Epidemiologic Patterns and Disparities in Cardiovascular Deaths Associated With Respiratory Failure Across Two Decades in the U.S

Epidemiologic Patterns and Disparities in Cardiovascular Deaths Associated With Respiratory Failure Across Two Decades in the U.S | 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 Epidemiologic Patterns and Disparities in Cardiovascular Deaths Associated With Respiratory Failure Across Two Decades in the U.S Lixing Ma, Mingyu Li, Haiyu Zhao, Penggang Dong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8241552/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 Cardiovascular disease (CVD) remains the leading cause of death worldwide, with its burden in the U.S. continuing to rise despite substantial advances in prevention and care. Respiratory failure (RF) is a frequent terminal event in advanced CVD, yet national patterns and demographic disparities in CVD-related deaths involving RF remain poorly characterized. This study aimed to quantify temporal trends and regional variations in CVD mortality with RF as a contributing cause from 1999 to 2020. Methods We obtained U.S. death certificate data from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database (1999–2020). Deaths were identified using ICD-10 codes I00–I99 for CVD as the underlying cause and J96.0–J96.1, J96.9 for RF as a contributing cause. Age-adjusted mortality rates (AAMRs) were calculated per 100,000 population using the 2000 U.S. standard population. Joinpoint regression analysis was applied to estimate annual percent change (APC) and average annual percent change (AAPC) with 95% confidence intervals (CIs) across sex, ethnicity, census regions, urbanization, and state categories. Results From 1999 to 2020, the national AAMR for CVD-related deaths with RF increased markedly. In males, AAMR rose from 22.9 (95% CI, 22.5–23.3) to 32.9 (95% CI, 32.6–33.3) with an AAPC of 1.71% (95% CI, 1.37–2.05); in females, from 17.3 (95% CI, 17.1–17.6) to 24.5 (95% CI, 24.2–24.7) with an AAPC of 1.56% (95% CI, 0.83–2.29). Non-Hispanic Black adults consistently exhibited the highest mortality, whereas nonmetropolitan areas showed a steeper rise (AAPC, 2.67%; 95% CI, 2.27–3.08) than metropolitan regions (AAPC, 1.50%; 95% CI, 0.88–2.11). All four census regions demonstrated upward trends, with the Midwest showing the greatest increase (AAPC, 2.40%; 95% CI, 1.92–2.89). State-level analysis revealed pronounced geographic heterogeneity, with Idaho showing the largest rise in AAMR (AAPC, 7.44%; 95% CI, 2.17–12.98). Multiple joinpoints indicated distinct inflection periods, particularly after 2010, corresponding to accelerated increases across several subgroups. Conclusion Between 1999 and 2020, CVD-related mortality with RF as a contributing cause increased substantially across the U.S., with notable disparities by sex, ethnicity, geography, and urbanization. These findings underscore the growing intersection between cardiovascular and respiratory diseases and highlight the need for integrated prevention and management strategies targeting high-risk populations and regions. CDC WONDER Respiratory failure cardiovascular mortality Joinpoint Regression Global disease burden Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Cardiovascular disease (CVD) remains the leading cause of death globally and a persistent public health challenge in the U.S. [1, 2]. Although advances in prevention, diagnosis, and therapy have reduced mortality from some CVD subtypes, the overall burden continues to rise, driven by population aging, sedentary lifestyles, and the growing prevalence of metabolic comorbidities such as diabetes and obesity [3, 4]. RF frequently represents the terminal pathway of advanced CVD, compounding disease severity and mortality risk [5–7]. Characterizing long-term trends in CVD-related deaths with RF as a contributing cause is therefore essential for evaluating public health progress and identifying vulnerable populations. Comprehensive, population-based mortality data from national surveillance systems—such as the Centers for Disease Control and Prevention (CDC) Wide-Ranging Online Data for Epidemiologic Research (WONDER) database—provide unique opportunities to explore cause-specific mortality patterns over time [8]. While prior research has extensively documented overall CVD mortality trends [9], few studies have systematically examined CVD deaths accompanied by RF[10, 11]. Given the close pathophysiological interplay between cardiovascular and respiratory systems, especially among aging individuals and those with chronic conditions, investigating this overlapping mortality pattern may yield critical insights into evolving disease dynamics and healthcare inequities [12,13]. Here, we analyzed national and state-level trends in CVD-related mortality with RF as a contributing cause in the U.S. from 1999 to 2020. Using CDC WONDER data, we quantified changes in age-adjusted mortality rates (AAMRs) and applied Joinpoint regression analysis to detect inflection points that indicate shifts in mortality trajectories over time. Methods 2.1 Data sources The CDC’s Wide-Ranging Online Data for Epidemiologic Research (WONDER) database was used to obtain death certificate data from 1999 to 2020 [14]. CVD deaths were extracted using ICD-10 codes I00–I99 as the underlying cause of death, with RF coded as a contributing cause (ICD-10: J96.0–J96.1, J96.9). Since the dataset contains de-identified public use data, institutional review board approval was not applicable. The study was conducted in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines [15]. 2.2 Study variables We examined primary liver cancer-related deaths by sex, ethnicity [non-Hispanic White (NH White), non-Hispanic Black (NH Black), Hispanic, and non-Hispanic other (NH other)], census region, state, and urbanization status (metropolitan vs. nonmetropolitan, based on the 2013 NCHS Urban–Rural Classification Scheme) [16]. 