Adding anthropometric measures of regional adiposity to BMI improves prediction of cardiometabolic, inflammatory and adipokines profiles in youths: a cross-sectional study. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Samouda, Hanen; de Beaufort, Carine; Stranges, Saverio; Guinhouya, Benjamin; Gilson, Georges; Hirsch, Marco; Jacobs, Julien; Leite, Sonia; Vaillant, Michel; Dadoun, Frédéric
• Is Part Of: BMC pediatrics. Volume 15:Issue 1(2015)
• Page Start: 1
• Page End: 9
• Publication Date: 2015-12
• Subjects: Obesity -- Overweight -- Body mass index -- Body fat distribution -- DXA -- Anthropometry; Pediatrics -- Periodicals; 618.920005
• DOI: 10.1186/s12887-015-0486-5
• Languages: English
• ISSNs: 1471-2431

Abstract

Abstract Background Paediatric research analysing the relationship between the easy-to-use anthropometric measures for adiposity and cardiometabolic risk factors remains highly controversial in youth. Several studies suggest that only body mass index (BMI), a measure of relative weight, constitutes an accurate predictor, whereas others highlight the potential role of waist-to-hip ratio (WHR), waist circumference (Waist C), and waist-to-height ratio (WHtR). In this study, we examined the effectiveness of adding anthropometric measures of body fat distribution (Waist C Z Score, WHR Z Score and/or WHtR) to BMI Z Score to predict cardiometabolic risk factors in overweight and obese youth. We also examined the consistency of these associations with the "total fat mass + trunk/legs fat mass" and/or the "total fat mass + trunk fat mass" combinations, as assessed by dual energy X-ray absorptiometry (DXA), the gold standard measurement of body composition. Methods Anthropometric and DXA measurements of total and regional adiposity, as well as a comprehensive assessment of cardiometabolic, inflammatory and adipokines profiles were performed in 203 overweight and obese 7–17 year-old youths from thePaediatrics Clinic, Centre Hospitalier de Luxembourg. Results Adding only one anthropometric surrogate of regional fat to BMI Z Score improved the prediction of insulin resistance (WHR Z Score, R2 : 45.9 %. Waist C Z Score, R2 : 45.5 %), HDL-cholesterol (WHR Z Score, R2 : 9.6 %. Waist C Z Score, R2 : 10.8 %. WHtR, R2 : 6.5 %), triglycerides (WHR Z Score, R2 : 11.7 %. Waist C Z Score, R2 : 12.2 %), adiponectin (WHR Z Score, R2 : 14.3 %. Waist C Z Score, R2 : 17.7 %), CRP (WHR Z Score, R2 : 18.2 %. WHtR, R2 : 23.3 %), systolic (WHtR, R2 : 22.4 %), diastolic blood pressure (WHtR, R2 : 20 %) and fibrinogen (WHtR, R2 : 21.8 %). Moreover, WHR Z Score, Waist C Z Score and/or WHtR showed an independent significant contribution according to these models. These results were in line with the DXA findings. Conclusions Adding anthropometric measures of regional adiposity to BMI Z Score improves the prediction of cardiometabolic, inflammatory and adipokines profiles in youth.