Predictive Equations Based on Body Composition for Resting Energy Expenditure Estimation in Adults with Obesity

Background and Aim: An accurate estimation of Resting Energy Expenditure (REE) in patients with obesity is crucial. Therefore, our aim was to assess the validity of REE predictive equations based on body composition variables in treatment-seeking Arab adults with obesity. Methods: Body composition and REE were measured by Tanita BC-418 bioimpedance and Vmax Encore 229 IC, respectively, and predictive equations based on fat mass and fat-free mass were used in REE estimations among 87 adults of both genders, in the Outpatient Clinic in the Department of Nutrition and Dietetics at Beirut Arab University (Lebanon). The mean differences between the measured and estimated REE values were calculated to assess the accuracy, and the Bland-Altman method was used to assess the level of agreement. Results: Ten predictive equations were included. In males, all the predictive equations gave significantly different estimates of REE when compared to that measured by IC. On the other hand, in females, the mean difference between the REE value estimated by Huang and Horie-Waitzberg equations and that measured using IC was not significant, and the agreement was confirmed using Bland-Altman plots. Conclusion: Huang and Horie-Waitzberg equations are suggested for accurate REE estimation in females; however, new validated REE estimation equations for males in this population are still needed.

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Accuracy of predictive equations for evaluation of resting energy expenditure in Brazilian patients with type 2 diabetes.

10.21203/rs.3.rs-25229/v1 ◽

2020 ◽

Author(s):

Thaiciane Grassi ◽

Francesco Pinto Boeno ◽

Mauren Minuzzo de Freitas ◽

Tatiana Pedroso de Paula ◽

Luciana Vercoza Viana ◽

...

Keyword(s):

Type 2 Diabetes ◽

Body Composition ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Fat Free Mass ◽

Composition Analysis ◽

Cross Sectional ◽

Predictive Equations ◽

Resting Energy

Abstract Background Evaluation of the resting energy expenditure (REE) is essential to ensure an appropriate dietary prescription for patients with type 2 diabetes. The aim of this study was to evaluate the accuracy of predictive equations for REE estimation in patients with type 2 diabetes, considering indirect calorimetry (IC) as the reference method.Methods A cross-sectional study was conducted in 62 patients (31 men and 31 women) with type 2 diabetes. Clinical and laboratory variables were evaluated, as well as body composition by electrical bioimpedance. The REE was measured by IC (QUARK RMR, Cosmed, Rome, Italy) and estimated by predictive equations. Data were analyzed using Bland–Altman plots, paired t-tests, and Pearson’s correlation coefficients.Results Patients in the sample had a mean age of 63.1 ± 5.2 years, median diabetes duration of 11 (1–36) years, and mean A1C of 7.6 ± 1.2%. Body composition analysis revealed a mean fat free mass of 35.2 ± 11.8 kg and fat mass of 29.1 ± 8.8 kg. There was wide variation in the accuracy of REE values predicted by equations when compared to those measured by IC. For women, the FAO/WHO/UNO equation provided the best REE prediction in comparison to measured REE (-1.8% difference). For men, the Oxford equation yielded values closest to those measured by IC (-1.3% difference).Conclusions In this sample of the patients with type 2 diabetes, the best predictive equations to estimate REE were FAO/WHO/UNO and Oxford for women and men, respectively.

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Resting Energy Expenditure during Breastfeeding: Body Composition Analysis vs. Predictive Equations Based on Anthropometric Parameters

Nutrients ◽

10.3390/nu12051274 ◽

2020 ◽

Vol 12 (5) ◽

pp. 1274

Author(s):

Agnieszka Bzikowska-Jura ◽

Adriana Szulińska ◽

Dorota Szostak-Węgierek

Keyword(s):

Body Composition ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Accurate Estimation ◽

