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

BMC Pediatrics

Frédéric Dadoun⁶  Michel Vaillant⁴  Sonia Leite⁴  Julien Jacobs³  Marco Hirsch⁷  Georges Gilson¹  Benjamin C. Guinhouya²  Saverio Stranges³  Carine de Beaufort⁵  Hanen Samouda³ 

[1] Department of Clinical Biology, Centre Hospitalier de Luxembourg, Luxembourg, L-1210, Luxembourg;Faculty for Health engineering and management, UDSL/ILIS, University Lille-Northern France, EA 2694, Laboratory of Public Health, Loos, F-59120, France;Population Health Department, Epidemiology and Public Health Research Unit, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, Strassen, L-1445, Luxembourg;Luxembourg Institute of Health, Centre of Competence for Methodology and Statistics (CCMS), Strassen, L-1445, Luxembourg;Centre Hospitalier de Luxembourg, Diabetes & Endocrinology Care Clinique Pédiatrique (DECCP), Luxembourg, L-1210, Luxembourg;Endocrinology and Diabetology Department, Centre Hospitalier de Luxembourg, Luxembourg, L-1210, Luxembourg;ZithaKlinik, Rheumatology Department, Luxembourg, L-2763, Luxembourg

关键词: Anthropometry;    DXA;    Body fat distribution;    Body mass index;    Overweight;    Obesity;   

Others  :  1234547
DOI  :  10.1186/s12887-015-0486-5

 received in 2015-05-20, accepted in 2015-10-13,  发布年份 2015

【 摘 要 】

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.

【 授权许可】

   
2015 Samouda et al.

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