Rising Mortality from Atrial Fibrillation and COPD Comorbidity in the United States, 1999–2024: Implications for Cardiopulmonary Care in South Asia

Rising Mortality from Atrial Fibrillation and COPD Comorbidity in the United States, 1999–2024: Implications for Cardiopulmonary Care in South Asia | 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 Rising Mortality from Atrial Fibrillation and COPD Comorbidity in the United States, 1999–2024: Implications for Cardiopulmonary Care in South Asia Ammad Uddin, Muhammad Salik Uddin, Abbeha Talib, S M Aleem Hussain, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9064349/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Atrial fibrillation and chronic obstructive pulmonary disease COPD frequently coexist, yet national mortality patterns of this high-risk dyad are not clearly understood. We assessed long-range patterns and inequities of atrial fibrillation-related mortality among adults with COPD in the United States. Methods Using CDC WONDER Multiple Cause of Death files (1999–2024), we identified decedents of ≥ 25 years with atrial fibrillation (ICD-10 I48) and COPD (J41–J44) as contributing or underlying causes. We calculated age-adjusted mortality rates (AAMR) per 100,000 (2000 U.S. standard) and estimated Annual Percent Change (APC) and Average APC (AAPC) using Joinpoint Regression, stratifying on sex, race/ethnicity, census region/state, urbanicity, and place of death. Results There were 577,367 atrial fibrillation-COPD deaths. National AAMR increased from 5.56 (1999) to 13.96 (2024) (AAPC + 3.73%, 95% CI + 3.53 to + 3.91; p < 0.000001), with a rise through 2018 (APC + 4.08%) and a surge to 2021 (APC + 6.76%), followed by a nonsignificant decline thereafter (APC − 1.36%). Men had higher AAMR than women (overall 12.27 vs 7.64), but women’s rates rose faster (AAPC + 4.01% vs + 3.11%). AAMR was highest in White individuals (10.92), while the steepest increase occurred in Black individuals (AAPC + 5.11%). The Midwest had the highest regional AAMR (10.23) and the Northeast the lowest (8.31). Non-metropolitan areas exceeded metropolitan areas (10.68 vs 8.27; AAPC + 5.24% vs + 4.10%). Most deaths occurred in medical facilities (40.17%), followed by home (27.97%) and nursing homes/long-term care (22.64%). Conclusion Mortality from atrial fibrillation-COPD increased dramatically over 25 years, with more rapid expansion for women, non-Hispanic blacks, and people from non-metropolitan areas. These results argue for prevention aimed at selected subgroups, combined cardiopulmonary care, broader rural access, and earlier palliative care to narrow inequities and optimize outcome. Atrial Fibrillation Chronic Obstructive Pulmonary Disease Mortality CDC WONDER 1. INTRODUCTION Atrial fibrillation (AF), a common and increasingly deadly form of arrhythmia, accounted for a significant mortality burden in 2021, appearing on 232,030 death certificates across the United States (U.S.) and serving as the underlying cause in 28,037 deaths prevalence models predict that the number of affected individuals will reach several million in the decades ahead ( 1 , 2 ). The economic footprint of AF is substantial; recent syntheses estimate large per-patient and population costs and identify AF as a major driver of cardiovascular healthcare utilization and spending ( 3 ). Chronic obstructive pulmonary disease (COPD) likewise remains a leading cause of death in the U.S.: national data report more than 130,000 annual deaths from chronic lower respiratory diseases and persistently high morbidity ( 4 ). COPD imposes large direct and indirect costs both nationally and globally, and systematic reviews and economic models document substantial health-system and productivity losses that continue to rise ( 5 , 6 ). AF and COPD commonly co-exist COPD confers a markedly elevated risk of AF, with meta-analyses demonstrating approximately a 1.7–2.2-fold increase in AF incidence among individuals with COPD ( 7 ). Patients with both conditions experience worse clinical trajectories, including more frequent hospitalization, higher short-term and long-term mortality, and greater resource use compared with patients who have either condition alone ( 7 , 8 ). Shared and additive risk factors—advancing age, tobacco exposure, obesity, hypertension, diabetes, and systemic inflammation—concentrate vulnerability for both pulmonary and atrial disease ( 1 , 4 , 7 ). Biologic plausibility for the COPD–AF link rests on intersecting mechanisms, including chronic systemic inflammation, intermittent or sustained hypoxemia, oxidative stress, autonomic imbalance, pulmonary hypertension with atrial stretch, and medication effects (for example, β2-agonists) that alter atrial electrophysiology ( 6 , 8 ). Amid globally rising burdens of both atrial fibrillation and COPD—driven by aging populations, persistent tobacco use, and increasing exposure to biomass fuel and air pollution in rapidly urbanizing regions such as South Asia—the need for comprehensive mortality trend analyses is urgent ( 2 , 3 , 5 , 6 , 9 ). Given substantial projected cardiovascular costs through 2050 and the CDC’s robust surveillance datasets, this retrospective analysis of U.S. trends from 1999–2024 is timely. It quantifies comorbidity-associated mortality patterns and demographic disparities, providing insights that may inform prevention, resource allocation, and integrated cardiorespiratory care strategies both in the United States and in other settings facing similar epidemiological transitions. 2. METHODS 2.1. Population and Study Design Mortality data related to AF and COPD were extracted from the CDC WONDER database using the International Classification of Diseases, 10th Revision (ICD-10) ( 9 ). The CDC WONDER database is based on death certificates and is therefore deemed public data. As a result, no Institutional Review Board approval is required. In this study, the Multiple Cause of Death Public Use Record was used to select persons whose death certificate listed AF or COPD as the underlying or contributing cause of death from 1999 to 2024. AF is coded as I48 under the ICD-10 classification system ( 10 ). COPD mortality is coded as J41, J42, J43, and J44 under the ICD-10 classification system ( 11 – 13 ). This paper is written following the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist for reporting( 14 ). 2.2. Data Abstraction The data extracted includes the population, year, and other demographic factors, such as sex, race, level of urbanization, state, census region, and place of death, for the period 1999 to 2024. Sex includes male and female. Racial categories include Hispanic or Latino, non-Hispanic Black or African American, non-Hispanic White, and non-Hispanic other. The population includes urban (large metropolitan area and medium/small metropolitan area) and rural (populations of < 50,000) counties, as classified by the 2013 US Census classification ( 15 ). This includes the use of data from all 50 states. Regions used were Northeast, Midwest, South, and West, as classified by the US Census Bureau. 2.3. Statistical Analysis Age-adjusted mortality rates (AAMRs) per 100,000 population for 1999–2024 were calculated to assess the mortality trends related to Atrial Fibrillation (AF) and Chronic Obstructive Pulmonary Disease (COPD). The AAMRs were calculated after standardizing the deaths due to AF and COPD to the year 2000 United States population, and 95% confidence intervals (CIs) were calculated ( 16 ). The AAMRs were used to analyze mortality patterns across various demographic classifications. The trends in AAMR were determined using the Joinpoint Regression Program (Joinpoint Version 5.2.0, National Cancer Institute). The AAMRs were then used to analyze the mortality trends in different diverse populations. The trends were analyzed using the Joinpoint Regression Program (Joinpoint Version 5.2.0, National Cancer Institute) ( 17 ), to calculate the annual percentage changes (APCs) in mortality rates, and 95% CIs were calculated. The APCs were found to be either increasing or decreasing based on statistical significance, where P < 0.05. To calculate the average mortality trend from 1999 to 2024, average annual percentage change (AAPC) and 95% CIs were calculated as the weighted mean of APCs. 3. RESULTS Between 1999 and 2024, a total of 577,367 adults with Atrial Fibrillation in the United States had Chronic Obstructive Pulmonary Disease-related mortality. Most of these deaths occurred in medical facilities (40.17%), followed by 27.97% at the decedents' homes, 22.64% in nursing homes/long-term care facilities, 5.63% in hospice facilities, and the fewest deaths occurred at other locations (3.59%). (Supplemental Table 1, 2) 3.1. Annual Trends There was a significant increase in the