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Peter G. Breithaupt, Rachel C. Colley and Kristi B. Adamo

The aim of the current study was to investigate the relationship between the Oxygen Uptake Efficiency Slope (OUES) and traditional measures of cardiorespiratory function in an overweight/obese pediatric sample. Maximal treadmill exercise testing with indirect calorimetry was completed on 56 obese children aged 7–18 years. Maximal OUES, submaximal OUES, VO2peak, VEpeak, and ventilatory threshold (VT) were determined. In line with comparable research in healthy-weight samples, maximal and submaximal OUES were both correlated with VO2peak, VEpeak, and VT (r2= 0.44−0.91) in the obese pediatric sample. Correlations were also found with anthropometric variables, including height (cm), body surface area (m2), body mass (kg), and fat free mass (kg). In comparing our data to a published sample of healthy weight children, maximal and submaximal exercise OUES were both higher in our obese sample. However, when we adjusted for any of body mass (kg), BSA (m2), or FFM (kg) the obese children were found to be less efficient. The results of this study suggest the use of OUES to be an appropriate measure of efficiency of ventilation and cardiorespiratory function in obese children, while also showing that our sample of obese children were less efficient on a per kilogram basis when compared with their healthy weight peers.

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W. Daniel Schmidt, Gerald C. Hyner, Roseann M. Lyle, Donald Corrigan, Gerald Bottoms and Christopher L. Melby

This study examined resting metabolic rate (RMR) and thermic effect of a meal (TEM) among athletes who had participated in long-term anaerobic or aerobic exercise. Nine collegiate wrestlers were matched for age, weight, and fat-free weight with 9 collegiate swimmers. Preliminary testing included maximal oxygen consumption, maximal anaerobic capacity (MAnC) for both the arms and the legs, and percent body fat. On two separate occasions, RMR and TEM were measured using indirect calorimetry. VO2max was significantly higher in the swimmers while MAnC was significantly higher in the wrestlers for both the arms and the legs. RMR adjusted for fat-free weight was not significantly different between groups. The differences in total and percentage of TEM between the groups were not statistically significant, and there were no differences in baseline thyroid hormones. These data suggest that despite significant differences in VO2max and WAnT values following long-term aerobic and anaerobic exercise training, resting energy expenditure does not differ between these college athletes.

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Sofiya Alhassan, Kate Lyden, Cheryl Howe, Sarah Kozey Keadle, Ogechi Nwaokelemeh and Patty S. Freedson

This study examined the validity of commonly used regression equations for the Actigraph and Actical accelerometers in predicting energy expenditure (EE) in children and adolescents. Sixty healthy (8–16 yrs) participants completed four treadmill (TM) and five self-paced activities of daily living (ADL). Four Actigraph (AG) and three Actical (AC) regression equations were used to estimate EE. Bias (±95% CI) and root mean squared errors were used to assess the validity of the regression equations compared with indirect calorimetry. For children, the Freedson (AG) model accurately predicted EE for all activities combined and the Treuth (AG) model accurately predicted EE for TM activities. For adolescents, the Freedson model accurately predicted EE for TM activities and the Treuth model accurately predicted EE for all activities and for TM activities. No other equation accurately estimated EE. The percent agreement for the AG and AC equations were better for light and vigorous compared with moderate intensity activities. The Trost (AG) equation most accurately classified all activity intensity categories. Overall, equations yield inconsistent point estimates of EE.

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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.

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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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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.