The burden of rheumatoid arthritis in China from 1990-2021: An analysis based on the Global Burden of Disease Study 2021

The burden of rheumatoid arthritis in China from 1990-2021: An analysis based on the Global Burden of Disease Study 2021 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The burden of rheumatoid arthritis in China from 1990-2021: An analysis based on the Global Burden of Disease Study 2021 Qinglin Wu, Haiyang Wang, Ying Wu, Licheng Tao, Wuxia Wang, Shiyun Yin, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5008946/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Rheumatoid arthritis (RA) is the leading cause of disability and functional limitations in middle-aged and older adults. However, there is a paucity of studies examining the burden of disease associated with RA in China. This study comprehensively describes the prevalence and health loss associated with RA in China from 1990 to 2021, utilizing demographic and geographic variables. The findings of this study can inform effective health policy, healthcare resource allocation, and the optimization of patient management programs. Methods We utilized extensive data from the Global Burden of Disease (GBD) 2021 database to analyze the prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) of RA in China from 1990 to 2021. We conducted a disaggregated and comparative study by age, sex, and region. A comparison was subsequently made between the Chinese study results and global data, as well as data from Middle and High-middle Socio-demographic Index (SDI) countries with similar economic development to China. Results The age-standardized prevalence of RA in China increased by 17% from 1990 to 2021. Concurrently, there was a 22% reduction in mortality, a 33% decline in the YLL rate, a 17% increase in the YLD rate, and no change in the DALY rate. The majority of the burden associated with RA in China is attributable to disability. The YLL rate is higher than the global level and that observed in other Middle-SDI and High-middle SDI countries. There is a greater burden of disease in females across all indicators, and the DALY rate is higher in the middle-aged and older age groups, with a peak at 55–59 years of age. China's prevalence and DALY rates exceed the global average. Conclusion Systematic studies into the trends of RA burden, encompassing variations related to age and sex, are essential for policymakers, researchers, and healthcare providers in China. The early identification and management of RA, particularly among women and middle-aged to older adults, has the potential to significantly reduce the overall burden of the disease. Rheumatoid arthritis Epidemiology Disease burden Trend China Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Background Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic, erosive, symmetrical, and polyarticular inflammation. It represents a significant challenge among rheumatic diseases[ 1 ]. RA affects approximately 0.5-1% of the global population, with a prevalence that is at least twice as high in females as in males. RA prevalence increases with age, peaking in the 50–59 years age group[ 2 , 3 ]. It is linked to synovitis and destruction of articular cartilage and bone, and disease progression can lead to joint deformity, loss of function, and potential multisystem damage[ 4 ]. In 2015, $ 21.4 billion was spent globally on medications for RA, the highest expenditure among rheumatic diseases, according to the Global Burden of Disease results. Furthermore, the decline in quality of life due to pain and depression contributes to the intangible costs associated with this disease[ 5 ]. Moreover, medication and disability-related expenses can significantly strain the finances of families and society[ 6 ]. A comprehensive analysis of the burden of disease in RA patients is of significant clinical importance. In recent years, progress has been made in understanding the prevalence characteristics of RA in China. Previous studies have indicated that the prevalence of RA among residents of Beijing was 0.41% in 2012, with a male-to-female prevalence ratio of approximately 1:6[ 7 ]. In 2020, the prevalence of RA among middle-aged and elderly people in Nagchu, Tibet, was 4.86%, with a higher rate observed in females[ 8 ]. The prevalence of RA in the Yinzhou District of Ningbo was 32.65/100,000 from 2011 to 2020[ 9 ]. The evidence derived from these decentralized regional surveys encompasses a limited range of populations, with the majority of studies reporting prevalence rates solely owing to the inherent constraints of the survey methodology and the quality of the available data, which are clearly inadequate. At present, comprehensive nationwide epidemiological surveys and disease burden studies on RA are lacking. Furthermore, the relationship between the disease burden of RA and its social development in China remains largely uncharted. During the COVID-19 pandemic in 2020 and 2021, there was a notable increase in the global adult mortality rate[ 10 ]. The pandemic had a profound impact on the disease outcomes of elderly patients with RA and those with multiple comorbidities associated with RA. Consequently, a re-evaluation of the disease burden of RA in this context is crucial for a comprehensive understanding of the current status of RA in China post-pandemic[ 11 ]. We analyzed data from the GBD database for the period 1990–2021 to address these issues. We hope that this analysis will facilitate the development of new prevention and treatment methods and provide practical guidance for the planning and implementation of health services and policies related to RA in China. 2. Methodology 2.1 Data sources The Global Burden of Disease (GBD) study is the most extensive global health survey, covering 371 diseases and 88 risk factors in 204 countries and territories from 1990 to 2021[ 12 – 14 ]. This study provides a robust data foundation for global health policymaking and public health interventions by comprehensively assessing global health losses from major diseases. The primary data sources and main data research methods employed by the GBD project have been described in detail in previous studies[ 12 – 16 ]. In summary, disease burden estimates were derived from extensive datasets comprising multiple representative populations. These were collated through a synthesis of information from the literature reviews, published registry science and cohort studies identified in research collaborations, administrative health records and reports, and census data. The coherent burden of disease estimates was produced via DisMod-MR 2.1 and MR-BRT Bayesian meta-regression software via a combined approach. Uncertainty intervals (UIs) were derived from 1,000 samples taken from the model's posterior distribution. The 95th percentile of the UIs was defined as the 2nd and 97.5th percentiles of the distribution, quantifying the uncertainty of the estimates. We gathered extensive data on the prevalence, mortality, YLLs, YLDs, and DALYs related to RA in China from 1990 to 2021, sourced from the GBD 2021 database available at http://ghdx.healthdata.org/gbd-results-tool.For analysis, disease burden indicators were converted into specific numbers or age- standardized rates per 100,000 people. In this way, China’s findings can be compared with global data and data from Middle-SDI and High-middle-SDI countries with similar levels of economic development to China. To ensure transparency, reliability, and replicability, our study adhered to the Guidelines for Accurate and Transparent Health Evaluation Reporting (GATHER). This approach enhances the scientific value of the overall study[ 16 ]. Notably, no human participants or animal experiments were Involved in this study. The GBD is an openly accessible database, and all participant data are anonymized. Accordingly, no ethical approval was sought. 2.2 Definition of Disease RA is defined according to the 1987 American College of Rheumatology criteria[ 17 ]. The ICD codes for RA are 714.0-714.9 in the 9th edition and M05, M06, and M08 in the 10th edition. RA severity is categorized into mild, moderate, and severe levels. A disability weight (DW) was assigned to each class as follows: The disability weight for mild, moderate, and severe RA are 0.117 (95% uncertainty interval (UI) 0.080 to 0.163), 0.317 (95% UI 0.216 to 0.440), and 0.581 (95% UI 0.403 to 0.739). Derived from extensive population-based studies across multiple countries, DWs quantifies the health loss associated with RA, ranging from 0 (no disability) to 1 (death) [ 18 ]. Please refer to previous GBD publications for more details on this process[ 13 , 14 , 19 ]. 2.3 Disease burden The collected data are age-standardized and include all age groups and sexes. Mortality and prevalence rates are estimated using vital statistics, published literature, survey data, surveillance data, and health insurance claims. The YLLs indicator, which represents premature deaths, is calculated by multiplying the number of deaths attributable to a specific risk factor in each age group by the age-standardized life expectancy for that group. The standardized life expectancy is derived from the lowest observed mortality risk within each five-year age group in populations exceeding five million individuals. Given the severity of the health conditions under consideration, the life cycle illustrates the temporal occurrence of both short-term and long-term health conditions. DALYs were computed by multiplying the prevalence of RA by the disability weight for each severity level, categorized by class, age, sex, and year. The DALYs was calculated by summing the YLLs and YLDs for each age group, sex, and year[ 20 – 22 ]. The SDI is a composite indicator integrating per capita income, average educational attainment, and fertility rates. China's DALYs are benchmarked against those of countries with similar SDI classifications. The methodology employed to calculate the burden of disease indicators has been previously described in detail in the literature[ 12 , 14 ]. 2.4 Statistical analysis The prevalence, morbidity, mortality, and DALYs were projected per 100,000 people, including their 95% uncertainty intervals. All analyses and graphical generation were performed using the World Health Organization's Health Equity Assessment Toolkit and R (version 4.1). 3. Results 3.1 Prevalence In 2021, China reported 4,755,486.534 cases of RA (95% UI: 4,141,219.489-5,452,492.353). The age-standardized prevalence rate rose by 17.0%, from 205.705 per 100,000 (95% UI: 177.559-238.182) in 1990 to 240.695 per 100,000 (95% UI: 210.769-277.947) in 2021(Table 1 ). The age-standardized prevalence is significantly greater in males than in females. Stratified by sex, the age-standardized rates increased by 26.0% in males and 12.0% in females (Table 1 ). Globally, the number of RA cases is 17,924,667.325 (95% UI: 15,973,177.811-20,303,303.365) (Table S1 ). The age-standardized prevalence rate increased by 14.0%, from 182.539 (95% UI: 161.586-207.478) per 100,000 people in 1990 to 208.899 (95% UI: 186.338-236.334) in 2021 (Table S2 ). From 1990 to 2021, global rates were consistently lower than those reported in China (Fig. 1 ). During this period, the age-standardized prevalence rate in Middle-SDI countries increased by 22.0%, from 171.708 (95% UI: 150.602-197.151) per 100,000 in 1990 to 209.613 (95%UI: 185.505–238.440) in 2021(Table S3 ). High-middle SDI countries experienced a 24% increase in prevalence (Table S4 ), maintaining the highest prevalence throughout the study period. Table 1 Change over time for all-age and age-standardized burden of disease indicators per 100,000, China, 1990–2021 Indicator (95%UI) Standardisation Both (female & male) Change Year 1990 2021 Prevalence All-age 173.545(148.489-203.239) 334.247(291.072-383.237) 93% Age-standardized 205.705(177.559-238.182) 240.695(210.769-277.947) 17% Mortality All-age 0.406(0.332–0.504) 0.722(0.521–0.887) 78% Age-standardized 0.696(0.570–0.849) 0.543(0.391–0.662) -22% YLLs All-age 10.865(8.843–13.858) 14.198(10.337–17.407) 31% Age-standardized 14.948(12.233–18.895) 10.058(7.306–12.329) -33% YLDs All-age 23.395(15.660–33.560) 44.408(30.175–62.133) 90% Age-standardized 27.423(18.516–38.741) 32.137(21.649–44.861) 17% DALYs All-age 34.260(26.150-44.731) 58.606(43.685–76.157) 71% Age-standardized 42.371(33.040-54.323) 42.195(31.298–55.447) 0% Indicator (95%UI) Standardisation female Change Year 1990 2021 Prevalence All-age 248.07(212.57-289.114) 460.193(402.828-525.799) 86% Age-standardized 286.220(247.896-332.482) 321.686(280.041-369.685) 12% Mortality All-age 0.566(0.458–0.718) 0.881(0.654–1.123) 56% Age-standardized 0.842(0.683–1.062) 0.578(0.425–0.740) -31% YLLs All-age 15.429(12.188–19.709) 17.325(12.910-22.241) 12% Age-standardized 19.536(15.611–24.738) 11.243(8.391–14.429) -42% YLDs All-age 33.237(22.406–47.697) 60.922(41.699–85.548) 83% Age-standardized 38.043(25.901–53.781) 42.886(29.150-60.315) 13% DALYs All-age 48.666(36.810-63.311) 78.246(57.592–103.860) 61% Age-standardized 57.580(44.308–74.049) 54.129(39.320-72.606) -6% Indicator (95%UI) Standardisation male Change Year 1990 2021 Prevalence All-age 103.59(87.481-123.994) 214.089(184.754-250.436) 107% Age-standardized 127.990(109.845–150.140) 160.757(139.415-187.509) 26% Mortality All-age 0.255(0.137–0.339) 0.572(0.267–0.782) 124% Age-standardized 0.540(0.299–0.726) 0.524(0.247–0.701) -3% YLLs All-age 6.581(3.521–8.682) 11.215(5.222–15.737) 70% Age-standardized 10.403(5.680-13.952) 9.011(4.183–12.485) -13% YLDs