Introduction: It has been suggested that physical education (PE) can make a meaningful contribution to children's physical activity (PA) levels. The amount of moderate-to-vigorous physical activity (MVPA) in PE has been quantified in various manners, including heart rate monitoring and direct observation (Fairclough & Stratton, 2005). However, data on the contribution of PE to total PA is scarce, and PE's contribution to total physical activity energy expenditure (PAEE) has to our knowledge never been determined. This is probably explained by the methodological complexity of determining PAEE (Welk, 2002). However, the fairly recent emergence of combined sensing methodology allows for low-invasive measurement of PAEE in free-living conditions. In this paper, we present the first data of an ongoing study using combined heart rate monitoring and accelerometry, together with activity diaries. We assessed the contribution of PE and other school-related activity to PAEE and MVPA. Methods: Nineteen secondary school students (16 ± 0,7 yrs, BMI 22 ± 4) were included after they and their parents had consented. All had 100 minutes of scheduled PE per week. Actiheart monitors (CamNtech, Cambridge, UK) were used to determine PAEE on four weekdays and two weekend days consecutively. Actiheart monitors combine a heart rate monitor and an uniaxial accelerometer in a single 10 gram unit, that is applied to the chest with electrodes. Using a step test, an individual heart rate-energy expenditure relationship was determinded in each subject. Through a validated branched equation model (Brage, S. et al., 2007), energy expenditure was calculated. In addition, subjects kept an activity diary for the same six-day period. They recorded predefined activities including PE and active transport. These activities were then retraced to the Actiheart data by visual inspection. Results: Table 1 shows the (contribution of) PE, and school-related active transport to PAEE, while table 2 shows similar data for MVPA. Data are mean (± SD). Table 1: PAEE for PE, and active transport (AT). Table 2: MVPA for PE and active transport (AT). PAEE (KJ) % of total % of school PE 805(474) 5(4) 16(7) AT 1698(1033) 11(6) 31(11) MVPA (min) % of total % of school PE 36(19) 9(8) 22(11) AT 90(56) 20(11) 48(14) Over all six days, the physical activity level (PAL, which is total EE/Resting EE) was 1,54 ± 0,12; total MVPA was 472 min ± 179, and total PAEE 16262 KJ ± 5267. PAEE at school (4 days, including AT) was 5311 ± 3065 KJ, amounting to 34 % of total PAEE during the six measurement days. Students accumulated 179 ± 77 minutes of MVPA at school, which was 38% of total MVPA. Discussion: To our knowledge, this is the first study to present data on PE's contribution to total physical activity energy expenditure. Over the six measurement days, PE contributed 5% to total PAEE, and 16% to school-related PAEE. This was substantially less than the amount of energy expended for active transport to and from school. However, it should be noted that in the Netherlands, the vast majority of secondary school students cycle to school. And while PE was scheduled on one day per week in all of the measured students, active transport takes place on all school days. The total amount of MVPA accumulated at school was 179 minutes. With adolescent physical activity guidelines generally recommending 60 min of MVPA per day, i.e. 420 minutes per week, this means that school-related PA covered ~43% of this. PE provided 36 minutes to this total, all on one day. It could be argued that daily PE could potentially provide a substantial amount of MVPA. But with current time allocated to PE in the curriculum, its contribution to physical activity guidelines and PAEE is quite modest. The preliminary data presented here reflect a small subsample of a larger study that is still in progress. Therefore, care should be taken not to interpret these outcomes as representative for the whole of the Netherlands. However, they do provide a first indication for the order of magnitude of the contribution of PE and school-related activity to total PAEE. References: Fairclough, S. J. & Stratton, G. (2005) Physical Activity Levels in Middle and High School Physical Education: A Review. Pediatric Exercise Science, 17, 217. Welk, G. J. (2002) Physical activity assessments for health-related research, Champaign, Ill.; United States, Human Kinetics. Brage, S., Ekelund, U., Brage, N. Hennings, M.A., Froberg, K., Franks, P.W., Wareham. N.J. (2007). Hierarchy of individual calibration levels for heart rate and accelerometry to measure physical activity. J Appl Physiol, 103, (682-692)
