Social support as a mediator between social frailty and anxiety and depression in old patients with chronic heart failure: a cross-sectional study

Social support as a mediator between social frailty and anxiety and depression in old patients with chronic heart failure: a cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Social support as a mediator between social frailty and anxiety and depression in old patients with chronic heart failure: a cross-sectional study Junting Huang, Xiaobo Liu, Duolao Wang, Xiaorong Luan, Wanxia Yao, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6805502/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aim This study investigated the relationship between social frailty, anxiety and depression in old Chronic heart failure (CHF) patients. We paid particular attention to how social support moderated this relationship. Background Old patients with chronic heart failure have severe somatic symptoms, which lead to high levels of social frailty. Understanding the demographic and disease factors, as well as the relationship between social frailty, social support, anxiety and depression, is essential to improve health outcomes in old CHF patients. Methodology A cross-sectional study was conducted on 394 old CHF patients from three tertiary hospitals in China. The study questionnaire included a general information questionnaire, the HALFT scale (social frailty), The MSPSS (social support), and The HADS (anxiety and depression). Hierarchical regression analysis was used to assess the influencing factors of anxiety and depression; the SPSS PROCESS Marco Plug-in was used to conduct mediation analysis. Results The results showed that age, the number of hospitalization and NYHA classification were the influencing factors of anxiety and depression. Social frailty, social support, and anxiety and depression were related, and social support partially mediated the relationship between social frailty and anxiety and depression, with the mediating effect sizes of 13.67% and 10.15%, respectively. Conclusion Our study shows that high levels of social frailty are associated with increased anxiety and depression in old CHF patients. Social support helps to alleviate the adverse effects of social frailty (e.g. lack of social participation and social connections, feelings of loneliness, financial insufficiency) on anxiety and depression. In addition to focusing on patients’ somatic symptoms and treatments, physicians and nurses should also pay attention to the impact of psychosocial factors on the adverse health outcomes of CHF patients, increase the social support system for old adults, and improve patients’ treatment compliance and health outcomes. Reporting Method : The Strengthening Reporting of Observational Studies in Epidemiology (STROBE) guidelines were followed in the study. No Patient or Public Contribution: Recruitment for old CHF patients met the inclusion criteria. Chronic heart failure old adults social frailty anxiety depression social support Figures Figure 1 Figure 2 What does this paper contribute to the wider global clinical community? The mental health of old CHF patients has become a public concern worldwide. We collected data on three hundred ninety-four CHF patients from three tertiary hospitals in Northeast, Northwest, and South China to provide evidence for exploring the factors affecting physical and mental health. This study extends the mediating role of social support between social frailty and, anxiety and depression. This shows that psychosocial factors such as social networks and social participation, as well as feelings of loneliness, are essential factors in improving adverse health outcomes in old CHF patients. The mediating model suggests that a comprehensive body-mind-society intervention may be more effective in reducing anxiety and depression symptoms in CHF patients and improving their treatment compliance. Therefore, we propose the following recommendations: (1) With the development of the 'new elderly care model' in China, traditional 'filial piety' has been redefined. Increasing social support systems such as social networks can help improve older people's physical and mental health. (2) CHF is a chronic disease with both bodily and psychological disorders. Dual-heart treatment not only alleviates the physical symptoms and complications, such as activity limitations of old patients but is also an important measure to improve their mental health. (3) Further improve hospital-community-family integrated medical and nursing services and implement 'medical insurance for minor and major illnesses' for old adults in rural areas. Introduction The 2024 AHA/ACC/HFSA Heart Failure Guidelines state that heart failure places a substantial financial burden on patients' families and society(Hollenberg et al., 2024). Chronic heart failure (CHF) is a debilitating disease and is characterized by high prevalence, morbidity, and readmission rates. In China, the incidence of CHF among 60-69 and 70-79-year-olds is 23.5% and 30.8%, respectively(Jiurui Wang et al., 2023). Depression and anxiety disorders are prevalent in patients with CHF. A meta-analysis of 36 studies found that 21.5%-90% and above 50% of CHF patients exhibited clinically significant depression and anxiety symptoms(Celano et al., 2018). Studies have shown that there is an interaction between social frailty and depression in older people(Hayashi et al., 2022; Qi & Li, 2022). In addition, anxiety and depression are independent risk factors for social frailty in older adults. Social frailty is highly prevalent among patients hospitalized for heart failure and aged ≥65 years, accounting for approximately 66.5%(Jujo et al., 2021). However, there are no studies to explore whether SF is a risk factor for anxiety and depression and its function mechanism in old CHF patients. Anxiety and depression (AD) are common in old CHF patients. Studies reported that anxiety and depression can lead to loss of quality and adverse cardiovascular outcomes(Rashid et al., 2023; Veskovic et al., 2023). The discomfort experienced by old CHF patients interacts with their psychiatric conditions, which is associated with their functional impairment and limitation of social participation. Studies have shown that depressive symptoms lead to a twofold increase in the risk of death or cardiac events in old adults(Li et al.; Settergren et al., 2024; Tsabedze et al., 2021). Once anxiety and depression occur in CHF patients, the hormone levels in the body will rise further, as will sympathetically nerve excitability, further increasing myocardial load and myocardial oxygen consumption, thereby adversely affecting the heart and blood pressure. Social frailty (SF) is an individual's persistent risk of losing the resources, activities, and abilities needed to meet their basic social needs(Qi et al., 2023). Existing studies indicated that more than half of old CHF inpatients have two or more sub-types of frailty, and two-thirds of them have SF(Jujo et al., 2021). These patients often have low disease self-management capabilities and inadequate external care support, which increases the risk of adverse health outcomes. Many reports have pointed out that patients with severe depressive moods are more likely to experience SF, and the two mutually reinforce a vicious cycle(Hayashi et al., 2022; Liu et al., 2024). Patients with severe depression and anxiety often feel fatigue, loss of appetite and interest in hobbies, and lack of initiative to communicate with others. Social support (SS) refers to all support other than one's own, including multiple fields, i.e., providing spiritual and material resources(Chamberlain, 2017). SS mainly comes from medical staff, relatives, and friends of old CHF patients. Medical staff's SS is beneficial for forming a good doctor-nurse-patient relationship, and the care and love given by relatives and friends is also the vital essence of social support systems. Reports showed SS is a protective factor in old adults coping with negative emotions and adverse health outcomes in the face of stressful events(Chu et al., 2023; Wang et al., 2022). We applied the stress process model (SPM) to guide the selection of key factors influencing anxiety and depression in old CHF patients(J. Wang et al., 2023). SPM indicates that the stress process includes four elements: stressor (SF), mediator (SS), stress response (anxiety and depression), and outcome (health outcomes). SF is a stressor that stimulates the internal and external environment of the body and causes a stress response. Old CHF patients often were accompanied by clinical symptoms, i.e., dyspnoea, chest tightness, shortness of breath, etc., leading to loss of social participation due to a lack of health promotion behaviours and social interactions predisposing them to psychosomatic diseases, i.e., anxiety and depression. As a complex structural system, SS can alleviate the adverse effects of stressful events influencing cognition, behaviour, and psychological status. Therefore, we propose the following hypotheses in CHF patients based on SPM. Hypothesis 1: SF is an independent risk factor for anxiety and depression. Hypothesis 2: SF, SS, anxiety, and depression are correlated. Hypothesis 3: SS mediates between SF and anxiety and depression. Figure 1 shows the the mediator models. Figure 1.1 shows the mediator model of social support between social frailty and anxiety. And figure 1.2 shows the mediator model of social support between social frailty and depression. Methods Study participants This study is cross-sectional research from October 2022 to June 2023 using convenient sampling of old CHF patients. Participants were admitted to the Cardiology Departments of three tertiary Grade A hospitals in Shandong Province (northeast), Shaanxi Province (northwest), and Guizhou Province (south) in China. Inclusion criteria included a diagnosis of CHF according to heart failure guidelines; age 60 years and above; no severe hearing or visual impairments; no neurological diseases (e.g., dementia, stroke, epilepsy, etc.); no severe psychiatry disorders (e.g., schizophrenia, bipolar disorder, etc.); no other advanced diseases (e.g., leukaemia, breast cancer, etc.); fluency in speaking, listening, reading, and writing; and voluntary participation in the study. A rough sample size estimation method was used, which requires the sample size to be 10-20 times that of the study variables. This study included 14 variables, and the sample size should be 140-280 participants. The sample size was increased by 20% to 168-336 participants considering invalid questionnaires. Three hundred ninety-four CHF patients were invited to complete questionnaires; Figure 2 shows the flowchart process of participant recruitment. This study strictly abides by the Declaration of Helsinki and has been approved by the School of Nursing and Rehabilitation Ethics Review Committee of Shandong