AUXOLOGY – Studying Growth and Development

Michael Hermanussen (ed.) AUXOLOGY Studying Human Growth and Development With contributions by 56 internationally reputed experts Illustrated by Samson Goetze

2013. XII, 324 pp., with 283 ¿ gures and 89 tables 17 x 24 cm, hardcover

ISBN 978-3-510-65278-5 39.90.– € Information + : www.schweizerbart.com/9783510652785

This book is a comprehensive description of growth charts. National references (US, ARG, human physical growth and development BRA, CAN, IND, BEL, GER, IT, NL, PL, SW, (Auxology) with contributions by 56 interna- SWI, TUR, UK, WHO) for height, weight and tionally reputed experts. body mass index and head circumference for The entire spectrum of basic and advanced in- various countries are given as well as growth formation on growth tracking, growth predic- references for twins, preterm infants and syn- tion, short-term-, catch-up- and rapid growth, drome specific growth charts for clinical pur- nutritional and social factors influencing hu- poses. The book for the first time also contains man growth, and issues related to preventive references for height SDS changes, the mod- health care, growth in ethnic minorities and ern alternative to traditional growth velocity migrants, and growth in developing countries charts. is presented. The text is generously illustrated (283 color The book is of greatest interest to all pedia- figures and 89 comprehensive tables). It also tricians, to medical students and students of introduces new mathematical approaches human , health workers, nutritionists, to growth modelling and provides practical medical staff and professionals interested in information on how to use and to interpret child and adolescent growth and development.

Schweizerbart Publishers Johannesstr. 3A, 70176 Stuttgart, Germany. Tel. +49 (711) 351456-0 E Stuttgart Fax. +49 (711) 351456-99 [email protected] www.schweizerbart.de AUXOLOGY – Studying Human Growth and Development Contributors

Ghada M. Anwar, Cairo, Egypt Michael Hermanussen, Altenhof, Germany Emad Salama, Cairo, Egypt Christian Aßmann, Bamberg, Germany Reinhard Holl, Ulm, Germany Takashi Satake, Matsudo, Chiba, Japan Pavel Blaha, Prague, Czech Republic Eilin Jopp, Hamburg, Germany Christiane Scheffler, Potsdam, Germany Barry Bogin, Leicestershire, UK Maria Kaczmarek, Poznan, Poland Mithun Sikdar, Udaipur, Rajasthan, India Jesper L. Boldsen, Odense, Denmark Magdalena Skrzypczak, Poznan, Poland Kaspar Staub, Zurich, Switzerland Walter Bonfig, München, Germany Diana Mabel Kelmansky, Buenos Aires, Hans Henrik Thodberg, Holte, Denmark Marek Brabec, Praha, Czech Republic Argentina Jesus Angel Fernandez-Tresguerres, Fanny Breitman, Buenos Aires, Argentina Andreas Kersting, Bamberg, Germany Madrid, Spain Stef van Buuren, Leiden, The Netherlands Sylvia Kirchengast, Vienna, Austria Janina Tutkuviene, Vilnius, Lithuania Silvia Caino, Buenos Aires, Argentina Katja Zdešar Kotnik, Ljubljana, Slovenia Stanley Ulijaszek, Oxford, UK Noel Cameron, Leicestershire, UK Hans Lamecker, Berlin-Dahlem, Germany Maria Inês Varela-Silva, Leicestershire, UK Tim Cole, London, UK Andreas Lehmann, Luckenwalde, Germany Jerry K.H. Wales, Sheffield, UK Mortada El-Shabrawi, Cairo, Egypt Horacio Lejarraga, Buenos Aires, Argentina Ulrich Woitek, Zurich, Switzerland Mona El Housseiny, Cairo, Egypt Leslie Sue Lieberman, Oviedo, USA Cherie L. Yestrebsky, Orlando, USA Miranda Fredriks, Leiden, The Netherlands Matthew McIntyre, Orlando, USA Siegfried Zabransky, Homburg/Saar, Elena Godina, Moscow, Russia Jürgen Meier, München, Germany Germany Petra Golja, Ljubljana, Slovenia Christof Meigen, Bonn, Germany Stefan Zachow, Berlin-Dahlem, Germany Carl Martin Grewe, Berlin-Dahlem, Rebekka Mumm, Friedland, Germany Elzbieta Zadzinska, Lodz, Poland Germany Christina Papageorgopoulou, Komotini, Komei Hattori, Ibaraki University, Japan Greece Klaus-Peter Herm, Bad Oeynhausen, Tilman R. Rohrer, Homburg/Saar, Germany Germany Frank J. Rühli, Zurich, Switzerland

