Global burden of aortic aneurysm and its attributable risk factors from 1990 to 2021: an update from the GBD 2021

Global burden of aortic aneurysm and its attributable risk factors from 1990 to 2021: an update from the GBD 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 Global burden of aortic aneurysm and its attributable risk factors from 1990 to 2021: an update from the GBD 2021 Pinyan Huang, Junjie Zong, Song Wang, Han Zhang, Yuqing Niu, Zilong Luo, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7850745/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 Aims: This study aimed to assess the global burden of aortic aneurysm (AA) and its attributable risk factors from 1990 to 2021. Methods: We used data from the Global Burden of Disease (GBD) 2021 Study to analysis disease burden of AA. We assessed trends in deaths and disability-adjusted life years (DALYs) related to AA across different demographic and regional groups, along with major attributable risk factors. Results: In 2021, AA accounted for an estimated 153,900 deaths and 3.1 million DALYs globally. Compared to previous decades, the age-standardized rates (ASRs) of deaths and DALYs have declined by 26.7% and 25.1%, respectively. In addition, the ASRs of both deaths and DALYs remained consistently higher in males than in females and increased with age. Most high socio-demographic index (SDI) regions showed substantial reductions in AA-related ASRs, except for high-income Asia Pacific. Smoking remained the leading contributor to AA-related DALYs among males (45.7%). In contrast, high systolic blood pressure (HSBP) emerged as the predominant risk factor among females in low- and low-middle SDI regions, surpassing smoking (17.0% vs. 8.8% and 17.8% vs. 11.7%, respectively). Conclusion: While ASR of deaths and DALYs from AA have declined since 1990, the total burden continues to rise. Despite advancements in AA prevention and treatment in high-income regions, the burden is increasing in lower income areas, highlighting the need for improved detection and treatment of AA. Preventive programs should strengthen their focus on smoking and HSBP control to reduce the burden of AA. Aortic aneurysm global burden of disease sex risk factors Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Aortic aneurysm (AA) is the second most common aortic condition and poses a serious threat to life. 1 Although the prevalence of AA is lower than that of other cardiovascular diseases (CVDs), its high mortality rate and the rising number of cases make it a growing public health concern, particularly among older adults. 1 , 2 According to the Global Burden of Disease (GBD) 2019 Study, AA accounted for 172,427 deaths globally in 2019, with an 82.1% increase since 1990. Over the same period, AA-related disability-adjusted life years (DALYs) increased by 67.0%, reaching 3.3 million in 2019. 3 , 4 Modifiable risk factors, such as smoking and hypertension, elevate the risk of AA and contribute further to its disease burden. 5 , 6 Although previous GBD studies have documented the overall burden of AA, the coverage of risk factors is incomplete, and updated and detailed assessments of mortality, DALYs, and major risk factors across regions and populations remain scarce. Comprehensive and up-to-date epidemiological data on AA are needed to support more effective prevention and management strategies. This study aims to fill these research gaps, utilizing data from the GBD 2021. We systematically analyze the global disease burden of AA in terms of age-standardized mortality and DALYs, disaggregated by age group, sex, and regions as classified by socio-demographic index (SDI). In addition, we identify the modifiable risk factors contributing to AA in both males and females, including smoking, high systolic blood pressure (HSBP), high body mass index (BMI), lead exposure, and diets high in sodium and low in vegetables and fruits. By clarifying the evolving epidemiological patterns of AA, this study expands and updates previous research to support the development of targeted public health policies aimed at reducing the burden of AA and promoting cardiovascular health worldwide. METHODS Data sources GBD 2021 was a systematic epidemiological research initiative, encompassing 328 billion data sources to assess 459 health outcomes and risk factors in 204 countries and territories. 7 , 8 The waiver of informed consent was reviewed and approved by the University of Washington Institutional Review Board due to the use of deidentified aggregated data from the GBD 2021.The project adheres to the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Raw data were obtained from the GBD 2021 database using the Global Health Data Exchange (GHDx) online query tool ( https://vizhub.healthdata.org/gbd-results/ ). The comprehensive methodology for data collection and analytical processes has been previously documented. 7 , 8 Definitions AA, including both abdominal and thoracic subtypes, were identified based on the International Classification of Diseases (ICD) codes, ICD-9 441–441.9 and ICD-10 I71–I71.9. 9 The burden of AA was quantified in terms of cause-specific mortality and DALYs, calculated as the sum of years of life lost (YLLs) and years lived with disability (YLDs), respectively. YLLs were estimated by multiplying the number of deaths by the standard life expectancy at the age of death. YLDs were calculated by multiplying the prevalence of AA by the corresponding disability weights. 7 , 8 The SDI is a composite indicator reflecting a region’s developmental status, ranging from 0 (worst) to 1 (best). It is derived from three components: the total fertility rate of women under age 25, the mean educational attainment in individuals over 15 years, and lag-distributed income per capita. Countries were grouped into five SDI quintiles: low, low-middle, middle, high-middle, and high. 7 , 8 Seven modifiable risk factors for AA were included, based on the GBD 2021 comparative risk assessment framework: smoking, high BMI, HSBP, diets high in sodium, diets low in vegetables, diets low in fruits, and lead exposure. These risk factors were selected based on the following criteria: sufficient evidence for causation for each risk-outcome pair, using the Bradford Hill criteria; availability of risk exposure data; and potential for risk modification and policy relevance. 8 , 10 , 11 Statistical analysis We estimated counts, the age-standardized rate (ASR) per 100,000 people, and percentage change in ASR with 95% uncertainty interval (UI) to quantify GBD 2021 AA burden metrics. Included metrics were deaths and DALYs, assessed by age group, sex, region, country, and SDI quintile. The ASR was calculated by directly standardizing the global age structure. 7 , 8 UI for all estimates were calculated by averaging the data from 1,000 draws, with the lower and upper bounds of the 95% UI established by the 25th and 975th ranked values among all 1,000. Risk factor attribution was estimated using the population-attributable fraction (PAF), which was calculated for each risk–outcome pair based on population-level exposure, estimated relative risk, and the theoretical minimum risk exposure level. This approach was used to quantify the burden of disease attributable to each risk factor. 9 R software (version 4.3.1) was used for data analysis. For all estimates, a 95% UI excluding zero represents statistical significance. RESULTS Global and regional burden of aortic aneurysm by sex and age In 2021, AA was responsible for an estimated 153,900 deaths globally (95% UI: 138,400 to 165,700), with the highest counts observed in high-SDI regions. The global ASR of deaths was 1.9 per 100,000 population (95% UI: 1.7 to 2.0), a decrease of 26.7% (95% UI: 23.1 to 31.1) compared to 1990. Additionally, AA accounted for 3.1 million (95% UI: 2.9 to 3.4) DALYs globally in 2021. The age-standardized DALY rate was 36.5 per 100,000 (95% UI: 33.5 to 39.5), representing a 25.1% reduction (95% UI: 20.3 to 30.5) from 1990. However, a substantial increase in DALY rates was observed in low-middle SDI regions (45.9%; 95% UI: 19.2 to 73.3) (Table 1 ). Table 1 Counts and age-standardized deaths and DALYs rates of AA in 2021, and their percentage change in ASR from 1990 to 2021, by SDI quintile and GBD region. Deaths (95% UI) DALYs (95% UI) Location 2021 counts 2021 ASR Percentage change in ASR,1990–2021 2021 counts 2021 ASR per 100 000 people Percentage change in ASR,1990–2021 Global 153927.2 (138413.4,165738.7) 1.9 (1.7,2) -26.7 (-31.1, -23.1) 3107762.3 (2857319.7,3353857.8) 36.5 (33.5,39.5) -25.1 (-30.5, -20.3) Low SDI 6371.3 (3931.6,10433.7) 1.5 (0.9,2.4) 8.4 (-12,31.9) 162855 (99208.4,267958.2) 30.8 (18.9,50.4) 7.2 (-13.8,32.6) Low-middle SDI 16808.3 (13956.4,22468.1) 1.3 (1.1,1.8) 47.9 (22.9,73) 398279.7 (333989.6,529920.6) 27.5 (22.9,36.7) 45.9 (19.2,73.3) Middle SDI 28528.4 (25797.3,30958.6) 1.2 (1,1.3) 12.5 (-1.4,25.3) 662164.3 (600453.3,722827.1) 24.9 (22.6,27.1) 15 (-0.8,29.7) High-middle SDI 34826.6 (32309.3,37274.1) 1.8 (1.7,1.9) -10.1 (-17.3, -3.6) 760354.3 (709823.9,817072) 39.7 (37,42.7) -9.8 (-18.6, -2.1) High SDI 67201.9 (57735.4,72287.5) 2.9 (2.5,3.1) -39.8 (-43.5, -37.2) 1120317.3 (1010907.3,1182279.7) 54.5 (50.3,57.1) -40.8 (-43.2, -38.6) Andean Latin America 538.1 (449.4,643.8) 0.9 (0.8,1.1) -7 (-26.9,18.5) 12092.1 (10090.6,14633.2) 20.1 (16.8,24.3) -7.2 (-28.3,19.6) Australasia 1548.7 (1353.6,1679.7) 2.6 (2.3,2.8) -67.6 (-70.5, -65.2) 24880.2 (22366.8,26610.9) 45.5 (41.3,48.6) -69.3 (-71.7, -67.1) Caribbean 1405.2 (1240.5,1582.9) 2.6 (2.3,2.9) -31.7 (-39.7, -22.9) 26859.3 (23699.4,30389.1) 50 (44.1,56.5) -29.4 (-37.8, -20.1) Central Asia 1442.7 (1280.3,1615.1) 2 (1.8,2.2) 110.1 (71.5,150.9) 35159.5 (30894.5,39776.8) 42.7 (37.8,47.9) 80.9 (47.1,115.6) Central Europe 6681.6 (6141.4,7318.1) 2.9 (2.7,3.2) -4.8 (-12.2,4.6) 134478.5 (123463.3,148456.5) 63.7 (58.3,70.6) -7.8 (-16.3,2.7) Central Latin America 3292.7 (2865.4,3768.2) 1.4 (1.2,1.6) -12.3 (-23.1, -0.1) 72061.6 (62326.6,83068) 28.8 (24.9,33.1) -15 (-26.8, -2.5) Central Sub-Saharan Africa 1057.3 (590.7,1706) 2.4 (1.3,3.9) -10.6 (-30.9,16.1) 28158.8 (15580.2,46218.3) 50.5 (28.2,81.6) -10.1 (-32.3,19.1) East Asia 10199 (8228.6,12817.4) 0.5 (0.4,0.6) 40 (-1.6,92) 269442.6 (213790.7,344575.7) 13.3 (10.6,17) 40.1 (-4.6,99.6) Eastern Europe 13406 (12353.5,14430.5) 3.8 (3.5,4.1) 51.8 (38.9,64) 304640.9 (280046.2,328882.9) 91.3 (83.9,98.5) 46.7 (33.4,59.1) Eastern Sub-Saharan Africa 2636.1 (1427.4,4293.5) 1.8 (1,3) -0.8 (-25.7,32) 72025.1 (38938.5,115787.9) 38.5 (20.8,62.6) 0.1 (-26.5,37.9) High-income Asia Pacific 25772.7 (20940,28524.5) 4.4 (3.7,4.8) 56.9 (44.1,67.3) 378280.4 (325386.9,408692) 79.7 (71.8,84.5) 51 (41.2,61) High-income North America 13969.9 (12470.6,14793.3) 2.1 (1.9,2.2) -60.6 (-61.9, -59.5) 271835.2 (253830.1,283631.3) 45.4 (42.9,47.2) -56.8 (-58.2, -55.7) North Africa and Middle East 3693.7 (3202.7,4256.6) 0.9 (0.8,1) 35.8 (-4.8,87.8) 96331.3 (83715.8,112192.8) 20 (17.3,23.1) 22.1 (-16.2,74) Oceania 117.3 (90.5,151.2) 1.9 (1.5,2.5) -15.3 (-30.7,6.6) 3301.2 (2496.5,4381.7) 41.5 (32.1,53.5) -12.3 (-28.7,11.8) South Asia 15979.1 (11378.8,23410.1) 1.2 (0.9,1.8) 71.6 (27.9,136.1) 367475.1 (260596,539642.2) 25 (17.8,36.6) 63.6 (22.3,125.7) Southeast Asia 7390.6 (6476.2,8513.2) 1.4 (1.2,1.6) 34.6 (5.6,70.2) 158458 (137444.7,182388.8) 25.9 (22.6,29.8) 32.2 (1.6,68.4) Southern Latin America 2352.5 (2166.5,2527.6) 2.6 (2.4,2.8) -44.1 (-50.1, -38.2) 48688.9 (45137.7,52222.2) 56.5 (52.4,60.6) -44.1 (-50.4, -38) Southern Sub-Saharan Africa 1236.8 (1123.2,1348.9) 2.5 (2.2,2.7) -20.5 (-32.9,1.2) 30967.2 (27976.5,34411.6) 52 (47,57.2) -18.2 (-29,0.1) Tropical Latin America 10173.1 (9351.9,10728.8) 4 (3.7,4.3) 20.3 (13.6,26.3) 235449.1 (221293.8,246967.9) 91.1 (85.5,95.5) 14.1 (8.8,19.8) Western