Background: Active workstations offer the potential for augmenting energy expenditure (EE) in sedentary occupations. However, comparisons of EE during pedal and treadmill desk usage at self-selected intensities are lacking. Methods: A sample of 16 adult participants (8 men and 8 women; 33.9 [7.1] y, 22.5 [2.7] kg/m2) employed in sedentary occupations had their EE measured using indirect calorimetry during 4 conditions: (1) seated rest, (2) seated typing in a traditional office chair, (3) self-paced pedaling on a pedal desk while typing, and (4) self-paced walking on a treadmill desk while typing. Results: For men and women, self-paced pedal and treadmill desk typing significantly increased EE above seated typing (pedal desk: +1.20 to 1.28 kcal/min and treadmill desk: +1.43 to 1.93 kcal/min, P < .001). In men, treadmill desk typing (3.46 [0.19] kcal/min) elicited a significantly higher mean EE than pedal desk typing (2.73 [0.21] kcal/min, P < .001). No significant difference in EE was observed between treadmill desk typing (2.68 [0.19] kcal/min) and pedal desk typing among women (2.52 [0.21] kcal/min). Conclusions: Self-paced treadmill desk usage elicited significantly higher EE than self-paced pedal desk usage in men but not in women. Both pedal and treadmill desk usage at self-selected intensities elicited approximate 2-fold increases in EE above what would typically be expected during traditional seated office work.
John M. Schuna Jr., Daniel S. Hsia, Catrine Tudor-Locke and Neil M. Johannsen
Brian R. Hunt, James D. George, Pat R. Vehrs, A. Garth Fisher and Gilbert W. Fellingham
The purpose of this study was to validate the ability of the 1-mile jog test to predict VO2max in fit teenagers. Forty-one males and 42 females performed the steady-state, submaximal jogging test on an indoor track, along with a maximal graded exercise test (GXT) on a treadmill. Open circuit calorimetry was used during the GXT to measure maximal oxygen consumption (VO2max). We generated the following age-specific prediction equation applicable to boys and girls 13–17 years old (n = 83, Radj = .88, SEE = 3.26 ml · kg−1 · min−1): VO2max = 92.91 + 6.50 × gender (0 = female, 1 = male) − 0.141 × body mass (kg) − 1.562 × jog time (min) − 0.125 × heart rate (bpm). Cross-validation results were acceptable (SEEpress = 3.44 ml · kg−1 · min−1). As a field test, the submaximal 1-mile jogging test may alleviate problems associated with pacing, motivation, discouragement, injury, and fatigue that are sometimes associated with maximal effort timed or distance run tests.
Sally A. Sherman, Renee J. Rogers, Kelliann K. Davis, Ryan L. Minster, Seth A. Creasy, Nicole C. Mullarkey, Matthew O’Dell, Patrick Donahue and John M. Jakicic
Whether the energy cost of vinyasa yoga meets the criteria for moderate-to-vigorous physical activity has not been established.
To compare energy expenditure during acute bouts of vinyasa yoga and 2 walking protocols.
Participants (20 males, 18 females) performed 60-minute sessions of vinyasa yoga (YOGA), treadmill walking at a self-selected brisk pace (SELF), and treadmill walking at a pace that matched the heart rate of the YOGA session (HR-Match). Energy expenditure was assessed via indirect calorimetry.
Energy expenditure was significantly lower in YOGA compared with HR-Match (difference = 79.5 ± 44.3 kcal; P < .001) and SELF (difference = 51.7 ± 62.6 kcal; P < .001), but not in SELF compared with HR-Match (difference = 27.8 ± 72.6 kcal; P = .054). A similar pattern was observed for metabolic equivalents (HR-Match = 4.7 ± 0.8, SELF = 4.4 ± 0.7, YOGA = 3.6 ± 0.6; P < .001). Analyses using only the initial 45 minutes from each of the sessions, which excluded the restorative component of YOGA, showed energy expenditure was significantly lower in YOGA compared with HR-Match (difference = 68.0 ± 40.1 kcal; P < .001) but not compared with SELF (difference = 15.1 ± 48.7 kcal; P = .189).
