Trends and disparities in the burden of autoimmune diseases in China and globally: A comparative analysis based on the Global Burden of Disease Study 2021

Abstract

This study aimed to quantify long-term trends and burdens of 5 autoimmune diseases in China and globally from 1990 to 2021 using Global Burden of Disease 2021 data and identify drivers of change to guide prevention and health planning. Using Global Burden of Disease 2021 data, we analyzed type 1 diabetes mellitus (T1DM), inflammatory bowel disease (IBD), multiple sclerosis (MS), psoriasis (PS), and rheumatoid arthritis (RA) in China and worldwide from 1990 to 2021. We assessed age-standardized prevalence, disability-adjusted life years (DALYs), and temporal trends via joinpoint regression, and decomposed DALY changes into contributions from population growth, aging, and epidemiological transition. In 2021, global age-standardized prevalence (per 1,00,000) was highest for PS (515.95), followed by T1DM (238.19), RA (208.90), IBD (44.88), and MS (22.17). In China, RA (240.70) exceeded global levels, PS (474.02) was similar, and the other diseases were lower. All 5 autoimmune diseases showed increasing trends in China (IBD 1.62%, MS 1.21%, PS 0.88%, RA 0.51%, T1DM 1.15%), with growth rates surpassing global averages. DALY decomposition showed declines in IBD (AAPC = −2.86%) and T1DM (AAPC = −1.86%) driven by epidemiological improvements; increases in MS (AAPC = 0.95%) and PS (AAPC = 0.88%) driven by worsening patterns and aging; and stable RA burden (AAPC = −0.02%) mainly influenced by population growth and aging. Over 3 decades, autoimmune disease prevalence in China rose substantially, narrowing gaps with high-income regions. Declines in DALYs for IBD, T1DM, and RA reflect improved detection and care, while rising DALYs for MS and PS highlight the need for precision prevention, early intervention, and equitable resource allocation.

1. Introduction

Autoimmune diseases (AIDs) are a heterogeneous group of complex disorders triggered by immune tolerance dysregulation, whereby the immune system mounts aberrant responses against self-antigens, resulting in chronic inflammation and multi-organ or multisystem damage.^[1] These diseases are characterized not only by substantial clinical heterogeneity but also by high rates of disability, prolonged disease course, and intricate management demands, imposing significant health loss and socioeconomic burden.^[2] It is estimated that 5% to 10% of the global population is affected by various types of AIDs.^[3,4] Driven by genetic susceptibility, environmental exposures, population aging, and lifestyle changes,^[5-7] the prevalence of AIDs continues to rise. Although advances in biologics and small-molecule targeted therapies have substantially improved outcomes in some patients,^[8] AIDs remain a major global public health challenge.

Existing epidemiological studies are largely based on local registries or cohort investigations, with substantial variation in data sources, case definitions, and analytical methods, making standardized cross-country comparisons difficult. These methodological limitations constrain the ability to position national burdens within a global spectrum and hinder the exploration of multidimensional drivers underlying population-level differences. As the world’s most populous country undergoing rapid socioeconomic transformation and healthcare system reform, China represents a critical setting in which to quantify disease burden and compare with global trends. Such analyses not only clarify China’s position within the global landscape but also provide essential evidence for optimizing resource allocation and developing tailored prevention and control strategies.

Using data from the Global Burden of Disease (GBD) Study 2021, we systematically assessed the prevalence, health loss, and long-term trends of 5 major AIDs, namely inflammatory bowel disease (IBD), rheumatoid arthritis (RA), multiple sclerosis (MS), psoriasis (PS), and type 1 diabetes mellitus (T1DM) in China and globally from 1990 to 2021. In contemporary immunology and clinical literature, these conditions are also widely categorized as immune-mediated inflammatory diseases (IMIDs), reflecting their shared features of chronic inflammation and immune dysregulation despite heterogeneity in pathogenetic mechanisms. Given the substantial overlap between AIDs and IMIDs in population-level research, the terminology adopted in this study aligns with established epidemiological convention while remaining conceptually compatible with the broader IMID framework. This study aimed to address 3 key questions: changes in prevalence (“how many people are affected”), magnitude of health loss (“how severe is the burden”), and long-term evolutionary trends (“how fast is the change”). The findings are expected to provide theoretical insights and practical references for characterizing epidemiological patterns, identifying risk factors, and informing precision prevention strategies.

2. Materials and methods

2.1. Data source

This study is a population-level ecological trend analysis based on secondary data from the Global Burden of Disease (GBD) 2021 study. Data were obtained from the Global Burden of Disease, Injuries, and Risk Factors Study 2021, organized and maintained by the Institute for Health Metrics and Evaluation at the University of Washington. GBD 2021 is among the most comprehensive and standardized global database for disease burden, covering 204 countries and territories, 811 subnational regions, 371 diseases and injuries, and 88 risk factors, spanning the years 1990 to 2021.^[9,10] This study focused on 5 major AIDs: IBD, RA, MS, PS, and T1DM, extracting prevalence, mortality, years lived with disability, and disability-adjusted life years (DALYs) for both China and global levels. These 5 AIDs were selected because they represent distinct organ systems (gastrointestinal, musculoskeletal, neurologic, dermatologic, and endocrine, respectively) and have robust, standardized epidemiological data available within the GBD framework. Other autoimmune diseases were excluded due to incomplete or inconsistent reporting in GBD 2021.

