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Adult height prediction using the growth curve comparison method
Understanding the growth pattern is important in view of child and adolescent development. Due to different tempo of growth and timing of adolescent growth spurt, individuals reach their adult height at different ages. Accurate models to assess the growth involve intrusive radiological methods where...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934345/ https://www.ncbi.nlm.nih.gov/pubmed/36795791 http://dx.doi.org/10.1371/journal.pone.0281960 |
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author | Mlakar, Miha Gradišek, Anton Luštrek, Mitja Jurak, Gregor Sorić, Maroje Leskošek, Bojan Starc, Gregor |
author_facet | Mlakar, Miha Gradišek, Anton Luštrek, Mitja Jurak, Gregor Sorić, Maroje Leskošek, Bojan Starc, Gregor |
author_sort | Mlakar, Miha |
collection | PubMed |
description | Understanding the growth pattern is important in view of child and adolescent development. Due to different tempo of growth and timing of adolescent growth spurt, individuals reach their adult height at different ages. Accurate models to assess the growth involve intrusive radiological methods whereas the predictive models based solely on height data are typically limited to percentiles and therefore rather inaccurate, especially during the onset of puberty. There is a need for more accurate non-invasive methods for height prediction that are easily applicable in the fields of sports and physical education, as well as in endocrinology. We developed a novel method, called Growth Curve Comparison (GCC), for height prediction, based on a large cohort of > 16,000 Slovenian schoolchildren followed yearly from ages 8 to 18. We compared the GCC method to the percentile method, linear regressor, decision tree regressor, and extreme gradient boosting. The GCC method outperformed the predictions of other methods over the entire age span both in boys and girls. The method was incorporated into a publicly available web application. We anticipate our method to be applicable also to other models predicting developmental outcomes of children and adolescents, such as for comparison of any developmental curves of anthropometric as well as fitness data. It can serve as a useful tool for assessment, planning, implementation, and monitoring of somatic and motor development of children and youth. |
format | Online Article Text |
id | pubmed-9934345 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-99343452023-02-17 Adult height prediction using the growth curve comparison method Mlakar, Miha Gradišek, Anton Luštrek, Mitja Jurak, Gregor Sorić, Maroje Leskošek, Bojan Starc, Gregor PLoS One Research Article Understanding the growth pattern is important in view of child and adolescent development. Due to different tempo of growth and timing of adolescent growth spurt, individuals reach their adult height at different ages. Accurate models to assess the growth involve intrusive radiological methods whereas the predictive models based solely on height data are typically limited to percentiles and therefore rather inaccurate, especially during the onset of puberty. There is a need for more accurate non-invasive methods for height prediction that are easily applicable in the fields of sports and physical education, as well as in endocrinology. We developed a novel method, called Growth Curve Comparison (GCC), for height prediction, based on a large cohort of > 16,000 Slovenian schoolchildren followed yearly from ages 8 to 18. We compared the GCC method to the percentile method, linear regressor, decision tree regressor, and extreme gradient boosting. The GCC method outperformed the predictions of other methods over the entire age span both in boys and girls. The method was incorporated into a publicly available web application. We anticipate our method to be applicable also to other models predicting developmental outcomes of children and adolescents, such as for comparison of any developmental curves of anthropometric as well as fitness data. It can serve as a useful tool for assessment, planning, implementation, and monitoring of somatic and motor development of children and youth. Public Library of Science 2023-02-16 /pmc/articles/PMC9934345/ /pubmed/36795791 http://dx.doi.org/10.1371/journal.pone.0281960 Text en © 2023 Mlakar et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Mlakar, Miha Gradišek, Anton Luštrek, Mitja Jurak, Gregor Sorić, Maroje Leskošek, Bojan Starc, Gregor Adult height prediction using the growth curve comparison method |
title | Adult height prediction using the growth curve comparison method |
title_full | Adult height prediction using the growth curve comparison method |
title_fullStr | Adult height prediction using the growth curve comparison method |
title_full_unstemmed | Adult height prediction using the growth curve comparison method |
title_short | Adult height prediction using the growth curve comparison method |
title_sort | adult height prediction using the growth curve comparison method |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934345/ https://www.ncbi.nlm.nih.gov/pubmed/36795791 http://dx.doi.org/10.1371/journal.pone.0281960 |
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