AAMR for Atrial Fibrillation in individuals with Chronic Obstructive Pulmonary Disease, rising from 5.56 (95% CI: 5.45 to 5.67) in 1999 to 13.96 (95% CI: 13.82 to 14.10) in 2024. This represents an Average Annual Percentage Change (AAPC) of + 3.73 (95% CI: +3.53 to + 3.91, p-value = 0.01). Notably, the AAMR experienced a substantial increase from 5.56 (95% CI: 5.45 to 5.67) in 1999 to 11.84 (95% CI: 11.71 to 11.97) in 2018 (APC: +4.08; 95% CI: +3.42 to + 4.33, p-value = 0.01), followed by a more moderate increase to 14.39 (95% CI: 14.24 to 14.54) in 2021 (APC: +6.76; 95% CI: +4.45 to + 7.81, p-value = 0.01). After 2021, there was a decrease in AAMR to 13.96 (95% CI: 13.82 to 14.10) in 2024 (APC: -1.36; 95% CI: -3.56 to 0.31, p-value = 0.08). (Supplemental Table 1, 3; Supplementary Fig. 1) 3.2. Sex Trends A significant gender disparity was observed in AAMRs, with adult men consistently showing higher AAMRs than adult women [ Mean AAMR for men: 12.27 (95% CI: 12.04 to 12.50) vs. 7.64 (95% CI: 7.49 to 7.79) for women]. Both men and women experienced an increase in AAMRs from 1999 to 2024, with the increase being more pronounced in women (Men: Average Annual Percentage Change (AAPC): +3.11, 95% CI: +2.88 to + 3.44, p-value = 0.01; Women: AAPC: +4.01, 95% CI: +3.79 to + 4.21, p-value = 0.01). In particular, the AAMR for adult men exhibited a rise from 7.99 (95% CI: 7.76 to 8.21) in 1999 to 10.11 (95% CI: 9.89 to 10.33) in 2009 (APC: +2.72, 95% CI: -0.13 to + 6.34, p-value = 0.05), followed by a significant increase to 14.88 (95% CI: 14.64 to 15.11) by 2018 (APC: +4.11, 95% CI: +1.57 to + 4.98, p-value = 0.01). Post 2018, AAMR experienced a substantial increase to 18.20 (95% CI: 17.94 to 18.46) in 2021 (APC: +6.65, 95% CI: +4.48 to + 7.87, p-value = 0.01), followed by a decrease to 17.44 (95% CI: 17.20 to 17.68) in 2024 (APC: -1.95, 95% CI: -4.10 to -0.34, p-value = 0.03). Similarly, the AAMR for adult women increased substantially from 4.18 (95% CI: 4.06 to 4.30) in 1999 to 11.53 (95% CI: 11.35 to 11.70) in 2021 (APC: +4.51, 95% CI: +4.35 to + 4.76, p-value = 0.01), followed by a non-significant increase to 11.32 (95% CI: 11.16 to 11.49) by 2024 (APC: +0.42, 95% CI: -3.12 to + 2.51, p-value = 0.56). (Supplemental Table 1, 4; Supplementary Fig. 1) 3.3. Race Trends Significant variability in mortalities was found among different racial/ethnic groups. The non-Hispanic White population exhibited the highest mean AAMR at 10.92 (95% CI: 10.77 to 11.07), followed by the non-Hispanic Black or African American population at 4.73 (95% CI: 4.43 to 5.04). Comparatively, the Hispanic or Latino population had a rate of 3.43 (95% CI: 3.13 to 3.74), and the Non-Hispanic Other populations had an AAMR of 3.26 (95% CI: 2.88 to 3.65). All racial and ethnic groups showed notable increases in AAMRs from 1999 to 2024, with the most noticeable increase observed in the Non-Hispanic Blacks [Black: AAPC: +5.11, 95% CI: +4.77 to + 5.48, p-value = 0.01; Non-Hispanic Whites: AAPC: +4.10, CI: +3.92 to + 4.20, p-value = 0.01; Hispanics: AAPC: +3.41, CI: +2.63 to + 4.96, p-value = 0.01; Non-Hispanic Other populations: AAPC: +2.72, CI: +2.32 to + 3.34, p-value = 0.01]. (Supplemental Table 1, 5; Supplementary Fig. 2) 3.4. Geographic analysis 3.4.1. Census Region Notable difference in mortality rates was observed among census regions of the U.S. With the highest AAMRs recorded in the Midwest (AAMR: 10.23; 95% CI: 9.96 to 10.51), followed by the West (AAMR: 9.81; 95% CI: 9.53 to 10.09), the South (AAMR: 9.50; 95% CI: 9.29 to 9.71), and the least in Northeast (AAMR: 8.31; 95% CI: 8.04 to 8.58). (Supplemental Table 6; Supplementary Fig. 3) 3.4.2. Urbanization Non-metropolitan areas showed slightly higher AAMRs than metropolitan areas, with overall AAMRs of 10.68 (95% CI: 10.36 to 11.00) and 8.27 (95% CI: 8.13 to 8.40), respectively. Both metropolitan and non-metropolitan areas experienced a significant increase in AAMRs from 1999 to 2024, with a more significant increase observed in non-metropolitan areas [Metropolitan: AAPC: +4.10, (95% CI: +3.82 to + 4.28) (p-value = 0.01); Non-metropolitan: AAPC: +5.24, (95% CI: +4.99 to + 5.56) (p-value = 0.01)]. (Supplemental Table 7; Supplementary Fig. 4) 3.4.3. States AAMRs varied across states, with rates ranging from as low as 4.29 (95% CI: 3.85 to 4.74) in the District of Columbia to 9.32 (95% CI: 9.23 to 9.40) in California. States in the top 90th percentile, including Oklahoma, Oregon, Rhode Island, Vermont, West Virginia, and Wyoming, exhibited AAMRs more than double compared to states in the lower 10th percentile, such as the District of Columbia, Georgia, Hawaii, Louisiana, Nevada, and Utah. (Supplemental Table 8; Supplementary Fig. 5) 4. DISCUSSION This study provides a comprehensive analysis of mortality related to the comorbidity of AF and COPD among U.S. adults from 1999 to 2024, elucidating crucial temporal trends and demographic disparities. Our findings reveal a substantial and concerning escalation in the age-adjusted mortality rate (AAMR), which increased by nearly 150% over the 25-year period, with a particularly sharp acceleration from 2018 to 2021. While a majority of these deaths occurred in a medical facility, a notable proportion also took place in the decedent's home. The analysis underscores persistent disparities: men consistently experienced higher mortality rates than women. A complex racial dynamic emerged wherein NH White individuals bore the highest mortality burden overall, yet the most rapid rate of increase was observed in the NH Black population. Geographically, the highest mortality burden was concentrated in the Midwest census region and in non-metropolitan areas, the latter of which also saw a faster rise in mortality compared to their metropolitan counterparts. The fatal interplay between COPD and AFib stems from a vicious cycle of inflammation, hypoxia, and hemodynamic failure. COPD cultivates an arrhythmogenic substrate through two key pathways: its chronic systemic inflammation promotes atrial fibrosis, while disease-induced hypoxemia leads to pulmonary hypertension and atrial stretch, a direct mechanical trigger for AF ( 18 – 20 ). Once AF is established, it proves deadly by severely reducing cardiac output, which compromises oxygen delivery in patients with minimal pulmonary reserve, often precipitating respiratory collapse ( 21 ). This hemodynamic instability is further compounded by AF’s prothrombotic state, which is responsible for introducing the constant threat of a catastrophic pulmonary embolism in already damaged lungs ( 22 ). Thus, COPD creates the ideal conditions for AF to arise, while AF delivers the acute hemodynamic or thromboembolic insult that is lethal in such a physiologically depleted host. The 25-year mortality trajectory for this comorbidity unfolds in two distinct acts. The first was a steady, inexorable rise from 1999 to 2018, attributable to the confluence of an aging population living longer with chronic disease and progressively more accurate death certificate coding ( 23 – 25 ). Critically, this period also saw a paradoxical effect of medical progress: improved survival from acute cardiovascular events created a larger population of patients living longer with chronic heart conditions, thereby expanding the pool of individuals vulnerable to the lethal interplay of AF and COPD ( 26 ). The second act, an abrupt acceleration beginning in 2018, represents a multi-stage assault. This upturn was likely precipitated by the severe 2017–2018 influenza season, which placed an immense burden on this specific cardiorespiratory cohort ( 27 ). This period of heightened vulnerability was then met by the catastrophic force of the COVID-19 pandemic, which drove mortality to its peak in 2021 ( 28 ). The subsequent plateauing of the death rate does not signal recovery but a grim recalibration at a much higher mortality baseline, likely shaped by a pandemic "harvesting effect" on the most vulnerable individuals ( 29 ). This sequence demonstrates how the pandemic did not create a new trend but catastrophically accelerated an existing one, cementing a new, elevated standard of risk. Our analysis found a gender paradox: men bear higher mortality, but women's mortality is rising faster, narrowing the gap. Men's excess risk stems from historical factors—greater past tobacco use, higher lifetime occupational lung irritant exposure, and more cardiovascular comorbidity ( 30 – 33 ). Women's accelerating mortality reflects later smoking uptake, corrected underdiagnosis of COPD, and the growing obesity epidemic, which increases risk for both conditions ( 34 – 37 ). This marks a clinical and demographic shift. Mortality by race/ethnicity shows divergent risk overall. NH White had the highest absolute mortality from greater AF