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.
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.
The purpose of this study was to compare the energy expenditure and energy intake of normal-weight and overweight Korean adults. We recruited 242 adults to determine resting energy expenditure, physical activity and energy intake. Resting energy expenditure was measured by indirect calorimetry. Energy intake for consecutive two days was assessed by 24 hour recall method. Daily activity pattern for 24 hour was collected from each subject. Body weight, lean body mass and percentage body fat were measured by INBODY 3.0. The subject were divided into normal ($20\leqBMI$ < 25) and overweight ($BMI \geq 25$) groups by BMI. There was no significant difference in intake of energy between two groups. Energy intake of each group was lower than the 7th Korean RDA of energy. Overweight subjects showed significantly lower REE/kg body weight. However, REE/kg lean body mass (LBM) did not differ between the two groups. Total activity energy was significantly higher in the overweight group compared to the normal group. Daily activity coefficient of overweight group in male was lower than that of normal group. Daily activity coefficient was almost same in two female groups. LBM was highly correlated with REE and total energy expenditure. We concluded that the overweight group consumed more energy than the normal group due to the heavier body weight.
The purpose of this study was to provide baseline data for revising the recommended energy intake for Korean adults. We recruited 290 adults so as to determine their resting energy expenditure (REE) and energy intake. The REE was measured by indirect calorimetry. We also calculated the REE from prediction equations formulated by World Health Organization (WHO), The energy intake for two consecutive days was assessed using the 24 hour recall method. The body weight, lean body mass (LBM) and percentage body fat were measured using the INBODY 3.0 system. We compared the results of three age groups ; 20 to 29 years,30 to 49 years and 50 years or more. The average energy intake of each age group was below the 7th Korean Recommended Dietary Allowances (RDA). The average energy intake was lower in the older age groups. However, no difference was observed among the age groups when the energy intake as a percentage of the Korean RDA was compared. Our measurement of the REE was higher than the REE calculated by the WHO's method. Correlation coefficients between the measured and the calculated values of REE for all age groups showed significant correlations (r=0.475-0.672). As the ages of all the subjects increased, the REE/kg of body weight decreased. There were no significant differences in the REE / kg of the LBM between the different age groups; however, the REE/kg of the LBM was higher in the female group than in the male group. Negative correlations of the REE with the age (r=-0.242) and body fat ratio (r=-0.313) were observed; positive correlations of the REE with the BMI (r=0.265), height (r=0.570), weight (r=0.562) and LBM (r=0.586) were also found (p<0.01).
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), $R^2=0.23$.
The objective of this study was to examine the effects of a weight loss program on the degree of obesity and levels of resting energy expenditure (REE) in overweight subjects according to their mitochondrial uncoupling protein 2 (UCP 2) genotype. Twenty-three subjects with a body mass index (BMI) greater than 27 were recruited from the Obesity Clinic of the Kyung-Hee University Hospital during the period of December 2000 - August 2001. The subjects were genotyped for the exon 8 allele; 15 subjects were found to be of del/del genotype, 8 were del/ins, and none were of ins/ins genotype. No significant association was found between the different UCP 2 genotypes and the initial levels of weight, fat mass (FM), lean body mess (LBM), BMI, REE, and REE/LBM ratio. After 12 weeks of a weight loss program, body weight and FM were significantly decreased, while LBM, total body water (TBW), and REE were not changed, irrespective of UCP 2 genotype. Initial fasting plasma levels of albumin, glucose, triglyceride, lipoprotein cholesterol, insulin, free triiodo-thyronine (T3), free fatty acid (FFA), and leptin were not different according to the UCP 2 genotype; furthermore, these blood parameters were not changed after the 12-week weight loss program. However, plasma levels of leptin decreased in both the del/del and ins/del genotypes, from 18.7 ng/ml to 13.4 ng/ml (p<.05), and from 18.1 ng/ml to 13.9 ng/ml (p<.05), respectively, after the weight loss program. In conclusion, this study found no significant association between the del/del or del/ins UCP 2 genotypes and differing levels of REE or differing degrees of obesity, either before or after a weight loss program. This study provided evidence that a well- managed weight loss program could maintain levels of REE, which plays an important role in the maintenance of energy balance.
