{"paper_id":"0d7b4d94-d9ed-42b1-b027-3cdec8d231bf","body_text":"Social capital, health status, and sociodemographic factors associated with subjective well-being among older Adults: a comparative study of community dwellings and nursing homes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Social capital, health status, and sociodemographic factors associated with subjective well-being among older Adults: a comparative study of community dwellings and nursing homes Yan Chen, Dahui Wang, Wenhao Chen, EN Xi Zhao, Wanjing Li, Shanshan Zhu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5391128/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Apr, 2025 Read the published version in BMC Public Health → Version 1 posted 11 You are reading this latest preprint version Abstract Background: This study aimed to examine the differences in relationships among social capital components, health status, sociodemographic characteristics, and subjective well-being (SWB) among older adults in institutionalized versus non-institutionalized care environments. Methods: A cross-sectional survey was conducted involving 1,037 older adults aged 65-95 years from nine communities and nine nursing homes across three regions of Zhejiang Province, China. Social capital and SWB were assessed using the Social Capital Scale and the Memorial University of Newfoundland Scale of Happiness (MUNSH), respectively. Propensity score matching (PSM, 1:1, caliper width 0.02) was applied to balance key sociodemographic characteristics and health status between community-dwelling and nursing home residents. Multiple linear regression was utilized to analyze the relationships among social capital components, health status, sociodemographic factors, and SWB in both groups. Results: PSM identified 290 older adults in community dwellings and a comparable group (n = 290) in nursing homes. Comparative analysis showed that nursing home residents demonstrated lower SWB. Multiple linear regression revealed that social connection, trust, and cohesion positively associated with SWB in both groups. However, social participation was significantly linked only with community dwellings residents. Both groups showed a positive relationship between SWB and self-rated health, but no association was found with the number of chronic conditions. Additionally, higher income (≥3000 RMB) and education level (middle) were linked to increased SWB among community-dwelling older adults, whereas family structure—specifically, having no partner and three or more children—negatively impacted SWB in the nursing home group. Conclusion: Social capital and health status showed a strong and consistent association with SWB in both groups. Strengthening social connections, trust, and cohesion, along with maintaining positive health perceptions, is expected to enhance the well-being of older adults, particularly for those in institutional settings. Notably, differences in how sociodemographic factors influence SWB across settings. These findings indicate the necessity for tailored interventions that address the unique needs of each care environment to promote healthier aging experiences. Social capital Subjective well-being Older adults Community dwellings Nursing homes Comparative study Propensity score matching Figures Figure 1 Introduction Subjective well-being (SWB) refers to an individual's overall evaluation of themselves and their life circumstances[1], encompassing both positive and negative emotions[2], and demonstrating stability across different times and situations. A fulfilling life is characterized by a positive assessment from the individual. Pursuing SWB is a fundamental human goal[3], and policymakers are increasingly prioritizing the enhancement of SWB across various populations[4,5]. As global aging intensifies, improving the well-being of older adults has become a key focus of economic[3,6], health[3,7], and social policies[3,6], particularly in aging societies[6]. Social capital is increasingly recognized as a key determinant of Well-being[8,9]. Initially introduced by Bourdieu in 1986, social capital refers to the resources individuals gain from their social networks[10]. Over time, this concept has evolved, with Putnam emphasizing the collective nature of social capital, describing it as networks, norms, and trust that enable cooperation for mutual benefit[11]. Although definitions vary, social capital is generally seen as a multidimensional concept, consisting of structural (quantitative) and cognitive (qualitative) elements. Structural social capital includes participation in social networks and organizations, such as family, friends, and community groups, while cognitive social capital relates to trust, reciprocity, and a sense of belonging. These two aspects have distinct effects on health outcomes: structural social capital impacts physical well-being by offering access to resources and support[12], while cognitive social capital improves emotional and mental health through trust and social cohesion, reducing stress and fostering long-term psychological resilience[13,14]. Our study categorizes social capital into structural (social participation, support, and connection) and cognitive (trust, reciprocity, and cohesion) components and examines their relationships with SWB among older adults. Although social capital is typically found to have a positive impact on health, research on its specific components and their effect on SWB has produced mixed results across different residential[15–17] and geographical context[18,19]. For instance, Studies conducted in urban and rural areas of China, respectively, have shown that social participation has been linked to SWB among urban populations in China, while trust and reciprocity are more strongly associated with SWB in rural areas[15,16]. Conversely, a study conducted in Japan of people residing in earthquake-renovated public housing reported different results: distrust has been tied to lower SWB, but less participation and a lack of reciprocity did not show significant effects[17]. Additionally, regional studies in Austria have found that family contact has a greater impact on SWB in rural areas compared to urban ones[20]. In light of declining birth rates and demographic changes, the occupancy rates of nursing homes are rising in several countries, including China. However, prior research indicates that institutionalized environments often negatively affect the SWB of older adults. Although social capital was ecognized as a key factor in enhancing well-being, yet the relationship between social capital and SWB in institutionalized versus non-institutionalized settings remains unexplored. Although existing literature widely acknowledges the positive impact of social capital on SWB[15–17], most studies have focused on community-dwelling populations, leaving a gap in understanding how social capital functions in institutionalized environments such as nursing homes. Social capital, which includes both structural aspects (e.g., social participation, support networks) and cognitive aspects (e.g., trust, reciprocity), may have different implications depending on the living arrangement. Existing research suggests that the institutional context may amplify or diminish certain social capital components’ effects on SWB. For instance, studies have found that social participation is significantly associated with higher SWB in community settings[21,22], but its role in nursing homes is less clear, where opportunities for participation may be limited[23,24]. Likewise, factors such as trust[25] and cohesion[26,27] may have heightened importance in nursing homes, where residents rely more heavily on institutional care and peer relationships[25]. Furthermore, nursing home residents are often older[18,28], in poor health[18,28], and face different social dynamics, such as the absence of a partner or family[18,29]. These factors can modify the way social capital interacts with their SWB compared to community-dwelling older adults, whose broader social networks and more active lifestyles typically enhance structural social capital. Therefore, it is essential to investigate how both structural and cognitive dimensions of social capital impact SWB across different care environments, and whether specific components like social participation, support, or trust are more influential in institutionalized settings. In addition, Previous studies have shown that individual characteristics such as age[30,31], gender[32], marital status[29], education[33,34], income[35,36], and health status[18,36] also may influence the relationship between social capital and SWB. Given these complexities, accurately assessing the impact of different living arrangements on social capital and SWB requires careful balancing of these sociodemographic and health factors. However, achieving such alignment in real-world settings is challenging and may raise ethical concerns. To address this, our study employed Propensity Score Matching (PSM) to balance key sociodemographic characteristics (age, gender, education, marital status, and income) and health status (chronic diseases, self-rated health) between older adults in community housing and nursing homes. By reducing bias in sample selection, PSM makes observational studies more similar to randomized controlled trials[37,38]. Through this approach, we aimed to compare differences in social capital components, SWB, and the impact of social capital, individual characteristics, and health on SWB in these two settings. This analysis provides a clearer understanding of how different caregiving environments influence older adults' well-being and offers targeted recommendations for improving SWB in both institutional and community settings. Methods Design and participants This was a cross-sectional survey[39] conducted from July to September 2021 in Zhejiang Province, China. A three-stage stratified cluster sampling method was used for data collection. In the first stage, three cities, Hangzhou, Huzhou, and Lishui, were selected according to their high, medium, and low levels of GDP in Zhejiang Province in 2020; in the second stage, three districts were selected according to the level of urbanization in each city; and in the final stage, one community residence and one nursing home were randomly selected in each district. Finally, a total of nine nursing homes and nine communities were selected for the survey. Given our focus on SWB in later life[40], only individuals aged 65–95 years (n = 1037) were included in the analyses. The detailed sample selection process is reported in Figure 1. As of December 2021, the population of individuals aged 60 years and above in Zhejiang Province reached 120.7 million, accounting for 18.70% of the total provincial population. Among them, the population aged 65 and older was 8.57 million, constituting 13.27% of the total provincial population[41]. These figures coincide with the demographic trends in China as a whole, where more than 260 million people are aged 60 years and over (18.70%) and 190 million people are aged 65 years and over (13.50%)[41]. The proportion of the elderly in Zhejiang Province represents, to some extent, the degree of aging in China. Measurement SWB The Memorial University of Newfoundland Scale of Happiness (MUNSH) was used to assess the participants’ SWB. It was created by Kozma et al. and was originally used in Newfoundland in 1980 for individuals aged 65–95[40]. The Chinese version of the MUNSH has been applied to the study of SWB among older adults in China and has shown good reliability and validity[42,43]. It consists of 24 items divided into four subscales: positive affect (PA), negative affect (NA), positive experience (PE), and negative experience (NE). Ten of the 24 items reflected PA and NA, and 14 items reflected PE and NE. Participants were asked if they had experienced the emotions described in the items over the past few months. The MUNSH was scored as follows: Yes = 2; Don't Know = 1; No = 0. Item 19: Present Location = 2; Other Location = 0. Item 23: Satisfied = 2; Not Satisfied = 0. Total score of MUNSH = (PA - NA) + (PE - NE)[40]. Typically, a constant of 24 is added to the total score. Therefore, the final scores ranged from 0 to 48[1,44]. Higher final scores or higher levels indicate a more satisfied state[45]. Cronbach’s α for the MUNSH scale in this study was 0.71. Social capital The social capital