All-age 14.157(9.256–20.263) 28.653(19.261–40.589) 102% Age-standardized 17.224(11.423–24.253) 21.568(14.474–30.686) 25% DALYs All-age 20.738(15.263–27.507) 39.869(29.525–52.508) 92% Age-standardized 27.626(20.371–36.285) 30.579(22.706–40.278) 11% 3.2 Mortality and YLLs In 2021, the number of deaths from RA in China was 10,279.108 (95% UI: 7411.448-12,614.825) (Table S1 ), representing a 22.0% decline in the age-standardized mortality rate from 0.696 per 100,000 people (95% UI: 0.570–0.849) in 1990 to 0.543 in 2021 (95% UI: 0.391–0.662) (Table 1 ). The decline in mortality was more pronounced for women than for men (31.0% vs. 3.0%), yet women continue to exhibit a significantly elevated mortality rate. The number of deaths from RA globally was 37,330.348(95% UI: 31,060.305-43,135.539) (Table S1 ), with an age-standardized mortality rate that declined from 0.607 (95% UI: 0.538–0.678) / 100,000 in 1990 to 0.448 (95% UI: 0.373–0.519)/100,000, representing a 26.0% decline (Table S2 ). China is beginning to experience a more substantial decline in mortality than in the global mortality rate observed after 2005 (Fig. 2 ). During the study period, the age-standardized mortality rate for Middle-SDI countries decreased by 22.0%, from 0.638 (95% UI 0.528–0.726) per 100,000 in 1990 to 0.498 (95% UI 0.393–0.573) per 100,000 in 2021 (Table S3 ). It is noteworthy that the age-standardized mortality rates for High-middle SDI remained essentially unchanged at 0.4 (95% UI: 0.4–0.5) / 100,000 in 1990 and 0.4 (95% UI: 0.3–0.4) / 100,000 in 2021. (Table S4 ) The age-standardized YLL rate in China exhibited a trend akin to mortality, decreasing from 14.948 (95% UI 12.233–18.895) per 100,000 in 1990 to 10.058 (95% UI 7.306–12.329) per 100,000, representing a 33.0% reduction overall, with a 42.0% decline for females and a 1.0% decline for males (Table 1 ). The global trend shows a decrease from 12.351 (95% UI: 10.997–13.904) / 100,000 in 1990 to 8.442 (95% UI: 7.096-9.700) / 100,000 in 2021, a decrease of 32.0% (Table S2 ). China's post-2005 decline is even greater compared to the global trend, reflecting the country's mortality trend (Figure S1 ). The age-standardized YLL rate for Middle SDI countries decreased by 27.0%, from 13.086 (95% UI 10.895–15.192) per 100,000 in 1990 to 9.526 (95% UI 7.554–10.930) per 100,000 in 2021 (Table S3 ). Similarly, the High-middle SDI age-standardized YLL rate declined by 27.0%, from 9.9 (95% UI 9.0-11.2) per 100,000 in 1990 to 7.2 (95% UI 6.2–8.2) per 100,000 in 2021, which is consistent with the trend observed in Middle SDI countries (Table S4 and Figure S1 ). 3.3 YLDs and DALYs In 2021, the total number of YLDs due to RA was 631,813.822 (95% UI 429,315.833-883,990.616), indicating a 17.0% rise in the age-standardized YLD rate from 27,423 (95% UI 18,516 − 38,741) per 100,000 in 1990 to 32,137 (95% UI 21,649 − 44,861) in 2021(Table 1 ). The rate increases by 13.0% for females and 25.0% for males. Age-standardized YLD rates rose by 14% globally from 24.065 (95% UI 16.479–33.331) in 1990 to 27.452 (95% UI 18.733–37.824) in 2021(Table S2 ). From 1990 to 2021, YLDs in China grew faster than global YLDs. During the same period, the age-standardized YLD rate for Middle SDI countries also exhibited an increase by 22.0%, rising from 22.786 (95% UI: 15.444–32.246) per 100,000 people in 1990 to 27.689 (95% UI: 18.717–38.644) in 2021 (Table S3 ). In High-middle SDI countries, the age-standardized YLD rate increased by 24% from 1990–2021, increasing from 22.9 per 100,000 (95% UI 15.5–32.2) to 28.3 per 100,000 (95% UI 19.1–39.5), aligning closely with the rates observed in middle SDI countries (Table S4 and Figure S2 ). In China, DALYs grow at a slower rate than YLDs. Age-standardized DALYs showed minimal changes, from 42.371 (95% UI 33.040-54.323) per 100,000 population in 1990 to 42.195 (95% UI 31.298–55.447) in 2021, with a 6% decrease in female DALYs and an 11% increase in male DALYs (Table 1 ). The DALY rate in China is significantly higher compared to Global, Middle SDI, and High-middle SDI countries(Fig. 3 ). Globally, there was a 1% decline in DALYs from 36.416 per 100,000 people in 1990 (95% UI 28.711–45.996) to 35.894 per 100,000 people in 2021 (95% UI 26.953–46.464) (Table S2 ). The number of middle-SDI countries increased by 4% from 35.872 (95% UI: 28.404–45.568) per 100,000 people in 1990 to 37.215 (95% UI: 28.132–48.115) in 2021 (Table S3 ). High middle SDI countries, on the other hand, increased by 8%, from 32.8 (95% UI: 25.3–42.2) per 100,000 people in 1990 to 35.5 (95% UI: 26.3–46.9) in 2021 (Table S4 ). The burden of RA due to premature death andXXXdisability occurs mainly in the middle-aged population. Accordingly, the highest DALY rates were found in the 55–59 and 65–69 age groups (Fig. 4 ), with 96,142 (95% UI: 70,097–129,169) and 134,03 1 (95% UI: 101.517-172.857) per 100,000, respectively, which preceded a sharp increase and was followed by a slight decrease. Prior to this, there was a substantial increase, which was followed by a slight decrease. In all age groups, nearly two-thirds of the disability-adjusted years for rheumatoid arthritis were accounted for by females (Fig. 4 ). The relative contributions of YLLs and YLDs to DALYs have undergone significant changes over time. In 1990, DALYs were composed of 34.0% YLLs and 66.0% YLDs. By 2021, the proportion of YLDs had increased to 79.0% of the total DALYs in China (Fig. 5 ). 4. Discussion RA represents a significant global public health concern, with a considerable body of research dedicated to understanding its impact on prevalence and mortality. The present study encompasses a 30-year period and provides a comprehensive description of the disease burden in diverse populations over time. In 2021, the age-standardized prevalence of RA in China was estimated at 240.695 cases per 100,000 people, notably exceeding the global average. These findings suggest that China is a high-risk area for RA (Fig. 6 )[ 23 , 24 ]. As of 2021, the estimated number of RA patients in China is 4,755,487, nearly doubling over the past three decades. Concurrently, the age-standardized prevalence has also dramatically increased. This is significantly higher than the global average, as well as the averages for high-middle and middle SDI countries. The burden of RA due to disability constitutes more than 60% of total DALYs, surpassing both the global average and the averages of High-middle and Middle SDI countries with similar economic development to China (Fig. 5 ). Furthermore, our findings indicate that adults continue to represent the most affected demographic, with the highest DALY rates observed among individuals aged 55–59 years in China. These findings highlight the significant burden of RA in China, underscoring the need for improved management strategies. Prior research has revealed notable regional differences in the prevalence of RA in China[ 7 – 9 ]. These discrepancies may be attributed to various factors, including different time periods, statistical methodologies, and economic levels. Additionally, the occurrence of RA may be influenced by genetic, climatic, and environmental factors[ 25 , 26 ]. In July 2020, the National Clinical Medical Research Centre for Skin and Immunological Diseases published the China Rheumatoid Arthritis Development Report 2020, which indicated that RA is among the top 10 chronic disease prevalence rates among Chinese residents, with a prevalence rate of approximately 0.42% in mainland China. Despite a prevalence of 5 million people, China’'s large population base makes this disease a significant public health burden. This study presents a comprehensive analysis of RA prevalence, revealing a crude rate of 240.695 per 100,000 people in 2021, which is consistent with previous findings. The increase in the national prevalence of RA may be attributed, at least in part, to improvements in diagnosis and management[ 27 ]. Advancements in diagnostic techniques and criteria for RA, coupled with their widespread clinical use, have decreased misdiagnosis and underdiagnosis, indirectly leading to a higher observed prevalence of RA [ 28 ]. The GBD 2021 study estimates that RA prevalence is significantly lower in men than in women, irrespective of geographical region, socioeconomic status, or sex. In all regions, the prevalence of females is nearly double that of males. Studies from China and the United States indicate a significantly higher prevalence of RA in females compared to males. These findings align with those reported in this study[ 29 , 30 ]. Prior research has demonstrated that RA can manifest at any age, with the female population exhibiting a high prevalence of the disease. Numerous observations have postulated that alterations in sex hormone levels may influence the pathogenesis of RA[ 31 ]. However, women are more prone to induce modifications in hormone and metabolic levels due to physical disparities (including genetic variations). Additionally, physiological factors, such as menstruation, pregnancy, childbirth, and breastfeeding, as well as lifestyle and occupational influences, can potentially impact the immune system. The more severe and complex condition of female patients could explain the higher disease prevalence in females compared to males[ 32 – 34 ]. It is therefore recommended that clinicians consider sex as a factor in the individualized treatment of RA. The GBD data indicate a strong association between RA development and risk factors such as smoking and behavioral patterns (Figure S3 ). This finding has been corroborated by previous studies[ 35 , 36 ]. Evidence suggests that lifestyle interventions, such as smoking cessation, maintaining a healthy weight, and adhering to a healthy diet, can reduce disease activity in RA patients[ 37 ]. Screening first-degree relatives of early-stage RA patients can help identify their risk and enable targeted prevention strategies to reduce disease prevalence. RA is linked to a higher mortality risk. Compared with the general population, patients with RA may have a reduction in expected survival of between three and ten years. The primary causes of death in this group are malignant tumors, respiratory diseases, and cardiovascular diseases[ 38 ]. This suggests that there is a need for greater emphasis on the management of comorbid RA diseases. Furthermore, RA disease activity is also strongly associated with mortality[ 39 ]. Survival rates are expected to rise due to advancements in treatment paradigms over recent decades, including early intervention[ 40 ] and modernized therapies[ 41 ]. Data from the GBD show that age-standardized mortality rates in China, globally, and in countries with high-middle and middle SDI peaked around 2005 for the period 1990 to 2021, and have declined over time since then. Since the 21st century, the strengthening of China’'s rheumatology disciplines, the deepening of RA precision medicine, and the advent of individualized treatment have effectively slowed and stopped the progression of RA in patients in China. Currently, in addition to traditional therapeutic drugs, the popularization and application of novel RA therapeutic drugs such as targeted drugs for specific inflammatory mechanisms in China[ 42 ] have markedly enhanced the clinical treatment compliance rate of patients and prolonged their survival, which may be a contributing factor to the reduction of in RA mortality. Notwithstanding the aforementioned advances in treatment and early diagnosis, challenges persist. These include drug availability, financial constraints, insufficient specialists, and specialized care, which remain present in some areas[ 43 ]. On the basis of these data, future prevention and control strategies for RA should be assessed and enhanced in accordance with population dynamics and healthcare practices. This study revealed that age-standardized DALY rates in China, globally, and in high-middle and middle SDI countries exhibited consistent trends. Age-standardized YLL rates showed similar variations to DALY rates, whereas age-standardized YLD rates experienced significant increases. The DALY in China mainly consists of disability, likely due to insufficient management of RA.RA is a highly disabling autoimmune disease, with joint destruction largely irreversible once it occurs. Previous studies indicate that if left untreated, the 3-year disability rate can reach up to 70% [ 44 ]. In China, the average time from symptom onset to definitive diagnosis for patients exceeds two years, indicating a missed opportunity for RA treatment. The median disease duration of Chinese RA patients is 3.86 years, and the cross-sectional disease remission rate is only 4.27%, which is significantly lower than the remission rate of approximately 20% reported in developed countries. Furthermore, among patients not treated with bDMARDs or csDMARDs, 38.84% and 38.11% of patients, respectively, had moderate and high disease activity. Additionally, approximately 4.2% of patients had comorbidities[ 45 ]. Additionally, studies from the National Rheumatic Disease Data Center (CRDC) have demonstrated that the issue of unregulated medication use for RA in China is a significant concern. The utilization of methotrexate, hydroxychloroquine, and other primary medications for RA initial treatment is considerably lower than the global standard in China. Furthermore, patients exhibit inadequate awareness of the necessity for standardized RA treatment, and Chinese RA patients demonstrate lower treatment adherence and a lack of long-term regular