Association Between Depression and Subjective Well-being in older patients with Chronic Diseases in Rural Ethnic Areas of Qiannan, Guizhou: The Mediating Role of Social Support

Association Between Depression and Subjective Well-being in older patients with Chronic Diseases in Rural Ethnic Areas of Qiannan, Guizhou: The Mediating Role of Social Support | 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 Association Between Depression and Subjective Well-being in older patients with Chronic Diseases in Rural Ethnic Areas of Qiannan, Guizhou: The Mediating Role of Social Support Zhonglian Li, Suxian Qin, Yafen Zhu, Quanxiang Zhou, Aijing Yi, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4046318/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 Objective: To explore the associations among social support, depression, and subjective well-being in older patients with chronic diseases in the rural ethnic regions of Qiannan, Guizhou. Methods: This cross-sectional study enrolled oder patients with chronic diseases in Qiannan, Guizhou between June and September 2022. The social support, depression, and subjective well-being were assessed by a self-developed questionnaire on general information, the social support rating scale (SSRS), the geriatric depression scale (GDS-15), and the Memorial University of Newfoundland Happiness Scale (MUNSH), respectively. Results: A total of 2,156 participants (1,104 males; average age of 71.15±8.04) were included. Their mean SSRS and MUNSH scores were 34.96±7.98 and 27.17±9.48, respectively. The GDS-15 score was 7.23±2.59, with 1529 individuals (70.9%) having depressive symptoms. Multivariate linear regression analysis revealed that mild depression (B = -7.795, 95% CI: -8.437 to -7.153, P < 0.001), moderate to severe depression (B = -11.631, 95% CI: -12.623 to -10.639, P < 0.001), and moderate social support (B = -2.661, 95% CI: -4.063 to -1.259, P < 0.001) were independently associated with subjective well-being. The structural equation model results revealed that the total effect of depression symptoms on subjective well-being in elderly patients with chronic diseases is -0.528, with a direct effect of -0.474 (95% CI: -0.503 to -0.443), accounting for 89.77% of the total effect. The mediating effect of social support on the association between depression and subjective well-being is -0.133 (95% CI: -0.070 to -0.041), constituting 10.23% of the total effect. Conclusions: Older patients with chronic diseases in the rural ethnic areas of Qiannan, Guizhou, exhibited a high prevalence of depressive symptoms and low levels of subjective well-being. Social support partially mediated the association between depression and subjective well-being in this population. Thus, proactive measures are warranted to fortify the social support system for older patients with chronic diseases in Qiannan, Guizhou. Depression Subjective well-being Social support Mediating effect Older patients with chronic diseases Rural areas in ethnic areas Figures Figure 1 Introduction According to the 7th national census data, the proportion of elderly individuals aged ≥ 60 in rural areas of China is 23.81%, surpassing the national average by 5.11 % [1, 2]. With the population aging, the incidence of chronic diseases among older individuals has been steadily rising. Over 180 million of the older individuals in China are affected by chronic diseases, accounting for 75.0% of the elderly population [3]. Psychological issues arising from chronic diseases in senior citizens have become increasingly prominent. Older individuals with chronic diseases from rural areas constitute a substantial vulnerable group, so enhancing their physical and mental health is crucial for healthy aging. Subjective Well-being (SWB) is a critical indicator currently used to assess psychological health and life quality in older individuals [4, 5]. According to previous research, individuals with chronic diseases typically experience lower levels of happiness in comparison to those without such conditions, suggesting a potential association between higher subjective well-being and a lower prevalence of chronic diseases [6]. Furthermore, numerous studies emphasize the role of social support as a protective factor for subjective well-being, with positive social support having a crucial role in sustaining happiness among individuals with chronic diseases [7, 8]. Depression is a prevalent emotional disorder among older individuals [9]. Such individuals who have endured chronic diseases over the long term are more susceptible to psychological issues like anxiety and depression, which significantly reduce their subjective well-being and overall quality of life [10]. In China, the detection rate of depression in older patients with chronic diseases has been reported to range from 40.2% to 48.86% [11]. Moreover, the prevalence of depression is higher among senior individuals from rural areas compared to their urban counterparts [12, 13]. The coexistence of depression among older individuals with chronic diseases can lead to further deterioration of their health, ultimately resulting in increased disability and mortality rates [10, 16]. Existing studies suggest that individuals grappling with depression often lack a robust social support network, underscoring the role of low social support as a contributing factor to depression [14]. Currently, there is a substantial body of research, both on a global scale and domestically, that delves into the pairwise relationships among social support, depression, and subjective well-being in older individuals [15-17]. However, studies explicitly examining the triadic relationship between depression, social support, and subjective well-being remain limited. The existing research has predominantly focused on urban or general rural elderly populations, with a notable scarcity of studies on ethnic minority rural elderly individuals grappling with chronic diseases [18, 19]. Based on the abovementioned studies, the following hypotheses were formulated: Hypothesis 1 (H1), in the ethnic rural communities of Qiannan, Guizhou, depression among older patients with chronic diseases is anticipated to have a detrimental impact on their subjective well-being; Hypothesis 2 (H2), in this demographic, social support is expected to positively influence the subjective well-being of these individuals; Hypothesis 3 (H3), social support may act as a mediating factor in the dynamic between symptoms of depression and subjective well-being in this population. The exploration of these hypotheses aims to unravel the intricate association between mental health, social dynamics, and overall life satisfaction in this unique and under-researched community. The region of Qiannan, characterized by its multi-ethnic composition, remote rural areas, and relatively limited economic and healthcare resources, necessitates particular attention concerning the psychological well-being of older patients with chronic diseases. Consequently, this study aimed to explore the associations among social support, depression, and subjective well-being in older individuals with chronic diseases from the ethnic rural areas of Qiannan, Guizhou. Methods Study design and patients Older individuals aged ³ 60 with chronic diseases living in the ethnic rural regions of Qiannan, Guizhou, were recruited in this cross-sectional study between June and September 2022. Inclusion criteria were: 1) residents aged 60 and above with a residence history of at least 5 years; 2) individuals registered with local health clinics for at least one chronic disease; 3) willingness to provide informed consent and participate voluntarily. Exclusion criteria were: 1) severe visual or hearing impairment; 2) history of severe mental illness; 3) refusal to participate in the survey. This study obtained ethical approval from the Ethics Review Committee of Qiannan Nationalities Medical College (Approval No: 2022 Ethics Review No. 202209). All participants provided informed consent before the initiation of the study. Procedures The stratified random cluster sampling method was used to divide the 12 counties and cities into three levels (good, medium, and poor) according to the economic level of Qiannan Prefecture. Two counties and cities were randomly selected from each county and city with the corresponding economic level, two townships (towns) were randomly selected from each selected city (county), and then 3-4 villages were randomly selected from each selected township to investigate the older individuals who met the survey criteria. This study was performed by a team of 12 investigators, including licensed physicians and medical students with a certain level of medical knowledge, and it employed a questionnaire survey method. Before the survey, the project leader trained the investigators on the survey content and standardized survey language. During the survey, either centralized interviews or one-on-one household visits were conducted. The investigators explained the purpose and significance of the survey to the participants, obtained their consent, and distributed the questionnaires. Older individuals were guided to self-complete the questionnaires, or the investigators recorded the responses based on the participants' answers. Completed questionnaires were collected promptly, and invalid questionnaires were excluded. Survey Content and Questionnaires First, the researchers designed a questionnaire containing key demographic details such as gender, age, ethnicity, education, marital status, living arrangement, family relationships, the number and severity of chronic diseases, self-care abilities, participation in collective activities, and socio-economic indicators like being a precision poverty alleviation target and a minimum living allowance. Short Form Geriatric Depression Scale (GDS-15), initially developed by Sheikh et al. was used to evaluate depressive symptoms among participants. This scale consists of 15 items, scored with 1 point for "yes" and 0 points for "no" [20]; some items are reverse-scored. The total score, ranging from 0 to 15, classifies depression levels into no symptoms (0-5 points), mild symptoms (6-10 points), and moderate to severe symptoms (11-15 points) [21]. The Cronbach's α coefficient, i.e., the internal consistency of this scale, was 0.797 in the present study. Social support was assessed using the Social Support Rating Scale (SSRS), initially developed by Xiao Shuiyuan et al [22]. This scale comprises 10 items distributed across three dimensions: objective support, subjective support, and social support utilization. The total score, ranging from 12 to 66, reflects the overall level of social support, with higher scores indicating stronger support. Social support was categorized into high (³45), moderate (23-44), and low levels (£22) based on total scores. The reliability of this scale in the study was confirmed by a Cronbach's α coefficient of 0.765. Subjective well-being was measured using the Memorial University of Newfoundland Scale of Happiness (MUNSH) developed by Kozma et al. [23]. This scale encompasses 24 items across four dimensions. The assessment of subjective well-being involves considering positive affect (PA) and negative affect (NA), as well as positive experiences (PE) and negative experiences (NE). The total score, ranging from 0 to 48, classifies subjective well-being into high (≥36), moderate (13-35), and low levels (≤12). The lower the total score, the lower the level of subjective well-being. The Cronbach's α coefficient for this scale in the study was 0.811. Statistical analysis Epidata 3.1 was employed for the dual-check data entry process, while data analysis was conducted using SPSS 23.0 (IBM, Armonk, NY, USA) and AMOS 23.0. Categorical data were presented using counts (n) and percentages (%), and continuous data were described with means ± standard deviations. Group comparisons were performed using t-tests for continuous variables and t/F-tests for categorical variables. Pearson correlation analysis was utilized to investigate the relationships among variables, particularly focusing on the correlation between depression, social support, and subjective well-being. Multiple linear regression analysis was employed to identify factors influencing subjective well-being, incorporating variables with a significance level of P < 0.05 from the univariate analysis. AMOS 23.0 was used to construct a structural equation model (SEM). Mediation analysis, evaluating the mediating role of social support between depression and subjective well-being, employed Bootstrap resampling (5000 times). Two-sided