11.1 EFERENCES NATIONAL GROWTH R EFERENCES NATIONAL GROWTH R 11.1 Table 36: BELGIUM harmonised [after Roelants et al. 2009]. ARGENTINA harmonised Table 35: Height Weight BMI [after Lejarraga et al. 2009]. Age years mean SD p10 p50 p90 L M S Weight BMI 13.2 0.074 Height 0.001 s Age 0 50.0 2.0 2.8 3.3 3.9 -0.1 15.8 0.101 years mean SD p10 p50 p90 L M S 16.6 0.079 0.001 13.1 0.074 0.25 59.6 2.0 4.9 5.6 6.4 -0.3 0.101 16.7 0.083 0 49.3 1.8 2.7 3.2 3.8 -0.1 16.3 0.5 66.4 2.2 6.4 7.3 8.4 -0.5 16.7 0.080 59.8 2.1 5.0 5.8 6.9 -0.3 16.9 0.079 0.75 70.9 2.4 7.4 8.4 9.7 -0.6 0.25 0.085 5 16.7 0.083 1 74.7 2.5 8.1 9.3 10.7 .5 -1.0 16.3 0.5 65.7 2.3 6.2 7.3 8.6 -0.5 9.4 10.8 12 Sample page 16.3 0.080 81.4 2.8 9.4 10.8 12.5 -1.3 15.9 0.084 0.75 70.2 2.4 7.1 8.2 9.6 -0.66 1.5 4.0 0.085 10.6 12.1 1 5.8 0.076 1 74.0 2.6 7.7 8.9 10.5 -1.00 15.7 2 87.3 3.1 10.6 12.1 14.0 6.7 -1.4 1 0.084 12.42.4 14.3 1 15.6 0.079 1.5 80.7 2.9 8.8 10.2 12.0 -1.3.3 15.4 3 95.3 3.6 12.41 14.3 16.7 -1.4 15.8 0.076 19.2 -1.6 0.078 14.0 16.3 15.4 0.08 6 2 86.4 3.2 9.8 11.5 13.5 -1.5.5 15.7 4 102.4 4.1 14.0 16.3 19.2 -1.6 15.6 0.079 22.2 -1.8 0.082 15.8 18.5 15.4 0.097 3 95.0 3.9 12.2 14.2 16.6 -1.8.8 15.9 5 109.5 4.6 15.8 18.5 22.2 -1.8 15.4 0.086 25.3 -1.9 0.0890 089 17.4 20.7 15.5 0.110 EIGHT PREDICTION 4 101.2 4.5 14.1 16.3 19.2 -1.9.9 15.9 6 116.4 4.9 17.4 20.7 25.3 -1.9 15.4 0.097 29.2 -1.9 FINAL H 0.0910 091 19.4 23.4 15.9 0.12 2 5 106.7 4.8 15.5 18.1 21.4 -2.02.00 15.7 7 123.0 5.3 19.4 23.4 29.2EIGHT -1.9 15.5 P 0.110REDICTIONS33.8 -1.9 Thodberg [personal communication 201 0.1020 102 FINAL H 21.8 26.6 16.4 0.133 6113.05.117.020.124.2-1.9.99 15.9 8 129.0 5.6 21.8 26.6 33.8 -1.9 15.9 0.122 38.6 -1.9 In contrast to the metric scales for height (cm) 5.40.107 24.2 29.8 16.9 0.14 2 posed to use bone age SD scores instead. 7 118.8 5.5 18.8 22.5 27.6 -1.71.77 16.4 9 134.3 6.0 24.2 29.8 38.6 -1.9 16.4 0.133 44.0 -1.7 0.112 4 26.7 33.3 17.5 0.147 and physical time (years) there is no apparentis not a 8 124.1 6.1 20.8 25.2 31.4 -1.61.66 16.9 10 139.9 6.4 26.7 33.3 44.0 -1.7 16.9 0.142 50.2 -1.6 bone age 0.1195 B-P 29.6 37.5 18.1 0.149 metric scale for maturation ( Differences in developmental tempo a 9 129.2 6.7 22.9 28.2 35.5 -1.51.55 17.4 RWT 197511 146.63.5 6.9 29.6 37.5 50.2 -1.6 17.5 0.147 56.6 -1.5 but relates 0.124 33.2 42.3 18.8 0.148 metric scale for developmental tempo uncertainty of the moment when pubert 10 134.6 7.3 25.4 31.5 40.0 -1.41.44 18.0 4 RWT (MCSS)12 153.2 7.13 33.2 42.3 56.6 -1.5 18.1 0.149 61.9 -1.5 0.138 TW‘75(+MPS) 37.4 47.1 19.5 0.14 3 to calendar age). Hewitt and Acheson [1961a,b] 11 140.6 7.6 28.5 35.6 45.4 -1.31.33 18.7 3 13 158.72.5 6.9 37.4 47.1 61.9 -1.5 18.8 0.148 66.2 -1.4 inflate height variance so that the associa 0.139 TW‘83 (3v) including 42.0 51.5 20.2 0.13 9 12 147.0 7.2 32.5 40.5 51.4 -1.31.33 19.4 2 14 162.4 6.52 42.0 51.5 66.2 -1.4 19.5 0.143 69.3 -1.4 introduced a scoring system, and found a more tween actual height and final height d 0.128 parents 45.5 54.9 20.8 0.136 Ź5.3 Adolescent Growt 13 152.9 6.7 36.8 45.2 56.7 -1.33 19.8 1 15 164.7 6.2 45.5 54.9 69.3 -1.4 20.2 0.139 71.8 -1.5 rapid increase in unweighted bone scores at pu- during puberty ( 0.116 1.5 47.9 57.2 21.1 0.135 even persists w 14 157.2 6.3 40.6 48.9 60.2 -1.33 20.1 16 165.8 6.0 47.9 57.2 71.8 -1.5 20.8 0.136 73.4 -1.5 berty than before. Based on similar considera- The pubertal uncertainty 0 1 including49.1 58.5 21.4 0.13 7 -1.22 20.4 0.110 17 166.2(cm) error RMS 6.0 49.1 58.5 73.4 -1.5 21.1 0.135 74.1 -1.6 15 159.6 6.1 43.3 51.3 62.3 -1 0.5 menarche49.8 59.2 tions Tanner and co-workers developed an alter- endar time is replaced by biological tim -1.22 20.5 0.110 18 166.3 6.0 49.8 59.2 74.1 -1.6 21.4 0.137 Tanner-Whitehouse (TW) skeletal 16 160.5 6.1 44.7 52.5 63.3 0.085 native system ( 101). This is counterintuitive. Everybod

