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American Journal of Clinical Nutrition, Vol. 85, No. 1, 66-72, January 2007
© 2007 American Society for Nutrition

ORIGINAL RESEARCH COMMUNICATION

Total body protein in healthy adolescent girls: validation of estimates derived from simpler measures with neutron activation analysis1,2,3

Verena K Haas, Jane R Allen, Michael R Kohn, Simon D Clarke, ShuHua Zhang, Julie N Briody, Margie Gruca, Sloane Madden, Manfred J Müller and Kevin J Gaskin

1 From the Departments of Adolescent Medicine (VKH and MRK), Nuclear Medicine (JNB), and Psychological Medicine (SM), and the James Fairfax Institute of Pediatric Nutrition (JRA, MG, SZ, and KJG), the Children's Hospital at Westmead, Sydney, Australia; the Centre for Research into Adolescent's Health, Westmead Hospital, Sydney, Australia (SDC); the University of Sydney, Sydney, Australia (KJG); the Meridian Clinic, Sydney, Australia (MRK); and the Institut für Humanernährung und Lebensmittelkunde der Christian–Albrechts–Universität zu Kiel, Kiel, Germany (VKH and MJM)

2 Supported by grants from the Centre for Research into Adolescent's Health, Westmead Hospital, Sydney, Australia; the James Fairfax Institute of Pediatric Nutrition, the Children's Hospital at Westmead, Sydney, Australia; and the DAAD, German Academic Exchange Service, Bonn, Germany.

3 Address reprint requests to MR Kohn, Department of Adolescent Medicine, the Children's Hospital at Westmead, Locked Bag 4001, Westmead NSW 2145, Australia. E-mail: michaek2{at}chw.edu.au.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Little recent and accurate information about body protein content in healthy adolescent girls is available.

Objective: The objective was to assess the total body nitrogen (TBN) and total body protein (TBPr) contents of fat-free mass (P:FFM) in a group of healthy adolescent girls and to validate previously published TBN prediction equations.

Design: TBN was measured with in vivo neutron activation analysis (TBNNAA). Bone mineral density and FFM were measured with dual-energy X-ray absorptiometry (FFMDXA), total body water and FFM were measured with bioimpedance analysis, and FFM was assessed by measuring skinfold thicknesses in 51 girls with a mean (±SD) age of 14.7 ± 0.7 y. The validity of the TBN prediction equations was assessed with Bland-Altman analysis.

Results: TBNNAA in our adolescent group was higher (1.49 kg) than values reported in earlier studies of women (1.25 and 1.31 kg), and P:FFM was slightly higher (23%) than that documented in adults (19–21%). Previously published TBN equations showed either systematic bias or wide limits of agreement.

Conclusion: A predictive equation derived from the present study population based on FFMDXA improves the prediction of TBN for groups of young girls but may not be helpful for individuals in clinical settings.

Key Words: Body composition • adolescents • total body protein • total body nitrogen • fat-free mass • neutron activation analysis • dual-energy X-ray absorptiometry • anthropometric measures • bioimpedance analysis


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Adequate dietary protein intake and protein deposition are essential to achieve normal growth in children and adolescents. However, what constitutes sufficient protein intake and deposition is less than certain. To determine minimal protein requirements for growing populations, the World Health Organization (WHO) developed guidelines in 1985. These guidelines relied on short-term nitrogen balance studies that were carried out in children and adults. Protein requirements for intermediate age groups were obtained by extrapolation after an allowance for growth increment was added (1). These guidelines clearly emphasize the considerable limitations of this method and the need for an accurate indicator of protein nutritional status, the need to identify protein inadequacy before clinically detectable changes occur, and the need to gather information on long-term protein accretion associated with normal growth.