Europe 27511.1 (24097.6,29189.4) 2.6 (2.3,2.7) -46.2 (-48.9, -44.2) 449312.2 (408553.8,471934.1) 48.5 (45.1,50.6) -47.5 (-49.6, -45.6) Western Sub-Saharan Africa 3523 (1744.6,5980.5) 2.2 (1.1,3.7) -7.2 (-30.6,14.4) 87865 (42721.7,151832.2) 43.5 (21.4,74.1) -6.3 (-30.6,18.6) Data in parentheses are 95% UI. AA, aortic aneurysm; ASR, age-standardized rate; DALYs, disability-adjusted life years; GBD, Global Burden of Diseas; SDI, Socio-Demographic Index; UI, uncertainty interval. From 1980 to 2021, both the total count and ASR of AA-related deaths were consistently higher in males than in females. However, while ASR of deaths declined steadily in males, it remained relatively stable in females (Fig. 1 A). A similar trend was observed for DALYs (Fig. 1 B). In 2021, the highest number of AA-related deaths occurred among males aged 70–74 and females aged 80–84. Death counts were higher in males than in females up to the 85–89 age group, after which females accounted for the majority (Fig. 2 A). DALYs peaked at ages 65–69 in males and 70–74 in females, with consistently higher rates in males across most age groups (Fig. 2 B). The aortic aneurysm burden in different countries Among 204 countries in 2021, the highest AA-related ASRs for deaths (9.2; 95% UI: 7.6 to 10.8) and DALYs (192.8; 95% UI: 159.7 to 228.2) were seen in Armenia; the lowest were observed in Saudi Arabia for both deaths (0.2; 95% UI: 0.2 to 0.3) and DALYs (5.1; 95% UI: 3.7 to 6.7). From 1990 to 2021, the largest drops in ASRs for deaths and DALYs were seen in Serbia (-74.4; 95% UI: -80 to -67.6) and Papua New Guinea (-70.6; 95% UI: -73.3 to -68.2), respectively. Meanwhile, the largest increases ASRs for deaths and DALYs were observed in Japan (385.9; 95% UI: 225.1 to 595) and Indonesia (357.4; 95% UI: 242.4 to 498.6), respectively. Notably, Japan reported the highest absolute number of AA-related deaths (23,800; 95% UI: 19,200 to 26,500) and DALYs (344,000; 95% UI: 294,000 to 372,000) in 2021. This was accompanied by a substantial increase in the ASR of death (185.5%; 95% UI: 114.0 to 272.3), despite a concurrent decline in the DALYs ASR (− 28.0%; 95% UI: −34.1 to − 22.2). (Fig. 3 , Supplementary Table S1). Association of aortic aneurysm burden with socio-demographic index In 2021, high SDI regions exhibited the highest ASRs of death (2.9; 95% UI: 2.5 to 3.1) and DALYs (54.5; 95% UI: 50.3 to 57.1), while low SDI regions exhibited the lowest ASRs of death (1.5; 95% UI: 0.9 to 2.4) and DALYs (30.8; 95% UI: 18.9 to 50.4) (Table 1 ). In the 21 GBD regions, AA-associated death and DALY ASRs exhibited a clear linear relationship with SDI: rates declined markedly in high-SDI regions but remained stable in low- and middle-SDI regions. Over the studied period, higher SDI regions exhibited fluctuations in AA ASRs of death and DALY, following SDI value, while the trends in lower and middle SDI regions remained more stable. Among the 21 GBD regions in 2021, the high-income Asia Pacific (4.4; 95% UI: 3.7 to 4.8) and Tropical Latin America (4.0; 95% UI: 3.7 to 4.3) had the highest AA-related ASRs of death, while the lowest rate was observed in East Asia (0.5; 95% UI: 0.4 to 0.6). The highest ASRs of DALYs were reported in Eastern Europe (91.3; 95% UI: 83.9 to 98.5) and Tropical Latin America (91.1; 95% UI: 85.5 to 95.5), while the lowest rate was reported in East Asia (13.3; 95% UI: 10.6 to 17). From 1980/1990 to 2021, high-income Asia Pacific exhibited the greatest increase in the ASRs of deaths (56.9; 95% UI: 44.1 to 67.3) and DALYs (79.7; 95% UI: 71.8 to 84.5) among the four regions with the highest SDI. Notably, all regions in Asia exhibited increasing AA-related ASRs of deaths and DALYs (Fig. 4 and Table 1 ). The ASRs of deaths and DALYs also showed significant linear associations with SDI at the country level (Supplementary Figure S1). The burden of aortic aneurysm attributable to risk factors by sex group Among the seven risk factors for AA in the GBD 2021, smoking was the primary contributor to DALYs in males globally (45.7%), followed by HSBP (16.8%) and high BMI (7.6%). In comparison, both smoking and HSBP were primary risk factors for DALYs in females globally (17.6% and 17.2%, respectively), followed by high BMI (8.4%). A diet low in fruits (3.7% in male and 3.8% in female) and low in vegetables (2.9% in male and 3% in female) also significantly contributed to AA-related DALYs, followed by a diet high in sodium (1.1% in male and 0.7% in female) and lead exposure (0.7% in male and 0.6% in female). Sex-stratified analyses identified smoking, high-sodium diets, and lead exposure as disproportionate contributors to the DALY ASR of AA, with a greater burden observed in males than females. In contrast, HSBP and high BMI were found to have a larger impact on the DALY ASR in females than in males. Among the SDI quintiles, the proportional contribution of smoking and high BMI to the DALY ASR of AA increased with higher SDI, with the highest percentage in high-middle SDI regions. In contrast, the contribution of diets low in vegetables decreased with higher SDI, with the lowest percentage in high-middle SDI regions (Fig. 5 ). DISCUSSION Our study provides a comprehensive analysis of the global burden of AA and its associated risk factors, revealing substantial disparities in mortality and DALYs across age groups, sex, regions, and SDI levels. Between 1990 and 2021, the global ASRs of AA-related deaths and DALYs declined by 26.7% and 25.1%, respectively. However, the absolute number of AA-related deaths and DALYs continued to increase annually in both males and females; this likely reflects improvements in diagnostic technologies, improved epidemiologic knowledge, population growth, and population ageing. Notably, the ASR of DALYs was higher in males than in females across all years and in most age groups, which may be attributable to tobacco use as a major contributing factor. This study underscores the significant impact of AA on global health and emphasises the need for targeted interventions to mitigate this growing burden, including enhanced control of risk factors, improved screening programs, and equitable access to healthcare. Sex and age differences in global disease burden of aortic aneurysm Consistent with previous epidemiological studies, our findings confirm marked sex- and age-specific disparities in the global burden of AA. 12 We observed that AA-related ASRs of mortality and DALYs were consistently higher in males, aligning with prior evidence that men experience a higher burden of aortic disease. 3 , 4 , 13 – 15 These sex differences are likely driven by a combination of biological and behavioural factors. Biologically, sex-based variations at the cellular and tissue levels may influence disease susceptibility and therapeutic responses. 16 For example, oestrogen is believed to exert protective vascular effects in females, whereas males generally have a lower degree of such hormonal protection. 17 , 18 Men are also considered more likely to adopt unhealthy behaviours, such as smoking, excessive alcohol consumption, and poor dietary habits. These behaviours, along with lower healthcare adherence, cumulatively increase their risk of CVDs. Notably, the AA-related burden in females has remained relatively stable over the past three decades, while the burden in males has shown a substantial decline. This trend may reflect the atypical clinical presentation and delayed onset of AA in females, which potentially contribute to underdiagnosis and treatment delays. Meanwhile, the more substantial burden reduction in males may be partly attributed to the greater benefits of smoking cessation efforts. These findings highlight the importance of sex- and gender-specific approaches in the prevention, diagnosis, and management of AA to address distinct biological risks, behavioural factors, and disease trajectories in both men and women. Age was also a key determinant of AA burden. The ASRs of both deaths and DALYs increased markedly with advancing age, reflecting the progressive nature of AA and its cumulative risk over time. This trend likely results from age-related vascular degeneration and the accumulation of comorbidities in older adults. 19 – 21 Our findings demonstrate that both sex and age significantly shape the global burden of AA. These disparities highlight the urgent need for sex- and age-specific strategies to improve early detection, risk factor management, and outcomes in high-risk populations. Discrepancies across different socio-demographic index levels Significant variation was observed in the temporal trends and cross-national distribution of AA-related DALY and mortality ASRs across regions stratified by SDI quintiles. The SDI—reflecting years of education, per capita income, and total fertility rate—highlights the critical influence of social factors on outcomes relating to AA. 7,8 While regions with higher SDI displayed higher mortality ASRs, low-SDI regions reported lower rates. This may indicate underreporting or misclassification of AA-related deaths in these areas. This underscores the need to enhance early and accurate diagnosis of AA, particularly for paroxysmal or asymptomatic cases. In low-SDI regions, the ASRs of both DALYs and mortality continue to rise, likely due to limited access to essential diagnostic tools and definitive treatments for AA—such as advanced imaging technologies, elective surgical repair, and endovascular aneurysm repair—which are unevenly distributed across socio-economic contexts. 22 – 24 While high-SDI regions have achieved significant reductions in age-standardized incidence and DALYs, low-SDI regions are facing a substantial increase in age-standardized mortality. Recent advances in managing the AA burden in high-SDI regions have overshadowed the neglect of AA care in low-SDI areas. Moving forward, prioritizing prevention, diagnosis, and treatment of AA in low-SDI regions is essential to address these disparities. Discrepancies across different regions and countries This study revealed pronounced regional and national disparities in the burden of AA, which cannot be fully explained by SDI classification alone. Among the four regions with the highest SDI, high-income Asia Pacific was the only one to exhibit an increasing trend in the ASRs of deaths and DALYs from AA over the past three decades. At the country level, Saudi Arabia—despite being a high-SDI country—reported the lowest AA-related burden globally. In contrast, Armenia, a high-middle SDI country, exhibited the highest burden. This suggests that SDI alone is insufficient to account for national disparities in disease burden and that factors such as healthcare quality, prevention programs, and risk factor control play a crucial role. Japan reported the highest absolute number of AA-related deaths and DALYs in 2021. This was accompanied by a rising ASR for deaths, but a declining ASR for DALYs. This phenomenon highlights the impact of an ageing population and underscores the importance of effective disease management and age-specific interventions in minimizing overall health loss, especially among older adults. 25 These findings illustrate the fact that national and regional disparities in AA burden are shaped by more than socioeconomic development alone. Targeted, context-specific strategies are essential to address local gaps in prevention, diagnosis, and long-term management, especially in countries facing rapid population ageing. Attributable risk factors Previous reviews have indicated that AA-related DALYs are associated with several modifiable risk factors, such as smoking, hypertension, and obesity. 5 , 6 Consistent with analysis of the GBD 2019, smoking and HSBP remain the two leading risk factors for AA-related DALYs. 