Rising Obesity-Related Cardiovascular Mortality in the United States, 1999–2020: Accelerating Trends and Widening Disparities

Rising Obesity-Related Cardiovascular Mortality in the United States, 1999–2020: Accelerating Trends and Widening Disparities | 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 Obesity-Related Cardiovascular Mortality in the United States, 1999–2020: Accelerating Trends and Widening Disparities Gaurav Sharma, Sai Swetha Pavuluri, Suhas Kataveni, Shashank Trivedi, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7530128/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Obesity is a major and growing driver of cardiovascular disease (CVD) in the United States, contributing to hypertension, diabetes, dyslipidemia, and structural cardiac changes that elevate the risk of ischemic heart disease, heart failure, and stroke. After decades of declining CVD mortality, recent national trends show a concerning reversal, coinciding with record-high obesity prevalence. We quantified national trends and disparities in obesity-related CVD mortality from 1999–2020 using de-identified death certificate data from the CDC WONDER database for U.S. residents aged 15–84 years, including deaths with circulatory disease (ICD-10 I00–I99) as the underlying cause and obesity (E66.0–E66.9) as a contributing cause. Age-adjusted mortality rates (AAMR) standardized to the 2000 U.S. population were analyzed using joinpoint regression to estimate annual percent change (APC) and detect inflection points. From 1999–2018, AAMR rose from 2.75 to 6.61 per 100,000 (APC 4.79%; 95% CI 4.60–4.98), followed by a significant post-2018 acceleration (APC 11.05%; 95% CI 6.76–15.51) to 8.36 in 2020. Mortality was highest among adults 65–74 years, males, Black Americans, and nonmetropolitan residents, with a 5.1-fold state variation. Young adults (15–24 years) had the largest relative increase (+210%). The 2020 surge was independent of COVID-19 mortality, indicating gaps in chronic disease management. These results highlight a growing obesity-related CVD mortality burden, with widening disparities by age, sex, race, and geography, emphasizing urgent, equity-focused prevention and targeted interventions. Hospital Medicine Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Obesity has become a nationwide epidemic in the United States and a leading driver of cardiovascular risk. Approximately 39–40% of U.S. adults meet the criteria for obesity (body mass index ≥ 30 kg/m²) ( 1 ), with rates disproportionately higher among disadvantaged and rural populations. Excess adiposity adversely affects nearly every organ system and, in particular, promotes hypertension, dyslipidemia, insulin resistance, systemic inflammation, and endothelial dysfunction. As noted in a recent World Heart Federation statement, “increased adiposity, particularly visceral fat, is linked to cardiovascular risk and CVD via multiple direct and indirect mechanisms” ( 2 ). Obesity triggers metabolic and neurohormonal cascades that accelerate coronary atherosclerosis and cardiac remodeling and independently elevate the risk of ischemic heart disease (IHD), heart failure (HF), and stroke ( 2 ). It contributes to type 2 diabetes, hypertension, and dyslipidemia ( 2 ) and induces structural changes such as left ventricular hypertrophy, diastolic dysfunction, and a pro-thrombotic state. These mechanisms explain why over two-thirds of global deaths attributable to high body mass index are due to cardiovascular disease ( 3 ). In essence, obesity is a chronic, systemic condition that seeds multiple cardiovascular pathologies. Historically, U.S. cardiovascular mortality declined steadily for decades; however, that progress has stalled. National analyses revealed that the decline in CVD mortality began decelerating around 2010–2011 ( 4 ). By the late 2010s, heart disease mortality had plateaued, and overall U.S. life expectancy leveled off, even reversing in some years ( 5 ). Mehta et al. demonstrated that from 2010–2017, slowing declines in CVD deaths, especially at midlife, were the primary cause of the plateau in life expectancy ( 5 ). These changes coincided with a sharp rise in obesity prevalence, which surged during the 2000s and reached record highs in the 2010s ( 1 ). The increasing burden of weight-related complications has undermined cardiovascular health, threatening decades of progress. Recent evidence indicates a rising mortality burden specifically attributable to obesity. Our analysis of CDC WONDER data, using joinpoint regression, identified a marked inflection in 2018 in obesity-related cardiovascular deaths, mirroring other national reports. Raisi-Estabragh et al. found that obesity-related cardiovascular deaths nearly tripled between 1999 and 2020 (age-adjusted mortality rising from 2.2 to 6.6 per 100,000) ( 6 ), with IHD as the predominant cause and hypertensive heart disease especially prominent among Black decedents ( 6 ). Sohail et al. reported that obesity-related IHD mortality more than doubled during this period, with a sharp acceleration after 2018 ( 7 ). Ahmed et al. documented a steady rise in age-adjusted coronary artery disease mortality from 1999–2018, followed by a surge from 2018–2022 ( 8 ). Achara et al. observed an increase in obesity-related circulatory deaths between 2010–2020 (AAMR from 1.8 to 3.1 per 100,000), with the steepest increases among midlife and older adults and among Black Americans ( 9 ). These findings confirm that obesity’s mortality impact has intensified, with a clear change-point near 2018. Importantly, this inflection predates the COVID-19 pandemic, implicating broader health system and population factors. The burden of obesity-related CVD mortality is unevenly distributed. Across studies, men have higher rates than women; Ashraf et al. reported an age-adjusted rate of 5.8 per 100,000 for men versus 4.0 for women ( 10 ). Older adults have the highest rates, with Achara et al. noting the largest absolute increases in those aged 55–74 years ( 9 ). Racial disparities are stark: non-Hispanic Black Americans consistently show the highest rates and fastest growth ( 6 , 10 ), with Raisi-Estabragh et al. reporting Black mortality rates three times those of White individuals by 2020 ( 6 ). American Indian/Alaska Native populations have seen the steepest percentage increases ( 6 ), consistent with very high obesity prevalence and limited healthcare access in those communities. Geographic disparities align with obesity and CVD hotspots, with rural and socioeconomically disadvantaged areas experiencing higher mortality; for example, CDC data from 2013–2016 show obesity prevalence at 47% among women in nonmetropolitan areas compared with 38% in large cities ( 1 ). Ashraf et al. found AAMR for obesity-related CVD of 3.47 in non-metro versus 2.78 in metro areas ( 7 ), and several Deep South and Appalachian states (e.g., Mississippi, West Virginia, Oklahoma) consistently rank among the highest nationally ( 11 ). These disparities reflect underlying social and structural determinants. Economic deprivation, food insecurity, and limited healthcare access cluster obesity and CVD risk in marginalized communities. Sociologists and health equity experts highlight that “neighbourhood disadvantage” and “reduced food security” are linked to poorer cardiovascular health ( 12 ). Food insecurity is also linked to higher rates of hypertension, coronary disease and related conditions ( 12 ). Structural racism and inequity further entrench these disparities: for example, policies that restrict minority communities to unhealthy environments and unequal healthcare produce higher CVD risk in Black and Hispanic groups ( 13 ). A recent AHA Presidential Advisory explicitly calls out structural racism as a fundamental driver of health disparities ( 14 ). Socioeconomic disadvantage including low education and income, confers CVD risk comparable to traditional biomedical factors ( 15 ). Rural residents face additional barriers, including fewer healthcare resources and longer emergency response times, which the AHA has highlighted as a critical health equity concern ( 16 ). In summary, obesity interacts with demographic and geographic inequities, disproportionately affecting male, Black, and rural populations due to a lifetime of stacked disadvantages. At the molecular and physiological level, obesity’s cardiovascular effects are multifactorial. Adipose tissue in obesity secretes inflammatory cytokines (e.g., IL-6, TNF-α), adipokines (e.g., leptin, adiponectin imbalance), and promotes insulin resistance and hyperglycemia, fueling atherosclerosis and cardiomyopathy ( 2 ). Hemodynamically, obesity increases blood volume and cardiac output, leading to left ventricular hypertrophy and diastolic dysfunction. The combined metabolic and pressure overload makes obesity a potent cause of heart failure – indeed, HF is often described as the cardiovascular condition “most closely linked” to obesity ( 17 ). Abdesselam et al. note that obesity-driven hemodynamic and endocrine changes create a “vicious cycle” of heart failure and cardiovascular mortality ( 17 ). In summary, both epidemiology and basic science converge: chronic obesity fundamentally alters cardiovascular physiology in ways that raise disease incidence and worsen outcomes. Finally, it is important to note that the recent acceleration in obesity-related CVD mortality is not simply an artifact of the COVID-19 pandemic. While 2020 saw a noticeable jump in deaths, analyses show that most of that excess is likely due to indirect effects of the pandemic era (like delayed care and unhealthy lifestyle changes), rather than the virus itself. For example, a UK study estimated that only ~ 5% of the rise in cardiovascular deaths during 