mean residuals (cm) residuals mean 0.105-2 0 13.6 17 160.7 6.1 45.4 53.1 63.9 -1.11 20.7 0.001 assessment system) based on 20 bones -3 6 8 10 12 14 16 182.9 3.5 4.1 16.4 0.077 maturity expect that the prediction error when 18 160.7 6.1 45.8 53.4 64.2 10 11 12 13 14 15 0 50.7 2.1 2.9 3.5 4.1 bone age (years) -0.1 0.085 9 5.3 6.1 7.0 17.1 0.079 [Tanner et al. 1962]. The TW system defines a would decrease as the ta 0.001.0011 13.2 0.25 61.0 2.2 5.3 6.1 7.0 -0.2 summed ma- biological age bone age (years) 6.9 7.9 9.0 0.091 1 16.9 0.077 0.5 67.9 2.3 6.9 7.9 9.0 4 -0.3 17.3 score to each stage, from which a is final height) is approached. But this 0 50.0 1.8 2.8 3.3 3.9 -0.1 , Figure 101: The observed7.9 9.1 10.root mean square 0.079 72.6 2.4 7.9 9.1 10.4 -0.4 17.2 0.086 (SMS) was formed ranging from 0 0.25 61.4 2.1 5.4 6.4 7.4 -0.22 17.4 Mean error of Bayley-Pinneau0.75 .4 turity score case. Figure 100: (RMS) error of height prediction.8.7 10.0 11 The lower lines 16.8 0.087 later defined 67.6 2.2 6.9 7.9 9.1 -0.33 17.2 0.091 [Roche et al. 1975], Tan-1 76.3 2.5 8.7 10.0 11.4 3.2 -0.6 (immature) to 1000 (adult). Tanner 0.5 10.1. 11.5Dashed 1 line includes 16.8 Roche-Wainer-Thissen0.086 include82.7 2.8 parental 10.1 11.5 13.2height -0.7 16.1 0.084 0.75 72.0 2.2 7.8 8.9 10.2 -0.44 height predictions in Turkish1.5 4.5 a 13-bone system called RUS (radius, ulna, and Also the signs of sexual maturation ner-Whitehouse0.087 menarche. There is a11.0 characteristic 12.6 1 plateau in 5.9 0.075 1 75.7 2.4 8.4 9.6 11.1 -0.66 16.4 2 88.4 3.1 11.0 12.6 14.5 7.2 -1.9 1 short bone) (TW2 [Tanner et al. 1975]) and girls0.084 [after Onat 1995]. 12.9 14.8 1 15.6 0.07 8 used for predictions: pubic hair (PH) s 1.5 81.8 2.6 9.5 10.9 12.6 -0.77 15.8 3 both96.3 sexes, 3.6 12.9 and 14.8 a 17.2mild -1.9 maximum 15.9 0.075 in the predic-19.7 [after -2.0 0.071 14.6 16.8 15.5 0.08 2 showed that mean maturity score increments per curs when about 86% of final height 2 87.8 2.9 10.5 12.2 14.1 -1.00 15.8 4 tion103.5 error 4.114.6 shortly 16.8 after 19.7 -2.0peak 15.6 height 0.078 velocity22.4 -2.2 0.072 16.2 18.8 15.4 0.08 8 chronological year differed throughout child- reached in girls, and about 85% in boy 3 96.4 3.4 12.6 14.6 17.1 -1.22 15.9 5 Thodberg110.3 4.5 16.2 2012]. 18.8 22.4 -2.2 15.5 0.082 25.5 -2.3 0.075 18.0 21.1 15.5 0.09 6 hood and adolescence, with sharp increments/ curs when about 91% in girls, and 89 4 102.6 4.0 14.3 16.7 19.7 -1.44 16.0 6 117.2 4.9 18.0 21.1 25.5 -2.3 15.4 0.088 29.1 -2.4 0.081 20.0 23.6 15.8 0.10 4 yr of RUS scores during mid- and end-pubertal 5 107.9 4.5 15.8 18.7 22.2 -1.66 15.9 7 123.8 5.2 20.0 23.6 29.1 -2.4 15.5 0.096 33.3 -2.4 TW3) PH4 occurs when 94% in girls and 92 0.092 22.2 26.5 16.1 0.11 3 6 114.2 4.8 17.4 20.7 25.0 -1.77 16.0 8 129.9 5.5 22.2 26.5 33.3 -2.4 15.8 0.104 37.9 -2.4 age. A further refinement of this method ( and PH5 occurs when 97% in girls 0.098 24.6 29.6 16.6 0.12 2 7 120.2 5.1 19.3 23.1 28.1 -1.88 16.2 9 135.4 5.8 24.6 29.6 37.9 -2.4 16.1 0.113 1930-3442.9 -2.4 was published by Tanner et al. [2001]. Maturi- 95% of final height has been achieve 0.102 180 27.0 32.9 1935-39 17.0 0.129 may be used 8 125.9 5.4 21.3 25.7 31.6 -1.99 16.6 10 140.5 6.1 27.0 32.9 42.9 -2.4 16.6 0.122 47.9 -2.4 ty scores exhibit significant gender dimorphism, I.e. the Tanner stages 0.10816 175 29.6 36.4 1940-44 17.6 0.133 Fels bone 9 131.1 5.8 23.6 28.6 35.5 -1.99 17.2 11 145.8 6.5 29.6 36.4 47.9 -2.4 17.0 0.129 1945-4954.0 -2.4 32.8 40.8 18.2 0.135 with girls scoring earlier than boys. The height prediction [Onat 1983], but -1.99 17.8 0.112 12 152.0 7.0 32.8 40.8 54.0 -2.4 17.6 0.133 1950-5461.0 -2.3 Me 10 135.8 6.2 25.9 31.7 39.7 170 36.5 46.1 5 age method [Roche et al. 1988] is similar to the 18.5 0.11712 13 158.8 7.6 36.5 46.1 61.0 -2.3 18.2 0.135 1955-59 -2.2 18.8 0.13 prevailed in the clinical routine. 11 140.3 6.8 28.3 35.0 44.4 -1.88 1960-6468.9 0.119 165 41.3 52.5 TW method, but involves more bones, more ma- often been used to predict height, bu 12 145.4 7.5 31.1 39.1 50.0 -1.88 19.3 14 166.0 7.8 41.3 52.5 68.9 -2.2 18.8 0.135 1965-6975.1 -2.2 19.5 0.132 46.9 58.5 1970-74 20.1 0.128 turity features, and more advanced mathematics; -1.77 20.1 0.1228 15 171.9160 7.7 46.9 58.5 75.1 -2.2 19.5 0.132 79.0 -2.1 is too simplistic: the association is gen 13 151.5 8.2 34.8 44.3 56.8 51.6 62.8 1975-79

