scholarly journals Resting Energy Expenditure in the Elderly: Systematic Review and Comparison of Equations in an Experimental Population

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 458
Author(s):  
Honoria Ocagli ◽  
Corrado Lanera ◽  
Danila Azzolina ◽  
Gianluca Piras ◽  
Rozita Soltanmohammadi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Energy Expenditure ◽  
Web Application ◽  
Intraclass Correlation ◽  
Resting Energy Expenditure ◽  
The Elderly ◽  
Elderly Subjects ◽  
Experimental Population ◽  
Predictive Equations ◽  
Resting Energy

Elderly patients are at risk of malnutrition and need an appropriate assessment of energy requirements. Predictive equations are widely used to estimate resting energy expenditure (REE). In the study, we conducted a systematic review of REE predictive equations in the elderly population and compared them in an experimental population. Studies involving subjects older than 65 years of age that evaluated the performance of a predictive equation vs. a gold standard were included. The retrieved equations were then tested on a sample of 88 elderly subjects enrolled in an Italian nursing home to evaluate the agreement among the estimated REEs. The agreement was assessed using the intraclass correlation coefficient (ICC). A web application, equationer, was developed to calculate all the estimated REEs according to the available variables. The review identified 68 studies (210 different equations). The agreement among the equations in our sample was higher for equations with fewer parameters, especially those that included body weight, ICC = 0.75 (95% CI = 0.69–0.81). There is great heterogeneity among REE estimates. Such differences should be considered and evaluated when estimates are applied to particularly fragile populations since the results have the potential to impact the patient’s overall clinical outcome.

scholarly journals Resting energy expenditure in obese women: comparison between measured and estimated values

2016 ◽  
Vol 116 (7) ◽  
pp. 1306-1313 ◽  
Author(s):  
Vanessa Fadanelli Schoenardie Poli ◽  
Ricardo Badan Sanches ◽  
Amanda dos Santos Moraes ◽  
João Pedro Novo Fidalgo ◽  
Maythe Amaral Nascimento ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Intraclass Correlation ◽  
Resting Energy Expenditure ◽  
Fat Free Mass ◽  
Interdisciplinary Therapy ◽  
Obese Women ◽  
Predictive Equations ◽  
Before And After ◽  
Resting Energy

AbstractAssessing energy requirements is a fundamental activity in clinical dietetic practice. The aim of this study was to investigate which resting energy expenditure (REE) predictive equations are the best alternatives to indirect calorimetry before and after an interdisciplinary therapy in Brazilian obese women. In all, twelve equations based on weight, height, sex, age, fat-free mass and fat mass were tested. REE was measured by indirect calorimetry. The interdisciplinary therapy consisted of nutritional, physical exercise, psychological and physiotherapy support during the course of 1 year. The average differences between measured and predicted REE, as well as the accuracy at the ±10 % level, were evaluated. Statistical analysis included paired t tests, intraclass correlation coefficients and Bland–Altman plots. Validation was based on forty obese women (BMI 30–39·9 kg/m2). Our major findings demonstrated a wide variation in the accuracy of REE predictive equations before and after weight loss in non-morbid, obese women. The equations reported by Harris–Benedict and FAO/WHO/United Nations University (UNU) were the only ones that did not show significant differences compared with indirect calorimetry and presented a bias <5 %. The Harris–Benedict equation provided 40 and 47·5 % accurate predictions before and after therapy, respectively. The FAO equation provided 35 and 47·5 % accurate predictions. However, the Bland–Altman analysis did not show good agreement between these equations and indirect calorimetry. Therefore, the Harris–Benedict and FAO/WHO/UNU equations should be used with caution for obese women. The need to critically re-assess REE data and generate regional and more homogeneous REE databases for the target population is reinforced.

scholarly journals Comparison of Predictive Equations for Resting Energy Expenditure in Overweight and Obese Adults

