Collision activity during training increases total energy expenditure measured via doubly labelled water.
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ABSTRACT: Collision sports are characterised by frequent high-intensity collisions that induce substantial muscle damage, potentially increasing the energetic cost of recovery. Therefore, this study investigated the energetic cost of collision-based activity for the first time across any sport.Using a randomised crossover design, six professional young male rugby league players completed two different 5-day pre-season training microcycles. Players completed either a collision (COLL; 20 competitive one-on-one collisions) or non-collision (nCOLL; matched for kinematic demands, excluding collisions) training session on the first day of each microcycle, exactly 7 days apart. All remaining training sessions were matched and did not involve any collision-based activity. Total energy expenditure was measured using doubly labelled water, the literature gold standard.Collisions resulted in a very likely higher (4.96?±?0.97 MJ; ES?=?0.30?±?0.07; p?=?0.0021) total energy expenditure across the 5-day COLL training microcycle (95.07?±?16.66 MJ) compared with the nCOLL training microcycle (90.34?±?16.97 MJ). The COLL training session also resulted in a very likely higher (200?±?102 AU; ES?=?1.43?±?0.74; p?=?0.007) session rating of perceived exertion and a very likely greater (-?14.6?±?3.3%; ES?=?-?1.60?±?0.51; p?=?0.002) decrease in wellbeing 24 h later.A single collision training session considerably increased total energy expenditure. This may explain the large energy expenditures of collision-sport athletes, which appear to exceed kinematic training and match demands. These findings suggest fuelling professional collision-sport athletes appropriately for the "muscle damage caused" alongside the kinematic "work required".
<h4>Purpose</h4>Collision sports are characterised by frequent high-intensity collisions that induce substantial muscle damage, potentially increasing the energetic cost of recovery. Therefore, this study investigated the energetic cost of collision-based activity for the first time across any sport.<h4>Methods</h4>Using a randomised crossover design, six professional young male rugby league players completed two different 5-day pre-season training microcycles. Players completed either a collisi ...[more]
Project description:RationaleThe doubly labelled water (DLW) method is the reference method for the estimation of free-living total energy expenditure (TEE). In this method, where both 2 H and 18 O are employed, different approaches have been adopted to deal with the non-conformity observed regarding the distribution space for the labels being non-coincident with total body water. However, the method adopted can have a significant effect on the estimated TEE.MethodsWe proposed a Bayesian reasoning approach to modify an assumed prior distribution for the space ratio using experimental data to derive the TEE. A Bayesian hierarchical approach was also investigated. The dataset was obtained from 59 adults (37 women) who underwent a DLW experiment during which the 2 H and 18 O enrichments were measured using isotope ratio mass spectrometry (IRMS).ResultsTEE was estimated at 9925 (9106-11236) [median and interquartile range], 9646 (9167-10540), and 9,638 (9220-10340) kJ·day-1 for women and at 13961 (12851-15347), 13353 (12651-15088) and 13211 (12653-14238) kJ·day-1 for men, using normalized non-Bayesian, independent Bayesian and hierarchical Bayesian approaches, respectively. A comparison of hierarchical Bayesian with normalized non-Bayesian methods indicated a marked difference in behaviour between genders. The median difference was -287 kJ·day-1 for women, and -750 kJ·day-1 for men. In men there is an appreciable compression of the TEE distribution obtained from the hierarchical model compared with the normalized non-Bayesian methods (range of TEE 11234-15431 kJ·day-1 vs 10786-18221 kJ·day-1 ). An analogous, yet smaller, compression is seen in women (7081-12287 kJ·day-1 vs 6989-13775 kJ·day-1 ).ConclusionsThe Bayesian analysis is an appealing method to estimate TEE during DLW experiments. The principal advantages over those obtained using the classical least-squares method is the generation of potentially more useful estimates of TEE, and improved handling of outliers and missing data scenarios, particularly if a hierarchical model is used.
Project description:BACKGROUND:Increasing population lifespan necessitates a greater understanding of nutritional needs in older adults (65 year and over). A synthesis of total energy expenditure in the older population has not been undertaken and is needed to inform nutritional requirements. We aimed to establish the extent of the international evidence for total energy expenditure (TEE) using doubly-labelled water (DLW) in older adults (65 years and over), report challenges in obtaining primary data, and make recommendations for future data sharing. METHODS:Four databases were searched to identify eligible studies; original research of any study design where participant level TEE was measured using DLW in participants aged ?65 years. Once studies were identified for inclusion, authors were contacted where data were not publicly available. RESULTS:Screening was undertaken of 1223 records; the review of 317 full text papers excluded 170 records. Corresponding or first authors of 147 eligible studies were contacted electronically. Participant level data were publicly available or provided by authors for 45 publications (890 participants aged ?65 years, with 248 aged ?80 years). Sixty-seven percent of the DLW data in this population were unavailable due to authors unable to be contacted or declining to participate, or data being irretrievable. CONCLUSIONS:The lack of data access limits the value of the original research and its contribution to nutrition science. Openly accessible DLW data available through publications or a new international data repository would facilitate greater integration of current research with previous findings and ensure evidence is available to support the needs of the ageing population. TRIAL REGISTRATION:The protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO), registration number CRD42016047549 .
