Trends and Demographic Disparities Among Adults With Sudden Cardiac Death and Diabetes Mellitus in the United States: A Nationwide Analysis

Taha Mehmood; Muhammad Abdullah; Masab Ali; Amina Jamil; Muhammad Husnain Ahmad; Muhammad Mujtaba Tariq; Areej Asif; Sunnia Khan; Moeez Ahmad Saeed; Muhammad Hassan; Aasim Ali; Muhammad Umar Shahid; Shahzaib Ihsan; Muhammad Usama Yasin; Usama Siddique

doi:10.1002/joa3.70467

. 2026 Oct 1;42(5):e70467. doi: 10.1002/joa3.70467

Trends and Demographic Disparities Among Adults With Sudden Cardiac Death and Diabetes Mellitus in the United States: A Nationwide Analysis

Taha Mehmood ¹, Muhammad Abdullah ¹, Masab Ali ², Amina Jamil ³, Muhammad Husnain Ahmad ^4,^✉, Muhammad Mujtaba Tariq ¹, Areej Asif ⁵, Sunnia Khan ¹, Moeez Ahmad Saeed ¹, Muhammad Hassan ¹, Aasim Ali ⁶, Muhammad Umar Shahid ¹, Shahzaib Ihsan ¹, Muhammad Usama Yasin ¹, Usama Siddique ¹

PMCID: PMC13628289 PMID: 42824888

ABSTRACT

Background

Sudden cardiac death (SCD) represents a major cause of cardiovascular mortality, with diabetes mellitus (DM) significantly increasing susceptibility. However, long‐term national trends and demographic disparities in SCD among decedents with co‐documented SCD and DM remain insufficiently characterized.

Methods

We conducted a retrospective analysis using the CDC WONDER database from 1999 to 2020. Adults with SCD and DM listed on death certificates were included. Age‐adjusted mortality rates (AAMRs) per 100 000 population were calculated and stratified by sex, age group, race/ethnicity, census region, state, and urbanization status. Temporal trends were assessed using annual percent changes (APCs), with p < 0.05 considered statistically significant.

Results

A total of 51 756 deaths among decedents with co‐documented SCD and DM were identified. Overall AAMR increased from 1.29 in 1999 to 1.46 in 2020 (APC +0.46%, p = 0.012). Men had significantly higher mortality than women. Older adults (≥ 75 years) exhibited the highest mortality burden, though relative increases were notable in younger groups. Black individuals had the highest mortality, with a sharp rise in 2020. Rural populations experienced higher mortality than urban counterparts, with significant upward trends. Southern states demonstrated the highest regional burden.

Conclusion

The population‐level burden of co‐documented SCD and DM in the United States has increased modestly over the past two decades, with significant demographic and geographic disparities. Targeted public health interventions and equitable cardiovascular risk management are urgently needed to reduce these disparities.

Keywords: diabetes mellitus, health disparities, mortality trends, sudden cardiac death

From 1999 to 2020, 51 756 U.S. deaths documented both sudden cardiac death and diabetes mellitus, with population‐level burden rising significantly (APC +0.46%). Disparities were greatest among men, Black populations, rural residents, and Southern states, with a sharp mortality surge in 2020 coinciding with the COVID‐19 pandemic.

graphic file with name JOA3-42-e70467-g005.webp

Abbreviations

(AAMR): age‐adjusted mortality rates
(AI/AN): NH American Indian/Alaska Native
(APC): annual percent change
(API): Asian/Pacific Islander
(CDC WONDER): Centers for Disease Control Wide‐Ranging Online Data for Epidemiologic Research
(DM): diabetes mellitus
(NH): non‐Hispanic
(SCD): sudden cardiac death

