Breast cancer (BC) is a malignant disease that occurs worldwide and poses serious health burden. To assess the prevalence of BC burden in the Western Pacific region (WPR) from 1990 to 2019, and to predict trends from 2020 to 2044. To analyze the driving factors and put forward the region-oriented improvement. Based on the Global Burden of Disease Study 2019, BC cases, deaths, disability-adjusted life years (DALYs) cases, age-standardized incidence rate (ASIR), age-standardized death rate (ASDR), and age-standardized DALYs rate in WPR from 1990 to 2019 was obtained and analysed. Age-period-cohort (APC) model was used to analyze age, period, and cohort effects in BC, and Bayesian APC (BAPC) was used to predict trends over the next 25 years. In conclusion, BC incidence and deaths in the WPR have increased rapidly over the past 30 years and are expected to continue to increase between 2020 and 2044. Among behavioral and metabolic factors, high body-mass index was the main risk factor for BC mortality in middle-income countries, whereas alcohol use was the main risk factor in Japan. Age is a key factor in the development of BC, with 40 years being the critical point. Incidence trends coincide with the course of economic development. The BC burden remains an essential public health issue in the WPR and will increase substantially in the future. More efforts should be made in middle-income countries to prompt the health behavior and minimize the burden of BC because these nations accounts for the majority of BC burden in the WPR.

Background: China’s fragmentation of social health insurance schemes has become a key obstacle that hampers equal access to health care and financial protection. This study aims to explores if the policy intervention Urban and Rural Residents Basic Medical Insurance (URRBMI) scheme, which integrates Urban Resident Basic Medical Insurance (URBMI) and New Rural Cooperative Medical Scheme (NCMS), can curb the persistent inequity of catastrophic health expenditure (CHE) and further analyses the determinants causing inequity. Methods: Data were derived from the Fifth National Health Service Survey (NHSS). A total of 11,104 households covered by URRBMI and 20,590 households covered by URBMI or NCMS were selected to analyze CHE and the impoverishment rate from medical expenses. Moreover, the decomposition method based on a probit model was employed to analyse factors contributing CHE inequity. Results: The overall incidence of CHE under integrated insurance scheme was 15.53%, about 1.10% higher than the non-integrated scheme; however, the intensity of CHE and impoverishment among the poorest was improved. Although CHE was still concentrated among the poor under URRBMI (CI = -0.53), it showed 28.38% lower in the degree of inequity. For URRBMI households, due to the promotion of integration reform to the utilization of rural residents’ better health services, the factor of residence (24.41%) turns out to be a major factor in increasing inequity, the factor of households with hospitalized members (− 84.53%) played a positive role in reducing inequity and factors related to social economic status also contributed significantly in increasing inequity. Conclusion: The progress made in the integrated URRBMI on CHE equity deserves recognition, even though it did not reduce the overall CHE or the impoverishment rate effectively. Therefore, for enhanced equity, more targeted solutions should be considered, such as promoting more precise insurance intervention for the most vulnerable population and including costly diseases suitable for outpatient treatment into benefit packages. Additionally, comprehensive strategies such as favourable targeted benefit packages or job creation are required for the disadvantaged.

Background: We examined the physiological, household, and spatial agglomeration characteristics of the health poverty population in China. We identified weak links that affect the implementation of the medical insurance and further improve its effectiveness for health poverty alleviation. Methods: A national representative sample from the China Health and Retirement Longitudinal Study (CHARLS) was analyzed. The WHO recommended method was adopted to calculate catastrophic health expenditure (CHE) and impoverishment by medical expenses (IME). We created a binary indicator for IME as the outcome variable and applied the treatment-effect model to analyze the determinants of IME. Results: The incidence of IME was 7.2% of the overall population, compared to 20.3% of the sample households trapped in CHE. The incidence of IME enrolled in insurance schemes was 7.4% higher than that of uninsured families (4.8%). Economic level, living area, family size, age of household head, having hospitalized members, and participating in insurance were statistically significant for the occurrence of IME. Conclusions: The original poverty-promoting policies has not reached the maximum point of convergence with China’s current demand for health. The overlapped health vulnerabilities exacerbated the risk of poverty among the elderly and households with high health needs and utilization. In addition, the medical insurance schemes have proven to be insufficient for protection against economic burden of poor households. So, special health needs, age, and household capacity to pay should be comprehensively considered while strengthening the connection between the disease insurance scheme with supplementary insurance.