p-values<0.05 represented statistical significance. Results Basic Characteristics A total of 2,201 subjects completed questionnaires, 45 subjects were excluded as they were incomplete, resulting in 2,156 valid responses and a questionnaire effective recovery rate of 97.96%. There were 1,104 male participants (51.2%). The average age was (71.15±8.04) years, with 1,182 individuals (54.8%) aged 60-70, 630 individuals (29.2%) aged 71-80, and 344 individuals (16.0%) aged over 80. Regarding ethnicity, 1,416 individuals (65.7%) belonged to minority ethnic groups. Concerning education, 1,168 participants (54.2%) were illiterate, 702 (32.6%) had completed primary school, 208 (9.6%) had completed junior high school, and 78 (3.6%) had completed high school or above. There were 1,476 individuals (68.5%) who were married and still living with their partner and 680 individuals (31.5%) with another marital status. The total MUNSH score for rural elderly patients with chronic diseases was (27.17±9.48)，PA was (5.02±2.64), NA was (4.06±3.00), , PE was (7.56±3.60) and NE was (5.35±3.67).A total of 512 (23.7%) individuals had high subjective well-being, 1538 (71.3%) had moderate subjective well-being, and 106 (4.9%) had low subjective well-being. Significant differences in MUNSH scores were observed among different marital statuses, living arrangements, whether they had a family doctor, whether they were precision-targeted for poverty alleviation, whether they were with minimum living allowance, different education, family relationships, severity of illness, ability to perform daily activities, and participation in social activities (all P < 0.05) ( Table 1 ). Associations between Depression, Social Support, and Subjective Well-being in Older Patients with Chronic Diseases The GDS-15 score for older patients with chronic diseases was (7.23±2.59), with 627 individuals (29.1%) having no depressive symptoms, 1,246 individuals (57.8%) experiencing mild depressive symptoms, and 283 individuals (13.1%) experiencing moderate to severe depressive symptoms. The SRSS total average score was(34.96±7.97), subjective support was （18.80±4.21）, objective support was （8.63±3.47）, and support utilization was （7.53±2.04）. A total of 102 (4.7%) individuals had low social support, 1786 (82.8%) had moderate social support, and 268 (12.4%) had high social support. Significant differences were observed in MUNSH scores and various dimensions among older patients with different degrees of depression and social support levels (all P < 0.05) ( Table 2 ). Pearson correlation analysis results showed that the GDS-15 score was negatively correlated with MUNSH, PA, and NA score (r = -0.528, -0.139, -0.276, P < 0.01) and positively correlated with PE and NE score (r = 0.546, 0.546, P < 0.05). The SSRS score, subjective support score, objective support score, and support utilization score were all negatively correlated with the GDS-15 score (r = -0.243, -0.256, -0.177, -0.121, P < 0.05). The SSRS score was positively correlated with the MUNSH score, PA score, NA score, subjective support score, objective support score, and support utilization score (r = 0.280, 0.282, 0.173, 0.878, 0.815, 0.708, P < 0.05) and negatively correlated with PE score and NE score (r = -0.245, -0.149, P < 0.05). Subjective support was positively correlated with MUNSH score, PA score, and NA score (r = 0.258, 0.242, 0.124, P < 0.05) and negatively correlated with PE score and NE score (r = -0.222, -0.189, P < 0.05). Objective support was positively correlated with MUNSH score, PA score, NA score (r = 0.204, 0.199, 0.170, P < 0.05) and negatively correlated with PE score and NE score (r = -0.177, -0.071, P < 0.05). Support utilization score was positively correlated with MUNSH score, PA score, and NA score (r = 0.214, 0.264, 0.132, P < 0.05) and negatively correlated with PE score and NE score (r = -0.197, -0.073, P < 0.05) ( Table 3 ). Multivariate linear regression analysis revealed that mild depression (B = -7.795, 95% CI: -8.437- -7.153, P < 0.001), moderate to severe depression (B = -11.631, 95% CI: -12.623 - -10.639, P < 0.001), moderate social support (B = -2.661, 95% CI: -4.063- -1.259, P < 0.001), primary school education (B = 1.487, 95% CI: 0.854 - 2.12, P < 0.001), junior high school education (B = 1.882, 95% CI: 0.901 - 2.863, P < 0.001), fair family relationships (B = 6.264, 95% CI: 4.560 - 7.968, P < 0.001), relatively good family relationships (B = 6.372, 95% CI: 4.726 - 8.018, P < 0.001), very good family relationships (B = 9.894, 95% CI: 8.225 - 11.562, P < 0.001), moderate severity of illness (B = -0.893, 95% CI: -1.531 - -0.256, P = 0.006), complete self-care ability (B = 1.601, 95% CI: 0.324 - 2.878, P = 0.014), being a precision-targeted poverty alleviation recipient (B = 7.149, 95% CI: 6.552-7.746, P < 0.001), occasional participation in social activities (B = 1.506, 95% CI: 0.714 - 2.299, P < 0.001), frequent participation in social activities (B = 2.352, 95% CI: 1.366 - 3.337, P < 0.001), and consistently participating in social activities (B = 3.643, 95% CI: 2.448 - 4.838, P < 0.001) were independently associated with subjective well-being ( Table 4 ). Social Support Mediation Analysis of Depression and Subjective Well-being in Older Patients with Chronic Diseases The SEM results indicated a good model fit ( χ 2 /df =7.672, GFI=0.994, NFI=0.987, RFI=0.967, IFI=0.989, TLI= 0.971,CFI=0.989, RMSEA=0.056). The path coefficients for the impact of depression symptoms on social support and subjective well-being in older patients with chronic diseases were -0.28 and -0.47, respectively. The path coefficient for the impact of social support on subjective well-being was 0.19. All standardized path coefficients in the model were statistically significant (all P < 0.001) ( Figure 1 ). The bootstrap test results revealed that the total effect of depression symptoms on subjective well-being in older patients with chronic diseases was -0.528, with a direct effect of -0.474 (95% CI: -0.503 to -0.443), accounting for 89.77% of the total effect. The mediating effect of social support on the association between depression and subjective well-being was -0.133 (95% CI: -0.070 to -0.041), constituting 10.23% of the total effect ( Table 5 ). Discussion This study found that older patients with chronic diseases in the rural ethnic areas of Qiannan, Guizhou, had a high prevalence of depressive symptoms and low levels of subjective well-being. Social support partially mediated the association between depression and subjective well-being in this population. This study may provide a theoretical framework for enhancing the physical and mental health and the overall quality of life of older individuals residing in ethnic regions. The results showed that the overall average subjective well-being score among 2156 older patients with chronic diseases in the rural areas of the southern Guizhou ethnic region was 27.17±9.48, which is lower than the score reported by Fu et al. in their study on older individuals with chronic diseases in Shanxi [24]. This suggests that the subjective well-being of older patients with chronic diseases in the rural areas of the southern Guizhou ethnic region is relatively low, which could be due to the high prevalence of comorbidities, the severity of illnesses, and the high proportion of older patients who were excluded from this survey. In the present study, 48.1% of older individuals had two or more chronic diseases, and 67% of the patients had moderate to severe disease severity. Chronic diseases, characterized by their prolonged and incurable nature, high disability and mortality rates, and the challenges faced by elderly individuals dealing with multiple and severe illnesses, may contribute to increased physical harm and psychological stress. This situation can exacerbate negative emotions, including anxiety and depression, which adversely affect subjective well-being [25]. Additionally, the rural areas of the southern Guizhou ethnic region, characterized by underdeveloped economic, cultural, and medical services, pose further challenges. This survey revealed that 58.5% of the older patients had children working away for extended periods. The restrictions related to the COVID-19 pandemic have significantly reduced the income of migrant workers, leading to diminished family companionship, life care, and emotional and economic support for many elderly individuals with chronic diseases, further impacting their subjective well-being [26]. This study indicated that subjective well-being was notably lower among older individuals characterized by lower educational attainment, unmarried status, solitary living, strained family relationships, more severe health conditions, limited daily activity capabilities, lack of a dedicated family doctor, low social engagement, and non-eligibility for precision poverty alleviation programs. These observations align with the conclusions of prior studies, reaffirming the interconnectedness of the socioeconomic, health, and relational factors in influencing the well-being of older individuals [27-29]. Contrary to expectations and previous research, this study found that elderly patients with chronic diseases who receive minimum living allowance exhibited significantly lower subjective well-being levels than those not receiving such aid. This deviation from established findings suggests complex underlying dynamics, potentially involving the perceived stigma or inadequacy of the assistance received, highlighting the need to reevaluate the effectiveness and psychological impact of current social support systems on the well-being of older individuals with chronic conditions [30]. The lower subjective well-being among older patients receiving minimum living allowance could be attributed to their position as the most economically disadvantaged group. While the assistance offers some financial relief, it often falls short of their medical needs. Additionally, the public nature of the selection and announcement process for receiving a minimum living allowance could inadvertently harm their self-esteem. Thus, a minimum living allowance in its current form does not substantially enhance their well-being. Authorities should consider raising minimum living allowance standards for this vulnerable group and revising the selection process to make it more sensitive to the psychological well-being of these elderly individuals. Our results revealed that the average Geriatric Depression Scale (GDS-15) score among older patients with chronic diseases is 7.23±2.59, translating to a notably high depression detection rate of 70.9%, which is significantly greater than the findings of Chang et al. and Zhao et al . (44.6%, 45.65%) [11, 31]. There was a significant difference in the subjective well-being of older patients with chronic diseases at different levels of depression (p＜0.001). The more severe the depressive symptoms, the lower the subjective well-being, which is consistent with previous research [32, 33]. Further correlation analysis showed that depression significantly increased negative emotions and negative experiences in older patients with chronic diseases while decreasing positive emotions and positive experiences. Older patients with chronic diseases experiencing depressive symptoms may exhibit a sense of hopelessness and pointlessness toward life. Long-term negative self-evaluation and negative emotions can lead to increased isolation and withdrawal from social activities, reducing their initiative and enthusiasm for various activities [14], which, in turn, can result in reduced interpersonal interactions and impaired access to social support, leading to a significant decrease in positive emotions and positive experiences. This research indicated that the Social Support Rating Scale (SRSS) score of older patients with chronic diseases was 34.96±7.97, slightly surpassing Cao's findings [34]. This increase could be linked to recent government efforts in rural and minority ethnic areas, like precision poverty alleviation and family doctor programs, enhancing economic and medical support. There was a strong association between social support levels and subjective well-being. Significantly, social support was found to bolster positive emotions and experiences while reducing negative ones [33]. This study further revealed that social support markedly enhanced positive emotions and experiences while reducing negative ones among elderly patients with chronic diseases. It is worth noting that the analysis showed that social support had a greater impact on the emotional dimension of subjective well-being than the