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Sarah Kozey, Kate Lyden, John Staudenmayer and Patty Freedson

Purpose:

To compare intensity misclassification and activity MET values using measured RMR (measMET) compared with 3.5 ml·kg−1·min−1 (standMET) and corrected METs [corrMET = mean standMET × (3.5 ÷ Harris-Benedict RMR)] in subgroups.

Methods:

RMR was measured for 252 subjects following a 4-hr fast and before completion of 11 activities. VO2 was measured during activity using indirect calorimetry (n = 2555 activities). Subjects were classified by BMI category (normal-weight or overweight/obese), sex, age (decade 20, 30, 40, or 50 y), and fitness quintiles (low to high). Activities were classified into low, moderate, and vigorous intensity categories.

Results:

The (mean ± SD) measMET was 6.1 ± 2.64 METs. StandMET [mean (95% CI)] was (0.51(0.42, 0.59) METs) less than measMET. CorrMET was not statistically different from measMET (−0.02 (−0.11, 0.06) METs). 12.2% of the activities were misclassified using standMETs compared with an 8.6% misclassification rate for METs based on predicted RMR (P < .0001). StandMET differences and misclassification rates were highest for low fit, overweight, and older individuals while there were no differences when corrMETs were used.

Conclusion:

Using 3.5 ml·kg−1·min−1 to calculate activity METs causes higher misclassification of activities and inaccurate point estimates of METs than a corrected baseline which considers individual height, weight, and age. These errors disproportionally impact subgroups of the population with the lowest activity levels.

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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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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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Benjamin J. Darter, Kathleen F. Janz, Michael L. Puthoff, Barbara Broffitt and David H. Nielsen

Background:

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.

Methods:

Young adult volunteers (n = 41) wearing two AMP units walked and ran on a treadmill with energy cost data simultaneously collected through indirect calorimetry.

Results:

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.

Conclusions:

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.

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Barbara E. Ainsworth, Robert G. McMurray and Susan K. Veazey

The purpose of this study was to determine the accuracy of two submaximal exercise tests, the Sitting-Chair Step Test (Smith & Gilligan. 1983) and the Modified Step Test (Amundsen, DeVahl, & Ellingham, 1989) to predict peak oxygen uptake (VO2 peak) in 28 adults ages 60 to 85 years. VO2 peak was measured by indirect calorimetry during a treadmill maximal graded exercise test (VO2 peak, range 11.6–31.1 ml · kg −l · min−1). In each of the submaximal tests, VO2 was predicted by plotting stage-by-stage submaximal heart rate (HR) and perceived exertion (RPE) data against VO2 for each stage and extrapolating the data to respective age-predicted maximal HR or RPE values. In the Sitting-Chair Step Test (n = 23), no significant differences were observed between measured and predicted VO2 peak values (p > .05). However, predicted VO2 peak values from the HR were 4.3 ml · kg−1 · min−1 higher than VO2 peak values predicted from the RPE data (p < .05). In the Modified Step Test (n = 22), no significant differences were observed between measured and predicted VO2 peak values (p > .05). Predictive accuracy was modest, explaining 49–78% of the variance in VO2 peak. These data suggest that the Sitting-Chair Step Test and the Modified Step Test have moderate validity in predicting VO2 peak in older men and women.

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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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Christopher L. Melby, Kristen L. Osterberg, Alyssa Resch, Brenda Davy, Susan Johnson and Kevin Davy

Thirteen physically active, eumenorrheic, normal-weight (BMI ≤ 25 kg/m2) females, aged 18–30 years, completed 4 experimental conditions, with the order based on a Latin Square Design: (a) CHO/Ex: moderate-intensity exer-· cise (65% V̇O2peak) with a net energy cost of ~500 kcals, during which time the subject consumed a carbohydrate beverage (45 g CHO) at specific time intervals; (b) CHO/NoEx: a period of time identical to (a) but with subjects consuming the carbohydrate while sitting quietly rather than exercising; (c) NoCHO/ Ex: same exercise protocol as condition (a) during which time subjects consumed a non-caloric placebo beverage; and (d) NoCHO/NoEx: same as the no-exercise condition (b) but with subjects consuming a non-caloric placebo beverage. Energy expenditure, and fat and carbohydrate oxidation rates for the entire exercise/sitting period plus a 90-min recovery period were determined by continuous indirect calorimetry. Following recovery, subjects ate ad libitum amounts of food from a buffet and were asked to record dietary intake during the remainder of the day. Total fat oxidation (exercise plus recovery) was attenuated by carbohydrate compared to placebo ingestion by only ~4.5 g. There was a trend (p = .08) for a carbohydrate effect on buffet energy intake such that the CHO/Ex and CHO/NoEx energy intakes were lower than the NoCHO/Ex and NoCHO/NoEx energy intakes, respectively (mean for CHO conditions: 683 kcal; NoCHO conditions: 777 kcal). Average total energy intake (buffet plus remainder of the day) was significantly lower (p < .05) following the conditions when carbohydrate was consumed (CHO/Ex = 1470 kcal; CHO/NoEx = 1285 kcal) compared to the noncaloric placebo (NoCHO/Ex =1767 kcal; NoCHO/ NoEx = 1660 kcal). In conclusion, in young women engaging in regular exercise, ingestion of 45 g of carbohydrate during exercise only modestly suppresses total fat oxidation during exercise. Furthermore, the ingestion of carbohydrate with or without exercise resulted in a lower energy intake for the remainder of the day

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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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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.