2.3 Statistical analysis AAMRs per 100,000 population were calculated using the 2000 U.S. standard population. Temporal trends were assessed using Joinpoint Regression Program (version 5.4.0; National Cancer Institute, Bethesda, MD, USA) [17, 18]. The maximum number of joinpoints was set to 4, and a log-linear model was used to estimate the APC and the AAPC, both with 95% CIs [19]. Statistical significance was defined as p < 0.05. Statistically significant values are marked with an asterisk (*) in the results section. Analyses were stratified by geographic variables to evaluate disparities in mortality patterns. Results 3.1 Trends by sex From 1999 to 2020, the AAMR in males increased from 22.88 (95% CI: 22.51–23.26) in 1999 to 32.94 (95% CI: 32.61–33.28) in 2020, with an AAPC of 1.71 (95% CI: 1.37–2.05)*. The APC for males varied across time periods: 1999–2010: APC = -0.24 (95% CI : -0.56-0.08); 2010–2017: APC = 4.80 (95% CI : 4.11–5.50); 2017–2020: APC = 1.83 (95% CI : 0.18–3.52). In female patients, the AAMR also increased over the study period, from 17.31 (95% CI: 17.07–17.56) in 1999 to 24.45 (95% CI: 24.20–24.70) in 2020. The AAPC was 1.56 (95% CI: 0.83–2.29). The APC by time period for females was: 1999–2009: APC = -0.09 (95% CI: -0.50-0.33); 2009–2014: APC = 2.79 (95% CI: 1.20–4.40); 2014–2017: APC = 5.83 (95% CI: 1.29–10.57); 2017–2020: APC = 0.86 (95% CI: -1.15-2.91). All the above changes are visualized in Fig. 1 and further detailed in Supplemental Table 1. 3.2 Trends by race Minor discrepancies were observed between the total number of subjects and the sum across ethnic groups in 1999 and 2020. Specifically, ethnicity information was missing for 91 subjects in 1999 and 125 subjects in 2020. The proportion of missing cases was minimal (< 0.3%) and is unlikely to have influenced the observed temporal trends in age-adjusted mortality rates. NH Black consistently had the highest AAMR among racial groups, increasing from 26.17 (95% CI: 25.33–27.01) in 1999 to 37.17 (95% CI: 36.41–37.92) in 2020, with an AAPC of 1.35 (95% CI: 1.01–1.69)*. APC by time period for NH Black: 1999–2012: APC = 0.04 (95% CI: -0.37-0.46); 2012–2020: APC = 3.52 (95% CI:2.83–4.22)*. Among Hispanic patients, the AAMR increased from 21.56 (95% CI: 20.49–22.64) in 1999 to 25.45 (95% CI: 24.81–26.09) in 2020. The AAPC was 0.96 (95% CI: 0.47–1.44)*. APC by time period: 1999–2010: APC = -0.16 (95% CI: -0.95-0.64); 2010–2020: APC = 2.19 (95% CI: 1.55–2.84)*. Among NH White, AAMR decreased from 18.67 (95% CI: 18.45–18.88) in 1999 to 27.79 (95% CI: 27.55–28.02) in 2020. The AAPC was 1.85 (95% CI: 1.23–2.48)*. APC by time period: 1999–2009: APC = -0.15 (95% CI: -0.55-0.25); 2009–2013: APC = 3.29 (95% CI: 0.86–5.78); 2013–2017: APC = 6.11 (95% CI: 3.88–8.38); 2017–2020: APC = 1.14 (95% CI: -0.77-3.08). The AAMR for NH Other increased from 18.97 (95% CI: 17.59–20.34) in 1999 to 18.92 (95% CI: 18.22–19.62) in 2020. The AAPC was 0.40 (95% CI: -0.03-0.83)*. APC by time period: 1999–2014: APC = -0.50(95% CI: -0.94–0.07); 2014–2020: APC = 2.69 (95% CI: 1.47–3.92). See Fig. 2 and Supplemental Table 1 for detailed trends for all racial groups. 3.3 Trends by census regions All census regions showed an increase in AAMR over time. The AAMR for Midwest increased from 16.21 (95% CI: 15.83–16.60) in 1999 to 27.22 (95% CI: 26.78–27.65) in 2020. The AAPC was 2.40 (95% CI: 1.92–2.89)*. APC by time period: 1999–2010: APC = -0.18 (95% CI: -0.63-0.27); 2010–2017: APC = 6.37 (95% CI: 5.36–7.39); 2017–2020: APC = 2.90 (95% CI: 0.51–5.35). Among Northeast, the AAMR increased from 18.71 (95% CI: 18.28–19.15) in 1999 to 25.62 (95% CI: 25.17–26.07) in 2020. The AAPC was 1.50 (95% CI: 1.23–1.77)*. APC by time period: 1999–2009: APC = 0.01 (95% CI: -0.46-0.48); 2009–2020: APC = 2.88 (95% CI: 2.52–3.24)*. For South, the AAMR also increased over the study period, from 20.48 (95% CI: 20.12–20.84) in 1999 to 29.66 (95% CI: 29.32-30.00) in 2020. The AAPC was 1.64 (95% CI: 1.25–2.03)*. The APC by time period for South was: 1999–2010: APC = 0.05 (95% CI: -0.27-0.38); 2010–2018: APC = 4.26 (95% CI: 3.71–4.82)*; 2018–2020: APC = 0.10 (95% CI: -3.24-3.55). Among West, the AAMR increased from 22.68 (95% CI: 22.17–23.18) in 1999 to 28.73 (95% CI: 28.30-29.17) in 2020. The AAPC was 1.29 (95% CI: 0.61–1.96)*. APC by time period: 1999–2013: APC = 0.00 (95% CI: -0.34-0.34); 2013–2017: APC = 6.79 (95% CI: 3.60-10.08)*; 2017–2020: APC = 0.18 (95% CI: -2.47-2.90). Regional differences are illustrated in Fig. 3 and further detailed in Supplemental Table 1. 3.4 Trends by urbanization From 1999 to 2020, the AAMR in metropolitan areas increased from 19.98 (95% CI: 19.75–20.21) in 1999 to 27.61 (95% CI: 27.39–27.83) in 2020, with an AAPC of 1.50 (95% CI: 0.88–2.11)*. APC for metropolitan areas: 1999–2009: APC = -0.18 (95% CI: -0.54-0.18); 2009–2014: APC = 2.81 (95% CI: 1.47–4.18); 2014–2017: APC = 5.57 (95% CI: 1.75–9.53); 2017–2020: APC = 0.96 (95% CI: -0.72-2.67). In nonmetropolitan areas, the AAMR also increased from 17.52 (95% CI: 17.07–17.96) in 1999 to 31.56 (95% CI: 31.02–32.10) in 2020. The AAPC was 2.67 (95% CI: 2.27–3.08)*. APC by time period: 1999–2011: APC = 0.44 (95% CI: 0.13–0.76); 2011–2017: APC = 7.48 (95% CI: 6.41–8.56); 2017–2020: APC = 2.31 (95% CI: 0.39–4.27)*. See Fig. 4 and Supplemental Table 1 for details. 