University (Approval No.: 2023-R-004; Approval Date: 3 February 2023)(Association, 2024). Questionnaires were collected using face-to-face interviews by a trained researcher. Interview and questionnaire completion took approximately 20-25 minutes. Before completing the questionnaires, all participants signed an informed consent form and were told they had the right to withdraw from the study without affecting subsequent treatment. All data were processed anonymously and destroyed after the end of the study. Measurements Independent variable = SF SF was assessed using the HALFT scale (Help, Participation, Loneliness, Financial, and Talk, HALFT)(Ma et al., 2018). The HALFT scale consists of five items and five dimensions: being unable to help others, limited social participation, loneliness, financial difficulties, and having no one to talk to. Five items: Item 1: Have you helped friends or family this past year? Item 2: Have you participated in social or leisure activities in the past year? Item 3: Have you felt lonely in the past week? Item 4: Was your income last year sufficient to cover your living expenses for one year? Item 5: Do you have someone to talk to every day? One point is calculated for 'no' answers to items 1, 2, 4, and 5, but for 'yes' answers to item 3. The total scores of the HALFT scale ranged from 0 to 5 points; the higher the scores were, the higher the SF level was. The Cronbach's alpha coefficient of the HALFT scale is 0.736. Mediator = SS SS was assessed by The MSPSS (Multidimensional Scale of Perceived Social Support MSPSS)(Zimet et al., 1990). The MSPSS includes 12 items and three dimensions: family (4 items), friends (4 items), and significant others (4 items). Each item was rated on a seven-point scale from 1 ('strongly disagree') to 7 ('strongly agree'). The minimum and maximum scores were 12 and 84, respectively, with higher scores indicating better social support. The Cronbach's alpha coefficient of the Chinese version of the MSPSS is 0.906(Yang et al., 2024). Dependent variables = AD AD was assessed by The HADS (Hospital Anxiety and Depression Scale, HADS)(Zigmond & Snaith, 1983). The HADS consists of 14 items with two dimensions: HADS-anxiety (HADS-A) and HADS-depression (HADS-D). The HADS-A and HADS-D both include seven items. Each item is scored on a four-point Likert scale, with 3 representing the most negative response and 0 the most positive. The total scores of HAD-A ranged from 0 to 21 points, as well as HADS-D. The higher the score, the more severe the anxiety symptoms and depression symptoms. The Cronbach's alpha coefficients of the Chinese version of the HADS-A and HADS-D are 0.753 and 0.764, respectively(Yang et al., 2014). Covariates Covariates included age, gender, marital status, residence, education level, living conditions, monthly household income, number of hospitalizations, the NYHA (New York Heart Association, NYHA) classes, and number of chronic diseases. The coding of the category variables is as follows: gender (1=female, 2=male), marital status (1=married, 2=divorced/widowed/single), education level (1=primary school or illiterate, 2=secondary school, 3=college or above), residence (1=rural, 2=urban), living conditions (1=living alone, 2=living with others), monthly household income (1=less than 1,000 yuan, 2=1,000 yuan to 2,999 yuan, 3=3,000 yuan to 5,999 yuan, 4=6,000 yuan or above), NYHA classes (1=Class I, 2=Class II, 3=Class III, 4=Class IV), number of chronic diseases (1=none or one, 2=two or more). Statistical analysis IBM SPSS Statistics Version 26.0 (IBM, Armonk, NY, USA) was applied for data analysis. Category variables are described as frequencies and percentages. Numerical variables are expressed as means (M) and standard deviations (SD). Considering the lack of normal distribution of some variables based on skewness-kurtosis tests, Spearman correlation analysis opted to explore the relationships of variables. An independent sample t-test and ANOVA were used to perform a single-factor analysis of AD. The multiple stepwise regression analysis was used for multiple-factor analysis of AD. The variance inflation factor (VIF) is less than 5, so there is no multicollinearity. In the regression analysis, covariates were added to Model 1, SF to Model 2, and SS to Model 3. Mediation effects were tested using the SPSS PROCESS Macro Plug-in Model 4 developed by Preacher and Hayes(Hayes, 2009, 2017). SF was set as X, SS was set as M, anxiety was set as Y1, and depression was set as Y2. This model's indirect effect is through the Mediator (M). If M is not present, the direct effect of X on Y is c'. The total effect of X on Y (c) is the direct effect + indirect effects: c = c' + ab. All covariates were controlled in the mediation model. A bootstrap 95% confidence interval (CI) based on 5000 samples was applied to assess the significance of direct and indirect effects. Bootstrap results were considered significant if the 95% CI did not contain zeros. Results Participants’ characteristics Four hundred twenty questionnaires were distributed for this study, of which 15 were lost and 11 were invalid. Three hundred ninety-four valid questionnaires were returned for a valid response rate of 93.81%. Table 1 shows comparison of differences between anxiety and depression in demographic and disease-related data. The mean age of the participants was 69.06 years (SD=6.578), and the majority were female (64.2%). Approximately 11.9% of the participants were divorced, widowed, or single; 59.9% had an education level of primary school or below; 347 people were cohabiting with others, 42 were living alone; 149 people had two or more chronic diseases; 203 people were living in rural areas; the mean of the number of hospitalizations was 1.97 (SD=1.641); and 332 people had a monthly household income of less than 6,000 yuan. There were 80, 119, 114, and 81 people with NYHA classes I-IV, respectively. Single-factor analysis of AD Independent sample t-test showed that marital status (t=-1.965, p=0.05) is an influencing factor of AD. ANOVA results showed that NYHA classes (F=14.931, p<0.001) influence AD. Spearman correlation analysis showed that age (r=0.259, p<0.01) and number of hospitalizations (r=0.2, p<0.01) are influencing factors of AD. Table 1 shows comparison of differences between anxiety and depression in demographic and disease-related data. Correlation of SF, SS, and AD The mean of SF is 2.26(SD=1.38), the mean of SS is 54.02(SD=14.476), the mean of anxiety is 8.25(SD=3.389), the mean of depression is 8.5(SD=3.345). Spearman correlation analysis indicated SF (r=.320, p<0.01) and SS (r=.290, p<0.01) were negatively correlated with anxiety. It also revealed that SF (r=.388, p<0.01) and SS (r=-.257, p<0.01) were negatively correlated with depression. Table 2 shows correlation analysis of social frailty, social support, anxiety and depression. Multiple-factor analysis of Anxiety The multiple stepwise regression analysis results showed in model 1, R2 is 0.145, indicating that age, the number of hospitalizations, and NYHA classes can predict anxiety, with an explanation of 14.5%. In model 2, R2 is 0.206, indicating that SF can significantly expect anxiety, with a net explanation of 6.1%. In model 3, R2 is 0.263, indicating that SS can predict anxiety, with a net explanation of 5.7%. The main effect of SF on anxiety is significantly reduced, suggesting that SS may mediate between SF and anxiety. Table 3 shows regression analysis of anxiety and depression. Multiple-factor Analysis of Depression The multiple stepwise regression analysis results showed in model 1, R2 is 0.147, indicating that age and NYHA classification can predict depression, with an explanation of 14.7%. In model 2, R2 is 0.198, indicating that SF can significantly predict depression, with a net explanation of 5.1%. In model 3, R2 is 0.279, indicating that SS can expect depression, with a net explanation of 8.1%. The main effect of SF on depression is significantly reduced, suggesting that SS may have a mediating impact between SF and depression. Table 3 shows regression analysis of anxiety and depression. Mediation analysis of SS between SF and anxiety The bootstrap results indicated that the path coefficient of SF on SS (path a1) was -2.2169 (95% CI: -3.2600, -1.1739), and the path coefficient of SS on anxiety (path b1) was -0.0538 (95% CI: -.0750, -.0326). The total effect (path c1) and direct effect (path c1') of SF on anxiety were .9910 (95% CI: .7617, 1.2204) and .8718 (95% CI: .6443, 1.0994), respectively. The indirect effect of SF on anxiety (path a1*b1) is .1192 (95% CI: .0500,.2074). The indirect impact of SS is 13.67%, calculated by (path a1*b1)/ (path c1'), and is a partial mediation. Table 4 shows mediating analysis of social frailty, social support, and anxiety and depression. Mediation analysis of SS between SF and depression The bootstrap results indicated that the path coefficient of SF on SS (path a2) was -2.2169 (95% CI: -3.2600, -1.1739), and the path coefficient of SS on depression (path b2) was -.0452 (95%CI:-.0658, -.0245), and the total effect (path c2) and direct effect (path c2') of SF on depression were 1.0860 (95%CI:.8646,1.3075) and .9859 (95%CI:.7 644, 1.2073). The indirect impact of SF on depression (path a2*b2) was .1001 (95% CI: .0369,.1847). The mediating effect of SS was calculated as (path a2*b2)/ (path c2') and was 10.15%, which was a partial mediation. Table 4 shows mediating analysis of social frailty, social support, and anxiety and depression. Discussion The study examined the association between SF and AD in old Chinese patients with CHF. We also explored the effects of demographic and disease factors and SS on AD. In addition, we verified the mediating roles of SS between SF and AD. Our findings confirm that SF directly affects AD and indirectly through SS or AD, which suggests that reducing SF is crucial in enhancing AD in old CHF patients. We found that age, number of hospitalizations and NYHA classes are vital factors affecting AD in old CHF patients. Age is positively correlated with AD in old CHF patients, meaning that the older the patient, the higher the likelihood of developing AD symptoms. The hypothesis that serotonin deficiency leads to short (S) or long (L) alleles is one of the earliest hypotheses for the cause of depression(Cui et al., 2024; Szymkowicz et al., 2023). A study of the old population in South Korea found that when exposed to stressful life events (e.g., CHF or other cardiovascular diseases), carriers of the S allele showed a higher risk of late-life depression (LLD)(Song et al., 2019). This study found a positive correlation between the number of hospitalizations and the AD level in elderly CHF patients; that is, the AD level increased with the number of hospitalizations. Studies have shown that frequent hospital admissions improve the psychological burden on patients and their families and increase their financial burden(Guo