Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Aug 11;24(1):328.
doi: 10.1186/s12933-025-02885-4.

Improving cardiovascular risk stratification: the role of abdominal obesity in predicting MACEs

Carlo De Matteis #  1 , Stefano Petruzzelli #  1 , Giusi Graziano  2 , Fabio Novielli  1 , Ersilia Di Buduo  1 , Salvatore Cantatore  1 , Elsa Berardi  1 , Gianfranco Antonica  1 , Maria Arconzo  1 , Marica Cariello  1   3 , Marilina Florio  1 , Lucilla Crudele  4   5   6 , Antonio Moschetta  7   8   9
Affiliations

Improving cardiovascular risk stratification: the role of abdominal obesity in predicting MACEs

Carlo De Matteis et al. Cardiovasc Diabetol. .

Abstract

Background: Accurate cardiovascular risk (CVR) stratification remains challenging, particularly in identifying individuals with residual risk despite current screening tools. Abdominal obesity reflects visceral adipose tissue, which is metabolically active and strongly linked to pro-inflammatory and atherogenic states. This study aimed to evaluate the predictive utility of baseline cardiometabolic risk factors, with a particular focus on abdominal obesity as quantified by waist circumference (WC), alongside established 10-year CVR scores, for incident Major Adverse Cardiovascular Events (MACEs).

Methods: We prospectively followed 736 outpatients (347 males, 389 females) from an Italian Internal Medicine Unit, initially free of MACEs. Baseline data included anthropometrics, biochemical markers, and calculated Framingham Risk Score (FRS) and SCORE2/SCORE2-OP. Abdominal obesity was defined according to the International Diabetes Federation criteria for Metabolic Syndrome (MetS) as a WC ≥ 94 cm in males and ≥ 80 cm in females. Incident MACEs were recorded during follow-up. Statistical analyses included t-tests, Chi-Square, ANOVA, and logistic regression.

Results: Over a median follow-up of 84.9 months, 132 participants (17.9%) developed MACEs. Baseline abdominal obesity, present in 78.1% of the cohort, was significantly associated with incident MACEs (OR = 1.784, 95% CI = 1.04-3.118, p = 0.038), whereas BMI-defined obesity showed no such association (p = 0.394). Low HDL-cholesterol also emerged as a key predictor (OR = 1.672, 95% CI = 1.115-2.482, p = 0.012). In multivariate logistic regression, adjusted for age and other MetS components, abdominal obesity (OR = 2.2, 95% CI = 1.6-4.2, p = 0.001) and low HDL-c (OR = 1.9, 95% CI = 1.4-3.5, p = 0.001) remained robustly associated with MACEs. Notably, individuals within the SCORE2/SCORE2-OP 'Moderate-Risk' category, despite not being the highest risk overall, exhibited the highest baseline LDL-c levels and accounted for the largest proportion of MACEs (36.4%). Even among participants without baseline abdominal obesity, those who developed MACEs had significantly higher WC (p < 0.0001) and lower HDL-c (p = 0.0078) at baseline.

Conclusion: Abdominal obesity and low HDL-c are potent, independent predictors of cardiovascular events, outperforming traditional markers like BMI. Together with the need of reaching LDL-c serum target levels, these biomarkers are crucial for unmasking the residual risk missed by current stratification models.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent to participate: This study was approved by the Ethics Committee (Interdisciplinary Department of Medicine; n. 311, MSC/PBMC/2015, approved on 12 January 2015) of the Azienda Ospedaliero-Universitaria Policlinico di Bari (Bari, Italy) in accordance with the requirements of the Declaration of Helsinki. In accordance with the approved Ethics Committee, only patients who were already 18 years old or older were included. Informed consent was obtained from all subjects involved in the study. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Cardiometabolic biomarkers according to SCORE2/SCORE2-OP risk classes. Box plots show median (second quartile), first and third quartile. Tukey whiskers reach 1.5 times the interquartile distance or the highest or lowest point, whichever is shorter. Any data beyond the whiskers are shown as black dots. Comparisons were performed using ANOVA method. (*p < 0.05; ** p < 0.01). a Box plots of waist circumference according to SCORE2/SCORE2-OP risk classes; b Box plots of total cholesterol according to SCORE2/SCORE2-OP risk classes; c Box plots of HDL-c according to SCORE2/SCORE2-OP risk classesd Box plots of LDL-c according to SCORE2/SCORE2-OP risk classes. a indicates significance vs. Low-risk group; b indicates significance vs. Moderate-risk group; c indicates significance vs. High-risk group; d indicates significance vs. Very-high risk group. Abbreviations: Waist Circumference, WC; Total cholesterol, TC; High-density lipoprotein cholesterol, HDL-c; Low-density lipoprotein cholesterol, LDL-c
Fig. 2
Fig. 2
MACEs distribution during follow-up time in our study cohort. The median time to MACEs development during the follow-up period, estimated using the Kaplan–Meier method, was 84.9 months.
Fig. 3
Fig. 3
Association of CVE and cardiometabolic conditions. Odds Ratios for patients with specific cardiometabolic risk factors are represented. Contingency tables, OR value and 95% C.I. are reported. Fisher’s Exact test was calculated and p < 0.05 was considered significant. Abbreviations: Odds Ratio, OR; Confidence Interval, CI; High Density Lipoprotein-cholesterol, HDL-c; Body Mass Index, BMI
Fig. 4
Fig. 4
Comparison of waist circumference and lipid profile in individuals without abdominal obesity, based on CVE development. Box plots show median (second quartile), first and third quartile. Tukey whiskers reach 1.5 times the interquartile distance or the highest or lowest point, whichever is shorter. Any data beyond the whiskers are shown as black dots. Comparisons were performed using Students’ t-test. (** p < 0.01, *** p < 0.001). a Box plots of waist circumference according to MACE development; b Box plots of total cholesterol according to MACE development; c Box plots of HDL-c according to MACE development; d Box plots of LDL-c according to MACE development. Abbreviations: Major adverse cardiovascular events, MACE; Waist circumference, WC; Total cholesterol, TC; High-density lipoprotein cholesterol, HDL-c; Low-density lipoprotein cholesterol, LDL-c
See this image and copyright information in PMC

References

    1. Miao B, Hernandez AV, Alberts MJ, Mangiafico N, Roman YM, Coleman CI. Incidence and predictors of major adverse cardiovascular events in patients with established atherosclerotic disease or multiple risk factors. J Am Heart Assoc. 2020;9(2):e014402. - PMC - PubMed
    1. Higashi Y, Sasaki S, Nakagawa K, Matsuura H, Oshima T, Chayama K. Endothelial function and oxidative stress in renovascular hypertension. N Engl J Med. 2002;346(25):1954–62. - PubMed
    1. Chen W, Li Z, Zhao Y, Chen Y, Huang R. Global and national burden of atherosclerosis from 1990 to 2019: trend analysis based on the Global Burden of Disease Study 2019. Chin Med J (Engl). 2023;136(20):2442–50. - PMC - PubMed
    1. Herrington W, Lacey B, Sherliker P, Armitage J, Lewington S. Epidemiology of atherosclerosis and the potential to reduce the global burden of atherothrombotic disease. Circ Res. 2016;118(4):535–46. - PubMed
    1. Kong Q, Ma X, Li L, Wang C, Du X, Wan Y. Atherosclerosis Burden of Brain- and Heart-Supplying Arteries and the Relationship With Vascular Risk in Patients With Ischemic Stroke. J Am Heart Assoc. 2023;12(16):e029505. - PMC - PubMed

MeSH terms

LinkOut - more resources