scale was based on the World Bank's Social Capital Assessment Tool and previous studies. This scale has been used in studies on older populations in China and has good reliability[39,46]. The Social Capital Scale includes six dimensions: social participation, social support, social connection, trust, cohesion, and reciprocity. Social connection, social participation, and social support reflect structural social capital, whereas trust, cohesion, and reciprocity reflect cognitive social capital. The total scale has 24 items, of which four reflect social participation, four reflect social support, three reflect social connection, three reflect trust, five reflect cohesion, and three reflect reciprocity. The social capital questionnaire used a 5-point Likert scale (1 = never, 2 = rarely, 3 = usually, 4 = often, 5 = more often), in which respondents were asked to rate their level of agreement. The higher the score of each dimension, the better the social capital status of the corresponding dimension[47].The Cronbach’s α of six subscales in this study ranged from 0.762 to 0.885. Covariates The sociodemographic factors included age (65, 75, and 85–95 years old), gender (male vs. female), marital status (married vs. no partner for single, widowed, and divorced), number of children (0–1, 2, and ≥3), and education (primary or below refers to participants with 6 years or fewer of education). Middle refers to those with 7 to 9 years of education. High or above refers to participants with 10 years or more of education, monthly income (less than 3000 RMB vs. 3000 RMB or more), and number of chronic diseases (0, 1, and ≥1). Self-rated health was recorded on a standard 5-point Likert scale (1–5: Very poor–Excellent) [48]. Typically, self-rated health was recoded as a dichotomous variable, with very poor, poor, or fair categorized as one group and good or excellent categorized as another[49]. Propensity score matching (PSM) A matching caliper of 0.02 and 1:1 nearest neighbor matching were used in this matching analysis. The matched samples comprised 290 older adults from community dwellings and 290 from nursing homes, respectively, and were subsequently included in the final outcome comparison. Baseline characteristics (age, gender, marital status, number of children, educational level, monthly income, number of chronic diseases, and self-rated health) were compared between the two groups to assess the balance achieved after matching. Statistical analysis Statistical analyses were performed using IBM SPSS Statistics 26.0 (IBM Corp., Armonk, NY, USA). Count data were presented as n or %. Measurement data were expressed as Mean (SD). T-tests and one-way ANOVA were used to compare the means of continuous variables across different categories. Mann-Whitney U tests and Kruskal-Wallis H statistic (H) were employed to compare the medians of continuous variables across categories. Chi-square tests were used to compare proportions of categorical variables. Multiple linear stepwise regression was employed to analyze the relationships between social capital components, sociodemographic factors, health status, and SWB across different two living environments. The Variance Inflation Factor (VIF) was used to assess multicollinearity among the independent variables in the regression model. All statistical analyses were two-tailed, and significance was set at P ≤ 0.05. Results Characteristics of the studied population Table 1 presents the sociodemographic factors, health status, social capital, and SWB of the matched samples, along with the quality of PSM. The PSM process matched 290 older adults living in community dwellings with a comparable group of 290 residents in nursing homes. After matching, we achieved a good balance for covariates such as age ( 65.9% vs.57.2% aged 65-74), gender (47.2% vs. 44.8% male), marital status (67.2% vs. 69.0% married), number of children (51.7% vs. 44.5% with one or none), education (46.9% vs. 54.8% with primary education or less), monthly income (76.2% vs. 77.6% earning ≥3000 RMB), number of chronic diseases (46.9% vs. 43.1% with one), and self-rated health (50.3% vs. 51.4% good or excellent) between the groups (P > 0.05), indicating a high quality of matching. Regarding social capital, with the exception of social participation, which did not differ significantly between the groups, older adults in community dwellings had higher levels of social support (13.96 vs. 12.16, p < 0.05), social connection (8.88 vs. 8.15, p < 0.05), trust (12.13 vs. 10.78, p < 0.05), reciprocity (11.42 vs. 10.56, p < 0.05), and cohesion (18.94 vs. 17.59, p < 0.05) compared to those in nursing homes. In terms of SWB, older adults in community dwellings reported higher total SWB (35.68 vs. 30.86, p < 0.05), PA (7.34 vs. 4.99, p < 0.05), PE (10.36 vs. 8.37, p < 0.05), and lower NA (2.46 vs. 2.68, p < 0.05) and NE (3.56 vs. 3.82, p < 0.05) compared to their counterparts in nursing homes. Details on the SWB dimensions of the matched samples can be found in Table S1. Table 1. Characteristics of the matched samples and PSM quality Variable Community dwellings (n = 290) Nursing homes (n = 290) Differences between two groups Mean (SD) / N (%) Mean (SD) / N (%) χ 2 / t / U Age (years) 65-74 191 (65.9%) 166 (57.2%) χ 2 = 4.681 75-84 84 (29.0%) 103 (35.5%) 85-95 15 (5.2%) 21 (7.2%) Gender χ 2 = 0.340 Male 137 (47.2%) 130 (44.8%) Female 153 (52.8%) 160 (55.2%) Marital status χ 2 = 0.198 Married 195 (67.2%) 200 (69.0%) No partner 95 (32.8%) 90 (31.0%) Number of children χ 2 = 3.048 0-1 150 (51.7%) 129 (44.5%) 2 104 (35.9%) 120 (41.4%) 3- 36 (12.4%) 41 (14.1%) Educational level χ 2 = 5.087 Primary or below 136 (46.9%) 159 (54.8%) Middle 78 (26.9%) 57 (19.7%) High or above 76 (26.2%) 74 (25.5%) Monthly income level χ 2 = 0.155 0-2999 RMB 69 (23.8%) 65 (22.4%) 3000 RMB or above 221 (76.2%) 225 (77.6%) Number of chronic diseases χ 2 = 0.870 0 63 (21.7%) 66 (22.8%) 1 136 (46.9%) 125 (43.1%) 2- 91 (31.4%) 99 (34.1%) Self-rated health χ 2 = 0.062 Poor, very poor, or fair 144 (49.7%) 141 (48.6%) Good or excellent 146 (50.3%) 149 (51.4%) Social capital Social participation 7.3 (3.8) 7.1 (3.5) t = 0.647 Social support 14.0 (3.7) 12.2 (3.1) U = -6.962 *** Social connection 8.9 (2.5) 8.2 (2.5) t = 3.511 *** Trust 12.1 (2.3) 10.8 (2.6) U = -6.571 *** Reciprocity 11.4 (2.2) 10.6 (2.5) U = -3.971 *** Cohesion 18.9 (3.2) 17.6 (3.6) t = 4.793 *** SWB 35.7 (9.4) 30.9 (7.9) U = -6.724 *** SD=Standard deviation; * p < 0.05, ** p < 0.01, *** p < 0.001. Differences in SWB among older adults across socioeconomic characteristics and health status Table 2 illustrates the variations in SWB among older adults living in community dwellings versus nursing homes across various sociodemographic characteristics. Age demonstrated a significant association with SWB in both groups. Specifically, older adults aged 85–95 reported the highest SWB (42.1) in community dwellings, whereas those residing in nursing homes reported markedly lower SWB (27.5). Gender differences in SWB were evident in community dwellings, where female (36.7) reported higher SWB than male (34.5); however, this disparity was less pronounced in nursing homes (females: 30.3, males: 31.6). The relationships between marital status and health conditions with SWB varied between the two living environments. In community dwellings, older adults without partners, those with multiple chronic diseases (two or more), or those with poorer self-rated health experienced lower SWB, whereas these distinctions were less evident in nursing homes. Additionally, relatively higher educational attainment (community dwellings: middle school 37.9; nursing homes: high school or above 34.0), higher monthly income (community dwellings: ≥3000 RMB 37.0; nursing homes: ≥3000 RMB 32.2), and having fewer children (community dwellings: 0-1 children 36.7; nursing homes: 0-1 children 32.5) were associated with higher SWB in both groups. Table 2. Differences in SWB among older adults with different socioeconomic characteristics and health status Variable Community dwellings (n = 290) Nursing homes (n = 290) Mean (SD) Significance level ( F/H/t/U) Mean (SD) Significance level ( F/H/t/U) Age (years) H = 7.484 * F = 21.513 *** 65-74 35.4 (9.3) 33.3 (7.4) 75-84 35.1 (9.9) 27.5 (7.3) 85-95 42.1 (5.3) 27.5 (7.4) Gender t = -1.996 * U = -1.111 Male 34.5 (9.0) 31.6 (8.3) Female 36.7 (9.7) 30.3 (7.5) Marital status t = 1.633 U = -4.091 *** Married 36.3 (8.9) 32.2 (8.0) No partner a 34.4 (10.3) 28.0 (6.7) Number of children F = 3.368 * H = 37.453 *** 0-1 36.7 (9.4 ) 32.5 (7.2) 2 35.4 (9.0) 31.4 (8.0) 3- 32.2 (9.4) 24.2 (7.9) Educational level b F = 3.812 * F = 9.636 *** Primary or below 34.3 (9.2) 29.3 (7.6) Middle 37.9 (9.5) 31.1 (7.0) High or above 35.8 (9.3) 34.0 (8.1) Monthly income in RMB (US$1 = 6.5RMB) t = -4.481 *** U = -5.824 *** 0-2999 31.4 (8.8) 26.2 (6.5) 3000 or above 37.0 (9.2) 32.2 (7.7) Number of chronic diseases F = 2.055 H = 45.042 *** 0 35.8 (8.8) 35.0 (7.6) 1 36.7 (8.7) 31.8 (7.3) 2- 34.1 (10.6) 26.9 (6.9) Self-rated health t = -1.319 U = -5.484 *** Poor, very poor, or fair 34.9 (9.9) 28.3(6.9) Good or excellent 36.4 (8.8) 33.3 (8.0) SD = Standard deviation; * p < 0.05, ** p < 0.01, *** p < 0.001. The relationship between social capital and SWB Multiple linear stepwise regression models were applied to investigate social capital, health status, and sociodemographic factors of SWB in each studied group (Table 3). Model 1 for the community dwellings group showed a Durbin-Watson value of 1.779 and a VIF range of 1.082–1.954, while for the nursing homes group, the Durbin-Watson value was 1.534 with a VIF range of 1.249–2.314. For Model 2, the community dwellings group had a Durbin-Watson value of 1.859 and a VIF range of 1.084–1.637, whereas the nursing homes group had a Durbin-Watson value of 1.971 and a VIF range of 1.094–1.598. The results indicate that there is generally no issue of multicollinearity in the regression models (VIF < 5), with residual independence being relatively good, as the Durbin-Watson values are close to the ideal value of 2. Overall, the model fit is satisfactory, suggesting a reliable relationship between the predictor variables and SWB. Table 3. Relationships between social capital, health status, socioeconomic characteristics, and SWB Variable Community dwellings (n = 290) Nursing homes (n = 290) Model 1 Model 2 Model 1 Model 2 Social capital Social participation -0.455 ** -0.505 *** 0.083 — Social support 0.270 — -0.021 — Social connection 0.514 * 0.649 ** 0.679 *** 0.702 *** Trust 0.868 ** 0.810 ** 0.630 ** 0.478 ** Reciprocity -0.244 — 0.528 * — Cohesion 0.695 ** 0.614 ** 0.376 * 0.434 *** Age (Ref: 65-74) 75-84 — — — -2.376 ** 85-95 — — — — Gender (Ref: male) Female — — — — Marital status (Ref: married) No partner a — — — -1.987 * Number of children (Ref: 0-1) 2 — — — — 3- — — — -3.943 *** Educational level (Ref: Primary or below) Middle — 2.290 * — — High or above — — — — Monthly income (Ref: 0-2999 RMB ) 3000 RMB or above — 2.829 * — — Number of chronic diseases (Ref: 0) 1 — — — — 2- — — — — Self-rated health (Ref: Poor, very poor, or fair) Good or excellent — 2.248 * — 1.682 * R 2 0.262 0.302 0.360 0.438 △R 2 0.246 0.284 0.346 0.424 F 16.731 17.406 26.492 31.416 p < 0.001 < 0.001 < 0.001 < 0.001 Ref. reference group; (-) Not applicable; US$1 = 6.5RMB; * p < 0.05, ** p < 0.01, *** p < 0.001. Social capital showed a strong and consistent association with SWB in both groups. As shown in Model 1 (unadjusted) and Model 2 (adjusted for covariates), social connection, trust, and cohesion were positively associated with SWB in both groups (p < 0.05). However, social participation was negatively associated with SWB among older adults in community dwellings (β = -0.505, p < 0.001), while this relationship was not significant for those in nursing homes. Additionally, reciprocity and social support did not show significant associations with SWB in either group. The relationship between health status and SWB In Model 2, a consistent association between health status and SWB was observed in both groups. Self-rated good or excellent health was significantly linked to higher SWB among older adults in both community dwellings (β = 2.248, p < 0.05) and nursing homes (β = 1.682, p < 0.05). However, the number of chronic diseases showed no significant association with SWB in either group. The relationship between sociodemographic factors and SWB In Model 2, sociodemographic