YOGA meets the criteria for moderate-intensity physical activity. Thus, YOGA may be a viable form of physical activity to achieve public health guidelines and to elicit health benefits.
Orjan Ekblom, Gisela Nyberg, Elin Ekblom Bak, Ulf Ekelund and Claude Marcus
Wrist-worn accelerometers may provide an alternative to hip-worn monitors for assessing physical activity as they are easier to wear and may thus facilitate long-term recordings. The current study aimed at a) assessing the validity of the Actiwatch (wrist-worn) for estimating energy expenditure, b) determining cut-off values for light, moderate, and vigorous activities, c) studying the comparability between the Actiwatch and the Actigraph (hip-worn), and d) assessing reliability.
For validity, indirect calorimetry was used as criterion measure. ROC-analyses were applied to identify cut-off values. Comparability was tested by simultaneously wearing of the 2 accelerometers during free-living condition. Reliability was tested in a mechanical shaker.
All-over correlation between accelerometer output and energy expenditure were found to be 0.80 (P < .001).Based on ROC-analysis, cut-off values for 1.5, 3, and 6 METs were found to be 80, 262, and 406 counts per 15 s, respectively. Energy expenditure estimates differed between the Actiwatch and the Actigraph (P < .05). The intra- and interinstrument coefficient of variation of the Actiwatch ranged between 0.72% and 8.4%.
The wrist-worn Actiwatch appears to be valid and reliable for estimating energy expenditure and physical activity intensity in children aged 8 to 10 years.
Mathieu L. Maltais, Karine Perreault, Alexandre Courchesne-Loyer, Jean-Christophe Lagacé, Razieh Barsalani and Isabelle J. Dionne
The decrease in resting energy expenditure (REE) and fat oxidation with aging is associated with an increase in fat mass (FM), and both could be prevented by exercise such as resistance training. Dairy consumption has also been shown to promote FM loss in different subpopulations and to be positively associated with fat oxidation. Therefore, we sought to determine whether resistance exercise combined with dairy supplementation could have an additive impact on FM and energy metabolism, especially in individuals with a deficit in muscle mass. Twenty-six older overweight sarcopenic men (65 ± 5 years old) were recruited for the study. They participated in 4 months of resistance exercise and were randomized into three groups for postexercise shakes (control, dairy, and nondairy isocaloric and isoprotein supplement with 375 ml and ~280 calories per shake). Body composition was measured by dual X-ray absorptiometry and REE by indirect calorimetry. Fasting glucose, insulin, leptin, inflammatory profile, and blood lipid profile were also measured. Significant decreases were observed with FM only in the dairy supplement group; no changes were observed for any other variables. To conclude, FM may decrease without changes in metabolic parameters during resistance training and dairy supplementation with no caloric restriction without having any impact on metabolic properties. More studies are warranted to explain this significant decrease in FM.
James Cameron Morehen, Warren Jeremy Bradley, Jon Clarke, Craig Twist, Catherine Hambly, John Roger Speakman, James Peter Morton and Graeme Leonard Close
Rugby League is a high-intensity collision sport competed over 80 min. Training loads are monitored to maximize recovery and assist in the design of nutritional strategies although no data are available on the total energy expenditure (TEE) of players. We therefore assessed resting metabolic rate (RMR) and TEE in six Super League players over 2 consecutive weeks in-season including one game per week. Fasted RMR was assessed followed by a baseline urine sample before oral administration of a bolus dose of hydrogen (deuterium 2H) and oxygen (18O) stable isotopes in the form of water (2H2 18O). Every 24 hr thereafter, players provided urine for analysis of TEE via DLW method. Individual training load was quantified using session rating of perceived exertion (sRPE) and data were analyzed using magnitude-based inferences. There were unclear differences in RMR between forwards and backs (7.7 ± 0.5 cf. 8.0 ± 0.3 MJ, respectively). Indirect calorimetry produced RMR values most likely lower than predictive equations (7.9 ± 0.4 cf. 9.2 ± 0.4 MJ, respectively). A most likely increase in TEE from Week 1 to 2 was observed (17.9 ± 2.1 cf. 24.2 ± 3.4 MJ) explained by a most likelyincrease in weekly sRPE (432 ± 19 cf. 555 ± 22 AU), respectively. The difference in TEE between forward and backs was unclear (21.6 ± 4.2 cf. 20.5 ± 4.9 MJ, respectively). We report greater TEE than previously reported in rugby that could be explained by the ability of DLW to account for all match and training-related activities that contributes to TEE.
