Document Detail

Is growth saltatory? The usefulness and limitations of frequency distributions in analyzing pulsatile data.
MedLine Citation:
PMID:  8940335     Owner:  NLM     Status:  MEDLINE    
Several investigators have proposed that descriptive statistics can be employed to identify and discriminate growth patterns. These studies assumed that the shape of the frequency distribution of daily growth velocities (FDGVs) is diagnostic in differentiating between a pattern of growth characterized by smooth, continuous daily acquisition and a pattern of growth characterized by a discontinuous, i.e. pulsatile process. The FDGV from a saltation and stasis, i.e. episodic or pulsatile, growth pattern was assumed to be bimodal or significantly skewed to the right, whereas a continuous growth function was assumed to be approximately Gaussian. The use of FDGV characteristics is an unprecedented approach to the analysis of longitudinal growth data and was not previously validated for this use. The present study investigates the performance characteristics of the FDGV method by Monte-Carlo simulations of known saltatory, i.e. pulsatile, growth patterns. These analyses show that the FDGV for a saltation and stasis growth process can be either unimodal or bimodal and either skewed to the right or to the left. Data collection frequency, measurement error, and total study duration all determine the shape of the FDGV and the statistical significance of the results. If the FDGV is highly skewed, then it is consistent with saltatory growth. However, if the FDGV is not highly skewed, then it is consistent with both the saltatory model and a smooth, continuous growth model, and thus, the results are ambiguous. We conclude that FDGV analysis is not a valid method to exclude saltation and stasis growth processes in longitudinal growth studies.
M L Johnson; J D Veldhuis; M Lampl
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Endocrinology     Volume:  137     ISSN:  0013-7227     ISO Abbreviation:  Endocrinology     Publication Date:  1996 Dec 
Date Detail:
Created Date:  1997-01-23     Completed Date:  1997-01-23     Revised Date:  2007-11-14    
Medline Journal Info:
Nlm Unique ID:  0375040     Medline TA:  Endocrinology     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  5197-204     Citation Subset:  AIM; IM    
Department of Pharmacology, University of Virginia Health Sciences Center, Charlottesville 22908, USA.
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MeSH Terms
Child Development / physiology
Growth / physiology*
Monte Carlo Method
Grant Support

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