Before NAA measurement, direct assessment of total body protein (TBPr) could only be achieved with chemical carcass analysis. In children, these chemical assessments were limited to very few subjects who died of severe illness or malnutrition (2-4) and thus were not representative of normal body protein content. Current studies often assess fat-free mass (FFM), which is then used as a surrogate for protein nutritional status, assuming that protein is a relatively fixed constituent of FFM (5). However, FFM is a heterogeneous body compartment consisting of water, protein, and bone. Adolescence, in particular, is a period characterized by growth and maturation known to be associated with significant changes in the composition of FFM (6-8). Common methods to measure FFM, such as dual-energy X-ray absorptiometry (DXA), anthropometric measures, and bioimpedance analysis (BIA) are only indirect measures of FFM, based on assumptions, and therefore need to be evaluated against a direct measure in children and adolescents.

TBN measurements with neutron activation analysis (NAA) provide a direct and accurate measure of TBPr. Although most centers with NAA facilities have not examined children because of unacceptably high levels of radiation, the Children's Hospital at Westmead has developed a low-radiation-dose facility specifically for pediatric use (9). Previously developed TBN prediction equations derived from NAA measurements were developed in adult groups of mixed sex with the use of a 5-compartment model based on NAA and tritiated water analysis (10) or from a regression analysis based on height and age (11). Our previously published pediatric TBN prediction equation was based on a group of 43 girls and boys aged 4–16 y in whom NAA and anthropometric measures were used (9).

The aim of this study was to accurately assess TBN, and its relation to other body compartments, in an exclusively adolescent female population to provide further reference data on body composition in this age group. Furthermore, we aimed to investigate whether TBN could be estimated with other techniques (DXA, BIA, and anthropometric measures) in adolescent girls. We therefore evaluated previously published TBN prediction equations derived from NAA measurements (9-11) and generated a new prediction equation based on data from our adolescent study population.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Study population
A multiethnic group of 51 healthy adolescent girls with a mean age of 14.7 y (range: 13.4–16.0 y) was recruited from a girls school in Westmead, Sydney, Australia. All study participants had been born in Australia, but had family backgrounds from 5 different ethnic groups: white or European Australian (n = 35), at least one parent from the Middle East (n = 8), at least one parent from Asia (n = 6), black African (n = 1), and Latin American (n = 1). Thirty-four girls were tested in the follicular phase (ie, days 1–10) and 17 were tested in the luteal phase (ie, after day 10) of their menstrual cycle. The Ethics Committees at the Children's Hospital at Westmead and Westmead Hospital approved the study protocol. Before participating, all girls and their parents gave informed written consent.

Anthropometric measurements
All measurements were performed on the same morning after the subjects had fasted overnight. Height (±0.1 cm) was measured with a stadiometer (Holtain Ltd, Crymych, United Kingdom) and body weight (± 0.1 kg) was measured with an electronic scale (model FW-150K; AND Tokyo, Japan) while the subjects were wearing light clothing. Body mass index (BMI) was calculated as body weight/height2 (in kg/m2), and SD scores for weight, height, and BMI were estimated from WHO reference data. Skinfold thicknesses were measured in duplicate on the dominant side of the body at 4 sites (biceps, triceps, subscapular, and suprailiac) with a Harpenden skinfold caliper (British Indicators Ltd, Hertfordshire, United Kingdom) by 2 trained investigators. Skinfold thickness data were used to calculate percentage body fat (%BF), fat mass (FM), and FFM (body weight minus FM) according to Slaughter et al (12). This equation, derived from a multicompartment model with hydrostatic weighing, deuterium dilution, and photon absorptiometry in a population of 132 females (age: 8–29 y), has an SEE of 3.8%.

Maturation status
Pubertal stage (breast and pubic hair development) was self-reported by the study participants on the basis of criteria developed by Tanner (13) and Duke et al (14).

Bioimpedance analysis
Resistance (R) and reactance (Xc) were measured at 50 kHz with a multifrequency bioelectrical impedance meter (model SFB3, version 1.0; SEAC, Queensland, Australia) with a tetrapolar arrangement of self-adhesive electrodes while the subject was supine on a nonconductive surface with their limbs slightly abducted. The impedance index (ZI) was calculated as height2 (m)/reactance. For 4 study participants, BIA data could not be obtained because of technical problems. To calculate FFM, the equation of Houtkooper et al (15) was used, which is based on underwater weighing and deuterium dilution in a study group of 225 young girls and boys aged 10–19 y (CV: 5.1%). To calculate total body water from BIA, a prediction equation was developed based on deuterium oxide dilution carried out in a subgroup of 14 normal-weight girls from our study population.