Rationale: It is well established that resting energy expenditure (REE) decreases with age. Data derived from indirect calorimetry (IC) are still limited with respect to the number of high aged individuals, BMI groups and health conditions. Therefore, IC generated REE of the BASAROT sample and those calculated according to the Harris-Benedict (HB) equation were used to re-evaluate the proposed association between REE and age. Methods: The IC-BASAROT sample combines the result of IC performed in 2622 individuals from 10 centers (7 Germany, 2 Italy, 1 Netherlands) done under strictly standardized conditions (e.g. at least 8h of fasting) in free-living, mostly healthy adults aged 18 to 100 years including all BMI ranges. IC was performed by canopy technique (Cosmed Quark RMR/Sensor Medics Vmax29) in 96.5% of cases and by face mask (Cosmed Fitmate) in 3.5%. Weight was measured by calibrated scales and height was determined to the nearest of 1mm. Results: REE in the total sample (BMI: 26.9±9.1 kg/m², 43.7±17.6 y) correlated more positively with body weight than with BMI (r=0.768; p<0.001 vs. r=0.571; p<0.001). Gender+body weight explained 75% of REE variance, gender+BMI 69% and gender+age only 28%. To reduce confounding by body weight we performed age-related analysis in the subgroup of women weighing 50-79 kg (n=780, BMI: 23.4±3.4 kg/m², 41.4±18.5 y) and men weighing 60-89 kg (n=500, BMI: 24.9±3.0 kg/m², 47.5±19.3 y) and compared results with REEHB (tab. 1). IC results from 18 to 100 y showed an approximately 50% lower decrease in REE than HB in women (-129 kcal/d vs. - 257 kcal/d) and in men (-200 kcal/d vs. -406 kcal/d, tab. 1). REEIC (n=1280) did not correlate with age (r=-0.042; p=0.132). In line, we observed a significant overestimation of REE by HB up to 39 y in both sexes and an underestimation in men 60 y of age and older. Conclusion: Age-related decline in REE appears to be lower than expected and might due to changes in body composition both in the younger and older generation. No indication of the often proposed systematic overestimation of HB in women was seen. Overall, findings should be considered in future models for estimating REE.
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Background & aims: Individual energy requirements of overweight and obese adults can often not be measured by indirect calorimetry, mainly due to the time-consuming procedure and the high costs. To analyze which resting energy expenditure (REE) predictive equation is the best alternative for indirect calorimetry in Belgian normal weight to morbid obese women.Methods: Predictive equations were included when based on weight, height, gender, age, fat free mass and fat mass. REE was measured with indirect calorimetry. Accuracy of equations was evaluated by the percentage of subjects predicted within 10% of REE measured, the root mean squared prediction error (RMSE) and the mean percentage difference (bias) between predicted and measured REE.Results: Twenty-seven predictive equations (of which 9 based on FFM) were included. Validation was based on 536 F (18–71 year). Most accurate and precise for the Belgian women were the Huang, Siervo, Muller (FFM), Harris–Benedict (HB), and the Mifflin equation with 71%, 71%, 70%, 69%, and 68% accurate predictions, respectively; bias −1.7, −0.5, +1.1, +2.2, and −1.8%, RMSE 168, 170, 163, 167, and 173 kcal/d. The equations of HB and Mifflin are most widely used in clinical practice and both provide accurate predictions across a wide range of BMI groups. In an already overweight group the underpredicting Mifflin equation might be preferred. Above BMI 45 kg/m2, the Siervo equation performed best, while the FAO/WHO/UNU or Schofield equation should not be used in this extremely obese group.Conclusions: In Belgian women, the original Harris–Benedict or the Mifflin equation is a reliable tool to predict REE across a wide variety of body weight (BMI 18.5–50). Estimations for the BMI range between 30 and 40 kg/m2, however, should be improved.
