a theoretical and practical guidance for primary care providers in the health management of multimorbidity.

Background The severe trend of the aging population,the rapid increase in the prevalence of chronic diseases among older adults,and the greater prominence of multimorbidity have posed challenges to the prevention and treatment of chronic diseases in China.Adverse health-related behaviors are modifiable risk factors for chronic diseases.Exploring the latent classes of health-related behaviors in older adults with multimorbidity and their associations with quality of life will help identify the characteristics of their health-related behaviors and uncover risk behaviors affecting the quality of life,providing references for precise health management to improve the quality of life of older adults.Objective To explore the latent classes of health-related behaviors in older adults with multimorbidity and the differences in the quality of life among the different classes.Methods Based on the baseline data from the Community Health and Behavior of the Elderly Panel Study(CHBEPS)conducted by our team in 2021,a total of 1 395 older adults aged 60 years and above with multimorbidity were included as study participants.A self-designed questionnaire was used to collect basic information,including disease status,smoking status,alcohol consumption,and dietary preferences of the participants.The Pittsburgh Sleep Quality Index(PSQI),International Physical Activity Questionnaire-Short-Chinese Version(IPAQ-S-C),and Lubben Social Network Scale-6(LSNS-6)were used to assess staying up late,physical activity,and social network of the participants,respectively.The EuroQol five-dimensional five-level questionnaire(EQ-5D-5L)was used to measure the quality of life of the participants.Latent class analysis of health-related behaviors among older adults with multimorbidity was conducted using Mplus 8.3 software.Based on the fitted model,the different latent classes of health-related behaviors among older adults with multimorbidity were used as groups,and the Kruskal-Wallis and Wilcoxon rank-sum tests were performed using SPSS 26.0 software to analyze the differences in quality of life among these groups.Results Four latent classes of health-related behaviors were identified among older adults with multimorbidity,which are named the health behavior group(n=280),risk behavior group(n=366),comprehensive behavior group(n=173),and adverse behavior group(n=576).There were statistically significant differences in quality of life among the four latent classes(P<0.05).Specifically,the quality of life in the health behavior group was higher than that in the risk behavior group and adverse behavior group(P<0.05).Conclusion When implementing precise health management for older adults with multimorbidity,the characteristics of their health-related behaviors should be taken into account.Special attention should be given to those with a higher probability of behaviors such as smoking,alcohol consumption,and a preference for sweet,spicy,and salty tastes,as well as those with a lower probability of behaviors such as a balanced diet,regular consumption of vegetables and fruits,and social networks.Additionally,measures targeted at addressing common issues such as insufficient physical activity should be implemented to improve the effectiveness of health management and the quality of life of older adults with multimorbidity.

BackgroundThe aim of this research is to explore the interrelationships between different psychological issues and the potential role of eating behavior and physical activity among nursing students.MethodsUndergraduate nursing students (n = 892) from some medical universities in China were recruited through convenience and snowball sampling methods using online platforms. Participants completed measures on demographics, fear of negative evaluation (FNE), social avoidance and distress (SAD), psychological distress (DASS), disordered eating behavior (TFEQ) and physical activity. The relationship models among the aforementioned variables were established using Process 3.5.ResultsA total of 290 males and 602 females were included in this study. The average FNE score of students was (39.44 +/- 8.78), SAD was (13.83 +/- 7.06), DASS was (22.45 +/- 20.47), and TFEQ was (56.09 +/- 12.57), respectively. TFEQ and SAD independently and jointly acted as mediators in the relationship between FNE and DASS. Physical activity played a moderating role, with the interaction effect between FNE and groups Q2, Q3, and Q4 determined to be 0.407 (95%CI 0.136 to 0.678), 0.328 (95%CI 0.061 to 0.596) and 0.332 (95%CI 0.073 to 0.591), respectively.ConclusionsThis study supports that disordered eating behaviors have a negative impact on mechanisms of psychological changes, and enhancing physical activity is an effective prevention strategy for psychological distress and disordered eating behaviors among nursing students.

The health status of secondary school students has received widespread attention, and family plays an extremely important role in protecting and promoting their health. However, the relationship between family health and suboptimal health status (SHS) among secondary school students and its underlying mechanisms are unclear. This study aims to understand the prevalence of SHS among Chinese secondary school students and analyze the relationship between family health and SHS, and examine the mediating roles of perceived stress and problematic internet use. The 2,094 secondary school students (52.6

