Assessment Of Energy Expenditure Research Articles

Prediction Equation for Physical Activity Energy Expenditure in 11-13-Year-Old Sri Lankan Children.

This study aimed to develop a regression equation to predict physical activity energy expenditure (PAEE) using accelerometry. Children aged 11-13 years were recruited and randomly assigned to validation (n = 54) and cross-validation (n = 25) groups. The doubly labelled water (DLW) technique was used to assess energy expenditure and accelerometers were worn by participants across the same period. A preliminary equation was developed using stepwise multiple regression analysis with sex, height, weight, body mass index, fat-free mass, fat mass and counts per minute (CPM) as independent variables. Goodness-of-fit statistics were used to select the best prediction variables. The PRESS (predicted residual error sum of squares) statistical method was used to validate the final prediction equation. The preliminary equation was cross-validated on an independent group and no significant (p > 0.05) difference was observed in the PAEE estimated from the two methods. Independent variables of the final prediction equation (PAEE = [0.001CPM] - 0.112) accounted for 70.6% of the variance. The new equation developed to predict PAEE from accelerometry was found to be valid for use in Sri Lankan children.

Unveiling the Relationships Between Seismocardiogram Signals, Physical Activity Types and Metabolic Equivalent of Task Scores.

The diagnosis of metabolic syndrome and cardiovascular disorders can highly benefit from physical activity and energy expenditure assessment. In this study, we investigated the relationship between metabolic equivalent of task (MET) scores and seismocardiogram (SCG)-derived parameters. We worked with the PAMAP2 dataset and focused on the 3-axial chest acceleration data. We first segmented the 3-axial SCG signals into respiration (0-1Hz), cardiac vibrations (1-20Hz) and heart sounds (20-40Hz) components. Additionally, we investigated their combinations: 0-20Hz, 1-40Hz and 0-40Hz. We then windowed each signal, and extracted time and frequency domain features from each window. Using the MET scores and activity types, we trained linear regression and random forest classification models first using 80-20% split, then with leave-one-subject-out cross-validation (LOSO-CV). Additionally, we investigated the significance of each feature and axis. For the 80-20% task, the best performing frequency bands were 0-1Hz, 0-20Hz, and 0-40Hz, which yielded a (MET mean-squared-error, classification accuracy) pair of (0.354, 0.952), (0.367, 0.904), and (0.377, 0.914), respectively. When LOSO-CV was applied, we obtained (1.059, 0.865), (0.681, 0.868), and (0.804, 0.875) for each band, respectively. Additionally, our results revealed that the lateral axis provides the most critical information about cardiorespiratory effect of performed activities. Different SCG components can provide unique and substantial contributions to activity and energy expenditure assessment. This framework can be leveraged in the design of wearable systems for monitoring the activity and energy expenditure levels, and understanding their relationship with underlying cardiorespiratory parameters.

Chaperonin counteracts diet-induced non-alcoholic fatty liver disease by aiding sirtuin 3 in the control of fatty acid oxidation.