3 , 4 Smoking is a well-established cardiovascular risk factor, and declines in smoking prevalence are closely correlated with reductions in AA-related DALYs. 26 , 27 In our study, the burden of smoking-attributable risk factors was significantly higher in males, suggesting that smoking may be a key contributor to sex differences in the ASR of DALYs. In 2021, smoking-attributable AA risk factors were more prominent in high-income regions than in low-income regions, possibly due to higher tobacco consumption among populations with greater economic resources. Smoking is a critical risk factor for AA expansion and rupture. 28 , 29 Clinicians should actively promote smoking cessation interventions for patients, while governments should further strengthen public health campaigns and tobacco control policies to reduce the disease burden associated with smoking. Meanwhile, pathological haemodynamic alterations also constitute a significant risk factor for the development and progression of AA. 30,31 HSBP remains a leading risk factor 32 , particularly among females, with limited control observed in all regions. This highlights the importance of blood pressure control for patients diagnosed with AA. Clinicians should adopt a more proactive approach in managing blood pressure and blood volume through the use of diuretics and vasodilators. Previous studies have also identified high BMI as an independent risk factor for AA; our findings confirm that it has continued to contribute substantially to AA risk in middle- and high-income countries. 5 , 33 Poor dietary habits, such as low intakes of fruits and vegetables, and environmental pollutants, such as lead exposure, have also been previously linked to CVDs. 34 Our study found that each of these factors contributed more significantly to AA-related DALYs in low- and low-middle SDI regions. Therefore, greater attention should be given to environmental pollution and dietary patterns in low-income regions to mitigate AA risk. Public health initiatives should prioritize improving access to healthy weight management resources and nutrient-rich foods, raising awareness of healthy dietary habits, and enforcing policies to reduce exposure to environmental pollutants to reduce AA risk. Addressing these modifiable risk factors through targeted public health interventions and clinical management strategies is essential for reducing the global burden of AA. Future efforts should focus on strengthening prevention measures, improving early detection, and ensuring equitable access to healthcare resources across different socio-demographic regions. Limitations This study has certain limitations. First, the quality of data included in the GBD analysis may be influenced by various factors, such as differences in data collection methods and the reliability of data sources. This potentially affects the completeness and accuracy of the estimates. Second, the lack of AA subtype stratification (e.g., thoracic vs. abdominal AA) limits more nuanced assessments of disease burden. Third, as many AA cases remain asymptomatic and are only diagnosed at the time of rupture or death, the true burden may be underestimated. Lastly, although the main risk factors identified in the GBD framework were included, other clinically relevant contributors to AA may have been overlooked. CONCLUSION Our study provides a comprehensive overview of the global burden of AA and its attributable risk factors. Although the global ASRs of deaths and DALYs related to AA have declined from 1990 to 2021, the total burden has continued to rise, particularly among males and older adults. Significant geographic and socioeconomic disparities persist, with high-SDI regions exhibiting greater disease burden but achieving more substantial declines over time, likely reflecting improving detection and intervention capacity. Smoking, HSBP, high BMI, and poor dietary habits were identified as related modifiable risk factors; among these, HSBP has become increasingly prominent, especially among women in low-SDI regions. These findings highlight the need for effective, targeted strategies to address modifiable risk factors and reduce the burden of AA globally. Abbreviations AA: Aortic aneurysm ASR: Age-standardized rate BMI: Body mass index CVD: Cardiovascular diseases DALYs: Disability-adjusted life years GATHER: Guidelines for accurate and transparent health estimates reporting GBD: Global burden of disease GHDx: Global health data exchange HSBP: High systolic blood pressure ICD: International classification of diseases SDI: Socio-demographic index PAF: Population-attributable fraction UI: Uncertainty interval YLDs: Years lived with disability YLLs: Years of life lost Declarations Clinical trial number Not applicable. Disclosures: All authors have reported that they have no relationships relevant to the contents of this paper to disclose. Funding: This study was supported by following foundation: National Key Research and Development Program of China (2023YFC2706200), the National Natural Science Foundation of China (82371795, 82400475, 82300461, 82071803, 82170504, 82241217, 823B2036), and the Natural Science Foundation of Hubei Province (2022CFB241). Author Contribution C.G., J.Y. and C.Z. conceived and supervised the study. P.H., J.Z., S.W. and H.Z. were responsible for data collection, analysis, and drafting of the initial manuscript. Y.N., Z.L., R.L. and participated in data acquisition and assisted in data interpretation and figure preparation. C.G., J.Y., and C.Z. critically revised the manuscript and provided valuable input during the revision process. All authors reviewed and approved the final manuscript and agreed to be accountable for the integrity and accuracy of the work. Acknowledgements: We extend our gratitude to the GBD team for providing access to their comprehensive and publicly available database. Data Availability The data for this article was obtained from the GBD 2021 database using the Global Health Data Exchange (GHDx) online query tool ( [https://vizhub.healthdata.org/gbd-results/](https:/vizhub.healthdata.org/gbd-results) ). References Bossone E, Eagle KA. Epidemiology and management of aortic disease: aortic aneurysms and acute aortic syndromes. Nat Rev Cardiol. 2021;18:331–48. Song P, He Y, Adeloye D, Zhu Y, Ye X, Yi Q, et al. The Global and Regional Prevalence of Abdominal Aortic Aneurysms: A Systematic Review and Modeling Analysis. Ann Surg. 2023;277:912–9. Huang X, Wang Z, Shen Z, Lei F, Liu Y-M, Chen Z, et al. Projection of global burden and risk factors for aortic aneurysm - timely warning for greater emphasis on managing blood pressure. Ann Med. 2022;54:553–64. Wang Z, You Y, Yin Z, Bao Q, Lei S, Yu J, et al. Burden of Aortic Aneurysm and Its Attributable Risk Factors from 1990 to 2019: An Analysis of the Global Burden of Disease Study 2019. Front Cardiovasc Med. 2022;9:901225. Koba A, Yamagishi K, Sairenchi T, Noda H, Irie F, Takizawa N, et al. Risk Factors for Mortality From Aortic Aneurysm and Dissection: Results From a 26-Year Follow-Up of a Community-Based Population. J Am Heart Association. 2023;12:e027045. Sakalihasan N, Michel J-B, Katsargyris A, Kuivaniemi H, Defraigne J-O, Nchimi A, et al. Abdominal aortic aneurysms. Nat Reviews Disease Primers. 2018;4:34. 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;403:2100–32. 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;403:2133–61. Mensah GA, Fuster V, Murray CJL, Roth GA. Global Burden of Cardiovascular Diseases and Risks, 1990–2022. J Am Coll Cardiol. 2023;82:2350–473. Lindstrom M, DeCleene N, Dorsey H, Fuster V, Johnson CO, LeGrand KE, et al. Global Burden of Cardiovascular Diseases and Risks Collaboration, 1990–2021. J Am Coll Cardiol. 2022;80:2372–425. 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;403:2162–203. Goyal A, Saeed H, Shahnoor S, Arshad MK, Wasay A, Abdullah, et al. Mortality trends, sex, and racial disparities in older adults due to abdominal aortic aneurysm: a nationwide cross-sectional analysis. Int J Surg (London England). 2024;110:8241–5. Wei L, Bu X, Wang X, Liu J, Ma A, Wang T. Global Burden of Aortic Aneurysm and Attributable Risk Factors from 1990 to 2017. Global Heart. 2021;16:35. Lo RC, Bensley RP, Hamdan AD, Wyers M, Adams JE, Schermerhorn ML. Gender differences in abdominal aortic aneurysm presentation, repair, and mortality in the Vascular Study Group of New England. J Vasc Surg 2013;57. Crousillat D, Briller J, Aggarwal N, Cho L, Coutinho T, Harrington C, et al. Sex Differences in Thoracic Aortic Disease and Dissection: JACC Review Topic of the Week. J Am Coll Cardiol. 2023;82:817–27. Colafella KMM, Denton KM. Sex-specific differences in hypertension and associated cardiovascular disease. Nat Rev Nephrol. 2018;14:185–201. Schmit BM, Yang P, Fu C, DeSart K, Berceli SA, Jiang Z. Hypertension overrides the protective effect of female hormones on the development of aortic aneurysm secondary to Alk5 deficiency via ERK activation. Am J Physiol Heart Circ Physiol. 2015;308:H115–25. Hultgren R. The role of sex hormones in abdominal aortic aneurysms: a topical review. Annals Cardiothorac Surg. 2023;12:536–48. Meuli L, Zimmermann A, Petersen JK, Fosbøl EL, Dabravolskaité V, Makaloski V, et al. Risk Stratification and Treatment Selection in Patients With Asymptomatic Abdominal Aortic Aneurysms. JAMA Netw Open. 2025;8:e253559. Tyrrell DJ, Chen J, Li BY, Wood SC, Rosebury-Smith W, Remmer HA, et al. Aging Alters the Aortic Proteome in Health and Thoracic Aortic Aneurysm. Arterioscler Thromb Vasc Biol. 2022;42:1060–76. Talvitie M, Stenman M, Roy J, Leander K, Hultgren R. Sex Differences in Rupture Risk and Mortality in Untreated Patients With Intact Abdominal Aortic Aneurysms. J Am Heart Association. 2021;10:e019592. Golledge J, Thanigaimani S, Powell JT, Tsao PS. Pathogenesis and management of abdominal aortic aneurysm. Eur Heart J. 2023;44:2682–97. Isselbacher EM, Preventza O, Hamilton Black Iii J, Augoustides JG, Beck AW, Bolen MA, et al. 2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines. J Am Coll Cardiol. 2022;80:e223–393. Golledge J, Muller J, Daugherty A, Norman P. Abdominal aortic aneurysm: pathogenesis and implications for management. Arterioscler Thromb Vasc Biol. 2006;26:2605–13. Kitakaze M. Trends in Characteristics of CVD in Asia and Japan: The Importance of Epidemiological Studies and Beyond. J Am Coll Cardiol. 2015;66:196–8. Sidloff D, Stather P, Dattani N, Bown M, Thompson J, Sayers R, et al. Aneurysm global epidemiology study: public health measures can further reduce abdominal aortic aneurysm mortality. Circulation. 2014;129:747–53. Khan Minhas AM, Sedhom R, Jean ED, Shapiro MD, Panza JA, Alam M, et al. Global burden of cardiovascular disease attributable to smoking, 1990–2019: an analysis of the 2019 Global Burden of Disease Study. Eur J Prev Cardiol. 2024;31:1123–31. Sweeting MJ, Thompson SG, Brown LC, Powell JT. Meta-analysis of individual patient data to examine factors affecting growth and rupture of small abdominal aortic aneurysms. Br J Surg. 2012;99:655–65. Aune D, Schlesinger S, Norat T, Riboli E. Tobacco smoking and the risk of abdominal aortic aneurysm: a systematic review and meta-analysis of prospective studies. Sci Rep. 2018;8:14786. Obel LM, Diederichsen AC, Steffensen FH, Frost L, Lambrechtsen J, Busk M, et al. Population-Based Risk Factors for Ascending, Arch, Descending, and Abdominal Aortic Dilations for 60-74-Year-Old Individuals. J Am Coll Cardiol. 2021;78:201–11. Kobeissi E, Hibino M, Pan H, Aune D. Blood pressure, hypertension and the risk of abdominal aortic aneurysms: a systematic review and meta-analysis of cohort studies. Eur J Epidemiol. 2019;34:547–55. Suzuki Y, Kaneko H, Yano Y, Okada A, Itoh H, Ueno K, et al. Dose-dependent relationship of blood pressure and glycaemic status with risk of aortic dissection and aneurysm. Eur J Prev Cardiol. 