prevalence, 20th-century smoking, and longer life expectancy that lets chronic diseases become fatal ( 38 – 40 ). NH Black saw the fastest acceleration, reflecting systemic inequities—greater comorbidity, pollutant exposure, and barriers to care ( 41 – 43 ). Hispanic and NH Other had lower burdens; Hispanic rates may reflect the ‘Hispanic Paradox’ ( 44 ), while ‘NH Other’ aggregation masks disparities ( 45 ). These patterns show that mortality risk is a mosaic, shaped not just by who develops a disease, but by how legacy behaviors and societal structures alter its final outcome. Geographic mortality shows a widening non-metropolitan vs metropolitan divide, explaining why the Midwest has the nation's highest death rate. The Midwest’s excess mortality reflects rural disadvantages: limited healthcare access, higher risk-factor prevalence, lower health literacy, and weaker public-health infrastructure ( 46 – 49 ). By contrast, the Northeast’s low mortality reflects urbanization: greater healthcare density, different risk profiles, and stronger public-health interventions( 50 – 52 ). Urbanization thus primarily drives these regional mortality disparities across the U.S. The location of death for these patients highlights a healthcare system geared towards acute crisis over planned end-of-life care. A clear majority of deaths occurred in institutional settings, with a plurality in medical facilities. This reflects the clinical nature of terminal cardiorespiratory failure, a reality often reinforced by payment models that incentivize aggressive, hospital-based interventions over palliative approaches ( 53 , 54 ). Conversely, that over a quarter of patients died at home points to a complex mix of honored end-of-life wishes and sudden, unmanaged events ( 55 ). Perhaps the most critical finding is the small fraction of deaths in dedicated hospice facilities. This suggests a systemic failure in transitioning patients to comfort-focused care, rooted in the unpredictable prognosis of end-stage COPD ( 56 ). This gap is likely exacerbated by the geographic disparities discussed previously, as rural and underserved areas often lack dedicated hospice infrastructure, further limiting end-of-life options for these communities ( 57 ). The trends uncovered by this analysis are more than just statistics; they are a call to action against a worsening public health crisis. The widening mortality gap between rural and urban America, for instance, is a clear warning that geography is a potent determinant of survival, making access to specialized care a necessity, not a luxury. At the same time, the rapid acceleration of deaths among women and non-Hispanic Black individuals demands that equity become a central component, not an afterthought, in chronic disease management ( 58 ). The overall trend points to a larger truth: our current, often fragmented, strategies for managing chronic illness are failing the growing population of patients with complex cardiorespiratory multimorbidity. The path forward, therefore, must be multifaceted. A clear priority is the development of new integrated care models that treat AF and COPD as a single, high-risk clinical syndrome, as siloed approaches are proving insufficient ( 59 , 60 ). We must also look beyond acute hospitalizations to proactively address the profound gaps in end-of-life care, as the low utilization of hospice points to a systemic failure to provide comfort and honor patient wishes ( 61 ). Furthermore, there is a pressing need for research into prophylactic strategies, such as enhanced vaccination protocols, to shield this exceptionally vulnerable population from the impact of future viral threats ( 62 ). These efforts must ultimately inform smarter, targeted interventions that embed comprehensive cardiorespiratory care, from prevention to palliation, within the routine management of chronic disease. Clinical Implications for South Asia The present study used U.S. data from CDC WONDER and showed increasing mortality rates in AF and its comorbidity with COPD during 1999–2024, the results here could be of significant potential applicability to South Asia, especially India, considering both these conditions are on the rise in the backdrop of rapid epidemiological transition. Both AF and COPD are highly prevalent in South Asia. The prevalence of COPD in India is around 7–13% of the adult population and is even higher in rural areas due to exposure to biomass fuel and in urban areas due to exposure to ambient air pollution ( 63 , 64 ). The prevalence of AF, although dependent on etiology, is increasing due to ageing, urbanisation, and a growing number of cardiovascular risk factors, as indicated by registries such as the Indian Heart Rhythm Society-Atrial Fibrillation (IHRS-AF) and Kerala AF registries ( 65 , 66 ). The coexistence of AF and COPD is especially worrisome, since COPD is an established independent risk factor for AF through systemic inflammation, hypoxia and pulmonary capacitance pathways that are presumably identical to those underlying the U.S. trends identified in this report ( 67 ). The coexistence of AF with COPD is associated with increased risks for heart failure, stroke, and mortality, which is evident in the world data and in Asian cohorts where patients with COPD have an elevated rate of cardiovascular events ( 67 ). Uniquely challenging in South Asia are high rates of rheumatic heart disease (still a major cause of AF), tobacco and biomass smoke exposure (key drivers of COPD), and comorbidities such as hypertension and diabetes ( 68 ). Should U.S.-style patterns begin to take hold driven by aging populations and enduring risk factors - the result may well be rising AF-COPD mortality in South Asia to alarmingly little advantage. In terms of clinical implications, these data support integrated cardiopulmonary care in South Asia: consideration of early screening for AF in COPD (e.g., opportunistic pulse checks or ECG in high-risk groups), intensified risk factor management (smoking cessation, cleaner cooking fuels, pollution mitigation), and enhanced anticoagulation adherence – despite barriers such as cost and monitoring. Registries reveal underutilisation of guideline-directed therapies, identifying potential public health efforts to fill in by bridging data gaps and improving outcomes. In conclusion, although straightforward extrapolation from U.S. data is counseled against, the common pathophysiologic intersections indicate that a forward-thinking approach may be beneficial to avert increasing burden in South Asia. Additional region-specific longitudinal studies are needed to validate these trends. Limitations This study's findings should be interpreted within the context of several limitations inherent to using the CDC WONDER database. Our analysis is dependent on the accuracy of death certificates, which introduces the possibility of diagnostic misclassification and a "coding drift" from increased clinical awareness over time, both of which could misestimate the true mortality burden ( 69 ). Furthermore, the ecological design precludes claims of individual causality and lacks granular clinical data, such as disease severity or medication adherence, preventing adjustment for key confounders ( 70 ). The use of broad demographic categories may also mask significant internal heterogeneity, particularly within the 'Non-Hispanic Other' racial group. Despite these constraints, the study’s nationwide, population-based scope is its principal strength, providing a powerful and comprehensive view of broad epidemiological trends that demand urgent public health attention. 5. CONCLUSION In conclusion, mortality from the combined burden of atrial fibrillation (AF) and chronic obstructive pulmonary disease (COPD) has emerged as a worsening public health crisis in the United States, marked by profound demographic, racial, and geographic inequities. Our analysis highlights how fragmented healthcare delivery and entrenched social determinants amplify the lethality of this cardiorespiratory comorbidity. While the trends documented here are U.S.