The mitochondrial chaperonin heat shock protein (HSP) 60 is indispensable in protein folding and the mitochondrial stress response; however, its role in nutrient metabolism remains uncertain. This study investigated the role of HSP60 in diet-induced non-alcoholic fatty liver disease (NAFLD). We studied human biopsies from individuals with NAFLD, murine high-fat-diet (HFD; a diet with 60% energy from fat)-induced obesity (DIO), transgenic (Tg) mice overexpressing Hsp60 (Hsp60-Tg), and human HepG2 cells transfected with HSP60 cDNA or with HSP60 siRNA. Histomorphometry was used to assess hepatic steatosis, biochemistry kits were used to measure insulin resistance and glucose tolerance, and an automated home cage phenotyping system was used to assess energy expenditure. Body fat was assessed using MRI. Macrophage infiltration, the lipid oxidation marker 4-hydroxy-2-nonenal (4-HNE) and the oxidative damage marker 8-hydroxy-2'-deoxyguanosine (8-OHdG) were detected using immunohistochemistry. Intracellular lipid droplets were evaluated by Nile red staining. Expression of HSP60, and markers of lipogenesis and fatty acid oxidation were quantified using RT-PCR and immunoblotting. Investigations were analysed using the two-way ANOVA test. Decreased HSP60 expression correlated with severe steatosis in human NAFLD biopsies and murine DIO. Hsp60-Tg mice developed less body fat, had reduced serum triglyceride levels, lower levels of insulin resistance and higher serum adiponectin levels than wild-type mice upon HFD feeding. Respiratory quotient profile indicated that fat in Hsp60-Tg mice may be metabolised to meet energy demands. Hsp60-Tg mice showed amelioration of HFD-mediated hepatic steatosis, M1/M2 macrophage dysregulation, and 4-HNE and 8-OHdG overproduction. Forced HSP60 expression reduced the mitochondrial unfolded protein response, while preserving mitochondrial respiratory complex activity and enhancing fatty acid oxidation. Furthermore, HSP60 knockdown enhanced intracellular lipid formation and loss of sirtuin 3 (SIRT3) signalling in HepG2 cells upon incubation with palmitic acid (PA). Forced HSP60 expression improved SIRT3 signalling and repressed PA-mediated intracellular lipid formation. SIRT3 inhibition compromised HSP60-induced promotion of AMP-activated protein kinase (AMPK) phosphorylation and peroxisome proliferator-activated receptor α (PPARα levels), while also decreasing levels of fatty acid oxidation markers. Mitochondrial HSP60 promotes fatty acid oxidation while repressing mitochondrial stress and inflammation to ameliorate the development of NAFLD by preserving SIRT3 signalling. This study reveals the hepatoprotective effects of HSP60 and indicates that HSP60 could play a fundamental role in the development of therapeutics for NAFLD or type 2 diabetes.

Large Estimate Variations in Assessed Energy Expenditure and Physical Activity Levels during Active Virtual Reality Gaming: A Short Report.

The purpose of the study was to compare methods for estimating energy expenditure (EE) and physical activity (PA) intensity during a 30 min session of active virtual reality (VR) gaming. Eight individuals (age = 25.4 ± 2.0 yrs) participated, with a maximal oxygen consumption (VO2max) of 41.3 ± 5.7 mL∙kg-1∙min-1. All tests were conducted over two days. An incremental test to determine the VO2max when running was performed on day 1, while 30 min of active VR gaming was performed on day 2. The instruments used for EE estimations and PA measurements were indirect calorimetry, a heart rate (HR) monitor, and waist- and wrist-worn accelerometer. Compared to indirect calorimetry, waist-worn accelerometers underestimated EE (mean difference: -157.3 ± 55.9 kcal, p < 0.01) and PA levels. HR-based equations overestimated EE (mean difference: 114.8 ± 39.0 kcal, p < 0.01 and mean difference: 141.0 ± 81.6 kcal, p < 0.01). The wrist-worn accelerometer was the most accurate in estimating EE (mean difference: 23.9 ± 45.4 kcal, p = 0.95). The large variations in EE have implications for population-based surveillance of PA levels and for clinical studies using active VR gaming.

Validation of the physical activity classification table for Korean youth and assessment of total energy expenditure, estimated energy requirement and physical activity in Korean children and adolescents

Validation of the physical activity classification table for Korean youth and assessment of total energy expenditure, estimated energy requirement and physical activity in Korean children and adolescents

Contemporary approaches to the assessment of energy intake and energy expenditure in athletes

