Mortality Trends Related to Congenital Heart Defects in United States: a CDC WONDER analysis

Mortality Trends Related to Congenital Heart Defects in United States: a CDC WONDER analysis | 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 Mortality Trends Related to Congenital Heart Defects in United States: a CDC WONDER analysis Novera Amir Akbani, Muhammad Hani, Sadia Ghafur, Danish Ali Ashraf, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9144914/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 BACKGROUND Congenital heart defects (CHD) are diagnosed in 1/100 live births in the United States. Advances in medical care have reduced CHD-related mortality, but disparities remain across demographic and geographic groups. METHODS Death certificates from the CDC WONDER database were analyzed from 1999 to 2020 in children aged < 1–14 years. Age-adjusted mortality rates (AAMRs) per 100,000 individuals were calculated and stratified by race, gender, place of death, and census region. Joinpoint regression analysis was used to determine annual percent changes (APC) and identify trends in mortality rates. RESULTS A total of 49,890 deaths occurred due to CHD from 1999–2020. The AAMR declined from 4.748 in 1999 to 3.473 in 2010 (APC − 2.55*; 95%CI:-4.57 to -2.08) and from 3.473 in 2010 to 2.987 in 2020 (APC − 1.25; 95% CI: -1.85 to 1.23). Males had a higher overall AAMR (3.81) than females (3.56). Non-Hispanic Black had the highest AAMR (4.919), while Non-Hispanic Asian had the lowest (2.759). The South showed the highest AAMR (3.953) and the Northwest the lowest (2.823). The majority of deaths occurred in medical facilities (91%), followed by decedents' homes (7.3%), hospice facilities (0.4%), and nursing homes/long-term care (0.2%). Among CHD subtypes, VSD-related mortality had the highest AAMR (0.245) while Malformation of coronary vessels the lowest (0.039). CONCLUSION CHD-related AAMR fell from 1999 to 2020 with a slower decline between 2010 and 2020. The data showed that the AAMR was consistently higher in males, NH Black, and in Southern and Midwestern regions, with most deaths occurring in medical facilities. Congenital heart disease Pediatric mortality Cross-sectional study CDC WONDER database United States Cardiothoracic surgery Figures Figure 1 Figure 2 INTRODUCTION Congenital Heart Defects (CHD) encompass structural and functional abnormalities of the heart that are present at birth and affect approximately 0.8% of live births worldwide. 1 Between 1990–2017, global CHD incidence remained stable; though, high–SDI regions such as the United States saw an increase. 2 Approximately 1/100 children in the United States are born with CHD. 3 Advances in medical and surgical advancements have led to a significant decrease in worldwide mortality. 1 , 2 Nevertheless, CHD continues to remain one of the leading causes of death due to congenital defects among infants in the United States. 4 Prior studies have found disparities in CHD mortality based on gender, race, and census region. Higher mortality rates were reported in Non-Hispanic Blacks and males in comparison to Non-Hispanic Whites and females, respectively. 2 , 5 Census region has also been associated with infant mortality due to CHD in the USA. 6 However, a comprehensive national analysis examining the trends of CHD related mortality across multiple variables in the pediatric population remains limited. Therefore, this study aimed to assess trends in CHD-related mortality stratified by race, gender, place of death and census region from 1999–2020 among children < 1–14 years of age in the United States. Improved understanding of these patterns may help identify vulnerable populations and inform targeted interventions to reduce mortality rates. METHODOLOGY Study Setting and Population We performed a retrospective, population-based cross-sectional analysis using death certificate data from the Centers for Disease Control and Prevention WONDER (Wide-Ranging Online Data for Epidemiologic Research) database. Our main objective was to evaluate the mortality rates among children aged < 1–14 with Congenital Heart Disease (CHD) from 1999 to 2020. To identify these cases, we utilized the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) codes: Q20, Q21, Q22, Q23, Q24, Q21.1, Q21.0, Q21.2, Q21.3, Q22.5, and Q24.5. Data were obtained from the Multiple Cause of Death Public Use dataset, including records where CHD was listed as either a contributing factor or the primary cause of death. Since we used a de-identified public-use dataset provided by the government, institutional review board approval was not required. Data Abstraction Data were stratified by gender, race/ethnicity, place of death, census region, and annual trends. Places of death included inpatient and outpatient medical facilities. Racial/ethnic categories were Hispanic (Latino), Non-Hispanic (NH) White, NH Black/African American, NH American Indian/Alaskan Native, and NH Asian. U.S. regions were classified according to the U.S Census Bureau’s classification: Northeast, Midwest, South, and West. Yearly analyses were also conducted for individual ICD-10 codes to assess temporal trends. Statistical Analysis CHD-related mortality trends from 1999 to 2020 were analyzed by gender, race, age, place of death, year, and census region. Crude and age-adjusted mortality rates (AAMR) per 100,000 individuals were calculated, using the 2000 U.S population for AAMR standardization. Temporal trends were evaluated using Joinpoint Regression Program (Version 5.0.2, National Cancer Institute), fitting log-linear regression models to the crude data trends to determine the annual percent change (APC) in AAMR along with its 95% confidence interval (CI). APCs were categorized as increasing or decreasing based on their statistical deviation from the null hypothesis of zero change. Statistical significance was assessed using a 2-tailed t-test with a significance level of P < 0.05. During manuscript preparation, the authors used ChatGPT (OpenAI, GPT-5) for some sections solely to improve language clarity and readability. No AI tools were used for data analysis, statistical modeling, or interpretation of results. All content was reviewed and verified by the authors, who take full responsibility for the accuracy and integrity of the work. RESULTS From 1999 to 2020, a total of 49,890 deaths were reported due to congenital heart disease in individuals aged < 1–14 years. Demographics: Of these deaths, 23,605 (47.3%) were females and 26,285 (52.7%) were males. Data for race was available for 49,639 deaths, out of which 25,200 (50.8%) were white, 11,853 (23.9%) were Hispanic, 10,055 (20.3%) were Black or African American, 1,916 (3.9%) were Asian or Pacific Islander, and 615 (1.2%) were Alaskan American or Native American. (Table 1 ) Place of death data was available for 49,738 deaths, of which 45,377 (91%) occurred in medical facilities, 3,630 (7.3%) occurred at decedents' homes, 194 (0.4%) occurred at hospice facilities, and 121 (0.2%) occurred at nursing homes/long-term care (Supplemental Table 1). Table 1 Congenital Heart Disease Related Mortality, Stratified