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

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.

Fig 1

Assessment of model calibration for fat-free mass and fat mass. The developed model for predicting natural logarithm of fat-free mass was used to derive estimates of fat-free mass and fat mass, which were each used to assess model calibration. Broken orange line represents a lowess smoother through the data points, showing a linear relation between observed and predicted values of both fat-free mass and fat mass

Fig 2

Assessment of calibration slope and calibration-in-the-large for fat mass and fat-free mass from internal-external cross validation. Calibration slopes and calibration-in-the-large (and respective 95% confidence intervals) were obtained by fitting the final model in three studies and assessing the external validity in terms of the slope and intercept for fat-free mass and fat mass in the data from the fourth study. This was repeated until each of the four studies had been used as a validation dataset. A random effects meta-analysis was used to obtain the pooled estimates (95% confidence intervals) along with the τ² statistic for heterogeneity. Also see supplementary table 2 for data in tabular form. ABCC=Assessment of Body Composition in Children study; ELBI=East London Bioelectrical Impedance, RC=Reference Child, SLIC=Size and Lung function in Children study

Fig 3

Calibration plot of mean observed against mean predicted values, across 10ths of predicted fat mass, from external validation before recalibration of intercept. Data points are mean predicted against mean observed fat mass within 10ths of predicted fat mass. Individual level data points not shown for confidentiality reasons. Broken orange line represents a local regression smoother through individual level data points. Broken black line represents line of equality