Owen Equation Research Articles

Assessment of estimated and measured resting metabolic rates in type 1 and type 2 diabetes mellitus

AimThis study aimed to compare the estimated and measured resting metabolic rates of patients with type 1 and type 2 diabetes mellitus in an outpatient clinical setting. Material and methodsParticipants were categorized into three groups that included type 1 diabetes, type 2 diabetes, and individuals without diabetes. Bland–Altman analysis was used to identify the equation that most accurately predicted the measured resting metabolic rates. Multiple regression analysis was used to identify the factors affecting resting metabolic rates. ResultsResting metabolic rates was observed to be higher in subjects with type 2 diabetes compared to that of the other groups. There was a proportional bias between predicted and measured resting metabolic rates. Type 1 diabetes, type 2 diabetes, male sex, body weight, waist circumference, and triglyceride level were factors that positively predicted resting metabolic rates, and age was a factor that negatively predicted it. ConclusionsAlthough there was a bias between estimated and measured RMR, the most accurate results were achieved with the Mifflin–St Jeor equation for women with type 1 diabetes, with the Owen equation for men with type 1 diabetes, with the Harris Benedict equation for women with type 2 diabetes, and with the Ikeda equation for men with type 2 diabetes as well as for women and men in the control group.

Revised Harris-Benedict Equation: New Human Resting Metabolic Rate Equation.

This paper contains a revision of the Harris-Benedict equations through the development and validation of new equations for the estimation of resting metabolic rate (RMR) in normal, overweight, and obese adult subjects, taking into account the same anthropometric parameters. A total of 722 adult Caucasian subjects were enrolled in this analysis. After taking a detailed medical history, the study enrolled non-hospitalized subjects with medically and nutritionally controlled diseases such as diabetes mellitus, cardiovascular disease, and thyroid disease, excluding subjects with active infections and pregnant or lactating women. Measurement of somatometric characteristics and indirect calorimetry were performed. The values obtained from RMR measurement were compared with the values of the new equations and the Harris-Benedict, Mifflin-St Jeor, FAO/WHO/UNU, and Owen equations. New predictive RMR equations were developed using age, body weight, height, and sex parameters. RMR males: (9.65 × weight in kg) + (573 × height in m) - (5.08 × age in years) + 260; RMR females: (7.38 × weight in kg) + (607 × height in m) - (2.31 × age in years) + 43; RMR males: (4.38 × weight in pounds) + (14.55 × height in inches) - (5.08 × age in years) + 260; RMR females: (3.35 × weight in pounds) + (15.42 × height in inches) - (2.31 × age in years) + 43. The accuracy of the new equations was tested in the test group in both groups, in accordance with the resting metabolic rate measurements. The new equations showed more accurate results than the other equations, with the equation for men (R-squared: 0.95) showing better prediction than the equation for women (R-squared: 0.86). The new equations showed good accuracy at both group and individual levels, and better reliability compared to other equations using the same anthropometric variables as predictors of RMR. The new equations were created under modern obesogenic conditions, and do not exclude individuals with regulated (dietary or pharmacological) Westernized diseases (e.g., cardiovascular disease, diabetes, and thyroid disease).

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

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.

Low accuracy of predictive equations for resting metabolic rate in overweight women after weight loss

