Precision of measurement and body size in whole-body air-displacement plethysmography

Transcription

1 ]> PAPER (2001) 25, 1161±1167 ß 2001 Nature Publishing Group All rights reserved 0307±0565/01 $ of measurement and body size in whole-body air-displacement plethysmography JCK Wells 1 * and NJ Fuller 1 1 Childhood Nutrition Research Centre, Institute of Child Health, London, UK OBJECTIVE: To investigate methodological and biological precision for air-displacement plethysmography (ADP) across a wide range of body size. DESIGN: Repeated measurements of body volume (BV) and body weight (WT), and derived estimates of density (BD) and indices of fat mass (FM) and fat-free mass (FFM). SUBJECTS: Sixteen men, aged 22±48 y; 12 women, aged 24±42 y; 13 boys, aged 5±14 y; 17 girls, aged 5±16 y. MEASUREMENTS: BV and WT were measured using the Bodpod ADP system from which estimates of BD, FM and FFM were derived. FM and FFM were further adjusted for height to give fat mass index (FMI) and fat-free mass index (FFMI). RESULTS: ADP is very precise for measuring both BV and BD (between 0.16 and 0.44% of the mean). After removing two outliers from the database, and converting BD to body composition, precision of FMI was < 6% in adults and within 8% in children, while precision of FFMI was within 1.5% for both age groups. CONCLUSION: ADP shows good precision for BV and BD across a wide range of body size, subject to biological artefacts. If aberrant values can be identi ed and rejected, precision of body composition is also good. Aberrant values can be identi ed by using pairs of ADP procedures, allowing the rejection of data where successive BD values differed by > kg=l. of FMI obtained using pairs of procedures improves to < 4.5% in adults and < 5.5% in children. (2001) 25, 1161±1167 Keywords: body composition; body density; body fat; fat-free mass Introduction Body weight (WT) and body volume (BV) may be used to calculate body density (BD ˆ WT=BV) from which assessments of body composition, particularly fat mass (FM) and fat-free mass (FFM), can be calculated. These variables can be obtained either directly, by using two-component (2C) models based on assumed constant values for the densities of fat and FFM, or by integrating BD into multi-component models. 1 The 2C densitometric model presents particular dif culties in younger age groups because density of the FFM changes markedly with age 2 and is not constant between individuals at any given age. 3 We have recently demonstrated that other 2C techniques, such as isotope dilution and dualenergy X-ray absorptiometry (DXA), are more accurate in children than those based on densitometry alone. 3 *Correspondence: JCK Wells, Childhood Nutrition Research Centre, Institute of Child Health, 30 Guilford Street, London WC1N 1EH, UK. Received 11 October 2000; accepted 7 December 2000 Nevertheless, measurement of BV can also make an important contribution to multi-component models of body composition. The three component (3C) model, for example, requires measurements of WT, BV and total body water while the similar but slightly more sophisticated four component (4C) model requires integration of an additional measure of bone mineral content. 1 Such multi-component models are essential for the study of body composition in disease states that alter certain properties of tissues, such as hydration fraction and density of the FFM, which are assumed to be constant in healthy subjects of a given age and sex. Traditionally, BV has been assessed using hydrodensitometry in both adults and children. 3±8 However, this technique has major limitations in that it requires cumbersome in-house equipment, restricting its availability, and is unsuitable for most patients, many young children and some older or in rm adult subjects. The development of alternative methodologies that may improve acceptability and compliance in patients and children is key to facilitating the widespread measurement of body composition where it is most needed. Air-displacement plethysmography (ADP), in the

