Nasopharyngeal carcinoma (NPC) is an uncommon and aggressive malignant head and neck cancer, which is highly prevalent in southern and southwestern provinces in China. The aim of this study was to examine the disease burden and risk factors of nasopharyngeal carcinoma in China from 1990 to 2019 and to predict the incidence trends from 2020 to 2049. All data were extracted from the 2019 Global Burden of Disease (GBD) study. Joinpoint regression and age-period-cohort (APC) models were chosen to analyze prevalence trends. The temporal trends and age distribution of risk factors were also analyzed descriptively. Bayesian APC models were used to predict the prevalence from 2020 to 2049. The results indicate a higher disease burden in men and older adults. Their attributable risk factors are smoking, occupational exposure to formaldehyde, and alcohol use. We predict that the incidence will be on the rise in all age groups between 2020 and 2049, with the highest incidence in people aged 70 to 89 years. In 2049, the incidence rate is expected to reach 13.39 per 100,000 (50–54 years), 16.43 (55–59 years), 17.26 (60–64 years), 18.02 (65–69 years), 18.55 (70–74 years), 18.39 (75–79 years), 19.95 (80–84 years), 23.07 (85–89 years), 13.70 (90–94 years), and 6.68 (95+ years). The findings of this study might deserve consideration in China’s NPC prevention and control policy design.

Lip and oral cavity cancer is a common malignancy faced by many developing countries, and the disease burden is high in China. This study explored this cancer burden and its risk factors using data from China in the GBD 2019, along with predicting the incidence trends in 2020–2049. Data on age-standardized rates (ASR), incidence, death and disability-adjusted life years (DALY), by sex, age and risk factors were collected from the Institute for Health Metrics and Evaluation (IHME). Joinpoint regression and Age–Period–Cohort (APC) models were selected to analyze the epidemic trend of this cancer in China, and descriptive analysis was used for the time trend and age distribution of risk factors. The Bayesian APC model was selected to foresee the incidence trend in 2020–2049. This cancer burden was found to be in an upward trend in China in 1990–2019. The upward trend was more pronounced among men than among women. These cancer deaths and DALYs are overwhelmingly attributable to smoking and drinking. On APC analysis, the younger generation in China demonstrated a lower cancer risk. In 2049, the incidence of this cancer is projected to be 3.99/100,000, 6.07/100,000, 7.37/100,000, 10.49/100,000, 14.82/100,000, 19.19/100,000, 20.71/100,000, 23.64/100,000, 16.42/100,000 and 9.91/100,000 among those aged 50–54, 55–59, 60–64, 65–69, 70–74, 75–79, 80–84, 85–89, 85–89 and over 95 years, respectively. Disease control policies and early screening should focus on men and the elderly and target different risk factors.

Musculoskeletal disorders are one of the three major disabling diseases in the world. However, the current disease burden in China is not well-known. This study aimed to explore the burden and risk factors of musculoskeletal disorders in China from 1990 to 2019, predicting the incidence trend from 2020 to 2044. All data were extracted from the Global Burden of Disease Study 2019 (GBD 2019). Joinpoint regression and age–period–cohort (APC) models were selected to analyze the epidemic trend, and descriptive analyses of the time trends and age distributions of risk factors were performed. The Bayesian APC model was used to foresee the incidence trend from 2020 to 2044. The results indicated that the burden of musculoskeletal disorders is higher in women and older adults. Its attributable risk factors were found to be tobacco, a high body mass index, kidney dysfunction and occupational risks. In 2044, musculoskeletal disorders in China showed a downward trend for 35–59-year-olds and a slight upward trend for 30–34- and 65–84-year-olds. The 70–74 year age group saw the largest increase in incidence at 4.66%. Overall, the incidence increased with age. Therefore, prevention and control policies should focus on women and the elderly, and health interventions should be carried out based on risk factors.