Jeanne F. Nichols, Hilary Aralis, Sonia Garcia Merino, Michelle T. Barrack, Lindsay Stalker-Fader and Mitchell J. Rauh
There is a growing need to accurately assess exercise energy expenditure (EEE) in athletic populations that may be at risk for health disorders because of an imbalance between energy intake and energy expenditure. The Actiheart combines heart rate and uniaxial accelerometry to estimate energy expenditure above rest. The authors’ purpose was to determine the utility of the Actiheart for predicting EEE in female adolescent runners (N = 39, age 15.7 ± 1.1 yr). EEE was measured by indirect calorimetry and predicted by the Actiheart during three 8-min stages of treadmill running at individualized velocities corresponding to each runner’s training, including recovery, tempo, and 5-km-race pace. Repeated-measures ANOVA with Bonferroni post hoc comparisons across the 3 running stages indicated that the Actiheart was sensitive to changes in intensity (p < .01), but accelerometer output tended to plateau at race pace. Pairwise comparisons of the mean difference between Actiheart- and criterion-measured EEE yielded values of 0.0436, 0.0539, and 0.0753 kcal · kg−1 · min−1 during recovery, tempo, and race pace, respectively (p < .0001). Bland–Altman plots indicated that the Actiheart consistently underestimated EEE except in 1 runner’s recovery bout. A linear mixed-model regression analysis with height as a covariate provided an improved EEE prediction model, with the overall standard error of the estimate for the 3 speeds reduced to 0.0101 kcal · kg−1 · min−1. Using the manufacturer’s equation that combines heart rate and uniaxial motion, the Actiheart may have limited use in accurately assessing EEE, and therefore energy availability, in young, female competitive runners.
Steven Gastinger, Guillaume Nicolas, Anthony Sorel, Hamid Sefati and Jacques Prioux
The aim of this article was to compare 2 portable devices (a heart-rate monitor and an electromagnetic-coil system) that evaluate 2 different physiological parameters—heart rate (HR) and ventilation (VE)—with the objective of estimating energy expenditure (EE). The authors set out to prove that VE is a more pertinent setting than HR to estimate EE during light to moderate activities (sitting and standing at rest and walking at 4, 5, and 6 km/hr). Eleven healthy men were recruited to take part in this study (27.6 ± 5.4 yr, 73.7 ± 9.7 kg). The authors determined the relationships between HR and EE and between VE and EE during light to moderate activities. They compared EE measured by indirect calorimetry (EEREF) with EE estimated by HR monitor (EEHR) and EE estimated by electromagnetic coils (EEMAG) in upright sitting and standing positions and during walking exercises. They compared EEREF with EEHR and EEMAG. The results showed no significant difference between the values of EEREF and EEMAG. However, they showed several significant differences between the values of EEREF and EEHR (for standing at rest and walking at 5 and 6 km/hr). These results showed that the electromagnetic-coil system seems to be more accurate than the HR monitor to estimate EE at rest and during exercise. Taking into consideration these results, it would be interesting to associate the parameters VE and HR to estimate EE. Furthermore, a new version of the electromagnetic-coil device was recently developed and provides the possibility to perform measurement under daily life conditions.