2022;29:2338–46. Sun J, Qiao Y, Zhao M, Magnussen CG, Xi B. Global, regional, and national burden of cardiovascular diseases in youths and young adults aged 15–39 years in 204 countries/territories, 1990–2019: a systematic analysis of Global Burden of Disease Study 2019. BMC Med. 2023;21:222. Rosengren E, Barregard L, Sallsten G, Fagerberg B, Engström G, Fagman E, et al. Exposure to Lead and Coronary Artery Atherosclerosis: A Swedish Cross-Sectional Population-Based Study. J Am Heart Association. 2025;14:e037633. Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":894162,"visible":true,"origin":"","legend":"\u003cp\u003eGlobal Trends in AA-Related Deaths and DALYs. Global trends in the AA-related number and ASRs of deaths from 1980–2021 (A) and DALYs from 1990–2021 (B). Shaded areas represent the 95% UI for rates. AA, aortic aneurysm; DALYs, disability-adjusted life years; ASR, age-standardized rate; UI, uncertainty interval.\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7850745/v1/3b01c37d9a3068b649c299d1.jpg"},{"id":96690237,"identity":"ea176e4d-e5d3-444c-a8fd-2e8d0ae613b7","added_by":"auto","created_at":"2025-11-25 06:25:23","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":540158,"visible":true,"origin":"","legend":"\u003cp\u003eAA Burden by Sex and Age Group in 2021. Number and ASRs of AA-related deaths (A) and DALYs (B) by sex in 2021. Error bars represent 95% UI for counts; shaded areas indicate 95% UI for rates. AA, aortic aneurysm; DALYs, disability-adjusted life years; ASR, age-standardized rate; UI, uncertainty interval.\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7850745/v1/03bb099340ad3ee37be442ff.jpg"},{"id":96690236,"identity":"2ce80e64-8c2b-4718-a8dd-247dc8169653","added_by":"auto","created_at":"2025-11-25 06:25:23","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":742334,"visible":true,"origin":"","legend":"\u003cp\u003eGlobal Distribution of AA Burden in 2021 by Countries. The global burden of ASRs of AA deaths (A) and DALY (B) across 204 countries in 2021. AA, aortic aneurysm.; DALY; disability-adjusted life year; ASR, age-standardized rate.\u003c/p\u003e","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7850745/v1/054cd8c85f187c7231a7740f.jpg"},{"id":96690239,"identity":"56778e7b-3e6d-4744-b234-37f4be65544c","added_by":"auto","created_at":"2025-11-25 06:25:23","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":726881,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in AA Burden by SDI.\u003cstrong\u003e \u003c/strong\u003eTrend in AA-related ASRs of deaths (A) and DALYs (B) globally and for 21 GBD regions by SDI, 1990–2021. For each region, points from left to right depict estimates from each year from 1990 to 2021. AA, aortic aneurysm; DALYs, disability-adjusted life years; GBD, Global Burden of Disease; ASR, age-standardized rate; SDI, Socio-Demographic Index.\u003c/p\u003e","description":"","filename":"fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7850745/v1/b87d860acb6e16815dccce9f.jpg"},{"id":96690240,"identity":"82b8a0c3-25dc-47c1-9cd0-9c7e35096dac","added_by":"auto","created_at":"2025-11-25 06:25:23","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":963772,"visible":true,"origin":"","legend":"\u003cp\u003eContribution of Risk Factors to AA DALYs. Percentage contributions of major risk factors to AA-related ASRs of DALYs in male (A) and female (B), 1990–2021. AA, aortic aneurysm; DALYs, disability-adjusted life years; ASR, age-standardized rate.\u003c/p\u003e","description":"","filename":"fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7850745/v1/7fff3ac80e91cfa4a6ff97ee.jpg"},{"id":100871729,"identity":"ea0358ab-ccb9-46d2-8b8d-af88f0d8d0b8","added_by":"auto","created_at":"2026-01-22 09:28:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4793226,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7850745/v1/a6b68516-0ffb-40a4-bde9-77b34dc4eac3.pdf"},{"id":96690252,"identity":"47d50c29-d41f-4276-84f0-2d4e00540b59","added_by":"auto","created_at":"2025-11-25 06:25:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":416767,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7850745/v1/b33f55d153f538b179105596.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Global burden of aortic aneurysm and its attributable risk factors from 1990 to 2021: an update from the GBD 2021","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAortic aneurysm (AA) is the second most common aortic condition and poses a serious threat to life.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Although the prevalence of AA is lower than that of other cardiovascular diseases (CVDs), its high mortality rate and the rising number of cases make it a growing public health concern, particularly among older adults.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e According to the Global Burden of Disease (GBD) 2019 Study, AA accounted for 172,427 deaths globally in 2019, with an 82.1% increase since 1990. Over the same period, AA-related disability-adjusted life years (DALYs) increased by 67.0%, reaching 3.3\u0026nbsp;million in 2019.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Modifiable risk factors, such as smoking and hypertension, elevate the risk of AA and contribute further to its disease burden.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Although previous GBD studies have documented the overall burden of AA, the coverage of risk factors is incomplete, and updated and detailed assessments of mortality, DALYs, and major risk factors across regions and populations remain scarce. Comprehensive and up-to-date epidemiological data on AA are needed to support more effective prevention and management strategies.\u003c/p\u003e\u003cp\u003eThis study aims to fill these research gaps, utilizing data from the GBD 2021. We systematically analyze the global disease burden of AA in terms of age-standardized mortality and DALYs, disaggregated by age group, sex, and regions as classified by socio-demographic index (SDI). In addition, we identify the modifiable risk factors contributing to AA in both males and females, including smoking, high systolic blood pressure (HSBP), high body mass index (BMI), lead exposure, and diets high in sodium and low in vegetables and fruits. By clarifying the evolving epidemiological patterns of AA, this study expands and updates previous research to support the development of targeted public health policies aimed at reducing the burden of AA and promoting cardiovascular health worldwide.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData sources\u003c/h2\u003e\u003cp\u003eGBD 2021 was a systematic epidemiological research initiative, encompassing 328\u0026nbsp;billion data sources to assess 459 health outcomes and risk factors in 204 countries and territories.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e The waiver of informed consent was reviewed and approved by the University of Washington Institutional Review Board due to the use of deidentified aggregated data from the GBD 2021.The project adheres to the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).\u003c/p\u003e\u003cp\u003eRaw data were obtained from the GBD 2021 database using the Global Health Data Exchange (GHDx) online query tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://vizhub.healthdata.org/gbd-results/\u003c/span\u003e\u003cspan address=\"https://vizhub.healthdata.org/gbd-results/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The comprehensive methodology for data collection and analytical processes has been previously documented.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDefinitions\u003c/h3\u003e\n\u003cp\u003eAA, including both abdominal and thoracic subtypes, were identified based on the International Classification of Diseases (ICD) codes, ICD-9 441\u0026ndash;441.9 and ICD-10 I71\u0026ndash;I71.9.\u003csup\u003e9\u003c/sup\u003e The burden of AA was quantified in terms of cause-specific mortality and DALYs, calculated as the sum of years of life lost (YLLs) and years lived with disability (YLDs), respectively. YLLs were estimated by multiplying the number of deaths by the standard life expectancy at the age of death. YLDs were calculated by multiplying the prevalence of AA by the corresponding disability weights.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe SDI is a composite indicator reflecting a region\u0026rsquo;s developmental status, ranging from 0 (worst) to 1 (best). It is derived from three components: the total fertility rate of women under age 25, the mean educational attainment in individuals over 15 years, and lag-distributed income per capita. Countries were grouped into five SDI quintiles: low, low-middle, middle, high-middle, and high.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eSeven modifiable risk factors for AA were included, based on the GBD 2021 comparative risk assessment framework: smoking, high BMI, HSBP, diets high in sodium, diets low in vegetables, diets low in fruits, and lead exposure. These risk factors were selected based on the following criteria: sufficient evidence for causation for each risk-outcome pair, using the Bradford Hill criteria; availability of risk exposure data; and potential for risk modification and policy relevance.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eWe estimated counts, the age-standardized rate (ASR) per 100,000 people, and percentage change in ASR with 95% uncertainty interval (UI) to quantify GBD 2021 AA burden metrics. Included metrics were deaths and DALYs, assessed by age group, sex, region, country, and SDI quintile. The ASR was calculated by directly standardizing the global age structure.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e UI for all estimates were calculated by averaging the data from 1,000 draws, with the lower and upper bounds of the 95% UI established by the 25th and 975th ranked values among all 1,000. Risk factor attribution was estimated using the population-attributable fraction (PAF), which was calculated for each risk\u0026ndash;outcome pair based on population-level exposure, estimated relative risk, and the theoretical minimum risk exposure level. This approach was used to quantify the burden of disease attributable to each risk factor.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e R software (version 4.3.1) was used for data analysis. For all estimates, a 95% UI excluding zero represents statistical significance.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eGlobal and regional burden of aortic aneurysm by sex and age\u003c/h2\u003e\u003cp\u003eIn 2021, AA was responsible for an estimated 153,900 deaths globally (95% UI: 138,400 to 165,700), with the highest counts observed in high-SDI regions. The global ASR of deaths was 1.9 per 100,000 population (95% UI: 1.7 to 2.0), a decrease of 26.7% (95% UI: 23.1 to 31.1) compared to 1990. Additionally, AA accounted for 3.1\u0026nbsp;million (95% UI: 2.9 to 3.4) DALYs globally in 2021. The age-standardized DALY rate was 36.5 per 100,000 (95% UI: 33.5 to 39.5), representing a 25.1% reduction (95% UI: 20.3 to 30.5) from 1990. However, a substantial increase in DALY rates was observed in low-middle SDI regions (45.9%; 95% UI: 19.2 to 73.3) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eCounts and age-standardized deaths and DALYs rates of AA in 2021, and their percentage change in ASR from 1990 to 2021, by SDI quintile and GBD region.