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

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: Fou...

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Autores principales: Hudda, Mohammed T, Fewtrell, Mary S, Haroun, Dalia, Lum, Sooky, Williams, Jane E, Wells, Jonathan C K, Riley, Richard D, Owen, Christopher G, Cook, Derek G, Rudnicka, Alicja R, Whincup, Peter H, Nightingale, Claire M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group Ltd. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650932/
https://www.ncbi.nlm.nih.gov/pubmed/31340931
http://dx.doi.org/10.1136/bmj.l4293
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author Hudda, Mohammed T
Fewtrell, Mary S
Haroun, Dalia
Lum, Sooky
Williams, Jane E
Wells, Jonathan C K
Riley, Richard D
Owen, Christopher G
Cook, Derek G
Rudnicka, Alicja R
Whincup, Peter H
Nightingale, Claire M
author_facet Hudda, Mohammed T
Fewtrell, Mary S
Haroun, Dalia
Lum, Sooky
Williams, Jane E
Wells, Jonathan C K
Riley, Richard D
Owen, Christopher G
Cook, Derek G
Rudnicka, Alicja R
Whincup, Peter H
Nightingale, Claire M
author_sort Hudda, Mohammed T
collection PubMed
description 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 R(2): 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 (R(2): 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.
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spelling pubmed-66509322019-08-28 Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data Hudda, Mohammed T Fewtrell, Mary S Haroun, Dalia Lum, Sooky Williams, Jane E Wells, Jonathan C K Riley, Richard D Owen, Christopher G Cook, Derek G Rudnicka, Alicja R Whincup, Peter H Nightingale, Claire M BMJ Research 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 R(2): 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 (R(2): 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. BMJ Publishing Group Ltd. 2019-07-24 /pmc/articles/PMC6650932/ /pubmed/31340931 http://dx.doi.org/10.1136/bmj.l4293 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions 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/.
spellingShingle Research
Hudda, Mohammed T
Fewtrell, Mary S
Haroun, Dalia
Lum, Sooky
Williams, Jane E
Wells, Jonathan C K
Riley, Richard D
Owen, Christopher G
Cook, Derek G
Rudnicka, Alicja R
Whincup, Peter H
Nightingale, Claire M
Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data
title Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data
title_full Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data
title_fullStr Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data
title_full_unstemmed Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data
title_short Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data
title_sort development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650932/
https://www.ncbi.nlm.nih.gov/pubmed/31340931
http://dx.doi.org/10.1136/bmj.l4293
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