by Sex and Race, in the United States, 1999 to 2020 Year Total Deaths Total Population Overall Male Female NH American Indian or Alaska Native NH Asian or Pacific Islander NH Black or African American NH White Hispanic 1999 2802 1469 1333 32 81 540 1586 546 59955368 2000 2741 1433 1308 31 90 538 1528 538 60253375 2001 2649 1411 1238 34 89 531 1444 534 60450257 2002 2623 1431 1192 22 103 504 1433 543 60563030 2003 2564 1371 1193 36 96 481 1356 580 60628650 2004 2484 1304 1180 27 79 491 1340 540 60651802 2005 2420 1281 1139 35 83 431 1287 578 60519046 2006 2417 1279 1138 25 86 509 1216 577 60516709 2007 2499 1292 1207 28 97 519 1236 611 60681615 2008 2413 1267 1146 33 86 492 1181 608 60907384 2009 2203 1164 1039 26 102 453 1070 539 61087581 2010 2133 1096 1037 27 67 442 1036 555 61227213 2011 2142 1136 1006 34 91 415 1050 544 61201106 2012 2113 1097 1016 27 82 418 1020 547 61144098 2013 2078 1118 960 23 87 412 1008 540 61089123 2014 1988 1064 924 26 89 418 923 521 61067955 2015 2079 1103 976 28 83 439 992 524 61016787 2016 2051 1083 968 30 92 437 968 514 60975069 2017 1973 1008 965 28 97 406 909 521 61021552 2018 1885 979 906 23 80 427 888 455 60885444 2019 1885 985 900 17 67 383 898 510 60570846 2020 1748 914 834 23 89 369 831 428 60293426 Abbreviations: NH non-Hispanic Annual trends From 1999–2020, the AAMR for CHD-related deaths decreased from 4.75 to 2.98. The AAMR declined from 1999 to 2010 (APC − 2.55*; 95% CI: -4.57 to -2.08), followed by a slower decline from 2010 to 2020 (APC − 1.25; 95% CI: -1.85 to 1.23) (Fig. 1 , Tables 1 and 2 ). Table 2 Annual Percentage Change (APC) of Congenital Heart Disease Related Age-Adjusted Mortality Rates Per 100,000 in the United States, 1999–2020 Year Interval APC (95% CL) Overall 1999–2010 -2.55*(-4.6–2.1) 2010–2020 -1.3(-1.9-1.2) Female 1999–2002 -4.96*(-8.3–2.1) 2002–2020 -1.61*(-1.9–0.5) Male 1999–2010 -2.59*(-4.6–2.1) 2010–2020 -1.3(-2.0-1.2) NH American Indian or Alaskan Native 1999–2020 -1.1(-2.3-0.0) NH Asian or Pacific Islander 1999–2020 -2.02*(-2.7–1.3) NH Black or African American 1999–2020 -1.7(-2.1–1.3) NH White 1999–2010 -2.67*(-4.1–2.3) 2010–2020 -1.4(-2.0-0.6) Hispanic 1999–2001 -7.1*(-10.3–1.6) 2001–2020 -1.6(-4.1-0.6) Northeast 1999–2020 -2.27*(-2.8–1.8) Midwest 1999–2020 -1.92*(-2.3–1.6) South 1999–2011 -2.63*(-3.7–1.7) 2011–2016 1.4(-3.3-5.0) 2016–2020 -3.3(-8.0–0.6) West 1999–2020 -2.58*(-3.0–2.2) Abbreviations: NH non-Hispanic, APC Annual percentage change, CI Confidence interval Trends by gender The AAMR was consistently higher in males, with an overall AAMR of 3.81 (95% CI: 3.77–3.86) compared to 3.56 (95% CI: 3.52–3.61) in females. In males, the AAMR significantly decreased from 1999 to 2010 (APC − 2.59*; 95% CI: -4.61 to -2.11), followed by a marginal decrease from 2010 to 2020 (APC-1.34; 95% CI: -1.96 to 1.16). In females, there was a steep decline in AAMR from 1999–2002 (APC − 4.96*; 95% CI: -8.29 to -2.05), followed by a steady decline from 2002 to 2020 (APC − 1.61*; 95% CI: -1.89 to -0.5) (Fig. 1 , Table 2 , and Supplemental Table 2). Trends by race Overall, the AAMR was the highest in NH Black or African Americans, followed by NH American Indian or Alaskan native, Hispanics, NH White, and NH Asian or Pacific Islanders (overall AAMR NH Black or African American: 4.919; 95% CI: 4.82 to 5.02; NH American Indian or Alaskan Natives: 4.48; 95% CI: 4.12 to 4.83; NH Hispanic: 3.576; 95% CI: 3.51 to 3.64; NH White: 3.409; 95% CI: 3.37 to 3.45; NH Asian or Pacific Islander: 2.759; 95% CI: 2.64 to 2.88). AAMR declined in NH American Indian or Alaskan Natives (APC − 1.11; 95% CI: -2.28 to 0.00), NH Black or African American (APC − 1.69; 95% CI: -2.07 to -1.29), and NH Asian or Pacific Islander (APC − 2.02*; 95% CI: -2.73 to -1.29) from 1999–2020. The AAMR for NH white declined from 1999 to 2010 (APC − 2.67*; 95% CI: -4.14 to -2.28) followed by a marginal decline till 2020 (APC − 1.42; 95% CI: -1.96 to 0.63). Among Hispanics, AAMR declined sharply from 1999 to 2001 (APC-7.1*; 95% CI: -10.3 to -1.6), then gradually until 2020 (APC − 1.64; 95% CI: -4.12 to 0.57) (Supplemental Fig. 1, Tables 2 and Supplemental Table 3). Trends by Region Regional trends mirrored the overall decline in AAMR. The South had the highest AAMR of 3.95 (95% CI: 3.9 to 4.01), followed by the Midwest 3.9 (95% CI: 3.82 to 3.97) and the West 3.71 (95% CI: 3.68 to 3.74). The Northeast had a comparatively lower AAMR of 2.83 (95% CI: 2.75 to 2.89). From 1999 to 2020, the AAMR declined in the West (APC − 2.58*; 95% CI: -3.03 to -2.16), Northeast (APC − 2.27*; 95% CI: -2.79 to -1.79), and Midwest (APC-1.92*; 95% CI: -2.32 to -1.55). The South showed a different trend, with an initial decline from 1999 to 2011 (APC − 2.63*; 95% CI: -3.71 to -1.65), followed by a gradual rise from 2011 to 2016 (APC 1.39; 95% CI -3.27 to 4.95), and another steep decline from 2016 to 2020 (APC − 3.26; 95% CI: -8.01 to -0.57) (Fig. 2 and Supplemental Fig. 2, Tables 2 and Supplemental Table 4). Mortality trends and AAMRS (Age-Adjusted Mortality Rates) by ICD codes The total number of deaths for ICD code Q-20 was 4, 442. The AAMR dropped significantly until 2009 (APC − 3.60 * ; 95% CI: -11.36 to -1.68), followed by a gradual rise until 2020. For ICD code Q-21, there were 9,788 deaths. The AAMR significantly declined from 1999 to 2012 (APC − 2.68 * ; 95% CI: -5.15 to -1.8) and then increased till 2020. The ICD Codes Q-22 and Q-24 showed an overall declining mortality trend, with Q-24 showing a significant decline from 1999 to 2020 (APC-2.10 * ; 95% CI: -2.368 to -1.846). There were 10,151 total deaths for ICD Code Q-23. The AAMR significantly dropped from 1999 to 2002 (APC-6.62 * ; 95% CI: -12.91 to -1.53) and continued to decrease slowly thereafter (Supplemental Table 5). Ventricular Septal Defects (VSD) caused the most deaths among all subtypes, totaling 3,434 deaths, followed by Tetralogy of Fallot (TOF), with 3125 deaths and Atrioventricular Septal Defect (AVSD) with 2020 deaths. Atrial Septal Defect (ASD) caused 1660 deaths. Malformation of coronary vessels led to 918 deaths, and Ebstein Anomaly had the fewest deaths with 918 (Supplemental Table 6). The overall AAMR for VSD was 0.245, declining from 0.322 in 1999 to 0.257 in 2020. It reached its lowest in 2012 (APC: -3.0418*; 95% CI: -10.2157 to -1.5038), followed by a rise till 2020 (APC:2.12; 95% CI: -1.2364 to 14.9586). AAMR for AVSD fluctuated significantly, with an overall rate of 0.148. The value reached its lowest of 0.109 in 2009 from 0.161 in 1999 (APC: -3.6633; 95% CI: -7.8727 to 1.1709), peaked at 0.187 in 2016 (APC: 6.0364; 95% CI: -6.3073 to 17.0749), and ended at 0.154 in 2020 (APC: -3.49; 95% CI: -3.4872 to -14.9189). AAMRs for TOF (overall 0.206), ASD (overall 0.122), Malformation of coronary vessels (overall 0.039), and Ebstein Anomaly (overall 0.051) steadily declined from 1999 to 2020. AAMR for TOF decreased from 0.29 in 1999 to 0.157 in 2020 (APC: -1.9523*; 95% CI: -2.6538 to -1.2732). For ASD, AAMR decreased from 0.129 to 0.109 (APC: -1.00*; 95% CI:-1.8939 to -0.1146), Malformation of coronary vessels, from 0.084 to 0.026 (APC:-3.8149*; 95% CI: -7.5503 to -0.3052) and Ebstein Anomaly, from 0.058 to 0.014 (APC:-1.4881*; 95% CI: -2.6820 to -0.3183). DISCUSSION This article describes the mortality trends of CHD in the age group of < 1–14 years from 1999–2020, retrieved from the Center for Disease Control and Prevention WONDER database. Key findings include a decline in overall CHD mortality of individuals aged 0–14 with males having the highest overall AAMR. Non-Hispanic Black/ African Americans and the Southern region of the United States had the highest burden of mortality. In the individual CHD analysis, AVSD, Ebstein Anomaly (EA), and Malformation of coronary vessels (MOCV) displayed a fall in mortality, while VSD mortality declined till 2012, after which a surge was reported. VSD related mortality also contributed to the most deaths amongst all subtypes. Our analysis demonstrated that males with CHD experienced higher mortality than females, although AAMR declined in both genders from 1999 to 2020. These findings are consistent with a prior study of CHD mortality from infancy to adulthood, which reported higher mortality in males and declining trends in both sexes. 5 This may partially be explained by the lower incidence of females with severe CHD, resulting in a lower mortality rate. 7 However, some studies evaluating CHD mortality after cardiac surgery found it to be elevated in females. 8 , 9 This suggests that biological differences in the two genders, including genetics, hormones, and other unexplored characteristics, can play an important role in influencing outcomes. Our results emphasize the importance of accounting for sex in conditions that show differences in illness severity or death between males and females. 7 When stratified based on the race/ethnicity of individuals aged 0–14 years, NH Blacks had the highest mortality, while Asians had the lowest. Although a previous study 5 mostly found similar trends, it also found that NH Whites had higher death rates than Hispanics, contrasting with our result. This discrepancy likely reflects methodological differences, as that study included individuals up to 65 years of age and additional ICD-10 codes (Q25–Q26), whereas our analysis was restricted to ages 0–14 years and ICD-10 codes Q20–Q24. Research has found that Hispanics and NH Blacks are more likely to live under the poverty line with low community funding, which can restrict access to specialized cardiology care, contributing to a higher mortality rate than NH Whites. 10 Blacks and Hispanics are also less likely to attend regular cardiology follow-ups and can experience bias in the healthcare system. 10 , 11 Delays in care and inconsistent post-surgical extracorporeal membrane oxygenation (ECMO) use further increase mortality. 12 Lower Childhood Opportunity Index (COI) of Black children may play a role, as reduced COI following CHD surgery is linked to worse outcomes. 13 Additionally, American Indian/Alaskan Native (AI/AN) exhibited a higher mortality than NH Whites, Hispanics and Asians. This may be attributable to higher poverty rates and, notably, the highest proportion of uninsured individuals with limited funding for Indian Health Services. 14 Genetic differences amongst races may play a role; nevertheless, it remains unproven. 15 Therefore, disparities across races likely reflect differences in access to primary care, health insurance coverage, quality of CHD treatment, and socioeconomic barriers, including limited understanding of the importance of ongoing CHD care. 16 According to our study, all subtypes of CHD showed an overall decline in mortality rate, this is consistent with previous studies that found a substantial decline in CHD mortality for most lesions. 17 Our results demonstrated a significantly higher death toll and AAMR for VSDs over other CHD. Moreover, unlike other lesions, the AAMR of VSD increased in recent years from 2010 to 2020. This may be because VSDs are the most common subtype and can have a broad spectrum of clinical variability and severity. 18 In addition, the prevalence of maternal diabetes, 19 and use of alcohol, marijuana, opium, or SSRIs 20 , 21 have increased in recent years; these exposures have been associated with an increased risk of congenital heart defects, including ventricular septal defects. Notably, maternal hypertension, a common condition in pregnancy, has also been shown to increase the risk of VSD. 22 Furthermore, exposure to ondansetron, the most common medication prescribed during pregnancy for nausea and vomiting, has been linked to a dose-dependent increase in the incidence of VSD. 23 Previous studies indicate that survival in VSD can vary based on repair status and timing of diagnosis, which may influence mortality trends observed in our data. 24,25 According to our analysis, the AAMR for AVSD decreased from 1999 to 2009, followed by a rise from 2009 to 2016 and, finally, a decline from 2016 to 2020. Literature suggests that optimal surgical repair and hospital volume affect AVSD survival and improve mortality rates, which may help explain the recent decline in AVSD AAMR 26 , 27 Overall, all CHD subtypes that were analyzed showed an overall decline in mortality rate from 1999 to 2020. These findings emphasize the progress made in CHD diagnosis and management while also highlighting the need to continue strengthening efforts to reduce CHD related mortality. Targeted interventions in high-mortality regions, such as promoting healthy maternal lifestyles, enhancing prenatal and postnatal care, and reducing exposure to established CHD risk factors may further decrease mortality and improve outcomes for affected children. This study is limited by the CDC WONDER database, which lacks patient-level data on comorbidities, echocardiograms, genetics, CHD-specific treatments, and socioeconomic status. Moreover, analysis for Non-Hispanic American Indians and Alaskan Natives in 2019 showed unreliable data. The strengths of this study include a nationwide, 20-year dataset enabling robust analysis of temporal trends, demographic disparities, and lesion-specific mortality in U.S. children. CONCLUSION Our study demonstrates an initial sharp decline followed by a moderate decline from 2010–2020 in the AAMR of congenital heart defect related mortality amongst individuals aged < 1–14 years. Highest AAMRs are reported amongst males, Non-Hispanic Black or African American individuals and the Southern region of the United States. Further efforts in research, diagnosis, and management are needed to lower the CHD-mortality rates in the future. Abbreviations • AAMR Age–Adjusted Mortality Rate • APC Annual Percent Change • ASD Atrial Septal Defect • AVSD Atrioventricular Septal Defect • CDC Centers for Disease Control and Prevention • CHD Congenital Heart Disease • CI Confidence Interval • EA Ebstein Anomaly • MOCV Malformation of Coronary Vessels • TOF Tetralogy of Fallot • VSD Ventricular Septal Defect • SSRIs Selective Serotonin Reuptake Inhibitors Declarations Ethical approval: Not applicable. This study used publicly available, de-identified data from the CDC WONDER database. Consent for publication: Not Applicable Data availability: The datasets analyzed during the current study are publicly available from the Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database at https://wonder.cdc.gov/. Competing interests: The authors declare that they have no competing interests Funding: No funding was received for this study. Informed consent: Not applicable. No human subjects were directly involved. Author contributions: N.A, M.H, and S.G contributed to conceptualization, data curation, formal analysis, project administration, validation, visualization, and writing of the original draft. N.A also contributed to writing - review and editing. M.O.A, I.N, M.I, and M.A contributed to data curation, formal analysis, and writing of the original draft. HR contributed to data curation and formal analysis. A.M, A.E, and S.A.Q contributed to writing of the original draft. 