BACKGROUND/OBJECTIVES: Indirect calorimetry is the gold-standard method for the measurement of resting energy expenditure. However, this method is time consuming, expensive, and requires highly trained personnel. To overcome these limitations, various predictive equations have been developed. The objective of this study was to assess the validity of predictive equations for resting energy expenditure (REE) in Korean non-obese adults. SUBJECTS/METHODS: The present study involved 109 participants (54 men and 55 women) aged between 20 and 64 years. The REE was measured by indirect calorimetry. Nineteen REE equations were evaluated for validity, by comparing predicted and measured REE results. Predictive equation accuracy was assessed by determining percent bias, root mean squared prediction error (RMSE), and percentage of accurate predictions. RESULTS: The measured REE was significantly higher in men than in women (P < 0.001), but the difference was not significant after adjusting for body weight (P > 0.05). The equation developed in this study had an accuracy rate of 71%, a bias of 0%, and an RMSE of 155 kcal/day. Among published equations, the $FAO_{weight}$ equation gave the highest accuracy rate (70%), along with a bias of -4.4% and an RMSE of 184 kcal/day. CONCLUSIONS: The newly developed equation provided the best accuracy in predicting REE for Korean non-obese adults. Among the previously published equations, the $FAO_{weight}$ equation showed the highest overall accuracy. Regardless, at an individual level, the equations could lead to inaccuracies in a considerable number of subjects.
Background : Elevation of resting energy expenditure(REE) in patients with lung cancer has been described in earlier studies and may contribute to cancer cachexia, but limited information is available regarding the prevalence and determinants of the increased REE. The aim of this study was to assess the prevalence and contributing factors of a hypermetabolic state in newly detected patients with lung cancer and to assess the energy balance in order to improve our knowledge about weight loss in patients with lung cancer. Method : Thirty one consecutive, newly detected patients with lung cancer and 20 control patients with benign lung diseases were included in this study. Resting energy expenditure(REE) was measured by indirect calorimetry using ventilated hood system and predicted REE was calculated by the Harris-Benedict formular. Results : The energy balance in newly detected lung cancer patients was disturbed in a high proportion of patients, and hypermetabolic state occurred in 61% of the patients. Tumor volume, cancer type, location, stage, the presence of atelectasis or infiltration, pulmonary function, or smoking behavior were not associated with increase in REE. But patients with distant metastasis had significantly higher REE comparing with patients without metastasis. Thirty nine percents of the patients with lung cancer had substantial loss of more than 10% of their pre-illness weight. Weight losing patients with lung cancer were not accompanied by an increase in REE. Conclusion : We concluded that the REE was elevated in a higher proportion of patients with lung cancer and distant metastasis was found to be contributing factor to the elevated REE.
The objective of this study was to examine how circulating leptin concentrations and resting energy expenditures (REE) are related to body composition in obese adults, and to examine differences in these parameters according to gender. Twenty-three subjects, 6 males and 17 females, were recruited from patients with a body mass index (BMI) of greater than 27 at the Obesity Clinic of the K University Hospital. Anthropometric assessments and biochemical analyses were performed, and REEs were measured. In spite of having similar BMI values the plasma leptin levels of females (20.0$\pm$6.5 ng/ml) were significantly higher (p<.05) than those of males (14.2$\pm$6.1) ng/ml). In females, plasma leptin concentrations were found to be positively related to body weight. BMI, waist-hip ratio (WHR), fat mass (FM), body fat, and to the circumferences of forearm, waist and hip (p<.0001). However, in males, plasma leptin concentrations were positively related only to suprailiac thickness (p<.05). The higher plasma leptin levels in females compared to males may, at least partially. be explained by the females' higher subcutaneous fat mass. Plasma leptin concentrations appeared to reflect not only total fat mass but also regional fat distribution, especially in females. REE values of males (2254.3$\pm$256.2 kcal/day) were significantly higher (p<.01) than those of females (1799.1$\pm$454.7 kcal/day). REE values for females were positively related to body weight, BMI, lean body mass (LBM), FM, body fat, and to the circumferences of waist and hip (p<.05); however, REE values for males were (positively) related only to LBM (p<.05). REE values were not related to plasma leptin concentrations for either males or females, indicating that the plasma level of leptin might not be a predictor for REE value.
Hak-Jae Lee;Sung-Bak Ahn;Jung Hyun Lee;Ji-Yeon Kim;Sungyeon Yoo;Suk-Kyung Hong
Journal of Trauma and Injury
/
v.36
no.4
/
pp.337-342
/
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.
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