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1 From the Department of Animal Science, the University of California, Davis (RDS), and Life Measurement Inc, Concord, CA (AU).
2 Supported by California Agricultural Experiment Station Project number CA-D*-ASC-6548-H and Life Measurement Inc, Concord, CA. 3 Address reprint requests to RD Sainz, Department of Animal Science, University of California, Davis, One Shields Avenue, Davis, CA 95616-8521. E-mail: rdsainz{at}ucdavis.edu.
ABSTRACT
Background: Body-composition assessment reflects infant growth and nutritional status but is limited by practical considerations, accuracy, and safety.
Objective: This study evaluated the precision and accuracy of a new air-displacement plethysmography (ADP) system for pediatric body-composition assessment.
Design: We used 24 phantoms constructed from bovine lean muscle and fat. The phantoms varied in mass (1.3894–9.9516 kg) and percentage fat (%Fat; 2.08–34.40%), thereby representing infants between birth and 6 mo of age. Estimates of %Fat obtained with chemical analysis (CA), hydrostatic weighing, and ADP were compared.
Results: There was no significant difference between %Fat measured with ADP (%FatADP) and %Fat measured with CA (%FatCA); the mean values were 18.55% and 18.59%, respectively. SDs for %FatADP and %FatCA were not significantly different (0.70% and 0.73%, respectively). %Fat measurements obtained with ADP, CA, and hydrostatic weighing were highly correlated (r > 0.99, P < 0.0001). The regression equation (%FatCA = 0.996%FatADP + 0.119; SEE = 0.600; adjusted R2 = 0.997; P < 0.0001) did not differ significantly from the line of identity (%FatCA = %FatADP). There was high agreement between individual measurements of %FatADP and %FatCA, as shown by the narrow 95% limits of agreements between methods (-1.22% to 1.13%), and there was no systematic bias in individual differences across the phantom mass and %Fat ranges.
Conclusion: ADP provides a highly precise and accurate estimate of %Fat in bovine tissue phantoms in the pediatric ranges of body weight and body fatness.
Key Words: Body composition • infants • air-displacement plethysmography • chemical analysis • precision • accuracy • body fat • infant growth • infant nutrition • pediatrics • pediatric nutrition
INTRODUCTION
Body-composition assessment is recognized as the most accurate method of measuring infant growth and nutritional status. However, because of the specific challenges associated with the infant population, body-composition assessment has yet to replace length and weight measurements as the standard method of evaluating infant growth and nutritional status. In fact, even though various methods have been used to measure infant body composition (1), their use has been restricted because of practical considerations, training requirements, limited availability, cost, accuracy, and safety.
Air-displacement plethysmography (ADP) is a method used to measure body composition in children, adults, and the elderly (2–4) that has yet to be applied in the infant population. ADP uses gas laws to determine body volume, which is used with body mass to compute body density. Body density is then used in a 2-compartment model (5, 6) to determine fat mass, fat-free mass, and percentage fat (%Fat).
The only commercially available ADP system is the BOD POD Body Composition System (Life Measurement Inc, Concord, CA), which has been used to measure body composition in different populations (2–4). Compared with 2-, 3-, and 4-compartment models, the ADP testing procedure offers greater accuracy and simplicity, allowing for the evaluation of children, adults, and the elderly (2, 4). Therefore, ADP has the potential to be applied successfully in the infant population.
The present study was designed to evaluate the precision and accuracy of a new pediatric ADP system, the PEA POD Infant Body Composition System (Life Measurement Inc, Concord, CA), in reference to chemical analysis (CA). We tested this ADP system using bovine tissue phantoms varying in mass and fat content. Hydrostatic weighing (HW) was also performed. This study was part of the development of PEA POD; the objective was to assess its potential use for body-composition assessment in the pediatric population.
MATERIALS AND METHODS
Air-displacement plethysmography system
Although the pediatric and adult ADP systems differ in layout, the pediatric ADP system used in this study has the same theoretical basis for the calculations and operation principles reported previously in detail for the adult ADP system (7). A concise overview of the pediatric ADP system used in this study follows. The PEA POD is an ADP system consisting of 2 chambers, a test chamber and a reference chamber, connected by a volume-perturbing diaphragm. The diaphragm creates volume changes in the 2 chambers that are equal in size but opposite in sign. The opening and closing of a calibration valve allows the test chamber to be connected to a known reference volume used to calibrate the system. The test chamber is mounted on the top surface of a movable cart with the reference chamber and calibration volume housed inside the cart along with the electronic components, computer, printer, keyboard, and mouse. Both chambers are made of clear acrylic plastic. An electronic scale and a computer screen are secured to the top surface of the cart.
Each ADP test is preceded by an automated system calibration. Pressure changes associated with volume perturbations are continuously monitored and recorded in both chambers. These pressure changes never exceed 1 cm of H2O. During calibration, the test chamber is emptied and the calibration valve is kept closed initially and then opened. The pressure changes collected during this procedure and the known calibration volume are used to perform a 2-point calibration, which results in a linear relation between the ratio of the pressures recorded in the 2 chambers and changes in volume in the test chamber.