1. Introduction

Sudden cardiac death (SCD) is a major and under‐recognized contributor to cardiovascular mortality, and diabetes mellitus (DM) is a powerful risk enhancer for SCD. In large epidemiologic studies, diabetes has been consistently linked to markedly higher SCD rates. For example, a recent meta‐analysis found that adults with diabetes had approximately a two‐fold higher risk (RR 2.02, 95% CI 1.81–2.25) of SCD than non‐diabetic individuals [1]. Nationwide registry studies in Denmark found that both Type 1 and Type 2 diabetics face dramatically elevated SCD incidence, with 3.7 times higher for Type 1 diabetes and 6.5 times higher for Type 2 diabetes than the general population [2], with an especially pronounced relative risk in younger age groups [2, 3]. These findings accord with mechanistic insights: Diabetes accelerates coronary artery disease, myocardial infarction, autonomic neuropathy, and arrhythmogenic vulnerability, all of which predispose to fatal arrhythmias. In diabetics, the molecular pathways to these changes involve enhanced oxidative stress, mitochondrial dysfunction, ion channel remodeling, and prolonged QT intervals—mechanisms that could differentially affect demographic subgroups based on comorbidity burden, treatment access, and risk factor control [4, 5].

In the United States (where ~30 million people have diagnosed diabetes), SCD is a substantial contributor to national mortality. In the present study, 51 756 deaths with both SCD and DM documented on the death certificate were identified over the 21‐year period from 1999 to 2020, averaging approximately 2 500 certified SCD‐DM deaths annually, underscoring the significant population‐level burden of this comorbid condition. Thus, understanding how SCD mortality patterns in diabetics have changed over recent decades is of urgent public health interest. Despite falling overall CVD mortality, emerging data suggest persistent disparities in SCD burden. CVD mortality in diabetics declined significantly by 32% per decade for vascular deaths from 1988 to 2015; yet these gains may not be uniform across demographic subgroups [6] Recent data show concerning reversals, with diabetes‐related cardiovascular mortality increasing from 2014 to 2019 after a decade of decline [7].

Although in the general U.S. population, SCD rates are higher in men than women [8], providing a cardiovascular protective benefit to women, women with diabetes face disproportionately elevated cardiovascular mortality, experiencing a 58% greater excess risk of coronary heart disease (women‐to‐men ratio of relative risks 1.58) and 13% elevated mortality rates compared to diabetic men, and this “female disadvantage” is particularly pronounced for diabetes‐related cardiovascular death. This paradox, where diabetes appears to eliminate or reverse the typical female cardiovascular advantage, is a critical disparity worth investigating the sex‐specific vulnerabilities [9, 10].

While absolute SCD rates increase with age, the relative risk of SCD is highest in younger diabetics. Including the subgroup disparities, Black men experiencing SCD are on average 6+ years younger than White counterparts [11, 12]. SCD rates roughly double in Black Americans compared to Whites [8, 13]. These differences mirror the sociodemographic pattern of diabetes itself: Minority and socioeconomically disadvantaged groups have higher diabetes prevalence. For instance, non‐Hispanic Black and American Indian adults have diabetes prevalence twice that of non‐Hispanic Whites [14].

Recent analyses demonstrate that mortality gains have been smallest in non‐metropolitan areas and the South, regions that also bear higher diabetes prevalence, raising concerns about widening geographic inequities [7, 15]. Rural, Southern, and Midwestern regions of the U.S. also record higher age‐adjusted cardiovascular mortality rates for ASCVD in diabetics. Yet no prior study has systematically examined long‐term SCD mortality trends specifically among U.S. adults with diabetes by demographic subgroup. Non‐metropolitan areas have not only higher baseline rates but also smaller declines in mortality (−0.52% vs. −1.94% in metropolitan areas) [15]. Treatment disparities also exist among subgroups including women, racial/ethnic groups, and certain geographical lines [16]. An important contributor is that women with diabetes are less likely to receive appropriate cardiovascular risk reduction therapy (worse HbA1c control, lower rates of lipid‐lowering therapy, less aspirin use) compared to men. Similar treatment gaps likely exist across racial/ethnic and geographic lines [16].

We therefore analyzed CDC WONDER death certificate data from 1999 to 2020 to characterize national SCD death rates in people with diabetes, stratified by age, sex, race/ethnicity, and region. This study will test the hypothesis that SCD mortality in the co‐documented SCD‐DM population has declined unevenly and remains disproportionately elevated in vulnerable demographic groups. By illuminating these trends and disparities, the work aims to identify these subgroups, including women, resource‐limited populations, and racial minorities, and guide targeted prevention and resource allocation to reduce premature cardiac deaths in diabetics.