2011 ◽  
Vol 2011 ◽  
pp. 1-5 ◽  
Author(s):  
Erick Prado de Oliveira ◽  
Fábio Lera Orsatti ◽  
Okesley Teixeira ◽  
Nailza Maestá ◽  
Roberto Carlos Burini
Keyword(s):  
Body Mass Index ◽  
Energy Expenditure ◽  
Systematic Error ◽  
Indirect Calorimetry ◽  
Intraclass Correlation ◽  
Resting Energy Expenditure ◽  
Obese Adults ◽  
Predictive Equations ◽  
New Equation ◽  
Resting Energy

Objective. To compare values from predictive equations of resting energy expenditure (REE) with indirect calorimetry (IC) in overweight and obese adults.Methods. Eighty-two participants aged 30 to 60 years old were retrospectively analyzed. The persons had a body mass index ≥25 kg/m2. REE was estimated by IC and other five equations of the literature (Harris and Benedict, WHO1, WHO2, Owen, Mifflin).Results. All equations had different values when compared to those of IC. The best values were found by Harris and Benedict, WHO1, and WHO2, with high values of intraclass correlation coefficient and low values of mean difference. Furthermore, WHO1 and WHO2 showed lower systematic error and random.Conclusion. No predictive equations had the same values of REE as compared to those of indirect calorimetry, and those which least underestimated REE were the equations of WHO1, WHO2, and Harris and Benedict. The next step would be to validate the new equation proposed.

Estimation of Resting Energy Expenditure Using Predictive Equations in Critically Ill Children: Results of a Systematic Review

2018 ◽  
Vol 42 (6) ◽  
pp. 976-986 ◽  
Author(s):  
Corinne Jotterand Chaparro ◽  
Clémence Moullet ◽  
Patrick Taffé ◽  
Jocelyne Laure Depeyre ◽  
Marie-Hélène Perez ◽  
...  
Keyword(s):  
Systematic Review ◽  
Energy Expenditure ◽  
Critically Ill ◽  
Resting Energy Expenditure ◽  
Critically Ill Children ◽  
Predictive Equations ◽  
Resting Energy

scholarly journals Systematic Review of Equations for Estimating Energy Requirement in the Elderly: Results and Future Perspectives

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 28-28
Author(s):  
Dario Gregori ◽  
Honoria Ocagli ◽  
Corrado Lanera ◽  
Silvia Gallipoli ◽  
Giulia Lorenzoni
Keyword(s):  
Systematic Review ◽  
Nursing Home ◽  
Web Application ◽  
Energy Requirement ◽  
Intraclass Correlation ◽  
Laboratory Data ◽  
Resting Energy Expenditure ◽  
The Elderly ◽  
Normal Weight ◽  
The Body

Abstract Objectives Estimating the right energy requirement for the elderly is a clinically relevant topic since malnutrition is common in such population. Predictive equations are widely used to estimate the resting energy expenditure (REE). However, only a few equations have been specifically developed for the elderly, and they often provide different outputs. The present work aimed at presenting a web application able to assist the clinicians in identifying the most appropriate equation to estimate the REE in the elderly. Methods The development of the application is based on a systematic review of studies that had tested the performance of a predictive equation to estimate REE vs. a gold standard in subjects older than 65 years of age. The systematic review was carried out using PubMed, Scopus, and Embase following the PRISMA guidelines. Furthermore, the equations retrieved were applied to a sample of 88 subjects enrolled in an Italian nursing home to evaluate the agreement among the estimated REE. The agreement was assessed using the Intraclass Correlation Coefficient (ICC) for the sample overall and for specific subsets of patients (males, females, normal-weight and overweight/obese subjects). Results The initial search identified 6353 studies. After the screening, 69 studies, corresponding to 210 single equations, were included in the analysis. The type and number of parameters used in each equation were highly variable and the most frequently used were demographics, anthropometric and laboratory data, and physical activity frequency. The application of the equations to the sample of 88 subjects enrolled in the nursing home showed that the ones that included a small number of parameters were found to have a good agreement (especially those including the body weight alone: ICC = 0.75, 95% IC 0.69–0.81) while the addition of other parameters resulted in a worsening of the agreement. The same results were obtained for the sample overall and for the specific subsets of patients considered. The results of the systematic review served as a basis for the development of the web application (http://r-ubesp.dctv.unipd.it:3838/equationer). Conclusions The proposed web application is expected to guide the clinicians in identifying the most appropriate equation to estimate REE according to the subject's characteristics. Funding Sources University of Padova.