2020 was attributable to COVID-19 infection, with the rest due to acute myocardial infarctions, strokes, and heart failure likely from care disruptions ( 18 ). Similarly, Ashraf et al. report that the obesity-CVD mortality acceleration from 2018–2020 was partly linked to pandemic-related weight gain, but emphasize that a notable upturn already began in 2018 ( 10 ). Qamar et al. also quantified thousands of excess obesity-CVD deaths in early 2020 ( 19 ). Thus, the inflection point we identified in 2018 precedes COVID-19, indicating that underlying trends (worsening obesity rates, stagnating risk-factor control, and inequities in care) were already driving higher mortality. In sum, mounting evidence indicates that obesity has emerged as a major and growing contributor to cardiovascular mortality in the U.S. Obesity triggers metabolic and structural pathways that cause heart disease, and this effect is magnified among the elderly, men, and historically disadvantaged groups. Structural factors, including poverty, food environments, and systemic racism, underlie the observed disparities by race, geography, and urbanization status ( 13 , 15 ). The joinpoint-identified inflection in 2018 highlights that the worst of these trends began before COVID-19, underscoring the need for urgent public health action. Using national mortality data from 1999–2020, we characterize the trajectory of obesity-related cardiovascular deaths by demographic and regional subgroups, quantifying the scale of this public health crisis. Methods 1. Data Source and Case Definition De-identified mortality records (1999–2020) were extracted from the CDC WONDER database, restricted to U.S. residents aged 15–84 years. Deaths were included if: Underlying cause was circulatory disease (ICD-10: I00-I99) Obesity (E66.0-E66.9) was listed as a contributing cause. Population denominators came from U.S. Census bridged-race estimates. 2. Stratification Variables Analyses were stratified across five axes: Age: Seven ten-year groups (15–24 to 75–84 years) Urbanization: Six 2013 NCHS categories (e.g., Large Central Metro to NonCore Nonmetro) Race: White, Black, Asian/Pacific Islander, American Indian/Alaska Native Sex: Male/Female Geography: 50 states and the District of Columbia 3. Rate Calculation and Standardization Crude mortality rates (deaths per 100,000 person-years) were computed for age subgroups. Age-adjusted rates (AAR) standardized to the 2000 U.S. standard population were calculated using direct standardization. Standard errors (SE) accounted for sparse data per CDC protocols. 4. Joinpoint Regression Analysis Temporal trends were modeled using Joinpoint Regression Software (v5.4.0.0; National Cancer Institute). Parameters: Model: Log-linear rates with heteroscedastic errors Inflection detection: Grid search with permutation testing (overall α = 0.05; 4,499 replicates) Constraints: Minimum 2 observations between joinpoints; minimum 2 at endpoints Output: Annual percent change (APC), inflection points (τ) with 95% CIs (parametric method) Final model selection: Permutation tests identified optimal joinpoints (1 joinpoint retained, *p*=0.012) 5. Disparity Quantification Subgroup comparisons used: Rate ratios with 95% confidence intervals Weighted *t*-tests for geographic extremes (e.g., Vermont vs. Virginia) SE-based z-scores for racial/urbanization contrasts (α = 0.05) 6. Software and Ethics Tools: Joinpoint (trends), Datawrapper/RAWGraphs (visualization), Excel (descriptive statistics) Ethics: CDC WONDER provides de-identified public data; IRB exemption granted per 45 CFR § 46.104(d)( 4 ). Key Methodological Rigor Standardization: All AARs used identically weighted 2000 U.S. population for cross-strata comparability. Bias Control: Permutation tests prevented overfitting in joinpoint selection; SEs addressed small-count instability. Reproducibility: Full CDC WONDER query parameters and Joinpoint configuration files archived. Results Joinpoint regression analysis revealed a statistically significant inflection point in 2018 (95% CI: 2017–2018; permutation test p = 0.012), partitioning obesity-related circulatory mortality trends into two distinct phases. From 1999–2018, mortality increased steadily at an Annual Percent Change (APC) of 4.79% (95% CI: 4.60–4.98; p < 0.001), rising from 2.75 to 6.53 per 100,000. This 19-year period exhibited consistent linear progression ( R² = 0.98), with average annual increases of 3.1%. The trajectory shifted dramatically post-2018, accelerating to an APC of 11.05% (95% CI: 6.76–15.51; p < 0.001). This acceleration culminated in an unprecedented 2020 rate of 8.36 per 100,000—a 3.4-fold surge since 1999 and a 19.1% single-year leap from 2019 (Fig. 1 ). Model diagnostics confirmed robustness (Mean Squared Error: 11.29; uncorrelated errors). Line graph showing age-adjusted mortality rates (per 100,000) standardized to the 2000 U.S. population, for adults aged 15–84 years. Rates increased steadily from 2.75 in 1999 to 6.82 in 2019, followed by a sharp rise to 8.36 in 2020. Joinpoint regression identified a significant inflection point in 2018, marking an acceleration in the rate of increase. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00–I99 with contributing cause ICD-10: E66.0–E66.9. Age-specific mortality demonstrated a steep gradient, escalating from 0.23 per 100,000 in 15–24 year-olds to a peak of 11.37 in 65–74 year-olds. Young adults (25–34 years) experienced a clinically significant burden (1.20/100,000), while the 55–64 year cohort accounted for the highest absolute deaths (78,164), reflecting demographic distribution. Notably, the 15–24 year group saw a 210% cumulative increase since 1999—the largest relative rise across age strata (Fig. 2 ). Bar chart showing total number of obesity-related cardiovascular deaths over the study period stratified by 10-year age cohorts (15–24 to 75–84 years). Death counts were derived from CDC WONDER Multiple Cause of Death data, restricted to U.S. residents aged 15–84 years with obesity (ICD-10: E66.0–E66.9) listed as a contributing cause and circulatory disease (ICD-10: I00–I99) as the underlying cause. The 55–64 year age group accounted for the highest number of deaths, followed by 45–54 and 65–74 years. Urbanization profoundly influenced outcomes, with a clear rural-urban disparity gradient (Fig. 3 ). Micropolitan (nonmetro) areas recorded the highest mortality (5.48 ± 0.03), exceeding Large Fringe Metro rates (3.80 ± 0.02) by 44.2% (p < 0.001). Nonmetropolitan regions collectively (Micropolitan + NonCore) averaged 5.31 ± 0.03 versus 4.57 ± 0.01 in metropolitan areas (rate ratio: 1.16; p < 0.001). Medium Metro (4.88 ± 0.02) and Small Metro (5.06 ± 0.03) zones exhibited intermediate burdens, though all urban categories remained significantly below rural counterparts. Horizontal bar chart showing total number of obesity-related cardiovascular deaths over the study period, stratified by 2013 NCHS Urban–Rural Classification. Large central metropolitan areas accounted for the highest number of deaths overall, followed by medium metro and large fringe metro areas. Nonmetropolitan regions (micropolitan and noncore) had smaller absolute death counts but higher age-adjusted mortality rates in relative terms. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00–I99 (circulatory diseases) with contributing cause ICD-10: E66.0–E66.9 (obesity). Racial disparities were stark and persistent (Fig. 4 ). Black Americans endured the highest mortality (8.47 ± 0.04)—1.88× the White rate (4.50 ± 0.01; p < 0.001) and 7.6× the Asian/Pacific Islander rate (1.12 ± 0.02). This Black-White disparity widened post-2010 (rate ratio: 1.72 → 1.88). American Indian/Alaska Natives showed elevated mortality (4.83 ± 0.10) but did not significantly differ from Whites after error adjustment (p = 0.07). Pie chart showing the racial distribution of total obesity-related cardiovascular deaths over the study period. White individuals accounted for the majority of deaths, followed by Black or African American individuals. American Indian/Alaska Native and Asian/Pacific Islander groups contributed smaller proportions. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00–I99 (circulatory diseases) with contributing cause ICD-10: E66.0–E66.9 (obesity). Sex-based inequities remained pronounced throughout the study period. Males experienced 47% higher mortality than females (5.79 ± 0.01 vs. 3.93 ± 0.01; p < 0.001), with peak disparity in the 55–64 year cohort (male rate: 13.1 vs. female: 6.8; ratio: 1.92). During the 2018–2020 acceleration phase, male mortality surged 23.6% versus 17.2% in females, amplifying pre-existing gaps (Fig. 5 ). Pie chart showing the sex distribution of total obesity-related cardiovascular deaths over the study period. Males accounted for the majority of deaths (~ 57%), while females accounted for ~ 43%. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00–I99 (circulatory diseases) with contributing cause ICD-10: E66.0–E66.9 (obesity). Geographic analysis revealed a 5.1-fold state-level variation (Fig. 6 ). Vermont (12.62 ± 0.32) and Oklahoma (10.51 ± 0.13) emerged as unexpected hotspots—exceeding national leaders in obesity prevalence (e.g., West Virginia: 5.83 ± 0.13) by > 40%. Conversely, Virginia (2.46 ± 0.04) and Alabama (2.47 ± 0.05) demonstrated the lowest burdens. Regional clustering was evident: New England exhibited elevated mortality (Vermont: 12.62; Rhode Island: 6.03 ± 0.18; New Hampshire: 4.01 ± 0.13), while the South Atlantic formed a low-burden cluster (Virginia: 2.46; Alabama: 2.47; Florida: 3.70 ± 0.03). Appalachia showed concerning elevations (West Virginia: 5.83 ± 0.13; Kentucky: 4.93 ± 0.08; Tennessee: 5.87 ± 0.07), contrasting sharply with neighboring states. Choropleth map showing total number of obesity-related cardiovascular deaths aggregated over the study period. Mortality counts range from 594 to 34,002. Vermont (12.62 ± 0.32) and Oklahoma (10.51 ± 0.13) emerged as unexpected high-burden states, exceeding rates in West Virginia (5.83 ± 0.13) — a national leader in obesity prevalence — by over 40%. Lowest mortality burdens were observed in Virginia (2.46 ± 0.04) and Alabama (2.47 ± 0.05). Regional clustering was evident, with elevated rates in New England and Appalachia, and lower rates across the South Atlantic. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00–I99 with contributing cause ICD-10: E66.0–E66.9. The post-2018 acceleration phase disproportionately impacted specific subpopulations: Black males experienced an APC surge from 5.2% (1999–2018) to 14.1% (2018–2020) Rural residents saw APC jump from 4.1–12.7% in Micropolitan areas Young adults (25–34 years) endured an 18.9% single-year rise in 2020 Synergistic disadvantages were observed at demographic intersections. Rural Black males in high-burden states (Vermont, Oklahoma) experienced mortality rates 5.2× the national average and 7.9× those of urban White females in low-burden states (Virginia, Alabama). This disparity amplification during the acceleration phase suggests emergent vulnerability among historically marginalized groups. Notably, the 2020 mortality surge occurred independently of COVID-19 infection patterns. States with low COVID-19 mortality (e.g., Vermont: 40.6/100,000 COVID deaths) showed extreme obesity-circulatory mortality, while high-COVID states (New Jersey: 353.2/100,000) recorded only moderate increases (3.51 ± 0.05), indicating disruption of chronic disease management as the primary driver. Cumulatively, these results identify 2018 as a critical inflection point for obesity-related circulatory mortality, with accelerating disparities concentrated among Black Americans, males, rural populations, and residents of Vermont/Oklahoma. The 2020 rate (8.36/100,000) represents the highest recorded burden since surveillance began. Discussion Analysis of CDC WONDER mortality data from 1999–2020 reveals a sustained and accelerating rise in U.S. cardiovascular disease (CVD) mortality where obesity is a contributing cause. The APC shifted from 4.79–11.05%, with AAMR increasing from 2.75 to 6.61 per 100,000 before 2018, then surging to 8.36 by 2020; a 3.4-fold increase since 1999. These results parallel national studies attributing post-2018 increases to worsening obesity prevalence, stagnant risk-factor control, and preventive care disruptions ( 20 , 21 ). Age stratification demonstrated a steep gradient, with middle-aged adults (55–64 years) contributing the highest absolute deaths, but the younger group (15–24 years) cohort experiencing the largest proportional increases, underscoring an emerging younger-age burden. These findings parallel reports of rising premature CVD mortality linked to obesity ( 22 ). Marked rural–urban disparities were evident with Micropolitan nonmetro areas recording the highest AAMR (5.48), exceeding large fringe metro rates (3.80) by 44.2% (p < 0.001), with a rural–urban rate ratio of 1.16. National analyses confirm that rural residents face slower improvements in CVD outcomes and higher obesity prevalence ( 23 , 24 ). Limited healthcare access, longer emergency response times, and socioeconomic disadvantage contribute to these differences ( 25 ). Racial disparities were striking, with Black Americans experiencing nearly double the mortality of Whites and much higher rates than Asian/Pacific Islanders. American Indian/Alaska Natives had elevated rates but differences from Whites were not statistically significant after error adjustment. National studies similarly show Black and AI/AN populations suffer disproportionate obesity-related CVD mortality, with AI/AN populations experiencing the steepest proportional increases (> 400%) since 1999 ( 20 , 26 ). Structural racism, healthcare access barriers, and higher comorbidity prevalence are key drivers ( 27 ). Sex-based differences persisted, with males having substantially higher mortality than females. Similar male predominance has been reported nationally, often attributed to differences in health behaviors, comorbidity profiles, and biological factors such as estrogen-mediated cardioprotection in premenopausal women ( 28 ). Geographic patterns revealed up to a 5.1-fold variation in AAMR between states. Vermont and Oklahoma had the highest burdens, far exceeding states with the highest obesity prevalence, such as West Virginia. Conversely, Virginia and Alabama recorded the lowest rates. Regional clustering was apparent, with New England showing elevated mortality and the South Atlantic exhibiting lower burdens. Appalachia, however, demonstrated consistently higher rates than neighboring states. These spatial variations mirror literature identifying high-obesity, low-resource states as CVD mortality hotspots ( 29 ). Importantly, the 2020 surge in obesity-related CVD mortality occurred independently of COVID-19 infection patterns. Vermont, with low COVID-19 mortality, had among the highest obesity–CVD rates, whereas high-COVID states like New Jersey showed only moderate increases. This aligns with evidence that pandemic-era disruptions in chronic disease management, rather than direct viral effects, were primary contributors ( 23 , 25 ). Collectively, these results, reinforced by peer-reviewed literature, depict an accelerating crisis concentrated among Black Americans, males, rural residents, and certain geographic regions. The interplay between biological vulnerability, structural inequities, and healthcare access disparities is evident. Without targeted interventions, the upward trajectory in obesity-related CVD mortality is likely to continue. Conclusion Our findings reveal a sharp post-2018 acceleration in U.S. obesity-related CVD mortality, with profound disparities by race, sex, geography, and urbanization. Black Americans face nearly double the mortality of Whites, rural residents have 44% higher rates than those in large metropolitan areas, and states such as Vermont and Oklahoma record burdens five times higher than low-mortality states. Young adults, though still at lower absolute risk, show alarming proportional increases. These findings demand urgent, equity-focused public health action. First, preventive strategies must prioritize high-risk groups. This includes community-based blood pressure and weight management programs tailored for Black, AI/AN, and rural populations. Second, expanding healthcare infrastructure in nonmetropolitan areas through telehealth, incentives for rural clinicians, and improved emergency services can narrow the rural–urban mortality gap. Third, upstream social determinants must be addressed: improving access to healthy foods, safe physical activity spaces, and stable healthcare coverage will help reduce the underlying drivers of obesity and CVD. Fourth, continuous monitoring is essential. Fifth, targeted policy investments in high-burden states, particularly those with unexpected mortality hotspots like Vermont, can address localized drivers. Without decisive intervention, the convergence of obesity and cardiovascular disease threatens to reverse decades of progress in reducing heart disease mortality. An integrated approach, combining medical care, public health policy, and structural reform, offers the best opportunity to slow and eventually reverse these trends. References Hales, C. M., Fryar, C. D., Carroll, M. D., Freedman, D. S., Aoki, Y., & Ogden, C. L. (2018). Differences in obesity prevalence by demographic characteristics and urbanization level among adults in the United States, 2013–2016. JAMA, 319 (23), 2419–2429. https://doi.org/10.1001/jama.2018.7270 Powell-Wiley TM, Poirier P, Burke LE, Després JP, Gordon-Larsen P, Lavie CJ, et al. 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ESC Heart Failure [Internet]. 2021 Feb [cited 2025 Aug 11];8(1):356–67. Available from: https://onlinelibrary.wiley.com/doi/10.1002/ehf2.13081 Vidal-Perez R, Brandão M, Pazdernik M, Kresoja KP, Carpenito M, Maeda S, et al. Cardiovascular disease and COVID-19, a deadly combination: A review about direct and indirect impact of a pandemic. WJCC [Internet]. 2022 Sept 26 [cited 2025 Aug 11];10(27):9556–72. Available from: https://www.wjgnet.com/2307-8960/full/v10/i27/9556.htm Nabi R, Zanub A, Akhtar M, Chaudhry SAA, Awais AR, Farooqi HA, et al. Concomitant mortality trends due to obesity and hypertension in the U.S.: a 20-year retrospective analysis of the CDC WONDER database. BMC Cardiovasc Disord [Internet]. 2025 July 7 [cited 2025 Aug 11];25(1):496. Available from: https://bmccardiovascdisord.biomedcentral.com/articles/10.1186/s12872-025-04909-z Raisi-Estabragh, Z., et al. (2023). Racial disparities in obesity-related cardiovascular mortality in the United States: Temporal trends from 1999 to 2020. Journal of the American Heart Association, 12 (18), e028409. https://doi.org/10.1161/JAHA.122.028409 Ahmed, M., et al. (2024). Trends and disparities in coronary artery disease and obesity-related mortality in the United States from 1999–2022. Endocrinology, Diabetes & Metabolism, 7 (6), e70010. https://doi.org/10.1002/edm2.70010 Okobi, O. E., et al. (2024). Trends and patterns in obesity-related deaths in the US (2010–2020): A comprehensive analysis using CDC WONDER data. Cureus, 16 (9), e68376. https://doi.org/10.7759/cureus.68376 Cross SH, Mehra MR, Bhatt DL, Nasir K, O’Donnell CJ, Califf RM, et al. Rural-Urban Differences in Cardiovascular Mortality in the US, 1999-2017. JAMA [Internet]. 