Cardiovascular diseases (CVD) is one of the major global public health issues. In 2020, it was estimated that approximately 19 million people worldwide died from CVD, an 18.7% increase from 2010 (1). Age is closely associated with CVD. A study conducted in 2021 identified three critical age milestones for cardiovascular health: 25–45 years, 45–65 years, and over 65 years. It was noted that individuals over 65 are particularly vulnerable to cardiovascular risks, which subsequently increases healthcare demand (2). As populations age, improving cardiovascular health in individuals aged 65 and over has become a key research focus in public health. Numerous studies have identified this age group as high-risk for myocardial infarction, stroke, and heart failure (3, 4). After experiencing adverse cardiovascular events, patients may suffer a severe decline in their quality of life, affecting daily living, social activities, and mental health. Thus, effectively assessing and predicting the risk of cardiovascular events in the elderly is crucial for formulating preventive and treatment strategies.

Research has shown that central obesity is an independent risk factor for CVD (5). While traditional body mass index (BMI) is commonly used to assess obesity, it fails to accurately reflect fat distribution (6), whereas the Body Roundness Index (BRI), which incorporates height and waist circumference, provides a more precise evaluation of abdominal fat. It is calculated using the following formula: BRI = 364.2 − 365.5 × √(1 − [Waist circumference (cm)/2π]2/[0.5 × Height (cm) ]) (7). Compared to BMI and waist circumference alone, BRI has shown a stronger correlation with cardiovascular risk (7–9). BRI allows for a more effective assessment of the risks associated with body fat distribution in older adults, which plays a key role in cardiovascular health (10). In parallel, the Atherogenic Index of Plasma (AIP), which is derived from the ratio of triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C), has gained recognition as an important marker of lipid metabolism. AIP is calculated as: AIP = lg[TG (mmol/L)/HDL-C (mmol/L)] (11). where TG is the triglyceride level (mg/dl) and HDLC is the high-density lipoprotein cholesterol level (mg/dl). Triglycerides are a type of fat found in the blood, and their levels are closely associated with the presence of small, dense, atherogenic particles (12). These triglyceride-rich lipoproteins play a significant role in the development of atherosclerosis. This index reflects the partial esterification rate of HDL-C and the balance between protective and atherogenic lipoproteins. A growing body of evidence supports its association with cardiovascular disease, showing that AIP provides superior predictive value for CVD outcomes compared to traditional lipid parameters (13–15). Although BRI and AIP are independently associated with cardiovascular risk, the potential mediating role of AIP between BRI and cardiovascular outcomes in the elderly has not been fully explored.

The novelty of this study lies in its first comprehensive analysis of the impact of the BRI on CVD risk in elderly individuals using large-scale data from the NHANES database and further uncovers the mediating role of the AIP in this relationship. The study hypothesize that AIP, by reflecting lipid metabolism abnormalities, amplifies the association between BRI and CVD, thereby elucidating the underlying mechanisms linking central obesity to cardiovascular health (Figure 1). This study provides new insights into early risk assessment and personalized management strategies for CVD in older adults, addressing gaps in understanding the synergistic effects of BRI and AIP.

CVD is closely related to the quality of life of patients, which not only damages the physical function and sleep quality of patients, but also aggravates the feeling of loneliness of patients, and brings fatigue and lack of sleep to the family members (19–21). With advances in diagnosis and treatment technology, the prognosis of cardiovascular disease has been sufficiently improved, but according to one study, the average annual costs of cardiovascular disease in the U.S. in 2017–2018 were estimated at $378 billion, and predicted that the pressure of cardiovascular disease on the social health care system will continue to increase in 2025–2050. This is mainly driven by the ageing of the global population (22–25). At the same time, studies have pointed out that elderly people over 65 years old are generally faced with cardiovascular risk and are at high risk of CVD (2). Therefore, it is particularly important to formulate scientific and reasonable prevention and treatment strategies for this kind of elderly population to improve people's happiness index and reduce social medical burden.

Obesity is a well-established independent risk factor for CVD and has traditionally been assessed using body mass index (BMI). However, recent research in 2024 highlights the limitations of BMI, as it does not accurately reflect visceral fat thickness or differentiate between muscle and fat mass. Abdominal fat, particularly visceral fat surrounding key organs such as the liver, has been identified as a stronger predictor of CVD than BMI (26). The BRI, which incorporates both height and waist circumference, provides a more precise assessment of abdominal fat and has shown a stronger correlation with CVD incidence. Researchs have also shown that BRI exhibits superior discriminatory power in assessing metabolic disease risk, particularly when accounting for gender differences, compared to traditional measures such as BMI and waist circumference (7–9, 27). Additionally, the relationship between obesity and CVD is partially mediated by the triglyceride-glucose (TyG) index, indicating that metabolic factors play a role in obesity-related CVD risk (28). Lipid metabolism is a crucial component of cardiovascular risk, and the AIP, a composite lipid marker, offers a more comprehensive evaluation of lipid status, AIP has shown superior predictive ability for CVD compared to individual lipid parameters and is also associated with BRI, suggesting a potential interrelationship between these two indices in the context of cardiovascular health (13–15, 29). Both BRI and AIP are independent markers of metabolic disturbances, with higher levels of BRI reflecting increased central obesity and a greater risk of CVD. Similarly, elevated AIP values, which represent an imbalance in lipid metabolism, have been linked to an increased risk of atherosclerosis and cardiovascular events. However, we recognize that HDL-C is a highly heterogeneous molecule, and its concentration may not fully reflect the patient's lipid profile, especially if influenced by oxidative stress and inflammation, which can modify HDL-C and its functionality (30, 31). Despite these complexities, previous studies have established AIP, calculated as the ratio of TG to HDL-C, as an important marker for cardiovascular risk (32, 33). Given that both BRI and AIP are implicated in the pathophysiology of cardiovascular diseases, it appears that AIP may serve as an intermediary, bridging the association between BRI and CVD risk.

Using data from the NHANES database, this study provides robust evidence that the AIP plays a significant biological role in the pathway linking the BRI to CVD, as supported by epidemiological analysis. Notably, both BRI and AIP consistently demonstrated strong associations with CVD across various model adjustments. Mediation analysis, controlling for demographic variables, revealed a significant direct effect of BRI on the incidence of CVD, while AIP exhibited a notable indirect effect, further reinforcing the relationship between BRI and CVD. These findings underscore the potential of incorporating BRI and AIP into clinical practice for more precise cardiovascular risk stratification, particularly in populations at higher risk of metabolic and cardiovascular disorders. Early identification and intervention based on these indices may improve preventative strategies and optimize patient outcomes. Future research should focus on longitudinal studies to validate the causal relationships observed in this cross-sectional analysis. Additionally, exploring the impact of lifestyle interventions, such as targeted dietary and physical activity programs, on modulating BRI and AIP could provide actionable insights for reducing cardiovascular risk. Integrating these indices into personalized risk prediction models may further enhance their clinical utility and contribute to the development of precision medicine in cardiovascular care.

In this NHANES-based study involving 3,584 participants, we found that the Body Roundness Index (BRI) is significantly associated with the occurrence of cardiovascular disease (CVD), and this relationship is partially mediated by the Atherogenic Index of Plasma (AIP). Our findings suggest that a reduction in BRI, particularly in older adults, may contribute to a lower risk of CVD. Mediation analysis further supported that AIP plays a significant role in linking BRI to CVD occurrence. These results underscore the importance of managing lifestyle factors, such as body fat distribution, to mitigate the risk of cardiovascular diseases in older adults.