All data were obtained from the official GBD Results Tool (http://ghdx.healthdata.org/gbd-results-tool), with disease definitions strictly following the standardized GBD mapping and International Classification of Diseases-10 coding. Data were stratified by sex and 5-year age groups (<5, 5–9, 10–14 … ≥95 years). The study focused on AIDs that met the following inclusion criteria: standardized case definitions based on International Classification of Diseases-10 codes, availability of continuous data from 1990 to 2021, and availability of age-standardized prevalence and DALYs estimates for both China and global levels. Diseases with incomplete time-series data or inconsistent reporting were excluded. Estimates derived directly from the GBD database are presented with 95% uncertainty intervals, reflecting uncertainties from modeling processes. For the regression analyses (Joinpoint), 95% confidence intervals (CIs) were used to represent the precision of the estimated trends. All data were directly extracted from the GBD Results Tool. No additional data cleaning was performed beyond standard extraction procedures. Countries with modeled estimates but wider uncertainty intervals were retained, as GBD provides internally adjusted estimates accounting for incomplete raw data through Bayesian meta-regression modeling. Data extraction occurred in August 2025, and all analyses were completed between September and October 2025. As this study used publicly available data without individual identifiers, ethical approval was not required. The analysis adhered to the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER),^[11] ensuring transparency and reproducibility.

2.2. Statistical analysis

To control for differences in age structure, all metrics were age-standardized, including incidence, prevalence, mortality, years lived with disability, and DALYs rate. The primary focus of this study was on age-standardized prevalence rate (disease magnitude) and age-standardized DALYs rate (overall burden), with other metrics presented in Table S1, Supplemental Digital Content.

Temporal trends in the age-standardized prevalence rate and age-standardized DALYs rate for each autoimmune diseases were evaluated using the Joinpoint Regression Program. Joinpoint regression identifies statistically significant changes in long-term trends and divides the entire observation period into several linear segments, each characterized by a distinct slope. For each segment, the annual percent change (APC) and its 95% confidence interval (CI) were estimated using log-linear regression models. The average annual percent change (AAPC) was then calculated as a weighted geometric mean of the APCs across all segments to describe the overall trend throughout the study period. The statistical significance of APC and AAPC values was assessed using Monte Carlo permutation tests with 4499 random resamples, allowing up to 5 joinpoints.^[12] A trend was considered increasing if the lower bound of the 95% CI was greater than zero, decreasing if the upper bound was less than zero, and stable if the CI included zero.

To further explore the driving factors underlying changes in disease burden, we applied the standard decomposition approach used in the GBD framework. This method partitions the total change in DALYs between 1990 and 2021 into 3 major components: population growth, representing the effect of increasing population size; population aging, capturing the impact of shifts in the age structure; and epidemiological transition, reflecting changes in disease-specific rates independent of demographic effects. This decomposition allows quantification of how much of the overall change in DALYs can be attributed to demographic versus epidemiological factors. Analyses were stratified by sex to identify heterogeneity in the evolution of autoimmune diseases burdens.

All data processing and visualization were conducted using R software (version 4.5.1). Joinpoint regression analyses were performed using the Joinpoint Regression Program (version 5.1.0) developed by the US National Cancer Institute, ensuring reproducibility and methodological rigor.

3. Results

3.1. Disease magnitude: evolution of patient populations

From 1990 to 2021, the number of patients with the 5 major AIDs increased substantially in both China and globally, though the growth rate and distribution varied across diseases (Table 1).

Table 1.

Prevalence of major autoimmune diseases in China and globally in 1990 and 2021.