2020 May 12 [cited 2025 Aug 11];323(18):1852. Available from: https://jamanetwork.com/journals/jama/fullarticle/2765719 Goyal, A., et al. (2025). Emerging trends and disparities in cardiovascular, kidney, and diabetes-related mortality: A retrospective analysis of the CDC WONDER database. PLOS One, 20 (5), e0320670. https://doi.org/10.1371/journal.pone.0320670 .Qamar, A., et al. (2024). Has the first year of the COVID pandemic impacted the trends in obesity-related cardiovascular disease mortality between 1999 and 2019 in the United States? International Journal of Cardiology: Cardiovascular Risk and Prevention, 21 , 200248. https://doi.org/10.1016/j.ijcrp.2024.200248 Nabi, R., et al. (2025). Concomitant mortality trends due to obesity and hypertension in the U.S.: A 20-year retrospective analysis of the CDC WONDER database. BMC Cardiovascular Disorders, 25 (1), 496. https://doi.org/10.1186/s12872-025-04909-z Hameed, I., et al. (2024). Demographic and regional trends of cardiovascular disease and obesity-related mortality in the United States from 1999 to 2021. American Journal of Cardiology, 233 , 51–54. https://doi.org/10.1016/j.amjcard.2024.09.028 Ashraf H, Ashfaq H, Ashraf A. Gender and racial disparities in obesity-related cardiovascular-induced mortality in the USA, 1999–2020. Current Problems in Cardiology [Internet]. 2024 Jan [cited 2025 Aug 11];49(1):102178. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0146280623005959 Yang, H., et al. (2025). A systematic bibliometric analysis of cardiovascular disease risk in obesity (2014–2024). Journal of Multidisciplinary Healthcare, 18 , 3233–3255. https://doi.org/10.2147/JMDH.S504022 Additional Declarations The authors declare no competing interests. Supplementary Files Supplementaryfiles.docx Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-7530128","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":509892889,"identity":"259604d3-abe4-4e1c-8ce5-a8bb258b6116","order_by":0,"name":"Gaurav Sharma","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIie3PsWrDMBCAYR0H8qI6q4QLfQWHToEmeRUbrw30ATKoGOTFzZxOeYVMmRUC6WI6F7S09AXsqWkJoXK2DLHdLVD9ww3HfcMR4nJdYrr39V0dpqMeQlaWdkG9VkLCgNNtIrJUwbwm2IFwRhGWxYtCVm/aiG90dDTkLVafdz+rGx8JlNX9eSJeIx098Gsf5nF2O5mZvkKC4nl1noQFSM1DishjGUxyA5ZQvGokCJJFCKomg9yMOxD7BtMIOVurgOxM3EpEYV8Xcptw7zHtP0mTKIS08RffEqjkdDTeeB/vu70ZLrJ0XVYN5DRQxym73tft/3Lscrlc/6VfBGZQaOrO/38AAAAASUVORK5CYII=","orcid":"","institution":"Clinical Intructor, JNU Medical College, Jaipur","correspondingAuthor":true,"prefix":"","firstName":"Gaurav","middleName":"","lastName":"Sharma","suffix":""},{"id":509892890,"identity":"19808c06-35e5-47e9-95a5-80104f19e403","order_by":1,"name":"Sai Swetha Pavuluri","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIiWNgGAWjYFACxgYQmcDAwHzwwQcgi42dOC0GQC1syYYzQFqYibMKpIXHTJoHxCakRb79cPNnnoo/efyze8ykbX5tk+djZmD88DEHj/FnEtukec4YFEvcOVZsndt327CNmYFZcuY2PFoYEtuYc9sMEhtuJG+8ndtzmxGohY2ZF48W+f6HzZ9z/xkkzr+RYCBt2XPbnqAWhhuJDdK5DQaJG26kGEkz/LidSFCLwY2HbdJ/jhknbrxzLNmwt+F2chszYzNev8j3pz/+OKNGLnHe7eaDD378uW07v7354IeP+BwGBxJAzNgGYkHSA5FaGP4QqXgUjIJRMApGFAAAUjRWwIL+vjsAAAAASUVORK5CYII=","orcid":"","institution":"All India Institute of Medical Sciences, Bhubaneswar, India","correspondingAuthor":true,"prefix":"","firstName":"Sai","middleName":"Swetha","lastName":"Pavuluri","suffix":""},{"id":509893162,"identity":"514a2ac8-4b03-4f7f-9024-f2f974e71b51","order_by":2,"name":"Suhas Kataveni","email":"","orcid":"","institution":"Gandhi Medical College, Hyderabad, India","correspondingAuthor":false,"prefix":"","firstName":"Suhas","middleName":"","lastName":"Kataveni","suffix":""},{"id":509893163,"identity":"00e57b17-de38-4bd5-8bc5-ff44c9b1e9f1","order_by":3,"name":"Shashank Trivedi","email":"","orcid":"","institution":"Attending Physician, Internal Medicine, Rochester General Hospital, United States","correspondingAuthor":false,"prefix":"","firstName":"Shashank","middleName":"","lastName":"Trivedi","suffix":""},{"id":509893164,"identity":"bdb904bf-8498-4950-bdcb-106459e44765","order_by":4,"name":"Suman Pasupuleti","email":"","orcid":"","institution":"Program Director, Cardiovascular Fellowship, HCA Florida Citrus Hospital, United States","correspondingAuthor":false,"prefix":"","firstName":"Suman","middleName":"","lastName":"Pasupuleti","suffix":""},{"id":509893165,"identity":"8aa22fce-8a1c-4d97-a45a-19bd75640a8c","order_by":5,"name":"Akshat Sahai","email":"","orcid":"","institution":"Internal Medicine, Texas Tech Permian Basin, United States","correspondingAuthor":false,"prefix":"","firstName":"Akshat","middleName":"","lastName":"Sahai","suffix":""},{"id":509893752,"identity":"c4fa9f8b-5716-4e21-8daa-5fa61b0a5a9f","order_by":6,"name":"Salar Haidar","email":"","orcid":"","institution":"Brigham and Women’s Hospital, United States","correspondingAuthor":false,"prefix":"","firstName":"Salar","middleName":"","lastName":"Haidar","suffix":""},{"id":509893753,"identity":"1cde8f50-e06f-466e-9575-5157149c107c","order_by":7,"name":"Kumar Vashisht","email":"","orcid":"","institution":"Internal Medicine, Bronxcare Health System, United States","correspondingAuthor":false,"prefix":"","firstName":"Kumar","middleName":"","lastName":"Vashisht","suffix":""},{"id":509893754,"identity":"a381cc9c-e590-4376-afe1-1e5e369eab2c","order_by":8,"name":"Vikram Adithya","email":"","orcid":"","institution":"Cardiovascular Fellow, HCA Florida Citrus Hospital, United States","correspondingAuthor":false,"prefix":"","firstName":"Vikram","middleName":"","lastName":"Adithya","suffix":""},{"id":509893755,"identity":"e7974c86-96b9-4afe-ae26-bf1da08143ab","order_by":9,"name":"Nidhi Lanka","email":"","orcid":"","institution":"Endocrinology, Mayo Clinic Rochester, United States","correspondingAuthor":false,"prefix":"","firstName":"Nidhi","middleName":"","lastName":"Lanka","suffix":""}],"badges":[],"createdAt":"2025-09-03 20:33:51","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7530128/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7530128/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90756255,"identity":"e3756e28-5e11-4718-bc9e-029e3955e0fa","added_by":"auto","created_at":"2025-09-07 13:26:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":60801,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrend in age-adjusted mortality rate for obesity-related cardiovascular disease, United States, 1999–2020.\u003c/strong\u003e\u003cbr\u003e\nLine graph showing age-adjusted mortality rates (per 100,000) standardized to the 2000 U.S. population, for adults aged 15–84 years. Rates increased steadily from 2.75 in 1999 to 6.82 in 2019, followed by a sharp rise to 8.36 in 2020. Joinpoint regression identified a significant inflection point in 2018, marking an acceleration in the rate of increase. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00–I99 with contributing cause ICD-10: E66.0–E66.9.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7530128/v1/34cc2b3c2fe0d5ac15410447.png"},{"id":90756723,"identity":"152458c3-663e-4bad-a8a9-738e065b51cd","added_by":"auto","created_at":"2025-09-07 13:42:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53799,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTotal obesity-related cardiovascular deaths by age group, United States, 1999–2020.\u003c/strong\u003e\u003cbr\u003e\n Bar chart showing total number of obesity-related cardiovascular deaths over the study period stratified by 10-year age cohorts (15–24 to 75–84 years). Death counts were derived from CDC WONDER Multiple Cause of Death data, restricted to U.S. residents aged 15–84 years with obesity (ICD-10: E66.0–E66.9) listed as a contributing cause and circulatory disease (ICD-10: I00–I99) as the underlying cause. The 55–64 year age group accounted for the highest number of deaths, followed by 45–54 and 65–74 years.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7530128/v1/6ead84b8f622248c5b8d52bb.png"},{"id":90756353,"identity":"245cd62f-96fb-4768-83e5-227220f2bd07","added_by":"auto","created_at":"2025-09-07 13:34:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":14211,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTotal obesity-related cardiovascular deaths by urbanization category, United States, 1999–2020.\u003c/strong\u003e\u003cbr\u003e\n Horizontal bar chart showing total number of obesity-related cardiovascular deaths over the study period, stratified by 2013 NCHS Urban–Rural Classification. Large central metropolitan areas accounted for the highest number of deaths overall, followed by medium metro and large fringe metro areas. Nonmetropolitan regions (micropolitan and noncore) had smaller absolute death counts but higher age-adjusted mortality rates in relative terms. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00–I99 (circulatory diseases) with contributing cause ICD-10: E66.0–E66.9 (obesity).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7530128/v1/9b96ab9b776c9bd691055c02.png"},{"id":90756261,"identity":"fc241d5d-ef83-45f4-8945-58d64ce491cb","added_by":"auto","created_at":"2025-09-07 13:26:52","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":18977,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProportion of total obesity-related cardiovascular deaths by race, United States, 1999–2020.\u003c/strong\u003e\u003cbr\u003e\n Pie chart showing the racial distribution of total obesity-related cardiovascular deaths over the study period. White individuals accounted for the majority of deaths, followed by Black or African American individuals. American Indian/Alaska Native and Asian/Pacific Islander groups contributed smaller proportions. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00–I99 (circulatory diseases) with contributing cause ICD-10: E66.0–E66.9 (obesity).