2 1162 form of the Bodpod, has recently been introduced as such an alternative. 9 It has been successfully validated in adults, 10±12 although additional studies suggest that ADP may slightly over-estimate BD compared to hydrodensitometry. 13 The technique is readily accepted by children, 11,14,15 although accuracy is still being assessed, and underestimation of fat has again been reported. 15 Since the Bodpod ADP uses a chamber of constant size to accommodate subjects, it might be expected that precision would worsen in those subjects with smaller body size; that is, increased random error would be predicted because subject size is measured by difference between the volumes of air present in the anterior chamber of the Bodpod when empty and with the subject in place. It is important, therefore, to consider whether or not there is indeed an effect of body size on measurement precision, when using ADP to measure BV. We reported no difference in absolute precision between adults (10 subjects) and children (10) in a previous study. 14 However, the majority of children in that study were aged 8 y and over, and those ndings may not be applicable to younger children. Therefore, in this study we have investigated the effects of body size on precision, using a larger number of subjects distributed over a greater range of body size. We have also aimed to distinguish the effects of methodological and biological factors on precision. Methods Ethical approval for the study was granted by the local Ethical Committees of Addenbrooke's Hospital, and the Dunn Clinical Nutrition Centre, and informed consent was obtained from each subject or from the parents of each child. Verbal consent was also ascertained from each child. In all measurements, WT was measured as an integral part of the Bodpod procedure (see below), the methodological validity of which had been established during a previous study against calibrated electronic scales. 14 Standing height (HT) was measured against a wall-mounted stadiometer. Body mass index (BMI) was determined as Quetelet's index (kg=m 2 ). A series of repeated measurements (10 repeats) using ADP, performed with the Bodpod 1 Body Composition System (Life Measurement Instruments, California, USA) on phantoms of known weights and volumes (two cylinders of nominal volumes about 50 and 25 l), was obtained for the assessment of methodological error. Duplicate measurements were then performed using the Bodpod according to manufacturer's instructions and recommendations, with each subject wearing tight- tting swimsuit and swimcap. 9,10,14 A single ADP procedure consisted of two measurements of BV (about 50 s each) unless they differed by more than 150 ml, in which case the system required that a third measurement be performed. 9 Values for these two raw volume measurements, which were uncorrected for the effects on BV of isothermal conditions created by the subject due to thoracic gas and skin surface area, appeared transiently on the screen during the procedure, and were recorded. Predicted lung volume was used for the calculation of BV, using adult- 16 or child-speci c 17,18 equations as appropriate. 14 Appropriate corrections for thoracic gas volume and skin surface area artefact in adults and children were applied to this raw measurement to obtain actual BV. 9,14 The nal result reported by the Bodpod instrumentation was calculated from the average of the raw measurements, or the average of the closest two where three measurements were required. Data on BD were converted to body composition values as follows. For the adults, FM and FFM were calculated using the equation of Siri, 4 as utilized by the Bodpod software. However, for the children, fat and FFM were estimated from BD using age-speci c equations for children. 19 All these equations are in the form: percentage fat ˆ x=bd y 1 where x and y represent constants that vary in relation to both gender and age. FM and FFM were then calculated from data on percentage fat and WT. These data were further adjusted for height to give fat mass index (FMI ˆ FM=HT 2 ) and fat-free mass index (FFMI ˆ FFM=HT 2 ). 20 These indices of body composition allow independent evaluation of both fatfree and fat components of body composition taking variation in body size into account. A single value for HT was applied to both duplicates of each index, as precision of HT, known to be good, 21 is not the issue under investigation here. Statistics The bias between repeated measurements was calculated as the mean of differences. 22 The signi cance of the difference between the bias and zero was ascertained. Standard deviation (s.d.) of the difference between duplicate measurements (s.d. d ) was calculated as the square root of the sum of squared differences between duplicates divided by the number of subjects. 