Trends in Atrial Fibrillation-Related Mortality Among Older Adults With hypertension in the United States, 2001–2023

Trends in Atrial Fibrillation-Related Mortality Among Older Adults With hypertension in the United States, 2001–2023 | 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 Trends in Atrial Fibrillation-Related Mortality Among Older Adults With hypertension in the United States, 2001–2023 Hangyu Liu, Juan Hua, Liang Xiong, Shuanghua Zhu, Ziyang Ding, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7422150/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background The coexistence of atrial fibrillation (AF) or atrial flutter (AFL) and hypertension represents a major public health challenge, particularly among older adults, due to its strong association with adverse cardiovascular outcomes and mortality. Methods We conducted a nationwide, population-based study using mortality data from the Centers for Disease Control and Prevention’s Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) system between 2001 and 2023. Deaths among U.S. adults aged ≥ 65 years with AF/AFL and hypertension were identified using ICD-10 codes. Crude mortality rates (CMRs) and age-adjusted mortality rates (AAMRs) were calculated and stratified by sex, race/ethnicity, census region, and urban–rural classification. Temporal trends were assessed using Joinpoint regression analysis to estimate annual percentage change (APC) and average annual percentage change (AAPC). Results From 2001 to 2023, 77,599 AF/AFL-related deaths were attributed to concomitant hypertension, with a disproportionate burden observed among women (65%) compared to men (35%). Overall, the AAMR increased from 2.77 per 100,000 in 2001 to 12.54 in 2023 (AAPC 7.15%, p < 0.001). Women consistently exhibited higher mortality rates than men, and non-Hispanic White individuals experienced the steepest rise in AAMRs compared with non-Hispanic Black and Hispanic populations. Geographic disparities were also evident, with the Midwest and South showing the highest increases. Older adults aged ≥ 85 years demonstrated the highest mortality rates across all subgroups. Conclusions Mortality related to AF/AFL in the presence of hypertension has risen substantially in the United States over the past two decades, with notable disparities by sex, race/ethnicity, age, and region. These findings underscore the urgent need for targeted public health interventions and clinical strategies to improve risk factor control, enhance early detection, and address inequities in care among high-risk populations. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction The prevalence of atrial fibrillation (AF) and atrial flutter (AFL) has risen markedly in recent decades, particularly among older adults, where these arrhythmias frequently coexist with hypertension [ 1 ] . This combination substantially increases the risk of cardiovascular events and mortality, establishing AF and AFL as major public health concerns. The interaction of these conditions creates a complex clinical scenario characterized by heightened morbidity and escalating healthcare costs, underscoring the need for a clearer understanding of their epidemiology and management. The growing incidence of AF and AFL is partly attributable to population aging and the rising prevalence of hypertension. Hypertensive patients face a significantly higher risk of developing AF, with each standard deviation increase in diastolic blood pressure linked to a 37% increase in AF prevalence [ 2 ] . The burden of AF and AFL is further compounded by coexisting cardiovascular risk factors such as obesity and diabetes, which are also increasing globally [ 3 – 5 ] . These trends highlight the necessity for prevention and management strategies that target both hypertension and arrhythmias to reduce overall cardiovascular morbidity and mortality. Despite advances in pharmacological and catheter-based therapies, major gaps remain in the early diagnosis and management of AF and AFL. Treatment adherence is particularly challenging, and nonadherence is strongly associated with worse outcomes and increased cardiovascular events [ 6 ] . Improving patient education and adherence strategies is therefore essential for optimizing care. The interplay between AF/AFL and hypertension also requires careful monitoring and individualized management. Blood pressure control is critical, as uncontrolled hypertension exacerbates arrhythmia episodes and worsens outcomes. Evidence indicates that maintaining target blood pressure can significantly reduce the risk of stroke and other AF-related complications [ 7 ] . Thus, integrating effective blood pressure management into AF care pathways is vital to improving prognosis. Given these considerations, this study aimed to analyze long-term trends in AF/AFL-related mortality among older U.S. adults with coexisting hypertension using data from the CDC WONDER database (2001–2023). We also assessed demographic and geographic variations to provide insights that may inform targeted prevention strategies and public health interventions. 2. Methods 2.1 Study Setting and Population We utilized mortality data from the National Center for Health Statistics (NCHS), accessed via the Centers for Disease Control and Prevention’s Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) system, to examine annual mortality trends among U.S. adults aged ≥ 65 years from 2001 to 2023. These data are updated annually based on death certificates of U.S. residents and include underlying causes of death and demographic characteristics. Using the Multiple Cause of Death (final) public-use files and International Classification of Diseases, Tenth Revision (ICD-10) codes—I48 for atrial fibrillation (AF) and I10–I15 for hypertension (HT)—we identified death certificates listing these conditions as either the underlying or contributing cause of death. These ICD-10 codes have been employed in prior studies [ 8 , 9 ] . Because the data are publicly available, de-identified, and provided by a government agency, the study was exempt from institutional review board approval and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. 2.2 Data abstraction The dataset included population counts, year of occurrence, place of death, demographic variables, U.S. Census region, and urban–rural classification. Deaths occurred in various settings, including hospitals, homes, hospices, nursing homes, and long-term care facilities. “Demographic characteristics” encompassed sex, age, race, and ethnicity. Race and ethnicity were categorized as Hispanic or Latino, non-Hispanic (NH) White, and NH Black/African American. Other NH racial groups were excluded due to insufficient data. The source data, derived from death certificates, have been used in previous WONDER-based analyses [ 10 ] . Urban–rural classification followed the NCHS Urban–Rural Classification Scheme for Counties: metropolitan areas included large metro areas (≥ 1 million residents) and medium/small metro areas (50,000–999,999 residents); nonmetropolitan areas included micropolitan and rural counties (< 50,000 residents). This classification was based on the 2013 U.S. Census Bureau standards [ 11 ] . Geographic regions were categorized into Northeast, Midwest, South, and West according to U.S. Census Bureau definitions. 2.3 Statistical Analysis To evaluate national trends in AF/atrial flutter (AFL) and hypertension-related mortality from 2001 to 2023, we calculated crude mortality rates (CMRs) and age-adjusted mortality rates (AAMRs) per 100,000 persons. Rates were stratified by year, sex, race/ethnicity, census region, and urban–rural status, and presented with 95% confidence intervals (CIs). CMRs were computed by dividing the total number of AF/AFL and hypertension-related deaths by the corresponding U.S. population for each year. AAMRs were standardized to the U.S. standard population in 2001. Temporal trends were assessed using Joinpoint regression analysis (version 5.1.0; National Cancer Institute) [ 12 ] . This method fits log-linear regression models to estimate the annual percentage change (APC) in AAMRs with 95% CIs. A slope significantly different from zero (two-tailed t-test) indicated a statistically significant upward or downward trend. Statistical significance was defined as p < 0.05. Tests of parallelism were used to compare trends across subgroups; a significant p-value indicated that average annual percentage change (AAPC) trends differed significantly between groups [ 13 ] . 