2. Method

2.1. Study Setting and Population

We extracted mortality data from the CDC's WONDER (Wide‐Ranging Online Data for Epidemiologic Research) database [17] and examined mortality rates among adults diagnosed with both SCD and DM from 1999 to 2020. Specifically, the Multiple Cause‐of‐Death Public Use Record database was used to identify cases where SCD and DM were listed as contributing causes on U.S. death certificates [18]. This methodology has been employed in several prior studies using CDC WONDER data [19, 20].

Cases of SCD and DM were identified using the International Classification of Diseases, 10th Revision (ICD‐10) codes: I46.1 for SCD and E10‐14 for DM [21]. Given that CDC WONDER encompasses all registered U.S. deaths, the dataset provides a complete national census of mortality events, rendering formal sample size justification unnecessary and ensuring adequate statistical power for subgroup analyses.

The use of ICD‐10 code I46.1 exclusively to identify SCD reflects a deliberate prioritization of diagnostic specificity. Unlike I46.0 (cardiac arrest with successful resuscitation) or I46.9 (cardiac arrest, unspecified), I46.1 is the only code that unambiguously designates a death as formally certified sudden cardiac death on the death certificate, ensuring a homogeneous and consistently defined outcome across the 21‐year study period. Broader clinical SCD estimates—including those cited above—are derived from epidemiologic and forensic surveillance using wider ascertainment criteria that encompass presumed cardiac deaths and out‐of‐hospital arrests; these are fundamentally different from certificate‐documented SCD and are therefore not directly comparable to death certificate‐based counts. The use of I46.1 as the sole identifier for SCD in CDC WONDER analyses is consistent with recent methodology in the published literature [22, 23].

As this study used de‐identified public‐use data from government sources, it was exempt from institutional review board approval, in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [24].

2.2. Data Abstraction

Our demographic variables included population size, age distribution, gender composition, racial/ethnic background, geographic location, and urbanization level, spanning the years 1999 to 2020. The locations of death encompassed medical facilities, decedents' homes, hospices/nursing homes, long‐term care facilities, and unspecified locations. Racial and ethnic groups were categorized as Hispanic (Latino), Non‐Hispanic (NH) White, NH Black, NH American Indian/Alaskan Native, and NH Asian. These classifications are consistent with previous CDC WONDER database analyses and align with the U.S. Office of Budget and Management Guidelines as reflected on death certificates [18].

Age was grouped in ten‐year intervals: 35–54 years (young adults), 55–74 years (middle‐aged adults), and 75 years old and above (older adults), mirroring conventions used in previous national mortality analyses [25]. Geographic stratification followed the 2023 NCHS urban–rural classification scheme for counties (large central, large fringe, medium, small metro; micropolitan; non‐core) [26]. The U.S. Census Bureau's four‐region classification (Northeast, Midwest, South, and West) was used for regional comparisons.

Instances of missing demographic or location data were handled by excluding incomplete entries from subgroup analyses while retaining them in total mortality counts to preserve aggregate accuracy. Missing data comprised < 1% of the dataset and were not expected to materially influence trend estimates.

2.3. Statistical Analysis

We analyzed temporal and demographic patterns by calculating both crude and age‐adjusted mortality rates (AAMRs) per 100 000 population, using the 2000 U.S. population as the standard for age adjustment [27]. It should be noted that AAMRs are calculated using the total U.S. population as the denominator rather than the diabetic population specifically; these rates therefore reflect the population‐level burden of deaths where both SCD and DM were co‐documented on the death certificate, rather than the per‐diabetic risk of SCD. Temporal changes in mortality rates were assessed using the Joinpoint Regression Program (Version 5.0.2, National Cancer Institute) [28], applying log‐linear regression models to evaluate changes over time. The software identifies inflection points (“joinpoints”) representing significant shifts in mortality trends. Given the 25‐year study period, we allowed up to four joinpoints, though fewer could be detected if fewer adequately captured variability. The Grid Search method (2,2,0), permutation test, and parametric approach were used to estimate annual percent change (APC) with 95% confidence intervals (CIs). An APC was deemed statistically significant if the slope differed from 0 (two‐tailed t‐test, p ≤ 0.05). We also accounted for ICD coding transitions (from ICD‐9 to ICD‐10 in 1999) by restricting the study period to ICD‐10‐coded deaths, thereby ensuring consistency in disease classification and trend interpretation.

