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Gianluca Vernillo, Aldo Savoldelli, Barbara Pellegrini and Federico Schena

Background:

Accurate assessments of physical activity and energy expenditure (EE) are needed to advance research on positive and negative graded walking.

Purpose:

To evaluate the validity of 2 SenseWear Armband monitors (Pro3 and the recently released Mini) during graded walking.

Methods:

Twenty healthy adults wore both monitors during randomized walking activities on a motorized treadmill at 7 grades (0%, ±5%, ±15%, and ±25%). Estimates of total EE from the monitors were computed using different algorithms and compared with values derived from indirect calorimetry methodology using a 2-way mixed model ANOVA (Device × Condition), correlation analyses and Bland-Altman plots.

Results:

There was no significant difference in EE between the 2 armbands in any of the conditions examined. Significant main effects for device and condition, as well as a consistent bias, were observed during positive and negative graded walking with a greater over- and under-estimation at higher slope.

Conclusions:

Both the armbands produced similar EE values and seem to be not accurate in estimation of EE during activities involving uphill and downhill walking. Additional work is needed to understand factors contributing to this discrepancy and to improve the ability of these monitors to accurately measure EE during graded walking.

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Chinmay Manohar, Shelly McCrady, Ioannis T. Pavlidis and James A. Levine

Background:

Physical activity is important in ill-health. Inexpensive, accurate and precise devices could help assess daily activity. We integrated novel activity-sensing technology into an earpiece used with portable music-players and phones; the physical-activity-sensing earpiece (PASE). Here we examined whether the PASE could accurately and precisely detect physical activity and measure its intensity and thence predict energy expenditure.

Methods:

Experiment 1: 18 subjects wore PASE with different body postures and during graded walking. Energy expenditure was measured using indirect calorimetry. Experiment 2: 8 subjects wore the earpiece and walked a known distance. Experiment 3: 8 subjects wore the earpiece and ‘jogged’ at 3.5mph.

Results:

The earpiece correctly distinguished lying from sitting/standing and distinguished standing still from walking (76/76 cases). PASE output showed excellent sequential increases with increased in walking velocity and energy expenditure (r 2 > .9). The PASE prediction of free-living walking velocity was, 2.5 ± (SD) 0.18 mph c.f. actual velocity, 2.5 ± 0.16 mph. The earpiece successfully distinguished walking at 3.5 mph from ‘jogging’ at the same velocity (P < .001).

Conclusions:

The subjects tolerated the earpiece well and were comfortable wearing it. The PASE can therefore be used to reliably monitor free-living physical activity and its associated energy expenditure.

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Joel D. Reece, Vaughn Barry, Dana K. Fuller and Jennifer Caputo

Background:

This study determined the validity and sensitivity of the SenseWear armband (SWA) during sedentary and light office duties compared with indirect calorimetry (IC).

Methods:

Participants (N = 22), 30 to 64 years of age, randomly performed 6 conditions for 5 minutes each (ie, supine, sitting no movement, standing no movement, sitting office work, standing office work, walking at 1.0 mph). Steady state for each activity (ie, average for minutes 4 and 5) was analyzed.

Results:

Energy expenditure (EE) for the SWA (1.58 kcal/min) and the IC (1.64 kcal/min) were significantly correlated, r(20) = 0.90, P < .001 and ICC = 0.90, 95% CI (0.699, 0.966). Correlation results for each condition varied in strength, r(20) = 0.53 to 0.83 and ICC = 0.49 to 0.81, but were all significant (P < .05). A significant interaction between measurement method and condition existed (P < .001). The SWA under predicted EE during standing with no movement, sitting office work, and standing office work.

Conclusion:

The SWA and IC EE rates were strongly correlated during sedentary and light activity office behaviors. However, the SWA may under predict EE during office work (standing or sitting) and when standing motionless, making it slightly less sensitive than IC.

Open access

Alison L. Innerd and Liane B. Azevedo

Background:

The aim of this study is to establish the energy expenditure (EE) of a range of child-relevant activities and to compare different methods of estimating activity MET.

Methods:

27 children (17 boys) aged 9 to 11 years participated. Participants were randomly assigned to 1 of 2 routines of 6 activities ranging from sedentary to vigorous intensity. Indirect calorimetry was used to estimate resting and physical activity EE. Activity metabolic equivalent (MET) was determined using individual resting metabolic rate (RMR), the Harrell-MET and the Schofield equation.

