English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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.

bmc pediatrics

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