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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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Dennis van Hamont, Christopher R. Harvey, Denis Massicotte, Russell Frew, François Peronnet and Nancy J. Rehrer

Effects of feeding glucose on substrate metabolism during cycling were studied. Trained (60.0 ± 1.9 mL · kg−1 · min−1) males (N = 5) completed two 75 min, 80% VO2max trials: 125 g 13C-glucose (CHO); 13C-glucose tracer, 10 g (C). During warm-up (30 min 30% VO2max) 2 ⋅ 2 g 13C-glucose was given as bicarbonate pool primer. Breath samples and blood glucose were analyzed for 13C/ 12C with IRMS. Protein oxidation was estimated from urine and sweat urea. Indirect calorimetry (protein corrected) and 13C/ 12C enrichment in expired CO2 and blood glucose allowed exogenous (Gexo), endogenous (Gendo), muscle (Gmuscle), and liver glucose oxidation calculations. During exercise (75 min) in CHO versus C (respectively): protein oxidation was lower (6.8 ± 2.7, 18.8 ± 5.9 g; P = 0.01); Gendo was reduced (71.2 ± 3.8, 80.7 ± 5.7%; P = 0.01); Gmuscle was reduced (55.3 ± 6.1, 65.9 ± 6.0%; P = 0.01) compensated by increased Gexo (58.3 ± 2.1, 3.87 ± 0.85 g; P = 0.000002). Glucose ingestion during exercise can spare endogenous protein and carbohydrate, in fed cyclists, without gly-cogen depletion.

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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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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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Lance Ratcliff, Sareen S. Gropper, B. Douglas White, David M. Shannon and Kevin W. Huggins

This study compared type of habitual exercise and meal form on diet-induced thermogenesis (DIT) in 29 men age 19–28 yr. Resting metabolic rate (RMR) and DIT response to solid-meal (bar) vs. liquid-meal (shake) ingestion were measured via indirect calorimetry; classifications were sedentary (n = 9), endurance trained (n = 11), or resistance trained (n = 9). Height, weight, and body composition (using bioelectrical impedance) were measured for each subject. Energy expenditure was determined before and every 30 min after meal consumption for 210 min. RMR was significantly (p = .045) higher in the endurance- and resistance-trained groups. However, when expressed per kilogram fat-free mass (FFM; relative RMR), differences were not significant. Both DIT (kcal/min) and relative DIT (kcal · min−1 · kg FFM−1) significantly increased with time (p < .0001) from RMR for each meal form. There was no significant exercise-group effect on DIT or relative DIT. There was a significant (p = .012) effect of meal form on DIT; shakes elicited a higher DIT. This significant difference was not found for relative DIT. There was a significant interaction between group and meal form for DIT (p = .008) and relative DIT (p < .0001). Shakes elicited a significantly greater DIT (p = .0002) and relative DIT (p = .0001) in the resistance-trained group. In the sedentary group, relative DIT from shakes was significantly lower than from bars (p = .019). In conclusion, habitual exercise appears to increase RMR, and meal form may impart changes in relative DIT depending on exercise status.

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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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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.

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John S. Cuddy, Dustin R. Slivka, Walter S. Hailes, Charles L. Dumke and Brent C. Ruby

Purpose:

The purpose of this study was to determine the metabolic profile during the 2006 Ironman World Championship in Kailua-Kona, Hawaii.

Methods:

One recreational male triathlete completed the race in 10:40:16. Before the race, linear regression models were established from both laboratory and feld measures to estimate energy expenditure and substrate utilization. The subject was provided with an oral dose of 2H2 18O approximately 64 h before the race to calculate total energy expenditure (TEE) and water turnover with the doubly labeled water (DLW) technique. Body weight, blood sodium and hematocrit, and muscle glycogen (via muscle biopsy) were analyzed pre- and postrace.

Results:

The TEE from DLW and indirect calorimetry was similar: 37.3 MJ (8,926 kcal) and 37.8 MJ (9,029 kcal), respectively. Total body water turnover was 16.6 L, and body weight decreased 5.9 kg. Hematocrit increased from 46 to 51% PCV. Muscle glycogen decreased from 152 to 48 mmoL/kg wet weight pre- to postrace.

Conclusion:

These data demonstrate the unique physiological demands of the Ironman World Championship and should be considered by athletes and coaches to prepare sufficient nutritional and hydration plans.

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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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Seth A. Creasy, Renee J. Rogers, Thomas D. Byard, Robert J. Kowalsky and John M. Jakicic

Background:

Identifying strategies to increase energy expenditure (EE) may help combat the harmful effects of sedentary behavior. This study examined EE during sitting, standing, and walking.

Methods:

Participants (N = 74) were randomized to 2 of the following activities: sitting using a laptop computer (SIT-C), sitting watching television (SIT-T), standing watching television (STAND), and walking at a self-selected pace ≤3.0 (mph) (WALK). Each activity lasted 15 minutes with a 3-minute transition period between activities. The experimental conditions were: SIT-C to STAND (N = 18), SIT-T to WALK (N = 18), STAND to SIT-C (N = 20), and WALK to SIT-T (N = 18). EE was measured using indirect calorimetry.

Results:

Based on the first activity performed, EE during WALK (55.92 ± 14.19 kcal) was significantly greater than SIT-C (19.63 ± 6.90 kcal), SIT-T (18.66 ± 4.01 kcal), and STAND (21.92 ± 5.08 kcal) (P < .001). Cumulative EE in SIT-T to WALK (74.50 ± 17.88 kcal) and WALK to SIT-T (82.72 ± 21.70 kcal) was significantly greater than EE in SIT-C to STAND (45.38 ± 14.78 kcal) and STAND to SIT-C (45.64 ± 9.69 kcal) (P < .001).

Conclusions:

Conclusion: Substituting periods of sitting or standing with walking significantly increases EE, but substituting periods of sitting with standing may not affect EE. Thus, the potential benefits of standing as opposed to sitting need further investigation beyond the role of EE.