Inhibitory control mediates the effect of high intensity interval exercise on food choice.

Exercise is associated with changes in food consumption and cognitive function. The aim of this study was to examine the immediate effects of acute exercise on appetite, food choices, and cognitive processes, and the mediating role of cognitive functioning, namely inhibitory control, working memory, cognitive flexibility and decision making. We compared the effects of high-intensity interval exercise (HIIE) to a resting condition on appetite and food choices, using visual analogue rating scales and a computerised portion selection task. Mediation analysis was performed with exercise/rest condition as a predictor variable and cognitive measures were entered as mediating variables and food choice measures as outcomes. Young women with low activity levels, aged between 18-35 years with a body mass index (BMI) between 18-25 kg/m2, were recruited. Participants (n=30) demonstrated improved performance on a Stroop task following HIIE compared to the rest session, indicating enhanced attentional inhibition. Accuracy on an N-back task was significantly higher after HIIE, indicating an improvement in working memory and response times on the N-back task were shorter after HIIE, suggesting increased processing speed. Delay discounting for food (but not money) was reduced after HIEE but there were no significant on go/no-go task performance. On the trail-making task (a measure of cognitive flexibility), the time difference between trail B and A was significantly lower after HIIE, compared to rest. HIIE reduced rated enjoyment and ideal portion size selection for high energy dense foods. The relationship between exercise and food choices was mediated by inhibition as assessed by the Stoop task. These results suggest that HIIE leads to cognitive benefits and a reduced preference for high-calorie foods and that an enhancement of attentional inhibition may underlie this relationship.

Accuracy of the Apple Watch Series 4 and Fitbit Versa for Assessing Energy Expenditure and Heart Rate of Wheelchair Users During Treadmill Wheelchair Propulsion: Cross-sectional Study.

BACKGROUND: The Apple Watch (AW) Series 1 provides energy expenditure (EE) for wheelchair users but was found to be inaccurate with an error of approximately 30%, and the corresponding error for heart rate (HR) provided by the Fitbit Charge 2 was approximately 10% to 20%. Improved accuracy of estimated EE and HR is expected with newer editions of these smart watches (SWs). OBJECTIVE: This study aims to assess the accuracy of the AW Series 4 (wheelchair-specific setting) and the Fitbit Versa (treadmill running mode) for estimating EE and HR during wheelchair propulsion at different intensities. METHODS: Data from 20 manual wheelchair users (male: n=11, female: n=9; body mass: mean 75, SD 19 kg) and 20 people without a disability (male: n=11, female: n=9; body mass: mean 75, SD 11 kg) were included. Three 4-minute wheelchair propulsion stages at increasing speed were performed on 3 separate test days (0.5%, 2.5%, or 5% incline), while EE and HR were collected by criterion devices and the AW or Fitbit. The mean absolute percentage error (MAPE) was used to indicate the absolute agreement between the criterion device and SWs for EE and HR. Additionally, linear mixed model analyses assessed the effect of exercise intensity, sex, and group on the SW error. Interclass correlation coefficients were used to assess relative agreement between criterion devices and SWs. RESULTS: The AW underestimated EE with MAPEs of 29.2% (SD 22%) in wheelchair users and 30% (SD 12%) in people without a disability. The Fitbit overestimated EE with MAPEs of 73.9% (SD 7%) in wheelchair users and 44.7% (SD 38%) in people without a disability. Both SWs underestimated HR. The device error for EE and HR increased with intensity for both SWs (all comparisons: P<.001), and the only significant difference between groups was found for HR in the AW (-5.27 beats/min for wheelchair users; P=.02). There was a significant effect of sex on the estimation error in EE, with worse accuracy for the AW (-0.69 kcal/min; P<.001) and better accuracy for the Fitbit (-2.08 kcal/min; P<.001) in female participants. For HR, sex differences were found only for the AW, with a smaller error in female participants (5.23 beats/min; P=.02). Interclass correlation coefficients showed poor to moderate relative agreement for both SWs apart from 2 stage-incline combinations (AW: 0.12-0.57 for EE and 0.11-0.86 for HR; Fitbit: 0.06-0.85 for EE and 0.03-0.29 for HR). CONCLUSIONS: Neither the AW nor Fitbit were sufficiently accurate for estimating EE or HR during wheelchair propulsion. The AW underestimated EE and the Fitbit overestimated EE, and both SWs underestimated HR. Caution is hence required when using SWs as a tool for training intensity regulation and energy balance or imbalance in wheelchair users.

