Abstract
Aims
The study aims to comprehensively evaluate the global burden of heart failure attributable to atrial fibrillation (AF) and atrial flutter (AFL) from 1990 to 2021.
Methods
Using data from the Global Burden of Disease Study 2021, we estimated the prevalence and years lived with disability (YLDs) of heart failure attributable to AF/AFL across 204 countries and territories. Estimates were stratified by age, sex and socio‐demographic index (SDI). Age‐standardized rates per 100 000 population were calculated, and percentage changes between 1990 and 2021 were analysed to assess temporal trends.
Results
In 2021, AF/AFL were responsible for an estimated 714 137.5 [95% uncertainty interval (UI) 520 543.5 to 940 900.6] heart failure cases and 63 942.8 (95% UI 39 057.9 to 96 196.5) YLDs globally. The age‐standardized prevalence and YLD rates were 8.85 (95% UI 6.38 to 11.63) and 0.79 (95% UI 0.49 to 1.19) per 100 000 population, respectively. Between 1990 and 2021, global absolute numbers of heart failure cases and YLDs attributable to AF/AFL increased by 339.3% (95% UI 292.7 to 387.0) and 337.5% (95% UI 290.1 to 387.0), respectively. Age‐standardized prevalence and YLD rates increased by 65.2% (95% UI 47.7 to 83.8) and 65.4% (95% UI 46.6 to 83.5), respectively. The burden progressively increased with age, peaking among individuals aged ≥95 years. Females experienced a higher burden than males from age 55 years onward, with the greatest disparity observed in the 85–89 years age group. High SDI regions, such as Australasia and Western Europe, exhibited the highest prevalence and YLD rates.
Conclusions
The global burden of heart failure attributable to AF/AFL increased substantially from 1990 to 2021, disproportionately affecting older adults, females aged 55 years and above and populations in high SDI regions. These findings highlight the urgent need for targeted interventions and resource allocation to address the growing challenges, particularly for vulnerable groups.
Keywords: atrial fibrillation and flutter, epidemiology, heart failure, years lived with disability
Introduction
Atrial fibrillation (AF) and atrial flutter (AFL) are significant contributors to heart failure, imposing a substantial global health burden due to their widespread prevalence and deleterious pathophysiological effects. 1 , 2 These arrhythmias disrupt normal cardiac electrical conduction, impair atrial contractility and induce irregular and elevated ventricular filling pressures, thereby significantly increasing the risk of heart failure through acute hemodynamic disturbances and progressive structural remodelling. 3 , 4 , 5 Over recent decades, the prevalence of AF/AFL has risen markedly, primarily driven by ageing populations and the growing burden of risk factors such as obesity, hypertension, and diabetes. 2 , 6 , 7 This rise has been accompanied by substantial economic costs, including substantial healthcare expenditures for hospitalizations, treatments, and long‐term care, as well as indirect costs from lost productivity and disability. 8 , 9 Despite the growing recognition of this issue, comprehensive global data on the specific contribution of AF/AFL to the burden of heart failure remain scarce, hindering the development of targeted prevention and management strategies.
To address this critical gap, the present study utilized data from the most recent Global Burden of Disease Study (GBD) 2021 to conduct the first comprehensive analysis of the global burden of heart failure attributable to AF/AFL. 10 By examining key metrics such as prevalence, years lived with disability (YLDs) and temporal trends at global, regional and national levels, the study provides a detailed evaluation of the impact of these arrhythmias on heart failure. Through stratification by age, sex and socio‐economic development, it aims to uncover disparities and identify populations disproportionately affected by AF/AFL‐related heart failure. These findings are expected to guide evidence‐based public health strategies, optimize resource allocation and drive the development of targeted interventions to alleviate the clinical and economic burden associated with AF/AFL‐induced heart failure.
Methods
Overview
The GBD study, conducted by the Institute for Health Metrics and Evaluation, represents the most comprehensive effort to quantify and compare the burden and associated risk factors of diseases and injuries at the global, regional and national levels. 10 , 11 , 12 Its latest iteration, GBD 2021, encompassed data from 204 countries and territories across 21 regions, covering 371 diseases, 288 causes of death and 88 risk factors. By integrating a wide range of high‐quality data sources and applying advanced statistical modelling techniques, GBD 2021 produced rigorous, standardized estimates that facilitate robust comparative assessments. Detailed methodological information has been published in previous reports. 10 , 11 , 12 Here, we summarize the methodologies applied to evaluate the burden of heart failure attributable to AF/AFL. The GBD study received ethical approval from the University of Washington Institutional Review Board, with informed consent waived due to the use of de‐identified data.
