Evaluating the discriminatory capacity of traditional and novel anthropometric indices in cardiovascular disease risk factors, considering sex differences.

Abstract

Objective: Cardiovascular disease (CVD) rates are rising rapidly worldwide, making it crucial to implement simple and effective screening measures to identify individuals at increased risk for CVD risk factors. This study aims to examine the relationship between innovative anthropometric indices and the occurrence of cardiovascular risk factors among the population of Mashhad, located in northeastern Iran, over a ten-year follow-up period.

Methods: In this cohort study, a total of 9704 individuals aged 35-65 years were recruited at baseline, with 7560 individuals completing the study. Anthropometric indices were measured and calculated using standardized methods. After a 10-year follow-up, the incidence of hypertension (HTN), diabetes mellitus (DM), dyslipidemia, obesity, and metabolic syndrome (MetS) and their association with each anthropometric index were determined using Cox regression analysis. Receiver operating characteristic (ROC) analysis was employed to assess the predictive capacity of each index for the CVD risk factors.

Results: We found that WHtR exhibited the strongest association with various CVD risk factors. However, the predictive capacity of BMI was higher than other indices in DM and MetS (AUCs: 0.69 and 0.78, respectively). Moreover, BMI, WHtR, and BRI showed equal discriminatory power to predict HTN (AUCs: 0.61). Our analysis indicated that Iranian individuals with a BMI of more than 24.71, 26, and 25.2 kg/m2 are at a 54%, 88%, and 121% increased risk for the development of HTN, DM, and MetS over 10 years; respectively.

Conclusion: In this study, BMI was identified as the most powerful predictor of CVD risk factors among the anthropometric indices examined. These findings support previous research indicating that BMI is a valuable screening tool for identifying individuals at higher risk of developing CVDs and associated conditions.