22 Estimates of precision for a single measurement were calculated by dividing s.d. d by p 2. The strength of relationships between variables was assessed using Pearson's correlation coef cient. The effects on precision of biological and methodological factors were distinguished using the equation presented by Wells et al 3 Vt 2 ˆ Vb 2 V2 m 2 where, the standard deviation (s.d.) of biological variation (V b ) is determined from the observed s.d.s of methodological variation (V m ) and total variation (V t ), in the same units and assumed to be uncorrelated with V b. Methodological error was then propagated for body composition values calculated by 2C, 3C and 4C models, using the delta method in combination with previously published precision data for the other measurement methods. 1,3

3 Table 1 Characteristics of the subjects 1163 Men (n ˆ 16) Women (n ˆ 12) Boys (n ˆ 13) Girls a (n ˆ 17) Age range (y) 22±48 24±42 5±14 5±16 Body weight (kg) 67.9 (8.3) 58.3 (4.8) 27.8 (7.5) 34.9 (14.7) Height (m) 1.75 (0.06) 1.62 (0.07) 1.30 (0.11) 1.37 (0.20) Body mass index (kg=m 2 ) 22.2 (2.3) 22.2 (3.1) 16.2 (1.5) 17.7 (2.3) Body fat (percentage weight) 18.0 (7.6) 27.5 (8.6) 12.6 (4.0) 19.7 (6.8) Fat-free mass (kg) 55.5 (6.7) 42.0 (4.3) 24.2 (6.3) 27.2 (10.5) Body volume (l) 64.2 (8.4) 56.2 (5.3) 26.3 (7.0) 33.1 (14.7) Body density (kg=l) (0.017) (0.018) (0.008) (0.013) a n ˆ 16 for percentage fat, fat-free mass, body volume and body density. Results Characteristics of the 58 healthy subjects who volunteered for this study appear in Table 1. The children were representative of the UK population in terms of BMI s.d. score (boys 0.10, s.d. 0.68; girls 0.37, s.d. 0.73). 23 All subjects successfully completed pairs of ADP procedures without dif culty. The resulting range of body volume, corrected for lung volume and surface area artefacts, is shown in Figure 1. The methodological precision of the weighing scale integral to the Bodpod instrumentation was de ned as zero, as any variation arising from repeat measurements using phantoms was below the sensitivity of the scale. Biological variability of WT, calculated from duplicate measurements of subjects, was kg in both adults and children, equivalent to 0.01% for a 70 kg man, and 0.03% for a 25 kg child. There was a slight trend for weight to decrease with each subsequent measurement, due to insensible water loss through the skin, but, as the percentage change indicates, this change in weight was negligible. The volume precision for a phantom of 50 l was 0.03 l and for a small phantom of 17 l was l. There was no trend evident in consecutive measurements of volume for either of the phantoms. Collectively, the combined effects of precision of WT and Figure 1 Range of body volume of the subjects measured by airdisplacement plethysmography. volume propagate to a methodological density precision of kg=l in adults and kg=l in children. Of the 58 subjects, only one of the girls had all three measurements rejected for one ADP procedure as no two values were within 150 ml. Therefore, these results were used for the estimation of precision for the raw data but were excluded from subsequent analyses of derived body composition data. Raw data was not recorded directly from the screen for nine subjects. Average raw volume values in these nine subjects were calculated back from the nal results, but duplicate raw volumes within a single measurement were not available, and analysis of internal ADP precision was therefore restricted to 48 of the 58 subjects. The numbers of subjects requiring three measurements for either ADP procedure, the closest two of which were accepted, were in the same proportions for each measurement run, and similar between the age groups: 3=15 men, 2=12 women, 2=9 boys and 3=13 girls. In no case of repeated measurements (raw volumes, BD, body composition etc) was a signi cant difference (bias) observed between values obtained during the rst and second procedures. Therefore, the estimation of precision was enabled for the data without requiring its log transformation. Table 2 shows the precision (absolute and as percentage of the mean) for the raw volume measurements taken from the rst and second repeated ADP procedure, for the measurement of volume used by the Bodpod for estimation of body composition (ie the average of the rst and second raw measurement corrected for lung volume and surface area artefact) and BD. There were two outlying values, both boys, which had a disproportionately large in uence on the precision values. Whereas density measurements from successive procedures fell within kg=l in all other subjects, the difference exceeded kg=l in these two subjects. Separate analyses, either including or excluding these subjects, indicated that relative precision of FMI estimation was reduced from 17% to < 8% in the boys by omitting these outliers. of body composition variables (FFM, percentage fat, FFMI and FMI), after exclusion of the outliers, is given in Table 3. There was no signi cant relationship between body size, as assessed by BV, and precision of density measurement

