Relationship between sleep stages and metabolic rate in humans

Differences in sleeping metabolic rate (SMR) among subjects may be related to different levels of energy expenditure associated with sleep stages. The relationship between energy expenditure and sleep stages was investigated overnight in 29 subjects (14 Caucasians and 15 Pima Indians, 18 males and 11 females; mean +/- SD, 31 +/- 7 yr, 83 +/- 26 kg, 27 +/- 11% fat). Sleep stages were determined by electroencephalogram recording, whereas energy expenditure was measured in a 1,000-liter Plexiglas sleep box constructed around a bed as a fast-response open-circuit indirect calorimeter. Eighty-five percent of the interindividual variability in SMR was explained by differences in fat-free mass, fat mass, age, sex, and race (r2 = 0.85). The intra-individual variance in SMR over time was related to sleep stages and to clock time. Within subjects, SMR in stage 3 was significantly lower than in stage 2 (-39 +/- 18 kcal/day; P < 0.05) and rapid eye movement sleep (-51 +/- 23 kcal/day; P < 0.05). Also, sleep stages were associated with different respiratory quotients. Because sleep stages are associated with only small differences in energy metabolism, our results suggest that sleep stages play a minor role in the variance of SMR among subjects. However, the duration of sleep may contribute to the variability of 24-h energy expenditure.

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Energy Balance and Energy Availability During a Selection Course for Belgian Paratroopers

Military Medicine ◽

10.1093/milmed/usab140 ◽

2021 ◽

Author(s):

Patrick Mullie ◽

Pieter Maes ◽

Laurens van Veelen ◽

Damien Van Tiggelen ◽

Peter Clarys

Keyword(s):

Physical Activity ◽

Energy Balance ◽

Energy Expenditure ◽

Metabolic Rate ◽

Energy Intake ◽

Rest Metabolic Rate ◽

Negative Energy ◽

Fat Free Mass ◽

Negative Energy Balance ◽

Energy Availability

ABSTRACT Introduction Adequate energy supply is a prerequisite for optimal performances and recovery. The aims of the present study were to estimate energy balance and energy availability during a selection course for Belgian paratroopers. Methods Energy expenditure by physical activity was measured with accelerometer (ActiGraph GT3X+, ActiGraph LLC, Pensacola, FL, USA) and rest metabolic rate in Cal.d−1 with Tinsley et al.’s equation based on fat-free mass = 25.9 × fat-free mass in kg + 284. Participants had only access to the French individual combat rations of 3,600 Cal.d−1, and body fat mass was measured with quadripolar impedance (Omron BF508, Omron, Osaka, Japan). Energy availability was calculated by the formula: ([energy intake in foods and beverages] − [energy expenditure physical activity])/kg FFM−1.d−1, with FFM = fat-free mass. Results Mean (SD) age of the 35 participants was 25.1 (4.18) years, and mean (SD) percentage fat mass was 12.0% (3.82). Mean (SD) total energy expenditure, i.e., the sum of rest metabolic rate, dietary-induced thermogenesis, and physical activity, was 5,262 Cal.d−1 (621.2), with percentile 25 at 4,791 Cal.d−1 and percentile 75 at 5,647 Cal.d−1, a difference of 856 Cal.d−1. Mean daily energy intake was 3,600 Cal.d−1, giving a negative energy balance of 1,662 (621.2) Cal.d−1. Mean energy availability was 9.3 Cal.kg FFM−1.d−1. Eleven of the 35 participants performed with a negative energy balance of 2,000 Cal.d−1, and only five participants out of 35 participants performed at a less than 1,000 Cal.d−1 negative energy balance level. Conclusions Energy intake is not optimal as indicated by the negative energy balance and the low energy availability, which means that the participants to this selection course had to perform in suboptimal conditions.