et al., 2019; Huang et al., 2020). In addition, during hospitalization, patients need to receive various treatments and take medications such as anti-heart failure drugs, which are all predisposing factors for AD. In this study, the higher the NYHA classification level, the higher the anxiety and depression scores in old CHF patients, which is consistent with the findings of Yin’s study (Yin et al., 2019) . Studies pointed out that for patients with cardiovascular disease, the milder the coronary artery stenosis, the more severe the anxiety and depression symptoms (Bai et al., 2021; Das et al., 2022) . Anxiety and depression are a form of stress response in the body. When the elderly have severe cardiovascular disease, excessive mental stress can stimulate the sympathetic nervous system. In addition, when the heart muscle is severely ischemic, the stress value exceeds the physical and psychological threshold, and the disease becomes unstable. SF was associated with AD in old CHF patients in the study. Specifically, old CHF patients who lacked social participation, social contact, financial support, and a sense of loneliness had higher levels of AD, which is consistent with the results of Hayashi’s and Li’s studies(Hayashi et al., 2022; Li et al., 2024). Due to the long course of CHF, high hospitalization rate, and repeated acute exacerbations, old CHF patients often have somatic symptoms and a high incidence of both SF and AD. One study found that about 60% of old CHF patients showed SF and other subtypes of weakness(Jujo et al., 2021; Li Vigni et al., 2024); other studies have also pointed out the convergence of frailty and its subtypes and anxiety and depression disorders, giving rise to the hypothesis of an 'overlapping syndrome'(Wang et al., 2024). Collard et al. conducted a cross-sectional observational study, the results of which showed that 27% of older adults with anxiety and depression showed physical frailty and other frailty subtypes, and advanced age and severe anxiety and depression were independent risk factors for the occurrence of frailty and its subtypes(Odaci Comertoglu et al., 2024). The present study showed that old CHF patients had high SF levels, which is consistent with Yu’s study(Yu et al., 2023). High SF levels decrease patients’ social and physical activities and affect their bodily function. Coupled with the severe physical symptoms and lengthy course of CHF, the patient’s QOL is reduced, which is also a significant cause of AD. SS levels are negatively correlated with AD levels in elderly CHF patients. In other words, the lower the SS level, the more likely it is to induce high levels of AD. Black points out that social support has a protective effect against depression and suicidal tendencies in adults with autism(Black et al., 2024). In addition, the amount of social support has a negative predictive effect on loneliness, and it also predicts satisfaction with social support, which in turn is associated with depression(Black et al., 2024; Zhou et al.). Zhang et al. showed that good SS can relieve patients' psychological pressure and improve their coping ability. For example, if spouses, offspring, and friends support survivors through daily care, increased companionship, and financial support, it can improve the patient's well-being(Song et al., 2024). Medical staff can greatly help cancer survivors by providing disease-related information and teaching self-management skills, which will assist survivors in assessing their disease status, motivating them to adhere to rehabilitation treatments and promoting psychological adaptation. AD is a negative psychological state that has become a common mental illness among CHD patients. We found that SS partially mediated the relationship between SF and anxiety and depression, which is consistent with Liu's research(Liu et al., 2024). Studies have found that a long-term lack of social activity can reduce the brain's ability to regulate neuroinflammation, while more social behaviour can reduce inflammation. A surge in neuroinflammation is an essential trigger for the development of depression. A systematic review found that loneliness in older people is positively correlated with anxiety and depression, and the worse the social support, the more likely psychological problems such as anxiety and depression are to occur(Nemati-Vakilabad et al.; Sherman et al., 2024). In addition, the company of family and significant others and social networks play an essential role in preventing anxiety and depression. Another study also found that inadequate support from partners, friends and family is associated with an increased likelihood of depression and anxiety(X. Wang et al., 2023). Family and friends can provide emotional support and make individuals feel cared for and supported. In addition, family members and significant others can also provide information and education about depression and anxiety. Understanding their symptoms and coping methods can help patients understand the disease and take immediate action. This helps reduce anxiety about the disease and life, thereby reducing the onset of depressive symptoms. Limitations This study has some limitations. First, this study is a cross-sectional study that cannot determine the causal relationship between variables. It is recommended that future longitudinal studies be conducted to investigate further the mediating effect of SS on SF and AD. Second, China faces the impact of the 'new elderly care model', which contradicts the traditional 'filial piety' culture. However, this study did not include cultural variables, which limits the generalizability of the results. Finally, we collected data through a self-administered questionnaire, which may be subject to recall bias. However, the measurement tools in this study are all reliable and valid. Relevance to clinical practice This study investigated the relationship between SF and AD in old CHF patients, and SS plays a mediator between them. The results provide valuable insights into intervention strategies for old CHF patients. We recommend that physicians and nurses assess patients’ SF and AD risk during their hospital stay, pay attention to their needs and formulate targeted social support care. In addition, enhancing patients’ SS systems and encouraging old CHF patients to participate actively in rehabilitation is also vital in improving their health outcomes. Conclusions We provide extended evidence for the influence of psychosocial factors on AD in old CHF patients. Old CHF patients with SF are more likely to experience a lack of social participation and social connections, loneliness and financial insufficiency, which are closely related to the occurrence of AD. In addition, SS plays a negative mediating role in the relationship between SF and AD. Increasing SS is conducive to improving both SF and AD in old CHF patients. Finally, there should also be attention to the influence of age, marital status and the NYHA classes on AD in old CHF patients. Declarations Ethical approval and consent to participate The research design was reviewed and approved by the School of Nursing and Rehabilitation Ethics Review Committee of Shandong University (Approval No.: 2023-R-004; Approval Date: 3 February 2023). All methods were carried out in accordance with the Declaration of Helsinki and relevant national and institutional guidelines. In strict adherence to the principle of informed consent, all data were collected anonymously after obtaining the permission and informed consent signed by respondents. Consent for publication Not applicable. Clinical Trial Number Not applicable. Availability of data and materials Data are available on request by contacting the author upon reasonable request. Competing interests The authors declare no competing interests. Funding The study is supported by the Shaanxi Provincial Science and Technology Department Research Project (No. 2023-JC-YB-806). Authors' contributions JTH was responsible for the methodology, data analysis, and writing of the first draft. JTH and XBL were accountable for managing the data. CY and DLW was responsible for data analysis. XRL and JTHwere answerable for the study design. WXY, JTH and XRL were accountable for supervising writing, reviewing, and editing. The authors read and approved the final draft. Acknowledgement We would like to take this opportunity to thank all participants in this study for sharing their valuable time with us. References Association, W. M. (2024). World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Participants. JAMA . https://doi.org/10.1001/jama.2024.21972 Bai, B., Yin, H., Guo, L., Ma, H., Wang, H., Liu, F., Liang, Y., Liu, A., & Geng, Q. (2021). 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J Pers Assess , 55 (3-4), 610-617. https://doi.org/10.1080/00223891.1990.9674095 Tables Table 1. Comparison of differences between anxiety and depression in demographic and disease-related data (n=394) Variables n(%)/M(SD) Anxiety Depression M(SD) t/F/r value P value M(SD) t/F/r value P value Age 69.06(6.578) 8.25(3.389) .259 <0.01 8.5(3.345) .290 <0.01 Gender -1.469 0.143 -1.632 0.104 Female 253(64.2%) 8.44(3.216) 8.71(3.196) Male 141(35.8%) 7.9(3.665) 8.12(3.577) Education level 0.726 0.485 2.609 0.075 Primary school and below 236(59.9%) 8.08(3.491) 8.19(3.458) Junior school or High school 126(32%) 8.49(3.329) 8.96(3.178) College or University and above 32(8.1%) 8.53(2.828) 9(2.929) Marital status -1.965 0.05 -2.266 0.024 Single 47(11.9%) 8.37(3.338) 8.64(3.286) Married 347(88.1%) 7.34(3.655) 7.47(3.623) Residence 0.669 0.504 -0.256 0.798 Rural 203(51.5%) 8.37(3.282) 8.46(3.335) Urban 191(48.5%) 8.14(3.491) 8.54(3.361) Living situation 0.351 0.704 0.527 0.591 Living alone 42(10.7%) 7.95(3.485) 8.17(3.655) Living with others 347(88.1%) 8.3(3.373) 8.56(3.289) other situation 5(1.3%) 7.4(4.219) 7.4(4.827) Number of chronic diseases 0.706 0.48 0.543 0.587 None or one 245(62.2%) 8.34(3.4) 8.57(3.389) Two or more 149(37.8%) 8.09(3.376) 8.38(3.279) Number of hospitalizations 1.97(1.641) 8.25(3.389) .200 <0.01 8.5(3.345) .268 <0.01 Table 1. Comparison of differences between anxiety and depression in demographic and disease-related data (n=394)(continued table) Variables n(%)/M(SD) Anxiety Depression M(SD) t/F/r value P value M(SD) t/F/r value P value Monthly household income 1.452 0.227 2.431 0.065 Less than 1,000 RMB 92(23.4%) 8.4(3.439) 8.41(3.255) 1,000 to 2,999 RMB 117(29.7%) 7.78(3.55) 7.98(3.591) 3,000 to 5,999 RMB 123(31.2%) 8.28(3.251) 8.62(3.225) 6,000 RMB and more 62(15.7%) 8.84(3.23) 9.37(3.101) NYHA classification 17.805 <.001 19.597 <.001 Class I 80(20.3%) 6.18(4.26) 6.55(4.206) Class II 119(30.2%) 8.42(3.246) 8.43(2.993) Class III 114(28.9%) 8.43(3.016) 8.65(3.151) Class IV 81(20.6%) 9.79(1.822) 10.32(1.745) Table 2. Correlation analysis of social frailty, social support, anxiety and depression(n=394) Variables M(SD) Anxiety Depression Social