3.5. Distribution of state-Level mortality and trends in the U.S. In the spatial analysis, we mapped state-level total deaths (Fig. 5A) and AAMR (Fig. 5B) in 2020, as well as the percentage change in deaths (Fig. 5C) and AAPC (Fig. 5D) from 1999 to 2020. State-level distributions of deaths and AAMR were displayed using discrete classification with fixed legends, ensuring comparability across states. While some states reported the highest absolute number of deaths in 2020, their corresponding AAMR values were not always the highest, reflecting differences in population size and age structure (Supplemental Table 1). In addition, Idaho exhibited one of the steepest increases in age-adjusted mortality rate (AAMR) nationwide, rising from 8.11 (95% CI: 6.19–10.44) in 1999 to 35.35 (95% CI: 32.13–38.57) in 2020, with an AAPC of 7.44% (95% CI: 2.17–12.98)*. The percentage change in deaths over 1999–2020 was visualized with a warm color scale, highlighting substantial heterogeneity in growth magnitude across states. Most states experienced an increase, but the extent of change varied considerably. Finally, the distribution of AAPC was represented on a blue-to-red gradient, with positive values indicating an increase. Most states exhibited positive AAPC, consistent with a long-term upward trend (Supplemental Table 1). Discussion In this nationally representative, multidecade analysis of U.S. mortality records, we found that CVD deaths with RF listed as a contributing cause increased steadily across sex, ethnicity, census regions, urbanization, and state categories from 1999 to 2020. These findings extend prior work on overall CVD mortality trends, which typically gave limited attention to the cardiopulmonary overlap that frequently precedes terminal decline [9, 20, 21]. Earlier studies documented that U.S. CVD mortality plateaued in the early 2000s and began rising in some subgroups over the last decade, largely because of increasing metabolic disease and population aging [22–24]. In our analysis, the rise in cardiopulmonary-related CVD deaths was even more pronounced—particularly after 2010—characterized by sharp inflection points across both sexes and nearly all racial and geographic strata. This pattern aligns with growing evidence that respiratory comorbidities such as chronic obstructive pulmonary disease, obesity hypoventilation, and acute pulmonary infections are increasingly common among patients with advanced cardiac disease [25–28]. However, the rate of increase we observed exceeded what would be expected from CVD burden alone [29], suggesting a compounding effect of multimorbidity in vulnerable populations [30, 31]. Consistent with historical patterns, males maintained higher age-adjusted mortality rates than females throughout the study period [32, 33]. Prior literature has attributed sex differences in CVD outcomes to variations in cardiopulmonary physiology, healthcare-seeking behavior, and comorbidity profiles [34–40]. Our findings build on this evidence by demonstrating that both sexes experienced significant long-term increases in RF-related CVD mortality, with particularly steep rises between 2010 and 2017. This pronounced inflection likely reflects the growing burden of obesity, diabetes, and chronic lung disease, compounded by environmental stressors such as deteriorating air quality, all of which heighten cardiopulmonary vulnerability [41, 42]. In line with longstanding demographic research on CVD disparities, non-Hispanic Black adults consistently exhibited the highest mortality rates, with especially rapid increases after 2012 [43, 44]. Hispanics and non-Hispanic Whites also demonstrated significant upward trends, albeit with different temporal patterns. Together, these observations indicate that although risk profiles vary across populations, the rising burden of cardiopulmonary mortality is widespread and layered upon persistent structural inequities. Geographic trends further highlight the influence of contextual factors. Mortality increased across all regions and levels of urbanization, with particularly sharp rises in nonmetropolitan areas and persistently high rates in the Midwest and South. These patterns underscore how disparities in healthcare access, chronic disease management, and socioeconomic conditions amplify cardiopulmonary mortality [45]. While populous states contributed the largest absolute number of deaths, several smaller states—such as Idaho—experienced among the fastest relative increases. These steep trends may reflect shifting demographic structures, state-level differences in public health initiatives, and evolving environmental exposures, including wildfire-related air pollution in western states [46–48]. Overall, these findings demonstrate that cardiopulmonary mortality is dynamic and shaped by intersecting demographic, environmental, and healthcare system transitions. The observed trajectory underscores the urgent need for integrated management of cardiac and respiratory comorbidities—an area traditionally divided between specialties. As heart failure, arrhythmias, and ischemic disease increasingly co-occur with chronic respiratory insufficiency, coordinated cardiopulmonary care models may improve patient outcomes [49–52]. At the population level, prevention efforts must address upstream determinants common to both conditions, including smoking, air pollution, obesity, and inadequate access to chronic disease management resources [53, 54]. The sharp acceleration in mortality after 2010 coincides with rising multimorbidity in the aging U.S. population, suggesting that without targeted interventions, the burden of overlapping chronic diseases is likely to intensify [55, 56]. This study offers valuable insights into long-term trends in CVD mortality associated with RF across the U.S., but several limitations warrant consideration. First, reliance on aggregated CDC mortality data introduces potential misclassification and underreporting, and the absence of individual-level information limits assessment of their specific contributions to observed trends [57]. Second, we did not evaluate the impact of therapeutic interventions nor differentiate among causes of death within the broader CVD population. Future research should build on this descriptive framework by linking population-based mortality data with detailed clinical, behavioral, and treatment information (e.g., SEER–Medicare or institutional datasets) and by applying spatial regression or multivariable modeling to more precisely identify contextual determinants underlying these disparities [58–61]. Conclusions In summary, CVD mortality with RF as a contributing cause increased substantially in the U.S. from 1999 to 2020, with