factors demonstrated differing associations with SWB across the two groups. For older adults in community dwellings, middle-level education (β = 2.290, p < 0.05) and a monthly income of 3000 RMB or above (β = 2.829, p < 0.05) were positively associated with SWB. In contrast, for those in nursing homes, factors such as having no partner (β = −1.987, p < 0.001), being aged 74–84 (β = −2.376, p < 0.05), and having three or more children (β = −3.943, p < 0.001) were negatively associated with SWB. Discussion This study examined the relationships among social capital components, sociodemographic characteristics, health status, and SWB among older adults living in community dwellings and nursing homes. By employing PSM to control for key sociodemographic and health variables, we aimed to isolate the effects of care settings on well-being and to clarify the interconnections among these factors and SWB. Our findings indicate that even after adjusting for sociodemographic and health factors, older adults in nursing homes reported lower SWB compared to those living in community settings. This supports previous research highlighting the adverse effects of institutionalized environments, such as increased social isolation, loneliness, depression, and anxiety[50,51]. The influence of social capital on SWB is typically shaped by factors like gender, age, income, and health[19,52]. Our study found that, after controlling for these variables, social connection, cohesion, and trust consistently correlated positively with SWB in both settings. This underscores the importance of fostering strong social relationships and community trust to enhance the well-being of older adults, regardless of their living situation. However, the institutionalized environment may hinder the development of social capital. We observed that nursing home residents scored lower on various social capital components compared to their community-dwelling counterparts, despite similar levels of social participation. This difference may be attributed to the interaction of older adults' social relationships in these two different care settings. In China, elderly interpersonal relationships often rely on family-based structures[53,54]. Relocation to nursing homes distances older adults from their established networks, forcing them to depend more on formal support systems, which can weaken personal connections, making it more challenging to foster intimate relationships[25]. The restrictive nature of nursing home settings often limits social activities, diminishing existing ties[18] and leading to feelings of isolation. Additionally, the standardized management practices in these facilities can reduce residents' autonomy[23,24], further impacting their sense of belonging and connection[26,27]. Therefore, it is essential to implement strategies that specifically promote intimate relationships among nursing home residents. Creating more opportunities for personal interactions and encouraging deeper connections with family and friends can help counteract the negative effects of institutionalization on social capital. Interestingly, our study did not find a significant association between reciprocity and social support with SWB in institutionalized settings. This could reflect contextual differences in how these factors manifest. Unlike previous studies on rural elderly populations[15,16], our research found that reciprocity did not significantly impact the SWB of urban older adults. Reciprocity, defined as mutual assistance and benefit exchange[55], may not always yield positive emotional experiences[56]. Its influence on SWB is often moderated by factors such as emotional resource enhancement[15,16] and income levels[15,16]. Additionally, the effect of social support on SWB varies based on type and quality. Support from family typically has a stronger positive impact[57], but in our study, we assessed social support solely in terms of material and emotional assistance, without evaluating its type or quality in detail. Furthermore, rural Chinese communities tend to have closer-knit, emotionally connected networks compared to urban settings[15], which may explain why reciprocity and social support did not significantly enhance the SWB of urban older adults in our study. Notably, our study found a negative correlation between social participation and the SWB of older adults in community dwellings. Further analysis indicated that social participation was positively correlated with NA and NE (details can be found in Table S2), suggesting that, in non-institutionalized settings, it may lead to social pressure or conflict. Factors such as socialization barriers[58], fall worry[59], and time constraints[60] could also influence this relationship. Our investigation into the relationship between health status and SWB showed consistent results across both care settings: SWB was positively correlated with self-rated health but not with the number of chronic conditions. This suggests that SWB is influenced more by individuals' perceptions and understanding of their health status than by the objective burden of chronic illness. Even those with chronic conditions can experience high SWB when they manage their health effectively and receive adequate support[61]. Significant differences emerged in how sociodemographic characteristics relate to SWB across care environments. In nursing homes, family structure had a strong impact on SWB, particularly among individuals without partners or those with three or more children, who reported lower SWB. This finding aligns with disengagement theory[62], indicating that limited social networks in nursing homes are insufficient to compensate for the lack of emotional family ties. In contrast, older adults in community settings maintained greater social interactions and family connections, reducing the impact of family structure on their SWB. We also identified a U-shaped relationship between age and SWB in nursing homes, with the 75-84 age group reporting significantly lower SWB compared to the 65-74 age group. This decline may be attributed to health deterioration and role loss during this transitional period, whereas those aged 85 and older tend to have adapted to their care needs and developed better coping mechanisms[63,64]. Among community settings elderly, higher SWB was typically associated with those who had higher incomes and moderate educational attainment. This may have been due to their greater access to resources, social participation, and life opportunities, which allowed them to better meet their daily needs and fulfill social role expectations[65,66]. However, individuals with higher education may have faced greater self-expectations, and if these expectations were unmet, their SWB may have been negatively impacted[67]. In contrast, no significant relationships were found between personal income or education and SWB in nursing home residents, possibly due to standardized living conditions that lessen the impact of socioeconomic factors[68]. Overall, this study highlights the similarities and differences in the relationships between social capital, health status, sociodemographic characteristics, and SWB across institutionalized and non-institutionalized settings. These findings have important implications for policy development, practice, and future research in elderly care and active aging. Limitations This study has several limitations. First, the cross-sectional design limits to conclude the causal relationships between social capital, health status, sociodemographic factors, and SWB. Longitudinal studies are necessary to determine the directionality and causality of these relationships. Second, the data were based on self-reports, which may be subject to recall or reporting bias. Third, although we employed PSM to balance key sociodemographic and health characteristics, residual confounding factors may still influence the observed relationships. For example, unmeasured variables such as psychological resilience or coping strategies could affect the outcomes. Fourth, our study focused on public nursing homes, and the differences between public and private facilities remain unclear. Future research should explore this aspect further. Lastly, we considered social capital components as a collective measure without a detailed analysis of specific dimensions. A more nuanced examination of these dimensions could provide deeper insights into their distinct impacts on SWB. Despite these limitations, this study contributes valuable insights into the associations between social capital, health status, sociodemographic characteristics, and SWB across institutionalized and non-institutionalized settings. Conclusion In conclusion, this study examined how social capital, health status, and sociodemographic factors relate to the SWB of older adults in both community and nursing home settings. Using PSM to balance key characteristics, we aimed to isolate the impact of living arrangements on SWB. Our findings revealed that older adults in nursing homes reported generally lower SWB than those in community settings, highlighting the challenges posed by institutional environments. Social capital—particularly strong social connection, cohesion, and trust—was a critical factor in enhancing SWB, suggesting that supportive social networks are essential regardless of setting. Health status also emerged as an important predictor of SWB, with self-rated health showing a stronger association with SWB than objective health measures like the number of chronic conditions. This emphasizes the role of positive health perceptions in maintaining higher SWB among older adults, even when managing chronic illnesses, underscoring the need for interventions that foster positive health outlooks in this population. Additionally, we observed differences in how sociodemographic factors influence SWB across settings. Family structure played a more significant role in institutionalized settings, with residents without partners or with multiple children experiencing notably lower SWB. In contrast, income and education disparities had a stronger impact on SWB in community settings. These insights suggest that effective interventions must be tailored to the unique characteristics of each care environment. By addressing specific sociodemographic needs, we can create more supportive surroundings that promote healthier and more fulfilling aging experiences for diverse older populations. Abbreviations SWB Subjective well-being PA Positive affect NA Negative affect PE Positive experience NE Negative experience MUNSH Memorial University of Newfoundland Scale of Happiness PSM Propensity score matching Declarations Acknowledgements We give our sincere thanks to staff of community and nursing homes for helping collect data and all respondents for their contribution.. Authors’ contributions YC and DHW contributed to conception and design of the study. WHC, EXZ, and WJL performed the statistical analysis and drafted the original manuscript. SSZ and XLW collected and processed data. YC and DHW reviewed and revised the manuscript. All authors read and approved the final manuscript. Funding This research was supported by Zhejiang Provincial Department of Education (grant Number Y202250035), and the National Natural Science Foundation of China (grant Number 71904037). Availability of data and materials The datasets generated and analysed during the current study are not publicly available due to reasons of sensitivity but are available from the corresponding author on reasonable request. Ethics approval and consent to participate Ethical approval of this study was obtained from the Ethics Committee of Hangzhou Normal University (No.20210002). All methods in our study were performed in accordance with the guidelines and regulations of the Declaration of Helsinki. Informed consent was obtained from all subjects involved in the study. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Han B, Yan B, Zhao N, et al. 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well-being among older Adults: a comparative study of community dwellings and nursing homes\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eSubjective well-being (SWB) refers to an individual\\u0026apos;s overall evaluation of themselves and their life circumstances[1], encompassing both positive and negative emotions[2], and demonstrating stability across different times and situations. A fulfilling life is characterized by a positive assessment from the individual. Pursuing SWB is a fundamental human goal[3], and policymakers are increasingly prioritizing the enhancement of SWB across various populations[4,5]. As global aging intensifies, improving the well-being of older adults has become a key focus of economic[3,6], health[3,7], and social policies[3,6], particularly in aging societies[6].