frailty Social support Anxiety 8.25(3.389) 1 Depression 8.5(3.345) .625** 1 Social frailty 2.26(1.348) .320** .388** 1 Social support 54.02(14.476) -.290** -.257** -.196** 1 Table 3. Regression analysis of anxiety and depression(n=394) Variables Anxiety Depression The first layer The second layer The third layer The first layer The second layer The third layer Beta p value Beta p value Beta p value Beta p value Beta p value Beta p value Covariables Age 0.143 0.002 0.13 0.004 0.056 0.224 0.103 0.025 0.092 0.041 0.004 0.932 The number of hospitalizations -0.408 0.025 -0.37 0.034 -0.691 <.001 -0.271 0.129 -0.237 0.172 -0.617 <.001 NYHA - class II 2.005 <.001 1.762 <.001 0.484 0.327 1.691 <.001 1.473 0.001 -0.043 0.929 NYHA - class III 1.714 0.001 1.429 0.005 -1.095 0.104 1.644 0.001 1.387 0.006 -1.605 0.015 NYHA - class IV 2.893 <.001 2.557 <.001 -0.946 0.316 3.135 <.001 2.833 <.001 -1.319 0.152 Marital status 0.457 0.362 0.616 0.203 0.25 0.595 0.609 0.218 0.752 0.117 0.319 0.489 Independent variable Social frailty -0.059 <.001 -0.045 <.001 -0.053 <.001 -0.037 <.001 Mediator Social support 1.654 <.001 1.961 <.001 R 2 0.145 0.206 0.263 0.147 0.198 0.279 F value 10.907 <.001 14.348 <.001 17.149 <.001 11.084 <.001 13.618 <.001 18.64 <.001 Table 4. Mediating analysis of social frailty, social support, and anxiety and depression(n=394) Model path Anxiety Depression Effect BootSE BootLLCI BootULCI Effect BootSE BootLLCI BootULCI Path a SF→SS -2.2169 .5305 -3.2600 -1.1739 -2.2169 .5305 -3.2600 -1.1739 Path b SS→A/D -.0538 .0108 -.0750 -.0326 -.0452 .0105 -.0658 -.0245 Total effect (path c) SF→A/D .9910 .1167 .7617 1.2204 1.0860 .1126 .8646 1.3075 Direct effect (path c’) SF→A/D .8718 .1158 .6443 1.0994 .9859 .1126 .7644 1.2073 Indirect effect (path a*b) SF→SS→AD .1192 .0404 .0500 .2074 .1001 .0373 .0369 .1847 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6805502","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":480388565,"identity":"ff999f8a-8c9c-4ddb-a47a-e12350b013e2","order_by":0,"name":"Junting Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIiWNgGAWjYBACAzDJA8TMUBF+EJFQQIQWHpgWyQaQFgNCWqAWQUQOoIhjAnOJ5GcPv8gczrNn5z38uqLijt3m86sTPzwwYJDnFzuAVYvljDRzYxmew8U8zHxplmfOPEveduPtZgmgwwxnzk7A7rAbCWbSEjyHE3uYecwMG9sOJ5vdOLsBpCXB4DYuLenfULUYzzi7+Qd+LTlmkh8gWowfArXYGfD3bsNvy5k3ZdIMPOmJPYd5zBgbzhxOkLjBu80iwUACt1+Op2+T/Nljndjef8b4Y0PFYXv+/rObb/6osJHnl8auBQSYeXvANJsEkEhskACrlMCpHAQYf/yAaP0AJOwZ+A/gVT0KRsEoGAUjDwAAUNRiLNCN6YMAAAAASUVORK5CYII=","orcid":"","institution":"School of Nursing and Rehabilitation, Shandong University, Jinan, Shandong, China;","correspondingAuthor":true,"prefix":"","firstName":"Junting","middleName":"","lastName":"Huang","suffix":""},{"id":480388566,"identity":"69c5dbe0-71a0-413f-af99-68cd863f9d91","order_by":1,"name":"Xiaobo Liu","email":"","orcid":"","institution":"Yanan University Affiliated Hospital, Yan'an, Shaanxi, China","correspondingAuthor":false,"prefix":"","firstName":"Xiaobo","middleName":"","lastName":"Liu","suffix":""},{"id":480388567,"identity":"015a129d-b139-4b99-8b22-fd817d98247c","order_by":2,"name":"Duolao Wang","email":"","orcid":"","institution":"Liverpool School of Tropical Medicine, Liverpool, United Kingdom","correspondingAuthor":false,"prefix":"","firstName":"Duolao","middleName":"","lastName":"Wang","suffix":""},{"id":480388568,"identity":"e0072ba2-5afe-47eb-8bb3-95935086c2e4","order_by":3,"name":"Xiaorong Luan","email":"","orcid":"","institution":"4.Qilu Hospital of Shandong University, Jinan, Shandong, China;","correspondingAuthor":false,"prefix":"","firstName":"Xiaorong","middleName":"","lastName":"Luan","suffix":""},{"id":480388569,"identity":"410e87c3-3d1a-4f7f-af87-6c9d2734f7e1","order_by":4,"name":"Wanxia Yao","email":"","orcid":"","institution":"5.School of Medicine, Xi 'an Peihua University, Xi 'an, Shaanxi , China;","correspondingAuthor":false,"prefix":"","firstName":"Wanxia","middleName":"","lastName":"Yao","suffix":""},{"id":480388570,"identity":"9ea17b52-024c-4a79-a0ac-6a76f5585d06","order_by":5,"name":"Cong Yao","email":"","orcid":"","institution":"The Department of Nursing, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China","correspondingAuthor":false,"prefix":"","firstName":"Cong","middleName":"","lastName":"Yao","suffix":""}],"badges":[],"createdAt":"2025-06-02 23:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6805502/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6805502/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86131002,"identity":"7c47a48a-a3c2-4a81-a9d3-cad412a6e2a5","added_by":"auto","created_at":"2025-07-07 06:43:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":266028,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6805502/v1/8f840c053771c0022bf6dbff.png"},{"id":86131597,"identity":"3cbb16be-411e-4cf2-bfd8-6a70ed94850a","added_by":"auto","created_at":"2025-07-07 06:51:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38164,"visible":true,"origin":"","legend":"\u003cp\u003eThe flowchart process of participant recruitment\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6805502/v1/38b586dfdfd1d8f859e5398f.png"},{"id":88574214,"identity":"d901ccb2-c4b0-470a-943f-c40b3a77dbb9","added_by":"auto","created_at":"2025-08-08 01:01:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1273952,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6805502/v1/2fdeaf2b-1a99-4d91-8fd1-aaf86fe137fc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Social support as a mediator between social frailty and anxiety and depression in old patients with chronic heart failure: a cross-sectional study","fulltext":[{"header":"What does this paper contribute to the wider global clinical community?","content":"\u003cp\u003eThe mental health of old CHF patients has become a public concern worldwide. We collected data on three hundred ninety-four CHF patients from three tertiary hospitals in Northeast, Northwest, and South China to provide evidence for exploring the factors affecting physical and mental health. This study extends the mediating role of social support between social frailty and, anxiety and depression. This shows that psychosocial factors such as social networks and social participation, as well as feelings of loneliness, are essential factors in improving adverse health outcomes in old CHF patients. The mediating model suggests that a comprehensive body-mind-society intervention may be more effective in reducing anxiety and depression symptoms in CHF patients and improving their treatment compliance. Therefore, we propose the following recommendations: (1) With the development of the \u0026apos;new elderly care model\u0026apos; in China, traditional \u0026apos;filial piety\u0026apos; has been redefined. Increasing social support systems such as social networks can help improve older people\u0026apos;s physical and mental health. (2) CHF is a chronic disease with both bodily and psychological disorders. Dual-heart treatment not only alleviates the physical symptoms and complications, such as activity limitations of old patients but is also an important measure to improve their mental health. (3) Further improve hospital-community-family integrated medical and nursing services and implement \u0026apos;medical insurance for minor and major illnesses\u0026apos; for old adults in rural areas.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe 2024 AHA/ACC/HFSA Heart Failure Guidelines state that heart failure places a substantial financial burden on patients\u0026apos; families and society(Hollenberg et al., 2024). Chronic heart failure (CHF) is a debilitating disease and is characterized by high prevalence, morbidity, and readmission rates. In China, the incidence of CHF among 60-69 and 70-79-year-olds is 23.5% and 30.8%, respectively(Jiurui Wang et al., 2023). Depression and anxiety disorders are prevalent in patients with CHF. A meta-analysis of 36 studies found that 21.5%-90% and above 50% of CHF patients exhibited clinically significant depression and anxiety symptoms(Celano et al., 2018). Studies have shown that there is an interaction between\u0026nbsp;social frailty and depression in older people(Hayashi et al., 2022; Qi \u0026amp; Li, 2022). In addition, anxiety and depression are independent risk factors for social frailty in older adults. Social frailty is highly prevalent among patients hospitalized for heart failure and aged \u0026ge;65 years, accounting for approximately 66.5%(Jujo et al., 2021). However, there are no studies to explore whether SF is a risk factor for anxiety and depression and its function mechanism in old CHF patients.\u003c/p\u003e\n\u003cp\u003eAnxiety and depression (AD) are common in old CHF patients. Studies reported that anxiety and depression can lead to loss of quality and adverse cardiovascular outcomes(Rashid et al., 2023; Veskovic et al., 2023). The discomfort experienced by old CHF patients interacts with their psychiatric conditions, which is associated with their functional impairment and limitation of social participation. Studies have shown that depressive symptoms lead to a twofold increase in the risk of death or cardiac events in old adults(Li et al.; Settergren et al., 2024; Tsabedze et al., 2021). Once anxiety and depression occur in CHF patients, the hormone levels in the body will rise further, as will sympathetically nerve excitability, further increasing myocardial load and myocardial oxygen consumption, thereby adversely affecting the heart and blood pressure.\u003c/p\u003e\n\u003cp\u003eSocial frailty (SF) is an individual\u0026apos;s persistent risk of losing the resources, activities, and abilities needed to meet their basic social needs(Qi et al., 2023).\u0026nbsp;Existing studies indicated that more than half of old CHF inpatients have two or more sub-types of frailty, and two-thirds of them have SF(Jujo et al., 2021). These patients often have low disease self-management capabilities and inadequate external care support, which increases the risk of adverse health outcomes. Many reports have pointed out that patients with severe depressive moods are more likely to experience SF, and the two mutually reinforce a vicious cycle(Hayashi et al., 2022; Liu et al., 2024).\u0026nbsp;Patients with severe depression and anxiety often feel fatigue, loss of appetite and interest in hobbies, and lack of initiative to communicate with others.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSocial support (SS) refers to all support other than one\u0026apos;s own, including multiple fields, i.e., providing spiritual and material resources(Chamberlain, 2017). SS mainly comes from medical staff, relatives, and friends of old CHF patients. Medical staff\u0026apos;s SS is beneficial for forming a good doctor-nurse-patient relationship, and the care and love given by relatives and friends is also the vital essence of social support systems. Reports showed SS is a protective factor in old adults coping with negative emotions and adverse health outcomes in the face of stressful events(Chu et al., 2023; Wang et al., 2022).