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Spiegelhalter DJ. Mortality and volume of cases in paediatric cardiac surgery: retrospective study based on routinely collected data. BMJ. 2002;324(7332):261–3. 10.1136/bmj.324.7332.261 . Additional Declarations No competing interests reported. Supplementary Files SupplementalDigitalContentfinal.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. 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-9144914","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":614796263,"identity":"bf64b771-cf79-431e-86a1-63be8638ed47","order_by":0,"name":"Novera Amir Akbani","email":"","orcid":"","institution":"Dow University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Novera","middleName":"Amir","lastName":"Akbani","suffix":""},{"id":614796264,"identity":"97385da5-aefc-499f-a824-c5de84f53545","order_by":1,"name":"Muhammad Hani","email":"","orcid":"","institution":"Dow University of Health 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Hassan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYBACNgkGBmYGA4SAHIg48IAULcZgLQn4rAFrQQKJDSASnxY+6d6HnwsKtuXx969O3VxRcyd9ftjhh0Bb7OR0G3A4TOa4sfQMg9vFEjfebrt55tiz3I230wyAWpKNzQ7g8ksagzSPwe3Ehhtnt91sbDicu3F2AkjLgcRtuLUw/wZpmQ/Vkm44O/0DIS1sYFs2nO8Fa0mQl84hYIvMMTZrkJaNN3i33Ww49sxwg3ROwYEEA9x+kZ/dxnyb58/txHnngQ5rqLkjLz87ffOHDxV2cri0IIBEAog8wGAAVmmATykM8B+AaJFvIEb1KBgFo2AUjCQAAMZbavqiUHPjAAAAAElFTkSuQmCC","orcid":"","institution":"University of Khartoum","correspondingAuthor":true,"prefix":"","firstName":"Ibrahim","middleName":"Nagmeldin","lastName":"Hassan","suffix":""}],"badges":[],"createdAt":"2026-03-17 06:38:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9144914/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9144914/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105927822,"identity":"9f83677b-5e30-4177-bf19-7514bd2e51f0","added_by":"auto","created_at":"2026-04-01 13:42:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85867,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cu\u003eOverall and Sex-Stratified Congenital heart disease- Related AAMRs per 100,000 in the United States, 1999 to 2020\u003c/u\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9144914/v1/cb57352a87355c5e982b671b.png"},{"id":105927829,"identity":"e2fb619f-684a-4b6d-b159-72e889b22cf3","added_by":"auto","created_at":"2026-04-01 13:42:43","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":99132,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cu\u003eCongenital Heart Disease-related Age-Adjusted Mortality Rates per 100,000 in the United States Census Regions, 1999-2020\u003c/u\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9144914/v1/3e6f6da473f323e8304d23e2.jpeg"},{"id":106516385,"identity":"a5e7e5cc-a28d-4514-921b-fa976ba94444","added_by":"auto","created_at":"2026-04-09 11:58:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":996136,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9144914/v1/4ec0c813-9815-425a-a35b-898356fdac80.pdf"},{"id":105927733,"identity":"46abb79a-07ef-4a87-be61-5aeabae68170","added_by":"auto","created_at":"2026-04-01 13:42:25","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2651729,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalDigitalContentfinal.docx","url":"https://assets-eu.researchsquare.com/files/rs-9144914/v1/6a2e993f971438c2972f73fe.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mortality Trends Related to Congenital Heart Defects in United States: a CDC WONDER analysis","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCongenital Heart Defects (CHD) encompass structural and functional abnormalities of the heart that are present at birth and affect approximately 0.8% of live births worldwide.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Between 1990\u0026ndash;2017, global CHD incidence remained stable; though, high\u0026ndash;SDI regions such as the United States saw an increase. \u003csup\u003e2\u003c/sup\u003e Approximately 1/100 children in the United States are born with CHD.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAdvances in medical and surgical advancements have led to a significant decrease in worldwide mortality.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Nevertheless, CHD continues to remain one of the leading causes of death due to congenital defects among infants in the United States.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePrior studies have found disparities in CHD mortality based on gender, race, and census region. Higher mortality rates were reported in Non-Hispanic Blacks and males in comparison to Non-Hispanic Whites and females, respectively.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Census region has also been associated with infant mortality due to CHD in the USA.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e However, a comprehensive national analysis examining the trends of CHD related mortality across multiple variables in the pediatric population remains limited.\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to assess trends in CHD-related mortality stratified by race, gender, place of death and census region from 1999\u0026ndash;2020 among children\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026ndash;14 years of age in the United States. Improved understanding of these patterns may help identify vulnerable populations and inform targeted interventions to reduce mortality rates.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Setting and Population\u003c/h2\u003e \u003cp\u003eWe performed a retrospective, population-based cross-sectional analysis using death certificate data from the Centers for Disease Control and Prevention WONDER (Wide-Ranging Online Data for Epidemiologic Research) database. Our main objective was to evaluate the mortality rates among children aged\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026ndash;14 with Congenital Heart Disease (CHD) from 1999 to 2020. To identify these cases, we utilized the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) codes: Q20, Q21, Q22, Q23, Q24, Q21.1, Q21.0, Q21.2, Q21.3, Q22.5, and Q24.5. Data were obtained from the Multiple Cause of Death Public Use dataset, including records where CHD was listed as either a contributing factor or the primary cause of death. Since we used a de-identified public-use dataset provided by the government, institutional review board approval was not required.