\\u003c/p\\u003e\\n\\u003cp\\u003eSocial capital is increasingly recognized as a key determinant of Well-being[8,9]. Initially introduced by Bourdieu in 1986, social capital refers to the resources individuals gain from their social networks[10].\\u0026nbsp;Over time, this concept has evolved, with Putnam emphasizing the collective nature of social capital, describing it as networks, norms, and trust that enable cooperation for mutual benefit[11].\\u0026nbsp;Although definitions vary, social capital is generally seen as a multidimensional concept, consisting of structural (quantitative) and cognitive (qualitative) elements. Structural social capital includes participation in social networks and organizations, such as family, friends, and community groups, while cognitive social capital relates to trust, reciprocity, and a sense of belonging. These two aspects have distinct effects on health outcomes: structural social capital impacts physical well-being by offering access to resources and support[12], while cognitive social capital improves emotional and mental health through trust and social cohesion, reducing stress and fostering long-term psychological resilience[13,14].\\u003c/p\\u003e\\n\\u003cp\\u003eOur study categorizes social capital into structural (social participation, support, and connection) and cognitive (trust, reciprocity, and cohesion) components and examines their relationships with SWB among older adults. Although social capital is typically found to have a positive impact on health, research on its specific components and their effect on SWB has produced mixed results across different\\u0026nbsp;residential[15\\u0026ndash;17]\\u0026nbsp;and geographical context[18,19]. For instance, Studies conducted in urban and rural areas of China, respectively, have shown that social participation has been linked to SWB among urban populations in China, while trust and reciprocity are more strongly associated with SWB in rural areas[15,16]. Conversely, a study conducted in Japan of people residing in earthquake-renovated public housing reported different results: distrust has been tied to lower SWB, but less participation and a lack of reciprocity did not show significant effects[17]. Additionally, regional studies in Austria have found that family contact has a greater impact on SWB in rural areas compared to urban ones[20].\\u003c/p\\u003e\\n\\u003cp\\u003eIn light of declining birth rates and demographic changes, the occupancy rates of nursing homes are rising in several countries, including China. However, prior research indicates that institutionalized environments often negatively affect the SWB of older adults. Although social capital was ecognized as a key factor in enhancing well-being, yet the relationship between social capital and SWB in institutionalized versus non-institutionalized settings remains unexplored. Although existing literature widely acknowledges the positive impact of social capital on SWB[15\\u0026ndash;17], most studies have focused on community-dwelling populations, leaving a gap in understanding how social capital functions in institutionalized environments such as nursing homes.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eSocial capital, which includes both structural aspects (e.g., social participation, support networks) and cognitive aspects (e.g., trust, reciprocity), may have different implications depending on the living arrangement. Existing research suggests that the institutional context may amplify or diminish certain social capital components\\u0026rsquo; effects on SWB. For instance, studies have found that social participation is significantly associated with higher SWB in community settings[21,22], but its role in nursing homes is less clear, where opportunities for participation may be limited[23,24]. Likewise, factors such as trust[25]\\u0026nbsp;and cohesion[26,27]\\u0026nbsp;may have heightened importance in nursing homes, where residents rely more heavily on institutional care and peer relationships[25]. Furthermore, nursing home residents are often older[18,28], in poor health[18,28], and face different social dynamics, such as the absence of a partner or family[18,29]. These factors can modify the way social capital interacts with their SWB compared to community-dwelling older adults, whose broader social networks and more active lifestyles typically enhance structural social capital. Therefore, it is essential to investigate how both structural and cognitive dimensions of social capital impact SWB across different care environments, and whether specific components like social participation, support, or trust are more influential in institutionalized settings.\\u003c/p\\u003e\\n\\u003cp\\u003eIn addition, Previous studies have shown that individual characteristics such as age[30,31], gender[32], marital status[29], education[33,34], income[35,36], and health status[18,36]\\u0026nbsp;also may influence the relationship between social capital and SWB. Given these complexities, accurately assessing the impact of different living arrangements on social capital and SWB requires careful balancing of these sociodemographic and health factors. However, achieving such alignment in real-world settings is challenging and may raise ethical concerns.\\u003c/p\\u003e\\n\\u003cp\\u003eTo address this, our study employed Propensity Score Matching (PSM) to balance key sociodemographic characteristics (age, gender, education, marital status, and income) and health status (chronic diseases, self-rated health) between older adults in community housing and nursing homes. By reducing bias in sample selection, PSM makes observational studies more similar to randomized controlled trials[37,38]. Through this approach, we aimed to compare differences in social capital components, SWB, and the impact of social capital, individual characteristics, and health on SWB in these two settings. This analysis provides a clearer understanding of how different caregiving environments influence older adults\\u0026apos; well-being and offers targeted recommendations for improving SWB in both institutional and community settings.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eDesign and participants\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis was a cross-sectional survey[39]\\u0026nbsp;conducted from July to September 2021 in Zhejiang Province, China. A three-stage stratified cluster sampling method was used for data collection. In the first stage, three cities, Hangzhou, Huzhou, and Lishui, were selected according to their high, medium, and low levels of GDP in Zhejiang Province in 2020; in the second stage, three districts were selected according to the level of urbanization in each city; and in the final stage, one community residence and one nursing home were randomly selected in each district. Finally, a total of nine nursing homes and nine communities were selected for the survey. Given our focus on SWB in later life[40], only individuals aged 65–95 years (n = 1037) were included in the analyses. The detailed sample selection process is reported in\\u0026nbsp;Figure 1.\\u003c/p\\u003e\\n\\u003cp\\u003eAs of December 2021, the population of individuals aged 60 years and above in Zhejiang Province reached 120.7 million, accounting for 18.70% of the total provincial population. Among them, the population aged 65 and older was 8.57 million, constituting 13.27% of the total provincial population[41]. These figures coincide with the demographic trends in China as a whole, where more than 260 million people are aged 60 years and over (18.70%) and 190 million people are aged 65 years and over (13.50%)[41]. The proportion of the elderly in Zhejiang Province represents, to some extent, the degree of aging in China.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eMeasurement\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSWB\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe Memorial University of Newfoundland Scale of Happiness (MUNSH) was used to assess the participants’ SWB. It was created by Kozma et al. and was originally used in Newfoundland in 1980 for individuals aged 65–95[40]. The Chinese version of the MUNSH has been applied to the study of SWB among older adults in China and has shown good reliability and validity[42,43]. It consists of 24 items divided into four subscales: positive affect (PA), negative affect (NA), positive experience (PE), and negative experience (NE). Ten of the 24 items reflected PA and NA, and 14 items reflected PE and NE. Participants were asked if they had experienced the emotions described in the items over the past few months. The MUNSH was scored as follows: Yes = 2; Don't Know = 1; No = 0. Item 19: Present Location = 2; Other Location = 0. Item 23: Satisfied = 2; Not Satisfied = 0. Total score of MUNSH = (PA - NA) + (PE - NE)[40]. Typically, a constant of 24 is added to the total score. Therefore, the final scores ranged from 0 to 48[1,44]. Higher final scores or higher levels indicate a more satisfied state[45]. Cronbach’s α for the MUNSH scale in this study was 0.71.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSocial capital\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe social capital scale was based on the World Bank's Social Capital Assessment Tool and previous studies. This scale has been used in studies on older populations in China and has good reliability[39,46]. The Social Capital Scale includes six dimensions: social participation, social support, social connection, trust, cohesion, and reciprocity. Social connection, social participation, and social support reflect structural social capital, whereas trust, cohesion, and reciprocity reflect cognitive social capital. The total scale has 24 items, of which four reflect social participation, four reflect social support, three reflect social connection, three reflect trust, five reflect cohesion, and three reflect reciprocity. The social capital questionnaire used a 5-point Likert scale (1 = never, 2 = rarely, 3 = usually, 4 = often, 5 = more often), in which respondents were asked to rate their level of agreement. The higher the score of each dimension, the better the social capital status of the corresponding dimension[47].The Cronbach’s α of six subscales in this study ranged from 0.762 to 0.885.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eCovariates\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe sociodemographic factors included age (65, 75, and 85–95 years old), gender (male vs. female), marital status (married vs. no partner for single, widowed, and divorced), number of children (0–1, 2, and ≥3), and education (primary or below refers to participants with 6 years or fewer of education). Middle refers to those with 7 to 9 years of education. High or above refers to participants with 10 years or more of education, monthly income (less than 3000 RMB vs. 3000 RMB or more), and number of chronic diseases (0, 1, and ≥1). Self-rated health was recorded on a standard 5-point Likert scale (1–5: Very poor–Excellent) [48]. Typically, self-rated health was recoded as a dichotomous variable, with very poor, poor, or fair categorized as one group and good or excellent categorized as another[49].\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003ePropensity score matching (PSM)\\u0026nbsp;\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eA matching caliper of 0.02 and 1:1 nearest neighbor matching were used in this matching analysis. The matched samples comprised 290 older adults from community dwellings and 290 from nursing homes, respectively, and were subsequently included in the final outcome comparison. Baseline characteristics (age, gender, marital status, number of children, educational level, monthly income, number of chronic diseases, and self-rated health) were compared between the two groups to assess the balance achieved after matching.