Activity and energy expenditure

1990 ◽  
Vol 68 (1) ◽  
pp. 17-27 ◽  
Author(s):  
M. J. Dauncey
Keyword(s):  
Energy Balance ◽  
Environmental Factors ◽  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Individual Variability ◽  
Energy Requirements ◽  
Resting Metabolism ◽  
The Subject ◽  
Activity Energy ◽  
Minor Activity

The influence of small changes in activity on energy expenditure and hence on energy requirements and energy balance is assessed. Evidence from direct and indirect calorimetry suggests that differences in spontaneous minor activity could readily alter 24-h energy expenditure by as much as 20%. This compares with values in the order of 10% for moderate overfeeding and somewhat less than this during mild cold exposure. Individual variability in 24-h energy expenditure can therefore be accounted for not only by differences in resting metabolism and the thermic responses to energy intake and temperature but also by differences in minor activity. Interactions between activity and environmental factors such as nutrition and temperature can modify the effect of activity on energy balance. Very little is known about mechanisms that could account for differences in spontaneous activity and these need to be the subject of future investigations.Key words: activity, energy balance, nutrition, temperature, thermogenesis.

scholarly journals Effect of raw and encapsulated policosanol on lipid profiles, blood biochemistry, activity, energy expenditure and macronutrient metabolism of adult cats

2021 ◽  
pp. 1098612X2110137
Author(s):  
James R Templeman ◽  
Kylie Hogan ◽  
Alexandra Blanchard ◽  
Christopher PF Marinangeli ◽  
Alexandra Camara ◽  
...  
Keyword(s):  
Body Weight ◽  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Respiratory Quotient ◽  
Blood Count ◽  
Complete Blood Count ◽  
Serum Biochemistry ◽  
Blood Collection ◽  
Adult Cats ◽  
Activity Energy

Objectives The objective of this study was to verify the safety of policosanol supplementation for domestic cats. The effects of raw and encapsulated policosanol were compared with positive (L-carnitine) and negative (no supplementation) controls on outcomes of complete blood count, serum biochemistry, energy expenditure, respiratory quotient and physical activity in healthy young adult cats. Methods The study was a replicated 4 × 4 complete Latin square design. Eight cats (four castrated males, four spayed females; mean age 3.0 ± 1.0 years; mean weight 4.36 ± 1.08 kg; mean body condition score 5.4 ± 1.4) were blocked by sex and body weight then randomized to treatment groups: raw policosanol (10 mg/kg body weight), encapsulated policosanol (50 mg/kg body weight), L-carnitine (200 mg/kg body weight) or no supplementation. Treatments were supplemented to a basal diet for 28 days with a 1-week washout between periods. Food was distributed equally between two offerings to ensure complete supplement consumption (first offering) and measure consumption time (second offering). Blood collection (lipid profile, complete blood count, serum biochemistry) and indirect calorimetry (energy expenditure, respiratory quotient) were conducted at days 0, 14 and 28 of each period. Activity monitors were worn 7 days prior to indirect calorimetry and blood collection. Data were analyzed using a repeated measures mixed model (SAS, v.9.4). Results Food intake and body weight were similar among treatments. There was no effect of treatment on lipid profile, serum biochemistry, activity, energy expenditure or respiratory quotient ( P >0.05); however, time to consume a second meal was greatest in cats fed raw policosanol ( P <0.05). Conclusions and relevance These data suggest that policosanol is safe for feline consumption. Further studies with cats demonstrating cardiometabolic risk factors are warranted to confirm whether policosanol therapy is an efficacious treatment for hyperlipidemia and obesity.

Determining energy expenditure in preterm infants: comparison of 2H(2)18O method and indirect calorimetry

1992 ◽  
Vol 263 (3) ◽  
pp. R685-R692 ◽  
Author(s):  
C. L. Jensen ◽  
N. F. Butte ◽  
W. W. Wong ◽  
J. K. Moon
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Preterm Infants ◽  
Indirect Calorimetry ◽  
Water Flux ◽  
High Ratio ◽  
Individual Variability ◽  
Study Time ◽  
Co2 Production ◽  
Turnover Rates