Assessment and interpreting of the energy expenditure (EE) in highly skilled athletes are important components of an effective training and performance prediction. Each component of EE (resting energy expenditure, thermic effect of food, and physical activity energy expenditure) is closely related to dietary patterns, the intensity and duration of physical activity, as well as a number of other factors that affect the functional state of athletes. Despite the importance of EE in the training process, coaches and athletes often do not take EE into account, which reduces the objectivity of assessing athletes' functional state. The purpose of this research was to summarize the recent information on the structure of EE and energy consumption in athletes. Material and methods. The search and analysis of publications was carried out using the PubMed, MEDLINE, Scopus, Web of Science, eLIBRARY databases, mainly for the last 10 years, using the search keywords: rest energy expenditure, thermic effect of food, physical activity energy expenditure, energy intake, total energy expenditure, athletes. Results. This overview includes information on the components of total energy expenditure, such as rest energy expenditure, thermic effect of food and physical activity energy expenditure, as well as generalized information on the factors affecting the variability of their values and methods for assessing one or another type of energy expenditure. International nutritional recommendations regarding the level of physical activity of athletes are systematized, as well as the advantages and disadvantages of methods for studying energy consumption and total energy expenditure are presented. Conclusion. Combined study of energy intake and energy expenditure will help athletes avoid the negative impact of energy deficiency on performance, and the correct construction of the training process with the maintenance of adequate energy consumption will have a positive impact on the performance and recovery processes after intensive physical exertion.

Оценка основного обмена у несовершеннолетних спортсменов

Objective. To assess the intensity of basal metabolism in adolescent elite athletes. Patients and methods. This study included 154 adolescent athletes (42 boys, 112 girls) aged 13–18 years (mean age: 15.3 ± 2.5 years). Basal metabolic rate (BMR) was measured in all participants using respiratory indirect calorimetry and the Harris–Benedict equation. Study design: single-center, cross-sectional, randomized, uncontrolled. Results. An increase in BMR was revealed in 79 (51%) participants, normal BMR – in 50 (33%) participants, and a decrease in BMR – in 25 (16%) participants. Increased BMR was statistically significantly more common in boys compared to girls (83% and 39% respectively, p = 0,01), whereas decreased BMR was more characteristic of girls compared to boys (20% and 4%, respectively, p = 0.001). Conclusion. Most adolescent athletes show an increase in BMR, which reflects an adaptation of the organism to high physical exertion. A decrease in BMR may indicate the presence of relative energy deficiency in athletes. The Harris–Benedict equation significantly underestimates the value of BMR in adolescent athletes and is not an alternative to respiratory indirect calorimetry when individual assessment of energy expenditure is necessary as part of biomedical support. Key words: children, high-performance sport, basal metabolic rate, indirect calorimetry

Preface

The 2nd International Conference on Computers, Remote Sensing and Aerospace (CRSA 2022) was successfully held in Nagoya, Japan, on August 26-28, 2022. Due to the impact of COVID-19, it was changed to be held online. The conference mainly focused on the latest researches on Computer, Remote Sensing and Aerospace, gathering experts, scholars, and researchers in these fields from all over the world to share research achievements, explore hot issues, and exchange experience and new ideas.In the conference, we were greatly honored to have both Prof. Yanguo Jing from Coventry University, UK and Prof. Jiang Zhu from Tokyo Institute of Technology, Japan to serve as our Conference Chairs. 100 scholars around the world took part in the conference. Divided into three parts, the conference agenda included keynote speeches, oral presentations and online Q&A discussion. Primarily, the keynote speakers were each allocated 30-45 minutes to address their speeches. Then in the next part, oral presentations, the excellent papers we had selected were presented by their authors one by one.Three distinguished professors were invited to hold keynote speeches during the conference. Among them, Prof. Yanguo Jing from Coventry University, UK performed a thought-provoking speech on Artificial Intelligence Applications in Sports Performance. Although Artificial Intelligence (AI) are being used to create new values and opportunities in business and society, there are many challenges in developing these AI applications. In the speech, Yanguo shared his own journey of use artificial intelligence and machine learning to monitor sports performance, and evaluated their effectiveness in assessing energy expenditure during sport exercise. What’s more, Assoc. Prof. Thippa Reddy Gadekallu from Vellore Institute of Technology, India addressed a speech: Federated Learning for Healthcare. He introduced the applications of FL for healthcare informatics, the need for FL in healthcare domain, the fundamentals of FL, and the major motivations behind FL for healthcare applications, etc. And some lessons learnt, challenges, as well as future directions were highlighted. Their insightful speeches had triggered heated discussion. And every participant praised this conference for disseminating useful and insightful knowledge.We are glad to share with you that we received lots of submissions from the conference and we selected a bunch of high-quality papers and compiled them into the proceedings after rigorously reviewing them. These papers feature but are not limited to the following topics: Remote Sensing, Global Positioning and Navigation System, Manned/Unmanned Aviation, High Performance Computing, Algorithms, etc. All the papers have been checked through rigorous review and processes to meet the requirements of publication.We would like to acknowledge all of those who supported CRSA 2022 and made it a great success. Particularly, we would like to thank the Journal of Physics: Conference Series, for all the efforts of its colleagues in publishing this paper volume. We sincerely hope that the CRSA 2022 turned out to be a forum for excellent discussions that enable new ideas to come about, promoting collaborative research.Committee of CRSA 2022List of Committee member is available in this Pdf.