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Abstraction\u003c/h3\u003e\n\u003cp\u003eData were stratified by gender, race/ethnicity, place of death, census region, and annual trends. Places of death included inpatient and outpatient medical facilities. Racial/ethnic categories were Hispanic (Latino), Non-Hispanic (NH) White, NH Black/African American, NH American Indian/Alaskan Native, and NH Asian. U.S. regions were classified according to the U.S Census Bureau\u0026rsquo;s classification: Northeast, Midwest, South, and West. Yearly analyses were also conducted for individual ICD-10 codes to assess temporal trends.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eCHD-related mortality trends from 1999 to 2020 were analyzed by gender, race, age, place of death, year, and census region. Crude and age-adjusted mortality rates (AAMR) per 100,000 individuals were calculated, using the 2000 U.S population for AAMR standardization. Temporal trends were evaluated using Joinpoint Regression Program (Version 5.0.2, National Cancer Institute), fitting log-linear regression models to the crude data trends to determine the annual percent change (APC) in AAMR along with its 95% confidence interval (CI). APCs were categorized as increasing or decreasing based on their statistical deviation from the null hypothesis of zero change. Statistical significance was assessed using a 2-tailed t-test with a significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eDuring manuscript preparation, the authors used ChatGPT (OpenAI, GPT-5) for some sections solely to improve language clarity and readability. No AI tools were used for data analysis, statistical modeling, or interpretation of results. All content was reviewed and verified by the authors, who take full responsibility for the accuracy and integrity of the work.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eFrom 1999 to 2020, a total of 49,890 deaths were reported due to congenital heart disease in individuals aged\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026ndash;14 years.\u003c/p\u003e\n\u003ch3\u003eDemographics:\u003c/h3\u003e\n\u003cp\u003eOf these deaths, 23,605 (47.3%) were females and 26,285 (52.7%) were males. Data for race was available for 49,639 deaths, out of which 25,200 (50.8%) were white, 11,853 (23.9%) were Hispanic, 10,055 (20.3%) were Black or African American, 1,916 (3.9%) were Asian or Pacific Islander, and 615 (1.2%) were Alaskan American or Native American. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) Place of death data was available for 49,738 deaths, of which 45,377 (91%) occurred in medical facilities, 3,630 (7.3%) occurred at decedents' homes, 194 (0.4%) occurred at hospice facilities, and 121 (0.2%) occurred at nursing homes/long-term care (Supplemental Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCongenital Heart Disease Related Mortality, Stratified by Sex and Race, in the United States, 1999 to 2020\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003eTotal Deaths\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal Population\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNH American Indian or Alaska Native\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNH Asian or Pacific Islander\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNH Black or African American\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNH White\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e59955368\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60253375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60450257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60563030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60628650\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60651802\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60519046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60516709\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60681615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60907384\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e61087581\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e61227213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e61201106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e61144098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e61089123\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e61067955\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e61016787\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60975069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e61021552\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60885444\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60570846\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60293426\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eAbbreviations: NH non-Hispanic\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAnnual trends\u003c/h2\u003e \u003cp\u003eFrom 1999\u0026ndash;2020, the AAMR for CHD-related deaths decreased from 4.75 to 2.98. The AAMR declined from 1999 to 2010 (APC\u0026thinsp;\u0026minus;\u0026thinsp;2.55*; 95% CI: -4.57 to -2.08), followed by a slower decline from 2010 to 2020 (APC\u0026thinsp;\u0026minus;\u0026thinsp;1.25; 95% CI: -1.85 to 1.23) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnual Percentage Change (APC) of Congenital Heart Disease Related Age-Adjusted Mortality Rates Per 100,000 in the United States, 1999\u0026ndash;2020\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026minus;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear Interval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPC (95% CL)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-2.55*(-4.6\u0026ndash;2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2010\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-1.3(-1.9-1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-4.96*(-8.3\u0026ndash;2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2002\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-1.61*(-1.9\u0026ndash;0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-2.59*(-4.6\u0026ndash;2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2010\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-1.3(-2.0-1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNH American Indian or Alaskan Native\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-1.1(-2.3-0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNH Asian or Pacific Islander\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-2.02*(-2.7\u0026ndash;1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNH Black or African American\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-1.7(-2.1\u0026ndash;1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNH White\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-2.67*(-4.1\u0026ndash;2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2010\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-1.4(-2.0-0.