• 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).

• 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 Trauma and Injury
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• v.36 no.4
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• pp.337-342
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• 2023

Purpose: This study aimed to compare the resting energy expenditure (REE) measured using indirect calorimetry with that estimated using predictive equations in severe trauma patients to determine the appropriate caloric requirements. Methods: Patients admitted to the surgical intensive care unit between January 2020 and March 2023 were included in this study. Indirect calorimetry was used to measure the patients' REE values. These values were subsequently compared with those estimated using predictive equations: the weight-based equation (rule of thumb, 25 kcal/kg/day), Harris-Benedict, Ireton-Jones, and the Penn State 2003 equations. Results: A total of 27 severe trauma patients were included in this study, and 47 indirect calorimetric measurements were conducted. The weight-based equation (mean difference [MD], -28.96±303.58 kcal) and the Penn State 2003 equation (MD, - 3.56±270.39 kcal) showed the closest results to REE measured by indirect calorimetry. However, the REE values estimated using the Harris-Benedict equation (MD, 156.64±276.54 kcal) and Ireton-Jones equation (MD, 250.87±332.54 kcal) displayed significant differences from those measured using indirect calorimetry. The concordance rate, which the predictive REE differs from the measured REE value within 10%, was up to 36.2%. Conclusions: The REE values estimated using predictive equations exhibited substantial differences from those measured via indirect calorimetry. Therefore, it is necessary to measure the REE value through indirect calorimetry in severe trauma patients.

• Korean Journal of Community Nutrition
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• v.23 no.5
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• pp.424-430
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• 2018

Objectives: The purpose of this study was to compare predictions and measurements of the resting energy expenditure (REE) of overweight and obese adult women in Korea. Methods: The subjects included 65 overweight or obese adult women ranging in age from 20~60 with a recorded body mass index (BMI) of 23 or higher. Their height, weight, waist-hip ratio, and blood pressure were measured. The investigator also measured their body fat, body fat percentage, and body composition of total weight without fat using Dual energy X-ray absorptiometry (DXA) and measured resting energy expenditure by indirect calorimetry. Measured resting energy expenditures were compared with predictions from six methods: Harris-Benedict, Mifflin, Owen, WHO-WH, Henry-WH, and KDRI. Results: Harris-Benedict predictions showed the smallest differences from measured resting energy expenditure at an accurate prediction rate of 70%. The study analyzed regression between measured resting energy expenditure and body measurements including height, weight and age. The formula proposed by this research is as follows: Proposed REE equation for overweight and obese Korean women = $721-(1.5{\times}age)+(0.4{\times}height)+(9.9{\times}weight)$. Conclusions: These findings suggest that age is a significant variable when predicting resting energy expenditure in overweight and obese women. Therefore, prediction of resting energy expenditure should consider age when determining energy requirements in overweight and obese women.

• Journal of Trauma and Injury
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• v.34 no.1
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• pp.13-20
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• 2021

Purpose: Nutritional therapy in the intensive care unit is an essential factor for patient progress. The purpose of this study was to compare resting energy expenditure (REE) calculated by prediction equations (PEs) to the REE measured by indirect calorimetry (IC) in trauma patients. Methods: Patients admitted to the trauma intensive care unit who received mechanical ventilation between January and December 2015 were enrolled. REE was measured by IC (CCM Express, MGC Diagnostics) and calculated by the following PEs: Harris-Benedict, Fleisch, Robertson and Reid, Ireton-Jones, and the maximum value (25 kcal/kg/day) of the European Society for Clinical Nutrition and Metabolism (ESPEN). All patients were ventilated at a fraction of inspired oxygen (FiO2) below 60%. Results: Of the 31 patients included in this study, 24 (77.4%) were men and seven (22.6%) were women. The mean age of the patients was 49.7±13.2 years, their mean weight was 68.1±9.6 kg, and their mean Injury Severity Score was 26.1±11.3. The mean respiratory quotient on IC was 0.93±0.19, and their mean FiO2 was 38.72%±6.97%. The mean REE measured by IC was 2,146±444.36 kcal/day, and the mean REE values calculated by the PEs were 1,509.39±205.34 kcal/day by the Harris and Benedict equation, 1,509.39±154.33 kcal/day by the Fleisch equation, and 1,443.39±159.61 kcal/day by the Robertson and Reid equation. The Ireton-Jones equation yielded a higher value (2,278.90±202.35 kcal/day), which was not significantly different from the value measured using IC (p=0.53). The ESPEN maximum value (1,704.03±449.36 kcal/day) was lower, but this difference was likewise not significant (p=0.127). Conclusions: The REE measured by IC was somewhat higher than that calculated using PEs. Further studies are needed to determine the proper nutritional support for trauma patients.

