Rheumatoid arthritis continues to increase in low-middle SDI and low SDI quintiles based on GBD 1990–2021 

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Methods: The burden of RA was investigated in relation to age, sex, and sociodemographic index (SDI), drawing upon data from the GBD 2021 study. The ASIR, ASPR, and ASDR at the global, regional, and national levels were extracted. The estimated annual percentage change (EAPC) in the ASIR, ASPR, and ASDR was calculated across all levels from 1990 to 2021, supplemented by cluster and frontier analyses. Results: In 2021, there were 17.92 million cases of RA globally, with the ASIR increasing from 10.42 to 11.8 cases per 100,000 individuals (EAPC of 0.49 [95% confidence interval: 0.46–0.52]) between 1990 and 2021. This considerable increase was evident across all age and sex groups, SDI quintiles, and GBD regions. The most pronounced increase was in the low-middle SDI quintile in the ASIR for RA between 1990 and 2021. Among 54 GBD regions, the most significant increase was observed in Andean Latin America and Equatorial Guinea. Conclusion: By 2021, the global burden of RA was largely concentrated in the low-middle and low SDI quintiles, especially in Andean Latin America and Northern Africa, with the burden continuing to grow. Global Burden of Disease study estimated annual percentage change epidemiology trends Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Rheumatoid arthritis (RA) is an autoimmune disease characterized primarily by synovial inflammation. It can occur at any age and is associated with a high risk of disability. The precise etiology of RA remains incompletely understood but involves a complex interplay of genetic susceptibility, environmental triggers (such as smoking or infection), hormonal factors, and dysregulated immune responses. A key pathophysiological mechanism of RA involves the dysregulation of citrullination. This process, which is potentially initiated or amplified by the aforementioned etiological factors, particularly in genetically predisposed individuals, leads to the formation of citrullinated proteins. These abnormal proteins can breach immune tolerance and drive the production of highly specific anti-citrullinated protein antibodies (ACPAs). ACPAs are thought to play a central role in the pathogenesis of RA. If RA is not treated properly, symptoms progressively worsen, causing irreversible joint damage. This results in a significant financial burden and severely affects the patients’ physical and mental health. 1 – 4 A recent meta-analysis estimated an annual direct medical cost in the US for RA of $ 12,509 for all patients using any treatment regimen and $ 36,053 for biologic users. Therefore, it is important to conduct a comprehensive assessment of the burden and trends of RA to gain a more nuanced understanding of its impact on the health of populations, so that the most accurate responses can be made. The Global Burden of Disease (GBD) for RA was first reported as part of the GBD in 1990, and these data were comprehensively updated in GBD 2010 and reported in a separate report on the Global Burden of Rheumatoid Arthritis (GBRAR) in 2014, where the data were updated and expanded; it has been a long time since the latest data have been available since 2017 for RA was conducted again. 5 , 6 An article by GBD 2021 Rheumatoid Arthritis Collaborators states that over the past three decades, the global mortality rate for RA has declined. During the same period, the global age-standardized prevalence and YLD have increased, and it is projected that by 2050, there will be 317,000 (25.8–39.0) people with RA worldwide. However, the disease burden of RA in 2021 was not addressed, and estimated annual percentage change (EAPC) and cluster analyses were not performed 7 . With the rapid advancement of society and emergence of the precision medicine era, the demand for high-resolution, real-time data on RA has escalated markedly. However, a profound deficiency and lag in current data availability present a critical bottleneck. This updated analysis is essential to help overcome this bottleneck by providing contemporary estimates, thereby aiding the formulation of effective public health strategies, optimizing clinical diagnosis and treatment, rationalizing resource allocation, enabling scientific disease management, and facilitating research and innovation. Therefore, this study aimed to analyze the global burden and trends of RA from 1990 to 2021 using the latest GBD 2021 data. Specifically, we stratified global trends by age, sex, and sociodemographic index (SDI) and analyzed the burden and trends at the national and regional levels. Material and methods Overview GBD 2021 is a systematic analysis of health losses caused by 369 diseases, injuries, risk factors, impairments, and causes of death. GBD 2021 estimated RA mortality, incidence, prevalence, and associated disability by year, age, and sex for 204 countries and territories, using a Bayesian meta-regression tool, DisMod-MR 2.1. Data are reported by country, region, and super-region, with super-regions based on epidemiological similarity and geographical proximity. The GBD estimated the prevalence of RA in all countries. For most disease models in the GBD, the input data were not available for every location where the prevalence was estimated. In these cases, prevalence estimates in DisMod-MR 2.1 were made through two main mechanisms: (1) an analytical cascade with initial models at more aggregate levels (global, super-region, and regional), with information from such models passed as priors to models at the geographical level below; and (2) predictive covariates. In regions with no data, the estimates are informed by super-regional priors. GBD adheres to the GATHER statement.14 This article was produced as part of the GBD Collaborator Network and in accordance with the GBD protocol9. Data sources All data used in this study were sourced directly from the latest 2021 GBD of Disease Study. The 2021 GBD study encompasses data on 371 diseases and injuries as well as 88 major risk factors across 204 countries and territories. 8 , 9 Estimates in the GBD 2021 database were derived from vital registration systems, vital registration samples, cause-of-death autopsies, survey record data from the Global Health Data Exchange, and the GBD Population Health Data Repository. The existing literature provides comprehensive descriptions of the methods used to estimate the burden of fatal and nonfatal diseases. 10 A more detailed description of the GBD protocol can be found online ( https://www.healthdat . cresearch-analysis/about-gbd/protocol). Ethical reviews were not required for this study because the GBD 2021 database is publicly accessible. The reference case definition for RA was based on the 1987 guidelines of the American College of Rheumatology (ACR 1987), 13 which explain seven diagnostic criteria (1. morning stiffness, 2. arthritis in three or more joint areas; and 3. symmetric arthritis, and 4. arthritis of hand, 5. rheumatoid nodules, 6. serum rheumatoid factor level; and 7. radiographic changes), four of which must be satisfied for a diagnosis. Criteria 1–4 must have been present for at least 6 weeks. 11 This study utilized the Global Health Data Exchange Results Tool to query the data ( https://vizhub.healthdat . cgbd-results/). “Rheumatoid arthritis” was designated as the cause of the disease. “Prevalence,” “incidence,” and “disability-adjusted life years (DALYs),” as well as their corresponding age-standardized rates (ASRs), were selected as the evaluation indicators. Subsequently, the retrieved data were collected according to years, levels of socioeconomic development, countries and regions, sex, and various age groups. All raw data are summarized in Supplementary Table I. Statistical analysis The number of incident cases, prevalent cases, DALYs, and their respective ASRs were obtained directly from the GBD 2021. All ASRs were reported per 100,000 individuals. The 95% uncertainty intervals (UIs) were defined by the 2.5th and 97.5th percentiles of the ordered 1,000 estimates derived from the GBD algorithm. To track the trend in ASRs between 1990 and 2021, the EAPC was determined using a linear regression model to determine the 95% confidence interval (CI) for the EAPC. A linear regression line was constructed using the natural logarithm of the fitted rate (represented by the equation y = α + β x + ε, where x denotes the calendar year and y is the logarithm of the rate), and the calendar year was designated as the dependent variable. The EAPC was calculated as 100 * (exp(β) − 1). If both the EAPC value and the lower limit of the 95% CI were greater than 0, the ASR was considered increasing; conversely, if both the EAPC value and the upper limit of the 95% CI were less than 0, the ASR was considered decreasing. Hierarchical cluster analysis was conducted based on the EAPC values to characterize patterns in the evolving burden of disease across GBD regions and identify groups exhibiting similar trajectories. All 45 GBD regions were categorized into four distinct clusters: significant increase, modest increase, relative stability or slight decline, and significant decrease. Furthermore, frontier analyses were conducted based on the three ASRs and SDIs to evaluate the untapped health potential of each country or region according to its level of development. Analyses were performed in the study using R programming language (version 4.3.2) and several R software packages, including ggplot2, dplyr, purrr, tidyr, and ggsci. Results Global trends As depicted in Fig. 1 and Table I, the global incidence of RA increased markedly from 1990 to 2021, with rates escalating from 10.42 per 100,000 population [95% UI: 9.32–11.64] in 1990 to 11.8 per 100,000 population [95% UI: 10.64–13.12] in 2021, reflecting an EAPC of 0.49 [95% CI: 0.46–0.52]. Consequently, the age-standardized prevalence rate (ASPR) of RA surged between 1990 and 2021, increasing from 182.54 per 100,000 population [161.59–207.48] in 1990 to 208.9 per 100,000 population [186.34–236.33] in 2021, with an EAPC of 0.53 (0.5–0.57). The age-standardized disability-adjusted life years (ASDR) attributable to RA between 1990 and 2021 decreased from 36.42 per 100,000 population [28.71–46] in 1990 to 35.89 per 100,000 population [26.95–46.46] in 2021, with an EAPC of 0.05 (0.01–0.1). Compared to data from 1990, the global incidence of RA, number of prevalent cases, and DALYs increased by factors of 1.05, 1.25, and 0.98, respectively (incidence: 1000319 in 2021 vs. 488269 in 1990; prevalence: 17924667 in 2021 vs. 7959055 in 1990; DALYs: 3075303 in 2021 vs. 1545699 in 1990) (Supplementary Table II). The global subscale in Supplementary Table I presents detailed data on the RA incidence and DALYs for each year from 1990 to 2021. SDI trends In 2021, the age-standardized incidence rate (ASIR) of RA showed the most pronounced increase in the low-middle SDI quintile, with an EAPC of 1.03 (95% CI: 0.98–1.08; from 9.72 per 100,000 population [8.61–10.95] in 1990 to 11.9 per 100,000 population [10.67–13.38] in 2021), followed by the low SDI quintile (EAPC: 0.83 [0.73–0.92]), high-middle SDI quintile (EAPC: 0.38 [0.35–0.42]), middle SDI quintile (EAPC: 0.71 [0.69–0.74]), and high SDI quintile (EAPC: 0.33 [0.26–0.4]). The ASPR of RA showed a similar trend; ASPR increased substantially across all countries with varying SDI quintiles, with the most significant rise observed in the low-middle SDI quintile, exhibiting an EAPC of 1.19 (95% CI: 1.12–1.27; from 121.21 per 100,000 population [105.91–140.23] in 1990 to 168.37 per 100,000 population [149.42–192.37] in 2021), followed by the low SDI quintile (EAPC: 0.89 [0.78–1.01]), high-middle SDI quintile (EAPC: 0.76 [0.73–0.78]), middle SDI quintile (EAPC: 0.72 [0.69–0.75]), and high SDI quintile (EAPC: 0.37 [0.3–0.44]). The ASDR in the high SDI quintile showed a declining trend, with an EAPC of -0.27 (95% CI: -0.31–-0.22; from 49.57 per 100,000 population [38.84–62.18] in 1990 to 44.15 per 100,000 population [32.56–58.11] in 2021) (Table I). The high-SDI quintile exhibited the highest ASIR, ASPR, and ASDR values for RA from 1990 to 2021 (Fig. 2 ). In 2021, the number of RA incident cases, prevalent cases, and DALYs in the middle SDI quintile reached 0.32 million (32.2%), 5.79 million (32.3%), and 1.01 million (33.0%), respectively. 