The doubly labeled water (2H(2)18O) method used to estimate total energy expenditure (EETotal) is particularly sensitive to analytic error in preterm infants, because of their high percentage of body water and the high ratio of water flux to CO2 production. To evaluate further use of this method, the EE of 12 preterm infants was measured by indirect calorimetry and 2H(2)18O simultaneously and continuously for 5 days. Initial infant weight, age, and postconceptional age were (means +/- SD) 1,674 +/- 173 g, 4.4 +/- 2.6 wk, and 34.6 +/- 1.6 wk, respectively. The indirect calorimeter system included an air-temperature-controlled chamber and heart rate monitor. EE was measured by indirect calorimetry for 85.6 +/- 4.7% of study time and estimated from the linear regression of heart rate on EE for 14.4 +/- 4.7% of study time. The 2H(2)18O method entailed an initial dose of 100 mg 2H2O and 250 mg 18O/kg and a final dose of 75 mg 18O/kg; urine was collected twice daily. 2H and 18O enrichments were measured by gas-isotope-ratio mass spectrometry. EE was calculated from measured 2H and 18O dilution spaces (NH, NO), turnover rates (kH, kO), and measured respiratory quotient. The ratio of 2H to 18O dilution spaces was 1.01 +/- 0.01 and the ratio of kO to kH was 1.16 +/- 0.04. Estimation of EE from 2H(2)18O and indirect calorimetry agreed within 1%, although individual variability in methods was large.

scholarly journals Energy balance dynamics during short-term high-intensity functional training

2019 ◽  
Vol 44 (2) ◽  
pp. 172-178 ◽  
Author(s):  
Matthew M. Schubert ◽  
Elyse A. Palumbo
Keyword(s):  
Body Composition ◽  
Energy Balance ◽  
Energy Expenditure ◽  
Energy Intake ◽  
High Intensity ◽  
Energy Deficit ◽  
Air Displacement Plethysmography ◽  
Functional Training ◽  
Before And After ◽  
Activity Energy

CrossFit (CF; CrossFit Inc., Washington, DC, USA) is a form of high-intensity functional training that focuses on training across the entire spectrum of physical fitness. CF has been shown to improve a number of indicators of health but little information assessing energy balance exists. The purpose of the present study was to investigate energy balance during 1 week of CF training. Men and women (n = 21; mean ± SD; age, 43.5 ± 8.4 years; body mass index, 27.8 ± 4.9 kg·m−2), with ≥3 months CF experience, had body composition assessed via air displacement plethysmography before and after 1 week of CF training. Participants wore ActiHeart monitors to assess total energy expenditure (TEE), activity energy expenditure, and CF energy expenditure (CF EE). Energy intake was assessed from TEE and Δ body composition. CF EE averaged 605 ± 219 kcal per 72 ± 10 min session. Weekly CF EE was 2723 ± 986 kcal. Participants were in an energy deficit (TEE: 3674 ± 855 kcal·day−1; energy intake: 3167 ± 1401 kcal·day−1). Results of the present study indicate that CF training can account for a significant portion of daily activity energy expenditure. The weekly expenditure is within levels shown to induce clinically meaningful weight loss in overweight/obese populations.

scholarly journals An evaluation of the IDEEA™ activity monitor for estimating energy expenditure

2012 ◽  
Vol 109 (1) ◽  
pp. 173-183 ◽  
Author(s):  
Stephen Whybrow ◽  
Patrick Ritz ◽  
Graham W. Horgan ◽  
R. James Stubbs
Keyword(s):  
Energy Balance ◽  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Activity Patterns ◽  
Activity Monitor ◽  
Whole Body ◽  
Similar Estimate ◽  
Free Living ◽  
Doubly Labelled Water ◽  
D 12

Objective estimates of activity patterns and energy expenditure (EE) are important for the measurement of energy balance. The Intelligent Device for Energy Expenditure and Activity (IDEEA) can estimate EE from the thirty-five postures and activities it can identify and record. The present study evaluated the IDEEA system's estimation of EE using whole-body indirect calorimetry over 24 h, and in free-living subjects using doubly-labelled water (DLW) over 14 d. EE was calculated from the IDEEA data using calibration values for RMR and EE while sitting and standing, both as estimated by the IDEEA system (IDEEAest) and measured by indirect calorimetry (IDEEAmeas). Subjects were seven females and seven males, mean age 38·1 and 39·7 years, mean BMI 25·2 and 26·2 kg/m2, respectively. The IDEEAest method produced a similar estimate of EE to the calorimeter (10·8 and 10·8 MJ, NS), while the IDEEAmeas method underestimated EE (9·9 MJ, P < 0·001). After removing data from static cycling, which the IDEEA was unable to identify as an activity, both the IDEEAest and IDEEAmeas methods overestimated EE compared to the calorimeter (9·9 MJ, P < 0·001; 9·1 MJ, P < 0·05 and 8·6 MJ, respectively). Similarly, the IDEEA system overestimated EE compared to DLW over 14 d; 12·7 MJ/d (P < 0·01), 11·5 MJ/d (P < 0·01) and 9·5 MJ/d for the IDEEAest, IDEEAmeas and DLW, respectively. The IDEEA system overestimated EE both in the controlled laboratory and free-living environments. Using measured EE values for RMR, sitting and standing reduced, but did not eliminate, the error in estimated EE.

