Cargando…
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 accur...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4620021/ https://www.ncbi.nlm.nih.gov/pubmed/26497052 http://dx.doi.org/10.1186/s12887-015-0486-5 |
Sumario: | 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. |
---|