3. Results Between 2001 and 2023, a total of 77,599 deaths in U.S. adults aged 25 years and older were attributed to AF/AFL in conjunction with hypertension, comprising 27,004 deaths among men and 50,595 among women. Analyses were stratified by year, sex, race/ethnicity, urbanization level, and census region 3.1 Overall AF/AFL and Hypertension related AAMR From 2001 to 2010, the national AAMR increased significantly (APC, 10.37%; 95% CI, 8.01–12.79; P < 0.001), with continued but slower growth from 2010 to 2023 (APC, 4.98%; 95% CI, 4.21–5.75; P < 0.001). Across the full study period, the AAMR rose from 2.77 in 2001 to 12.54 in 2023 (AAPC, 7.15%; 95% CI, 6.17–8.14; P < 0.001) (Table 1 ). Table 1 Demographic characteristics of deaths due to hypertension related atrial fibrillation/ flutter among all ages in the USA from 2001 to 2023. Characteristic Deaths (%) AAMR 2001 (95% CI) 2023 (95% CI) AAPC (95% CI) Total 77599 (100) 2.77 (2.59 to 2.94) 12.54 (12.24 to 12.84) 7.15 (6.17 to 8.14)* Sex Female 50595 (65.20) 3.04 (2.81 to 3.26) 12.50 (12.11 to 12.89) 6.63 (5.66 to 7.61)* Male 27004 (34.80) 2.11 (1.85 to 2.37) 12.35 (11.88 to 12.83) 8.41 (7.28 to 9.54)* Census Region Northeast 13065 (16.84) 2.83 (2.46 to 3.20) 9.43 (8.83 to 10.04) 5.81 (4.66 to 6.98)* Midwest 18726 (24.13) 2.68 (2.34 to 3.03) 13.72 (13.03 to 14.41) 7.68 (6.58 to 8.80)* South 27004 (34.80) 2.67 (2.38 to 2.96) 13.12 (12.61 to 13.63) 7.50 (6.24 to 8.77)* West 18804 (24.23) 2.86 (2.46 to 3.26) 13.15 (12.49 to 13.81) 7.62 (6.31 to 8.93)* Race Hispanic 3052 (3.93) 1.69 (1.09 to 2.50) 6.62 (5.86 to 7.37) 6.61 (5.55 to 7.69)* NH Black 4742 (6.11) 2.30 (1.76 to 2.95) 9.91 (9.00 to 10.83) 6.05 (5.29 to 6.82)* NH White 67774 (87.34) 2.82 (2.63 to 3.01) 14.08 (13.71 to 14.45) 7.55 (6.53 to 8.56)* Urbanization 1 Metropolitan 46999 (60.57) 2.62 (2.43 to 2.80) 9.59 (9.30 to 9.88) 7.08 (6.06 to 8.11)* Nonmetropolitan 11797 (15.20) 3.23 (2.80 to 3.66) 12.76 (12.01 to 13.51) 7.71 (6.51 to 8.94)* Age 2 65–74 years 8165 (10.52) 0.48 (0.38 to 0.59) 2.40 (2.23 to 2.56) 7.39 (6.76 to 8.03)* 75–84 years 21498 (27.70) 2.69 (2.41 to 2.98) 10.40 (9.94 to 10.87) 6.18 (5.12 to 7.26)* 85 + years 47936 (61.77) 12.64 (11.58 to 13.70) 61.90 (59.95 to 63.86) 7.55 (6.55 to 8.56)* Statistically significant AAPCs are denoted by an asterisk (*). 1 For the urbanization section, the 2023 AAMR data point was substituted with the 2020 value due to unavailability; the corresponding AAPC was calculated from 2001 through 2023. 2 Within the Age group categories, AAMRs presented are based on crude mortality rates; the AAPC values were calculated using these crude mortality rates. AAMR, age-adjusted mortality rate; CI, confidence interval; AAPC, average annual percent change; NH, non-Hispanic. Women consistently exhibited higher AAMRs (mean 10.70) than men (mean 5.24). Among men, the AAMR surged from 2001 to 2010 (APC 11.21; 95% CI, 8.45–14.03; p < 0.001) and continued to increase from 2010 to 2023 (APC 6.51; 95% CI, 5.71–7.31; p < 0.001), with an overall AAPC of 8.41 (95% CI, 7.28–9.54; p < 0.001). For women, the AAMR rose significantly from 2001 to 2010 (APC 10.24; 95% CI, 7.92–12.61; p < 0.001) and, although growth slowed between 2010 and 2023 (APC 4.20; 95% CI, 3.42–5.00; p < 0.001), the overall AAPC remained significant at 6.63 (95% CI, 5.66–7.61; p < 0.001) (Fig. 1 , Supplementary table 1 ). 3.2 AF/AFL and Hypertension related AAMR stratified by race/ethnicity In terms of race/ethnicity, NH White individuals had the highest AAMR, followed by NH Black or African American individuals, and Hispanic or Latino individuals. Due to missing data, other non-Hispanic were not included in this study. The AAMR for NH White individuals significantly increased from 2001 to 2010 (APC 10.76; 95% CI: 8.33–13.25, p < 0.001), and although the growth rate slowed from 2010 to 2023, it still exhibited a significant upward trend (APC 5.37; 95% CI 4.58–6.17). The AAMR for NH Black or African American individuals also showed a steady upward trend, rising from 2.30 in 2001 to 9.91 in 2023 (APC 6.05; 95% CI 5.29–6.82, p < 0.001). The AAMR for Hispanic or Latino individuals sharply increased from 2001 to 2016 (APC 8.51; 95% CI 7.13–9.91, p < 0.001), and while the rate of increase slowed from 2010 to 2023, it remained statistically significant (APC 2.66; 95% CI 0.67–4.69, p = 0.011) (Table 1 ). Overall, the NH White group exhibited the greatest increase (AAPC 7.55; 95% CI: 6.53–8.56; p < 0.001), followed by Hispanic or Latino individuals (AAPC 6.61; 95% CI: 5.55–7.69; p < 0.001) and NH Black or African American individuals (AAPC 6.05; 95% CI: 5.29–6.82; p < 0.001) (Fig. 2 , Supplementary table 1 ). 3.3 AF/AFL and Hypertension related AAMR stratified by urbanization From 2001 to 2020, metropolitan areas consistently had higher AAMRs (mean 7.70) than nonmetropolitan areas (mean 6.75). In metropolitan areas, the AAMR rose markedly from 2001 to 2011 (APC 10.14; 95% CI, 8.33–11.98; p < 0.001) and more slowly from 2011 to 2020 (APC 3.78; 95% CI, 2.53–5.04; p < 0.001). Nonmetropolitan areas showed a similar pattern, with a significant increase from 2001 to 2012 (APC 10.06; 95% CI, 8.19–11.96; p < 0.001) and a slower rise from 2011 to 2020 (APC 4.58; 95% CI, 2.80–6.38; p < 0.001). The AAPC for metropolitan areas reached 7.08% (p < 0.001), whereas the increase in nonmetropolitan areas was slightly less steep. CDC mortality data for 2021–2022 were unavailable (Fig. 3 , Supplementary table 2). 3.4 AF/AFL and Hypertension related AAMR stratified by census region From 2001 to 2023, all census regions experienced significant increases in AAMRs. In the Northeast, rates rose from 2.83 (95% CI, 2.46–3.20) to 9.43 (95% CI, 8.83–10.04) (AAPC, 5.81%; 95% CI, 4.66–6.98; P < 0.001). In the Midwest, rates increased from 2.68 (95% CI, 2.34–3.03) to 13.72 (95% CI, 13.03–14.41) (AAPC, 7.68%; 95% CI, 6.58–8.80; P < 0.001). In the South, rates rose from 2.67 (95% CI, 2.38–2.96) to 13.12 (95% CI, 12.61–13.63) (AAPC, 7.50%; 95% CI, 6.24–8.77; P < 0.001). In the West, rates increased from 2.86 (95% CI, 2.46–3.26) to 13.15 (95% CI, 12.49–13.81) (AAPC, 7.62%; 95% CI, 6.31–8.93; P < 0.001) (Table 1 ). Temporal patterns varied: the Northeast experienced a rise from 2001 to 2011 (APC, 8.76%; 95% CI, 6.38–11.20; P < 0.001) and slower growth thereafter (APC, 3.41%; 95% CI, 2.27–4.57; P < 0.001). The Midwest rose from 2001 to 2009 (APC, 11.50%; 95% CI, 8.45–14.63; P < 0.001) and from 2009 to 2023 (APC, 5.56%; 95% CI, 4.81–6.32; P < 0.001). Similar decelerations were observed in the South (2001–2010 APC, 9.68%; 2010–2023 APC, 6.01%) and West (2001–2008 APC, 14.98%; 2008–2023 APC, 4.34%) (Fig. 4 , Supplementary table 3). 3.5 AF/AFL and Hypertension related AAMR stratified by Ten-Year Age Group Among older adults with AF/AFL and hypertension, CMRs increased sharply with age and demonstrated significant temporal growth across all age strata. Rates were lowest and increased most gradually in those aged 65–74 years. In contrast, individuals aged ≥ 85 years exhibited markedly higher CMRs, with a significant overall upward trend (AAPC 7.55; 95% CI, 6.55–8.56; p < 0.001) (Table 1 , Fig. 5 ). 4. Discussion The increasing prevalence of atrial fibrillation (AF) and atrial flutter (AFL), particularly in aging populations, has positioned these conditions as significant public health concerns globally. AF/AFL is associated with heightened risks of thromboembolic events, heart failure, and mortality, which collectively contribute to a substantial burden on healthcare systems. This is especially pronounced in older adults, where the coexistence of hypertension—a prevalent condition in this demographic—exacerbates the risks associated with AF/AFL. Hypertension is widely recognized as one of the most important and clinically modifiable risk factors for atrial fibrillation (AF). Large-scale epidemiological studies have demonstrated that more than 70% of patients with AF present concomitant hypertension [ 14 , 15 ] , thereby highlighting the close pathophysiological association between the two conditions. Moreover, compared with normotensive individuals, patients with hypertension exhibit a 73% higher risk of developing AF [ 16 ] , a finding that may be largely attributed to hypertension-induced atrial structural remodeling, electrical remodeling, and alterations in autonomic regulation. In addition, longitudinal cohort studies have reported that a history of hypertension accounts for approximately 24% of the attributable risk of AF incidence [ 14 ] , underscoring the pivotal role of hypertension in the etiology of AF. Importantly, this relationship appears to follow a non-linear, curvilinear pattern rather than a simple linear association: both patients with short-term hypertension and those with long-standing hypertension demonstrate a significantly higher risk of AF compared with individuals with intermediate-duration hypertension [ 17 ] . These observations suggest that the temporal dynamics of hypertension exposure may exert complex influences on atrial pathophysiology and ultimately on the risk of AF development. Beyond epidemiological associations, hypertension promotes the initiation and progression of AF through multiple interrelated pathophysiological mechanisms. Chronic elevation of blood pressure leads to hemodynamic alterations and activation of neurohormonal pathways, which induce diffuse atrial structural and electrical remodeling, thereby increasing atrial electrical instability [ 14 ] . Furthermore, persistent inflammatory responses, alterations in hormonal homeostasis, and autonomic nervous system dysregulation act synergistically to enhance atrial electrophysiological vulnerability. Left ventricular hypertrophy and systolic or diastolic dysfunction, which are frequently observed in hypertensive individuals, serve as important mediators by elevating left atrial pressure load and facilitating atrial remodeling. Notably, an elevated risk of AF has also been documented in individuals with prehypertension as well as in those with reduced aortic compliance and increased arterial stiffness. Taken together, these findings indicate that the pro-arrhythmic effects of hypertension extend beyond overt hypertension and may emerge as early as the preclinical stages of cardiovascular dysfunction [ 18 ] . The coexistence of hypertension and AF also has profound implications for clinical outcomes. Patients with both conditions exhibit markedly higher risks of stroke and major bleeding, reflecting the dual burden of thromboembolic complications and anticoagulation-related adverse events [ 19 ] . In addition, all-cause mortality is significantly higher in hypertensive patients with AF than in those with AF alone, particularly among individuals with advanced target organ damage such as renal impairment, heart failure, or cerebrovascular disease [ 20 ] . Proteinuria, as an early marker of hypertensive end-organ injury, not only reflects renal microvascular damage but also independently increases the risk of AF [ 21 ] , further underscoring the interplay between systemic organ involvement and arrhythmogenesis. Moreover, in patients with pulmonary hypertension, the onset of AF often signals disease progression and is strongly associated with adverse prognosis [ 22 ] . Collectively, these findings emphasize that hypertension and AF interact synergistically, accelerating disease progression while simultaneously amplifying the risk of adverse outcomes, thereby posing a significant threat to long-term prognosis. As such, understanding the epidemiology and associated risk factors of AF/AFL, particularly in the context of hypertension, is crucial for developing effective prevention and management strategies aimed at reducing morbidity and mortality in this high-risk population. This study aims to systematically analyze the trends in mortality associated with AF/AFL and hypertension among older adults in the United States over the past two decades. Using data from the CDC WONDER database, we will examine mortality rates, specifically focusing on demographic factors such as age, sex, race, and geographic location. Previous research has highlighted significant disparities in mortality rates associated with these conditions, with evidence suggesting that females and certain racial groups experience higher mortality rates [ 23 ] . Furthermore, the study will explore the implications of these findings for public health interventions and clinical practice, aiming to provide insights that could inform tailored strategies for managing AF/AFL and hypertension in older adults. Through a comprehensive analysis of long-term mortality trends, we seek to elucidate the evolving burden of these conditions and their impact on the aging population, thereby contributing to the ongoing discourse on cardiovascular health management in the United States [ 24 ] . The innovation of this study lies in its comprehensive approach to analyzing the mortality trends associated with atrial fibrillation (AF) and hypertension in the elderly population of the United States. By leveraging the extensive CDC WONDER database, we have filled a critical knowledge gap regarding the intersection of these two prevalent cardiovascular conditions over a significant time period (2001 to 2023). Previous studies predominantly focused on either AF or hypertension in isolation or assessed trends over shorter durations, which limited the understanding of their combined impact on mortality. Our findings reveal that the mortality rates associated with AF and hypertension have markedly increased, particularly among women and non-Hispanic white populations, indicating a need for targeted interventions in these high-risk groups. Moreover, the observed regional disparities underscore the necessity for localized public health strategies that address the specific needs of different communities, a consideration that has been less emphasized in earlier research. 5. Limitation Despite our efforts to optimize the methodology and analytical procedures, several limitations of this study should be acknowledged. First, the determination of cause of death relied on ICD coding from death certificates, which may have introduced misclassification bias. Specifically, the diagnoses of atrial fibrillation (AF) or atrial flutter (AFL) were not validated by electrocardiographic or other clinical data, and attribution of AF/AFL-related mortality to hypertension may have been affected by inaccuracies in coding. Second, due to limitations in data completeness within the CDC WONDER database, we were unable to analyze mortality trends at the individual state level. Nevertheless, comparisons across different census regions revealed notable geographic disparities in mortality rates, providing meaningful insights into regional variation. Finally, our analysis lacked detailed information on other comorbidities and lifestyle-related factors, which may have exerted significant influence on AF/AFL and hypertension-related mortality. As relevant data were not available within the CDC WONDER database, we were unable to account for the potential confounding effects of socioeconomic status, healthcare accessibility, or coexisting medical conditions. 6. Conclusion In conclusion, this nationwide analysis demonstrates a marked increase in mortality related to AF/AFL and hypertension among older adults in the United States from 2001 to 2023. The burden of mortality was disproportionately higher among women, non-Hispanic White individuals, and the very elderly, while substantial geographic disparities further highlight the heterogeneous impact of these conditions across different communities. These findings reinforce the pivotal role of hypertension as a modifiable risk factor in the pathogenesis and prognosis of AF/AFL and emphasize the need for integrated prevention strategies that combine optimal blood pressure control, early arrhythmia detection, and comprehensive management of comorbidities. Future efforts should prioritize equitable healthcare delivery, improved patient adherence to therapy, and tailored interventions for vulnerable populations to mitigate the growing mortality burden associated with AF/AFL and hypertension. Abbreviations AF Atrial Fibrillation AFL Atrial Flutter HT Hypertension NCHS National Center for Health Statistics CDC WONDER Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research CMR Crude Mortality Rate AAMR Age-Adjusted Mortality Rate CI Confidence Interval APC Annual Percentage Change AAPC Average Annual Percentage Change NH Non-Hispanic STROBE Strengthening the Reporting of Observational Studies in Epidemiology Declarations Clinical trial number Not applicable. Ethics approval and consent to participate This study was exempt from institutional review board approval because it utilized publicly available, de-identified data. The CDC WONDER system is a publicly accessible service developed and maintained by the CDC, an agency of the United States federal government. The database is in the public domain and provides only aggregated, non-identifiable information ( http://wonder.cdc.gov ). Accordingly, no informed consent was required. This study was conducted in full compliance with the ethical principles outlined in the Declaration of Helsinki ( https://www.wma.net/policies-post/wma-declaration-of-helsinki/ ). Consent for publication Not Applicable because CDC WONDER is a publicly available platform. Competing interests The authors declare no competing interests. Author Contribution Hangyu Liu: Research concept and design, Collection of data, Data analysis and interpretation, Writing the article, Revision of the article.Juan Hua: Collection of data.Liang Xiong: Revision of the article.Shuanghua Zhu: Collection of data.Ziyang Ding: Collection of dataQi Chen: Research concept and design, Revision of the article, Final approval of the article. Acknowledgements Not applicable. Data Availability The dataset supporting the conclusions of this article is included in this article. The study uses the dataset from the publicly available platform of CDC WONDER at http://wonder.cdc.gov. 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19:34:09","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":84397,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7422150/v1/2feec11d322203d132424f4c.html"},{"id":92542844,"identity":"1fac0e0e-0730-4a44-ac46-18e41203a1d8","added_by":"auto","created_at":"2025-09-30 19:34:09","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":184422,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in AF/AFL and hypertension‐related mortality with stratified by sex and overall, United States, 2001–2023.