Effects of pre-meal whey protein consumption on acute food intake and energy balance over a 48-hour period

• Whey protein (20 g) reduced energy intake in both HW (193.4 kcal, 15.9 %) and OV/OB (215.81 kcal, 17.8 %) when consumed 20 min prior to mealtime, compared to placebo. • Energy deficits induced in an ad libitum test meal did not upregulate compensatory behaviours over the following 48 h. • A slowed eating rate may influence food intake following premeal whey ingestion. The effects of pre-meal whey protein consumption on acute food intake and subsequent energy balance measured over 48-h was investigated in males of healthy-weight (HW) or living with overweight and obesity (OV/OB). On two separate trial days, following a controlled breakfast (09:00) and lunch (13:00), 12 HW and 12 OV/OB males consumed either whey protein (20 g) or flavoured water beverages (16:40), and ad libitum test meal (17:00). A controlled 48-h assessment of energy intake and expenditure was used to determine any compensatory behaviour. Test meal energy intake reduced 15.9 % in HW (P = 0.003), and 17.8 % in OV/OB (P = 0.005) following whey protein, compared to placebo. We report no between-group differences and no changes in compensatory behaviour. A small dose of whey protein reduces energy intake at the next meal, without upregulating compensatory behaviours in both HW and OV/OB males. However, chronic effects on body composition and weight loss remain to be elucidated.

Accurate assessment of walking energy expenditure in the main seafront walking route of Las Palmas de Gran Canaria to promote health-related tourism

Accurate assessment of walking energy expenditure in the main seafront walking route of Las Palmas de Gran Canaria to promote health-related tourism

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.

Deficiency of Irx5 protects mice from obesity and associated metabolic abnormalities.

Obesity, a leading cause of several metabolic abnormalities, is mainly caused by imbalanced energy homeostasis. IRX3 and IRX5 have been suggested as genetic determinants of obesity in connection with the intronic variants of the FTO gene, the strongest genetic risk factor of polygenic obesity in humans. Although the causal effects of Irx3 and its cooperation with Irx5 in obesity and associated metabolic abnormalities have been demonstrated in vivo, the function of Irx5 in energy homeostasis remains unclear. Here we aim to decipher the actions of Irx5 in the regulation of obesity and metabolic abnormalities. We employed a mouse model homozygous for an Irx5-knockout (Irx5KO) allele and determined its metabolic phenotype in the presence or absence of a high-fat diet challenge. To investigate the function of Irx5 in the regulation of energy homeostasis, adipose thermogenesis and hypothalamic leptin response were assessed, and single-cell RNA sequencing (scRNA-seq) in the hypothalamic arcuate-median eminence (ARC-ME) was conducted. Irx5KO mice were leaner and resistant to diet-induced obesity as well as associated metabolic abnormalities, primarily through loss of adiposity. Assessments of energy expenditure and long-term dietary intake revealed that an increase in basal metabolic rate with adipose thermogenesis and a reduction of food intake with improved hypothalamic leptin response in Irx5KO mice may contribute to the anti-obesity effects. Utilizing scRNA-seq and marker gene analyses, we demonstrated the number of ARC-ME neurons was elevated in Irx5KO mice, suggesting a direct role for Irx5 in hypothalamic feeding control. Our study demonstrates that Irx5 is a genetic factor determining body mass/composition and obesity and regulates both energy expenditure and intake.