Project description:BackgroundContemporary energy expenditure data are crucial to inform and guide nutrition policy in older adults to optimize nutrition and health.ObjectiveThe aim was to determine the optimal method of estimating total energy expenditure (TEE) in adults (aged ?65 y) through 1) establishing which published predictive equations have the closest agreement between measured resting metabolic rate (RMR) and predicted RMR and 2) utilizing the RMR equations with the best agreement to predict TEE against the reference method of doubly labeled water (DLW).MethodsA database consisting of international participant-level TEE data from DLW studies was developed to enable comparison with energy requirements estimated by 17 commonly used predictive equations. This database included 31 studies comprising 988 participant-level RMR data and 1488 participant-level TEE data. Mean physical activity level (PAL) was determined for men (PAL = 1.69, n = 320) and women (PAL = 1.66, n = 668). Bland-Altman plots assessed agreement of measured RMR and TEE with predicted RMR and TEE in adults aged ?65 y, and subgroups of 65-79 y and ?80 y. Linear regression assessed proportional bias.ResultsThe Ikeda, Livingston, and Mifflin equations most closely agreed with measured RMR and TEE in all adults aged ?65 y and in the 65-79 y and ?80 y subgroups. In adults aged ?65 y, the Ikeda and Livingston equations overestimated TEE by a mean ± SD of 175 ± 1362 kJ/d and 86 ± 1344 kJ/d, respectively. The Mifflin equation underestimated TEE by a mean ± SD of 24 ± 1401 kJ/d. Proportional bias was present as energy expenditure increased.ConclusionsThe Ikeda, Livingston, or Mifflin equations are recommended for estimating energy requirements of older adults. Future research should focus on developing predictive equations to meet the requirements of the older population with consideration given to body composition and functional measures.
Project description:BackgroundAccurate assessment of energy expenditure (EE) is important for the study of energy balance and metabolic disorders. Combined heart rate (HR) and acceleration (ACC) sensing may increase precision of physical activity EE (PAEE) which is the most variable component of total EE (TEE).ObjectiveTo evaluate estimates of EE using ACC and HR data with or without individual calibration against doubly-labelled water (DLW) estimates of EE.Design23 women and 23 men (22-55 yrs, 48-104 kg, 8-46%body fat) underwent 45-min resting EE (REE) measurement and completed a 20-min treadmill test, an 8-min step test, and a 3-min walk test for individual calibration. ACC and HR were monitored and TEE measured over 14 days using DLW. Diet-induced thermogenesis (DIT) was calculated from food-frequency questionnaire. PAEE (TEE ÷ REE ÷ DIT) and TEE were compared to estimates from ACC and HR using bias, root mean square error (RMSE), and correlation statistics.ResultsMean(SD) measured PAEE and TEE were 66(25) kJ·day(-1)·kg(-1), and 12(2.6) MJ·day(-1), respectively. Estimated PAEE from ACC was 54(15) kJ·day(-1)·kg(-1) (p<0.001), with RMSE 24 kJ·day(-1)·kg(-1) and correlation r = 0.52. PAEE estimated from HR and ACC+HR with treadmill calibration were 67(42) and 69(25) kJ·day(-1)·kg(-1) (bias non-significant), with RMSE 34 and 20 kJ·day(-1)·kg(-1) and correlations r = 0.58 and r = 0.67, respectively. Similar results were obtained with step-calibrated and walk-calibrated models, whereas non-calibrated models were less precise (RMSE: 37 and 24 kJ·day(-1)·kg(-1), r = 0.40 and r = 0.55). TEE models also had high validity, with biases <5%, and correlations r = 0.71 (ACC), r = 0.66-0.76 (HR), and r = 0.76-0.83 (ACC+HR).ConclusionsBoth accelerometry and heart rate may be used to estimate EE in adult European men and women, with improved precision if combined and if heart rate is individually calibrated.