accelerated rises in the past decade and disproportionately high burdens among Black adults, residents of the Midwest and South, and individuals living in nonmetropolitan areas. These findings highlight the growing need to reconceptualize cardiopulmonary disease prevention and management through an integrated lens and to address structural determinants driving persistent disparities. As the population continues to age and multimorbidity becomes increasingly common, the intersection of cardiovascular and respiratory disease will represent a pivotal frontier for clinical innovation and public health intervention. Declarations Ethics approval and consent to participate Not applicable. Competing interests The authors declare that they have no competing interests. Author Contribution LM, ML and HZ analyzed the data and wrote the manuscript. PD designed the research. All authors read and approved the manuscript and agree to be accountable for all aspects of the research in ensuring that the accuracy or integrity of any part of the work (including the provided data) are appropriately investigated and resolved. All authors read and approved the final manuscript. Acknowledgements Not applicable. Funding Statement Funding: No funding was received. Data Availability data available on request References Virani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, et al. Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association. Circulation. 2021;143(8):e254-e743. Benjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, et al. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Circulation. 2019;139(10):e56-e528. Roth GA, Mensah GA, Fuster V. 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Supplementary Files SupplementalTable1.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 02 Jan, 2026 Reviewers agreed at journal 24 Dec, 2025 Reviewers invited by journal 24 Dec, 2025 Editor invited by journal 02 Dec, 2025 Editor assigned by journal 01 Dec, 2025 Submission checks completed at journal 01 Dec, 2025 First submitted to journal 30 Nov, 2025 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8241552","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":565279657,"identity":"7c108673-a1cc-47f3-b213-acfa9f933329","order_by":0,"name":"Lixing Ma","email":"","orcid":"","institution":"Changzhi People's Hospital, The Affiliated Hospital of Changzhi Medical College","correspondingAuthor":false,"prefix":"","firstName":"Lixing","middleName":"","lastName":"Ma","suffix":""},{"id":565279658,"identity":"2a16aa47-f363-4d7e-a920-2dd91714b337","order_by":1,"name":"Mingyu Li","email":"","orcid":"","institution":"Changzhi People's 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1","display":"","copyAsset":false,"role":"figure","size":1842126,"visible":true,"origin":"","legend":"\u003cp\u003eSex-stratified deaths due to primary liver cancer: Age-adjusted mortality rates per 100000 in the U.S., 1999–2020. APC: Annual percent change.\u003c/p\u003e","description":"","filename":"fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-8241552/v1/758500441ddde3fce61352ca.png"},{"id":99313896,"identity":"187bd8b3-7b96-45bd-8091-ca489dd4388a","added_by":"auto","created_at":"2025-12-31 16:20:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2053533,"visible":true,"origin":"","legend":"\u003cp\u003eEthnicity-stratified deaths due to primary liver cancer: Age-adjusted mortality rates per 100000 in the U.S., 1999–2020. APC: Annual percent change.\u003c/p\u003e","description":"","filename":"fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-8241552/v1/b6204a22e55df82638059dea.png"},{"id":99056687,"identity":"5f94c98f-2aec-4feb-8911-5e98cc35e455","added_by":"auto","created_at":"2025-12-26 19:00:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2248577,"visible":true,"origin":"","legend":"\u003cp\u003eCensus regions-stratified deaths due to primary liver cancer: Age-adjusted mortality rates per 100000 in the U.S., 1999–2020. APC: Annual percent change.\u003c/p\u003e","description":"","filename":"fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-8241552/v1/566b57cfd1a8b17b0dccd58b.png"},{"id":99056691,"identity":"99af7283-bbbc-4e20-ae3c-49677b27096b","added_by":"auto","created_at":"2025-12-26 19:00:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1436535,"visible":true,"origin":"","legend":"\u003cp\u003eUrbanization-stratified deaths due to primary liver cancer: Age-adjusted mortality rates per 100000 in the U.S., 1999–2020. APC: Annual percent change.\u003c/p\u003e","description":"","filename":"fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-8241552/v1/e51dd8f13633195188923025.png"},{"id":99056694,"identity":"b0d838f2-eda4-4b30-a27f-b949f64f5288","added_by":"auto","created_at":"2025-12-26 19:00:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3321335,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of state-Level mortality and trends in the U.S.. (A) state-level total deaths in 2020. (B) AAMR in 2020. (C) percentage change in deaths from 1999 to 2020. (D) AAPC from 1999 to 2020. AAMR: Age-adjusted mortality rate. AAPC: average annual percent change.\u003c/p\u003e","description":"","filename":"fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-8241552/v1/b7a176b9d7671c435da9741a.png"},{"id":99323468,"identity":"e070b512-3170-4e46-9a7e-68cf58543c38","added_by":"auto","created_at":"2025-12-31 16:45:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11288320,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8241552/v1/7d2c841c-9efe-46f8-9071-806e9c17594a.pdf"},{"id":99313659,"identity":"45aa7f31-ffd7-4e0f-938e-7c73e31ec713","added_by":"auto","created_at":"2025-12-31 16:20:24","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15580,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8241552/v1/c55a12c6fd2a372415ba2855.