Variability in results from predicted resting energy needs as compared to measured resting energy expenditure in Korean children

Lawrence, Jeannine C.; Lee, Hyun-Mi; Kim, Jaehee; Kim, Min Jung

doi:10.1016/j.nutres.2009.10.017

Cited by 12 publications

(14 citation statements)

References 24 publications

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“…Meanwhile, the Maffeis equation provided the higher accuracy in the non-obese group (accurate prediction: 68%, bias: 1.9%, RMSPE: 107.7 kcal/d) than in the obese group of our study. Lawrence et al [19] elucidated that REE predicted by the Maffeis equation was not significantly different with REE measured for Korean children with normal weight. These results showed that the Maffeis equation was good for the non-obese Korean children and adolescents only, not for the obese group.…”

Section: Discussionmentioning

confidence: 99%

“…The Kim (W) and the Liu equations were selected for use to account for the ethnic differences of REE. The Kim (W) equation was developed from 92 Korean children, aged from 4 to 11 years [19], and the Liu equation was generated from 119 Chinese adults whose ages ranged from 20 to 78 years old [13]. Previous study concluded that FFM (fat-free mass)-based equations did not improve the REE prediction in 121 Dutch obese adolescents [10].…”

Section: Methodsmentioning

confidence: 99%

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Accuracy of predictive equations for resting energy expenditure (REE) in non-obese and obese Korean children and adolescents

Kim

2012

Nutr Res Pract

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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, 25.9 kg/m2) than in the non-obese group (44.8 kg, 19.0 kg/m2). 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.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Accuracy of predictive equations for resting energy expenditure (REE) in non-obese and obese Korean children and adolescents

Kim

2012

Nutr Res Pract

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“…The FAO/WHO/UNU and Schofield equations were developed from predominantly normal-weight samples. The Harris-Benedict equation was also included because it was the most widely used of the earlier studies [ 14 ]. Cunningham equation based on measurement of fat-free mass as an independent variable was selected, along with De Lorenzo and Park's equations were developed for athletes [ 15 18 19 ].…”

Section: Methodsmentioning

confidence: 99%

“…Cunningham's equation was not developed for an athletic population, but rather for healthy untrained adult subjects. In addition, Harris-Benedict's and Cunningham's formulas were developed in 1918 and 1980, respectively [ 9 14 ]. Over the years, many prediction equations have become available, some of which might be regarded as more appropriate.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of predictive equations for resting metabolic rate in Korean athletic and non-athletic adolescents

Kim

et al. 2015

Nutr Res Pract

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BACKGROUND/OBJECTIVESAthletes 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/METHODSA total of 50 athletes (mean age of 16.6 ± 1.0 years, 30 males and 20 females) and 50 non-athletes (mean age of 16.5 ± 0.5 years, 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.RESULTSUntil 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 × fat-free mass] is paramount when examining athletes.CONCLUSIONSThe RMR prediction equation developed in this study is better in assessing the resting metabolic rate of Korean athletic adolescents.

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“…Lawrence et al ( 13 ) designed several REE prediction equation models, known as Kim's equations, in 2009. They studied a sample size of 92 apparently healthy preschool children and third and fifth graders (38 boys and 54 girls) aged 4–11 years from a rural area of South Korea.…”

Section: Resultsmentioning

confidence: 99%

Resting Energy Expenditure Prediction Equations in the Pediatric Population: A Systematic Review

et al. 2021

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Background and Aims: The determination of energy requirements is necessary to promote adequate growth and nutritional status in pediatric populations. Currently, several predictive equations have been designed and modified to estimate energy expenditure at rest. Our objectives were (1) to identify the equations designed for energy expenditure prediction and (2) to identify the anthropometric and demographic variables used in the design of the equations for pediatric patients who are healthy and have illness.Methods: A systematic search in the Medline/PubMed, EMBASE and LILACS databases for observational studies published up to January 2021 that reported the design of predictive equations to estimate basal or resting energy expenditure in pediatric populations was carried out. Studies were excluded if the study population included athletes, adult patients, or any patients taking medications that altered energy expenditure. Risk of bias was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies.Results: Of the 769 studies identified in the search, 39 met the inclusion criteria and were analyzed. Predictive equations were established for three pediatric populations: those who were healthy (n = 8), those who had overweight or obesity (n = 17), and those with a specific clinical situation (n = 14). In the healthy pediatric population, the FAO/WHO and Schofield equations had the highest R2 values, while in the population with obesity, the Molnár and Dietz equations had the highest R2 values for both boys and girls.Conclusions: Many different predictive equations for energy expenditure in pediatric patients have been published. This review is a compendium of most of these equations; this information will enable clinicians to critically evaluate their use in clinical practice.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=226270, PROSPERO [CRD42021226270].

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Variability in results from predicted resting energy needs as compared to measured resting energy expenditure in Korean children

Cited by 12 publications

References 24 publications

Accuracy of predictive equations for resting energy expenditure (REE) in non-obese and obese Korean children and adolescents

Accuracy of predictive equations for resting energy expenditure (REE) in non-obese and obese Korean children and adolescents

Accuracy of predictive equations for resting metabolic rate in Korean athletic and non-athletic adolescents

Resting Energy Expenditure Prediction Equations in the Pediatric Population: A Systematic Review

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