Definition and data sources
Heart failure was defined based on clinical criteria, including the Framingham and European Society of Cardiology (ESC) guidelines. 13 , 14 Beginning with GBD 2016, the American College of Cardiology (ACC)/American Heart Association (AHA) Stage C and above was used capture both symptomatic individuals and those previously diagnosed but asymptomatic. 15 Heart failure severity was further classified using the New York Heart Association (NYHA) functional classification. 16 AF/AFL, classified as supraventricular arrhythmias, were defined as follows: AF involves disorganized atrial depolarization while AFL is a macro‐reentrant arrhythmia typically involving the cavo‐tricuspid isthmus. Diagnosis relied on ECG findings, including irregular RR intervals, absence of P waves or characteristic flutter patterns. AF/AFL were identified using ICD‐10 codes I48–I48.9 and ICD‐9 code 427.3. In GBD 2021, high‐quality data from literature, hospitals and claims were utilized to estimate the burden of heart failure and AF/AFL. The final data sources for these estimates are publicly available through the GBD 2021 Data Input Sources Tool (https://ghdx.healthdata.org/gbd-2021/sources).
Estimation of prevalence and years lived with disability
The prevalence of heart failure attributable to AF/AFL was estimated using DisMod‐MR 2.1, a Bayesian meta‐regression tool widely employed in GBD analyses. Inpatient hospital data were carefully adjusted for factors such as readmission rates, primary‐to‐any diagnosis ratios and inpatient‐to‐outpatient utilization rates, utilizing correction factors derived from individual‐level claims data. Additional covariates, including ICD‐coded data from diverse sources (e.g., US claims and ICPC‐coded data from Norway), were incorporated to improve accuracy. A systematic approach was employed to allocate heart failure cases across major causal groupings, followed by specific adjustments to exclude overlapping conditions such as Chagas disease, valve pathologies and calcific aortic valve disease. This methodology ensured that the final estimates accurately reflect the burden attributable solely to AF/AFL. 10
YLDs were calculated by stratifying cases of heart failure into four severity levels: treated, mild, moderate and severe. 10 Each severity category was assigned a specific disability weight, quantifying the health loss on a scale from 0 (no disability) to 1 (equivalent to death). The YLD burden was then determined by multiplying the prevalence of heart failure at each severity level by the corresponding disability weight. 10 This process provided a detailed quantification of the non‐fatal burden of heart failure attributable to AF/AFL, capturing the variation in disability across different severity levels.
Statistical analysis
The burden of heart failure attributable to AF/AFL was quantified using annual prevalent cases, YLDs and corresponding age‐standardized rates, all reported with 95% uncertainty intervals (UIs). Age‐standardized rates were calculated via the direct method, standardized to the global age structure, facilitating robust regional comparisons and evaluations of temporal trends. We calculated percentage changes in age‐standardized rates from 1990 to 2021 to quantify the direction and magnitude of these trends. The findings were then compared across geographical locations, sexes, age groups and socio‐demographic index (SDI) levels. The SDI is a composite indicator used to quantify the development status of countries and regions, based on average educational attainment among individuals aged 15 years and older, fertility rates for women under 25 years and lag‐adjusted per capita income, ranging from 0 (least developed) to 1 (most developed). 10 , 11 , 12 In GBD 2021, all 204 countries and territories were categorized into five SDI quintiles (low, low‐middle, middle, high‐middle, and high) based on their SDI values. The relationship between SDI and age‐standardized rates was analysed using a generalized additive model with local regression smoothing (LOESS). 17 To ensure analytical robustness and capture variability, uncertainty was thoroughly addressed through 500 simulation draws at each analytical step, with final values calculated as the mean of these draws. 10 , 11 , 12 The 95% UIs, defined by the 2.5th and 97.5th percentiles, were deemed statistically significant if they excluded zero. Statistical analyses and visualizations were conducted using R software (version 4.3.2).
Results
Global level
In 2021, AF/AFL were estimated to contribute to approximately 714 137.5 (95% UI 520 543.5 to 940 900.6) cases of heart failure worldwide, resulting in 63 942.8 (95% UI 39 057.9 to 96 196.5) YLDs. The global age‐standardized prevalence and YLD rates per 100 000 population were 8.85 (95% UI 6.38 to 11.63) and 0.79 (95% UI 0.49 to 1.19), respectively. Between 1990 and 2021, the age‐standardized prevalence rate rose by 65.2% (95% UI 47.7 to 83.8), accompanied by a 65.4% increase (95% UI 46.6 to 83.5) in the age‐standardized YLD rate. Over the same period, the global absolute numbers of heart failure cases and YLDs attributable to AF/AFL increased by 339.3% (95% UI 292.7 to 387.0) and 337.5% (95% UI 290.1 to 387.0), respectively.
