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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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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

Background:

Whether the energy cost of vinyasa yoga meets the criteria for moderate-to-vigorous physical activity has not been established.

Purpose:

To compare energy expenditure during acute bouts of vinyasa yoga and 2 walking protocols.

Methods:

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.

Results:

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).

Conclusions:

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.

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Kristin L. Osterberg and Christopher L. Melby

This study determined the effect of an intense bout of resistive exercise on postexercise oxygen consumption, resting metabolic rate, and resting fat oxidation in young women (N = 7, ages 22-35). On the morning of Day 1, resting metabolic rate (RMR) was measured by indirect calorimetry. At 13:00 hr, preexercise resting oxygen consumption was measured followed by 100 min of resistive exercise. Postexercise oxygen consumption was then measured for a 3-hr recovery period. On the following morning (Day 2), RMR was once again measured in a fasted state at 07:00. Postexercise oxygen consumption remained elevated during the entire 3-hr postexercise recovery period compared to the pre-exercise baseline. Resting metabolic rate was increased by 4.2% (p < .05) from Day 1 (morning prior to exercise: 1,419 ± 58 kcal/24 hr) compared to Day 2 (16 hr following exercise: 1,479 ± 65 kcal/24 hr). Resting fat oxidation as determined by the respiratory exchange ratio was also significantly elevated on Day 2 compared to Day 1. These results indicate that among young women, acute strenuous resistance exercise of the nature used in this study is capable of producing modest but prolonged elevations of postexercise metabolic rate and possibly fat oxidation.

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Brett R. Ely, Matthew R. Ely and Samuel N. Cheuvront

The use of caffeine supplements in athletic and military populations has increased in recent years. Excessive caffeine consumption in conjunction with exercise in a hot environment may predispose individuals to heat illness.

Purpose:

To examine heat balance induced by a large dose of caffeine during exercise in a hot environment.

Methods:

Ten men, not heat acclimated and not habitual caffeine users, consumed either caffeine (CAF; 9 mg/kg) or placebo (PLA) before performing cycle-ergometer exercise for 30 min at 50% VO2peak in a 40 °C, 25% relative humidity environment while body temperature (core and skin) and ratings of thermal comfort (TC) were monitored. Heat-exchange variables were calculated using partitional calorimetry and thermometry.

Results:

Mean body temperature (Tb) was higher (p < .05) with CAF (37.18 ± 0.15 °C) than with PLA (36.93 ± 0.15 °C) at the start of exercise. Heat production was slightly higher (~8 W, p < .05) with CAF. There were no differences in heat storage, dry heat gains, TC, or Tb during exercise.

Conclusions:

A caffeine dose of 9 mg/kg does not appreciably alter heat balance during work in a hot environment. The small increase in Tb observed with CAF was undetected by the participants and is unlikely to increase physiological strain sufficiently to affect endurance performance or risk of heat illness.

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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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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.

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Shelby L. Francis, Ajay Singhvi, Eva Tsalikian, Michael J. Tansey and Kathleen F. Janz

Purpose:

Determining fitness is important when assessing adolescents with type 1 diabetes mellitus (T1DM). Submaximal tests estimate fitness, but none have been validated in this population. This study cross-validates the Ebbeling and Nemeth equations to predict fitness (VO2max (ml/kg/min)) in adolescents with T1DM.

Methods:

Adolescents with T1DM (n = 20) completed a maximal treadmill test using indirect calorimetry. Participants completed one 4-min stage between 2.0 and 4.5 mph and 5% grade (Ebbeling/Nemeth protocol). Speed and grade were then increased until exhaustion. Predicted VO2max was calculated using the Ebbeling and Nemeth equations and compared with observed VO2max using paired t tests. Pearson correlation coefficients, 95% confidence intervals, coefficients of determination (R2), and total error (TE) were calculated.

Results:

The mean observed VO2max was 47.0 ml/kg/min (SD = 6.9); the Ebbeling and Nemeth mean predictions were 42.4 (SD = 9.4) and 43.5 ml/kg/min (SD = 6.9), respectively. Paired t tests resulted in statistically significant (p < .01) mean differences between observed and predicted VO2max for both predictions. The association between the Ebbeling prediction and observed VO2max was r = .90 (95% CI = 0.76, 0.96), R 2 = .81, and TE = 6.5 ml/kg/min. The association between the Nemeth prediction and observed VO2max was r = .81 (95% CI = 0.57, 0.92), R 2 = .66, and TE = 5.6 ml/kg/min.

Conclusion:

The Nemeth submaximal treadmill protocol provides a better estimate of fitness than the Ebbeling in adolescents with T1DM.

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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.

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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.

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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.