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eDeaths (95% UI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eDALYs (95% UI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2021 counts\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2021 ASR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003ePercentage change in ASR,1990\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2021 counts\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2021 ASR per 100 000 people\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePercentage change in ASR,1990\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlobal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e153927.2\u003c/p\u003e\u003cp\u003e(138413.4,165738.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.9 (1.7,2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-26.7\u003c/p\u003e \u003cp\u003e(-31.1, -23.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3107762.3 (2857319.7,3353857.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e36.5\u003c/p\u003e\u003cp\u003e(33.5,39.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-25.1\u003c/p\u003e \u003cp\u003e(-30.5, -20.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow SDI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6371.3\u003c/p\u003e\u003cp\u003e(3931.6,10433.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.5 (0.9,2.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.4\u003c/p\u003e\u003cp\u003e(-12,31.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e162855 (99208.4,267958.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e30.8\u003c/p\u003e\u003cp\u003e(18.9,50.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7.2\u003c/p\u003e\u003cp\u003e(-13.8,32.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow-middle SDI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16808.3\u003c/p\u003e\u003cp\u003e(13956.4,22468.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.3 (1.1,1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e47.9\u003c/p\u003e\u003cp\u003e(22.9,73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e398279.7 (333989.6,529920.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e27.5\u003c/p\u003e\u003cp\u003e(22.9,36.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e45.9\u003c/p\u003e\u003cp\u003e(19.2,73.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle SDI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28528.4\u003c/p\u003e\u003cp\u003e(25797.3,30958.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.2 (1,1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.5\u003c/p\u003e\u003cp\u003e(-1.4,25.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e662164.3\u003c/p\u003e\u003cp\u003e(600453.3,722827.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24.9\u003c/p\u003e\u003cp\u003e(22.6,27.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e15\u003c/p\u003e\u003cp\u003e(-0.8,29.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh-middle SDI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34826.6\u003c/p\u003e\u003cp\u003e(32309.3,37274.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.8 (1.7,1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-10.1\u003c/p\u003e \u003cp\u003e(-17.3, -3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e760354.3\u003c/p\u003e\u003cp\u003e(709823.9,817072)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e39.7\u003c/p\u003e\u003cp\u003e(37,42.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-9.8\u003c/p\u003e \u003cp\u003e(-18.6, -2.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh SDI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67201.9\u003c/p\u003e\u003cp\u003e(57735.4,72287.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.9 (2.5,3.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-39.8\u003c/p\u003e \u003cp\u003e(-43.5, -37.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1120317.3\u003c/p\u003e\u003cp\u003e(1010907.3,1182279.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e54.5\u003c/p\u003e\u003cp\u003e(50.3,57.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-40.8\u003c/p\u003e \u003cp\u003e(-43.2, -38.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAndean Latin America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e538.1\u003c/p\u003e\u003cp\u003e(449.4,643.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.9 (0.8,1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-7\u003c/p\u003e \u003cp\u003e(-26.9,18.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12092.1\u003c/p\u003e\u003cp\u003e(10090.6,14633.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20.1\u003c/p\u003e\u003cp\u003e(16.8,24.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-7.2\u003c/p\u003e \u003cp\u003e(-28.3,19.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAustralasia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1548.7\u003c/p\u003e\u003cp\u003e(1353.6,1679.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.6 (2.3,2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-67.6\u003c/p\u003e \u003cp\u003e(-70.5, -65.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24880.2\u003c/p\u003e\u003cp\u003e(22366.8,26610.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e45.5\u003c/p\u003e\u003cp\u003e(41.3,48.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-69.3\u003c/p\u003e \u003cp\u003e(-71.7, -67.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaribbean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1405.2\u003c/p\u003e\u003cp\u003e(1240.5,1582.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.6 (2.3,2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-31.7\u003c/p\u003e \u003cp\u003e(-39.7, -22.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26859.3\u003c/p\u003e\u003cp\u003e(23699.4,30389.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e50\u003c/p\u003e\u003cp\u003e(44.1,56.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-29.4\u003c/p\u003e \u003cp\u003e(-37.8, -20.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral Asia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1442.7 (1280.3,1615.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2 (1.8,2.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e110.1\u003c/p\u003e\u003cp\u003e(71.5,150.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e35159.5 (30894.5,39776.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e42.7 (37.8,47.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e80.9\u003c/p\u003e\u003cp\u003e(47.1,115.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral Europe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6681.6 (6141.4,7318.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.9 (2.7,3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-4.8\u003c/p\u003e \u003cp\u003e(-12.2,4.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e134478.5 (123463.3,148456.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e63.7 (58.3,70.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-7.8\u003c/p\u003e \u003cp\u003e(-16.3,2.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral Latin America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3292.7 (2865.4,3768.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.4 (1.2,1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-12.3\u003c/p\u003e \u003cp\u003e(-23.1, -0.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e72061.6 (62326.6,83068)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e28.8 (24.9,33.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-15\u003c/p\u003e \u003cp\u003e(-26.8, -2.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral Sub-Saharan Africa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1057.3\u003c/p\u003e\u003cp\u003e(590.7,1706)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.4 (1.3,3.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-10.6\u003c/p\u003e \u003cp\u003e(-30.9,16.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e28158.8 (15580.2,46218.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e50.5 (28.2,81.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-10.1\u003c/p\u003e \u003cp\u003e(-32.3,19.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEast Asia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10199 (8228.6,12817.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.5 (0.4,0.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40\u003c/p\u003e\u003cp\u003e(-1.6,92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e269442.6 (213790.7,344575.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.3\u003c/p\u003e\u003cp\u003e(10.6,17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e40.1\u003c/p\u003e\u003cp\u003e(-4.6,99.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEastern Europe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13406 (12353.5,14430.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3.8 (3.5,4.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e51.8\u003c/p\u003e\u003cp\u003e(38.9,64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e304640.9 (280046.2,328882.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e91.3 (83.9,98.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e46.7\u003c/p\u003e\u003cp\u003e(33.4,59.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEastern Sub-Saharan Africa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2636.1 (1427.4,4293.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.8\u003c/p\u003e\u003cp\u003e(1,3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.8\u003c/p\u003e \u003cp\u003e(-25.7,32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e72025.1 (38938.5,115787.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e38.5 (20.8,62.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003cp\u003e(-26.5,37.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh-income Asia Pacific\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25772.7 (20940,28524.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e4.4\u003c/p\u003e\u003cp\u003e(3.7,4.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56.9\u003c/p\u003e\u003cp\u003e(44.1,67.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e378280.4 (325386.9,408692)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e79.7 (71.8,84.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e51\u003c/p\u003e\u003cp\u003e(41.2,61)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh-income North America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13969.9 (12470.6,14793.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003cp\u003e(1.9,2.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-60.6\u003c/p\u003e \u003cp\u003e(-61.9, -59.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e271835.2 (253830.1,283631.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e45.4 (42.9,47.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-56.8\u003c/p\u003e \u003cp\u003e(-58.2, -55.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorth Africa and Middle East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3693.7 (3202.7,4256.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003cp\u003e(0.8,1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35.8\u003c/p\u003e\u003cp\u003e(-4.8,87.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e96331.3 (83715.8,112192.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20\u003c/p\u003e\u003cp\u003e(17.3,23.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e22.1\u003c/p\u003e\u003cp\u003e(-16.2,74)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOceania\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e117.3\u003c/p\u003e\u003cp\u003e(90.5,151.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.9\u003c/p\u003e\u003cp\u003e(1.5,2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-15.3\u003c/p\u003e \u003cp\u003e(-30.7,6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3301.2\u003c/p\u003e\u003cp\u003e(2496.5,4381.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e41.5 (32.1,53.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-12.3\u003c/p\u003e \u003cp\u003e(-28.7,11.