<h2>Summary</h2><h3>Background & Aims</h3> The better equation to predict resting metabolic rate (pRMR) to use for overweight individuals mainly after weight loss is unclear. This study aimed to identify the best equation to pRMR in overweight adult women before and after a nutritional intervention aiming to lose weight. <h3>Methods</h3> Thirty overweight adult women were enrolled in this study. Subjects underwent 6-month energy-restricted diet intervention. Anthropometrics and body composition measures were evaluated. Nine equations that are widely used to pRMR were performed based on anthropometric and body composition parameters. Measured RMR (mRMR) was obtained by indirect calorimetry. A new equation to predict resting metabolic rate (npRMR) was also developed by multiple regression analysis based on anthropometric and body composition variables. The validity of the equations was investigated through comparisons, accuracy, and agreement tests. <h3>Results</h3> Before the nutrition intervention, only the Mifflin equation was similar to mRMR, with a mean difference of 12kcal and 83% of accuracy. The mean weight loss was 4.2% after 6 months. Following weight loss, only the Owen equation was similar to mRMR, with a mean difference of −33 kcal. However, this equation showed low accuracy (63%). All the others equations showed reduction of accuracy, increase of bias and overestimation of RMR. A npRMR was calculated, and this showed a lower mean difference to mRMR with 70% of accuracy. <h3>Conclusions</h3> Out of the nine resting metabolic rate equations evaluated only the Mifflin equation was similar to mRMR before intervention. Interestingly, after weight loss none of the assessed equations were reliable to pRMR. Based on that we propose a new equation that showed greater accuracy and lower mean difference when compared with mRMR.

Field observations of sand flux and dust emission above a gobi desert surface

Gobi deserts are a major source of natural and anthropogenic aerosols in China. However, the characteristics of the sand flow and dust emission processes are still an open question. This study intends to accurately describe the characteristics of the sand flow and dust emission and to determine the relationship between the sand transport rate and the vertical dust flux above a gobi surface. In this study, a field observation was conducted over a gobi (gravel) desert surface (Yangguan Gobi Desert, Gansu Province, China). We investigated the wind velocity, sand flux, and concentration of particles smaller than 10 μm (PM10) by using cup anemometers, a sonic anemometer, sand traps, and DustTrak. We found that (1) piecewise regression described the vertical sand flux profiles; the upper part of the profile (above 17 cm) should be described by a power function and the lower part should be described by a Gaussian function. (2) An empirical model based on the modified Owen equation could predict the sand transport rate accurately. (3) The vertical dust flux was described well by Fv∝u*3 and the dust emission above the gobi surface should follow Aρu*t (u*2 − u*t2), where A is an empirical regression coefficient. (4) The efficiency of saltation bombardment (Fv/Q) was linearly related to the ratio u*t/u*. The results of this study show that the characteristics of the sand flow and dust emission above a gobi surface were highly different from those of bare sandy surface. In future research, it will be necessary to account for the effect of surface characteristics, and particularly the characteristics of the gravel, to improve the predictive ability of our model.

Evaluating The Accuracy Of Basal Metabolic Rate Prediction Equations For Masters Athletes

Basal metabolic rate (BMR) is the energy required to perform basic metabolic functions at rest. Indirect calorimetry is one method of measuring BMR, but it can also be predicted using BMR prediction equations. Depending on the equation used, a prediction can take into account a combination of different factors (e.g., age, body weight, height, lean body mass, fat mass). These equations tend to overestimate BMR. However, most of the researchers relied on small sample sizes or specific populations. PURPOSE: To determine the accuracy of BMR prediction equations for Masters Athletes. METHODS: Two hundred and eighty-five athletes (157 women, 128 men; ≥ 26 years of age) representing a number of sports and physical activities, who exercised at least twice a week and were non-smokers, participated in our cross-sectional study. Resting metabolic rate (RMR) was measured using indirect calorimetry. Prior to measuring RMR, participants fasted and refrained from caffeine for 12 hours, avoided alcohol and exercise for 24 hours, and rested in a recliner for 15 minutes prior to data collection. Body composition was determined using dual-energy X-ray absorptiometry (DXA). We compared the Mifflin-St. Jeor, Harris-Benedict, Cunningham, and Owen to indirect calorimetry using one-way analysis of variance (ANOVA) with repeated measures. RESULTS: We found that indirect calorimetry measured significantly lower (p < 0.001) kilocalories (kcal) compared to any of the four prediction equations. The Mifflin-St. Jeor equation was more closely aligned with indirect calorimetry for all participants combined and women (mean difference, percent accuracy: 115, 54.8%; 95, 57.2%, respectively) compared to indirect calorimetry. However, the Owen equation was more accurate for men (98, 61.3%). The Cunningham equation generated the highest mean difference and lowest percent accuracy for all participants combined, women, and men (234, 29.1%; 221, 23.6%; 250, 35.9%, respectively). CONCLUSIONS: We found that the four BMR prediction equations analyzed significantly over-predicted BMR compared to indirect calorimetry. Our results emphasize the need for a more appropriate BMR prediction equation for athletes. This study was not funded

Validity of predictive equations to estimate RMR in females with varying BMI.