\u003c/p\u003e\n\u003cp\u003eWe applied the stress process model (SPM) to guide the selection of key factors influencing anxiety and depression in old CHF patients(J. Wang et al., 2023). SPM indicates that the stress process includes four elements: stressor (SF), mediator (SS), stress response (anxiety and depression), and outcome (health outcomes). SF is a stressor that stimulates the internal and external environment of the body and causes a stress response. Old CHF patients often were accompanied by clinical symptoms, i.e., dyspnoea, chest tightness, shortness of breath, etc., leading to loss of social participation due to a lack of health promotion behaviours and social interactions predisposing them to psychosomatic diseases, i.e., anxiety and depression. As a complex structural system, SS can alleviate the adverse effects of stressful events influencing cognition, behaviour, and psychological status. Therefore, we propose the following hypotheses in CHF patients based on SPM. Hypothesis 1: SF is an independent risk factor for anxiety and depression. Hypothesis 2: SF, SS, anxiety, and depression are correlated. Hypothesis 3: SS mediates between SF and anxiety and depression. Figure 1 shows the the mediator models. Figure 1.1 shows the mediator model of social support between social frailty and anxiety. And figure 1.2 shows the mediator model of social support between social frailty and depression.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy participants\u003c/p\u003e\n\u003cp\u003eThis study is cross-sectional research from October 2022 to June 2023 using convenient sampling of old CHF patients. Participants were admitted to the Cardiology Departments of three tertiary Grade A hospitals in Shandong Province (northeast), Shaanxi Province (northwest), and Guizhou Province (south) in China. Inclusion criteria included a diagnosis of CHF according to heart failure guidelines; age 60 years and above; no severe hearing or visual impairments; no neurological diseases (e.g., dementia, stroke, epilepsy, etc.); no severe psychiatry disorders (e.g., schizophrenia, bipolar disorder, etc.); no other advanced diseases (e.g., leukaemia, breast cancer, etc.); fluency in speaking, listening, reading, and writing; and voluntary participation in the study. A rough sample size estimation method was used, which requires the sample size to be 10-20 times that of the study variables. This study included 14 variables, and the sample size should be 140-280 participants. The sample size was increased by 20% to 168-336 participants considering invalid questionnaires. Three hundred ninety-four CHF patients were invited to complete questionnaires; Figure 2 shows the flowchart process of participant recruitment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study strictly abides by the Declaration of Helsinki and has been approved by the School of Nursing and Rehabilitation Ethics Review Committee of Shandong University (Approval No.: 2023-R-004; Approval Date: 3 February 2023)(Association, 2024). Questionnaires were collected using face-to-face interviews by a trained researcher. Interview and questionnaire completion took approximately 20-25 minutes. Before completing the questionnaires, all participants signed an informed consent form and were told they had the right to withdraw from the study without affecting subsequent treatment. All data were processed anonymously and destroyed after the end of the study.\u003c/p\u003e\n\u003cp\u003eMeasurements\u003c/p\u003e\n\u003cp\u003eIndependent variable = SF\u003c/p\u003e\n\u003cp\u003eSF was assessed using the HALFT scale (Help, Participation, Loneliness, Financial, and Talk, HALFT)(Ma et al., 2018). The HALFT scale consists of five items and five dimensions: being unable to help others, limited social participation, loneliness, financial difficulties, and having no one to talk to. Five items: Item 1: Have you helped friends or family this past year? Item 2: Have you participated in social or leisure activities in the past year? Item 3: Have you felt lonely in the past week? Item 4: Was your income last year sufficient to cover your living expenses for one year? Item 5: Do you have someone to talk to every day? One point is calculated for \u0026apos;no\u0026apos; answers to items 1, 2, 4, and 5, but for \u0026apos;yes\u0026apos; answers to item 3. The total scores of the HALFT scale ranged from 0 to 5 points; the higher the scores were, the higher the SF level was. The Cronbach\u0026apos;s alpha coefficient of the HALFT scale is 0.736.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMediator = SS\u003c/p\u003e\n\u003cp\u003eSS was assessed by The MSPSS (Multidimensional Scale of Perceived Social Support MSPSS)(Zimet et al., 1990). The MSPSS includes 12 items and three dimensions: family (4 items), friends (4 items), and significant others (4 items). Each item was rated on a seven-point scale from 1 (\u0026apos;strongly disagree\u0026apos;) to 7 (\u0026apos;strongly agree\u0026apos;). The minimum and maximum scores were 12 and 84, respectively, with higher scores indicating better social support. The Cronbach\u0026apos;s alpha coefficient of the Chinese version of\u0026nbsp;the MSPSS is 0.906(Yang et al., 2024).\u003c/p\u003e\n\u003cp\u003eDependent variables = AD\u003c/p\u003e\n\u003cp\u003eAD was assessed by The HADS (Hospital Anxiety and Depression Scale, HADS)(Zigmond \u0026amp; Snaith, 1983). The HADS consists of 14 items with two dimensions: HADS-anxiety (HADS-A) and HADS-depression (HADS-D). The HADS-A and HADS-D both include seven items. Each item is scored on a four-point Likert scale, with 3 representing the most negative response and 0 the most positive. The total scores of HAD-A ranged from 0 to 21 points, as well as HADS-D. The higher the score, the more severe the anxiety symptoms and depression symptoms. The Cronbach\u0026apos;s alpha coefficients of the Chinese version of the HADS-A and HADS-D are 0.753 and 0.764, respectively(Yang et al., 2014).\u003c/p\u003e\n\u003cp\u003eCovariates\u003c/p\u003e\n\u003cp\u003eCovariates included age, gender, marital status, residence, education level, living conditions, monthly household income, number of hospitalizations, the NYHA (New York Heart Association, NYHA) classes, and number of chronic diseases. The coding of the category variables is as follows: gender (1=female, 2=male), marital status (1=married, 2=divorced/widowed/single), education level (1=primary school or illiterate, 2=secondary school, 3=college or above), residence (1=rural, 2=urban), living conditions (1=living alone, 2=living with others), monthly household income (1=less than 1,000 yuan, 2=1,000 yuan to 2,999 yuan, 3=3,000 yuan to 5,999 yuan, 4=6,000 yuan or above), NYHA classes (1=Class I, 2=Class II, 3=Class III, 4=Class IV), number of chronic diseases (1=none or one, 2=two or more).\u003c/p\u003e\n\u003cp\u003eStatistical analysis\u003c/p\u003e\n\u003cp\u003eIBM SPSS Statistics Version 26.0 (IBM, Armonk, NY, USA) was applied for data analysis. Category variables are described as frequencies and percentages. Numerical variables are expressed as means (M) and standard deviations (SD). Considering the lack of normal distribution of some variables based on skewness-kurtosis tests, Spearman correlation analysis opted to explore the relationships of variables. An independent sample t-test and ANOVA were used to perform a single-factor analysis of AD. The multiple stepwise regression analysis was used for multiple-factor analysis of AD. The variance inflation factor (VIF) is less than 5, so there is no multicollinearity. In the regression analysis, covariates were added to Model 1, SF to Model 2, and SS to Model 3.\u003c/p\u003e\n\u003cp\u003eMediation effects were tested using the SPSS PROCESS Macro Plug-in Model 4 developed by Preacher and Hayes(Hayes, 2009, 2017). SF was set as X, SS was set as M, anxiety was set as Y1, and depression was set as Y2. This model\u0026apos;s indirect effect is through the Mediator (M). If M is not present, the direct effect of X on Y is c\u0026apos;. The total effect of X on Y (c) is the direct effect + indirect effects: c = c\u0026apos; + ab. All covariates were controlled in the mediation model. A bootstrap 95% confidence interval (CI) based on 5000 samples was applied to assess the significance of direct and indirect effects. Bootstrap results were considered significant if the 95% CI did not contain zeros.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eParticipants\u0026rsquo; characteristics\u003c/p\u003e\n\u003cp\u003eFour hundred twenty questionnaires were distributed for this study, of which 15 were lost and 11 were invalid. Three hundred ninety-four valid questionnaires were returned for a valid response rate of 93.81%.\u0026nbsp;Table 1 shows comparison of differences between anxiety and depression in demographic and disease-related data. The mean age of the participants was 69.06 years (SD=6.578), and the majority were female (64.2%). Approximately 11.9% of the participants were divorced, widowed, or single; 59.9% had an education level of primary school or below; 347 people were cohabiting with others, 42 were living alone; 149 people had two or more chronic diseases; 203 people were living in rural areas; the mean of the number of hospitalizations was 1.97 (SD=1.641); and 332 people had a monthly household income of less than 6,000 yuan. There were 80, 119, 114, and 81 people with NYHA classes I-IV, respectively.\u003c/p\u003e\n\u003cp\u003eSingle-factor analysis of AD\u003c/p\u003e\n\u003cp\u003eIndependent sample t-test showed that marital status (t=-1.965, p=0.05) is an influencing factor of AD. ANOVA results showed that NYHA classes (F=14.931, p\u0026lt;0.001) influence AD. Spearman correlation analysis showed that age (r=0.259, p\u0026lt;0.01) and number of hospitalizations (r=0.2, p\u0026lt;0.01) are influencing factors of AD. Table 1 shows comparison of differences between anxiety and depression in demographic and disease-related data.\u003c/p\u003e\n\u003cp\u003eCorrelation of SF, SS, and AD\u003c/p\u003e\n\u003cp\u003eThe mean of SF is 2.26(SD=1.38), the mean of SS is 54.02(SD=14.476), the mean of anxiety is 8.25(SD=3.389), the mean of depression is 8.5(SD=3.345). Spearman correlation analysis indicated SF (r=.320, p\u0026lt;0.01) and SS (r=.290, p\u0026lt;0.01) were negatively correlated with anxiety. It also revealed that SF (r=.388, p\u0026lt;0.01) and SS (r=-.257, p\u0026lt;0.01) were negatively correlated with depression. Table 2 shows correlation analysis of social frailty, social support, anxiety and depression.