This study aimed to explore the relationship between individual social capital and functional ability, with a focus on whether there is an interactive relationship that exists among social capital related to functional ability among older people in Anhui province, China. We conducted a cross-sectional study with a multi-stage stratified cluster random sampling method from July to September 2017. Data were collected through questionnaire including demographic characteristics, individual social capital status, and functional capability status. Binary logistic regression analysis model and classification and regression tree model (CART) were utilized. Overall, this study included 1810 elderly people, 43% of whom had functional disability. After the adjustment, subjects with lower social participation (AOR = 1.60; 95% CI: 1.26–2.03) and lower social connection (AOR = 1.74; 95% CI: 1.34–2.25) had an increased risk of functional disability. However, social support (AOR = 0.73; 95% CI: 0.57–0.94) was inversely related to functional ability. We also observed interactive relationship of social capital associated with functional ability, which indicated that special attention and efforts should be paid to older adults with less educational attainment, with multimorbidity, with advanced age, and with lower level of social participation, cohesion for the purpose of maintaining sound functional ability. Our findings may be of salient relevance for devising more targeted and effective interventions to prevent the onset of functional limitations among community-dwelling older adults.

Background To examine the relationship between social capital and depression among community-dwelling older adults in Anhui Province, China. Methods A cross-sectional study was conducted among older people selected from three cities of Anhui Province, China using a multi-stage stratified cluster random sampling method. Data were collected through questionnaire interviews and information on demographic characteristics, social capital, and depression was collected. The generalized linear model and classification and regression tree model were employed to assess the association between social capital and depression. Results Totally, 1810 older people aged ≥60 years were included in the final analysis. Overall, all of the social capital dimensions were positively associated with depression: social participation (coefficient: 0.35, 95% CI: 0.22–0.48), social support (coefficient:0.18, 95% CI:0.07–0.28), social connection (coefficient: 0.76, 95% CI:0.53–1.00), trust (coefficient:0.62, 95% CI:0.33–0.92), cohesion (coefficient:0.31, 95% CI:0.17–0.44) and reciprocity (coefficient:0.30, 95% CI:0.11–0.48), which suggested that older people with higher social capital had a smaller chance to develop depression. A complex joint effect of certain social capital dimensions on depression was also observed. The association with depression and the combinative effect of social capital varied among older adults across the cities. Conclusions Our study suggests that improving social capital could aid in the prevention of depression among older adults.

Background We aimed to examine the association between social capital and loneliness in Anhui Province, China. Methods Data were collected from a cross-sectional study using a multi-stage stratified cluster sampling strategy. Data on demographic characteristics, socioeconomic factors, social capital, and loneliness in 1810 older adults (aged 60 years and older) were used for analysis. Binary logistic regression models and a classification and regression tree model were performed to assess the association of social capital and loneliness. Results Our results indicated that social capital in terms of lower level of social participation (AOR = 1.38; 95% CI: 1.10–1.74), social connection (AOR = 1.51; 95% CI: 1.18–1.93), and reciprocity (AOR = 1.47; 95% CI: 1.13–1.90) were associated with higher odds of developing loneliness. We noted the interactive effect of different social capital dimensions on loneliness, suggesting that the risk for suffering loneliness was greatest in older people limited in functional ability, with less trust, less social connection, and less social participation. Conclusions Our findings show that social capital is associated with loneliness in older adults. This implies that social capital, especially in terms of trust, social connection, and social participation may be significant for alleviating loneliness in later life.

Background: To examine the relationship between social capital and depression among community-dwelling older adults in Anhui Province, China.Methods: A cross-sectional study was conducted among older people selected from three cities of Anhui Province, China using a multi-stage stratified cluster random sampling method. Data were collected through questionnaire interviews and information on demographic characteristics, social capital, and depression was collected. The generalized linear model and classification and regression tree model were employed to assess the association between social capital and depression.Results: Totally, 1,810 older people aged ≥ 60 years were included in the final analysis. Overall, all of the social capital dimensions were positively associated with depression: social participation (coefficient: 0.35, 95% CI: 0.22 - 0.48), social support (coefficient:0.18, 95% CI:0.07 - 0.28), social connection (coefficient: 0.76, 95% CI:0.53 - 1.00), trust (coefficient:0.62, 95% CI:0.33 - 0.92), cohesion (coefficient:0.31, 95% CI:0.17 - 0.44) and reciprocity (coefficient:0.30, 95% CI:0.11 - 0.48), which suggested that older people with higher social capital had a smaller chance to develop depression. A complex joint effect of certain social capital dimensions on depression was also observed. The association with depression and the combinative effect of social capital varied among older adults across the cities.Conclusions: Our study suggests that improving social capital could aid in the prevention of depression among older adults.