Objective Recently, Chinese ministries and commissions have issued a series of policies and systems in response to violent injuries to doctors, physical violence have been managed to a certain extent. However, verbal violence has not been deterred and is still prevalent, it has not received appropriate attention. This study thus aimed to assess the impact of verbal violence on the organisational level and identify its risk factors among healthcare workers, so as to provide practical methods for verbal violence reduction and treatment of the complete period. Methods Six tertiary public hospitals were selected in three provinces (cities) in China. After excluding physical and sexual violence, a total of 1567 remaining samples were included in this study. Descriptive, univariate, Pearson correlation and mediated regression analyses were employed to assess the difference between the variables, emotional responses of healthcare workers to verbal violence and the relationship between verbal violence and emotional exhaustion, job satisfaction, and work engagement. Results Nearly half of the healthcare workers in China’s tertiary public hospitals experienced verbal violence last year. Healthcare workers who experienced verbal violence had strong emotional response. The exposure of healthcare workers to verbal violence significantly positively predicted the emotional exhaustion (r=0.20, p<0.01), significantly negatively predicted job satisfaction (r=−0.17, p<0.01) and work engagement (r=−0.18, p<0.01), but was not associated with turnover intention. Emotional exhaustion partially mediated the effects of verbal violence on job satisfaction and work engagement. Conclusions The results indicate that the incidence of workplace verbal violence in tertiary public hospitals in China is high and cannot be ignored. This study is to demonstrate the organisational-level impact of verbal violence experienced by healthcare workers and to propose training solutions to help healthcare workers reduce the frequency and mitigate the impact of verbal violence.

Background: Digital health is important for sustainable health systems and universal health coverage. Since the outbreak of COVID-19, many countries, including China, have promoted the introduction of digital health in their medical services. Developing the next generation of physicians with digital health knowledge and skills is a prerequisite for maximizing the potential of digital health. Objective: We aimed to understand the perception of digital health among Chinese medical students, the current implementation of digital health education in China, and the urgent need of medical students. Methods: Our cross-sectional survey was conducted online and anonymously among current medical students in China. We used descriptive statistical analysis to examine participant demographic characteristics and the demand for digital health education. Additional analysis was conducted by grouping responses by current participation in a digital health course. Results: A total of 2122 valid responses were received from 467 medical schools. Most medical students had positive expectations that digital health will change the future of medicine. Compared with wearable devices (85.53%), telemedicine (84.16%), and medical big data (86.38%), fewer respondents believed in the benefits of clinical decision support systems (CDSS) (63.81%). Most respondents said they urgently needed digital health knowledge and skills, and the teaching method of practical training and internship (78.02%) was more popular than the traditional lecture (10.54%). However, only 41.45% wanted to learn about the ethical and legal issues surrounding digital health. Conclusions: Our study shows that the current needs of Chinese medical students for digital health education remain unmet. A national initiative on digital health education, is necessary and attention should be paid to digital health equity and education globally, focusing on CDSS and artificial intelligence. Ethics knowledge must also be included in medical curriculum. Students as Partners (SAP) is a promising approach for designing digital health courses.

Elite hospitals represent the highest level of Chinese hospitals in medical service and management, medical quality and safety, technical level and efficiency, which are also one of the important indicators reflecting high-quality medical resources in the region, and their spatial allocation is directly related to the fairness of health resource allocation. We explored the allocation pattern of high-quality resources and its influencing factors in the development of China's health system using geographic weighted regression (GWR), Multi-scale Geographically Weighted Regression (MGWR), GWR and MGWR with Spatial Autocorrelation(GWR-SAR and MGWR-SAR), spatial lag model (SLM), and spatial error model (SEM). The results of OLS regression showed that city level, number of medical colleges, urbanization rate, permanent population and GDP per capita were its significant variables. And spatial auto-correlation of elite hospitals in China is of great significance. Further, its spatial agglomeration phenomenon was confirmed through SLM and SEM. Among them, the city level is the most important factor affecting the spatial allocation of elite hospitals in China. Its action intensity shows a solid and weak mosaic trend in the Middle East, relatively concentrated in some areas with medium intensity and concentrated in the West China. Obviously, China's elite hospitals are unevenly distributed and have evident spatial heterogeneity. Therefore, we suggest that we should pay attention to the spatial governance of high-quality medical resources, attract medical elites in the region, increase investment in medical education in the scarce areas of elite hospitals and develop tele-medicine service.