4 1164 Table 2 Absolute and relative precision of raw data obtained by air displacement plethysmography Group Measurement Mean for successive ADP procedures (Figure 2). However, when density was converted into body composition, there was a moderate relationship between body volume and FMI precision (r ˆ 0.29; P ˆ 0.027). This is explained by the effect of age on the equation by which density is converted to fatness. Relative precision of fatness was poorer in men, boys and girls than in women due to the lower levels of fatness in these categories. Table 3 of body composition variables using airdisplacement plethgysmography in combination with the twocomponent model Group Measurement Mean (absolute) (absolute) a (relative) a Men Raw volume 1 (l) b 0.19 Raw volume 2 (l) b 0.22 Actual volume (l) c 0.23 Body density (kg=l) c 0.21 Women Raw volume 1 (l) b 0.21 Raw volume 2 (l) b 0.16 Actual volume (l) c 0.16 Body density (kg=l) c 0.16 Boys Raw volume 1 (l) b 0.27 Raw volume 2 (l) b 0.41 Actual volume (l) c 0.42 Body density (kg=l) c 0.44 Girls Raw volume 1 (l) b 0.34 Raw volume 2 (l) b 0.28 Actual volume (l) c 0.18 Body density (kg=l) c 0.19 a Absolute precision expressed as percentage of mean value. b Single measurement within a procedure, uncorrected for artefacts, from 15 men, 12 women, 9 boys and 13 girls. c Complete procedure, mean of two raw volumes corrected for lung volume and surface area artefacts, from 16 men, 12 women, 13 boys and 16 girls. (relative) b Men (n ˆ 16) Fat-free mass (kg) Body fat (%) FFMI (kg=ht 2 ) FMI (kg=ht 2 ) Women (n ˆ 12) Fat-free mass (kg) Body fat (%) FFMI (kg=ht 2 ) FMI (kg=ht 2 ) Boys (n ˆ 11) Fat-free mass (kg) Body fat (%) FFMI (kg=ht 2 ) FMI (kg=ht 2 ) Girls (n ˆ 16) Fat-free mass (kg) Body fat (%) FFMI (kg=ht 2 ) FMI (kg=ht 2 ) a of complete procedure, corrected for lung volume and surface area artefacts. b Absolute precision expressed as percentage of mean value. Even after excluding the two outliers, methodological error was found to make a trivial contribution to total reproducibility. Observed density precision of subjects (given in Table 2) was at least 10 times the magnitude of methodological precision described above, for both age groups and sexes. Thus, biological factors account overwhelmingly for differences between successive procedures. Propagation of error in body composition models implied by such precision values is given in Table 4. Discussion Air-displacement plethysmography is potentially of great value in medical research, being a relatively easy measurement procedure for healthy subjects and many patients. The present study indicates that it is readily accepted by children aged 5 y and over, in contrast to many other body composition techniques. However, information regarding precision and accuracy remains of great importance for the appropriate use of this technique. The present study therefore evaluated precision of ADP for assessment of body composition across a wide range of body size in the healthy population. In common with most other investigators we have examined precision in terms of BV, BD and percentage fat. This approach, however, is insuf cient for evaluating the full signi cance of ADP precision for speci c aspects of body composition. Percentage fat is in uenced both by the amount of FM in WT and by the amount of FFM. More objective independent indices of fatness and leanness are given by the FM index (FMI) and FFM index (FFMI) respectively, where FM and FFM are normalised for HT rather than WT. 20 These indices allow independent evaluation of the signi cance of ADP precision for both fat and fat-free components of body weight, while taking variability in body size into account. Observed differences in absolute precision for individual groups of children and adults (Table 3) are therefore attributable to other inconsistencies between measurements such as movement or during the procedure, changes in posture, variable depth of breathing patterns and the effects of body hair. Repeated ADP measurements were slightly less precise for this study (mean precision l for adults and l for Table 4 Comparison between hydrodensitometry and ADP for precision of body composition variables (FM or FFM) calculated using different models of FFM or FM (kg) Bodpod Hydrodensitometry Two-component Adults Children Three-component Adults Children Four-component Adults Children