Background: We aimed to examine the association between social capital and loneliness in Anhui Province, China. Methods: Data were collected from a cross-sectional study using a multi-stage stratified cluster sampling strategy. Data on demographic characteristics, socioeconomic factors, social capital, and loneliness in 1810 older adults (aged 60 years and older) were used for analysis. Binary logistic regression models and a classification and regression tree model were performed to assess the association of social capital and loneliness. Results: Our results indicated that social capital in terms of lower level of social participation (AOR = 1.38; 95% CI: 1.10-1.74), social connection (AOR = 1.51; 95% CI: 1.18-1.93), and reciprocity (AOR = 1.47; 95% CI: 1.13-1.90) were associated with higher odds of developing loneliness. We noted the interactive effect of different social capital dimensions on loneliness, suggesting that the risk for suffering loneliness was greatest in older people limited in functional ability, with less trust, less social connection, and less social participation. Conclusions: Our findings show that social capital is associated with loneliness in older adults. This implies that social capital, especially in terms of trust, social connection, and social participation may be significant for alleviating loneliness in later life.

Background: Depression is a prevalent health condition among hypertension patients in elderly caring social organizations (SOs). Patients with hypertension and depression symptoms have worse health outcomes than those without depression. As the population ages, chronic and mental health issues such as depression of hypertension patients in elderly caring SOs have become prominent. However, the combined effects of social support, institutional satisfaction, and anxiety on depression among hypertension individuals in elderly caring SOs remain unclear. This study aimed to explore the mediating effects of institutional satisfaction and anxiety on the relationship between social support and depression among hypertension patients in elderly caring SOs in Anhui Province, China.Methods: A cross-sectional study was conducted using a multi-stage stratified random sampling method. A questionnaire was used to collect data on demographic characteristics, the satisfaction of elderly caring SOs, social support, anxiety, and depression. A multiple linear regression model was utilized to investigate depression-related factors, and structural equation modeling (SEM) was employed to examine the relationships between social support, institutional satisfaction, anxiety, and depression among patients with hypertension in elderly caring SOs.Results: Our results indicated that the mean scores of social support were 20.19 ± 6.98 and 1.92 ± 3.18 for anxiety, and 6.24 ± 5.03 for depression; besides, 33.3% of participants were very satisfied with elderly caring SOs, 48.5% were satisfied, and only 6.0% were dissatisfied or very dissatisfied. Comorbid chronic diseases were significantly associated with depression. Institutional satisfaction was directly negatively related to depression, whereas anxiety was directly positively correlated with depression. Social support had an indirect negative association with depression by the mediating effects of institutional satisfaction and anxiety.Conclusions: The study highlights the importance of social support in maintaining mental health among hypertension patients residing in elderly caring SOs. To alleviate depression among hypertension patients in elderly caring SOs, strategies that target enhancing social support, institutional satisfaction, and anxiety reduction should be prioritized. More importantly, more attention should be paid to patients with comorbid chronic diseases.

Objective Turnover intention of employees in elderly caring social organizations has a significant impact on elderly care service delivery. This study investigated the associated factors of turnover intention among employees of elderly caring social organizations in Anhui Province, China. Methods A total of 605 participants were selected using a multi-stage stratified random sampling method. A self-administered questionnaire was used to collect information on socio-demographic, social support, and turnover intention from the participants. The data was analyzed through descriptive statistical analysis, one-way variance analysis, Spearman correlation analysis, and multiple linear regression were used to analyze the factors related to turnover intention. Results Results of our study showed that the total score of turnover intention, turnover intention I (possibility of quitting a current job),turnover intention II (motivation to find other jobs) and turnover intention III (obtaining the external possibility of work) were 8.84, 2.32, 2.38, and 4.14, respectively. Social support negatively correlated with turnover intention I and turnover intention II. However, it showed positive correlation with turnover intention III and total turnover intention scores; turnover intentionI (coefficient: − 0.082), turnover intention II (coefficient: − 0.071), turnover intention III (coefficient: 0.19), Total score of turnover intention (coefficient: 0.093). Ethnic group, age, education level, and job satisfaction were associated with turnover intention. Conclusion Improvement of social support play an important role in reducing the turnover intention of employees in elderly caring social organizations. It is important to increase organizational commitment and strengthen psychological empowerment, combined with decreasing job burnout for stability.

Background: To examine the relationship between social capital and depression among community-dwelling older adults in Anhui Province, China.Methods: A cross-sectional study was conducted among older people selected from three cities of Anhui Province, China using a multi-stage stratified cluster random sampling method. Data were collected through questionnaire interviews and information on demographic characteristics, social capital, and depression was collected. The generalized linear model and classification and regression tree model were employed to assess the association between social capital and depression. Results: Totally, 1,810 older people aged ≥ 60 years were included in the final analysis. Overall, all of the social capital dimensions were positively associated with depression: social participation (coefficient: 0.35, 95% CI: 0.22 - 0.48), social support (coefficient:0.18, 95% CI:0.07 - 0.28), social connection (coefficient: 0.76, 95% CI:0.53 - 1.00), trust (coefficient:0.62, 95% CI:0.33 - 0.92), cohesion (coefficient:0.31, 95% CI:0.17 - 0.44) and reciprocity (coefficient:0.30, 95% CI:0.11 - 0.48), which suggested that older people with higher social capital had a smaller chance to develop depression. A complex joint effect of certain social capital dimensions on depression was also observed. The association with depression and the combinative effect of social capital varied among older adults across the cities. Conclusions: Our study suggests that improving social capital could aid in the prevention of depression among older adults.