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth Asia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15979.1 (11378.8,23410.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003cp\u003e(0.9,1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71.6\u003c/p\u003e\u003cp\u003e(27.9,136.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e367475.1 (260596,539642.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e25\u003c/p\u003e\u003cp\u003e(17.8,36.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e63.6\u003c/p\u003e\u003cp\u003e(22.3,125.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSoutheast Asia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7390.6 (6476.2,8513.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.4 (1.2,1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34.6\u003c/p\u003e\u003cp\u003e(5.6,70.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e158458 (137444.7,182388.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e25.9 (22.6,29.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e32.2\u003c/p\u003e\u003cp\u003e(1.6,68.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouthern Latin America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2352.5 (2166.5,2527.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.6 (2.4,2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-44.1\u003c/p\u003e \u003cp\u003e(-50.1, -38.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e48688.9 (45137.7,52222.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e56.5 (52.4,60.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-44.1\u003c/p\u003e \u003cp\u003e(-50.4, -38)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouthern Sub-Saharan Africa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1236.8 (1123.2,1348.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.5 (2.2,2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-20.5\u003c/p\u003e \u003cp\u003e(-32.9,1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30967.2 (27976.5,34411.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e52\u003c/p\u003e\u003cp\u003e(47,57.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-18.2\u003c/p\u003e \u003cp\u003e(-29,0.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTropical Latin America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10173.1 (9351.9,10728.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e4 (3.7,4.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20.3\u003c/p\u003e\u003cp\u003e(13.6,26.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e235449.1 (221293.8,246967.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e91.1 (85.5,95.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e14.1\u003c/p\u003e\u003cp\u003e(8.8,19.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWestern Europe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27511.1 (24097.6,29189.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.6 (2.3,2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-46.2\u003c/p\u003e \u003cp\u003e(-48.9, -44.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e449312.2 (408553.8,471934.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e48.5 (45.1,50.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-47.5\u003c/p\u003e \u003cp\u003e(-49.6, -45.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWestern Sub-Saharan Africa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3523\u003c/p\u003e\u003cp\u003e(1744.6,5980.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.2 (1.1,3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-7.2\u003c/p\u003e \u003cp\u003e(-30.6,14.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e87865 (42721.7,151832.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e43.5 (21.4,74.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-6.3\u003c/p\u003e \u003cp\u003e(-30.6,18.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eData in parentheses are 95% UI.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eAA, aortic aneurysm; ASR, age-standardized rate; DALYs, disability-adjusted life years; GBD, Global Burden of Diseas; SDI, Socio-Demographic Index; UI, uncertainty interval.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFrom 1980 to 2021, both the total count and ASR of AA-related deaths were consistently higher in males than in females. However, while ASR of deaths declined steadily in males, it remained relatively stable in females (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). A similar trend was observed for DALYs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In 2021, the highest number of AA-related deaths occurred among males aged 70\u0026ndash;74 and females aged 80\u0026ndash;84. Death counts were higher in males than in females up to the 85\u0026ndash;89 age group, after which females accounted for the majority (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). DALYs peaked at ages 65\u0026ndash;69 in males and 70\u0026ndash;74 in females, with consistently higher rates in males across most age groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eThe aortic aneurysm burden in different countries\u003c/h2\u003e\u003cp\u003eAmong 204 countries in 2021, the highest AA-related ASRs for deaths (9.2; 95% UI: 7.6 to 10.8) and DALYs (192.8; 95% UI: 159.7 to 228.2) were seen in Armenia; the lowest were observed in Saudi Arabia for both deaths (0.2; 95% UI: 0.2 to 0.3) and DALYs (5.1; 95% UI: 3.7 to 6.7). From 1990 to 2021, the largest drops in ASRs for deaths and DALYs were seen in Serbia (-74.4; 95% UI: -80 to -67.6) and Papua New Guinea (-70.6; 95% UI: -73.3 to -68.2), respectively. Meanwhile, the largest increases ASRs for deaths and DALYs were observed in Japan (385.9; 95% UI: 225.1 to 595) and Indonesia (357.4; 95% UI: 242.4 to 498.6), respectively. Notably, Japan reported the highest absolute number of AA-related deaths (23,800; 95% UI: 19,200 to 26,500) and DALYs (344,000; 95% UI: 294,000 to 372,000) in 2021. This was accompanied by a substantial increase in the ASR of death (185.5%; 95% UI: 114.0 to 272.3), despite a concurrent decline in the DALYs ASR (\u0026minus;\u0026thinsp;28.0%; 95% UI: \u0026minus;34.1 to \u0026minus;\u0026thinsp;22.2). (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplementary Table S1).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAssociation of aortic aneurysm burden with socio-demographic index\u003c/h3\u003e\n\u003cp\u003eIn 2021, high SDI regions exhibited the highest ASRs of death (2.9; 95% UI: 2.5 to 3.1) and DALYs (54.5; 95% UI: 50.3 to 57.1), while low SDI regions exhibited the lowest ASRs of death (1.5; 95% UI: 0.9 to 2.4) and DALYs (30.8; 95% UI: 18.9 to 50.4) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the 21 GBD regions, AA-associated death and DALY ASRs exhibited a clear linear relationship with SDI: rates declined markedly in high-SDI regions but remained stable in low- and middle-SDI regions. Over the studied period, higher SDI regions exhibited fluctuations in AA ASRs of death and DALY, following SDI value, while the trends in lower and middle SDI regions remained more stable. Among the 21 GBD regions in 2021, the high-income Asia Pacific (4.4; 95% UI: 3.7 to 4.8) and Tropical Latin America (4.0; 95% UI: 3.7 to 4.3) had the highest AA-related ASRs of death, while the lowest rate was observed in East Asia (0.5; 95% UI: 0.4 to 0.6). The highest ASRs of DALYs were reported in Eastern Europe (91.3; 95% UI: 83.9 to 98.5) and Tropical Latin America (91.1; 95% UI: 85.5 to 95.5), while the lowest rate was reported in East Asia (13.3; 95% UI: 10.6 to 17). From 1980/1990 to 2021, high-income Asia Pacific exhibited the greatest increase in the ASRs of deaths (56.9; 95% UI: 44.1 to 67.3) and DALYs (79.7; 95% UI: 71.8 to 84.5) among the four regions with the highest SDI. Notably, all regions in Asia exhibited increasing AA-related ASRs of deaths and DALYs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The ASRs of deaths and DALYs also showed significant linear associations with SDI at the country level (Supplementary Figure S1).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eThe burden of aortic aneurysm attributable to risk factors by sex group\u003c/h3\u003e\n\u003cp\u003eAmong the seven risk factors for AA in the GBD 2021, smoking was the primary contributor to DALYs in males globally (45.7%), followed by HSBP (16.8%) and high BMI (7.6%). In comparison, both smoking and HSBP were primary risk factors for DALYs in females globally (17.6% and 17.2%, respectively), followed by high BMI (8.4%).\u003c/p\u003e\u003cp\u003eA diet low in fruits (3.7% in male and 3.8% in female) and low in vegetables (2.9% in male and 3% in female) also significantly contributed to AA-related DALYs, followed by a diet high in sodium (1.1% in male and 0.7% in female) and lead exposure (0.7% in male and 0.6% in female). Sex-stratified analyses identified smoking, high-sodium diets, and lead exposure as disproportionate contributors to the DALY ASR of AA, with a greater burden observed in males than females. In contrast, HSBP and high BMI were found to have a larger impact on the DALY ASR in females than in males.\u003c/p\u003e\u003cp\u003eAmong the SDI quintiles, the proportional contribution of smoking and high BMI to the DALY ASR of AA increased with higher SDI, with the highest percentage in high-middle SDI regions. In contrast, the contribution of diets low in vegetables decreased with higher SDI, with the lowest percentage in high-middle SDI regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur study provides a comprehensive analysis of the global burden of AA and its associated risk factors, revealing substantial disparities in mortality and DALYs across age groups, sex, regions, and SDI levels. Between 1990 and 2021, the global ASRs of AA-related deaths and DALYs declined by 26.7% and 25.1%, respectively. However, the absolute number of AA-related deaths and DALYs continued to increase annually in both males and females; this likely reflects improvements in diagnostic technologies, improved epidemiologic knowledge, population growth, and population ageing. Notably, the ASR of DALYs was higher in males than in females across all years and in most age groups, which may be attributable to tobacco use as a major contributing factor. This study underscores the significant impact of AA on global health and emphasises the need for targeted interventions to mitigate this growing burden, including enhanced control of risk factors, improved screening programs, and equitable access to healthcare.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSex and age differences in global disease burden of aortic aneurysm\u003c/h2\u003e\u003cp\u003eConsistent with previous epidemiological studies, our findings confirm marked sex- and age-specific disparities in the global burden of AA.\u003csup\u003e12\u003c/sup\u003e We observed that AA-related ASRs of mortality and DALYs were consistently higher in males, aligning with prior evidence that men experience a higher burden of aortic disease.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e These sex differences are likely driven by a combination of biological and behavioural factors. Biologically, sex-based variations at the cellular and tissue levels may influence disease susceptibility and therapeutic responses.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e For example, oestrogen is believed to exert protective vascular effects in females, whereas males generally have a lower degree of such hormonal protection.