Diseases	Region	1990		2021		1990–2021 AAPC	P-value
		All-ages cases, n (95% CI)	Age-standardized rates per 1,00,000 people, n (95% CI)	All-ages cases, n (95% CI)	Age-standardized rates per 1,00,000 people, n (95% CI)	n (95% CI)
IBD	China	62,098 (52,446, 75,050)	5.59 (4.73, 6.69)	1,68,077 (1,41,521, 2,01,684)	9.16 (7.8, 11.01)	1.62 (1.10, 2.14)	<.001
IBD	Global	21,70,243 (18,92,402, 25,22,561)	48.02 (41.94, 55.78)	38,30,119 (33,12,834, 45,11,555)	44.88 (38.8, 52.86)	−0.22 (−0.27, −0.17)	<.001
MS	China	17,887 (13,402, 23,693)	1.55 (1.19, 2.01)	40,159 (31,807, 50038)	2.23 (1.74, 2.83)	1.21 (1.14, 1.28)	<.001
MS	Global	10,04,660 (8,68,374, 11,65,225)	22.26 (19.3, 25.65)	18,87,768 (16,88,654, 21,13,708)	22.17 (19.77, 24.82)	−0.01 (−0.04, 0.01)	.251
PS	China	39,21,863 (37,89,618, 40,53,307)	362.04 (350.27, 373.61)	84,53,045 (81,61,389, 8743685)	474.02 (458.6, 488.88)	0.88 (0.85, 0.90)	<.001
PS	Global	2,30,56,630 (2,23,17,288, 2,38,05,091)	477.72 (462.1, 492.7)	4,29,83,446 (4,16,54,457, 4,43,13,231)	515.95 (500.2, 531.62)	0.24 (0.23, 0.26)	<.001
RA	China	20,41,682 (17,46,913, 23,91,022)	205.7 (177.56, 238.18)	47,55,487 (4141219, 54,52,492)	240.7 (210.77, 277.95)	0.51 (0.49, 0.53)	<.001
RA	Global	79,59,055 (70,41,419, 90,85,469)	182.54 (161.59, 207.48)	1,79,24,667 (1,59,73,178, 2,03,03,303)	208.9 (186.34, 236.33)	0.44 (0.42, 0.46)	<.001
T1DM	China	7,26,871 (5,92,900, 8,89,667)	61.36 (50.48, 74.39)	14,42,775 (1173170, 17,79,499)	86.78 (70.55, 107.44)	1.15 (1.04, 1.26)	<.001
T1DM	Global	95,28,448 (80,64,482, 1,13,21,859)	191.96 (163.71, 226.38)	1,96,16,530 (1,66,33,387, 2,31,79,713)	238.19 (202.2, 281.43)	0.70 (0.68, 0.72)	<.001

AAPC = average annual percent change, CI = confidence interval, IBD = inflammatory bowel disease, MS = multiple sclerosis, PS = psoriasis, RA = rheumatoid arthritis T1DM = type 1 diabetes mellitus.

In addition to temporal changes, the global distribution of crude prevalence rates for the 5 autoimmune diseases in 2021 is shown in Figure 1. The maps display marked geographical heterogeneity across all diseases. Higher crude prevalence rates were observed in North America, Northern and Western Europe, and Australia, while lower rates occurred in most regions of Africa and South Asia. IBD (Fig. 1A) and MS (Fig. 1B) showed a west-to-east gradient, with the highest prevalence in Europe and Oceania. PS (Fig. 1C) and RA (Fig. 1D) were most prevalent in North America and Europe. T1DM (Fig. 1E) showed dispersed high-prevalence areas in Northern Europe and North America.

Figure 1.

Global crude prevalence rate of 5 major autoimmune diseases in 2021. Each country is shaded according to its crude prevalence rate in 2021, based on estimates from the GBD study. The maps use 5-level quantile classifications specific to each disease, representing increasing prevalence from light yellow (lowest) to dark red (highest). Gray areas indicate countries with no available data (NA). Regional insets highlight the Caribbean & Central America, Persian Gulf, Balkan Peninsula, Southeast Asia, West Africa, Eastern Europe, Northern Europe, and North America to facilitate visualization of small-area details. (A) Global crude prevalence rate of inflammatory bowel disease in 2021. (B) Global crude prevalence rate of multiple sclerosis in 2021. (C) Global crude prevalence rate of psoriasis in 2021. (D) Global crude prevalence rate of rheumatoid arthritis in 2021. (E) Global crude prevalence rate of type 1 diabetes mellitus in 2021. GBD = Global Burden of Disease, NA= no available data.

In China, the number of patients with IBD increased markedly from 62,000 in 1990 to 1,68,000 in 2021, representing a 171% rise. The age-standardized prevalence rate also rose from 5.6 to 9.2 per 1,00,000, with a notable acceleration around 2010 (Fig. 2A). At the global level, the total number of IBD patients remained high but the growth rate slowed, reaching approximately 3.83 million cases in 2021. During the same period, the age-standardized prevalence rate declined slightly from 48.02 to 44.88 per 1,00,000 (Fig. 2B).

Figure 2.

Number of cases and age-standardized prevalence rates of 5 major autoimmune diseases in China and globally, stratified by sex, 1990 to 2021. (A) Number of cases and age-standardized prevalence rate of inflammatory bowel disease in China. (B) Number of cases and age-standardized prevalence rate of inflammatory bowel disease globally. (C) Number of cases and age-standardized prevalence rate of multiple sclerosis in China. (D) Number of cases and age-standardized prevalence rate of multiple sclerosis globally. (E) Number of cases and age-standardized prevalence rate of psoriasis in China. (F) Number of cases and age-standardized prevalence rate of psoriasis globally. (G) Number of cases and age-standardized prevalence rate of rheumatoid arthritis in China. (H) Number of cases and age-standardized prevalence rate of rheumatoid arthritis globally. (I) Number of cases and age-standardized prevalence rate of type 1 diabetes mellitus in China. (J) Number of cases and age-standardized prevalence rate of type 1 diabetes mellitus globally.