54 GBD regional trends As shown in Fig. 3 and Table I, the most significant increase in ASIR for RA between 1990 and 2021 was observed in Andean Latin America (from 13.57 cases per 100,000 population [95% UI: 12.25–15.03] in 1990 to 21.72 cases per 100,000 population [19.62–23.94] in 2021), with an EAPC of 1.62 (1.57–1.67); Northern Africa (from 3.01 cases per 100,000 population [2.57–3.51] in 1990 to 4.76 cases per 100,000 population [4.11–5.45] in 2021), with an EAPC of 1.48 (1.41–1.56); and Southern Latin America (from 9.44 cases per 100,000 population [8.41–10.52] in 1990 to 14.75 cases per 100,000 population [13.28–16.19] in 2021), with an EAPC of 1.41 (1.33–1.49). Similarly, the regions exhibiting the most substantial increases in ASDR for RA between 1990 and 2021 were Central Asia (from 17.97 per 100,000 population [12.39–25.51] in 1990 to 28.71 per 100,000 population [20.66–39.12] in 2021), with an EAPC of 1.75 (1.6–1.9); Northern Africa (from 10.29 per 100,000 population [7.38–13.99] in 1990 to 15.25 per 100,000 population [10.67–20.84] in 2021), with an EAPC of 1.36 (1.31–1.41); and Middle East and North Africa (from 11.05 per 100,000 population [7.96–15.18] in 1990 to 15.51 per 100,000 population [10.93–21.07] in 2021), with an EAPC of 1.19 (1.13–1.24). Additionally, the cluster analysis of the EAPC (Fig. 4 ) revealed a significantly increasing trend in the burden of RA from 1990 to 2021 in Central Asia. In 2021, the highest ASPR for RA is observed in the Andean region of Latin America. The highest ASIR for RA is observed in the Australasia. The highest ASDR for RA was observed in Central Latin America. Asia reported the highest numbers of RA prevalent cases, incident cases, and DALYs, with 10.3 million cases (9.14%), 0.598 million cases (9.40%), and 1.82 million DALYs (10.1%), respectively (Supplementary Table II). National trends As depicted in Fig. 5 , the most significant increase in ASIR for RA between 1990 and 2021 was observed in Equatorial Guinea (from 5.4 cases per 100,000 population [95% UI: 4.83–6.01] in 1990 to 9.04 cases per 100,000 population [8.08–10.12] in 2021), with an EAPC of 2.03 (1.87–2.18); Oman (from 2.41 cases per 100,000 population [2.05–2.83] in 1990 to 4.31 cases per 100,000 population [3.66–5.04] in 2021), with an EAPC of 1.91 (1.87–1.95); and Albania (from 5.06 cases per 100,000 population [4.32–5.87] in 1990 to 8.39 cases per 100,000 population [7.29–9.65] in 2021), with an EAPC of 1.86 (1.79–1.94). All three countries experienced the most significant increase in the ASPR and DALYs for RA between 1990 and 2019. In 2021, China, India, and the United States had the highest number of RA cases, accounting for 24.74% (n = 247307), 19.86% (n = 198511), and 8.15% (n = 81505) of the global total, respectively. They also represented significant proportions of the global prevalence of RA, with 4755487 (26.55%), 2766749 (15.45%), and 1459692 (8.15%) global cases. Global trends by sex The ASIR for RA increased globally in both men and women between 1990 and 2019 (Fig. 6 ). The EAPC was 0.49 (95% CI: 0.46–0.52; from 10.42 per 100 000 population [95% CI: 10.42 9.32–11.64] in 1990 to 11.8 per 100 000 population [10.64–13.12] in 2021) for females and 0.53 (95% CI: 0.5–0.56; from 6.39 per 100 000 population [5.66–7.22] in 1990 to 7.33 per 100 000 population [6.56–8.26] in 2021) for males. Consequently, the ASPR for RA also rose in both females (EAPC: 0.52 [0.48–0.55]) and males (EAPC: 0.61 [0.58–0.64]) between 1990 and 2021. The DALYs for RA trends were relatively stable in both males and females between 1990 and 2021, with an EAPC of 0.03 (95% CI: -0.02–0.07; from 50.02 per 100,000 population [39.24–63.67] in 1990 to 48.93 per 100,000 population [36.37–64.28] in 2021) for females and an EAPC of 0.18 (95% CI: 0.18 [0.13–0.22]; from 21.57 per 100,000 population [16.88–27.54] in 1990 to 22.06 per 100,000 population [16.91–28.53] in 2021) for males. Global trends by age group Globally, the most substantial increase in ASIR for RA between 1990 and 2021 was observed in individuals aged 65–69 years, with an EAPC of 0.92 (95% UI: 0.83–1.01; from 28.29 per 100,000 population in 1990 [95% UI: 17.74–39.25] to 34.73/100,000 population in 2021 [22.56–47.51]). This was followed by those aged 70–74 years (EAPC: 0.85 [0.78–0.92]) and 60–64 years (EAPC: 0.67 [0.57–0.76]). However, the most substantial increase in the ASIR of RA was noted in individuals aged 95 + years, with an EAPC of 0.79 (95% CI: 0.69–0.89; from 450.76 per 100,000 population in 1990 [95% UI: 1396.67–512.86] to 565.25 per 100,000 population in 2021 [499.87–643.11]). As for the ASDR, the fastest growth rate was observed in those aged 70–74 years, with an EAPC of 0.37 (95% CI: 0.34–0.41; from 19.9 per 100,000 population in 1990 [95% UI: 13.42–29.51] to 21.89 per 100,000 population in 2021 [14.63–33.18]) (Supplementary Table II). The ASIR for RA among individuals aged 65–69 years reached its peak between 1990 and 2021 (Fig. 7 ). Additionally, the ASPR for RA exhibited a progressive upward trajectory with advancing age over the same period; however, the ASDR tended towards relative stability over time. Frontier analysis As shown in Fig. 8 and Supplementary Table III, the five countries exhibiting the greatest absolute differences in ASPR in 2021 were the Bolivarian Republic of Venezuela, Denmark, the Netherlands, Cyprus, and New Zealand, with values ranging from 281.45 to 359.16 per 100,000 population. With respect to the ASIR, the largest disparities were observed in Canada, Honduras, Chile, the Netherlands, and Cyprus, ranging from 18.71 22.56. In terms of ASDR, the most pronounced differences were noted in the plurinational states of Bolivia, Costa Rica, Estonia, Peru, and Honduras, with rates spanning from 51.79 to 75.89 per 100,000 people. Discussion Although RA can be better controlled by standardized treatment, the level of treatment is inconsistent and unequal worldwide and remains incurable. As elaborated above, the prolonged presence of this autoimmune disease has caused direct physical, psychological, and economic damage to people worldwide and has increased GBD 12 – 14 . Therefore, epidemiological studies are urgently needed. To the best of our knowledge, this is the first study to analyze the epidemiology of RA in a large sample of patients during the 1990–2021 period using the GBD2021 database. In this study, we examined the disease burden and trends of RA at the global, regional, and national levels and for all populations within this period using age, sex, and SDI. This study revealed a marked increase in both the prevalence and incidence of RA over the three-decade period from 1990 to 2021. These trends reflect improvements in socioeconomic conditions and the accelerating pace of global population aging. Additionally, heightened awareness of RA, coupled with expanded screening efforts, may have contributed to greater case ascertainment, thereby inflating both the incidence and prevalence estimates. Notably, the relative stabilization of DALYs over the same period suggests that earlier detection and timely therapeutic intervention may mitigate the overall disease burden. 15 This stabilization or decline in DALYs, which stands in contrast to the upward trajectory observed in earlier studies, may be attributable to the widespread adoption of novel antirheumatic therapies, particularly biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs), as well as the increasing implementation of evidence-based treatment strategies focused on early intervention and tight disease control, such as the treat-to-target approach. 16 , 17 Our results indicated that the prevalence, incidence, and DALYs of RA were significantly higher in women than in men. In 2021, the prevalence in women was 2.6 times higher than that in men, and the incidence in women was 2.3 times higher than that in men. The DALYs and incidence in women were 2.3 times higher than those in men and 2.4 times higher than those in men in 2021, and the rate of increase was also significantly higher than that of men. This may be attributed to hormonal influences, genetic predispositions, alterations in immune system function, environmental exposure, and social determinants. 3 , 18 During 1990–2021, the ASDR in all age groups tended to increase, peaking in 2021. Among all age groups, the incidence of RA was high in the 60–74-year age group. As we age, the immune system wanes, and the body's natural aging process, changes in hormone levels, and the accumulation of low-grade inflammation in the body over time increase the risk of developing the disease. Some individuals have a family history or a specific genotype, and the probability of RA in this group of patients gradually increases as they grow and develop. People over the age of 60 tend to have a variety of chronic conditions (e.g., high blood pressure and diabetes), and the lifestyle of older adults (e.g., physical inactivity and unhealthy diets) may also have an impact on joint health to some degree. Over the past 30 years, both the ASIR and ASDR of RA have shown increasing trends across all SDI regions. ASIR and ASDR in middle, high-middle, and high SDI quintiles were significantly higher than those in the low-middle and low SDI quintiles, with the high-middle SDI quintile showing the highest ASIR and ASDR values. This aligns with the findings of previous research. Potential reasons for this phenomenon could be as follows: (1) lifestyle and dietary habits (high SDI regions are often associated with modern lifestyles, including unhealthy dietary habits such as high intake of processed foods and low dietary fiber, which may lead to obesity and metabolic syndrome, thereby increasing the risk of RA; (2) environmental factors, such as high levels of pollution or other environmental risks, including exposure to chemicals, which could trigger autoimmune diseases; and (3) other reasons such as medical diagnosis and reporting, genetic factors, and psychosocial factors. From 1990 to 2021, the ASIR of RA increased the most in Andean Latin America, Northern Africa, and Southern Latin America, with Andean Latin America having the highest ASIR among the 54 regions in 2021. This is consistent with the conclusions of previous studies. Our comprehensive analysis reveals that similar characteristics exist in these areas. On the one hand, there is the geomorphological features: the rugged terrain is mostly mountainous. Economic development has been slow, mostly in the agricultural sector. Moreover, there are education and health concerns. 19 , 20 However, all of these areas are at high altitudes, and some studies have pointed out that the people living at high altitudes showed microflora enriched with butyrate-producing bacteria in response to harsh environments, and the core microbiota comprised Prevotella, Faecalibacterium, and Blautia in Tibetans. 21 Moreover, it was reported that the presence of Prevotella is strongly correlated with disease in patients with new-onset untreated RA (NORA). 22 In addition, the lack of oxygen at high altitudes can enhance certain immune responses, thus aggravating the symptoms of RA. 23 Healthcare systems in the high-income Asia-Pacific region are typically well developed, providing better health screening, early diagnoses, and timely treatments. This facilitates the identification and management of patients with RA, thereby reducing incidence rates and disease progression. Additionally, the availability of biologics and other novel therapies in this region has made RA treatment more effective, improving patients' quality of life and potentially decreasing the number of new cases. 