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Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data

Hudda, MT; Fewtrell, M; Haroun, D; Lum, S; Williams, J; Wells, J; Riley, R; Owen, C; Cook, D; Rudnicka, AR; et al. Hudda, MT; Fewtrell, M; Haroun, D; Lum, S; Williams, J; Wells, J; Riley, R; Owen, C; Cook, D; Rudnicka, AR; Whincup, P; Nightingale, C (2019) Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data. BMJ-British Medical Journal, 366. l4293. ISSN 1756-1833 https://doi.org/10.1136/bmj.l4293
SGUL Authors: Nightingale, Claire Owen, Christopher Grant Whincup, Peter Hynes Hudda, Mohammed Taqui

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Abstract

Objectives To develop and validate a prediction model for fat mass in children aged 4-15 years using routinely available risk factors of height, weight, and demographic information without the need for more complex forms of assessment. Design Individual participant data meta-analysis. Setting Four population based cross sectional studies and a fifth study for external validation, United Kingdom. Participants A pooled derivation dataset (four studies) of 2375 children and an external validation dataset of 176 children with complete data on anthropometric measurements and deuterium dilution assessments of fat mass. Main outcome measure Multivariable linear regression analysis, using backwards selection for inclusion of predictor variables and allowing non-linear relations, was used to develop a prediction model for fat-free mass (and subsequently fat mass by subtracting resulting estimates from weight) based on the four studies. Internal validation and then internal-external cross validation were used to examine overfitting and generalisability of the model’s predictive performance within the four development studies; external validation followed using the fifth dataset. Results Model derivation was based on a multi-ethnic population of 2375 children (47.8% boys, n=1136) aged 4-15 years. The final model containing predictor variables of height, weight, age, sex, and ethnicity had extremely high predictive ability (optimism adjusted R2: 94.8%, 95% confidence interval 94.4% to 95.2%) with excellent calibration of observed and predicted values. The internal validation showed minimal overfitting and good model generalisability, with excellent calibration and predictive performance. External validation in 176 children aged 11-12 years showed promising generalisability of the model (R2: 90.0%, 95% confidence interval 87.2% to 92.8%) with good calibration of observed and predicted fat mass (slope: 1.02, 95% confidence interval 0.97 to 1.07). The mean difference between observed and predicted fat mass was −1.29 kg (95% confidence interval −1.62 to −0.96 kg). Conclusion The developed model accurately predicted levels of fat mass in children aged 4-15 years. The prediction model is based on simple anthropometric measures without the need for more complex forms of assessment and could improve the accuracy of assessments for body fatness in children (compared with those provided by body mass index) for effective surveillance, prevention, and management of clinical and public health obesity.

Item Type: Article
Additional Information: This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: BMJ-British Medical Journal
ISSN: 1756-1833
Dates:
DateEvent
24 July 2019Published
6 June 2019Accepted
Publisher License: Creative Commons: Attribution-Noncommercial 4.0
Projects:
Project IDFunderFunder ID
PG/15/19/31336British Heart Foundationhttp://dx.doi.org/10.13039/501100000274
FS/17/76/33286British Heart Foundationhttp://dx.doi.org/10.13039/501100000274
NIHR CLAHRC-2013-10022National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
204809/Z/16/ZWellcome Trusthttp://dx.doi.org/10.13039/100004440
PG/11/42/28895British Heart Foundationhttp://dx.doi.org/10.13039/501100000274
TBF-S09-019Bupa Foundationhttp://dx.doi.org/10.13039/501100000355
GR 10/03Child Growth FoundationUNSPECIFIED
WT094129MAWellcome Trusthttp://dx.doi.org/10.13039/100004440
UNSPECIFIEDMedical Research Councilhttp://dx.doi.org/10.13039/501100000265
102215/2/13/2Wellcome Trusthttp://dx.doi.org/10.13039/100004440
URI: https://openaccess.sgul.ac.uk/id/eprint/110907
Publisher's version: https://doi.org/10.1136/bmj.l4293

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