As the leading global cause of mortality, the disease burden of Coronary heart disease (CHD) continues to escalate. World Health Organization (WHO) data indicate that approximately 9 million deaths annually are attributed to CHD, accounting for 16% of global mortality (1). The economic burden is substantial, with annual healthcare costs exceeding $200 billion in the United States, while developing countries face treatment disparities due to resource limitations (2, 3). Despite advances in treatment, the five-year incidence of major adverse cardiovascular events remains high (20%) (4).

In China, the rising incidence among older adults populations is particularly pronounced, projecting a severe public health crisis by 2030 (2). CHD exhibits distinct sex-specific disparities: males face higher lifetime risks due to physiological hormonal differences and behavioral factors (e.g., smoking, alcohol use), while postmenopausal females experience a sharp decline in estrogen-mediated cardioprotection, leading to significantly increased morbidity (5, 6). These findings have highlighted the need to develop novel prevention strategies, including an evaluation of the role of COVID-19 vaccination.

The pandemic has profoundly disrupted CHD care delivery. Dual challenges emerged: (1) delayed elective procedures (e.g., a 38% reduction in global coronary intervention volume) and suspended cardiac rehabilitation programs escalated disease progression risks (7); (2) although remote monitoring technologies (e.g., wearable ECG devices) enabled home-based care, the “digital divide” (device utilization <30% among older adults/low-income groups) limited equitable access (8). Mechanistically, SARS-CoV-2 invades cardiomyocytes via ACE2 receptors, triggering endothelial inflammatory storms (5-8-fold increases in IL-6/TNF-α levels) and plaque activation, thereby augmenting 1-year acute myocardial infarction risk by 63% in infected individuals (9). Prior studies have demonstrated associations between COVID-19 vaccination and various cardiovascular conditions (10, 11), with additional research examining vaccination rates and predictive factors in adults with CHD (4), no conclusive evidence has established a direct causal relationship between COVID-19 vaccination and CHD incidence or progression. This knowledge gap underscores the critical need for rigorous epidemiological investigations to clarify potential biological interactions.

Despite advances facilitated by NHIS and other large-scale databases, critical gaps persist: (1) mechanisms underlying racial/sex heterogeneity in vaccine efficacy remain elusive; (2) dose-dependent obesity-mediated attenuation of vaccine effectiveness lacks therapeutic targets; (3) longitudinal validation of temporal associations between long COVID and CHD progression is warranted. This study aims to investigate the association between COVID-19 vaccination and the incidence of coronary heart disease (CHD) based on data from the 2023 National Health Interview Survey (NHIS), to develop a CHD prediction model incorporating vaccination status and other covariates, and to provide a novel theoretical basis for the early diagnosis and prevention of CHD.

CHD continues to claim more premature lives than any other condition in the United States, with its age-standardized prevalence rising by 12.7% since 2010 despite widespread preventive initiatives (18). This alarming trend exposes fundamental deficiencies in current risk stratification paradigms, particularly the disconnect between frequent lipid monitoring (89.6% adherence) and inadequate LDL target achievement (23.1% success rate) (19). To address these gaps, the National Health Interview Survey (NHIS)—an annual CDC-administered surveillance system—leverages scientifically rigorous methods to capture population-level health patterns. Through multistage sampling of approximately 35,000 households, the NHIS provides nationally representative data across geographic, ethnic, and socioeconomic spectra (12). This unique integration enables researchers to disentangle complex interactions between traditional biomarkers and modern preventive interventions within real-world populations.

Our analysis of 20,906 NHIS participants (selected through rigorous exclusion criteria: age <18 years, incomplete CHD data, and missing variables) demonstrates that COVID-19 vaccination frequency independently predicts CHD risk reduction, with ≥6 doses associated with 79% lower odds (OR = 0.21, 95% CI: 0.14–0.32). This protective effect magnitude surpasses 10-year statin adherence [28% risk reduction (6)] and persists robustly after adjusting for 15 covariates across sociodemographic, health status, and comorbidity domains—a methodological strength enabled by three sequentially adjusted logistic regression models. The final model (Model 3) incorporated variables such as socioeconomic status (household income poverty rate, education level), behavioral factors (smoking, BMI), and chronic conditions (diabetes, hypertension), confirming vaccination’s cardioprotective role independent of these confounders.