While mortality data from death certificates are a reliable source of population‐level information, they can introduce misclassification or reporting bias, especially when comorbidities are underreported. However, their nationwide coverage, standardized format, and consistency across years make them a valuable source for long‐term epidemiologic assessment.

3. Results

The population‐level burden of co‐documented SCD and DM in the United States exhibited an overall annual percent change (APC) of +0.46% from 1999 to 2020, reflecting periods of initial increase followed by decline and a sharp rise during the COVID‐19 era. Overall deaths rose from 1806 in 1999 to a peak of 3 139 in 2020, with age‐adjusted mortality rates (AAMR) fluctuating from 1.29 per 100 000 in 1999 to 1.46 in 2020, reflecting a statistically significant upward trend in population‐level SCD‐DM burden (p = 0.012). The majority of deaths occurred in medical facilities (45.0%), followed by home settings (35.0%) and nursing homes/long‐term care facilities (14.6%). Hospice facilities (2.4%) and other locations (3.8%) accounted for smaller proportions (Figure 1, Table S1 and Table S2).

Overall AAMRs for Sudden Cardiac Death and Diabetes mellitus per 100 000 adults in the US. APC significantly different from zero (α = 0.05).

There were marked disparities across sex, with men accounting for substantially higher population‐level SCD‐DM burden than women over the 1999–2020 period, totaling 30 901 male deaths compared to 20 855 female deaths. AAMR further underscored this gap, averaging 1.83 per 100 000 for men versus 0.99 for women, with men reaching an overall study‐period peak of 2.039 in 2007 before declining, and subsequently rebounding to 2.024 in 2020, while women's rates remained lower at 1.003. Temporal trends showed men with a modest overall increase (APC +0.55%, p = 0.044), driven by early rises and a sharp 2020 rebound, whereas women's rates exhibited no significant long‐term change (APC 0.11%, p = 0.62) (Figure 2, Tables S3 and S4).

Gender‐specific AAMRs for Sudden Cardiac Death and Diabetes mellitus per 100 000 adults in the US. APC significantly different from zero (α = 0.05).

Age‐specific analyses revealed older adults were disproportionately affected, with those aged 75+ years experiencing 20 059 deaths and the highest AAMR of 4.78, compared to middle‐aged adults (AAMR 2.05) and young adults (AAMR 0.315). Middle‐aged rates showed phased trends, including an initial surge (APC +2.60%, 1999–2004), decline, and dramatic 2020 increase (APC 13.2%, p = 0.001), while young adults experienced steady growth (APC +1.59%, p = 0.022). Older adults displayed relative stability with a non‐significant overall decline (APC –0.25%) (Figure 3, Table S5).

Age‐specific AAMRs for Sudden Cardiac Death and Diabetes mellitus per 100 000 adults in the US. APC significantly different from zero (α = 0.05).

Racial and ethnic variations highlighted Black or African American populations at highest risk, with an overall AAMR of 2.49, exceeding Whites (1.32), American Indian or Alaska Native (2.22), Hispanics or Latinos (0.78), and Asian or Pacific Islanders (0.59). Black rates fluctuated dramatically, rising early (APC +5.48%, 1999–2006), declining sharply, then surging in 2020 (APC +27.28%, p = 0.001), while Whites showed borderline increases (APC +0.50%, p = 0.086). These patterns persisted across years, with Black AAMR consistently above 2.0 until late declines followed by rebound (Figure 4, Table S6).

Race‐specific AAMRs for Sudden Cardiac Death and Diabetes mellitus per 100 000 adults in the US. APC significantly different from zero (α = 0.05).