Deuterium oxide dilution
Subjects had fasted for ≥8 h and voided before receiving an oral dose of 0.4 g D2O/kg body wt that was mixed with drinkable water. It was previously shown that deuterium oxide reaches equilibrium in body fluids 3 h after administration (16); therefore, saliva samples were collected before and 3 h after administration. The deuterium oxide concentration was measured by Fourier transform infrared spectrophotometry according to Jennings et al (17), and TBW was calculated as deuterium dilution space x 0.99 (to correct for water space in saliva) x 1.04 (to correct for overestimation of TBW by the deuterium method). The precision of this method has been shown to be 0.1–0.9% (17).

Dual-energy X-ray absorptiometry
Bone mineral content (BMC) and soft tissue lean mass (STLM) were determined with a Lunar Prodigy whole-body scanner in conjunction with EnCORE software version 8.10 (Lunar Corp, Madison, WI). A whole-body scan takes <10 min, and involves a very low radiation dose of <0.02 mSv. FFMDXA was calculated as LTM + BMC assessed with DXA. The precision for this technique in vivo, as assessed at the hospital, was 0.82% for LTM (18).

Neutron activation analysis
TBN was measured by using a modification of the method of prompt {gamma} NAA with a single californium source as described previously (9). In the modified technique, we now expose subjects bilaterally to neutrons from two 252Cf sources placed above and below the scan table, which halves the scan time. 14N is converted to 15N with the emission of a 10.8-MeV {gamma} ray, and {gamma} ray emission is measured with 4 detectors. TBN is calculated as the integral under the nitrogen peak centered at 10.8 MeV on the {gamma} ray spectrum. The accuracy and precision of these techniques are both 3%, as determined from the measurement of nitrogen mass in child-sized boxes and anthropomorphic phantoms (19). The scan involves a radiation dose of <0.2 mSv and takes <10 min. Nitrogen can be assumed to be a constant constituent of protein (16% by weight), so that TBPr is derived from TBN by the equation TBPrNAA = 6.25 x TBNNAA (20).

Estimates of FFM and TBN
FFM was estimated by using skinfold thicknesses (FFMSF), BIA (FFMBIA), DXA (FFMDXA), and a modified 4-compartment model (FFM4CBIA) with TBPr derived from NAA, bone mineral from DXA, and total body water from BIA. We tested 1) the Baur equations used to calculate predicted TBN (PTBNBaur), which were developed earlier in our unit in a pediatric population on a single-source TBN machine and based on height and FFMSF (9); 2) the Ryde equation developed with 31 men and women and based on a 5-compartment model of body composition (10); and 3) the Ellis equation developed with a group of 61 women and based on height and age (11).

Formula 1(1)

Formula 2(2)

Formula 3(3)

Formula 4(4)
Prediction equations based on weight or SF measurements were not included because these parameters are commonly used to correct for hydrogen background when calculating TBN (19).

Statistical analysis
Statistical analyses were performed by using SPSS (version 11.5.1; SPSS Inc, Cary, NC). All data are presented as means ± SDs at a significance level of P < 0.05. Bland-Altman analysis was used to compare agreement between methods to assess TBN (21). Pearson correlation coefficients were used to describe the relation between 2 continuous variables, and stepwise regression was carried out to assess the predictive value of FFM measures to estimate TBN. Analysis was carried out with and without overweight subjects.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Body composition
General physical characteristics of the study population, maturation status, and body fat estimated with different methods are shown in Table 1Go. SD scores (SDS) relative to WHO reference data were 0.3 ± 1.1 for height, 0.4 ± 1.3 for weight, and 0.1 ± 1.0 for BMI. Many girls were overweight: eleven (22% of the study sample) according to the cutoff established by Cole et al of a BMI > 23.9 for 15-y-old girls (22); 4 of these girls could be classified as obese (BMI > 29.1). The prevalence of overweight subjects in our study sample reflected the population prevalence of overweight and obese persons reported in a large survey of young Australians (23).