-specific, the underlying pathophysiological mechanisms and drivers aging populations, tobacco exposure, and environmental risk factors are increasingly relevant to South Asia, where rising burdens of both AF and COPD signal a parallel epidemiological transition. The next step is to shift the focus from separate treatment of chronic diseases to integrated, equitable, and proactive models of cardiorespiratory care. In the U.S. and globally including in South Asia. This includes early screening, aggressive risk factor modification (smoking cessation and reduction of biomass fuel exposure), better anticoagulation and adherence to guidelines directed therapy and integration of palliative measures. Treating this fatal comorbidity as one clinical syndrome at a unified level spanning prevention to end-of-life care will serve to both blunt its rising toll and add equity in care for future at-risk populations worldwide. Abbreviations Atrial Fibrillation (AF) Chronic Obstructive Pulmonary Disease (COPD) Age Adjusted Mortality Rates (AAMR) Annual Percentage Change (APC) Non-Hispanic (NH) Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests All authors declare no competing interests. Central Illustration. Temporal trends in Atrial Fibrillation and COPD-related mortality in the U.S.: A population-based study using CDC WONDER, 1999–2024 Funding The authors received no funds, grants, or financial support for this study. Author Contribution Ammad Uddin: Conceptualization, data curation, formal analysis, methodology, manuscript drafting, and critical revision of the manuscript.Muhammad Salik Uddin: Study design, data interpretation, methodology, manuscript drafting, and critical revision.Abbeha Talib: Literature review, data interpretation, manuscript drafting, and editing.S M Aleem Hussain: Data validation, statistical interpretation, and manuscript review.Rida Shakeel: Literature search, data organization, and manuscript editing.Muhammad Tahir: Data extraction from CDC WONDER, data management, and manuscript review.Shaheer Bin Shafiq: Visualization, figure preparation, and manuscript editing.Ahmed Anwaar Uddin: Methodology support, data verification, and manuscript review.Hermann Yokolo: Scientific oversight, international collaboration support, and critical revision of the manuscript.Mohid Zulfiqar: Conceptualization, project administration, supervision, methodology, data interpretation, and final approval of the manuscript. Acknowledgements Not applicable. Data Availability The data supporting the findings of this study were obtained from the CDC WONDER online database (Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research). The datasets used and analyzed during the current study are publicly available and can be accessed at [*https://wonder.cdc.gov*](https:/wonder.cdc.gov) . References About Atrial Fibrillation. | Heart Disease | CDC [Internet]. [cited 2025 Dec 1]. Available from: https://www.cdc.gov/heart-disease/about/atrial-fibrillation.html Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, et al. Heart Disease and Stroke Statistics-2022 Update: A Report from the American Heart Association. Circulation. 2022;145(8):E153–639. ;PAGE:STRING:ARTICLE/CHAPTER PubMed PMID: 35078371. Buja A, Rebba V, Montecchio L, Renzo G, Baldo V, Cocchio S, et al. The Cost of Atrial Fibrillation: A Systematic Review. 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Exposing some important barriers to health care access in the rural USA. Public Health. 2015;129(6):611–20. 04.001 PubMed PMID: 26025176. Health Literacy in Healthy People. 2030 - Healthy People 2030 | odphp.health.gov [Internet]. [cited 2025 Dec 1]. Available from: https://odphp.health.gov/healthypeople/priority-areas/health-literacy-healthy-people-2030 Ricketts TC. The changing nature of rural health care. Annu Rev Public Health. 2000;21(Volume 21, 2000):639–57. 10.1146/ANNUREV.PUBLHEALTH.21.1.639 /CITE/REFWORKS PubMed PMID: 10884968. Downey LH. Rural Populations and Health: Determinants, Disparities, and Solutions. Prev Chronic Dis. 2013;10:E104. 10.5888/PCD10.130097 . U.S. Healthcare Rankings by State. 2023 | Commonwealth Fund [Internet]. [cited 2025 Dec 1]. Available from: https://www.commonwealthfund.org/publications/scorecard/2023/jun/2023-scorecard-state-health-system-performance Walton AA, Marr J, Cahillane MJ, Bush K, Caron M, Aytur SA et al. 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Burge F, Lawson B, Johnston G, Asada Y, McIntyre PF, Flowerdew G, Preferred. and Actual Location of Death: What Factors Enable a Preferred Home Death? https://home.liebertpub.com/jpm . 2015;18(12):1054–9. 10.1089 /JPM.2015.0177 PubMed PMID: 26398744. Vermylen JH, Szmuilowicz E, Kalhan R. Palliative care in COPD: an unmet area for quality improvement. Int J Chron Obstruct Pulmon Dis. 2015;10(1):1543–51. 10.2147. /COPD.S74641 PubMed PMID: 26345486. Lynch S, Hospice, Palliative Care Access Issues in Rural Areas. Am J Hospice Palliat Med. 2013;30(2):172–7. doi:10.1177/1049909112444592;WEBSITE:WEBSITE:SAGE;WGROUP:STRING:PUBLICATION PubMed PMID: 22531150. Jackson CS, Nadine Gracia J. Addressing health and health-care disparities: The role of a diverse workforce and the social determinants of health. Public Health Reports. 2014;129(SUPPL. 2):57–61. 10.1177/00333549141291S211 ;WEBSITE:WEBSITE:SAGE;WGROUP:STRING:PUBLICATION PubMed PMID: 24385666. Kotlyarov S, Lyubavin A. Early Detection of Atrial Fibrillation in Chronic Obstructive Pulmonary Disease Patients. Medicina 2024. Page 352. 2024;60(3):352. doi:10.3390/MEDICINA60030352 PubMed PMID: 38541078. Parekh AK, Goodman RA, Gordon C, Koh HK. Managing multiple chronic conditions: A strategic framework for improving health outcomes and quality of life. Public Health Rep. 2011;126(4):460–71. ;WGROUP:STRING:PUBLICATION PubMed PMID: 21800741. Dalgaard KM, Bergenholtz H, Nielsen ME, Timm H. Early integration of palliative care in hospitals: A systematic review on methods, barriers, and outcome. Palliat Support Care. 2014;12(6):495–513. 10. 1017/S1478951513001338 PubMed PMID: 24621947. Schaffner W, Gabbay RA, Taylor AJ. Protecting Vulnerable Patients from Influenza during the COVID-19 Pandemic: An Urgent Call to Action for Health Care Professionals. Infect Dis Clin Pract. 2021;29(4):E202–3. 10.1097/IPC.0000000000001048 . Daniel R, Aggarwal P, Kalaivani M, Gupta S. Prevalence of chronic obstructive pulmonary disease in India: A systematic review and meta-analysis. Lung India. 2021;38(6):506. 10.4103/lungindia.lungindia_159_21 PubMed PMID: 34747730. Salvi S, Kumar GA, Dhaliwal RS, Paulson K, Agrawal A, Koul PA, et al. The burden of chronic respiratory diseases and their heterogeneity across the states of India: the Global Burden of Disease Study 1990–2016. Lancet Glob Health. 2018;6(12):e1363–74. 10.1016/S2214-109X . (18)30409-1 PubMed PMID: 30219316. Vora A, Kapoor A, Nair M, Lokhandwala Y, Narsimhan C, Ravikishore AG, et al. Clinical presentation, management, and outcomes in the Indian Heart Rhythm Society-Atrial Fibrillation (IHRS-AF) registry. Indian Heart J. 2017;69(1):43–7. 10.1016/j.ihj.2016.06.006 . PubMed PMID: 28228305. Charantharayil Gopalan B, Namboodiri N, Abdullakutty J, Lip GYH, Koshy AG, Krishnan Nair V, et al. Kerala Atrial Fibrillation Registry: a prospective observational study on clinical characteristics, treatment pattern and outcome of atrial fibrillation in Kerala, India, cohort profile. BMJ Open. 2019;9(7). 10.1136/bmjopen-2018-025901 . PubMed PMID: 31352410. Rhee CK, Ko FWS, Giap V, Van, Kawamatawong T, Lee JK, Matsunaga K, et al. Management of COPD With Cardiovascular Risk in Asia: A Review by the Asian Pacific Society of Respirology COPD Assembly. Respirology. 2025;30(9):817–30. 10.1111/resp.70103 . PubMed PMID: 40785398. Shenthar J. Management of atrial fibrillation in rheumatic heart disease. Heart Rhythm O2. 2022;3(6Part B):752. 10.1016/j.hroo.2022. 09.020 PubMed PMID: 36589001. McGivern L, Shulman L, Carney JK, Shapiro S, Bundock E. Death certification errors and the effect on mortality statistics. Public Health Rep. 2017;132(6):669–75. ;WGROUP:STRING:PUBLICATION PubMed PMID: 29091542. Van Walraven C, Austin P. Administrative database research has unique characteristics that can risk biased results. J Clin Epidemiol. 2012;65(2):126–31. 10.1016/j.jclinepi.2011.08.002 . Additional Declarations No competing interests reported. Supplementary Files CentralIllustration.docx figurescopdandAF.docx tablesAFCOPD.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 06 May, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 06 Apr, 2026 Editor invited by journal 18 Mar, 2026 Submission checks completed at journal 17 Mar, 2026 First submitted to journal 17 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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02:13:33","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1767807,"visible":true,"origin":"","legend":"","description":"","filename":"figurescopdandAF.docx","url":"https://assets-eu.researchsquare.com/files/rs-9064349/v1/6ba3fa763a11210dc6731c35.docx"},{"id":107011152,"identity":"e148aa49-67c9-4cb2-a5c8-8455b1480968","added_by":"auto","created_at":"2026-04-15 17:48:39","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":54000,"visible":true,"origin":"","legend":"","description":"","filename":"tablesAFCOPD.docx","url":"https://assets-eu.researchsquare.com/files/rs-9064349/v1/a8ca1aa6a6fbf16f4fdafe21.