Assessment Of Daily Physical Energy Expenditure By Accelerometer Body Placement Using Doubly Labeled Water: Does Placement Matter?

PURPOSE: To assess the contribution of accelerometer-measured physical activity by body placement (left wrist, right wrist, or trunk) to daily activity energy expenditure using doubly labeled water. METHODS: This study enrolled 49 adults from the Baltimore Longitudinal Study of Aging that wore ActiGraph accelerometers on both wrists and the chest while their energy expenditure was measured using doubly labeled water (DLW) over 7 consecutive days. Total activity counts (TAC) from the 3 accelerometers were calculated (scaled to 1000 counts/day) and served as the daily physical activity measure. On the day participants began to wear the accelerometers, they received doses of approximately 2.5 g/kg of 10% enriched H218O and 0.12 g/kg of 99.9% enriched 2H2O. Urine samples were collected before and after DLW dosing and after 7 days of physical activity monitoring to determine mean activity energy expenditure (AEE). Sample characteristics were summarized using medians (IQR) and frequencies. Linear regression models with TAC alone and with TAC, age, sex, body composition and height were used to predict AEE for each placement location. R-square (R2) increases due to TAC were used to evaluate the influence of accelerometer placement with respect to variance explained in AEE. RESULTS: Participants (55% women, median age 74 years) recorded a median of 2396 (IQR: 2099, 2679) activity counts/day on the dominant wrist, 2069 (1815, 2322) counts/day on the non-dominant wrist, 37 (25, 43) counts/day on the chest and generated AEE of 725 (538, 979) kCal/day. In the TAC only models, TAC was not associated with AEE and explained minimal variance (R2 = .03-.04; all p > .05). In the multi-predictor models TAC measured through dominant wrist worn and non-dominant wrist worn were associated with AEE (β = 0.19, SE = 0.09; p = .033 and β = 0.22, SE = 0.10; p = .039), but chest worn was not (p = .25). The addition of TAC measured through dominant and non-dominant wrist to the multi-predictor models explained 7% and 8% more variance predicting AEE, respectively (p < .05). CONCLUSIONS: Wrist-worn accelerometers are more closely associated with AEE than chest-worn. Accelerometer placement and participant characteristics are important considerations when estimating daily activity energy expenditure.

Comparison of the accuracy of resting energy expenditure assessment using bioimpedance analysis and indirect respiratory calorimetry in children with simple obesity

Background: Assessment of resting energy expenditure (REE) is necessary for the formation of a diet for obesity patients. The «gold standard» for assessment of resting energy expenditure (REE) is indirect respiratory calorimetry. Currently, bioimpedance analyzers are increasingly being used in clinical practice to assess energy consumption at rest, including in obese children. However, the accuracy of such an assessment remains unclear.Aims: To determine the accuracy of the assessment of resting energy expenditure using bioimpedance analysis in children with simple obesity compared with indirect respiratory calorimetry.Materials and methods: Resting energy expenditure was assessed by bioimpedance analysis, Harris-Benedict formula and indirect respiratory calorimetry in all obese children. Comparability of methods was assessed using the Bland-Altman analysis.Results: The study included 320 children aged 7 to 17 years with simple obesity.Resting energy expenditure assessed by bioimpedance analysis was on average 232 kcal lower than the actual. A significant CI (-448 to 912 kcal) was revealed, as well as a large LOA from -514 to 979 kcal. REE calculated by the Harris-Benedict formula on average corresponded to the actual one, and CI varied from -38 to 27 kcal. However, large LOA from -514 to 979 kcal, indicating a high individual variability of resting energy consumption.Conclusions: Bioimpedance analyzers underestimate REE in obese children compared to indirect respiratory calorimetry and the Harris-Benedict formula. Given the significant discrepancies in the accuracy of REE assessment, bioimpedance analysis cannot be considered as an alternative to indirect respiratory calorimetry to assess resting energy in children with simple obesity.