scholarly journals Comparison of Conventional and Individualized 1-MET Values for Expressing Maximum Aerobic Metabolic Rate and Habitual Activity Related Energy Expenditure

Nutrients ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 458 ◽  
Author(s):  
Juliane Heydenreich ◽  
Yves Schutz ◽  
Katarina Melzer ◽  
Bengt Kayser
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Resting Metabolic Rate ◽  
Healthy Controls ◽  
Metabolic Capacity ◽  
Men And Women ◽  
Habitual Activity ◽  
The Individual ◽  
Activity Energy

The maximum aerobic metabolic rate can be expressed in multiple metabolically equivalent tasks (MET), i.e., METmax. The purpose was to quantify the error when the conventional (3.5 mL∙kg−1∙min−1) compared to an individualized 1-MET-value is used for calculating METmax and estimating activity energy expenditure (AEE) in endurance-trained athletes (END) and active healthy controls (CON). The resting metabolic rate (RMR, indirect calorimetry) and aerobic metabolic capacity (spiroergometry) were assessed in 52 END (46% male, 27.9 ± 5.7 years) and 53 CON (45% male, 27.3 ± 4.6 years). METmax was calculated as the ratio of VO2max over VO2 during RMR (METmax_ind), and VO2max over the conventional 1-MET-value (METmax_fix). AEE was estimated by multiplying published MET values with the individual and conventional 1-MET-values. Dependent t-tests were used to compare the different modes for calculating METmax and AEE (α = 0.05). In women and men CON, men END METmax_fix was significantly higher than METmax_ind (p < 0.01), whereas, in women END, no difference was found (p > 0.05). The conventional 1-MET-value significantly underestimated AEE in men and women CON, and men END (p < 0.05), but not in women END (p > 0.05). The conventional 1-MET-value appears inappropriate for determining the aerobic metabolic capacity and AEE in active and endurance-trained persons.

scholarly journals Activity Energy Expenditure in Youth: Sex, Age, and Body Size Patterns

2016 ◽  
Vol 13 (s1) ◽  
pp. S62-S70 ◽  
Author(s):  
Jung-Min Lee ◽  
Pedro F. Saint-Maurice ◽  
Youngwon Kim ◽  
Glenn A. Gaesser ◽  
Gregory Welk
Keyword(s):  
Physical Activity ◽  
Body Size ◽  
Energy Expenditure ◽  
Relative Intensity ◽  
Indirect Calorimetry ◽  
Physical Activities ◽  
Childhood And Adolescence ◽  
Energy Costs ◽  
Diverse Range ◽  
Activity Energy

Background:The assessment of physical activity (PA) and energy expenditure (EE) in youth is complicated by inherent variability in growth and maturation during childhood and adolescence. This study provides descriptive summaries of the EE of a diverse range of activities in children ages 7 to 13.Methods:A sample of 105 7- to 13-year-old children (boys: 57%, girls: 43%, and Age: 9.9 ± 1.9) performed a series of 12 activities from a pool of 24 activities while being monitored with an indirect calorimetry system.Results:Across physical activities, averages of VO2 ml·kg·min-1, VO2 L·min-1, EE, and METs ranged from 3.3 to 53.7 ml·kg·min-1, from 0.15 to 3.2 L·min-1, from 0.7 to 15.9 kcal·min-1, 1.5 MET to 7.8 MET, respectively.Conclusions:The energy costs of the activities varied by age, sex, and BMI status reinforcing the need to consider adjustments when examining the relative intensity of PA in youth.

scholarly journals Indirect calorimetry in laboratory mice and rats: principles, practical considerations, interpretation and perspectives

2012 ◽  
Vol 303 (5) ◽  
pp. R459-R476 ◽  
Author(s):  
Patrick C. Even ◽  
Nachiket A. Nadkarni
Keyword(s):  
Energy Balance ◽  
Food Intake ◽  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Very High Frequency ◽  
Metabolic Challenge ◽  
The Common ◽  
Free Feeding ◽  
Basal Energy Expenditure

