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A mechanistic approach to tracing anthropometric charts: The extended mechanistic growth function method
Author(s) -
Spada Elena,
Gilli Giulio,
Coscia Alessandra,
Milani Silvano
Publication year - 2014
Publication title -
american journal of human biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.559
H-Index - 81
eISSN - 1520-6300
pISSN - 1042-0533
DOI - 10.1002/ajhb.22635
Subject(s) - anthropometry , statistics , skewness , mathematics , smoothing , standard deviation , standard error , medicine , birth weight , pregnancy , biology , genetics
Objectives The Extended Mechanistic Growth Function (EMGF) method (Clementi et al. [1999]: Am J Med Genet 87:317–323) is a possible alternative to the Cole and Green LMS method ([1992] Stat Med 11:1305‐1319) to construct cross‐sectional anthropometric charts. It differs from the technique used by Kuczmarski et al. ([2002]: Vital Health Stat 11:1–190) to trace the CDC growth charts in that all centiles are simultaneously fitted with a single function. The aim of this study is to show how an EMGF model can be designed. Methods To illustrate the structure and properties of the EMGF method, the data of the Italian Neonatal Study (Bertino et al. [2010]: J Pediatr Gastroenterol Nutr 51:353–361) were analyzed. The dataset included the birth weight of 45,272 single liveborn babies with gestational ages ranging from 23 to 42 weeks. The EMGF method consists of three steps. In the preliminary step, selected age‐dependent raw centiles of the anthropometric trait are computed. In the smoothing step, all centiles are simultaneously fitted with a growth function extended with the inclusion of a few extra parameters. In the transformation step, estimates of the age‐dependent L (skewness), M (median), and S (coefficient of variation) parameters are derived. Results A four‐parameter generalized logistic function, extended with five parameters to model between‐sex differences, distance between centiles and their slope, was found to fit the raw centiles of birth weight distribution with a residual standard deviation of 51.3 g. Conclusions The EMGF method represents a bridge to link cross‐sectional and longitudinal studies and allows us to identify milestones of the median growth in a population in the same way used for individual profiles. Am. J. Hum. Biol. 27:175–183, 2015. © 2014 Wiley Periodicals, Inc.