1. The University of Alabama, Tuscaloosa, AL
BODY FAT PERCENTAGE MEASURES VIA FOUR-COMPARTMENT MODEL WHEN PREDICTING RESIDUAL LUNG VOLUME
Brett S. Nickerson, Bailey A. Welborn, Kelsey A. Pezzuti, Phillip A. Bishop, and Michael R. Esco
The University of Alabama, Tuscaloosa, AL
Table 1. Comparison of 4C model BF% when simultaneously measuring and predicting BV measurements (n = 80)
Abstract
Methods
RLV Method
Mean ± SD P
Cohen’s d R
SEE CE
Limits
Simultaneous RLV
22.1 ± 7.4 -
RLV_Boren
22.1 ± 7.0
0.729
0.00
0.98
1.3
0.1
2.7, -2.6
RLV_GB
20.6 ± 6.8
<0.001
0.21
1.5
-1.5
1.5, -4.4
RLV_Miller
22.3 ± 7.0
0.112
-0.03
0.2
2.8, -2.3
Residual lung volume (RLV) is a major factor to consider when determining body volume (BV) from underwater weighing (UWW). However, RLV measures are often difficult to obtain as lack of equipment and issues with subject compliance are common. Therefore, prediction equations for RLV exist. BV is an important metric within the four-compartment model (4C) approach to measuring body fat percentage (BF%). PURPOSE: The purpose of this study was to compare 4C model BF% values when RLV for BV was either simultaneously measured or predicted. METHODS: Eighty participants (47 women and 33 men) volunteered for this study (age 21.9 ± 4.8 years, height = ± 10.0 cm, weight = 68.4 ± 14.3 kg). Criterion BF% was determined with the Wang 4C model, which included body mass, BV via UWW and simultaneous RLV, total body water via bioimpedance spectrscopy, and bone mineral content via dual energy x-ray absorptiometry. RLV prediction equations derived by Boren et al. (Equation 1), Goldman and Becklake (Equation 2), and Miller et al. (Equation 3) were also used to determine BV via UWW and then used to calculate 4C BF%. The average of the three highest underwater weight values (6 to 10 trials) was used for calculating BV via UWW. RESULTS: Mean BF% for criterion 4C BF%, Equation 1, Equation, 2, and Equation 3 was 22.1 ± 7.4%, 22.1 ± 7.0%, 20.6 ± 6.8%, 22.3 ± 7.0% respectively. No significant mean difference was seen for Equation 1 (p > 0.05, Cohen’s d = 0.0, r = 0.98) and Equation 3 (p > 0.05, Cohen’s d = 0.02, r = 0.98) versus the criterion 4C BF%. Equation 2 resulted in a significantly lower (p < 0.001, Cohen’s d = 0.21, r = 0.98) BF% compared to the criterion 4C BF%. The SEE for Equation 1, Equation 2, and Equation 3 was 1.3% 1.5%, and 1.3% respectively when compared to the criterion 4C BF%. CONCLUSIONS: The non-significant mean differences, trivial effect size, near perfect correlation, and low SEE in BF% values obtained via Equation 1 and Equation 3 suggest the prediction of RLV during BV measurements in a 4C model is acceptable. Equation 2 produced a significantly lower mean BF% than the criterion 4C BF%, which suggest the prediction of RLV with Equation 2 should be done with caution. PRACTICAL APPLICATIONS: When simultaneous RLV is not available in 4C model body composition testing, Equation 1 and Equation 3 are recommended for use when determining BV via UWW. Conversely, Equation 2 should not be utilized for determining BV measurements due to the significantly lower mean BF% values.
Eighty adults (47 women and 33 men) volunteered to participate (age 21.9 ± 4.8 years, height = ± 10.0 cm, weight = 68.4 ± 14.3 kg).
Prior to body composition testing, all participants were required to be hydrated and provide a urine specific gravity <
Once hydration was confirmed, subjects had their height and weight measured.
After height and weight measurements, subjects laid on a gurney for 5 min and had TBW determined with bioimpedance spectroscopy.
Dual energy X-ray absorptiometry was then administered to determine subjects’ BMC.
Lastly, UWW with simultaneous RLV was used to determine BV. Subjects completed 6-10 UWW trials and the 3 highest underwater weights were averaged and used with the three RLV prediction equations to estimate BV.
4C = four-compartment; BF% = body fat percentage; RLV = residual lung volume; RLV_Boren = RLV prediction model from Boren et al. (1966); RLV_GB = RLV prediction model from Goldman and Becklake (1959); RLV_Miller = RLV prediction model from Miller et al. (1998); SEE = standard error of estimate; CE = constant error
Effect sizes were trivial to small
SEE < 1.5% for all RLV equations used to predict BV
Correlations were near perfect.
Results
Conclusions
Boren et al. (1966) and Miller et al. (1998) can both be used to predict RLV when determining BV measurements that will be used to calculate 4C model BF%.
Caution should be employed when using the RLV equation from Goldman and Becklake (1959).
Practical Applications
Simultaneous measurement of RLV might not be available. Furthermore it is time consuming and expensive.
When 4C model BF% is being determined, health and fitness professionals can predict RLV during the UWW procedure for BV measurements with the equations of Boren et al. and Miller et al. instead of simultaneously measuring it.
Intro & Purpose
RLV equations have been developed as an alternative to measured RLV, but these equations have produced large error when used for estimating UWW BF%
The impact of predicting RLV for BV in the 4C model has yet to be determined
The purpose of this study was to compare 4C model BF% values when RLV for BV was either simultaneously measured or predicted.
Figure 1. Mean between the 4C model BF% determined with the RLV equations and simultaneously measured RLV (n = 82)
*4C model with RLV equation was significantly different than 4C model with simultaneous RLV p < 0.001