follow-up. Currently, there is a dearth of guiding standards for the management of chronic rheumatic diseases and standardized chronic management models with evidence-based medical evidence [ 46 ]. These factors contribute to the increased disability rate and higher DALYs in Chinese RA patients. Fortunately, since 2017, several new medications have been approved and introduced into clinical practice, including JAKi inhibitors such as tofacitinib and baricitinib, and biologics such as adalimumab and infliximab. These developments are anticipated to contribute to slowing the progression of severe disability in RA patients[ 47 ].To further assess the risk of DALYs and mortality risk of RA in China in the future (2035), we employed the method of Riebler A and Held L[ 48 ], which is based on the available continuous data, and utilized the Bayesian Age-Period-Cohort(BAPC) model. This model offers a comprehensive framework for projections using integrated nested Laplace approximations (INLAs) for Bayesian inference and data prediction. The findings indicated a decline in the risk of DALYs and mortality (Figures S4 ).It is anticipated that the advancement of RA disease management in the future will prove instrumental in reducing the disease burden. The present study has several notable strengths, and monitoring trends in the burden of RA is crucial for the development of public health policies. Our study provides the latest estimates of RA prevalence and mortality in the Chinese population. The primary strength of this study is its extensive coverage spanning nearly three decades, surpassing the scope of most prior research. Furthermore, this study offers valuable insights into RA mortality, a topic that is currently underrepresented in the existing literature. This study has several limitations, including the reliance on global GBD RA data from a limited number of countries, potentially resulting in data incompleteness and affecting the accuracy of burden estimates and the certainty of observed trends. Second, discrepancies in the diagnosis, documentation, and reporting of the disease in disparate countries and regions may impinge upon the comparability of the data. Future research should prioritize incorporating more high-quality studies to increase estimation accuracy. Third, China’'s extensive geography and significant socioeconomic disparities, coupled with insufficient provincial data analysis, may have led to healthcare inequalities and an underestimation of the disease burden in less developed regions. Our study highlights the necessity of addressing the RA burden in diverse populations, especially in densely populated Asian countries. 5. Conclusion This study provides a detailed analysis of the demographic and temporal trends in the disease burden and prevalence of RA in China, highlighting its increase over the past 30 years. Furthermore, this study reveals that RA is a significant public health concern in China, with a considerable proportion of disability and a high economic burden. These findings indicate that China may be behind developed countries in RA health management. This underscores the necessity for enhanced disease surveillance and chronic disease management. Enhancing public awareness and continuous medical education in rheumatology is crucial for advancing the diagnosis, treatment, and management of RA. Abbreviations Rheumatoid arthritis (RA) Global Burden of Disease (GBD) years of life lost (YLLs) years lived with disability (YLDs) disability-adjusted life years (DALYs) Socio-demographic Index (SDI) Uncertainty intervals (uIs) disability weight (DW) Declarations Acknowledgements We thank all members of Global Burden of Disease Collaborative Network and Institute for Health Metrics and Evaluation (IHME). Authors’ contributions Qinglin Wu and Xiaohu Tang designed the research. Haiyang Wang, Ying Wu and Licheng Tao collected and arranged the data. Haiyang Wang, Wuxia Wang and Shiyun Yin performed the statistical analysis and made the figures and tables. Qinglin Wu, Haiyang Wang, Xiaohu Tang, and Ying Wu wrote and revised the manuscript. All authors read, critically reviewed, and approved the final manuscript. Funding This project is jointly funded by the Yunnan Province Xingdian Talent Program for Famous Physicians [No. Yunnan Health Human Development (2019) 1], Yunnan Province 2024 famous old Chinese medicine experts inheritance studio construction project (Xiaohu Tang famous old Chinese medicine experts inheritance studio). Data Availability The datasets generated and/or analyzed during the current study are available in the GBD Data Tool repository (http://ghdx.healthdata.org/gbd-results-tool). This public link to GBD database is open, and the use of data does not require additional consent from IHME. Consent for publication Not applicable. Competing interests The authors declare no potential conflict of interest. Ethics approval and consent to participate Not applicable. References Cush JJ: Rheumatoid Arthritis . Rheumatic Disease Clinics of North America 2022, 48 (2):537-547. Latitude gradient influences the age of onset of rheumatoid arthritis: a worldwide survey . Clinical Rheumatology 2016, 36 (3):485-497. Gibofsky A: Epidemiology, pathophysiology, and diagnosis of rheumatoid arthritis: A Synopsis . The American journal of managed care 2014, 20 (7 Suppl):S128-135. Onuora S: Itaconate targets fibroblast-like synoviocytes in RA . Nature Reviews Rheumatology 2024, 20 (8):456-456. !!! INVALID CITATION !!! . Hsieh P-H, Wu O, Geue C, McIntosh E, McInnes IB, Siebert S: Economic burden of rheumatoid arthritis: a systematic review of literature in biologic era . Annals of the Rheumatic Diseases 2020, 79 (6):771-777. Li R, Sun J, Ren LM, Wang HY, Liu WH, Zhang XW, Chen S, Mu R, He J, Zhao Y et al : Epidemiology of eight common rheumatic diseases in China: a large-scale cross-sectional survey in Beijing . Rheumatology 2011, 51 (4):721-729. Zhang Q, Liu Q, Lin C, Baima Y, Li H, Gong H, Lin J: The prevalence of rheumatoid arthritis in middle-aged and elderly people living in Naqu City, Tibet, Autonomous Region of China . Journal of Orthopaedic Surgery and Research 2020, 15 (1). Zeng XY, Liu ZK, Shen P, Sun YX, Liu X, Zhan SY, Lin HB, Sun F: [Epidemiological study on the incidence of rheumatoid arthritis in adults in Yinzhou district, Ningbo city from 2011-2020] . Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi 2022, 43 (8):1288-1295. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021 . Lancet (London, England) 2024, 403 (10440):1989-2056. D'Silva KM, Wallace ZS: COVID-19 and rheumatoid arthritis . Curr Opin Rheumatol 2021, 33 (3):255-261. Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021 . Lancet (London, England) 2024, 403 (10440):2204-2256. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021 . Lancet (London, England) 2024, 403 (10440):2162-2203. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021 . Lancet (London, England) 2024, 403 (10440):2133-2161. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021 . Lancet (London, England) 2024, 403 (10440):2100-2132. Stevens GA, Alkema L, Black RE, Boerma JT, Collins GS, Ezzati M, Grove JT, Hogan DR, Hogan MC, Horton R et al : Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement . Lancet (London, England) 2016, 388 (10062):e19-e23. Arnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF, Cooper NS, Healey LA, Kaplan SR, Liang MH, Luthra HS et al : The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis . Arthritis and rheumatism 1988, 31 (3):315-324. Gonzalez A, Maradit Kremers H, Crowson CS, Nicola PJ, Davis JM, 3rd, Therneau TM, Roger VL, Gabriel SE: The widening mortality gap between rheumatoid arthritis patients and the general population . Arthritis and rheumatism 2007, 56 (11):3583-3587. Hassen N, Lacaille D, Xu A, Alandejani A, Sidi S, Mansourian M, Butt ZA, Cahill LE, Iyamu IO, Lang JJ et al : National burden of rheumatoid arthritis in Canada, 1990-2019: findings from the Global Burden of Disease Study 2019 - a GBD collaborator-led study . RMD open 2024, 10 (1). Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017 . Lancet (London, England) 2018, 392 (10159):1789-1858. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017 . Lancet (London, England) 2018, 392 (10159):1859-1922. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017 . Lancet (London, England) 2018, 392 (10159):1736-1788. Finckh A, Gilbert B, Hodkinson B, Bae S-C, Thomas R, Deane KD, Alpizar-Rodriguez D, Lauper K: Global epidemiology of rheumatoid arthritis . Nature Reviews Rheumatology 2022. Almutairi K, Nossent J, Preen D, Keen H, Inderjeeth C: The global prevalence of rheumatoid arthritis: a meta-analysis based on a systematic review . Rheumatology International 2020, 41 (5):863-877. Scherer HU, Häupl T, Burmester GR: The etiology of rheumatoid arthritis . Journal of Autoimmunity 2020, 110 . Kronzer VL, Davis JM: Etiologies of Rheumatoid Arthritis: Update on Mucosal, Genetic, and Cellular Pathogenesis . Current Rheumatology Reports 2021, 23 (4). Cush JJ: Rheumatoid Arthritis: Early Diagnosis and Treatment . Rheumatic diseases clinics of North America 2022, 48 (2):537-547. Li Y, Zhang Z, Liu C, Kang Z, Li Z: Significance of High‐Frequency Sonography for the Subclinical Progression of Rheumatoid Arthritis . Journal of Ultrasound in Medicine 2024, 43 (8):1509-1520. Jiang N, Li Q, Li H, Fang Y, Wu L, Duan X, Xu J, Zhao C, Jiang Z, Wang Y et al : Chinese registry of rheumatoid arthritis (CREDIT) V: sex impacts rheumatoid arthritis in Chinese patients . Chinese Medical Journal 2022, 135 (18):2210-2217. Sacks JJ, Luo YH, Helmick CG: Prevalence of specific types of arthritis and other rheumatic conditions in the ambulatory health care system in the United States, 2001–2005 . Arthritis Care & Research 2010, 62 (4):460-464. Cutolo M, Gotelli E: Complex role of oestrogens in the risk and severity of rheumatoid arthritis in menopause . RMD open 2023, 9 (2). Kosztyła-Hojna B, Moskal D, Kuryliszyn-Moskal A: Parameters of the assessment of voice quality and clinical manifestation of rheumatoid arthritis . Advances in Medical Sciences 2015, 60 (2):321-328. Euesden J, Matcham F, Hotopf M, Steer S, Cope AP, Lewis CM, Scott IC: The Relationship Between Mental Health, Disease Severity, and Genetic Risk for Depression in Early Rheumatoid Arthritis . Psychosomatic Medicine 2017, 79 (6):638-645. Zamanpoor M: The genetic pathogenesis, diagnosis and therapeutic insight of rheumatoid arthritis . Clinical Genetics 2019, 95 (5):547-557. Maisha JA, El-Gabalawy HS, O’Neil LJ: Modifiable risk factors linked to the development of rheumatoid arthritis: evidence, immunological mechanisms and prevention . Frontiers in Immunology 2023, 14 . van der Woude D, van der Helm-van Mil AHM: Update on the epidemiology, risk factors, and disease outcomes of rheumatoid arthritis . Best practice & research Clinical rheumatology 2018, 32 (2):174-187. Koller‐Smith L, Mehdi AM, March L, Tooth L, Mishra GD, Thomas R: Rheumatoid arthritis is a preventable disease: 11 ways to reduce your patients' risk . Internal Medicine Journal 2022, 52 (5):711-716. Lee YK, Ahn GY, Lee J, Shin JM, Lee TH, Park DJ, Song YJ, Kim MK, Bae SC: Excess mortality persists in patients with rheumatoid arthritis . International Journal of Rheumatic Diseases 2021, 24 (3):364-372. Listing J, Kekow J, Manger B, Burmester G-R, Pattloch D, Zink A, Strangfeld A: Mortality in rheumatoid arthritis: the impact of disease activity, treatment with glucocorticoids, TNFα inhibitors and rituximab . Annals of the Rheumatic Diseases 2015, 74 (2):415-421. Yu Z, Lu B, Agosti J, Bitton A, Corrigan C, Fraenkel L, Harrold LR, Losina E, Katz JN, Solomon DH: Implementation of Treat‐to‐Target for Rheumatoid Arthritis in the US: Analysis of Baseline Data From a Randomized Controlled Trial . Arthritis Care & Research 2018, 70 (5):801-806. Laha A, Nasra S, Bhatia D, Kumar A: Advancements in rheumatoid arthritis therapy: a journey from conventional therapy to precision medicine via nanoparticles targeting immune cells . Nanoscale 2024. Babiker-Mohamed MH, Bhandari S, Ranganathan P: Pharmacogenetics of therapies in rheumatoid arthritis: An update . Best Practice & Research Clinical Rheumatology 2024. Steffens D, Contreras-Yáñez I, Cabrera-Vanegas Á, Robledo-Torres A, Cáceres-Giles C, Valverde-Hernández S, Padilla-Ortiz D, Guaracha-Basáñez GA, Pascual-Ramos V: Association of significant risk perception with the use of complementary and alternative medicine: A cross-sectional study in Hispanic patients with rheumatoid arthritis . Plos One 2020, 15 (8). Goekoop-Ruiterman YP, de Vries-Bouwstra JK, Allaart CF, van Zeben D, Kerstens PJ, Hazes JM, Zwinderman AH, Ronday HK, Han KH, Westedt ML et al : Clinical and radiographic outcomes of four different treatment strategies in patients with early rheumatoid arthritis (the BeSt study): A randomized, controlled trial . Arthritis and rheumatism 2008, 58 (2 Suppl):S126-135. Yu C, Li M, Duan X, Fang Y, Li Q, Wu R, Liu S, Wang Y, Wu Z, Shi X et al : Chinese registry of rheumatoid arthritis (CREDIT): I. Introduction and prevalence of remission in Chinese patients with rheumatoid arthritis . Clinical and experimental rheumatology 2018, 36 (5):836-840. Xiang Y, Wang Q, Li H, Duan X, Fang Y, Yang P, Li Q, Wu R, Huo Y, Shi X et al : Chinese registry of rheumatoid arthritis (CREDIT): III. The transition of disease activity during follow‐ups and predictors of achieving treatment target . International Journal of Rheumatic Diseases 2020, 23 (12):1719-1727. Caporali R, Kadakia