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.

As the fifth-largest global mortality risk factor, air pollution has caused nearly one-tenth of the world’s deaths, with a death toll of 5 million. 21% of China’s disease burden was related to environmental pollution, which is 8% higher than the US. Air pollution will increase the demand and utilisation of Chinese residents’ health services, thereby placing a greater economic burden on the government. This study reveals the spatial impact of socioeconomic, health, policy and population factors combined with environmental factors on government health expenditure. Spearman’s correlation coefficient and GeoDetector were used to identify the determinants of government health expenditure. The GeoDetector consist of four detectors: factor detection, interaction detection, risk detection, and ecological detection. One hundred sixty-nine prefecture-level cities in China are studied. The data sources are the 2017 data from China’s Economic and Social Big Data Research Platform and WorldPOP gridded population datasets. It is found that industrial sulfur dioxide attributed to government health expenditure, whose q value (explanatory power of X to Y) is 0.5283. The interaction between air pollution factors and other factors will increase the impact on government health expenditure, the interaction value (explanatory power of × 1∩× 2 to Y) of GDP and industrial sulfur dioxide the largest, whose values is 0.9593. There are 96 simple high-risk areas in these 169 areas, but there are still high-risk areas affected by multiple factors. First, multiple factors influence the spatial heterogeneity of government health expenditure. Second, health and socio-economic factors are still the dominant factors leading to increased government health expenditure. Third, air pollution does have an important impact on government health expenditure. As a catalytic factor, combining with other factors, it will strengthen their impact on government health expenditure. Finally, an integrated approach should be adopted to synergisticly governance the high-risk areas with multi-risk factors.

This study is interested in global vaccine confidence because it directly impacts vaccination rates and public health outcomes, especially during the COVID-19 pandemic. Furthermore, due to the unique vulnerabilities to vaccine-preventable diseases, misinformation, and access to health information among adults aged 65 and older, understanding vaccine confidence in this population is crucial for developing targeted interventions and improving vaccination rates. The current research is limited by single-country surveys and cross-sectional designs, providing limited insights into these issues. We compared the vaccine confidence between the population over 65 and under 65 in terms of vaccine safety, effectiveness, compatibility with religious beliefs, and importance to children. We employed a hierarchical logistic model, and compared human development index (HDI) values to investigate determinants of vaccine confidence. Vaccine confidence increased between 2015 and 2019, but decreased between 2019 and 2022 across most global regions, exhibiting an inverted U-shaped trend. Population over 65 in high-income countries was more likely to agree on the safety, effectiveness, importance to children, and compatibility of vaccines with religious beliefs than those under 65, with agreement levels exceeding 80% for most aspects. Gender, education, income, and religion influenced vaccine attitudes among adults aged 65 and older. Countries with an HDI exceeding 0.9 consistently demonstrated positive trends in vaccine confidence. This relationship between HDI and vaccine confidence underscores the importance of comprehensive societal development in shaping attitudes toward vaccination. These findings can help develop targeted interventions and policies to improve vaccination rates among older adults.

Background: Air pollution has been identified as related to the diseases of susceptible population, but the spatial heterogeneity of its economic burden and its determinants are rarely investigated. The issue is of great policy significance, especially after the epidemic of COVID-19, when human are facing the joint crisis of health and environment, and some areas is prone to falling into poverty. Methods: The geographical detector was adopted to study the spatial distribution characteristics of the incidence of catastrophic health expenditure (ICHE) for older adults in 100 rural areas in China at the prefecture-city level. The health factors, sociological factors, policy factors and environmental factors and their interactions are identified. Results: First, most health service factors had strong explanatory power for ICHE whether it interacts with air pollution. Second, 50 single-factor high-risk areas of ICHE were found in the study, but at the same time, there were 21 areas dominated by multiple factors. Conclusion: The different contributions and synergy among the factors constitute the complex mechanism of factors and catastrophic health expenditure. Moreover, during this process, air pollution aggravates the contribution of health service factors toward ICHE. In addition, the leading factors of ICHE are different among regions. At the end, this paper also puts forward some policy suggestions from the perspective of health and environment crisis in the post-COVID-19 world: environmental protection policies should be combined with the prevention of infectious diseases; advanced health investment is the most cost-effective policy for the inverse health sequences of air pollution and infectious diseases such as coronavirus disease 2019 (COVID-19); integrating environmental protection policy into healthy development policy, different regions take targeted measures to cope with the intertwined crisis.

Background: Currently, breast cancer (BC) is ranked among the top malignant tumors in the world, and has attracted widespread attention. Compared with the traditional analysis on biological determinants of BC, this study focused on macro factors, including light at night (LAN), PM2.5, per capita consumption expenditure, economic density, population density, and number of medical beds, to provide targets for the government to implement BC interventions.Methods: A total of 182 prefecture-level cities in China from 2013 to 2016 were selected as the sample of the study. The geographically and temporally weighted regression (GTWR) model was adopted to describe the spatiotemporal correlation between the scale of BC and macro factors.Results: The results showed that the GTWR model can better reveal the spatiotemporal variation. In the temporal dimension, the fluctuations of the regression coefficients of each variable were significant. In the spatial dimension, the positive impacts of LAN, per capita consumption expenditure, population density and number of medical beds gradually increased from west to east, and the positive coefficient of PM2.5 gradually increased from north to south. The negative impact of economic density gradually increased from west to east.Conclusion: The fact that the degree of effect of each variable fluctuates over time reminds the government to pay continuous attention to BC prevention. The spatial heterogeneity features also urge the government to focus on different macro indicators in eastern and western China or southern and northern China. In other words, our research helps drive the government to center on key regions and take targeted measures to curb the rapid growth of BC.