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  		TABLE 1 General physical characteristics of the study population (n = 51) and body fat estimated with different methods1

 
Body protein, FFM determined according to the different techniques used in this study, and the composition of FFM are shown in Table 2Go. A 4-compartment model of body composition obtained by combining several measurement techniques is more robust to interindividual variability in the composition of FFM (8). Because our 4-compartment model includes BIA measurements of TBW and not a "gold standard" for TBW assessment, we compared TBW estimates from BIA with deuterium dilution in a subgroup of 14 normal-weight girls from our study group. Mean (±SD) values for TBW predicted with BIA and deuterium dilution were 28.2 ± 3.0 and 28.1 ± 3.6 L, respectively. No significant difference was observed between the means of the 2 methods (P = 0.914), and the r2 value was 0.70 when TBW values measured with the 2 methods were regressed against each other. The prediction equation was as follows:

Formula 5(5)
where ZI50 is the impedance index measured at 50 kHz. No significant difference was observed between the mean FFM values measured with different techniques. TBN content itself provides only limited information about nutritional status. It is common to express TBN in relation to weight or height (Figure 1Go). A strong relation was observed between TBN and both weight and height. The best fitting model to describe TBN in relation to weight was quadratic, whereas the association between TBN and height was linear. Even though the "surplus" weight of the overweight subgroup did not appear to be stored as nitrogen, all overweight subjects had a relatively high TBN content. No significant difference was observed in TBN between the 13 girls with a Tanner stage of ≤3 (1.44 ± 0.22 kg N) and those with a Tanner stage of 4 to 5 (1.52 ± 0.18 kg N).


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  		TABLE 2 Fat-free mass (FFM) and FFM composition of the study population (n = 51)1

 

Figure 1
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  		FIGURE 1. Relation between total body nitrogen (TBN) measured by neutron activation analysis and body weight and height in 51 adolescent girls by regression analysis. Normal weight and overweight were defined according to Cole et al (22). A: y = 0.011x + 0.881 (linear regression), r2 = 0.54, P < 0.001; y = –0.0003x2 + 0.0514x – 0.3218 (quadratic regression), r2 = 0.70, P < 0.001). B: y = 2.1469x – 2.002, r2 = 0.65 (linear regression), P < 0.001.

 
To determine whether TBN can be estimated with simpler techniques that assess FFM, we examined the relation between TBN and estimates of FFM from DXA (Figure 2Go) and BIA (Table 3Go). FFMSF was not included because %fat based on SF is part of the TBN calculation to correct for hydrogen background (19), and FFM4CBIA was not included because our 4-compartment model was derived with the use of TBN data. On the basis of the methods and equations used in the current study, FFMDXA was more closely associated with TBN than was FFMBIA (r2 = 0.81 compared with r2 = 0.64; Table 3Go) and was therefore used subsequently to generate TBN prediction equations. Exclusion of the overweight participants improved the associations between TBN and FFMDXA (Table 3Go).


Figure 2
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  		FIGURE 2. Relation between fat-free mass measured by dual-energy X-ray absorptiometry (FFMDXA) and total body nitrogen measured by neutron activation analysis (TBNNAA) in 51 adolescent girls by linear regression analysis. Regression equation: y = 0.033x + 0.218, r2 = 0.81, SEE = 2.3 kg FFMDXA, or 6% of the group mean FFMDXA.