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Men are also considered more likely to adopt unhealthy behaviours, such as smoking, excessive alcohol consumption, and poor dietary habits. These behaviours, along with lower healthcare adherence, cumulatively increase their risk of CVDs. Notably, the AA-related burden in females has remained relatively stable over the past three decades, while the burden in males has shown a substantial decline. This trend may reflect the atypical clinical presentation and delayed onset of AA in females, which potentially contribute to underdiagnosis and treatment delays. Meanwhile, the more substantial burden reduction in males may be partly attributed to the greater benefits of smoking cessation efforts. These findings highlight the importance of sex- and gender-specific approaches in the prevention, diagnosis, and management of AA to address distinct biological risks, behavioural factors, and disease trajectories in both men and women.\u003c/p\u003e\u003cp\u003eAge was also a key determinant of AA burden. The ASRs of both deaths and DALYs increased markedly with advancing age, reflecting the progressive nature of AA and its cumulative risk over time. This trend likely results from age-related vascular degeneration and the accumulation of comorbidities in older adults.\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eOur findings demonstrate that both sex and age significantly shape the global burden of AA. These disparities highlight the urgent need for sex- and age-specific strategies to improve early detection, risk factor management, and outcomes in high-risk populations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eDiscrepancies across different socio-demographic index levels\u003c/h2\u003e\u003cp\u003eSignificant variation was observed in the temporal trends and cross-national distribution of AA-related DALY and mortality ASRs across regions stratified by SDI quintiles. The SDI\u0026mdash;reflecting years of education, per capita income, and total fertility rate\u0026mdash;highlights the critical influence of social factors on outcomes relating to AA.\u003csup\u003e7,8\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eWhile regions with higher SDI displayed higher mortality ASRs, low-SDI regions reported lower rates. This may indicate underreporting or misclassification of AA-related deaths in these areas. This underscores the need to enhance early and accurate diagnosis of AA, particularly for paroxysmal or asymptomatic cases. In low-SDI regions, the ASRs of both DALYs and mortality continue to rise, likely due to limited access to essential diagnostic tools and definitive treatments for AA\u0026mdash;such as advanced imaging technologies, elective surgical repair, and endovascular aneurysm repair\u0026mdash;which are unevenly distributed across socio-economic contexts.\u003csup\u003e\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e While high-SDI regions have achieved significant reductions in age-standardized incidence and DALYs, low-SDI regions are facing a substantial increase in age-standardized mortality. Recent advances in managing the AA burden in high-SDI regions have overshadowed the neglect of AA care in low-SDI areas. Moving forward, prioritizing prevention, diagnosis, and treatment of AA in low-SDI regions is essential to address these disparities.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eDiscrepancies across different regions and countries\u003c/h2\u003e\u003cp\u003eThis study revealed pronounced regional and national disparities in the burden of AA, which cannot be fully explained by SDI classification alone. Among the four regions with the highest SDI, high-income Asia Pacific was the only one to exhibit an increasing trend in the ASRs of deaths and DALYs from AA over the past three decades. At the country level, Saudi Arabia\u0026mdash;despite being a high-SDI country\u0026mdash;reported the lowest AA-related burden globally. In contrast, Armenia, a high-middle SDI country, exhibited the highest burden. This suggests that SDI alone is insufficient to account for national disparities in disease burden and that factors such as healthcare quality, prevention programs, and risk factor control play a crucial role.\u003c/p\u003e\u003cp\u003eJapan reported the highest absolute number of AA-related deaths and DALYs in 2021. This was accompanied by a rising ASR for deaths, but a declining ASR for DALYs. This phenomenon highlights the impact of an ageing population and underscores the importance of effective disease management and age-specific interventions in minimizing overall health loss, especially among older adults.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThese findings illustrate the fact that national and regional disparities in AA burden are shaped by more than socioeconomic development alone. Targeted, context-specific strategies are essential to address local gaps in prevention, diagnosis, and long-term management, especially in countries facing rapid population ageing.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eAttributable risk factors\u003c/h2\u003e\u003cp\u003ePrevious reviews have indicated that AA-related DALYs are associated with several modifiable risk factors, such as smoking, hypertension, and obesity.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Consistent with analysis of the GBD 2019, smoking and HSBP remain the two leading risk factors for AA-related DALYs.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Smoking is a well-established cardiovascular risk factor, and declines in smoking prevalence are closely correlated with reductions in AA-related DALYs.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e In our study, the burden of smoking-attributable risk factors was significantly higher in males, suggesting that smoking may be a key contributor to sex differences in the ASR of DALYs. In 2021, smoking-attributable AA risk factors were more prominent in high-income regions than in low-income regions, possibly due to higher tobacco consumption among populations with greater economic resources. Smoking is a critical risk factor for AA expansion and rupture.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Clinicians should actively promote smoking cessation interventions for patients, while governments should further strengthen public health campaigns and tobacco control policies to reduce the disease burden associated with smoking.\u003c/p\u003e\u003cp\u003eMeanwhile, pathological haemodynamic alterations also constitute a significant risk factor for the development and progression of AA.\u003csup\u003e30,31\u003c/sup\u003e HSBP remains a leading risk factor\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, particularly among females, with limited control observed in all regions. This highlights the importance of blood pressure control for patients diagnosed with AA. Clinicians should adopt a more proactive approach in managing blood pressure and blood volume through the use of diuretics and vasodilators. Previous studies have also identified high BMI as an independent risk factor for AA; our findings confirm that it has continued to contribute substantially to AA risk in middle- and high-income countries.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePoor dietary habits, such as low intakes of fruits and vegetables, and environmental pollutants, such as lead exposure, have also been previously linked to CVDs.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e Our study found that each of these factors contributed more significantly to AA-related DALYs in low- and low-middle SDI regions. Therefore, greater attention should be given to environmental pollution and dietary patterns in low-income regions to mitigate AA risk. Public health initiatives should prioritize improving access to healthy weight management resources and nutrient-rich foods, raising awareness of healthy dietary habits, and enforcing policies to reduce exposure to environmental pollutants to reduce AA risk.\u003c/p\u003e\u003cp\u003eAddressing these modifiable risk factors through targeted public health interventions and clinical management strategies is essential for reducing the global burden of AA. Future efforts should focus on strengthening prevention measures, improving early detection, and ensuring equitable access to healthcare resources across different socio-demographic regions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis study has certain limitations. First, the quality of data included in the GBD analysis may be influenced by various factors, such as differences in data collection methods and the reliability of data sources. This potentially affects the completeness and accuracy of the estimates. Second, the lack of AA subtype stratification (e.g., thoracic vs. abdominal AA) limits more nuanced assessments of disease burden. Third, as many AA cases remain asymptomatic and are only diagnosed at the time of rupture or death, the true burden may be underestimated. Lastly, although the main risk factors identified in the GBD framework were included, other clinically relevant contributors to AA may have been overlooked.\u003c/p\u003e\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOur study provides a comprehensive overview of the global burden of AA and its attributable risk factors. Although the global ASRs of deaths and DALYs related to AA have declined from 1990 to 2021, the total burden has continued to rise, particularly among males and older adults. Significant geographic and socioeconomic disparities persist, with high-SDI regions exhibiting greater disease burden but achieving more substantial declines over time, likely reflecting improving detection and intervention capacity. Smoking, HSBP, high BMI, and poor dietary habits were identified as related modifiable risk factors; among these, HSBP has become increasingly prominent, especially among women in low-SDI regions. These findings highlight the need for effective, targeted strategies to address modifiable risk factors and reduce the burden of AA globally.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAA: Aortic aneurysm\u003c/p\u003e\n\u003cp\u003eASR: Age-standardized rate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBMI: Body mass index\u003c/p\u003e\n\u003cp\u003eCVD: Cardiovascular diseases\u003c/p\u003e\n\u003cp\u003eDALYs: Disability-adjusted life years\u003c/p\u003e\n\u003cp\u003eGATHER: Guidelines for accurate and transparent health estimates reporting\u003c/p\u003e\n\u003cp\u003eGBD: Global burden of disease\u003c/p\u003e\n\u003cp\u003eGHDx: Global health data exchange\u003c/p\u003e\n\u003cp\u003eHSBP: High systolic blood pressure\u003c/p\u003e\n\u003cp\u003eICD: International classification of diseases\u003c/p\u003e\n\u003cp\u003eSDI: Socio-demographic index\u003c/p\u003e\n\u003cp\u003ePAF: Population-attributable fraction\u003c/p\u003e\n\u003cp\u003eUI: Uncertainty interval\u003c/p\u003e\n\u003cp\u003eYLDs: Years lived with disability\u003c/p\u003e\n\u003cp\u003eYLLs: Years of life lost\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eDisclosures:\u003c/h2\u003e\u003cp\u003eAll authors have reported that they have no relationships relevant to the contents of this paper to disclose.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis study was supported by following foundation: National Key Research and Development Program of China (2023YFC2706200), the National Natural Science Foundation of China (82371795, 82400475, 82300461, 82071803, 82170504, 82241217, 823B2036), and the Natural Science Foundation of Hubei Province (2022CFB241).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC.G., J.Y. and C.Z. conceived and supervised the study. P.H., J.Z., S.W. and H.Z. were responsible for data collection, analysis, and drafting of the initial manuscript. Y.N., Z.L., R.L. and participated in data acquisition and assisted in data interpretation and figure preparation. C.G., J.Y., and C.Z. critically revised the manuscript and provided valuable input during the revision process. All authors reviewed and approved the final manuscript and agreed to be accountable for the integrity and accuracy of the work.