Objective:To investigate the mediating effects of medical inquiry ability and attitudes toward aging on the relationship between socioeconomic status and mental health among the elderly.Methods:Utilizing data from the 2021 China General Social Survey(CGSS), a sample of 957 individuals aged 60 years and older was selected for analysis.The influence of each variable was assessed through regression analysis, and the mediating effects were evaluated using the Bootstrap method.Results:The study samples ranged in age from 60 to 95 years, including 479 females and 478 males.Socioeconomic status significantly positively influenced mental health( β=0.208, P<0.001).Additionally, socioeconomic status had a notable positive effect on medical inquiry ability( β=0.244, P<0.001)and attitudes toward aging( β=0.163, P<0.001)among the elderly population.Furthermore, medical inquiry ability positively affected both attitudes toward aging( β=0.158, P<0.001)and mental health( β=0.139, P<0.001).The attitude toward aging also had a significant positive impact on mental health( β=0.216, P<0.001).Notably, both medical inquiry ability and attitudes toward aging served as significant mediators between socioeconomic status and mental health in the elderly, with a total indirect effect value of 0.091(95% CI: 0.063-0.123).The chain mediating effect of medical inquiry ability and pension mentality was also significant, with an effect size of 0.010(95% CI: 0.005-0.017). Conclusions:Enhancing the socioeconomic status of older adults can foster their medical inquiry ability, positively influence their attitudes toward aging, and ultimately contribute to the promotion of their mental health.

Objective:This study aims to investigate the impact of socioeconomic status on cognitive function in older adults, while analyzing the mediating role of health-related social determinants.The findings will provide a foundation for the implementation of an active aging strategy.Methods:Utilizing data from the China Health and Retirement Longitudinal Study(CHARLS)2020, this study employed multiple linear regression analysis to investigate the relationship between socioeconomic status and cognitive function among older adults.A multiple mediation model was applied to evaluate the mediating effects of health-related social determinants on the association between socioeconomic status and cognitive function, with these mediation effects assessed using the Bootstrap method.Results:The results of the multiple linear regression analysis indicated that socioeconomic status significantly positively influences cognitive function in older adults.Factors such as younger age, male gender, Han ethnicity, and urban residence were associated with higher cognitive scores.The mediation analysis demonstrated that, of the total effect of socioeconomic status on cognitive function, health status accounted for 1.564%, individual lifestyle for 14.820%, social support networks for 2.719%, living conditions for 1.632%, and other social structural factors for 1.496%.In the multiple mediation model, a total of 17.945% of the effect of socioeconomic status on cognitive function in older adults was jointly mediated by health-related social determinants.Conclusions:Socioeconomic status is a critical determinant of cognitive impairment among older adults in China.To address this issue, comprehensive interventions should be implemented to promote the equitable distribution of economic and social resources, reduce socioeconomic disparities, and mitigate health inequalities, thereby enhancing the overall cognitive function of disadvantaged groups.Preventive measures and strategies aimed at improving health status, encouraging healthy lifestyle choices, strengthening social support networks, enhancing living conditions, and optimizing social structural factors could serve as essential intervention points to improve the cognitive function of older adults with lower socioeconomic status.

Objective:The arrival of the big data era has accelerated the development of information technology in the healthcare sector. Internationally, developed countries such as the United States, the United Kingdom, and the European Union have taken pioneering initiatives in data openness. Since 2015, China has rapidly promoted the application of big data through policy layout. This study aims to help the open and shared development of healthcare big data in our country by investigating the status quo of open and shared healthcare big data at home and abroad.Methods:Through literature research and information integration, this study summarized the development history and current situation of open and sharing health and medical big data at home and overseas, analyzed related problems and challenges, and proposed countermeasures and development suggestions.Results:The open sharing of health and medical big data in developed countries and regions abroad had made outstanding achievements in legislation, standard formulation, platform construction, etc. The domestic policy layout was relatively perfect, and the relevant construction was being actively promoted. Problems and challenges still existed in five aspects, including privacy security, data format standards, data quality, laws and regulations, and property rights and interests.Conclusions:Combined with the problems found in the current research process, the following countermeasures and development suggestions are proposed for domestic health and medical big data open sharing: establish a privacy protection mechanism to ensure data security, unify data standards to improve data interoperability, build a data quality control system to ensure data accuracy, improve laws and regulations to standardize data sharing behavior, clarify the ownership of interests and protect intellectual property rights.