Project description:BackgroundMany large studies have implemented wrist or thigh accelerometry to capture physical activity, but the accuracy of these measurements to infer activity energy expenditure (AEE) and consequently total energy expenditure (TEE) has not been demonstrated. The purpose of this study was to assess the validity of acceleration intensity at wrist and thigh sites as estimates of AEE and TEE under free-living conditions using a gold-standard criterion.MethodsMeasurements for 193 UK adults (105 men, 88 women, aged 40-66 years, BMI 20.4-36.6 kg m-2) were collected with triaxial accelerometers worn on the dominant wrist, non-dominant wrist and thigh in free-living conditions for 9-14 days. In a subsample (50 men, 50 women) TEE was simultaneously assessed with doubly labelled water (DLW). AEE was estimated from non-dominant wrist using an established estimation model, and novel models were derived for dominant wrist and thigh in the non-DLW subsample. Agreement with both AEE and TEE from DLW was evaluated by mean bias, root mean squared error (RMSE), and Pearson correlation.ResultsMean TEE and AEE derived from DLW were 11.6 (2.3) MJ day-1 and 49.8 (16.3) kJ day-1 kg-1. Dominant and non-dominant wrist acceleration were highly correlated in free-living (r = 0.93), but less so with thigh (r = 0.73 and 0.66, respectively). Estimates of AEE were 48.6 (11.8) kJ day-1 kg-1 from dominant wrist, 48.6 (12.3) from non-dominant wrist, and 46.0 (10.1) from thigh; these agreed strongly with AEE (RMSE ~12.2 kJ day-1 kg-1, r ~ 0.71) with small mean biases at the population level (~6%). Only the thigh estimate was statistically significantly different from the criterion. When combining these AEE estimates with estimated REE, agreement was stronger with the criterion (RMSE ~1.0 MJ day-1, r ~ 0.90).ConclusionsIn UK adults, acceleration measured at either wrist or thigh can be used to estimate population levels of AEE and TEE in free-living conditions with high precision.
Project description: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.
Project description:The aim of this pilot study was to assess body composition and total energy expenditure (TEE) in 35 obese 7-9 years old Kuwaiti children (18 girls and 17 boys). Total body water (TBW) and TEE were assessed by doubly-labeled water technique. TBW was derived from the intercept of the elimination rate of deuterium and TEE from the difference in elimination rates of 18O and deuterium. TBW was used to estimate fat-free mass (FFM), using hydration factors for different ages and gender. Fat mass (FM) was calculated as the difference between body weight and FFM. Body weight was not statistically different but TBW was significantly higher (p = 0.018) in boys (44.9% ± 3.3%) than girls (42.4% ± 3.0%), while girls had significantly higher estimated FM (45.2 ± 3.9 weight % versus 41.6% ± 4.3%; p = 0.014). TEE was significantly higher in boys (2395 ± 349 kcal/day) compared with girls (1978 ± 169 kcal/day); p = 0.001. Estimated physical activity level (PAL) was significantly higher in boys; 1.61 ± 0.167 versus 1.51 ± 0.870; p = 0.034. Our results provide the first dataset of TEE in 7-9 years old obese Kuwaiti children and highlight important gender differences to be considered during the development of school based interventions targeted to combat childhood obesity.
Project description:IntroductionWrist-mounted motion sensors can quantify the volume and intensity of physical activities, but little is known about their long-term validity. Our aim was to validate a wrist motion sensor in estimating daily energy expenditure, including any change induced by long-term participation in endurance and strength training. Supplemental heart rate monitoring during weekly exercise was also investigated.MethodsA 13-day doubly labeled water (DLW) measurement of total energy expenditure (TEE) was performed twice in healthy male subjects: during two last weeks of a 12-week Control period (n = 15) and during two last weeks of a 12-week combined strength and aerobic Training period (n = 13). Resting energy expenditure was estimated using two equations: one with body weight and age, and another one with fat-free mass. TEE and activity induced energy expenditure (AEE) were determined from motion sensor alone, and from motions sensor combined with heart rate monitor, the latter being worn during exercise only.ResultsWhen body weight and age were used in the calculation of resting energy expenditure, the motion sensor data alone explained 78% and 62% of the variation in TEE assessed by DLW at the end of Control and Training periods, respectively, with a bias of +1.75 (p <.001) and +1.19 MJ/day (p = .002). When exercise heart rate data was added to the model, the combined wearable device approach explained 85% and 70% of the variation in TEE assessed by DLW with a bias of +1.89 and +1.75 MJ/day (p <.001 for both). While significant increases in TEE and AEE were detected by all methods as a result of participation in regular training, motion sensor approach underestimated the change measured by DLW: +1.13±0.66 by DLW, +0.59±0.69 (p = .004) by motion sensor, and +0.98±0.70 MJ/day by combination of motion sensor and heart rate. Use of fat-free mass in the estimation of resting energy expenditure removed the biases between the wearable device estimations and the golden standard reference method of TEE and demonstrated a training-induced increase in resting energy expenditure by +0.18±0.13 MJ/day (p <.001).ConclusionsWrist motion sensor combined with a heart rate monitor during exercise sessions, showed high agreement with the golden standard measurement of daily TEE and its change induced by participation in a long-term training protocol. The positive findings concerning the validity, especially the ability to follow-up the change associated with a lifestyle modification, can be considered significant because they partially determine the feasibility of wearable devices as quantifiers of health-related behavior.