Energy expenditure and dietary intake in professional female football players in the Dutch Women's League: Implications for nutritional counselling.

In contrast to male football players, research on the nutritional requirements of female football players is limited. This study aimed to assess total daily energy expenditure (TDEE) in professional female football players, along with body composition, physical activity and dietary intake. This observational study included 15 professional football players playing in the highest Dutch Women's League. TDEE was assessed by doubly labelled water over 14 days, along with resting metabolic rate (RMR; ventilated hood), fat-free mass (FFM; dual-energy x-ray absorptiometry), and dietary intake (24-h recalls). Physical activity energy expenditure (PAEE) was derived from subtracting RMR and estimated diet-induced thermogenesis (10%) from TDEE. TDEE was 2882 ± 278 kcal/day (58 ± 5 kcal/kg FFM) and significantly (p < 0.05) correlated with FFM (r = 0.62). PAEE was 1207 ± 213 kcal/d. Weighted energy intake was 2344 kcal [2023-2589]. Carbohydrate intakes were 3.2 ± 0.7, 4.4 ± 1.1 and 5.3 ± 1.9 g/kg body mass for rest, training and match days, respectively, while weighted mean protein intake was 1.9 ± 0.4 g/kg body mass. In conclusion, the energy requirements of professional female football players are moderate to high and can be explained by the substantial PAEE. To fuel these requirements, sports nutritionists should consider shifting the players' focus towards prioritizing adequate carbohydrate intakes, rather than emphasizing high protein consumption.

Differences in running technique between runners with better and poorer running economy and lower and higher milage: An artificial neural network approach.

BACKGROUND: Prior studies investigated selected discrete sagittal-plane outcomes (e.g., peak knee flexion) in relation to running economy, hereby discarding the potential relevance of running technique parameters during noninvestigated phases of the gait cycle and in other movement planes. PURPOSE: Investigate which components of running technique distinguish groups of runners with better and poorer economy and higher and lower weekly running distance using an artificial neural network (ANN) approach with layer-wise relevance propagation. METHODS: Forty-one participants (22 males and 19 females) ran at 2.78 m∙s-1 while three-dimensional kinematics and gas exchange data were collected. Two groups were created that differed in running economy or weekly training distance. The three-dimensional kinematic data were used as input to an ANN to predict group allocations. Layer-wise relevance propagation was used to determine the relevance of three-dimensional kinematics for group classification. RESULTS: The ANN classified runners in the correct economy or distance group with accuracies of up to 62% and 71%, respectively. Knee, hip, and ankle flexion were most relevant to both classifications. Runners with poorer running economy showed higher knee flexion during swing, more hip flexion during early stance, and more ankle extension after toe-off. Runners with higher running distance showed less trunk rotation during swing. CONCLUSION: The ANN accuracy was moderate when predicting whether runners had better, or poorer running economy, or had a higher or lower weekly training distance based on their running technique. The kinematic components that contributed the most to the classification may nevertheless inform future research and training.

Energy Requirements of Paralympic Athletes: Insights from the Doubly Labeled Water Approach.

PURPOSE: Advanced insight in energy requirements of Paralympic athletes is imperative for optimizing their nutritional counseling. Given the lack of accurate data on total daily energy expenditure (TDEE) of Paralympic athletes, this study aimed to assess energy expenditure and nutritional intake of a large cohort of Paralympic athletes, across different sports and disabilities. METHODS: In this cross-sectional study, 48 Dutch and Norwegian Paralympic athletes (19 male/29 female) with various disabilities, competing in Para cycling, wheelchair tennis, wheelchair basketball, Para Nordic skiing, and alpine skiing participated. TDEE was assessed by the gold standard doubly labeled water method over a 14-d period, resting metabolic rate by ventilated hood indirect calorimetry, energy intake by three unannounced 24-h dietary recalls, body composition by dual-energy x-ray absorptiometry, and exercise training duration by a training log. RESULTS: Mean TDEE was 2908 ± 797 kcal·d -1 , ranging from 2322 ± 340 kcal·d -1 for wheelchair basketball players to 3607 ± 1001 kcal·d -1 for Para cyclists. Regression analysis identified fat-free mass, exercise duration, and the presence of a spinal cord disorder as the primary predictors of TDEE, explaining up to 73% of the variance in TDEE. Athletes' energy intake (2363 ± 905 kcal·d -1 ) was below their TDEE, whereas their body mass remained constant, indicating underreporting. Carbohydrate intake (4.1 ± 1.9 g·kg -1 body mass) was low, even when considering underreporting, whereas protein intake (1.8 ± 0.6 g·kg -1 body mass) was relatively high. CONCLUSIONS: Paralympic athletes display moderate- to high-energy expenditure, varying across sports and individuals. Much of the variation in TDEE can be attributed to individual differences in fat-free mass and exercise duration. This study establishes the benchmarks for energy requirements of Paralympic athletes, serving as the foundation for future dietary guidelines within this population.

