We examined the acute effect of cold-water temperature on post-exercise energy intake (EI) for 1 h. In a randomized, crossover design, 11 men (25.6 ± 5 y) exercised for 45 min on a submersed cycle ergometer at 60 ± 2% VO2max in 33°C (neutral) and 20° (cold) water temperatures, and also rested for 45 min (control). Energy expenditure (EE) was determined using indirect calorimetry before, during, and after each condition. Following exercise or rest, subjects had free access to a standard assortment of food items of known caloric value. EE was similar for the cold and neutral water conditions, averaging 505 ± 22 (± standard deviation) and 517 ± 42 kcal, respectively (P = NS). EI after the cold condition averaged 877 ± 457 kcal, 44% and 41% higher (P < 0.05) than for the neutral and resting conditions, respectively. Cold-water temperature thus stimulated post-exercise EI. Water temperature warrants consideration in aquatic programs designed for weight loss.
Lesley J. White, Rudolph H. Dressendorfer, Eric Holland, Sean C. McCoy and Michael A. Ferguson
Michael C. Riddell, Oded Bar-Or, Beatriz V. Ayub, Randolph E. Calvert and George J.F. Heigenhauser
There are currently no guidelines regarding the carbohydrate (CHO) dosage required to prevent exercise-induced hypoglycemia in children with insulin-dependent diabetes mellitus (IDDM). To prevent hypoglycemia by matching glucose ingestion with total-CHO utilization, 20 adolescents with IDDM attended 2 trials: control (CT; drinking water) and glucose (GT; drinking 6-8% glucose). Participants performed 60 min of moderate-intensity cycling 100 min after insulin injection and breakfast. CT's total-CHO utilization during exercise was determined using indirect calorimetry. In GT, participants ingested glucose in the amount equal to total CHO utilization in the CT. A total of 9 participants had BG <4.0 mmol/L in CT compared to 3 in GT (p < .05). In conclusion, glucose ingestion equal to total-CHO utilization attenuates the drop in blood glucose and reduces the likelihood of hypoglycemia during exercise in adolescents with IDDM.
Gianluca Vernillo, Aldo Savoldelli, Barbara Pellegrini and Federico Schena
The current study aimed to show the validity of a portable motion sensor, the SenseWear Armband (SWA), for the estimation of energy expenditure during pole walking. Twenty healthy adults (mean ± SD: age 30.1 ± 7.2 year, body mass 66.1 ± 10.6 kg, height 172.4 ± 8.0 cm, BMI 22.1 ± 2.4 kg·m−2) wore the armband during randomized pole walking activities at a constant speed (1.25 m·s−1) and at seven grades (0%, ±5%, ±15% and ±25%). Estimates of total energy expenditure from the armband were compared with values derived from indirect calorimetry methodology (IC) using a 2–way mixed model ANOVA (Device × Slope), correlation analyses and Bland-Altman plots. Results revealed significant main effects for device, and slope (p < .025) as well as a significant interaction (p < .001). Significant differences between IC and SWA were observed for all conditions (p < .05). SWA generally underestimate the EE values during uphill PW by 0.04 kcal·kg−1·min−1 (p < .05). Whereas, a significant overestimation has been detected during flat and downhill PW by 0.01 and 0.03 kcal·kg−1·min−1 (p < .05), respectively. The Bland-Altman plots revealed bias of the armband compared with the indirect calorimetry at any condition examined. The present data suggest that the armband is not accurate to correctly detect and estimate the energy expenditure during pole walking activities. Therefore, the observed over- and under-estimations warrants more work to improve the ability of SWA to accurately measure EE for these activities.
Chinmay Manohar, Shelly McCrady, Ioannis T. Pavlidis and James A. Levine
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.
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.
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).
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.
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.
Dac Minh Tuan Nguyen, Virgile Lecoultre, Yoshiyuki Sunami and Yves Schutz
Physical activity (PA) and related energy expenditure (EE) is often assessed by means of a single technique. Because of inherent limitations, single techniques may not allow for an accurate assessment both PA and related EE. The aim of this study was to develop a model to accurately assess common PA types and durations and thus EE in free-living conditions, combining data from global positioning system (GPS) and 2 accelerometers.
Forty-one volunteers participated in the study. First, a model was developed and adjusted to measured EE with a first group of subjects (Protocol I, n = 12) who performed 6 structured and supervised PA. Then, the model was validated over 2 experimental phases with 2 groups (n = 12 and n = 17) performing scheduled (Protocol I) and spontaneous common activities in real-life condition (Protocol II). Predicted EE was compared with actual EE as measured by portable indirect calorimetry.
In protocol I, performed PA types could be recognized with little error. The duration of each PA type could be predicted with an accuracy below 1 minute. Measured and predicted EE were strongly associated (r = .97, P < .001).
Combining GPS and 2 accelerometers allows for an accurate assessment of PA and EE in free-living situations.
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.
Benjamin J. Darter, Kathleen F. Janz, Michael L. Puthoff, Barbara Broffitt and David H. Nielsen
A new triaxial accelerometer (AMP 331) provides a novel approach to understanding free-living activity through its ability to measure real time speed, cadence, and step length. This study examined the reliability and accuracy of the AMP 331, along with construction of prediction equations for oxygen consumption and energy cost.
Young adult volunteers (n = 41) wearing two AMP units walked and ran on a treadmill with energy cost data simultaneously collected through indirect calorimetry.
Statistically significant differences exist in inter-AMP unit reliability for speed and step length and in accuracy between the AMP units and criterion measures for speed, oxygen consumption, and energy cost. However, the differences in accuracy for speed were very small during walking (≤ 0.16 km/h) and not clinically relevant. Prediction equations constructed for walking oxygen uptake and energy expenditure demonstrated R 2 between 0.76 to 0.90 and between subject deviations were 1.53 mL O2 · kg-1 · min−1 and 0.43 kcal/min.
In young adults, the AMP 331 is acceptable for monitoring walking speeds and the output can be used in predicting energy cost during walking but not running.
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.
Jennie A. Gilbert and James E. Misner
This study examined the metabolic response to a 763-kcal mixed meal at rest and during 30 min of exercise at 50% maximal oxygen consumption (