A, Howell O, Patel J, Milligan J, Strengholt S, Barlow S, Taylor PC: A Real-World Comparison of Clinical Effectiveness in Patients with Rheumatoid Arthritis Treated with Upadacitinib, Tumor Necrosis Factor Inhibitors, and Other Advanced Therapies After Switching from an Initial Tumor Necrosis Factor Inhibitor . Advances in therapy 2024, 41 (9):3706-3721. Riebler A, Held L: Projecting the future burden of cancer: Bayesian age-period-cohort analysis with integrated nested Laplace approximations . Biometrical journal Biometrische Zeitschrift 2017, 59 (3):531-549. Additional Declarations No competing interests reported. Supplementary Files FigureS1.png FigureS2.png FigureS3A.png FigureS3B.png FigureS3C.png FigureS3D.png FigureS4A.png FigureS4B.png TableS1.xlsx TableS2.xlsx TableS3.xlsx TableS4.xlsx SupplementaryLegends.docx Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5008946","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":360234441,"identity":"6e91bd84-6e8a-45d0-a2ca-3c9933d41464","order_by":0,"name":"Qinglin Wu","email":"","orcid":"","institution":"The First Clinical of Medicine College, Yunnan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Qinglin","middleName":"","lastName":"Wu","suffix":""},{"id":360234442,"identity":"e76d45eb-761c-4a7f-943b-6fd2112f7a83","order_by":1,"name":"Haiyang Wang","email":"","orcid":"","institution":"The First Clinical of Medicine College, Yunnan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Haiyang","middleName":"","lastName":"Wang","suffix":""},{"id":360234443,"identity":"9606448f-96e9-48a7-b112-eb379aff82a0","order_by":2,"name":"Ying Wu","email":"","orcid":"","institution":"Yan'an Hospital Affiliated To Kunming Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Wu","suffix":""},{"id":360234444,"identity":"01ffafcd-7688-45b0-bebf-2affc94fc639","order_by":3,"name":"Licheng Tao","email":"","orcid":"","institution":"The First Clinical of Medicine College, Yunnan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Licheng","middleName":"","lastName":"Tao","suffix":""},{"id":360234445,"identity":"9cbec836-f230-4fe1-8a69-1d53d86ca321","order_by":4,"name":"Wuxia Wang","email":"","orcid":"","institution":"The First Clinical of Medicine College, Yunnan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Wuxia","middleName":"","lastName":"Wang","suffix":""},{"id":360234446,"identity":"5543f3a2-cc43-4ac4-a056-8726354e64eb","order_by":5,"name":"Shiyun Yin","email":"","orcid":"","institution":"Department of Rheumatology, Yunnan Provincial Hospital of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shiyun","middleName":"","lastName":"Yin","suffix":""},{"id":360234447,"identity":"dc719c90-f150-41b2-a9d0-7e9b57ba5d94","order_by":6,"name":"Xiaohu Tang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYDACZhBRAOV8MLCRI6iDB6zFgEGCgY2BgXFGQZoxYS0MSFqYeT4cTiSoxZ6d/eLjCgObOgb55qebbQyYExjYDx/dgN9hPMWGZwzSgLawmd3OMWDLY+BJS7tBQEuaZIPBYaAWHjagFp5iBgkeM0Ja0n82GPyHaLEwkEhsIKyF/Rhjg8EBiBYGAwMitBzmYQY6LFmygS3N7GaPQYIxGyG/sPcff/ixocKOn4H58LMbP/78l+NnP3wMrxagPQZgyv4AlM+GXznYngeE1YyCUTAKRsHIBgCrBTzuy0hQfQAAAABJRU5ErkJggg==","orcid":"","institution":"The First Clinical of Medicine College, Yunnan University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Xiaohu","middleName":"","lastName":"Tang","suffix":""}],"badges":[],"createdAt":"2024-08-31 12:27:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5008946/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5008946/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66945727,"identity":"19232f7d-1fc9-465f-ae02-db0a1bd66b7e","added_by":"auto","created_at":"2024-10-18 09:39:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":271620,"visible":true,"origin":"","legend":"\u003cp\u003eAge-standardized RA prevalence, China, global, middle SDI, high-middle SDI, 1990–2021. SDI, Socio-Demographic Index\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/021630e813b5b4c64bb354e6.png"},{"id":66946632,"identity":"18afc5cd-592a-47b7-a4a8-cfdec5301a45","added_by":"auto","created_at":"2024-10-18 09:47:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":324296,"visible":true,"origin":"","legend":"\u003cp\u003eAge-standardized RA deaths, China, global, middle SDI, high-middle SDI, 1990-2021. SDI, Socio-Demographic Index.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/0e575613f3e49c3630eed797.png"},{"id":66945731,"identity":"55b3e72d-fecf-4276-85da-da66b8d9d98e","added_by":"auto","created_at":"2024-10-18 09:39:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":292467,"visible":true,"origin":"","legend":"\u003cp\u003eAge-standardized RA DALYs, China, global, middle SDI, high-middle SDI,1990–2021. DALYs, disability-adjusted life-years; SDI, Socio-Demographic Index.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/159a9240cc8ebcb27a144938.png"},{"id":66945725,"identity":"e0fe7f81-d270-4f6e-bdff-d95a879bb623","added_by":"auto","created_at":"2024-10-18 09:39:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":263931,"visible":true,"origin":"","legend":"\u003cp\u003eDALYs by age group and sex, China, 2021. DALYs: disability-adjusted life-years; RA, rheumatoid arthritis.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/7b0c8b1abd62edba42fd3f3f.png"},{"id":66946618,"identity":"e5832cb0-e024-46d8-ad12-191802c9c20b","added_by":"auto","created_at":"2024-10-18 09:47:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":91768,"visible":true,"origin":"","legend":"\u003cp\u003eProportion of age-standardised RA DALYs due to age-standardised YLLs and age-standardised YLDs, China, 1990 vs 2021. RA, rheumatoid arthritis; YLDs, years lived with disability; YLLs, years of life lost.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/6142b40c15d737aa8363ddb1.png"},{"id":66945732,"identity":"e3d5af3b-64fe-433e-9051-47e133c51e25","added_by":"auto","created_at":"2024-10-18 09:39:12","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":134109,"visible":true,"origin":"","legend":"\u003cp\u003eAge standardized prevalence rates for RA in 204 countries and territories, 2021.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/a842e4f704dee7c9f51dc2e1.png"},{"id":85188392,"identity":"a41cdc84-066e-4890-a28d-bddf489cf87c","added_by":"auto","created_at":"2025-06-23 08:32:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4322322,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/5494c264-70c6-4981-8d74-eaf2c86b47bd.pdf"},{"id":66946615,"identity":"f8259563-2c2d-4381-811c-a86d814cd797","added_by":"auto","created_at":"2024-10-18 09:47:11","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":342791,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/45183b4dd4c41f704956a7c2.png"},{"id":66946616,"identity":"732e9d3f-c3d0-4c36-a59e-ec15af34fa10","added_by":"auto","created_at":"2024-10-18 09:47:11","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":271382,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/375aa320139196b84719d67f.png"},{"id":66946636,"identity":"c918d9ec-0385-48b2-a3f0-03f9e77d8b45","added_by":"auto","created_at":"2024-10-18 09:47:13","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":108103,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS3A.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/e44eaf63e5c468428483f8ee.png"},{"id":66945730,"identity":"da660a45-69b5-4d8a-9306-b81097c09b99","added_by":"auto","created_at":"2024-10-18 09:39:12","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":108071,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS3B.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/eb512eeb8de74dcc14a39ba2.png"},{"id":66945726,"identity":"4eb31c3d-6987-45f1-a23d-26be5b70027b","added_by":"auto","created_at":"2024-10-18 09:39:11","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":98314,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS3C.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/52a8c842851519b885a360ac.png"},{"id":66945772,"identity":"37d530b9-2437-44c5-9189-e4b8c2e89e77","added_by":"auto","created_at":"2024-10-18 09:39:13","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":109227,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS3D.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/50cfa2291d6c0b283710f049.png"},{"id":66945721,"identity":"22ed5246-b47f-49e7-a191-697f1c717b86","added_by":"auto","created_at":"2024-10-18 09:39:11","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":259303,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS4A.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/5a019b0be21c58bd6a9b4cb7.png"},{"id":66945719,"identity":"e1324eeb-cf9e-430c-8b3c-af5921f35b45","added_by":"auto","created_at":"2024-10-18 09:39:11","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":376411,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS4B.png","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/2e4c4c5b66d956b19c70bd29.png"},{"id":66946617,"identity":"74c96e9b-2f76-41c1-b277-e2efb42484d4","added_by":"auto","created_at":"2024-10-18 09:47:11","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":13393,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/3904101e1a3bd39c957f79bf.xlsx"},{"id":66945723,"identity":"65176a41-a4ba-4429-8896-674a082dc082","added_by":"auto","created_at":"2024-10-18 09:39:11","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":12857,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/8c5b89c9f52bcc367437b4bc.xlsx"},{"id":66945735,"identity":"acf4b9ad-a639-44de-ae86-72defb477aef","added_by":"auto","created_at":"2024-10-18 09:39:13","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":12737,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/d938bd52c38e74172b141078.xlsx"},{"id":66946621,"identity":"08d740a0-dc82-4615-bf04-222487078fd8","added_by":"auto","created_at":"2024-10-18 09:47:12","extension":"xlsx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":12390,"visible":true,"origin":"","legend":"","description":"","filename":"TableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/bb705f9d60da215233864d38.xlsx"},{"id":66945736,"identity":"e1645137-b9a6-482d-aa7f-74b032e8605c","added_by":"auto","created_at":"2024-10-18 09:39:13","extension":"docx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":13998,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryLegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-5008946/v1/723f54f32779c5bc66a22c25.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The burden of rheumatoid arthritis in China from 1990-2021: An analysis based on the Global Burden of Disease Study 2021","fulltext":[{"header":"1. Background","content":"\u003cp\u003eRheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic, erosive, symmetrical, and polyarticular inflammation. It represents a significant challenge among rheumatic diseases[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. RA affects approximately 0.5-1% of the global population, with a prevalence that is at least twice as high in females as in males. RA prevalence increases with age, peaking in the 50\u0026ndash;59 years age group[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It is linked to synovitis and destruction of articular cartilage and bone, and disease progression can lead to joint deformity, loss of function, and potential multisystem damage[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In 2015, \u003cspan\u003e$\u003c/span\u003e21.4\u0026nbsp;billion was spent globally on medications for RA, the highest expenditure among rheumatic diseases, according to the Global Burden of Disease results. Furthermore, the decline in quality of life due to pain and depression contributes to the intangible costs associated with this disease[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, medication and disability-related expenses can significantly strain the finances of families and society[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A comprehensive analysis of the burden of disease in RA patients is of significant clinical importance.\u003c/p\u003e \u003cp\u003eIn recent years, progress has been made in understanding the prevalence characteristics of RA in China. Previous studies have indicated that the prevalence of RA among residents of Beijing was 0.41% in 2012, with a male-to-female prevalence ratio of approximately 1:6[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In 2020, the prevalence of RA among middle-aged and elderly people in Nagchu, Tibet, was 4.86%, with a higher rate observed in females[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The prevalence of RA in the Yinzhou District of Ningbo was 32.65/100,000 from 2011 to 2020[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The evidence derived from these decentralized regional surveys encompasses a limited range of populations, with the majority of studies reporting prevalence rates solely owing to the inherent constraints of the survey methodology and the quality of the available data, which are clearly inadequate. At present, comprehensive nationwide epidemiological surveys and disease burden studies on RA are lacking. Furthermore, the relationship between the disease burden of RA and its social development in China remains largely uncharted. During the COVID-19 pandemic in 2020 and 2021, there was a notable increase in the global adult mortality rate[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The pandemic had a profound impact on the disease outcomes of elderly patients with RA and those with multiple comorbidities associated with RA. Consequently, a re-evaluation of the disease burden of RA in this context is crucial for a comprehensive understanding of the current status of RA in China post-pandemic[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. We analyzed data from the GBD database for the period 1990\u0026ndash;2021 to address these issues. We hope that this analysis will facilitate the development of new prevention and treatment methods and provide practical guidance for the planning and implementation of health services and policies related to RA in China.