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Estimating Age- and Height-Specific Percentile Curves for Children Using GAMLSS in the IDEFICS Study

  • Timm Intemann
  • Hermann Pohlabeln
  • Diana Herrmann Wolfgang Ahrens
  • Iris Pigeot
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

In medical diagnostics age-specific reference values are needed for assessing the health status of children. However, for many clinical parameters such as blood cholesterol or insulin reference curves are still missing for children. To fill this gap, the IDEFICS study provides an excellent data base with 18,745 children aged 2.0–10.9 years. The generalised additive model for location, scale and shape (GAMLSS) was used to derive such reference curves while controlling for the influence of various covariates on the parameters of interest. GAMLSS, an extension of the LMS method, is able to model the influence of more than one covariate. It is also able to model the kurtosis using different distributions. The Bayesian information criterion (BIC), Q-Q plots and wormplots were applied to assess the goodness of fit of alternative models. GAMLSS has proven to be a useful tool to model the influence of more than one covariate when deriving age- and sex-specific percentile curves for clinical parameters in children. This will be demonstrated exemplarily for the bone stiffness index (SI) where age- and height-specific percentile curves were calculated for boys and girls based on the model which showed the best goodness of fit.

Keywords

Bayesian Information Criterion Reference Curve Stiffness Index Power Exponential Bone Stiffness 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work was done as part of the IDEFICS study (www.idefics.eu). We gratefully acknowledge the financial support of the European community within the Sixth RTD Framework Programme Contract No. 016181 (FOOD).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Timm Intemann
    • 1
    • 2
  • Hermann Pohlabeln
    • 1
    • 2
  • Diana Herrmann Wolfgang Ahrens
    • 1
    • 2
  • Iris Pigeot
    • 1
    • 2
  1. 1.Leibniz Institute for Prevention Research and Epidemiology - BIPSBremenGermany
  2. 2.IDEFICS consortiumBremenGermany

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