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7530128/v1/77cdf7b7f6706a7cefac0eb8.png"},{"id":90756355,"identity":"3793204e-7116-430e-9c7d-2bd3843d1f91","added_by":"auto","created_at":"2025-09-07 13:34:52","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":13184,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProportion of total obesity-related cardiovascular deaths by sex, United States, 1999–2020.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePie chart showing the sex distribution of total obesity-related cardiovascular deaths over the study period. Males accounted for the majority of deaths (~57%), while females accounted for ~43%. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00–I99 (circulatory diseases) with contributing cause ICD-10: E66.0–E66.9 (obesity).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7530128/v1/1a22fc9623268754a74f8e05.png"},{"id":90756357,"identity":"b44f5b1e-c907-4b79-ae1a-5a31a2afd396","added_by":"auto","created_at":"2025-09-07 13:34:52","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":95517,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGeographic distribution of total obesity-related cardiovascular deaths by state, United States, 1999–2020.\u003c/strong\u003e\u003cbr\u003e\nChoropleth map showing total number of obesity-related cardiovascular deaths aggregated over the study period. Mortality counts range from 594 to 34,002. Vermont (12.62 ± 0.32) and Oklahoma (10.51 ± 0.13) emerged as unexpected high-burden states, exceeding rates in West Virginia (5.83 ± 0.13) — a national leader in obesity prevalence — by over 40%. Lowest mortality burdens were observed in Virginia (2.46 ± 0.04) and Alabama (2.47 ± 0.05). Regional clustering was evident, with elevated rates in New England and Appalachia, and lower rates across the South Atlantic. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00–I99 with contributing cause ICD-10: E66.0–E66.9.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7530128/v1/d5a749527b8aa8e1d983db23.png"},{"id":90757394,"identity":"6440b686-0b0a-4a54-8892-a9f18aa2e8a1","added_by":"auto","created_at":"2025-09-07 13:58:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":988070,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7530128/v1/eb9098ef-a29d-4675-966b-6ec51e47c452.pdf"},{"id":90756865,"identity":"6d34734b-440d-4bee-bf82-e8de711d87f2","added_by":"auto","created_at":"2025-09-07 13:50:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":555941,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfiles.docx","url":"https://assets-eu.researchsquare.com/files/rs-7530128/v1/7d5cdc9acdd372ee11287538.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eRising Obesity-Related Cardiovascular Mortality in the United States, 1999–2020: Accelerating Trends and Widening Disparities\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObesity has become a nationwide epidemic in the United States and a leading driver of cardiovascular risk. Approximately 39\u0026ndash;40% of U.S. adults meet the criteria for obesity (body mass index\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u0026sup2;) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), with rates disproportionately higher among disadvantaged and rural populations. Excess adiposity adversely affects nearly every organ system and, in particular, promotes hypertension, dyslipidemia, insulin resistance, systemic inflammation, and endothelial dysfunction. As noted in a recent World Heart Federation statement, \u0026ldquo;increased adiposity, particularly visceral fat, is linked to cardiovascular risk and CVD via multiple direct and indirect mechanisms\u0026rdquo; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Obesity triggers metabolic and neurohormonal cascades that accelerate coronary atherosclerosis and cardiac remodeling and independently elevate the risk of ischemic heart disease (IHD), heart failure (HF), and stroke (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). It contributes to type 2 diabetes, hypertension, and dyslipidemia (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) and induces structural changes such as left ventricular hypertrophy, diastolic dysfunction, and a pro-thrombotic state. These mechanisms explain why over two-thirds of global deaths attributable to high body mass index are due to cardiovascular disease (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In essence, obesity is a chronic, systemic condition that seeds multiple cardiovascular pathologies.\u003c/p\u003e\u003cp\u003eHistorically, U.S. cardiovascular mortality declined steadily for decades; however, that progress has stalled. National analyses revealed that the decline in CVD mortality began decelerating around 2010\u0026ndash;2011 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). By the late 2010s, heart disease mortality had plateaued, and overall U.S. life expectancy leveled off, even reversing in some years (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Mehta et al. demonstrated that from 2010\u0026ndash;2017, slowing declines in CVD deaths, especially at midlife, were the primary cause of the plateau in life expectancy (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). These changes coincided with a sharp rise in obesity prevalence, which surged during the 2000s and reached record highs in the 2010s (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The increasing burden of weight-related complications has undermined cardiovascular health, threatening decades of progress.\u003c/p\u003e\u003cp\u003eRecent evidence indicates a rising mortality burden specifically attributable to obesity. Our analysis of CDC WONDER data, using joinpoint regression, identified a marked inflection in 2018 in obesity-related cardiovascular deaths, mirroring other national reports. Raisi-Estabragh et al. found that obesity-related cardiovascular deaths nearly tripled between 1999 and 2020 (age-adjusted mortality rising from 2.2 to 6.6 per 100,000) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), with IHD as the predominant cause and hypertensive heart disease especially prominent among Black decedents (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Sohail et al. reported that obesity-related IHD mortality more than doubled during this period, with a sharp acceleration after 2018 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Ahmed et al. documented a steady rise in age-adjusted coronary artery disease mortality from 1999\u0026ndash;2018, followed by a surge from 2018\u0026ndash;2022 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Achara et al. observed an increase in obesity-related circulatory deaths between 2010\u0026ndash;2020 (AAMR from 1.8 to 3.1 per 100,000), with the steepest increases among midlife and older adults and among Black Americans (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). These findings confirm that obesity\u0026rsquo;s mortality impact has intensified, with a clear change-point near 2018. Importantly, this inflection predates the COVID-19 pandemic, implicating broader health system and population factors.\u003c/p\u003e\u003cp\u003eThe burden of obesity-related CVD mortality is unevenly distributed. Across studies, men have higher rates than women; Ashraf et al. reported an age-adjusted rate of 5.8 per 100,000 for men versus 4.0 for women (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Older adults have the highest rates, with Achara et al. noting the largest absolute increases in those aged 55\u0026ndash;74 years (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Racial disparities are stark: non-Hispanic Black Americans consistently show the highest rates and fastest growth (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), with Raisi-Estabragh et al. reporting Black mortality rates three times those of White individuals by 2020 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). American Indian/Alaska Native populations have seen the steepest percentage increases (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), consistent with very high obesity prevalence and limited healthcare access in those communities. Geographic disparities align with obesity and CVD hotspots, with rural and socioeconomically disadvantaged areas experiencing higher mortality; for example, CDC data from 2013\u0026ndash;2016 show obesity prevalence at 47% among women in nonmetropolitan areas compared with 38% in large cities (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Ashraf et al. found AAMR for obesity-related CVD of 3.47 in non-metro versus 2.78 in metro areas (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), and several Deep South and Appalachian states (e.g., Mississippi, West Virginia, Oklahoma) consistently rank among the highest nationally (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese disparities reflect underlying social and structural determinants. Economic deprivation, food insecurity, and limited healthcare access cluster obesity and CVD risk in marginalized communities. Sociologists and health equity experts highlight that \u0026ldquo;neighbourhood disadvantage\u0026rdquo; and \u0026ldquo;reduced food security\u0026rdquo; are linked to poorer cardiovascular health (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Food insecurity is also linked to higher rates of hypertension, coronary disease and related conditions (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Structural racism and inequity further entrench these disparities: for example, policies that restrict minority communities to unhealthy environments and unequal healthcare produce higher CVD risk in Black and Hispanic groups (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). A recent AHA Presidential Advisory explicitly calls out structural racism as a fundamental driver of health disparities (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Socioeconomic disadvantage including low education and income, confers CVD risk comparable to traditional biomedical factors (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Rural residents face additional barriers, including fewer healthcare resources and longer emergency response times, which the AHA has highlighted as a critical health equity concern (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In summary, obesity interacts with demographic and geographic inequities, disproportionately affecting male, Black, and rural populations due to a lifetime of stacked disadvantages.