24 In high-income areas, there is an increased public awareness of RA and its risk factors (such as smoking and obesity), promoting the adoption of preventive measures. Furthermore, societal interventions aimed at lifestyle modifications, such as health promotion programs advocating for better diet and exercise, have positively impacted obesity rates and overall health, thereby lowering the risk of RA. Epidemiological studies in high-income regions can promptly identify disease trends and implement corresponding public health measures. 25 , 26 Conversely, the uneven distribution of healthcare resources in Andean Latin America, Northern Africa, and Southern Latin America has resulted in some populations being unable to access timely and appropriate medical interventions and disease management. As these regions undergo rapid social modernization, many traditional healthy lifestyles may be abandoned, leading to changes in lifestyle, dietary habits, and environmental issues that may increase the incidence of chronic diseases. 19 Among the countries analyzed, Equatorial Guinea, Oman, and Albania exhibited the fastest growth in the ASIR from 1990 to 2021. An analysis of the reasons reveals that these three countries are classified as low-to middle-income nations. Although Oman has a relatively good economy, Equatorial Guinea and Albania face significant economic challenges. Limited healthcare resources, public health infrastructure, and health education in these countries adversely affect the management and treatment of RA. Our analysis reveals that the three all exhibit significant marine geographical characteristics with high humidity. We therefore hypothesized that high humidity may be the cause of rheumatoid joint arthritis. 24 , 27 On the one hand, a high humidity environment may promote water retention in the body, increase tissue edema around the joints, and aggravate the inflammatory response. In addition, high humidity may change the local microenvironment, affecting the activity of immune cells and the release of inflammatory factors, further aggravating the condition, and on the other hand, cold and humid environment may cause blood circulation to slow down, making the local blood supply to the joints insufficient, exacerbating pain and stiffness. In addition, dampness may aggravate patient discomfort by stimulating nerve endings and amplifying pain signals. 28 Furthermore the early economic foundations in these regions lead to insufficient disease detection and management, resulting in an underestimation of RA incidence. However, with recent economic improvements, increased detection rates have significantly contributed to the increase in ASIR in these countries. In 2021, China, India, and the United States will report the highest number of incident RA cases, representing a substantial proportion of the global prevalence of RA. Research indicates that China and India are the two most populous countries worldwide, each with over one billion inhabitants. While the United States has a smaller population, it remains a significant population center. This natural increase in the total population led to a corresponding increase in the number of RA cases. Over the past 30 years, improvements in living standards and healthcare conditions have resulted in an increasing proportion of the elderly population in China, India, and the United States. Additionally, lifestyle factors such as sedentary behavior, unhealthy diets, and increased stress levels are associated with an increased risk of developing RA. Furthermore, as China and India experience rapid economic growth, their healthcare systems are advancing, leading to more diagnoses and better record-keeping of RA cases. However, certain cities in China and India face severe air pollution issues owing to rapid industrial development, which may further contribute to the increased incidence of RA. We found that Cyprus, Honduras, and the Netherlands have significant increases in these categories. Our combined analysis led to the following conclusions: all three countries are located next to the ocean, with Cyprus in the Mediterranean Sea, Honduras near the Caribbean Sea, and the Netherlands with an extensive North Sea coastline. The relatively high prevalence of smoking in all three locations may be associated with an increased prevalence. 29 , 30 Currently, there is no cure for RA, and its progression can lead to irreversible joint changes, resulting in joint deformities that severely impact the quality of life and exacerbate the disease burden. Therefore, epidemiological research on RA is critical. We conducted a detailed study of RA based on the GBD 2021 data. Our findings revealed that the incidence was higher among female patients than among males, with the highest incidence rates observed in the elderly population aged 60–74 years. Additionally, higher incidence rates were found in the low-middle and low SDI quintiles as well as in regions such as Andean Latin America, Northern Africa, Southern Latin America, Equatorial Guinea, Oman, and Albania. Venezuela, Denmark, the Netherlands, Cyprus, and New Zealand also have high incidence rates. Thus, in future disease management, we must focus on these populations and develop strategies to minimize the disease burden as much as possible. The principal limitations of this study arose from the intrinsic characteristics and methodological framework of the GBD dataset. At the data acquisition level, the GBD synthesizes information from diverse and often heterogeneous sources; however, the completeness and reliability of these health data remain uncertain, particularly in regions with underdeveloped civil registration and vital statistics systems. At the level of disease definition and adjudication, although the GBD employs standardized case definitions, variations in clinical practice, diagnostic implementation, and medical coding across countries introduce substantial heterogeneity in the identification of RA cases within the primary data. Furthermore, at the modelling level, estimates for comparable diseases within the same region may vary owing to differences in methodology, introducing inherent uncertainty that complicates both temporal and geographical comparisons and limits the interpretability of point estimates with precision. Conclusion Given the disproportionate and rising burden of RA in resource-constrained regions, particularly in low- and lower-middle SDI areas such as Andean Latin America and North Africa, and its pronounced impact on individuals aged 60–69 years, we urge public health policymakers and international health organizations to take immediate action. First, resources for RA prevention and control, including screening, diagnosis, accessible treatment, and patient education, must be prioritized in low- and lower-middle SDI settings. Second, cost-effective strategies for the early detection and standardized management of RA should be developed and implemented, with a particular focus on populations aged 60–69 years. These measures are essential to mitigate disease burden and forestall disability in this vulnerable population. Declarations Acknowledge The authors would like to express their gratitude to all the participants of the GBD study. Data availability statement The datasets generated and analysed during the current study are available in the GBD repository, https://vizhub.healthdata.org/gbd-results/. Ethics statement According to local regulations and institutional requirements, this study did not necessitate ethical review and approval. Conflict of interest The authors declare no competing interests. Funding ： This study was supported by grants from Hangzhou Science and Technology Planning Project (NO. 20220919Y084 to Weibin Du), Zhejiang Province Traditional Chinese Medicine Science and Technology Project (NO. 2023ZR046 to Weibin Du) and Hangzhou bio-medicine and health industry development support science and technology project (NO. 2023WJC243, 2023WJC249 to Weibin Du). Exploration Project of Natural Science Foundation of Zhejiang Province (Q24H270079 to Zhengcong Ye), Zhejiang Provincial Medical and Health Science and Technology Program (2024KY1446 to Zhengcong Ye) Clinical trial number not applicable. References Cush, J. J. Rheumatoid Arthritis: Early Diagnosis and Treatment. Rheum Dis Clin North Am 48 , 537-547 (2022). https://doi.org:10.1016/j.rdc.2022.02.010 Shen, X. et al. Systematic review of Janus kinases inhibitors for rheumatoid arthritis: methodology, reporting, and quality of evidence evaluation. 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The Key Comorbidities in Patients with Rheumatoid Arthritis: A Narrative Review. J Clin Med 10 (2021). https://doi.org:10.3390/jcm10030509 Yuan, L. et al. Global, regional, national burden of asthma from 1990 to 2021, with projections of incidence to 2050: a systematic analysis of the global burden of disease study 2021. EClinicalMedicine 80 , 103051 (2025). https://doi.org:10.1016/j.eclinm.2024.103051 Smolen, J. S. et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2022 update. Ann Rheum Dis 82 , 3-18 (2023). https://doi.org:10.1136/ard-2022-223356 Roodenrijs, N. M. T. et al. Pharmacological and non-pharmacological therapeutic strategies in difficult-to-treat rheumatoid arthritis: a systematic literature review informing the EULAR recommendations for the management of difficult-to-treat rheumatoid arthritis. RMD Open 7 (2021). https://doi.org:10.1136/rmdopen-2020-001512 Yang, J. & Li, Q. 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Mater Sociomed 27 , 172-175 (2015). https://doi.org:10.5455/msm.2015.27.172-175 Wang, H. et al. High Humidity Alters Myeloid-Derived Suppressor Cells in Spleen Tissue: Insights into Rheumatoid Arthritis Progression. J Inflamm Res 17 , 9805-9822 (2024). https://doi.org:10.2147/jir.S490860 van der Woude, D. & van der Helm-van Mil, A. H. M. Update on the epidemiology, risk factors, and disease outcomes of rheumatoid arthritis. Best Pract Res Clin Rheumatol 32 , 174-187 (2018). https://doi.org:10.1016/j.berh.2018.10.005 van Delft, M. A. M. & Huizinga, T. W. J. An overview of autoantibodies in rheumatoid arthritis. J Autoimmun 110 , 102392 (2020). https://doi.org:10.1016/j.jaut.2019.102392 Table Table 1. The number of incidences, prevalence, DALYs, and the corresponding ASRs and EAPCs for rheumatoid arthritis at the global, gender, age, country or region level in 2021. Region Incidence Prevalence DALYs number in 2021 (95% UI) ASIR per 100,000 population (95% UI) EAPC from 2019 to 2021 (95% CI) number in 2021(95% UI) ASPR per 100,000 population (95% UI) EAPC from 2019 to 2021 (95% CI) number in 2021 (95% UI) ASDR per 100,000 population (95% UI) EAPC from 2019 to 2021 (95% CI) Global 1000319 (902687-1114213) 11.8 (10.64-13.12) 0.49 (0.46-0.52) 17924667 (15973178-20303303) 208.9 (186.34-236.33) 0.53 (0.5-0.57) 3075303 (2310381-3974046) 35.89 (26.95-46.46) 0.05 (0.01-0.1) Female 695501 (628227-772973) 16.23 (14.65-18) 0.46 (0.43-0.49) 12975146 (11647165-14611571) 293.66 (263.52-331.33) 0.52 (0.48-0.55) 2177017 (1627793-2845902) 48.93 (36.37-64.28) 0.03 (-0.02-0.07) Male 304818 (272328-342831) 7.33 (6.56-8.26) 0.53 (0.5-0.56) 4949521 (4369799-5705323) 119.68 (105.95-137.45) 0.61 (0.58-0.64) 898287 (684568-1168744) 22.06 (16.91-28.53) 0.18 (0.13-0.22) 65-69 years 95800 (62225-131039) 34.73 (22.56-47.51) 0.92 (0.83-1.01) 1997899 (1722725-2323991) 724.29 (624.53-842.51) 0.56 (0.49-0.64) 364307 (285629-466155) 132.07 (103.55-168.99) -0.1 (-0.15-0.04) 70-74 years 70639 (43927-102813) 34.32 (21.34-49.95) 0.85 (0.78-0.92) 1659306 (1447190-1907391) 806.12 (703.07-926.64) 0.57 (0.5-0.63) 324954 (258607-404088) 157.87 (125.64-196.31) -0.12 (-0.17-0.07) 60-64 years 98434 (62903-141685) 30.76 (19.65-44.27) 0.67 (0.57-0.76) 1948105 (1678737-2265243) 608.69 (524.53-707.78) 0.53 (0.46-0.6) 333859 (251419-438473) 104.32 (78.56-137) -0.06 (-0.13-0) High-middle SDI 190166 (169306-213515) 11.66 (10.43-12.97) 0.77 (0.75-0.8) 3839358 (3402908-4364606) 213.28 (188.45-242.99) 0.76 (0.73-0.78) 646310 (482517-842256) 35.53 (26.33-46.93) 0.31 (0.26-0.35) High SDI 255315 (231186-282039) 16.88 (15.44-18.47) 0.33 (0.26-0.4) 4823674 (4405653-5320056) 282.73 (256.44-313.88) 0.37 (0.3-0.44) 774616 (579737-998733) 44.15 (32.56-58.11) -0.27 (-0.31--0.22) Low-middle SDI 180057 (160663-202101) 10.49 (9.36-11.78) 1.03 (0.98-1.08) 2731071 (2419932-3150263) 168.37 (149.42-192.37) 1.19 (1.12-1.27) 513042 (391548-655665) 33.46 (26.23-41.97) 0.64 (0.59-0.68) Low SDI 52398 (46046-59971) 7.04 (6.27-7.92) 0.83 (0.73-0.92) 726534 (623789-855562) 110.98 (98.21-127.44) 0.89 (0.78-1.01) 125255 (90153-167106) 20.81 (15.75-27.17) 0.6 (0.51-0.7) Middle SDI 321824 (287295-361682) 11.9 (10.67-13.38) 0.71 (0.69-0.74) 5792479 (5116784-6613510) 209.61 (185.51-238.44) 0.72 (0.69-0.75) 1014159 (761009-1317131) 37.22 (28.13-48.12) 0.24 (0.17-0.3) Andean Latin America 14555 (13019-16096) 21.72 (19.62-23.94) 1.62 (1.57-1.67) 279947 (247543-315605) 432.76 (384.44-486.44) 1.76 (1.69-1.82) 43359 (30922-57568) 67.82 (48.77-89.56) 0.95 (0.87-1.03) Northern Africa 10002 (8576-11495) 4.76 (4.11-5.45) 1.48 (1.41-1.56) 193365 (161799-228806) 97.89 (82.58-115.07) 1.46 (1.39-1.54) 29634 (20595-40901) 15.25 (10.67-20.84) 1.36 (1.31-1.41) Southern Latin America 11285 (10211-12405) 14.75 (13.28-16.19) 1.41 (1.33-1.49) 215374 (193283-241137) 267.62 (239.07-301.08) 1.54 (1.44-1.63) 36211 (27300-47553) 44.56 (33.32-58.57) 1.02 (0.89-1.14) Equatorial Guinea 91 (79-106) 9.04 (8.08-10.12) 2.03 (1.87-2.18) 1213 (1026-1430) 155.44 (137.26-176.62) 2.31 (2.13-2.49) 166 (109-240) 20.99 (14.27-30.24) 1.89 (1.73-2.04) Oman 214 (172-257) 4.31 (3.66-5.04) 1.91 (1.87-1.95) 3844 (3095-4705) 87.16 (72.44-104.46) 2.03 (1.99-2.07) 548 (355-804) 12.67 (8.61-18.09) 1.87 (1.81-1.92) Albania 269 (233-311) 8.39 (7.29-9.65) 1.86 (1.79-1.94) 5785 (4946-6767) 156.6 (132.78-183.48) 1.86 (1.79-1.94) 905 (649-1238) 24.15 (16.85-33.49) 0.74 (0.64-0.84) Abbreviations: UI, uncertainty interval; CI, confidence interval; DALYs, disability-adjusted life years; EAPC, estimated annual percentage change; ASIR, age standardized incidence rate; ASPR, age standardized prevalence rate; ASDR, age standardized DALYs rate Additional Declarations No competing interests reported. Supplementary Files Supplementarytable1rawdata.xlsx Supplementarytable2.xlsx Supplementarytable3.xlsx Cite Share Download PDF Status: Published Journal Publication published 03 Oct, 2025 Read the published version in BMC Rheumatology → Version 1 posted Editorial decision: Revision requested 21 Jul, 2025 Reviews received at journal 20 Jul, 2025 Reviews received at journal 19 Jul, 2025 Reviewers agreed at journal 18 Jul, 2025 Reviews received at journal 16 Jul, 2025 Reviewers agreed at journal 16 Jul, 2025 Reviewers agreed at journal 14 Jul, 2025 Reviewers agreed at journal 13 Jul, 2025 Reviewers agreed at journal 11 Jul, 2025 Reviewers invited by journal 10 Jul, 2025 Editor invited by journal 08 Jul, 2025 Editor assigned by journal 07 Jul, 2025 Submission checks completed at journal 07 Jul, 2025 First submitted to journal 03 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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of prevalence, incidence, death, DALYs, and ASRs for RA in different age groups from 1990 to 2021.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7036091/v1/1e49c2bd5e972ba69142dd3f.png"},{"id":86777204,"identity":"cf558481-0538-4681-99be-fc64cb995265","added_by":"auto","created_at":"2025-07-15 12:48:46","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":280424,"visible":true,"origin":"","legend":"\u003cp\u003eFrontier analysis of ASIR and ASPR in RA from 1990 to 2021.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7036091/v1/9ac1c5bee7e6f48bb82607d0.png"},{"id":92883884,"identity":"e40e750d-e37e-4480-8152-98bc4146b5f7","added_by":"auto","created_at":"2025-10-06 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12:48:45","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":105341,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7036091/v1/36ecf5c13562be1bbf557117.xlsx"},{"id":86778810,"identity":"bc616094-0063-47cc-b580-2d7dd2614cc2","added_by":"auto","created_at":"2025-07-15 13:04:45","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":20702,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7036091/v1/342874874e19d1637d955894.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rheumatoid arthritis continues to increase in low-middle SDI and low SDI quintiles based on GBD 1990–2021 ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRheumatoid arthritis (RA) is an autoimmune disease characterized primarily by synovial inflammation. It can occur at any age and is associated with a high risk of disability. The precise etiology of RA remains incompletely understood but involves a complex interplay of genetic susceptibility, environmental triggers (such as smoking or infection), hormonal factors, and dysregulated immune responses. A key pathophysiological mechanism of RA involves the dysregulation of citrullination. This process, which is potentially initiated or amplified by the aforementioned etiological factors, particularly in genetically predisposed individuals, leads to the formation of citrullinated proteins. These abnormal proteins can breach immune tolerance and drive the production of highly specific anti-citrullinated protein antibodies (ACPAs). ACPAs are thought to play a central role in the pathogenesis of RA. If RA is not treated properly, symptoms progressively worsen, causing irreversible joint damage. This results in a significant financial burden and severely affects the patients\u0026rsquo; physical and mental health.\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e A recent meta-analysis estimated an annual direct medical cost in the US for RA of \u003cspan\u003e$\u003c/span\u003e12,509 for all patients using any treatment regimen and \u003cspan\u003e$\u003c/span\u003e36,053 for biologic users. Therefore, it is important to conduct a comprehensive assessment of the burden and trends of RA to gain a more nuanced understanding of its impact on the health of populations, so that the most accurate responses can be made.\u003c/p\u003e\u003cp\u003eThe Global Burden of Disease (GBD) for RA was first reported as part of the GBD in 1990, and these data were comprehensively updated in GBD 2010 and reported in a separate report on the Global Burden of Rheumatoid Arthritis (GBRAR) in 2014, where the data were updated and expanded; it has been a long time since the latest data have been available since 2017 for RA was conducted again.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e An article by GBD 2021 Rheumatoid Arthritis Collaborators states that over the past three decades, the global mortality rate for RA has declined. During the same period, the global age-standardized prevalence and YLD have increased, and it is projected that by 2050, there will be 317,000 (25.8\u0026ndash;39.0) people with RA worldwide. However, the disease burden of RA in 2021 was not addressed, and estimated annual percentage change (EAPC) and cluster analyses were not performed\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWith the rapid advancement of society and emergence of the precision medicine era, the demand for high-resolution, real-time data on RA has escalated markedly. However, a profound deficiency and lag in current data availability present a critical bottleneck. This updated analysis is essential to help overcome this bottleneck by providing contemporary estimates, thereby aiding the formulation of effective public health strategies, optimizing clinical diagnosis and treatment, rationalizing resource allocation, enabling scientific disease management, and facilitating research and innovation.\u003c/p\u003e\u003cp\u003eTherefore, this study aimed to analyze the global burden and trends of RA from 1990 to 2021 using the latest GBD 2021 data. Specifically, we stratified global trends by age, sex, and sociodemographic index (SDI) and analyzed the burden and trends at the national and regional levels.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003e\u003cb\u003eOverview\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGBD 2021 is a systematic analysis of health losses caused by 369 diseases, injuries, risk factors, impairments, and causes of death. GBD 2021 estimated RA mortality, incidence, prevalence, and associated disability by year, age, and sex for 204 countries and territories, using a Bayesian meta-regression tool, DisMod-MR 2.1. Data are reported by country, region, and super-region, with super-regions based on epidemiological similarity and geographical proximity. The GBD estimated the prevalence of RA in all countries. For most disease models in the GBD, the input data were not available for every location where the prevalence was estimated. In these cases, prevalence estimates in DisMod-MR 2.1 were made through two main mechanisms: (1) an analytical cascade with initial models at more aggregate levels (global, super-region, and regional), with information from such models passed as priors to models at the geographical level below; and (2) predictive covariates. In regions with no data, the estimates are informed by super-regional priors. GBD adheres to the GATHER statement.14 This article was produced as part of the GBD Collaborator Network and in accordance with the GBD protocol9.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData sources\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll data used in this study were sourced directly from the latest 2021 GBD of Disease Study. The 2021 GBD study encompasses data on 371 diseases and injuries as well as 88 major risk factors across 204 countries and territories. \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003eEstimates in the GBD 2021 database were derived from vital registration systems, vital registration samples, cause-of-death autopsies, survey record data from the Global Health Data Exchange, and the GBD Population Health Data Repository. The existing literature provides comprehensive descriptions of the methods used to estimate the burden of fatal and nonfatal diseases.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e A more detailed description of the GBD protocol can be found online (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.healthdat\u003c/span\u003e\u003cspan address=\"https://www.healthdat\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. cresearch-analysis/about-gbd/protocol). Ethical reviews were not required for this study because the GBD 2021 database is publicly accessible.\u003c/p\u003e\u003cp\u003eThe reference case definition for RA was based on the 1987 guidelines of the American College of Rheumatology (ACR 1987),\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e which explain seven diagnostic criteria (1. morning stiffness, 2. arthritis in three or more joint areas; and 3. symmetric arthritis, and 4. arthritis of hand, 5. rheumatoid nodules, 6. serum rheumatoid factor level; and 7. radiographic changes), four of which must be satisfied for a diagnosis. Criteria 1\u0026ndash;4 must have been present for at least 6 weeks.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThis study utilized the Global Health Data Exchange Results Tool to query the data (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://vizhub.healthdat\u003c/span\u003e\u003cspan address=\"https://vizhub.healthdat\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. cgbd-results/). \u0026ldquo;Rheumatoid arthritis\u0026rdquo; was designated as the cause of the disease. \u0026ldquo;Prevalence,\u0026rdquo; \u0026ldquo;incidence,\u0026rdquo; and \u0026ldquo;disability-adjusted life years (DALYs),\u0026rdquo; as well as their corresponding age-standardized rates (ASRs), were selected as the evaluation indicators. Subsequently, the retrieved data were collected according to years, levels of socioeconomic development, countries and regions, sex, and various age groups. All raw data are summarized in Supplementary Table I.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eThe number of incident cases, prevalent cases, DALYs, and their respective ASRs were obtained directly from the GBD 2021. All ASRs were reported per 100,000 individuals. The 95% uncertainty intervals (UIs) were defined by the 2.5th and 97.5th percentiles of the ordered 1,000 estimates derived from the GBD algorithm.