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data sources\u003c/h2\u003e \u003cp\u003eThe Global Burden of Disease (GBD) study is the most extensive global health survey, covering 371 diseases and 88 risk factors in 204 countries and territories from 1990 to 2021[\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This study provides a robust data foundation for global health policymaking and public health interventions by comprehensively assessing global health losses from major diseases.\u003c/p\u003e \u003cp\u003eThe primary data sources and main data research methods employed by the GBD project have been described in detail in previous studies[\u003cspan additionalcitationids=\"CR13 CR14 CR15\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In summary, disease burden estimates were derived from extensive datasets comprising multiple representative populations. These were collated through a synthesis of information from the literature reviews, published registry science and cohort studies identified in research collaborations, administrative health records and reports, and census data. The coherent burden of disease estimates was produced via DisMod-MR 2.1 and MR-BRT Bayesian meta-regression software via a combined approach. Uncertainty intervals (UIs) were derived from 1,000 samples taken from the model's posterior distribution. The 95th percentile of the UIs was defined as the 2nd and 97.5th percentiles of the distribution, quantifying the uncertainty of the estimates.\u003c/p\u003e \u003cp\u003eWe gathered extensive data on the prevalence, mortality, YLLs, YLDs, and DALYs related to RA in China from 1990 to 2021, sourced from the GBD 2021 database available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ghdx.healthdata.org/gbd-results-tool.For\u003c/span\u003e\u003cspan address=\"http://ghdx.healthdata.org/gbd-results-tool.For\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e analysis, disease burden indicators were converted into specific numbers or age- standardized rates per 100,000 people. In this way, China\u0026rsquo;s findings can be compared with global data and data from Middle-SDI and High-middle-SDI countries with similar levels of economic development to China. To ensure transparency, reliability, and replicability, our study adhered to the Guidelines for Accurate and Transparent Health Evaluation Reporting (GATHER). This approach enhances the scientific value of the overall study[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Notably, no human participants or animal experiments were Involved in this study. The GBD is an openly accessible database, and all participant data are anonymized. Accordingly, no ethical approval was sought.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Definition of Disease\u003c/h2\u003e \u003cp\u003eRA is defined according to the 1987 American College of Rheumatology criteria[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The ICD codes for RA are 714.0-714.9 in the 9th edition and M05, M06, and M08 in the 10th edition. RA severity is categorized into mild, moderate, and severe levels. A disability weight (DW) was assigned to each class as follows: The disability weight for mild, moderate, and severe RA are 0.117 (95% uncertainty interval (UI) 0.080 to 0.163), 0.317 (95% UI 0.216 to 0.440), and 0.581 (95% UI 0.403 to 0.739). Derived from extensive population-based studies across multiple countries, DWs quantifies the health loss associated with RA, ranging from 0 (no disability) to 1 (death) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Please refer to previous GBD publications for more details on this process[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Disease burden\u003c/h2\u003e \u003cp\u003eThe collected data are age-standardized and include all age groups and sexes. Mortality and prevalence rates are estimated using vital statistics, published literature, survey data, surveillance data, and health insurance claims. The YLLs indicator, which represents premature deaths, is calculated by multiplying the number of deaths attributable to a specific risk factor in each age group by the age-standardized life expectancy for that group.\u003c/p\u003e \u003cp\u003eThe standardized life expectancy is derived from the lowest observed mortality risk within each five-year age group in populations exceeding five million individuals. Given the severity of the health conditions under consideration, the life cycle illustrates the temporal occurrence of both short-term and long-term health conditions. DALYs were computed by multiplying the prevalence of RA by the disability weight for each severity level, categorized by class, age, sex, and year. The DALYs was calculated by summing the YLLs and YLDs for each age group, sex, and year[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe SDI is a composite indicator integrating per capita income, average educational attainment, and fertility rates. China's DALYs are benchmarked against those of countries with similar SDI classifications. The methodology employed to calculate the burden of disease indicators has been previously described in detail in the literature[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eThe prevalence, morbidity, mortality, and DALYs were projected per 100,000 people, including their 95% uncertainty intervals. All analyses and graphical generation were performed using the World Health Organization's Health Equity Assessment Toolkit and R (version 4.1).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Prevalence\u003c/h2\u003e \u003cp\u003eIn 2021, China reported 4,755,486.534 cases of RA (95% UI: 4,141,219.489-5,452,492.353). The age-standardized prevalence rate rose by 17.0%, from 205.705 per 100,000 (95% UI: 177.559-238.182) in 1990 to 240.695 per 100,000 (95% UI: 210.769-277.947) in 2021(Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The age-standardized prevalence is significantly greater in males than in females. Stratified by sex, the age-standardized rates increased by 26.0% in males and 12.0% in females (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Globally, the number of RA cases is 17,924,667.325 (95% UI: 15,973,177.811-20,303,303.365) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The age-standardized prevalence rate increased by 14.0%, from 182.539 (95% UI: 161.586-207.478) per 100,000 people in 1990 to 208.899 (95% UI: 186.338-236.334) in 2021 (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). From 1990 to 2021, global rates were consistently lower than those reported in China (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e). During this period, the age-standardized prevalence rate in Middle-SDI countries increased by 22.0%, from 171.708 (95% UI: 150.602-197.151) per 100,000 in 1990 to 209.613 (95%UI: 185.505\u0026ndash;238.440) in 2021(Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). High-middle SDI countries experienced a 24% increase in prevalence (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e), maintaining the highest prevalence throughout the study period.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChange over time for all-age and age-standardized burden of disease indicators per 100,000, China, 1990\u0026ndash;2021\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIndicator (95%UI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eStandardisation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eBoth (female \u0026amp; male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eChange\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePrevalence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e173.545(148.489-203.239)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e334.247(291.072-383.237)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205.705(177.559-238.182)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e240.695(210.769-277.947)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.406(0.332\u0026ndash;0.504)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.722(0.521\u0026ndash;0.887)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.696(0.570\u0026ndash;0.849)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.543(0.391\u0026ndash;0.662)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-22%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eYLLs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.865(8.843\u0026ndash;13.858)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.198(10.337\u0026ndash;17.407)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.948(12.233\u0026ndash;18.895)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.058(7.306\u0026ndash;12.329)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-33%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eYLDs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.395(15.660\u0026ndash;33.560)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.408(30.175\u0026ndash;62.133)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.423(18.516\u0026ndash;38.741)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.137(21.649\u0026ndash;44.861)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eDALYs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.260(26.150-44.731)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.606(43.685\u0026ndash;76.157)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.371(33.040-54.323)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.195(31.298\u0026ndash;55.447)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eIndicator (95%UI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eStandardisation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003efemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eChange\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eYear\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1990\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePrevalence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e248.07(212.57-289.114)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e460.193(402.828-525.799)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e286.220(247.896-332.482)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e321.686(280.041-369.685)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.566(0.458\u0026ndash;0.718)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.881(0.654\u0026ndash;1.123)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.842(0.683\u0026ndash;1.062)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.578(0.425\u0026ndash;0.740)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-31%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eYLLs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.429(12.188\u0026ndash;19.709)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.325(12.910-22.241)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.536(15.611\u0026ndash;24.738)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.243(8.391\u0026ndash;14.429)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eYLDs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.237(22.406\u0026ndash;47.697)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.922(41.699\u0026ndash;85.548)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.043(25.901\u0026ndash;53.781)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.886(29.150-60.315)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eDALYs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.666(36.810-63.311)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.246(57.592\u0026ndash;103.860)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.580(44.308\u0026ndash;74.049)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.129(39.320-72.606)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eIndicator (95%UI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eStandardisation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003emale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eChange\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eYear\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1990\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePrevalence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103.59(87.481-123.994)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e214.089(184.754-250.436)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e107%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127.990(109.845\u0026ndash;150.140)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160.757(139.415-187.509)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.255(0.137\u0026ndash;0.339)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.572(0.267\u0026ndash;0.782)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.540(0.299\u0026ndash;0.726)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.524(0.247\u0026ndash;0.701)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eYLLs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.581(3.521\u0026ndash;8.682)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.215(5.222\u0026ndash;15.737)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.403(5.680-13.952)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.011(4.183\u0026ndash;12.485)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-13%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eYLDs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.157(9.256\u0026ndash;20.263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.653(19.261\u0026ndash;40.589)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.224(11.423\u0026ndash;24.253)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.568(14.474\u0026ndash;30.686)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eDALYs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.738(15.263\u0026ndash;27.507)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.869(29.525\u0026ndash;52.508)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge-standardized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.626(20.371\u0026ndash;36.285)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.579(22.706\u0026ndash;40.278)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Mortality