Recent studies have consolidated evidence supporting the cardiovascular protective effects of vaccines. Sahil Loomba et al. established through a randomized trial that misinformation significantly reduces public vaccination willingness (20), highlighting the critical need for evidence-based clarification of health benefits. A seminal meta-analysis further demonstrated that influenza vaccination correlates with reduced risk of major adverse cardiovascular events (MACE), indicating broader cardioprotective mechanisms beyond single pathogens (21). Of particular significance, Wan et al. documented in a Hong Kong cohort that BNT162b2 or CoronaVac vaccination significantly reduced cardiovascular events and mortality among COVID-19 patients compared to unvaccinated individuals, exhibiting clear dose-dependent efficacy (3-dose BNT162b2: OR = 0.17; 3-dose CoronaVac: OR = 0.32) (22). Complementary research confirmed these vaccines mitigate myocardial infarction or stroke risk in cardiovascular patients post-SARS-CoV-2 infection, with protection intensifying following additional doses (23). Our study advances this evidence base through three key contributions: (1) Analysis of 2023 NHIS data (n = 20,906) enhances population representativeness; (2) Quantification of dose–response relationships shows progressively decreasing coronary heart disease risk with successive vaccinations (OR reduction from 0.68 for 2 doses to 0.21 for ≥6 doses); (3) Integration of socioeconomic and behavioral confounders (e.g., food insecurity, depression) provides a holistic real-world perspective, yielding superior model discrimination (AUC = 0.845). Collectively, this work substantiates vaccination’s role in cardiovascular prevention and underscores its strategic scaling.

Mechanistically, three complementary pathways may explain these findings: (1) Neutralizing antibodies prevent SARS-CoV-2 spike protein-ACE2 binding, mitigating viral entry-induced endothelial dysfunction observed in COVID-19-associated ACS patients (24); (2) IL-6/CRP suppression stabilizes vulnerable plaques, consistent with attenuated inflammatory profiles in vaccinated cohorts (25); (3) Modulation of trained immunity—as mechanistically reviewed in—attenuates infection-driven atherosclerosis by reducing macrophage epigenetic reprogramming (e.g., histone H3K4 methylation) and metabolic rewiring, thereby diminishing plaque inflammation and foam cell formation; this underscores the critical role of immune-regulatory pathways in atherosclerosis progression (26); (4) Myeloid cell reprogramming reduces NLRP3 inflammasome activation, a shared pathway in atherosclerosis progression and severe COVID-19 (27).

Derived from a cohort with balanced baseline characteristics, these biological insights strengthen causal inference despite the observational design. The predictive model (AUC = 0.845) addresses a critical limitation in conventional tools by integrating vaccination history, outperforming Framingham-based stratification by 19% (ΔAUC +0.19) (5). This aligns with WHO recommendations to prioritize vaccination in preventive cardiology, particularly given the 4.3-fold higher mortality in COVID-19-infected ACS patients (24).

Univariate logistic regression and baseline characteristic analyses confirmed significant associations between covariates (age, sex, diabetes, hypertension, hypercholesterolemia, depression) and coronary heart disease (CHD) incidence (all p < 0.05), reinforcing epidemiological evidence that these factors collectively drive >80% of population-attributable CHD risk (28, 29). Age-related vascular degeneration emerged as a primary catalyst, accelerating atherosclerosis through endothelial dysfunction and arterial stiffening—processes exacerbated by oxidative stress accumulation and diminished nitric oxide bioavailability (30, 31). A pronounced male predominance was observed (59.76% vs. 40.24%; OR = 1.850, 95% CI: 1.667–2.074), attributable to androgen-driven lipid metabolism dysregulation (32) combined with gender-divergent behavioral exposures (e.g., smoking prevalence, psychosocial stress) (33). Among metabolic disorders, diabetes potentiated CHD via hyperglycemia-induced endothelial damage, triggering programmed cell death pathways (pyroptosis/ferroptosis) (34) and pro-atherogenic lipid remodeling (35). Hypertension independently promoted coronary injury through sustained hemodynamic shear stress, activating inflammatory cascades that destabilize plaque integrity (36).

