An Anthropometric Measure Based on an Age-Related Model of Human Growth
7.4 Application of the Growth Models to Other Areas
148 M.K. Lebiedowska and S.J. Stanhope
Table 7.5 Thresholds for overweight and obesity based on a model of growth of Polish children (5–18 years old) between years 1985 and 1990.
Ranges of indices in Polish children population
Sex Girls ( N = 444) Boys ( N = 403)
HBSI G (kg/m 2.84 ) Underweight <10.67 –
Normal 10.67–14.97
At risk of overweight 14.97–16.4
Overweight ³ 16.4
HBSI B (kg/m 2.68 ) Underweight – >11.27
Normal 11.27–15.36
At risk of overweight 15.36–17.19
Overweight ³ 17.19
HBSI (kg/m 2.76 ) Underweight >10.96 >10.97
Normal 10.96–15.39 10.97–14.93
At risk of overweight 15.39 – 16.85 14.93–16.57
Overweight ³ 16.85 ³ 16.57
Modifi ed from Lebiedowska et al. (2008). With permission
This table displays the ranges of sex-independent (HBSI) and sex-specifi c (HBSI B , HBSI G ) body shape indices for: underweight (<5th percentiles), normal (5th percentiles–85th percentiles), at risk of overweight ( ³ 85th percentiles and ³ 95th percentiles) and overweight ( ³ 95th percentiles) conditions
N : number of children, B , G : boys and girls respectively
using sample distributions, the development of physiologically based thresholds for overweight and obesity should be explored. There exists a discrepancy between the defi nitions for abnormal HBS in children and adults. It is well established that increased BMIs in adults (for overweight BMI ³ 25 and for obesity BMI ³ 30) are associated with the changes in other anthropometric, biochemical and instrumental measure of obesity (Dahlström et al. 1985 ; Wang et al. 2004). The projection of well established adult thresholds into the pediatric population may lead to the development of physiologically based thresholds. It seems however, that the thresholds may be sex specifi c.
149 7 The Human Body Shape Index (HBSI): An Anthropometric Measure Based on an Age-Related…
5–18 years and the age independent, normalized databases of various biomechanical parameters (maximum knee extension and fl exion isometric movement of force, lower-leg moment of inertia, passive stiffness and damping of the knee joint (Lebiedowska et al. 1996 ) . The approach presented in this chapter can be easily applied in ergonomics (Lebiedowska 2006 ) , sport and other research disciplines where human growth affects the outcome measures.
Summary Points
The growth of Polish children 1985–1990 was close to the geometrically similar growth (10.6%
•
accuracy in boys and 5.3% accuracy in girls).
The lack of any other “golden standard” suggests that the model based on the population of Polish
•
children 1985–1990 may serve as a model of natural growth.
The age independent, sex-specifi c index (HBSI) was based on the mathematical model of Polish
•
children’s growth.
HBSI characterizes the shape of children 5–18 years old with one sex specifi c, age-independent
•
mean and one standard deviation .
HBSI allows for comparison of the changes in the human body shape during growth in individu-
•
als and between different populations (time, location).
Comparison of sensitivity and specifi city of HBSI and standard BMI to detect overweight and
•
obesity in children should be explored.
References
Agarwal KN, Saxena A, Bansai AK, Agarwal DK. Physical growth assessment in adolescence. Indian Pediatr.
2001;38(11):1217–35.
Alley RA, Narduzzi JV, Robbins TJ, Weir TF, Sabeh G, Danowski TS. Measuring success in the reduction of obesity in childhood. Limited weight reduction success among 50 outpatients. Clin Pediatr. 1968;7(2):112–8.
Benn RT. Some mathematical properties of weight-for-height indices used as measures of adiposity. Br J Prev Soc Med. 1971;25(1):42–50.
Bryce J, Boschi-Pinto C, Shibuya K, Black RE. WHO Child Health Epidemiology Reference Group. WHO estimates of the causes of death in children. Lancet. 2005;365(9465):1147–52.
Cole TJ, Freeman JV, Preece MA. Body mass index reference curves for the UK, 1990. Arch Dis Child 1995;73(1):25–9.
Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard defi nition for child overweight and obesity worldwide: international survey. BMJ. 2000;320(7244):1240–3.
Dahlstrom S, Viikari J, Akerblom HK, et al. Atherosclerosis precursors in Finnish children and adolescents. II. Height, weight, body mass index, and skinfolds, and their correlation to metabolic variables. Acta Paediatr Scand Suppl.
1985;318:65–78.
Davies DP and Beverley D. Changes in body proportions over the fi rst year of life: comparisons between ‘light-for- dates’ and ‘appropriate-for-dates” term infants. Early Hum Dev. 1979;3(3):263–5.
de Onis M. The use of anthropometry in the prevention of childhood overweight and obesity. Int J Obes Relat Metab Disord. 2004;28 Suppl 3:S81–5.
Field AE, Laird N, Steinberg E, Fallon E, Semega-Janneh M, Yanovski JA. Which metric of relative weight best captures body fatness in children? Obesity Res. 2003 11(11):1345–52.
Flegal KM. Curve smoothing and transformations in the development of growth curve. Am J Clin Nutr. 1999;70 (1 Part 2):163S–5S.
Garn SM, Leonard WR, Hathworne VM. Three limitations of the body mass index [letter]. Am J Clin Nutr.
