Assessment Of Energy Expenditure Research Articles

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.

Resting costs too: the relative importance of active and resting energy expenditure in a sub-arctic seabird.

ABSTRACTBreeding is costly for many animals, including birds that must deliver food to a central place (i.e. nest). Measuring energy expenditure throughout the breeding season can provide valuable insight into physiological limitations by highlighting periods of high demand, and ultimately allows improvement of conservation strategies. However, quantifying energy expenditure in wildlife can be challenging, as existing methods do not measure both active (e.g. foraging) and resting energy costs across short and long time scales. Here, we developed a novel method for comparing active and resting costs in 66 pre-breeding and breeding seabirds (black-legged kittiwakes, Rissa tridactyla) by combining accelerometry and triiodothyronine (T3) as proxies for active and resting costs, respectively. Active energy costs were higher during incubation (P=0.0004) and chick rearing (P<0.0001) than during pre-laying, because of an increase in the time spent in flight of 11% (P=0.0005) and 15% (P<0.0001), respectively. Levels of T3, reflecting resting costs, peaked marginally during incubation with a mean (±s.d.) concentration of 4.71±1.97 pg ml−1 in comparison to 2.66±1.30 pg ml−1 during pre-laying (P=0.05) and 3.16±2.85 pg ml−1 during chick rearing (P=0.11). Thus, although chick rearing is often assumed to be the costliest breeding stage by multiple studies, our results suggest that incubation could be more costly as a result of high resting costs. We highlight the importance of accounting for both active and resting costs when assessing energy expenditure.

POS-726 NOVEL EQUATIONS FOR ESTIMATING RESTING ENERGY EXPENDITURE IN PERITONEAL DIALYSIS PATIENTS

With the development of chronic kidney disease (CKD), the risk of protein-energy wasting is increasing. It is urgent to have a convenient method to assess energy expenditure accurately in these patients. However, besides the direct measurement, which is expensive and time-consuming, there is no resting energy expenditure (REE) equations focus on peritoneal dialysis patients. We aimed to develop and validate REE equations in peritoneal dialysis patients. This cross-sectional study enrolled 140 patients with peritoneal dialysis according to inclusion and exclusion criteria. After random sampling matched 1:1 by age, gender and dialysis duration, stepwise linear regression analysis was used to derive a new REE equation (eREEpd) according to actual REE (aREE) measured using indirect calorimetry in the development dataset. The eREEpd value was then validated with aREE in the validation dataset in terms of bias, precision, and accuracy. Bias was assessed as the difference between the estimated and measured REE values, precision was assessed as the absolute value of difference, and accuracy was assessed as the percentage of estimates that differed >20% from the measured REE (1- P20). The eREEpd equation: eREEpd (kcal) = (1 if male; 0 if female) × 144.08 − 5.8 × age (y) + 10.33 × weight (kg)+ 850.71 (R2 = 0.649). The bias, precision, and accuracy of the eREEpd equation were -11.3 (IQR: −195.7, 115.0) kcal, 22.2 (IQR:64.9, 249.3) kcal, and 20.3%, respectively with indirect calorimetry as the reference method. Besides, we found hemoglobin was an independent predictive factor of REE developed an REE equation using age, sex, weight, and hemoglobin data, as eREEpd_Hb (kcal) = (1 if male; 0 if female) × 172.16 − 4.87 × age (y) + 9.63 × weight (kg)-3.05×hemoglobin (g/L)+ 1180.04 (R2 = 0.673).The bias, precision, and accuracy (percentage of estimates that differed >20% from the measured REE) of the eREEpd_Hb equation were 31.5 (IQR: −174.3, 102.0) kcal, 120.8 (IQR:59.6, 239.2) kcal, and 18.6%, respectively with indirect calorimetry as the reference method. The REE equation using age, sex, weight with or without hemoglobin data could serve as a reliable tool for estimating REE in patients with peritoneal dialysis.

Life cycle assessment of the human energy expenditure in mobility activities

Life cycle assessment of the human energy expenditure in mobility activities

Perspective: Opportunities and Challenges of Technology Tools in Dietary and Activity Assessment: Bridging Stakeholder Viewpoints