\u003c/p\u003e\n\u003cp\u003eMultiple-factor analysis of Anxiety\u003c/p\u003e\n\u003cp\u003eThe multiple stepwise regression analysis results showed in model 1, R2 is 0.145, indicating that age, the number of hospitalizations, and NYHA classes can predict anxiety, with an explanation of 14.5%. In model 2, R2 is 0.206, indicating that SF can significantly expect anxiety, with a net explanation of 6.1%. In model 3, R2 is 0.263, indicating that SS can predict anxiety, with a net explanation of 5.7%. The main effect of SF on anxiety is significantly reduced, suggesting that SS may mediate between SF and anxiety. Table 3 shows regression analysis of anxiety and depression.\u003c/p\u003e\n\u003cp\u003eMultiple-factor Analysis of Depression\u003c/p\u003e\n\u003cp\u003eThe multiple stepwise regression analysis results showed in model 1, R2 is 0.147, indicating that age and NYHA classification can predict depression, with an explanation of 14.7%. In model 2, R2 is 0.198, indicating that SF can significantly predict depression, with a net explanation of 5.1%. In model 3, R2 is 0.279, indicating that SS can expect depression, with a net explanation of 8.1%. The main effect of SF on depression is significantly reduced, suggesting that SS may have a mediating impact between SF and depression. Table 3 shows regression analysis of anxiety and depression.\u003c/p\u003e\n\u003cp\u003eMediation analysis of SS between SF and anxiety\u003c/p\u003e\n\u003cp\u003eThe bootstrap results indicated that the path coefficient of SF on SS (path a1) was -2.2169 (95% CI: -3.2600, -1.1739), and the path coefficient of SS on anxiety (path b1) was -0.0538 (95% CI: -.0750, -.0326). The total effect (path c1) and direct effect (path c1\u0026apos;) of SF on anxiety were .9910 (95% CI: .7617, 1.2204) and .8718 (95% CI: .6443, 1.0994), respectively. The indirect effect of SF on anxiety (path a1*b1) is .1192 (95% CI: .0500,.2074). The indirect impact of SS is 13.67%, calculated by (path a1*b1)/ (path c1\u0026apos;), and is a partial mediation. Table 4 shows mediating analysis of social frailty, social support, and anxiety and depression.\u003c/p\u003e\n\u003cp\u003eMediation analysis of SS between SF and depression\u003c/p\u003e\n\u003cp\u003eThe bootstrap results indicated that the path coefficient of SF on SS (path a2) was -2.2169 (95% CI: -3.2600, -1.1739), and the path coefficient of SS on depression (path b2) was -.0452 (95%CI:-.0658, -.0245), and the total effect (path c2) and direct effect (path c2\u0026apos;) of SF on depression were 1.0860 (95%CI:.8646,1.3075) and .9859 (95%CI:.7 644, 1.2073). The indirect impact of SF on depression (path a2*b2) was .1001 (95% CI: .0369,.1847). The mediating effect of SS was calculated as (path a2*b2)/ (path c2\u0026apos;) and was 10.15%, which was a partial mediation. Table 4 shows mediating analysis of social frailty, social support, and anxiety and depression.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study examined the association between SF and AD in old Chinese patients with CHF. We also explored the effects of demographic and disease factors and SS on AD. In addition, we verified the mediating roles of SS between SF and AD. Our findings confirm that SF directly affects AD and indirectly through SS or AD, which suggests that reducing SF is crucial in enhancing AD in old CHF patients.\u003c/p\u003e\n\u003cp\u003eWe found that age, number of hospitalizations and NYHA classes are vital factors affecting AD in old CHF patients. Age is positively correlated with AD in old CHF patients, meaning that the older the patient, the higher the likelihood of developing AD symptoms. The hypothesis that serotonin deficiency leads to short (S) or long (L) alleles is one of the earliest hypotheses for the cause of depression(Cui et al., 2024; Szymkowicz et al., 2023). A study of the old population in South Korea found that when exposed to stressful life events (e.g., CHF or other cardiovascular diseases), carriers of the S allele showed a higher risk of late-life depression (LLD)(Song et al., 2019). This study found a positive correlation between the number of hospitalizations and the AD level in elderly CHF patients; that is, the AD level increased with the number of hospitalizations. Studies have shown that frequent hospital admissions improve the psychological burden on patients and their families and increase their financial burden(Guo et al., 2019; Huang et al., 2020). In addition, during hospitalization, patients need to receive various treatments and take medications such as anti-heart failure drugs, which are all predisposing factors for AD. \u003cstrong\u003eIn this study, the higher the NYHA classification level, the higher the anxiety and depression scores in old CHF patients, which is consistent with the findings of Yin\u0026rsquo;s study\u003c/strong\u003e\u003cstrong\u003e(Yin et al., 2019)\u003c/strong\u003e\u003cstrong\u003e. Studies pointed out that for patients with cardiovascular disease, the milder the coronary artery stenosis, the more severe the anxiety and depression symptoms\u003c/strong\u003e\u003cstrong\u003e(Bai et al., 2021; Das et al., 2022)\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e \u003cstrong\u003eAnxiety and depression are a form of stress response in the body. When the elderly have severe cardiovascular disease, excessive mental stress can stimulate the sympathetic nervous system. In addition, when the heart muscle is severely ischemic, the stress value exceeds the physical and psychological threshold, and the disease becomes unstable.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSF was associated with AD in old CHF patients in the study. Specifically, old CHF patients who lacked social participation, social contact, financial support, and a sense of loneliness had higher levels of AD, which is consistent with the results of Hayashi\u0026rsquo;s and Li\u0026rsquo;s studies(Hayashi et al., 2022; Li et al., 2024). Due to the long course of CHF, high hospitalization rate, and repeated acute exacerbations, old CHF patients often have somatic symptoms and a high incidence of both SF and AD. One study found that about 60% of old CHF patients showed SF and other subtypes of weakness(Jujo et al., 2021; Li Vigni et al., 2024); other studies have also pointed out the convergence of frailty and its subtypes and anxiety and depression disorders, giving rise to the hypothesis of an \u0026apos;overlapping syndrome\u0026apos;(Wang et al., 2024). Collard et al. conducted a cross-sectional observational study, the results of which showed that 27% of older adults with anxiety and depression showed physical frailty and other frailty subtypes, and advanced age and severe anxiety and depression were independent risk factors for the occurrence of frailty and its subtypes(Odaci Comertoglu et al., 2024). The present study showed that old CHF patients had high SF levels, which is consistent with Yu\u0026rsquo;s study(Yu et al., 2023). High SF levels decrease patients\u0026rsquo; social and physical activities and affect their bodily function. Coupled with the severe physical symptoms and lengthy course of CHF, the patient\u0026rsquo;s QOL is reduced, which is also a significant cause of AD.\u003c/p\u003e\n\u003cp\u003eSS levels are negatively correlated with AD levels in elderly CHF patients. In other words, the lower the SS level, the more likely it is to induce high levels of AD. Black points out that social support has a protective effect against depression and suicidal tendencies in adults with autism(Black et al., 2024). In addition, the amount of social support has a negative predictive effect on loneliness, and it also predicts satisfaction with social support, which in turn is associated with depression(Black et al., 2024; Zhou et al.). Zhang et al. showed that good SS can relieve patients\u0026apos; psychological pressure and improve their coping ability. For example, if spouses, offspring, and friends support survivors through daily care, increased companionship, and financial support, it can improve the patient\u0026apos;s well-being(Song et al., 2024). Medical staff can greatly help cancer survivors by providing disease-related information and teaching self-management skills, which will assist survivors in assessing their disease status, motivating them to adhere to rehabilitation treatments and promoting psychological adaptation. AD is a negative psychological state that has become a common mental illness among CHD patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe found that SS partially mediated the relationship between SF and anxiety and depression, which is consistent with Liu\u0026apos;s research(Liu et al., 2024). Studies have found that a long-term lack of social activity can reduce the brain\u0026apos;s ability to regulate neuroinflammation, while more social behaviour can reduce inflammation. A surge in neuroinflammation is an essential trigger for the development of depression. A systematic review found that loneliness in older people is positively correlated with anxiety and depression, and the worse the social support, the more likely psychological problems such as anxiety and depression are to occur(Nemati-Vakilabad et al.; Sherman et al., 2024). In addition, the company of family and significant others and social networks play an essential role in preventing anxiety and depression. Another study also found that inadequate support from partners, friends and family is associated with an increased likelihood of depression and anxiety(X. Wang et al., 2023). Family and friends can provide emotional support and make individuals feel cared for and supported. In addition, family members and significant others can also provide information and education about depression and anxiety. Understanding their symptoms and coping methods can help patients understand the disease and take immediate action. This helps reduce anxiety about the disease and life, thereby reducing the onset of depressive symptoms.\u003c/p\u003e\n\u003cp\u003eLimitations\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study has some limitations. First, this study is a cross-sectional study that cannot determine the causal relationship between variables. It is recommended that future longitudinal studies be conducted to investigate further the mediating effect of SS on SF and AD. Second, China faces the impact of the \u0026apos;new elderly care model\u0026apos;, which contradicts the traditional \u0026apos;filial piety\u0026apos; culture. However, this study did not include cultural variables, which limits the generalizability of the results. Finally, we collected data through a self-administered questionnaire, which may be subject to recall bias. However, the measurement tools in this study are all reliable and valid.\u003c/p\u003e\n\u003cp\u003eRelevance to clinical practice\u003c/p\u003e\n\u003cp\u003eThis study investigated the relationship between SF and AD in old CHF patients, and SS plays a mediator between them. The results provide valuable insights into intervention strategies for old CHF patients. We recommend that physicians and nurses assess patients\u0026rsquo; SF and AD risk during their hospital stay, pay attention to their needs and formulate targeted social support care. In addition, enhancing patients\u0026rsquo; SS systems and encouraging old CHF patients to participate actively in rehabilitation is also vital in improving their health outcomes.