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Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
Published on: September 27, 2024
Anthropometric Cutoffs for Increased Cardiometabolic Risk Among Lebanese Adults: A Cross-Sectional Study
Lara Nasreddine1, Nivine Bachir1, Samer Kharroubi1
1Department of Nutrition and Food Sciences, Faculty of Agricultural and Food Sciences, American University of Beirut, Beirut, Lebanon.
Abstract:
Obesity is associated with increased risk for metabolic syndrome (MetS). Anthropometric cutoffs derived for Caucasians may not be applicable to identify obesity in Middle Eastern populations. This study aims to (1) determine optimal cutoff values of body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) for the prediction of MetS among Lebanese adults and (2) to evaluate the ability of the derived cutoffs in predicting MetS, in comparison with published cutoffs. A cross-sectional study involving adults aged ≥20 years (n = 305) with no history of chronic diseases was conducted. Data collection included sociodemographic characteristics, anthropometric measurements, and fasting blood samples. The International Diabetes Federation criteria were used to identify MetS. Receiver operating characteristic analyses were performed to determine optimal cutoff values. The ability of the derived cutoffs in predicting MetS was examined using multiple logistic regression analyses. The derived cutoff values for men and women were 26.35 and 25.74 kg/m2 for BMI, 94 and 83 cm for WC, and 0.54 and 0.53 for WHtR, respectively. The use of the derived cutoffs improved the prediction of MetS compared to reference published cutoffs. In men, abdominal adiposity indicators performed better than BMI in predicting MetS, while in women, BMI, WC, and WHtR were all strong predictors. The study identified, for three anthropometric indices, the optimal cutoff values that identify MetS among Lebanese adults, hence responding to the need for ethnic-and population-specific cutoffs. Of interest, the study results documented gender differences in the association between anthropometric indices and MetS.
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