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eStatistical analysis\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eStatistical analyses were performed using IBM SPSS Statistics 26.0 (IBM Corp., Armonk, NY, USA). Count data were presented as n or %. Measurement data were expressed as Mean (SD). T-tests and one-way ANOVA were used to compare the means of continuous variables across different categories. Mann-Whitney U tests and Kruskal-Wallis H statistic (H) were employed to compare the medians of continuous variables across categories. Chi-square tests were used to compare proportions of categorical variables. Multiple linear stepwise regression was employed to analyze the relationships between social capital components, sociodemographic factors, health status, and SWB across different two living environments. The Variance Inflation Factor (VIF) was used to assess multicollinearity among the independent variables in the regression model. All statistical analyses were two-tailed, and significance was set at P ≤ 0.05.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eCharacteristics of the studied population\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTable 1\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003epresents the sociodemographic factors, health status, social capital, and SWB of the matched samples, along with the quality of PSM. The PSM process matched 290 older adults living in community dwellings with a comparable group of 290 residents in nursing homes. After matching, we achieved a good balance for covariates such as age (\\u0026nbsp;65.9% vs.57.2% aged\\u0026nbsp;65-74), gender (47.2% vs. 44.8% male), marital status (67.2% vs. 69.0% married), number of children (51.7% vs. 44.5% with one or none), education (46.9% vs. 54.8% with primary education or less), monthly income (76.2% vs. 77.6% earning \\u0026ge;3000 RMB), number of chronic diseases (46.9% vs. 43.1% with one), and self-rated health (50.3% vs. 51.4% good or excellent) between the groups (P \\u0026gt; 0.05), indicating a high quality of matching.\\u003c/p\\u003e\\n\\u003cp\\u003eRegarding social capital, with the exception of social participation, which did not differ significantly between the groups, older adults in community dwellings had higher levels of social support (13.96 vs. 12.16, p \\u0026lt; 0.05), social connection (8.88 vs. 8.15, p \\u0026lt; 0.05), trust (12.13 vs. 10.78, p \\u0026lt; 0.05), reciprocity (11.42 vs. 10.56, p \\u0026lt; 0.05), and cohesion (18.94 vs. 17.59, p \\u0026lt; 0.05) compared to those in nursing homes.\\u003c/p\\u003e\\n\\u003cp\\u003eIn terms of SWB, older adults in community dwellings reported higher total SWB (35.68 vs. 30.86, p \\u0026lt; 0.05), PA (7.34 vs. 4.99, p \\u0026lt; 0.05), PE (10.36 vs. 8.37, p \\u0026lt; 0.05), and lower NA (2.46 vs. 2.68, p \\u0026lt; 0.05) and NE (3.56 vs. 3.82, p \\u0026lt; 0.05) compared to their counterparts in nursing homes. Details on the SWB dimensions of the matched samples can be found in\\u0026nbsp;Table S1.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 1.\\u0026nbsp;\\u003c/strong\\u003eCharacteristics of the matched samples and PSM quality\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"99%\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariable\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCommunity dwellings (n = 290)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNursing homes (n = 290)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eDifferences between two \\u0026nbsp; \\u0026nbsp; groups\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMean (SD) / N (%)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMean (SD) / N (%)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026chi;\\u003csup\\u003e2\\u003c/sup\\u003e / t / U\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eAge (years)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e65-74\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e191 (65.9%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e166 (57.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026chi;\\u003csup\\u003e2\\u0026nbsp;\\u003c/sup\\u003e=\\u0026nbsp;4.681\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e75-84\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e84 (29.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e103 (35.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e\\u0026nbsp;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e85-95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e15 (5.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e21 (7.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e\\u0026nbsp;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eGender\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026chi;\\u003csup\\u003e2\\u0026nbsp;\\u003c/sup\\u003e=\\u0026nbsp;0.340\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eMale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e137 (47.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e130 (44.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e153 (52.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e160 (55.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMarital status\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026chi;\\u003csup\\u003e2\\u0026nbsp;\\u003c/sup\\u003e=\\u0026nbsp;0.198\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eMarried\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e195 (67.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e200 (69.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eNo partner\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e95 (32.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e90 (31.0%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNumber of children\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026chi;\\u003csup\\u003e2\\u0026nbsp;\\u003c/sup\\u003e=\\u0026nbsp;3.048\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e0-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e150 (51.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e129 (44.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e\\u0026nbsp;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e104 (35.9%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e120 (41.4%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e\\u0026nbsp;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e3-\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e36 (12.4%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e41 (14.1%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e\\u0026nbsp;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eEducational level\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026chi;\\u003csup\\u003e2\\u0026nbsp;\\u003c/sup\\u003e=\\u0026nbsp;5.087\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003ePrimary or below\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e136 (46.9%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e159 (54.8%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eMiddle\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e78 (26.9%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e57 (19.7%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eHigh or above\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e76 (26.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e74 (25.5%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMonthly income level\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026chi;\\u003csup\\u003e2\\u0026nbsp;\\u003c/sup\\u003e=\\u0026nbsp;0.155\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e0-2999 RMB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e69 (23.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e65 (22.4%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e3000 RMB or above\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e221 (76.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e225 (77.6%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNumber of chronic diseases\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026chi;\\u003csup\\u003e2\\u0026nbsp;\\u003c/sup\\u003e= 0.870\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e63 (21.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e66 (22.8%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e136 (46.9%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e125 (43.1%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e2-\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e91 (31.4%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e99 (34.1%) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSelf-rated health\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026chi;\\u003csup\\u003e2\\u0026nbsp;\\u003c/sup\\u003e= 0.062\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003ePoor, very poor, or fair\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e144 (49.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e141 (48.6%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eGood or excellent\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e146 (50.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e149 (51.4%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSocial capital\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eSocial participation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e7.3 (3.8)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e7.1 (3.5) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003et\\u003c/em\\u003e = 0.647\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eSocial support\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e14.0 (3.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e12.2 (3.1) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eU\\u003c/em\\u003e = -6.962\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eSocial connection\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e8.9 (2.5)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e8.2 (2.5) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003et\\u003c/em\\u003e = 3.511\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eTrust\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e12.1 (2.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e10.8 (2.6) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eU\\u003c/em\\u003e = -6.571\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eReciprocity\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e11.4 (2.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e10.6 (2.5) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eU\\u003c/em\\u003e = -3.971\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003eCohesion\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e18.9 (3.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e17.6 (3.6) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003et\\u003c/em\\u003e = 4.793\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 36%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSWB\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23%;\\\"\\u003e\\n \\u003cp\\u003e35.7 (9.4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22%;\\\"\\u003e\\n \\u003cp\\u003e30.9 (7.9) \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 17%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eU\\u003c/em\\u003e = -6.724\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eSD=Standard deviation; \\u003csup\\u003e*\\u003c/sup\\u003e\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.05, \\u003csup\\u003e**\\u003c/sup\\u003e\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.01, \\u003csup\\u003e***\\u003c/sup\\u003e\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eDifferences in SWB among older adults across socioeconomic characteristics and health status\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTable 2 illustrates the variations in SWB among older adults living in community dwellings versus nursing homes across various sociodemographic characteristics. Age demonstrated a significant association with SWB in both groups. Specifically, older adults aged 85\\u0026ndash;95 reported the highest SWB (42.1) in community dwellings, whereas those residing in nursing homes reported markedly lower SWB (27.5). Gender differences in SWB were evident in community dwellings, where female (36.7) reported higher SWB than male (34.5); however, this disparity was less pronounced in nursing homes (females: 30.3, males: 31.6). The relationships between marital status and health conditions with SWB varied between the two living environments. In community dwellings, older adults without partners, those with multiple chronic diseases (two or more), or those with poorer self-rated health experienced lower SWB, whereas these distinctions were less evident in nursing homes. Additionally, relatively higher educational attainment (community dwellings: middle school 37.9; nursing homes: high school or above 34.0), higher monthly income (community dwellings: \\u0026ge;3000 RMB 37.0; nursing homes: \\u0026ge;3000 RMB 32.2), and having fewer children (community dwellings: 0-1 children 36.7; nursing homes: 0-1 children 32.5) were associated with higher SWB in both groups.