While the creation of an energy deficit (ED) is required for weight loss, it is well documented that actual weight loss is generally lower than what expected based on the initially imposed ED, a result of adaptive mechanisms that are oppose to initial ED to result in energy balance at a lower set-point. In addition to leading to plateauing weight loss, these adaptive responses have also been implicated in weight regain and weight cycling (add consequences). Adaptions occur both on the intake side, leading to a hyperphagic state in which food intake is favored (elevated levels of hunger, appetite, cravings etc.), as well as on the expenditure side, as adaptive thermogenesis reduces energy expenditure through compensatory reductions in resting metabolic rate (RMR), non-exercise activity expenditure (NEAT) and the thermic effect of food (TEF). Two strategies that have been utilized to improve weight loss outcomes include increasing dietary protein content and increasing energy flux during weight loss. Preliminary data from our group and others demonstrate that both approaches - especially when combined - have the capacity to reduce the hyperphagic response and attenuate reductions in energy expenditure, thereby minimizing the adaptive mechanisms implicated in plateauing weight loss, weight regain and weight cycling. Past research has largely focused on one specific component of energy balance (e.g. hunger or RMR) rather than assessing the impact of these strategies on all components of energy balance. Given that all components of energy balance are strongly connected with each other and therefore can potentially negate beneficial impacts on one specific component, the primary objective of this application is to use a comprehensive approach that integrates all components of energy balance to quantify the changes in response to a high protein and high energy flux, alone and in combination, during weight loss (Fig 1). Our central hypothesis is that a combination of high protein intake and high energy flux will be most effective at minimizing both metabolic and behavioral adaptations in several components of energy balance such that the hyperphagic state and adaptive thermogenesis are attenuated to lead to superior weight loss results and long-term weight maintenance.
Along with the rapidly growing number of disabled people participating in competitive sports, there is an increased need for (para)medical support in disability sports. Disabled athletes experience differences in body composition, metabolism, training load and habitual activity patterns compared with non-disabled athletes. Moreover, it has been suggested that the well-recognized athlete triad, and low energy availability and low bone mineral density in particular, is even a greater challenge in disabled athletes. Therefore, it is not surprising that sport nutritionists of disabled athletes have expressed an urgency for increased knowledge and insights on the nutritional demands of this group. This project aims to investigate energy expenditure, dietary intake, body composition and bone health of disabled athletes, ultimately leading to nutritional guidelines that promote health and optimal sports performance for this unique population. For this purpose, we will conduct a series of studies and implementation activities that are inter-related and build on the latest insights from sports practice, technology and science. Our international consortium is highly qualified to achieve this goal. It consists of knowledge institutes including world-leading experts in sport and nutrition research, complemented with practical insights from nutritionists working with disabled athletes and the involvement of athletes and teams through the Dutch and Norwegian Olympic committees. The international collaboration, which is a clear strength of this project, is not only focused on research, but also on the optimization of professional practice and educational activities. In this regard, the outcomes of this project will be directly available for practical use by the (para)medical staff working with disabled athletes, and will be extensively communicated to sport teams to ensure that the new insights are directly embedded into daily practice. The project outcomes will also be incorporated in educational activities for dietetics and sport and exercise students, thereby increasing knowledge of future practitioners.
Along with the rapidly growing number of disabled people participating in competitive sports, there is an increased need for (para)medical support in disability sports. Disabled athletes experience differences in body composition, metabolism, training load and habitual activity patterns compared with non-disabled athletes. Moreover, it has been suggested that the well-recognized athlete triad, and low energy availability and low bone mineral density in particular, is even a greater challenge in disabled athletes. Therefore, it is not surprising that sport nutritionists of disabled athletes have expressed an urgency for increased knowledge and insights on the nutritional demands of this group. This project aims to investigate energy expenditure, dietary intake, body composition and bone health of disabled athletes, ultimately leading to nutritional guidelines that promote health and optimal sports performance for this unique population. For this purpose, we will conduct a series of studies and implementation activities that are inter-related and build on the latest insights from sports practice, technology and science. Our international consortium is highly qualified to achieve this goal. It consists of knowledge institutes including world-leading experts in sport and nutrition research, complemented with practical insights from nutritionists working with disabled athletes and the involvement of athletes and teams through the Dutch and Norwegian Olympic committees. The international collaboration, which is a clear strength of this project, is not only focused on research, but also on the optimization of professional practice and educational activities. In this regard, the outcomes of this project will be directly available for practical use by the (para)medical staff working with disabled athletes, and will be extensively communicated to sport teams to ensure that the new insights are directly embedded into daily practice. The project outcomes will also be incorporated in educational activities for dietetics and sport and exercise students, thereby increasing knowledge of future practitioners.
