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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
- Source :
- BMJ (e), 378:e071185. BMJ Publishing Group
- Publication Year :
- 2022
- Publisher :
- BMJ, 2022.
-
Abstract
- Peer reviewed: True<br />Acknowledgements: We thank John Reilly for his advice on data sources and data access; Cara L Eckhardt, Josephine Avila, Igor Y Kon, and Jinzhong Wang from the Eckhardt et al study23; and all staff involved in recruitment and data collection from the included studies. Data gathered from South Africa was supported by South Africa Medical Research Council and National Research Foundation.<br />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
Details
- ISSN :
- 17561833
- Database :
- OpenAIRE
- Journal :
- BMJ
- Accession number :
- edsair.doi.dedup.....6308bf0e51397f05217b1c90d7a073fe
- Full Text :
- https://doi.org/10.1136/bmj-2022-071185