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

2021 ◽  
Vol 9 ◽  
Author(s):  
Jimena Fuentes-Servín ◽  
Azalia Avila-Nava ◽  
Luis E. González-Salazar ◽  
Oscar A. Pérez-González ◽  
María Del Carmen Servín-Rodas ◽  
...  
Keyword(s):  
Systematic Review ◽  
Energy Expenditure ◽  
Pediatric Patients ◽  
Assessment Tool ◽  
Pediatric Population ◽  
Resting Energy Expenditure ◽  
Cross Sectional ◽  
Predictive Equations ◽  
Pediatric Populations ◽  
Resting Energy

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].

Reliability of resting energy expenditure in major burns: Comparison between measured and predictive equations

2019 ◽  
Vol 38 (6) ◽  
pp. 2763-2769 ◽  
Author(s):  
Jinwoo Jeon ◽  
Dohern Kym ◽  
Yong Suk Cho ◽  
Youngmin Kim ◽  
Jaechul Yoon ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Resting Energy Expenditure ◽  
Predictive Equations ◽  
Resting Energy

scholarly journals Resting energy expenditure in elite athletes: development of new predictive equations based on anthropometric variables and bioelectrical impedance analysis derived phase angle

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Maurizio Marra ◽  
Olivia Di Vincenzo ◽  
Iolanda Cioffi ◽  
Rosa Sammarco ◽  
Delia Morlino ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Phase Angle ◽  
Elite Athletes ◽  
Resting Energy Expenditure ◽  
Sport Performance ◽  
Accurate Estimation ◽  
Anthropometric Parameters ◽  
Predictive Equations ◽  
Good Prediction Accuracy ◽  
Resting Energy

Abstract Background An accurate estimation of athletes’ energy needs is crucial in diet planning to improve sport performance and to maintain an appropriate body composition. This study aimed to develop and validate in elite athletes new equations for estimating resting energy expenditure (REE) based on anthropometric parameters as well as bioimpedance analysis (BIA)-derived raw variables and to validate the accuracy of selected predictive equations. Methods Adult elite athletes aged 18–40 yrs were studied. Anthropometry, indirect calorimetry and BIA were performed in all subjects. The new predictive equations were generated using different regression models. The accuracy of the new equations was assessed at the group level (bias) and at the individual level (precision accuracy), and then compared with the one of five equations used in the general population or three athletes-specific formulas. Results One-hundred and twenty-six male athletes (age 26.9 ± 9.1 yrs; weight 71.3 ± 10.9 kg; BMI 22.8 ± 2.7 kg/m2) from different sport specialties were randomly assigned to the calibration (n = 75) or validation group (n = 51). REE was directly correlated with individual characteristics, except for age, and raw BIA variables. Most of the equations from the literature were reasonably accurate at the population level (bias within ±5%). The new equations showed a mean bias −0.3% (Eq. A based on anthropometric parameters) and −0.6% (Eq. B based on BIA-derived raw variables). Precision accuracy (individual predicted-measured differences within ±5%) was ~75% in six out of eight of the selected equations and even higher for Eq. A (82.4%) and Eq. B (92.2%). Conclusion In elite athletes, BIA-derived phase angle is a significant predictor of REE. The new equations have a very good prediction accuracy at both group and individual levels. The use of phase angle as predictor of REE requires further research with respect to different sport specialties, training programs and training level.

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