Regional level
At the regional level, Australasia, Western Europe and high‐income North America, which are all high SDI regions, reported the highest age‐standardized prevalence and YLD rates of heart failure attributable to AF/AFL (Table 1). In contrast, the lowest rates were observed in Central Asia, North Africa and the Middle East, and South Asia. Between 1990 and 2021, Western Europe experienced the largest percentage increases in age‐standardized prevalence and YLD rates of heart failure attributable to AF/AFL, with prevalence increasing by 114.1% (95% UI 82.3 to 146.3) and YLD by 114.7% (95% UI 80.8 to 149.6), followed by Australasia and high‐income Asia Pacific (Table 1). Conversely, the smallest percentage increases occurred in Western Sub‐Saharan Africa, Southern Sub‐Saharan Africa and Oceania.
Table 1.
Prevalence and YLDs of heart failure attributable to AF/AFL in 2021, with percentage changes in age‐standardized rates by sex and GBD region.
| Prevalence | YLDs | |||||
|---|---|---|---|---|---|---|
| Number | Age‐standardized rate (per 100 000 people) | Percentage change in age‐standardized rates, 1990–2021 | Number | Age‐standardized rate (per 100 000 people) | Percentage change in age‐standardized rates, 1990–2021 | |
| Global | 714 137.5 (520 543.5 to 940 900.6) | 8.85 (6.38 to 11.63) | 65.2% (47.7 to 83.8) | 63 942.8 (39 057.9 to 96 196.5) | 0.79 (0.49 to 1.19) | 65.4% (46.6 to 83.5) |
| Sex | ||||||
| Male | 288 502.0 (210 442.8 to 384 366.2) | 8.61 (6.15 to 11.34) | 68.7% (51.4 to 86.9) | 25 892.9 (15 490.6 to 40 106.5) | 0.77 (0.47 to 1.17) | 69.2% (50.1 to 89.0) |
| Female | 425 635.5 (309 454.8 to 555 878.6) | 9.04 (6.59 to 11.80) | 63.7% (45.2 to 82.5) | 38 049.9 (23 570.1 to 57 017.7) | 0.81 (0.50 to 1.21) | 63.7% (45.2 to 82.0) |
| GBD region | ||||||
| Central Sub‐Saharan Africa | 3113.3 (2046.8 to 4682.0) | 10.48 (6.77 to 15.36) | 19.5% (8.2 to 34.6) | 278.8 (159.4 to 470.4) | 0.93 (0.52 to 1.54) | 19.5% (2.1 to 40.0) |
| Eastern Sub‐Saharan Africa | 7891.8 (5269.3 to 11 602.4) | 7.63 (4.94 to 10.68) | 25.8% (17.8 to 34.9) | 701.7 (405.2 to 1165.5) | 0.67 (0.38 to 1.11) | 26.3% (16.2 to 36.9) |
| Southern Sub‐Saharan Africa | 3929.1 (2659.9 to 5613.2) | 9.80 (6.40 to 13.64) | 13.2% (7.1 to 19.0) | 352.3 (203.0 to 572.8) | 0.87 (0.50 to 1.39) | 13.5% (5.0 to 22.3) |
| Western Sub‐Saharan Africa | 9599.6 (6462.2 to 13 383.1) | 8.31 (5.56 to 11.35) | 12.8% (7.0 to 19.1) | 851.8 (501.2 to 1396.4) | 0.73 (0.43 to 1.18) | 13.2% (6.1 to 20.9) |
| Andean Latin America | 6748.0 (5006.5 to 8880.3) | 12.14 (8.97 to 16.02) | 32.6% (15.3 to 49.8) | 602.7 (366.9 to 874.5) | 1.08 (0.66 to 1.57) | 33.6% (11.9 to 57.6) |
| Tropical Latin America | 25 946.1 (18 018.7 to 35 262.2) | 10.85 (7.45 to 14.82) | 82.7% (62.1 to 105.2) | 2299.6 (1375.2 to 3580.3) | 0.96 (0.57 to 1.49) | 83.9% (62.7 to 108.2) |
| Central Latin America | 23 295.8 (17 811.4 to 30 234.0) | 10.06 (7.67 to 13.08) | 32.2% (19.7 to 44.5) | 2078.8 (1286.8 to 3135.1) | 0.90 (0.55 to 1.34) | 33.1% (20.9 to 47.5) |
| Southern Latin America | 4972.7 (3253.1 to 6884.2) | 5.39 (3.55 to 7.44) | 74.2% (44.9 to 104.9) | 447.3 (249.6 to 712.8) | 0.49 (0.27 to 0.77) | 74.5% (38.0 to 114.4) |