During a test, the subject or object being tested is placed in the test chamber with the calibration valve open. The ratio of the pressures recorded in the 2 chambers is then used to compute the volume of the subject or object being tested. For this study, the calibration procedure and each measurement period lasted 50 s.
The ADP principles used to calculate volumes from pressure measurements result from the different ways that air behaves under isothermal and adiabatic conditions. Under isothermal conditions, air temperature remains constant as its volume changes. In contrast, under adiabatic conditions, air temperature does not remain constant as its volume changes. Boyle’s Law and Poisson’s Law govern the compressibility characteristics of gases under isothermal and adiabatic conditions, respectively. These laws are expressed as follows:
RESULTS
By design, the phantoms varied widely in mass (1.3894–9.9516 kg) and %Fat (2.08–34.40%). The average SD for mass was 0.0039 kg. The SDs for %FatADP and %FatCA were not significantly different from each other (0.70% and 0.73% for ADP and CA, respectively) (Table 1). To assess whether measurement variability was similar across the range of %Fat values, CV values were compared among the 4 %Fat subgroups. The CV values for the mass and %FatCA measurements did not differ significantly among the 4 %Fat subgroups. However, the CV values for %FatADP were significantly different among the 4 %Fat subgroups (P = 0.001), with a higher mean CV (18.14%) in the lowest %Fat subgroup than in the other 3 subgroups (4.13%, 2.58%, and 3.21%) (Table 2).
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TABLE 1 . Mass and percentage fat of individual phantoms, determined by using chemical analysis (%FatCA), air-displacement plethysmography (%FatADP), and hydrostatic weighing (%FatHW), in 4 %Fat subgroups
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TABLE 2 . Measurement variability of repeated measurements on individual phantoms of mass and percentage fat by air-displacement plethysmography (%FatADP) and chemical analysis (%FatCA), by %Fat subgroup
There were high correlations (r > 0.99, P < 0.0001) for each of the 3 possible combinations of %Fat measurement techniques (ADP, CA, and HW) (Table 3). Mean %FatADP did not differ significantly from mean %FatCA (18.55% and 18.59%, respectively; P = 0.917), but there was a significant difference between %FatHW and %FatCA (18.29% and 18.59%, respectively; P = 0.028).
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TABLE 3 . Correlations among the 3 techniques for measuring percentage fat: chemical analysis (CA), air-displacement plethysmography (ADP), and hydrostatic weighing (HW)1
Linear regression and Bland-Altman analyses of %FatADP and %FatCA (Figure 1) indicated a high degree of agreement. The regression equation (%FatCA = 0.996%FatADP + 0.119) gave very low SEE and very high adjusted R2. The slope and intercept of the regression line were not significantly different from 1 and 0, respectively (left panel). Furthermore, the 95% limits of agreement from Bland-Altman analyses were -1.22% to 1.13% Fat, with no trend in %FatADP - %FatCA as %Fat varied (right panel). In addition, the mean difference between ADP and CA (ie, %FatADP - %FatCA) was -0.04% fat, with individual differences ranging from -1.54 to 0.81% fat.
FIGURE 1. . Comparison of percentage fat (%Fat) values determined by using chemical analysis (CA) and air-displacement plethysmography (ADP) in 24 bovine tissue phantoms. Linear regression (left panel) of %FatCA on %FatADP (%FatCA = 0.996%FatADP + 0.119, SEE = 0.600, adjusted R2 = 0.997, P < 0.0001) and its Bland-Altman plot (right panel), in which the solid line shows the mean difference between methods (bias) and the dotted lines represent ± 2 SDs from the mean difference (95% limits of agreements).
Regression analysis was also performed to assess whether the differences between %FatADP and %FatCA were a function of phantom mass. As shown in Figure 2, the differences in %Fat between methods were not significantly related to phantom mass (r < 0.0001, P = 0.33), indicating that none of the individual differences were a function of phantom mass.
FIGURE 2. . Differences between percentage fat (%Fat) values determined by using air-displacement plethysmography (ADP) and %Fat values determined by using chemical analysis (CA) for individual phantoms regressed against phantom mass; the differences in %Fat between methods were not significantly related to phantom mass (r < 0.0001, P = 0.33).
DISCUSSION
This was the first study to evaluate the performance of a new ADP system designed for the infant population using CA of bovine tissue phantoms as the reference method. Our data suggested that ADP provided precise and accurate measurement of %Fat when compared with CA of phantoms in the pediatric ranges of body weight and body fatness.
The unique feature of the study design was that we used phantoms with wide ranges of mass and %Fat values. The ranges of mass (1.3894–9.9516 kg) and %Fat (2.08–34.40%) of the phantoms tested covered the ranges of body weight and body fatness of preterm and term infants from birth to 6 mo of age, for which the ADP system was designed. This represented an improvement over previous studies designed to evaluate other methods of infant body-composition assessment as compared with CA; in these studies, the ranges of body weight, body composition, or both of the animals tested did not cover the ranges most often found in infants (13, 14). In the present study, the use of fabricated bovine tissue phantoms enabled evaluation of all possible combinations of mass and %Fat categories within the selected ranges, without confounding of these factors.