Background Currently,research on the factors influencing the health status of older adults with multimorbidity in China is scattered,and it is difficult to give a comprehensive consideration from a holistic perspective,and the contribution of factors leading to health disparities is not explored,resulting in the ineffectiveness of current health management often programs in older adults with multimorbidity.Objective By introducing a health bifactor model,this study aims to understand the endogenous and exogenous influencing factors and their contributions to the health of older adults with multimorbidity and provide a practical basis for developing precise health management plans for older adults with multimorbidity.Methods In this study,using the China Health and Retirement Longitudinal Survey(CHARLS)2018 data and introducing the two-factor model of health developed from the Grossman health production function(including both endogenous and exogenous aspects of health determinants).First,the Wilcoxon rank sum test was used to analyze whether there were differences in the health status of older adults with multimorbidity by gender.Secondly,the OLS regression model was used to analyze the mechanism of the two-factor model of health on the health of older adults with multimorbidity.Finally,the Shapley value method was further used to decompose the contribution of health endogenous factors to their health.Results The study found that factors such as still drinking alcohol,having no disease control methods,being satisfied with medical services,having a high level of education,having a pension,not using health services,attending free health checks,caring for grandchildren and being satisfied with their children's relationship were more likely to improve the health of older people with multiple chronic conditions.The results of the Shapley decomposition showed that socioeconomic status was the most important factor in the full sample,while family health support,health-related behaviors,and health-related behaviors were the most important factors.Coping strategies was the next most important,and social health resources was the least influential.In the gender subgroup analysis,socioeconomic status remained the most important factor;for older men with multiple chronic illnesses,health-related behaviors were the next most important factor;for older women with multiple chronic illnesses,coping strategies were the next most important.Conclusion The health status of older men with multimorbidity is better than that of women,socioeconomic status is the most important factor affecting the health of older adults with multimorbidity,and the remaining four dimensions have different contributions to the health differences between men and women.It is recommended that precise health management should be implemented according to the size of the contribution of each dimension of different health endogenous factors to improve the health status of older adults with multimorbidity with maximum benefit.

Objectives The aim of this study is to establish a self-simple-to-use nomogram to predict the risk of multimorbidity among middle-aged and older adults.Design A retrospective cohort study.Participants We used data from the Chinese Longitudinal Healthy Longevity Survey, including 7735 samples.Main outcome measures Samples’ demographic characteristics, modifiable lifestyles and depression were collected. Cox proportional hazard models and nomogram model were used to estimate the risk factors of multimorbidity.Results A total of 3576 (46.2%) participants have multimorbidity. The result showed that age, female (HR 0.80, 95% CI 0.72 to 0.89), chronic disease (HR 2.59, 95% CI 2.38 to 2.82), sleep time (HR 0.78, 95% CI 0.72 to 0.85), regular physical activity (HR 0.88, 95% CI 0.81 to 0.95), drinking (HR 1.27 95% CI 1.16 to 1.39), smoking (HR 1.40, 95% CI 1.26 to 1.53), body mass index (HR 1.04, 95% CI 1.03 to 1.05) and depression (HR 1.02, 95% CI 1.01 to 1.03) were associated with multimorbidity. The C-index of nomogram models for derivation and validation sets were 0.70 (95% CI 0.69 to 0.71, p=0.006) and 0.71 (95% CI 0.70 to 0.73, p=0.008), respectively.Conclusions We have crafted a user-friendly nomogram model for predicting multimorbidity risk among middle-aged and older adults. This model integrates readily available and routinely assessed risk factors, enabling the early identification of high-risk individuals and offering tailored preventive and intervention strategies.

Background Multimorbidity have become a major character in the course of chronic diseases that brings a challenge for public health development in China. The development of multimorbidity research in China is in an early stage with fewer literature,and there is a lack of systematic and comprehensive literature analysis. Objective To conduct a bibliometric and visual analysis of research hotspots and evolutionary trends in the field of multimorbidity in China,grasp the research frontiers and development directions in the field,thereby providing a reference for future research directions. Methods CNKI（Chinese data source）and WOS（foreign data source） were searched for the literature in the field of multimorbidity researches published by Chinese researchers from 2002 to 2022. CiteSpace software was used to analyze the spatial and temporal distribution of multimorbidity and explore the research hotspots and evolutionary trends in the field of multimorbidity by plotting the collaboration network map of institutions and co-occurrence map of keywords for researches in the field of multimorbidity published by Chinese researchers. Results The number of published literatures in the field of multimorbidity showed an increasing trend from 2002 to 2022. The top 5 Chinese keywords were “comorbidity（342 times）”“older adults（161 times）”“depression（155times）”“chronic diseases（106 times）”“diabetes（94 times）”;and the top 5 English keywords were “prevalence（126 times）”“older adults（92 times）”“multimorbidity（91 times）”“health（75 times）” “disease（71 times）”. There were 4 development stages in the research development history of multimorbidity:the initial stage of research,the researchers focused on the comorbidity characteristics but did not define it in a uniform way;the second stage of research,the researchers focused on comorbidity and chronic disease in older adults,discovered the high prevalence of multimorbidity in the elderly population;the third stage of research,the domestic researches on multimorbidity developed rapidly,involving influencing factors,comorbidity patterns,polypharmacy,quality of life and debilitation;the fourth stage of research,the definition of multimorbidity is becoming clearer,showing a trend of research diversification. Conclusion Researches in the field of multimorbidity is becoming increasingly diversified. Researchers should focus on the prevention and treatment of complex multimorbidity,and construct health management strategies and community intervention programs for multimorbidity population in China.