| Caribbean | 5200.2 (3763.1 to 6950.9) | 9.45 (6.84 to 12.69) | 29.5% (12.4 to 47.3) | 462.2 (278.8 to 690.5) | 0.84 (0.51 to 1.27) | 29.9% (10.2 to 49.8) |
| Central Europe | 18 657.3 (13 907.3 to 25 102.9) | 7.64 (5.72 to 10.19) | 54.5% (34.0 to 77.7) | 1677.1 (1010.2 to 2626.9) | 0.69 (0.42 to 1.07) | 54.9% (33.1 to 76.2) |
| Eastern Europe | 17 274.7 (11 587.0 to 24 057.3) | 4.72 (3.17 to 6.59) | 36.9% (21.0 to 55.1) | 1546.7 (880.5 to 2554.9) | 0.42 (0.24 to 0.69) | 36.8% (18.6 to 56.3) |
| North Africa and Middle East | 13 076.0 (10 166.3 to 16 510.2) | 3.89 (2.93 to 5.01) | 52.6% (36.9 to 68.7) | 1177.9 (733.3 to 1708.3) | 0.35 (0.21 to 0.50) | 53.2% (34.0 to 72.3) |
| Central Asia | 1180.7 (774.7 to 1640.0) | 1.86 (1.20 to 2.64) | 20.5% (2.9 to 37.5) | 107.7 (59.0 to 172.6) | 0.17 (0.09 to 0.27) | 20.3% (−2.5 to 41.8) |
| South Asia | 47 727.1 (33 253.6 to 65 420.0) | 4.57 (3.11 to 6.37) | 52.1% (35.6 to 68.5) | 4222.1 (2530.7 to 6645.1) | 0.40 (0.23 to 0.61) | 52.4% (34.6 to 71.1) |
| Southeast Asia | 39 748.4 (29 983.2 to 51 956.2) | 8.81 (6.52 to 11.60) | 66.6% (52.7 to 80.2) | 3513.5 (2154.2 to 5227.0) | 0.77 (0.47 to 1.13) | 67.6% (49.9 to 85.4) |
| East Asia | 132 965.9 (94 567.8 to 179 236.3) | 7.02 (4.92 to 9.41) | 53.7% (36.3 to 73.3) | 11 890.7 (7128.4 to 18 740.4) | 0.63 (0.38 to 0.97) | 54.3% (34.0 to 74.2) |
| Oceania | 220.4 (166.7 to 290.2) | 4.93 (3.59 to 6.75) | 19.4% (5.4 to 34.8) | 19.8 (11.8 to 30.3) | 0.44 (0.26 to 0.67) | 18.6% (1.0 to 39.3) |
| High‐income Asia Pacific | 49 181.5 (34 365.6 to 64 950.5) | 8.67 (6.33 to 11.24) | 100.1% (74.5 to 134.9) | 4419.2 (2599.3 to 6727.8) | 0.78 (0.48 to 1.19) | 99.4% (72.5 to 137.1) |
| High‐income North America | 92 452.3 (65 516.3 to 126 087.1) | 12.79 (9.10 to 17.54) | 92.2% (61.9 to 134.4) | 8333.8 (4920.8 to 12 787.9) | 1.15 (0.68 to 1.79) | 92.1% (58.7 to 136.5) |
| Western Europe | 195 488.7 (140 039.6 to 260 363.5) | 16.90 (12.28 to 22.38) | 114.1% (82.3 to 146.3) | 17 574.4 (10 644.7 to 26 744.1) | 1.52 (0.93 to 2.32) | 114.7% (80.8 to 149.6) |
| Australasia | 15 467.8 (11 242.1 to 20 978.1) | 25.24 (18.51 to 34.05) | 111.4% (74.1 to 161.1) | 1384.8 (812.0 to 2058.8) | 2.26 (1.32 to 3.38) | 111.4% (73.1 to 168.3) |
Note: Data in parentheses are 95% uncertainty intervals. GBD, Global Burden of Disease Study; YLDs, years lived with disability.
National level
In 2021, the age‐standardized prevalence rates of heart failure attributable to AF/AFL showed a striking 44.8‐fold variation across countries and territories (Figures 1 and 2 and Table S1). Among these, Sweden [38.94 (95% UI 25.81 to 55.09) per 100 000 population] and France [38.17 (95% UI 27.77 to 51.34) per 100 000 population] reported the highest age‐standardized prevalence rates, whereas Tajikistan [0.87 (95% UI 0.59 to 1.23) per 100 000 population] and Uzbekistan [1.08 (95% UI 0.67 to 1.54) per 100 000 population] had the lowest. Over the period from 1990 to 2021, Republic of Korea [270.9% (95% UI 204.7 to 366.9)] and Denmark [204.9% (95% UI 146.3 to 276.7)] experienced the most pronounced percentage increases in age‐standardized prevalence rates, while only a few countries showed a decline, with Antigua and Barbuda [−12.2% (95% UI −28.3 to 3.9)] and Greece [−7.7% (95% UI −28.3 to 15.6)] recording the largest decreases.