Objective:To investigate the mediating effects of medical inquiry ability and attitudes toward aging on the relationship between socioeconomic status and mental health among the elderly.Methods:Utilizing data from the 2021 China General Social Survey(CGSS), a sample of 957 individuals aged 60 years and older was selected for analysis.The influence of each variable was assessed through regression analysis, and the mediating effects were evaluated using the Bootstrap method.Results:The study samples ranged in age from 60 to 95 years, including 479 females and 478 males.Socioeconomic status significantly positively influenced mental health( β=0.208, P<0.001).Additionally, socioeconomic status had a notable positive effect on medical inquiry ability( β=0.244, P<0.001)and attitudes toward aging( β=0.163, P<0.001)among the elderly population.Furthermore, medical inquiry ability positively affected both attitudes toward aging( β=0.158, P<0.001)and mental health( β=0.139, P<0.001).The attitude toward aging also had a significant positive impact on mental health( β=0.216, P<0.001).Notably, both medical inquiry ability and attitudes toward aging served as significant mediators between socioeconomic status and mental health in the elderly, with a total indirect effect value of 0.091(95% CI: 0.063-0.123).The chain mediating effect of medical inquiry ability and pension mentality was also significant, with an effect size of 0.010(95% CI: 0.005-0.017). Conclusions:Enhancing the socioeconomic status of older adults can foster their medical inquiry ability, positively influence their attitudes toward aging, and ultimately contribute to the promotion of their mental health.

Objective:This study aims to investigate the impact of socioeconomic status on cognitive function in older adults, while analyzing the mediating role of health-related social determinants.The findings will provide a foundation for the implementation of an active aging strategy.Methods:Utilizing data from the China Health and Retirement Longitudinal Study(CHARLS)2020, this study employed multiple linear regression analysis to investigate the relationship between socioeconomic status and cognitive function among older adults.A multiple mediation model was applied to evaluate the mediating effects of health-related social determinants on the association between socioeconomic status and cognitive function, with these mediation effects assessed using the Bootstrap method.Results:The results of the multiple linear regression analysis indicated that socioeconomic status significantly positively influences cognitive function in older adults.Factors such as younger age, male gender, Han ethnicity, and urban residence were associated with higher cognitive scores.The mediation analysis demonstrated that, of the total effect of socioeconomic status on cognitive function, health status accounted for 1.564%, individual lifestyle for 14.820%, social support networks for 2.719%, living conditions for 1.632%, and other social structural factors for 1.496%.In the multiple mediation model, a total of 17.945% of the effect of socioeconomic status on cognitive function in older adults was jointly mediated by health-related social determinants.Conclusions:Socioeconomic status is a critical determinant of cognitive impairment among older adults in China.To address this issue, comprehensive interventions should be implemented to promote the equitable distribution of economic and social resources, reduce socioeconomic disparities, and mitigate health inequalities, thereby enhancing the overall cognitive function of disadvantaged groups.Preventive measures and strategies aimed at improving health status, encouraging healthy lifestyle choices, strengthening social support networks, enhancing living conditions, and optimizing social structural factors could serve as essential intervention points to improve the cognitive function of older adults with lower socioeconomic status.

Objective:The arrival of the big data era has accelerated the development of information technology in the healthcare sector. Internationally, developed countries such as the United States, the United Kingdom, and the European Union have taken pioneering initiatives in data openness. Since 2015, China has rapidly promoted the application of big data through policy layout. This study aims to help the open and shared development of healthcare big data in our country by investigating the status quo of open and shared healthcare big data at home and abroad.Methods:Through literature research and information integration, this study summarized the development history and current situation of open and sharing health and medical big data at home and overseas, analyzed related problems and challenges, and proposed countermeasures and development suggestions.Results:The open sharing of health and medical big data in developed countries and regions abroad had made outstanding achievements in legislation, standard formulation, platform construction, etc. The domestic policy layout was relatively perfect, and the relevant construction was being actively promoted. Problems and challenges still existed in five aspects, including privacy security, data format standards, data quality, laws and regulations, and property rights and interests.Conclusions:Combined with the problems found in the current research process, the following countermeasures and development suggestions are proposed for domestic health and medical big data open sharing: establish a privacy protection mechanism to ensure data security, unify data standards to improve data interoperability, build a data quality control system to ensure data accuracy, improve laws and regulations to standardize data sharing behavior, clarify the ownership of interests and protect intellectual property rights.

