Novel Equations to Estimate Resting Energy Expenditure during Sitting and Sleeping

2021 ◽  
pp. 1-9
Author(s):  
Akiko Uchizawa ◽  
Masanobu Hibi ◽  
Hiroyuki Sagayama ◽  
Simeng Zhang ◽  
Haruka Osumi ◽  
...  
Keyword(s):  
Body Composition ◽  
Body Weight ◽  
Energy Expenditure ◽  
Resting Energy Expenditure ◽  
Individual Characteristics ◽  
The Body ◽  
Fat Free Mass ◽  
Middle Aged ◽  
Metabolic Chamber ◽  
Resting Energy

<b><i>Introduction:</i></b> Young and early middle-aged office workers spend most of the day sitting or sleeping. Few studies have used a metabolic chamber to report sitting resting energy expenditure (REE) or sleeping metabolic rate (SMR) estimation equations. This study aimed to develop novel equations for estimating sitting REE and SMR, and previously published equations for SMR were compared against measured values. <b><i>Methods:</i></b> The relationships among sitting REE, SMR, and body composition measured in clinical trials were analyzed. The body composition (fat-free mass [FFM] and fat mass) and energy metabolism of 85 healthy young and early middle-aged Japanese individuals were measured using dual-energy X-ray absorptiometry and a metabolic chamber, respectively. Novel estimate equations were developed using stepwise multiple regression analysis. Estimates of SMR using a new equation and 2 published equations were compared against measured SMR. <b><i>Results:</i></b> The sitting mREE and mSMR were highly correlated (<i>r</i> = 0.756, <i>p</i> &#x3c; 0.01). The new FFM-based estimate accounted for 50.4% of the variance in measured sitting REE (mREE) and 82.3% of the variance in measured SMR (mSMR). The new body weight-based estimate accounted for 49.3% of the variance in sitting mREE and 82.2% of the variance in mSMR. Compared with mSMR, the SMR estimate using an FFM-based published equation was slightly underestimated. <b><i>Conclusion:</i></b> These novel body weight- and FFM-based equations may help estimate sitting REE and SMR in young and early middle-aged adults. Previous SMR estimated FFM-based equations were slightly underestimated against measured SMR; however, we confirmed the previous SMR estimate equations could be useful. This finding suggests that sitting REE and SMR can be easily estimated from individual characteristics and applied in clinical settings.

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

2020 ◽  
Vol 105 (4) ◽  
pp. e1741-e1748 ◽  
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) &gt; 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.

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

2000 ◽  
Vol 24 (9) ◽  
pp. 1153-1157 ◽  
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

scholarly journals Resting Energy Expenditure and Body Composition in Overweight Men and Women Living in a Temperate Climate

2020 ◽  
Vol 9 (1) ◽  
pp. 203
Author(s):  
Marcos Martin-Rincon ◽  
Mario Perez-Valera ◽  
David Morales-Alamo ◽  
Ismael Perez-Suarez ◽  
Cecilia Dorado ◽  
...  
Keyword(s):  
Body Composition ◽  
Energy Expenditure ◽  
Resting Energy Expenditure ◽  
The Body ◽  
Temperate Climate ◽  
Obese Patients ◽  
Men And Women ◽  
Significant Bias ◽  
Overweight Or Obesity ◽  
Resting Energy

This study aimed to determine whether the measured resting energy expenditure (REE) in overweight and obese patients living in a temperate climate is lower than the predicted REE; and to ascertain which equation should be used in patients living in a temperate climate. REE (indirect calorimetry) and body composition (DXA) were measured in 174 patients (88 men and 86 women; 20–68 years old) with overweight or obesity (BMI 27–45 kg m−2). All volunteers were residents in Gran Canaria (monthly temperatures: 18–24 °C). REE was lower than predicted by most equations in our population. Age and BMI were similar in both sexes. In the whole population, the equations of Mifflin, Henry and Rees, Livingston and Owen, had similar levels of accuracy (non-significant bias of 0.7%, 1.1%, 0.6%, and −2.2%, respectively). The best equation to predict resting energy expenditure in overweight and moderately obese men and women living in a temperate climate all year round is the Mifflin equation. In men, the equations by Henry and Rees, Livingston, and by Owen had predictive accuracies comparable to that of Mifflin. The body composition-based equation of Johnston was slightly more accurate than Mifflin’s in men. In women, none of the body composition-based equations outperformed Mifflin’s.

scholarly journals Energy intake, physical activity and body weight: a simulation model

1995 ◽  
Vol 73 (3) ◽  
pp. 337-347 ◽  
Author(s):  
Klaas R. Westerterp ◽  
Jeroen H. H. L. M. Donkers ◽  
Elisabeth W. H. M. Fredrix ◽  
Piet oekhoudt
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Body Weight ◽  
Energy Balance ◽  
Energy Expenditure ◽  
Dietary Intake ◽  
Energy Intake ◽  
Relative Size ◽  
The Body ◽  
Fat Free Mass

In adults, body mass (BM) and its components fat-free mass (FFM) and fat mass (FM) are normally regulated at a constant level. Changes in FM and FFM are dependent on energy intake (EI) and energy expenditure (EE). The body defends itself against an imbalance between EI and EE by adjusting, within limits, the one to the other. When, at a given EI or EE, energy balance cannot be reached, FM and FFM will change, eventually resulting in an energy balance at a new value. A model is described which simulates changes in FM and FFM using EI and physical activity (PA) as input variables. EI can be set at a chosen value or calculated from dietary intake with a database on the net energy of foods. PA can be set at a chosen multiple of basal metabolic rate (BMR) or calculated from the activity budget with a database on the energy cost of activities in multiples of BMR. BMR is calculated from FFM and FM and, if necessary, FFM is calculated from BM, height, sex and age, using empirical equations. The model uses existing knowledge on the adaptation of energy expenditure (EE) to an imbalance between EI and EE, and to resulting changes in FM and FFM. Mobilization and storage of energy as FM and FFM are functions of the relative size of the deficit (EI/EE) and of the body composition. The model was validated with three recent studies measuring EE at a fixed EI during an interval with energy restriction, overfeeding and exercise training respectively. Discrepancies between observed and simulated changes in energy stores were within the measurement precision of EI, EE and body composition. Thus the consequences of a change in dietary intake or a change in physical activity on body weight and body composition can be simulated.

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

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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