Global burden of female breast cancer and its association with socioeconomic development status, 1990-2044.

BACKGROUND: Breast cancer is a widespread disease in women worldwide. AIM: We aimed to explore the global epidemiological trends of female breast cancer (FBC) between 1990 and 2044. METHODS AND RESULTS: Disease burden, population, and socio-demographic index (SDI) data were obtained from the Global Health Data Exchange (GHDx) database. We analyzed temporal trends, age differences, risk factors, and geographic patterns of FBC disease burden globally and explored the association between age-standardized incidence rate (ASIR) of FBC and SDI. Bayesian age-period-cohort model was also performed to predict the changes in FBC incidence worldwide from 2020 to 2044. First, the global ASIR of FBC increased by 14.31% from 1990 to 2019 (95% Uncertainty Interval 4.75% to 23.98%). The death rate presented a falling trend. Second, alcohol use is the most-highlighted risk factor for FBC in some high-income regions such as Europe. A high fasting plasma glucose levels is the most prominent risk factor for FBC in Latin America and Africa. Third, the ASIR of the FBC increases with the SDI. Fourth, the incidence is expected to increase faster among women aged 35-60 years and fastest for those aged 50-54 years from 2020 to 2044. Countries with a high incidence of FBC that is expected to increase significantly include Barbados, Burkina Faso, Senegal, Monaco, Lebanon, Togo, and Uganda. CONCLUSION: The disease burden of FBC varies worldwide; the findings suggest attaching importance to the control of middle and low-middle SDI regions. Public health as well as cancer prevention experts should pay more attention to regions and populations at an increased risk of developing FBC, focusing on their prevention and rehabilitation while conducting further epidemiological studies to investigate the risk factors of their increase.

Spatial Disparities in Access to Healthcare Professionals in Sichuan: Evidence from County-Level Data.

As a southwestern province of China, Sichuan is confronted with geographical disparities in access to healthcare professionals because of its complex terrain, uneven population distribution and huge economic gaps between regions. With 10-year data, this study aims to explore the county-level spatial disparities in access to different types of healthcare professionals (licensed doctors, registered nurses, pharmacists, technologists and interns) in Sichuan using temporal and spatial analysis methods. The time-series results showed that the quantity of all types of healthcare professionals increased, especially the registered nurses, while huge spatial disparities exist in the distribution of healthcare professionals in Sichuan. The local Moran's I calculations showed that high-high clusters (significantly high healthcare professional quantity in a group of counties) were detected in Chengdu (capital of Sichuan) and relatively rich areas, while low-low clusters (significantly low healthcare professional quantity in a group of counties) were usually found near the mountain areas, namely, Tsinling Mountains and Hengduan Mountains. The findings may deserve considerations in making region-oriented policies in educating and attracting more healthcare professionals to the disadvantaged areas.

Detecting the priority areas for health workforce allocation with LISA functions: an empirical analysis for China.

BACKGROUND: Health workforce misdistribution leads to severe inequity and low-efficiency in health services in the developing countries. Targeting at China, this research aims to reveal, visualize and compare the geographical distribution patterns of different subtypes of urban and rural health workforce and identify the priority regions for health workforce planning and allocation policies designing. METHODS: The health workforce density (workforce-to-population ratio) is adopted to represent the accessibility to health workforce in each geographical unit. Besides a descriptive geography of health workforce as a whole, the local indicators of spatial association (LISA) are used to explore the spatial clusters of different subtypes of health workforce, which are visualized by geographical tools. RESULTS: Results reveal that regional disparities and spatial clusters exist in China's health workforce distribution, with different types of workforce exhibiting relatively different spatial distribution characteristics. Besides, huge urban-rural disparities are found in the distribution of health workforce in China. Unexpectedly but intriguingly, most of the high-high and high-low cluster area of urban health workforce are concentrated in the western China (Xinjiang, Xizang etc.), indicating the relative abundant stock of urban health workforce in these units, while the low-low and low-high cluster area of different types of urban health workforce are mainly distributed in middle China. Regarding the rural health workforce, there is an obvious and similar low-low and low-high clustering pattern in western provinces (Sichuan, Yunnan) for the licensed doctors, pharmacists, technologists, which play a critical role in health services delivery. CONCLUSIONS: Different types of health workforce displayed distinct spatial distribution patterns, while the misdistribution of rural health workforce imposed more challenges to the Chinese health sector due to its poorer stock and more disadvantaged positions of backward regions (i.e., low-low and low-high cluster area). Subtype-specific and region-oriented health workforce planning and allocation policies are suggested to be made, aiming at the urban and rural health workforce respectively, by prioritizing the identified low-low and low-high cluster areas.