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External validation of a prediction model for estimating fat mass in children and adolescents in 19 countries: individual participant data meta-analysis

Hudda, MT; Wells, JCK; Adair, LS; Alvero-Cruz, JRA; Ashby-Thompson, MN; Ballesteros-Vásquez, MN; Barrera-Exposito, J; Caballero, B; Carnero, EA; Cleghorn, GJ; et al. Hudda, MT; Wells, JCK; Adair, LS; Alvero-Cruz, JRA; Ashby-Thompson, MN; Ballesteros-Vásquez, MN; Barrera-Exposito, J; Caballero, B; Carnero, EA; Cleghorn, GJ; Davies, PSW; Desmond, M; Devakumar, D; Gallagher, D; Guerrero-Alcocer, EV; Haschke, F; Horlick, M; Ben Jemaa, H; Khan, AI; Mankai, A; Monyeki, MA; Nashandi, HL; Ortiz-Hernandez, L; Plasqui, G; Reichert, FF; Robles-Sardin, AE; Rush, E; Shypailo, RJ; Sobiecki, JG; ten Hoor, GA; Valdés, J; Wickramasinghe, VP; Wong, WW; Riley, RD; Owen, CG; Whincup, PH; Nightingale, CM (2022) External validation of a prediction model for estimating fat mass in children and adolescents in 19 countries: individual participant data meta-analysis. BMJ, 378. e071185. ISSN 1756-1833 https://doi.org/10.1136/bmj-2022-071185
SGUL Authors: Hudda, Mohammed Taqui

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Abstract

Objective To evaluate the performance of a UK based prediction model for estimating fat-free mass (and indirectly fat mass) in children and adolescents in non-UK settings. Design Individual participant data meta-analysis. Setting 19 countries. Participants 5693 children and adolescents (49.7% boys) aged 4 to 15 years with complete data on the predictors included in the UK based model (weight, height, age, sex, and ethnicity) and on the independently assessed outcome measure (fat-free mass determined by deuterium dilution assessment). Main outcome measures The outcome of the UK based prediction model was natural log transformed fat-free mass (lnFFM). Predictive performance statistics of R2, calibration slope, calibration-in-the-large, and root mean square error were assessed in each of the 19 countries and then pooled through random effects meta-analysis. Calibration plots were also derived for each country, including flexible calibration curves. Results The model showed good predictive ability in non-UK populations of children and adolescents, providing R2 values of >75% in all countries and >90% in 11 of the 19 countries, and with good calibration (ie, agreement) of observed and predicted values. Root mean square error values (on fat-free mass scale) were <4 kg in 17 of the 19 settings. Pooled values (95% confidence intervals) of R2, calibration slope, and calibration-in-the-large were 88.7% (85.9% to 91.4%), 0.98 (0.97 to 1.00), and 0.01 (−0.02 to 0.04), respectively. Heterogeneity was evident in the R2 and calibration-in-the-large values across settings, but not in the calibration slope. Model performance did not vary markedly between boys and girls, age, ethnicity, and national income groups. To further improve the accuracy of the predictions, the model equation was recalibrated for the intercept in each setting so that country specific equations are available for future use. Conclusion The UK based prediction model, which is based on readily available measures, provides predictions of childhood fat-free mass, and hence fat mass, in a range of non-UK settings that explain a large proportion of the variability in observed fat-free mass, and exhibit good calibration performance, especially after recalibration of the intercept for each population. The model demonstrates good generalisability in both low-middle income and high income populations of healthy children and adolescents aged 4-15 years.

Item Type: Article
Additional Information: http://creativecommons.org/licenses/by-nc/4.0/ 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/.
Keywords: 1103 Clinical Sciences, 1117 Public Health and Health Services, General & Internal Medicine
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: BMJ
ISSN: 1756-1833
Language: en
Dates:
DateEvent
21 September 2022Published
2 August 2022Accepted
Publisher License: Creative Commons: Attribution-Noncommercial 4.0
Projects:
Project IDFunderFunder ID
FS/17/76/33286British Heart Foundationhttp://dx.doi.org/10.13039/501100000274
204809/Z/16/ZWellcome Trusthttp://dx.doi.org/10.13039/100004440
URI: https://openaccess.sgul.ac.uk/id/eprint/114870
Publisher's version: https://doi.org/10.1136/bmj-2022-071185

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