\u003c/p\u003e\u003cp\u003eTo track the trend in ASRs between 1990 and 2021, the EAPC was determined using a linear regression model to determine the 95% confidence interval (CI) for the EAPC. A linear regression line was constructed using the natural logarithm of the fitted rate (represented by the equation \u003cem\u003ey\u003c/em\u003e\u0026thinsp;=\u0026thinsp;α\u0026thinsp;+\u0026thinsp;β\u003cem\u003ex\u003c/em\u003e\u0026thinsp;+\u0026thinsp;ε, where \u003cem\u003ex\u003c/em\u003e denotes the calendar year and \u003cem\u003ey\u003c/em\u003e is the logarithm of the rate), and the calendar year was designated as the dependent variable. The EAPC was calculated as 100 * (exp(β) \u0026minus;\u0026thinsp;1). If both the EAPC value and the lower limit of the 95% CI were greater than 0, the ASR was considered increasing; conversely, if both the EAPC value and the upper limit of the 95% CI were less than 0, the ASR was considered decreasing. Hierarchical cluster analysis was conducted based on the EAPC values to characterize patterns in the evolving burden of disease across GBD regions and identify groups exhibiting similar trajectories. All 45 GBD regions were categorized into four distinct clusters: significant increase, modest increase, relative stability or slight decline, and significant decrease.\u003c/p\u003e\u003cp\u003eFurthermore, frontier analyses were conducted based on the three ASRs and SDIs to evaluate the untapped health potential of each country or region according to its level of development. Analyses were performed in the study using R programming language (version 4.3.2) and several R software packages, including ggplot2, dplyr, purrr, tidyr, and ggsci.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eGlobal trends\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table I, the global incidence of RA increased markedly from 1990 to 2021, with rates escalating from 10.42 per 100,000 population [95% UI: 9.32\u0026ndash;11.64] in 1990 to 11.8 per 100,000 population [95% UI: 10.64\u0026ndash;13.12] in 2021, reflecting an EAPC of 0.49 [95% CI: 0.46\u0026ndash;0.52]. Consequently, the age-standardized prevalence rate (ASPR) of RA surged between 1990 and 2021, increasing from 182.54 per 100,000 population [161.59\u0026ndash;207.48] in 1990 to 208.9 per 100,000 population [186.34\u0026ndash;236.33] in 2021, with an EAPC of 0.53 (0.5\u0026ndash;0.57). The age-standardized disability-adjusted life years (ASDR) attributable to RA between 1990 and 2021 decreased from 36.42 per 100,000 population [28.71\u0026ndash;46] in 1990 to 35.89 per 100,000 population [26.95\u0026ndash;46.46] in 2021, with an EAPC of 0.05 (0.01\u0026ndash;0.1). Compared to data from 1990, the global incidence of RA, number of prevalent cases, and DALYs increased by factors of 1.05, 1.25, and 0.98, respectively (incidence: 1000319 in 2021 vs. 488269 in 1990; prevalence: 17924667 in 2021 vs. 7959055 in 1990; DALYs: 3075303 in 2021 vs. 1545699 in 1990) (Supplementary Table II). The global subscale in Supplementary Table I presents detailed data on the RA incidence and DALYs for each year from 1990 to 2021.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSDI trends\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn 2021, the age-standardized incidence rate (ASIR) of RA showed the most pronounced increase in the low-middle SDI quintile, with an EAPC of 1.03 (95% CI: 0.98\u0026ndash;1.08; from 9.72 per 100,000 population [8.61\u0026ndash;10.95] in 1990 to 11.9 per 100,000 population [10.67\u0026ndash;13.38] in 2021), followed by the low SDI quintile (EAPC: 0.83 [0.73\u0026ndash;0.92]), high-middle SDI quintile (EAPC: 0.38 [0.35\u0026ndash;0.42]), middle SDI quintile (EAPC: 0.71 [0.69\u0026ndash;0.74]), and high SDI quintile (EAPC: 0.33 [0.26\u0026ndash;0.4]). The ASPR of RA showed a similar trend; ASPR increased substantially across all countries with varying SDI quintiles, with the most significant rise observed in the low-middle SDI quintile, exhibiting an EAPC of 1.19 (95% CI: 1.12\u0026ndash;1.27; from 121.21 per 100,000 population [105.91\u0026ndash;140.23] in 1990 to 168.37 per 100,000 population [149.42\u0026ndash;192.37] in 2021), followed by the low SDI quintile (EAPC: 0.89 [0.78\u0026ndash;1.01]), high-middle SDI quintile (EAPC: 0.76 [0.73\u0026ndash;0.78]), middle SDI quintile (EAPC: 0.72 [0.69\u0026ndash;0.75]), and high SDI quintile (EAPC: 0.37 [0.3\u0026ndash;0.44]). The ASDR in the high SDI quintile showed a declining trend, with an EAPC of -0.27 (95% CI: -0.31\u0026ndash;-0.22; from 49.57 per 100,000 population [38.84\u0026ndash;62.18] in 1990 to 44.15 per 100,000 population [32.56\u0026ndash;58.11] in 2021) (Table I).\u003c/p\u003e\u003cp\u003eThe high-SDI quintile exhibited the highest ASIR, ASPR, and ASDR values for RA from 1990 to 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In 2021, the number of RA incident cases, prevalent cases, and DALYs in the middle SDI quintile reached 0.32\u0026nbsp;million (32.2%), 5.79\u0026nbsp;million (32.3%), and 1.01\u0026nbsp;million (33.0%), respectively.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e54 GBD regional trends\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table I, the most significant increase in ASIR for RA between 1990 and 2021 was observed in Andean Latin America (from 13.57 cases per 100,000 population [95% UI: 12.25\u0026ndash;15.03] in 1990 to 21.72 cases per 100,000 population [19.62\u0026ndash;23.94] in 2021), with an EAPC of 1.62 (1.57\u0026ndash;1.67); Northern Africa (from 3.01 cases per 100,000 population [2.57\u0026ndash;3.51] in 1990 to 4.76 cases per 100,000 population [4.11\u0026ndash;5.45] in 2021), with an EAPC of 1.48 (1.41\u0026ndash;1.56); and Southern Latin America (from 9.44 cases per 100,000 population [8.41\u0026ndash;10.52] in 1990 to 14.75 cases per 100,000 population [13.28\u0026ndash;16.19] in 2021), with an EAPC of 1.41 (1.33\u0026ndash;1.49). Similarly, the regions exhibiting the most substantial increases in ASDR for RA between 1990 and 2021 were Central Asia (from 17.97 per 100,000 population [12.39\u0026ndash;25.51] in 1990 to 28.71 per 100,000 population [20.66\u0026ndash;39.12] in 2021), with an EAPC of 1.75 (1.6\u0026ndash;1.9); Northern Africa (from 10.29 per 100,000 population [7.38\u0026ndash;13.99] in 1990 to 15.25 per 100,000 population [10.67\u0026ndash;20.84] in 2021), with an EAPC of 1.36 (1.31\u0026ndash;1.41); and Middle East and North Africa (from 11.05 per 100,000 population [7.96\u0026ndash;15.18] in 1990 to 15.51 per 100,000 population [10.93\u0026ndash;21.07] in 2021), with an EAPC of 1.19 (1.13\u0026ndash;1.24). Additionally, the cluster analysis of the EAPC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) revealed a significantly increasing trend in the burden of RA from 1990 to 2021 in Central Asia.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn 2021, the highest ASPR for RA is observed in the Andean region of Latin America. The highest ASIR for RA is observed in the Australasia. The highest ASDR for RA was observed in Central Latin America. Asia reported the highest numbers of RA prevalent cases, incident cases, and DALYs, with 10.3\u0026nbsp;million cases (9.14%), 0.598\u0026nbsp;million cases (9.40%), and 1.82\u0026nbsp;million DALYs (10.1%), respectively (Supplementary Table II).\u003c/p\u003e\u003cp\u003e\u003cb\u003eNational trends\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the most significant increase in ASIR for RA between 1990 and 2021 was observed in Equatorial Guinea (from 5.4 cases per 100,000 population [95% UI: 4.83\u0026ndash;6.01] in 1990 to 9.04 cases per 100,000 population [8.08\u0026ndash;10.12] in 2021), with an EAPC of 2.03 (1.87\u0026ndash;2.18); Oman (from 2.41 cases per 100,000 population [2.05\u0026ndash;2.83] in 1990 to 4.31 cases per 100,000 population [3.66\u0026ndash;5.04] in 2021), with an EAPC of 1.91 (1.87\u0026ndash;1.95); and Albania (from 5.06 cases per 100,000 population [4.32\u0026ndash;5.87] in 1990 to 8.39 cases per 100,000 population [7.29\u0026ndash;9.65] in 2021), with an EAPC of 1.86 (1.79\u0026ndash;1.94). All three countries experienced the most significant increase in the ASPR and DALYs for RA between 1990 and 2019. In 2021, China, India, and the United States had the highest number of RA cases, accounting for 24.74% (n\u0026thinsp;=\u0026thinsp;247307), 19.86% (n\u0026thinsp;=\u0026thinsp;198511), and 8.15% (n\u0026thinsp;=\u0026thinsp;81505) of the global total, respectively. They also represented significant proportions of the global prevalence of RA, with 4755487 (26.55%), 2766749 (15.45%), and 1459692 (8.15%) global cases.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eGlobal trends by sex\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe ASIR for RA increased globally in both men and women between 1990 and 2019 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The EAPC was 0.49 (95% CI: 0.46\u0026ndash;0.52; from 10.42 per 100 000 population [95% CI: 10.42 9.32\u0026ndash;11.64] in 1990 to 11.8 per 100 000 population [10.64\u0026ndash;13.12] in 2021) for females and 0.53 (95% CI: 0.5\u0026ndash;0.56; from 6.39 per 100 000 population [5.66\u0026ndash;7.22] in 1990 to 7.33 per 100 000 population [6.56\u0026ndash;8.26] in 2021) for males. Consequently, the ASPR for RA also rose in both females (EAPC: 0.52 [0.48\u0026ndash;0.55]) and males (EAPC: 0.61 [0.58\u0026ndash;0.64]) between 1990 and 2021. The DALYs for RA trends were relatively stable in both males and females between 1990 and 2021, with an EAPC of 0.03 (95% CI: -0.02\u0026ndash;0.07; from 50.02 per 100,000 population [39.24\u0026ndash;63.67] in 1990 to 48.93 per 100,000 population [36.37\u0026ndash;64.28] in 2021) for females and an EAPC of 0.18 (95% CI: 0.18 [0.13\u0026ndash;0.22]; from 21.57 per 100,000 population [16.88\u0026ndash;27.54] in 1990 to 22.06 per 100,000 population [16.91\u0026ndash;28.53] in 2021) for males.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eGlobal trends by age group\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGlobally, the most substantial increase in ASIR for RA between 1990 and 2021 was observed in individuals aged 65\u0026ndash;69 years, with an EAPC of 0.92 (95% UI: 0.83\u0026ndash;1.01; from 28.29 per 100,000 population in 1990 [95% UI: 17.74\u0026ndash;39.25] to 34.73/100,000 population in 2021 [22.56\u0026ndash;47.51]). This was followed by those aged 70\u0026ndash;74 years (EAPC: 0.85 [0.78\u0026ndash;0.92]) and 60\u0026ndash;64 years (EAPC: 0.67 [0.57\u0026ndash;0.76]). However, the most substantial increase in the ASIR of RA was noted in individuals aged 95\u0026thinsp;+\u0026thinsp;years, with an EAPC of 0.79 (95% CI: 0.69\u0026ndash;0.89; from 450.76 per 100,000 population in 1990 [95% UI: 1396.67\u0026ndash;512.86] to 565.25 per 100,000 population in 2021 [499.87\u0026ndash;643.11]). As for the ASDR, the fastest growth rate was observed in those aged 70\u0026ndash;74 years, with an EAPC of 0.37 (95% CI: 0.34\u0026ndash;0.41; from 19.9 per 100,000 population in 1990 [95% UI: 13.42\u0026ndash;29.51] to 21.89 per 100,000 population in 2021 [14.63\u0026ndash;33.18]) (Supplementary Table II). The ASIR for RA among individuals aged 65\u0026ndash;69 years reached its peak between 1990 and 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Additionally, the ASPR for RA exhibited a progressive upward trajectory with advancing age over the same period; however, the ASDR tended towards relative stability over time.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFrontier analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and Supplementary Table III, the five countries exhibiting the greatest absolute differences in ASPR in 2021 were the Bolivarian Republic of Venezuela, Denmark, the Netherlands, Cyprus, and New Zealand, with values ranging from 281.45 to 359.16 per 100,000 population. With respect to the ASIR, the largest disparities were observed in Canada, Honduras, Chile, the Netherlands, and Cyprus, ranging from 18.71 22.56. In terms of ASDR, the most pronounced differences were noted in the plurinational states of Bolivia, Costa Rica, Estonia, Peru, and Honduras, with rates spanning from 51.79 to 75.89 per 100,000 people.