For MS, although the overall patient base in China was relatively small, the growth rate was substantial, with cases rising from 18,000 in 1990 to 40,000 in 2021, a 125% increase. The age-standardized prevalence rate rose from 1.6 to 2.2 per 1,00,000, and female prevalence remained consistently higher than male prevalence throughout the study period (Fig. 2C). Globally, MS cases increased steadily to approximately 1.89 million, whereas the age-standardized prevalence rate remained largely stable (Fig. 2D).

PS represented the largest patient population among the 5 diseases studied. In China, the number of patients increased from 3.92 million in 1990 to 8.45 million in 2021, corresponding to a 116% rise. The age-standardized prevalence rate also increased from 362 to 474 per 1,00,000 (Fig. 2E). At the global level, PS cases rose from 23 million to 43 million, with the age-standardized prevalence rate increasing by about 8%, confirming its status as the most prevalent autoimmune disease worldwide (Fig. 2F).

For RA, patient numbers in China grew from 2.04 million in 1990 to 4.76 million in 2021, while the age-standardized prevalence rate increased from 205.7 to 240.7 per 1,00,000. As with MS, women consistently exhibited higher prevalence than men (Fig. 2G). Globally, RA cases increased to approximately 17.92 million during the same period, with the age-standardized prevalence rate rising by 14.4%, indicating the continuing global burden of the disease (Fig. 2H).

T1DM also showed rapid expansion in China, with the number of patients doubling from 7,27,000 in 1990 to 1.44 million in 2021. The age-standardized prevalence rate rose from 61.4 to 86.8 per 1,00,000 (Fig. 2I). Globally, nearly 19.62 million individuals were affected, and the age-standardized prevalence rate increased by 24.1%, representing the fastest rise among all 5 autoimmune diseases studied and underscoring its significant public health challenge (Fig. 2J).

3.2. Age and sex distribution

Age and sex stratified analyses revealed distinct epidemiological differences across the 5 major autoimmune diseases. In China, the prevalence of IBD increased with age, peaking between 40 and 50 years before gradually declining, with slightly higher rates in women (Fig. 3A). Globally, IBD prevalence rose steadily until reaching a plateau at ages 50 to 70, after which it leveled off, and sex differences were minimal (Fig. 3B).

Figure 3.

Age- and sex-specific prevalence of 5 major autoimmune diseases in China and globally in 2021. (A) Age- and sex-specific prevalence of inflammatory bowel disease in China. (B) Age- and sex-specific prevalence of inflammatory bowel disease globally. (C) Age- and sex-specific prevalence of multiple sclerosis in China. (D) Age- and sex-specific prevalence of multiple sclerosis globally. (E) Age- and sex-specific prevalence of psoriasis in China. (F) Age- and sex-specific prevalence of psoriasis globally. (G) Age- and sex-specific prevalence of rheumatoid arthritis in China. (H) Age- and sex-specific prevalence of rheumatoid arthritis globally. (I) Age- and sex-specific prevalence of type 1 diabetes mellitus in China. (J) Age- and sex-specific prevalence of type 1 diabetes mellitus globally.

MS in China demonstrated a unimodal distribution, peaking around age 30 and declining thereafter. Women consistently exhibited higher prevalence, with the largest sex gap observed at the peak, although the difference persisted at older ages (Fig. 3C). Globally, MS also showed a unimodal pattern, but with a later peak at approximately 40 years of age. Female prevalence was consistently higher worldwide, and the sex gap was more pronounced than in China (Fig. 3D).

PS in China showed a bimodal distribution, with 1 peak in early adulthood and another in middle age. Sex differences varied by age group, showing stage-specific reversals (Fig. 3E). Globally, PS prevalence followed a monotonic increase from adolescence, forming a broad plateau between ages 50 and 60 before declining gradually, with no consistent sex reversal observed (Fig. 3F).

RA in China exhibited a monotonically increasing age distribution, with prevalence rising sharply after age 40 and peaking around age 60 before slowly declining. Women consistently had higher prevalence, with the sex gap most pronounced in middle-aged and older groups (Fig. 3G). Globally, RA displayed a similar pattern but at higher overall levels, peaking around ages 60 to 70 before declining, with women persistently higher than men (Fig. 3H).

T1DM in China rose rapidly from childhood to early adulthood, reaching a relatively high plateau in young or middle adulthood. Male prevalence was generally higher, and while female rates declined slightly after age 60, male rates continued to increase modestly into older age (Fig. 3I). Globally, T1DM prevalence demonstrated an almost monotonic increase with age. Men were slightly higher in most age groups, though sex differences were not substantial (Fig. 3J).

3.3. Disease severity: DALYs burden

When measured by DALYs, China exhibited a clear pattern of a “double burden” (Table 2). The age-standardized DALYs rate for IBD declined markedly from 18.38 per 1,00,000 in 1990 to 7.68 per 1,00,000 in 2021, with an AAPC of–2.86, substantially greater than the global decline (AAPC = −0.57). A similar trend was observed for T1DM, where the age-standardized DALYs rate fell from 28.22 to 15.59 per 1,00,000 (AAPC = −1.86), again outpacing the global reduction (AAPC = –0.41). In contrast, the age-standardized DALYs rate for MS in China increased from 0.62 to 0.83 per 1,00,000 (AAPC = 0.95), whereas the global burden decreased (AAPC = −0.37). PS also showed a substantial rise in China, with the age-standardized DALYs rate increasing from 31.45 to 41.23 per 1,00,000 (AAPC = 0.88), compared with only a slight global increase (AAPC = 0.24). RA remained essentially stable in China (AAPC = –0.02).