5 1165 Figure 2 Relationship between body size (body volume) and difference in body density according to successive air-displacement plethysmography procedures in each subject. children) than we reported previously (0.071 l and l, respectively). 14 Part of this difference can be attributed to the outliers, omission of which reduced precision to l in children. However, the values in the present study were still below equivalent values for hydrodensitometry (0.148 l and l, respectively), 14 which are similar to those reported in other studies. 1,7 This enhanced precision for ADP assessments of BV improves the precision of derived estimates of body composition, whether estimated by 2C, 3C or 4C models, as demonstrated in Table 4. The present study was not designed to assess accuracy and did not consider in detail between-subject variability in the density of FFM, which is known to be in uenced by age, sex, hydration status, and relative mineral and protein deposition. 1,3,19 However, our study indicates that such changes do in uence precision of body composition measurements. Although absolute precision for BV and BD is relatively consistent across the range of size from young children to adults, the relative precision of FMI in children is poorer. This can be attributed to two factors. Firstly, the difference between the age-speci c constants x and y (see eqn. (1) above) increases with age, so that any error in BD has a proportionally lesser effect in adults than in children. Secondly, relative precision of FMI in children is inevitably poorer than in adults of the same sex due to the lower levels of fatness in the younger age groups. Of all the measurements obtained from the 57 subjects, two clear outliers were evident, representing data obtained from two boys. Possible causes of such outliers include inconsistent breathing patterns between the two procedures, or different levels of body movement, possibly due to subjects feeling more relaxed during the second procedure. On the basis of single Bodpod procedures, it would have been impossible to identify such subjects, and hence impossible to justify their rejection from the database. However, obtaining duplicate ADP procedures overcomes this problem in two ways. Firstly, measurement in duplicate allows the average of the two results to be used in subsequent calculations. This has an additional bene t in that the precision of such an average is better by a factor of p 2 than that of a single procedure. Secondly, it is possible to reject subjects (or to perform a third procedure) where successive procedures yield density values differing by more than a certain amount. In the present study, over 95% of the subjects differed by less than kg=l between successive procedures, equivalent to 3.2% fat in adults, or 3.6% in children. (Use of the average of the two procedures then gives precision of 2.3% and 2.5% fat in adults and children, respectively). Alternative cut-off values could be set in speci c circumstances, according to the requirements of the study. The likelihood of rogue data being produced can also be minimised by ensuring that the measurement protocol and the immediate environment are consistent: for example, that ambient pressure changes due to the opening of doors etc, and aberrant breathing patterns between measurements are avoided. Appropriate clothing must also be worn. 9,24 Measurement imprecision would still exist despite elimination of obvious outliers arising from biological or environmental factors, due to non-biological methodological factors. However, assessment of internal measurement precision for ADP using cylinder phantoms indicates that the overwhelming majority of total precision for a subject can be attributed to non-methodological variables (Table 2). Successive measurements of raw volume in subjects showed no signi cant trend towards greater or lesser values according to the positional order of measurement, indicating that the rst measurement had no in uence on the second.