Figure 1.
Age‐standardized prevalence rates of heart failure attributable to AF/AFL across 204 countries and territories in 2021. AF, atrial fibrillation; AFL, atrial flutter.
Figure 2.
Age‐standardized YLD rates of heart failure attributable to AF/AFL across 204 countries and territories in 2021. AF, atrial fibrillation; AFL, atrial flutter; YLD, years lived with disability.
The age‐standardized YLD rates of heart failure attributable to AF/AFL in 2021 ranged from 0.08 to 3.53 per 100 000 population (Figures 1 and 2 and Table S2). Consistent with the prevalence rates, Sweden [3.53 (95% UI 1.98 to 5.68) per 100 000 population] and France [3.44 (95% UI 2.10 to 5.29) per 100 000 population] ranked highest in age‐standardized YLD rates, whereas Tajikistan [0.08 (95% UI 0.05 to 0.12) per 100 000 population] and Uzbekistan [0.10 (95% UI 0.05 to 0.16) per 100 000 population] remained at the lowest. Between 1990 and 2021, Republic of Korea [270.7% (95% UI 188.1 to 399.1)] and Denmark [204.5% (95% UI 132.6 to 312.2)] recorded the most substantial percentage increases in age‐standardized YLD rates. By contrast, Antigua and Barbuda [−11.9% (95% UI −32.0 to 12.0)] and Greece [−7.0% (95% UI −34.1 to 27.4)] exhibited the greatest percentage declines.
Age and sex patterns
In 2021, females experienced a greater global burden of heart failure attributable to AF/AFL, with higher numbers of prevalent cases (425 635.5 vs. 288 502.0) and YLDs (38 049.9 vs. 25 892.9) than males, alongside slightly elevated age‐standardized rates (Table 1, Figures 3 and S1). Both prevalence and YLD rates increased progressively with age in both sexes, peaking in the oldest age group (≥95 years), reflecting the cumulative impact of ageing (Figures 3 and S1). Across all age groups, treated and severe heart failure contributed the majority of the prevalence burden, with the total number of prevalent cases attributable to severe heart failure rising substantially in older populations (≥65 years). Severe heart failure also dominated the YLD burden, accounting for over 60% of the total and reflecting its significant role in driving disability. The distribution of disease burden also varied by sex. Males reached their highest number of prevalent cases and YLDs earlier, at ages 80–84 years, whereas females peaked later, at ages 85–89 years. From the age of 55 years onward, females consistently exhibited a higher burden than males, with the most pronounced disparity observed in the 85–89 years group, where females had nearly twice as many prevalent cases and significantly more YLDs than males (Figure 4)
Figure 3.
Age‐specific prevalence rates and numbers of heart failure attributable to AF/AFL by severity in 1990 and 2021. AF, atrial fibrillation; AFL, atrial flutter.
Figure 4.
Temporal trends in numbers and age‐standardized rates of AF/AFL‐related heart failure burden by SDI quintile from 1990 to 2021. AF, atrial fibrillation; AFL, atrial flutter; SDI, socio‐demographic index; YLD, years lived with disability.
Association with the SDI
By SDI quintile, the highest age‐standardized prevalence and YLD rates of heart failure attributable to AF/AFL in 2021 were observed in countries within the high SDI quintile, followed by those in high‐middle SDI quintile (Tables S1 and S2). Between 1990 and 2021, the percentage increase in age‐standardized prevalence and YLD rates showed a progressive rise with higher SDI levels. The high SDI quintile experienced the largest increases, with prevalence rates rising by 91.7% (95% UI 68.0 to 118.1) and YLD rates increasing by 91.8% (95% UI 66.2 to 118.7). Conversely, the lowest increases were recorded in the low SDI quintile, where prevalence rates increased by 27.2% (95% UI 21.0 to 34.1) and YLD rates by 27.4% (95% UI 19.4 to 35.9). Figure 5 illustrates the trends in age‐standardized prevalence and YLD rates of heart failure attributable to AF/AFL across 21 GBD regions from 1990 to 2021, generally showing an increasing trend with higher SDI levels. Regions with higher SDI, such as Australasia and Western Europe, exhibited the highest prevalence and YLD rates, reflecting the significant burden of AF/AFL‐related heart failure in more developed regions.
Figure 5.
Trends in age‐standardized prevalence and YLD rates of heart failure attributable to AF/AFL for 21 GBD regions by SDI, 1990–2021. AF, atrial fibrillation; AFL, atrial flutter; GBD, Global Burden of Disease Study; SDI, socio‐demographic index; YLD, years lived with disability.