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlthough RA can be better controlled by standardized treatment, the level of treatment is inconsistent and unequal worldwide and remains incurable. As elaborated above, the prolonged presence of this autoimmune disease has caused direct physical, psychological, and economic damage to people worldwide and has increased GBD\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Therefore, epidemiological studies are urgently needed.\u003c/p\u003e\u003cp\u003eTo the best of our knowledge, this is the first study to analyze the epidemiology of RA in a large sample of patients during the 1990\u0026ndash;2021 period using the GBD2021 database. In this study, we examined the disease burden and trends of RA at the global, regional, and national levels and for all populations within this period using age, sex, and SDI.\u003c/p\u003e\u003cp\u003eThis study revealed a marked increase in both the prevalence and incidence of RA over the three-decade period from 1990 to 2021. These trends reflect improvements in socioeconomic conditions and the accelerating pace of global population aging. Additionally, heightened awareness of RA, coupled with expanded screening efforts, may have contributed to greater case ascertainment, thereby inflating both the incidence and prevalence estimates. Notably, the relative stabilization of DALYs over the same period suggests that earlier detection and timely therapeutic intervention may mitigate the overall disease burden.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e This stabilization or decline in DALYs, which stands in contrast to the upward trajectory observed in earlier studies, may be attributable to the widespread adoption of novel antirheumatic therapies, particularly biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs), as well as the increasing implementation of evidence-based treatment strategies focused on early intervention and tight disease control, such as the treat-to-target approach.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eOur results indicated that the prevalence, incidence, and DALYs of RA were significantly higher in women than in men. In 2021, the prevalence in women was 2.6 times higher than that in men, and the incidence in women was 2.3 times higher than that in men. The DALYs and incidence in women were 2.3 times higher than those in men and 2.4 times higher than those in men in 2021, and the rate of increase was also significantly higher than that of men. This may be attributed to hormonal influences, genetic predispositions, alterations in immune system function, environmental exposure, and social determinants.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eDuring 1990\u0026ndash;2021, the ASDR in all age groups tended to increase, peaking in 2021. Among all age groups, the incidence of RA was high in the 60\u0026ndash;74-year age group. As we age, the immune system wanes, and the body's natural aging process, changes in hormone levels, and the accumulation of low-grade inflammation in the body over time increase the risk of developing the disease. Some individuals have a family history or a specific genotype, and the probability of RA in this group of patients gradually increases as they grow and develop. People over the age of 60 tend to have a variety of chronic conditions (e.g., high blood pressure and diabetes), and the lifestyle of older adults (e.g., physical inactivity and unhealthy diets) may also have an impact on joint health to some degree.\u003c/p\u003e\u003cp\u003eOver the past 30 years, both the ASIR and ASDR of RA have shown increasing trends across all SDI regions. ASIR and ASDR in middle, high-middle, and high SDI quintiles were significantly higher than those in the low-middle and low SDI quintiles, with the high-middle SDI quintile showing the highest ASIR and ASDR values. This aligns with the findings of previous research. Potential reasons for this phenomenon could be as follows: (1) lifestyle and dietary habits (high SDI regions are often associated with modern lifestyles, including unhealthy dietary habits such as high intake of processed foods and low dietary fiber, which may lead to obesity and metabolic syndrome, thereby increasing the risk of RA; (2) environmental factors, such as high levels of pollution or other environmental risks, including exposure to chemicals, which could trigger autoimmune diseases; and (3) other reasons such as medical diagnosis and reporting, genetic factors, and psychosocial factors.\u003c/p\u003e\u003cp\u003eFrom 1990 to 2021, the ASIR of RA increased the most in Andean Latin America, Northern Africa, and Southern Latin America, with Andean Latin America having the highest ASIR among the 54 regions in 2021. This is consistent with the conclusions of previous studies. Our comprehensive analysis reveals that similar characteristics exist in these areas. On the one hand, there is the geomorphological features: the rugged terrain is mostly mountainous. Economic development has been slow, mostly in the agricultural sector. Moreover, there are education and health concerns. \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e However, all of these areas are at high altitudes, and some studies have pointed out that the people living at high altitudes showed microflora enriched with butyrate-producing bacteria in response to harsh environments, and the core microbiota comprised Prevotella, Faecalibacterium, and Blautia in Tibetans.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Moreover, it was reported that the presence of Prevotella is strongly correlated with disease in patients with new-onset untreated RA (NORA).\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e In addition, the lack of oxygen at high altitudes can enhance certain immune responses, thus aggravating the symptoms of RA.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eHealthcare systems in the high-income Asia-Pacific region are typically well developed, providing better health screening, early diagnoses, and timely treatments. This facilitates the identification and management of patients with RA, thereby reducing incidence rates and disease progression. Additionally, the availability of biologics and other novel therapies in this region has made RA treatment more effective, improving patients' quality of life and potentially decreasing the number of new cases.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e In high-income areas, there is an increased public awareness of RA and its risk factors (such as smoking and obesity), promoting the adoption of preventive measures. Furthermore, societal interventions aimed at lifestyle modifications, such as health promotion programs advocating for better diet and exercise, have positively impacted obesity rates and overall health, thereby lowering the risk of RA. Epidemiological studies in high-income regions can promptly identify disease trends and implement corresponding public health measures.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eConversely, the uneven distribution of healthcare resources in Andean Latin America, Northern Africa, and Southern Latin America has resulted in some populations being unable to access timely and appropriate medical interventions and disease management. As these regions undergo rapid social modernization, many traditional healthy lifestyles may be abandoned, leading to changes in lifestyle, dietary habits, and environmental issues that may increase the incidence of chronic diseases.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eAmong the countries analyzed, Equatorial Guinea, Oman, and Albania exhibited the fastest growth in the ASIR from 1990 to 2021. An analysis of the reasons reveals that these three countries are classified as low-to middle-income nations. Although Oman has a relatively good economy, Equatorial Guinea and Albania face significant economic challenges. Limited healthcare resources, public health infrastructure, and health education in these countries adversely affect the management and treatment of RA. Our analysis reveals that the three all exhibit significant marine geographical characteristics with high humidity. We therefore hypothesized that high humidity may be the cause of rheumatoid joint arthritis.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e On the one hand, a high humidity environment may promote water retention in the body, increase tissue edema around the joints, and aggravate the inflammatory response. In addition, high humidity may change the local microenvironment, affecting the activity of immune cells and the release of inflammatory factors, further aggravating the condition, and on the other hand, cold and humid environment may cause blood circulation to slow down, making the local blood supply to the joints insufficient, exacerbating pain and stiffness. In addition, dampness may aggravate patient discomfort by stimulating nerve endings and amplifying pain signals.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Furthermore the early economic foundations in these regions lead to insufficient disease detection and management, resulting in an underestimation of RA incidence. However, with recent economic improvements, increased detection rates have significantly contributed to the increase in ASIR in these countries.\u003c/p\u003e\u003cp\u003eIn 2021, China, India, and the United States will report the highest number of incident RA cases, representing a substantial proportion of the global prevalence of RA. Research indicates that China and India are the two most populous countries worldwide, each with over one billion inhabitants. While the United States has a smaller population, it remains a significant population center. This natural increase in the total population led to a corresponding increase in the number of RA cases. Over the past 30 years, improvements in living standards and healthcare conditions have resulted in an increasing proportion of the elderly population in China, India, and the United States. Additionally, lifestyle factors such as sedentary behavior, unhealthy diets, and increased stress levels are associated with an increased risk of developing RA. Furthermore, as China and India experience rapid economic growth, their healthcare systems are advancing, leading to more diagnoses and better record-keeping of RA cases. However, certain cities in China and India face severe air pollution issues owing to rapid industrial development, which may further contribute to the increased incidence of RA.\u003c/p\u003e\u003cp\u003eWe found that Cyprus, Honduras, and the Netherlands have significant increases in these categories. Our combined analysis led to the following conclusions: all three countries are located next to the ocean, with Cyprus in the Mediterranean Sea, Honduras near the Caribbean Sea, and the Netherlands with an extensive North Sea coastline. The relatively high prevalence of smoking in all three locations may be associated with an increased prevalence.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eCurrently, there is no cure for RA, and its progression can lead to irreversible joint changes, resulting in joint deformities that severely impact the quality of life and exacerbate the disease burden. Therefore, epidemiological research on RA is critical. We conducted a detailed study of RA based on the GBD 2021 data. Our findings revealed that the incidence was higher among female patients than among males, with the highest incidence rates observed in the elderly population aged 60\u0026ndash;74 years. Additionally, higher incidence rates were found in the low-middle and low SDI quintiles as well as in regions such as Andean Latin America, Northern Africa, Southern Latin America, Equatorial Guinea, Oman, and Albania. Venezuela, Denmark, the Netherlands, Cyprus, and New Zealand also have high incidence rates. Thus, in future disease management, we must focus on these populations and develop strategies to minimize the disease burden as much as possible.