Background The disease burden of non-melanoma skin cancer (NMSC) has become a significant public health threat. We aimed to conduct a comprehensive analysis to mitigate the health hazards of NMSC. Methods This study had three objectives. First, we reported the NMSC-related disease burden globally and for different subgroups (sex, socio-demographic index (SDI), etiology, and countries) in 2019. Second, we examined the temporal trend of the disease burden from 1990 to 2019. Finally, we used the Bayesian age-period-cohort (BAPC) model integrated nested Laplacian approximation to predict the disease burden in the coming 25 years. The Norpred age-period-cohort (APC) model and the Autoregressive Integrated Moving Average (ARIMA) model were used for sensitivity analysis. Results The disease burden was significantly higher in males than in females in 2019. The results showed significant differences in disease burden in different SDI regions. The better the socio-economic development, the heavier the disease burden of NMSC. The number of new cases and the ASIR of basal cell carcinoma (BCC) were higher than that of squamous cell carcinoma (SCC) in 2019 globally. However, the number of DALYs and the age-standardized DALYs rate were the opposite. There were statistically significant differences among different countries. The age-standardized incidence rate (ASIR) of NMSC increased from 54.08/100,000 (95% uncertainty interval (UI): 46.97, 62.08) in 1990 to 79.10/100,000 (95% UI: 72.29, 86.63) in 2019, with an estimated annual percentage change (EAPC) of 1.78. Other indicators (the number of new cases, the number of deaths, the number of disability-adjusted life years (DALYs), the age-standardized mortality rate (ASMR), and the age-standardized DALYs rate) showed the same trend. Our predictions suggested that the number of new cases, deaths, and DALYs attributable to NMSC would increase by at least 1.5 times from 2020 to 2044. Conclusions The disease burden attributable to NMSC will continue to increase or remain stable at high levels. Therefore, relevant policies should be developed to manage NMSC, and measures should be taken to target risk factors and high-risk groups.

In the twenty-first century, exposure to air pollution has become a threat to human health worldwide due to industrial development. Timely, comprehensive, and reliable assessment and prediction of disease burden can help mitigate the health hazards of air pollution. This study conducted a two-stage analysis. First, we reported the air pollution–related disease burden globally and for different subgroups like socio-demographic index (SDI), sex, and age. We analyzed the trend of the disease burden from 1990 to 2019. In addition, we explored whether and how some national indicators modified the disease burden. Second, we predicted the number and the age-standardized rates of death and disability-adjusted life years (DALYs) attributable to air pollution from 2020 to 2044 by the autoregressive integrated moving average (ARIMA) model and exponential smoothing model. The age-period-cohort (APC) model in the maximum likelihood framework and the Bayesian APC model integrated nested Laplace approximations (INLAs) were further applied to perform sensitivity analysis. In 2019, air pollution accounted for 11.62% of death and 0.84% of DALY worldwide. The corresponding age-standardized rate was 85.62 (95% uncertainty interval (UI): 75.71, 96.07) and 2791.08 (95% UI: 2468.81, 3141.39) per 100,000 population. From 1990 to 2019, the number of death attributable to air pollution remained stable, and the number of DALY exhibited a downward trend. The corresponding age-standardized rates both declined. In some countries with larger population densities, higher proportions of elders, and lower proportions of females, the disease burden attributable to air pollution was lower. The predicted results showed that the number of air pollution-related death and DALY would increase. This study comprehensively assessed and predicted the air pollution–related disease burden worldwide. The results indicated that the disease burden would remain very serious in the future. Hence, some relevant policies should be developed to prevent and manage air pollution. Supplementary information The online version contains supplementary material available at 10.1007/s11356-022-22318-z.

Objective Diabetes is a life-long disease that poses a serious threat to safety and health. We aimed to assess the disease burden attributable to diabetes globally and by different subgroups, and to predict future disease burden using statistical models. Methods This study was divided into three stages. Firstly, we evaluated the disease burden attributable to diabetes globally and by different subgroups in 2019. Second, we assessed the trends from 1990 to 2019. We estimated the annual percentage change of disease burden by applying a linear regression model. Finally, the age-period-cohort model was used to predict the disease burden from 2020 to 2044. Sensitivity analysis was performed with time-series models. Results In 2019, the number of incidence cases of diabetes globally was 22239396 (95% uncertainty interval (UI): 20599519–24058945). The number of prevalence cases was 459875371 (95% UI 423474244–497980624) the number of deaths cases was 1551170 (95% UI 1445555–1650675) and the number of disability-adjusted life years cases was 70880155 (95% UI 59707574–84174005). The disease burden was lower in females than males and increased with age. The disease burden associated with type 2 diabetes mellitus was greater than that with type 1; the burden also varied across different socio-demographic index regions and different countries. The global disease burden of diabetes increased significantly over the past 30 years and will continue to increase in the future. Conclusion The disease burden of diabetes contributed significantly to the global disease burden. It is important to improve treatment and diagnosis to halt the growth in disease burden.

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