experience dimension, indicating that the more subjective support is given, the better the resilience becomes, resulting in higher subjective well-being [35, 36]. The mediating effect analysis in our study indicated that social support served as a partial mediator between depression and subjective well-being among older patients with chronic diseases in rural areas, thus verifying H3. This implies that while depression directly affects their well-being, it also exerts a mediating role through social support. Higher levels of social support can mitigate the adverse effects of depression on well-being. This support enhances neuroendocrine and immune system functioning, improves cognitive conditions, reduces negative emotions like depression, and boosts positive feelings, thereby amplifying the sense of well-being in these individuals [37]. Multivariate analysis indicated that objective support does not significantly impact subjective well-being, which is inconsistent with some existing studies. In contrast, subjective support had a pronounced effect on both subjective well-being and depression levels, which aligns more closely with the findings of Liu Y et al[38], suggesting that the emotional and perceived aspects of support have a more critical role in influencing the mental health and overall well-being of individuals than tangible forms of support [39-40]. Objective support, encompassing tangible aids like economic and policy support, contrasts with subjective support, which involves emotional assistance [41]. Recent policy implementations, including precision poverty alleviation and family doctor programs, have increased objective support for older patients with chronic diseases in rural areas, addressing their material needs while elevating their psychological requirements [29]. Life course theory suggests that as older individuals face physical decline and social role changes, their need for psychological comfort grows [42]. Thus, adequate emotional support can enhance their positive emotions, bolster confidence in disease management, foster a sense of belonging and purpose, and potentially alleviate depressive symptoms, thereby improving their subjective well-being. The limitations of the present study are noteworthy and warrant consideration for future research. First, the single-center design, confined to a specific rural ethnic area in Qiannan, Guizhou, limits the generalizability of the reported findings. The unique demographic and cultural context of this region may not reflect the broader population of older individuals with chronic diseases, thereby restricting the applicability of our conclusions to other settings. Second, the relatively small sample size, although substantial for a single-center study, potentially impacts the statistical power and robustness of the findings. This limitation hindered our ability to perform detailed subgroup analyses that could offer deeper insights into specific population segments. Finally, the absence of a control group in our study design significantly limits the ability to draw definitive causal inferences. It is challenging to attribute the observed effects directly to the studied factors without a comparative baseline, such as a group of older individuals without chronic diseases or from different demographic backgrounds. The inclusion of a control group in future studies would provide a more robust framework for comparing and strengthening the conclusions drawn from the research. Addressing these limitations is essential for a more comprehensive understanding of the interplay between mental health, social support, and well-being in elderly populations. In conclusion, older patients with chronic diseases in Rural Ethnic Areas of Qiannan, Guizhou, experienced significant mental health challenges, primarily a high prevalence of depressive symptoms and low levels of subjective well-being. Social support partially mediated the association between depression and subjective well-being in this population. These results underscore the need for comprehensive care strategies that extend beyond physical health to include robust psychological support and community engagement. Declarations Acknowledgements We frankly thank all participants involved in the survey, as well as other staff members on the scene. Funding The research is supported by: National Science Foundation of China(No:82160097); Humanities and Social Science Research Project of Colleges and Universities in Guizhou Province（No:2021ZC092）; Research Fund Project of of Qiannan Nationalities Medical College（No: qnyz202209） Authors and Affiliations School of Clinical Medicine, Guizhou Medical University, Guiyang, 550004, China Zhonglian Li，Tianhui Wang Department of Medicine, Qiannan Medical College for Ethnic Minorities, Duyun, 558003,China Zhonglian Li,Suxian Qin, Yafen Zhu, Quanxiang Zhou, Aijing Yi, Caiyun Mo,Jun Gao Guiyang Public Health Service Center, Guiyang,550004,China Juhai Chen Department of Neurology, The Affiliated Hospital of Guizhou Medical University. Guiyang, 550004,China Zhanhui Feng Department of Comprehensive Ward, The Affiliated Hospital of Guizhou Medical University, Guiyang,550004, China Xiangang Mo Contributions ZLL、ZHF and XGM: contributed to the study design. ZLL、SXQ、YFZ、AJY、CYM、JG、JHC and THW : material preparation and data collection . ZLL and QXZ :Analyzed and interpreted the data.ZLL:Writing-original draft preparation all authors commented on previous versions of the manuscript.ZHF and XGM:Funding acquisition and Supervision.All authors reviewed and approved the final manuscript. corresponding author Correspondence to * Zhanhui Feng E-mail: [email protected] or ** Xiangang Mo E-mail: [email protected] Ethics declarations Competing Interests The authors declare that there are no conflicts of interest in relation to the subject of this study. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Review Committee of Qiannan Nationalities Medical College (Approval No: 2022 Ethics Review No. 202209). Informed consent Informed consent was obtained from all individual participants included in the study. Participants were informed about their freedom for refusal. 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Comparison of Subjective Well-being among Older Patients with Chronic Diseases with Different Characteristics Variable Category N (%) MUNSH score P Gender Female 1052(48.8) 27.00±9.70 0.407 Male 1104(51.2) 27.34±9.26 Age (years) 60-70 1182(54.8) 27.31±9.48 0.742 71-80 630(29.2) 27.07±8.91 ＞80 344(16.0) 26.90±10.44 Education Illiterate 1168(54.2) 26.65±9.71 0.007 Elementary school 702(32.6) 27.44±8.96 Junior high school 208(9.6) 28.99±10.09 High school and above 78(3.6) 27.80±8.08 Marital status Other marital status 680(31.5) 26.03±9.41 <0.001 Married and with a surviving partner 1476(68.5) 27.70±9.47 Living arrangement Living alone 352(16.3) 25.58±10.07 0.001 Not living alone 1804(83.7) 27.48±9.33 Family relationship Poor 66(3.1) 18.00±6.37 <0.001 Average 402(18.6) 22.74±7.78 Quite good 854(39.6) 25.13±9.33 Very good 834(38.7) 32.13±8.11 Number of chronic diseases (types) 1 1120(51.9) 27.08±9.36 0.124 2 662(30.7) 26.84±8.74 ≥3 374(17.4) 28.05±10.94 Disease severity Mild 712(33.0) 29.29±9.45 <0.001 Moderate 1110(51.5) 26.12±9.22 Severe and above 334(15.5) 26.15±9.65 Self-care ability Unable to self-care 134(6.2) 23.30±12.00 <0.001 Partial self-care 826(38.3) 25.92±9.63 Complete self-care 1196(55.5) 28.47±8.80 Family doctor contract No 152(7.1) 20.83±6.08 <0.001 Yes 2004(92.9) 27.66±9.52 Precise poverty alleviation status No 924(42.9) 21.85±8.20 <0.001 Yes 1232(57.1) 31.17±8.34 Minimum living allowance No 1718(79.7) 27.58±9.66 <0.001 Yes 438(20.3) 25.57±8.53 Social activity participation Never participate 453(21.0) 25.00±9.94 <0.001 Occasionally participate 1128(52.3) 26.51±9.02 Sometimes participate 347(16.1) 28.69±9.63 Always participate 228(10.6) 32.48±8.16 MUNSH: the Memorial University of Newfoundland Happiness Scale Table 2. Associations between depression, social support and subjective well-being in Older Patients with Chronic Diseases in the ethnic rural areas of Qiannan Project Classification N (%) MUNSH total score PA NA PE NE GDS-15 No depression 627(29.1) 34.14±7.78 5.56±2.44 1.74±1.83 9.02±3.52 2.67±2.52 Mild depression 1246(57.8) 25.45±8.55 4.97±2.51 4.76±2.86 7.33±3.33 6.09±3.32 Moderate to severe depression 283(13.1) 19.32±6.80 4.06±3.29 6.11±2.61 5.32±3.54 7.94±3.93 P 0.001 <0.001 <0.001 <0.001 <0.001 SSRS Low support 102(4.7) 26.34±9.37 4.78±2.11 4.31±3.12 7.33±3.62 5.57±3.70 Moderate support 1786(82.8) 27.65±9.48 4.85±2.65 4.27±2.99 8.28±3.08 5.10±3.82 High support 268(12.4) 32.55±8.38 6.25±2.43 2.54±2.55 8.79±3.37 3.95±3.13 P <0.001 <0.001 <0.001 <0.001 <0.001 GDS-15: Geriatric Depression Scale; SSRS: the Social Support Rating Scale Table 3. Correlation Analysis of Depression, Social Support, and Subjective Well-being in Older Patients with Chronic Diseases in the ethnic rural areas of Qiannan ( r value) Variable GDS-15 score SSRS score Subjective support Objective support Support utilization MUNSH score PA NA PE NE GDS-15 score 1 SSRS score -0.243 ** 1 Subjective support -0.256 ** 0.878** 1 Objective support -0.177 ** 0.815** 0.509** 1 Support utilization -0.121 ** 0.708** 0.500** 0.432** 1 MUNSH score -0.528 ** 0.280** 0.258** 0.204** 0.214** 1 PA -0.139 ** 0.282** 0.242** 0.199** 0.264** 0.656** 1 NA 0.546 ** -0.245** -0.222** -0.177** -0.197** -0.778** -0.316** 1 PE -0.276 ** 0.173** 0.124** 0.170** 0.132** 0.737** 0.572** -0.289** 1 NE 0.546 ** -0.149** -0.189** -0.071** -0.073** -0.750** -0.155** 0.681** -0.274** 1 GDS-15: Geriatric Depression Scale; SSRS: the Social Support Rating Scale; MUNSH: the Memorial University of Newfoundland Happiness Scale; PA: positive affect; NA: negative affect; PE: positive experiences; NE: negative experiences * * represents P < 0.01. Table 4. Multifactorial Linear Regression Analysis of the Impact of Depression, Social Support, and Demographic Factors on Subjective Well-being in Older Patients with Chronic Diseases from rural areas Variable Standardized coefficient B 95%CI P value LLCI ULCI GDS-15 No depression Ref Mild depression -7.795 -8.437 -7.153 <0.001 Moderate to severe depression -11.631 -12.623 -10.639 <0.001 SSRS Low support Ref Moderate support -2.661 -4.063 -1.259 <0.001 High support -0.833 -2.519 0.854 0.333 Education Illiterate Ref Elementary school 1.487 0.854 2.12 <0.001 Junior high school 1.882 0.901 2.863 <0.001 High school and above 1.359 -0.149 2.867 0.077 Marital status Other marital status Ref Married and with a surviving partner 0.327 -0.300 0.954 0.307 Living arrangement Living alone Ref Not living alone 0.829 0.007 1.651 0.048 Family relationship Poor Ref Average 6.264 4.560 7.968 <0.001 Quite good 6.372 4.726 8.018 <0.001 Very good 9.894 8.225 11.562 <0.001 Disease severity Non-married Ref Moderate -0.893 -1.531 -0.256 0.006 Severe -0.872 -1.747 0.003 0.051 Self-care ability Unable to self-care Ref Partial self-care 1.218 -0.061 2.497 0.062 Complete self-care 1.601 0.324 2.878 0.014 Family doctor contract No Ref Yes 0.464 -0.714 1.642 0.44 Precise poverty alleviation status No Ref Yes 7.149 6.552 7.746 <0.001 Minimum living allowance No Ref Yes -0.268 -0.999 0.462 0.471 Social activity participation Never participate Ref Occasionally participate 1.506 0.714 2.299 <0.001 Sometimes participate 2.352 1.366 3.337 <0.001 Always participate 3.643 2.448 4.838 <0.001 GDS-15: Geriatric Depression Scale; SSRS: the Social Support Rating Scale Table 5. Bootstrap Mediation Analysis of the Mediating Effect of Social Support on Depression and Subjective Well-being in Older Patients with Chronic Diseases (Standardized Coefficients) Effect Path Effect value Effect ratio 95% CI a P value Direct effect Depression→subjective well-being -0.474 89.77% -0.503- -0.443 <0.001 Mediation effect Depression → social support → subjective well-being -0.133 10.23% -0.070- -0.041 <0.001 Total effect -0.528 100% Note: a represents the 95% confidence interval calculated in percentage form. CI: confidence interval 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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15:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4046318/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4046318/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52622435,"identity":"2efc7070-b026-40dc-a4fb-0bf723da33a0","added_by":"auto","created_at":"2024-03-13 17:13:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49689,"visible":true,"origin":"","legend":"\u003cp\u003eModel Pathway Diagram of Depression, Social Support, and Subjective Well-being among Older Patients with Chronic Diseases.