The Effect of Wearable-Based Real-Time Feedback on Running Injuries and Running Performance: A Randomized Controlled Trial.

BACKGROUND: Running technique and running speed are considered important risk factors for running injuries. Real-time feedback on running technique and running speed by wearables may help reduce injury risk. PURPOSE: To investigate whether real-time feedback on spatiotemporal metrics and relative speed by commercially available pressure-sensitive insoles would reduce running injuries and improve running performance compared with no real-time feedback. STUDY DESIGN: Randomized controlled trial; Level of evidence, 1. METHODS: A total of 220 recreational runners were randomly assigned into the intervention and control groups. Both groups received pressure-sensitive insoles, but only the intervention group received real-time feedback on spatiotemporal metrics and relative speed. The feedback aimed to reduce loading on the joint/segment estimated to exhibit the highest load. Injury rates were compared between the groups using Cox regressions. Secondary outcomes compared included injury severity, the proportion of runners with multiple injuries, changes in self-reported personal best times and motivation (Behavioral Regulation in Exercise Questionnaire-2), and interest in continuing wearable use after study completion. RESULTS: A total of 160 participants (73%) were included in analyses of the primary outcome. Intention-to-treat analysis showed no significant difference in injury rate between the groups (Hazard ratio [HR], 1.11; P = .70). This was expected, as 53 of 160 (33%) participants ended up in the unassigned group because they used incorrect wearable settings, nullifying any interventional effects. As-treated analysis showed a significantly lower injury rate among participants receiving real-time feedback (HR, 0.53; P = .03). Similarly, the first-time injury severity was significantly lower (-0.43; P = .042). Per-protocol analysis showed no significant differences in injury rates, but the direction favored the intervention group (HR, 0.67; P = .30). There were no significant differences in the proportion of patients with multiple injuries (HR, 0.82; P = .40) or changes in running performance (3.07%; P = .26) and motivation. Also, ~60% of the participants who completed the study showed interest in continuing wearable use. CONCLUSION: Real-time feedback on spatiotemporal metrics and relative speed provided by commercially available instrumented insoles may reduce the rate and severity of injuries in recreational runners. Feedback did not influence running performance and exercise motivation. REGISTRATION: NL8472 (Dutch Trial Register).

Changes in running economy and running technique following 6 months of running with and without wearable-based real-time feedback.

BACKGROUND: An increasing number of commercially available wearables provide real-time feedback on running biomechanics with the aim to reduce injury risk or improve performance. OBJECTIVE: Investigate whether real-time feedback by wearable insoles (ARION) alters running biomechanics and improves running economy more as compared to unsupervised running training. We also explored the correlation between changes in running biomechanics and running economy. METHODS: Forty recreational runners were randomized to an intervention and control group and performed ~6 months of in-field training with or without wearable-based real-time feedback on running technique and speed. Running economy and running biomechanics were measured in lab conditions without feedback pre and post intervention at four speeds. RESULTS: Twenty-two individuals (13 control, 9 intervention) completed both tests. Both groups significantly reduced their energetic cost by an average of -6.1% and -7.7% for the control and intervention groups, respectively. The reduction in energy cost did not significantly differ between groups overall (-0.07 ± 0.14 J∙kg∙m-1 , -1.5%, p = 0.63). There were significant changes in spatiotemporal metrics, but their magnitude was minor and did not differ between the groups. There were no significant changes in running kinematics within or between groups. However, alterations in running biomechanics beyond typical session-to-session variation were observed during some in-field sessions for individuals that received real-time feedback. CONCLUSION: Alterations in running biomechanics as observed during some in-field sessions for individuals receiving wearable-based real-time feedback did not result in significant differences in running economy or running biomechanics when measured in controlled lab conditions without feedback.