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epidemiologic Patterns and Disparities in Cardiovascular Deaths Associated With Respiratory Failure Across Two Decades in the U.S","fulltext":[{"header":"Background","content":"\u003cp\u003eCardiovascular disease (CVD) remains the leading cause of death globally and a persistent public health challenge in the U.S. [1, 2]. Although advances in prevention, diagnosis, and therapy have reduced mortality from some CVD subtypes, the overall burden continues to rise, driven by population aging, sedentary lifestyles, and the growing prevalence of metabolic comorbidities such as diabetes and obesity [3, 4].\u003c/p\u003e\n\u003cp\u003eRF frequently represents the terminal pathway of advanced CVD, compounding disease severity and mortality risk [5\u0026ndash;7]. Characterizing long-term trends in CVD-related deaths with RF as a contributing cause is therefore essential for evaluating public health progress and identifying vulnerable populations.\u003c/p\u003e\n\u003cp\u003eComprehensive, population-based mortality data from national surveillance systems\u0026mdash;such as the Centers for Disease Control and Prevention (CDC) Wide-Ranging Online Data for Epidemiologic Research (WONDER) database\u0026mdash;provide unique opportunities to explore cause-specific mortality patterns over time [8].\u003c/p\u003e\n\u003cp\u003eWhile prior research has extensively documented overall CVD mortality trends [9], few studies have systematically examined CVD deaths accompanied by RF[10, 11].\u003c/p\u003e\n\u003cp\u003eGiven the close pathophysiological interplay between cardiovascular and respiratory systems, especially among aging individuals and those with chronic conditions, investigating this overlapping mortality pattern may yield critical insights into evolving disease dynamics and healthcare inequities [12,13]. Here, we analyzed national and state-level trends in CVD-related mortality with RF as a contributing cause in the U.S. from 1999 to 2020. Using CDC WONDER data, we quantified changes in age-adjusted mortality rates (AAMRs) and applied Joinpoint regression analysis to detect inflection points that indicate shifts in mortality trajectories over time.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data sources\u003c/h2\u003e \u003cp\u003eThe CDC\u0026rsquo;s Wide-Ranging Online Data for Epidemiologic Research (WONDER) database was used to obtain death certificate data from 1999 to 2020 [14]. CVD deaths were extracted using ICD-10 codes I00\u0026ndash;I99 as the underlying cause of death, with RF coded as a contributing cause (ICD-10: J96.0\u0026ndash;J96.1, J96.9). Since the dataset contains de-identified public use data, institutional review board approval was not applicable. The study was conducted in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines [15].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study variables\u003c/h2\u003e \u003cp\u003eWe examined primary liver cancer-related deaths by sex, ethnicity [non-Hispanic White (NH White), non-Hispanic Black (NH Black), Hispanic, and non-Hispanic other (NH other)], census region, state, and urbanization status (metropolitan vs. nonmetropolitan, based on the 2013 NCHS Urban\u0026ndash;Rural Classification Scheme) [16].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e \u003cp\u003eAAMRs per 100,000 population were calculated using the 2000 U.S. standard population. Temporal trends were assessed using Joinpoint Regression Program (version 5.4.0; National Cancer Institute, Bethesda, MD, USA) [17, 18]. The maximum number of joinpoints was set to 4, and a log-linear model was used to estimate the APC and the AAPC, both with 95% CIs [19]. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Statistically significant values are marked with an asterisk (*) in the results section. Analyses were stratified by geographic variables to evaluate disparities in mortality patterns.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003e3.1 Trends by sex\u003c/h2\u003e\n \u003cp\u003eFrom 1999 to 2020, the AAMR in males increased from 22.88 (95% CI: 22.51\u0026ndash;23.26) in 1999 to 32.94 (95% CI: 32.61\u0026ndash;33.28) in 2020, with an AAPC of 1.71 (95% CI: 1.37\u0026ndash;2.05)*. The APC for males varied across time periods: 1999\u0026ndash;2010: APC = -0.24 (95% CI : -0.56-0.08); 2010\u0026ndash;2017: APC\u0026thinsp;=\u0026thinsp;4.80 (95% CI : 4.11\u0026ndash;5.50); 2017\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;1.83 (95% CI : 0.18\u0026ndash;3.52). In female patients, the AAMR also increased over the study period, from 17.31 (95% CI: 17.07\u0026ndash;17.56) in 1999 to 24.45 (95% CI: 24.20\u0026ndash;24.70) in 2020. The AAPC was 1.56 (95% CI: 0.83\u0026ndash;2.29). The APC by time period for females was: 1999\u0026ndash;2009: APC = -0.09 (95% CI: -0.50-0.33); 2009\u0026ndash;2014: APC\u0026thinsp;=\u0026thinsp;2.79 (95% CI: 1.20\u0026ndash;4.40); 2014\u0026ndash;2017: APC\u0026thinsp;=\u0026thinsp;5.83 (95% CI: 1.29\u0026ndash;10.57); 2017\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;0.86 (95% CI: -1.15-2.91). All the above changes are visualized in Fig.\u0026nbsp;1 and further detailed in Supplemental Table\u0026nbsp;1.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003e3.2 Trends by race\u003c/h2\u003e\n \u003cp\u003eMinor discrepancies were observed between the total number of subjects and the sum across ethnic groups in 1999 and 2020. Specifically, ethnicity information was missing for 91 subjects in 1999 and 125 subjects in 2020. The proportion of missing cases was minimal (\u0026lt;\u0026thinsp;0.3%) and is unlikely to have influenced the observed temporal trends in age-adjusted mortality rates.\u003c/p\u003e\n \u003cp\u003eNH Black consistently had the highest AAMR among racial groups, increasing from 26.17 (95% CI: 25.33\u0026ndash;27.01) in 1999 to 37.17 (95% CI: 36.41\u0026ndash;37.92) in 2020, with an AAPC of 1.35 (95% CI: 1.01\u0026ndash;1.69)*. APC by time period for NH Black: 1999\u0026ndash;2012: APC\u0026thinsp;=\u0026thinsp;0.04 (95% CI: -0.37-0.46); 2012\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;3.52 (95% CI:2.83\u0026ndash;4.22)*.