Correlates of seasonal changes in metabolism in Atlantic harbour seals (Phoca vitulina concolor)

1998 ◽  
Vol 76 (8) ◽  
pp. 1520-1528 ◽  
Author(s):  
D A Rosen ◽  
D Renouf
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Total Energy ◽  
Energy Intake ◽  
Body Mass ◽  
Seasonal Changes ◽  
Energy Use ◽  
Phoca Vitulina ◽  
Harbour Seals ◽  
Gross Energy

This study tested the hypothesis that seasonal variation in resting metabolic rate (RMR) was more closely related to changes in total energy use than to energy intake. It also quantified the extent to which variation in metabolism contributed to changes in total energy expenditure. RMR, gross energy intake, and body mass and composition were measured in six captive Atlantic harbour seals (Phoca vitulina concolor) over 16 months. Gross energy intake during the year (across all seals) averaged 25.4 ± 4.1 MJ/d (mean ± SD). The energy used by the seals Eused a composite measure of energy expenditure from ingested energy and tissue catabolism) averaged 19.2 ± 3.4 MJ/d. RMR averaged 11.2 ± 1.5 MJ/d during the year, while mass-corrected metabolism declined with age. The seals displayed significant changes in both absolute and mass-corrected metabolism during the year. Overall, Eused was a stronger predictor of changes in metabolism than either gross energy intake or body mass. Mass-corrected metabolic rate was more closely related to Eused than was absolute metabolism. Energy changes in metabolism during the year (range = 6.9 ± 1.9 MJ/d) were minor compared with those in Eused (27.8 ± 7.3 MJ/d). These results suggest that seasonal changes in metabolism were a response to, or facilitated by, concurrent changes in Eused but were not the cause of variation in Eused. Rather, variation in both RMR and Eused was the result of changes in other bioenergetic components of the seals' energy budget, such as activity.

scholarly journals Physical activity and energy balance

1999 ◽  
Vol 2 (3a) ◽  
pp. 335-339 ◽  
Author(s):  
Marleen A. Van Baak
Keyword(s):  
Physical Activity ◽  
Energy Balance ◽  
Energy Expenditure ◽  
Total Energy ◽  
Energy Intake ◽  
Body Mass ◽  
Resting Energy Expenditure ◽  
Total Energy Expenditure ◽  
Activity Level ◽  
Resting Energy

AbstractEnergy expenditure rises above resting energy expenditure when physical activity is performed. The activity-induced energy expenditure varies with the muscle mass involved and the intensity at which the activity is performed: it ranges between 2 and 18 METs approximately. Differences in duration, frequency and intensity of physical activities may create considerable variations in total energy expenditure. The Physical Activity Level (= total energy expenditure divided by resting energy expenditure) varies between 1.2 and 2.2–2.5 in healthy adults. Increases in activity-induced energy expenditure have been shown to result in increases in total energy expenditure, which are usually greater than the increase in activity-induced energy expenditure itself. No evidence for increased spontaneous physical activity, measured by diary, interview or accelerometer, was found. However, this does not exclude increased physical activity that can not be measured by these methods. Part of the difference may also be explained by the post-exercise elevation of metabolic rate.If changes in the level of physical activity affect energy balance, this should result in changes in body mass or body composition. Modest decreases of body mass and fat mass are found in response to increases in physical activity, induced by exercise training, which are usually smaller than predicted from the increase in energy expenditure. This indicates that the training-induced increase in total energy expenditure is at least partly compensated for by an increase in energy intake. There is some evidence that the coupling between energy expenditure and energy intake is less at low levels of physical activity. Increasing the level of physical activity for weight loss may therefore be most effective in the most sedentary individuals.

Determination of total energy expenditure, resting metabolic rate and physical activity in lean and overweight people

1997 ◽  
Vol 36 (4) ◽  
pp. 310-312 ◽  
Author(s):  
F. Thielecke ◽  
J. Möseneder ◽  
A. Kroke ◽  
K. Klipstein-Grobusch ◽  
H. Boeing ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Total Energy ◽  
Resting Metabolic Rate ◽  
Total Energy Expenditure ◽  
Overweight People

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

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.

scholarly journals Validating accelerometry-derived proxies of energy expenditure using the doubly-labelled water method in the smallest penguin species

Biology Open ◽  
2021 ◽  
pp. bio.055475
Author(s):  
G. J. Sutton ◽  
J. A. Botha ◽  
J. R. Speakman ◽  
J. P. Y. Arnould
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Energy Use ◽  
Travel Speed ◽  
Specific Energy Expenditure ◽  
Doubly Labelled Water ◽  
Data Collection And Analysis ◽  
Behavioural Patterns ◽  
Free Ranging ◽  
The Relationship