Composition Analysis ◽

Anthropometric Parameters ◽

Predictive Equations ◽

Body Composition Analysis ◽

Mathematical Equations ◽

Resting Energy

Accurate estimation of energy expenditure in a breastfeeding woman is crucial for maintaining the proper nutritional status of the woman and healthy development of the infant. The current literature does not contain data regarding resting energy expenditure (REE) in breastfeeding women. Using mathematical equations is the most common method of REE assessment. However, due to changes in metabolism and body composition during pregnancy and lactation, the mathematical equations used among the general population may not apply. The aim of this study was to evaluate the resting energy expenditure of exclusively breastfeeding women by using body composition analysis–estimated REE (eREE) and to provide the most appropriate predictive equations–predicted REE (pREE) based on anthropometric parameters to estimate it. This was a pilot study with 40 exclusively breastfeeding women. Height and weight were measured and body composition analysis was performed. We predicted REE using fourteen self-selected equations, based on anthropometric parameters and/or age, and/or sex. The median eREE was 1515.0 ± 68.4 kcal (95% Cl, 1477–1582 kcal) and the pREE ranged from 1149.7 kcal (95% Cl, 1088.7–1215.0) by Bernstein et al., to 1576.8 kcal (95% Cl, 1479.9–1683.4), by Müller et al. Significant differences between eREE and all pREE were observed (p < 0.001, except Korth et al. equations). The Müller et al. equation was the most accurate with the smallest individual variation. All predictive equations showed low agreement, and in most cases, the results were underestimated. These findings indicate the need for further studies to propose more suitable methods to determine the energy requirements for breastfeeding women.

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

Journal of the International Society of Sports Nutrition ◽

10.1186/s12970-021-00465-x ◽

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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Are Predictive Energy Expenditure Equations Accurate in Cirrhosis?

Nutrients ◽

10.3390/nu11020334 ◽

2019 ◽

Vol 11 (2) ◽

pp. 334 ◽

Cited By ~ 11

Author(s):

Tannaz Eslamparast ◽

Benjamin Vandermeer ◽

Maitreyi Raman ◽

Leah Gramlich ◽

Vanessa Den Heyer ◽

...

Keyword(s):

Energy Expenditure ◽

English Language ◽

Resting Energy Expenditure ◽

Pooled Analysis ◽

Energy Requirements ◽

Significant Heterogeneity ◽

Predictive Equations ◽

Language Studies ◽

The Mean ◽

Mean Differences

Malnutrition is associated with significant morbidity and mortality in cirrhosis. An accurate nutrition prescription is an essential component of care, often estimated using time-efficient predictive equations. Our aim was to compare resting energy expenditure (REE) estimated using predictive equations (predicted REE, pREE) versus REE measured using gold-standard, indirect calorimetry (IC) (measured REE, mREE). We included full-text English language studies in adults with cirrhosis comparing pREE versus mREE. The mean differences across studies were pooled with RevMan 5.3 software. A total of 17 studies (1883 patients) were analyzed. The pooled cohort was comprised of 65% men with a mean age of 53 ± 7 years. Only 45% of predictive equations estimated energy requirements to within 90–110% of mREE using IC. Eighty-three percent of predictive equations underestimated and 28% overestimated energy needs by ±10%. When pooled, the mean difference between the mREE and pREE was lowest for the Harris–Benedict equation, with an underestimation of 54 (95% CI: 30–137) kcal/d. The pooled analysis was associated with significant heterogeneity (I2 = 94%). In conclusion, predictive equations calculating REE have limited accuracy in patients with cirrhosis, most commonly underestimating energy requirements and are associated with wide variations in individual comparative data.

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Resting Energy Expenditure in Obese Women with Primary Hypothyroidism and Appropriate Levothyroxine Replacement Therapy

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/clinem/dgaa097 ◽

2020 ◽

Vol 105 (4) ◽

pp. e1741-e1748 ◽

Cited By ~ 3

Author(s):

Emanuele Muraca ◽

Stefano Ciardullo ◽

Alice Oltolini ◽

Francesca Zerbini ◽

Eleonora Bianconi ◽

...

Keyword(s):

Body Composition ◽

Energy Expenditure ◽

Replacement Therapy ◽

Resting Energy Expenditure ◽

Primary Hypothyroidism ◽

Normal Serum ◽

Fat Free Mass ◽

Model Assessment ◽

Obese Women ◽

Resting Energy

Abstract Context Growing evidence suggests that appropriate levothyroxine (LT4) replacement therapy may not correct the full set of metabolic defects afflicting individuals with hypothyroidism. Objective To assess whether obese subjects with primary hypothyroidism are characterized by alterations of the resting energy expenditure (REE). Design Retrospective analysis of a set of data about obese women attending the outpatients service of a single obesity center from January 2013 to July 2019. Patients A total of 649 nondiabetic women with body mass index (BMI) > 30 kg/m2 and thyrotropin (TSH) level 0.4–4.0 mU/L were segregated into 2 groups: patients with primary hypothyroidism taking LT4 therapy (n = 85) and patients with normal thyroid function (n = 564). Main outcomes REE and body composition assessed using indirect calorimetry and bioimpedance. Results REE was reduced in women with hypothyroidism in LT4 therapy when compared with controls (28.59 ± 3.26 vs 29.91 ± 3.59 kcal/kg fat-free mass (FFM)/day), including when adjusted for age, BMI, body composition, and level of physical activity (P = 0.008). This metabolic difference was attenuated only when adjustment for homeostatic model assessment of insulin resistance (HOMA-IR) was performed. Conclusions This study demonstrated that obese hypothyroid women in LT4 therapy, with normal serum TSH level compared with euthyroid controls, are characterized by reduced REE, in line with the hypothesis that standard LT4 replacement therapy may not fully correct metabolic alterations related to hypothyroidism. We are not able to exclude that this feature may be influenced by the modulation of insulin sensitivity at the liver site, induced by LT4 oral administration.

