The Role of Different Indexes of Adiposity and Body Composition for the Identification of Metabolic Syndrome in Women with Obesity

Abstract

The aim of this study was to compare the accuracy of different indexes of adiposity and/or body composition in identifying the metabolic syndrome (MetS) in a group of 1528 Caucasian women with obesity: (age ± standard deviation (SD): 50.8 ± 14 years (range 18–83); body mass index (BMI) 43.3 ± 5.9 kg/m2 (30.7–72.9 kg/m2)). The following indexes were assessed in each subject: BMI, fat-free mass index (FFMI), fat mass index (FMI), tri-ponderal mass index (TMI), waist-to-height ratio (WtHR), and the body mass fat index (BMFI). Thereafter, a threshold value adjusted for age, which could identify MetS, was calculated for each index. A significant correlation was found among all indexes (p < 0.0001 for all). However, when the area under the curve (AUC) was compared, WtHR performed significantly better in the whole group and in the different age groups, apart from a lack of statistical difference between WtHR and BMFI in the 45–55 years age group. In conclusion, WtHR seems to be a fair index useful for identifying MetS in women with obesity. The use of thresholds appropriate for age can help further improve its accuracy, thus reinforcing the clinical evaluation for MetS screening.

Evaluation of Adiposity Phenotypes: Lipid Accumulation Product Index, Visceral Adipose Index and Body Roundness Index as Predictor Markers for Metabolic Syndrome Development in Type 2 Diabetes Mellitus

“…Obesity indexes were estimated in all T2DM patients, and data showed that BMI, WC, VAI, BF%, BRI, and LAP were higher in MetS+ patients compared with MetS-patients. These results were consistent with the result of Radetti et al 35 , who reported that MetS+ patients have the highest average of both WC and BMI compared with Met-patients. After that, Obesity indexes were evaluated in MetS+ patients and compared according to the number of metabolic syndrome components (MetS-3, MetS-4, and MetS-5), the average of BF%, VAI, and LAP increased with the increasing number of components, while BMI, WC, and BRI did not show a statistically significant difference.…”

Evaluation of the Relationships between Simple Anthropometric Measures and Bioelectrical Impedance Assessment Variables with Multivariate Linear Regression Models to Estimate Body Composition and Fat Distribution in Adults: Preliminary Results

“…Several authors have demonstrated the interest in estimating the body composition and fat distribution in adults using anthropometric measures [ 46 , 47 , 48 , 49 ], however few studies explored the relation between TBW and obesity. In the current study, TBW (a) correlated with the following anthropometric measures NC, C-index, MAC, WC, HC, BMI, BM and WHR ( Table 2 and Figure 3 ) and (b) with Multiple linear regression analysis, presented positive coefficients to NC, ABSI, WHR and BM, and negative coefficient to C-index ( Table 3 ).…”

High Tg/HDL-Cholesterol Ratio Highlights a Higher Risk of Metabolic Syndrome in Children and Adolescents with Severe Obesity

“…The objective is to find the simplest and least expensive tool that can identify the probability of having MetS in obese subjects, avoiding unnecessary investigation. In this context, we have previously compared indexes requiring or not instrumental support in a large group of children and adolescents, with different degrees of obesity [ 19 ]. We demonstrated that the indexes that considered body composition, as assessed by Bioelectrical Impedance Analysis (BIA), did not perform better than BMI for detecting MetS.…”

“…We demonstrated that the indexes that considered body composition, as assessed by Bioelectrical Impedance Analysis (BIA), did not perform better than BMI for detecting MetS. More recently, we have demonstrated that the evaluation of body composition throughout BIA did not add any additional value to simple anthropometric measures, such as BMI or WtHR, in identifying the risk of MetS in a large number of obese women [ 19 ].…”