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 2.\\u0026nbsp;\\u003c/strong\\u003eDifferences in SWB among older adults with different socioeconomic characteristics and health status\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"99%\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariable\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCommunity dwellings (n = 290)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNursing homes (n = 290)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMean (SD)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSignificance level (\\u003c/strong\\u003e\\u003cstrong\\u003eF/H/t/U)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMean (SD)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSignificance level (\\u003c/strong\\u003e\\u003cstrong\\u003eF/H/t/U)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eAge (years)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eH\\u0026nbsp;\\u003c/em\\u003e= 7.484\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eF\\u0026nbsp;\\u003c/em\\u003e= 21.513\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e65-74\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e35.4 (9.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e33.3 (7.4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e75-84\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e35.1 (9.9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e27.5 (7.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e85-95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e42.1 (5.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e27.5 (7.4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eGender\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003et\\u0026nbsp;\\u003c/em\\u003e= -1.996\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eU\\u0026nbsp;\\u003c/em\\u003e= -1.111\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003eMale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e34.5 (9.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e31.6 (8.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e36.7 (9.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e30.3 (7.5)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMarital status\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003et\\u0026nbsp;\\u003c/em\\u003e= 1.633\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eU\\u0026nbsp;\\u003c/em\\u003e= -4.091\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003eMarried\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e36.3 (8.9)\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e32.2 (8.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003eNo partner \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e34.4 (10.3)\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e28.0 (6.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNumber of children\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eF\\u0026nbsp;\\u003c/em\\u003e= 3.368\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eH\\u0026nbsp;\\u003c/em\\u003e= 37.453\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e0-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e36.7 (9.4 )\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e32.5 (7.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e35.4 (9.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e31.4 (8.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e3-\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e32.2 (9.4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e24.2 (7.9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eEducational level \\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eF\\u0026nbsp;\\u003c/em\\u003e= 3.812\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eF\\u0026nbsp;\\u003c/em\\u003e= 9.636\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003ePrimary or below\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e34.3 (9.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e29.3 (7.6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003eMiddle\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e37.9 (9.5)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e31.1 (7.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003eHigh or above\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e35.8 (9.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e34.0 (8.1)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMonthly income in RMB (US$1 = 6.5RMB)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003et\\u0026nbsp;\\u003c/em\\u003e= -4.481\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eU\\u0026nbsp;\\u003c/em\\u003e= -5.824\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e0-2999 \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e31.4 (8.8)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e26.2 (6.5)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e3000 or above\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e37.0 (9.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e32.2 (7.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNumber of chronic diseases\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eF\\u0026nbsp;\\u003c/em\\u003e= 2.055\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eH\\u0026nbsp;\\u003c/em\\u003e= 45.042\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e35.8 (8.8)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e35.0 (7.6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e36.7 (8.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e31.8 (7.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e2-\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e34.1 (10.6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e26.9 (6.9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSelf-rated health\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003et\\u0026nbsp;\\u003c/em\\u003e= -1.319\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eU\\u0026nbsp;\\u003c/em\\u003e= -5.484\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003ePoor, very poor, or fair\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e34.9 (9.9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e28.3(6.9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 33%;\\\"\\u003e\\n \\u003cp\\u003eGood or excellent\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 15%;\\\"\\u003e\\n \\u003cp\\u003e36.4 (8.8)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 14%;\\\"\\u003e\\n \\u003cp\\u003e33.3 (8.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19%;\\\"\\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\\u003eSD = Standard deviation; \\u003csup\\u003e*\\u003c/sup\\u003e\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.05, \\u003csup\\u003e**\\u003c/sup\\u003e\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.01, \\u003csup\\u003e***\\u003c/sup\\u003e\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eThe relationship between social capital and SWB\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eMultiple linear stepwise regression models were applied to investigate social capital, health status, and sociodemographic factors of SWB in each studied group (Table 3). Model 1 for the community dwellings group showed a Durbin-Watson value of 1.779 and a VIF range of 1.082\\u0026ndash;1.954, while for the nursing homes group, the Durbin-Watson value was 1.534 with a VIF range of 1.249\\u0026ndash;2.314. For Model 2, the community dwellings group had a Durbin-Watson value of 1.859 and a VIF range of 1.084\\u0026ndash;1.637, whereas the nursing homes group had a Durbin-Watson value of 1.971 and a VIF range of 1.094\\u0026ndash;1.598. The results indicate that there is generally no issue of multicollinearity in the regression models (VIF \\u0026lt; 5), with residual independence being relatively good, as the Durbin-Watson values are close to the ideal value of 2. Overall, the model fit is satisfactory, suggesting a reliable relationship between the predictor variables and SWB.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 3.\\u003c/strong\\u003e Relationships between social capital, health status, socioeconomic characteristics, and SWB\\u003c/p\\u003e\\n\\u003cdiv\\u003e\\n \\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"99%\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariable\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 27%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCommunity dwellings (n = 290)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 25%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNursing homes (n = 290)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003eModel 1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003eModel 2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003eModel 1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003eModel 2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSocial capital\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eSocial participation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e-0.455\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e-0.505\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.083\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eSocial support\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.270\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e-0.021\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eSocial connection\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.514\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.649\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.679\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.702\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eTrust\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.868\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.810\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.630\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.478\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eReciprocity\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e-0.244\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.528\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eCohesion\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.695\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.614\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.376\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.434\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eAge (Ref: 65-74)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e75-84\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e-2.376\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e85-95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eGender (Ref: male)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMarital status (Ref: married)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eNo partner \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e-1.987\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNumber of children (Ref: 0-1)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e3-\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e-3.943\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eEducational level (Ref: Primary or below)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eMiddle\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e2.290\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eHigh or above\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMonthly income (Ref: 0-2999 RMB )\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e3000 RMB or above\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e2.829\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNumber of chronic