Literature DB >> 25214151

Introducing excess body weight in childhood and adolescence and comparison with body mass index and waist-to-height ratio.

D Petroff1, K Kromeyer-Hauschild2, S Wiegand3, D l'Allemand-Jander4, G Binder5, K-O Schwab6, R Stachow7, W Kiess8, E Hammer9, S Sturm10, R W Holl11, S Blüher12.   

Abstract

BACKGROUND: Weight status in children and adolescents is commonly defined using age- and gender-corrected standard deviation scores for body mass index (BMI-SDS, also called z-scores). Values are not reliable for the extremely obese however. Moreover, paediatricians and parents may have difficulties understanding z-scores, and while percentiles are easier to gauge, the very obese have values above the 99th percentile, making distinction difficult. The notion of excess body weight (EBW) is increasingly applied in adult patients, mainly in the context of bariatric surgery. However, a clear definition is not available to date for the paediatric population.
METHODS: A simple definition of EBW for children and adolescents is introduced, with median weight as a function of height, age and gender (characterized by an asterisk): EBW (%) = 100x(weight-median weight*)/median weight*. EBW is compared with BMI-SDS and waist-to-height ratio (WHtR). Using two data sources (APV registry and German Health Interview and Examination Survey for Children and Adolescents (KiGGS)) including more than 14,000 children, the relationships between these anthropometric and various metabolic parameters are analysed for a group of overweight/obese children who have sought obesity therapy (APV), for the general paediatric population and for the subset of overweight/obese children from the general population (KiGGS).
RESULTS: The three anthropometric parameters are strongly correlated, with the linear correlation coefficients exceeding 0.8 in the general population and 0.75 in those seeking obesity therapy. Moreover, their relationship to metabolic parameters is quite similar regarding correlations and area under the curve from receiver operating characteristic analyses.
CONCLUSIONS: EBW has similar predictive value for metabolic or cardiovascular comorbidities compared with BMI and WHtR. As it is reliable at the extreme end of the obesity spectrum, easily communicable and simple to use in daily practice, it would make a very useful addition to existing tools for working with obese children and adolescents. Its usefulness in assessing weight change needs to be studied however.

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Year:  2014        PMID: 25214151     DOI: 10.1038/ijo.2014.170

Source DB:  PubMed          Journal:  Int J Obes (Lond)        ISSN: 0307-0565            Impact factor:   5.095


  21 in total

1.  Prediction of visceral adipose tissue from simple anthropometric measurements in youths with obesity.

Authors:  S Owens; M Litaker; J Allison; S Riggs; M Ferguson; B Gutin
Journal:  Obes Res       Date:  1999-01

2.  BMI centile curves for Japanese children aged 5-17 years in 2000-2005.

Authors:  Naoko Sakamoto; Limin Yang
Journal:  Public Health Nutr       Date:  2009-06-23       Impact factor: 4.022

Review 3.  A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0·5 could be a suitable global boundary value.

Authors:  Lucy M Browning; Shiun Dong Hsieh; Margaret Ashwell
Journal:  Nutr Res Rev       Date:  2010-09-07       Impact factor: 7.800

4.  The absence of insulin resistance in metabolic syndrome definition leads to underdiagnosing of metabolic risk in obese patients.

Authors:  Selim Kurtoglu; Leyla Akin; Mustafa Kendirci; Nihal Hatipoglu; Ferhan Elmali; Mümtaz Mazicioglu
Journal:  Eur J Pediatr       Date:  2012-03-28       Impact factor: 3.183

5.  Waist-to-height ratio is the best predictor of cardiovascular disease risk factors in Japanese schoolchildren.

Authors:  Mitsuhiko Hara; Emiko Saitou; Fujihiko Iwata; Tomoo Okada; Kensuke Harada
Journal:  J Atheroscler Thromb       Date:  2002       Impact factor: 4.928

Review 6.  Diagnostic performance of body mass index to identify obesity as defined by body adiposity in children and adolescents: a systematic review and meta-analysis.

Authors:  A Javed; M Jumean; M H Murad; D Okorodudu; S Kumar; V K Somers; O Sochor; F Lopez-Jimenez
Journal:  Pediatr Obes       Date:  2014-06-25       Impact factor: 4.000

7.  Cut-off values of visceral fat area and waist-to-height ratio: diagnostic criteria for obesity-related disorders in Korean children and adolescents.

Authors:  Kang-Kon Lee; Hye-Soon Park; Keun-Sang Yum
Journal:  Yonsei Med J       Date:  2012-01       Impact factor: 2.759

Review 8.  Predicting cardiometabolic risk: waist-to-height ratio or BMI. A meta-analysis.

Authors:  Savvas C Savva; Demetris Lamnisos; Anthony G Kafatos
Journal:  Diabetes Metab Syndr Obes       Date:  2013-10-24       Impact factor: 3.168

9.  What is the best measure of adiposity change in growing children: BMI, BMI %, BMI z-score or BMI centile?

Authors:  T J Cole; M S Faith; A Pietrobelli; M Heo
Journal:  Eur J Clin Nutr       Date:  2005-03       Impact factor: 4.016

10.  The challenge of comprehensively mapping children's health in a nation-wide health survey: design of the German KiGGS-Study.

Authors:  Bärbel-Maria Kurth; Panagiotis Kamtsiuris; Heike Hölling; Martin Schlaud; Rüdiger Dölle; Ute Ellert; Heidrun Kahl; Hiltraud Knopf; Michael Lange; Gert Bm Mensink; Hannelore Neuhauser; Angelika Schaffrath Rosario; Christa Scheidt-Nave; Liane Schenk; Robert Schlack; Heribert Stolzenberg; Michael Thamm; Wulf Thierfelder; Ute Wolf
Journal:  BMC Public Health       Date:  2008-06-04       Impact factor: 3.295

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  3 in total

1.  Association between junk food consumption and cardiometabolic risk factors in a national sample of Iranian children and adolescents population: the CASPIAN-V study.

Authors:  Bahar Azemati; Roya Kelishadi; Zeinab Ahadi; Gita Shafiee; MajZoubeh Taheri; Hasan Ziaodini; Mostafa Qorbani; Ramin Heshmat
Journal:  Eat Weight Disord       Date:  2018-10-11       Impact factor: 4.652

Review 2.  Waist-to-height ratio as a screening tool for obesity and cardiometabolic risk.

Authors:  Eun-Gyong Yoo
Journal:  Korean J Pediatr       Date:  2016-11-18

3.  Effects of a novel mobile health intervention compared to a multi-component behaviour changing program on body mass index, physical capacities and stress parameters in adolescents with obesity: a randomized controlled trial.

Authors:  T Kowatsch; D l'Allemand; A Stasinaki; D Büchter; C-H I Shih; K Heldt; S Güsewell; B Brogle; N Farpour-Lambert
Journal:  BMC Pediatr       Date:  2021-07-09       Impact factor: 2.125

  3 in total

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