Urban–rural divides were pronounced, as non‐metropolitan areas reported higher overall AAMR (2.53) than metropolitan areas (1.83), with rural rates climbing steadily (APC +1.58%, p = 0.001) and peaking at 3.03 in 2020 versus urban 1.21. Non‐metropolitan trends included early gains (APC +2.79%, 1999–2006) and a late surge (APC +8.4%, 2018–2020), contrasting urban stability turning to decline before a 2020 rebound (APC +13.2%). This disparity suggests rural vulnerabilities in access or risk factors (Figure 5, Table S9).

Urbanization‐specific AAMRs for Sudden Cardiac Death and Diabetes mellitus per 100 000 adults in the US. APC significantly different from zero (α = 0.05).

Across U.S. Census regions, distinct temporal trends in AAMRs were observed. The Northeast demonstrated a significant overall decline (APC −1.12%, p = 0.02), with rates decreasing modestly over the study period despite some year‐to‐year fluctuations, including a transient rise in 2020. In contrast, the Midwest showed a stable trend with no statistically significant change over time (APC +0.22%, p = 0.29), although rates remained consistently higher than the Northeast. Overall, the South had a small but significant increase across the full period (AAPC +0.53%, p < 0.001). The West showed no significant overall change (APC +0.13%, p = 0.66), with relatively stable rates throughout the study period, despite a slight increase toward 2020. In terms of proportional mortality, the South consistently accounted for the highest percentage of total deaths annually (see Figure 6, Table S8).

Consensus region‐specific AAMRs for Sudden Cardiac Death and Diabetes mellitus per 100 000 adults in the US. APC significantly different from zero (α = 0.05).

State‐level AAMR varied widely, from lows in Nevada (0.23) and Arizona (0.49) to extremes in Mississippi (9.07) and Louisiana (4.62), with southern states like Tennessee (2.62) and North Carolina (2.59) also elevated. Higher‐risk states often aligned with South and Midwest regions, where overall rates exceeded national averages (e.g., South 1.77 in 2020), while West and Northeast tended to be lower (West 1.01 in 2020). These geographic inequities, intersecting with race and urban status, indicate targeted public health needs (see Table S7).

4. Discussion

The study characterizes population‐level trends in certified SCD deaths with co‐documented DM in the United States. Overall, age‐adjusted mortality rates (AAMR) increased from 1.299 per 100 000 in 1999 to 1.463 in 2020 with a statistically significant rise from 1999 to 2020 (p = 0.012). Gender disparities were substantial, with men experiencing almost double the age‐specific mortality rate (AAMR) of 1.841 compared to 0.986 for women. This AAMR reached its study‐period peak of 2.039 in 2007 for men before declining, with a subsequent rebound to 2.024 in 2020, while it remained lower at 1.003 for women. Older adults had the highest AAMR of 4.78, followed by 2.04 for middle‐aged adults and 0.315 for young adults. Racial disparities showed that Black or African American populations had the highest AAMR of 2.48, followed by American Indian or Alaska Native (2.22), Whites (1.32), Hispanics or Latinos (0.78), and Asian or Pacific Islanders (0.59). Moreover, the AAMR for Black or African American populations consistently remained above 2.0, only to decline later, followed by a rebound increase. Regionally, the findings highlight heterogeneity in AAMR, with declining trends in the Northeast, stability in the Midwest and West, and marked fluctuations in the South. Geographic trends revealed a higher AAMR in the Southern United States, particularly in states like Mississippi (9.07) and Louisiana (4.62), and in non‐metropolitan areas (2.53) than in metropolitan areas (1.83), with rates peaking in 2020.

These state‐level differences should, however, be interpreted with considerable caution. A disparity of this magnitude—nearly 38‐fold between Nevada (0.23) and Mississippi (9.07)—exceeds what can plausibly be explained by true biological or epidemiologic variation alone. A substantial contributor is likely to be interstate heterogeneity in death certificate completion practices, specifically in how frequently and consistently certifying physicians apply ICD‐10 code I46.1 to cardiac deaths. States with higher rates of I46.1 certification will mechanically produce higher observed AAMRs under this study's methodology, regardless of underlying disease burden. The state‐level findings should therefore be understood as reflecting patterns in certified SCD documentation rather than confirmed differences in true SCD incidence, and caution is warranted before drawing policy conclusions based on individual state rankings.

