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Early stature prediction method using stature growth parameters
DC Field | Value | Language |
---|---|---|
dc.contributor.author | LEE, SHIN-JAE | - |
dc.contributor.author | AN, HONGSEOK | - |
dc.contributor.author | AHN, SUG-JOON | - |
dc.contributor.author | KIM, YOUNG HO | - |
dc.contributor.author | PAK, SUNYOUNG | - |
dc.contributor.author | LEE, JAE WON | - |
dc.date.accessioned | 2010-04-01 | - |
dc.date.available | 2010-04-01 | - |
dc.date.issued | 2008-09 | - |
dc.identifier.citation | Annals of Human Biology, 2008;35(5): 509–517 | en |
dc.identifier.issn | 0301-4460 (print) | - |
dc.identifier.issn | 1464-5033 (online) | - |
dc.identifier.uri | https://hdl.handle.net/10371/62253 | - |
dc.description.abstract | Background: The creation of an accurate growth prediction method for human stature at a stage of
growth has been an interesting challenge in medical science and human biology. Aim: The aim of this study was to develop a non-radiographic final stature prediction method that is applicable in the early pubertal growth period. Subjects and methods: Randomly selected 12-year serial stature growth data for 400 Koreans were fitted with two nonlinear growth curves: Preece and Baines model 1 (PB1) and Jolicoeur–Pontier–Pernin– Sempe (JPPS) functions. Five biological parameters, including take-off (TO) related parameters, were derived by differentiation of the two curves, respectively. Those five variables were composed into a multiple linear regression equation for final stature prediction. In the cross-validation subjects, TO-related variables were estimated by linear interpolation from the partial growth data prior to estimation age, then incorporated into the prediction equation. Results: The final stature prediction model had excellent validity and accuracy when applied to the cross-validation samples. Prediction accuracy increased according to increasing years after take-off. Conclusions: This study suggests that a final stature prediction method using multiple regression analysis that includes biological parameters can predict stature growth with sufficient validity and accuracy. Incorporation of TO-related parameters allowed us to develop earlier growth evaluation and prediction methods compared with other previous methods. | en |
dc.description.sponsorship | This work was supported by the Korea Research Foundation Grant funded by the
Korean Government (Ministry of Education and Human Resources Development) (KRF-2006-311-E00490). We wish to thank K.H. Kyung and B.K. Ahn for their elaborate assistance in serial growth data collection. | en |
dc.language.iso | en | en |
dc.publisher | Informa | en |
dc.subject | Early prediction | en |
dc.subject | biological parameters | en |
dc.subject | multiple regressions | en |
dc.subject | curve fitting | en |
dc.title | Early stature prediction method using stature growth parameters | en |
dc.type | Article | en |
dc.contributor.AlternativeAuthor | 이신재 | - |
dc.contributor.AlternativeAuthor | 안홍석 | - |
dc.contributor.AlternativeAuthor | 안석준 | - |
dc.contributor.AlternativeAuthor | 김용호 | - |
dc.contributor.AlternativeAuthor | 박선영 | - |
dc.contributor.AlternativeAuthor | 이재원 | - |
dc.identifier.doi | 10.1080/03014460802286942 | - |
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