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rising Mortality from Atrial Fibrillation and COPD Comorbidity in the United States, 1999–2024: Implications for Cardiopulmonary Care in South Asia","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eAtrial fibrillation (AF), a common and increasingly deadly form of arrhythmia, accounted for a significant mortality burden in 2021, appearing on 232,030 death certificates across the United States (U.S.) and serving as the underlying cause in 28,037 deaths prevalence models predict that the number of affected individuals will reach several million in the decades ahead (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The economic footprint of AF is substantial; recent syntheses estimate large per-patient and population costs and identify AF as a major driver of cardiovascular healthcare utilization and spending (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Chronic obstructive pulmonary disease (COPD) likewise remains a leading cause of death in the U.S.: national data report more than 130,000 annual deaths from chronic lower respiratory diseases and persistently high morbidity (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). COPD imposes large direct and indirect costs both nationally and globally, and systematic reviews and economic models document substantial health-system and productivity losses that continue to rise (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAF and COPD commonly co-exist COPD confers a markedly elevated risk of AF, with meta-analyses demonstrating approximately a 1.7\u0026ndash;2.2-fold increase in AF incidence among individuals with COPD (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Patients with both conditions experience worse clinical trajectories, including more frequent hospitalization, higher short-term and long-term mortality, and greater resource use compared with patients who have either condition alone (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Shared and additive risk factors\u0026mdash;advancing age, tobacco exposure, obesity, hypertension, diabetes, and systemic inflammation\u0026mdash;concentrate vulnerability for both pulmonary and atrial disease (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBiologic plausibility for the COPD\u0026ndash;AF link rests on intersecting mechanisms, including chronic systemic inflammation, intermittent or sustained hypoxemia, oxidative stress, autonomic imbalance, pulmonary hypertension with atrial stretch, and medication effects (for example, β2-agonists) that alter atrial electrophysiology (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Amid globally rising burdens of both atrial fibrillation and COPD\u0026mdash;driven by aging populations, persistent tobacco use, and increasing exposure to biomass fuel and air pollution in rapidly urbanizing regions such as South Asia\u0026mdash;the need for comprehensive mortality trend analyses is urgent (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Given substantial projected cardiovascular costs through 2050 and the CDC\u0026rsquo;s robust surveillance datasets, this retrospective analysis of U.S. trends from 1999\u0026ndash;2024 is timely. It quantifies comorbidity-associated mortality patterns and demographic disparities, providing insights that may inform prevention, resource allocation, and integrated cardiorespiratory care strategies both in the United States and in other settings facing similar epidemiological transitions.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Population and Study Design\u003c/h2\u003e \u003cp\u003eMortality data related to AF and COPD were extracted from the CDC WONDER database using the International Classification of Diseases, 10th Revision (ICD-10) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The CDC WONDER database is based on death certificates and is therefore deemed public data. As a result, no Institutional Review Board approval is required. In this study, the Multiple Cause of Death Public Use Record was used to select persons whose death certificate listed AF or COPD as the underlying or contributing cause of death from 1999 to 2024. AF is coded as I48 under the ICD-10 classification system (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). COPD mortality is coded as J41, J42, J43, and J44 under the ICD-10 classification system (\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This paper is written following the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist for reporting(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Data Abstraction\u003c/h2\u003e \u003cp\u003eThe data extracted includes the population, year, and other demographic factors, such as sex, race, level of urbanization, state, census region, and place of death, for the period 1999 to 2024. Sex includes male and female. Racial categories include Hispanic or Latino, non-Hispanic Black or African American, non-Hispanic White, and non-Hispanic other. The population includes urban (large metropolitan area and medium/small metropolitan area) and rural (populations of \u0026lt;\u0026thinsp;50,000) counties, as classified by the 2013 US Census classification (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). This includes the use of data from all 50 states. Regions used were Northeast, Midwest, South, and West, as classified by the US Census Bureau.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistical Analysis\u003c/h2\u003e \u003cp\u003eAge-adjusted mortality rates (AAMRs) per 100,000 population for 1999\u0026ndash;2024 were calculated to assess the mortality trends related to Atrial Fibrillation (AF) and Chronic Obstructive Pulmonary Disease (COPD). The AAMRs were calculated after standardizing the deaths due to AF and COPD to the year 2000 United States population, and 95% confidence intervals (CIs) were calculated (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The AAMRs were used to analyze mortality patterns across various demographic classifications. The trends in AAMR were determined using the Joinpoint Regression Program (Joinpoint Version 5.2.0, National Cancer Institute). The AAMRs were then used to analyze the mortality trends in different diverse populations. The trends were analyzed using the Joinpoint Regression Program (Joinpoint Version 5.2.0, National Cancer Institute) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), to calculate the annual percentage changes (APCs) in mortality rates, and 95% CIs were calculated. The APCs were found to be either increasing or decreasing based on statistical significance, where P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. To calculate the average mortality trend from 1999 to 2024, average annual percentage change (AAPC) and 95% CIs were calculated as the weighted mean of APCs.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003eBetween 1999 and 2024, a total of 577,367 adults with Atrial Fibrillation in the United States had Chronic Obstructive Pulmonary Disease-related mortality. Most of these deaths occurred in medical facilities (40.17%), followed by 27.97% at the decedents' homes, 22.64% in nursing homes/long-term care facilities, 5.63% in hospice facilities, and the fewest deaths occurred at other locations (3.59%). \u003cb\u003e(Supplemental Table\u0026nbsp;1, 2)\u003c/b\u003e\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Annual Trends\u003c/h2\u003e \u003cp\u003eThere was a significant increase in the AAMR for Atrial Fibrillation in individuals with Chronic Obstructive Pulmonary Disease, rising from 5.56 (95% CI: 5.45 to 5.67) in 1999 to 13.96 (95% CI: 13.82 to 14.10) in 2024. This represents an Average Annual Percentage Change (AAPC) of +\u0026thinsp;3.73 (95% CI: +3.53 to +\u0026thinsp;3.91, p-value\u0026thinsp;=\u0026thinsp;0.01). Notably, the AAMR experienced a substantial increase from 5.56 (95% CI: 5.45 to 5.67) in 1999 to 11.84 (95% CI: 11.71 to 11.97) in 2018 (APC: +4.08; 95% CI: +3.42 to +\u0026thinsp;4.33, p-value\u0026thinsp;=\u0026thinsp;0.01), followed by a more moderate increase to 14.39 (95% CI: 14.24 to 14.54) in 2021 (APC: +6.76; 95% CI: +4.45 to +\u0026thinsp;7.81, p-value\u0026thinsp;=\u0026thinsp;0.01). After 2021, there was a decrease in AAMR to 13.96 (95% CI: 13.82 to 14.10) in 2024 (APC: -1.36; 95% CI: -3.56 to 0.31, p-value\u0026thinsp;=\u0026thinsp;0.08). \u003cb\u003e(Supplemental Table\u0026nbsp;1, 3; Supplementary Fig.