Background: Rheumatoid arthritis (RA) is a key health issue worldwide. Due to early identification and effective treatment strategies, the disease pattern of RA has also changed. However, the most comprehensive and up-to-date information about the burden of RA and its trends in subsequent years is lacking. Objective: this study aimed to report the global burden of RA by sex, age, region, and forecast for 2030. Method: Publicly available data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 were used in this study. The trends in the prevalence, incidence, and disability-adjusted life years (DALYs) of RA from 1990 to 2019 were reported. The global burden of RA in 2019 was reported by a sex, age, and sociodemographic index (SDI). Finally, the trends in the following years were predicted by Bayesian age-period-cohort (BAPC) models. Results: Globally, the age-standardized prevalence rate increased from 207.46 (95% UI:189.99 to 226.95) in 1990 to 224.25 (95% UI: 204.94 to 245.99) in 2019, with an estimated annual percent change (EAPC) of 0.37% (95% CI: 0.32 to 0.42). Regarding the incidence, the age-standardized incidence rate (ASR) increased from 12.21 (95% UI: 11.13 to 13.38) to 13 (95% UI: 11.83 to 14.27) per 100,000 people from 1990 to 2019, with an EAPC of 0.3% (95% CI: 11.83 to 14.27). The age-standardized DALY rate also increased from 39.12 (95% UI: 30.13 to 48.56) per 100,000 people in 1990 to 39.57 (95% UI: 30.51 to 49.53) in 2019, with an EAPC of 0.12% (95% CI: 0.08% to 0.17%). There was no significant association between the SDI and ASR when the SDI was lower than 0.7, while there was a positive association between the SDI and ASR when the SDI was higher than 0.7 The BAPC analysis showed that the ASR was estimated to be up to 18.23 in females and approximately 8.34 per 100,000 people in males by 2030. Conclusion: RA is still a key public health issue worldwide. The global burden of RA has increased over the past decades and will continue to increase in the coming years, and much more attention should be given to early diagnosis and treatment to reduce the burden of RA.

This study aims to report the most up-to-date information about the global disease burden of glaucoma from 1990 to 2019 and to forecast trends in the next few years. Publicly available data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 were used in this study. The prevalence and disability-adjusted life years (DALYs) of glaucoma from 1990 to 2019 were reported. Finally, trends in the years following 2019 were predicted by Bayesian age–period–cohort (BAPC) models. We showed that, globally, the number of prevalent cases was 3,881,624 [95% uncertainty interval (UI): 3,301,963 to 4,535,045] in 1990 and increased to 7,473,400 (95% UI: 6,347,183 to 8,769,520) in 2019, while the age-standardized prevalence rate decreased from 111.92 [95% uncertainty interval (UI): 94.76 to 130.28 per 100,000] in 1990 to 94.68 (95% UI: 80.42 to 110.87 per 100,000) in 2019. The DALY number of glaucoma increased between 1990 and 2019, from 442,182 (95% UI: 301,827 to 626,486) in 1990 to 748,308 (95% UI: 515,636 to 1,044,667) in 2019. There was a significantly negative association between the sociodemographic index (SDI) and age-standardized DALY rates. The BAPC showed that the age-standardized DALY rate is predicted to decrease gradually in both males and females over the next few years. In summary, from 1990 to 2019, the global burden of glaucoma increased and the age-standardized DALY rate is predicted to decrease in the next few years. With the largest burden of glaucoma found in low-SDI regions, clinical diagnosis and treatment in such areas are more challenging and may warrant more attention.

Background: Adiposity is closely related to osteoarthritis, but the causal effects of different types of adiposity on osteoarthritis are indistinct. This study conducted a Mendelian Randomization (MR) analysis for the causal effects of general adiposity and abdominal adiposity on knee osteoarthritis (KOA) and hip osteoarthritis (HOA). Methods: The general adiposity was assessed by body mass index (BMI), while the abdominal adiposity was evaluated with waist circumference (WC), hip circumference (HC), and waist-to-hip ratio (WHR). The data used in this two-sample MR analysis originated from genome-wide association studies (GWAS). Significant (p < 5 × 10⁻⁸) and independent (r² < 0.01) single-nucleotide polymorphisms were selected as instrumental variables for the MR analysis. Subsequently, this study used the inverse variance weighted, weighted median, and other methods for the causal inference, and the results were presented as odds ratios (OR). Moreover, sensitivity analyses were conducted to assess the stability and reliability of the results. Results: The MR results revealed positive causal effects of BMI on KOA (OR: 1.694; 95% CI: from 1.492 to 1.923; p = 3.96 × 10⁻¹⁶) and HOA (OR: 1.412; 95% CI: from 1.196 to 1.666; p = 4.58 × 10⁻⁵). Additionally, WC and HC both positively and causally related to KOA (WC: OR: 1.827; 95% CI: from 1.564 to 2.134; p = 2.68 × 10⁻¹⁴; HC: OR: 1.610; 95% CI: from 1.357 to 1.912; p = 5.03 × 10⁻⁸) and HOA (WC: OR: 1.491; 95% CI: from 1.254 to 1.772; p = 5.85 × 10⁻⁶; HC: OR: 1.439; 95% CI: from 1.205 to 1.719; p = 5.82 × 10⁻⁵). However, no causal relationship existed between WHR and obesity. These results were robust according to the sensitivity analyses. Conclusions: This study indicated that both general and abdominal obesity had positive causal effects on knee osteoarthritis and hip osteoarthritis.

Several studies have shown that rheumatologic patients can benefit from metformin, but it remains unclear whether metformin treatment is causally associated with the risk of rheumatoid arthritis (RA). A two-sample Mendelian randomization (MR) study was conducted to investigate the causal relationship between metformin treatment and the incidence of rheumatoid arthritis. The genome-wide significant (p < 5 × 10⁻⁸) single-nucleotide polymorphisms (SNPs) associated with metformin use were selected as instrumental variables (IVs). Summary statistics on RA were extracted from a large genome-wide association study (GWAS) meta-analysis. The inverse variance-weighted (IVW) method was used as the determinant of the causal effects of metformin treatment on RA. Cochran’s Q was used to detect heterogeneity. Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test and MR-Egger regression were used to detect horizontal pleiotropy. A total of 34 SNPs significantly associated with metformin treatment were obtained. Thirty-two SNPs were selected as IVs after removing two SNPs for being palindromic with intermediate allele frequencies (rs11658063 and rs4930011). The IVW results showed a negative causal association between metformin treatment and RA (OR = 0.0232, 95% CI 1.6046 × 10⁻³ − 0.3368; p = 0.006). Meanwhile, no heterogeneity or pleiotropy was detected, indicating that the results were reliable. This study indicated a negative causality between metformin treatment and RA, indicating that the treatment of metformin can prevent the pathogenesis of RA.