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Institut für Humanernährung und Lebensmittelkunde der Christian-Albrechts University Kiel, Germany
2To whom correspondence should be addressed. E-mail: mmueller{at}nutrfoodsc.uni-kiel.de.
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ABSTRACT |
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 TOP ABSTRACT SUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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KEY WORDS: • fat mass • air-displacement plethysmography • thoracic gas volume • children • adolescents
Because of the increasing prevalence of overweight and obesity in childhood and adolescence, there is need for a detailed assessment of nutritional status. In addition to high accuracy and precision, methodological requirements on body composition research originate from the characteristics of the pediatric target group. In children and adolescents, the method should be noninvasive, place low demands on subject performance, and take into account the properties of the growing organism [i.e., development in the hydration of fat-free mass (FFM)3 ]. Air-displacement plethysmography (ADP) has been used increasingly for body composition analysis in children and adolescents (1–11), and the technique is commercially available. The use of ADP in pediatric populations was validated against dual X-ray absorptiometry (DXA) (4,5,9), hydrostatic weighing (1,3,4,7), or 3- (8) and 4-compartment models (2,9). Because of its high precision and validity, ADP is now considered to be a criterion method. However, the manufacturer’s software was developed for adults, and several inherent equations have to be corrected for use in children and adolescents. These equations concern the prediction of 1) body surface area to correct for the isothermal behavior of air near the skin, 2) thoracic gas volume (TGV) to account for isothermal behavior of lung volume, and 3) the age- and sex-specific density of FFM that is due mainly to variance in its hydration but may also be influenced by variation in bone mineral content in this age group. Nevertheless, the use of child-specific corrections for ADP data is not a common practice among researchers. With the exception of 2 papers (4,7), all studies somehow corrected for child-specific density of FFM (1,3,5,8–11), e.g., by using Lohman’s equations (12). In contrast, child-specific prediction of TGV was performed by only 1 group of authors from the UK (3,8,11). Moreover, child-specific correction of surface area artifact (SAA) was reported in only 1 case for 5- to 7-y-old children (8). Furthermore, knowledge about the amount and etiology of bias due to the uncorrected use of ADP in children is limited because of small sample sizes for comparison of measured and predicted TGV (4,5,7) or differences in age or BMI ranges examined. The variety of formulas used, an unpublished manufacturer constant for SAA calculation, as well as the different ways of predicting TGV [e.g., according to Rosenthal et al. (13) and Zapletal et al. (14) or to Fields et al. (15)], also add to the complexity of ADP correction in children and adolescents and thus confuse the user.
The present study aimed to investigate different child-specific corrections of ADP results for body surface area, TGV, and density of FFM in 258 children between 5 and 18 y old with a wide range of BMI. In analyzing the bias, we wanted to quantify the overestimation of body fat mass (FM) by the manufacturer’s software; we analyzed its etiology by estimating its dependency on age or BMI. Finally we provided a recommendation for implementation of ADP correction in children by giving step-by-step advice for the required calculations.
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SUBJECTS AND METHODS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Children were recruited from the Kiel Obesity Prevention Study (KOPS) (16) by advertisements in local newspapers, by notice-board postings, and writing to families that are continuously followed up as a KOPS subcohort. A total of 258 healthy subjects participated, 143 girls and 115 boys aged between 5 and 18 y (mean age 10.8 ± 3.1 y). Exclusion criteria were diagnosed obstructive lung diseases and asthma. All participants were of Caucasian descent. The study protocol was approved by the local ethical committee of the Christian-Albrechts-University Kiel. Children’s informed assent and parent written informed consent were obtained before participation. BMI reference values (17) used to define overweight and obesity are given in Table 1.