Results:

Activity EE ranges from 123.7± 35.7 J/min/Kg (playing cards) to 823.1 ± 177.8 J/min/kg (basketball). Individual RMR, the Harrell-MET and the Schofield equation MET prediction were relatively similar at light and moderate but not at vigorous intensity. Schofield equation provided a better comparison with the Compendium of Energy Expenditure for Youth.

Conclusion:

This information might be advantageous to support the development of a new Compendium of Energy Expenditure for Youth.

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Meredith C. Peddie, Claire Cameron, Nancy Rehrer and Tracy Perry

Background:

Interrupting sedentary time induces improvements in glucose metabolism; however, it is unclear how much activity is required to reduce the negative effects of prolonged sitting.

Methods:

Sixty-six participants sat continuously for 9 hours except for required bathroom breaks. Participants were fed meal replacement beverages at 60, 240 and 420 min. Blood samples were obtained hourly for 9 hours, with additional samples collected 30 and 45 min after each feeding. Responses were calculated as incremental area under the curve (iAUC) for plasma glucose, insulin and triglyceride. Participants wore a triaxial accelerometer and a heart rate monitor. Energy expenditure was estimated using indirect calorimetry.

Results:

After controlling for age, sex and BMI, every 100 count increase in accelerometer derived total movement was associated with a 0.06 mmol·L-1·9 hours decrease in glucose iAUC (95% CI 0.004–0.1; P = .035), but not associated with changes in insulin or triglyceride iAUC. Every 1 bpm increase in mean heart rate was associated with a 0.76 mmol·L-1·9 hours increase in triglyceride iAUC (95% CI 0.13–1.38).

Conclusion:

Accelerometer measured movement during periods of prolonged sitting can result in minor improvements in postprandial glucose metabolism, but not lipid metabolism.

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Daniel Arvidsson, Mark Fitch, Mark L. Hudes and Sharon E. Fleming

Background:

Overweight children show different movement patterns during walking than normal-weight children, suggesting the accuracy of multisensory activity monitors may differ in these groups.

Methods:

Eleven normal and 15 high BMI African American children walked at 2, 4, 5, and 6 km/h on a treadmill wearing the Intelligent Device for Energy Expenditure and Activity (IDEEA) and SenseWear (SW). Accuracy was determined using indirect calorimetry and manually counted steps as references.

Results:

For IDEEA, no significant differences in accuracy were observed between BMI groups for energy expenditure (EE), but differences were significant by speed (+15% at 2 km/h to −10% at 6 km/h). For SW, EE accuracy was significantly different for high (+21%) versus normal BMI girls (−13%) at 2 km/h. For high BMI girls, EE was overestimated at low speed and underestimated at higher speeds. Underestimations in steps did not differ by BMI group at 4 to 6 km/h, but were significantly larger at 2 km/h than at the other speeds for all groups with IDEEA, and for normal BMI children with SW.

Conclusions:

Similar accuracies during walking may be expected in normal and overweight children using IDEEA and SW. Both monitors showed small errors for steps provided speed exceeded 2 km/h.

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Scott A. Conger, Stacy N. Scott, Eugene C. Fitzhugh, Dixie L. Thompson and David R. Bassett

Background:

It is unknown if activity monitors can detect the increased energy expenditure (EE) of wheelchair propulsion at different speeds or on different surfaces.

Methods:

Individuals who used manual wheelchairs (n = 14) performed 5 wheeling activities: on a level surface at 3 speeds, on a rubberized track at 1 fixed speed and on a sidewalk course at a self-selected speed. EE was measured using a portable indirect calorimetry system and estimated by an Actical (AC) worn on the wrist and a SenseWear (SW) activity monitor worn on the upper arm. Repeated-measures ANOVA was used to compare measured EE to the estimates from the standard AC prediction equation and SW using 2 different equations.

Results:

Repeated-measures ANOVA demonstrated a significant main effect between measured EE and estimated EE. There were no differences between the criterion method and the AC across the 5 activities. The SW overestimated EE when wheeling at 3 speeds on a level surface, and during sidewalk wheeling. The wheelchair-specific SW equation improved the EE prediction during low intensity activities, but error progressively increased during higher intensity activities.

Conclusions:

During manual wheelchair propulsion, the wrist-mounted AC provided valid estimates of EE, whereas the SW tended to overestimate EE.