\u0026nbsp;1)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Sex Trends\u003c/h2\u003e \u003cp\u003eA significant gender disparity was observed in AAMRs, with adult men consistently showing higher AAMRs than adult women [ Mean AAMR for men: 12.27 (95% CI: 12.04 to 12.50) vs. 7.64 (95% CI: 7.49 to 7.79) for women]. Both men and women experienced an increase in AAMRs from 1999 to 2024, with the increase being more pronounced in women (Men: Average Annual Percentage Change (AAPC): +3.11, 95% CI: +2.88 to +\u0026thinsp;3.44, p-value\u0026thinsp;=\u0026thinsp;0.01; Women: AAPC: +4.01, 95% CI: +3.79 to +\u0026thinsp;4.21, p-value\u0026thinsp;=\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003eIn particular, the AAMR for adult men exhibited a rise from 7.99 (95% CI: 7.76 to 8.21) in 1999 to 10.11 (95% CI: 9.89 to 10.33) in 2009 (APC: +2.72, 95% CI: -0.13 to +\u0026thinsp;6.34, p-value\u0026thinsp;=\u0026thinsp;0.05), followed by a significant increase to 14.88 (95% CI: 14.64 to 15.11) by 2018 (APC: +4.11, 95% CI: +1.57 to +\u0026thinsp;4.98, p-value\u0026thinsp;=\u0026thinsp;0.01). Post 2018, AAMR experienced a substantial increase to 18.20 (95% CI: 17.94 to 18.46) in 2021 (APC: +6.65, 95% CI: +4.48 to +\u0026thinsp;7.87, p-value\u0026thinsp;=\u0026thinsp;0.01), followed by a decrease to 17.44 (95% CI: 17.20 to 17.68) in 2024 (APC: -1.95, 95% CI: -4.10 to -0.34, p-value\u0026thinsp;=\u0026thinsp;0.03).\u003c/p\u003e \u003cp\u003eSimilarly, the AAMR for adult women increased substantially from 4.18 (95% CI: 4.06 to 4.30) in 1999 to 11.53 (95% CI: 11.35 to 11.70) in 2021 (APC: +4.51, 95% CI: +4.35 to +\u0026thinsp;4.76, p-value\u0026thinsp;=\u0026thinsp;0.01), followed by a non-significant increase to 11.32 (95% CI: 11.16 to 11.49) by 2024 (APC: +0.42, 95% CI: -3.12 to +\u0026thinsp;2.51, p-value\u0026thinsp;=\u0026thinsp;0.56). \u003cb\u003e(Supplemental Table\u0026nbsp;1, 4; Supplementary Fig.\u0026nbsp;1)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Race Trends\u003c/h2\u003e \u003cp\u003eSignificant variability in mortalities was found among different racial/ethnic groups. The non-Hispanic White population exhibited the highest mean AAMR at 10.92 (95% CI: 10.77 to 11.07), followed by the non-Hispanic Black or African American population at 4.73 (95% CI: 4.43 to 5.04). Comparatively, the Hispanic or Latino population had a rate of 3.43 (95% CI: 3.13 to 3.74), and the Non-Hispanic Other populations had an AAMR of 3.26 (95% CI: 2.88 to 3.65).\u003c/p\u003e \u003cp\u003eAll racial and ethnic groups showed notable increases in AAMRs from 1999 to 2024, with the most noticeable increase observed in the Non-Hispanic Blacks [Black: AAPC: +5.11, 95% CI: +4.77 to +\u0026thinsp;5.48, p-value\u0026thinsp;=\u0026thinsp;0.01; Non-Hispanic Whites: AAPC: +4.10, CI: +3.92 to +\u0026thinsp;4.20, p-value\u0026thinsp;=\u0026thinsp;0.01; Hispanics: AAPC: +3.41, CI: +2.63 to +\u0026thinsp;4.96, p-value\u0026thinsp;=\u0026thinsp;0.01; Non-Hispanic Other populations: AAPC: +2.72, CI: +2.32 to +\u0026thinsp;3.34, p-value\u0026thinsp;=\u0026thinsp;0.01]. \u003cb\u003e(Supplemental Table\u0026nbsp;1, 5; Supplementary Fig.\u0026nbsp;2)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Geographic analysis\u003c/h2\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1. Census Region\u003c/h2\u003e \u003cp\u003eNotable difference in mortality rates was observed among census regions of the U.S. With the highest AAMRs recorded in the Midwest (AAMR: 10.23; 95% CI: 9.96 to 10.51), followed by the West (AAMR: 9.81; 95% CI: 9.53 to 10.09), the South (AAMR: 9.50; 95% CI: 9.29 to 9.71), and the least in Northeast (AAMR: 8.31; 95% CI: 8.04 to 8.58). \u003cb\u003e(Supplemental Table\u0026nbsp;6; Supplementary Fig.\u0026nbsp;3)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2. Urbanization\u003c/h2\u003e \u003cp\u003eNon-metropolitan areas showed slightly higher AAMRs than metropolitan areas, with overall AAMRs of 10.68 (95% CI: 10.36 to 11.00) and 8.27 (95% CI: 8.13 to 8.40), respectively. Both metropolitan and non-metropolitan areas experienced a significant increase in AAMRs from 1999 to 2024, with a more significant increase observed in non-metropolitan areas [Metropolitan: AAPC: +4.10, (95% CI: +3.82 to +\u0026thinsp;4.28) (p-value\u0026thinsp;=\u0026thinsp;0.01); Non-metropolitan: AAPC: +5.24, (95% CI: +4.99 to +\u0026thinsp;5.56) (p-value\u0026thinsp;=\u0026thinsp;0.01)]. \u003cb\u003e(Supplemental Table\u0026nbsp;7; Supplementary Fig.\u0026nbsp;4)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.4.3. States\u003c/h2\u003e \u003cp\u003eAAMRs varied across states, with rates ranging from as low as 4.29 (95% CI: 3.85 to 4.74) in the District of Columbia to 9.32 (95% CI: 9.23 to 9.40) in California. States in the top 90th percentile, including Oklahoma, Oregon, Rhode Island, Vermont, West Virginia, and Wyoming, exhibited AAMRs more than double compared to states in the lower 10th percentile, such as the District of Columbia, Georgia, Hawaii, Louisiana, Nevada, and Utah. \u003cb\u003e(Supplemental Table\u0026nbsp;8; Supplementary Fig.\u0026nbsp;5)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThis study provides a comprehensive analysis of mortality related to the comorbidity of AF and COPD among U.S. adults from 1999 to 2024, elucidating crucial temporal trends and demographic disparities. Our findings reveal a substantial and concerning escalation in the age-adjusted mortality rate (AAMR), which increased by nearly 150% over the 25-year period, with a particularly sharp acceleration from 2018 to 2021. While a majority of these deaths occurred in a medical facility, a notable proportion also took place in the decedent's home. The analysis underscores persistent disparities: men consistently experienced higher mortality rates than women. A complex racial dynamic emerged wherein NH White individuals bore the highest mortality burden overall, yet the most rapid rate of increase was observed in the NH Black population. Geographically, the highest mortality burden was concentrated in the Midwest census region and in non-metropolitan areas, the latter of which also saw a faster rise in mortality compared to their metropolitan counterparts.\u003c/p\u003e \u003cp\u003eThe fatal interplay between COPD and AFib stems from a vicious cycle of inflammation, hypoxia, and hemodynamic failure. COPD cultivates an arrhythmogenic substrate through two key pathways: its chronic systemic inflammation promotes atrial fibrosis, while disease-induced hypoxemia leads to pulmonary hypertension and atrial stretch, a direct mechanical trigger for AF (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Once AF is established, it proves deadly by severely reducing cardiac output, which compromises oxygen delivery in patients with minimal pulmonary reserve, often precipitating respiratory collapse (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). This hemodynamic instability is further compounded by AF\u0026rsquo;s prothrombotic state, which is responsible for introducing the constant threat of a catastrophic pulmonary embolism in already damaged lungs (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Thus, COPD creates the ideal conditions for AF to arise, while AF delivers the acute hemodynamic or thromboembolic insult that is lethal in such a physiologically depleted host.\u003c/p\u003e \u003cp\u003eThe 25-year mortality trajectory for this comorbidity unfolds in two distinct acts. The first was a steady, inexorable rise from 1999 to 2018, attributable to the confluence of an aging population living longer with chronic disease and progressively more accurate death certificate coding (\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Critically, this period also saw a paradoxical effect of medical progress: improved survival from acute cardiovascular events created a larger population of patients living longer with chronic heart conditions, thereby expanding the pool of individuals vulnerable to the lethal interplay of AF and COPD (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). The second act, an abrupt acceleration beginning in 2018, represents a multi-stage assault. This upturn was likely precipitated by the severe 2017\u0026ndash;2018 influenza season, which placed an immense burden on this specific cardiorespiratory cohort (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). This period of heightened vulnerability was then met by the catastrophic force of the COVID-19 pandemic, which drove mortality to its peak in 2021 (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The subsequent plateauing of the death rate does not signal recovery but a grim recalibration at a much higher mortality baseline, likely shaped by a pandemic \"harvesting effect\" on the most vulnerable individuals (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). This sequence demonstrates how the pandemic did not create a new trend but catastrophically accelerated an existing one, cementing a new, elevated standard of risk.