and YLLs\u003c/h2\u003e \u003cp\u003eIn 2021, the number of deaths from RA in China was 10,279.108 (95% UI: 7411.448-12,614.825) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), representing a 22.0% decline in the age-standardized mortality rate from 0.696 per 100,000 people (95% UI: 0.570\u0026ndash;0.849) in 1990 to 0.543 in 2021 (95% UI: 0.391\u0026ndash;0.662) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The decline in mortality was more pronounced for women than for men (31.0% vs. 3.0%), yet women continue to exhibit a significantly elevated mortality rate. The number of deaths from RA globally was 37,330.348(95% UI: 31,060.305-43,135.539) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), with an age-standardized mortality rate that declined from 0.607 (95% UI: 0.538\u0026ndash;0.678) / 100,000 in 1990 to 0.448 (95% UI: 0.373\u0026ndash;0.519)/100,000, representing a 26.0% decline (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). China is beginning to experience a more substantial decline in mortality than in the global mortality rate observed after 2005 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e2\u003c/span\u003e). During the study period, the age-standardized mortality rate for Middle-SDI countries decreased by 22.0%, from 0.638 (95% UI 0.528\u0026ndash;0.726) per 100,000 in 1990 to 0.498 (95% UI 0.393\u0026ndash;0.573) per 100,000 in 2021 (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). It is noteworthy that the age-standardized mortality rates for High-middle SDI remained essentially unchanged at 0.4 (95% UI: 0.4\u0026ndash;0.5) / 100,000 in 1990 and 0.4 (95% UI: 0.3\u0026ndash;0.4) / 100,000 in 2021. (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe age-standardized YLL rate in China exhibited a trend akin to mortality, decreasing from 14.948 (95% UI 12.233\u0026ndash;18.895) per 100,000 in 1990 to 10.058 (95% UI 7.306\u0026ndash;12.329) per 100,000, representing a 33.0% reduction overall, with a 42.0% decline for females and a 1.0% decline for males (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The global trend shows a decrease from 12.351 (95% UI: 10.997\u0026ndash;13.904) / 100,000 in 1990 to 8.442 (95% UI: 7.096-9.700) / 100,000 in 2021, a decrease of 32.0% (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). China's post-2005 decline is even greater compared to the global trend, reflecting the country's mortality trend (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The age-standardized YLL rate for Middle SDI countries decreased by 27.0%, from 13.086 (95% UI 10.895\u0026ndash;15.192) per 100,000 in 1990 to 9.526 (95% UI 7.554\u0026ndash;10.930) per 100,000 in 2021 (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Similarly, the High-middle SDI age-standardized YLL rate declined by 27.0%, from 9.9 (95% UI 9.0-11.2) per 100,000 in 1990 to 7.2 (95% UI 6.2\u0026ndash;8.2) per 100,000 in 2021, which is consistent with the trend observed in Middle SDI countries (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e and Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 YLDs and DALYs\u003c/h2\u003e \u003cp\u003eIn 2021, the total number of YLDs due to RA was 631,813.822 (95% UI 429,315.833-883,990.616), indicating a 17.0% rise in the age-standardized YLD rate from 27,423 (95% UI 18,516\u0026thinsp;\u0026minus;\u0026thinsp;38,741) per 100,000 in 1990 to 32,137 (95% UI 21,649\u0026thinsp;\u0026minus;\u0026thinsp;44,861) in 2021(Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The rate increases by 13.0% for females and 25.0% for males. Age-standardized YLD rates rose by 14% globally from 24.065 (95% UI 16.479\u0026ndash;33.331) in 1990 to 27.452 (95% UI 18.733\u0026ndash;37.824) in 2021(Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). From 1990 to 2021, YLDs in China grew faster than global YLDs. During the same period, the age-standardized YLD rate for Middle SDI countries also exhibited an increase by 22.0%, rising from 22.786 (95% UI: 15.444\u0026ndash;32.246) per 100,000 people in 1990 to 27.689 (95% UI: 18.717\u0026ndash;38.644) in 2021 (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). In High-middle SDI countries, the age-standardized YLD rate increased by 24% from 1990\u0026ndash;2021, increasing from 22.9 per 100,000 (95% UI 15.5\u0026ndash;32.2) to 28.3 per 100,000 (95% UI 19.1\u0026ndash;39.5), aligning closely with the rates observed in middle SDI countries (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e and Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn China, DALYs grow at a slower rate than YLDs. Age-standardized DALYs showed minimal changes, from 42.371 (95% UI 33.040-54.323) per 100,000 population in 1990 to 42.195 (95% UI 31.298\u0026ndash;55.447) in 2021, with a 6% decrease in female DALYs and an 11% increase in male DALYs (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The DALY rate in China is significantly higher compared to Global, Middle SDI, and High-middle SDI countries(Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Globally, there was a 1% decline in DALYs from 36.416 per 100,000 people in 1990 (95% UI 28.711\u0026ndash;45.996) to 35.894 per 100,000 people in 2021 (95% UI 26.953\u0026ndash;46.464) (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). The number of middle-SDI countries increased by 4% from 35.872 (95% UI: 28.404\u0026ndash;45.568) per 100,000 people in 1990 to 37.215 (95% UI: 28.132\u0026ndash;48.115) in 2021 (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). High middle SDI countries, on the other hand, increased by 8%, from 32.8 (95% UI: 25.3\u0026ndash;42.2) per 100,000 people in 1990 to 35.5 (95% UI: 26.3\u0026ndash;46.9) in 2021 (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe burden of RA due to premature death andXXXdisability occurs mainly in the middle-aged population. Accordingly, the highest DALY rates were found in the 55\u0026ndash;59 and 65\u0026ndash;69 age groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003e), with 96,142 (95% UI: 70,097\u0026ndash;129,169) and 134,03 1 (95% UI: 101.517-172.857) per 100,000, respectively, which preceded a sharp increase and was followed by a slight decrease. Prior to this, there was a substantial increase, which was followed by a slight decrease. In all age groups, nearly two-thirds of the disability-adjusted years for rheumatoid arthritis were accounted for by females (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe relative contributions of YLLs and YLDs to DALYs have undergone significant changes over time. In 1990, DALYs were composed of 34.0% YLLs and 66.0% YLDs. By 2021, the proportion of YLDs had increased to 79.0% of the total DALYs in China (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eRA represents a significant global public health concern, with a considerable body of research dedicated to understanding its impact on prevalence and mortality. The present study encompasses a 30-year period and provides a comprehensive description of the disease burden in diverse populations over time. In 2021, the age-standardized prevalence of RA in China was estimated at 240.695 cases per 100,000 people, notably exceeding the global average. These findings suggest that China is a high-risk area for RA (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003e)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. As of 2021, the estimated number of RA patients in China is 4,755,487, nearly doubling over the past three decades. Concurrently, the age-standardized prevalence has also dramatically increased. This is significantly higher than the global average, as well as the averages for high-middle and middle SDI countries. The burden of RA due to disability constitutes more than 60% of total DALYs, surpassing both the global average and the averages of High-middle and Middle SDI countries with similar economic development to China (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Furthermore, our findings indicate that adults continue to represent the most affected demographic, with the highest DALY rates observed among individuals aged 55\u0026ndash;59 years in China. These findings highlight the significant burden of RA in China, underscoring the need for improved management strategies.\u003c/p\u003e \u003cp\u003ePrior research has revealed notable regional differences in the prevalence of RA in China[\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These discrepancies may be attributed to various factors, including different time periods, statistical methodologies, and economic levels. Additionally, the occurrence of RA may be influenced by genetic, climatic, and environmental factors[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In July 2020, the National Clinical Medical Research Centre for Skin and Immunological Diseases published the China Rheumatoid Arthritis Development Report 2020, which indicated that RA is among the top 10 chronic disease prevalence rates among Chinese residents, with a prevalence rate of approximately 0.42% in mainland China. Despite a prevalence of 5\u0026nbsp;million people, China\u0026rsquo;'s large population base makes this disease a significant public health burden. This study presents a comprehensive analysis of RA prevalence, revealing a crude rate of 240.695 per 100,000 people in 2021, which is consistent with previous findings. The increase in the national prevalence of RA may be attributed, at least in part, to improvements in diagnosis and management[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Advancements in diagnostic techniques and criteria for RA, coupled with their widespread clinical use, have decreased misdiagnosis and underdiagnosis, indirectly leading to a higher observed prevalence of RA [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe GBD 2021 study estimates that RA prevalence is significantly lower in men than in women, irrespective of geographical region, socioeconomic status, or sex. In all regions, the prevalence of females is nearly double that of males. Studies from China and the United States indicate a significantly higher prevalence of RA in females compared to males. These findings align with those reported in this study[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Prior research has demonstrated that RA can manifest at any age, with the female population exhibiting a high prevalence of the disease. Numerous observations have postulated that alterations in sex hormone levels may influence the pathogenesis of RA[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, women are more prone to induce modifications in hormone and metabolic levels due to physical disparities (including genetic variations). Additionally, physiological factors, such as menstruation, pregnancy, childbirth, and breastfeeding, as well as lifestyle and occupational influences, can potentially impact the immune system. The more severe and complex condition of female patients could explain the higher disease prevalence in females compared to males[\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. It is therefore recommended that clinicians consider sex as a factor in the individualized treatment of RA.\u003c/p\u003e \u003cp\u003eThe GBD data indicate a strong association between RA development and risk factors such as smoking and behavioral patterns (Figure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). This finding has been corroborated by previous studies[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Evidence suggests that lifestyle interventions, such as smoking cessation, maintaining a healthy weight, and adhering to a healthy diet, can reduce disease activity in RA patients[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Screening first-degree relatives of early-stage RA patients can help identify their risk and enable targeted prevention strategies to reduce disease prevalence.