Background: We projected global trends in ischemic stroke from 2020 to 2030 according to age, sex, and socio-demographic index (SDI) quintile. Methods: Estimated annual percentage changes (EAPCs) were used to project trends in the incidence of deaths from and disability-adjusted life years (DALYs) due to ischemic stroke between 2020 and 2030. EAPCs were computed using generalized additive models and data from the Global Burden of Disease study during the 1990 to 2019 period. Results: The global age-standardized incidence rate of ischemic stroke was projected to increase to 89.32 per 100 000 population in 2030 (EAPC=0.89), whereas the associated global age-standardized death and DALY rates were projected to decrease to 18.28 (EAPC, −3.58) and 500.37 per 100 000 (EAPC=−1.75), respectively, in 2030. The projections indicated a higher age-standardized incidence rate of ischemic stroke among women than among men in 2030 (90.70 versus 87.64 per 100 000). The incidence rate of ischemic stroke was projected to increase across all age groups and SDI quintiles between 2020 and 2030. At the national level, the greatest increase in the age-standardized incidence rate of ischemic stroke between 2020 and 2030 was projected to occur in Cyprus (EAPC=4.16), followed by Palestine (EAPC=3.50) and South Africa (EAPC=2.64). Additionally, the projections suggested increases in the age-standardized death and DALY rates due to ischemic stroke for countries in low-SDI quintiles (EAPC=3.68 and EAPC=5.30, respectively). Conclusions: The projections indicated that the incidence rate of ischemic stroke will increase both sexes, all age groups, and all SDI quintiles and in some countries between 2020 and 2030. Furthermore, countries with a low SDI should be aware of potential increases in the age-standardized death and DALY due to ischemic stroke.

Vitamin A deficiency (VAD) is one of the important public health issues worldwide. However, a detailed understanding of the incidence and disability-adjusted life years (DALYs) due to VAD in recent years is lacking. We aimed to estimate the incidence and DALYs of VAD at global, regional, and national levels in terms of sex, age, and socio-demographic index (SDI). Using data from the 2019 Global Burden of Disease (GBD) study, the estimated annual percentage change (EAPC) was measured to assess trends in the age-standardized incidence and DALY rates from 1990 to 2019. The global age-standardized incidence and DALY rates of VAD decreased with an EAPC of −3.11% (95% confidence interval (CI): −3.24% to −2.94%) and −2.18% (95% CI: −2.38% to −1.93%), respectively. The age-standardized incidence and DALY rates decreased least in low-SDI regions, which had the highest age-standardized incidence and DALY rates of all SDI regions. Sub-Saharan Africa, especially central sub-Saharan Africa, had the highest age-standardized incidence and DALY rates in 2019. At the national level, Somalia and Niger had the highest age-standardized incidence and DALY rates. The age-standardized incidence and DALY rates were higher in males than in females. Younger children, especially those aged < 5 years in low-SDI regions, had a higher VAD burden than other age groups. Although the global burden of VAD has decreased, future work should aim to improve the prevention and treatment strategies for VAD, particularly in children aged < 5 years in countries and territories with low SDI values, such as sub-Saharan Africa.

From 1990 to 2019, the age-standardized incidence rate of nutritional deficiencies in China remained stable. However, the age-standardized disability-adjusted life-years (DALY) rate of nutritional deficiencies decreased from 1990 to 2019. Data were extracted from the GBD 2019 datasets. Estimated annual percentage changes (EAPCs) were calculated to assess the incidence rate, and DALY trends of nutritional deficiencies. Measures were stratified by subtypes, regions, and age groups. In 2019, the age-standardized DALY rates of dietary iron deficiency and protein-energy malnutrition reached their highest levels. The main population groups with protein-energy malnutrition and dietary iron deficiency were adults over the age of 70 and children under the age of five. The latter group also had a greater burden of vitamin A deficiency. Zhejiang, Beijing, and Guangdong reported the highest age-standardized incidence rates of nutritional deficiencies, which mainly pertained to protein-energy malnutrition and vitamin A deficiency. Tibet, Xinjiang, and Hainan had the highest age-standardized DALY rates of nutritional deficiencies, which mainly pertained to dietary iron deficiency and protein-energy malnutrition.

Even though China launched a series of measures to alleviate several financial burdens (including health insurance scheme, increased government investment, and so on), the economic burden of health expenditure has still not been alleviated. Out-of-pocket payments (OPPs) show not only a time correlation but also some degree of spatial correlation. The aims of the current study were thus to identify the spatial cluster of OPPs, to investigate the main factors affecting variation, and to explore the spatial spillover sources of China’s OPP. Global and local spatial autocorrelation tests were validated to identify the spatial cluster of OPPs using the panel data of 31 provinces in China from 2005 to 2016. The Spatial Durbin Model, established in this paper, measured the spatial spillover effect of OPPs and analyzed the possible spillover sources (demand, supply, and socio-economic factors. OPPs were found to have a significant and positive spatial correlation. The results of the Spatial Durbin Model showed the direct and indirect effects of demand, supply, and socio- economic factors on China’s OPPs. Among the demand factors, the direct and indirect correlation (elasticity) coefficients were positive. Among the supply factors, the direct and indirect effects of the share of primary health beds on residents’ OPPs were negative. The ratio of health technicians in hospitals to those in primary health institutions on per capital OPPs had a significant indirect effect. Among the socio-economic factors, the direct effects of GDP, government health expenditure, and urbanization on OPPs were found to be positive. There were no significant indirect effects of socio-economic factors on OPPs. This paper finds that China’s OPPs are not randomly distributed but, overall, present a positive spatial cluster, even though a series of measures have been launched to promote health equity. Socio-economic factors and those associated with demand were found to be the main influences of variation in OPPs, while demand was seen to be the driver of the positive spatial spillover of OPPs, whereby effective supply could inhibit these positive spillover effects.