Discussion
This study provides the first comprehensive global assessment of the burden of heart failure attributable to AF/AFL, revealing significant increases in both absolute numbers and age‐standardized rates of prevalence and YLDs between 1990 and 2021. Over this period, the absolute numbers of heart failure cases and YLDs related to AF/AFL surged by over 300%, while age‐standardized prevalence and YLD rates rose by approximately 65%. These trends were primarily driven by demographic shifts, including population ageing and growth, the rising prevalence of modifiable cardiovascular risk factors such as hypertension, obesity and diabetes and advancements in diagnostic capabilities that enhanced the detection of both clinical and subclinical cases. 2 , 6 , 18 , 19 These findings emphasize the urgent need for targeted prevention, early diagnosis and equitable care to address the growing burden of AF/AFL‐related heart failure.
There are significant geographic disparities in the burden of heart failure attributable to AF/AFL. High SDI regions, such as Australasia and Western Europe, reported the highest age‐standardized prevalence and YLD rates. This elevated burden reflects the combined effects of ageing populations, a high prevalence of non‐communicable diseases and advanced healthcare systems that facilitate earlier and more accurate diagnoses. 20 Republic of Korea's dramatic rise in age‐standardized rates, exceeding 270% over the study period, underscores how urbanization, dietary transitions and increased exposure to cardiovascular risk factors can amplify disease prevalence. 21 , 22 In addition, genetic predispositions may partly explain regional differences, with studies identifying population‐specific genetic variants linked to AF/AFL, such as certain risk alleles more prevalent in European populations than in East Asians. 23 While high SDI regions have the resources to manage the long‐term care burden, the associated economic challenges, including hospitalizations, treatments and rehabilitation, remain substantial.
In contrast, low SDI regions exhibited lower age‐standardized prevalence and YLD rates of AF/AFL‐related heart failure. This observed lower burden is likely influenced by demographic factors, such as younger population structures and shorter life expectancies, which reduce cumulative exposure to age‐related cardiovascular conditions. 24 Additionally, lower levels of urbanization and limited adoption of western dietary patterns may contribute to reduced prevalence. 25 However, underdiagnosis and inadequate access to healthcare services play a significant role in this disparity. In many low SDI countries, healthcare priorities are centred on infectious diseases, leaving limited resources for the detection, treatment and management of chronic conditions like AF/AFL. 25 Even when AF/AFL is diagnosed, access to appropriate treatments, such as anticoagulation therapies and rhythm‐control strategies, is often limited, further exacerbating the progression to heart failure. These findings highlight the critical need for enhanced healthcare infrastructure, including diagnostic tools, affordable treatments and comprehensive management programmes, to address the growing burden of AF/AFL‐related heart failure in these regions.
Age and sex disparities also influence the burden of AF/AFL‐related heart failure. The disease burden increases substantially with age, peaking among individuals aged ≥95 years, which reflects the cumulative impact of prolonged exposure to arrhythmias and age‐related declines in cardiac function. Severe heart failure disproportionately contributes to the overall burden, particularly among older adults, emphasizing the profound disability associated with advanced disease stages. Females experience a higher burden than males from the age of 55 years onward, with the greatest disparity observed in those aged 85–89 years. This disparity is likely influenced by longer life expectancy in females, post‐menopausal hormonal changes that elevate cardiovascular risk and a higher prevalence of heart failure with preserved ejection fraction in females. 26 , 27 These findings underscore the need for tailored prevention, diagnostic and treatment strategies that address the unique cardiovascular health challenges faced by females, particularly in older age groups.
Limitations
This study has several limitations that warrant consideration. First, geographical disparities in data availability and quality posed challenges for burden estimation, particularly in regions with sparse datasets such as Sub‐Saharan Africa. To mitigate these gaps, the GBD framework employed advanced statistical modelling and data borrowing techniques from neighbouring regions, which significantly enhance the reliability of estimates in data‐limited settings. Nevertheless, the paucity of data in certain regions may limit the generalizability of our findings, as even sophisticated modelling cannot fully substitute for high‐quality primary data. Second, the absence of stratification by clinical subtypes—such as heart failure with reduced versus preserved ejection fraction or paroxysmal versus persistent AF—limits the granularity of insights into disease heterogeneity. Third, despite integrating high‐quality data from diverse sources, the GBD framework may still face biases arising from variations in diagnostic criteria, underreporting and healthcare access across countries. These differences, especially in low‐resource settings, could lead to an underestimation of the true burden of AF/AFL‐related heart failure. Lastly, temporal changes in diagnostic capabilities and awareness may have influenced the observed trends in prevalence and burden. Although the GBD framework addresses these variations through standardized methodologies, residual uncertainties remain in interpreting long‐term trends.