\u003c/p\u003e\n \u003cp\u003eAmong Hispanic patients, the AAMR increased from 21.56 (95% CI: 20.49\u0026ndash;22.64) in 1999 to 25.45 (95% CI: 24.81\u0026ndash;26.09) in 2020. The AAPC was 0.96 (95% CI: 0.47\u0026ndash;1.44)*. APC by time period: 1999\u0026ndash;2010: APC = -0.16 (95% CI: -0.95-0.64); 2010\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;2.19 (95% CI: 1.55\u0026ndash;2.84)*.\u003c/p\u003e\n \u003cp\u003eAmong NH White, AAMR decreased from 18.67 (95% CI: 18.45\u0026ndash;18.88) in 1999 to 27.79 (95% CI: 27.55\u0026ndash;28.02) in 2020. The AAPC was 1.85 (95% CI: 1.23\u0026ndash;2.48)*. APC by time period: 1999\u0026ndash;2009: APC = -0.15 (95% CI: -0.55-0.25); 2009\u0026ndash;2013: APC\u0026thinsp;=\u0026thinsp;3.29 (95% CI: 0.86\u0026ndash;5.78); 2013\u0026ndash;2017: APC\u0026thinsp;=\u0026thinsp;6.11 (95% CI: 3.88\u0026ndash;8.38); 2017\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;1.14 (95% CI: -0.77-3.08).\u003c/p\u003e\n \u003cp\u003eThe AAMR for NH Other increased from 18.97 (95% CI: 17.59\u0026ndash;20.34) in 1999 to 18.92 (95% CI: 18.22\u0026ndash;19.62) in 2020. The AAPC was 0.40 (95% CI: -0.03-0.83)*.\u003c/p\u003e\n \u003cp\u003eAPC by time period: 1999\u0026ndash;2014: APC = -0.50(95% CI: -0.94\u0026ndash;0.07); 2014\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;2.69 (95% CI: 1.47\u0026ndash;3.92). See Fig.\u0026nbsp;2 and Supplemental Table\u0026nbsp;1 for detailed trends for all racial groups.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003e3.3 Trends by census regions\u003c/h2\u003e\n \u003cp\u003eAll census regions showed an increase in AAMR over time. The AAMR for Midwest increased from 16.21 (95% CI: 15.83\u0026ndash;16.60) in 1999 to 27.22 (95% CI: 26.78\u0026ndash;27.65) in 2020. The AAPC was 2.40 (95% CI: 1.92\u0026ndash;2.89)*. APC by time period: 1999\u0026ndash;2010: APC = -0.18 (95% CI: -0.63-0.27); 2010\u0026ndash;2017: APC\u0026thinsp;=\u0026thinsp;6.37 (95% CI: 5.36\u0026ndash;7.39); 2017\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;2.90 (95% CI: 0.51\u0026ndash;5.35).\u003c/p\u003e\n \u003cp\u003eAmong Northeast, the AAMR increased from 18.71 (95% CI: 18.28\u0026ndash;19.15) in 1999 to 25.62 (95% CI: 25.17\u0026ndash;26.07) in 2020. The AAPC was 1.50 (95% CI: 1.23\u0026ndash;1.77)*. APC by time period: 1999\u0026ndash;2009: APC\u0026thinsp;=\u0026thinsp;0.01 (95% CI: -0.46-0.48); 2009\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;2.88 (95% CI: 2.52\u0026ndash;3.24)*.\u003c/p\u003e\n \u003cp\u003eFor South, the AAMR also increased over the study period, from 20.48 (95% CI: 20.12\u0026ndash;20.84) in 1999 to 29.66 (95% CI: 29.32-30.00) in 2020. The AAPC was 1.64 (95% CI: 1.25\u0026ndash;2.03)*. The APC by time period for South was: 1999\u0026ndash;2010: APC\u0026thinsp;=\u0026thinsp;0.05 (95% CI: -0.27-0.38); 2010\u0026ndash;2018: APC\u0026thinsp;=\u0026thinsp;4.26 (95% CI: 3.71\u0026ndash;4.82)*; 2018\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;0.10 (95% CI: -3.24-3.55).\u003c/p\u003e\n \u003cp\u003eAmong West, the AAMR increased from 22.68 (95% CI: 22.17\u0026ndash;23.18) in 1999 to 28.73 (95% CI: 28.30-29.17) in 2020. The AAPC was 1.29 (95% CI: 0.61\u0026ndash;1.96)*. APC by time period: 1999\u0026ndash;2013: APC\u0026thinsp;=\u0026thinsp;0.00 (95% CI: -0.34-0.34); 2013\u0026ndash;2017: APC\u0026thinsp;=\u0026thinsp;6.79 (95% CI: 3.60-10.08)*; 2017\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;0.18 (95% CI: -2.47-2.90). Regional differences are illustrated in Fig.\u0026nbsp;3 and further detailed in Supplemental Table\u0026nbsp;1.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003e3.4 Trends by urbanization\u003c/h2\u003e\n \u003cp\u003eFrom 1999 to 2020, the AAMR in metropolitan areas increased from 19.98 (95% CI: 19.75\u0026ndash;20.21) in 1999 to 27.61 (95% CI: 27.39\u0026ndash;27.83) in 2020, with an AAPC of 1.50 (95% CI: 0.88\u0026ndash;2.11)*. APC for metropolitan areas: 1999\u0026ndash;2009: APC = -0.18 (95% CI: -0.54-0.18); 2009\u0026ndash;2014: APC\u0026thinsp;=\u0026thinsp;2.81 (95% CI: 1.47\u0026ndash;4.18); 2014\u0026ndash;2017: APC\u0026thinsp;=\u0026thinsp;5.57 (95% CI: 1.75\u0026ndash;9.53); 2017\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;0.96 (95% CI: -0.72-2.67). In nonmetropolitan areas, the AAMR also increased from 17.52 (95% CI: 17.07\u0026ndash;17.96) in 1999 to 31.56 (95% CI: 31.02\u0026ndash;32.10) in 2020. The AAPC was 2.67 (95% CI: 2.27\u0026ndash;3.08)*. APC by time period: 1999\u0026ndash;2011: APC\u0026thinsp;=\u0026thinsp;0.44 (95% CI: 0.13\u0026ndash;0.76); 2011\u0026ndash;2017: APC\u0026thinsp;=\u0026thinsp;7.48 (95% CI: 6.41\u0026ndash;8.56); 2017\u0026ndash;2020: APC\u0026thinsp;=\u0026thinsp;2.31 (95% CI: 0.39\u0026ndash;4.27)*. See Fig.\u0026nbsp;4 and Supplemental Table\u0026nbsp;1 for details.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003e3.5. Distribution of state-Level mortality and trends in the U.S.\u003c/h2\u003e\n \u003cp\u003eIn the spatial analysis, we mapped state-level total deaths (Fig. 5A) and AAMR (Fig. 5B) in 2020, as well as the percentage change in deaths (Fig. 5C) and AAPC (Fig. 5D) from 1999 to 2020. State-level distributions of deaths and AAMR were displayed using discrete classification with fixed legends, ensuring comparability across states. While some states reported the highest absolute number of deaths in 2020, their corresponding AAMR values were not always the highest, reflecting differences in population size and age structure (Supplemental Table 1). In addition, Idaho exhibited one of the steepest increases in age-adjusted mortality rate (AAMR) nationwide, rising from 8.11 (95% CI: 6.19\u0026ndash;10.44) in 1999 to 35.35 (95% CI: 32.13\u0026ndash;38.57) in 2020, with an AAPC of 7.44% (95% CI: 2.17\u0026ndash;12.98)*. The percentage change in deaths over 1999\u0026ndash;2020 was visualized with a warm color scale, highlighting substantial heterogeneity in growth magnitude across states. Most states experienced an increase, but the extent of change varied considerably. Finally, the distribution of AAPC was represented on a blue-to-red gradient, with positive values indicating an increase. Most states exhibited positive AAPC, consistent with a long-term upward trend (Supplemental Table 1).