In this article, we review some fundamentals of indirect calorimetry in mice and rats, and open the discussion on several debated aspects of the configuration and tuning of indirect calorimeters. On the particularly contested issue of adjustment of energy expenditure values for body size and body composition, we discuss several of the most used methods and their results when tested on a previously published set of data. We conclude that neither body weight (BW), exponents of BW, nor lean body mass (LBM) are sufficient. The best method involves fitting both LBM and fat mass (FM) as independent variables; for low sample sizes, the model LBM + 0.2 FM can be very effective. We also question the common calorimetry design that consists of measuring respiratory exchanges under free-feeding conditions in several cages simultaneously. This imposes large intervals between measures, and generally limits data analysis to mean 24 h or day-night values of energy expenditure. These are then generally compared with energy intake. However, we consider that, among other limitations, the measurements of V̇o2, V̇co2, and food intake are not precise enough to allow calculation of energy balance in the small 2–5% range that can induce significant long-term alterations of energy balance. In contrast, we suggest that it is necessary to work under conditions in which temperature is set at thermoneutrality, food intake totally controlled, activity precisely measured, and data acquisition performed at very high frequency to give access to the part of the respiratory exchanges that are due to activity. In these conditions, it is possible to quantify basal energy expenditure, energy expenditure associated with muscular work, and response to feeding or to any other metabolic challenge. This reveals defects in the control of energy metabolism that cannot be observed from measurements of total energy expenditure in free feeding individuals.

From individual variation in energy intakes...to variations in energy requirements and adaptations to them

1997 ◽  
Vol 78 (s2) ◽  
pp. S81-S94 ◽  
Author(s):  
Gail R. Goldberg
Keyword(s):  
Individual Differences ◽  
Energy Expenditure ◽  
Extreme Values ◽  
Individual Variability ◽  
Scientific Data ◽  
Energy Requirements ◽  
Daily Energy Expenditure ◽  
Daily Energy ◽  
Women And Children ◽  
The Individual

Dr Widdowson and Professor McCance always expressed a great deal of interest in the inter-individual variability in their scientific data considering that extreme values often provided the most revealing results. Their interest developed as a result of Dr Widdowson’s studies of the individual diets of men, women and children conducted in the 1930s; she later used the phrase ‘nutritional individuality’ to describe between-individual variability in intake and expenditure (Widdowson, 1962). This paper continues Dr Widdowson’s theme of individual variability. It focuses on recent data which describe between-individual differences in daily energy expenditure, particularly the extremes, and also on the insights these have given into the measurements of energy intake (EI).

Validation of the Kenz Lifecorder EX and ActiGraph GT1M accelerometers for walking and running in adults

2008 ◽  
Vol 33 (6) ◽  
pp. 1155-1164 ◽  
Author(s):  
Mark G. Abel ◽  
James C. Hannon ◽  
Katie Sell ◽  
Tia Lillie ◽  
Geri Conlin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Walking Speed ◽  
Treadmill Walking ◽  
Activity Monitors ◽  
Step Counts ◽  
Equation Analysis ◽  
Walking Speeds ◽  
Activity Energy

Accelerometer-based activity monitors are commonly used by researchers and clinicians to assess physical activity. Recently, the Kenz Lifecorder EX (KL) and ActiGraph GT1M (AG) accelerometers have been made commercially available, but there is limited research on the validity of these devices. Therefore, we sought to validate step count, activity energy expenditure (EE), and total EE output from the KL and AG during treadmill walking and running. Ten male and 10 female participants performed 10 min treadmill walking and running trials, at speeds of 54, 80, 107, 134, 161, and 188 m·min–1. Step counts were hand tallied by 2 observers, and indirect calorimetry was used to validate the accelerometers’ estimates of EE. AG total EE was calculated using the Freedson equation. Analysis of variance (ANOVA) and Pearson’s correlations were used to analyze the data. At the slowest walking speed, the AG and KL counted 64% ± 15% and 92% ± 6% of the observed steps, respectively. At all other treadmill speeds, both activity monitors undercounted, compared with observed steps, by ≤3%. The KL underestimated activity EE at faster running speeds (p < 0.01), overestimated total EE at some walking speeds, and underestimated total EE at some running speeds (p < 0.01). The Freedson equation inaccurately measured total EE at most walking and running speeds. The KL and the AG are moderately priced accelerometers that provide researchers and clinicians with accurate estimates of step counts and activity EE at most walking and running speeds.

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