» Articles » PMID: 38610696

Body Mass Index and Waist Circumference As Predictors of Above-Average Increased Cardiovascular Risk Assessed by the SCORE2 and SCORE2-OP Calculators and the Proposition of New Optimal Cut-Off Values: Cross-Sectional Single-Center Study

Overview
Journal J Clin Med
Specialty General Medicine
Date 2024 Apr 13
PMID 38610696
Authors
Affiliations
Soon will be listed here.
Abstract

Obesity has been perceived as one of the important cardiovascular risk factors, but SCORE2 calculators used in clinical practice do not include the most popular parameters assessed for body composition: body mass index (BMI) and waist circumference (WC). The objective of this research was to determine which of the aforementioned variables is a more reliable predictor of an above-average increased cardiovascular risk for gender and age (ICVR). Data from 2061 patients were analyzed; the 10-year risk of cardiovascular events was assessed by SCORE2 tables, and the correlations with BMI and WC were analyzed. BMI and WC independently predicted ICVR (OR 1.10-1.27). In males, BMI was a more accurate predictor (AUC = 0.816); however, in females, it was WC (AUC = 0.739). A novel threshold for BMI (27.6 kg/m) was suggested, which increases the risk of cardiovascular disease by 3.3-5.3 times depending on gender; the same holds true for WC (93 cm in women and 99 cm in men; 3.8-4.8-fold higher risk). Despite their heterogeneity, BMI and WC are effective cardiovascular risk predictors, especially BMI for males and WC for females; therefore, more research is needed to include them in future models for predicting unfavorable cardiometabolic events.

Citing Articles

Effects of Weight Loss on Endothelium and Vascular Homeostasis: Impact on Cardiovascular Risk.

Tiezzi M, Vieceli Dalla Sega F, Gentileschi P, Campanelli M, Benavoli D, Tremoli E Biomedicines. 2025; 13(2).

PMID: 40002792 PMC: 11853214. DOI: 10.3390/biomedicines13020381.


Assessing Cardiovascular Risk in Geriatric Patients Without Atherosclerotic Cardiovascular Disease.

Zuranski W, Nowak J, Danikiewicz A, Zubelewicz-Szkodzinska B, Hudzik B J Clin Med. 2024; 13(23).

PMID: 39685592 PMC: 11641976. DOI: 10.3390/jcm13237133.

References
1.
van Trier T, Snaterse M, Boekholdt S, Scholte Op Reimer W, Hageman S, Visseren F . Validation of Systematic Coronary Risk Evaluation 2 (SCORE2) and SCORE2-Older Persons in the EPIC-Norfolk prospective population cohort. Eur J Prev Cardiol. 2023; 31(2):182-189. PMC: 10809184. DOI: 10.1093/eurjpc/zwad318. View

2.
. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Eur Heart J. 2021; 42(25):2439-2454. PMC: 8248998. DOI: 10.1093/eurheartj/ehab309. View

3.
Venkatrao M, Nagarathna R, Patil S, Singh A, Rajesh S, Nagendra H . A composite of BMI and waist circumference may be a better obesity metric in Indians with high risk for type 2 diabetes: An analysis of NMB-2017, a nationwide cross-sectional study. Diabetes Res Clin Pract. 2020; 161:108037. DOI: 10.1016/j.diabres.2020.108037. View

4.
Yin J, Tian L . Joint confidence region estimation for area under ROC curve and Youden index. Stat Med. 2013; 33(6):985-1000. DOI: 10.1002/sim.5992. View

5.
Rodrigues de Oliveira B, Magalhaes E, Braganca M, Coelho C, Lima N, Bettiol H . Performance of Body Fat Percentage, Fat Mass Index and Body Mass Index for Detecting Cardiometabolic Outcomes in Brazilian Adults. Nutrients. 2023; 15(13). PMC: 10346298. DOI: 10.3390/nu15132974. View