Epidemiological trends in the burden of atrial fibrillation and atrial flutter in China (1990-2023)
Sikai Xu , Yi Li , Fan Lin , Ping Zuo , Jingjing Fan , Xiaoyun Yang
Vessel Plus ›› 2026, Vol. 10 ›› Issue (1) : 32
Aim: Atrial fibrillation and atrial flutter (AF/AFL) represent a growing public health challenge in China amid rapid population aging. This study aimed to comprehensively assess long-term trends, sex- and age-specific patterns, driving factors, and future projections of AF/AFL burden in China from 1990 to 2023.
Methods: Data were obtained from Global Burden of Disease 2023. Temporal trends, driving factors, and future projections were evaluated using joinpoint regression, age-period-cohort models, decomposition analysis, frontier analysis, and autoregressive integrated moving average (ARIMA) models.
Results: From 1990 to 2023, the absolute numbers of AF/AFL cases, deaths, and disability-adjusted life years (DALYs) increased substantially in China, whereas age-standardized mortality and DALY rates declined overall, with a recent upturn after 2020. Incidence and prevalence were generally higher in males, whereas females had higher mortality and DALYs at older ages. Population aging was the dominant contributor to increases in incidence, prevalence, mortality, and DALYs. Age-period-cohort models analyses showed that among individuals born after 1944, the burden of AF/AFL was higher in males than in females. Frontier analysis indicated that China still lags behind several high Socio-demographic Index regions in AF/AFL burden control. ARIMA projections suggested declining mortality and DALYs but heterogeneous future trends in incidence and prevalence by sex.
Conclusions: Despite improvements in age-standardized mortality and DALYs, the overall burden of AF/AFL in China continues to increase, primarily driven by population aging. Targeted prevention, early detection, and optimized management strategies - particularly among older adults and high-risk males - are urgently needed.
Atrial fibrillation and flutter / disease burden / population aging / decomposition analysis / joinpoint regression / prediction
| [1] |
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| [2] |
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| [3] |
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| [4] |
|
| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
|
| [18] |
|
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
|
| [23] |
|
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
|
| [34] |
|
| [35] |
|
| [36] |
|
| [37] |
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