Estimation of RMR using prediction equations is the basis for calculating energy requirements. In the present study, RMR was predicted by Harris-Benedict, Schofield, Henry, Mifflin-St Jeor and Owen equations and measured by indirect calorimetry in 125 healthy adult women of varying BMI (17-44 kg/m2). Agreement between methods was assessed by Bland-Altman analyses and each equation was assessed for accuracy by calculating the percentage of individuals predicted within ± 10 % of measured RMR. Slopes and intercepts of bias as a function of average RMR (mean of predicted and measured RMR) were calculated by regression analyses. Predictors of equation bias were investigated using univariate and multivariate linear regression. At group level, bias (the difference between predicted and measured RMR) was not different from zero only for Mifflin-St Jeor (0 (sd 153) kcal/d (0 (sd 640) kJ/d)) and Henry (8 (sd 163) kcal/d (33 (sd 682) kJ/d)) equations. Mifflin-St Jeor and Henry equations were most accurate at the individual level and predicted RMR within 10 % of measured RMR in 71 and 66 % of participants, respectively. For all equations, limits of agreement were wide, slopes of bias were negative, and intercepts of bias were positive and significantly (P < 0⋅05) different from zero. Increasing age, height and BMI were associated with underestimation of RMR, but collectively these variables explained only 15 % of the variance in estimation bias. Overall accuracy of equations for prediction of RMR is low at the individual level, particularly in women with low and high RMR. The Mifflin-St Jeor equation was the most accurate for this dataset, but prediction errors were still observed in about one-third of participants.

Predicting Equations and Resting Energy Expenditure Changes in Overweight Adults.

IntroductionThe aim of the study is to show the differences between the measured and estimated values of resting energy expenditure and any changes occurring after the 6-month weight loss intervention program.MethodsWe included 33 healthy adults aged 25–49 years with an average body mass index 29.1±2.7 kg/m 2 for female and 29.8±2.8 kg/m2 for male. The measured resting energy expenditure was obtained by indirect calorimeter MedGem® Microlife and estimated resting energy expenditure by the Harris–Benedict equation, the Mifflin–St Jeor equation, the Owen equation, the Wright equation, and by the Tanita body composition analyser. All measurements and calculations were carried out before and after the 6-month intervention. Results were compared using paired t-tests. P value less than 0.05 was considered statistically significant.ResultsA comparison of the measured resting energy expenditure of female subjects with the estimated resting energy expenditure using the Harris–Benedict equation, the Mifflin–St Jeor equation and the Wright equation showed a statistically significant difference. A comparison of the measured resting energy expenditure of male subjects with the estimated resting energy expenditure using the Harris–Benedict equation and the Wright equation showed a statistically significant difference. There was a significant difference in the measured resting energy expenditure and estimated resting energy expenditure using Tanita.ConclusionsWe concluded that the most comparable equation for our sample was the Owen’s equation. After losing weight, the measured resting energy expenditure has decreased, which must be taken into account in further diet therapy.

Smoothed particle hydrodynamics for the interaction of Newtonian and non-Newtonian fluids using the μ(I) model

