Human linear growth trajectory defined.
OBJECTIVE
The purpose of this study was to assess the applicability of a simple mathematical formula for prediction of individual child linear growth. The formula describes a square root dependence of height on age with only two constants, k and C.


METHODS
Retrospective serial height measurements of 137 healthy children (61 female), who attended clinic in the Pediatrics Department at the University of California, San Francisco were used. For each child, two of the initial measurements and their corresponding measurement times were used to determine the values of k and C. By substituting the determined values of k and C into the formula, the formula was then used to predict the trajectory of the child's growth.


RESULTS
The 137 children were comprised of 20% Hispanic, 23% African-American, 27% Caucasian and 30% Asian. The formula predicted growth trajectories of 136 out of the 137 children with minimal discrepancies between the measured data and the corresponding predicted data. The mean of the discrepancies was 0.8 cm.


CONCLUSIONS
Our proposed formula is very easy to use and predicts individual child growth with high precision irrespective of gender or ethnicity. The formula will be a valuable tool for studying human growth and possibly growths of other animals.
Department of Radiology and Biomedical Imaging, University of California, San Francisco, California; NCIRE, Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, California; Department of Biomedical Engineering, All Nations University College, Koforidua, Ghana.
Anderson
A
Mon
Michael
M
Cabana
Bonnie
B
Halpern-Felsher
Dieter Johannes
DJ
Meyerhoff
D000293:Adolescent; D041923:Adolescent Development; D017677:Age Distribution; D000886:Anthropometry / Q000379:methods*; D001827:Body Height; D002648:Child; D002657:Child Development; D002675:Child, Preschool; D005006:Ethnicity; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D008954:Models, Biological; D012189:Retrospective Studies; D012495:San Francisco; D012727:Sex Characteristics