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe provide extended evidence for the influence of psychosocial factors on AD in old CHF patients. Old CHF patients with SF are more likely to experience a lack of social participation and social connections, loneliness and financial insufficiency, which are closely related to the occurrence of AD. In addition, SS plays a negative mediating role in the relationship between SF and AD. Increasing SS is conducive to improving both SF and AD in old CHF patients. Finally, there should also be attention to the influence of age, marital status and the NYHA classes on AD in old CHF patients.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003eEthical approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe research design was reviewed and approved by the School of Nursing and Rehabilitation Ethics Review Committee of Shandong University (Approval No.: 2023-R-004; Approval Date: 3 February 2023). All methods were carried out in accordance with the Declaration of Helsinki and relevant national and institutional guidelines. In strict adherence to the principle of informed consent, all data were collected anonymously after obtaining the permission and informed consent signed by respondents.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClinical Trial Number\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eData are available on request by contacting the author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe study is supported by the Shaanxi Provincial Science and Technology Department Research Project (No. 2023-JC-YB-806).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eJTH was responsible for the methodology, data analysis, and writing of the first draft. JTH and XBL were accountable for managing the data. CY and DLW was responsible for data analysis. XRL and JTHwere answerable for the study design. WXY, JTH and XRL were accountable for supervising writing, reviewing, and editing. The authors read and approved the final draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgement\u003c/p\u003e\n\u003cp\u003eWe would like to take this opportunity to thank all participants in this study for sharing their valuable time with us.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAssociation, W. M. (2024). World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Participants. \u003cem\u003eJAMA\u003c/em\u003e. https://doi.org/10.1001/jama.2024.21972\u003c/li\u003e\n\u003cli\u003eBai, B., Yin, H., Guo, L., Ma, H., Wang, H., Liu, F., Liang, Y., Liu, A., \u0026amp; Geng, Q. (2021). 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Comparison of differences between anxiety and depression in demographic and disease-related data (n=394)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003en(%)/M(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eM(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003et/F/r value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eM(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003et/F/r value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e69.06(6.578)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.25(3.389)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.5(3.345)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e.290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 423px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e-1.469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e-1.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e253(64.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.44(3.216)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.71(3.196)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e141(35.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7.9(3.665)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.12(3.577)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 423px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003ePrimary school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e236(59.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.08(3.491)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.19(3.458)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eJunior school or High school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e126(32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.49(3.329)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.96(3.178)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eCollege or University and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e32(8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.53(2.828)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e9(2.929)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 423px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e-1.965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e-2.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e47(11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.37(3.338)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.64(3.286)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e347(88.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7.34(3.655)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7.47(3.623)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 423px;\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e-0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e203(51.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.37(3.282)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.46(3.335)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e191(48.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.14(3.491)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.54(3.361)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eLiving situation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eLiving alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e42(10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7.95(3.485)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.17(3.655)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eLiving with others\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e347(88.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.3(3.373)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.56(3.289)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eother situation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5(1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7.4(4.219)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7.4(4.827)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eNumber of chronic diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eNone or one\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e245(62.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.34(3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.57(3.389)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eTwo or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e149(37.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.09(3.376)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.38(3.279)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eNumber of hospitalizations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e1.97(1.641)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.25(3.389)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.5(3.345)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e.268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1. Comparison of differences between anxiety and depression in demographic and disease-related data (n=394)(continued table)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003en(%)/M(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eM(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003et/F/r value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eM(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003et/F/r value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 423px;\"\u003e\n \u003cp\u003eMonthly household income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eLess than 1,000 RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e92(23.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.4(3.439)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"4\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.41(3.255)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"4\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e1,000 to 2,999 RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e117(29.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7.78(3.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7.98(3.591)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e3,000 to 5,999 RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e123(31.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.28(3.251)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.62(3.225)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e6,000 RMB and more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e62(15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.84(3.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e9.37(3.101)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 423px;\"\u003e\n \u003cp\u003eNYHA classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e17.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e19.597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eClass I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e80(20.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e6.18(4.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"4\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e6.55(4.206)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"4\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eClass II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e119(30.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.42(3.246)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.43(2.993)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eClass III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e114(28.