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\u003cp\u003eWe extend our gratitude to the GBD team for providing access to their comprehensive and publicly available database.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data for this article was obtained from the GBD 2021 database using the Global Health Data Exchange (GHDx) online query tool ( [https://vizhub.healthdata.org/gbd-results/](https:/vizhub.healthdata.org/gbd-results) ).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBossone E, Eagle KA. Epidemiology and management of aortic disease: aortic aneurysms and acute aortic syndromes. Nat Rev Cardiol. 2021;18:331\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSong P, He Y, Adeloye D, Zhu Y, Ye X, Yi Q, et al. The Global and Regional Prevalence of Abdominal Aortic Aneurysms: A Systematic Review and Modeling Analysis. Ann Surg. 2023;277:912\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang X, Wang Z, Shen Z, Lei F, Liu Y-M, Chen Z, et al. Projection of global burden and risk factors for aortic aneurysm - timely warning for greater emphasis on managing blood pressure. Ann Med. 2022;54:553\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Z, You Y, Yin Z, Bao Q, Lei S, Yu J, et al. Burden of Aortic Aneurysm and Its Attributable Risk Factors from 1990 to 2019: An Analysis of the Global Burden of Disease Study 2019. Front Cardiovasc Med. 2022;9:901225.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKoba A, Yamagishi K, Sairenchi T, Noda H, Irie F, Takizawa N, et al. Risk Factors for Mortality From Aortic Aneurysm and Dissection: Results From a 26-Year Follow-Up of a Community-Based Population. J Am Heart Association. 2023;12:e027045.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSakalihasan N, Michel J-B, Katsargyris A, Kuivaniemi H, Defraigne J-O, Nchimi A, et al. Abdominal aortic aneurysms. Nat Reviews Disease Primers. 2018;4:34.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGlobal burden of. 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990\u0026ndash;2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet (London England). 2024;403:2100\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\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\u0026ndash;2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet (London England). 2024;403:2133\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMensah GA, Fuster V, Murray CJL, Roth GA. Global Burden of Cardiovascular Diseases and Risks, 1990\u0026ndash;2022. J Am Coll Cardiol. 2023;82:2350\u0026ndash;473.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLindstrom M, DeCleene N, Dorsey H, Fuster V, Johnson CO, LeGrand KE, et al. Global Burden of Cardiovascular Diseases and Risks Collaboration, 1990\u0026ndash;2021. J Am Coll Cardiol. 2022;80:2372\u0026ndash;425.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGlobal burden and strength of evidence for. 88 risk factors in 204 countries and 811 subnational locations, 1990\u0026ndash;2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet (London England). 2024;403:2162\u0026ndash;203.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoyal A, Saeed H, Shahnoor S, Arshad MK, Wasay A, Abdullah, et al. Mortality trends, sex, and racial disparities in older adults due to abdominal aortic aneurysm: a nationwide cross-sectional analysis. Int J Surg (London England). 2024;110:8241\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWei L, Bu X, Wang X, Liu J, Ma A, Wang T. Global Burden of Aortic Aneurysm and Attributable Risk Factors from 1990 to 2017. Global Heart. 2021;16:35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLo RC, Bensley RP, Hamdan AD, Wyers M, Adams JE, Schermerhorn ML. Gender differences in abdominal aortic aneurysm presentation, repair, and mortality in the Vascular Study Group of New England. J Vasc Surg 2013;57.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCrousillat D, Briller J, Aggarwal N, Cho L, Coutinho T, Harrington C, et al. Sex Differences in Thoracic Aortic Disease and Dissection: JACC Review Topic of the Week. J Am Coll Cardiol. 2023;82:817\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eColafella KMM, Denton KM. Sex-specific differences in hypertension and associated cardiovascular disease. Nat Rev Nephrol. 2018;14:185\u0026ndash;201.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchmit BM, Yang P, Fu C, DeSart K, Berceli SA, Jiang Z. Hypertension overrides the protective effect of female hormones on the development of aortic aneurysm secondary to Alk5 deficiency via ERK activation. Am J Physiol Heart Circ Physiol. 2015;308:H115\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHultgren R. The role of sex hormones in abdominal aortic aneurysms: a topical review. Annals Cardiothorac Surg. 2023;12:536\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeuli L, Zimmermann A, Petersen JK, Fosb\u0026oslash;l EL, Dabravolskait\u0026eacute; V, Makaloski V, et al. Risk Stratification and Treatment Selection in Patients With Asymptomatic Abdominal Aortic Aneurysms. JAMA Netw Open. 2025;8:e253559.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTyrrell DJ, Chen J, Li BY, Wood SC, Rosebury-Smith W, Remmer HA, et al. Aging Alters the Aortic Proteome in Health and Thoracic Aortic Aneurysm. Arterioscler Thromb Vasc Biol. 2022;42:1060\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTalvitie M, Stenman M, Roy J, Leander K, Hultgren R. Sex Differences in Rupture Risk and Mortality in Untreated Patients With Intact Abdominal Aortic Aneurysms. J Am Heart Association. 2021;10:e019592.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGolledge J, Thanigaimani S, Powell JT, Tsao PS. Pathogenesis and management of abdominal aortic aneurysm. Eur Heart J. 2023;44:2682\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIsselbacher EM, Preventza O, Hamilton Black Iii J, Augoustides JG, Beck AW, Bolen MA, et al. 2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines. J Am Coll Cardiol. 2022;80:e223\u0026ndash;393.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGolledge J, Muller J, Daugherty A, Norman P. Abdominal aortic aneurysm: pathogenesis and implications for management. Arterioscler Thromb Vasc Biol. 2006;26:2605\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKitakaze M. Trends in Characteristics of CVD in Asia and Japan: The Importance of Epidemiological Studies and Beyond. J Am Coll Cardiol. 2015;66:196\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSidloff D, Stather P, Dattani N, Bown M, Thompson J, Sayers R, et al. Aneurysm global epidemiology study: public health measures can further reduce abdominal aortic aneurysm mortality. Circulation. 2014;129:747\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhan Minhas AM, Sedhom R, Jean ED, Shapiro MD, Panza JA, Alam M, et al. Global burden of cardiovascular disease attributable to smoking, 1990\u0026ndash;2019: an analysis of the 2019 Global Burden of Disease Study. Eur J Prev Cardiol. 2024;31:1123\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSweeting MJ, Thompson SG, Brown LC, Powell JT. Meta-analysis of individual patient data to examine factors affecting growth and rupture of small abdominal aortic aneurysms. Br J Surg. 2012;99:655\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAune D, Schlesinger S, Norat T, Riboli E. Tobacco smoking and the risk of abdominal aortic aneurysm: a systematic review and meta-analysis of prospective studies. Sci Rep. 2018;8:14786.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eObel LM, Diederichsen AC, Steffensen FH, Frost L, Lambrechtsen J, Busk M, et al. Population-Based Risk Factors for Ascending, Arch, Descending, and Abdominal Aortic Dilations for 60-74-Year-Old Individuals. J Am Coll Cardiol. 2021;78:201\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKobeissi E, Hibino M, Pan H, Aune D. Blood pressure, hypertension and the risk of abdominal aortic aneurysms: a systematic review and meta-analysis of cohort studies. Eur J Epidemiol. 2019;34:547\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSuzuki Y, Kaneko H, Yano Y, Okada A, Itoh H, Ueno K, et al. Dose-dependent relationship of blood pressure and glycaemic status with risk of aortic dissection and aneurysm. Eur J Prev Cardiol. 2022;29:2338\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSun J, Qiao Y, Zhao M, Magnussen CG, Xi B. Global, regional, and national burden of cardiovascular diseases in youths and young adults aged 15\u0026ndash;39 years in 204 countries/territories, 1990\u0026ndash;2019: a systematic analysis of Global Burden of Disease Study 2019. BMC Med. 2023;21:222.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRosengren E, Barregard L, Sallsten G, Fagerberg B, Engstr\u0026ouml;m G, Fagman E, et al. Exposure to Lead and Coronary Artery Atherosclerosis: A Swedish Cross-Sectional Population-Based Study. J Am Heart Association. 2025;14:e037633.\u003c/span\u003e\u003c/li\u003e\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":"Aortic aneurysm, global burden of disease, sex, risk factors","lastPublishedDoi":"10.21203/rs.3.rs-7850745/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7850745/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims:\u003c/h2\u003e\u003cp\u003eThis study aimed to assess the global burden of aortic aneurysm (AA) and its attributable risk factors from 1990 to 2021.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eWe used data from the Global Burden of Disease (GBD) 2021 Study to analysis disease burden of AA. We assessed trends in deaths and disability-adjusted life years (DALYs) related to AA across different demographic and regional groups, along with major attributable risk factors.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eIn 2021, AA accounted for an estimated 153,900 deaths and 3.1\u0026nbsp;million DALYs globally. Compared to previous decades, the age-standardized rates (ASRs) of deaths and DALYs have declined by 26.7% and 25.1%, respectively. In addition, the ASRs of both deaths and DALYs remained consistently higher in males than in females and increased with age. Most high socio-demographic index (SDI) regions showed substantial reductions in AA-related ASRs, except for high-income Asia Pacific. Smoking remained the leading contributor to AA-related DALYs among males (45.7%). In contrast, high systolic blood pressure (HSBP) emerged as the predominant risk factor among females in low- and low-middle SDI regions, surpassing smoking (17.0% vs. 8.8% and 17.8% vs. 11.7%, respectively).\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e\u003cp\u003eWhile ASR of deaths and DALYs from AA have declined since 1990, the total burden continues to rise. Despite advancements in AA prevention and treatment in high-income regions, the burden is increasing in lower income areas, highlighting the need for improved detection and treatment of AA. Preventive programs should strengthen their focus on smoking and HSBP control to reduce the burden of AA.\u003c/p\u003e","manuscriptTitle":"Global burden of aortic aneurysm and its attributable risk factors from 1990 to 2021: an update from the GBD 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-25 06:25:19","doi":"10.21203/rs.3.rs-7850745/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":"ab4be244-f04b-42ac-9ae1-9012e8c0e729","owner":[],"postedDate":"November 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-22T09:26:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-25 06:25:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7850745","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7850745","identity":"rs-7850745","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}