Background: Previous studies have demonstrated the effect of socioeconomic status on the health status of the elderly. Nevertheless, the specific dimensions of the effect and the mechanism await further investigation. In this study, socioeconomic status was divided into three dimensions and we used social participation as the mediation variable to investigate the specific path of effect. Methods: Using the 2018 Waves of Chinese Longitudinal Healthy Longevity Survey (CLHLS) dataset, a total of 10,197 effective samples of the elderly over 65 years old were screened out. Socioeconomic status included income, education level, and main occupation before retirement. The physical health and mental health of the elderly was measured by the Instrumental Activities of Daily Living Scale and the Minimum Mental State Examination, respectively. The social participation of the elderly was the mediation variable, including group exercise, organized social activities and interacting with friends. Omnibus mediation effect analysis was adopted to examine the mediation effect and mediation analysis was completed using the SPSS PROCESS program. Results: First, the results showed that when the income gap between the elderly reached a certain level, there was a significant difference in health status. Significant differences existed in health status amongst with different education levels. There was no sufficient evidence to show that occupation has a significant effect on the physical health. But when the dependent variable was mental health, the effect was significant. Second, group exercise mediated 64.11% (a_ib = 0.24, 95% CI [0.17,0.3]) and up to 20.44% (a_ib = 0.12, 95% CI [0.07,0.17]) of the disparity in physical and mental health due to income gap, respectively. And it could mediate the effect up to 56.30% (a_ib = 0.62, 95% CI [0.52,0.73]) and 17.87% (a_ib = 0.50, 95% CI [0.4,0.61]) of education on physical and mental health status, respectively. The proportion of relative mediation effect of occupation was up to 28.74% (a_ib = 0.19, 95% CI [0.13,0.25]) on mental health. Interacting with friends mediated only on the path that the education affected the health status of the elderly. The proportion was up to 33.72% (a_ib = 0.29, 95% CI [0.16,0.44]). The relative mediation effect of organized social activities on the health gap caused by income or education level gap was significant at some levels. The proportion was up to 21.20% (a_ib = 0.33, 95% CI [0.26,0.4]). Conclusion: The SES of the elderly including relatively large income gap, different education levels and occupational categories could indeed have a significant effect on health status of the elderly, and the reason why this effect existed could be partly explained by the mediation effect of social participation. Policymakers should pay more attention to the social participation of the elderly.

This study aimed to explore the impact of social participation (SP) on physical functioning and depression among empty-nest elderly taking part in the fourth wave of the China Health and Retirement Longitudinal Survey (CHARLS, 2018). The instrumental variable (IV) method and propensity score matching (PSM) method were used to analyse the impact of SP. The two-stage regression results of the IV method showed that SP has a significant negative impact on the physical functioning scores of empty-nest elderly (β = −3.539, p < 0.001) and non-empty-nest elderly (β = −4.703, p < 0.001), and SP has a significant negative impact on the depression scores of empty-nest elderly (β = −2.404, p < 0.001) and non-empty-nest elderly (β = −1.957, p < 0.001). The results of the PSM method were basically consistent with the IV method. Compared with non-empty-nest elderly, SP had more positive effects on the depression of empty-nest elderly (Wald χ² = 6.62, p = 0.010). Providing a friendly and supportive environment for the SP of empty-nest elderly was an important measure to promote healthy ageing. Targeted SP may be one of the greatest opportunities to improve the mental health of empty-nest elderly.

Background: The initial outbreak of COVID-19 caused by SARS-CoV-2 in China in 2019 has been severely tested in other countries worldwide. We aimed to describe the spatial distribution of the COVID-19 pandemic worldwide and assess the effects of various socio-ecological factors on COVID-19 risk. Methods: We collected COVID-19 pandemic infection data and social-ecological data of 178 countries/regions worldwide from three database. We used spatial econometrics method to assess the global and local correlation of COVID-19 risk indicators for COVID-19. To estimate the adjusted incidence rate ratio (IRR), we modelled negative binomial regression analysis with spatial information and socio-ecological factors. Findings: The study indicated that 37, 29 and 39 countries/regions were strongly opposite from the IR, CMR and DCI index “spatial autocorrelation hypothesis”, respectively. The IRs were significantly positively associated with GDP per capita, the use of at least basic sanitation services and social insurance program coverage, and were significantly negatively associated with the proportion of the population spending more than 25% of household consumption or income on out-of-pocket health care expenses and the poverty headcount ratio at the national poverty lines. The CMR was significantly positively associated with urban populations, GDP per capita and current health expenditure, and was significantly negatively associated with the number of hospital beds, number of nurses and midwives, and poverty headcount ratio at the national poverty lines. The DCI was significantly positively associated with urban populations, population density and researchers in R&D, and was significantly negatively associated with the number of hospital beds, number of nurses and midwives and poverty headcount ratio at the national poverty lines. We also found that climatic factors were not significantly associated with COVID-19 risk. Conclusion: Countries/regions should pay more attention to controlling population flow, improving diagnosis and treatment capacity, and improving public welfare policies.

Background: China advocates a health insurance system with social health insurance (SHI) as the main body and private health insurance (PHI) as the supplement. The study of PHI's complementary role in health is conducive to providing evidence for PHI's policy expansion and encouraging the public to participate in PHI, which is insufficient in China.Methods: We used the three-wave balanced panel data of the China Health and Retirement Longitudinal Survey (CHARLS). Taking the ownership of supplementary PHI as the independent variable and EQ-5D index scores as the dependent variable, the panel instrumental variable (IV) method was used to analyze the impact of participation in PHI on health. We also assessed the heterogeneity of the health effects of PHI between chronic and non-chronic disease groups and between low- and high-income groups.Results: The coverage rate of PHI at baseline was 10.53%. The regression results showed that participating in PHI on the basis of SHI could result in an additional 8.21% health gain (p < 0.001). At the same time, PHI had greater health gain for chronic disease population than for healthy population (9.25 vs. 6.24%, p < 0.001), and greater health gain for high-income population than for low-income population (8.32 vs. 5.31%, p < 0.001).Conclusion: Participating in supplementary PHI can effectively enhance the health status of the insured, and has a more significant effect on patients with chronic diseases. The development of PHI should be further supported, while the health inequality in different income groups should be paid attention to.

This study investigates the complex relationship between internet use and citizen political participation, emphasizing the mediating role of social networks. Using cross-sectional data from the 2021 Chinese Social Survey (CSS), we classify political participation into government-led and citizen-led activities and internet use into informational, entertainment-oriented, and service-oriented types. Overall, our findings reveal a positive correlation between internet use and both citizen-led participation and government-led participation (excluding voting), with a stronger association observed in the former. From a categorical perspective, informational and service-oriented internet use significantly influences all types of political participation, while entertainment-oriented use shows no significant correlation. Additionally, social networks mediate the relationship between internet use and political participation. Service-oriented internet use is more dependent on social networks to connect with political participation compared to information-oriented internet use. This study contributes to the ongoing debate on the impact of digital media on civic engagement by providing nuanced insights into how specific internet activities and social networks shape political participation in China.