The global prevalence of cardiovascular disease (CVD) continues to rise, driven by an aging population and changing lifestyle factors, making it the leading cause of death worldwide. This poses significant challenges for individuals and healthcare systems alike (1). Recent studies have highlighted the growing age and socioeconomic disparities in CVD incidence, with these disparities showing persistence over time (2). Abdominal aortic calcification (AAC), a common form of vascular calcification (VC), is a key independent risk factor for CVD (3).

VC, characterized by the accumulation of mineral deposits, particularly calcium phosphate complexes, within the blood vessels (4), contributes significantly to vascular stiffness, especially in the aorta. Increased aortic stiffness is an established independent risk factor for cardiovascular diseases (5). In older adults, the progression of aortic stiffness is also strongly linked to poorer socioeconomic status (6). Beyond serving as a reliable indicator of atherosclerotic disease, AAC has been associated with increased cardiovascular events and all-cause mortality in prior studies (7, 8). Calcified plaques in the aorta are associated with structural changes, including increased aortic diameter, which can lead to the rupture of aortic aneurysms (9, 10). Furthermore, the presence of extensive calcification complicates and heightens the risks of open surgical procedures (11). Although abdominal aortic aneurysm is less prevalent in women, their prognosis tends to be worse, likely due to less effective cardiovascular risk management in females (12, 13). Population-based studies have indicated a correlation between the severity of AAC and spinal X-ray findings (14).

Recent attention has focused on the relationship between metabolic status and AAC (15, 16). Individuals with aortic calcification tend to be older, have elevated cholesterol levels, and are more likely to have diabetes than those without calcification (17, 18). Obesity has been identified as a key factor that increases the likelihood of severe AAC (19). In obese individuals, altered lipid metabolism and systemic metabolic disruptions contribute to this increased risk, positioning lipid profiles as valuable biomarkers for AAC (20). Interestingly, men with lower income levels show higher rates of obesity, while wealthier women tend to have a higher prevalence of obesity as well. The reasons for racial disparities in lipid management remain poorly understood (21, 22), underscoring the importance of assessing body fat accumulation as a risk indicator for AAC, with consideration of factors such as gender, race, and socioeconomic status (23). In clinical settings, the diagnosis of lipid metabolism disorders typically requires a combination of anthropometric data and biochemical markers. The cardiometabolic index (CMI), which includes metrics such as the waist-to-height ratio (WHtR) and the triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C) ratio, has been associated with utility in identifying individuals with diabetes and obesity (24, 25). Numerous studies have reported associations between CMI and various conditions including fatty liver disease, hypertension, atherosclerosis, chronic kidney disease (CKD), and depression (26–28). CMI has been proposed as a potential tool for assessing cardiometabolic risk at the population level. When compared to individual risk factors, the CMI offers superior predictive value, providing a holistic assessment of an individual’s cardiac metabolic risk. This makes it an essential reference for early prediction, evaluation, and clinical decision-making in cardiovascular health.

Compared with indices like LAP and VAI, CMI combines the TG/HDL-C ratio and waist-to-height ratio (WHtR), capturing both dyslipidemia and central adiposity. These components are key drivers of metabolic syndrome and vascular damage, particularly relevant to AAC pathogenesis (27). Currently, there is a lack of literature exploring the association between the cardiometabolic index (CMI) and abdominal aortic calcification (AAC). A better understanding of this relationship may offer insights into the cardiometabolic characteristics associated with AAC. This study, based on cross-sectional data from the 2013 to 2014 NHANES cycle, aims to evaluate the statistical association between CMI and both the prevalence and severity of AAC, while exploring potential contributing factors behind this association.

This cross-sectional analysis of 2,675 participants identified a statistically significant association between higher CMI levels and greater severity of AAC. This association remained evident after adjustment for potential confounders and was observed regardless of whether CMI was modeled as a continuous or categorical variable. Subgroup analyses demonstrated variation in the strength of this association across different populations, particularly among females, non-Hispanic White individuals, with higher educational attainment, those with hypertension, and those without diabetes. These findings indicate a statistical relationship between CMI and AAC burden in this cross-sectional dataset.

