RESUMEN
The use of bioelectrical impedance analysis (BIA) in clinical settings is common. However, the value of BIA-based parameters in diagnosing metabolic syndrome (MetS) in children is under-investigated. Herein, we aimed to study the usefulness of BIA-indices in the diagnoses of MetS in 6-10-year-old girls. Therefore, a diagnostic accuracy case-control study was conducted, which included 75 girls aged 10-16 years, divided into three age-matched groups (normal, None-MetS, and MetS). Anthropometric indices, BIA parameters (including fat-free mass (FFM), body fat percent (BFP), and total body water (TBW)), blood pressure (BP), and blood samples were collected. Our main findings show that for girls in None-MetS and MetS groups, the waist circumference (WC) correlated positively with waist-hip ratio and mid-arm circumference (r = 0.58, 0.47, respectively), but not with BFP based on skinfold thickness (SFT), or mid-arm muscle area. WC was positively correlated with FFM and TBW, while high-density lipoprotein was inversely correlated with FFM. However, fasting blood glucose, triglycerides and BP showed no association with anthropometric measurements and BIA components. WC was the best indicator of MetS (AUC = 0.88, cut-off = 81.5 cm), followed by BMI (AUC = 0.84, cut-off = 26.9 kg/m2), while BFP based on SFT was the least sensitive (62.5%). In conclusion, apart from the FM index, anthropometric parameters such as WC are more valuable in diagnosing MetS in young adolescent girls.
RESUMEN
OBJECTIVES: To investigate the prediction of long-term cardiometabolic risk using anthropometric and central obesity parameters. Methods: A total of 390 Saudi subjects (men 42.8%) aged 18-50 years were enrolled in a cross-sectional study in King Saud University, Riyadh, Kingdom of Saudi Arabia between August 2014 and January 2016. All participants were instructed to fast for 12 hours before taking blood samples for glucose and lipid panel analyses. A full anthropometric measurement and bioelectric impedance analysis was performed. The anthropometric and central obesity parameters were used for correlation with 30-year Framingham and life-time American College of Cardiology/American Heart Association risk scores. We used receiver operator characteristic curves to select the best predictors with the highest sensitivity and specificity. Results: The best discriminators of the long-term cardiometabolic risk among all the studied variables in men were the visceral adiposity index (VAI) (AUC=0.767), conicity index (CI) (AUC=0.817), and mid-arm muscular area (MAMA) (AUC=0.639). The best predictors for women were body mass index (AUC=0.912), waist circumference (AUC=0.752), and lipid accumulation product (AUC=0.632). The Kappa coefficient and 95% confidence interval ranged from 0.1 to 0.35, which suggests that there is a poor to fair agreement between these indices and cardiovascular risk scores. Conclusion: Long-term cardiometabolic risk can be predicted using simple anthropometric and central obesity indices, and these discriminators were not the same in Saudi men and women.