Social Participation: A Strategy to Manage Depression in Disabled Populations.

This study aimed to investigate whether social participation (SP) can decrease depressive symptom severity in disabled older adults. A total of 5,937 disabled participants (4877, 1970, 219, and 8 participants responding 1, 2, 3, 4 times, respectively), obtained from the China Health and Retirement Longitudinal Study, were enrolled in our analysis. Based on pooled Ordinary Least Square regressions, SP was associated with decreased depressive symptom severity, and this association was significant in recreational activities and interacting with friends. For brain-disabled respondents, the association was not significant. SP is effective in decreasing depressive symptom severity in disabled older populations. Diversified activities and targeted interventions should be applied to specified older disabled populations to prevent depression.

Correlations between depressives symptom severity and social participation (SP) among disable older adults were measured in a Chinese context.Pooled Ordinary Least Square regression were used to explore the impact of SP on depressives symptom severity in older populations with disabilities.Social participation, including recreational activities and interacting with friends, was associated with decreased depressives symptom severity in disabled middle-aged and older adults.The impact of SP on depressives symptom severity was not significant for older adults with brain disabilities.

Urban-rural disparities in the healthy ageing trajectory in China: a population-based study.

PURPOSE: The aim of this study is to measure the trajectory of healthy ageing among Chinese middle-aged and older population, and explore the disparity of the trajectory, as well as contributing factors, between urban and rural areas in China. METHODS: A total of 9402 respondents aged 45 years and older interviewed in four waves (2011, 2013, 2015 and 2018) were selected from the China Health and Retirement Longitudinal Study. Healthy ageing score was calculated through item response theory. A latent growth mixture model (LGMM) was applied to distinguish the trajectory of healthy aging. A multinomial logistics regression model (MLRM) was used to explore the relationship between urban-rural areas and healthy aging trajectories, and further to explore associated factors in rural and urban areas separately. RESULTS: The healthy ageing score was lower in rural areas than urban areas in each survey wave. Five classes ("continuing-low", "continuing-middle", "continuing-middle-to-high", "significantly-declining", "continuing-high") were grouped through LGMM. The MLRM results showed that urban living was significantly associated with a higher likelihood of being healthy (for [continuing-low/continuing-high]: ß = - 1.17, RRR = 0.31, P < 0.001, 95% CI = 0.18-0.53; and for [continuing-middle/continuing-high]: ß = - 0.53, RRR = 0.59, P < 0.001, 95% CI = 0.49-0.71). CONCLUSION: Healthy ageing is a prominent objective in the development of a country, and rural-urban disparities are an essential obstacle to overcome, with the rural population more likely to develop a low level of healthy ageing trajectory. Prevention and standardized management of chronic diseases should be enhanced, and social participation should be encouraged to promote healthy ageing. The policy inclination and resource investment should be enhanced to reduce disparity in healthy ageing between urban and rural areas in China.

Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey.

BACKGROUND: Digital health has become a heated topic today and smart homes have received much attention as an important area of digital health. Smart home is a device that enables automation and remote control in a home environment via the internet. However, most of the existing studies have focused on discussing the impact of smart home on people. Only few studies have focused on relationship between health skills and use of smart home. AIMS: To analyze the health skills of Chinese adults and segment them to compare and analyze the use of smart home for each group. METHODS: We used data from 11,031 participants aged 18 and above. The population was clustered based on five health skills factors: perceived social support, family health, health literacy, media use, and chronic diseases self-behavioral management. A total of 23 smart homes were categorized into three sub-categories based on their functions: entertainment smart home, functional smart home, and health smart home. We analyzed demographic characteristics and utilization rate of smart home across different cluster. Each groups' features and the differences in their needs for smart home functions were compared and analyzed. RESULTS: As a result of the survey on health skills, three groups with different characteristics were clustered: good health skills, middle health skills, and poor health skills. The utilization rate of smart home was the highest was good health skills group (total smart home: 92.7%; entertainment smart home: 61.1%, functional smart home: 77.4%, and health smart home: 75.3%; P < 0.001). For entertainment smart home, smart TV had the highest utilization rate (good health skills: 45.7%; middle health skills: 43.5%, poor health skills: 33.4%, P < 0.001). For functional smart home, smart washing machine (good health skills: 37.7%, middle health skills: 35.11%, poor health skills: 26.5%; P < 0.001) and smart air conditioner (good health skills: 36.0%, middle health skills: 29.1%, poor health skills: 24.6%) were higher than other of this category. For health smart home, sports bracelet has the highest utilization rate (good health skills: 37.3%, middle health skills: 24.5%, poor health skills: 22.8%). CONCLUSION: People can be divided into different categories based on health skill profiles, those with good health skills had a better utilization rate of smart home. The government and smart home companies need to focus on people with poor smart home use in various ways to promote their use of smart homes for personal health management.

Association of depression symptoms and sleep quality with state-trait anxiety in medical university students in Anhui Province, China: a mediation analysis.