The accuracy of commercially available instrumented insoles (ARION) for measuring spatiotemporal running metrics.

Spatiotemporal metrics such as step frequency have been associated with running injuries in some studies. Wearables can measure these metrics and provide real-time feedback in-field, but are often not validated. This study assessed the validity of commercially available wireless instrumented insoles (ARION) for quantifying spatiotemporal metrics during level running at different speeds (2.78-5.0 m s-1 ,) and slopes (3° and 6° up/downhill) to an instrumented treadmill. Mean raw, percentage and absolute percentage error, and limits of agreement (LoA) were calculated. Agreement was statistically quantified using four thresholds: excellent, <5%; good, <10%; acceptable, <15%; and poor, >15% error. Excellent agreement (<5% error) was achieved for stride time across all conditions, and for step frequency across all but one condition with good agreement. Contact time and swing time generally showed at least good agreement. The mean difference across all conditions was -0.95% for contact time, 0.11% for stride time, 0.6% for swing time, -0.11% for step frequency, and -0.09% when averaged across all outcomes and conditions. The accuracy at an individual level was generally good to excellent, being <10% for all but two conditions, with these conditions being <15%. Additional experiments among four runners showed that step length could also be measured with an accuracy of 1.76% across different speeds with an updated version of the insoles. These findings suggests that the ARION wearable may not only be useful for large-scale in-field studies investigating group differences, but also to quantify spatiotemporal metrics with generally good to excellent accuracy for individual runners.

Energy Expenditure, Body Composition, and Skeletal Muscle Oxidative Capacity in Patients with Myotonic Dystrophy Type 1.

BACKGROUND: Myotonic dystrophy type 1 (DM1) patients are at risk for metabolic abnormalities and commonly experience overweight and obesity. Possibly, weight issues result from lowered resting energy expenditure (EE) and impaired muscle oxidative metabolism. OBJECTIVES: This study aims to assess EE, body composition, and muscle oxidative capacity in patients with DM1 compared to age-, sex- and BMI-matched controls. METHODS: A prospective case control study was conducted including 15 DM1 patients and 15 matched controls. Participants underwent state-of-the-art methodologies including 24 h whole room calorimetry, doubly labeled water and accelerometer analysis under 15-days of free-living conditions, muscle biopsy, full body magnetic resonance imaging (MRI), dual-energy x-ray absorptiometry (DEXA), computed tomography (CT) upper leg, and cardiopulmonary exercise testing. RESULTS: Fat ratio determined by full body MRI was significantly higher in DM1 patients (56 [49-62] %) compared to healthy controls (44 [37-52] % ; p = 0.027). Resting EE did not differ between groups (1948 [1742-2146] vs (2001 [1853-2425>] kcal/24 h, respectively; p = 0.466). In contrast, total EE was 23% lower in DM1 patients (2162 [1794-2494] vs 2814 [2424-3310] kcal/24 h; p = 0.027). Also, DM1 patients had 63% less steps (3090 [2263-5063] vs 8283 [6855-11485] steps/24 h; p = 0.003) and a significantly lower VO2 peak (22 [17-24] vs 33 [26-39] mL/min/kg; p = 0.003) compared to the healthy controls. Muscle biopsy citrate synthase activity did not differ between groups (15.4 [13.3-20.0] vs 20.1 [16.6-25.8] µM/g/min, respectively; p = 0.449). CONCLUSIONS: Resting EE does not differ between DM1 patients and healthy, matched controls when assessed under standardized circumstances. However, under free living conditions, total EE is substantially reduced in DM1 patients due to a lower physical activity level. The sedentary lifestyle of DM1 patients seems responsible for the undesirable changes in body composition and aerobic capacity.

Energy expenditure, dietary intake and energy availability in female professional football players.