6 1166 These ndings indicate that methodological precision of ADP is good, and that the nal quality of the results obtained will therefore be optimised by minimising biological and environmental sources of imprecision. When the two outliers were removed from the analyses, precision in the boys was comparable with the other three groups. Our study demonstrated no signi cant relationship between density precision and body size. When BD was converted to body composition, there was a moderate relationship between body size and FMI precision, however this is due to the internal mathematics of the equation by which BD and fatness are related. The effect of size on fatness precision was small in magnitude, and our study found that precision of FMI was < 6% for adults and < 8% for children. These values improve to < 4.5% in adults, and < 5.5% in children, if pairs of ADP procedures are used. There is therefore no indication that ADP precision is substantially worse for body composition estimation in children. However, pairs of ADP procedures are of particular value in younger age groups as children appear more prone to occasional rogue values. This is consistent with our previous study, where agreement between hydrodensitmetry and ADP (one procedure only) was good in most children but much poorer in four subjects. 14 Lung volume can be either predicted or measured during ADP. Previously, the measurement of lung volume has been advocated in adults. 25 However, it was our initial experience that a high proportion of duplicate measures of lung volume were so disparate (greater than 0.5 l difference between them or from predicted values) as to be of major concern. This suggests that many subjects, especially children, are unable to comply with the protocol for measurement of lung volume. An error of 0.5 l in lung volume, undetectable by the observer, for a 70 kg man of 21% fat would create an error of 0.2 l ( litre) in BV, giving a value of 19.5% fat, an absolute error in percentage fat of about 1.5% and a relative error of 7%. Prediction of lung volume is fairly accurate in individuals, 26 and we have shown previously that the use of alternative prediction equations in children makes negligible difference to the nal body composition data. 14 Therefore, in this investigation, only predicted lung volume, based on weight and height, was applied in order to concentrate on precision for the BV measurement uncomplicated by the issue of consistent lung volume. Any subject producing erratic breathing patterns would create erroneous estimates of body density irrespective of whether or not predicted or measured lung volumes were used. Conclusions ADP demonstrates good precision in the measurement of BV and hence BD for body size ranging from children aged 5 y with < 20 l to adult men with > 80 l. Because of the way in which BD data are converted to body composition data, a given BD precision equates to slightly poorer relative precision of fatness in children compared to adults. However, the difference is small in magnitude and FMI is measured by a single ADP procedure with precision of < 6% in adults and < 8% in children. ADP represents an important technique for body composition research, particularly in multi-component modelling where its precision is substantially greater than alternative techniques for measuring BV. The technique appears prone to occasional rogue values (10=49 for the initial procedure in which such values are eliminated; 2=57 outliers remaining according to repeated ADP measurement procedures). These aberrant values are probably due to alterations in the external environment, or inconsistency in movement and lung volume of the subject, all of which may be beyond the control and notice of the experimenter. Pairs of ADP procedures are therefore advised to allow elimination of problematic results and to provide a best average volume for subsequent calculations. Using pairs of procedures, precision of FMI improves to < 4.5% in adults and < 5.5% in children. Acknowledgements We are extremely grateful to Professor Tim Cole of the Institute of Child Health, London, for his advice regarding the statistical analyses and error propagation. References 1 Fuller NJ, Jebb SA, Laskey MA, Coward WA, Elia