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Dietary Intake and Energy Expenditure in Breast Cancer Survivors: A Review

Nutrients ◽

10.3390/nu13103394 ◽

2021 ◽

Vol 13 (10) ◽

pp. 3394

Author(s):

Sarah A. Purcell ◽

Ryan J. Marker ◽

Marc-Andre Cornier ◽

Edward L. Melanson

Keyword(s):

Breast Cancer ◽

Physical Activity ◽

Energy Balance ◽

Energy Expenditure ◽

Dietary Intake ◽

Metabolic Rate ◽

Cancer Survivors ◽

Breast Cancer Survivors ◽

Resting Metabolic Rate ◽

Fat Free Mass

Many breast cancer survivors (BCS) gain fat mass and lose fat-free mass during treatment (chemotherapy, radiation, surgery) and estrogen suppression therapy, which increases the risk of developing comorbidities. Whether these body composition alterations are a result of changes in dietary intake, energy expenditure, or both is unclear. Thus, we reviewed studies that have measured components of energy balance in BCS who have completed treatment. Longitudinal studies suggest that BCS reduce self-reported energy intake and increase fruit and vegetable consumption. Although some evidence suggests that resting metabolic rate is higher in BCS than in age-matched controls, no study has measured total daily energy expenditure (TDEE) in this population. Whether physical activity levels are altered in BCS is unclear, but evidence suggests that light-intensity physical activity is lower in BCS compared to age-matched controls. We also discuss the mechanisms through which estrogen suppression may impact energy balance and develop a theoretical framework of dietary intake and TDEE interactions in BCS. Preclinical and human experimental studies indicate that estrogen suppression likely elicits increased energy intake and decreased TDEE, although this has not been systematically investigated in BCS specifically. Estrogen suppression may modulate energy balance via alterations in appetite, fat-free mass, resting metabolic rate, and physical activity. There are several potential areas for future mechanistic energetic research in BCS (e.g., characterizing predictors of intervention response, appetite, dynamic changes in energy balance, and differences in cancer sub-types) that would ultimately support the development of more targeted and personalized behavioral interventions.

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Effect of age on body composition and resting metabolic rate

AJP Endocrinology and Metabolism ◽

10.1152/ajpendo.1990.259.2.e233 ◽

1990 ◽

Vol 259 (2) ◽

pp. E233-E238 ◽

Cited By ~ 20

Author(s):

N. K. Fukagawa ◽

L. G. Bandini ◽

J. B. Young

Keyword(s):

Body Composition ◽

Metabolic Rate ◽

Isotope Dilution ◽

Resting Metabolic Rate ◽

Bioelectrical Impedance ◽

Impedance Analysis ◽

Open Circuit ◽

Fat Free Mass ◽

The Difference ◽

Old Men

The relationship between fat-free mass (FFM) and resting metabolic rate (RMR) was compared in young men (n = 24; age 18-33 yr), old men (n = 24; 69-89 yr), and old women (n = 20; 67-75 yr). Body composition was assessed using anthropometry, bioelectrical impedance analysis (BIA), and isotope dilution with 18O-labeled water. RMR was measured at least twice using an open-circuit indirect calorimetry system with a ventilated hood. The results indicate that the different methods for assessing body composition vary substantially and should not be used interchangeably. Anthropometry was not adequate to assess group differences in body fatness, although skinfold measures may be appropriate for within-group comparisons. BIA correlated well with the isotope-dilution technique and may be a useful measure of FFM. Finally, RMR was lower in the old men than the young (1.04 +/- 0.02 vs. 1.24 +/- 0.03 kcal/min, P less than 0.001) and remained lower even when adjusted for FFM estimated by isotope dilution (P less than 0.001). RMR in the women was also lower (0.84 +/- 0.02 kcal/min), but in contrast to the difference between young and old men, RMR adjusted for FFM did not differ (P = 0.16) between old men and women. Therefore, it is clear that differences in FFM cannot fully account for the lower RMR in the old, suggesting that aging is associated with an alteration in tissue energy metabolism.

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Effects of different types of training on weight loss

Medicinski pregled ◽

10.2298/mpns1910272s ◽

2019 ◽

Vol 72 (9-10) ◽

pp. 272-279

Author(s):

Danijel Slavic ◽

Dea Karaba-Jakovljevic ◽

Andrea Zubnar ◽

Borislav Tapavicki ◽

Tijana Aleksandric ◽

...