The precision (expressed as SD) of both the ADP and CA methods was found to be excellent for assessing the %Fat of phantoms varying in mass and fat content. SD values for the 2 methods were not significantly different from each other, indicating that the precision of ADP compared favorably to that of CA. It was found that with the ADP method, CV values were higher for the lowest %Fat subgroup, but this should not be considered a problem in practical applications as long as enough measurements are taken to obtain a mean value representative of the true value. This was the case in the present study, as shown by the high accuracy of ADP compared with CA even in the lowest %Fat subgroup; the results suggest that 6 ADP measurements should be performed to obtain accurate results.
The results of this study indicate excellent agreement between %FatADP and %FatCA. In this regard, the 2 methods gave virtually identical mean values for %Fat and very close individual results. Regression analysis of %FatADP against %FatCA gave very low SEE and very high R2, with the intercept and slope not significantly different from 0 and 1, respectively. Furthermore, it is important that a method be valid on an individual basis in addition to reporting statistics for the group. There was excellent agreement between %FatADP and %FatCA for individual phantoms; for 22 of 24 phantoms (92%), the difference between methods was less than ± 1%, and these differences were not related to fat content or mass.
Even though HW is not applicable for infant body-composition assessment, it was included in this study because it has been used frequently as a reference technique when evaluating ADP, and this study afforded for the first time the opportunity to compare HW and ADP to CA, which is considered the best reference method. As specified above, the 3 methods gave almost identical mean values for %Fat. Although there was a significant difference between %Fat measured with HW and with CA, this difference (18.29% and 18.59% for HW and CA, respectively) is most likely negligible from a clinical standpoint.
Concerning infant body-composition assessment, there is currently no method for measuring body fatness that has been found safe, precise, and accurate. The most frequently used methods include dual-energy X-ray absorptiometry (DXA), total body electrical conductivity, and skinfold-thickness measurements.
Many studies have evaluated DXA for assessing body composition by comparing it to CA of animals in the pediatric body weight range. Recently, Speakman et al (15) used DXA to measure the body composition of 16 animals (weighing between 1.8 and 22.1 kg) and subsequently performed CA of the carcasses. The study results indicated that on average, DXA provided acceptable estimates of fat mass (r = 0.98, mean percentage error = 2.04%). However, individual errors were much greater, ranging from underestimates of 20.7% to overestimates of 31.5%. In other validation studies using animal models, fat contents (in grams or % of weight) measured with both DXA and CA were generally highly correlated (r > 0.96), and the percentage errors between DXA estimates and CA measurements averaged < 15% (13, 14, 16–21). Such studies found that the mean discrepancies in the estimated fat content across a group of animals were relatively small, but the variations between individuals were found to be 2–10 times greater than the mean errors. Further, the individual variations were occasionally related to body size, fat content, or the scanning program and software solutions for scan analysis (13, 17, 22, 23). In most of these studies, calibration of DXA to the laboratory standard of carcass analysis (ie, using conversion equations or correction factors for DXA) was applied to improve the accuracy of DXA measurements (13, 16, 18, 24–26). However, even the calibrated results from DXA measurement were only valid for a specific machine with a specific software version and for a specific subject population for which CA could be performed. Therefore, it would be inappropriate to use these conversion equations or correction factors with infants. In contrast, the ADP system evaluated in this study did not require conversion equations or correction factors, and therefore it would be appropriate for use in infants and would result in accurate measurements when compared with other available methods, even though the percentage errors for ADP were found to be similar to those described above for DXA.
Total body electrical conductivity has been validated against CA for measuring fat-free mass in minipigs (27), but limited reports of critical validation and cross-calibration with other techniques for infant body-composition measurements indicate that the accuracy of individual fat estimates obtained with total body electrical conductivity is relatively poor (1).
Body-composition data derived from skinfold-thickness measurements correlated well with data obtained by using other techniques, but had poor agreement for individual measurements of body composition (28, 29). Further, skinfold-thickness measurements involve multiple sources of potential error (ie, the equipment, the techniques, and the observer), which restrict its use to field studies and group comparisons.
In summary, ADP was found to be a highly precise and accurate method for measuring %Fat compared with CA of phantoms in the pediatric ranges of body weight and body fatness. These results are encouraging in light of the potential for ADP to be useful in the infant population. Body-composition assessment in infancy has always been characterized by difficulty in obtaining accurate measurements on an individual basis. In addition, infant body-composition assessment requires a noninvasive testing procedure that involves minimal subject compliance. The ADP system used in this study has these characteristics. Moreover, in addition to the precision and accuracy shown in this study, the ADP system is rapid and noninvasive and has the potential to be very well tolerated by infants, as shown by the successful use of ADP in special populations (2, 4). Therefore, further studies should be conducted to assess the performance of ADP in infants.
ACKNOWLEDGMENTS
We are grateful to R Vernazza for technical assistance with data collection. R Sainz and A Urlando were responsible for the study design, conducting the study, and analyzing the data and they wrote the manuscript. R Sainz has no affiliations with the institutions sponsoring this research. A Urlando is an employee of Life Measurement Inc.
REFERENCES