0.117 (cm) height 20.6 0.124 it is laborious and less common than the Greu- 14 158.4 8.4 39.5 50.5 64.2 -1.66 20.9 16 175.8155 7.3 51.6 62.8 79.0 -2.1 20.1 0.128 1980-8481.6 -2.0 short girls tend to add more centimet 0.115 54.9 65.9 21.0 0.120 /Bayley-Pinneau, and the TW2 method. 15 164.6 8.2 44.7 56.5 70.6 -1.66 21.2 4 17 178.1150 7.0 54.9 65.9 81.6 -2.0 20.6 0.124 1985-8883.5 lich-Pyle girls (Figure 102); and late maturing menarche (cm) menarche 57.2 68.0 models are -1.66 21.5 0.115 18 179.4 6.9 57.2 68.0 83.5 -2.0 21.0 0.120 Yet, none of these height prediction end up taller [Onland-Moret et al. 2

16 169.1 7.7 48.9 60.8 74.5 at height remaining 21.7 0.117 145 17 171.7 7.2 51.8 63.3 76.4 -1.55 0 170 175 8 10121416182022 perfect; the models differ markedly in accuracy 103). The association between me 150 155 160 165 indicate syntheticmenarche valuesvalues (year) 18 172.7 6.9 53.6 64.8 77.5 140 145 Green numbers [Onat 1995] (Figure 100). maturation does not hold true in h height at menarche (cm) | Brown numbers indicatedicate WHO values The association between final height tings where menarche may be exc indicate synthetic values Figure 103: Ź5.3 Green numbers The remaining height growth after in over 70,000221 Iceland Unfortunately, all scoring methods turn the scores [Hermanussen et al. 2012b] ( Figure 102: and menarcheal age Michael H for skeletal maturity back into male and female of Menarcheal Age). Ŷ menarche in girls of different height [after Thod- women born between 1930 and 1988. Both the 220 bone ages, muddling up calendar age, and mean berg 2012]. secular increase in stature, and the growth ad- population versus individual progress in matura- vantage in late menstruating women are visible tion. This uncomfortable semantic confusion still Final height predictions shoul [data provided by courtesy of Laufey Tryggvadót- persists [Hermanussen 2010]. Determining an formed before the expected on tir, and Tryggvadóttir et al. 1994]. individual’s bone age usually causes no prob- berty, i.e. at BA < 12 in boys lems per se, but problems arise when describ- 10.5 in girls, and there is little ra ing bone age progression. Maturity scores¬bone ad- repeating a final height predic vance with age. But simple ratios such as puberty. that have often been age/¬chronological age used in paediatric , ignore that the metric of physical time differs from the internal dynamics of growth, that is the progress in matu- rity scores. These ratios cause awkward and age- dependent artefacts and should be questioned.

87

86 AUXOLOGY – Studying Human Growth and Development

Contents 1. Introduction 6. Prevention and Health 9. Statistical Approaches 1.1 Some Initial Remarks . . . . . 1 6.1 Breast Feeding ...... 90 9.1 Statistics for Bunnies . . . . . 176 1.2 A Short Introduction to 6.2 Infant, Toddler and Child 9.2 Growth Velocity ...... 178 Growth ...... 2 ...... 92 9.3 SDS and LMS...... 182 6.3 Short and Tall Stature. . . . . 98 9.4 Synthetic Growth Charts . . 184 2. Basics 6.4 Primary Growth Failure . . . 102 9.5 Harmonising National 2.1 Growth References and 6.5 Secondary Growth Failure 104 Growth Charts ...... 186 Growth Charts ...... 4 6.6 SGA and IUGR ...... 106 9.6 Stability and Instability in 2.2 Tempo and Amplitude . . . . 8 6.7 The Shortest People: Peri- hSDS Changes ...... 188 2.3 Short Term Growth and centrin mutations...... 108 9.7 Jump Preserving Smoothing Mini Growth Spurts ...... 10 6.8 Growth in Diabetic Patients 110 Technique ...... 190 2.4 Periodicity in Growth . . . . 12 6.9 Body Proportions in Rela- 9.8 Rounding-Off and Heaping 192 2.5 Growth Tracking ...... 14 tion to Health ...... 112 9.9 Parametric and Non-Param- 2.6 Catch-up Growth...... 16 6.10 Social Determinants of etric Regression Models . . . 194 2.7 Rapid Growth ...... 18 Health ...... 114 9.10 Landmark based Statistical 2.8 The Growth Plate...... 20 6.11 Migrants...... 116 Shape Analysis...... 200 2.9 Growth Hormone ...... 24 6.12 Childhood Obesity in 9.11 A Bayesian Approach 2.10 Negative Growth ...... 26 Developing Countries . . . . 118 towards Modelling Growth 204 6.13 Childhood Obesity: The 9.12 Methods that still Lack 3. Body Shape, Composition and Impact of Migration ...... 120 Adequate Recognition . . . . 206 Proportions 6.14 PEM in Children: Anthropo- 3.1 Types of Body Shape . . . . . 28 metric Evaluation...... 122 10. Miscellaneous 3.2 Body Composition ...... 30 6.15 Nutrition Transition in 10.1 Geometry and Auxology . . 208 3.3 Determining Body Composi- Developing Countries . . . . 124 10.2 Finger Length Ratios...... 210 tion in Field Studies ...... 32 6.16 How Good is the BMI for 10.3 Patents in Auxology ...... 212 3.4 Body Size, Somatotype and Detecting Obesity?...... 126 10.4 Myths, Tales and Beliefs . . 214 Sports...... 34 6.17 Comments on Obesity . . . . 128 3.5 Fluctuating Asymmetry . . . 36 6.18 Growth and Pollutants . . . . 130 11. Reference Values 11.1 National Growth Referen- 4. From birth to maturity 7. Auxology of the Past ces...... 218 s 4.1 Comparative Biology and 7.1 A Short of the Study 11.2 References for Preterm Human Life History ...... 38 of Human Growth ...... 132 Infants and Twins...... 234 4.2 Foetal Programming and 7.2 Secular Trends ...... 138 11.3 Syndrome Specific Growth Epigenetics...... 42 7.3 Trends in Amplitude and Charts ...... 244 5.4 4.3 Biological Age ...... 44 Tempo ...... 140 11.4 References for Growth 2] pro- . 4.4 Variation in Tempo ...... 48 7.4 How to Plot Secular Growth Velocity ...... 248 and the ty starts, 4.5 Twins...... 50 Changes...... 142 11.5 References for SD Score ation be- decreases th Spurt). 4.6 Very Low Birth Weight 7.5 The History of Menarcheal Changes...... 256 when cal- me (Figure Children ...... 52 Age ...... 144 11.6 References for Tempo, dy would based on arget (that 4.7 Failure to Thrive during the 7.6 Impact and Pitfalls of Timing and Puberty ...... 258 is not the First 2 Years ...... 54 Conscription Data ...... 146 11.7 References for Sitting n can be stage 2 oc- 4.8 Signs of Sexual Maturation 56 7.7 Conscript Height ...... 150 Height ...... 262 t has been ys; PH3 oc- 4.9 Timing Puberty by Stage 7.8 Long Term Changes in Head 11.8 Body Proportion Chart . . . . 264 % in boys; 2% in boys; and about Line Diagrams ...... 60 Dimensions ...... 152 11.9 References for MUAC, BF ed in boys. to improve 4.10 Menarcheal Age in Egypt . . 62 7.9 Harris Lines ...... 154 and Skinfold Thickness . . . 266 have never enarche has ut this vision 4.11 Adolescent Growth Spurt. . 64 7.10 Growth and Death in the 11.10 References for WC and nerally poor, tres than tall 4.12 Body Image and Body Size Past ...... 156 WHR ...... 270 girls tend to 2005] (Figure enarche and during Puberty ...... 66 11.11 References and Equations historical set- cessively late 4.13 The Community Effect on 8. Auxological Methods for Body Composition . . . . 272 3 The History Hermanussen Growth ...... 68 8.1 Requirements for Anthropo- 11.12 Body Surface and Ambigu- d be per- 4.14 The Community Effect in metric References ...... 158 ous Genitalia ...... 276 nset of pu- and BA < ationale for Swiss Conscripts ...... 72 8.2 Measurement Error in 11.13 References for IGF1 and tion during ...... 160 IGFBP3 ...... 278 5. Height Predictions 8.3 Standardised Measurements 5.1 Final Height...... 74 162 12. Glossary ...... 281 5.2 A Flow Chart to Final 8.4 Daily Home-Made Measure- 13. Literature and Internet Height Prediction...... 76 ments...... 164 Resources ...... 295 5.3 Target Height...... 78 8.5 Automated Bone Age Deter- 14. Index...... 319 5.4 Final Height Prediction . . . 82 mination ...... 166 5.5 Factors that Influence Bone 8.6 Knemometry ...... 168 Ageing ...... 88 8.7 Testing for Hormone Deficiency ...... 174 AUXOLOGY – Studying Human Growth and Development

