• Journal of the Korean Dietetic Association
• /
• v.13 no.2
• /
• pp.157-168
• /
• 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 Geotechnical Society
• /
• v.25 no.10
• /
• pp.67-76
• /
• 2009

Statistical analysis was performed using a series of data on RMR, RMR* and crown settlements collected from sites of weathering rock tunnels in Korea. The crown settlements were predicted by recurrence analysis, exponential function, and artificial neural network (ANN) using collected in-situ data. The result of the prediction fitted well compared to the measured settlement in the order of ANN, exponential function, and recurrence analysis. The range of crown settlement predicted by recurrence analysis widely scattered and promised larger settlement than the measured. Also in all method, the predicted value by RMR well matched compared to the measured settlement predicted by RMR*.

• Korean Journal of Community Nutrition
• /
• v.14 no.4
• /
• pp.462-473
• /
• 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 Life Science
• /
• v.18 no.6
• /
• pp.865-870
• /
• 2008

The purpose of this study was to examine resting metabolic rate (RMR) and thyroid hormonal (TSH, $T_3$, and $T_4$) changes following weight loss by diet with regular exercise in obese women. The subjects of the present study were 7 women who were above 30% body fat. The subjects arrived into the laboratory in the morning after 12 hour overnight fasting. All subjects measured RMR, % body fat, and fat free mass at weight loss program start time, after 4 weeks and after 8 weeks. All the RMR values were expressed as absolute value (kcal/day), absolute value/FFM (kcal/day/FFM), and absolute value/BSA (kcal/$m^2$/hr), and were calculated predicted RMR value minus actual RMR value. Also, correlation of blood thyroid hormonal (TSH, $T_3$, and $T_4$) secretion and RMR were analyzed. There were significant differences in weight, % body fat, and BSA following diet with exercise (p<0.05). Also, there was a difference between predicted RMR and actual RMR value following weight loss (p<0.05). We also examined the hormonal changes according to weight loss. After weight loss, the level of TSH and $T_4$ were higher than before. But there were no significant differences. Also, the level of $T_3$ was lower than rather before but there was no significant difference. Among the anthropometric factors, FFM was highly correlated (r=0.761) with actual RMR value before weight loss. Also, there was a correlation (r=0.771) with actual RMR value after weight loss. Therefore, actual RMR expressed as FFM increased in weight loss program by diet with exercise. There were no changes in the level of thyroid hormonal TSH and $T_4$.

• Korean Journal of Exercise Nutrition
• /
• v.24 no.1
• /
• pp.9-13
• /
• 2020

[Purpose] This preliminary study aimed to develop a regression model to estimate the resting metabolic rate (RMR) of young and middle-aged Koreans using various easy-to-measure dependent variables. [Methods] The RMR and the dependent variables for its estimation (e.g. age, height, body mass index, fat-free mass; FFM, fat mass, % body fat, systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, and resting heart rate) were measured in 53 young (male n = 18, female n = 16) and middle-aged (male n = 5, female n = 14) healthy adults. Statistical analysis was performed to develop an RMR estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and age were important variables in both the regression models based on the regression coefficients. Mean explanatory power of RMR₁ regression models estimated only by FFM was 66.7% (R²) and 66.0% (adjusted R²), while mean standard errors of estimates (SEE) was 219.85 kcal/day. Additionally, mean explanatory power of RMR₂ regression models developed by FFM and age were 70.0% (R²) and 68.8% (adjusted R²), while the mean SEE was 210.64 kcal/day. There was no significant difference between the measured RMR by the canopy method using a metabolic gas analyzer and the predicted RMR by RMR₁ and RMR₂ equations. [Conclusion] This preliminary study developed a regression model to estimate the RMR of young and middle-age healthy Koreans. The regression model was as follows: RMR₁ = 24.383 × FFM + 634.310, RMR₂ = 23.691 × FFM - 5.745 × age + 852.341.

• Nutrition Research and Practice
• /
• v.9 no.4
• /
• pp.370-378
• /
• 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 Tunnelling and Underground Space Association
• /
• v.12 no.6
• /
• pp.463-473
• /
• 2010

A new approach for prediction of a fault zone ahead of tunnel face by using statistical control charts is suggested and applied to the construction site. $x-R_s$ control charts of RMR parameters were investigated as approaching and passing through fault zone. The abnormal signal from the control charts was observed and analyzed based on statistical criteria. Fault zones in the application area were predicted in advance using this method and it was verified by comparing with observation data like horizontal boring and face mapping.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.18 no.4
• /
• pp.341-354
• /
• 2016

This article is to apply the tunnel support system selected after comparatively analyzing of RMR and tunnel instrumentation between the tunnel behavior characteristic predicted through geotechnical investigations and the numerical analysis at the design stage and the properties deformation occurred at the construction stage. This attempt results from the behavior characteristic of the tunnel excavation ground shown differently in accordance with the ground quality and reinforcement method. This, therefore, provide the data and results analysed the actual decision RMR-crown settlement & convergence and reduction of material property of ground as parameters. Also, it's shown that the tunnel designer is able to predict tunnel behavior characteristic when designing in bedrock areas excessively distributed faults and fractured zones.

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

• Tunnel and Underground Space
• /
• v.16 no.3 s.62
• /
• pp.251-258
• /
• 2006

In this paper, the applicability to the Korean rock condition of using the deformation moduli based on Rock Mass Rating (RMR) and Pressuremeter Test (PMT) is evaluated. The correlations among deformation moduli and various rock properties were also analyzed. It appears that the existing correlations using RMR overestimate the deformation moduli and wide variation was found between predicted moduli using these correlations and measured values. As for the correlations among the deformation moduli and various rock properties, Rock Quality Designation (RQD) and unconfined compressive strength (UCS) were found to correlate to deformation moduli reasonably well, but joint spacing and joint conditions appear to correlate poorly to RQD and UCS. Additionally, groundwater can not be correlated with the modulus values. While the depth has very little contribution to deformation modulus, it should be factored in the simple regression analyses with various rock mass properties, especially with the correlations made with UCS, RQD etc. With the deficiencies of these correlations, more in depth analysis techniques such as multivariate correlations may be to reliably estimate deformation modulus of rock mass.