\u003c/p\u003e\u003cp\u003eThe principal limitations of this study arose from the intrinsic characteristics and methodological framework of the GBD dataset. At the data acquisition level, the GBD synthesizes information from diverse and often heterogeneous sources; however, the completeness and reliability of these health data remain uncertain, particularly in regions with underdeveloped civil registration and vital statistics systems. At the level of disease definition and adjudication, although the GBD employs standardized case definitions, variations in clinical practice, diagnostic implementation, and medical coding across countries introduce substantial heterogeneity in the identification of RA cases within the primary data. Furthermore, at the modelling level, estimates for comparable diseases within the same region may vary owing to differences in methodology, introducing inherent uncertainty that complicates both temporal and geographical comparisons and limits the interpretability of point estimates with precision.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eGiven the disproportionate and rising burden of RA in resource-constrained regions, particularly in low- and lower-middle SDI areas such as Andean Latin America and North Africa, and its pronounced impact on individuals aged 60\u0026ndash;69 years, we urge public health policymakers and international health organizations to take immediate action. First, resources for RA prevention and control, including screening, diagnosis, accessible treatment, and patient education, must be prioritized in low- and lower-middle SDI settings. Second, cost-effective strategies for the early detection and standardized management of RA should be developed and implemented, with a particular focus on populations aged 60\u0026ndash;69 years. These measures are essential to mitigate disease burden and forestall disability in this vulnerable population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledge\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their gratitude to all the participants of the GBD study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are available in the GBD repository,\u0026nbsp;https://vizhub.healthdata.org/gbd-results/.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to local regulations and institutional requirements, this study did not necessitate ethical review and approval.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from Hangzhou Science and Technology Planning Project (NO. 20220919Y084 to Weibin Du), Zhejiang Province Traditional Chinese Medicine Science and Technology Project (NO. 2023ZR046 to Weibin Du) and Hangzhou bio-medicine and health industry development support science and technology project (NO. 2023WJC243, 2023WJC249 to Weibin Du). Exploration Project of Natural Science Foundation of Zhejiang Province (Q24H270079 to Zhengcong Ye), Zhejiang Provincial Medical and Health Science and Technology Program (2024KY1446 to Zhengcong Ye)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Clinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003enot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eCush, J. J. 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M.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Elucidating the role of hypoxia-inducible factor in rheumatoid arthritis. \u003cem\u003eInflammopharmacology\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, 737-748 (2022). https://doi.org:10.1007/s10787-022-00974-4\u003c/li\u003e\n \u003cli\u003eZou, W., Fang, Y., Xu, D. \u0026amp; Zhu, Y. Increasing global burden of rheumatoid arthritis: an epidemiological analysis from 1990 to 2019. \u003cem\u003eArch Med Sci\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 1037-1048 (2023). https://doi.org:10.5114/aoms/162629\u003c/li\u003e\n \u003cli\u003eRudan, I.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Prevalence of rheumatoid arthritis in low- and middle-income countries: A systematic review and analysis. \u003cem\u003eJ Glob Health\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 010409 (2015). https://doi.org:10.7189/jogh.05.010409\u003c/li\u003e\n \u003cli\u003eCallhoff, J., Luque Ramos, A., Zink, A., Hoffmann, F. \u0026amp; Albrecht, K. The Association of Low Income with Functional Status and Disease Burden in German Patients with Rheumatoid Arthritis: Results of a Cross-sectional Questionnaire Survey Based on Claims Data. \u003cem\u003eJ Rheumatol\u003c/em\u003e \u003cstrong\u003e44\u003c/strong\u003e, 766-772 (2017). https://doi.org:10.3899/jrheum.160966\u003c/li\u003e\n \u003cli\u003eKoko, V., Ndrepepa, A. \u0026amp; Skenderaj, S. Epidemiology of Rheumatoid Arthritis in Southern Albania. \u003cem\u003eMater Sociomed\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 172-175 (2015). https://doi.org:10.5455/msm.2015.27.172-175\u003c/li\u003e\n \u003cli\u003eWang, H.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e High Humidity Alters Myeloid-Derived Suppressor Cells in Spleen Tissue: Insights into Rheumatoid Arthritis Progression. \u003cem\u003eJ Inflamm Res\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 9805-9822 (2024). https://doi.org:10.2147/jir.S490860\u003c/li\u003e\n \u003cli\u003evan der Woude, D. \u0026amp; van der Helm-van Mil, A. H. M. Update on the epidemiology, risk factors, and disease outcomes of rheumatoid arthritis. \u003cem\u003eBest Pract Res Clin Rheumatol\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 174-187 (2018). https://doi.org:10.1016/j.berh.2018.10.005\u003c/li\u003e\n \u003cli\u003evan Delft, M. A. M. \u0026amp; Huizinga, T. W. J. An overview of autoantibodies in rheumatoid arthritis. \u003cem\u003eJ Autoimmun\u003c/em\u003e \u003cstrong\u003e110\u003c/strong\u003e, 102392 (2020). https://doi.org:10.1016/j.jaut.2019.102392\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1. The number of incidences, prevalence, DALYs, and the corresponding ASRs and EAPCs for rheumatoid arthritis at the global, gender, age, country or region level in 2021.\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"777\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 60px;\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 235px;\"\u003e\n \u003cp\u003eIncidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 252px;\"\u003e\n \u003cp\u003ePrevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 231px;\"\u003e\n \u003cp\u003eDALYs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003enumber in 2021 (95% UI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eASIR per 100,000 population (95% UI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eEAPC from 2019 to 2021 (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003enumber in 2021(95% UI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003eASPR per 100,000 population (95% UI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eEAPC from 2019 to 2021 (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003enumber in 2021 (95% UI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eASDR per 100,000 population (95% UI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eEAPC from 2019 to 2021 (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1000319 (902687-1114213)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e11.8 (10.64-13.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.49 (0.46-0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e17924667 (15973178-20303303)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e208.9 (186.34-236.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.53 (0.5-0.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e3075303 (2310381-3974046)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e35.89 (26.95-46.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.05 (0.01-0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" style=\"width: 777px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e695501 (628227-772973)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e16.23 (14.65-18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.46 (0.43-0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e12975146 (11647165-14611571)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e293.66 (263.52-331.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.52 (0.48-0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e2177017 (1627793-2845902)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e48.93 (36.37-64.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.03 (-0.02-0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e304818 (272328-342831)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7.33 (6.56-8.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.53 (0.5-0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e4949521 (4369799-5705323)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e119.68 (105.95-137.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.61 (0.58-0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e898287 (684568-1168744)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e22.06 (16.91-28.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.18 (0.13-0.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" style=\"width: 777px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e65-69 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e95800 (62225-131039)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e34.73 (22.56-47.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.92 (0.83-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1997899 (1722725-2323991)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e724.29 (624.53-842.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.56 (0.49-0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e364307 (285629-466155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e132.07 (103.55-168.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.1 (-0.15-0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;70-74 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e70639 (43927-102813)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e34.32 (21.34-49.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.85 (0.78-0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1659306 (1447190-1907391)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e806.12 (703.07-926.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.57 (0.5-0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e324954 (258607-404088)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e157.87 (125.64-196.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.12 (-0.17-0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e60-64 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e98434 (62903-141685)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e30.76 (19.65-44.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.67 (0.57-0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1948105 (1678737-2265243)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e608.69 (524.53-707.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.53 (0.46-0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e333859 (251419-438473)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e104.32 (78.56-137)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.06 (-0.13-0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" style=\"width: 777px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eHigh-middle SDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e190166 (169306-213515)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e11.66 (10.43-12.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.77 (0.75-0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e3839358 (3402908-4364606)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e213.28 (188.45-242.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.76 (0.73-0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e646310 (482517-842256)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e35.53 (26.33-46.