The science and tools of measuring energy intake and output in humans have rapidly advanced in the last decade. Engineered devices such as wearables and sensors, software applications, and Web-based tools are now ubiquitous in both research and consumer environments. The assessment of energy expenditure in particular has progressed from reliance on self-report instruments to advanced technologies requiring collaboration across multiple disciplines, from optics to accelerometry. In contrast, assessing energy intake still heavily relies on self-report mechanisms. Although these tools have improved, moving from paper-based to online reporting, considerable room for refinement remains in existing tools, and great opportunities exist for novel, transformational tools, including those using spectroscopy and chemo-sensing. This report reviews the state of the science, and the opportunities and challenges in existing and emerging technologies, from the perspectives of 3 key stakeholders: researchers, users, and developers. Each stakeholder approaches these tools with unique requirements: researchers are concerned with validity, accuracy, data detail and abundance, and ethical use; users with ease of use and privacy; and developers with high adherence and utilization, intellectual property, licensing rights, and monetization. Cross-cutting concerns include frequent updating and integration of the food and nutrient databases on which assessments rely, improving accessibility and reducing disparities in use, and maintaining reliable technical assistance. These contextual challenges are discussed in terms of opportunities and further steps in the direction of personalized health.

The Use of Indirect Calorimetry in Nutrition Therapy and Its Impact on Clinical Outcomes in Critically ill Patients: A review

Adequate “nutritional support is an essential element for achieving favorable outcomes in critically ill patients, which requires an accurate evaluation of energy needs to avoid under or overfeeding.” Energy requirements of critically ill patients can be assessed either by Predictive equations (PEs) or by “indirect calorimetry(IC) measurements.” However, assessment of energy expenditure (EE) is a challenging task in intensive care unit patients” because EE during critical illness is widely variable and the current PEs are inaccurate to determine the caloric requirement in these patients.” Currently, IC is considered a gold standard for measuring EE as recommended by guidelines.” Despite being the most accurate method of measuring EE, adequate data are lacking to validate the beneficial effects of IC-guided nutrition therapy on clinical outcomes in critically ill patients. Because of this, the actual clinical benefits of IC are poorly appreciated, and it is still an underutilized tool among dietitians in clinical practice.” Therefore, in many centers, PEs are commonly used instead. The purpose of this review is to summarize the findings of recent studies regarding IC-guided nutrition therapy and its impact on clinical outcomes in critically ill patients.

Agonism and Antagonism of the Muscles of the Elbow Joint: An SEMG Approach

The relationship among the muscles of any joint such as the elbow joint reflects the range of motion energy expenditure of these muscles. It can be fairly stated that SEMG (surface electromyography) is a technology that enables the measurements of any muscle range of motion (ROM) and the synergism (agonism) and antagonism relationships among these muscles. The magnitude of the amplitude potentials of any motion of any muscle is relevant in the assessment of the total energy expenditure for any given motion in ergonomic terms and in clinical terms. The joints function best in terms of effectiveness and efficiency when any motion is performed with the least effort at the least fatigue potential. SEMG permits the measurement of the energy expenditure. Aside from the actual energy used, the relationships of any two muscles of the joint during the range of motion can be assessed in terms of correlation coefficients, thus enabling the clinician or ergonomist to evaluate the synergism or antagonism of the muscles in question for the ROM tested. Understanding the magnitude of the agonism and antagonism is highly relevant in ergonomics as well as in the process of rehabilitation of the muscles of any joint.

Excessive energy expenditure due to acute physical restraint disrupts Drosophila motivational feeding response

To study the behavior of Drosophila, it is often necessary to restrain and mount individual flies. This requires removal from food, additional handling, anesthesia, and physical restraint. We find a strong positive correlation between the length of time flies are mounted and their subsequent reflexive feeding response, where one hour of mounting is the approximate motivational equivalent to ten hours of fasting. In an attempt to explain this correlation, we rule out anesthesia side-effects, handling, additional fasting, and desiccation. We use respirometric and metabolic techniques coupled with behavioral video scoring to assess energy expenditure in mounted and free flies. We isolate a specific behavior capable of exerting large amounts of energy in mounted flies and identify it as an attempt to escape from restraint. We present a model where physical restraint leads to elevated activity and subsequent faster nutrient storage depletion among mounted flies. This ultimately further accelerates starvation and thus increases reflexive feeding response. In addition, we show that the consequences of the physical restraint profoundly alter aerobic activity, energy depletion, taste, and feeding behavior, and suggest that careful consideration is given to the time-sensitive nature of these highly significant effects when conducting behavioral, physiological or imaging experiments that require immobilization.

Physiological and Metabolic Requirements, and User-Perceived Exertion of Immersive Virtual Reality Exergaming Incorporating an Adaptive Cable Resistance System: An Exploratory Study.