Objectives: To quantify energy expenditure and intake in professional female footballers playing on a national and/or international level. Second, to determine the prevalence of low energy availability among these players, defined as <30 kcal/kg fat-free mass (FFM)/day. Methods: Fifty-one players completed a 14-day prospective observational study during the 2021/2022 football season. Energy expenditure was determined using the doubly labelled water method. Energy intake was assessed using dietary recalls, while global positioning system determined the external physiological load. Descriptive statistics, stratification and the correlation between explainable variables and outcomes were conducted to quantify the energetic demands. Results: The mean energy expenditure for all players (22±4 years) was 2918±322 kcal. Mean energy intake was 2274±450 kcal, resulting in a discrepancy of ~22%. Carbohydrate intake was below the recommended guidelines on match day at 4.5±1.9 g/kg. The mean energy availability was 36.7±17.7 kcal/kg FFM/day on matchday and 37.9±11.7 kcal/kg FFM/day on training days, resulting in a prevalence of 36% and 23% for low energy availability during the observational period, respectively. Conclusion: These elite female football players displayed moderate energy expenditure levels and failed to meet the recommended levels of carbohydrate intake. In conjunction with inadequate nutritional periodisation, this will likely hamper performance through inadequate muscle glycogen resynthesis. In addition, we found a considerable prevalence of low energy availability on match and training days.

The increased perceived exertion during the six minute walking test is not accompanied by changes in cost of walking, gait characteristics or muscle fatigue in persons with multiple sclerosis.

BACKGROUND: Persons with Multiple Sclerosis (pwMS) frequently experience walking difficulties, often expressed as a slower walking speed during the 6 Minute Walking Test (6MWT). In addition, slower walking speeds are also related to higher levels of perceived exertion. PwMS are also known to have a higher energetic Cost of walking (Cw) and may experience muscle fatigue during prolonged walking. In this study, we aimed to explore changes in Rate of Perceived Exertion (RPE) and the Cw within participants during the 6MWT in pwMS. Additionally, concomitant changes in the mean and variability of gait characteristics and changes in muscle activation describing muscle fatigue were assessed. METHODS: The 6MWT was performed on an instrumented treadmill while three-dimensional motion capture and gas exchange were measured continuously. RPE on the 6-20 borg-scale was questioned directly before and after the 6MWT. Cost of walking was expressed in Joules/kg/m. Muscle fatigue was assessed by increases in Root Median Square (RMdS) and decreases in Median Frequency (MF) of the recorded EMGs. Wilcoxon-Signed Rank test was used to assess a difference in RPE before and after the 6MWT. Linear mixed models, while controlling for walking speed, were used to assess changes in Cw, mean and variability of gait characteristics and RMdS and MF of muscle activation. RESULTS: 28 pwMS (23 females, mean ± standard deviation age 46 ± 10 years, height 1.69 ± 0.08 meter, weight 76 ± 18 kilogram, EDSS 2.7 ± 1.3) were included. Although the RPE increased from 8 to 12, no changes in Cw were found. Walking speed was the only spatiotemporal parameter which increased during the 6MWT and RMdS of the gastrocnemius and tibialis anterior muscles increased. The soleus muscle decreased in MF over time. CONCLUSION: The increases in RPE and walking speed was not accompanied by a change in Cw during the 6MWT which indicates that the perceived exertion was not accompanied by an increased physical exertion. Changes in muscle activation might give an indication for muscle fatigue but were inconclusive. Although the 6MWT reflects daily life walking challenges for pwMS, this test did not show the expected changes in gait parameters in our sample.

Moderators of the Effectiveness of UPcomplish on Office Workers' Sedentary Behaviour, Quality of Life, and Psychosocial Determinants: A Stepped Wedge Design.