Table 2.

DALYs of major autoimmune diseases in China and globally in 1990 and 2021.

Diseases	Region	1990		2021		1990–2021 AAPC	P-value
		All-ages cases, n (95% CI)	Age-standardized rates per 1,00,000 people, n (95% CI)	All-ages cases, n (95% CI)	Age-standardized rates per 1,00,000 people, n (95% CI)	n (95% CI)
IBD	China	1,62,186 (1,15,400, 2,06,768)	18.38 (12.69, 23.14)	1,36,932 (1,09,830, 1,71,866)	7.68 (6.2, 9.57)	−2.86 (−3.05, −2.67)	<.001
IBD	Global	9,48,861 (8,08,101, 10,96,717)	21.54 (18.47, 24.82)	15,10,784 (13,08,508, 17,50,363)	18.07 (15.67, 20.91)	−0.57 (−0.68, −0.46)	<.001
MS	China	7016 (5078, 9796)	0.62 (0.46, 0.87)	15,005 (11,002, 19,590)	0.83 (0.61, 1.09)	0.95 (0.78, 1.12)	<.001
MS	Global	5,74,234 (4,96,156, 6,62,160)	12.78 (11.1, 14.72)	9,73,298 (8,38,210, 11,33,291)	11.37 (9.77, 13.23)	−0.37 (−0.49, −0.25)	<.001
PS	China	3,43,657 (2,47,483, 4,61,828)	31.45 (22.71, 42.12)	7,28,553 (5,28,686, 9,71,655)	41.23 (29.83, 55.12)	0.88 (0.86, 0.91)	<.001
PS	Global	19,96,756 (1441303, 26,70,809)	41.08 (29.75, 54.94)	36,89,928 (26,84,040, 49,17,113)	44.38 (32.23, 59.16)	0.24 (0.22, 0.26)	<.001
RA	China	4,03,058 (3,07,641, 5,26,244)	42.37 (33.04, 54.32)	8,33,818 (6,21,520, 10,83,523)	42.19 (31.3, 55.45)	−0.02 (−0.13, 0.09)	.759
RA	Global	15,45,699 (12,01,479, 19,77,786)	36.42 (28.71, 46)	30,75,303 (23,10,381, 39,74,046)	35.89 (26.95, 46.46)	−0.05 (−0.10, 0.01)	.090
T1DM	China	3,28,727 (2,76,234, 3,92,069)	28.22 (23.53, 34.27)	2,48,596 (2,01,970, 3,02,828)	15.59 (12.75, 18.82)	−1.86 (−2.07, −1.64)	<.001
T1DM	Global	25,73,014 (22,69,185, 29,27,132)	50.53 (44.35, 57.9)	35,97,713 (30,37,759, 42,49,994)	44.47 (37.57, 52.38)	−0.41 (−0.48, −0.34)	<.001

AAPC = average annual percent change, CI = confidence interval, IBD = inflammatory bowel disease, MS = multiple sclerosis, PS = psoriasis, RA = rheumatoid arthritis T1DM = type 1 diabetes mellitus.

At the global level, age-standardized DALYs rate for all 5 autoimmune diseases demonstrated a gradual overall decline. However, PS and RA continued to represent the greatest contributors to disease burden, with age-standardized DALYs rate in 2021 of 44.38 and 35.89 per 1,00,000, respectively.

3.4. Core trends: rate of change

Joinpoint regression analysis revealed modeled divergences in the rates of change between China and the global level for both age-standardized prevalence rate and age-standardized DALYs rate. Based on GBD estimates, all 5 autoimmune diseases in China showed increasing trends in age-standardized prevalence rate over the past 3 decades, with AAPCs ranging from 0.51% to 1.62%, generally outpacing global trends, though the uncertainty intervals varied in width across diseases. For IBD, prevalence in China showed steady growth from 1990 to 2006, followed by a rapid acceleration between 2006 and 2015, when annual increases exceeded 3%, before leveling off; women exhibited slightly higher rates than men (Fig. 4A). By contrast, global prevalence began to decline after 2010 (Fig. 4B). MS in China rose rapidly from 2000 onward, with a more pronounced increase among women (Fig. 4C), whereas global levels remained largely stable (Fig. 4D). PS in China increased steadily from 1990, with a further acceleration after 2010, producing a notably steeper curve (Fig. 4E); globally, the upward trend was more gradual (Fig. 4F). RA in China showed a moderate rise, with faster increases among women (Fig. 4G), while global prevalence continued to grow steadily with relatively stable sex differences (Fig. 4H). T1DM increased continuously in China, at a pace markedly faster than that observed globally (Fig. 4I, J).