 

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  		TABLE 3 Associations between fat-free mass (FFM) assessed with different methods and total body nitrogen measured by neutron activation analysis (TBNNAA)1

 
TBN predicted from height, weight, and FFM
Agreement between TBNNAA and previously developed TBN prediction equations, and the prediction equation developed with regression analysis of our current data, is shown in Table 4Go. Because techniques to assess body composition have different accuracies in normal-weight and overweight populations, the normal-weight subgroup was also analyzed separately. For both groups, close agreement was provided by the prediction equations derived from FFMDXA that were developed in our unit. For these equations, prediction power improved slightly when overweight subjects were excluded. The Ellis equation performed well in both groups, although it was developed in women. With the Ryde equation, which was developed in a group of adults, including males, TBN was underestimated in both of our adolescent groups. The Bland-Altman plots shown in Figure 3Go give more detailed information about the agreement between selected methods.


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  		TABLE 4 Analysis of agreement for total body nitrogen (TBN) prediction equations1

 

Figure 3
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  		FIGURE 3. Bland-Altman plots comparing total body nitrogen measured by neutron activation analysis (TBNNAA) with TBN predicted with the Baur equation on the basis of height (A), with TBN predicted with the Baur equation on the basis of fat-free mass measured by bioimpedance analysis (FFMBIA) (B), and with TBN predicted with the Gaskin equation on the basis of FFM measured by dual-energy X-ray absorptiometry (FFMDXA) (C) in 51 normal-weight (•) and overweight ({circ}) adolescent girls. The broken lines represent mean bias, and the unbroken lines represent the upper and lower limits of agreement (Formula 5 bias ± 1.96 SD).

 
As expected, TBN predicted according to the equation derived from the normal-weight group in the present study population showed the smallest limits of agreement (–134 to 136 g N; data not shown), which, however, is still equivalent to just <10% of the mean TBNNAA. TBN predicted according to Baur on the basis of height showed a negative systematic bias, which suggests that the underestimation of TBN increases as TBN increases. In a regression analysis with weight as an independent variable and this bias as a dependent variable, weight was a significant predictor of the bias (P = 0.001). This implies that TBN in the heavier and taller girls will be underestimated when based on height, which is also evident from Figure 1Go. The mean bias close to zero for TBN predicted according to Baur and FFMBIA for all girls could be explained by an underestimation of TBN in the normal-weight participants that was compensated for by an overestimation of TBN in the overweight participants (Figure 3GoB). In the normal-weight group, TBN was underestimated when based on FFMBIA (Table 4Go).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
This study accurately describes total body nitrogen (TBN) content and its relation to other body compartments in a group of adolescent girls. The TBN values of the adolescent girls were higher than those reported previously for women (10, 11), and the protein content of FFM was slightly higher than that expected from early chemical studies of the protein content of children (2-4).

TBN in relation to weight, height, and FFM in adolescent girls
In our group of healthy girls, TBN was closely associated with height (Figure 1GoB) and also with weight, although not linearly (Figure 1GoA). Describing nitrogen in relation to weight does not account for the fact that most of the "surplus" weight in overweight subjects normally consists of fat and not protein. Even though this was true for our overweight subjects, we also showed that the body nitrogen content of all overweight girls was relatively high when considering the entire study group. The adolescent group in our study had higher TBN values (1.49 kg) than did adult women in 2 other studies: 1.25 kg (10) and 1.31 kg (11). This difference can be explained by the fact that protein mass is building up during puberty (24) and decreases in adulthood with increasing age. Our data agree with those of Cohn et al (25), which showed that TBN was 1.45 kg in healthy women 20–29 y of age and steadily decreased to 1.15 kg at 70–79 y of age.

