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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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Neha Singhal and Anupa Siddhu

Background:

The relationship between leisure-time physical activity (LTPA) and cardiorespiratory fitness (CRF) is not clearly understood in Indian men. It is important to elucidate whether the duration or intensity of LTPA is responsible for increasing CRF. This will help in designing better physical activity intervention strategies for improving CRF in Indian men.

Methods:

Healthy nondiabetic urban Indian men with no history of coronary heart disease (CHD) were selected (n = 603; aged 22–64 years) and their energy intake and physical activity was determined using a questionnaire. Body fat (percent) was determined by leg-to-leg bioelectrical impedance analysis while CRF was measured on multistage, continuous treadmill test using Bruce protocol.

Results:

Intensity of physical activity (METs) emerged as the best independent predictor of CRF (β = 0.217; P < .001). Using univariate General Linear Model, it was found that CRF is more a function of LTPA intensity than LTPA duration, since LTPA duration was not related to CRF when controlled for LTPA intensity. However, LTPA intensity remained significantly associated with CRF even after adjustment for LTPA duration.

Conclusion:

LTPA of preferably higher intensity should be incorporated in the lifestyle to improve CRF and prevent CHD in Indian men.

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Larry Tucker and Travis Peterson

Background:

This study was conducted to determine if cardiorespiratory fitness at baseline, and changes in fitness, influence risk of weight gain (≥3 kg) over 20 months. Another aim was to ascertain if potential confounding factors, including age, education, strength training, energy intake, and weight, influence risk of weight gain.

Methods:

In a prospective study of 257 women, fitness (VO2max) was assessed using a graded, maximal treadmill test at baseline and follow-up. Energy intake was measured using 7-day, weighed food records. Subjects were divided into quartiles based on fitness. Risk ratios were used to show the risk of weight gain among those who were fit at baseline compared with their counterparts.

Results:

Most women gained weight and 23% gained ≥3 kg. Mean VO2max was 35.7 ± 7.2 mL·kg−1·min−1. Women with low-fitness at baseline had 3.18 times (95% CI: 1.46 to 6.93) greater risk, and moderately fit women had 2.24 times (95% CI: 1.04 to 4.82) greater risk of weight gain than women in the high-fitness quartile. Adjusting for potential confounders had little effect on results.

Conclusions:

High levels of fitness seem to help protect middle-aged women against weight gain, whereas low and moderate fitness increase risk of weight gain over time.

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Jessica L. Unick, Kelley Strohacker, George D. Papandonatos, David Williams, Kevin C. O’Leary, Leah Dorfman, Katie Becofsky and Rena R. Wing

This study examined whether inactive, overweight/obese women experience consistent affective responses to moderate-intensity exercise. Twenty-eight women participated in 3 identical (same treadmill grade and speed within a subject) 30-min exercise sessions. The Feeling Scale (FS), Positive and Negative Affect Schedule and Subjective Exercise Experience Scale were administered pre- and postexercise and FS was also administered every 5 min during exercise. All measures exhibited less than optimal agreement in pre-to-postexercise change within an individual across the 3 sessions (ICCs = 0.02–0.60), even after controlling for within-subject variations in heart rate. Only FS exhibited “good” consistency when controlling for preexercise values (ICC = 0.72). However, the mean FS score during exercise was highly consistent within an individual (ICC = 0.83). Thus, an individual’s affective response to an exercise session does not provide reliable information about how they will respond to subsequent exercise sessions. Taking the average of FS measurements during exercise may yield more consistent findings.

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Stephen R. Bird, Simon C. Theakston, Andrew Owen and Alan M. Nevill

This study assessed physiological and cardiac factors associated with 10-km running performance in a group of highly trained endurance runners age 21–63 years. Participants (N = 37) underwent a resting echocardiograph and incremental treadmill running test. They also provided information on their recent 10-km races. Data were analyzed using “best subsets” multiple regression. Declines with age were found for 10-km running speed (0.26 m · s−1 · decade−1), maximum heart rate (4 beats/decade), VO2peak (6 ml · kg−1 · min−1 · decade−1), velocity at lactate threshold (1 m · s−1 · decade−1), and VO2 at lactate threshold (4 ml · kg−1 · min−1 · decade−1). The percentage of VO2peak at which lactate threshold occurred increased with age by 1.5% per decade. The rate of change of displacement of the atrioventricular plane at the left free wall and septum both declined by 1 cm · s−1 · decade−1. The best single predictor of 10-km running speed was velocity at lactate threshold.

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Jeremy A. Steeves, Brian M. Tyo, Christopher P. Connolly, Douglas A. Gregory, Nyle A. Stark and David R. Bassett

Background:

This study compared the validity of a new Omron HJ-303 piezoelectric pedometer and 2 other pedometers (Sportline Traq and Yamax SW200).

Methods:

To examine the effect of speed, 60 subjects walked on a treadmill at 2, 3, and 4 mph. Twenty subjects also ran at 6, 7, and 8 mph. To test lifestyle activities, 60 subjects performed front-back-side-side stepping, elliptical machine and stair climbing/descending. Twenty others performed ballroom dancing. Sixty participants completed 5 100-step trials while wearing 5 different sets of the devices tested device reliability. Actual steps were determined using a hand tally counter.