11.3 SYNDROME SPECIFIC GROWTH CHARTS SYNDROME SPECIFIC GROWTH CHARTS 11.3

Short stature is a recognised feature of many dys- outdated, and were obtained from biased sam- morphic syndromes . Growth reference charts have ples. A lot of data was published before these Table 58: Prader-Willi syndrome [Hauffa et al. 2000]. been published for many syndromes of which a syndromes were genetically defined. I.e. the small number will be presented here. Some of charts were derived from patients who looked Age Height Weight BMI these charts have been published as tables, most like that syndrome. We therefore limit this chap- years MSDL M S L M S as smoothed charts. In general, syndrome specific ter to a spectrum of published syndrome specific 1 70.1 4.9 -0.07 7.4 0.20 -0.84 14.9 0.11 growth charts give mean values and centiles for growth charts that have been clinically used in 2 80.2 5.5 -0.07 11.0 0.21 -0.84 16.2 0.13 height. Some charts also provide information on the past. We strongly recommend high levels of 3 89.0 6.0 -0.07 14.2 0.23 -0.84 17.3 0.14 weight and BMI. Some relate to national referenc- scepticism when using these charts. Particularly 4 96.4 6.4 -0.07 17.4 0.24 -0.84 18.4 0.16 es (e.g. Figure 253). References for head circum- Turner syndrome patiences have been shown to 5 103.0 6.6 -0.07 20.9 0.26 -0.84 19.5 0.17 ference have been published for children with exhibit significant variation in the dysmorphic 6 109.0 6.8 -0.07 24.2 0.27 -0.84 20.3 0.19 Down syndrome [Styles et al. 2002]. features with many patients who grow and devel- 7 114.7 7.0 -0.07 27.4 0.28 -0.84 21.0 0.20 op well within the range of normal girls. 8 120.1 7.2 -0.07 30.4 0.29 -0.84 21.7 0.21 Syndrome specific growth charts suffer from a Ŷ Michael Hermanussen 9 125.2 7.3 -0.07 33.7 0.30 -0.84 22.3 0.23 10 130.2 7.3 -0.07 37.6 0.31 -0.84 23.0 0.24 number of serious drawbacks. Many charts are 11 135.0 7.4 -0.07 42.6 0.32 -0.84 23.9 0.25 12 139.3 7.4 -0.07 48.5 0.32 -0.84 24.9 0.26 Table 57: Silver-Russell 13 143.0 7.3 -0.07 54.9 0.32 -0.84 26.2 0.27 Table 56: Turner syndrome [Rongen-Westerlaken et al. 1997]. syndrome [Wollmann et al. 14 145.8 7.2 -0.07 61.5 0.32 -0.84 27.5 0.28 Age Height Weight 1995]. 15 147.6 7.0 -0.07 67.7 0.32 -0.84 28.9 0.28 years mean SD - 2SD + 2SD mean - 2SD + 2SD Age Height 16 148.4 6.8 -0.07 73.1 0.32 -0.84 30.3 0.29 years mean SD 17 148.5 6.5 -0.07 77.6 0.31 -0.84 31.7 0.29 0 47.6 2.5 42.6 52.6 3.0 2.1 4.3 18 148.3 6.2 -0.07 81.2 0.30 -0.84 33.0 0.29 0.25 56.4 2.6 51.2 61.6 4.4 3.2 6.0 2 73.0 5.0 19 148.3 5.8 -0.07 83.9 0.29 -0.84 34.1 0.29 0.5 62.2 2.6 57.0 67.4 5.8 4.3 7.9 3 79.2 5.4 20 148.6 5.5 -0.07 85.8 0.28 -0.84 35.2 0.29 0.75 7.2 5.4 9.6 4 1 69.9 2.8 64.3 75.5 8.4 6.4 11.0 5 91.0 6.1 1 70.2 5.0 0.15 7.4 0.24 -0.71 15.1 0.15 1.5 76.1 2.9 70.3 81.9 9.8 7.6 12.6 6 96.6 6.4 2 80.2 5.6 0.15 11.0 0.25 -0.71 16.3 0.16 2 80.6 3.1 74.4 86.8 10.6 8.5 13.2 7102.06.6 3 88.8 6.0 0.15 14.3 0.25 -0.71 17.4 0.16 Sample pages 3 87.6 3.4 80.8 94.4 12.2 9.7 15.3 8107.26.8 4 96.2 6.3 0.15 17.6 0.26 -0.71 18.4 0.17 4 93.7 3.7 86.3 101.1 13.7 10.6 17.7 9112.26.9 5 102.8 6.6 0.15 21.0 0.26 -0.71 19.3 0.18 5 99.3 3.9 91.5 107.1 15.44.9 11.7 20.3 10T 117.0IMING P 7.0UBERTY BY STAGE LINE DIAGRAM6 108.9 6.7 0.15TIMING 24.3 P 0.26UBERTY -0.71 BY STAGE 20.1 LINE 0.18 DIAGRAM 4.9 6 104.5 4.2 96.1 112.9 17.3 12.9 23.2 11 121.6 7.1 7 114.8 6.8 0.15 27.6 0.26 -0.71 20.8 0.19 7 109.5 4.4 100.7 118.3 19.3 14.2 26.4 12 126.0 7.1 8 120.7 6.9 0.15The 31.0 developmental 0.26 progress -0.71 of puberty 21.5 is a con- 0.19stage line diagram: an age-conditional reference 13 130.2 7.0 9 126.8 7.0 0.15 34.9 0.26 -0.71 22.2 0.19 8 114.1 4.6 104.9 123.3 21.6 15.6 29.9Table 7: Reference values (%) for pubertal development in boys. tinuous process. But it is difficult to precisely of breast development (B1– B5). The horizontal 14 134.2 6.9 10 132.8 7.0 0.15 39.8 0.26 -0.71 23.0 0.20 9 118.5 4.8 108.9 128.1 24.0 17.2 33.6 track continuity. Instead we describe the progress axis indicates age. The vertical axis indicates 15 138.0 6.8 11 138.8 7.0 0.15 45.5 0.26 -0.71 24.0 0.20 10 122.5 5.0 112.5 132.5 26.6Age 18.9 37.4 Genitalia Pubic Hair Testicular volume in puberty by 5 developmental stages – genitals maturation status as SDS correcting for age. Low- 11 126.3 5.2 115.9 136.7 29.3 20.7 41.4 16 141.5 6.6 12 144.4 7.0 0.15 51.7 0.26 -0.71 25.0 0.20 years G2 G3 G4 G5 PH2 PH3 PH4 PH5 4 ml 8 ml 12 ml 15 ml 20 