Keyword(s):

Energy Expenditure ◽

Metabolic Rate ◽

Body Mass ◽

Resting Metabolic Rate ◽

Young Male ◽

Fat Free Mass ◽

Daily Energy Expenditure ◽

Total Body Mass ◽

Daily Energy ◽

Different Types

Introduction. The difference between 24-hour daily energy intake and total daily energy expenditure determines whether we lose or gain weight. The resting metabolic rate is the major component of daily energy expenditure, which depends on many different factors, but also on the level of physical activity. The aim of the study was to determine anthropometric and metabolic parameters of athletes engaged in different types of training, to compare obtained results and to examine whether there are statistically significant differences among them. Material and Methods. The study included a total of 42 young male athletes divided into two groups. The first group included 21 athletes who were predominantly engaged in aerobic type of training, and the other group of 21 athletes in anaerobic type of training. Anthropometric measurements were taken and resting metabolic rate was assessed using the indirect calorimetry method. The results were statistically analyzed and the differences in parameters between the two groups were compared. Results. Statistically significant differences were established in total body mass, amount of fat-free mass and muscle mass, body mass index, as well as in the relative metabolic indices between two groups of subjects. Conclusion. The percentage of fat-free body mass has the greatest impact on the resting metabolic rate. The rate of metabolic activity of this body compartment is higher in athletes engaged in aerobic than in athletes engaged in anaerobic type of training.

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Metabolic Adaptations to Weight Loss: Relative Changes in Resting Metabolic Rate and Energy Expenditure for Physical Activity and Association With Weight Loss Maintenance

Current Developments in Nutrition ◽

10.1093/cdn/nzab041_041 ◽

2021 ◽

Vol 5 (Supplement_2) ◽

pp. 526-526

Author(s):

Rachel Silver ◽

Sai Das ◽

Michael Lowe ◽

Susan Roberts

Keyword(s):

Physical Activity ◽

Weight Loss ◽

Linear Regression ◽

Energy Expenditure ◽

Metabolic Rate ◽

Fat Mass ◽

Weight Regain ◽

Resting Metabolic Rate ◽

Fat Free Mass ◽

The Mean

Abstract Objectives There is persistent controversy over the extent to which different components of energy expenditure disproportionately decrease after weight loss and contribute to weight regain through decreased energy requirements. We conducted a secondary analysis of the CALERIE I study to test the hypothesis that decreased resting metabolic rate (RMR) and energy expenditure for physical activity (EEPA) after a 6-month calorie restriction intervention would predict weight regain at 12 months, with a greater decrease in RMR than EEPA. Methods Participants (n = 46) received all food and energy-containing beverages for 6 months. Outcome measures included total energy expenditure by doubly labeled water, RMR by indirect calorimetry, and body composition by BOD POD. Predictions for RMR and EEPA were derived from baseline linear regression models including age, sex, fat mass, and fat free mass. Baseline regression coefficients were used to calculate the predicted RMR and EEPA at 6 months. Residuals were calculated as the difference between measured and predicted values and were adjusted for body weight. The presence of metabolic adaptation was evaluated by a paired t-test comparing measured and predicted RMR at 6 months. Differences between 6-month RMR and EEPA residuals were evaluated by the same method. Linear regression was used to assess the association between 6-month residuals and weight loss maintenance (% weight change, 6 to 12 months). Results Mean weight loss was 6.9% at 6 months with 2.1% regain from 6 to 12 months. No adaptation in RMR was observed at 6 months (mean residual: 19 kcal; 95% confidence interval: −9, 48; P = 0.18). However, significant adaptation was observed in EEPA (mean residual: −199 kcal; −126, −272; P < 0.0001). In addition, the mean 6-month RMR residual was significantly greater than the mean 6-month EEPA residual (218 kcal; 133, 304; P < 0.0001). There was no significant association between 6-month RMR or EEPA residuals and weight regain at 12 months (P = 0.56, 0.34). Conclusions There was no measurable decrease in RMR with weight loss after adjusting for changes in fat free mass and fat mass, but there was a decrease in EEPA. Changes in RMR and EEPA with weight loss over 6 months did not predict weight regain at 12 months. Funding Sources Jean Mayer USDA Human Nutrition Research Center on Aging Doctoral Scholarship; USDA agreement #8050–51000-105–01S

