TY - JOUR
T1 - Adding anthropometric measures of regional adiposity to BMI improves prediction of cardiometabolic, inflammatory and adipokines profiles in youths
T2 - A cross-sectional study
AU - Samouda, Hanen
AU - de Beaufort, Carine
AU - Stranges, Saverio
AU - Guinhouya, Benjamin C.
AU - Gilson, Georges
AU - Hirsch, Marco
AU - Jacobs, Julien
AU - Leite, Sonia
AU - Vaillant, Michel
AU - Dadoun, Frédéric
N1 - Funding Information:
We thank the children and the parents for their participation. We also thank Dr Van Buuren (Department of Statistics, TNO Quality of Life, 2301 CE Leiden, The Netherlands) who provided us with the L, M and S values initially developed in the Dutch population. This study has been funded by the Ministry for Culture, Higher Education and Research, Luxembourg and by the National Research Fund, Luxembourg.
Publisher Copyright:
© 2015 Samouda et al.
PY - 2015/10/24
Y1 - 2015/10/24
N2 - 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, 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.
AB - 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, 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.
KW - Anthropometry
KW - Body fat distribution
KW - Body mass index
KW - DXA
KW - Obesity
KW - Overweight
UR - http://www.scopus.com/inward/record.url?scp=84944704326&partnerID=8YFLogxK
U2 - 10.1186/s12887-015-0486-5
DO - 10.1186/s12887-015-0486-5
M3 - Article
C2 - 26497052
AN - SCOPUS:84944704326
SN - 1471-2431
VL - 15
JO - BMC Pediatrics
JF - BMC Pediatrics
IS - 1
M1 - 168
ER -