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7422150/v1/5f80d10a279e17614028d9af.jpg"},{"id":92542853,"identity":"ce3dc30c-2292-459b-9729-989136817e18","added_by":"auto","created_at":"2025-09-30 19:34:10","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":180543,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in AF/AFL and hypertension‐related mortality with stratified by race/ethnicity, United States, 2001–2023.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7422150/v1/f5db37c45109b0610bbc3b36.jpg"},{"id":92542854,"identity":"80ee00f7-b45b-46e5-8664-7335f5a05206","added_by":"auto","created_at":"2025-09-30 19:34:10","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":166044,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in AF/AFL and hypertension‐related mortality with stratified by urbanization, United States, 2001–2023.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7422150/v1/c0fab300bed6ddaea74e8fee.jpg"},{"id":92542856,"identity":"1a197462-4626-4dca-979f-bfdb5d87116f","added_by":"auto","created_at":"2025-09-30 19:34:10","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":213283,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in AF/AFL and hypertension‐related mortality with stratified by census region, United States, 2001–2023.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7422150/v1/a752bc284a3223dffd40bbf3.jpg"},{"id":92542841,"identity":"8db91cb3-7a4e-4176-8b73-2d2b24d29c30","added_by":"auto","created_at":"2025-09-30 19:34:09","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":180806,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in AF/AFL and hypertension‐related mortality with stratified by Ten‐Year Age Group, United States, 2001–2023.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7422150/v1/261b92eb37f7a0c57e166a3f.jpg"},{"id":92543495,"identity":"90cb49e0-8398-4d29-a007-951fb4b89a7e","added_by":"auto","created_at":"2025-09-30 19:42:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1698452,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7422150/v1/68676c6c-2ad5-412b-b39c-bfbf574f6bbd.pdf"},{"id":92542849,"identity":"1dfd0cbc-126b-45e7-ac44-5f1301424714","added_by":"auto","created_at":"2025-09-30 19:34:09","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29001,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-7422150/v1/6a3bfd9453985c0bfa3c60c2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Trends in Atrial Fibrillation-Related Mortality Among Older Adults With hypertension in the United States, 2001–2023","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe prevalence of atrial fibrillation (AF) and atrial flutter (AFL) has risen markedly in recent decades, particularly among older adults, where these arrhythmias frequently coexist with hypertension\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. This combination substantially increases the risk of cardiovascular events and mortality, establishing AF and AFL as major public health concerns. The interaction of these conditions creates a complex clinical scenario characterized by heightened morbidity and escalating healthcare costs, underscoring the need for a clearer understanding of their epidemiology and management.\u003c/p\u003e\u003cp\u003eThe growing incidence of AF and AFL is partly attributable to population aging and the rising prevalence of hypertension. Hypertensive patients face a significantly higher risk of developing AF, with each standard deviation increase in diastolic blood pressure linked to a 37% increase in AF prevalence\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. The burden of AF and AFL is further compounded by coexisting cardiovascular risk factors such as obesity and diabetes, which are also increasing globally\u003csup\u003e[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. These trends highlight the necessity for prevention and management strategies that target both hypertension and arrhythmias to reduce overall cardiovascular morbidity and mortality.\u003c/p\u003e\u003cp\u003eDespite advances in pharmacological and catheter-based therapies, major gaps remain in the early diagnosis and management of AF and AFL. Treatment adherence is particularly challenging, and nonadherence is strongly associated with worse outcomes and increased cardiovascular events\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Improving patient education and adherence strategies is therefore essential for optimizing care.\u003c/p\u003e\u003cp\u003eThe interplay between AF/AFL and hypertension also requires careful monitoring and individualized management. Blood pressure control is critical, as uncontrolled hypertension exacerbates arrhythmia episodes and worsens outcomes. Evidence indicates that maintaining target blood pressure can significantly reduce the risk of stroke and other AF-related complications\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Thus, integrating effective blood pressure management into AF care pathways is vital to improving prognosis.\u003c/p\u003e\u003cp\u003eGiven these considerations, this study aimed to analyze long-term trends in AF/AFL-related mortality among older U.S. adults with coexisting hypertension using data from the CDC WONDER database (2001\u0026ndash;2023). We also assessed demographic and geographic variations to provide insights that may inform targeted prevention strategies and public health interventions.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Setting and Population\u003c/h2\u003e\u003cp\u003eWe utilized mortality data from the National Center for Health Statistics (NCHS), accessed via the Centers for Disease Control and Prevention\u0026rsquo;s Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) system, to examine annual mortality trends among U.S. adults aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years from 2001 to 2023. These data are updated annually based on death certificates of U.S. residents and include underlying causes of death and demographic characteristics. Using the Multiple Cause of Death (final) public-use files and International Classification of Diseases, Tenth Revision (ICD-10) codes\u0026mdash;I48 for atrial fibrillation (AF) and I10\u0026ndash;I15 for hypertension (HT)\u0026mdash;we identified death certificates listing these conditions as either the underlying or contributing cause of death. These ICD-10 codes have been employed in prior studies\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Because the data are publicly available, de-identified, and provided by a government agency, the study was exempt from institutional review board approval and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Data abstraction\u003c/h2\u003e\u003cp\u003eThe dataset included population counts, year of occurrence, place of death, demographic variables, U.S. Census region, and urban\u0026ndash;rural classification. Deaths occurred in various settings, including hospitals, homes, hospices, nursing homes, and long-term care facilities. \u0026ldquo;Demographic characteristics\u0026rdquo; encompassed sex, age, race, and ethnicity. Race and ethnicity were categorized as Hispanic or Latino, non-Hispanic (NH) White, and NH Black/African American. Other NH racial groups were excluded due to insufficient data. The source data, derived from death certificates, have been used in previous WONDER-based analyses\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eUrban\u0026ndash;rural classification followed the NCHS Urban\u0026ndash;Rural Classification Scheme for Counties: metropolitan areas included large metro areas (\u0026ge;\u0026thinsp;1\u0026nbsp;million residents) and medium/small metro areas (50,000\u0026ndash;999,999 residents); nonmetropolitan areas included micropolitan and rural counties (\u0026lt;\u0026thinsp;50,000 residents). This classification was based on the 2013 U.S. Census Bureau standards\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Geographic regions were categorized into Northeast, Midwest, South, and West according to U.S. Census Bureau definitions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Statistical Analysis\u003c/h2\u003e\u003cp\u003eTo evaluate national trends in AF/atrial flutter (AFL) and hypertension-related mortality from 2001 to 2023, we calculated crude mortality rates (CMRs) and age-adjusted mortality rates (AAMRs) per 100,000 persons. Rates were stratified by year, sex, race/ethnicity, census region, and urban\u0026ndash;rural status, and presented with 95% confidence intervals (CIs). CMRs were computed by dividing the total number of AF/AFL and hypertension-related deaths by the corresponding U.S. population for each year. AAMRs were standardized to the U.S. standard population in 2001.