Project description:BackgroundThe accuracy of dietary energy assessment tools is critical to understanding the role of diet in the increasing rate of obesity.ObjectivesThe purposes of our study in overweight adolescent boys and girls were 1) to assess the energy reporting bias of diet records against the referent of total energy expenditure (TEE) and 2) to compare the methods of determining energy needs by using measured metabolizable energy intake (MEI) and TEE.DesignTwenty girls [12-15 y, body mass index (in kg/m2) = 33.0 +/- 5] and 14 boys (12-14 y, body mass index = 27.4 +/- 4) participated in 2- to 3-wk metabolic balance studies. TEE was measured by using doubly labeled water (TEE(DLW)), and MEI was measured by bomb calorimetry of composite daily diet, urine, and fecal collections. Food records were collected before each study.ResultsFood records underreported TEE(DLW) by 35 +/- 20%. Underreporting of energy intake was correlated with all macronutrient intake concentrations (g or kcal) (P < 0.0001). A multiple regression model showed that 86.4% of the variance in underreporting error was explained by dietary fat (g), BMI, and sex. The intrasubject CV was 3.9% for TEE(DLW) and 9.9% for MEI. MEI for weight stability (MEI(wtstb)) averaged 99 +/- 11% of TEE.ConclusionsThe increased underreporting of dietary intake with increasing body weight in teens may explain in part previous reports noting that there has been an increased incidence of obesity, although energy intakes have not appeared to increase. MEI(wtstb) and TEE(DLW) gave similar estimates of energy needs. This trial was registered at clinicaltrials.gov as NCT 00592137.
Project description:BACKGROUND:Low-carbohydrate diets have been reported to significantly increase human energy expenditure when measured using doubly labeled water (DLW) but not by respiratory chambers. Although DLW may reveal true physiological differences undetected by respiratory chambers, an alternative possibility is that the expenditure differences resulted from failure to correctly estimate the respiratory quotient (RQ) used in the DLW calculations. OBJECTIVE:To examine energy expenditure differences between isocaloric diets varying widely in carbohydrate and to quantitatively compare DLW data with respiratory chamber and body composition measurements within an energy balance framework. DESIGN:DLW measurements were obtained during the final 2 wk of month-long baseline (BD; 50% carbohydrate, 35% fat, 15% protein) and isocaloric ketogenic diets (KD; 5% carbohydrate, 80% fat, 15% protein) in 17 men with a BMI of 25-35 kg/m2. Subjects resided 2 d/wk in respiratory chambers to measure energy expenditure (EEchamber). DLW expenditure was calculated using chamber-determined RQ either unadjusted (EEDLW) or adjusted (EEDLW?RQ) for net energy imbalance using diet-specific coefficients. Accelerometers measured physical activity. Body composition changes were measured by dual-energy X-ray absorptiometry (DXA) which were combined with energy intake measurements to calculate energy expenditure by balance (EEbal). RESULTS:After transitioning from BD to KD, neither EEchamber nor EEbal were significantly changed (?EEchamber = 24 ± 30 kcal/d; P = 0.43 and ?EEbal = -141 ± 118 kcal/d; P = 0.25). Similarly, physical activity (-5.1 ± 4.8%; P = 0.3) and exercise efficiency (-1.6 ± 2.4%; P = 0.52) were not significantly changed. However, EEDLW was 209 ± 83 kcal/d higher during the KD (P = 0.023) but was not significantly increased when adjusted for energy balance (EEDLW?RQ = 139 ± 89 kcal/d; P = 0.14). After removing 2 outliers whose EEDLW were incompatible with other data, EEDLW was marginally increased during the KD by 126 ± 62 kcal/d (P = 0.063) and EEDLW?RQ was only 46 ± 65 kcal/d higher (P = 0.49). CONCLUSIONS:DLW calculations failing to account for diet-specific energy imbalance effects on RQ erroneously suggest that low-carbohydrate diets substantially increase energy expenditure. This trial was registered at clinicaltrials.gov as NCT01967563.