• Korean Journal of Community Nutrition
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• v.14 no.4
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• pp.462-473
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• 2009

The purpose of this study is to analyze the accuracy of predictive equations for resting metabolic rate (RMR) in Korean college students. Subjects were 60 healthy Korean college students (30 males, 30 females) aged 18-25 years. RMR was measured by indirect calorimetry. Predicted RMRs were calculated using the Harris-Benedict, Schofield (W)/(WH), FAO/ WHO/UNU(W)/(WH), Owen, Mifflin, Cunningham, Liu, IMNA and Henry (W)/(WH) equations. The accuracy of the equations was evaluated on basis of accurate prediction (the percentage of subjects whose RMR was predicted within 90% to 110% of the RMR measured), mean difference, RMSPE, mean % difference, limits of agreement of Bland- Altman method between predicted and measured RMR. Measured RMR of male and female students were $1833.4{\pm}307.4kcal/day$ and $1454.3{\pm}208.0kcal/day$, respectively. All predictive equations underestimated measured RMR. Of the predictive equations tested, the Harris-Benedict equation (mean difference: -80.4 kcal/day, RMSPE: 236 kcal/day, mean % difference: -3.1%) was the most accurate and precise, but accurate prediction of the equation was only 42%. Thus, this study suggests that the ethnicity-specific predictive equation from Korean people should be developed to improve the accuracy of predicted RMR for Koreans. (Korean J Community Nutrition 14(4) : 462${\sim}$473, 2009)

• Journal of Korean Medicine for Obesity Research
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• v.19 no.1
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• pp.31-41
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• 2019

Objectives: The purpose of this study was to investigate the effects of gender, age, body weight, muscle mass, fat mass, body mass index (BMI), metabolism, and compliance with medication on weight loss in obese adults. Methods: We reviewed the medical records of 178 patients who were visited to the Korean Oriental Clinic for 3~6 month and had obesity treatment using Gamitaeumjowee-tang from April 2017 to May 2017. We conducted a paired T-test, correlation coefficient and decision tree to analyze factors influencing obesity treatment. Results: The results of correlation analysis showed that initial weight (kg), initial fat mass (kg), BMI ($kg/m^2$), compliance with medication (%), Original Harris-Benedict Equation, Revised Harris-Benedict Equation and The Mifflin St Jeor Equation was significantly correlated to weight loss (kg) (P<0.001). As a result of constructing the decision tree model, it showed that over 5% weight loss of their initial weight (n=154) was related with initial BMI ($kg/m^2$), compliance with medication (%) and initial muscle mass (kg). In case of over 5 kg weight loss of their initial weight (n=131), it was related with initial BMI ($kg/m^2$), compliance with medication (%) and final BMI ($kg/m^2$). Conclusions: This study suggests that weight loss may be affected by initial factors and that initial factors can be used for obesity treatment.

• Nutrition Research and Practice
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• v.6 no.1
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• pp.51-60
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• 2012