Christopher L. Melby, Kristen L. Osterberg, Alyssa Resch, Brenda Davy, Susan Johnson and Kevin Davy
Thirteen physically active, eumenorrheic, normal-weight (BMI ≤ 25 kg/m2) females, aged 18–30 years, completed 4 experimental conditions, with the order based on a Latin Square Design: (a) CHO/Ex: moderate-intensity exer-· cise (65% V̇O2peak) with a net energy cost of ~500 kcals, during which time the subject consumed a carbohydrate beverage (45 g CHO) at specific time intervals; (b) CHO/NoEx: a period of time identical to (a) but with subjects consuming the carbohydrate while sitting quietly rather than exercising; (c) NoCHO/ Ex: same exercise protocol as condition (a) during which time subjects consumed a non-caloric placebo beverage; and (d) NoCHO/NoEx: same as the no-exercise condition (b) but with subjects consuming a non-caloric placebo beverage. Energy expenditure, and fat and carbohydrate oxidation rates for the entire exercise/sitting period plus a 90-min recovery period were determined by continuous indirect calorimetry. Following recovery, subjects ate ad libitum amounts of food from a buffet and were asked to record dietary intake during the remainder of the day. Total fat oxidation (exercise plus recovery) was attenuated by carbohydrate compared to placebo ingestion by only ~4.5 g. There was a trend (p = .08) for a carbohydrate effect on buffet energy intake such that the CHO/Ex and CHO/NoEx energy intakes were lower than the NoCHO/Ex and NoCHO/NoEx energy intakes, respectively (mean for CHO conditions: 683 kcal; NoCHO conditions: 777 kcal). Average total energy intake (buffet plus remainder of the day) was significantly lower (p < .05) following the conditions when carbohydrate was consumed (CHO/Ex = 1470 kcal; CHO/NoEx = 1285 kcal) compared to the noncaloric placebo (NoCHO/Ex =1767 kcal; NoCHO/ NoEx = 1660 kcal). In conclusion, in young women engaging in regular exercise, ingestion of 45 g of carbohydrate during exercise only modestly suppresses total fat oxidation during exercise. Furthermore, the ingestion of carbohydrate with or without exercise resulted in a lower energy intake for the remainder of the day
Alexander H.K. Montoye, Jordana Dahmen, Nigel Campbell and Christopher P. Connolly
Purpose: This purpose of this study was to validate consumer-based and research-grade PA monitors for step counting and Calorie expenditure during treadmill walking. Methods: Participants (n = 40, 24 in second trimester and 16 in third trimester) completed five 2-minute walking activities (1.5–3.5 miles/hour in 0.5 mile/hour increments) while wearing five PA monitors (right hip: ActiGraph Link [AG]; left hip: Omron HJ-720 [OM]; left front pants pocket: New Lifestyles NL 2000 [NL]; non-dominant wrist: Fitbit Flex [FF]; right ankle: StepWatch [SW]). Mean absolute percent error (MAPE) was used to determine device accuracy for step counting (all monitors) and Calorie expenditure (AG with Freedson equations and FF) compared to criterion measures (hand tally for steps, indirect Calorimetry for Calories). Results: For step counting, the SW had MAPE ≤ 10% at all walking speeds, and the OM and NL had MAPE ≤ 10% for all speeds but 1.5 miles/hour. The AG had MAPE ≤ 10% for only 3.0–3.5 miles/hour speeds, and the FF had high MAPE for all speeds. For Calories, the FF and AG had MAPE > 10% for all speeds, with the FF overestimating Calories expended. Trimester did not affect PA monitor accuracy for step counting but did affect accuracy for Calorie expenditure. Conclusion: The ankle-worn SW and hip-worn OM had high accuracy for measuring step counts at all treadmill walking speeds, whereas the NL had high accuracy for speeds ≥2.0 miles/hour. Conversely, the monitors tested for Calorie expenditure have poor accuracy and should be interpreted cautiously for walking behavior.