Since its introduction in 2015, the Cardiometabolic Index (CMI) has emerged as a composite indicator of visceral adiposity and dyslipidemia (42). Several studies have reported that CMI is associated with cardiovascular conditions and may offer advantages over traditional anthropometric indices in specific settings (43). The selection of CMI in our study was driven by its alignment with the pathophysiology of abdominal aortic calcification (AAC), which is influenced by both atherogenic lipid patterns and visceral fat accumulation. CMI captures these dual mechanisms by combining TG/HDL-C ratio with WHtR, a validated proxy for central obesity, both implicated in vascular aging processes. Compared to indices like LAP and VAI, CMI has been reported to show robust associations with metabolic dysfunction in large-scale studies. Cai et al. (44) reported that CMI outperformed VAI (AUC = 0.819 vs. 0.807) in identifying metabolic dysfunction-associated fatty liver disease (44). In a recent prospective cohort, Sun et al. (45) also found CMI to be more strongly correlated with acute pancreatitis incidence than LAP, suggesting its broader relevance to metabolic dysregulation (45). In contrast to LAP and VAI, which require sex-specific or population-specific coefficients and complex transformations, CMI is more practical and generalizable. WHtR, the central component of CMI, has outperforms BMI and WC in predicting cardiometabolic risk (46). CMI’s height-adjusted design also reduces stature-related confounding, making it more practical for routine screening in large population-based studies or clinical settings. LAP does not incorporate protective lipids such as HDL-C and is sex-specific, limiting generalizability. VAI includes regression-derived constants that may lack external validity across diverse populations. Moreover, visceral adiposity, reflected by WHtR, is associated with vascular calcification and atherosclerosis, supporting the relevance of CMI in AAC research (47). In addition, greater vulnerability of atherosclerotic lesions within the aorta was described for those with central adiposity (48). In light of these points, we believe that CMI represents a robust, generalizable, and physiologically integrative index, making it particularly suitable for investigating its association with vascular aging phenotypes such as AAC. Nonetheless, it is important to emphasize that our findings are based on cross-sectional data, and as such, CMI should not be interpreted as a causal or predictive tool for AAC.

The restricted cubic spline analysis was used to characterize the non-linear association between CMI and severe AAC in this cross-sectional study. The restricted cubic spline analysis revealed that when CMI exceeds approximately 0.66, the odds of severe abdominal aortic calcification increase progressively. This threshold may correspond to a level of cardiometabolic burden where central adiposity and atherogenic dyslipidemia are more strongly associated with vascular calcification. Although causality cannot be established due to the cross-sectional design, this inflection point may help characterize a population subgroup with elevated AAC burden in relation to metabolic risk. Higher CMI values were associated with greater diabetes prevalence, a finding consistent with prior observational studies. Hyperlipidemia is commonly observed in individuals with type 2 diabetes and is frequently associated with cardiovascular and renal complications in epidemiologic research (49). Interestingly, our study identified a numerically stronger association between CMI and AAC severity in non-diabetic individuals compared with diabetic ones. Research suggests that individuals with diabetes are more likely to use lipid-lowering medications, which often result in lower LDL cholesterol levels (50). The use of lipid-lowering therapy has been associated with reduced AAC burden in previous studies, which may help explain the weaker association between CMI and AAC observed in diabetic individuals in our analysis. Furthermore, our results indicate that elevated CMI levels in individuals with hypertension were more prominently associated with AAC severity, consistent with prior observational findings. Individuals with high blood pressure often exhibit metabolic and cardiovascular dysfunctions (51), which are frequently linked with metabolic abnormalities and vascular calcification (52, 53). Hypertension may modify the observed association between CMI and AAC, as the relationship appeared more pronounced among hypertensive individuals in our study. Chronic kidney disease (CKD) also commonly coexists with both diabetes and hypertension (54, 55). Individuals with CKD frequently exhibit lipid metabolism abnormalities (56), and previous studies have reported that lipid accumulation in the kidneys is associated with renal dysfunction, particularly in patients with glomerular disease or glycogen storage disorders (57). The scavenger receptor CD36 has been implicated in lipid metabolism dysregulation and may play a role in CKD pathophysiology, as suggested by previous experimental studies. The observed negative correlation between HDL-C and AAC severity is consistent with prior evidence suggesting a potential inverse relationship between HDL-C levels and vascular calcification (58). The OR for TGs and severe AAC was 1.07 (95% CI: 1.02–1.12, P = 0.014), indicating a positive correlation. This finding is consistent with earlier studies linking lipid profiles to cardiovascular health. For example, the LAP, which incorporates waist circumference and fasting triglycerides, has been shown in previous studies to be associated with increased cardiovascular risk (59). Although the limited AUC values suggest weak statistical separation, these findings remain relevant for understanding population-level metabolic associations. Given the multifactorial nature of AAC, which involves genetic, inflammatory, and metabolic pathways, it is unlikely that any single metabolic marker would achieve high discriminative accuracy on its own.