\u003c/p\u003e \u003cp\u003eOur analysis found a gender paradox: men bear higher mortality, but women's mortality is rising faster, narrowing the gap. Men's excess risk stems from historical factors\u0026mdash;greater past tobacco use, higher lifetime occupational lung irritant exposure, and more cardiovascular comorbidity (\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Women's accelerating mortality reflects later smoking uptake, corrected underdiagnosis of COPD, and the growing obesity epidemic, which increases risk for both conditions (\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). This marks a clinical and demographic shift.\u003c/p\u003e \u003cp\u003eMortality by race/ethnicity shows divergent risk overall. NH White had the highest absolute mortality from greater AF prevalence, 20th-century smoking, and longer life expectancy that lets chronic diseases become fatal (\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). NH Black saw the fastest acceleration, reflecting systemic inequities\u0026mdash;greater comorbidity, pollutant exposure, and barriers to care (\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Hispanic and NH Other had lower burdens; Hispanic rates may reflect the \u0026lsquo;Hispanic Paradox\u0026rsquo; (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e), while \u0026lsquo;NH Other\u0026rsquo; aggregation masks disparities (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). These patterns show that mortality risk is a mosaic, shaped not just by who develops a disease, but by how legacy behaviors and societal structures alter its final outcome. Geographic mortality shows a widening non-metropolitan vs metropolitan divide, explaining why the Midwest has the nation's highest death rate. The Midwest\u0026rsquo;s excess mortality reflects rural disadvantages: limited healthcare access, higher risk-factor prevalence, lower health literacy, and weaker public-health infrastructure (\u003cspan additionalcitationids=\"CR47 CR48\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). By contrast, the Northeast\u0026rsquo;s low mortality reflects urbanization: greater healthcare density, different risk profiles, and stronger public-health interventions(\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Urbanization thus primarily drives these regional mortality disparities across the U.S.\u003c/p\u003e \u003cp\u003eThe location of death for these patients highlights a healthcare system geared towards acute crisis over planned end-of-life care. A clear majority of deaths occurred in institutional settings, with a plurality in medical facilities. This reflects the clinical nature of terminal cardiorespiratory failure, a reality often reinforced by payment models that incentivize aggressive, hospital-based interventions over palliative approaches (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Conversely, that over a quarter of patients died at home points to a complex mix of honored end-of-life wishes and sudden, unmanaged events (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Perhaps the most critical finding is the small fraction of deaths in dedicated hospice facilities. This suggests a systemic failure in transitioning patients to comfort-focused care, rooted in the unpredictable prognosis of end-stage COPD (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). This gap is likely exacerbated by the geographic disparities discussed previously, as rural and underserved areas often lack dedicated hospice infrastructure, further limiting end-of-life options for these communities (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe trends uncovered by this analysis are more than just statistics; they are a call to action against a worsening public health crisis. The widening mortality gap between rural and urban America, for instance, is a clear warning that geography is a potent determinant of survival, making access to specialized care a necessity, not a luxury. At the same time, the rapid acceleration of deaths among women and non-Hispanic Black individuals demands that equity become a central component, not an afterthought, in chronic disease management (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). The overall trend points to a larger truth: our current, often fragmented, strategies for managing chronic illness are failing the growing population of patients with complex cardiorespiratory multimorbidity. The path forward, therefore, must be multifaceted. A clear priority is the development of new integrated care models that treat AF and COPD as a single, high-risk clinical syndrome, as siloed approaches are proving insufficient (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). We must also look beyond acute hospitalizations to proactively address the profound gaps in end-of-life care, as the low utilization of hospice points to a systemic failure to provide comfort and honor patient wishes (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). Furthermore, there is a pressing need for research into prophylactic strategies, such as enhanced vaccination protocols, to shield this exceptionally vulnerable population from the impact of future viral threats (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). These efforts must ultimately inform smarter, targeted interventions that embed comprehensive cardiorespiratory care, from prevention to palliation, within the routine management of chronic disease.\u003c/p\u003e \u003cp\u003e \u003cb\u003eClinical Implications for South Asia\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe present study used U.S. data from CDC WONDER and showed increasing mortality rates in AF and its comorbidity with COPD during 1999\u0026ndash;2024, the results here could be of significant potential applicability to South Asia, especially India, considering both these conditions are on the\u0026ensp;rise in the backdrop of rapid epidemiological transition. Both AF and COPD are highly prevalent in South Asia.\u003c/p\u003e \u003cp\u003eThe prevalence of COPD in India is around 7\u0026ndash;13% of the adult population and is even higher\u0026ensp;in rural areas due to exposure to biomass fuel and in urban areas due to exposure to ambient air pollution (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). The prevalence of AF, although dependent on etiology, is increasing due to ageing, urbanisation, and a growing number of cardiovascular risk factors, as indicated by registries such as the Indian Heart Rhythm Society-Atrial Fibrillation (IHRS-AF) and Kerala AF registries (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e). The coexistence\u0026ensp;of AF and COPD is especially worrisome, since COPD is an established independent risk factor for AF through systemic inflammation, hypoxia and pulmonary capacitance pathways that are presumably identical to those underlying the U.S. trends identified in this report (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe coexistence of AF with COPD is associated with\u0026ensp;increased risks for heart failure, stroke, and mortality, which is evident in the world data and in Asian cohorts where patients with COPD have an elevated rate of cardiovascular events (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). Uniquely challenging in South Asia are high rates of rheumatic heart disease (still a major cause\u0026ensp;of AF), tobacco and biomass smoke exposure (key drivers of COPD), and comorbidities such as hypertension and diabetes (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e). Should U.S.-style patterns begin to take hold driven by aging populations and enduring risk factors - the result may well be rising AF-COPD mortality in South Asia to alarmingly little advantage.\u003c/p\u003e \u003cp\u003eIn terms of clinical implications, these data support\u0026ensp;integrated cardiopulmonary care in South Asia: consideration of early screening for AF in COPD (e.g., opportunistic pulse checks or ECG in high-risk groups), intensified risk factor management (smoking cessation, cleaner cooking fuels, pollution mitigation), and enhanced anticoagulation adherence \u0026ndash; despite barriers such as cost and monitoring. Registries reveal underutilisation of guideline-directed therapies, identifying potential public\u0026ensp;health efforts to fill in by bridging data gaps and improving outcomes.\u003c/p\u003e \u003cp\u003eIn conclusion, although straightforward extrapolation from U.S. data is counseled against, the\u0026ensp;common pathophysiologic intersections indicate that a forward-thinking approach may be beneficial to avert increasing burden in South Asia. Additional region-specific longitudinal studies are needed to validate these trends.