ml (boys), pubic hair (boys and girls), and female er values indicate delayed, higher values early 12 129.7 5.4 118.9 140.5 32.1 22.7 45.5 13 149.2 6.9 0.15 57.8 0.25 -0.71 26.1 0.19 2 75.1 4.8 14 153.0 6.8 0.15breast 63.3 (Ź4.8 Signs 0.24 of Sexual -0.71 Maturation 27.1, pages 0.19 maturation. The diagram contains 5 stage lines 13 132.8 5.5 121.8 143.8 34.98.0 24.6 11.5 49.5 1.1 3.2 7.2 1.8 0.1 3 81.0 4.9 15 155.6 6.6 0.1558 – 68.1 61, Tables 0.24 4 – 6). Menarche -0.71 can 28.0 be staged 0.19 each corresponding to one of the 5 Tanner stag- 14 135.7 5.7 124.3 147.1 37.78.5 26.6 14.9 53.3 1.5 5.3 0.0 9.7 2.4 0.2 4 16 157.3 6.4 0.15 72.3 0.23 -0.71 28.9 0.18 15 138.2 5.8 126.6 149.8 40.39.0 28.6 18.8 56.9 1.9 8.3 0.1 12.8 3.2 0.3 (yes/no), and testicular volume can be estimat- es . The observer marks the child’s stage B1– B5 5 92.3 5.2 17 158.2 6.1 0.15 76.0 0.22 -0.71 29.8 0.17 16 140.4 6.0 128.4 152.4 42.89.5 30.4 23.1 60.1 2.5 12.4 0.2 16.4 4.1 0.7 ed in millilitres using the orchidometer [Prader on the stage line corresponding to the child’s age, 6 97.7 5.4 18 158.6 5.8 0.15 79.1 0.20 -0.71 30.5 0.16 17 142.3 6.1 130.1 154.5 44.910.0 32.1 28.5 62.8 3.3 0.0 17.7 0.7 21.9 5.4 1.2 0.0 0.0 1966]. References of maturation are typically and connects the mark to the previous measure- 7103.05.6 19 158.8 5.5 0.15 81.8 0.19 -0.71 31.2 0.15 18 143.9 6.2 131.5 156.3 46.710.5 33.6 34.9 64.8 4.9 0.1 24.8 1.9 0.0 0.0 30.1 7.5 2.1 0.2 0.1 published as age p10, p50 and p90 at which ment. The curve gradually tails off as long as the 8108.15.8 20 159.1 5.3 0.15 84.3 0.18 -0.71 31.9 0.14 adult 146.9 6.4 134.1 159.7 11.0 42.0 7.8 0.3 33.5 4.3 0.2 0.1 40.0 10.9 3.7 0.6 0.2 respectively, 10, 50 and 90 percent of the pop- child remains in the same stage. A move to the 9113.06.1 11.5 52.0 13.2 1.2 0.0 44.4 9.1 0.7 0.3 53.2 17.1 6.7 2.0 0.5 10 117.8 6.3 ulation achieve a certain pubertal stage. In clin- next stage produces a jump in the curve. The age 12.0 66.5 22.9 3.7 0.2 58.0 18.9 3.1 0.8 69.0 27.7 12.1 5.0 1.3 11 122.4 6.6 ical practice, the physician examines the child, at which the child reaches the next stage is un- 12.5 80.8 37.1 9.7 0.9 72.4 34.9 10.0 2.4 81.3 42.3 20.5 10.6 2.9 determines the stage appropriate for that child, known, and can be anywhere between the two 13.0 90.5 54.1 20.512 3.2 126.9 84.1 53.4 6.9 23.1 6.1 89.0 58.4 31.99 19.1 6.1 13.5 95.8 70.0 35.513 8.4 131.2 91.6 69.6 7.2 40.5 13.0 93.8 73.3 45.223 30.00.0 11.6 andand compares the chichild’sld’s age to the ‘norma‘normal’l’ age aagesges surrounding the jump. Steeper jumps occur 14.0 98.3 82.0 52.314 17.0 135.3 95.9 81.9 7.6 58.7 23.2 97.2 84.9 59.11 42.1 19.6 rangerange p10 – p90 for that stastagege (Tab(Tablesles 7, 8). This fforor measurements that are ccloserloser in time. Jumps 14.5 99.3 89.7 67.715 28.5 139.3 98.0 89.9 7.9 74.8 36.1 99.1 92.1 71.99 54.7 29.5 procedureprocedure answers the question doesdoes thisthis childchild ccanan span two or more stages. Curves of normallynormally 15.0 99.7 94.4 79.616 41.7 143.1 98.9 94.7 8.3 86.5 50.8 99.8 95.9 82.33 67.1 40.5 4.3 mature ‘early’, ‘normal’ or ‘late’?? and worksB IOLOGICALwell ddevelopingeveloping A chichildrenGEldren are llocatedocated roughroughlyly between BIOLOGICAL AGE 4.3 15.5 99.9 97.1 87.8 54.6 99.4 97.3 93.1 65.1 100.0 97.9 89.22 77.6 50.9 ifif onlyonly a cclassificationlassification into ‘ear‘early’ly’ vs ‘norma‘normal’l’ vs –2 SDS and +2 SDS. EarEarlyly maturing chichildrenldren are 16.0 100.0 98.5 92.9 64.6 99.6 98.7 96.4 75.9 98.9 93.11 84.6 58.9 ‘late’‘late’ is needed. But it llacksacks any sense of continucontinu-- plplacedaced near the top, llateate maturinmaturingg chichildrenldren near Biological age refers to the state of maturation or It is the biological, rather than the calendar age Table 3: Change of proportions from birth to 18 years [Greil 2007]. 