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Weight and body composition changes affect resting energy expenditure predictive equations during a 12‐month weight‐loss intervention

Obesity ◽

10.1002/oby.23234 ◽

2021 ◽

Vol 29 (10) ◽

pp. 1596-1605

Author(s):

Jared H. Dahle ◽

Danielle M. Ostendorf ◽

Zhaoxing Pan ◽

Paul S. MacLean ◽

Daniel H. Bessesen ◽

...

Keyword(s):

Weight Loss ◽

Body Composition ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Weight Loss Intervention ◽

Predictive Equations ◽

Composition Changes ◽

Resting Energy

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Body composition and resting energy expenditure in humans: role of fat, fat-free mass and extracellular fluid

International Journal of Obesity ◽

10.1038/sj.ijo.0801317 ◽

2000 ◽

Vol 24 (9) ◽

pp. 1153-1157 ◽

Cited By ~ 46

Author(s):

S Nielsen ◽

DD Hensrud ◽

S Romanski ◽

JA Levine ◽

B Burguera ◽

...

Keyword(s):

Body Composition ◽

Energy Expenditure ◽

Extracellular Fluid ◽

Resting Energy Expenditure ◽

Fat Free Mass ◽

Resting Energy

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Resting energy expenditure measured longitudinally following hip fracture compared to predictive equations: is an injury adjustment required?

British Journal Of Nutrition ◽

10.1079/bjn20051593 ◽

2005 ◽

Vol 94 (6) ◽

pp. 976-982 ◽

Cited By ~ 13

Author(s):

Michelle D. Miller ◽

Lynne A. Daniels ◽

Elaine Bannerman ◽

Maria Crotty

Keyword(s):

Hip Fracture ◽

Energy Expenditure ◽

Total Energy ◽

Physiological Stress ◽

Resting Energy Expenditure ◽

Mean Difference ◽

Limits Of Agreement ◽

Predictive Equations ◽

The Mean ◽

Resting Energy

The present study measuring resting energy expenditure (REE; kJ/d) longitudinally using indirect calorimetry in six elderly women aged ≥70 years following surgery for hip fracture, describes changes over time (days 10, 42 and 84 post-injury) and compares measured values to those calculated from routinely applied predictive equations. REE was compared to REE predicted using the Harris Benedict and Schofield equations, with and without accounting for the theoretical increase in energy expenditure of 35 % secondary to physiological stress of injury and surgery. Mean (95 % CI) measured REE (kJ/d) was 4704 (4354, 5054), 4090 (3719, 4461) and 4145 (3908, 4382) for days 10, 42 and 84, respectively. A time effect was observed for measured REE,P=0·003. Without adjusting for stress the mean difference and 95 % limits of agreement for measured and predicted REE (kJ/kg per d) for the Harris Benedict equation were 1 (−9, 12), 10 (2, 18) and 9 (1, 17) for days 10, 42 and 84, respectively. The mean difference and 95 % limits of agreement for measured and predicted REE (kJ/kg per d) for the Schofield equation without adjusting for stress were 8 (−3, 19), 16 (6, 26) and 16 (10, 22) for days 10, 42 and 84, respectively. After adjusting for stress, REE predicted from the Harris Benedict or Schofield equations overestimated measured REE by between 38 and 69 %. Energy expenditure following fracture is poorly understood. Our data suggest REE was relatively elevated early in recovery but declined during the first 6 weeks. Using the Harris Benedict or Schofield equations adjusted for stress may lead to overestimation of REE in the clinical setting. Further work is required to evaluate total energy expenditure before recommendations can be made to alter current practice for calculating theoretical total energy requirements of hip fracture patients.

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

British Journal Of Nutrition ◽

10.1017/s0007114516003172 ◽

2016 ◽

Vol 116 (7) ◽

pp. 1306-1313 ◽

Cited By ~ 9

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.

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