The interaction between Newtonian and non-Newtonian fluid is one the most complicated problems for the engineers in the field of fluid mechanics. In the last decades, Lagrangian methods including smooth particle hydrodynamics has had the great interests among the different approaches in computational fluid dynamics (CFD). In this paper the collapse of the granular column and dry landslide and also two phase dam break and submerged landslide phenomena have been done through open source SPHysics2D code. The proposed model describes both fluid and sediment particles as weakly compressible flow where the sediment is treated as a non-Newtonian fluid using a viscoplastic model, called μ(I) model. This model is based on the properties of grains including inertia and friction coefficient. First, the performance of the viscoplastic code was investigated for a one- phase model by comparing the results measured in the laboratory and those obtained by developed code. Then, the movable dam break and submerged landslide phenomena were investigated, by the code developed for a two phase model, including Newtonian and non-Newtonian fluid. μ(I) viscoplastic model is utilized for the solid phase, Owen's equation and the mean harmonic viscosity are used to introduce the interactions between the particles containing different viscosities and densities. Results show that the model used in this research has reasonable accuracy by comparing with experimental models.

Congruent Validity of Resting Energy Expenditure Predictive Equations in Young Adults.

Having valid and reliable resting energy expenditure (REE) estimations is crucial to establish reachable goals for dietary and exercise interventions. However, most of the REE predictive equations were developed some time ago and, as the body composition of the current population has changed, it is highly relevant to assess the validity of REE predictive equations in contemporary young adults. In addition, little is known about the role of sex and weight status on the validity of these predictive equations. Therefore, this study aimed to investigate the role of sex and weight status in congruent validity of REE predictive equations in young adults. A total of 132 young healthy adults (67.4% women, 18–26 years old) participated in the study. We measured REE by indirect calorimetry strictly following the standard procedures, and we compared it to 45 predictive equations. The most accurate equations were the following: (i) the Schofield and the “Food and Agriculture Organization of the United Nations/World Health Organization/United Nations” (FAO/WHO/UNU) equations in normal weight men; (ii) the Mifflin and FAO/WHO/UNU equations in normal weight women; (iii) the Livingston and Korth equations in overweight men; (iv) the Johnstone and Frankenfield equations in overweight women; (v) the Owen and Bernstein equations in obese men; and (vi) the Owen equation in obese women. In conclusion, the results of this study show that the best equation to estimate REE depends on sex and weight status in young healthy adults.

Determination of Energy Expenditure

Nutrition interventions are often designed to influence energy balance, ultimately optimizing the health of individuals or groups. Goals include weight loss in obese and overweight individuals or weight gain in growing children, pregnant women, and the underweight. In some cases, weight maintenance is the intention for healthy weight adults or children who have the opportunity to grow into their current weight. Determining the energy requirements for each person can help explain the presence or absence of weight changes and direct subsequent nutrition goals and interventions. Quantifying energy requirements also helps to avoid over- and under- feeding. This is particularly relevant in people suffering from acute or chronic disease or illness. In the acute care setting overfeeding can worsen metabolic disturbances including, but not limited to, hyperglycemia and hypercarbia while underfeeding can negatively impact immunity, organ function, and activities of daily living. This review contains 3 Figures, 5 Tables and 66 references Key words: nutrition, energy expenditure, body composition, calorimetry, bioelectrical impedance analysis (BIA), doubly-labeled water (DLW), reverse Fick equation, Harris-Benedict equation, Millfin-St. Jeor Equation, Owen Equation, Ireton-Jones Equations, Penn State Equations, hypocaloric feeding

Validation of resting metabolic rate equations in obese and non-obese young healthy adults

Although validating resting metabolic rate (RMR) prediction equations in different populations is warranted to estimate total energy requirements, there are no data about the accuracy and applicability of RMR predictive equations in young healthy Jordanians. This study aimed to test the validity of predicted RMR using four prediction equations and its agreement with RMR measured using indirect calorimetry in healthy young obese and non-obese Jordanian adults. Predicted RMR was tested for agreement with indirect calorimetry. Harris-Benedict, Food and Agriculture Organization/World Health Organization/United Nations University, Mifflin and Owen equations were used to predict RMR. A total of 406 (200 females, 206 males) normal bodyweight, overweight, and obese healthy young adults aged 18-25 years were included. Of all tested equations, Harris-Benedict equation showed no significant differences compared to measured RMR using indirect calorimetry (p>0.05) in normal bodyweight (1374.1±72.5 vs. 1347.6±333.4), overweight (1513.1±66.8 vs. 1492.9±374.8) and obese (1673.5±178.4 vs. 1736.4±386.9) females. While significant differences (p<0.05) were found in all male participants. The other studied equations showed significant differences (p≤0.05) compared to measured RMR in gender based groups with different bodyweight status. Only Harris-Benedict equation was the most accurate in predicting RMR among females regardless of bodyweight status. Apart from that, these equations did not perform well at the group level. The tested prediction equations further underestimated RMR. Future studies aiming at validating RMR prediction equations in different populations are warranted in order to understand the factors that could affect the accuracy of RMR prediction.