24416.5 99.2 95.8 70.8 99.8 99.4 98.0 82.9 99.4 95.11 88.7 64.1 ityity 245between ‘ear‘early’ly’ and ‘‘late’.late’. the bottom of the diagram. Diagrams for sexuasexuall the degree of physical development of a human that is determined in paediatric screening inves- 17.0 99.6 97.3 74.5 99.9 99.7 98.8 87.4 99.7 96.11 90.6 66.9 Age ThI PSI RFL ScI ThI PSI RFLmmaturationaturation ScI are avaiavailablelable at Źhttp://vps.stefvan- organism. The tempo at which the biological age tigations, in forensic , and in physical 17.5 99.7 98.1 77.2 99.9 99.9 99.3 90.9 99.9 96.66 91.3 68.2 StageStage lineline ddiagramsiagrams [van Buuren & OomsOoms 2009, buuren.nl/pubertybuuren.nl/puberty. FigureFigure 75 shows a combined of an individual proceeds can differ from the pro- education, when identifying the position of a par- 18.0 99.8 98.7 80.4 100.0 100.0 99.7 93.5 99.9 97.00 91.7 69.1 0 92.3 72.8 46.1 49.3 92.2 72.6 45.5 50.1 vanvan Buuren 2013] modemodell the probability of the sstagetage llineine diadiagramgram for breast and pubic hair de- gress in calendar age; it depends on sex, type of ticular child in regard to height, dentition, sexual 1 75.5 72.8 41.8 56.1 75.8 72.6 41.4 56.7 transitiontransition betweenbetween successive categoriescategories, in vevelopmentlopment and menarche. Stef van BuurenBuuren body shape , , ethnicity, and environmen- maturation, cognition abilities etc., among the 2 74.6 73.0 40.0 64.0 74.3 72.7 39.5 64.8 Ŷ tal factors [Buckler 1979]. others. 3 73.3 74.1this 38.0 case, successive 71.5 stages 72.8 of puberty. 73.7 They relyrely 37.4 72.5 Table 8: Reference values (%) for pubertal development in girls. 4 72.7 74.1onon 36.5the assumption 73.5 that the 72.1 progressprogress 73.7 of puberty 36.0 77.4 5 72.2 73.8continuouslycontinuous 35.6ly advances 79.2 with 71.9 age, and 73.5 that the 35.0 SStagetag 80.2e llineine diagramsdiagrams provide quick insiinsightsghts Girls grow up and develop faster than boys Height age is an age defined by height. Taller Age Breast Pubic Hair Menarcheche 6 71.9 73.1observedobserved 34.9 data 81.5are manifestations 71.5 of 72.9an underly-underly 34.4- iintonto 82.6both status (in SDS) and tempo (in during childhood and puberty. On average, children tend to be older. But the term is mislead- years B2 B3 B4 B5 PH2 PH3 PH4 PH5 7 71.6 72.6inging 34.4variabvariable,le, which 83.6 are linkedlinked 71.3 through 72.5 a series of 33.9 SSDS/year)DS/year) 84.3 at which the individuaindividuall ppuber-uber- puberty starts some 2 years earlier than in boys, ing and should be abandoned. Body proportions 8 71.5 72.4 33.8 85.6 71.3 72.5 33.3 86.7 and girls tend to reach final height earlier. The are more sensitive for estimating the progress in 8.0 2.1 0.0 1.8 0.55 additiveadditive modelsmodels with a probiprobitt link, one for each tatall developmentdevelopment progresses.progresses. They exexpresspress 9 71.4 72.3 33.3 88.0 71.2 72.5 32.8 89.0 8.5 4.9 0.2 3.5 0.0 0.66 categorycategory transition. In this modemodel,l, the transition sstatustatus and tempo of discrete changeschanges on a progress in biological age is also influenced by maturation (Figures 56, 57). 10 71.2 72.3 33.0 90.3 70.9 73.0 32.4 90.8 9.0 10.3 0.5 0.0 6.8 0.2 0.0 0.88 probabilityprobability to go from one category to the next ccontinuousontinuous scale.scale. body shape: pyknomorph children of both sex- 11 71.0 72.4 32.6 92.3 70.6 73.7 32.1 91.8 9.5 18.9 1.6 0.1 12.5 0.9 0.2 0.0 1.11 smoothlysmoothly changeschanges with age. FFigureigure 7744 is such a es tend to develop faster and achieve puberty Proportional age defines the biological age by the 12 70.9 72.6 32.4 93.7 70.5 74.9 31.7 92.6 10.0 29.5 4.2 0.3 0.0 20.8 3.0 0.6 0.1 1.66 and maximum height up to 2 years earlier than change of head – trunk – extremity proportions 13 70.8 72.9 32.0 94.8 70.5 75.9 31.2 92.6 10.5 43.0 9.7 1.2 0.2 33.4 8.3 1.9 0.4 2.44 14 70.3 72.9 31.4 95.4 70.3 77.1 30.8 91.8 the leptomorph. Differences in biological age (Ź8.3 Standardised Measurements). Particularly in 11.0 59.7 20.0 4.2 0.7 49.6 19.1 5.2 1.2 4.11 15 69.9 73.0 31.13.3.00 94.9 70.0 77.8 30.5 91.1 between ethnicities are caused both by envi- younger children, the increase in body length large- 11.5 75.3 35.1 11.0 2.1 65.3 35.3 12.5 3.5 7.99 BreastBreast 16 69.5 72.6 30.9 94.1 70.0 78.2 30.4 90.5 ronmental (socioeconomic) and genetic fac- ly reflects the increase in leg length. The differential 12.0 87.1 53.8 22.6 5.3 79.7 54.4 25.4 8.4 15.33 2.0 22.0.0 PubicPPbiHiubic HHairair 17 69.2 72.0 30.9 93.1 70.0 78.5 30.4 90.0 tors. The recent improvements in living con- dynamics of long bone, rump and head growth is 12.5 94.3 73.2 38.3 11.1 90.4 72.5 43.0 17.0 27.77 11.0.0 11.0.0 MenarcheMenarche 18 69.9 71.3 30.9 92.3 70.0 78.6 30.5 89.6 ditions have led to an increase in the rate at nicely illustrated by the so called Philippine meas- S 13.0 97.6 87.5 55.6 19.9 95.9 85.8 60.8 29.1 43.99 S B5B5 D 0.0 D 00.0.0 which children and adolescents mature (Ź7.2 ure (Figure 58), a historic criterion of maturity that