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study's findings should be interpreted within the context of several limitations inherent to using the CDC WONDER database. Our analysis is dependent on the accuracy of death certificates, which introduces the possibility of diagnostic misclassification and a \"coding drift\" from increased clinical awareness over time, both of which could misestimate the true mortality burden (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e). Furthermore, the ecological design precludes claims of individual causality and lacks granular clinical data, such as disease severity or medication adherence, preventing adjustment for key confounders (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e). The use of broad demographic categories may also mask significant internal heterogeneity, particularly within the 'Non-Hispanic Other' racial group. Despite these constraints, the study\u0026rsquo;s nationwide, population-based scope is its principal strength, providing a powerful and comprehensive view of broad epidemiological trends that demand urgent public health attention.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eIn conclusion, mortality from the combined burden of atrial fibrillation (AF) and chronic obstructive pulmonary disease (COPD) has emerged as a worsening public health crisis in the United States, marked by profound demographic, racial, and geographic inequities. Our analysis highlights how fragmented healthcare delivery and entrenched social determinants amplify the lethality of this cardiorespiratory comorbidity. While the trends documented here are U.S.-specific, the underlying pathophysiological mechanisms and drivers aging populations, tobacco exposure, and environmental risk factors are increasingly relevant to South Asia, where rising burdens of both AF and COPD signal a parallel epidemiological transition.\u003c/p\u003e \u003cp\u003eThe next step is to shift the focus from separate treatment\u0026ensp;of chronic diseases to integrated, equitable, and proactive models of cardiorespiratory care. In the U.S. and globally\u0026ensp;including in South Asia. This includes early screening, aggressive risk\u0026ensp;factor modification (smoking cessation and reduction of biomass fuel exposure), better anticoagulation and adherence to guidelines directed therapy and integration of palliative measures. Treating this fatal comorbidity as one clinical syndrome at a unified level spanning prevention to end-of-life care will serve to both blunt its rising toll and add equity in care for future\u0026ensp;at-risk populations worldwide.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAtrial Fibrillation (AF)\u003c/p\u003e\u003cp\u003eChronic Obstructive Pulmonary Disease (COPD)\u003c/p\u003e\u003cp\u003eAge Adjusted Mortality Rates (AAMR)\u003c/p\u003e\u003cp\u003eAnnual Percentage Change (APC)\u003c/p\u003e\u003cp\u003eNon-Hispanic (NH)\u003c/p\u003e\u003cp\u003eCenters for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no competing interests.\u003c/p\u003e\n\u003ch2\u003eCentral Illustration.\u003c/h2\u003e\n\u003cp\u003eTemporal trends in Atrial Fibrillation and COPD-related mortality in the U.S.: A population-based study using CDC WONDER, 1999\u0026ndash;2024\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe authors received no funds, grants, or financial support for this study.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAmmad Uddin: Conceptualization, data curation, formal analysis, methodology, manuscript drafting, and critical revision of the manuscript.Muhammad Salik Uddin: Study design, data interpretation, methodology, manuscript drafting, and critical revision.Abbeha Talib: Literature review, data interpretation, manuscript drafting, and editing.S M Aleem Hussain: Data validation, statistical interpretation, and manuscript review.Rida Shakeel: Literature search, data organization, and manuscript editing.Muhammad Tahir: Data extraction from CDC WONDER, data management, and manuscript review.Shaheer Bin Shafiq: Visualization, figure preparation, and manuscript editing.Ahmed Anwaar Uddin: Methodology support, data verification, and manuscript review.Hermann Yokolo: Scientific oversight, international collaboration support, and critical revision of the manuscript.Mohid Zulfiqar: Conceptualization, project administration, supervision, methodology, data interpretation, and final approval of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data supporting the findings of this study were obtained from the CDC WONDER online database (Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research). 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J Clin Epidemiol. 2012;65(2):126\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jclinepi.2011.08.002\u003c/span\u003e\u003cspan address=\"10.1016/j.jclinepi.2011.08.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\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-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Atrial Fibrillation, Chronic Obstructive Pulmonary Disease, Mortality, CDC WONDER","lastPublishedDoi":"10.21203/rs.3.rs-9064349/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9064349/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAtrial fibrillation and chronic obstructive pulmonary disease COPD frequently coexist, yet national mortality patterns of this high-risk dyad are not clearly understood. We assessed long-range patterns and inequities of atrial fibrillation-related mortality among adults with COPD in the United States.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUsing CDC WONDER Multiple Cause of Death files (1999\u0026ndash;2024), we identified decedents of \u0026ge;\u0026thinsp;25 years with atrial fibrillation (ICD-10 I48) and COPD (J41\u0026ndash;J44) as contributing or underlying causes. We calculated age-adjusted mortality rates (AAMR) per 100,000 (2000 U.S. standard) and estimated Annual Percent Change (APC) and Average APC (AAPC) using Joinpoint Regression, stratifying on sex, race/ethnicity, census region/state, urbanicity, and place of death.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThere were 577,367 atrial fibrillation-COPD deaths. National AAMR increased from 5.56 (1999) to 13.96 (2024) (AAPC\u0026thinsp;+\u0026thinsp;3.73%, 95% CI\u0026thinsp;+\u0026thinsp;3.53 to +\u0026thinsp;3.91; p\u0026thinsp;\u0026lt;\u0026thinsp;0.000001), with a rise through 2018 (APC\u0026thinsp;+\u0026thinsp;4.08%) and a surge to 2021 (APC\u0026thinsp;+\u0026thinsp;6.76%), followed by a nonsignificant decline thereafter (APC\u0026thinsp;\u0026minus;\u0026thinsp;1.36%). Men had higher AAMR than women (overall 12.27 vs 7.64), but women\u0026rsquo;s rates rose faster (AAPC\u0026thinsp;+\u0026thinsp;4.01% vs\u0026thinsp;+\u0026thinsp;3.11%). AAMR was highest in White individuals (10.92), while the steepest increase occurred in Black individuals (AAPC\u0026thinsp;+\u0026thinsp;5.11%). The Midwest had the highest regional AAMR (10.23) and the Northeast the lowest (8.31). Non-metropolitan areas exceeded metropolitan areas (10.68 vs 8.27; AAPC\u0026thinsp;+\u0026thinsp;5.24% vs\u0026thinsp;+\u0026thinsp;4.10%). Most deaths occurred in medical facilities (40.17%), followed by home (27.97%) and nursing homes/long-term care (22.64%).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eMortality from atrial fibrillation-COPD increased dramatically over 25 years, with more rapid expansion for women, non-Hispanic blacks, and people from non-metropolitan areas. These results argue for prevention aimed at selected subgroups, combined cardiopulmonary care, broader rural access, and earlier palliative care to narrow inequities and optimize outcome.\u003c/p\u003e","manuscriptTitle":"Rising Mortality from Atrial Fibrillation and COPD Comorbidity in the United States, 1999–2024: Implications for Cardiopulmonary Care in South Asia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-15 17:48:35","doi":"10.21203/rs.3.rs-9064349/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-06T08:44:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201775400775959329294663729109380065677","date":"2026-04-24T03:19:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-08T05:08:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-06T13:25:29+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-18T12:25:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-17T22:58:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2026-03-17T16:05:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f351131b-cec2-4c9f-8639-09eb9aea8ad8","owner":[],"postedDate":"April 15th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-06T08:44:12+00:00","index":58,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-15T17:48:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-15 17:48:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9064349","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9064349","identity":"rs-9064349","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}