BACKGROUND: In the earlier developed and evaluated 12-week UPcomplish intervention, the aim was to reduce sedentary behaviour (SB) among office workers and increase their quality of life (QoL). In the current study, we explored moderators of effectiveness. METHOD: We applied a stepped wedge design with five intervention groups starting with time lags of seven weeks (n = 142, 96 females). Participants wore the VitaBit to continuously measure SB and received surveys about QoL and psychosocial determinants at the beginning, middle, and end of the intervention. We regressed baseline participant characteristics and behaviours onto intra-individual improvements (centred around calendar week means) in determinants, SB, performance objectives, and QoL. RESULTS: Those scoring high in baseline intention, task performance, stress, vitality, and emotional well-being improved less in these variables. Baseline stress (ß = - 0.05 [SE = 0.01; 95% CI = - 0.08, - 0.02; pcorrected = .02]) and emotional well-being (ß = 0.02 [SE = 0.01; 95% CI = 0.01, 0.03; pcorrected = .02]) were associated with improvement in contextual performance. Baseline attitude (ß = - 12.92 [SE = 3.93; 95% CI = - 20.80, - 5.04; pcorrected = .02]) and perceived behavioural control (PBC; ß = - 9.27 [SE = 3.04; 95% CI = - 15.37, - 3.16; pcorrected = .03]) were negatively associated with improvements in emotional well-being. Post hoc analyses with a sub-group scoring lower in determinants revealed that improvement in PBC was positively associated with SB registration. CONCLUSION: Participants scoring low in baseline determinants might profit from UPcomplish via an increase in PBC. In combination with changes within organizations (e.g. the implementation of standing desks), UPcomplish might potentially reduce SB. TRIAL REGISTRATION: NL7503 - registered 1 February 2019.

Determination of energy expenditure in professional cyclists using power data: Validation against doubly labeled water.

INTRODUCTION: Accurate determination of total daily energy expenditure (TDEE) in athletes is important for optimal performance and injury prevention, but current approaches are insufficiently accurate. We therefore developed an approach to determine TDEE in professional cyclists based on power data, basal metabolic rate (BMR), and a non-exercise physical activity level (PAL) value, and compared energy expenditure (EE) between multi-day and single-day races. METHODS: Twenty-one male professional cyclists participated. We measured: (1) BMR, (2) the relationship between power output and EE during an incremental cycling test, which was used to determine EE during exercise (EEE ), and (3) TDEE using doubly labeled water (DLW). A non-exercise PAL-value was obtained by subtracting EEE from TDEE and dividing this by BMR. RESULTS: Measured BMR was 7.9 ± 0.8 MJ/day, which was significantly higher than predicted by the Oxford equations. A new BMR equation for elite endurance athletes was therefore developed. Mean TDEE was 31.7 ± 2.8 and 27.3 ± 2.8 MJ/day during the Vuelta a España and Ardennes classics, while EEE was 17.4 ± 1.8 and 10.1 ± 1.4 MJ/day, respectively. Non-exercise PAL-values were 1.8 and 2.0 for the Vuelta and Ardennes classics, respectively, which is substantially higher than currently used generic PAL-values. CONCLUSION: We show that the proposed approach leads to a more accurate estimation of non-exercise EE than the use of a generic PAL-value in combination with BMR predictive equations developed for non-elite athletes, with the latter underestimating non-exercise EE by ~28%. The proposed approach may therefore improve nutritional strategies in professional cyclists.

Physiological, Spatiotemporal, Anthropometric, Training, and Performance Characteristics of a 75-Year-Old Multiple World Record Holder Middle-Distance Runner.

PURPOSE: This study assessed the cardiorespiratory capacity, anaerobic speed reserve, and anthropometric and spatiotemporal variables of a 75-year-old world-class middle-distance runner who previously obtained several European and world records in the age categories of 60-70 years, achieved 13 European titles and 15 world champion titles, and also holds several European records for the 75-year-old category. METHODS: Heart rate, oxygen uptake, carbon dioxide production, ventilation, step frequency, contact time, and velocity at maximal oxygen uptake (VO2max) were measured during treadmill running. Maximal sprinting speed was assessed during track sprinting and used to compute anaerobic speed reserve. Body fat percentage was assessed using air displacement plethysmography. RESULTS: Body fat percentage was 8.6%, VO2max was 50.5 mL·kg-1·min-1, maximal ventilation was 141 L·min-1, maximum heart rate was 164 beats·min-1, maximum respiratory exchange ratio was 1.18, and velocity at VO2max was 16.7 km·h-1. The average stride frequency and contact time during the last 30 seconds of the 4-minute run at 10 km·h-1 were 171 steps·min-1 and 241 ms and 187 steps·min-1 and 190 ms in the last 40 seconds at 17 km·h-1, respectively. The anaerobic speed reserve was 11.4 km·h-1, corresponding to an anaerobic speed reserve ratio of 1.68. CONCLUSION: This 75-year-old runner has an exceptionally high VO2max and anaerobic speed reserve ratio. In addition, his resilience to injuries, possibly due to a relatively high volume of easy runs, enabled him to sustain regular training since his 50s and achieve international performance in his age group.