\u003c/p\u003e \u003cp\u003eRA is linked to a higher mortality risk. Compared with the general population, patients with RA may have a reduction in expected survival of between three and ten years. The primary causes of death in this group are malignant tumors, respiratory diseases, and cardiovascular diseases[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This suggests that there is a need for greater emphasis on the management of comorbid RA diseases. Furthermore, RA disease activity is also strongly associated with mortality[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Survival rates are expected to rise due to advancements in treatment paradigms over recent decades, including early intervention[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and modernized therapies[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Data from the GBD show that age-standardized mortality rates in China, globally, and in countries with high-middle and middle SDI peaked around 2005 for the period 1990 to 2021, and have declined over time since then. Since the 21st century, the strengthening of China\u0026rsquo;'s rheumatology disciplines, the deepening of RA precision medicine, and the advent of individualized treatment have effectively slowed and stopped the progression of RA in patients in China. Currently, in addition to traditional therapeutic drugs, the popularization and application of novel RA therapeutic drugs such as targeted drugs for specific inflammatory mechanisms in China[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] have markedly enhanced the clinical treatment compliance rate of patients and prolonged their survival, which may be a contributing factor to the reduction of in RA mortality. Notwithstanding the aforementioned advances in treatment and early diagnosis, challenges persist. These include drug availability, financial constraints, insufficient specialists, and specialized care, which remain present in some areas[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. On the basis of these data, future prevention and control strategies for RA should be assessed and enhanced in accordance with population dynamics and healthcare practices.\u003c/p\u003e \u003cp\u003eThis study revealed that age-standardized DALY rates in China, globally, and in high-middle and middle SDI countries exhibited consistent trends. Age-standardized YLL rates showed similar variations to DALY rates, whereas age-standardized YLD rates experienced significant increases. The DALY in China mainly consists of disability, likely due to insufficient management of RA.RA is a highly disabling autoimmune disease, with joint destruction largely irreversible once it occurs. Previous studies indicate that if left untreated, the 3-year disability rate can reach up to 70% [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In China, the average time from symptom onset to definitive diagnosis for patients exceeds two years, indicating a missed opportunity for RA treatment. The median disease duration of Chinese RA patients is 3.86 years, and the cross-sectional disease remission rate is only 4.27%, which is significantly lower than the remission rate of approximately 20% reported in developed countries. Furthermore, among patients not treated with bDMARDs or csDMARDs, 38.84% and 38.11% of patients, respectively, had moderate and high disease activity. Additionally, approximately 4.2% of patients had comorbidities[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Additionally, studies from the National Rheumatic Disease Data Center (CRDC) have demonstrated that the issue of unregulated medication use for RA in China is a significant concern. The utilization of methotrexate, hydroxychloroquine, and other primary medications for RA initial treatment is considerably lower than the global standard in China. Furthermore, patients exhibit inadequate awareness of the necessity for standardized RA treatment, and Chinese RA patients demonstrate lower treatment adherence and a lack of long-term regular follow-up. Currently, there is a dearth of guiding standards for the management of chronic rheumatic diseases and standardized chronic management models with evidence-based medical evidence [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. These factors contribute to the increased disability rate and higher DALYs in Chinese RA patients. Fortunately, since 2017, several new medications have been approved and introduced into clinical practice, including JAKi inhibitors such as tofacitinib and baricitinib, and biologics such as adalimumab and infliximab. These developments are anticipated to contribute to slowing the progression of severe disability in RA patients[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].To further assess the risk of DALYs and mortality risk of RA in China in the future (2035), we employed the method of Riebler A and Held L[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], which is based on the available continuous data, and utilized the Bayesian Age-Period-Cohort(BAPC) model. This model offers a comprehensive framework for projections using integrated nested Laplace approximations (INLAs) for Bayesian inference and data prediction. The findings indicated a decline in the risk of DALYs and mortality (Figures \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e).It is anticipated that the advancement of RA disease management in the future will prove instrumental in reducing the disease burden.\u003c/p\u003e \u003cp\u003eThe present study has several notable strengths, and monitoring trends in the burden of RA is crucial for the development of public health policies. Our study provides the latest estimates of RA prevalence and mortality in the Chinese population. The primary strength of this study is its extensive coverage spanning nearly three decades, surpassing the scope of most prior research. Furthermore, this study offers valuable insights into RA mortality, a topic that is currently underrepresented in the existing literature. This study has several limitations, including the reliance on global GBD RA data from a limited number of countries, potentially resulting in data incompleteness and affecting the accuracy of burden estimates and the certainty of observed trends. Second, discrepancies in the diagnosis, documentation, and reporting of the disease in disparate countries and regions may impinge upon the comparability of the data. Future research should prioritize incorporating more high-quality studies to increase estimation accuracy. Third, China\u0026rsquo;'s extensive geography and significant socioeconomic disparities, coupled with insufficient provincial data analysis, may have led to healthcare inequalities and an underestimation of the disease burden in less developed regions. Our study highlights the necessity of addressing the RA burden in diverse populations, especially in densely populated Asian countries.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study provides a detailed analysis of the demographic and temporal trends in the disease burden and prevalence of RA in China, highlighting its increase over the past 30 years. Furthermore, this study reveals that RA is a significant public health concern in China, with a considerable proportion of disability and a high economic burden. These findings indicate that China may be behind developed countries in RA health management. This underscores the necessity for enhanced disease surveillance and chronic disease management. Enhancing public awareness and continuous medical education in rheumatology is crucial for advancing the diagnosis, treatment, and management of RA.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eRheumatoid arthritis (RA)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGlobal Burden of Disease (GBD)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eyears of life lost (YLLs)\u003c/p\u003e\n\u003cp\u003eyears lived with disability (YLDs)\u003c/p\u003e\n\u003cp\u003edisability-adjusted life years (DALYs)\u003c/p\u003e\n\u003cp\u003eSocio-demographic Index \u0026nbsp;(SDI)\u003c/p\u003e\n\u003cp\u003eUncertainty intervals (uIs)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003edisability weight (DW)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all members of Global Burden of Disease Collaborative Network and Institute for Health Metrics and Evaluation (IHME).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQinglin Wu and Xiaohu Tang designed the research. Haiyang Wang, Ying Wu and Licheng Tao collected and arranged the data. Haiyang Wang, Wuxia Wang and Shiyun Yin performed the statistical analysis and made the figures and tables. Qinglin Wu, Haiyang Wang, Xiaohu Tang, and Ying Wu wrote and revised the manuscript. All authors read, critically reviewed, and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project is jointly funded by the Yunnan Province Xingdian Talent Program for Famous Physicians [No. Yunnan Health Human Development (2019) 1], Yunnan Province 2024 famous old Chinese medicine experts inheritance studio construction project (Xiaohu Tang famous old Chinese medicine experts inheritance studio).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available in the GBD Data Tool repository (http://ghdx.healthdata.org/gbd-results-tool). This public link to GBD database is open, and the use of data does not require additional consent from IHME.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCush JJ: \u003cstrong\u003eRheumatoid Arthritis\u003c/strong\u003e. \u003cem\u003eRheumatic Disease Clinics of North America \u003c/em\u003e2022, \u003cstrong\u003e48\u003c/strong\u003e(2):537-547.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eLatitude gradient influences the age of onset of rheumatoid arthritis: a worldwide survey\u003c/strong\u003e. \u003cem\u003eClinical Rheumatology \u003c/em\u003e2016, \u003cstrong\u003e36\u003c/strong\u003e(3):485-497.\u003c/li\u003e\n\u003cli\u003eGibofsky A: \u003cstrong\u003eEpidemiology, pathophysiology, and diagnosis of rheumatoid arthritis: A Synopsis\u003c/strong\u003e. \u003cem\u003eThe American journal of managed care \u003c/em\u003e2014, \u003cstrong\u003e20\u003c/strong\u003e(7 Suppl):S128-135.\u003c/li\u003e\n\u003cli\u003eOnuora S: \u003cstrong\u003eItaconate targets fibroblast-like synoviocytes in RA\u003c/strong\u003e. \u003cem\u003eNature Reviews Rheumatology \u003c/em\u003e2024, \u003cstrong\u003e20\u003c/strong\u003e(8):456-456.\u003c/li\u003e\n\u003cli\u003e!!! INVALID CITATION !!! .\u003c/li\u003e\n\u003cli\u003eHsieh P-H, Wu O, Geue C, McIntosh E, McInnes IB, Siebert S: \u003cstrong\u003eEconomic burden of rheumatoid arthritis: a systematic review of literature in biologic era\u003c/strong\u003e. \u003cem\u003eAnnals of the Rheumatic Diseases \u003c/em\u003e2020, \u003cstrong\u003e79\u003c/strong\u003e(6):771-777.\u003c/li\u003e\n\u003cli\u003eLi R, Sun J, Ren LM, Wang HY, Liu WH, Zhang XW, Chen S, Mu R, He J, Zhao Y\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eEpidemiology of eight common rheumatic diseases in China: a large-scale cross-sectional survey in Beijing\u003c/strong\u003e. \u003cem\u003eRheumatology \u003c/em\u003e2011, \u003cstrong\u003e51\u003c/strong\u003e(4):721-729.\u003c/li\u003e\n\u003cli\u003eZhang Q, Liu Q, Lin C, Baima Y, Li H, Gong H, Lin J: \u003cstrong\u003eThe prevalence of rheumatoid arthritis in middle-aged and elderly people living in Naqu City, Tibet, Autonomous Region of China\u003c/strong\u003e. \u003cem\u003eJournal of Orthopaedic Surgery and Research \u003c/em\u003e2020, \u003cstrong\u003e15\u003c/strong\u003e(1).\u003c/li\u003e\n\u003cli\u003eZeng XY, Liu ZK, Shen P, Sun YX, Liu X, Zhan SY, Lin HB, Sun F: \u003cstrong\u003e[Epidemiological study on the incidence of rheumatoid arthritis in adults in Yinzhou district, Ningbo city from 2011-2020]\u003c/strong\u003e. \u003cem\u003eZhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi \u003c/em\u003e2022, \u003cstrong\u003e43\u003c/strong\u003e(8):1288-1295.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGlobal age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2024, \u003cstrong\u003e403\u003c/strong\u003e(10440):1989-2056.\u003c/li\u003e\n\u003cli\u003eD\u0026apos;Silva KM, Wallace ZS: \u003cstrong\u003eCOVID-19 and rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003eCurr Opin Rheumatol \u003c/em\u003e2021, \u003cstrong\u003e33\u003c/strong\u003e(3):255-261.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eBurden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2024, \u003cstrong\u003e403\u003c/strong\u003e(10440):2204-2256.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGlobal burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2024, \u003cstrong\u003e403\u003c/strong\u003e(10440):2162-2203.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGlobal incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2024, \u003cstrong\u003e403\u003c/strong\u003e(10440):2133-2161.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGlobal burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2024, \u003cstrong\u003e403\u003c/strong\u003e(10440):2100-2132.\u003c/li\u003e\n\u003cli\u003eStevens GA, Alkema L, Black RE, Boerma JT, Collins GS, Ezzati M, Grove JT, Hogan DR, Hogan MC, Horton R\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eGuidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2016, \u003cstrong\u003e388\u003c/strong\u003e(10062):e19-e23.\u003c/li\u003e\n\u003cli\u003eArnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF, Cooper NS, Healey LA, Kaplan SR, Liang MH, Luthra HS\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eThe American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003eArthritis and rheumatism \u003c/em\u003e1988, \u003cstrong\u003e31\u003c/strong\u003e(3):315-324.\u003c/li\u003e\n\u003cli\u003eGonzalez A, Maradit Kremers H, Crowson CS, Nicola PJ, Davis JM, 3rd, Therneau TM, Roger VL, Gabriel SE: \u003cstrong\u003eThe widening mortality gap between rheumatoid arthritis patients and the general population\u003c/strong\u003e. \u003cem\u003eArthritis and rheumatism \u003c/em\u003e2007, \u003cstrong\u003e56\u003c/strong\u003e(11):3583-3587.