There are several factors that contribute to SCD in the SCD‐DM population, including diabetic cardiomyopathy and arrhythmogenesis. This is characterized by myocardial hypertrophy, fibrosis, and apoptosis. Factors such as oxidative stress, mitochondrial dysfunction, ion‐channel remodeling, and prolonged QT intervals lead to lethal arrhythmias. Hyperglycemia and insulin resistance contribute to the expression of genes such as insulin‐like growth factor 1 receptor, B‐type natriuretic peptide, and β‐myosin heavy chain. Fibrosis is the result of upregulation of transforming growth factor β1 brought about by the renin‐angiotensin‐aldosterone system and sympathetic nervous system, in addition to hyperglycemia, hyperinsulinemia, and advanced glycation end products‐mediated signaling. Hyperlipidemia contributes to lipid deposition and lipotoxicity; hyperglycemia induces a pro‐apoptotic effect because of increased oxidative stress, glycosylation, and phosphorylation of p53. In addition, endothelial dysfunction, endothelin‐1 upregulation, nitric oxide downregulation, dysregulated autophagic response resulting in excessive cell death, and autonomic neuropathy can all reduce the coronary blood reserve [29].

In DM, ischemic cardiomyopathy contributes to an increased risk for arrhythmias. But other factors such as chronic hyperglycemia, systemic inflammation, and oxidative stress all contribute to the structural and conduction abnormalities. This, in addition to the autonomic neuropathy and electrolyte abnormalities that develop as a complication of diabetes, leads to various cardiac conduction abnormalities [30]. In particular, the variant alleles (O/O genotype) and a higher albumin/creatinine ratio were seen to exhibit the highest hazard ratio when it came to adverse cardiac outcomes [31]. Although the cause behind sudden cardiac death is usually multifactorial, no cause is identified in about 40% of deaths [32].

The increase in population‐level SCD‐DM mortality over time can be explained by an increased prevalence of the risk factors. For instance, in adults aged 20 to 44 years, there was an increase in the age‐adjusted prevalence of hypertension and obesity over the years. This increase also contributed to the gender disparities seen in the study, as from 2015 to 2020, this adjusted prevalence of hypertension was higher in men compared with women. Hyperlipidemia followed the same trend in addition to a personal history of smoking [33]. The prevalence of obesity significantly increased across all other racial and ethnic groups [34], [35] The cause behind these disparities is likely multifactorial, but inequities in access to health care and structural racism might be the contributing factors [36].

Several explanations can account for the increased population‐level SCD‐DM mortality rates during the COVID‐19 pandemic (2020). DM is a significant risk factor for severe infection and intensive care unit admission [37, 38, 39, 40, 41]. In addition, SARS‐CoV‐2 infection leads to worsened insulin resistance and glycemic control [38, 39]. Moreover, the course of diabetes mellitus worsened during the pandemic due to the need to stay at home, the decrease in physical activity, sedentary lifestyle, and mental stress [40, 41, 42]. In addition, outpatient visits and monitoring of diabetes mellitus saw a significant drop, hindering and creating a significant gap in access to care for these patients [43]. Moreover, the practices of avoiding vaccination and exhibiting an increased incidence of smoking and alcohol use also contributed to a worsened disease course in this population. The higher AAMR for Black or African American populations can be explained by the highest rates of hypertension being noted in black adults. These increases were also seen among Mexican American and other Hispanic adults [33]. In different studies, racial and ethnic minorities were seen to have a higher prevalence of diabetes and obesity in addition to a more sedentary lifestyle and poorer glycemic control [44, 45, 46, 47]. In addition, black adults also have the highest rates of heart failure, stroke, and hypertensive renal diseases [48]. Moreover, the mortality rates from premature cardiovascular disease for African Americans are the highest in the country [49].