\u003c/p\u003e\u003cp\u003eTemporal trends were assessed using Joinpoint regression analysis (version 5.1.0; National Cancer Institute)\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. This method fits log-linear regression models to estimate the annual percentage change (APC) in AAMRs with 95% CIs. A slope significantly different from zero (two-tailed t-test) indicated a statistically significant upward or downward trend. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Tests of parallelism were used to compare trends across subgroups; a significant p-value indicated that average annual percentage change (AAPC) trends differed significantly between groups\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eBetween 2001 and 2023, a total of 77,599 deaths in U.S. adults aged 25 years and older were attributed to AF/AFL in conjunction with hypertension, comprising 27,004 deaths among men and 50,595 among women. Analyses were stratified by year, sex, race/ethnicity, urbanization level, and census region\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Overall AF/AFL and Hypertension related AAMR\u003c/h2\u003e\u003cp\u003eFrom 2001 to 2010, the national AAMR increased significantly (APC, 10.37%; 95% CI, 8.01\u0026ndash;12.79; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with continued but slower growth from 2010 to 2023 (APC, 4.98%; 95% CI, 4.21\u0026ndash;5.75; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Across the full study period, the AAMR rose from 2.77 in 2001 to 12.54 in 2023 (AAPC, 7.15%; 95% CI, 6.17\u0026ndash;8.14; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (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\u003eDemographic characteristics of deaths due to hypertension related atrial fibrillation/ flutter among all ages in the USA from 2001 to 2023.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDeaths (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003eAAMR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2001 (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2023 (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAAPC (95% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e77599 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.77 (2.59 to 2.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.54 (12.24 to 12.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.15 (6.17 to 8.14)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50595 (65.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.04 (2.81 to 3.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.50 (12.11 to 12.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.63 (5.66 to 7.61)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27004 (34.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.11 (1.85 to 2.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.35 (11.88 to 12.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.41 (7.28 to 9.54)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCensus Region\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNortheast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13065 (16.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.83 (2.46 to 3.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.43 (8.83 to 10.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.81 (4.66 to 6.98)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMidwest\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18726 (24.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.68 (2.34 to 3.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.72 (13.03 to 14.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.68 (6.58 to 8.80)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27004 (34.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.67 (2.38 to 2.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.12 (12.61 to 13.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.50 (6.24 to 8.77)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWest\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18804 (24.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.86 (2.46 to 3.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.15 (12.49 to 13.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.62 (6.31 to 8.93)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHispanic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3052 (3.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.69 (1.09 to 2.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.62 (5.86 to 7.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.61 (5.55 to 7.69)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNH Black\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4742 (6.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.30 (1.76 to 2.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.91 (9.00 to 10.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.05 (5.29 to 6.82)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNH White\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67774 (87.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.82 (2.63 to 3.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.08 (13.71 to 14.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.55 (6.53 to 8.56)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrbanization\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetropolitan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46999 (60.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.62 (2.43 to 2.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.59 (9.30 to 9.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.08 (6.06 to 8.11)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonmetropolitan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11797 (15.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.23 (2.80 to 3.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.76 (12.01 to 13.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.71 (6.51 to 8.94)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e65\u0026ndash;74 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8165 (10.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.48 (0.38 to 0.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.40 (2.23 to 2.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.39 (6.76 to 8.03)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e75\u0026ndash;84 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21498 (27.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.69 (2.41 to 2.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.40 (9.94 to 10.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.18 (5.12 to 7.26)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e85\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47936 (61.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.64 (11.58 to 13.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61.90 (59.95 to 63.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.55 (6.55 to 8.56)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eStatistically significant AAPCs are denoted by an asterisk (*). \u003csup\u003e1\u003c/sup\u003eFor the urbanization section, the 2023 AAMR data point was substituted with the 2020 value due to unavailability; the corresponding AAPC was calculated from 2001 through 2023. \u003csup\u003e2\u003c/sup\u003eWithin the Age group categories, AAMRs presented are based on crude mortality rates; the AAPC values were calculated using these crude mortality rates. AAMR, age-adjusted mortality rate; CI, confidence interval; AAPC, average annual percent change; NH, non-Hispanic.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWomen consistently exhibited higher AAMRs (mean 10.70) than men (mean 5.24). Among men, the AAMR surged from 2001 to 2010 (APC 11.21; 95% CI, 8.45\u0026ndash;14.03; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and continued to increase from 2010 to 2023 (APC 6.51; 95% CI, 5.71\u0026ndash;7.31; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with an overall AAPC of 8.41 (95% CI, 7.28\u0026ndash;9.54; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For women, the AAMR rose significantly from 2001 to 2010 (APC 10.24; 95% CI, 7.92\u0026ndash;12.61; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and, although growth slowed between 2010 and 2023 (APC 4.20; 95% CI, 3.42\u0026ndash;5.00; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the overall AAPC remained significant at 6.63 (95% CI, 5.66\u0026ndash;7.61; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.2 AF/AFL and Hypertension related AAMR stratified by race/ethnicity\u003c/h2\u003e\u003cp\u003eIn terms of race/ethnicity, NH White individuals had the highest AAMR, followed by NH Black or African American individuals, and Hispanic or Latino individuals. Due to missing data, other non-Hispanic were not included in this study. The AAMR for NH White individuals significantly increased from 2001 to 2010 (APC 10.76; 95% CI: 8.33\u0026ndash;13.25, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and although the