M. Four-component model for the assessment of body composition in humans: comparison with alternative methods, and evaluation of the density and hydration of fat-free mass. Clin Sci 1992; 82: 687± Fomon SJ, Haschke F, Ziegler EE, Nelson SE. Body composition of reference children from birth to age 10 years. Am J Clin Nutr 1982; 35: 1169± Wells JCK, Fuller NJ, Dewit O, Fewtrell MS, Elia M, Cole TJ. Fourcomponent model of body composition in children: density and hydration of fat-free mass and comparison with simpler models. Am J Clin Nutr 1999; 69: 904± Siri WE. Body composition from uid spaces and density: analysis of methods. In: Brozek J, Henschel A (eds). Techniques for measuring body composition. National Academy of Sciences: Washington, DC; pp 223± Heald FP, Hunt EE, Schwartz R, Cook CD, Elliot D, Vajda B. Measures of body fat and hydration in adolescent boys. Pediatrics 1963; 31: 226± Boileau RA, Lohman TG, Slaughter MH, Ball TE, Going SB, Hendrix MK. Hydration of the fat-free body in children during maturation. Hum Biol 1984; 56: 651± Deurenberg P, van der Kooy K, Paling A, Withagen P. Assessment of body composition in 8±11 year old children by bioelectrical impedance. Eur J Clin Nutr 1989; 43: 623± Reilly JJ, Wilson J, Durnin JVGA. Determination of body composition from skinfold thickness: a validation study. Arch Dis Child 1995; 73: 305± Dempster P, Aitkens S. A new air displacement method for the determination of human body composition. Med Sci Sports Exerc 1995; 27: 1692± McCrory MA, Gornez TD, Bernauer EM, Mole PA. Evaluation of a new air displacement plethysmograph for measuring human body composition. Med Sci Sports Exerc 1995; 27: 1686± Nunez C, Kovera AJ, Pietrobelli A, Heshka S, Horlick M, Kehayias JJ, Wang Z, Heyms eld SB. Body composition in children and adults by air displacement plethysmography. Eur J Clin Nutr 1999; 53: 382±387.

7 12 Wagner DR, Heyward YH, Gibson AL. Validation of air displacement plethysmography for assessing body composition. Med Sci Sports Exerc 2000; 32: 1339± Collins MA, Millard-Stafford ML, Sparling PB, Snow TK, Rosskopf LB, Webb SA, Omer J. Evaluation of the BOD POD for assessing body fat in collegiate football players. Med Sci Sports Exerc 1999; 31: l350± Dewit O, Fuller NJ, Fewtrell MS, Elia M, Wells JCK. Whole body air displacement plethysmography compared with hydrodensitometry for body composition analysis. Arch Dis Child 2000; 82: 159± Lockner DW, Heyward VH, Baumgartner RN, Jenkins KA. Comparison of air-displacement plethysmography, hydrodensitometry, and dual X-ray absorptiometry for assessing body composition of children 10 to 18 years of age. Ann NY Acad Sci 2000; 904: 72± Crapo RO, Morris AH, Clayton PD, Nixon CR. Lung volumes in healthy non-smoking adults. Bull Eur Physiopath Resp 1982; 18: 419± Rosenthal M, Cramer D, Bain SH, Denison D, Bush A, Warner JO. Lung function in white children aged 4 to 19 years: II Ð single breath analysis and plethysmography. Thorax 1993; 48: 803± Zapletal A, Paul T, Samanek M. Normal values of static pulmonary volumes and ventilation in children and adolescents. Ceskoslovenska Pediatrie 1976; 31: 532± Lohman TG. Assessment of body composition in children. Pediatr Exerc Sci 1989; 1: 19± Van Itallie TB, Yang M, Heyms eld SB, Funk RC, Boileau RA. Height-normalised indices of the body's fat-free and fat mass: potentially useful indicators of nutritional status. Am J Clin Nutr 1990; 52: 953± Fuller NJ, Jebb SA, Goldberg GR, Pullicino E, Adams C, Cole TJ, Elia M. Inter-observer variability in the measurement of body composition. Eur J Clin Nutr 1991; 45: 43± Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; i: 307± Cole TJ, Freeman JV, Preece MA. Body mass index reference curves for the UK, Arch Dis Child 1995; 73: 25± Fields DA, Hunter GR, Goran MI. Validation of the BOD POD with hydrostatic weighing: in uence of body clothing. Int J Obes Relat Metab Disord 2000; 24: 200± McCrory MA, Mole PA, Gomez TD, Dewey KG, Bernauer EM. Body composition by air-displacement plethysmography by using predicted and measured thoracic gas volumes. J Appl Physiol 1998; 84: 1475± Stocks J, Quanjer PH. Reference values for residual volume, functional residual capacity and total lung capacity. Eur Respir J 1995; 8: 492±