Weight-controlling can be supported by a proper prescription of energy intake. The individual energy requirement is usually determined through resting energy expenditure (REE) and physical activity. Because REE contributes to 60-70% of daily energy expenditure, the assessment of REE is very important. REE is often predicted using various equations, which are usually based on the body weight, height, age, gender, and so on. The aim of this study is to validate the published predictive equations for resting energy expenditure in 76 normal weight and 52 obese Korean children and adolescents in the 7-18 years old age group. The open-circuit indirect calorimetry using a ventilated hood system was used to measure REE. Sixteen REE predictive equations were included, which were based on weight and/or height of children and adolescents, or which were commonly used in clinical settings despite its use based on adults. The accuracy of the equations was evaluated on bias, RMSPE, and percentage of accurate prediction. The means of age and height were not significantly different among the groups. Weight and BMI were significantly higher in obese group (64.0 kg, $25.9kg/m^2$) than in the non-obese group (44.8 kg, $19.0kg/m^2$). For the obese group, the Molnar, Mifflin, Liu, and Harris-Benedict equations provided the accurate predictions of > 70% (87%, 79% 77%, and 73%, respectively). On the other hand, for non-obese group, only the Molnar equation had a high level of accuracy (bias of 0.6%, RMSPE of 90.4 kcal/d, and accurate prediction of 72%). The accurate prediction of the Schofield (W/WH), WHO (W/WH), and Henry (W/WH) equations was less than 60% for all groups. Our results showed that the Molnar equation appears to be the most accurate and precise for both the non-obese and the obese groups. This equation might be useful for clinical professionals when calculating energy needs in Korean children and adolescents.

• Korean Journal of Community Nutrition
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• v.19 no.6
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• pp.568-580
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• 2014

Objectives: The purpose of this study was to measure the resting metabolic rate (RMR) and to assess the accuracy of RMR predictive equations for Korean farmers. Methods: Subjects were 161 healthy Korean farmers (50 males, 111 females) in Gangwon-area. The RMR was measured by indirect calorimetry for 20 minutes following a 12-hour overnight fasting. Selected predictive equations were Harris-Benedict, Mifflin, Liu, KDRI, Cunningham (1980, 1991), Owen-W, F, FAO/WHO/UNU-W, WH, Schofield-W, WH, Henry-W, WH. The accuracy of the equations was evaluated on the basis of bias, RMSPE, accurate prediction and Bland-Altman plot. Further, new RMR predictive equations for the subjects were developed by multiple regression analysis using the variables highly related to RMR. Results: The mean of the measured RMR was 1703 kcal/day in males and 1343 kcal/day in females. The Cunningham (1980) equation was the closest to measured RMR than others in males and in females (males Bias -0.47%, RMSPE 110 kcal/day, accurate prediction 80%, females Bias 1.4%, RMSPE 63 kcal/day, accurate prediction 81%). Body weight, BMI, circumferences of waist and hip, fat mass and FFM were significantly correlated with measured RMR. Thus, derived prediction equation as follow : males RMR = 447.5 + 17.4 Wt, females RMR = 684.5 - 3.5 Ht + 11.8 Wt + 12.4 FFM. Conclusions: This study showed that Cunningham (1980) equation was the most accurate to predict RMR of the subjects. Thus, Cunningham (1980) equation could be used to predict RMR of Korean farmers studied in this study. Future studies including larger subjects should be carried out to develop RMR predictive equations for Korean farmers.

• Journal of the Korean Dietetic Association
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• v.15 no.1
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• pp.52-68
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• 2009

This study compared activity factor. predicted resting metabolic rate (RMR), and nutrient intakes between athletic and non-athletic high school students in Gangwon-do. Fifty soccer players (30 males and 20 females; mean ages 16.7${\pm}$1.0 years and 16.4${\pm}$1.1 years. respectively) and 50 non-athletic (30 males and 20 females: mean ages 17.5${\pm}$0.4 years and 16.4${\pm}$1.1 years respectively) high school students were included. Anthropometric measurements included: weight and height. triceps skinfold, mid-ann circumference, and body fat. Prediction equations consisted of those from the Harris-Benedict. FAO/WHO/VNU, IMNA, Cunningham, Mifflin et al., and Owen et al. A one-day activity diary was collected by interview, and the 24-hour recall method was used to analyze nutrient intakes of subjects. The activity factors of the male and female athletic groups (2.23 and 2.16, respectively) were significantly higher than those (1.52 and 1.46, respectively) of the non-athletic group. There was only a significant difference in RMR by use of the Cunningham's equation between two groups. For the males. almost all nutrient intakes of the athletic group (except carbohydrate, iron, vitamin $B_1$, $B_6$, and niacin) of athletic group were significantly higher than those of the non-athletic group. The female athletic group showed significantly higher nutrient intakes with the exception of most vitamins. These results suggest that assessments of energy balance between energy intake and energy expenditure by employing RMR and activity factors would be useful to prevent and treat obesity in high school athletes. In addition, the Cunningham's equation would be appropriate for predicting their energy needs.