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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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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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Leslie Peacock, Allan Hewitt, David A. Rowe and Rona Sutherland

Purpose:

The study investigated (a) walking intensity (stride rate and energy expenditure) under three speed instructions; (b) associations between stride rate, age, height, and walking intensity; and (c) synchronization between stride rate and music tempo during overground walking in a population of healthy older adults.

Methods:

Twenty-nine participants completed 3 treadmill-walking trials and 3 overground-walking trials at 3 self-selected speeds. Treadmill VO2 was measured using indirect calorimetry. Stride rate and music tempo were recorded during overground-walking trials.

Results:

Mean stride rate exceeded minimum thresholds for moderate to vigorous physical activity (MVPA) under slow (111.41 ± 11.93), medium (118.17 ± 11.43), and fast (123.79 ± 11.61) instructions. A multilevel model showed that stride rate, age, and height have a significant effect (p < .01) on walking intensity.

Conclusions:

Healthy older adults achieve MVPA with stride rates that fall below published minima for MVPA. Stride rate, age, and height are significant predictors of energy expenditure in this population. Music can be a useful way to guide walking cadence.

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Akiko Sato, Yoshimitsu Shimoyama, Tomoji Ishikawa and Nobuko Murayama

The purpose of this study was to examine the effect of high-intensity physical activity during training on the biochemical status of thiamin and riboflavin in athletes. Thiamin and riboflavin concentrations in whole blood of a group of 19 athletes (6 men and 13 women) were measured during a low-intensity preparatory period and compared with measurements taken during a high-intensity training period. Additional variables measured included anthropometric characteristics, estimated energy expenditure during swim training, distance covered, resting energy expenditure obtained by indirect calorimetry, estimated energy requirement per day, and dietary intake of energy, thiamin, and riboflavin estimated from 3-day food records. For both male and female subjects, no major changes were observed in anthropometric characteristics or dietary intake, but energy expenditure during swim training per day significantly increased in the intensive-training period (496 ± 0 kcal in the preparation period compared with 995 ± 96 kcal in the intensive-training period for male subjects [p < .001] and 361 ± 27 kcal vs. 819 ± 48 kcal, respectively, for female subjects [p < .001]). Blood thiamin concentration decreased significantly during the intensive-training period compared with the preparation period (41 ± 6 ng/ml decreased to 36 ± 3 ng/ml for male subjects [p = .048], and 38 ± 10 ng/ml decreased to 31 ± 5 ng/ml for female subjects [p = .004]); however, the concentration of riboflavin was unchanged. These results suggest that intense training affects thiamin concentration, but not riboflavin concentration, in the whole blood of college swimmers.

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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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Orjan Ekblom, Gisela Nyberg, Elin Ekblom Bak, Ulf Ekelund and Claude Marcus

Background:

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.

Methods:

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.

Results:

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%.

Conclusion:

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.

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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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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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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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Claudia Ridel Juzwiak, Ciro Winckler, Daniel Paduan Joaquim, Andressa Silva and Marco Tulio de Mello

To compare basal metabolic rate (BMR) predicted by different equations with measured BMR of the Brazilian paralympic track & field team aiming to verify which of these equations is best suited for use in this group. Method: 19 male and 11 female athletes grouped according to functional classification (vision impairment-VI, limb deficiency-LD, and cerebral palsy-CP) had their BMR measured by indirect calorimetry and compared with values predicted by different equations: Cunningham, Owen, Harris-Benedict, FAO/OMS, Dietary Reference Intakes, and Mifflin. Body composition data were obtained by skinfold measurements. Results were reported as mean and standard deviation and analyzed using the Wilcoxon test and Pearson´s Correlation Coefficient. The Root Mean Squared Prediction Error (RMSPE) was calculated to identify the similarity between the estimated and predicted BMR. Results: Mean measured BMR was 25 ± 4.2, 26 ± 2.4, and 26 ± 2.7 kcal/kg of fat free mass/day for VI, LD, and CP, respectively. Owen´s equation had the best predictive performance in comparison with measured BMR for LD and CP athletes, within 104 and 125 kcal/day, while Mifflin’s equation predicted within 146 kcal/day for VI athletes. Conclusion: for this specific group of athletes the Owen and Mifflin equations provided the best predictions of BMR.