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4046318/v1/e942a0623ebac13e6a7c88bd.png"},{"id":52982255,"identity":"9b2fbd36-b065-4fd4-9e9e-66248cd0c314","added_by":"auto","created_at":"2024-03-19 10:29:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1385633,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4046318/v1/88217a66-f807-4420-89fd-21a0be752aa6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Depression and Subjective Well-being in older patients with Chronic Diseases in Rural Ethnic Areas of Qiannan, Guizhou: The Mediating Role of Social Support","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to the 7th national census data, the proportion of elderly individuals aged ≥ 60 in rural areas of China is 23.81%, surpassing the national average by 5.11 % [1, 2]. With the population aging, the incidence of chronic diseases among older individuals has been steadily rising. Over 180 million of the older individuals in China are affected by chronic diseases, accounting for 75.0% of the elderly population [3]. Psychological issues arising from chronic diseases in senior citizens have become increasingly prominent. Older individuals with chronic diseases from rural areas constitute a substantial vulnerable group, so enhancing their physical and mental health is crucial for healthy aging.\u003c/p\u003e\n\u003cp\u003eSubjective Well-being (SWB) is a critical indicator currently used to assess psychological health and life quality in older individuals [4, 5]. According to previous research, individuals with chronic diseases typically experience lower levels of happiness in comparison to those without such conditions, suggesting a potential association between higher subjective well-being and a lower prevalence of chronic diseases [6]. Furthermore, numerous studies emphasize the role of social support as a protective factor for subjective well-being, with positive social support having a crucial role in sustaining happiness among individuals with chronic diseases [7, 8].\u003c/p\u003e\n\u003cp\u003eDepression is a prevalent emotional disorder among older individuals [9]. Such individuals who have endured chronic diseases over the long term are more susceptible to psychological issues like anxiety and depression, which significantly reduce their subjective well-being and overall quality of life [10]. In China, the detection rate of depression in older patients with chronic diseases has been reported to range from 40.2% to 48.86% [11]. Moreover, the prevalence of depression is higher among senior individuals from rural areas compared to their urban counterparts [12, 13]. The coexistence of depression among older individuals with chronic diseases can lead to further deterioration of their health, ultimately resulting in increased disability and mortality rates [10, 16]. Existing studies suggest that individuals grappling with depression often lack a robust social support network, underscoring the role of low social support as a contributing factor to depression [14]. \u003c/p\u003e\n\u003cp\u003eCurrently, there is a substantial body of research, both on a global scale and domestically, that delves into the pairwise relationships among social support, depression, and subjective well-being in older individuals [15-17]. However, studies explicitly examining the triadic relationship between depression, social support, and subjective well-being remain limited. The existing research has predominantly focused on urban or general rural elderly populations, with a notable scarcity of studies on ethnic minority rural elderly individuals grappling with chronic diseases [18, 19]. Based on the abovementioned studies, the following hypotheses were formulated: Hypothesis 1 (H1), in the ethnic rural communities of Qiannan, Guizhou, depression among older patients with chronic diseases is anticipated to have a detrimental impact on their subjective well-being; Hypothesis 2 (H2), in this demographic, social support is expected to positively influence the subjective well-being of these individuals; Hypothesis 3 (H3), social support may act as a mediating factor in the dynamic between symptoms of depression and subjective well-being in this population. \u003c/p\u003e\n\u003cp\u003eThe exploration of these hypotheses aims to unravel the intricate association between mental health, social dynamics, and overall life satisfaction in this unique and under-researched community.\u003c/p\u003e\n\u003cp\u003eThe region of Qiannan, characterized by its multi-ethnic composition, remote rural areas, and relatively limited economic and healthcare resources, necessitates particular attention concerning the psychological well-being of older patients with chronic diseases. Consequently, this study aimed to explore the associations among social support, depression, and subjective well-being in older individuals with chronic diseases from the ethnic rural areas of Qiannan, Guizhou.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy design and patients\u003c/p\u003e\n\u003cp\u003eOlder individuals aged \u0026sup3; 60 with chronic diseases living in the ethnic rural regions of Qiannan, Guizhou, were recruited in this cross-sectional study between June and September 2022. Inclusion criteria were: 1) residents aged 60 and above with a residence history of at least 5 years; 2) individuals registered with local health clinics for at least one chronic disease; 3) willingness to provide informed consent and participate voluntarily. Exclusion criteria were: 1) severe visual or hearing impairment; 2) history of severe mental illness; 3) refusal to participate in the survey. This study obtained ethical approval from the Ethics Review Committee of Qiannan Nationalities Medical College (Approval No: 2022 Ethics Review No. 202209). All participants provided informed consent before the initiation of the study.\u003c/p\u003e\n\u003cp\u003eProcedures\u003c/p\u003e\n\u003cp\u003eThe stratified random cluster sampling method was used to divide the 12 counties and cities into three levels (good, medium, and poor) according to the economic level of Qiannan Prefecture. Two counties and cities were randomly selected from each county and city with the corresponding economic level, two townships (towns) were randomly selected from each selected city (county), and then 3-4 villages were randomly selected from each selected township to investigate the older individuals who met the survey criteria.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;This study was performed by a team of 12 investigators, including licensed physicians and medical students with a certain level of medical knowledge, and it employed a questionnaire survey method. Before the survey, the project leader trained the investigators on the survey content and standardized survey language. During the survey, either centralized interviews or one-on-one household visits were conducted. The investigators explained the purpose and significance of the survey to the participants, obtained their consent, and distributed the questionnaires. Older individuals were guided to self-complete the questionnaires, or the investigators recorded the responses based on the participants\u0026apos; answers. Completed questionnaires were collected promptly, and invalid questionnaires were excluded.\u003c/p\u003e\n\u003cp\u003eSurvey Content and Questionnaires\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;First, the researchers designed a questionnaire containing key demographic details such as gender, age, ethnicity, education, marital status, living arrangement, family relationships, the number and severity of chronic diseases, self-care abilities, participation in collective activities, and socio-economic indicators like being a precision poverty alleviation target and a minimum living allowance.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Short Form Geriatric Depression Scale (GDS-15), initially developed by Sheikh et al. was used to evaluate depressive symptoms among participants. This scale consists of 15 items, scored with 1 point for \u0026quot;yes\u0026quot; and 0 points for \u0026quot;no\u0026quot; [20]; some items are reverse-scored. The total score, ranging from 0 to 15, classifies depression levels into no symptoms (0-5 points), mild symptoms (6-10 points), and moderate to severe symptoms (11-15 points) [21]. The Cronbach\u0026apos;s \u0026alpha; coefficient, i.e., the internal consistency of this scale, was 0.797 in the present study.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Social support was assessed using the Social Support Rating Scale (SSRS), initially developed by Xiao Shuiyuan et al [22]. This scale comprises 10 items distributed across three dimensions: objective support, subjective support, and social support utilization. The total score, ranging from 12 to 66, reflects the overall level of social support, with higher scores indicating stronger support. Social support was categorized into high (\u0026sup3;45), moderate (23-44), and low levels (\u0026pound;22) based on total scores. The reliability of this scale in the study was confirmed by a Cronbach\u0026apos;s \u0026alpha; coefficient of 0.765.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Subjective well-being was measured using the Memorial University of Newfoundland Scale of Happiness (MUNSH) developed by Kozma \u003cem\u003eet al.\u003c/em\u003e [23]. This scale encompasses 24 items across four dimensions. The assessment of subjective well-being involves considering positive affect (PA) and negative affect (NA), as well as positive experiences (PE) and negative experiences (NE). The total score, ranging from 0 to 48, classifies subjective well-being into high (\u0026ge;36), moderate (13-35), and low levels (\u0026le;12). \u0026nbsp; The lower the total score, the lower the level of subjective well-being. The Cronbach\u0026apos;s \u0026alpha; coefficient for this scale in the study was 0.811.\u003c/p\u003e\n\u003cp\u003eStatistical analysis\u003c/p\u003e\n\u003cp\u003eEpidata 3.1 was employed for the dual-check data entry process, while data analysis was conducted using SPSS 23.0\u0026nbsp;(IBM,\u0026nbsp;Armonk,\u0026nbsp;NY,\u0026nbsp;USA) and AMOS 23.0. Categorical data were presented using counts (n) and percentages (%), and continuous data were described with means \u0026plusmn; standard deviations. Group comparisons were performed using t-tests for continuous variables and t/F-tests for categorical variables. Pearson correlation analysis was utilized to investigate the relationships among variables, particularly focusing on the correlation between depression, social support, and subjective well-being. Multiple linear regression analysis was employed to identify factors influencing subjective well-being, incorporating variables with a significance level of\u003cem\u003e\u0026nbsp;\u003c/em\u003eP \u0026lt; 0.05 from the univariate analysis. AMOS 23.0 was used to construct a structural equation model (SEM). Mediation analysis, evaluating the mediating role of social support between depression and subjective well-being, employed Bootstrap resampling (5000 times). Two-sided p-values\u0026lt;0.05 represented statistical significance.