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Body-size dependence of resting energy expenditure can be attributed to nonenergetic homogeneity of fat-free mass

AJP Endocrinology and Metabolism ◽

10.1152/ajpendo.2002.282.1.e132 ◽

2002 ◽

Vol 282 (1) ◽

pp. E132-E138 ◽

Cited By ~ 140

Author(s):

Steven B. Heymsfield ◽

Dympna Gallagher ◽

Donald P. Kotler ◽

Zimian Wang ◽

David B. Allison ◽

...

Keyword(s):

Skeletal Muscle ◽

Adipose Tissue ◽

Energy Expenditure ◽

Metabolic Rate ◽

Body Mass ◽

Resting Energy Expenditure ◽

Fat Free Mass ◽

High Metabolic Rate ◽

Tissue Mass ◽

Residual Mass

An enduring enigma is why the ratio of resting energy expenditure (REE) to metabolically active tissue mass, expressed as the REE/fat-free mass (FFM) ratio, is greater in magnitude in subjects with a small FFM than it is in subjects with a large FFM. This study tested the hypothesis that a higher REE/FFM ratio in subjects with a small body mass and FFM can be explained by a larger proportion of FFM as high-metabolic-rate tissues compared with that observed in heavier subjects. REE was measured by indirect calorimetry, FFM by dual-energy X-ray absorptiometry (DEXA), and tissue/organ contributions to FFM by whole body magnetic resonance imaging (MRI) in healthy adults. Four tissue heat-producing contributions to FFM were evaluated, low-metabolic-rate fat-free adipose tissue (18.8 kJ/kg), skeletal muscle (54.4 kJ/kg), and bone (9.6 kJ/kg); and high-metabolic-rate residual mass (225.9 kJ/kg). Initial evaluations in 130 men and 159 women provided strong support for two key, developed models, one linking DEXA FFM with MRI FFM estimates and the other linking REE predicted from the four MRI-derived components with measured REE. There was an inverse association observed between measured REE/FFM and FFM ( r 2 = 0.17, P < 0.001). Allometric models revealed a similar pattern of tissue change relative to body mass across males and females with greater proportional increases in fat-free adipose tissue and skeletal muscle than in FFM and a smaller proportional increase in residual mass than in FFM. When examined as a function of FFM, positive slopes were observed for skeletal muscle/FFM and pooled low-metabolic-rate components, and a negative slope for residual mass. Our linked REE-body composition models and associations strongly support the hypothesis that FFM varies systematically in the proportion of thermogenic components as a function of body mass and FFM. These observations have important implications for the interpretation of between-individual differences in REE expressed relative to metabolically active tissue mass.

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Muscle mitochondrial morphology, body composition, and energy expenditure in sedentary individuals

AJP Endocrinology and Metabolism ◽

10.1152/ajpendo.1991.260.1.e89 ◽

1991 ◽

Vol 260 (1) ◽

pp. E89-E94 ◽

Cited By ~ 4

Author(s):

S. P. Kirkwood ◽

F. Zurlo ◽

K. Larson ◽

E. Ravussin

Keyword(s):