growth rate slowed from 2010 to 2023, it still exhibited a significant upward trend (APC 5.37; 95% CI 4.58\u0026ndash;6.17). The AAMR for NH Black or African American individuals also showed a steady upward trend, rising from 2.30 in 2001 to 9.91 in 2023 (APC 6.05; 95% CI 5.29\u0026ndash;6.82, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The AAMR for Hispanic or Latino individuals sharply increased from 2001 to 2016 (APC 8.51; 95% CI 7.13\u0026ndash;9.91, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and while the rate of increase slowed from 2010 to 2023, it remained statistically significant (APC 2.66; 95% CI 0.67\u0026ndash;4.69, p\u0026thinsp;=\u0026thinsp;0.011) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOverall, the NH White group exhibited the greatest increase (AAPC 7.55; 95% CI: 6.53\u0026ndash;8.56; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), followed by Hispanic or Latino individuals (AAPC 6.61; 95% CI: 5.55\u0026ndash;7.69; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and NH Black or African American individuals (AAPC 6.05; 95% CI: 5.29\u0026ndash;6.82; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.3 AF/AFL and Hypertension related AAMR stratified by urbanization\u003c/h2\u003e\u003cp\u003eFrom 2001 to 2020, metropolitan areas consistently had higher AAMRs (mean 7.70) than nonmetropolitan areas (mean 6.75). In metropolitan areas, the AAMR rose markedly from 2001 to 2011 (APC 10.14; 95% CI, 8.33\u0026ndash;11.98; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and more slowly from 2011 to 2020 (APC 3.78; 95% CI, 2.53\u0026ndash;5.04; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Nonmetropolitan areas showed a similar pattern, with a significant increase from 2001 to 2012 (APC 10.06; 95% CI, 8.19\u0026ndash;11.96; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and a slower rise from 2011 to 2020 (APC 4.58; 95% CI, 2.80\u0026ndash;6.38; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The AAPC for metropolitan areas reached 7.08% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas the increase in nonmetropolitan areas was slightly less steep. CDC mortality data for 2021\u0026ndash;2022 were unavailable (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplementary table 2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.4 AF/AFL and Hypertension related AAMR stratified by census region\u003c/h2\u003e\u003cp\u003eFrom 2001 to 2023, all census regions experienced significant increases in AAMRs. In the Northeast, rates rose from 2.83 (95% CI, 2.46\u0026ndash;3.20) to 9.43 (95% CI, 8.83\u0026ndash;10.04) (AAPC, 5.81%; 95% CI, 4.66\u0026ndash;6.98; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the Midwest, rates increased from 2.68 (95% CI, 2.34\u0026ndash;3.03) to 13.72 (95% CI, 13.03\u0026ndash;14.41) (AAPC, 7.68%; 95% CI, 6.58\u0026ndash;8.80; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the South, rates rose from 2.67 (95% CI, 2.38\u0026ndash;2.96) to 13.12 (95% CI, 12.61\u0026ndash;13.63) (AAPC, 7.50%; 95% CI, 6.24\u0026ndash;8.77; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the West, rates increased from 2.86 (95% CI, 2.46\u0026ndash;3.26) to 13.15 (95% CI, 12.49\u0026ndash;13.81) (AAPC, 7.62%; 95% CI, 6.31\u0026ndash;8.93; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTemporal patterns varied: the Northeast experienced a rise from 2001 to 2011 (APC, 8.76%; 95% CI, 6.38\u0026ndash;11.20; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and slower growth thereafter (APC, 3.41%; 95% CI, 2.27\u0026ndash;4.57; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The Midwest rose from 2001 to 2009 (APC, 11.50%; 95% CI, 8.45\u0026ndash;14.63; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and from 2009 to 2023 (APC, 5.56%; 95% CI, 4.81\u0026ndash;6.32; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similar decelerations were observed in the South (2001\u0026ndash;2010 APC, 9.68%; 2010\u0026ndash;2023 APC, 6.01%) and West (2001\u0026ndash;2008 APC, 14.98%; 2008\u0026ndash;2023 APC, 4.34%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Supplementary table 3).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.5 AF/AFL and Hypertension related AAMR stratified by Ten-Year Age Group\u003c/h2\u003e\u003cp\u003eAmong older adults with AF/AFL and hypertension, CMRs increased sharply with age and demonstrated significant temporal growth across all age strata. Rates were lowest and increased most gradually in those aged 65\u0026ndash;74 years. In contrast, individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;85 years exhibited markedly higher CMRs, with a significant overall upward trend (AAPC 7.55; 95% CI, 6.55\u0026ndash;8.56; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe increasing prevalence of atrial fibrillation (AF) and atrial flutter (AFL), particularly in aging populations, has positioned these conditions as significant public health concerns globally. AF/AFL is associated with heightened risks of thromboembolic events, heart failure, and mortality, which collectively contribute to a substantial burden on healthcare systems. This is especially pronounced in older adults, where the coexistence of hypertension\u0026mdash;a prevalent condition in this demographic\u0026mdash;exacerbates the risks associated with AF/AFL. Hypertension is widely recognized as one of the most important and clinically modifiable risk factors for atrial fibrillation (AF). Large-scale epidemiological studies have demonstrated that more than 70% of patients with AF present concomitant hypertension\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e, thereby highlighting the close pathophysiological association between the two conditions. Moreover, compared with normotensive individuals, patients with hypertension exhibit a 73% higher risk of developing AF\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, a finding that may be largely attributed to hypertension-induced atrial structural remodeling, electrical remodeling, and alterations in autonomic regulation. In addition, longitudinal cohort studies have reported that a history of hypertension accounts for approximately 24% of the attributable risk of AF incidence\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, underscoring the pivotal role of hypertension in the etiology of AF. Importantly, this relationship appears to follow a non-linear, curvilinear pattern rather than a simple linear association: both patients with short-term hypertension and those with long-standing hypertension demonstrate a significantly higher risk of AF compared with individuals with intermediate-duration hypertension\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. These observations suggest that the temporal dynamics of hypertension exposure may exert complex influences on atrial pathophysiology and ultimately on the risk of AF development.\u003c/p\u003e\u003cp\u003eBeyond epidemiological associations, hypertension promotes the initiation and progression of AF through multiple interrelated pathophysiological mechanisms. Chronic elevation of blood pressure leads to hemodynamic alterations and activation of neurohormonal pathways, which induce diffuse atrial structural and electrical remodeling, thereby increasing atrial electrical instability\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Furthermore, persistent inflammatory responses, alterations in hormonal homeostasis, and autonomic nervous system dysregulation act synergistically to enhance atrial electrophysiological vulnerability. Left ventricular hypertrophy and systolic or diastolic dysfunction, which are frequently observed in hypertensive individuals, serve as important mediators by elevating left atrial pressure load and facilitating atrial remodeling. Notably, an elevated risk of AF has also been documented in individuals with prehypertension as well as in those with reduced aortic compliance and increased arterial stiffness. Taken together, these findings indicate that the pro-arrhythmic effects of hypertension extend beyond overt hypertension and may emerge as early as the preclinical stages of cardiovascular dysfunction\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe coexistence of hypertension and AF also has profound implications for clinical outcomes. Patients with both conditions exhibit markedly higher risks of stroke and major bleeding, reflecting the dual burden of thromboembolic complications and anticoagulation-related adverse events\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. In addition, all-cause mortality is significantly higher in hypertensive patients with AF than in those with AF alone, particularly among individuals with advanced target organ damage such as renal impairment, heart failure, or cerebrovascular disease\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Proteinuria, as an early marker of hypertensive end-organ injury, not only reflects renal microvascular damage but also independently increases the risk of AF\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e, further underscoring the interplay between systemic organ involvement and arrhythmogenesis. Moreover, in patients with pulmonary hypertension, the onset of AF often signals disease progression and is strongly associated with adverse prognosis\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Collectively, these findings emphasize that hypertension and AF interact synergistically, accelerating disease progression while simultaneously amplifying the risk of adverse outcomes, thereby posing a significant threat to long-term prognosis. As such, understanding the epidemiology and associated risk factors of AF/AFL, particularly in the context of hypertension, is crucial for developing effective prevention and management strategies aimed at reducing morbidity and mortality in this high-risk population.