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eBasic Characteristics\u003c/p\u003e\n\u003cp\u003eA total of 2,201 subjects completed questionnaires, 45 subjects were excluded as they were incomplete, resulting in 2,156 valid responses and a questionnaire effective recovery rate of 97.96%. There were 1,104 male participants (51.2%). The average age was (71.15±8.04) years, with 1,182 individuals (54.8%) aged 60-70, 630 individuals (29.2%) aged 71-80, and 344 individuals (16.0%) aged over 80. Regarding ethnicity, 1,416 individuals (65.7%) belonged to minority ethnic groups. Concerning education, 1,168 participants (54.2%) were illiterate, 702 (32.6%) had completed primary school, 208 (9.6%) had completed junior high school, and 78 (3.6%) had completed high school or above. There were 1,476 individuals (68.5%) who were married and still living with their partner and 680 individuals (31.5%) with another marital status. The total MUNSH score for rural elderly patients with chronic diseases was (27.17±9.48)，PA was (5.02±2.64), NA was (4.06±3.00), , PE was (7.56±3.60) and NE was (5.35±3.67).A total of 512 (23.7%) individuals had high subjective well-being, 1538 (71.3%) had moderate subjective well-being, and 106 (4.9%) had low subjective well-being. Significant differences in MUNSH scores were observed among different marital statuses, living arrangements, whether they had a family doctor, whether they were precision-targeted for poverty alleviation, whether they were with minimum living allowance, different education, family relationships, severity of illness, ability to perform daily activities, and participation in social activities (all P \u0026lt; 0.05) (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eAssociations between Depression, Social Support, and Subjective Well-being in Older Patients with Chronic Diseases\u003c/p\u003e\n\u003cp\u003eThe GDS-15 score for older patients with chronic diseases was (7.23±2.59), with 627 individuals (29.1%) having no depressive symptoms, 1,246 individuals (57.8%) experiencing mild depressive symptoms, and 283 individuals (13.1%) experiencing moderate to severe depressive symptoms. The SRSS total average score was(34.96±7.97), subjective support was （18.80±4.21）, objective support was （8.63±3.47）, and support utilization was （7.53±2.04）. A total of 102 (4.7%) individuals had low social support, 1786 (82.8%) had moderate social support, and 268 (12.4%) had high social support. Significant differences were observed in MUNSH scores and various dimensions among older patients with different degrees of depression and social support levels (all P \u0026lt; 0.05) (\u003cstrong\u003eTable 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003ePearson correlation analysis results showed that the GDS-15 score was negatively correlated with MUNSH, PA, and NA score (r = -0.528, -0.139, -0.276, P \u0026lt; 0.01) and positively correlated with PE and NE score (r = 0.546, 0.546, P \u0026lt; 0.05). The SSRS score, subjective support score, objective support score, and support utilization score were all negatively correlated with the GDS-15 score (r = -0.243, -0.256, -0.177, -0.121, P \u0026lt; 0.05). The SSRS score was positively correlated with the MUNSH score, PA score, NA score, subjective support score, objective support score, and support utilization score (r = 0.280, 0.282, 0.173, 0.878, 0.815, 0.708, P \u0026lt; 0.05) and negatively correlated with PE score and NE score (r = -0.245, -0.149, P \u0026lt; 0.05). Subjective support was positively correlated with MUNSH score, PA score, and NA score (r = 0.258, 0.242, 0.124, P \u0026lt; 0.05) and negatively correlated with PE score and NE score (r = -0.222, -0.189, P \u0026lt; 0.05). Objective support was positively correlated with MUNSH score, PA score, NA score (r = 0.204, 0.199, 0.170, P \u0026lt; 0.05) and negatively correlated with PE score and NE score (r = -0.177, -0.071, P \u0026lt; 0.05). Support utilization score was positively correlated with MUNSH score, PA score, and NA score (r = 0.214, 0.264, 0.132, P \u0026lt; 0.05) and negatively correlated with PE score and NE score (r = -0.197, -0.073, P \u0026lt; 0.05) (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Multivariate linear regression analysis revealed that mild depression (B = -7.795, 95% CI: -8.437- -7.153, P \u0026lt; 0.001), moderate to severe depression (B = -11.631, 95% CI: -12.623 - -10.639, P \u0026lt; 0.001), moderate social support (B = -2.661, 95% CI: -4.063- \u0026nbsp;-1.259, P \u0026lt; 0.001), primary school education (B = 1.487, 95% CI: 0.854 -\u0026nbsp;2.12, P \u0026lt; 0.001), junior high school education (B = 1.882, 95% CI: 0.901 - 2.863, P \u0026lt; 0.001), fair family relationships (B = 6.264, 95% CI: 4.560 - 7.968, P \u0026lt; 0.001), relatively good family relationships (B = 6.372, 95% CI: 4.726 - 8.018, P \u0026lt; 0.001), very good family relationships (B = 9.894, 95% CI: 8.225 - \u0026nbsp;11.562, P \u0026lt; 0.001), moderate severity of illness (B = -0.893, 95% CI: -1.531 - -0.256, P = 0.006), complete self-care ability (B = 1.601, 95% CI: 0.324 - 2.878, P = 0.014), being a precision-targeted poverty alleviation recipient (B = 7.149, 95% CI: 6.552-7.746, P \u0026lt; 0.001), occasional participation in social activities (B = 1.506, 95% CI: 0.714 - 2.299, P \u0026lt; 0.001), frequent participation in social activities (B = 2.352, 95% CI: 1.366 - 3.337, P \u0026lt; 0.001), and consistently participating in social activities (B = 3.643, 95% CI: 2.448 - 4.838, P \u0026lt; 0.001) were independently associated with subjective well-being (\u003cstrong\u003eTable 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Social Support Mediation Analysis of Depression and Subjective Well-being in Older Patients with Chronic Diseases\u003c/p\u003e\n\u003cp\u003eThe SEM results indicated a good model fit (\u003cem\u003eχ\u003csup\u003e2\u003c/sup\u003e/df\u003c/em\u003e=7.672, GFI=0.994, NFI=0.987, RFI=0.967, IFI=0.989, TLI= 0.971,CFI=0.989, RMSEA=0.056). The path coefficients for the impact of depression symptoms on social support and subjective well-being in older patients with chronic diseases were -0.28 and -0.47, respectively. The path coefficient for the impact of social support on subjective well-being was 0.19. All standardized path coefficients in the model were statistically significant (all P \u0026lt; 0.001) (\u003cstrong\u003eFigure 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The bootstrap test results revealed that the total effect of depression symptoms on subjective well-being in older patients with chronic diseases was -0.528, with a direct effect of -0.474 (95% CI: -0.503 to -0.443), accounting for 89.77% of the total effect. The mediating effect of social support on the association between depression and subjective well-being was -0.133 (95% CI: -0.070 to -0.041), constituting 10.23% of the total effect (\u003cstrong\u003eTable 5\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis\u0026nbsp;study found that older patients with chronic diseases in the rural ethnic areas of Qiannan, Guizhou, had a high prevalence of depressive symptoms and low levels of subjective well-being. Social support partially mediated the association between depression and subjective well-being in this population. This study may provide a theoretical framework for enhancing the physical and mental health and the overall quality of life of older individuals residing in ethnic regions.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The results showed that the overall average subjective well-being score among 2156 older patients with chronic diseases in the rural areas of the southern Guizhou ethnic region was 27.17±9.48, which is lower than the score reported by Fu et al. in their study on older individuals with chronic diseases in Shanxi\u0026nbsp;[24]. This suggests that the subjective well-being of older patients with chronic diseases in the rural areas of the southern Guizhou ethnic region is relatively low, which could be due to the high prevalence of comorbidities, the severity of illnesses, and the high proportion of older patients who were excluded from this survey. In the present study, 48.1% of older individuals had two or more chronic diseases, and 67% of the patients had moderate to severe disease severity. Chronic diseases, characterized by their prolonged and incurable nature, high disability and mortality rates, and the challenges faced by elderly individuals dealing with multiple and severe illnesses, may contribute to increased physical harm and psychological stress. This situation can exacerbate negative emotions, including anxiety and depression, which adversely affect subjective well-being\u0026nbsp;[25]. Additionally, the rural areas of the southern Guizhou ethnic region, characterized by underdeveloped economic, cultural, and medical services, pose further challenges. This survey revealed that 58.5% of the older patients had children working away for extended periods. The restrictions related to the COVID-19 pandemic have significantly reduced the income of migrant workers, leading to diminished family companionship, life care, and emotional and economic support for many elderly individuals with chronic diseases, further impacting their subjective well-being\u0026nbsp;[26].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;This study indicated that subjective well-being was notably lower among older individuals characterized by lower educational attainment, unmarried status, solitary living, strained family relationships, more severe health conditions, limited daily activity capabilities, lack of a dedicated family doctor, low social engagement, and non-eligibility for precision poverty alleviation programs. These observations align with the conclusions of prior studies, reaffirming the interconnectedness of the socioeconomic, health, and relational factors in influencing the well-being of older individuals\u0026nbsp;[27-29]. Contrary to expectations and previous research, this study found that elderly patients with chronic diseases who receive minimum living allowance exhibited significantly lower subjective well-being levels than those not receiving such aid. This deviation from established findings suggests complex underlying dynamics, potentially involving the perceived stigma or inadequacy of the assistance received, highlighting the need to reevaluate the effectiveness and psychological impact of current social support systems on the well-being of older individuals with chronic conditions\u0026nbsp;[30]. The lower subjective well-being among older patients receiving minimum living allowance could be attributed to their position as the most economically disadvantaged group. While the assistance offers some financial relief, it often falls short of their medical needs. Additionally, the public nature of the selection and announcement process for receiving a\u0026nbsp;minimum living allowance\u0026nbsp;could inadvertently harm their self-esteem. Thus, a\u0026nbsp;minimum living allowance\u0026nbsp;in its current form does not substantially enhance their well-being. Authorities should consider raising\u0026nbsp;minimum living allowance\u0026nbsp;standards for this vulnerable group and revising the selection process to make it more sensitive to the psychological well-being of these elderly individuals.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Our results revealed that the average Geriatric Depression Scale (GDS-15) score among older patients with chronic diseases is 7.23±2.59, translating to a notably high depression detection rate of 70.9%, which is significantly greater than the findings of Chang et al. and Zhao et al . (44.6%, 45.65%)\u0026nbsp;[11, 31]. There was a significant difference in the subjective well-being of older patients with chronic diseases at different levels of depression (p＜0.001). The more severe the depressive symptoms, the lower the subjective well-being, which is consistent with previous research\u0026nbsp;[32, 33]. Further correlation analysis showed that depression significantly increased negative emotions and negative experiences in older patients with chronic diseases while decreasing positive emotions and positive experiences. Older patients with chronic diseases experiencing depressive symptoms may exhibit a sense of hopelessness and pointlessness toward life. Long-term negative self-evaluation and negative emotions can lead to increased isolation and withdrawal from social activities, reducing their initiative and enthusiasm for various activities\u0026nbsp;[14], which, in turn, can result in reduced interpersonal interactions and impaired access to social support, leading to a significant decrease in positive emotions and positive experiences.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;This research indicated that the Social Support Rating Scale (SRSS) score of older patients with chronic diseases was 34.96±7.97, slightly surpassing Cao's findings\u0026nbsp;[34]. This increase could be linked to recent government efforts in rural and minority ethnic areas, like precision poverty alleviation and family doctor programs, enhancing economic and medical support. There was a strong association between social support levels and subjective well-being. Significantly, social support was found to bolster positive emotions and experiences while reducing negative ones\u0026nbsp;[33]. This study further revealed that social support markedly enhanced positive emotions and experiences while reducing negative ones among elderly patients with chronic diseases. It is worth noting that the analysis showed that social support had a greater impact on the emotional dimension of subjective well-being than the experience dimension, indicating that the more subjective support is given, the better the resilience becomes, resulting in higher subjective well-being\u0026nbsp;[35, 36].