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this nationally representative, multidecade analysis of U.S. mortality records, we found that CVD deaths with RF listed as a contributing cause increased steadily across sex, ethnicity, census regions, urbanization, and state categories from 1999 to 2020. These findings extend prior work on overall CVD mortality trends, which typically gave limited attention to the cardiopulmonary overlap that frequently precedes terminal decline [9, 20, 21]. Earlier studies documented that U.S. CVD mortality plateaued in the early 2000s and began rising in some subgroups over the last decade, largely because of increasing metabolic disease and population aging [22\u0026ndash;24]. In our analysis, the rise in cardiopulmonary-related CVD deaths was even more pronounced\u0026mdash;particularly after 2010\u0026mdash;characterized by sharp inflection points across both sexes and nearly all racial and geographic strata. This pattern aligns with growing evidence that respiratory comorbidities such as chronic obstructive pulmonary disease, obesity hypoventilation, and acute pulmonary infections are increasingly common among patients with advanced cardiac disease [25\u0026ndash;28]. However, the rate of increase we observed exceeded what would be expected from CVD burden alone [29], suggesting a compounding effect of multimorbidity in vulnerable populations [30, 31].\u003c/p\u003e\n\u003cp\u003eConsistent with historical patterns, males maintained higher age-adjusted mortality rates than females throughout the study period [32, 33]. Prior literature has attributed sex differences in CVD outcomes to variations in cardiopulmonary physiology, healthcare-seeking behavior, and comorbidity profiles [34\u0026ndash;40]. Our findings build on this evidence by demonstrating that both sexes experienced significant long-term increases in RF-related CVD mortality, with particularly steep rises between 2010 and 2017. This pronounced inflection likely reflects the growing burden of obesity, diabetes, and chronic lung disease, compounded by environmental stressors such as deteriorating air quality, all of which heighten cardiopulmonary vulnerability [41, 42]. In line with longstanding demographic research on CVD disparities, non-Hispanic Black adults consistently exhibited the highest mortality rates, with especially rapid increases after 2012 [43, 44]. Hispanics and non-Hispanic Whites also demonstrated significant upward trends, albeit with different temporal patterns. Together, these observations indicate that although risk profiles vary across populations, the rising burden of cardiopulmonary mortality is widespread and layered upon persistent structural inequities.\u003c/p\u003e\n\u003cp\u003eGeographic trends further highlight the influence of contextual factors. Mortality increased across all regions and levels of urbanization, with particularly sharp rises in nonmetropolitan areas and persistently high rates in the Midwest and South. These patterns underscore how disparities in healthcare access, chronic disease management, and socioeconomic conditions amplify cardiopulmonary mortality [45]. While populous states contributed the largest absolute number of deaths, several smaller states\u0026mdash;such as Idaho\u0026mdash;experienced among the fastest relative increases. These steep trends may reflect shifting demographic structures, state-level differences in public health initiatives, and evolving environmental exposures, including wildfire-related air pollution in western states [46\u0026ndash;48]. Overall, these findings demonstrate that cardiopulmonary mortality is dynamic and shaped by intersecting demographic, environmental, and healthcare system transitions.\u003c/p\u003e\n\u003cp\u003eThe observed trajectory underscores the urgent need for integrated management of cardiac and respiratory comorbidities\u0026mdash;an area traditionally divided between specialties. As heart failure, arrhythmias, and ischemic disease increasingly co-occur with chronic respiratory insufficiency, coordinated cardiopulmonary care models may improve patient outcomes [49\u0026ndash;52]. At the population level, prevention efforts must address upstream determinants common to both conditions, including smoking, air pollution, obesity, and inadequate access to chronic disease management resources [53, 54]. The sharp acceleration in mortality after 2010 coincides with rising multimorbidity in the aging U.S. population, suggesting that without targeted interventions, the burden of overlapping chronic diseases is likely to intensify [55, 56].\u003c/p\u003e\n\u003cp\u003eThis study offers valuable insights into long-term trends in CVD mortality associated with RF across the U.S., but several limitations warrant consideration. First, reliance on aggregated CDC mortality data introduces potential misclassification and underreporting, and the absence of individual-level information limits assessment of their specific contributions to observed trends [57]. Second, we did not evaluate the impact of therapeutic interventions nor differentiate among causes of death within the broader CVD population. Future research should build on this descriptive framework by linking population-based mortality data with detailed clinical, behavioral, and treatment information (e.g., SEER\u0026ndash;Medicare or institutional datasets) and by applying spatial regression or multivariable modeling to more precisely identify contextual determinants underlying these disparities [58\u0026ndash;61].