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Samantha Stephens, Tim Takken, Dale W. Esliger, Eleanor Pullenayegum, Joseph Beyene, Mark Tremblay, Jane Schneiderman, Doug Biggar, Pat Longmuir, Brian McCrindle, Audrey Abad, Dan Ignas, Janjaap Van Der Net and Brian Feldman

The purpose of this study was to assess the criterion validity of existing accelerometer-based energy expenditure (EE) prediction equations among children with chronic conditions, and to develop new prediction equations. Children with congenital heart disease (CHD), cystic fibrosis (CF), dermatomyositis (JDM), juvenile arthritis (JA), inherited muscle disease (IMD), and hemophilia (HE) completed 7 tasks while EE was measured using indirect calorimetry with counts determined by accelerometer. Agreement between predicted EE and measured EE was assessed. Disease-specific equations and cut points were developed and cross-validated. In total, 196 subjects participated. One participant dropped out before testing due to time constraints, while 15 CHD, 32 CF, 31 JDM, 31 JA, 30 IMD, 28 HE, and 29 healthy controls completed the study. Agreement between predicted and measured EE varied across disease group and ranged from (ICC) .13–.46. Disease-specific prediction equations exhibited a range of results (ICC .62–.88) (SE 0.45–0.78). In conclusion, poor agreement was demonstrated using current prediction equations in children with chronic conditions. Disease-specific equations and cut points were developed.

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Steven K. Malin, Brooke R. Stephens, Carrie G. Sharoff, Todd A. Hagobian, Stuart R. Chipkin and Barry Braun

Exercise and metformin may prevent or delay Type 2 diabetes by, in part, raising the capacity for fat oxidation. Whether the addition of metformin has additive effects on fat oxidation during and after exercise is unknown. Therefore, the purpose of this study was to evaluate the effect of metformin on substrate oxidation during and after exercise. Using a double-blind, counter-balanced crossover design, substrate oxidation was assessed by indirect calorimetry in 15 individuals taking metformin (2,000 mg/d) and placebo for 8–10 d. Measurements were made during cycle exercise at 5 submaximal cycle workloads, starting at 30% peak work (Wpeak) and increasing by 10% every 8 min to 70% Wpeak. Substrate oxidation was also measured for 50 min postexercise. Differences between conditions were assessed using analysis of variance with repeated measures, and values are reported as M ± SE. During exercise, fat oxidation (0.19 ± 0.03 vs. 0.15 ± 0.01 g/min, p < .01) and percentage of energy from fat (32% ± 3% vs. 28% ± 3%, p < .01) were higher with metformin than with placebo. Postexercise, metformin slightly lowered fat oxidation (0.12 ± 0.02 to 0.10 ± 0.02 g/min, p < .01) compared with placebo. There was an inverse relationship between postexercise fat oxidation and the rate of fat oxidation during exercise (r = –.68, p < .05). In healthy individuals, metformin has opposing actions on fat oxidation during and after exercise. Whether the same effects are evident in insulin-resistant individuals remains to be determined.

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Hermann-J. Engels, John C. Wirth, Sueda Celik and Jodee L. Dorsey

This study assessed the influence of caffeine on metabolic and cardiovascular functions during sustained, light intensity cycling and at rest. Eight healthy, recreationally active adults participated in four randomly assigned, double-blind experimental trials of 60 min upright seated cycle exercise (30% VO2max) or equivalent rest with caffeine (5 mg ⋅ kg−1) or placebo consumed 60 min prior to data collection. Gas exchange was measured by open-circuit spirom-etry indirect calorimetry. Global blood flow was evaluated by thoracic impedance cardiography and arterial blood pressure by auscultation. A repeated measures ANOVA indicated that pretrial caffeine increased oxygen uptake and energy expenditure rate (p < 0.05) but did not change respiratory exchange ratio. Systolic, diastolic, and mean arterial blood pressure were elevated following caffeine intake (p < 0.05). Cardiac output, heart rate, stroke volume, and systemic vascular resistance were not significantly different between caffeine and placebo sessions. For each of the metabolic and hemodynamic variables examined, the effects of caffeine were similar during constant-load, light intensity cycling and at rest. These data illustrate that caffeine's mild thermogenic influence can be mediated without a major shift in substrate oxidation mixture. Caffeine at this dosage level alters cardiovascular dynamics by augmenting arterial blood pressure.