\u003c/p\u003e\u003cp\u003eThis study aims to systematically analyze the trends in mortality associated with AF/AFL and hypertension among older adults in the United States over the past two decades. Using data from the CDC WONDER database, we will examine mortality rates, specifically focusing on demographic factors such as age, sex, race, and geographic location. Previous research has highlighted significant disparities in mortality rates associated with these conditions, with evidence suggesting that females and certain racial groups experience higher mortality rates\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Furthermore, the study will explore the implications of these findings for public health interventions and clinical practice, aiming to provide insights that could inform tailored strategies for managing AF/AFL and hypertension in older adults. Through a comprehensive analysis of long-term mortality trends, we seek to elucidate the evolving burden of these conditions and their impact on the aging population, thereby contributing to the ongoing discourse on cardiovascular health management in the United States\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe innovation of this study lies in its comprehensive approach to analyzing the mortality trends associated with atrial fibrillation (AF) and hypertension in the elderly population of the United States. By leveraging the extensive CDC WONDER database, we have filled a critical knowledge gap regarding the intersection of these two prevalent cardiovascular conditions over a significant time period (2001 to 2023). Previous studies predominantly focused on either AF or hypertension in isolation or assessed trends over shorter durations, which limited the understanding of their combined impact on mortality. Our findings reveal that the mortality rates associated with AF and hypertension have markedly increased, particularly among women and non-Hispanic white populations, indicating a need for targeted interventions in these high-risk groups. Moreover, the observed regional disparities underscore the necessity for localized public health strategies that address the specific needs of different communities, a consideration that has been less emphasized in earlier research.\u003c/p\u003e"},{"header":"5. Limitation","content":"\u003cp\u003eDespite our efforts to optimize the methodology and analytical procedures, several limitations of this study should be acknowledged. First, the determination of cause of death relied on ICD coding from death certificates, which may have introduced misclassification bias. Specifically, the diagnoses of atrial fibrillation (AF) or atrial flutter (AFL) were not validated by electrocardiographic or other clinical data, and attribution of AF/AFL-related mortality to hypertension may have been affected by inaccuracies in coding. Second, due to limitations in data completeness within the CDC WONDER database, we were unable to analyze mortality trends at the individual state level. Nevertheless, comparisons across different census regions revealed notable geographic disparities in mortality rates, providing meaningful insights into regional variation. Finally, our analysis lacked detailed information on other comorbidities and lifestyle-related factors, which may have exerted significant influence on AF/AFL and hypertension-related mortality. As relevant data were not available within the CDC WONDER database, we were unable to account for the potential confounding effects of socioeconomic status, healthcare accessibility, or coexisting medical conditions.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eIn conclusion, this nationwide analysis demonstrates a marked increase in mortality related to AF/AFL and hypertension among older adults in the United States from 2001 to 2023. The burden of mortality was disproportionately higher among women, non-Hispanic White individuals, and the very elderly, while substantial geographic disparities further highlight the heterogeneous impact of these conditions across different communities. These findings reinforce the pivotal role of hypertension as a modifiable risk factor in the pathogenesis and prognosis of AF/AFL and emphasize the need for integrated prevention strategies that combine optimal blood pressure control, early arrhythmia detection, and comprehensive management of comorbidities. Future efforts should prioritize equitable healthcare delivery, improved patient adherence to therapy, and tailored interventions for vulnerable populations to mitigate the growing mortality burden associated with AF/AFL and hypertension.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAtrial Fibrillation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAFL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAtrial Flutter\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNCHS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNational Center for Health Statistics\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCDC WONDER\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCenters for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCrude Mortality Rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAAMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAge-Adjusted Mortality Rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAPC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAnnual Percentage Change\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAAPC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAverage Annual Percentage Change\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNon-Hispanic\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSTROBE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStrengthening the Reporting of Observational Studies in Epidemiology\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003eThis study was exempt from institutional review board approval because it utilized publicly available, de-identified data. The CDC WONDER system is a publicly accessible service developed and maintained by the CDC, an agency of the United States federal government. The database is in the public domain and provides only aggregated, non-identifiable information (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://wonder.cdc.gov\u003c/span\u003e\u003cspan address=\"http://wonder.cdc.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Accordingly, no informed consent was required. This study was conducted in full compliance with the ethical principles outlined in the Declaration of Helsinki (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.wma.net/policies-post/wma-declaration-of-helsinki/\u003c/span\u003e\u003cspan address=\"https://www.wma.net/policies-post/wma-declaration-of-helsinki/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot Applicable because CDC WONDER is a publicly available platform.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eHangyu Liu: Research concept and design, Collection of data, Data analysis and interpretation, Writing the article, Revision of the article.Juan Hua: Collection of data.Liang Xiong: Revision of the article.Shuanghua Zhu: Collection of data.Ziyang Ding: Collection of dataQi Chen: Research concept and design, Revision of the article, Final approval of the article.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe dataset supporting the conclusions of this article is included in this article. The study uses the dataset from the publicly available platform of CDC WONDER at http://wonder.cdc.gov.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlmeida ED, Guimar\u0026atilde;es RB, Stephan LS, et al. Clinical Differences between Subtypes of Atrial Fibrillation and Flutter: Cross-Sectional Registry of 407 Patients. Arq Bras Cardiol. 2015;105(1):3\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang C, Du Z, Ye N, Liu S, Geng D, Sun Y. Prevalence and prognosis of atrial fibrillation in a hypertensive population: A prospective cohort study. J Clin Hypertens (Greenwich). 