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The mediating effect analysis in our study indicated that social support served as a partial mediator between depression and subjective well-being among older patients with chronic diseases in rural areas, thus verifying H3. This implies that while depression directly affects their well-being, it also exerts a mediating role through social support. Higher levels of social support can mitigate the adverse effects of depression on well-being. This support enhances neuroendocrine and immune system functioning, improves cognitive conditions, reduces negative emotions like depression, and boosts positive feelings, thereby amplifying the sense of well-being in these individuals\u0026nbsp;[37]. Multivariate analysis indicated that objective support does not significantly impact subjective well-being, which is inconsistent with some existing studies. In contrast, subjective support had a pronounced effect on both subjective well-being and depression levels, which aligns more closely with the findings of Liu Y et al[38], suggesting that the emotional and perceived aspects of support have a more critical role in influencing the mental health and overall well-being of individuals than tangible forms of support\u0026nbsp;[39-40]. Objective support, encompassing tangible aids like economic and policy support, contrasts with subjective support, which involves emotional assistance\u0026nbsp;[41]. Recent policy implementations, including precision poverty alleviation and family doctor programs, have increased objective support for older patients with chronic diseases in rural areas, addressing their material needs while elevating their psychological requirements\u0026nbsp;[29]. Life course theory suggests that as older individuals face physical decline and social role changes, their need for psychological comfort grows\u0026nbsp;[42]. Thus, adequate emotional support can enhance their positive emotions, bolster confidence in disease management, foster a sense of belonging and purpose, and potentially alleviate depressive symptoms, thereby improving their subjective well-being.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The limitations of the present study are noteworthy and warrant consideration for future research. First, the single-center design, confined to a specific rural ethnic area in Qiannan, Guizhou, limits the generalizability of the reported findings. The unique demographic and cultural context of this region may not reflect the broader population of older individuals with chronic diseases, thereby restricting the applicability of our conclusions to other settings. Second, the relatively small sample size, although substantial for a single-center study, potentially impacts the statistical power and robustness of the findings. This limitation hindered our ability to perform detailed subgroup analyses that could offer deeper insights into specific population segments. Finally, the absence of a control group in our study design significantly limits the ability to draw definitive causal inferences. It is challenging to attribute the observed effects directly to the studied factors without a comparative baseline, such as a group of older individuals without chronic diseases or from different demographic backgrounds. The inclusion of a control group in future studies would provide a more robust framework for comparing and strengthening the conclusions drawn from the research. Addressing these limitations is essential for a more comprehensive understanding of the interplay between mental health, social support, and well-being in elderly populations. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; In conclusion, older patients with chronic diseases \u0026nbsp;in Rural Ethnic Areas of Qiannan, Guizhou, experienced significant mental health challenges, primarily a high prevalence of depressive symptoms and low levels of subjective well-being. Social support partially mediated the association between depression and subjective well-being in this population. These results underscore the need for comprehensive care strategies that extend beyond physical health to include robust psychological support and community engagement.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe frankly thank all participants involved in the survey, as well as other staff members on the scene.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research is supported by: National Science Foundation of China(No:82160097); Humanities and Social Science Research Project of Colleges and Universities in Guizhou Province（No:2021ZC092）;\u0026nbsp;Research Fund Project of of Qiannan Nationalities Medical College（No: qnyz202209）\u003c/p\u003e\n\u003ch3\u003eAuthors and Affiliations\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eSchool of Clinical Medicine, Guizhou Medical University, Guiyang, 550004, China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhonglian Li，Tianhui Wang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Medicine, Qiannan Medical College for Ethnic Minorities, Duyun,\u0026nbsp;\u003c/strong\u003e \u003cstrong\u003e558003,China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhonglian Li,Suxian Qin, Yafen Zhu, Quanxiang Zhou, Aijing Yi, Caiyun Mo,Jun Gao\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGuiyang Public Health Service Center, Guiyang,550004,China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJuhai Chen\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Neurology, The Affiliated Hospital of Guizhou Medical University. Guiyang, 550004,China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhanhui Feng\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Comprehensive Ward, The Affiliated Hospital of Guizhou Medical University, Guiyang,550004, China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXiangang Mo\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZLL、ZHF and XGM: contributed to the study design. ZLL、SXQ、YFZ、AJY、CYM、JG、JHC and THW : material preparation and data collection . ZLL and QXZ :Analyzed and interpreted the data.ZLL:Writing-original draft preparation all authors commented on previous versions of the manuscript.ZHF and XGM:Funding acquisition and Supervision.All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ecorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to\u003csup\u003e*\u003c/sup\u003eZhanhui Feng \u0026nbsp;E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003eor \u003csup\u003e**\u003c/sup\u003eXiangang Mo \u0026nbsp;E-mail:[email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest in relation to the subject of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Review Committee of Qiannan Nationalities Medical College (Approval No: 2022 Ethics Review No. 202209).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study. Participants were informed about their freedom for refusal.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eThe Seventh National Population Census Bulletin (No. 5)\u0026nbsp;\u003c/strong\u003e.Retrieved from http://www.stats.gov.cn/tjsj/tjgb/rkpcgb/qgrkpcgb/202106/t20210628_1818824.html\u003c/li\u003e\n \u003cli\u003eAkimov A, Gemueva K, Semenova N.(2021). \u003cstrong\u003eThe Seventh Population Census in the PRC: Results and prospects of the country\u0026rsquo;s demographic development\u003c/strong\u003e. \u003cem\u003eHerald of the Russian Academy of Sciences,\u003c/em\u003e\u003cstrong\u003e91\u003c/strong\u003e(6):724-735.https://doi.org/10.1134/S1019331621060083\u003c/li\u003e\n \u003cli\u003eHealth China Action Promotion Committee. \u003cstrong\u003eHealthy China initiative (2019\u0026ndash; 2030)\u003c/strong\u003e.Retrieved from https://www.gov.cn/xinwen/2019-07/15/content_5409694.htm\u003c/li\u003e\n \u003cli\u003eWang, S., 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(2022). \u003cstrong\u003eThe mediating role of social support in the relationship between psychological capital and depression among Chinese emergency physicians\u003c/strong\u003e. \u003cem\u003ePsychology Research and Behavior Management\u003c/em\u003e, 977-990.https://doi.org/10.2147/PRBM.S360611\u003c/li\u003e\n \u003cli\u003eLu J, Zhang C, Xue Y, Mao D, Zheng X, Wu S, Wang X.(2019).\u003cstrong\u003eModerating effect of social support on depression and health promoting lifestyle for Chinese empty nesters: a cross-sectional study\u003c/strong\u003e. \u003cem\u003eJournal of Affective Disorders\u0026nbsp;\u003c/em\u003e, 256:495-508.https://doi.org/10.1016/j.jad.2019.04.003\u003c/li\u003e\n \u003cli\u003eMisbach, I. H, Maslihah, S, \u0026amp; Rusli, I. M.(2023). \u003cstrong\u003eThe Influence of Social Support and Self-esteem on Subjective well-being of High School Student in Bandung City.\u0026nbsp;\u003c/strong\u003e\u003cem\u003eIndonesian Psychological Research,\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;5(1)\u003c/strong\u003e. https://doi.org/10.29080/ipr.v5i1.881\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Comparison of Subjective Well-being among Older Patients\u0026nbsp;with Chronic Diseases with Different Characteristics\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"103%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003eMUNSH score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1052(48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.00\u0026plusmn;9.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1104(51.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.34\u0026plusmn;9.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e60-70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1182(54.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.31\u0026plusmn;9.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e71-80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e630(29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.07\u0026plusmn;8.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e＞80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e344(16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e26.90\u0026plusmn;10.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eEducation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1168(54.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e26.65\u0026plusmn;9.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eElementary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e702(32.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.44\u0026plusmn;8.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e208(9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e28.99\u0026plusmn;10.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eHigh school and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e78(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.80\u0026plusmn;8.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e\u0026nbsp;Other marital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e680(31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e26.03\u0026plusmn;9.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e\u0026nbsp;Married and with a surviving partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1476(68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.70\u0026plusmn;9.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eLiving arrangement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eLiving alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e352(16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e25.58\u0026plusmn;10.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eNot living alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1804(83.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.48\u0026plusmn;9.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eFamily relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e66(3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e18.00\u0026plusmn;6.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e402(18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e22.74\u0026plusmn;7.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eQuite good\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e854(39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e25.13\u0026plusmn;9.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eVery good\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e834(38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e32.13\u0026plusmn;8.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eNumber of chronic diseases (types)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1120(51.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.08\u0026plusmn;9.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e662(30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e26.84\u0026plusmn;8.