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHispanic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-7.1*(-10.3\u0026ndash;1.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2001\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-1.6(-4.1-0.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNortheast\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-2.27*(-2.8\u0026ndash;1.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMidwest\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-1.92*(-2.3\u0026ndash;1.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSouth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-2.63*(-3.7\u0026ndash;1.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2011\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e1.4(-3.3-5.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2016\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-3.3(-8.0\u0026ndash;0.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWest\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e-2.58*(-3.0\u0026ndash;2.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eAbbreviations: NH non-Hispanic, APC Annual percentage change, CI Confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTrends by gender\u003c/h3\u003e\n\u003cp\u003eThe AAMR was consistently higher in males, with an overall AAMR of 3.81 (95% CI: 3.77\u0026ndash;3.86) compared to 3.56 (95% CI: 3.52\u0026ndash;3.61) in females. In males, the AAMR significantly decreased from 1999 to 2010 (APC\u0026thinsp;\u0026minus;\u0026thinsp;2.59*; 95% CI: -4.61 to -2.11), followed by a marginal decrease from 2010 to 2020 (APC-1.34; 95% CI: -1.96 to 1.16). In females, there was a steep decline in AAMR from 1999\u0026ndash;2002 (APC\u0026thinsp;\u0026minus;\u0026thinsp;4.96*; 95% CI: -8.29 to -2.05), followed by a steady decline from 2002 to 2020 (APC\u0026thinsp;\u0026minus;\u0026thinsp;1.61*; 95% CI: -1.89 to -0.5) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and Supplemental Table\u0026nbsp;2).\u003c/p\u003e\n\u003ch3\u003eTrends by race\u003c/h3\u003e\n\u003cp\u003eOverall, the AAMR was the highest in NH Black or African Americans, followed by NH American Indian or Alaskan native, Hispanics, NH White, and NH Asian or Pacific Islanders (overall AAMR NH Black or African American: 4.919; 95% CI: 4.82 to 5.02; NH American Indian or Alaskan Natives: 4.48; 95% CI: 4.12 to 4.83; NH Hispanic: 3.576; 95% CI: 3.51 to 3.64; NH White: 3.409; 95% CI: 3.37 to 3.45; NH Asian or Pacific Islander: 2.759; 95% CI: 2.64 to 2.88). AAMR declined in NH American Indian or Alaskan Natives (APC\u0026thinsp;\u0026minus;\u0026thinsp;1.11; 95% CI: -2.28 to 0.00), NH Black or African American (APC\u0026thinsp;\u0026minus;\u0026thinsp;1.69; 95% CI: -2.07 to -1.29), and NH Asian or Pacific Islander (APC\u0026thinsp;\u0026minus;\u0026thinsp;2.02*; 95% CI: -2.73 to -1.29) from 1999\u0026ndash;2020. The AAMR for NH white declined from 1999 to 2010 (APC\u0026thinsp;\u0026minus;\u0026thinsp;2.67*; 95% CI: -4.14 to -2.28) followed by a marginal decline till 2020 (APC\u0026thinsp;\u0026minus;\u0026thinsp;1.42; 95% CI: -1.96 to 0.63). Among Hispanics, AAMR declined sharply from 1999 to 2001 (APC-7.1*; 95% CI: -10.3 to -1.6), then gradually until 2020 (APC\u0026thinsp;\u0026minus;\u0026thinsp;1.64; 95% CI: -4.12 to 0.57) (Supplemental Fig.\u0026nbsp;1, Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Supplemental Table\u0026nbsp;3).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTrends by Region\u003c/h2\u003e \u003cp\u003eRegional trends mirrored the overall decline in AAMR. The South had the highest AAMR of 3.95 (95% CI: 3.9 to 4.01), followed by the Midwest 3.9 (95% CI: 3.82 to 3.97) and the West 3.71 (95% CI: 3.68 to 3.74). The Northeast had a comparatively lower AAMR of 2.83 (95% CI: 2.75 to 2.89). From 1999 to 2020, the AAMR declined in the West (APC\u0026thinsp;\u0026minus;\u0026thinsp;2.58*; 95% CI: -3.03 to -2.16), Northeast (APC\u0026thinsp;\u0026minus;\u0026thinsp;2.27*; 95% CI: -2.79 to -1.79), and Midwest (APC-1.92*; 95% CI: -2.32 to -1.55). The South showed a different trend, with an initial decline from 1999 to 2011 (APC\u0026thinsp;\u0026minus;\u0026thinsp;2.63*; 95% CI: -3.71 to -1.65), followed by a gradual rise from 2011 to 2016 (APC 1.39; 95% CI -3.27 to 4.95), and another steep decline from 2016 to 2020 (APC\u0026thinsp;\u0026minus;\u0026thinsp;3.26; 95% CI: -8.01 to -0.57) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Supplemental Fig.\u0026nbsp;2, Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Supplemental Table\u0026nbsp;4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMortality trends and AAMRS (Age-Adjusted Mortality Rates) by ICD codes\u003c/h2\u003e \u003cp\u003eThe total number of deaths for ICD code Q-20 was 4, 442. The AAMR dropped significantly until 2009 (APC\u0026thinsp;\u0026minus;\u0026thinsp;3.60\u003cb\u003e*\u003c/b\u003e; 95% CI: -11.36 to -1.68), followed by a gradual rise until 2020. For ICD code Q-21, there were 9,788 deaths. The AAMR significantly declined from 1999 to 2012 (APC\u0026thinsp;\u0026minus;\u0026thinsp;2.68\u003cb\u003e*\u003c/b\u003e; 95% CI: -5.15 to -1.8) and then increased till 2020.\u003c/p\u003e \u003cp\u003eThe ICD Codes Q-22 and Q-24 showed an overall declining mortality trend, with Q-24 showing a significant decline from 1999 to 2020 (APC-2.10\u003cb\u003e*\u003c/b\u003e; 95% CI: -2.368 to -1.846). There were 10,151 total deaths for ICD Code Q-23. The AAMR significantly dropped from 1999 to 2002 (APC-6.62\u003cb\u003e*\u003c/b\u003e; 95% CI: -12.91 to -1.53) and continued to decrease slowly thereafter (Supplemental Table\u0026nbsp;5).\u003c/p\u003e \u003cp\u003eVentricular Septal Defects (VSD) caused the most deaths among all subtypes, totaling 3,434 deaths, followed by Tetralogy of Fallot (TOF), with 3125 deaths and Atrioventricular Septal Defect (AVSD) with 2020 deaths. Atrial Septal Defect (ASD) caused 1660 deaths. Malformation of coronary vessels led to 918 deaths, and Ebstein Anomaly had the fewest deaths with 918 (Supplemental Table\u0026nbsp;6).\u003c/p\u003e \u003cp\u003eThe overall AAMR for VSD was 0.245, declining from 0.322 in 1999 to 0.257 in 2020. It reached its lowest in 2012 (APC: -3.0418*; 95% CI: -10.2157 to -1.5038), followed by a rise till 2020 (APC:2.12; 95% CI: -1.2364 to 14.9586). AAMR for AVSD fluctuated significantly, with an overall rate of 0.148. The value reached its lowest of 0.109 in 2009 from 0.161 in 1999 (APC: -3.6633; 95% CI: -7.8727 to 1.1709), peaked at 0.187 in 2016 (APC: 6.0364; 95% CI: -6.3073 to 17.0749), and ended at 0.154 in 2020 (APC: -3.49; 95% CI: -3.4872 to -14.9189).\u003c/p\u003e \u003cp\u003eAAMRs for TOF (overall 0.206), ASD (overall 0.122), Malformation of coronary vessels (overall 0.039), and Ebstein Anomaly (overall 0.051) steadily declined from 1999 to 2020. AAMR for TOF decreased from 0.29 in 1999 to 0.157 in 2020 (APC: -1.9523*; 95% CI: -2.6538 to -1.2732). For ASD, AAMR decreased from 0.129 to 0.109 (APC: -1.00*; 95% CI:-1.8939 to -0.1146), Malformation of coronary vessels, from 0.084 to 0.026 (APC:-3.8149*; 95% CI: -7.5503 to -0.3052) and Ebstein Anomaly, from 0.058 to 0.014 (APC:-1.4881*; 95% CI: -2.6820 to -0.3183).