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Examinations took place between 0800 and 1000 h after an overnight fast. Height was measured to the nearest 0.5 cm with a stadiometer. Weight was assessed to the nearest gram by an electronic scale coupled to the BodPodTM-Body Composition System (Life Measurement Instruments). ADP is based on the assessment of body density (Db) from weight and body volume (Vb) and the subsequent calculation of the percentage of FM (%FM) based on assumed constant densities of FFM and FM. It involves a principle derived from the gas law of Poisson stating that pressure times volume in a closed chamber is constant at unchanging temperature under adiabatic conditions [for a detailed description, see (18,19)]. A 2-step calibration was carried out before each measurement: in the first step, the volume of the empty chamber was measured, and in the second step, the volume of a 50-L calibration cylinder was measured. The precision of 2 repeated volume measurements of a 50.005-L and a 20.003-L cylinder calculated as (SD/
2) were 0.019 and 0.016, respectively. When entering the BodPod device, all participants wore tight-fitting underwear and a swim cap. They were instructed to sit motionless during the 50 s of body volume measurement. Two repeated measurements of body raw volume (Vb raw) were performed and averaged for further data analysis. If the 2 measurements differed by >150 mL or 0.2%, a 3rd measurement was performed. For subsequent calculations, the mean of the 2 closest raw volume measurements within these agreement criteria was used. Body raw volume requires adjustment for air next to the skin [surface area artifact (SAA)] and TGV [functional residual capacity (FRC) + 0.5 x tidal volume). Algorithms included in the manufacturer’s software (version 1.69) calculate surface area and TGV for adults are as follows (20,21):
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The manufacturer’s values were as follows:
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TGV was assessed indirectly using the BodPod device. For this part of the test, subjects were prompted to puff gently against an occluded airway while changes in body volume were recorded. In 78 subjects (47 females and 31 males), a valid measure could not be obtained after 3 trials and the volume of thoracic gas was predicted.
Body density (Db) was calculated as body weight divided by body volume corrected for SAA and TGV. The %FM according to the manufacturer’s software was calculated using Siri’s equation (22):
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The CV for 2 repeated measurements of the %FM analyzed according to the manufacturer’s software in 10 children (5 girls and 5 boys, mean age 11.2 y) was 3.0 ± 0.77% (SD). Equations applied to child-specific correction of ADP results are provided in Table 2. The results from these corrections were compared with results derived from formulas for adults used in the manufacturer’s software.
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All data are given as means ± SD. Statistical analyses were performed using SPSS for Windows 8.0. The Mann-Whitney U-test was used for comparisons between sexes. Differences between intraindividual results from different prediction equations (i.e., for SAA, TGV, Db and %FM) were evaluated by repeated-measures ANOVA. Agreement between different models for predicting the same variable was assessed using the method of Bland and Altman (23). Bias and 95% limits of agreement (defined as mean difference ± 2 SDs of the difference between results from different formulas) were provided. Assessment was also made of the extent to which the magnitude of the difference was related to the magnitude of the variable (described by the correlation coefficient between the difference and the mean of the predicted values). Pearson’s correlation coefficients were given. Stepwise multiple regression analysis was used to explain the variance in biases due to age, sex, and BMI. All tests were 2-tailed and a P-value < 0.05 was accepted as the limit of significance.
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RESULTS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Body surface area calculated using the adult formula of DuBois and DuBois (20) exceeded surface area calculated from the child-specific equation of Haycock et al. (24) (1343 ± 330 cm2 vs. 743 ± 35 cm2, respectively). SAA calculated using the formula of Haycock et al. (24) was twice as high as that calculated from the equation of DuBois and DuBois’ (20) from the manufacturer’s software (Table 4). Results of both formulas were highly correlated with each other (r = 0.95, P < 0.001). A Bland-Altman plot revealed a systematic underestimation of SAA in children and adolescents by DuBois and DuBois’ formula compared with Haycock’s formula (Table 5). In stepwise multiple regression analysis, BMI, age, and sex together explained 92% of variance in the difference between SAADuBois and SAAHaycock with 71% due to BMI only. Applying the different SAAs in the prediction of Db and %FM resulted in significant underestimation of mean Db (1.032 vs. 1.039 g/cm3) and a respective overestimation of mean %FM of 2.97% (29.81 vs. 26.84%, Table 4).