\u003c/p\u003e\u003cp\u003eAt the molecular and physiological level, obesity\u0026rsquo;s cardiovascular effects are multifactorial. Adipose tissue in obesity secretes inflammatory cytokines (e.g., IL-6, TNF-α), adipokines (e.g., leptin, adiponectin imbalance), and promotes insulin resistance and hyperglycemia, fueling atherosclerosis and cardiomyopathy (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Hemodynamically, obesity increases blood volume and cardiac output, leading to left ventricular hypertrophy and diastolic dysfunction. The combined metabolic and pressure overload makes obesity a potent cause of heart failure \u0026ndash; indeed, HF is often described as the cardiovascular condition \u0026ldquo;most closely linked\u0026rdquo; to obesity (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Abdesselam et al. note that obesity-driven hemodynamic and endocrine changes create a \u0026ldquo;vicious cycle\u0026rdquo; of heart failure and cardiovascular mortality (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In summary, both epidemiology and basic science converge: chronic obesity fundamentally alters cardiovascular physiology in ways that raise disease incidence and worsen outcomes.\u003c/p\u003e\u003cp\u003eFinally, it is important to note that the recent acceleration in obesity-related CVD mortality is not simply an artifact of the COVID-19 pandemic. While 2020 saw a noticeable jump in deaths, analyses show that most of that excess is likely due to indirect effects of the pandemic era (like delayed care and unhealthy lifestyle changes), rather than the virus itself. For example, a UK study estimated that only\u0026thinsp;~\u0026thinsp;5% of the rise in cardiovascular deaths during 2020 was attributable to COVID-19 infection, with the rest due to acute myocardial infarctions, strokes, and heart failure likely from care disruptions (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Similarly, Ashraf et al. report that the obesity-CVD mortality acceleration from 2018\u0026ndash;2020 was partly linked to pandemic-related weight gain, but emphasize that a notable upturn already began in 2018 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Qamar et al. also quantified thousands of excess obesity-CVD deaths in early 2020 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Thus, the inflection point we identified in 2018 precedes COVID-19, indicating that underlying trends (worsening obesity rates, stagnating risk-factor control, and inequities in care) were already driving higher mortality.\u003c/p\u003e\u003cp\u003eIn sum, mounting evidence indicates that obesity has emerged as a major and growing contributor to cardiovascular mortality in the U.S. Obesity triggers metabolic and structural pathways that cause heart disease, and this effect is magnified among the elderly, men, and historically disadvantaged groups. Structural factors, including poverty, food environments, and systemic racism, underlie the observed disparities by race, geography, and urbanization status (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The joinpoint-identified inflection in 2018 highlights that the worst of these trends began before COVID-19, underscoring the need for urgent public health action. Using national mortality data from 1999\u0026ndash;2020, we characterize the trajectory of obesity-related cardiovascular deaths by demographic and regional subgroups, quantifying the scale of this public health crisis.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003e1. Data Source and Case Definition\u003c/h3\u003e\n\u003cp\u003eDe-identified mortality records (1999\u0026ndash;2020) were extracted from the CDC WONDER database, restricted to U.S. residents aged 15\u0026ndash;84 years. Deaths were included if:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eUnderlying cause was circulatory disease (ICD-10: I00-I99)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eObesity (E66.0-E66.9) was listed as a contributing cause.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePopulation denominators came from U.S. Census bridged-race estimates.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\n\u003ch3\u003e2. Stratification Variables\u003c/h3\u003e\n\u003cp\u003eAnalyses were stratified across five axes:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eAge: Seven ten-year groups (15\u0026ndash;24 to 75\u0026ndash;84 years)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eUrbanization: Six 2013 NCHS categories (e.g., Large Central Metro to NonCore Nonmetro)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eRace: White, Black, Asian/Pacific Islander, American Indian/Alaska Native\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSex: Male/Female\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eGeography: 50 states and the District of Columbia\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\n\u003ch3\u003e3. Rate Calculation and Standardization\u003c/h3\u003e\n\u003cp\u003eCrude mortality rates (deaths per 100,000 person-years) were computed for age subgroups. Age-adjusted rates (AAR) standardized to the 2000 U.S. standard population were calculated using direct standardization. Standard errors (SE) accounted for sparse data per CDC protocols.\u003c/p\u003e\n\u003ch3\u003e4. Joinpoint Regression Analysis\u003c/h3\u003e\n\u003cp\u003eTemporal trends were modeled using Joinpoint Regression Software (v5.4.0.0; National Cancer Institute). Parameters:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eModel: Log-linear rates with heteroscedastic errors\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eInflection detection: Grid search with permutation testing (overall α\u0026thinsp;=\u0026thinsp;0.05; 4,499 replicates)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eConstraints: Minimum 2 observations between joinpoints; minimum 2 at endpoints\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eOutput: Annual percent change (APC), inflection points (τ) with 95% CIs (parametric method)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eFinal model selection: Permutation tests identified optimal joinpoints (1 joinpoint retained, *p*=0.012)\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\n\u003ch3\u003e5. Disparity Quantification\u003c/h3\u003e\n\u003cp\u003eSubgroup comparisons used:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eRate ratios with 95% confidence intervals\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eWeighted *t*-tests for geographic extremes (e.g., Vermont vs. Virginia)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSE-based z-scores for racial/urbanization contrasts (α\u0026thinsp;=\u0026thinsp;0.05)\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\n\u003ch3\u003e6. Software and Ethics\u003c/h3\u003e\n\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eTools: Joinpoint (trends), Datawrapper/RAWGraphs (visualization), Excel (descriptive statistics)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eEthics: CDC WONDER provides de-identified public data; IRB exemption granted per 45 CFR \u0026sect;\u0026nbsp;46.104(d)(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eKey Methodological Rigor\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eStandardization: All AARs used identically weighted 2000 U.S. population for cross-strata comparability.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eBias Control: Permutation tests prevented overfitting in joinpoint selection; SEs addressed small-count instability.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eReproducibility: Full CDC WONDER query parameters and Joinpoint configuration files archived.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eJoinpoint regression analysis revealed a statistically significant inflection point in 2018 (95% CI: 2017\u0026ndash;2018; permutation test p\u0026thinsp;=\u0026thinsp;0.012), partitioning obesity-related circulatory mortality trends into two distinct phases. From 1999\u0026ndash;2018, mortality increased steadily at an Annual Percent Change (APC) of 4.79% (95% CI: 4.60\u0026ndash;4.98; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), rising from 2.75 to 6.53 per 100,000. This 19-year period exhibited consistent linear progression (\u003cem\u003eR\u0026sup2;\u003c/em\u003e = 0.98), with average annual increases of 3.1%. The trajectory shifted dramatically post-2018, accelerating to an APC of 11.05% (95% CI: 6.76\u0026ndash;15.51; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This acceleration culminated in an unprecedented 2020 rate of 8.36 per 100,000\u0026mdash;a 3.4-fold surge since 1999 and a 19.1% single-year leap from 2019 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Model diagnostics confirmed robustness (Mean Squared Error: 11.29; uncorrelated errors).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eLine graph showing age-adjusted mortality rates (per 100,000) standardized to the 2000 U.S. population, for adults aged 15\u0026ndash;84 years. Rates increased steadily from 2.75 in 1999 to 6.82 in 2019, followed by a sharp rise to 8.36 in 2020. Joinpoint regression identified a significant inflection point in 2018, marking an acceleration in the rate of increase. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00\u0026ndash;I99 with contributing cause ICD-10: E66.0\u0026ndash;E66.9.\u003c/p\u003e\u003cp\u003eAge-specific mortality demonstrated a steep gradient, escalating from 0.23 per 100,000 in 15\u0026ndash;24 year-olds to a peak of 11.37 in 65\u0026ndash;74 year-olds. Young adults (25\u0026ndash;34 years) experienced a clinically significant burden (1.20/100,000), while the 55\u0026ndash;64 year cohort accounted for the highest absolute deaths (78,164), reflecting demographic distribution. Notably, the 15\u0026ndash;24 year group saw a 210% cumulative increase since 1999\u0026mdash;the largest relative rise across age strata (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBar chart showing total number of obesity-related cardiovascular deaths over the study period stratified by 10-year age cohorts (15\u0026ndash;24 to 75\u0026ndash;84 years). Death counts were derived from CDC WONDER Multiple Cause of Death data, restricted to U.S. residents aged 15\u0026ndash;84 years with obesity (ICD-10: E66.0\u0026ndash;E66.9) listed as a contributing cause and circulatory disease (ICD-10: I00\u0026ndash;I99) as the underlying cause. The 55\u0026ndash;64 year age group accounted for the highest number of deaths, followed by 45\u0026ndash;54 and 65\u0026ndash;74 years.\u003c/p\u003e\u003cp\u003eUrbanization profoundly influenced outcomes, with a clear rural-urban disparity gradient (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Micropolitan (nonmetro) areas recorded the highest mortality (5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03), exceeding Large Fringe Metro rates (3.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02) by 44.2% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Nonmetropolitan regions collectively (Micropolitan\u0026thinsp;+\u0026thinsp;NonCore) averaged 5.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 versus 4.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 in metropolitan areas (rate ratio: 1.16; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Medium Metro (4.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02) and Small Metro (5.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03) zones exhibited intermediate burdens, though all urban categories remained significantly below rural counterparts.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eHorizontal bar chart showing total number of obesity-related cardiovascular deaths over the study period, stratified by 2013 NCHS Urban\u0026ndash;Rural Classification. Large central metropolitan areas accounted for the highest number of deaths overall, followed by medium metro and large fringe metro areas. Nonmetropolitan regions (micropolitan and noncore) had smaller absolute death counts but higher age-adjusted mortality rates in relative terms. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00\u0026ndash;I99 (circulatory diseases) with contributing cause ICD-10: E66.0\u0026ndash;E66.9 (obesity).\u003c/p\u003e\u003cp\u003eRacial disparities were stark and persistent (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u0026nbsp;Black Americans endured the highest mortality (8.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04)\u0026mdash;1.88\u0026times; the White rate (4.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01;\u0026nbsp;p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 7.6\u0026times; the Asian/Pacific Islander rate (1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02). This Black-White disparity widened post-2010 (rate ratio: 1.72 \u0026rarr; 1.88). American Indian/Alaska Natives showed elevated mortality (4.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10) but did not significantly differ from Whites after error adjustment (p\u0026thinsp;=\u0026thinsp;0.07).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePie chart showing the racial distribution of total obesity-related cardiovascular deaths over the study period. White individuals accounted for the majority of deaths, followed by Black or African American individuals. American Indian/Alaska Native and Asian/Pacific Islander groups contributed smaller proportions. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00\u0026ndash;I99 (circulatory diseases) with contributing cause ICD-10: E66.0\u0026ndash;E66.9 (obesity).\u003c/p\u003e\u003cp\u003eSex-based inequities remained pronounced throughout the study period. Males experienced 47% higher mortality than females (5.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 vs. 3.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with peak disparity in the 55\u0026ndash;64 year cohort (male rate: 13.1 vs. female: 6.8; ratio: 1.92). During the 2018\u0026ndash;2020 acceleration phase, male mortality surged 23.6% versus 17.2% in females, amplifying pre-existing gaps (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePie chart showing the sex distribution of total obesity-related cardiovascular deaths over the study period. Males accounted for the majority of deaths (~\u0026thinsp;57%), while females accounted for ~\u0026thinsp;43%. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00\u0026ndash;I99 (circulatory diseases) with contributing cause ICD-10: E66.0\u0026ndash;E66.9 (obesity).\u003c/p\u003e\u003cp\u003eGeographic analysis revealed a 5.1-fold state-level variation (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Vermont (12.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32) and Oklahoma (10.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13) emerged as unexpected hotspots\u0026mdash;exceeding national leaders in obesity prevalence (e.g., West Virginia: 5.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13) by \u0026gt;\u0026thinsp;40%. Conversely, Virginia (2.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04) and Alabama (2.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05) demonstrated the lowest burdens. Regional clustering was evident: New England exhibited elevated mortality (Vermont: 12.62; Rhode Island: 6.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18; New Hampshire: 4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13), while the South Atlantic formed a low-burden cluster (Virginia: 2.46; Alabama: 2.47; Florida: 3.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03). Appalachia showed concerning elevations (West Virginia: 5.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13; Kentucky: 4.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08; Tennessee: 5.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07), contrasting sharply with neighboring states.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eChoropleth map showing total number of obesity-related cardiovascular deaths aggregated over the study period. Mortality counts range from 594 to 34,002. Vermont (12.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32) and Oklahoma (10.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13) emerged as unexpected high-burden states, exceeding rates in West Virginia (5.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13) \u0026mdash; a national leader in obesity prevalence \u0026mdash; by over 40%. Lowest mortality burdens were observed in Virginia (2.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04) and Alabama (2.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05). Regional clustering was evident, with elevated rates in New England and Appalachia, and lower rates across the South Atlantic. Data source: CDC WONDER Multiple Cause of Death database; underlying cause ICD-10: I00\u0026ndash;I99 with contributing cause ICD-10: E66.0\u0026ndash;E66.9.\u003c/p\u003e\u003cp\u003eThe post-2018 acceleration phase disproportionately impacted specific subpopulations:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eBlack males experienced an APC surge from 5.2% (1999\u0026ndash;2018) to 14.1% (2018\u0026ndash;2020)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eRural residents saw APC jump from 4.1\u0026ndash;12.7% in Micropolitan areas\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eYoung adults (25\u0026ndash;34 years) endured an 18.9% single-year rise in 2020\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eSynergistic disadvantages were observed at demographic intersections. Rural Black males in high-burden states (Vermont, Oklahoma) experienced mortality rates 5.2\u0026times; the national average and 7.9\u0026times; those of urban White females in low-burden states (Virginia, Alabama). This disparity amplification during the acceleration phase suggests emergent vulnerability among historically marginalized groups.\u003c/p\u003e\u003cp\u003eNotably, the 2020 mortality surge occurred independently of COVID-19 infection patterns. States with low COVID-19 mortality (e.g., Vermont: 40.6/100,000 COVID deaths) showed extreme obesity-circulatory mortality, while high-COVID states (New Jersey: 353.2/100,000) recorded only moderate increases (3.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05), indicating disruption of chronic disease management as the primary driver.\u003c/p\u003e\u003cp\u003eCumulatively, these results identify 2018 as a critical inflection point for obesity-related circulatory mortality, with accelerating disparities concentrated among Black Americans, males, rural populations, and residents of Vermont/Oklahoma. The 2020 rate (8.36/100,000) represents the highest recorded burden since surveillance began.