1986;44(6):996–73.
Günter B. Dimensional analysis and theory of biological similarity. Physiol Rev. 1975;55(4):659–99.
Hattori K and Hirohara T. Age change of power in weight/height(p) indices used as indicators of adiposity in Japanese.
Am J Hum Biol. 2002;14(2):275–9.
150 M.K. Lebiedowska and S.J. Stanhope
Huber NM. Ponderal Index and Height. Am J Phys Anthrop. 1969:31(2):171–6.
Lebiedowska M, Syczewska M, Graff K, Kalinowska M. Application of Biomechanical Growth Models in the Quantitative Evaluation of The Child Motor System. Disabil & Rehab. 1996;18(3):137–42.
Lebiedowska MK. Growth Normalization of Biomechanical Factors in children 6-18 years old. In: Karwowski W, editor. International Encyclopedia of Ergonomics and Human Factors. New York: Francis & Taylor (2nd ed.);
2006. p. 360–4.
Lebiedowska M, Alter K, Stanhope S. (2008) Experimentally derived model of human growth. J Pediatr.
2008;152(1):45–9.
Mei Z, Grummer-Strawn LM, Pietrobelli A, Goulding A, Goran MI, Dietz WH, Validity body mass index compared with other body-composition screening indexes for the assessment of body fatness in children and adolescents. Am J Clin Nutr. 2002;75(6):978–85.
Nahum LH. The ponderal index. Conn Med. 1966;30(4):241–2.
Pietrobelli A, Faith MS, Allison DB, Gallagher D, Chiumello G, Heymsfi eld, SB. Body mass index as a measure of adiposity among children and adolescents: a validation study. J Pediatr. 1998;132(2):204–210.
Piers LS, Soares MJ, Frandsen SL, O’Drea K. Indirect estimates of body composition are useful for groups but unreli- able in individuals. Int J Obes Relat Metab Disord. 2000;24(9):1145–52.
Ricardo DR and Araujo CG. Body mass index: a scientifi c evidence-based inquiry. Arq Bras Cardiol, 2002:79(1):61–78.
Rolland-Cachera MF, Sempé M. Guilloud-Bataille M. Patois E, Pequignot-Guggenbuhl F, Fautrad V. Adiposity indi- ces in children. Am J Clin Nutr. 1982;36(1):178–84.
Rosenthal M, Bain SH, Bush A, Warner JO. Eur J Pediatr. Weight/height 2.88 as a screening test for obesity or thinness in schoolage children. Eur J Pediatr. 1994;153(12):876–83.
Seltzer CC. Some re-evaluations of the build and blood pressure study, 1959, as related to ponderal index, somatotype and mortality. New Eng J Med; 1966;274(5):259–9.
Sheldon WH, Stevens SS, Tucker WB. The varieties of human physique: an introduction to constitutional psychology.
New York and London: Harper; 1940.
Troiano RP, Flegal KM. Overweight prevalence among youth in the United States: why so many different numbers?
Int J Obes Relat Metab Disord. 1999;23 Suppl 2:S22–7.
Wang Y. Epidemiology of childhood obesity-methodological aspects and guidelines: what is new? Int J Obes Relat Metab Disord. 2004;28 Suppl 3:S21–8.
V.R. Preedy (ed.), Handbook of Anthropometry: Physical Measures 151 of Human Form in Health and Disease, DOI 10.1007/978-1-4419-1788-1_8,
© Springer Science+Business Media, LLC 2012
Abstract Measurements of bone mass and body composition using X-ray based dual photon absorptiometry (DXA) are used extensively to investigate patients suspected to be suffering from conditions that affect the skeleton or soft tissues. Commonly, such measurements seek to establish whether or not a change has occurred since a previous measurement. The ability to detect change is determined by perhaps the most important characteristic of a DXA system; that is the precision of the measurement. In this chapter, the results of precision assessments made in various groups of subjects using equipment housed in a routine, diagnostic Department of Nuclear Medicine are reviewed and compared to published values.
In phantoms, the precision or reproducibility of a bone mineral density (BMD) measurement is better than 0.005 g cm −2 even if the number of measurements from which the precision is derived is accumulated over an extended time period. In children, same-day precision for spine BMD, whole body BMD and proximal femur BMD worsens to values of 0.007, 0.009, and 0.011 g cm −2 , respec- tively. For adults, the same-day precision of spine BMD decreases further to 0.010 g cm −2 while femur BMD precision is virtually unchanged. Long-term precision for spine BMD and femur BMD decreases again to 0.029 and 0.023 g cm −2 while for the radius, long-term precision is 0.012 g cm −2 . The precision attained by routine clinical laboratories for the measurement of BMD can be compa- rable to that obtained by research laboratories.
The same-day precision of DXA measurements of body composition in children is about 20 g for whole body bone mineral content (WBBMC), 250 g for lean tissue mass (LBM) and 190 g for fat mass (FM). In adults, same-day precision for WBBMC is similar to that measured in children while for LBM and FM, same-day precision worsens to about 350 and 280 g, respectively. Extending the time interval between pairs of measurements to more than 1 day makes the reproducibility of soft tissue composition assessments much worse as the effect of daily fl uctuations in dietary balances will be included in the reproducibility evaluation. The presence of obesity means that the precision of measurements in all body composition compartments deteriorates.