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TGV predicted from the manufacturer’s software (TGVCrapo&BodPod) was 340–420 mL higher than the child-specific prediction equations of Fields et al. (15) and the equations of Zapletal et al. (14) and Rosenthal et al. (13) (TGVFields and TGVZ&R, Table 4). Regression of measured TGV (obtained in a subsample of 180 children and adolescents) on the predicted TGV indicated good agreement between the predicted and measured TGVs for individual subjects (R2 = 0.82 for TGVCrapo&BodPod, R2 = 0.83 for TGVZ&R, and R2 = 0.84 for TGVFields; all P < 0.001). However, Bland-Altman analysis revealed an overestimation of measured TGV by TGVCrapo&BodPod of 576 mL (Table 3). By contrast, overestimation of TGV by TGVFields was only 223 mL. Although the difference between measured TGV and TGVZ&R was very low (115 mL) there was a systematic bias indicated by the correlation between the difference and the mean (Table 3). The difference between measured TGV and TGVCrapo&BodPod or TGVFields was not associated with age, sex, or BMI, whereas 14% of the variance in the difference between measured TGV and TGVZ&R was explained by age and sex. Although the results in Db and %FM calculated with the 2 child-specific TGV equations did not differ significantly, there was an underestimation of Db (1.039 vs. 1.043 g/cm3) and respective overestimation of 2% in FM (26.84 vs. 24.98%) by using TGVCrapo&BodPod compared with TGVZ&R (Table 4).
Assumed values for tidal volume according to the manufacturer exceeded the measured values (0.7 L for girls and 1.2 L for boys vs. 0.6 L for girls and 0.7 L for boys, respectively). Tidal volume values predicted according to the child-specific equations of Zapletal et al. (14) were even lower (0.5 L for both girls and boys). Predicted values for FRC according to equations for adults by Crapo et al. (21) slightly exceeded the values obtained by the formula of Rosenthal et al. (13) (2.19 L girls and 2.02 L in boys vs. 1.85 L in girls and 1.94 L in boys, respectively). However, measured values of FRC were even lower in both sexes (1.60 L in girls and 1.80 L in boys).
Hydration and density of FFM.
Calculation of %FM from Db using Siri’s equation (22) integrated in the manufacturer’s software assumes an adult value of 1.1 g/cm3 for a constant density of FFM. By contrast, corrections of this equation for child-specific hydration of FFM are provided by Lohman (12). Comparing these 2 approaches irrespective of differences in SAA and TGV predictions resulted in an overestimation of 4.82%FM by Siri’s equation (Table 4).
Total difference for corrected vs. uncorrected ADP results.
There was a high correlation between %FM calculated according to the manufacturer’s software and the optimal child-specific correction of ADP results applying formulas from Haycock et al. (24) for SAA calculation, from Fields et al. (15) for prediction of TGV, and from Lohman (12) to correct for age-dependent differences in FFM-hydration (Fig. 1). Although the regression line showed a high R2 (0.95) and a low SEE (2.21%) there was a Y-intercept of 11% revealing a considerable overestimation of %FM using the uncorrected manufacturer’s software.
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DISCUSSION |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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The bias of 
2.97% in FM results derived from estimating SAA using the formula of DuBois and DuBois (20) compared with the formula of Haycock et al. (24) was higher than previously reported by Wells et al. (8), who found almost identical values of SAA from the 2 formulas (0.40 ± 0.05 L). However, in our study, the bias was highly dependent on BMI (see results); unlike in the study of Wells et al., overweight and obesity were highly prevalent in our study population. This would certainly contribute to the higher bias derived from SAA in our study, and our high BMI range may thus be an advantage with respect to revealing limitations of ADP application for body composition measurements in overweight and obese children. Consistent with this interpretation, Wells et al. (8) estimated that the difference for %FM in the 2 formulas approached 4% for children with ±3 BMI SD scores and they recommended the use of children’s equations to minimize error in very thin or fat subjects (14). Because the formula by DuBois and DuBois (20) is based on direct measurements of surface area in only 9 subjects including a 36-y-old with cretinism who had an underdeveloped physique, a tall, thin adult male, a short, obese adult female and only one 12-y-old boy, the formula by Haycock et al. (24) based on a larger number of 81 subjects and including infants and children may be more appropriate for use in children.
Bias derived from TGV estimation.
The overestimation of TGV predicted according to the manufacturer’s software compared with measured TGV was 576 mL in the present investigation (see results). In other studies, it was reported to be 190 mL in 37 children aged 10–18 y (4), 200 mL in 224 children aged 6–17 y (15), and 380 mL in 39 children aged 8–17 y (7). The last group of authors calculated the resulting error in %FM estimation to be 1.44%. By contrast, in 2 studies, equations used by the manufacturer did not affect body composition estimates (5,10). However, these authors investigated only 10 children (5) and 28 young adolescents (age 14.9 ± 0.5 y) (10).