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e374(17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e28.05\u0026plusmn;10.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eDisease severity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e712(33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e29.29\u0026plusmn;9.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1110(51.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e26.12\u0026plusmn;9.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eSevere and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e334(15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e26.15\u0026plusmn;9.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eSelf-care ability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eUnable to self-care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e134(6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e23.30\u0026plusmn;12.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003ePartial self-care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e826(38.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e25.92\u0026plusmn;9.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eComplete self-care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e1196(55.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e28.47\u0026plusmn;8.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eFamily doctor contract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e152(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e20.83\u0026plusmn;6.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2004(92.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.66\u0026plusmn;9.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003ePrecise poverty alleviation status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e924(42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e21.85\u0026plusmn;8.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1232(57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e31.17\u0026plusmn;8.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;Minimum living allowance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1718(79.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e27.58\u0026plusmn;9.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e438(20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e25.57\u0026plusmn;8.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eSocial activity participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eNever participate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e453(21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e25.00\u0026plusmn;9.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eOccasionally participate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1128(52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e26.51\u0026plusmn;9.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eSometimes participate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e347(16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e28.69\u0026plusmn;9.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eAlways participate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e228(10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e32.48\u0026plusmn;8.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\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\u003eMUNSH: the Memorial University of Newfoundland Happiness Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Associations between depression, social support and subjective well-being in Older Patients with Chronic Diseases in the ethnic rural areas of Qiannan\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"119%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.708333333333332%\" colspan=\"2\"\u003e\n \u003cp\u003eProject\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" colspan=\"2\"\u003e\n \u003cp\u003eClassification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.291666666666667%\" colspan=\"2\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003eMUNSH\u003c/p\u003e\n \u003cp\u003etotal score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003ePA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003ePE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\" colspan=\"2\"\u003e\n \u003cp\u003eNE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0833333333333335%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003eGDS-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" colspan=\"2\"\u003e\n \u003cp\u003eNo depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e627(29.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e34.14\u0026plusmn;7.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"3\"\u003e\n \u003cp\u003e5.56\u0026plusmn;2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u0026plusmn;1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e9.02\u0026plusmn;3.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e2.67\u0026plusmn;2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" colspan=\"2\"\u003e\n \u003cp\u003eMild depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e1246(57.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e25.45\u0026plusmn;8.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"3\"\u003e\n \u003cp\u003e4.97\u0026plusmn;2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" colspan=\"2\"\u003e\n \u003cp\u003e4.76\u0026plusmn;2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e7.33\u0026plusmn;3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e6.09\u0026plusmn;3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" colspan=\"2\"\u003e\n \u003cp\u003eModerate \u0026nbsp;to severe depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e283(13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e19.32\u0026plusmn;6.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"3\"\u003e\n \u003cp\u003e4.06\u0026plusmn;3.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" colspan=\"2\"\u003e\n \u003cp\u003e6.11\u0026plusmn;2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e5.32\u0026plusmn;3.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e7.94\u0026plusmn;3.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003eSSRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" colspan=\"2\"\u003e\n \u003cp\u003eLow support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e102(4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e26.34\u0026plusmn;9.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"3\"\u003e\n \u003cp\u003e4.78\u0026plusmn;2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" colspan=\"2\"\u003e\n \u003cp\u003e4.31\u0026plusmn;3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e7.33\u0026plusmn;3.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e5.57\u0026plusmn;3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" colspan=\"2\"\u003e\n \u003cp\u003eModerate support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e1786(82.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e27.65\u0026plusmn;9.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"3\"\u003e\n \u003cp\u003e4.85\u0026plusmn;2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" colspan=\"2\"\u003e\n \u003cp\u003e4.27\u0026plusmn;2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e8.28\u0026plusmn;3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e5.10\u0026plusmn;3.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" colspan=\"2\"\u003e\n \u003cp\u003eHigh support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e268(12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e32.55\u0026plusmn;8.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"3\"\u003e\n \u003cp\u003e6.25\u0026plusmn;2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" colspan=\"2\"\u003e\n \u003cp\u003e2.54\u0026plusmn;2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e8.79\u0026plusmn;3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e3.95\u0026plusmn;3.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\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\u003eGDS-15: Geriatric Depression Scale; SSRS: the Social Support Rating Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Correlation Analysis of Depression, Social Support, and Subjective Well-being in Older Patients with Chronic Diseases in the ethnic rural areas of Qiannan (\u003cem\u003er\u0026nbsp;\u003c/em\u003evalue)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"118%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"bottom\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" valign=\"bottom\"\u003e\n \u003cp\u003eGDS-15 score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" valign=\"bottom\"\u003e\n \u003cp\u003eSSRS score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" valign=\"bottom\"\u003e\n \u003cp\u003eSubjective support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" valign=\"bottom\"\u003e\n \u003cp\u003eObjective support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" valign=\"bottom\"\u003e\n \u003cp\u003eSupport utilization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eMUNSH score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.125%\" valign=\"bottom\"\u003e\n \u003cp\u003ePA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.208333333333333%\" valign=\"bottom\"\u003e\n \u003cp\u003ePE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\" valign=\"bottom\"\u003e\n \u003cp\u003eNE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"top\"\u003e\n \u003cp\u003eGDS-15 score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"top\"\u003e\n \u003cp\u003eSSRS score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e-0.243\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"top\"\u003e\n \u003cp\u003eSubjective support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e-0.256\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.878**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"top\"\u003e\n \u003cp\u003eObjective support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e-0.177\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.815**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.509**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"top\"\u003e\n \u003cp\u003eSupport utilization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e-0.121\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.708**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.500**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.432**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"top\"\u003e\n \u003cp\u003eMUNSH score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e-0.528\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.280**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.258**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.204**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.214**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"top\"\u003e\n \u003cp\u003ePA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e-0.139\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.282**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.242**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.199**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.264**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.656**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e0.546\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e-0.245**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e-0.222**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e-0.177**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e-0.197**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e-0.778**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003e-0.316**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"top\"\u003e\n \u003cp\u003ePE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e-0.276\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.173**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.124**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.170**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.132**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e0.737**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003e0.572**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e-0.289**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.583333333333334%\" valign=\"top\"\u003e\n \u003cp\u003eNE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e0.546\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e-0.149**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e-0.189**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e-0.071**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e-0.073**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\"\u003e\n \u003cp\u003e-0.750**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" colspan=\"2\"\u003e\n \u003cp\u003e-0.155**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e0.681**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e-0.274**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.166666666666667%\"\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\u003eGDS-15: Geriatric Depression Scale; SSRS: the Social Support Rating Scale; MUNSH: the Memorial University of Newfoundland Happiness Scale; PA: positive affect; NA: negative affect; PE: positive \u0026nbsp;experiences; NE: negative experiences\u003c/p\u003e\n\u003cp\u003e* * represents\u003cem\u003e\u0026nbsp;P\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Multifactorial Linear Regression Analysis of the Impact of Depression, Social Support, and Demographic Factors on Subjective Well-being in Older Patients with Chronic Diseases from rural areas\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"54.08163265306123%\" colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp\u003eVariable\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.734693877551024%\" colspan=\"3\"\u003e\n \u003cp\u003e\u0026nbsp;Standardized coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.545454545454547%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" colspan=\"2\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.454545454545453%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eLLCI \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eULCI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"3\"\u003e\n \u003cp\u003eGDS-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003eNo depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eMild depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e-7.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-8.437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-7.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eModerate to severe depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e-11.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-12.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-10.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"3\"\u003e\n \u003cp\u003eSSRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003eLow support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eModerate support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e-2.661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-4.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-1.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eHigh support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e-0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-2.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"4\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eElementary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e1.487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e1.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e2.863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eHigh school and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e1.359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e2.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"2\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Other marital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Married and with a surviving partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-0.300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"2\"\u003e\n \u003cp\u003eLiving arrangement\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003eLiving alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eNot living alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e0.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e1.651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"4\"\u003e\n \u003cp\u003eFamily relationship\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e6.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e4.560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e7.968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eQuite good\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e6.372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e4.726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e8.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eVery good\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e9.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e8.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e11.562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"3\"\u003e\n \u003cp\u003eDisease severity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003eNon-married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e-0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-1.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e-0.872\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-1.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"3\"\u003e\n \u003cp\u003eSelf-care ability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003eUnable to self-care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003ePartial self-care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e1.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e2.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eComplete self-care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e1.601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e2.878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"2\"\u003e\n \u003cp\u003eFamily doctor contract\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e1.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"2\"\u003e\n \u003cp\u003ePrecise poverty alleviation status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e7.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e6.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e7.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"2\"\u003e\n \u003cp\u003eMinimum living allowance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e-0.268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e-0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e0.471\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.742268041237114%\" rowspan=\"4\"\u003e\n \u003cp\u003eSocial activity participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003eNever participate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eOccasionally participate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e1.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e2.299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eSometimes participate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e2.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e1.366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e3.337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.726027397260275%\"\u003e\n \u003cp\u003eAlways participate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.80821917808219%\"\u003e\n \u003cp\u003e3.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e2.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.068493150684931%\"\u003e\n \u003cp\u003e4.838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.32876712328767%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eGDS-15: Geriatric Depression Scale; SSRS: the Social Support Rating Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u003c/strong\u003e Bootstrap Mediation Analysis of the Mediating Effect of Social Support on Depression and Subjective Well-being in Older Patients with Chronic Diseases (Standardized Coefficients) \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"104%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eEffect\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003ePath\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eEffect value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eEffect ratio\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003e95%\u003cem\u003eCI\u003c/em\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eDirect effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eDepression\u0026rarr;subjective well-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e-0.474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e89.77%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003e-0.503- -0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eMediation effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eDepression \u0026rarr; social support \u0026rarr; subjective well-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e-0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e10.23%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003e-0.070- -0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eTotal effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e-0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u0026nbsp;\u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e represents the 95% confidence interval calculated in percentage form.\u003c/p\u003e\n\u003cp\u003eCI: confidence interval\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":"Depression, Subjective well-being, Social support, Mediating effect;Older patients with chronic diseases, Rural areas in ethnic areas","lastPublishedDoi":"10.21203/rs.3.rs-4046318/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4046318/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To explore the associations among social support, depression, and subjective well-being in older patients with chronic diseases in the rural ethnic regions of Qiannan, Guizhou.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis cross-sectional study enrolled oder patients with chronic diseases in Qiannan, Guizhou between June and September 2022. The social support, depression, and subjective well-being were assessed by a self-developed questionnaire on general information, the social support rating scale (SSRS), the geriatric depression scale (GDS-15), and the Memorial University of Newfoundland Happiness Scale (MUNSH), respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eA total of 2,156 participants (1,104 males; average age of 71.15±8.04) were included. Their mean SSRS and MUNSH scores were 34.96±7.98 and 27.17±9.48, respectively. The GDS-15 score was 7.23±2.59, with 1529 individuals (70.9%) having depressive symptoms. Multivariate linear regression analysis revealed that mild depression (B = -7.795, 95% CI: -8.437 to -7.153, P \u0026lt; 0.001), moderate to severe depression (B = -11.631, 95% CI: -12.623 to -10.639, P \u0026lt; 0.001), and moderate social support (B = -2.661, 95% CI: -4.063 to -1.259, P \u0026lt; 0.001) were independently associated with subjective well-being. The structural equation model results revealed that the total effect of depression symptoms on subjective well-being in elderly patients with chronic diseases is -0.528, with a direct effect of -0.474 (95% CI: -0.503 to -0.443), accounting for 89.77% of the total effect. The mediating effect of social support on the association between depression and subjective well-being is -0.133 (95% CI: -0.070 to -0.041), constituting 10.23% of the total effect.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Older patients with chronic diseases in the rural ethnic areas of Qiannan, Guizhou, exhibited a high prevalence of depressive symptoms and low levels of subjective well-being. Social support partially mediated the association between depression and subjective well-being in this population. Thus, proactive measures are warranted to fortify the social support system for older patients with chronic diseases in Qiannan, Guizhou.\u003c/p\u003e","manuscriptTitle":"Association Between Depression and Subjective Well-being in older patients with Chronic Diseases in Rural Ethnic Areas of Qiannan, Guizhou: The Mediating Role of Social Support","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-13 17:11:58","doi":"10.21203/rs.3.rs-4046318/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":"32cd952e-879d-44fc-8a04-48901d34e26d","owner":[],"postedDate":"March 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-19T10:21:16+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-13 17:11:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4046318","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4046318","identity":"rs-4046318","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}