The Usefulness of Anthropometric Indices to Identify the Risk of Metabolic Syndrome

Abstract

Despite several papers having been published on the association between adiposity and the risk of metabolic syndrome (MetS), it is still difficult to determine unambiguously which of the indices of nutritional status is the best to identify MetS. The aim of this study was to analyze the ability of six anthropometric indices to identify MetS in the Polish population. The highest odds ratios for the occurrence of MetS, according to International Diabetes Federation (IDF), were noted for the following indices: waist-to-height ratio (WHtR, OR = 24.87) and Clínica Universidad de Navarra-body adiposity estimator (CUN-BAE, OR = 17.47) in men and WHtR (OR = 25.61) and body roundness index (BRI, OR = 16.44) in women. The highest odds ratios for the modified definition of MetS (without waist circumference) were found for the following indices: WHtR (OR = 7.32), BRI (OR = 6.57), and CUN-BAE (OR = 6.12) in women and CUN-BAE (OR = 5.83), WHtR (OR = 5.70), and body mass index (BMI, OR = 5.65) in men (p < 0.001 for all). According to the Receiver Operating Characteristic (ROC) analyses conducted for the identification of MetS, defined in accordance with IDF, the largest areas under the curve (AUCs) in men were observed for WHtR and CUN-BAE indices, whereas in women, they were observed for WHtR and BRI. In the analysis carried out for the identification of MetS (according to modified definition, without waist circumference), the AUCs were larger for WHtR and BRI in women, while in men, they were larger for CUN-BAE, BMI, and WHtR. BMI was also characterized by a relatively strong discriminatory power in identifying individuals with MetS. An optimal cut-off point for MetS, in accordance with the conventional definition, for both sexes was the value of BMI = 27.2 kg/m2. The weakest predictor of the syndrome was the ABSI (a body shape index) indicator. The most useful anthropometric indicator for the identification of MetS, both in men and in women in the Polish population, was WHtR. The optimal cut-off points for WHtR equaled 0.56 in men and 0.54 in women.

Effectiveness of body roundness index in predicting metabolic syndrome: A systematic review and meta‐analysis

“…However, BRI is limited in predicting percentage of fat mass in elite athletes when compared with other commonly and readily available field methods such as bio‐impedance analysis or skinfold prediction models 63 . Several recent studies have shown that BRI could be used as an adipose indicator for determining the presence of eccentric left ventricular hypertrophy, 64 hyperuricaemia, 41,65 arterial stiffness, 66–69 CVD, 70,71 diabetes, 41,72–75 dyslipidaemia, 41,76–78 hypertension 41,79,80 and MetS 41–55 …”

“…BRI is a predictor of body fat percentage and visceral adiposity tissue, and its values range from 1 to 16 35 . Although studies have compared the prediction of MetS by BRI with traditional and novel anthropometric indices, 41–55 there is currently no meta‐analysis indicating whether BRI is a better predictor of MetS than BMI, WC, WHR, WHtR, ABSI or BAI. Therefore, this meta‐analysis aims to investigate whether BRI is superior to BMI WC, WHR, WHtR, ABSI or BAI in predicting MetS.…”

The Relation of CUN-BAE Index with Body Mass Index and Waist Circumference in Adults Aged 50 to 85 Years: The MCC-Spain Study

“…That BMI and direct measurements of BF% are not strongly correlated has been known for over two decades [25,26]. In the general population, CUN-BAE has shown stronger correlations with direct measures of BF% than other anthropometric measures such as BMI, WC, body adiposity index (BAI), or body shape index (ABSI) [12,17,[19][20][21]. CUN-BAE-based on BMI, sex, and age-has been shown to be an independent measure of BMI [16].…”

“…CUN-BAE shows a strong correlation with BF% measured by direct techniques in all adults, especially in women, but studies in older adults are limited [15,20,21]. Also, the relation and concordance between the CUN-BAE and traditional anthropometrics are not clear, especially the relation with BMI as a component within the equation.…”

Anthropometric indices and cut-off points in the diagnosis of metabolic disorders

“…The early identification of metabolic disorders allows for an early intervention and the prevention of serious consequences. Overweight and obesity indices, calculated based on anthropometric measurements, have found a wide application in the identification of metabolic disorders [13][14][15][16][17][18]. The most significant advantages of anthropometric indices include the following: non-invasiveness, low cost, standardized techniques and simplicity of measurements, and the possibility to apply them on a large scale.…”