In addition, contrary to the reports that the neighborhood poverty gap is being narrowed, Black, Hispanic, and American Indian populations are much more likely to live in neighborhoods with a high poverty rate [50]. In addition, the increased consumption of processed food, on top of the barriers that limit access to insurance and healthy food, also contributes to the worsening of disease severity.

It's been shown that living in the Southern United States is linked to a decreased life expectancy regardless of diabetes mellitus, in addition to a poorer quality of life for patients with diabetes mellitus. Moreover, the probability of developing chronic disease co‐existing and contribute to the severity of diabetes mellitus and a worse prognosis is higher in people with diabetes who were born in the Southern United States. In addition, diabetes mellitus contributes to a shorter life expectancy for people living in the South, with a probability of 79.2% compared to the Northeast, 93.4% relative to the Midwest, and 66.2% when compared to the West [51].

DM also follows suboptimal treatment rates, with only about 1 in 2 young adults being on treatment. This may be because of the guidelines that have emphasized an age‐based approach to be followed for screening, not recommending screening until 35 years of age, resulting in delayed diagnosis and treatment [52].

Interventions that are aimed toward the risk factors and the maintenance of a healthy lifestyle that improves the comorbidities such as hypertension, diabetes, and hyperlipidemia contribute to a decrease in the risk of SCD [53]. For instance, the adoption of screening for pre‐diabetes and diabetes using Hemoglobin A1c levels at barbershops uncovered disease in people who were willing to be screened [54]. It's necessary to adopt similar interventions that encompass areas of primary, secondary, and tertiary care of DM, as this will improve treatment course, prognosis, medication compliance, and contribute to a reduction of the mortality rates from SCD.

4.1. Limitations

Our study has several limitations, primarily derived from the retrospective nature of the CDC WONDER database. The primary limitation of our research is that, although the CDC WONDER database provides comprehensive mortality data, it lacks crucial information regarding disease prevalence and incidence. While we analyzed population‐level mortality trends for co‐documented SCD and DM, we were unable to determine the true prevalence of diabetes within the population or differentiate between Type 1 and Type 2 diabetes, which may influence risk profiles and outcomes. Furthermore, because AAMRs are calculated against the total U.S. population denominator rather than the diabetic population specifically, rising rates may partly reflect increasing diabetes prevalence over the study period rather than a true increase in per‐diabetic SCD risk; this distinction cannot be resolved without a diabetes‐specific population denominator, which CDC WONDER does not provide.

Additionally, SCD and DM may have been underreported or misclassified on death certificates, particularly in earlier years, potentially leading to underestimation of mortality rates. We relied solely on ICD‐10 codes assigned by the World Health Organization, which may omit certain diagnoses and contain inaccuracies, thereby failing to capture the complete clinical context or distinguish between arrhythmic and non‐arrhythmic causes of sudden death.

Relatedly, the exclusive use of I46.1 captures only deaths where SCD was explicitly certified on the death certificate as a contributing cause alongside DM. This narrow definition was adopted deliberately rather than by necessity. I46.0 denotes cardiac arrest with successful resuscitation and is conceptually inconsistent with a fatal outcome, while I46.9 denotes cardiac arrest of unspecified mechanism and encompasses terminal arrest arising from non‐cardiac processes including respiratory failure, exsanguination, sepsis, and intoxication. Combining these codes would substitute a heterogeneous composite outcome carrying no consistent etiologic meaning for a single certified clinical entity, and would introduce additional temporal and geographic confounding, since reliance on unspecified codes varies substantially across certifying jurisdictions and has shifted over the study period. We therefore prioritized outcome homogeneity over case yield.

Related to this, the extreme variation in state‐level AAMRs—ranging from 0.23 in Nevada to 9.07 in Mississippi—is unlikely to reflect true differences in SCD burden alone. Interstate heterogeneity in death certificate completion practices, including variation in how frequently certifying physicians apply ICD‐10 code I46.1 specifically, is a plausible and important contributor to these differences. States where I46.1 is more consistently applied will yield higher observed AAMRs under this study's methodology regardless of underlying disease prevalence. This limitation is inherent to all death certificate‐based analyses using narrow ICD codes and cannot be corrected through study design adjustments alone. State‐level findings should therefore be interpreted as indicative of regional patterns in certified SCD documentation rather than as confirmed rankings of true disease burden, and individual state comparisons should not be used as the basis for targeted resource allocation without corroborating evidence from clinical or registry data.