Objective:To analyze the disparity in the prevalence of chronic comorbidities between the urban and rural elderly populations, providing scientific evidence to tailor health management strategies and policies.Methods:Data from 9, 252 participants aged 60 years and older, drawn from the 2020 China Health and Retirement Longitudinal Study(CHARLS, 2020), were analyzed.The urban-rural disparity in chronic comorbidities prevalence and the associated factors were examined using logistic regression analysis and Fairlie decomposition.Results:Of the 9, 252 participants, the rate of chronic comorbidities was 66.10%, with a higher prevalence observed in the urban population compared to the rural population(68.52% vs.64.86%, =12.421, P<0.001).Logistic regression analysis indicated that among the urban population, chronic comorbidities were less prevalent in participants who reported more than 6 hours of sleep, were employed, and assessed their health as good.Conversely, a higher prevalence was noted in individuals aged 65 and older.In the rural population, the rate of chronic comorbidities was lower in participants who reported more than 6 hours of sleep, were employed, had annual incomes exceeding RMB 10, 000, assessed their health as good, and reported higher life satisfaction.Utilizing the Fairlie decomposition method, it was found that the differences in the prevalence of chronic comorbidities between urban and rural elderly populations were primarily attributable to employment status and sleep duration( P<0.05), with contribution rates of 69.22% and 6.92%, respectively. Conclusions:In the context of global aging, this study examined the factors influencing the prevalence of comorbidity among elderly populations in urban and rural settings.The findings demonstrate that enhancing sleep quality, promoting employment opportunities, fostering community engagement, and encouraging family interaction may contribute to reducing the health disparities between urban and rural areas, thereby supporting healthy aging.

Objective:To analyze the disparity in the prevalence of chronic comorbidities between the urban and rural elderly populations, providing scientific evidence to tailor health management strategies and policies.Methods:Data from 9, 252 participants aged 60 years and older, drawn from the 2020 China Health and Retirement Longitudinal Study(CHARLS, 2020), were analyzed.The urban-rural disparity in chronic comorbidities prevalence and the associated factors were examined using logistic regression analysis and Fairlie decomposition.Results:Of the 9, 252 participants, the rate of chronic comorbidities was 66.10%, with a higher prevalence observed in the urban population compared to the rural population(68.52% vs.64.86%, =12.421, P<0.001).Logistic regression analysis indicated that among the urban population, chronic comorbidities were less prevalent in participants who reported more than 6 hours of sleep, were employed, and assessed their health as good.Conversely, a higher prevalence was noted in individuals aged 65 and older.In the rural population, the rate of chronic comorbidities was lower in participants who reported more than 6 hours of sleep, were employed, had annual incomes exceeding RMB 10, 000, assessed their health as good, and reported higher life satisfaction.Utilizing the Fairlie decomposition method, it was found that the differences in the prevalence of chronic comorbidities between urban and rural elderly populations were primarily attributable to employment status and sleep duration( P<0.05), with contribution rates of 69.22% and 6.92%, respectively. Conclusions:In the context of global aging, this study examined the factors influencing the prevalence of comorbidity among elderly populations in urban and rural settings.The findings demonstrate that enhancing sleep quality, promoting employment opportunities, fostering community engagement, and encouraging family interaction may contribute to reducing the health disparities between urban and rural areas, thereby supporting healthy aging.

Humans ; Intra-Abdominal Fat/diagnostic imaging* ; Coronary Artery Disease ; Body Mass Index

The general population cohort study in Beijing-Tianjin-Hebei area is a large-scale prospective longitudinal study conducted since 2017, which covers over 114 850 diverse populations from early life to senior age. Up to December 2021, 106 031 people had completed at least one follow-up, with an overall follow-up rate of 92.3%. Considering of the characteristics of the environmental and health problems in Beijing-Tianjin-Hebei area, in this cohort study we have focused on health problems of children and adolescents' growth and development, cardiometabolic diseases and their risk factors, aging and comorbidity, health hazards caused by air pollution. The long-term follow up of the general population cohort study in Beijing-Tianjin-Hebei area will contribute to establishing unique and invaluable data and biobank resource for scientific research. This paper aims to comprehensively describe the background, significance, current status and outcomes, limitations and challenges, and future plan and development of general population cohort study in Beijing-Tianjin-Hebei area, thus to provide reference for professionals both at home and abroad to carry out related research.