Figure 4.

Joinpoint regression analysis of prevalence trends for 5 major autoimmune diseases in China and globally, 1990 to 2021. (A) Joinpoint trend analysis of inflammatory bowel disease prevalence in China. (B) Joinpoint trend analysis of inflammatory bowel disease prevalence globally. (C) Joinpoint trend analysis of multiple sclerosis prevalence in China. (D) Joinpoint trend analysis of multiple sclerosis prevalence globally. (E) Joinpoint trend analysis of psoriasis prevalence in China. (F) Joinpoint trend analysis of psoriasis prevalence globally. (G) Joinpoint trend analysis of rheumatoid arthritis prevalence in China. (H) Joinpoint trend analysis of rheumatoid arthritis prevalence globally. (I) Joinpoint trend analysis of type 1 diabetes mellitus prevalence in China. (J) Joinpoint trend analysis of type 1 diabetes mellitus prevalence globally.

Trends in age-standardized DALYs rate showed greater heterogeneity across diseases. In China, IBD maintained high levels until 2005, followed by a sharp decline and subsequent stabilization (Fig. 5A), whereas globally, DALYs rates for IBD had already been decreasing since 2000, with a particularly accelerated decline after 2010 (Fig. 5B). For MS, China exhibited a slow upward trend, particularly among women (Fig. 5C), in contrast to the stable or slightly decreasing global levels (Fig. 5D). PS DALYs rates in China began to climb after 2005 and continued to accelerate, reflecting a pronounced cumulative burden (Fig. 5E), while the global rise was much more modest (Fig. 5F). RA in China remained generally stable, with some fluctuations before 2005 followed by a slight decline (Fig. 5G); global levels showed similar stability, although women consistently carried a substantially higher burden (Fig. 5H). For T1DM, China experienced a marked decline in DALYs rates, with the rate of reduction accelerating after 2004 (Fig. 5I), reflecting improved access to care and complication management. The global decline was even more substantial (Fig. 5J), indicating more pronounced progress in international disease control efforts.

Figure 5.

Joinpoint regression analysis of DALYs rate trends for 5 major autoimmune diseases in China and globally, 1990 to 2021. (A) Joinpoint trend analysis of DALYs rates for inflammatory bowel disease in China. (B) Joinpoint trend analysis of DALYs rates for inflammatory bowel disease globally. (C) Joinpoint trend analysis of DALYs rates for multiple sclerosis in China. (D) Joinpoint trend analysis of DALYs rates for multiple sclerosis globally. (E) Joinpoint trend analysis of DALYs rates for psoriasis in China. (F) Joinpoint trend analysis of DALYs rates for psoriasis globally. (G) Joinpoint trend analysis of DALYs rates for rheumatoid arthritis in China. (H) Joinpoint trend analysis of DALYs rates for rheumatoid arthritis globally. (I) Joinpoint trend analysis of DALYs rates for type 1 diabetes mellitus in China. (J) Joinpoint trend analysis of DALYs rates for type 1 diabetes mellitus globally. DALY = disability-adjusted life year.

3.5. Decomposition analysis of DALYs: contribution of driving factors

The decomposition analysis of DALYs reveals the principal drivers and divergent trajectories shaping the evolution of autoimmune disease burden in China compared with global patterns. For IBD and T1DM, China has experienced a pronounced decline in DALYs rates. The magnitude of this decline has been substantially greater in China than at the global level (Fig. 6A, B), underscoring the marked impact of advances in gastroenterology and endocrinology on mitigating disease burden.

Figure 6.

Decomposition analysis of disability-adjusted life years for 5 major autoimmune diseases in China and globally, stratified by sex, 1990 to 2021. (A) Decomposition analysis of DALYs for inflammatory bowel disease in China. (B) Decomposition analysis of DALYs for inflammatory bowel disease globally. (C) Decomposition analysis of DALYs for multiple sclerosis in China. (D) Decomposition analysis of DALYs for multiple sclerosis globally. (E) Decomposition analysis of DALYs for psoriasis in China. (F) Decomposition analysis of DALYs for psoriasis globally. (G) Decomposition analysis of DALYs for rheumatoid arthritis in China. (H) Decomposition analysis of DALYs for rheumatoid arthritis globally. (I) Decomposition analysis of DALYs for type 1 diabetes mellitus in China. (J) Decomposition analysis of DALYs for type 1 diabetes mellitus globally. DALY = disability-adjusted life year

In contrast, DALYs rates for MS and PS have continued to rise during the study period. This trend is especially pronounced in China: the burden of MS has risen most sharply among women (Fig. 6C), reflecting both demographic and gender-specific susceptibility factors. PS has exhibited a persistent and accelerating upward trajectory across the entire population (Fig. 6E). Globally, MS and PS have also shown increases, but the magnitudes of these rises remain lower than those observed in China (Fig. 6D, F).