Use of both quantitative and qualitative methods to improve assessment of resting energy expenditure equation performance in hospitalized adults

To introduce the use of qualitative assessment in energy expenditure (EE) equation research to improve the understanding of performance of the equations in the clinical setting. Hospitalized individuals who had an indirect calorimetry (IC) measurement during their hospital stay from 2010 to 2012 were included in the study (n=59). An additional 1000 patients hospitalized during this time were used to limit the IC cohort to a more "clinically relevant" BMI range (n=46). The following estimation equations were assessed: Harris-Benedict, 25kcal/kg using actual body weight, Mifflin St. Jeor, Ireton-Jones, Penn State, and Owen. Bland-Altman plots with Loess curves were generated to compare estimated basal caloric needs between EE equations and IC values. This study found a large amount of variability with all EE equations. As the mean calorie level increased, the Harris Benedict, Mifflin St. Jeor, Penn State, and Owen equations all tended to increasingly under-predict caloric need. In a research setting a qualitative assessment of EE equations can provide a more comprehensive understanding of equation performance by complementing traditional quantitative methods. The addition of a Loess curve to the Bland-Altman plot further enhances qualitative assessment.

Comparison between resting metabolic rate and indirect calorimetry in postmenopausal women

ABSTRACT Objective To compare resting metabolic rate values determined by indirect calorimetry with values estimated using different predictive equations in lean and overweight postmenopausal women. Methods Twenty-four women, who had stopped menstruating for at least two years, were subjected to anthropometric measurements and indirect calorimetry after 12-hour overnight fasting to determine, mathematically and experimentally, resting metabolic rate values. Results There was no difference in the indirect calorimetry values between the groups evaluated. Difference values of resting metabolic rate were obtained with all equations used. For the lean women, there was no difference between the values obtained by indirect calorimetry and those estimated using the equations proposed by Food and Agricultural Organization, Fredix, Lazzer, and Schofield. However, in the overweight group, the resting metabolic rate values estimated using the Institute of Medicine, Berstein and Owen equations were different from those obtained by indirect calorimetry. Conclusion This study suggests that differences in body composition in postmenopausal women influence the accuracy of predictive equations, demonstrating the need for more accurate estimation methods for resting metabolic rate in postmenopausal women with different body compositions.

Resting energy expenditure in male athletes with a spinal cord injury

Objective: To investigate whether there are differences in the resting energy expenditure (REE) and body composition of athletes with a spinal cord injury (SCI) compared to active able-bodied controls.Design: In this cross sectional study, male athletes with a SCI were compared to active able-bodied controls matched for age, stretch stature and body mass. In addition, the accuracy of standard REE prediction equations in estimating REE was assessed.Participants: Seven male wheelchair athletes with a SCI and six matched active able-bodied controls volunteered to participate.Outcome measures: REE was measured using indirect calorimetry and estimated using population-specific prediction equations. Body composition (lean tissue mass, fat mass and bone mineral content) was measured by dual energy X-ray absorptiometry (DXA).Results: While absolute and adjusted REE in the athletes with SCI was lower than controls, this difference was not significant (P = 0.259). When adjusted for lean tissue mass (LTM), REE was significantly higher (P = 0.038) in the athletes with SCI compared to the controls (146 ± 29kJ/kg LTM vs. 125 ± 8kJ/kg LTM). LTM was significantly lower in the athletes with SCI (44.35 ± 6.98 kg) compared to the able-bodied controls (56.02 ± 4.93 kg; P < 0.01). The differences between predicted and measured REE in the athletes with SCI were not statistically significant (except for the Owen equation), however there was no significant correlation between the measures.Conclusion: This suggests that existing prediction equations used to estimate energy requirements may require modification for athletes with SCI.