Results:

Significant differences existed among pedometers (P < .05). For walking, the Omron pedometers were the most valid. The Sportline overestimated and the Yamax underestimated steps (P < .05). Worn on the waist or in the backpack, the Omron device and Sportline were valid for running. The Omron was valid for 3 activities (elliptical machine, ascending and descending stairs). The Sportline overestimated all of these activities, and Yamax was only valid for descending stairs. The Omron and Yamax were both valid and reliable in the 100-step trials.

Conclusions:

The Omron HJ-303, worn on the waist, appeared to be the most valid of the 3 pedometers.

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Kate Lyden, Natalia Petruski, Stephanie Mix, John Staudenmayer and Patty Freedson

Background:

Physical activity and sedentary behavior measurement tools need to be validated in free-living settings. Direct observation (DO) may be an appropriate criterion for these studies. However, it is not known if trained observers can correctly judge the absolute intensity of free-living activities.

Purpose:

To compare DO estimates of total MET-hours and time in activity intensity categories to a criterion measure from indirect calorimetry (IC).

Methods:

Fifteen participants were directly observed on three separate days for two hours each day. During this time participants wore an Oxycon Mobile indirect calorimeter and performed any activity of their choice within the reception area of the wireless metabolic equipment. Participants were provided with a desk for sedentary activities (writing, reading, computer use) and had access to exercise equipment (treadmill, bike).

Results:

DO accurately and precisely estimated MET-hours [% bias (95% CI) = –12.7% (–16.4, –7.3), ICC = 0.98], time in low intensity activity [% bias (95% CI) = 2.1% (1.1, 3.2), ICC = 1.00] and time in moderate to vigorous intensity activity [% bias (95% CI) –4.9% (–7.4, –2.5), ICC = 1.00].

Conclusion:

This study provides evidence that DO can be used as a criterion measure of absolute intensity in free-living validation studies.

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Denise A. Baden, Lawrence Warwick-Evans and Julie Lakomy

Two studies tested the hypothesis that teleoanticipatory mechanisms regulate the perception of exertion (RPE) in the context of expected exercise duration by the adjustment of attentional focus. Study 1 involved 22 runners who participated in a short (8-mile) run and a long (10-mile) run on separate days. Pace did not differ between conditions (M = 6.3 mph). Runners reported on their attentional focus (proportion of associative to dissociative thoughts) and RPE at regular intervals. Study 2 involved 40 participants who ran twice on a treadmill at the same speed and gradient: once when they expected to run for 10 min (short condition) and once when they expected to run for 20 min (long condition). In both studies, RPE was lower throughout the long condition. In Study 1 there were more dissociative thoughts in the long condition. Study 2 showed the same trend, although the results were nonsignificant. In both studies RPE was inversely correlated with dissociative thoughts, supporting the hypothesis that runners pace themselves cognitively by manipulating their

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Ashleigh E. Smith, Roger G. Eston, Belinda Norton and Gaynor Parfitt

Peak oxygen uptake (V̇O2peak) is reliably predicted in young and middle-aged adults using a submaximal perceptually-regulated exercise test (PRET). It is unknown whether older adults can use a PRET to accurately predict V̇O2peak. In this study, the validity of a treadmill-based PRET to predict V̇O2peak was assessed in 24 participants (65.2 ± 3.9 years, 11 males). The PRET required a change in speed or incline corresponding to ratings of perceived exertion (RPE) 9, 11, 13, and 15. Extrapolation of submaximal V̇O2 from the PRET to RPE endpoints 19 and 20 and age-predicted HRmax were compared with measured V̇O2peak. The V̇O2 extrapolated to both RPE19 and 20 over-predicted V̇O2peak (p < .001). However, extrapolating V̇O2 to age-predicted HRmax accurately predicted V̇O2peak (r = .84). Results indicate older adults can use a PRET to predict V̇O2peak by extrapolating V̇O2 from submaximal intensities to an age-predicted HRmax.

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Kurusart Konharn, Wichai Eungpinichpong, Kluaymai Promdee, Paramaporn Sangpara, Settapong Nongharnpitak, Waradanai Malila and Jirachai Karawa

Background:

The suitability of smartphone applications (apps) currently used to track walking/running may differ depending on a person’s weight condition. This study aimed to examine the validity and reliability of apps for both normal-weight and overweight/obese young adults.

Methods:

Thirty normal-weight (aged 21.7 ± 1.0 years, BMI 21.3 ± 1.9 kg/m2) and 30 overweight/ obese young adults (aged 21.0 ± 1.4 years, BMI 28.6 ± 3.7 kg/m2) wore a smartphone and pedometer on their right hip while walking/running at 3 different intensities on treadmills. Apps was randomly assigned to each individual for measuring average velocity, step count, distance, and energy expenditure (EE), and these measurements were then analyzed.

Results:

The apps were not accurate in counting most of the measured variables and data fell significantly lower in the parameters than those measured with standard-reference instruments in both light and moderate intensity activity among the normal-weight group. Among the overweight and obese group, the apps were not accurate in detecting velocity, distance, or EE during either light or vigorous intensities. The percentages of mean difference were 30.1% to 48.9%.

Conclusion:

Apps may not have sufficient accuracy to monitor important physical parameters of human body movement. Apps need to be developed that can, in particular, respond differently based on a person’s weight status.