The DALYs rate of RA has remained relatively stable overall; however, decomposition results indicate that this stability stems from the counterbalancing effects of population aging, which exerted a positive upward contribution, and epidemiological improvements, which provided a negative offsetting influence. Among women, the aging-driven contribution was more prominent (Figs. 6G, H), suggesting an elevated need for healthcare resources directed toward functional disability and long-term management in this subgroup. Finally, despite demographic pressures, the DALYs rate of T1DM in China has continued to decline, with epidemiological improvements playing the dominant negative role. This reduction has been considerably more pronounced than the relatively modest global decline (Fig. 6I, J).

In summary, over the past 3 decades, China has experienced a faster increase in the prevalence of all 5 major AIDs compared with global averages. While age-standardized DALYs rates for IBD and T1DM declined markedly, reflecting improved disease management, MS and PS demonstrated rising burdens, particularly among women. Population aging and epidemiological transition were the principal drivers shaping these divergent trends.

4. Discussion

By jointly analyzing 5 major AIDs, namely IBD, MS, PS, RA, and T1DM, this study provides the first comprehensive cross-system and cross-disease comparison of long-term epidemiological trends in China and at the global level using GBD 2021 data. Unlike previous GBD-based analyses, which typically concentrated on single conditions or earlier GBD iterations, the present study offers a comprehensive evaluation across multiple organ systems and diverse immunopathological pathways. This approach yields novel insights into shared and divergent disease trajectories, sex-specific patterns, and the demographic and epidemiologic drivers of changing burden.

Over the past 3 decades, the age-standardized prevalence rates of all 5 diseases continued to increase in China, generally exceeding global average growth. The most substantial rises occurred in IBD, MS, and T1DM, indicating accelerated epidemiologic transition associated with rapid urbanization, environmental change, and lifestyle westernization. By contrast, corresponding global prevalence rates for IBD and MS remained relatively stable. Burden trends revealed even more heterogeneity: IBD and T1DM experienced substantial declines in age-standardized DALYs, suggesting improvements in diagnosis, glycemic control, and complication management. In contrast, the DALYs burden associated with MS and PS increased significantly, reflecting unmet needs in early diagnosis, disease-modifying therapies, and long-term functional management. RA exhibited a generally stable trajectory, although women continued to bear a disproportionately higher burden.

Age and sex-specific disparities in AIDs likely arise from multilevel interactions among immune regulation, endocrine function, genetic architecture, environmental exposures, and sociocultural determinants. Biologically, estrogens and progesterone enhance B and T cell activation, type I interferon signaling, and antigen presentation, while androgens exert broad immunosuppressive effects by reducing antibody production, T cell proliferation, and innate lymphoid cell activity. These mechanisms partly explain the higher susceptibility of women to MS and RA, and the relatively greater prevalence of PS and T1DM among men.^[13-16] In addition, X-linked immune gene dosage effects, skewed X-chromosome inactivation, and sex-specific microRNA expression further modulate immune homeostasis and predispose females to autoimmunity.^[17-19] Pregnancy-related immune reprogramming and postpartum hormonal fluctuations across the reproductive life course may affect disease activity and contribute to long-term variations in autoimmune risk.^[20-23] Moreover, sex differences in hypothalamic-pituitary-adrenal axis responses and cyclical hormone fluctuations may contribute to stress-induced immune dysregulation, thereby amplifying vulnerability in females with MS and RA.^[24,25]

Behavioral and environmental factors can further magnify these intrinsic differences. Smoking and obesity are strongly associated with both the onset and severity of PS and occur more frequently among men, which may contribute to the higher male burden observed in several populations.^[26] In T1DM, adolescent obesity and insulin resistance are believed to accelerate β-cell destruction and disease progression.^[27-29] Air pollution, including exposure to particulate matter (PM2.5 and PM10) and nitrogen oxides, has been linked to increased risk of several immune-mediated disorders through both epidemiological and genetic analyses.^[30-32] In addition, urbanization, Westernized diets, and gut microbiome alterations may collectively promote chronic inflammation and contribute to rising incidence of inflammatory and metabolic autoimmune diseases.^[33,34]

Sociocultural factors also play an important role in shaping these disparities. Gender-related differences in healthcare access,^[35] occupational exposures such as dust or silica in male-dominated industries,^[36] and variations in health behaviors including physical activity,^[37] alcohol consumption,^[38] and smoking patterns^[39] can all exacerbate sex-based differences in disease burden.

Compared with global averages, China has experienced faster increases in the prevalence and burden of AIDs, a pattern that aligns with rapid industrialization, urbanization, and population aging. According to the long-term GBD trend estimates, the increases in MS, PS, and T1DM have been more pronounced in China compared with many other upper-middle-income countries, potentially reflecting rapid environmental changes, expanding diagnostic capacity, and increasing disease awareness. Geographical distribution maps reveal consistently high-prevalence levels in high-income regions (North America, Northern and Western Europe, Australia), likely reflecting both truly elevated burden and stronger surveillance systems. Conversely, lower prevalence estimates in parts of Africa and South Asia may result from diagnostic gaps rather than biological differences, underscoring the importance of accounting for uncertainties in GBD modeling.