The Density and Surface Tension of Aqueous Solutions of Propionate Ionic Liquids: [C4mim][Pro] and [C6mim][Pro] at Different Temperatures

The propionate acid ionic liquids, 1-alkyl-3-methylimidazolium propionate [C4mim][Pro] and [C6mim][Pro] were prepared by the neutralization method and characterized by 1H NMR spectroscopy and differential scanning calorimetry. The values of density and surface tension of aqueous [C4mim][Pro] and [C6mim][Pro] with various molalities were determined at different temperatures, and the coefficient of thermal expansion, the apparent molar volume and the parachor for these solutions were calculated. The values of the apparent molar expansibility of the solute obtained from data of the apparent molar volume are in good agreement with the values calculated by the Harned–Owen equation. An empirical equation for prediction of surface tension for aqueous [C4mim][Pro] and [C6mim][Pro] was put forward and the values of the surface tension predicted by the empirical equation are very similar and highly correlated with the corresponding experimental values and the results predicted by the parachor semi-empirical method for solutions.

Accuracy and Applicability of Resting Metabolic Rate Prediction Equations Differ for Women Across the Lifespan

Background: Nutrition clinicians need accurate and reliable resting metabolic rate (RMR) assessments to determine energy needs and an appropriate nutrition care plan. Material/Methods: This cross-sectional study compared the accuracy of eight RMR prediction equations (Harris-Benedict, Robertson and Reid, Cunningham 1980, FAO/WHO/UNU, Owen, Mifflin-St. Jeor, Cunningham 1991, and Nelson) to measured RMR by indirect calorimetry among young (n=57; age: 25±3 years), midlife (n=57; age: 44±3 years), and older (n=46; age: 68±5 years) women. Paired t-tests examined differences between predicted and measured RMR. Statistical analyses were conducted using SPSS (version 21), with significance defined as p&lt;0.05. Bland-Altman plots displayed prediction bias and agreement. Prediction accuracy was defined when predicted RMR was ±10% of measured RMR. Serum thyroid stimulating hormone and follicle stimulating hormone concentrations were measured to assess thyroid function and ovarian reserve, respectively. Results: The difference between predicted and measured RMR ranged from +0.6% (Owen) to +17.7% (Cunningham 1980) for the young, -2.8% (Nelson) to +18.1% (Cunningham 1980) midlife, and +2.8 (Nelson) to +26.7% (Cunningham 1980) older women. For the young women, only the Owen equation predicted RMR similar to measured RMR (p=0.905). For the older women, only the Nelson equation predicted RMR similar to measured RMR (p=0.051). All estimates using prediction equations were significantly different from measured values for midlife women. Conclusion: Many RMR prediction equations have limited applicability for women at difference stages of the lifespan, thus impacting patient outcomes. Additional research is necessary to determine the appropriateness of RMR prediction equations among women of all ages.

Predicted versus measured resting energy expenditure in patients requiring home parenteral nutrition