Understanding energy use is central to understanding an animal's physiological and behavioural ecology. However, directly measuring energy expenditure in free-ranging animals is inherently difficult. The doubly-labelled water (DLW) method is widely used to investigate energy expenditure in a range of taxa. Although reliable, DLW data collection and analysis is both financially costly and time consuming. Dynamic body acceleration (e.g. VeDBA) calculated from animal-borne accelerometers has been used to determine behavioural patterns, and is increasingly being used as a proxy for energy expenditure. Still its performance as a proxy for energy expenditure in free-ranging animals is not well established and requires validation against established methods. In the present study, the relationship between VeDBA and the at-sea metabolic rate calculated from DLW was investigated in little penguins (Eudyptula minor) using three approaches. Both in a simple correlation and activity-specific approaches were shown to be good predictors of at-sea metabolic rate. The third approach using activity-specific energy expenditure values obtained from literature did not accurately calculate the energy expended by individuals. However, all three approaches were significantly strengthened by the addition of mean horizontal travel speed. These results provide validation for the use of accelerometry as a proxy for energy expenditure and show how energy expenditure may be influenced by both individual behaviour and environmental conditions.

scholarly journals Validation of energy intake by 24-hour multiple pass recall: comparison with total energy expenditure in children aged 5–7 years

2005 ◽  
Vol 93 (5) ◽  
pp. 671-676 ◽  
Author(s):  
Colette Montgomery ◽  
John J. Reilly ◽  
Diane M. Jackson ◽  
Louise A. Kelly ◽  
Christine Slater ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Total Energy ◽  
Energy Intake ◽  
School Children ◽  
Age Groups ◽  
Total Energy Expenditure ◽  
Doubly Labelled Water ◽  
Individual Level ◽  
Multiple Pass ◽  
The Individual

Accurate measurement of energy intake (EI) is essential in studies of energy balance in all age groups. Reported values for EI can be validated against total energy expenditure (TEE) measured using doubly labelled water (DLW). Our previous work has indicated that the use of the standardized 24 h multiple pass recall (24 h MPR) method produces slight overestimates of EI in pre-school children which are inaccurate at individual level but acceptable at group level. To extend this work, the current study validated EI by 24 h MPR against TEE by DLW in sixty-three (thirty-two boys) school-aged children (median age 6 years). In both boys and girls, reported EI was higher than TEE, although this difference was only significant in the girls (median difference 420 kJ/d, P=0·05). On analysis of agreement between TEE and EI, the group bias was an overestimation of EI by 250 kJ/d with wide limits of agreement (−2880, 2380 kJ/d). EI was over-reported relative to TEE by 7 % and 0·9 % in girls and boys, respectively. The bias in the current study was lower than in our previous study of pre-school children, suggesting that estimates of EI become less inaccurate as children age. However, the current study suggests that the 24 h MPR is inaccurate at the individual level.

Statistical Evaluation of Total Energy Intake Based on the Number of Food Portions and Body Weight

2021 ◽  
Vol 6 (2) ◽  
Author(s):  
Rousset S ◽  
◽  
Médard S ◽  
Fleury G ◽  
Fardet A ◽  
...  
Keyword(s):  
Body Weight ◽  
Energy Expenditure ◽  
Total Energy ◽  
Energy Intake ◽  
Test Sample ◽  
Normal Weight ◽  
Total Energy Intake ◽  
Validation Dataset ◽  
Linear Regression Models ◽  
The Mean

The evaluation of food intake based on various assessment methods is critical and underreporting is frequent. The aim of the study was to develop an indirect statistical method of the total energy intake estimation based on gender, weight and the number of portions. Energy intake prediction was developed and evaluated for validity using energy expenditure measurements given by the WellBeNet app. A total of 190 volunteers with various BMIs were recruited and assigned either in the train or the test sample. The mean energy provided by a portion was evaluated by linear regression models from the train sample. The absolute values of the error between the energy intake estimation and the energy expenditure measurement were calculated for each volunteer, by subgroup and for the whole group. The performance of the models was determined using the validation dataset. As the number of portions is the only variable used in the model, the error was 30.7% and 26.5% in the train and test sample. After adding body weight in the model, the error in absolute value decreased to 8.8% and 10.8% for the normal-weight women and men, and 11.7% and 12.8% for the overweight female and male volunteers, respectively. The findings of this study indicate that a statistical approach and knowledge of the usual number of portions and body weight is effective and sufficient to obtain a precise evaluation of energy intake (about 10% of error) after a simple and brief enquiry.

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