Conclusions
This study provides the first comprehensive global assessment of the burden of heart failure attributable to AF/AFL from 1990 to 2021. The findings reveal a significant increase in both absolute and age‐standardized prevalence and YLD rates. The burden was disproportionately higher among older adults, females aged 55 years and above and populations in high SDI regions. These results highlight the urgent need for targeted prevention and management strategies. Healthcare systems in high SDI regions must prioritize early detection, timely intervention and long‐term care, particularly for these vulnerable populations. In low SDI regions, improving access to diagnostics and treatments is crucial. Strengthening healthcare infrastructure in these areas will be essential to addressing the growing global burden of AF/AFL‐related heart failure. Incorporating these findings into health policy frameworks will be critical for shaping effective, evidence‐based strategies to reduce the disease's impact, enhance clinical outcomes and mitigate the societal and economic costs of AF/AFL‐related heart failure.
Funding
This study was supported by the Zhejiang Provincial Medical and Health Science and Technology Project (2025KY862). The funder played no role in the preparation of this manuscript.
Conflict of interest statement
None declared.
Supporting information
Figure S1. Age‐specific YLD rates and numbers of heart failure attributable to AF/AFL by severity in 1990 and 2021.
Table S1. Prevalence of heart failure attributable to AF/AFL in 1990 and 2021 for both sexes, along with percentage changes in age‐standardized rates by location.
Table S2. YLDs of heart failure attributable to AF/AFL in 1990 and 2021 for both sexes, along with percentage changes in age‐standardized rates by location.
Liu, Y. , Duan, J. , Wang, Y. , Bragazzi, N. L. , Huang, M. , Chen, H. , Dai, H. , and Ni, C. (2025) Atrial fibrillation and flutter as global drivers of heart failure: Burden and longitudinal trends over three decades. ESC Heart Failure, 12: 3697–3706. 10.1002/ehf2.15344.
Data availability statement
All data generated or analysed during this study are included in this published article. The datasets generated during and/or analyses during the current study are available in the Global Burden of Disease. The R code used for this study is available upon request. Please contact the corresponding author to obtain the code for reproducibility purposes.
References
- 1. Ngo LTH, Peng Y, Denman R, Yang I, Ranasinghe I. Long‐term outcomes after hospitalization for atrial fibrillation or flutter. Eur Heart J 2024;45:2133‐2141. doi: 10.1093/eurheartj/ehae204 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Ko D, Chung MK, Evans PT, Benjamin EJ, Helm RH. Atrial fibrillation: a review. JAMA 2024; doi: 10.1001/jama.2024.22451 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Verhaert DVM, Brunner‐La Rocca HP, van Veldhuisen DJ, Vernooy K. The bidirectional interaction between atrial fibrillation and heart failure: consequences for the management of both diseases. Europace 2021;23:ii40‐ii45. doi: 10.1093/europace/euaa368 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Manolis AS, Manolis TA, Manolis AA, Melita H. Atrial fibrillation‐induced tachycardiomyopathy and heart failure: an underappreciated and elusive condition. Heart Fail Rev 2022;27:2119‐2135. doi: 10.1007/s10741-022-10221-1 [DOI] [PubMed] [Google Scholar]
- 5. Diamant MJ, Andrade JG, Virani SA, Jhund PS, Petrie MC, Hawkins NM. Heart failure and atrial flutter: a systematic review of current knowledge and practices. ESC Heart Fail 2021;8:4484‐4496. doi: 10.1002/ehf2.13526 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Elliott AD, Middeldorp ME, Van Gelder IC, Albert CM, Sanders P. Epidemiology and modifiable risk factors for atrial fibrillation. Nat Rev Cardiol 2023;20:404‐417. doi: 10.1038/s41569-022-00820-8 [DOI] [PubMed] [Google Scholar]
- 7. Dai H, Zhang Q, Much AA, Maor E, Segev A, Beinart R, et al. Global, regional, and national prevalence, incidence, mortality, and risk factors for atrial fibrillation, 1990–2017: results from the Global Burden of Disease Study 2017. Eur Heart J Qual Care Clin Outcomes 2021;7:574‐582. doi: 10.1093/ehjqcco/qcaa061 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Buja A, Rebba V, Montecchio L, Renzo G, Baldo V, Cocchio S, et al. The cost of atrial fibrillation: a systematic review. Value Health 2024;27:527‐541. doi: 10.1016/j.jval.2023.12.015 [DOI] [PubMed] [Google Scholar]