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.43(3.016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.65(3.151)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eClass IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e81(20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e9.79(1.822)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e10.32(1.745)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Correlation analysis of social frailty, social support, anxiety and depression(n=394)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003eM(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eSocial frailty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003eSocial support\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e8.25(3.389)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e8.5(3.345)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e.625**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 31px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eSocial frailty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e2.26(1.348)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e.320**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e.388**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eSocial support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e54.02(14.476)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e-.290**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-.257**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e-.196**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3.\u0026nbsp;Regression analysis of anxiety and depression(n=394)\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eThe first layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eThe second layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eThe third layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eThe first layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eThe second layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eThe third layer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eCovariables\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.932\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eThe number of hospitalizations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eNYHA - class II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e2.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e1.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e1.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e1.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eNYHA - class III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e1.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e1.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-1.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e1.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e1.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-1.605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eNYHA - class IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e2.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e2.557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e3.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e2.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-1.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.616\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.489\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eIndependent variable\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eSocial frailty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e-0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMediator\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eSocial support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e1.654\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e1.961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eF value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e10.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e14.348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e17.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e11.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e13.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e18.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 4. Mediating analysis of social frailty, social support, and anxiety and depression(n=394)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003eModel path\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003eEffect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003eBootSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003eBootLLCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eBootULCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003eEffect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003eBootSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003eBootLLCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eBootULCI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePath a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003eSF\u0026rarr;SS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e-2.2169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e.5305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e-3.2600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-1.1739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e-2.2169 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.5305 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e-3.2600 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-1.1739\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePath b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003eSS\u0026rarr;A/D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e-.0538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e.0108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e-.0750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-.0326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e-.0452 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.0105 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e-.0658\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-.0245\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTotal effect (path c)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003eSF\u0026rarr;A/D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e.9910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e.1167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.7617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.2204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.0860 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.1126 \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.8646 \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.3075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eDirect effect (path c\u0026rsquo;)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003eSF\u0026rarr;A/D\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e.8718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e.1158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.6443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.0994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.9859 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.1126 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.7644 \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.2073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003eIndirect effect (path a*b)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003eSF\u0026rarr;SS\u0026rarr;AD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e.1192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e.0404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.0500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e.2074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.1001 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.0373 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e.0369 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e.1847\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Chronic heart failure, old adults, social frailty, anxiety, depression, social support","lastPublishedDoi":"10.21203/rs.3.rs-6805502/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6805502/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study investigated the relationship between social frailty, anxiety and depression in old Chronic heart failure (CHF) patients. We paid particular attention to how social support moderated this relationship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOld patients with chronic heart failure have severe somatic symptoms, which lead to high levels of social frailty. Understanding the demographic and disease factors, as well as the relationship between social frailty, social support, anxiety and depression, is essential to improve health outcomes in old CHF patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study was conducted on 394 old CHF patients from three tertiary hospitals in China. The study questionnaire included a general information questionnaire, the HALFT scale (social frailty), The MSPSS (social support), and The HADS (anxiety and depression). Hierarchical regression analysis was used to assess the influencing factors of anxiety and depression; the SPSS PROCESS Marco Plug-in was used to conduct mediation analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results showed that age, the number of hospitalization and NYHA classification were the influencing factors of anxiety and depression. Social frailty, social support, and anxiety and depression were related, and social support partially mediated the relationship between social frailty and anxiety and depression, with the mediating effect sizes of 13.67% and 10.15%, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study shows that high levels of social frailty are associated with increased anxiety and depression in old CHF patients. Social support helps to alleviate the adverse effects of social frailty (e.g. lack of social participation and social connections, feelings of loneliness, financial insufficiency) on anxiety and depression. In addition to focusing on patients’ somatic symptoms and treatments, physicians and nurses should also pay attention to the impact of psychosocial factors on the adverse health outcomes of CHF patients, increase the social support system for old adults, and improve patients’ treatment compliance and health outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReporting Method\u003c/strong\u003e: The Strengthening Reporting of Observational Studies in Epidemiology (STROBE) guidelines were followed in the study.\u003c/p\u003e\n\u003cp\u003eNo Patient or Public Contribution: Recruitment for old CHF patients met the inclusion criteria.\u003c/p\u003e","manuscriptTitle":"Social support as a mediator between social frailty and anxiety and depression in old patients with chronic heart failure: a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-07 06:43:45","doi":"10.21203/rs.3.rs-6805502/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fae1579b-0deb-47c7-87ec-15437fbec2f4","owner":[],"postedDate":"July 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-08T00:53:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-07 06:43:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6805502","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6805502","identity":"rs-6805502","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}