ObjectivesThe 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. MethodsTo 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. ResultsA 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. ConclusionsThe 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. (c) 2014 Wiley Periodicals, Inc.
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Hanze Univ Appl Sci, Res Grp Digital Transformat, Zernikepl 11, NL-9747 AS Groningen, Netherlands
Netherlands Org Appl Sci Res TNO, Dept Human Behav & Training, Kampweg 55, NL-3769 DE Soesterberg, Netherlands
Univ Med Ctr Groningen, Dept Hlth Psychol, Antonius Deusinglaan 1, NL-9713 AV Groningen, NetherlandsHanze Univ Appl Sci, Res Grp Digital Transformat, Zernikepl 11, NL-9747 AS Groningen, Netherlands
de Vries, Herman
Kamphuis, Wim
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Netherlands Org Appl Sci Res TNO, Dept Human Behav & Training, Kampweg 55, NL-3769 DE Soesterberg, NetherlandsHanze Univ Appl Sci, Res Grp Digital Transformat, Zernikepl 11, NL-9747 AS Groningen, Netherlands
Kamphuis, Wim
van der Schans, Cees
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Univ Med Ctr Groningen, Dept Hlth Psychol, Antonius Deusinglaan 1, NL-9713 AV Groningen, Netherlands
Univ Med Ctr Groningen, Dept Rehabil Med, Antonius Deusinglaan 1, NL-9713 AV Groningen, Netherlands
Hanze Univ Appl Sci, Res Grp Hlth Ageing Allied Hlth Care & Nursing, Petrus Driessenstr 3, NL-9714 CA Groningen, NetherlandsHanze Univ Appl Sci, Res Grp Digital Transformat, Zernikepl 11, NL-9747 AS Groningen, Netherlands
van der Schans, Cees
Sanderman, Robbert
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Univ Med Ctr Groningen, Dept Hlth Psychol, Antonius Deusinglaan 1, NL-9713 AV Groningen, Netherlands
Univ Twente, Dept Psychol Hlth & Technol, Drienerlolaan 5, NL-7522 NB Enschede, NetherlandsHanze Univ Appl Sci, Res Grp Digital Transformat, Zernikepl 11, NL-9747 AS Groningen, Netherlands
Sanderman, Robbert
Oldenhuis, Hilbrand
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Hanze Univ Appl Sci, Res Grp Digital Transformat, Zernikepl 11, NL-9747 AS Groningen, NetherlandsHanze Univ Appl Sci, Res Grp Digital Transformat, Zernikepl 11, NL-9747 AS Groningen, Netherlands