These findings have important implications for national health planning. At the global level, the World Health Organization’s Global Action Plan for the Prevention and Control of Noncommunicable Diseases (2013–2030) emphasizes integrated chronic disease management, continuity of care, and strengthened health-system capacity. Although AIDs have not yet been formally delineated as a distinct category within World Health Organization’s noncommunicable disease priority frameworks, their chronic clinical course, substantial disability impact, and increasing prevalence closely align them with the broader noncommunicable disease agenda. Incorporating AIDs into future World Health Organization strategies would support more systematic resource allocation, enhance standardized surveillance, and strengthen global coordination for these conditions.

In China, national initiatives such as Healthy China 2030, the National Chronic Disease Prevention and Control Plan, and updated clinical guidelines for diabetes and RA have markedly strengthened chronic disease infrastructure, standardized diagnostic and therapeutic pathways, and expanded access to essential care. These system-level improvements may help explain the observed reductions in DALYs for IBD and T1DM. Furthermore, emerging expert consensus in China increasingly advocates for multidisciplinary AIDs management models that integrate rheumatology, dermatology, gastroenterology, and neurology, reflecting a growing recognition of shared inflammatory mechanisms across AIDs and the need for coordinated long-term management.

Against this policy backdrop, the rising AIDs burden in China underscores the urgency of adopting comprehensive, multilevel strategies. These should include establishing national autoimmune disease registries to improve surveillance and facilitate long-term trend monitoring; implementing early screening and risk assessment programs in high-risk populations, particularly young and middle-aged women for MS and RA, and adolescents and young men for T1DM; strengthening primary-care-based management systems through integration of AIDs into existing noncommunicable disease frameworks; and developing evidence-based national clinical guidelines and referral pathways to enhance diagnostic accuracy and continuity of care. Equitable access to diagnostic services and biologic therapies should also be expanded, especially in rural and underdeveloped regions. In parallel, intersectoral policies addressing environmental exposures, air pollution, and lifestyle-related risk factors are critical for sustainable disease control.

This study has several limitations. First, as GBD estimates are based on modeled data, disease burden in regions with limited surveillance systems may be underestimated. In China, uneven surveillance capacity, urban-rural diagnostic gaps, and variable coding practices may also affect case ascertainment and input data quality for GBD modeling, potentially leading to underestimation in low-resource or under-served regions. Periodic updates to case definitions and clinical pathways can further influence data comparability over time. Second, regional disparities in diagnostic capability, reporting quality, and healthcare accessibility may have introduced heterogeneity. Third, temporal changes in diagnostic criteria and potential underreporting in rural or low-resource areas may further contribute to uncertainty. Moreover, the reliance on macro-level epidemiological estimates precludes assessment of individual-level immune dynamics and real-world intervention effects. Finally, residual confounding from unmeasured risk factors and heterogeneity in subnational data remain possible; interpretation should therefore emphasize patterns and directionality rather than precise point estimates.

Despite these limitations, the use of standardized GBD 2021 data ensures comparability across countries and over time. Future work should move beyond aggregate modeling to build national and regional autoimmune disease databases that integrate clinical, epidemiological, and molecular data. Longitudinal cohort studies and biobank networks are needed to elucidate gene-environment-immune interactions and disease trajectories in the Chinese population. Strengthening multiomics research and digital health infrastructures will support precision prevention and personalized management. In addition, evaluating the effectiveness and cost-efficiency of early screening, biologic therapies, and community-based care models can inform policy decisions and guide resource allocation in real-world contexts.

5. Conclusion

This study provides a comprehensive assessment of 5 major AIDs (IBD, MS, PS, RA, and T1DM) in China and globally from 1990 to 2021, revealing both common and distinct epidemiological trajectories. The prevalence of AIDs in China has increased faster than the global average, driven by industrialization, urbanization, and population aging. Declining DALYs rate for IBD and T1DM reflect advances in clinical management, whereas the continued rise in MS and PS burdens highlights unmet needs in early detection and long-term care. RA remains relatively stable but continues to disproportionately affect women.

These findings call for an integrated national response that links prevention, precision medicine, and chronic care. Priorities should include the establishment of national autoimmune disease registries, improvement of early screening and diagnosis, equitable access to biologic therapies, and incorporation of autoimmune diseases into existing noncommunicable disease frameworks. Addressing sex, age, and socioeconomic disparities through targeted and equitable health policies will be essential to reducing future disease burdens and improving population health in the era of immune-mediated disorders.

Acknowledgments

We thank the Institute for Health Metrics and Evaluation (IHME) and the Global Burden of Disease (GBD) study collaborators for their continuous efforts in generating and disseminating high-quality global health data.

Author contributions

Conceptualization: Xingzheng Liu.

Data curation: Xingzheng Liu, Zhengfu Xu.

Formal analysis: Xingzheng Liu, Zhengfu Xu.

Supervision: Gaofeng Song.

Visualization: Xingzheng Liu.

Writing – original draft: Xingzheng Liu.

Writing – review & editing: Zhengfu Xu, Gaofeng Song.