• Journal of Biomedical Engineering Research
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• v.23 no.5
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• pp.413-418
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• 2002

The purpose of this study was to design a single frequency BIA(Bioelectrical Impedance Analyzer) which can measure body impedance when patient is sitting on the toilet and to develope a prediction equation for designed BIA. For the purpose of this study, we acquired body impedances with designed BIA from 181 subjects composed of healthy Korean by attaching electrodes to suitable positions(wrist and thigh) for toilet measurement. We computed an appropriate FFM(Fat Free Mass) for Korean using modified-Siri equation to the same subjects instead of Siri equation which nay cause accuracy problems in hydrodensitometry when it applied to Korean. We used this FFM as reference value and developed a Korean FFM prediction equation based on body impedance index, body weight and sex. Correlation coefficient between prediction value and reference value of FFM was extremely high (r = 0.977) and SEE(Standard Error of Estimation) was low 2.47kg.(p<0.05) For comparison between existing electrode-attaching method and our method for toilet measurement, we acquired body impedance with designed BIA from same subjects attaching electrodes on existing positions (wrist and ankle) and made FFM prediction equation for BIA. Correlation coeffient between predicted value and reference value was 0.978 and SEE was 2.43kg(p<0.05). It means that the developed system has not significant differences with existing method. In conclusion bioelectrical impedance analyzer and the FFM prediction equation developed in this paper are evaluated to he adequate to compute FFM of Korean.

• Nutrition Research and Practice
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• v.9 no.4
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• pp.370-378
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• 2015

BACKGROUND/OBJECTIVES: Athletes generally desire changes in body composition in order to enhance their athletic performance. Often, athletes will practice chronic energy restrictions to attain body composition changes, altering their energy needs. Prediction of resting metabolic rates (RMR) is important in helping to determine an athlete's energy expenditure. This study compared measured RMR of athletic and non-athletic adolescents with predicted RMR from commonly used prediction equations to identify the most accurate equation applicable for adolescent athletes. SUBJECTS/METHODS: A total of 50 athletes (mean age of $16.6{\pm}1.0years$, 30 males and 20 females) and 50 non-athletes (mean age of $16.5{\pm}0.5years$, 30 males and 20 females) were enrolled in the study. The RMR of subjects was measured using indirect calorimetry. The accuracy of 11 RMR prediction equations was evaluated for bias, Pearson's correlation coefficient, and Bland-Altman analysis. RESULTS: Until more accurate prediction equations are developed, our findings recommend using the formulas by Cunningham (-29.8 kcal/day, limits of agreement -318.7 and +259.1 kcal/day) and Park (-0.842 kcal/day, limits of agreement -198.9 and +196.9 kcal/day) for prediction of RMR when studying male adolescent athletes. Among the new prediction formulas reviewed, the formula included in the fat-free mass as a variable [$RMR=730.4+15{\times}fat-free\;mass$] is paramount when examining athletes. CONCLUSIONS: The RMR prediction equation developed in this study is better in assessing the resting metabolic rate of Korean athletic adolescents.

• Journal of Korean Medicine for Obesity Research
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• v.5 no.1
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• pp.57-66
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• 2005

Objectives : The purpose of this study is to examine accuracy of predicted resting energy expenditure (REE), relationship fat free mass (FFM) and REE. Methods : 60 normal, obese women $(body\;mass\;index\;{\geq}25kg/m^2)$ were recruited for this study, they had low calorie diet for 8 weeks. At week 0, 4, and 8, REE was measured by MedGem (indirect calorimeter), Bioelectrical impedance analysis (BIA) using Cunningham equation, and Harris-Benedict (H-B) equation, FFM was also measured by BIA. Results : The REE predicted by BIA was lower than the REE measured by MedGem (MG) in every measurement. The REE predicted by H-B equation predicted REE was lower than that of MG in the second measurement (p<0.01). The REE measured by MedGem was declined after 8 weeks, BIA and H-B equation predicted REE were declined after 4 weeks (p<0.01). H-B equation predicted REE had more significant correlation with the REE measured by MedGem than that of BIA. There was significant correlation between measured REE and FFM, but measured REE declined after 8 weeks, FFM declined after 4 weeks (p<0.01). We derived a prediction equation as follows : REE = 108.36+31.42 (FFM), $R^2=0.23$.

• Journal of the Korean Dietetic Association
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• v.13 no.2
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• pp.157-168
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• 2007

The purposes of this study were to measure the resting metabolic rate(RMR) of 30-40 year old women and to compare it with values predicted using published equations. Body weight, height and body fat of subjects were measured. RMR was measured by two indirect calorimeter(method 1 and method 2). RMR was predicted using various equations. Average height, weight and body fat(%) of subjects were 158.6cm, 59.1kg and 30.9%, respectively. The RMR(1621.2$\pm$301.5 kcal/day) measured by portable indirect calorimeter(method 2) was significantly higher than RMR(1447.4$\pm$223.6 kcal/day) measured by typical indirect calorimeter(method 1). Comparison of measured RMR with predicted RMRs suggested that there was a least difference in RMR predicted by equation of Cunningham. According to RMSPEs(Root Mean Squared Prediction Errors), equations of Cunningham and body surface area were found to predict measured RMR(by method 1) most accurately (within 239.1kcal/day and 232.9kcal/day, respectively). The fat free mass and fat mass - adjusted correlation showed that measured RMR(by method 1) had negative relationships with muscle mass(r = -0.873) and fat free mass(r = -0.866). The equations of Cunningham and body surface area provide relatively accurate estimates of RMR when determining energy needs of 30-40 aged women. There are needs for development of RMR predicted equations that are derived from large samples of Korean.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.2
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• pp.196-201
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• 2005

The aim of this study was to confirm the validity of predictive equations for the calculation of basal energy expenditure (BEE). One hundred twenty female college students were participated in this study. The resting energy expenditure (REE) was measured by indirect calorimetry for 30 minutes following an 12 hour overnight fasting. Among the available equations for predict BEE, Harris-Benedict, WHO/FAO/UNU and Cunningham methods were selected. Body composition was estimated by bioelectrical impedance analysis (BIA) for the equation of predicted BEE. The mean of measured REE was 1257.2$\pm$147.9 kcal/day, while the predicted value by Harris-Benedict, WHO/FAO/UNU and Cunningham were 1373.3$\pm$45.4 kcal/day, 1290.0$\pm$61.7 kcal/day and 1187.6$\pm$49.2 kcal/day, respectively. The Cunningham equation was more closed to measured values than Harris-Benedict and WHO/FAO/UNU equation by the correlation coefficient. Comparing Pearson's correlation coefficients, fat-free mass (FFM), body surface area (BSA) and body weight were higher than others such as height, body mass index (BMI), fat and fat%. The FFM's correlation coefficient was the highest as 0.74. Thus, the conclusion of this study suggested that the main determinant of BEE was FFM, and we derived a prediction equation as follows: BEE=-569.86+48.27 (FFM).