Pulmonary Gas Exchange Dynamics and the Tolerance to Muscular Exercise: Effects of Fitness and Training.

Whipp, J.Brian; Ward, Ann

doi:10.2114/ahs1983.11.207

Cited by 30 publications

(36 citation statements)

References 20 publications

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“…The higher relative exercise intensity would be expected to result in a greater lactate concentration and lower pH in the weight-matched participants. This may have slowed the initial rate ofV0 2rise to steady state compared to the trained participants as has been previously reported (Barstow, 1994;Gaesser & Poole, 1996;Paterson & Whipp, 1991;Whipp & Ward, 1992).…”

Section: Weight-matched Men Body Buildersmentioning

confidence: 68%

Effect of Body Composition on Oxygen Uptake during Treadmill Exercise: Body Builders versus Weight-Matched Men

McInnis

Balady

1999

Research Quarterly for Exercise and Sport

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Oxygen uptake (VO2) during treadmill exercise is directly related to the speed and grade, as well as the participant's body weight. To determine whether body composition also affects VO2 (ml.kg-1.min-1) during exercise, we studied 14 male body builders (M weight = 99 kg, SD = 7; M height = 180 cm, SD = 8; M body fat = 8%, SD = 3; M fat free mass = 91 kg, SD = 7) and 14 weight-matched men (M weight = 99 kg, SD = 9; M height = 179 cm, SD = 5; M body fat = 24%, SD = 5; M fat free mass = 73 kg, SD = 9). Percentage of body fat, t(13) = 8.185, p < .0001, and fat free mass, t(13) = 5.723, p < .0001, were significantly different between groups. VO2 was measured by respiratory gas analysis at rest and during three different submaximal workrates while walking on the treadmill without using the handrails for support. VO2 was significantly greater for the lean, highly muscular men at rest: 5.6 +/- 1 vs. 4.0 +/- 1 ml.kg-1.min-1, F(1, 26) = 21.185, p < .001; Stage 1: 1.7 mph/10%, 18.5 +/- 2 vs. 16.1 +/- 2 ml.kg-1.min-1, F(1, 26) = 6.002, p < .05; Stage 2: 2.5 mph/12%, 26.6 +/- 3 vs. 23.1 +/- 2 ml.kg-1.min-1, F(1, 26) = 7.991, p < .01; and Stage 3:3.4 mph/14%, 39.3 +/- 5 vs. 33.5 +/- 5 ml.kg-1.min-1, F(1, 26) = 7.682, p< .01, body builders versus weight-matched men, respectively. However, net VO2 (i.e., exercise VO2 - rest VO2) was not significantly different between the two groups at any of the matched exercise stages. The findings from this study indicate that VO2 during weight-bearing exercise performed at the same submaximal workrate is higher for male body builders compared to that measured in weight-matched men and that which is predicted by standard equations. These observed differences in exercise VO2 appear to be due to the higher resting VO2 in highly muscular participants.

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Section: Weight-matched Men Body Buildersmentioning

confidence: 68%

Effect of Body Composition on Oxygen Uptake during Treadmill Exercise: Body Builders versus Weight-Matched Men

McInnis

Balady

1999

Research Quarterly for Exercise and Sport

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“…Throughout the PRTS and simulated ADL, the data were measured breath-by-breath by a portable metabolic system (K4b2, COSMED, Italy). The gas concentrations and air volume/flow were calibrated following manufacturer’s specifications before each visit.…”

Section: Methodsmentioning

confidence: 99%

“…Besides energy expenditure estimation, the evaluation of the temporal dynamics of the during physical activity transitions can provide valuable information about the aerobic system integrity23. From a practical perspective, abnormal aerobic responses to exercise may precede the clinical detection of non-communicable diseases4.…”

mentioning

confidence: 99%

Prediction of oxygen uptake dynamics by machine learning analysis of wearable sensors during activities of daily living

Beltrame

Amelard

Wong

et al. 2017

Sci Rep

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Currently, oxygen uptake () is the most precise means of investigating aerobic fitness and level of physical activity; however, can only be directly measured in supervised conditions. With the advancement of new wearable sensor technologies and data processing approaches, it is possible to accurately infer work rate and predict during activities of daily living (ADL). The main objective of this study was to develop and verify the methods required to predict and investigate the dynamics during ADL. The variables derived from the wearable sensors were used to create a predictor based on a random forest method. The temporal dynamics were assessed by the mean normalized gain amplitude (MNG) obtained from frequency domain analysis. The MNG provides a means to assess aerobic fitness. The predicted during ADL was strongly correlated (r = 0.87, P < 0.001) with the measured and the prediction bias was 0.2 ml·min−1·kg−1. The MNG calculated based on predicted was strongly correlated (r = 0.71, P < 0.001) with MNG calculated based on measured data. This new technology provides an important advance in ambulatory and continuous assessment of aerobic fitness with potential for future applications such as the early detection of deterioration of physical health.

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“…Eleven patients (1 female, 10 male; average age 53.8 years; see Table 1) completed the program, while 2 patients did not participate in follow-up studies because of private and/or occupational reasons. 5 There could be positive effects on the drive to breathing by regular aerobic and anaerobic ex-ORIGINAL ARTICLE individuals had formed a sports group, with the costs for the exercise site and for the instructors sponsored by public health insurance. To our knowledge, there are no data on this subject.…”

Section: Methodsmentioning

confidence: 99%

Physical Exercise as an Adjunct Therapy in Sleep Apnea—An Open Trial

et al. 2000

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BACKGROUND: The aim of this study was to determine in an open trial if physical exercise in sleep apnea patients is safe and/or influences respiratory disturbance index (RDI). METHODS: After being treated 3 months or more with nasal CPAP for moderate to severe sleep apnea syndrome, eleven patients (1 female, 10 male, mean age 52.2 years) began a six-month period of supervised physical exercise twice a week, 2 hours each time. Before and after this period a Polysomnography without CPAP was recorded, along with a bicycle exercise test with lactate profile, echocardiography, body-weight, and body-height measurement. RESULTS: No adverse effects or cardiopulmonary problems were observed. There was no significant change in body weight with physical training; no significant difference in either min SaO2 nor mean SaO2; and no significant improvement in fitness. No adverse cardiopulmonary effects or problems were observed. There was a decrease of the RDI from 32.8 to 23.6 (p < 0.05), without a significant change in the REM-sleep portion of total sleep time (TST), NREM sleep, or TST. CONCLUSIONS: A prescription for mild to moderate exercise is safe in the management of sleep apnea, and, even in the absence of a fitness improvement, there occurred a decrease in RDI without a change in sleep architecture.

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Pulmonary Gas Exchange Dynamics and the Tolerance to Muscular Exercise: Effects of Fitness and Training.

Cited by 30 publications

References 20 publications

Effect of Body Composition on Oxygen Uptake during Treadmill Exercise: Body Builders versus Weight-Matched Men

Effect of Body Composition on Oxygen Uptake during Treadmill Exercise: Body Builders versus Weight-Matched Men

Prediction of oxygen uptake dynamics by machine learning analysis of wearable sensors during activities of daily living

Physical Exercise as an Adjunct Therapy in Sleep Apnea—An Open Trial

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