diseases (Ref: 0)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e2-\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSelf-rated health (Ref: Poor, very poor, or fair)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003eGood or excellent\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e2.248\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026mdash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e1.682\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eR\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.262\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.302\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.360\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.438\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e△R\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.246\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e0.284\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.346\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e0.424\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eF\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e16.731\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e17.406\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e26.492\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e31.416\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003ep\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt; 0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12%;\\\"\\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\\u003eRef. reference group; (-) Not applicable; US$1 = 6.5RMB; \\u003csup\\u003e*\\u003c/sup\\u003e\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.05, \\u003csup\\u003e**\\u003c/sup\\u003e\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.01, \\u003csup\\u003e***\\u003c/sup\\u003e\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001.\\u003c/p\\u003e\\n\\u003cp\\u003eSocial capital showed a strong and consistent association with SWB in both groups. As shown in Model 1 (unadjusted) and Model 2 (adjusted for covariates), social connection, trust, and cohesion were positively associated with SWB in both groups (p \\u0026lt; 0.05). However, social participation was negatively associated with SWB among older adults in community dwellings (\\u0026beta; = -0.505, p \\u0026lt; 0.001), while this relationship was not significant for those in nursing homes. Additionally, reciprocity and social support did not show significant associations with SWB in either group.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eThe relationship between health status and SWB\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eIn Model 2, a consistent association between health status and SWB was observed in both groups. Self-rated good or excellent health was significantly linked to higher SWB among older adults in both community dwellings (\\u0026beta; = 2.248, p \\u0026lt; 0.05) and nursing homes (\\u0026beta; = 1.682, p \\u0026lt; 0.05). However, the number of chronic diseases showed no significant association with SWB in either group.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eThe relationship between sociodemographic factors and SWB\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eIn Model 2, sociodemographic factors demonstrated differing associations with SWB across the two groups. For older adults in community dwellings, middle-level education (\\u0026beta; = 2.290, p \\u0026lt; 0.05) and a monthly income of 3000 RMB or above (\\u0026beta; = 2.829, p \\u0026lt; 0.05) were positively associated with SWB. In contrast, for those in nursing homes, factors such as having no partner (\\u0026beta; = \\u0026minus;1.987, p \\u0026lt; 0.001), being aged 74\\u0026ndash;84 (\\u0026beta; = \\u0026minus;2.376, p \\u0026lt; 0.05), and having three or more children (\\u0026beta; = \\u0026minus;3.943, p \\u0026lt; 0.001) were negatively associated with SWB.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study examined the relationships among social capital components, sociodemographic characteristics, health status, and SWB among older adults living in community dwellings and nursing homes. By employing PSM to control for key sociodemographic and health variables, we aimed to isolate the effects of care settings on well-being and to clarify the interconnections among these factors and SWB.\\u003c/p\\u003e\\n\\u003cp\\u003eOur findings indicate that even after adjusting for sociodemographic and health factors, older adults in nursing homes reported lower SWB compared to those living in community settings. This supports previous research highlighting the adverse effects of institutionalized environments, such as increased social isolation, loneliness, depression, and anxiety[50,51].\\u003c/p\\u003e\\n\\u003cp\\u003eThe influence of social capital on SWB is typically shaped by factors like gender, age, income, and health[19,52]. Our study found that, after controlling for these variables, social connection, cohesion, and trust consistently correlated positively with SWB in both settings. This underscores the importance of fostering strong social relationships and community trust to enhance the well-being of older adults, regardless of their living situation.\\u003c/p\\u003e\\n\\u003cp\\u003eHowever, the institutionalized environment may hinder the development of social capital. We observed that nursing home residents scored lower on various social capital components compared to their community-dwelling counterparts, despite similar levels of social participation. This difference may be attributed to the interaction of older adults\\u0026apos; social relationships in these two different care settings. In China, elderly interpersonal relationships often rely on family-based structures[53,54]. Relocation to nursing homes distances older adults from their established networks, forcing them to depend more on formal support systems, which can weaken personal connections, making it more challenging to foster intimate relationships[25]. The restrictive nature of nursing home settings often limits social activities, diminishing existing ties[18]\\u0026nbsp;and leading to feelings of isolation. Additionally, the standardized management practices in these facilities can reduce residents\\u0026apos; autonomy[23,24], further impacting their sense of belonging and connection[26,27]. Therefore, it is essential to implement strategies that specifically promote intimate relationships among nursing home residents. Creating more opportunities for personal interactions and encouraging deeper connections with family and friends can help counteract the negative effects of institutionalization on social capital.\\u003c/p\\u003e\\n\\u003cp\\u003eInterestingly, our study did not find a significant association between reciprocity and social support with SWB in institutionalized settings. This could reflect contextual differences in how these factors manifest. Unlike previous studies on rural elderly populations[15,16], our research found that reciprocity did not significantly impact the SWB of urban older adults. Reciprocity, defined as mutual assistance and benefit exchange[55], may not always yield positive emotional experiences[56]. Its influence on SWB is often moderated by factors such as emotional resource enhancement[15,16]\\u0026nbsp;and income levels[15,16].\\u003c/p\\u003e\\n\\u003cp\\u003eAdditionally, the effect of social support on SWB varies based on type and quality. Support from family typically has a stronger positive impact[57], but in our study, we assessed social support solely in terms of material and emotional assistance, without evaluating its type or quality in detail. Furthermore, rural Chinese communities tend to have closer-knit, emotionally connected networks compared to urban settings[15], which may explain why reciprocity and social support did not significantly enhance the SWB of urban older adults in our study.\\u003c/p\\u003e\\n\\u003cp\\u003eNotably, our study found a negative correlation between social participation and the SWB of older adults in community dwellings. Further analysis indicated that social participation was positively correlated with NA and NE (details can be found in\\u0026nbsp;Table S2), suggesting that, in non-institutionalized settings, it may lead to social pressure or conflict. Factors such as socialization barriers[58], fall worry[59], and time constraints[60]\\u0026nbsp;could also influence this relationship.\\u003c/p\\u003e\\n\\u003cp\\u003eOur investigation into the relationship between health status and SWB showed consistent results across both care settings: SWB was positively correlated with self-rated health but not with the number of chronic conditions. This suggests that SWB is influenced more by individuals\\u0026apos; perceptions and understanding of their health status than by the objective burden of chronic illness. Even those with chronic conditions can experience high SWB when they manage their health effectively and receive adequate support[61].\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eSignificant differences emerged in how sociodemographic characteristics relate to SWB across care environments. In nursing homes, family structure had a strong impact on SWB, particularly among individuals without partners or those with three or more children, who reported lower SWB. This finding aligns with disengagement theory[62], indicating that limited social networks in nursing homes are insufficient to compensate for the lack of emotional family ties.\\u003c/p\\u003e\\n\\u003cp\\u003eIn contrast, older adults in community settings maintained greater social interactions and family connections, reducing the impact of family structure on their SWB. We also identified a U-shaped relationship between age and SWB in nursing homes, with the 75-84 age group reporting significantly lower SWB compared to the 65-74 age group. This decline may be attributed to health deterioration and role loss during this transitional period, whereas those aged 85 and older tend to have adapted to their care needs and developed better coping mechanisms[63,64].\\u003c/p\\u003e\\n\\u003cp\\u003eAmong community settings elderly, higher SWB was typically associated with those who had higher incomes and moderate educational attainment. This may have been due to their greater access to resources, social participation, and life opportunities, which allowed them to better meet their daily needs and fulfill social role expectations[65,66]. However, individuals with higher education may have faced greater self-expectations, and if these expectations were unmet, their SWB may have been negatively impacted[67]. In contrast, no significant relationships were found between personal income or education and SWB in nursing home residents, possibly due to standardized living conditions that lessen the impact of socioeconomic factors[68].\\u003c/p\\u003e\\n\\u003cp\\u003eOverall, this study highlights the similarities and differences in the relationships between social capital, health status, sociodemographic characteristics, and SWB across institutionalized and non-institutionalized settings. These findings have important implications for policy development, practice, and future research in elderly care and active aging.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eLimitations\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study has several limitations. First, the cross-sectional design limits to conclude the causal relationships between social capital, health status, sociodemographic factors, and SWB. Longitudinal studies are necessary to determine the directionality and causality of these relationships. Second, the data were based on self-reports, which may be subject to recall or reporting bias. Third, although we employed PSM to balance key sociodemographic and health characteristics, residual confounding factors may still influence the observed relationships. For example, unmeasured variables such as psychological resilience or coping strategies could affect the outcomes. Fourth, our study focused on public nursing homes, and the differences between public and private facilities remain unclear. Future research should explore this aspect further. Lastly, we considered social capital components as a collective measure without a detailed analysis of specific dimensions. A more nuanced examination of these dimensions could provide deeper insights into their distinct impacts on SWB. Despite these limitations, this study contributes valuable insights into the associations between social capital, health status, sociodemographic characteristics, and SWB across institutionalized and non-institutionalized settings.