- 9. Deshmukh A, Iglesias M, Khanna R, Beaulieu T. Atrial flutter‐related health care use and costs: an analysis of a nationally representative administrative claims database in the United States. Heart Rhythm O2 2023;4:367‐373. doi: 10.1016/j.hroo.2023.04.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. GBD 2021 Diseases and Injuries Collaborators . 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 2024;403:2133‐2161. doi: 10.1016/S0140-6736(24)00757-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. GBD 2021 Risk Factors Collaborators . 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 2024;403:2162‐2203. doi: 10.1016/S0140-6736(24)00933-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. GBD 2021 Causes of Death Collaborators . 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 2024;403:2100‐2132. doi: 10.1016/S0140-6736(24)00367-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. McKee PA, Castelli WP, McNamara PM, Kannel WB. The natural history of congestive heart failure: the Framingham study. N Engl J Med 1971;285:1441‐1446. doi: 10.1056/NEJM197112232852601 [DOI] [PubMed] [Google Scholar]
- 14. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2016;37:2129‐2200. doi: 10.1093/eurheartj/ehw128 [DOI] [PubMed] [Google Scholar]
- 15. Hunt SA, Abraham WT, Chin MH, Feldman AM, Francis GS, Ganiats TG, et al. 2009 focused update incorporated into the ACC/AHA 2005 guidelines for the diagnosis and management of Heart Failure in adults a report of the American College of Cardiology Foundation/American Heart Association task force on practice guidelines developed in collaboration with the International Society for Heart and Lung Transplantation. J Am Coll Cardiol 2009;53:e1‐e90. doi: 10.1016/j.jacc.2008.11.013 [DOI] [PubMed] [Google Scholar]
- 16. White PD, Myers M. The classification of cardiac diagnosis. JAMA 1921;77:1414‐1415. doi: 10.1001/jama.1921.02630440034013 [DOI] [Google Scholar]
- 17. Zhou L, Wei Y, Ge Y, Li Y, Liu K, Gao Y, et al. Global, regional, and national burden of stroke attributable to extreme low temperatures, 1990–2019: a global analysis. Int J Stroke 2024;19:676‐685. doi: 10.1177/17474930241238636 [DOI] [PubMed] [Google Scholar]
- 18. Ding EY, Marcus GM, McManus DD. Emerging technologies for identifying atrial fibrillation. Circ Res 2020;127:128‐142. doi: 10.1161/CIRCRESAHA.119.316342 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Nagarajan VD, Lee SL, Robertus JL, Nienaber CA, Trayanova NA, Ernst S. Artificial intelligence in the diagnosis and management of arrhythmias. Eur Heart J 2021;42:3904‐3916. doi: 10.1093/eurheartj/ehab544 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, et al. 2024 heart disease and stroke statistics: a report of US and global data from the American Heart Association. Circulation 2024;149:e347‐e913. doi: 10.1161/CIR.0000000000001209 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Joung B, Lee JM, Lee KH, Kim TH, Choi EK, Lim WH, et al. 2018 Korean guideline of atrial fibrillation management. Korean Circ J 2018;48:1033‐1080. doi: 10.4070/kcj.2018.0339 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Feng J, Zhang Y, Zhang J. Epidemiology and burden of heart failure in Asia. JACC Asia 2024;4:249‐264. doi: 10.1016/j.jacasi.2024.01.013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Roselli C, Chaffin MD, Weng LC, Aeschbacher S, Ahlberg G, Albert CM, et al. Multi‐ethnic genome‐wide association study for atrial fibrillation. Nat Genet 2018;50:1225‐1233. doi: 10.1038/s41588-018-0133-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. GBD 2021 Demographics Collaborators . Global age–sex‐specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID‐19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024;403:1989‐2056. doi: 10.1016/S0140-6736(24)00476-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Garg K, Satti DI, Yadav R, Brumfield J, Akwanalo CO, Mesubi OO, et al. Global health inequities in electrophysiology care: a state‐of‐the‐art review. JACC Adv 2024;3:101387. doi: 10.1016/j.jacadv.2024.101387 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Lam CS, Arnott C, Beale AL, Chandramouli C, Hilfiker‐Kleiner D, Kaye DM, et al. Sex differences in heart failure. Eur Heart J 2019;40:3859‐3868c. doi: 10.1093/eurheartj/ehz835 [DOI] [PubMed] [Google Scholar]
- 27. da Silva JS, Montagnoli TL, de Sa MPL, Zapata‐Sudo G. Heart failure in menopause: treatment and new approaches. Int J Mol Sci 2022;23:15140. doi: 10.3390/ijms232315140 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1. Age‐specific YLD rates and numbers of heart failure attributable to AF/AFL by severity in 1990 and 2021.
Table S1. Prevalence of heart failure attributable to AF/AFL in 1990 and 2021 for both sexes, along with percentage changes in age‐standardized rates by location.
Table S2. YLDs of heart failure attributable to AF/AFL in 1990 and 2021 for both sexes, along with percentage changes in age‐standardized rates by location.
Data Availability Statement
All data generated or analysed during this study are included in this published article. The datasets generated during and/or analyses during the current study are available in the Global Burden of Disease. The R code used for this study is available upon request. Please contact the corresponding author to obtain the code for reproducibility purposes.