Objective: To measure metabolic and physiological demand, subjective fatigue, and enjoyment during a signature 30-minute immersive virtual reality (IVR) adaptive cable resistance exergaming session. Methods: Fourteen healthy college-aged individuals (seven females) were initially acquainted with the IVR equipment and gameplay dynamics. Participants then underwent a 30-minute IVR exergaming session performing six different cable resistance exercises. A portable metabolic gas exchange analyzer concurrently assessed energy expenditure (EE) through indirect calorimetry while a chest-worn monitor captured heart rate (HR). Participants subsequently completed questionnaires, including the Borg scale for rating of perceived exertion (RPE), Physical Activity Enjoyment Scale (PACES), and Simulator Sickness Questionnaire (SSQ). Results: The mean EE, mean metabolic equivalent, and average total calories expended during the 30-minute session were 14.7 (standard deviation [SD] 2.8) kcal/minute, 12.9 (SD 0.5), and 440 (SD 84) kcals respectively. The mean HR was 176 (SD 3.1) beats per minute (bpm) with a mean max HR of 188 SD (SD 2.9) bpm. The combined training volume among all participants was 16,102 kg (SD 4137). Participants classified the IVR training session to be "somewhat hard-to-hard" with a RPE score of 14 (SD 1) while indicating the session to be "enjoyable" with a PACES score of 4.31 (SD 0.36). The participants did not report any cybersickness symptoms, demonstrating an average total SSQ score of 24.04 (SD 24.13). Conclusions: IVR exergaming incorporating cable resistance training elicits high EE and physiological demand with high enjoyment scores while attenuating perceived fatigue. The potential for IVR to elicit these acute training effects over long-term training periods warrants further investigation into its contribution to fitness and health.

Assessing Energy Expenditure in Female Healthcare Workers in a University Hospital.

The assessment of energy expenditure (EE) at workplaces maintains a central topic in occupational health due to increasing work-related issues. Today 80% of employees in the healthcare system are women. Limited research concerning their physical activity at work is available. The purpose of the study was the investigation of body composition, maximum physical capacity and quantification of physical work activity for female healthcare workers under real-time conditions. Occupational physical activity (PA) of 33 female healthcare workers in a university hospital was quantified. Health associate professionals (HAP), health professionals (HP), and females working from cleaners and helpers (CH) department participated. All underwent cardio pulmonary exercise test. For every working task VO2, VCO2 and RER were measured and EE was calculated individually for each task. Forty-two different working tasks were identified and grouped in seven categories to compare physical activity (PA): 'office and laboratory work', 'bedside patient care', 'instrument reprocessing, packing boxes', 'walking with patient, or alone', 'pushing carts or wheelchairs', 'strenuous cleaning in bent posture' and 'lifting heavy boxes, weights or items'. By comparing groups of healthcare workers, CH and HAP spent significant (p < 0.01) more EE (in kcal/min) 3.9 resp. 3.2 than HP 2.5. Light PA e.g. office and laboratory work (2.7 ± 0.6) and bedside patient care (2.9 ± 0.7) were accomplished by HP and HAP while HAP and CH performed moderate PA such as 'packing boxes' (3.6 ± 0.8), 'pushing carts' and 'strenuous cleaning' (4.7 ± 0.9). Work performed by CH and HAP, i.e. 'strenuous cleaning' and 'lifting heavy items' showed highest kcal per kg Fat Free Mass (FFM) per hour with 5.80 [4.05-7.81] and 6.94 [5.18-9.03] kcal/kgFFM/h. Our findings lend preliminary support to the hypothesis that the majority of activities in female healthcare workers were of low and moderate PA and can be accomplished by middle aged and even older female workers. CH performed tasks with heavy physical activities (PA) like cleaning and lifting heavy weights. HAP performed light/moderate PA below their maximum physical capacity.

The Assessment of Daily Energy Expenditure of Commercial Saturation Divers Using Doubly Labelled Water.

Commercial saturation divers are exposed to unique environmental conditions and are required to conduct work activity underwater. Consequently, divers’ physiological status is shown to be perturbed and therefore, appropriate strategies and guidance are required to manage the stress and adaptive response. This study aimed to evaluate the daily energy expenditure (DEE) of commercial saturation divers during a 21-day diving operation in the North Sea. Ten saturation divers were recruited during a diving operation with a living depth of 72 metres seawater (msw) and a maximum working dive depth of 81 msw. Doubly labelled water (DLW) was used to calculate DEE during a 10-day measurement period. Energy intake was also recorded during this period by maintaining a dietary log. The mean DEE calculated was 3030.9 ± 513.0 kcal/day, which was significantly greater than the mean energy intake (1875.3 ± 487.4 kcal; p = 0.005). There was also a strong positive correction correlation between DEE and total time spent performing underwater work (r = 0.7, p = 0.026). The results suggested saturation divers were in a negative energy balance during the measurement period with an intraindividual variability in the energy cost present that may be influenced by time spent underwater.