\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis article describes the mortality trends of CHD in the age group of \u0026lt;\u0026thinsp;1\u0026ndash;14 years from 1999\u0026ndash;2020, retrieved from the Center for Disease Control and Prevention WONDER database. Key findings include a decline in overall CHD mortality of individuals aged 0\u0026ndash;14 with males having the highest overall AAMR. Non-Hispanic Black/ African Americans and the Southern region of the United States had the highest burden of mortality. In the individual CHD analysis, AVSD, Ebstein Anomaly (EA), and Malformation of coronary vessels (MOCV) displayed a fall in mortality, while VSD mortality declined till 2012, after which a surge was reported. VSD related mortality also contributed to the most deaths amongst all subtypes.\u003c/p\u003e \u003cp\u003eOur analysis demonstrated that males with CHD experienced higher mortality than females, although AAMR declined in both genders from 1999 to 2020. These findings are consistent with a prior study of CHD mortality from infancy to adulthood, which reported higher mortality in males and declining trends in both sexes.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e This may partially be explained by the lower incidence of females with severe CHD, resulting in a lower mortality rate.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e However, some studies evaluating CHD mortality after cardiac surgery found it to be elevated in females.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e This suggests that biological differences in the two genders, including genetics, hormones, and other unexplored characteristics, can play an important role in influencing outcomes. Our results emphasize the importance of accounting for sex in conditions that show differences in illness severity or death between males and females.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWhen stratified based on the race/ethnicity of individuals aged 0\u0026ndash;14 years, NH Blacks had the highest mortality, while Asians had the lowest. Although a previous study\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e mostly found similar trends, it also found that NH Whites had higher death rates than Hispanics, contrasting with our result. This discrepancy likely reflects methodological differences, as that study included individuals up to 65 years of age and additional ICD-10 codes (Q25\u0026ndash;Q26), whereas our analysis was restricted to ages 0\u0026ndash;14 years and ICD-10 codes Q20\u0026ndash;Q24. Research has found that Hispanics and NH Blacks are more likely to live under the poverty line with low community funding, which can restrict access to specialized cardiology care, contributing to a higher mortality rate than NH Whites.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Blacks and Hispanics are also less likely to attend regular cardiology follow-ups and can experience bias in the healthcare system.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Delays in care and inconsistent post-surgical extracorporeal membrane oxygenation (ECMO) use further increase mortality.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Lower Childhood Opportunity Index (COI) of Black children may play a role, as reduced COI following CHD surgery is linked to worse outcomes.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAdditionally, American Indian/Alaskan Native (AI/AN) exhibited a higher mortality than NH Whites, Hispanics and Asians. This may be attributable to higher poverty rates and, notably, the highest proportion of uninsured individuals with limited funding for Indian Health Services.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Genetic differences amongst races may play a role; nevertheless, it remains unproven.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Therefore, disparities across races likely reflect differences in access to primary care, health insurance coverage, quality of CHD treatment, and socioeconomic barriers, including limited understanding of the importance of ongoing CHD care.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAccording to our study, all subtypes of CHD showed an overall decline in mortality rate, this is consistent with previous studies that found a substantial decline in CHD mortality for most lesions.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Our results demonstrated a significantly higher death toll and AAMR for VSDs over other CHD. Moreover, unlike other lesions, the AAMR of VSD increased in recent years from 2010 to 2020. This may be because VSDs are the most common subtype and can have a broad spectrum of clinical variability and severity.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e In addition, the prevalence of maternal diabetes,\u003csup\u003e19\u003c/sup\u003e and use of alcohol, marijuana, opium, or SSRIs \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003ehave increased in recent years; these exposures have been associated with an increased risk of congenital heart defects, including ventricular septal defects. Notably, maternal hypertension, a common condition in pregnancy, has also been shown to increase the risk of VSD.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Furthermore, exposure to ondansetron, the most common medication prescribed during pregnancy for nausea and vomiting, has been linked to a dose-dependent increase in the incidence of VSD.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Previous studies indicate that survival in VSD can vary based on repair status and timing of diagnosis, which may influence mortality trends observed in our data. \u003csup\u003e24,25\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAccording to our analysis, the AAMR for AVSD decreased from 1999 to 2009, followed by a rise from 2009 to 2016 and, finally, a decline from 2016 to 2020. Literature suggests that optimal surgical repair and hospital volume affect AVSD survival and improve mortality rates, which may help explain the recent decline in AVSD AAMR \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOverall, all CHD subtypes that were analyzed showed an overall decline in mortality rate from 1999 to 2020. These findings emphasize the progress made in CHD diagnosis and management while also highlighting the need to continue strengthening efforts to reduce CHD related mortality.\u003c/p\u003e \u003cp\u003eTargeted interventions in high-mortality regions, such as promoting healthy maternal lifestyles, enhancing prenatal and postnatal care, and reducing exposure to established CHD risk factors may further decrease mortality and improve outcomes for affected children.\u003c/p\u003e \u003cp\u003eThis study is limited by the CDC WONDER database, which lacks patient-level data on comorbidities, echocardiograms, genetics, CHD-specific treatments, and socioeconomic status. Moreover, analysis for Non-Hispanic American Indians and Alaskan Natives in 2019 showed unreliable data. The strengths of this study include a nationwide, 20-year dataset enabling robust analysis of temporal trends, demographic disparities, and lesion-specific mortality in U.S. children.