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.31 (0.26-0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eHigh SDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e255315 (231186-282039)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e16.88 (15.44-18.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.33 (0.26-0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e4823674 (4405653-5320056)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e282.73 (256.44-313.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.37 (0.3-0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e774616 (579737-998733)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e44.15 (32.56-58.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.27 (-0.31--0.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eLow-middle SDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e180057 (160663-202101)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e10.49 (9.36-11.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.03 (0.98-1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e2731071 (2419932-3150263)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e168.37 (149.42-192.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.19 (1.12-1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e513042 (391548-655665)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e33.46 (26.23-41.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.64 (0.59-0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eLow SDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e52398 (46046-59971)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7.04 (6.27-7.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.83 (0.73-0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e726534 (623789-855562)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e110.98 (98.21-127.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.89 (0.78-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e125255 (90153-167106)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e20.81 (15.75-27.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.6 (0.51-0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eMiddle SDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e321824 (287295-361682)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e11.9 (10.67-13.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.71 (0.69-0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e5792479 (5116784-6613510)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e209.61 (185.51-238.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.72 (0.69-0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e1014159 (761009-1317131)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e37.22 (28.13-48.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.24 (0.17-0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" style=\"width: 777px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eAndean Latin America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e14555 (13019-16096)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e21.72 (19.62-23.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.62 (1.57-1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e279947 (247543-315605)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e432.76 (384.44-486.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.76 (1.69-1.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e43359 (30922-57568)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e67.82 (48.77-89.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.95 (0.87-1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eNorthern Africa\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e10002 (8576-11495)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4.76 (4.11-5.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.48 (1.41-1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e193365 (161799-228806)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e97.89 (82.58-115.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.46 (1.39-1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e29634 (20595-40901)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e15.25 (10.67-20.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.36 (1.31-1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eSouthern Latin America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e11285 (10211-12405)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e14.75 (13.28-16.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.41 (1.33-1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e215374 (193283-241137)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e267.62 (239.07-301.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.54 (1.44-1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e36211 (27300-47553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e44.56 (33.32-58.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.02 (0.89-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" style=\"width: 777px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eEquatorial Guinea\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e91 (79-106)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e9.04 (8.08-10.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2.03 (1.87-2.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1213 (1026-1430)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e155.44 (137.26-176.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2.31 (2.13-2.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e166 (109-240)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e20.99 (14.27-30.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.89 (1.73-2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eOman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e214 (172-257)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4.31 (3.66-5.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.91 (1.87-1.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e3844 (3095-4705)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e87.16 (72.44-104.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2.03 (1.99-2.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e548 (355-804)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e12.67 (8.61-18.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.87 (1.81-1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eAlbania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e269 (233-311)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e8.39 (7.29-9.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.86 (1.79-1.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e5785 (4946-6767)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e156.6 (132.78-183.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.86 (1.79-1.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e905 (649-1238)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e24.15 (16.85-33.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.74 (0.64-0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" style=\"width: 777px;\"\u003e\n \u003cp\u003eAbbreviations: UI, uncertainty interval; CI, confidence interval; DALYs, disability-adjusted life years; EAPC, estimated annual percentage change; ASIR, age standardized incidence rate; ASPR, age standardized prevalence rate; ASDR, age standardized DALYs rate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-rheumatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brhm","sideBox":"Learn more about [BMC Rheumatology](http://bmcrheumatol.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/brhm/default.aspx","title":"BMC Rheumatology","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Global Burden of Disease study, estimated annual percentage change, epidemiology, trends","lastPublishedDoi":"10.21203/rs.3.rs-7036091/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7036091/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction:\u003c/strong\u003eAge-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), and age-standardized disability-adjusted life years (ASDR) of rheumatoid arthritis (RA) and their trends at the global, regional, and national levels were determined using data from the Global Burden of Disease (GBD) 2021 study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eThe burden of RA was investigated in relation to age, sex, and sociodemographic index (SDI), drawing upon data from the GBD 2021 study. The ASIR, ASPR, and ASDR at the global, regional, and national levels were extracted. The estimated annual percentage change (EAPC) in the ASIR, ASPR, and ASDR was calculated across all levels from 1990 to 2021, supplemented by cluster and frontier analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003eIn 2021, there were 17.92 million cases of RA globally, with the ASIR increasing from 10.42 to 11.8 cases per 100,000 individuals (EAPC of 0.49 [95% confidence interval: 0.46–0.52]) between 1990 and 2021. This considerable increase was evident across all age and sex groups, SDI quintiles, and GBD regions. The most pronounced increase was in the low-middle SDI quintile in the ASIR for RA between 1990 and 2021. Among 54 GBD regions, the most significant increase was observed in Andean Latin America and Equatorial Guinea.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e By 2021, the global burden of RA was largely concentrated in the low-middle and low SDI quintiles, especially in Andean Latin America and Northern Africa, with the burden continuing to grow.\u003c/p\u003e","manuscriptTitle":"Rheumatoid arthritis continues to increase in low-middle SDI and low SDI quintiles based on GBD 1990–2021 ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-15 12:48:40","doi":"10.21203/rs.3.rs-7036091/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-21T16:40:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-20T17:38:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-19T17:00:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"270608174932503407990645902897004812646","date":"2025-07-18T15:02:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-16T14:20:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"299787037624096381219090956071504730133","date":"2025-07-16T14:19:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"52628726098772060799058129604612319665","date":"2025-07-14T05:18:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180757220675845183292394541037809181754","date":"2025-07-13T10:53:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"57707842415247586615768896659354779156","date":"2025-07-11T08:00:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-11T02:19:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-08T17:59:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-07T04:38:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-07T04:37:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Rheumatology","date":"2025-07-03T08:49:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-rheumatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brhm","sideBox":"Learn more about [BMC Rheumatology](http://bmcrheumatol.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/brhm/default.aspx","title":"BMC Rheumatology","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2e2c5663-06de-40cb-ba56-06b6642f0527","owner":[],"postedDate":"July 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-06T16:04:21+00:00","versionOfRecord":{"articleIdentity":"rs-7036091","link":"https://doi.org/10.1186/s41927-025-00570-3","journal":{"identity":"bmc-rheumatology","isVorOnly":false,"title":"BMC Rheumatology"},"publishedOn":"2025-10-03 15:58:08","publishedOnDateReadable":"October 3rd, 2025"},"versionCreatedAt":"2025-07-15 12:48:40","video":"","vorDoi":"10.1186/s41927-025-00570-3","vorDoiUrl":"https://doi.org/10.1186/s41927-025-00570-3","workflowStages":[]},"version":"v1","identity":"rs-7036091","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7036091","identity":"rs-7036091","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}