ObjectivesGuidelines from the European Society for Clinical Nutrition and Metabolism (ESPEN) recommend between 20 and 35 kcal/kg daily for patients requiring home parenteral nutrition (PN). Other guidelines use predictive equations. However, these equations have not been validated. Indirect calorimetry is recommended as the gold standard for determining resting energy expenditure (REE). The aim of this study was to compare the frequently used equations with measured REE. MethodsSeventy-six hospitalized patients suffering from intestinal failure (ages 21–85 y) were enrolled between January 2012 and May 2014. They were eligible for implementation of home parenteral nutrition (HPN) due to short bowel syndrome (54%), intestinal fistulae (24%), cancer obstruction (16%), and radiation-induced intestinal injury (6%). REE measurements were compared with predictive equations by Harris and Benedict (HB), Owen, Ireton-Jones, and Mifflin, as well as recommendations from ESPEN. ResultsIn all, 152 calorimetry measurements (two per patient) were performed in 76 patients, after total PN administrations. An average result of REE measurement by indirect calorimetry was 1181 ± 322 kcal/d. Variability in momentary energy expenditure (MEE) from one measurement to the other was 8% ± 7%. Bland-Altman analysis showed a mean bias of –192 ± 300 kcal/d between MEE and estimated energy expenditure using the HB equation, which means that the equation increased the score on average by 192 ± 300 kcal/d. Limits of agreement (LoA) between the two methods was –780 to +396 kcal/d. Estimation energy expenditure using the Ireton-Jones equation gave a mean bias of –359 ± 335 kcal/d. LoA between the two methods was –1015 to +297 kcal/d. For Owen equation, Bland-Altman analysis showed a mean bias of –208 ± 313 kcal/d and the LoA between the two methods was –822 to +406 kcal/d. Using the Mifflin equation, estimation energy expenditure gave a mean bias of –172 ± 312 kcal/d and the LoA between the two methods was –784 to +439 kcal/d. Using the ESPEN range (20–35 kcal/kg daily) analysis showed mean bias of –13 ± 326 kcal/d and the LoA was –652 to +626 kcal/d for 20 kcal/kg daily and mean bias of –909 ± 436 kcal/d with the LoA between the two methods –1764 to –54 kcal/d for 35 kcal/kg daily. ConclusionIf REE cannot be measured by indirect calorimetry in patients qualified for HPN, the Ireton-Jones equation and the 20 kcal/kg/d ESPEN recommendation seem to be the most appropriate ones as it provides results that constitute the best approximation of calorimetric examination results.

Accuracy of Four Resting Metabolic Rate Predictive Equations in Obese Women

Calculating the estimated resting metabolic rate (RMR) in severely obese patients is useful, but there is controversy concerning the effectiveness of available predictive equations using body weight. This study compared the accuracy of four commonly used RMR predictive equations to measured RMR. We evaluated the efficacy of RMR equations against indirect calorimetry in forth female obese subjects. The subjects had their RMR measured by indirect calorimetry and compared to the most commonly used prediction equations (Harris-Benedict, Owen, and Mifflin-St Jeor, World Health Organization/Food and Agriculture Organization/United Nations University [WHO/FAU/UNU]). The results shows that Owen and Mifflin-St Jeor equations significantly under-estimated to our measured RMR. However, the WHO/FAO/UNU Equation was the most accurately predictive RMR values (1,543.6±110.3 vs. 1,484.3±218.3) compared to measured RMR. As based on data, we suggest that WHO/FAO/UNU equation and Harris-Benedicts equation would be most reasonable and useful for Korean obese women.

Accuracy of Resting Energy Expenditure Calculations in Unselected Overweight and Obese Patients

Aims: Measurements of resting energy expenditure (REE) were compared with the data of 14 equations to determine their accuracy. Methods: REE measurements by indirect calorimetry in 1,032 unselected overweight and obese men (n = 306) and women (n = 726) were compared with calculations by 14 different formulas. Results: The mean (± SD) values calculated with the Owen, Robertson and Reid and WHO-I equations were not significantly different from our measurement of 1,682 ± 441.9 kcal/24 h. The values obtained with the Livingston, Mifflin, Müller and Bernstein equations were significantly different but still within a range of ±100 kcal/24 h. For females, the best comparison was observed with the Müller equation which, however, differed substantially in males. For men, the Cunningham equation was best, but it gave the worst comparison in women. A good individual match was only obtained with the equation of Robertson and Reid in 34% of the men and with the Owen equation in 38% of the women. All other formulas were less accurate. Drug treatment for 55% of the subjects had no effect on the mismatch between calculated and measured data. Conclusion: Calculations of REE with most equations seem to be valid in a group analysis but they are not helpful for the estimation of an obese patient's individual energy expenditure.