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOur study demonstrates an initial sharp decline followed by a moderate decline from 2010\u0026ndash;2020 in the AAMR of congenital heart defect related mortality amongst individuals aged\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026ndash;14 years. Highest AAMRs are reported amongst males, Non-Hispanic Black or African American individuals and the Southern region of the United States. Further efforts in research, diagnosis, and management are needed to lower the CHD-mortality rates in the future.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; AAMR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAge\u0026ndash;Adjusted Mortality Rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; APC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnnual Percent Change\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; ASD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAtrial Septal Defect\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; AVSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAtrioventricular Septal Defect\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; CDC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCenters for Disease Control and Prevention\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; CHD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCongenital Heart Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; CI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; EA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEbstein Anomaly\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; MOCV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMalformation of Coronary Vessels\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; TOF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTetralogy of Fallot\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; VSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVentricular Septal Defect\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; SSRIs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSelective Serotonin Reuptake Inhibitors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthical approval: Not applicable. This study used publicly available, de-identified data from the CDC WONDER database.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication: Not Applicable \u0026nbsp;\u003cbr\u003eData availability: The datasets analyzed during the current study are publicly available from the Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database at https://wonder.cdc.gov/.\u003c/p\u003e\n\u003cp\u003eCompeting interests: The authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003eFunding: No funding was received for this study. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInformed consent: Not applicable. No human subjects were directly involved.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthor contributions: N.A, M.H, and S.G contributed to conceptualization, data curation, formal analysis, project administration, validation, visualization, and writing of the original draft. N.A also contributed to writing - review and editing. M.O.A, I.N, M.I, and M.A contributed to data curation, formal analysis, and writing of the original draft. HR contributed to data curation and formal analysis. A.M, A.E, and S.A.Q contributed to writing of the original draft. D.A.A contributed to supervision, project administration, data curation, and writing - review and editing. I.N.H and A.Z.K contributed to writing - review and editing. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBouma BJ, Mulder BJ. Changing landscape of congenital heart disease. 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Mortality and volume of cases in paediatric cardiac surgery: retrospective study based on routinely collected data. BMJ. 2002;324(7332):261\u0026ndash;3. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj.324.7332.261\u003c/span\u003e\u003cspan address=\"10.1136/bmj.324.7332.261\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":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":"Congenital heart disease, Pediatric mortality, Cross-sectional study, CDC WONDER database, United States, Cardiothoracic surgery","lastPublishedDoi":"10.21203/rs.3.rs-9144914/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9144914/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBACKGROUND\u003c/h2\u003e \u003cp\u003eCongenital heart defects (CHD) are diagnosed in 1/100 live births in the United States. Advances in medical care have reduced CHD-related mortality, but disparities remain across demographic and geographic groups.\u003c/p\u003e\u003ch2\u003eMETHODS\u003c/h2\u003e \u003cp\u003eDeath certificates from the CDC WONDER database were analyzed from 1999 to 2020 in children aged\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026ndash;14 years. Age-adjusted mortality rates (AAMRs) per 100,000 individuals were calculated and stratified by race, gender, place of death, and census region. Joinpoint regression analysis was used to determine annual percent changes (APC) and identify trends in mortality rates.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eA total of 49,890 deaths occurred due to CHD from 1999\u0026ndash;2020. The AAMR declined from 4.748 in 1999 to 3.473 in 2010 (APC\u0026thinsp;\u0026minus;\u0026thinsp;2.55*; 95%CI:-4.57 to -2.08) and from 3.473 in 2010 to 2.987 in 2020 (APC\u0026thinsp;\u0026minus;\u0026thinsp;1.25; 95% CI: -1.85 to 1.23). Males had a higher overall AAMR (3.81) than females (3.56). Non-Hispanic Black had the highest AAMR (4.919), while Non-Hispanic Asian had the lowest (2.759). The South showed the highest AAMR (3.953) and the Northwest the lowest (2.823). The majority of deaths occurred in medical facilities (91%), followed by decedents' homes (7.3%), hospice facilities (0.4%), and nursing homes/long-term care (0.2%). Among CHD subtypes, VSD-related mortality had the highest AAMR (0.245) while Malformation of coronary vessels the lowest (0.039).\u003c/p\u003e\u003ch2\u003eCONCLUSION\u003c/h2\u003e \u003cp\u003eCHD-related AAMR fell from 1999 to 2020 with a slower decline between 2010 and 2020. The data showed that the AAMR was consistently higher in males, NH Black, and in Southern and Midwestern regions, with most deaths occurring in medical facilities.\u003c/p\u003e","manuscriptTitle":"Mortality Trends Related to Congenital Heart Defects in United States: a CDC WONDER analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-01 13:38:26","doi":"10.21203/rs.3.rs-9144914/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":"3a111a6d-0274-4133-9673-97e3bf5d35c2","owner":[],"postedDate":"April 1st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T11:57:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-01 13:38:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9144914","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9144914","identity":"rs-9144914","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}