13.5 98.9 95.0 71.2 31.1 98.2 93.4 75.5 42.7 60.77 SDS S SDS S 14.0 99.4 98.1 82.8 42.7 99.2 97.0 85.8 54.9 74.88 ThI: Thoracic Index (= chest depth-1.-1.0 * 100/chest0 breadth) -1-1.0.0 Secular trends; Ź7.3 Trends in Amplitude and was used to define the right time to enter school. 14.5 99.7 99.2 89.9 52.4 99.6 98.6 92.1 64.4 84.88 PSI: Pelvic-Shoulder Index (= bicristal pelvic breadth *100/ biacromial shoulder breadth) Tempo). Proportional age [Greil 2007] can be estimated by -2.0 B4B4 -2-2.0.0 15.0 99.8 99.7 93.6 59.9 99.8 99.3 95.7 71.4 91.33 RFL: Relative Foot Length (= foot length*100/leg length) various indexes (Table 3). Christiane SchefÅ er B1B1 Ŷ 15.5 99.9 99.8 95.7 65.5 99.9 99.6 97.6 76.8 95.11 ScI: Scelic Index (= leg length * 100/sitting--3.03.0 height) B2B2 B3B3 --3.03.0 16.0 99.9 99.9 96.9 70.0 99.9 99.7 98.6 81.0 97.22 10 1515 20 10 1515 17 2020 16.5 100.0 100.0 97.8 73.6 100.0 99.8 99.0 84.3 98.33 ageage (years) age ((years)years) 17.0 98.3 76.5 99.8 99.3 86.7 98.99 17.5 98.7 79.1 99.8 99.4 88.4 99.33 FiFiguregure 74: Stage llineine diagram of an individuaindividuall FigureFigure 75: Stage llineine diagram for breast and pu- 18.0 98.9 81.6 99.8 99.5 89.7 99.44 progresprogresss in breast devedevelopment.lopment. bbicic hair development,development, and menarchemenarche..

60 61

Figure 57: Body proportions – the classic illustra- Figure 58: Philippine measure: the child either tion of Stratz [1903]. reaches, or does not yet reach, the contralateral Figure 56: Changes of proportion (serial photos of a boy aged 2.5 to 6.5 years) [Schüler 2009]. ear with the fingers.

44 45

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