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eIn conclusion, this study examined how social capital, health status, and sociodemographic factors relate to the SWB of older adults in both community and nursing home settings. Using PSM to balance key characteristics, we aimed to isolate the impact of living arrangements on SWB.\\u003c/p\\u003e\\n\\u003cp\\u003eOur findings revealed that older adults in nursing homes reported generally lower SWB than those in community settings, highlighting the challenges posed by institutional environments. Social capital\\u0026mdash;particularly strong social connection, cohesion, and trust\\u0026mdash;was a critical factor in enhancing SWB, suggesting that supportive social networks are essential regardless of setting.\\u003c/p\\u003e\\n\\u003cp\\u003eHealth status also emerged as an important predictor of SWB, with self-rated health showing a stronger association with SWB than objective health measures like the number of chronic conditions. This emphasizes the role of positive health perceptions in maintaining higher SWB among older adults, even when managing chronic illnesses, underscoring the need for interventions that foster positive health outlooks in this population.\\u003c/p\\u003e\\n\\u003cp\\u003eAdditionally, we observed differences in how sociodemographic factors influence SWB across settings. Family structure played a more significant role in institutionalized settings, with residents without partners or with multiple children experiencing notably lower SWB. In contrast, income and education disparities had a stronger impact on SWB in community settings.\\u003c/p\\u003e\\n\\u003cp\\u003eThese insights suggest that effective interventions must be tailored to the unique characteristics of each care environment. By addressing specific sociodemographic needs, we can create more supportive surroundings that promote healthier and more fulfilling aging experiences for diverse older populations.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cp\\u003eSWB \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Subjective well-being\\u003c/p\\u003e\\n\\u003cp\\u003ePA \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Positive affect\\u003c/p\\u003e\\n\\u003cp\\u003eNA \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Negative affect\\u003c/p\\u003e\\n\\u003cp\\u003ePE \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Positive experience\\u003c/p\\u003e\\n\\u003cp\\u003eNE \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Negative experience\\u003c/p\\u003e\\n\\u003cp\\u003eMUNSH \\u0026nbsp; Memorial University of Newfoundland Scale of Happiness\\u003c/p\\u003e\\n\\u003cp\\u003ePSM \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Propensity score matching\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe give our sincere thanks to staff of community and nursing homes for helping collect data and all respondents for their contribution..\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026rsquo; contributions\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eYC\\u0026nbsp;and DHW\\u0026nbsp;contributed to conception and design of the study.\\u0026nbsp;WHC, EXZ, and WJL\\u0026nbsp;performed the statistical analysis\\u0026nbsp;and drafted the original manuscript.\\u0026nbsp;SSZ and XLW collected and processed data.\\u0026nbsp;YC\\u0026nbsp;and\\u0026nbsp;DHW\\u0026nbsp;reviewed and revised the manuscript.\\u0026nbsp;All authors read and approved the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThis research was\\u0026nbsp;supported\\u0026nbsp;by Zhejiang Provincial Department of Education (grant Number Y202250035), and the National Natural Science Foundation of China (grant Number 71904037).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe datasets generated and analysed during the current study are not publicly available due to reasons of sensitivity but are available from the corresponding author on reasonable request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eEthical approval of this study was obtained from the Ethics Committee of Hangzhou Normal University (No.20210002). All methods in our study were performed in accordance with the guidelines and regulations of the Declaration of Helsinki. Informed consent was obtained from all subjects involved in the study.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eHan B, Yan B, Zhao N, et al. The influence of the functional capacity on subjective well-being and quality of life of patients with silicosis. \\u003cem\\u003eAging Ment Health\\u003c/em\\u003e. 2013;17(6):707-713. doi:10.1080/13607863.2013.788996.\\u003c/li\\u003e\\n\\u003cli\\u003eDiener E. 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Fall Worry Restricts Social Engagement in Older Adults. \\u003cem\\u003eJ Aging Health\\u003c/em\\u003e. 2020;32(5-6):422-431. doi:10.1177/0898264319825586.\\u003c/li\\u003e\\n\\u003cli\\u003eDawson-Townsend K. Social participation patterns and their associations with health and well-being for older adults. \\u003cem\\u003eSSM - Population Health\\u003c/em\\u003e. 2019;8:100424. doi:10.1016/j.ssmph.2019.100424.\\u003c/li\\u003e\\n\\u003cli\\u003eHan TC, Lin HS, Chen CM. Association between Chronic Disease Self-Management, Health Status, and Quality of Life in Older Taiwanese Adults with Chronic Illnesses. \\u003cem\\u003eHealthcare\\u003c/em\\u003e. 2022;10(4):609. doi:10.3390/healthcare10040609.\\u003c/li\\u003e\\n\\u003cli\\u003eTornstam L. Gero-transcendcncc: A reformulation of the disengagement theory. \\u003cem\\u003eAging Clin Exp Res\\u003c/em\\u003e. 1989;1(1):55-63. doi:10.1007/BF03323876.\\u003c/li\\u003e\\n\\u003cli\\u003eWiggins RD, Higgs PFD, Hyde M, Blane DB. 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Income and Financial Satisfaction among Older Adults in the United States. \\u003cem\\u003eSocial Indicators Research\\u003c/em\\u003e. 2004;66(3):249-266. doi:10.1023/B:SOCI.0000003585.94742.aa.\\u003c/li\\u003e\\n\\u003cli\\u003eKahneman D, Deaton A. High income improves evaluation of life but not emotional well-being. \\u003cem\\u003eProc Natl Acad Sci USA\\u003c/em\\u003e. 2010;107(38):16489-16493. doi:10.1073/pnas.1011492107.\\u003c/li\\u003e\\n\\u003cli\\u003eGerstorf D, Ram N, Estabrook R, Schupp J, Wagner GG, Lindenberger U. Life satisfaction shows terminal decline in old age: Longitudinal evidence from the German Socio-Economic Panel Study (SOEP). \\u003cem\\u003eDevelopmental Psychology\\u003c/em\\u003e. 2008;44(4):1148-1159. doi:10.1037/0012-1649.44.4.1148.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-public-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"pubh\",\"sideBox\":\"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/pubh/default.aspx\",\"title\":\"BMC Public Health\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Social capital, Subjective well-being, Older adults, Community dwellings, Nursing homes, Comparative study, Propensity score matching\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-5391128/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-5391128/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eBackground: \\u003c/strong\\u003eThis study aimed to examine the differences in relationships among social capital components, health status, sociodemographic characteristics, and subjective well-being (SWB) among older adults in institutionalized versus non-institutionalized care environments.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods: \\u003c/strong\\u003eA cross-sectional survey was conducted involving 1,037 older adults aged 65-95 years from nine communities and nine nursing homes across three regions of Zhejiang Province, China. Social capital and SWB were assessed using the Social Capital Scale and the Memorial University of Newfoundland Scale of Happiness (MUNSH), respectively. Propensity score matching (PSM, 1:1, caliper width 0.02) was applied to balance key sociodemographic characteristics and health status between community-dwelling and nursing home residents. Multiple linear regression was utilized to analyze the relationships among social capital components, health status, sociodemographic factors, and SWB in both groups.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults: \\u003c/strong\\u003ePSM identified 290 older adults in community dwellings and a comparable group (n = 290) in nursing homes. Comparative analysis showed that nursing home residents demonstrated lower SWB. Multiple linear regression revealed that social connection, trust, and cohesion positively associated with SWB in both groups. However, social participation was significantly linked only with community dwellings residents. Both groups showed a positive relationship between SWB and self-rated health, but no association was found with the number of chronic conditions. Additionally, higher income (≥3000 RMB) and education level (middle) were linked to increased SWB among community-dwelling older adults, whereas family structure—specifically, having no partner and three or more children—negatively impacted SWB in the nursing home group.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusion: \\u003c/strong\\u003eSocial capital and health status showed a strong and consistent association with SWB in both groups. Strengthening social connections, trust, and cohesion, along with maintaining positive health perceptions, is expected to enhance the well-being of older adults, particularly for those in institutional settings. Notably, differences in how sociodemographic factors influence SWB across settings. These findings indicate the necessity for tailored interventions that address the unique needs of each care environment to promote healthier aging experiences.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Social capital, health status, and sociodemographic factors associated with subjective well-being among older Adults: a comparative study of community dwellings and nursing homes\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-12-02 22:46:33\",\"doi\":\"10.21203/rs.3.rs-5391128/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2024-12-05T07:47:43+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-11-23T17:29:41+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-11-17T01:42:31+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"42304974608371362705346662034542495716\",\"date\":\"2024-11-15T00:19:20+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"121244960679571796115909062000178107530\",\"date\":\"2024-11-14T13:02:24+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"228480736398254622284635842838164908334\",\"date\":\"2024-11-14T08:56:44+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2024-11-14T03:23:18+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2024-11-05T11:59:33+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2024-11-05T09:34:31+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2024-11-05T09:32:37+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Public Health\",\"date\":\"2024-11-05T00:39:13+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-public-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"pubh\",\"sideBox\":\"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/pubh/default.aspx\",\"title\":\"BMC Public Health\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"3b4415d4-c5a0-40f9-bc30-a761672dd615\",\"owner\":[],\"postedDate\":\"December 2nd, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-04-07T16:08:04+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-5391128\",\"link\":\"https://doi.org/10.1186/s12889-025-22036-4\",\"journal\":{\"identity\":\"bmc-public-health\",\"isVorOnly\":false,\"title\":\"BMC Public Health\"},\"publishedOn\":\"2025-04-03 15:57:51\",\"publishedOnDateReadable\":\"April 3rd, 2025\"},\"versionCreatedAt\":\"2024-12-02 22:46:33\",\"video\":\"\",\"vorDoi\":\"10.1186/s12889-025-22036-4\",\"vorDoiUrl\":\"https://doi.org/10.1186/s12889-025-22036-4\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-5391128\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-5391128\",\"identity\":\"rs-5391128\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}