2023;25(4):335\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang X, Chen Y, Hu W, Lu S, Yu H, Sun Y. Global burden of atrial fibrillation/atrial flutter and its attributable risk factors in adolescents and young adults, 1990\u0026ndash;2021: insights from the global burden of disease study. Ann Med. 2025;57(1):2543524.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFoy AJ, Mandrola J, Liu G, Naccarelli GV. Relation of Obesity to New-Onset Atrial Fibrillation and Atrial Flutter in Adults. Am J Cardiol. 2018;121(9):1072\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMovahed MR, Hashemzadeh M, Jamal MM. Diabetes mellitus is a strong, independent risk for atrial fibrillation and flutter in addition to other cardiovascular disease. Int J Cardiol. 2005;105(3):315\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIbrahim S, Nurmohamed NS, Collard D, et al. Association Between Self-Rated Medication Adherence and Adverse Cardiovascular Outcomes in Patients With Hypertension. J Am Heart Assoc. 2023;12(22):e031418.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParcha V, Patel N, Kalra R, et al. Incidence and Implications of Atrial Fibrillation/Flutter in Hypertension: Insights From the SPRINT Trial. Hypertension. 2020;75(6):1483\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRethy L, Shah NS, Paparello JJ, Lloyd-Jones DM, Khan SS. Trends in Hypertension-Related Cardiovascular Mortality in the United States, 2000 to 2018. Hypertension. 2020;76(3):e23\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGhajar A, Essa M, DeLago A, et al. Atrial fibrillation/atrial flutter related mortality trends in the US population 2010\u0026ndash;2020: Regional, racial, sex variations. Pacing Clin Electrophysiol. 2023;46(6):519\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHassan IN, Ibrahim M, Yaqub S, et al. Trends in Atrial Fibrillation-Related Mortality Among Older Adults With Obstructive Sleep Apnea in the United States, 1999\u0026ndash;2020. Clin Cardiol. 2025;48(7):e70178.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIngram DD, Franco SJ. 2013 NCHS Urban-Rural Classification Scheme for Counties. Vital Health Stat 2. 2014. (166): 1\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJoinpoint Regression Program. Version 5.1.0.0. April. Statistical Research and Applications Branch, National Cancer Institute; 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim HJ, Fay MP, Yu B, Barrett MJ, Feuer EJ. Comparability of segmented line regression models. Biometrics. 2004;60(4):1005\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMiddeldorp ME, Ariyaratnam JP, Kamsani SH, Albert CM, Sanders P. Hypertension and atrial fibrillation. J Hypertens. 2022;40(12):2337\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNiiranen TJ, Schnabel RB, Schutte AE, et al. Hypertension and Atrial Fibrillation: A Frontier Review From the AF-SCREEN International Collaboration. Circulation. 2025;151(12):863\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGawałko M, Linz D. Atrial Fibrillation Detection and Management in Hypertension. Hypertension. 2023;80(3):523\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang W, Chen Y, Hu LX, et al. New-onset hypertension as a contributing factor to the incidence of atrial fibrillation in the elderly. Hypertens Res. 2024;47(6):1490\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWalker M, Patel P, Kwon O, Koene RJ, Duprez DA, Kwon Y. Atrial Fibrillation and Hypertension: Quo Vadis. Curr Hypertens Rev. 2022;18(1):39\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarskamp RE, Lucassen W, Lopes RD, Himmelreich J, Parati G, Weert H. Risk of stroke and bleeding in relation to hypertension in anticoagulated patients with atrial fibrillation: a meta-analysis of randomised controlled trials. Acta Cardiol. 2022;77(3):191\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChun MY, Chae W, Seo SW, et al. Effects of risk factors on the development and mortality of early- and late-onset dementia: an 11-year longitudinal nationwide population-based cohort study in South Korea. Alzheimers Res Ther. 2024;16(1):92.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark YJ, Yang PS, Yu HT, et al. Association of proteinuria and hypertension with incident atrial fibrillation in an elderly population: nationwide data from a community-based elderly cohort. J Hypertens. 2022;40(1):128\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAggarwal K, Valleru PS, Anamika F, et al. Unraveling the Complex Relationship-Atrial Fibrillation and Pulmonary Hypertension. Curr Cardiol Rep. 2024;26(9):885\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang XH, Zhang ZZ, Ou Y, et al. High-Salt Diet Inhibits the Expression of Bmal1 and Promotes Atrial Fibrosis and Vulnerability to Atrial Fibrillation in Dahl Salt-Sensitive Rats. Am J Hypertens. 2024;37(9):726\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJin Y, Wang K, Xiao B, et al. Global burden of atrial fibrillation/flutter due to high systolic blood pressure from 1990 to 2019: estimates from the global burden of disease study 2019. J Clin Hypertens (Greenwich). 2022;24(11):1461\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7422150/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7422150/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe coexistence of atrial fibrillation (AF) or atrial flutter (AFL) and hypertension represents a major public health challenge, particularly among older adults, due to its strong association with adverse cardiovascular outcomes and mortality.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe conducted a nationwide, population-based study using mortality data from the Centers for Disease Control and Prevention\u0026rsquo;s Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) system between 2001 and 2023. Deaths among U.S. adults aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years with AF/AFL and hypertension were identified using ICD-10 codes. Crude mortality rates (CMRs) and age-adjusted mortality rates (AAMRs) were calculated and stratified by sex, race/ethnicity, census region, and urban\u0026ndash;rural classification. Temporal trends were assessed using Joinpoint regression analysis to estimate annual percentage change (APC) and average annual percentage change (AAPC).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eFrom 2001 to 2023, 77,599 AF/AFL-related deaths were attributed to concomitant hypertension, with a disproportionate burden observed among women (65%) compared to men (35%). Overall, the AAMR increased from 2.77 per 100,000 in 2001 to 12.54 in 2023 (AAPC 7.15%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Women consistently exhibited higher mortality rates than men, and non-Hispanic White individuals experienced the steepest rise in AAMRs compared with non-Hispanic Black and Hispanic populations. Geographic disparities were also evident, with the Midwest and South showing the highest increases. Older adults aged\u0026thinsp;\u0026ge;\u0026thinsp;85 years demonstrated the highest mortality rates across all subgroups.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eMortality related to AF/AFL in the presence of hypertension has risen substantially in the United States over the past two decades, with notable disparities by sex, race/ethnicity, age, and region. These findings underscore the urgent need for targeted public health interventions and clinical strategies to improve risk factor control, enhance early detection, and address inequities in care among high-risk populations.\u003c/p\u003e","manuscriptTitle":"Trends in Atrial Fibrillation-Related Mortality Among Older Adults With hypertension in the United States, 2001–2023","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-30 19:33:31","doi":"10.21203/rs.3.rs-7422150/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-10-08T01:43:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315266273242951808771082572480071296958","date":"2025-09-27T21:44:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-24T11:00:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"191479878091934527791160608484876008436","date":"2025-09-18T13:16:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"249128484920452696284803485630241463344","date":"2025-09-18T13:08:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-18T12:31:14+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-26T06:00:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-25T03:34:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-25T03:33:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2025-08-21T04:24:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"76f2ff48-1388-46b7-92df-1237a268b60f","owner":[],"postedDate":"September 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-30T19:33:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-30 19:33:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7422150","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7422150","identity":"rs-7422150","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}