In our stratified analysis, a statistically significant interaction was observed between sex and CMI in relation to severe AAC, with women showing a stronger association than men. This may reflect a combination of biological and social factors possibly related to postmenopausal hormonal changes, altered lipid metabolism, and disparities in socioeconomic access to care among women. In vascular diseases, gender, socioeconomic status (SES), and ethnicity are crucial social determinants of health (SDHs) that contribute to health disparities and inequalities (60). Estrogen decline after menopause could disrupt lipid metabolism by increasing LDL-C and decreasing HDL-C levels, thereby promoting atherosclerotic processes, including vascular calcification (61). Moreover, postmenopausal women often exhibit increased central adiposity and atherogenic lipid profiles, both of which are captured by the CMI and are known contributors to vascular calcification (62). During post menopause, central adiposity has been associated with inflammatory and an increased risk of cardiovascular disease (63). Moreover, Depression is more commonly reported among women than men (64). This disparity is particularly pronounced during the menopausal transition. Fluctuating estrogen levels can disrupt the regulation of serotonin and norepinephrine, which may contribute to depression development (65). In postmenopausal women, depression has been associated with nearly a 50% increase in cardiovascular-related mortality (66). Socioeconomic factors also shape cardiometabolic risk profiles in sex-specific ways. In many lower-income countries, women tend to exhibit higher rates of obesity than men (67). Socioeconomic status (SES) in both childhood and adulthood influences the risk of metabolic syndrome (MetS) among women, with adult SES playing a particularly important role after menopause. Women from disadvantaged backgrounds face reduced access to healthcare and higher risks of underdiagnosed or unreported health conditions (68).

Individuals with lower socioeconomic status (SES) often exhibit higher rates of obesity, particularly in less urbanized regions. Lower educational attainment has been consistently associated with poorer dietary habits, reduced physical activity, and limited health literacy, all of which contribute to increased cardiometabolic risk (69). In contrast, those with higher education and income are more likely to adopt healthier lifestyles, seek timely medical care, and participate in comprehensive health plans (70). For instance, well-educated households are more responsive to dietary recommendations and more proactive in managing early symptoms and health conditions (71). Occupational stress and burnout have been associated with elevated cardiovascular risk in prior research (72). At the systemic level, economic disparities also influence healthcare access and quality. Regions with higher per capita GRP typically have better-funded hospitals, more advanced medical infrastructure, and greater access to skilled personnel, which together enhance service capacity. Conversely, economically disadvantaged communities face disproportionate burdens of disease and reduced access to preventive and specialized care (73).

The study found that CMI levels varied significantly by ethnicity, with higher values observed among non-Hispanic White individuals, Mexican Americans, and other groups. These differences may reflect underlying variations in body composition; for instance, Black individuals typically have higher lean mass and lower amounts of visceral and subcutaneous fat compared with Whites, which could contribute to their relatively lower CMI levels (74). While differences in BMI and poverty levels between Black and White men are less pronounced than among women, Black men consistently report lower alcohol consumption compared to White men (75). Stimulant medications, despite their clinical indications, have been disproportionately prescribed in affluent, predominantly White communities, raising concerns about overuse, and higher rates of obesity, alcohol dependence, and metabolic disorders in these populations (76). Ethnic background and experiences of marginalization have been associated with persistent health disparities, as socioeconomically advantaged populations tend to experience better health outcomes compared to underserved communities (77). Since 2005–2006, obesity rates among non-Hispanic Black men have remained stable, whereas Mexican American men have experienced a more rapid increase compared to non-Hispanic White men (78).

This cross-sectional study provides preliminary evidence of a positive association between the cardiometabolic index (CMI) and the severity of abdominal aortic calcification (AAC) in a representative U.S. adult population. Although the AUC of 0.548 suggests modest association strength, higher CMI levels were statistically related to increased AAC severity. Given the cross-sectional design, no causal or temporal inferences can be made. These findings indicate that CMI may be associated with underlying cardiometabolic features that coexist with AAC burden in observational contexts.