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

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 the Paediatrics 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, R(2): 45.9%. Waist C Z Score, R(2): 45.5%), HDL-cholesterol (WHR Z Score, R(2): 9.6%. Waist C Z Score, R(2): 10.8%. WHtR, R(2): 6.5%), triglycerides (WHR Z Score, R(2): 11.7%. Waist C Z Score, R(2): 12.2%), adiponectin (WHR Z Score, R(2): 14.3%. Waist C Z Score, R(2): 17.7%), CRP (WHR Z Score, R(2): 18.2%. WHtR, R(2): 23.3%), systolic (WHtR, R(2): 22.4%), diastolic blood pressure (WHtR, R(2): 20%) and fibrinogen (WHtR, R(2): 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.