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAnalysis of CDC WONDER mortality data from 1999\u0026ndash;2020 reveals a sustained and accelerating rise in U.S. cardiovascular disease (CVD) mortality where obesity is a contributing cause. The APC shifted from 4.79\u0026ndash;11.05%, with AAMR increasing from 2.75 to 6.61 per 100,000 before 2018, then surging to 8.36 by 2020; a 3.4-fold increase since 1999. These results parallel national studies attributing post-2018 increases to worsening obesity prevalence, stagnant risk-factor control, and preventive care disruptions (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAge stratification demonstrated a steep gradient, with middle-aged adults (55\u0026ndash;64 years) contributing the highest absolute deaths, but the younger group (15\u0026ndash;24 years) cohort experiencing the largest proportional increases, underscoring an emerging younger-age burden. These findings parallel reports of rising premature CVD mortality linked to obesity (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMarked rural\u0026ndash;urban disparities were evident with Micropolitan nonmetro areas recording the highest AAMR (5.48), exceeding large fringe metro rates (3.80) by 44.2% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with a rural\u0026ndash;urban rate ratio of 1.16. National analyses confirm that rural residents face slower improvements in CVD outcomes and higher obesity prevalence (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Limited healthcare access, longer emergency response times, and socioeconomic disadvantage contribute to these differences (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRacial disparities were striking, with Black Americans experiencing nearly double the mortality of Whites and much higher rates than Asian/Pacific Islanders. American Indian/Alaska Natives had elevated rates but differences from Whites were not statistically significant after error adjustment. National studies similarly show Black and AI/AN populations suffer disproportionate obesity-related CVD mortality, with AI/AN populations experiencing the steepest proportional increases (\u0026gt;\u0026thinsp;400%) since 1999 (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Structural racism, healthcare access barriers, and higher comorbidity prevalence are key drivers (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSex-based differences persisted, with males having substantially higher mortality than females. Similar male predominance has been reported nationally, often attributed to differences in health behaviors, comorbidity profiles, and biological factors such as estrogen-mediated cardioprotection in premenopausal women (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGeographic patterns revealed up to a 5.1-fold variation in AAMR between states. Vermont and Oklahoma had the highest burdens, far exceeding states with the highest obesity prevalence, such as West Virginia. Conversely, Virginia and Alabama recorded the lowest rates. Regional clustering was apparent, with New England showing elevated mortality and the South Atlantic exhibiting lower burdens. Appalachia, however, demonstrated consistently higher rates than neighboring states. These spatial variations mirror literature identifying high-obesity, low-resource states as CVD mortality hotspots (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eImportantly, the 2020 surge in obesity-related CVD mortality occurred independently of COVID-19 infection patterns. Vermont, with low COVID-19 mortality, had among the highest obesity\u0026ndash;CVD rates, whereas high-COVID states like New Jersey showed only moderate increases. This aligns with evidence that pandemic-era disruptions in chronic disease management, rather than direct viral effects, were primary contributors (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCollectively, these results, reinforced by peer-reviewed literature, depict an accelerating crisis concentrated among Black Americans, males, rural residents, and certain geographic regions. The interplay between biological vulnerability, structural inequities, and healthcare access disparities is evident. Without targeted interventions, the upward trajectory in obesity-related CVD mortality is likely to continue.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings reveal a sharp post-2018 acceleration in U.S. obesity-related CVD mortality, with profound disparities by race, sex, geography, and urbanization. Black Americans face nearly double the mortality of Whites, rural residents have 44% higher rates than those in large metropolitan areas, and states such as Vermont and Oklahoma record burdens five times higher than low-mortality states. Young adults, though still at lower absolute risk, show alarming proportional increases.\u003c/p\u003e\u003cp\u003eThese findings demand urgent, equity-focused public health action. First, preventive strategies must prioritize high-risk groups. This includes community-based blood pressure and weight management programs tailored for Black, AI/AN, and rural populations. Second, expanding healthcare infrastructure in nonmetropolitan areas through telehealth, incentives for rural clinicians, and improved emergency services can narrow the rural\u0026ndash;urban mortality gap. Third, upstream social determinants must be addressed: improving access to healthy foods, safe physical activity spaces, and stable healthcare coverage will help reduce the underlying drivers of obesity and CVD. Fourth, continuous monitoring is essential. Fifth, targeted policy investments in high-burden states, particularly those with unexpected mortality hotspots like Vermont, can address localized drivers.\u003c/p\u003e\u003cp\u003eWithout decisive intervention, the convergence of obesity and cardiovascular disease threatens to reverse decades of progress in reducing heart disease mortality. An integrated approach, combining medical care, public health policy, and structural reform, offers the best opportunity to slow and eventually reverse these trends.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHales, C. M., Fryar, C. D., Carroll, M. D., Freedman, D. S., Aoki, Y., \u0026amp; Ogden, C. L. (2018). 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Concomitant mortality trends due to obesity and hypertension in the U.S.: A 20-year retrospective analysis of the CDC WONDER database. \u003cem\u003eBMC Cardiovascular Disorders, 25\u003c/em\u003e(1), 496. https://doi.org/10.1186/s12872-025-04909-z\u003c/li\u003e\n\u003cli\u003eHameed, I., et al. (2024). Demographic and regional trends of cardiovascular disease and obesity-related mortality in the United States from 1999 to 2021. \u003cem\u003eAmerican Journal of Cardiology, 233\u003c/em\u003e, 51\u0026ndash;54. https://doi.org/10.1016/j.amjcard.2024.09.028\u003c/li\u003e\n\u003cli\u003eAshraf H, Ashfaq H, Ashraf A. Gender and racial disparities in obesity-related cardiovascular-induced mortality in the USA, 1999\u0026ndash;2020. Current Problems in Cardiology [Internet]. 2024 Jan [cited 2025 Aug 11];49(1):102178. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0146280623005959\u003c/li\u003e\n\u003cli\u003eYang, H., et al. (2025). A systematic bibliometric analysis of cardiovascular disease risk in obesity (2014\u0026ndash;2024). \u003cem\u003eJournal of Multidisciplinary Healthcare, 18\u003c/em\u003e, 3233\u0026ndash;3255. https://doi.org/10.2147/JMDH.S504022\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7530128/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7530128/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObesity is a major and growing driver of cardiovascular disease (CVD) in the United States, contributing to hypertension, diabetes, dyslipidemia, and structural cardiac changes that elevate the risk of ischemic heart disease, heart failure, and stroke. After decades of declining CVD mortality, recent national trends show a concerning reversal, coinciding with record-high obesity prevalence. We quantified national trends and disparities in obesity-related CVD mortality from 1999–2020 using de-identified death certificate data from the CDC WONDER database for U.S. residents aged 15–84 years, including deaths with circulatory disease (ICD-10 I00–I99) as the underlying cause and obesity (E66.0–E66.9) as a contributing cause. Age-adjusted mortality rates (AAMR) standardized to the 2000 U.S. population were analyzed using joinpoint regression to estimate annual percent change (APC) and detect inflection points. From 1999–2018, AAMR rose from 2.75 to 6.61 per 100,000 (APC 4.79%; 95% CI 4.60–4.98), followed by a significant post-2018 acceleration (APC 11.05%; 95% CI 6.76–15.51) to 8.36 in 2020. Mortality was highest among adults 65–74 years, males, Black Americans, and nonmetropolitan residents, with a 5.1-fold state variation. Young adults (15–24 years) had the largest relative increase (+210%). The 2020 surge was independent of COVID-19 mortality, indicating gaps in chronic disease management. These results highlight a growing obesity-related CVD mortality burden, with widening disparities by age, sex, race, and geography, emphasizing urgent, equity-focused prevention and targeted interventions.\u003c/p\u003e","manuscriptTitle":"Rising Obesity-Related Cardiovascular Mortality in the United States, 1999–2020: Accelerating Trends and Widening Disparities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-07 13:26:47","doi":"10.21203/rs.3.rs-7530128/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"68a94639-29f7-4ae4-bf6c-4a9b79269ab9","owner":[],"postedDate":"September 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":54157610,"name":"Hospital Medicine"}],"tags":[],"updatedAt":"2025-09-07T13:26:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-07 13:26:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7530128","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7530128","identity":"rs-7530128","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}