Because the comparison of the 2 possibilities of child-specific TGV prediction yielded equal results in %FM (Table 4), the equations for TGV by Fields et al. (15) for children aged 6–17 y can be used interchangeably with the equations for tidal volume by Zapletal et al. (14) for children aged 6–17 y and FRC by Rosenthal et al. (13) for children aged 4–19 y. Because the equations by Fields et al. are easier to calculate and show less systematic bias (Table 5), it may be preferable to use them.
In a study including 28 children between 7 and 8 y, Wells et al. (8) reported an underestimation of FRC (0.79 ± 0.43 L vs. 1.17 ± 0.13 L, difference 0.38 ± 0.37 L) and an overestimation of tidal volume (0.61 ± 0.24 L) using the equations for adults in the manufacturer’s software compared with the child-specific equations of Zapletal et al. (14) and Rosenthal et al. (13). They concluded that because these differences cancel each other out, leaving a remaining difference of TGV of 0.07 ± 0.27 L and a difference in Vb of 0.02 L, pediatric rather than adult equations for lung volume estimation should be used (8). Our data do not confirm an underestimation of FRC by the formula of Crapo et al. (20). Even if we consider only our 52 children in the age range 5–7 y, similar values of FRC were predicted by the formulas of Crapo et al. and Rosenthal et al. (1.20 ± 0.37 L vs. 1.27 ± 0.12 L). Thus, our findings suggest that the main bias was due to overestimation of the tidal volume.
Although the BodPod device is able to measure TGV, the measurement does not solve the problem because the prediction of TGV may be advantageous in the case of repeated measurements during follow-up (e.g., in a weight reduction program) in which the effect of precision from TGV measurements on the technical error of FM assessment should be minimized. In addition, obtaining TGV measurements may be difficult in pediatric populations (4). In our study group, we were unable to obtain a measurement of lung volume after 3 trials in 30% of cases. Some authors generally apply TGV prediction instead of direct measurement in children (3,8,11).
Bias derived from the density of FFM.
A fixed density of FFM assumed by the manufacturer’s software suggests a constant composition of FFM. However, proportions of FFM as water (73%, 0.9937 g/cm3), mineral (6.8%, 3.038 g/cm3) and protein (19.4%, 1.34 g/cm3) tend to vary under certain conditions such as growth, serious sports, race/ethnicity, severe illness, and aging (25–29). In each of these circumstances, possible shortcomings of ADP have to be examined carefully. In our pediatric study population, not taking into account the change in density of FFM during growth contributed to an overestimation of 4.8%FM (Table 4). However, using values of FFM density predicted by Lohman (12) yields an approximation that also can result in a bias. Thus, Wells et al. (8) estimated a bias of 2.3%FM in 28 children 5–7 y old in a comparison of ADP results corrected for Lohman’s values for FFM density with measured values obtained by a 3-compartment model using deuterium dilution to measure FFM hydration. However, the calculation of FFM hydration from this 3-compartment equation suffers from the limitation that total body water is included in the denominator as well as the numerator; thus, any error concerning total body water is included in both terms and largely cancels out due to covariance (30). Two studies applied a 4-compartment model using ADP for measurement of Db in children (2,9). The use of age- and gender-specific values for FFM density to calculate %FM from Db by ADP achieved the following: 1) it was the only technique that could accurately, precisely, and without bias estimate FM compared with DXA or hydrostatic weighing in 9- to 14-y-old children (2); and 2) it resulted in the most accurate %FM estimates compared with the criterion 4-compartment model even in overweight and obese children (9).
Although it has to be emphasized that our study group was Caucasian and different results might have been obtained in other ethnic groups, we conclude that there is a need to use child-specific equations in ADP raw data analysis considering SAA, TGV, and density of FFM to avoid a considerable overestimation of %FM.
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FOOTNOTES |
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3 Abbreviations used: ADP, air-displacement plethysmography; Db, body density; FFM, fat-free mass; FM, fat mass; FRC, functional residual capacity; SAA, surface area artifact; TGV, thoracic gas volume; Vb, body volume.
Manuscript received 5 April 2005. Initial review completed 4 June 2005. Revision accepted 26 June 2005.
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LITERATURE CITED |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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