Energy Expenditure ◽

Metabolic Rate ◽

Body Fat ◽

Vastus Lateralis ◽

Oxidative Capacity ◽

Fat Free Mass ◽

Mitochondrial Morphology ◽

Thigh Circumference ◽

Wide Range

To investigate whether differences in metabolic rate are related to differences in muscle mitochondrial morphology and/or to differences in in vitro muscle respiration, we studied 17 healthy Caucasians, covering a wide range of body weight and composition [9 males, 8 females; body wt 96 +/- 37 (SD) kg; body fat = 28 +/- 10%]. Central and peripheral mitochondrial volume density (Vmit c and Vmit p, respectively) and the ratio of mitochondrial outer surface to volume of mitochondria (SVmit c in center and SVmit p at periphery) were determined by stereological analyses of transmission electron micrographs from samples of the vastus lateralis. There was no relationship between mitochondrial morphology or muscle respiration and 24-h energy expenditure, basal metabolic rate, or sleeping energy expenditure adjusted for differences in fat-free mass, fat mass, age, and sex. Although total body fat was not associated with muscle cell morphology, central distribution of body fat [waist-to-thigh circumference ratio (W/T)] correlated negatively with Vmit c (r = -0.58, P = 0.01), SVmit c (r = -0.59, P = 0.01), and SVmit p (r = -0.48, P = 0.05). W/T was also negatively related to muscle respiration (r = -0.59, P = 0.01). Despite the lack of relationship between metabolic rate and muscle mitochondrial morphology, central distribution of body fat is associated with lower mitochondrial density and larger mitochondria in skeletal muscle and is associated with a decreased oxidative capacity of muscle.

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Effect of an 18-wk weight-training program on energy expenditure and physical activity

Journal of Applied Physiology ◽

10.1152/jappl.1997.82.1.298 ◽

1997 ◽

Vol 82 (1) ◽

pp. 298-304 ◽

Cited By ~ 68

Author(s):

Ludo M. L. A. Van Etten ◽

Klaas R. Westerterp ◽

Frans T. J. Verstappen ◽

Bart J. B. Boon ◽

Wim H. M. Saris

Keyword(s):

Physical Activity ◽

Energy Expenditure ◽

Metabolic Rate ◽

Training Program ◽

Energy Cost ◽

Weight Training ◽

Exercise Group ◽

Fat Free Mass ◽

Control Group ◽

Doubly Labeled Water

Van Etten, Ludo M. L. A., Klaas R. Westerterp, Frans T. J. Verstappen, Bart J. B. Boon, and Wim H. M. Saris. Effect of an 18-wk weight-training program on energy expenditure and physical activity. J. Appl. Physiol. 82(1): 298–304, 1997.—The purpose of this study was to examine the effect of an 18-wk weight-training program on average daily metabolic rate (ADMR). Before the intervention and in weeks 8 and 18(T0, T8, and T18, respectively) data on body composition, sleeping metabolic rate (SMR), food intake, energy cost of the weight-training program (EEex), and nontraining physical activity (accelerometer) were collected in the exercise group (EXER, n = 18 males). ADMR was determined in a subgroup (EX12, n = 12) by using doubly labeled water. At T0 and T18, data (except ADMR) were also collected in a control group (Con, n = 8). Body mass did not change in EXER or Con. Fat-free mass increased only in EXER with 2.1 ± 1.2 kg, whereas fat mass decreased in EXER as well as Con (2.0 ± 1.8 and 1.4 ± 1.0 kg, respectively). Initial ADMR (12.4 ± 1.2 MJ/day) increased at T8 (13.5 ± 1.3 MJ/day, P < 0.001) with no further increase at T18 (13.5 ± 1.9 MJ/day). SMR did not change in EXER (4.8 ± 0.5, 4.9 ± 0.5, 4.8 ± 0.5 kJ/min) or Con (4.7 ± 0.4, 4.8 ± 0.4 kJ/min). Energy intake did not change in EXER (10.1 ± 1.8, 9.7 ± 1.8, 9.2 ± 1.9 MJ/day) or Con (10.2 ± 2.6, 9.4 ± 1.8, 10.1 ± 1.5 MJ/day) and was systematically underreported in EX12 (−21 ± 14, −28 ± 18, −34 ± 14%, P < 0.001). EEex (0.47 ± 0.20, 0.50 ± 0.18 MJ/day) could only explain 40% of the increase in ADMR. Nontraining physical activity did not change in both groups. In conclusion, although of modest energy cost, weight-training induces a significant increase in ADMR.

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