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, CVD mortality with RF as a contributing cause increased substantially in the U.S. from 1999 to 2020, with accelerated rises in the past decade and disproportionately high burdens among Black adults, residents of the Midwest and South, and individuals living in nonmetropolitan areas. These findings highlight the growing need to reconceptualize cardiopulmonary disease prevention and management through an integrated lens and to address structural determinants driving persistent disparities. As the population continues to age and multimorbidity becomes increasingly common, the intersection of cardiovascular and respiratory disease will represent a pivotal frontier for clinical innovation and public health intervention.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eLM, ML and HZ analyzed the data and wrote the manuscript. PD designed the research. All authors read and approved the manuscript and agree to be accountable for all aspects of the research in ensuring that the accuracy or integrity of any part of the work (including the provided data) are appropriately investigated and resolved. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003cp\u003eFunding Statement\u003c/p\u003e \u003cp\u003eFunding: No funding was received.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003edata available on request\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVirani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, et al. Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association. Circulation. 2021;143(8):e254-e743.\u003c/li\u003e\n\u003cli\u003eBenjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, et al. 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Nutrition. 2022;102:111743.\u003c/li\u003e\n\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-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CDC WONDER, Respiratory failure, cardiovascular mortality, Joinpoint Regression, Global disease burden","lastPublishedDoi":"10.21203/rs.3.rs-8241552/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8241552/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCardiovascular disease (CVD) remains the leading cause of death worldwide, with its burden in the U.S. continuing to rise despite substantial advances in prevention and care. Respiratory failure (RF) is a frequent terminal event in advanced CVD, yet national patterns and demographic disparities in CVD-related deaths involving RF remain poorly characterized. This study aimed to quantify temporal trends and regional variations in CVD mortality with RF as a contributing cause from 1999 to 2020.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe obtained U.S. death certificate data from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database (1999\u0026ndash;2020). Deaths were identified using ICD-10 codes I00\u0026ndash;I99 for CVD as the underlying cause and J96.0\u0026ndash;J96.1, J96.9 for RF as a contributing cause. Age-adjusted mortality rates (AAMRs) were calculated per 100,000 population using the 2000 U.S. standard population. Joinpoint regression analysis was applied to estimate annual percent change (APC) and average annual percent change (AAPC) with 95% confidence intervals (CIs) across sex, ethnicity, census regions, urbanization, and state categories.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFrom 1999 to 2020, the national AAMR for CVD-related deaths with RF increased markedly. In males, AAMR rose from 22.9 (95% CI, 22.5\u0026ndash;23.3) to 32.9 (95% CI, 32.6\u0026ndash;33.3) with an AAPC of 1.71% (95% CI, 1.37\u0026ndash;2.05); in females, from 17.3 (95% CI, 17.1\u0026ndash;17.6) to 24.5 (95% CI, 24.2\u0026ndash;24.7) with an AAPC of 1.56% (95% CI, 0.83\u0026ndash;2.29). Non-Hispanic Black adults consistently exhibited the highest mortality, whereas nonmetropolitan areas showed a steeper rise (AAPC, 2.67%; 95% CI, 2.27\u0026ndash;3.08) than metropolitan regions (AAPC, 1.50%; 95% CI, 0.88\u0026ndash;2.11). All four census regions demonstrated upward trends, with the Midwest showing the greatest increase (AAPC, 2.40%; 95% CI, 1.92\u0026ndash;2.89). State-level analysis revealed pronounced geographic heterogeneity, with Idaho showing the largest rise in AAMR (AAPC, 7.44%; 95% CI, 2.17\u0026ndash;12.98). Multiple joinpoints indicated distinct inflection periods, particularly after 2010, corresponding to accelerated increases across several subgroups.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBetween 1999 and 2020, CVD-related mortality with RF as a contributing cause increased substantially across the U.S., with notable disparities by sex, ethnicity, geography, and urbanization. These findings underscore the growing intersection between cardiovascular and respiratory diseases and highlight the need for integrated prevention and management strategies targeting high-risk populations and regions.\u003c/p\u003e","manuscriptTitle":"Epidemiologic Patterns and Disparities in Cardiovascular Deaths Associated With Respiratory Failure Across Two Decades in the U.S","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-26 19:00:46","doi":"10.21203/rs.3.rs-8241552/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-01-02T13:26:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"20311878544658821150267897808116145551","date":"2025-12-24T12:52:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-24T12:42:23+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-02T06:09:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-02T02:43:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-02T02:42:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-11-30T11:05:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dfa57121-4a21-4e49-9a77-dcac6dc8dedd","owner":[],"postedDate":"December 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-26T19:00:46+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-26 19:00:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8241552","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8241552","identity":"rs-8241552","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}