Assessment of Energy Expenditure of Police Officers Trained in Polish Police Schools and Police Training Centers.

Knowledge of the energy expenditure related to the training of policemen allows for assessment of the intensity of the work performed and is an indispensable element of planning and implementing nutrition. This study on energy expenditure comprised a total of 280 persons, students of two Polish police schools and two police training centers. The energy expenditure of policemen was determined based on measurements of the heart rate using Polar RC3 GPS heart rate monitors. The energy expenditure of policemen associated with the training process in the police schools and training centers ranged from 1793 to 3043 kcal/8 h and amounted to 2314 ± 945 kcal/8 h during training on average. The values of energy expenditure related to a typical training day in Polish institutions conducting police training are diverse and depend on the specificity and nature of the training. According to the criteria for assessing the burden of work, the work performed by police officers can be classified as hard work and very hard work.

Energy expenditure in COVID-19 mechanically ventilated patients: A comparison of three methods of energy estimation.

BackgroundIndirect calorimetry (IC) is the gold standard for measuring resting energy expenditure. Energy expenditure (EE) estimated by ventilator‐derived carbon dioxide consumption (EEVCO2) has also been proposed. In the absence of IC, predictive weight‐based equations have been recommended to estimate daily energy requirements. This study aims to compare simple predictive weight‐based equations with those estimated by EEVCO2 and IC in mechanically ventilated patients of COVID‐19.MethodsRetrospective study of a cohort of critically ill adult patients with COVID‐19 requiring mechanical ventilation and artificial nutrition to compare energy estimations by three methods through the calculation of bias and precision agreement, reliability, and accuracy rates.ResultsIn 58 mechanically ventilated patients, a total of 117 paired measurements were obtained. The mean estimated energy derived from weight‐based calculations was 2576 ± 469 kcal/24 h, as compared with 1507 ± 499 kcal/24 h when EE was estimated by IC, resulting in a significant bias of 1069 kcal/day (95% CI [−2158 to 18.7 kcal]; P < 0.001). Similarly, estimated mean EEVCO2 was 1388 ± 467 kcal/24 h when compared with estimation of EE from IC. A significant bias of only 118 kcal/day (95% CI [−187 to 422 kcal]; P < 0.001), compared by the Bland‐Altman plot, was noted.ConclusionThe energy estimated with EEVCO2 correlated better with IC values than energy derived from weight‐based calculations. Our data suggest that the use of simple predictive equations may potentially lead to overfeeding in mechanically ventilated patients with COVID‐19.

Assessment of energy expenditure in postpartum women with prior gestational diabetes mellitus: Subjective versus objective methods

Background: Regular physical activity (PA) attenuates the development of type 2 diabetes mellitus in postpartum women with prior gestational diabetes mellitus (GDM). PA is assessed by calculating the energy expenditure (EE), thus accurate estimation of EE is crucial. International PA Questionnaire (IPAQ) and activity diary are widely used subjective methods while pedometer provides objective evidence of PA and EE. Aims and Objectives: This study aims to compare subjective and objective methods of assessing EE as a measure of PA in postpartum women with a history of GDM. Materials and Methods: Fifty postpartum women who had a history of GDM were advised to maintain activity diaries and pedometer readings for 1 week each month up to 1 year and IPAQ was administered at the end of 6 and 12 months. EE was calculated by all three methods separately and Bland-Altman plots were used to assess the level of agreement between IPAQ and the other tools at 6 and 12 months. Friedman test was performed to compare estimated EE between the three methods. Results: There was a poor agreement between the subjective and objective methods. According to Bland-Altman plot results, the highest mean difference was observed between IPAQ and pedometer at 12 months (mean difference was 75.9). This observation indicated an underestimation of pedometer values at 12 months. EE assessed by two subjective methods were statistically comparable at both time points whereas, EE assessed by pedometer was significantly lower (P&lt;0.017) compared to self-reported tools. Conclusion: Assessment of EE by subjective methods which are based on personal judgment may cause overestimation of PA. In contrast, pedometer readings are likely to underestimate the PA as it only reports kinetics activities. Therefore, a combination of subjective and objective methods is recommended to ameliorate the reliability and validity.