\u003c/li\u003e\n\u003cli\u003eHassen N, Lacaille D, Xu A, Alandejani A, Sidi S, Mansourian M, Butt ZA, Cahill LE, Iyamu IO, Lang JJ\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eNational burden of rheumatoid arthritis in Canada, 1990-2019: findings from the Global Burden of Disease Study 2019 - a GBD collaborator-led study\u003c/strong\u003e. \u003cem\u003eRMD open \u003c/em\u003e2024, \u003cstrong\u003e10\u003c/strong\u003e(1).\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGlobal, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2018, \u003cstrong\u003e392\u003c/strong\u003e(10159):1789-1858.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGlobal, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2018, \u003cstrong\u003e392\u003c/strong\u003e(10159):1859-1922.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGlobal, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2018, \u003cstrong\u003e392\u003c/strong\u003e(10159):1736-1788.\u003c/li\u003e\n\u003cli\u003eFinckh A, Gilbert B, Hodkinson B, Bae S-C, Thomas R, Deane KD, Alpizar-Rodriguez D, Lauper K: \u003cstrong\u003eGlobal epidemiology of rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003eNature Reviews Rheumatology \u003c/em\u003e2022.\u003c/li\u003e\n\u003cli\u003eAlmutairi K, Nossent J, Preen D, Keen H, Inderjeeth C: \u003cstrong\u003eThe global prevalence of rheumatoid arthritis: a meta-analysis based on a systematic review\u003c/strong\u003e. \u003cem\u003eRheumatology International \u003c/em\u003e2020, \u003cstrong\u003e41\u003c/strong\u003e(5):863-877.\u003c/li\u003e\n\u003cli\u003eScherer HU, H\u0026auml;upl T, Burmester GR: \u003cstrong\u003eThe etiology of rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003eJournal of Autoimmunity \u003c/em\u003e2020, \u003cstrong\u003e110\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eKronzer VL, Davis JM: \u003cstrong\u003eEtiologies of Rheumatoid Arthritis: Update on Mucosal, Genetic, and Cellular Pathogenesis\u003c/strong\u003e. \u003cem\u003eCurrent Rheumatology Reports \u003c/em\u003e2021, \u003cstrong\u003e23\u003c/strong\u003e(4).\u003c/li\u003e\n\u003cli\u003eCush JJ: \u003cstrong\u003eRheumatoid Arthritis: Early Diagnosis and Treatment\u003c/strong\u003e. \u003cem\u003eRheumatic diseases clinics of North America \u003c/em\u003e2022, \u003cstrong\u003e48\u003c/strong\u003e(2):537-547.\u003c/li\u003e\n\u003cli\u003eLi Y, Zhang Z, Liu C, Kang Z, Li Z: \u003cstrong\u003eSignificance of High‐Frequency Sonography for the Subclinical Progression of Rheumatoid Arthritis\u003c/strong\u003e. \u003cem\u003eJournal of Ultrasound in Medicine \u003c/em\u003e2024, \u003cstrong\u003e43\u003c/strong\u003e(8):1509-1520.\u003c/li\u003e\n\u003cli\u003eJiang N, Li Q, Li H, Fang Y, Wu L, Duan X, Xu J, Zhao C, Jiang Z, Wang Y\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eChinese registry of rheumatoid arthritis (CREDIT) V: sex impacts rheumatoid arthritis in Chinese patients\u003c/strong\u003e. \u003cem\u003eChinese Medical Journal \u003c/em\u003e2022, \u003cstrong\u003e135\u003c/strong\u003e(18):2210-2217.\u003c/li\u003e\n\u003cli\u003eSacks JJ, Luo YH, Helmick CG: \u003cstrong\u003ePrevalence of specific types of arthritis and other rheumatic conditions in the ambulatory health care system in the United States, 2001\u0026ndash;2005\u003c/strong\u003e. \u003cem\u003eArthritis Care \u0026amp; Research \u003c/em\u003e2010, \u003cstrong\u003e62\u003c/strong\u003e(4):460-464.\u003c/li\u003e\n\u003cli\u003eCutolo M, Gotelli E: \u003cstrong\u003eComplex role of oestrogens in the risk and severity of rheumatoid arthritis in menopause\u003c/strong\u003e. \u003cem\u003eRMD open \u003c/em\u003e2023, \u003cstrong\u003e9\u003c/strong\u003e(2).\u003c/li\u003e\n\u003cli\u003eKosztyła-Hojna B, Moskal D, Kuryliszyn-Moskal A: \u003cstrong\u003eParameters of the assessment of voice quality and clinical manifestation of rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003eAdvances in Medical Sciences \u003c/em\u003e2015, \u003cstrong\u003e60\u003c/strong\u003e(2):321-328.\u003c/li\u003e\n\u003cli\u003eEuesden J, Matcham F, Hotopf M, Steer S, Cope AP, Lewis CM, Scott IC: \u003cstrong\u003eThe Relationship Between Mental Health, Disease Severity, and Genetic Risk for Depression in Early Rheumatoid Arthritis\u003c/strong\u003e. \u003cem\u003ePsychosomatic Medicine \u003c/em\u003e2017, \u003cstrong\u003e79\u003c/strong\u003e(6):638-645.\u003c/li\u003e\n\u003cli\u003eZamanpoor M: \u003cstrong\u003eThe genetic pathogenesis, diagnosis and therapeutic insight of rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003eClinical Genetics \u003c/em\u003e2019, \u003cstrong\u003e95\u003c/strong\u003e(5):547-557.\u003c/li\u003e\n\u003cli\u003eMaisha JA, El-Gabalawy HS, O\u0026rsquo;Neil LJ: \u003cstrong\u003eModifiable risk factors linked to the development of rheumatoid arthritis: evidence, immunological mechanisms and prevention\u003c/strong\u003e. \u003cem\u003eFrontiers in Immunology \u003c/em\u003e2023, \u003cstrong\u003e14\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003evan der Woude D, van der Helm-van Mil AHM: \u003cstrong\u003eUpdate on the epidemiology, risk factors, and disease outcomes of rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003eBest practice \u0026amp; research Clinical rheumatology \u003c/em\u003e2018, \u003cstrong\u003e32\u003c/strong\u003e(2):174-187.\u003c/li\u003e\n\u003cli\u003eKoller‐Smith L, Mehdi AM, March L, Tooth L, Mishra GD, Thomas R: \u003cstrong\u003eRheumatoid arthritis is a preventable disease: 11 ways to reduce your patients\u0026apos; risk\u003c/strong\u003e. \u003cem\u003eInternal Medicine Journal \u003c/em\u003e2022, \u003cstrong\u003e52\u003c/strong\u003e(5):711-716.\u003c/li\u003e\n\u003cli\u003eLee YK, Ahn GY, Lee J, Shin JM, Lee TH, Park DJ, Song YJ, Kim MK, Bae SC: \u003cstrong\u003eExcess mortality persists in patients with rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003eInternational Journal of Rheumatic Diseases \u003c/em\u003e2021, \u003cstrong\u003e24\u003c/strong\u003e(3):364-372.\u003c/li\u003e\n\u003cli\u003eListing J, Kekow J, Manger B, Burmester G-R, Pattloch D, Zink A, Strangfeld A: \u003cstrong\u003eMortality in rheumatoid arthritis: the impact of disease activity, treatment with glucocorticoids, TNF\u0026alpha; inhibitors and rituximab\u003c/strong\u003e. \u003cem\u003eAnnals of the Rheumatic Diseases \u003c/em\u003e2015, \u003cstrong\u003e74\u003c/strong\u003e(2):415-421.\u003c/li\u003e\n\u003cli\u003eYu Z, Lu B, Agosti J, Bitton A, Corrigan C, Fraenkel L, Harrold LR, Losina E, Katz JN, Solomon DH: \u003cstrong\u003eImplementation of Treat‐to‐Target for Rheumatoid Arthritis in the US: Analysis of Baseline Data From a Randomized Controlled Trial\u003c/strong\u003e. \u003cem\u003eArthritis Care \u0026amp; Research \u003c/em\u003e2018, \u003cstrong\u003e70\u003c/strong\u003e(5):801-806.\u003c/li\u003e\n\u003cli\u003eLaha A, Nasra S, Bhatia D, Kumar A: \u003cstrong\u003eAdvancements in rheumatoid arthritis therapy: a journey from conventional therapy to precision medicine via nanoparticles targeting immune cells\u003c/strong\u003e. \u003cem\u003eNanoscale \u003c/em\u003e2024.\u003c/li\u003e\n\u003cli\u003eBabiker-Mohamed MH, Bhandari S, Ranganathan P: \u003cstrong\u003ePharmacogenetics of therapies in rheumatoid arthritis: An update\u003c/strong\u003e. \u003cem\u003eBest Practice \u0026amp; Research Clinical Rheumatology \u003c/em\u003e2024.\u003c/li\u003e\n\u003cli\u003eSteffens D, Contreras-Y\u0026aacute;\u0026ntilde;ez I, Cabrera-Vanegas \u0026Aacute;, Robledo-Torres A, C\u0026aacute;ceres-Giles C, Valverde-Hern\u0026aacute;ndez S, Padilla-Ortiz D, Guaracha-Bas\u0026aacute;\u0026ntilde;ez GA, Pascual-Ramos V: \u003cstrong\u003eAssociation of significant risk perception with the use of complementary and alternative medicine: A cross-sectional study in Hispanic patients with rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003ePlos One \u003c/em\u003e2020, \u003cstrong\u003e15\u003c/strong\u003e(8).\u003c/li\u003e\n\u003cli\u003eGoekoop-Ruiterman YP, de Vries-Bouwstra JK, Allaart CF, van Zeben D, Kerstens PJ, Hazes JM, Zwinderman AH, Ronday HK, Han KH, Westedt ML\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eClinical and radiographic outcomes of four different treatment strategies in patients with early rheumatoid arthritis (the BeSt study): A randomized, controlled trial\u003c/strong\u003e. \u003cem\u003eArthritis and rheumatism \u003c/em\u003e2008, \u003cstrong\u003e58\u003c/strong\u003e(2 Suppl):S126-135.\u003c/li\u003e\n\u003cli\u003eYu C, Li M, Duan X, Fang Y, Li Q, Wu R, Liu S, Wang Y, Wu Z, Shi X\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eChinese registry of rheumatoid arthritis (CREDIT): I. Introduction and prevalence of remission in Chinese patients with rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003eClinical and experimental rheumatology \u003c/em\u003e2018, \u003cstrong\u003e36\u003c/strong\u003e(5):836-840.\u003c/li\u003e\n\u003cli\u003eXiang Y, Wang Q, Li H, Duan X, Fang Y, Yang P, Li Q, Wu R, Huo Y, Shi X\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eChinese registry of rheumatoid arthritis (CREDIT): III. The transition of disease activity during follow‐ups and predictors of achieving treatment target\u003c/strong\u003e. \u003cem\u003eInternational Journal of Rheumatic Diseases \u003c/em\u003e2020, \u003cstrong\u003e23\u003c/strong\u003e(12):1719-1727.\u003c/li\u003e\n\u003cli\u003eCaporali R, Kadakia A, Howell O, Patel J, Milligan J, Strengholt S, Barlow S, Taylor PC: \u003cstrong\u003eA Real-World Comparison of Clinical Effectiveness in Patients with Rheumatoid Arthritis Treated with Upadacitinib, Tumor Necrosis Factor Inhibitors, and Other Advanced Therapies After Switching from an Initial Tumor Necrosis Factor Inhibitor\u003c/strong\u003e. \u003cem\u003eAdvances in therapy \u003c/em\u003e2024, \u003cstrong\u003e41\u003c/strong\u003e(9):3706-3721.\u003c/li\u003e\n\u003cli\u003eRiebler A, Held L: \u003cstrong\u003eProjecting the future burden of cancer: Bayesian age-period-cohort analysis with integrated nested Laplace approximations\u003c/strong\u003e. \u003cem\u003eBiometrical journal Biometrische Zeitschrift \u003c/em\u003e2017, \u003cstrong\u003e59\u003c/strong\u003e(3):531-549.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rheumatoid arthritis, Epidemiology, Disease burden, Trend, China","lastPublishedDoi":"10.21203/rs.3.rs-5008946/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5008946/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eRheumatoid arthritis (RA) is the leading cause of disability and functional limitations in middle-aged and older adults. However, there is a paucity of studies examining the burden of disease associated with RA in China. This study comprehensively describes the prevalence and health loss associated with RA in China from 1990 to 2021, utilizing demographic and geographic variables. The findings of this study can inform effective health policy, healthcare resource allocation, and the optimization of patient management programs.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe utilized extensive data from the Global Burden of Disease (GBD) 2021 database to analyze the prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) of RA in China from 1990 to 2021. We conducted a disaggregated and comparative study by age, sex, and region. A comparison was subsequently made between the Chinese study results and global data, as well as data from Middle and High-middle Socio-demographic Index (SDI) countries with similar economic development to China.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe age-standardized prevalence of RA in China increased by 17% from 1990 to 2021. Concurrently, there was a 22% reduction in mortality, a 33% decline in the YLL rate, a 17% increase in the YLD rate, and no change in the DALY rate. The majority of the burden associated with RA in China is attributable to disability. The YLL rate is higher than the global level and that observed in other Middle-SDI and High-middle SDI countries. There is a greater burden of disease in females across all indicators, and the DALY rate is higher in the middle-aged and older age groups, with a peak at 55\u0026ndash;59 years of age. China's prevalence and DALY rates exceed the global average.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eSystematic studies into the trends of RA burden, encompassing variations related to age and sex, are essential for policymakers, researchers, and healthcare providers in China. The early identification and management of RA, particularly among women and middle-aged to older adults, has the potential to significantly reduce the overall burden of the disease.\u003c/p\u003e","manuscriptTitle":"The burden of rheumatoid arthritis in China from 1990-2021: An analysis based on the Global Burden of Disease Study 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-18 09:39:04","doi":"10.21203/rs.3.rs-5008946/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"848e4739-6872-4d7b-bc23-0bbc4fcc919f","owner":[],"postedDate":"October 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-23T08:24:29+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-18 09:39:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5008946","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5008946","identity":"rs-5008946","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}