BACKGROUND: The prevalence of depression symptoms among medical students is particularly high, and it has increased during the COVID-19 epidemic. Sleep quality and state-trait anxiety are risk factors for depression, but no study has yet investigated the mediating role of state-trait anxiety in the relationship between poor sleep quality and depression symptoms in medical students. This study aims to investigate the relationship among depression symptoms, sleep quality and state-trait anxiety in medical university students in Anhui Province. METHODS: This was a cross-sectional survey of 1227 students' online questionnaires collected from four medical universities in Anhui Province using a convenience sampling method. We measured respondents' sleep quality, state-trait anxiety, and depression symptoms using three scales: the Pittsburgh Sleep Quality Index (PSQI), the State-Trait Anxiety Inventory (STAI) and the Self-rating Depression Scale (SDS). We analysed the mediating role of STAI scores on the association between PSQI scores and SDS scores through the Sobel-Goodman Mediation Test while controlling for covariates. P < 0.05 was considered statistically significant. RESULTS: A total of 74.33% (912) and 41.40% (518) of the respondents reported suffering from poor sleep quality and depression symptoms. Sleep quality, state-trait anxiety, and depression symptoms were positively associated with each other (ß = 0.381 ~ 0.775, P < 0.001). State-trait anxiety partially mediated the association between sleep quality and depression symptoms (Sobel test Z = 15.090, P < 0.001), and this mediating variable accounted for 83.79% of the association when adjusting for potential confounders. Subgroup analysis further revealed that STAI scores partially mediated the association between PSQI scores and SDS scores in females and rural students and fully mediated the association between PSQI scores and SDS scores in males and urban students. CONCLUSIONS: This study found that sleep quality and state-trait anxiety have a significant predictive effect on depression symptoms. State-trait anxiety mediated the relationship between sleep quality and depression symptoms, with a more complex mechanism observed among rural and female medical students. Multiple pathways of intervention should be adopted, such as encouraging students to self-adjust, providing professional psychological intervention and timely monitoring, enriching extracurricular activities, and making changes in policies regarding long shifts and working hours.

How is family health related to health-related quality of life among middle-aged and older adults in rural China? A cross-sectional study.

BACKGROUND: Health-related quality of life (HRQOL) is unequal between countries and regions, and the emphasis on HRQOL of populations of low-income countries and regions is unprecedented. OBJECTIVES: To examine the association between family health and HRQOL among middle-aged and older adults in rural China, and determine whether this association differs by age, gender and chronic disease subgroup. METHODS: Cross-sectional survey carried out from July to September 2021. The participants were 1059 people aged 46 and over living in rural China. We used the European Quality of Life Five Dimension Five Level (EQ-5D-5L) and Family Health Scale-Short Form (FHS-SF) to assess health-related quality of life (HRQOL) and family health, respectively. RESULTS: The mean EQ-VAS was 75.66, the mean EQ index score was 0.92, and the mean FHS was 37.90 in rural middle-aged and older adults. After Bonferroni correction, generalised linear regression models showed that FHS was significantly associated with the EQ-VAS (ß = 0.829; 95% confidence interval [CI]: 0.660 to 0.997; p < .001) and the EQ index score (ß = 0.003; 95%CI: 0.001 to 0.004; p < .001). Binary logistic regression models showed that FHS was associated with three dimensions of HRQOL (mobility, self-care and usual activities) (p < .01). Based on subgroup analyses, the effect of FHS on EQ-VAS and the EQ index score was significant in three subgroups after Bonferroni correction (p < .01), but the association between FHS and the dimensions of HRQOL differed by age, gender and chronic disease group (p > .01). CONCLUSIONS: This study is the first to explore that family health and its dimensions are significant positive predictors of HRQOL among middle-aged and older adults in rural China. Family-based measures may have more potential and value because better family health significantly improves HRQOL. IMPLICATIONS FOR PRACTICE: In the health strategy, the government and primary health care workers should include family health as an indicator and assess it before and after the implementation of the strategy.

Relationship between self-efficacy and adherence to self-management and medication among patients with chronic diseases in China: A multicentre cross-sectional study.

PURPOSE: This study aimed to explore the effects of self-efficacy on adherence to self-management and medication among patients with chronic diseases in China. METHODS: A cross-sectional survey of 2047 patients with chronic diseases in 120 cities across China was conducted between May and September 2021 using a multi-stage sampling method. Self-efficacy was measured using the New General Self-Efficacy Scale. The adherence to self-management was measured using the item response theory based self-management adherence scale, and the medication adherence was assessed using the Medication Adherence Scale for the Chronically Ill. The adherence to self-management and medication were evaluated by linear regression and logistic regression models, respectively. RESULTS: After adjusting for all covariates, self-efficacy was significantly associated with adherence to self-management (ß =0.207, 95% CI =0.064-0.350, P = 0.005), but not with medication adherence (for[middle/low]: OR = 1.119, 95% CI =0.828-1.511, P = 0.47; for[high/low]: OR = 1.281, 95% CI =0.935-1.754, P = 0.12). In subgroup analysis, self-efficacy positively correlated with adherence to self-management in patients with multiple chronic diseases (ß =0.286, 95% CI =0.037-0.535, P = 0.03), but not in those with only one chronic disease (P = 0.12). Self-efficacy was not significantly associated with medication adherence in any of the subgroups. CONCLUSION: Self-efficacy was positively associated with adherence to self-management in patients with chronic diseases, but not with medication adherence. Enhanced health education in patients with one chronic disease alone may have an association with better adherence to self-management and medication in daily life.