Assessment of Total Energy Expenditure and Physical Activity Using Activity Monitors.

To assess total daily energy expenditure (TDEE) under daily living conditions, the doubly labelled water (DLW) technique is considered the gold standard. This technique is accurate but also costly and requires specific lab equipment and expertise. It also provides an average measure of TDEE over a period of one to two weeks and hence no information on physical activity (PA) patterns is available. To overcome these shortcomings, activity monitors can be used to assess activity patterns and an estimate of TDEE can be made, provided the activity monitor has been previously validated in daily life using DLW. Most activity monitors contain accelerometers, that measure the acceleration of the body and hence represent body movement. By definition, body movement leads to energy expenditure (EE) and hence the two always need to be related. Activity monitors that provide an estimate of EE need to be validated so that the contribution of the sensor output to the prediction of EE is known. Subject characteristics such as body mass, height, gender and age already explain most of the variation of TDEE; the accelerometer should then represent the physical activity component of TDEE and improve the explained variation. Many activity monitors also contain additional sensors measuring other (physiological) output parameters such as heart rate, skin temperature, galvanic skin response or gps positioning. Although promising, so far there is no compelling evidence that these additional sensors improve the prediction of EE, so careful consideration is needed whether or not these are worth the extra cost, and the extra battery power and storage capacity needed. Again, it is important to know the individual contribution of each outcome parameter to the prediction of TDEE. In conclusion, activity monitors are valuable tools in PA research but also in nutritional research when energy balance is studied.

High daily energy expenditure of Tuvan nomadic pastoralists living in an extreme cold environment.

Research investigating thermoregulatory energy costs in free-living humans is limited. We determined the total energy expenditure (TEE) of Tuvan pastoralists living in an extreme cold environment and explored the contribution of physical activity and cold-induced thermogenesis. Twelve semi-nomadic pastoralists (47 ± 8 years, 64 ± 8 kg) living under traditional circumstances, in Tuva, south-central Siberia, Russia, were observed during two consecutive 6-day periods in winter. TEE was measured via the doubly labelled water technique. Skin and ambient temperatures, and physical activity were continuously monitored. The outdoor temperature during the observation period was - 27.4 ± 5.4 °C. During the daytime, the participants were exposed to ambient temperatures below 0 °C for 297 ± 131 min/day. The Tuvan pastoralists were more physically active compared to western populations (609 ± 90 min/day of light, moderate, and vigorous physical activity). In addition, TEE was 13.49 ± 1.33 MJ/day (3224 ± 318 kcal/day), which was significantly larger by 17% and 31% than predicted by body mass, and fat-free mass, respectively. Our research suggests the daily cold exposure combined with high levels of physical activity contributed to the elevated TEE. Future research should reconsider the assumption that energy costs due to thermoregulation are negligible in free-living humans.

External validation of a prediction model for estimating fat mass in children and adolescents in 19 countries: individual participant data meta-analysis.

OBJECTIVE: To evaluate the performance of a UK based prediction model for estimating fat-free mass (and indirectly fat mass) in children and adolescents in non-UK settings. DESIGN: Individual participant data meta-analysis. SETTING: 19 countries. PARTICIPANTS: 5693 children and adolescents (49.7% boys) aged 4 to 15 years with complete data on the predictors included in the UK based model (weight, height, age, sex, and ethnicity) and on the independently assessed outcome measure (fat-free mass determined by deuterium dilution assessment). MAIN OUTCOME MEASURES: The outcome of the UK based prediction model was natural log transformed fat-free mass (lnFFM). Predictive performance statistics of R2, calibration slope, calibration-in-the-large, and root mean square error were assessed in each of the 19 countries and then pooled through random effects meta-analysis. Calibration plots were also derived for each country, including flexible calibration curves. RESULTS: The model showed good predictive ability in non-UK populations of children and adolescents, providing R2 values of >75% in all countries and >90% in 11 of the 19 countries, and with good calibration (ie, agreement) of observed and predicted values. Root mean square error values (on fat-free mass scale) were <4 kg in 17 of the 19 settings. Pooled values (95% confidence intervals) of R2, calibration slope, and calibration-in-the-large were 88.7% (85.9% to 91.4%), 0.98 (0.97 to 1.00), and 0.01 (-0.02 to 0.04), respectively. Heterogeneity was evident in the R2 and calibration-in-the-large values across settings, but not in the calibration slope. Model performance did not vary markedly between boys and girls, age, ethnicity, and national income groups. To further improve the accuracy of the predictions, the model equation was recalibrated for the intercept in each setting so that country specific equations are available for future use. CONCLUSION: The UK based prediction model, which is based on readily available measures, provides predictions of childhood fat-free mass, and hence fat mass, in a range of non-UK settings that explain a large proportion of the variability in observed fat-free mass, and exhibit good calibration performance, especially after recalibration of the intercept for each population. The model demonstrates good generalisability in both low-middle income and high income populations of healthy children and adolescents aged 4-15 years.