Composition of FFM
From earlier chemical studies, it is suggested that protein is a relative constant of FFM in specific age groups, rising from 3.7% at birth to {approx}17% at 1 y and to between 19% and 21% in adults (2, 4). More recent studies involving NAA have confirmed these numbers in adults (10). To our knowledge, no comparable data are available for adolescents. The P:FFM ratio calculated with the help of a 4-component BIA model in the current study, 23.2%, is slightly greater than the value of 19–21% reported for adults. FFM hydration in our study population (71.2%) was also similar to adult values of between 72% and 73% (26). However, the FFM mineral content of 5.6% in our study was lower than the value of 7% reported for adults and closer to the value of 5% reported previously for children (8). Our analysis of FFM composition also showed that the mineral and protein contents varied more than did the content of water; the CVs for mineral and protein contents were 8.0% and 9.1%, respectively, but the CV for water content was only 2.8%. This finding is consistent with the study by Wells et al (8) in children. Our data confirm earlier findings that the protein chemical maturity of FFM is reached by 14.5 y in girls (27). The higher P:FFM ratio in the 4-compartment BIA model than in earlier chemical studies may be variously explained. FFM estimates depend on the methodology and their assumptions and could be inaccurate. Unfortunately, our study did not involve a "gold standard" test for FFM, and underestimating FFM will lead to an overestimation of the protein content of FFM. However, there might be more than just a methodologic reason for the observed discrepancy. Studies involving chemical carcass analyses were done in severely malnourished or diseased persons in whom not only absolute protein stores, but also TBPr in proportion to FFM, might have been significantly altered. Evidence exists that P:FFM adapts to nutritional status. The nitrogen content of lean body mass was found to be lower in malnourished cystic fibrosis patients than in well-nourished cystic fibrosis patients (28) and to increase in patients with anorexia nervosa during refeeding (29). Lastly, because of these early chemical studies, people have changed their lifestyle and dietary habits and are most likely better nourished than they were 40 y ago. It is tempting to speculate that the body protein content of FFM is gradually and steadily increasing, both in developing civilizations and in advancing generations.

Validation of TBN prediction equations
When cross-validating previously published TBN formulas with our study population, it became clear that formulas are less suitable when based on height or weight than when based on a DXA-derived measure of FFM and the inclusion of overweight subjects weakens their predictive power. We also conclude that both the sex and age of the study population used to derive the TBN prediction models are important factors that should be taken into account, as has been documented by other authors for different body-composition models. Additionally, we generated a prediction equation from our study population, based on FFM measured with DXA, which is a useful tool when estimating TBN in groups of adolescent girls in research settings where NAA is not available. Specifically, it could be helpful in future studies involving malnourished young girls to detect and quantify changes in body protein. However, clinical application to achieve TBPr assessment without NAA measurements cannot be achieved with our DXA model because of a residual variance of 10% in the TBN group mean. We suggest 2 explanations for this residual variance. First, it might originate from methodologic bias when FFM is measured indirectly with DXA. Studies that have assessed the body composition of animals in vivo and chemically show that DXA can provide accurate measures of FFM (30, 31). However, many authors have cautioned against the use of DXA as a reference method for body composition, other than for bone mineral content, in humans (32, 33). Second, the variance might point to the fact that the nitrogen content per unit FFM is an individual characteristic and is thus subject to biological variation.

Study limitations
Because the cohort was relatively small, it did not allow for random division of the participants into 2 groups to test the regression equations developed in the current study. Therefore, and also because of the narrow age range and diverse ethnicity of our study population, caution should be used when extrapolating the data to other populations. In addition, our analysis was complicated by the fact that >20% of our study participants were overweight. Even though our group represented a typical female adolescent Australian population, our overweight group was too small to carry out a separate analysis to better elucidate the effect of overweight on body-composition techniques and the protein content of FFM.

Conclusions
In our adolescent study population, TBN values were higher than those previously described for women, and the protein content of FFM was also higher than values observed in early chemical studies. A prediction model based on DXA measurements of FFM developed in this study can accurately predict the TBN content in a group of young adolescent girls, but not in individuals. This model will be helpful in future studies of the body nitrogen content of malnourished adolescent girls.


   ACKNOWLEDGMENTS
 
We thank Madeleine Thompson for assistance with the body-composition measurements.

VKH collected and analyzed the data and wrote the manuscript. JRA, SZ, JNB, and MG collected the data. KJG, MRK, and MJM: designed the study and provided advice. SDC and SM provided advice. None of the authors had a conflict of interest.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication May 5, 2006. Accepted for publication August 22, 2006.





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