Assessment of Energy Expenditure During Discrete Skill Performance Using Systematic Observation and Indirect Calorimetry

Purpose: To determine the accuracy of three systematic observation (SO) tools to estimate energy expenditure (EE) using different skill performance and observation intervals. Method: Three SO tools (Observational System for Recording Physical Activity in Children-Preschool, System for Observing Fitness Instruction Time, and System for Observing Play and Leisure Activity in Youth) were used to observe children (N = 42, Mage = 8.1 ± 0.7) during motor skill testing sessions. EE was measured using indirect calorimetry (COSMED K4b2). Results: Paired samples t tests, repeated-measures analysis of variance, and regression analyses were performed to compare the EE estimated from SO tools with EE measured by indirect calorimetry. The average mean difference between the estimated metabolic equivalence of task (METS) and actual METS ranged between −1.24 METS (SD = 1.62, p &lt; .01) and −3.46 METS (SD = 1.31, p &lt; .01) depending on skill performance interval or SO tool analyzed. Conclusions: SO tools did not accurately estimate EE during object control skill testing sessions. Physical educators should consider utilizing discrete motor skill practice to accumulate health-enhancing levels of physical activity while adhering to national standards.

Assessment of activity energy expenditure during competitive golf: The effects of bag carrying, electric or manual trolleys

ABSTRACT Golf is a sport played around the globe, with an estimated 42.6 million people playing within the United Kingdom and United States of America alone. To date, there is limited data on the energy expenditure of golf. The present study assessed the activity energy expenditure (AEE) of 16 high-standard (handicap under 5) golfers who completed three rounds of competitive golf either carrying the golf bag (BC), using a manual push trolley (MT) or an electric trolley (ET) (Stewart Golf, Gloucester, UK). Prior to each round, participants were fitted with an Actiheart® accelerometer (Camntech, Fenstanton, UK) to estimate AEE, whilst ratings of perceived exertion (RPE) and enjoyment were collected following each round. Data were analysed using a one-way repeated measures ANOVA, with Hedges g effect sizes (ES) calculated. Mean (SD) AEE was 688 ± 213 kcal for BC, 756 ± 210 kcal for MT and 663 ± 218 kcal for ET (p = .05) although these differences were deemed small or less. The ET condition resulted in the lowest mean heart rate, moderate or very large from BC or MT, respectively. There were no significant differences in enjoyment although perceived exertion was lowest in the ET condition. In summary, we report meaningful differences in AEE between the three conditions (p = .05), with perceived exertion and maximum HR being lowest when using the electric trolley. Golf may be considered as an effective intervention to increase step count and improve physical activity levels across the general population regardless of transportation methods of clubs.

Methodological Aspects of Indirect Calorimetry in Patients with Sepsis-Possibilities and Limitations.

The aim of the review was to analyse the challenges of using indirect calorimetry in patients with sepsis, including the limitations of this method. A systematic review of the literature was carried out. The analysis concerned the methodology and presentation of research results. In most studies assessing energy expenditure, energy expenditure was expressed in kcal per day (n = 9) and as the mean and standard deviation (n = 7). Most authors provided a detailed measurement protocol, including measurement duration (n = 10) and device calibration information (n = 7). Ten papers provided information on the day of hospitalisation when the measurements were obtained, nine on patient nutrition, and twelve on the criteria for inclusion and exclusion of participants from the study. Small study group sizes and study at a single centre were among the most cited limitations. Studies assessing energy expenditure in patients with sepsis by indirect calorimetry differ in the methodology and presentation of results, and their collective analysis is difficult. A meta-analysis of the results could enable multi-site and large patient evaluation. Standardisation of protocols and presentation of all collected data would enable their meta-analysis, which would help to achieve greater knowledge about metabolism in sepsis.