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In mammals, trait variation is often reported to be greater among males than females. However, to date, mainly only morphological traits have been studied. Energy expenditure represents the metabolic costs of multiple physical, physiological, and behavioral traits. Energy expenditure could exhibit particularly high greater male variation through a cumulative effect if those traits mostly exhibit greater male variation, or a lack of greater male variation if many of them do not. Sex differences in energy expenditure variation have been little explored. We analyzed a large database on energy expenditure in adult humans (1494 males and 3108 females) to investigate whether humans have evolved sex differences in the degree of interindividual variation in energy expenditure. We found that, even when statistically comparing males and females of the same age, height, and body composition, there is much more variation in total, activity, and basal energy expenditure among males. However, with aging, variation in total energy expenditure decreases, and because this happens more rapidly in males, the magnitude of greater male variation, though still large, is attenuated in older age groups. Considerably greater male variation in both total and activity energy expenditure could be explained by greater male variation in levels of daily activity. The considerably greater male variation in basal energy expenditure is remarkable and may be explained, at least in part, by greater male variation in the size of energy-demanding organs. If energy expenditure is a trait that is of indirect interest to females when choosing a sexual partner, this would suggest that energy expenditure is under sexual selection. However, we present a novel energetics model demonstrating that it is also possible that females have been under stabilizing selection pressure for an intermediate basal energy expenditure to maximize energy available for reproduction., Competing Interests: Conflicts of interest The authors have no conflicts of interest to declare., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Low total energy expenditure (TEE, MJ/d) has been a hypothesized risk factor for weight gain, but repeatability of TEE, a critical variable in longitudinal studies of energy balance, is understudied. We examine repeated doubly labeled water (DLW) measurements of TEE in 348 adults and 47 children from the IAEA DLW Database (mean ± SD time interval: 1.9 ± 2.9 y) to assess repeatability of TEE, and to examine if TEE adjusted for age, sex, fat-free mass, and fat mass is associated with changes in weight or body composition. Here, we report that repeatability of TEE is high for adults, but not children. Bivariate Bayesian mixed models show no among or within-individual correlation between body composition (fat mass or percentage) and unadjusted TEE in adults. For adults aged 20-60 y (N = 267; time interval: 7.4 ± 12.2 weeks), increases in adjusted TEE are associated with weight gain but not with changes in body composition; results are similar for subjects with intervals >4 weeks (N = 53; 29.1 ± 12.8 weeks). This suggests low TEE is not a risk factor for, and high TEE is not protective against, weight or body fat gain over the time intervals tested., (© 2022. The Author(s).)

Total daily energy expenditure ("total expenditure") reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass-adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

The doubly labeled water (DLW) method measures total energy expenditure (TEE) in free-living subjects. Several equations are used to convert isotopic data into TEE. Using the International Atomic Energy Agency (IAEA) DLW database (5,756 measurements of adults and children), we show considerable variability is introduced by different equations. The estimated rCO 2 is sensitive to the dilution space ratio (DSR) of the two isotopes. Based on performance in validation studies, we propose a new equation based on a new estimate of the mean DSR. The DSR is lower at low body masses (<10 kg). Using data for 1,021 babies and infants, we show that the DSR varies non-linearly with body mass between 0 and 10 kg. Using this relationship to predict DSR from weight provides an equation for rCO 2 over this size range that agrees well with indirect calorimetry (average difference 0.64%; SD = 12.2%). We propose adoption of these equations in future studies., Competing Interests: The authors declare no competing interests., (© 2021 The Authors.)

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.

To quantify day-to-day variability in energy expenditure (EE) during weight-training, 10 male subjects completed 6 training sessions that consisted of a warming-up and cooling-down phase (10 min; arm cranking or cycling) and a computer-paced weight-training phase using standard weights (42 min; 10 exercises, 3 x 15 repetitions, work to rest ratio = 1:1). The first 2 sessions were used to accommodate. During sessions 3-6 (labelled session A, B, C and D) cardiorespiratory response was continuously measured. Gas-exchange was converted to EE using the Weir formula. In the last two sessions training weights were raised by +/- 50% and the initial warming-up and cooling-down exercise being arm-cranking was replaced by cycling. Mean EE was calculated for last five minutes of the warming-up (WU5) and cooling-down (CD5) and the complete weight-training phase (WT). Mean EE during WT for session A to D was 20.0 +/- 2.7, 19.1 +/- 2.5, 22.2 +/- 2.2 and 21.9 +/- 2.4 kj.min-1, respectively. Daily variation was tested by comparing test-retest phases (A vs B and C vs D). Intra-individual variability in EE during respectively the lower (session A vs B) and higher (session C vs D) weight-training intensity was expressed as: absolute test-retest difference (0.9 +/- 0.5 and 0.7 +/- 0.6 kj.min-1), difference relative to the mean of the test-retest measurements (2.3 +/- 1.4 and 1.6 +/- 1.4%) and as the mean coefficient of variation (3.3 and 2.2%). There were no differences in variability between both WT-intensities nor exercise modes, irrespective of the way variability was expressed. In conclusion, intra-individual variability in EE during weight-training does not differ from variability during arm cranking or cycling.

This study was performed to investigate the effect of weight-training (12 wk; 21 male subjects) on energy expenditure and substrate utilization during sleep. Sleeping metabolic rate (SMR) as measured in a respiration chamber was calculated according to three procedures: the lowest mean energy expenditure of a shiftable 3-h interval between 0:00 and 6:00 (SMR3) and SMR over predetermined intervals from 3:00 to 6:00 (SMR3-6) and from 0:00 to 6:00 (SMR0-6). In analogy with SMR the corresponding respiratory quotients were expressed as RQ3, RQ3-6, and RQ0-6. Changes in body composition were assessed from changes in body weight, body volume (densitometry), and total body water (deuterium dilution). Weight-training induced an increase in fat-free mass (+1.1 +/- 1.3 kg; P < 0.001) and a decrease in fat mass (-2.3 +/- 1.5 kg; P < 0.001) and body weight (-1.1 +/- 2.1 kg; P < 0.05). There was no significant change in SMR, irrespective of the way SMR was expressed. Only RQ3 decreased significantly (from 0.82 +/- 0.04 to 0.79 +/- 0.02; P < 0.05). Remarkably RQ3, RQ3-6, and RQ0-6 were highly negative correlated with the pre-training RQ (r = -0.93, -0.91, and -0.90, respectively: P < 0.001) resulting in a diminished variation in post-training RQ (P < 0.001). These results suggest that weight-training has no effect on SMR but increases relative fat utilization in low fat oxidizers and vice versa for individuals displaying high pre-training lipid oxidation.