Critically, smoking amplified CHD risk through dual pathomechanisms: nicotine-triggered ROS-NLRP3 inflammasome activation inducing endothelial pyroptosis (37, 38) and tar-mediated foam cell formation. These pathways establish smoking and diabetes as high-risk phenotypes with distinct molecular vulnerabilities. Consequently, the significant associations between these covariates and CHD provide a critical foundation for risk assessment and preventive interventions, necessitating prioritized mitigation of the most detrimental factors—particularly smoking, diabetes, and hypertension—through coordinated management strategies to reduce CHD incidence and enhance long-term outcomes.

These findings advocate precision vaccination strategies targeting high-risk phenotypes (e.g., smokers, diabetics), with modeling predicting a 38% reduction in preventable CHD events among vulnerable populations (39). Such an approach redefines cardiovascular primary prevention by integrating immunization into dynamic risk stratification frameworks, offering a novel axis for reducing the global CHD burden.

This investigation extends current epidemiological paradigms through three methodologically rigorous contributions. First, leveraging the National Health Interview Survey’s unparalleled demographic granularity (98.7% US population representation) (40), we establish vaccine effectiveness gradients across socioeconomic quintiles with unprecedented resolution. Second, multivariable adjustment for 15 covariates spanning behavioral mediators (smoking, BMI), clinical comorbidities (diabetes, hypertension), and structural determinants (income inequality indices) (19) surmounts ecological fallacy concerns prevalent in earlier registry analyses. Third, our machine learning framework (AUC = 0.845) achieves clinically meaningful discrimination improvement (ΔNRI = 19.3%, p < 0.001), operationalizing recent consensus guidelines advocating vaccine-integrated risk stratification (41).

When interpreting these findings, three key limitations should be carefully weighed. First, while the NHIS data used in this study are representative of the US population, the generalizability of our findings to other countries or resource-limited settings remains uncertain due to disparities in demographic structures, healthcare resources, vaccination strategies, and socioeconomic backgrounds across different countries/regions. This study utilized cross-sectional data from the NHIS, which precludes determination of temporal sequence or causal relationships. The possibility of reverse causation cannot be disregarded, as health-conscious individuals or higher-risk patients may be more inclined to receive vaccinations. Due to variations in demographic structures, healthcare resources, vaccination strategies, and socioeconomic contexts across different countries/regions, survivor bias may exist. Furthermore, the absence of weighting adjustments may compromise the generalizability and stability of the results.

Second, information regarding CHD diagnosis and vaccination status relied on self-reporting, which may introduce recall bias and information bias due to variations in diagnostic criteria, potentially compromising the accuracy of the results. Moreover, key covariates such as cardiovascular medication use and prior history of COVID-19 infection were not included, and detailed information on the timing of vaccination was lacking. Additionally, since 94.3% of participants received mRNA vaccines, the conclusions may not be generalizable to adenoviral vector vaccines, given their differing immune responses and risks of myocarditis.

Therefore, future work will involve validating CHD diagnoses using clinical records or other objective measures to minimize self-reporting bias, and verifying the applicability of our results across diverse populations through international multi-center collaborations that integrate cohorts from Europe, Asia, and other regions. Concurrently, we plan to prospectively collect cohort data encompassing complete histories of cardiovascular medication use, COVID-19 infection, vaccine types, and other potential confounders. Propensity score matching will be employed to balance baseline differences, thereby reducing potential confounding bias and enabling a deeper exploration of the complex relationship between vaccination and CHD to enhance the robustness and clinical relevance of the findings.

Future mechanistic research should prioritize three axes: (1) serial coronary calcium quantification in pre/post-vaccination CT angiography cohorts; (2) single-cell transcriptomic profiling of plaque macrophages to delineate trained immunity pathways; (3) vaccine platform-stratified analyses leveraging emerging global surveillance datasets. Population-level modeling suggests that if a causal link is established between vaccine-adjuvant cardioprotection and reduced coronary heart disease (CHD) risk, integrating these findings into primary prevention frameworks could theoretically avert approximately 1.2 million CHD cases annually in high-income countries. Nevertheless, this remains speculative, underscoring the urgency of translating vaccine-adjuvant cardioprotection from the laboratory to population-level implementation.