The cost of chewing: The energetics and evolutionary significance of mastication in humans.

Any change in the energetic cost of mammalian mastication will affect the net energy gain from foods. Although the energetic efficiency of masticatory effort is fundamental in understanding the evolution of the human masticatory system, nothing is known currently about the associated metabolic costs of chewing different items. Here, using respirometry and electromyography of the masseter muscle, we demonstrate that chewing by human subjects represents a measurable energy sink. Chewing a tasteless odorless gum elevates metabolic rate by 10 to 15% above basal levels. Energy expenditure increases with gum stiffness and is paid for by greater muscle recruitment. For modern humans, it is likely that mastication represents a small part of the daily energy budget. However, for our ancestors, before the onset of cooking and sophisticated food processing methods, the costs must have been relatively high, adding a previously unexplored energetic dimension to the interpretation of hominin dentofacial fossils.

Human total, basal and activity energy expenditures are independent of ambient environmental temperature.

Lower ambient temperature (Ta) requires greater energy expenditure to sustain body temperature. However, effects of Ta on human energetics may be buffered by environmental modification and behavioral compensation. We used the IAEA DLW database for adults in the USA (n = 3213) to determine the effect of Ta (-10 to +30°C) on TEE, basal (BEE) and activity energy expenditure (AEE) and physical activity level (PAL). There were no significant relationships (p > 0.05) between maximum, minimum and average Ta and TEE, BEE, AEE and PAL. After adjustment for fat-free mass, fat mass and age, statistically significant (p < 0.01) relationships between TEE, BEE and Ta emerged in females but the effect sizes were not biologically meaningful. Temperatures inside buildings are regulated at 18-25°C independent of latitude. Hence, adults in the US modify their environments to keep TEE constant across a wide range of external ambient temperatures.

A New Approach to Improve the Validity of Doubly Labeled Water to Assess CO2 Production during High-Energy Turnover.

PURPOSE: Accurate measurement of energy expenditure (EE) using doubly labeled water depends on the estimate of total body water (TBW). The aims of this study were to 1) assess the accuracy of a new approach for estimating TBW and EE during high-energy turnover and 2) assess the accuracy of day-to-day assessment of EE with this new approach. METHODS: EE was measured in six healthy subjects (three male) for 5 consecutive days using three doubly labeled water methods: 1) the plateau, 2) slope-intercept, and 3) overnight-slope method, with whole-room indirect calorimetry as reference method. Urine samples were collected every evening and morning. High EE (physical activity level of >2.5) was achieved by cycling 4 h·d-1. RESULTS: Physical activity level was 2.8 ± 0.1. TBW values were 41.9 ± 6.1, 38.4 ± 5.7, and 40.4 ± 5.8 L for the plateau, slope-intercept, and overnight-slope methods, respectively. The overnight-slope method showed the highest accuracy in estimated CO2 production, when compared with indirect calorimetry over the complete 5-d period (mean ± SD difference, 0.9% ± 1.6%). The plateau method significantly overestimated CO2 production by 4.7% ± 2.6%, whereas the slope-intercept method underestimated CO2 production (-3.4% ± 2.3%). When CO2 production was assessed per day, the overnight-slope method showed an average difference of 9.4% ± 4.5% to indirect calorimetry. CONCLUSIONS: The overnight-slope method resulted in a more accurate estimation of CO2 production and EE compared with the plateau or slope-intercept method over a 5-d period in high physical activity conditions. Day-to-day determination of EE using the overnight-slope method was more accurate than diet recall and several standard prediction equations in athletes.