The Measurements of the Resting Metabolic Rate (RMR) and the Accuracy of RMR Predictive Equations for Korean Farmers

Son, Hee Ryoung; Yeon, Seo Eun; Choi, Jun Young; Kim, Min Jung

doi:10.5720/kjcn.2014.19.6.568

Cited by 4 publications

(5 citation statements)

References 20 publications

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“…There can be different results according to the sample population due to variations based on age, sex, ethnicity, or body composition. [31][32][33][34] Thom et al 13 stated that, in healthy women at the extremes of BMI (underweight and/ or obese), the validity of predictive equations in general is particularly poor, so in clinical settings these formulas should be used cautiously in underweight and obese individuals. According to Flack et al, 34 Harris-Benedict and FAO/WHO/UNU formulas give the most accurate results, but as lean body mass increases, the calculated BMR values tend to be lower than measured.…”

Section: Discussionmentioning

confidence: 99%

“…Determining the actual energy expenditure and the correct estimation formula is highly variable according to the studies conducted. There can be different results according to the sample population due to variations based on age, sex, ethnicity, or body composition 31–34. Thom et al13 stated that, in healthy women at the extremes of BMI (underweight and/ or obese), the validity of predictive equations in general is particularly poor, so in clinical settings these formulas should be used cautiously in underweight and obese individuals.…”

Section: Discussionmentioning

confidence: 99%

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Comparison of Various Predictive Energy Equations for Female University Students With Measured Basal Metabolic Rate

Meseri

Küçükerdönmez

Akder

2022

Topics in Clinical Nutrition

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The aim of this study was to compare basal metabolic rate (BMR) calculated with various equations and BMR measured using an indirect calorimeter. The study was carried out on second-year university female students (n = 48) with a body mass index of less than 30. Indirect calorimetry with a ventilated hood was accepted as the gold standard and 11 predictive equations were used. Among the equations, Mifflin-St Jeor had the highest correlation (r = 0.435), but Bernstein (66.7%) and Owen (56.3%) were the most accurate equations. According to Bland-Altman analysis, the lowest bias and the highest explanation were obtained with the Bernstein and Owen equations. More comprehensive studies are needed in different groups to develop new equations with higher accuracy.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Comparison of Various Predictive Energy Equations for Female University Students With Measured Basal Metabolic Rate

Meseri

Küçükerdönmez

Akder

2022

Topics in Clinical Nutrition

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“…Our calorimetrically measured REE results are comparable to those in previous studies of Korean adults. In a study conducted by Son et al [ 31 ], the REE was measured in Korean farmers (50 men aged 50.2 ± 8.7 yrs with mean BMI of 25.0 ± 2.9 and 111 women aged 52.3 ± 6.6 yrs with mean BMI of 25.1 ± 2.8), and they reported that REE was 1,703 ± 205 kcal/day in men and 1,343 ± 139 kcal/day in women. Another study by Lee and Kim [ 32 ], which involved 28 male police officers aged 23 to 46 yrs (BMI = 24.6 ± 3.0), reported that the REE measured by indirect calorimetry was 1,748.3 ± 205.9 kcal/day.…”

Section: Discussionmentioning

confidence: 99%

“…Application of the FAO weight equation to that study group resulted in a bias of −1.9%, and only 55% of participants had their REE accurately predicted. Another study, which involved Korean farmers [ 31 ], reported that the Cunningham equation [ 42 ], which is based on FFM, was the most accurate in predicting the subjects' REE. This equation had a bias of −0.47% in men and 1.4% in women, and the percentage of accurate predictions was 80% in men and 81% in women.…”

Section: Discussionmentioning

confidence: 99%

Validity of predictive equations for resting energy expenditure in Korean non-obese adults

et al. 2018

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BACKGROUND/OBJECTIVESIndirect 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/METHODSThe 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.RESULTSThe 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 FAOweight equation gave the highest accuracy rate (70%), along with a bias of −4.4% and an RMSE of 184 kcal/day.CONCLUSIONSThe newly developed equation provided the best accuracy in predicting REE for Korean non-obese adults. Among the previously published equations, the FAOweight equation showed the highest overall accuracy. Regardless, at an individual level, the equations could lead to inaccuracies in a considerable number of subjects.

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“…Equations derived only for specific ethnic groups or for participants with BMIs of ≥ 40 kg/m 2 were excluded from the scope of the current study. Based on these criteria, we selected five REE prediction equations developed in Korean study populations [ 24 ]. The predictive equations for REE are summarized in Table 1 .…”

Section: Methodsmentioning

confidence: 99%

Resting energy expenditure in Korean type 2 diabetes patients: comparison between measured and predicted values

Park

Cho²,

Yim

2023

Nutr Res Pract

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BACKGROUND/OBJECTIVES Estimation of energy demand using resting energy expenditure (REE) is a reasonable approach for optimizing glycemic control and weight management in patients with type 2 diabetes mellitus (T2DM). This study aimed to compare REE predictions and objective measurements in patients with T2DM in Korea. SUBJECTS/METHODS This study enrolled 36 participants with T2DM (age range, 20–60 years). Anthropometric variables including height, weight, waist-hip ratio, blood pressure, body fat, body fat percentage, and total body weight were measured using bioimpedance. REE was evaluated using indirect calorimetry. The measured REE values were compared to values estimated using five predictive equations: the Harris-Benedict, Mifflin, Owen, Food and Agriculture Organization of the United Nations/World Health Organization (FAO/WHO), and Schofield equations. This study evaluated the associations between measured REE values and anthropometric/clinical data, including height, weight, and age, using multivariate linear regression. RESULTS The mean measured REE value was 1891.79 ± 288.03 kcal/day (male), 1,502.00 ± 202.96 kcal/day (female). REE estimates generated from the Mifflin equation showed the largest differences from measured REE values, whereas estimates derived from the FAO/WHO equation were the closest to the measured REE values. This study also identified associations between measured REE values and various anthropometric/clinical variables. CONCLUSION The accuracy of REE prediction equations is critically important in promoting the efficacy of dietary counseling and the effective treatment of diabetes. Our results indicate the need for additional studies informing more suitable methods for determining the energy requirements of Korean patients with T2DM.

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The Measurements of the Resting Metabolic Rate (RMR) and the Accuracy of RMR Predictive Equations for Korean Farmers

Cited by 4 publications

References 20 publications

Comparison of Various Predictive Energy Equations for Female University Students With Measured Basal Metabolic Rate

Comparison of Various Predictive Energy Equations for Female University Students With Measured Basal Metabolic Rate

Validity of predictive equations for resting energy expenditure in Korean non-obese adults

Resting energy expenditure in Korean type 2 diabetes patients: comparison between measured and predicted values

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