Furthermore, the database lacks detailed patient‐level information, including glycemic control (e.g., HbA1c levels), duration of diabetes, medication use (such as insulin, antihyperglycemics, or cardioprotective therapies), comorbidities, laboratory values, and lifestyle factors—all of which are important determinants of cardiovascular risk and mortality. The absence of these variables limits our ability to adjust for confounding factors and explore mechanistic pathways underlying the observed trends.

Finally, data on socioeconomic status, healthcare access, and insurance coverage were not available, which may play a significant role in the demographic and geographic disparities observed. Additionally, the classification of race and ethnicity in CDC WONDER was modified in 2018 with the introduction of multiracial categories, which may have affected the consistency and comparability of race‐specific mortality trends over time and introduced potential misclassification bias.

5. Conclusion

This study demonstrates a significant rise in age‐adjusted population‐level mortality rates from co‐documented SCD and DM in the United States from 1999 to 2020. High‐risk groups include men, Black populations, rural residents, and individuals in the Southern U.S. and Midwest U.S. The sharp rise in mortality observed in 2020 further underscores the impact of the COVID‐19 pandemic on vulnerable populations. Targeted public health interventions focusing on early detection, risk factor modification, and equitable access to care are essential to reduce the population‐level burden of sudden cardiac death among individuals with diabetes mellitus.

Author Contributions

Masab Ali: Conceptualization, Methodology, Validation, Formal analysis, Supervision, Visualization, Writing – original draft, Writing – review and editing. Muhammad Abdullah: Resources, Writing – original draft. Taha Mehmood: Software, Data curation, Resources. Muhammad Hassan and Muhammad Umar Shahid: Software, Data curation, Resources, Validation, Visualization, Writing – review and editing. Muhammad Husnain Ahmad: Validation, Visualization. Sunnia Khan: Writing – original draft, Resources. Mujtaba Tariq: Writing – original draft, Resources. Amina Jamil: Writing – original draft, Resources.

Funding

The authors have nothing to report.

Ethics Statement

No ethical approval was required for this study design, as all data were obtained from publicly available sources.

Consent

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1: Mortality Stratified by Sex and Race Among Adults With Sudden Cardiac Death and Diabetes Mellitus, United States, 1999 to 2020.

Table S2: Annual Number of Deaths by Place of Death in the United States, 1999–2020.

Table S3: Annual Percent Change (APC) of Age‐Adjusted Mortality Rates in the United States, 1999 to 2020.

Table S4: Overall and Sex‐Stratified Age‐Adjusted Mortality Rates in Adults with Sudden Cardiac Death and Diabetes mellitus in the United States, 1999–2020.

Table S5: Age‐Stratified Deaths and Age‐Adjusted Mortality Rates in Adults with Sudden Cardiac Death and Diabetes mellitus in the United States, 1999–2020.

Table S6: Race/Ethnicity‐Stratified Age‐Adjusted Mortality Rates in Adults with Sudden Cardiac Death and Diabetes mellitus in the United States, 1999–2020.

Table S7: State‐Level Age‐Adjusted Mortality Rates in Adults with Sudden Cardiac Death and Diabetes mellitus in the United States, 1999–2020.

Table S8: Census Region‐Stratified Age‐Adjusted Mortality Rates in Adults with Sudden Cardiac Death and Diabetes mellitus in the United States, 1999–2020.

Table S9: Metropolitan and Non‐Metropolitan Age‐Adjusted Mortality Rates in Adults with Sudden Cardiac Death and Diabetes mellitus in the United States, 1999–2020.

JOA3-42-e70467-s001.docx^{(39.5KB, docx)}

Acknowledgments

The authors have nothing to report.

Data Availability Statement

The data supporting the findings of this study are openly available in CDC Wonder at https://wonder.cdc.gov/.

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