Metabolic and Physiological Stress During Skiing.
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|ClinicalTrials.gov Identifier: NCT02082106|
Recruitment Status : Completed
First Posted : March 10, 2014
Last Update Posted : April 29, 2015
Problem description In industrialized countries there is a rapid increase in the number of senior citizens. In Austria more than 50% of the population is overweight, with highest prevalence in the age group from 60 to 74 yrs and the WHO lists physical inactivity as one of the main behavioral risk factors of cardiovascular diseases.
Especially in winter months, activity related energy expenditure was 40% and 31% lower in the US and Canada, respectively. In addition, in an Austrian study the winter season was associated with higher blood pressure, total cholesterol and body mass index, giving an increasing risk of chronic coronary disease by 6.8% in men and 3.6% in women.
Therefore, the development of intervention programs that overcome the winter physical activity deficit and be feasible also for elderly should be goal of future research. Alpine skiing (AS) and cross country skiing (XCS) have a long standing tradition in Austria and could potentially fill the winter physical activity gap. The Salzburg Skiing for the Elderly Study (SASES) has found AS to be a save and feasible possibility to improve the health of the aged population in many parameters. XCS as a competitive sport is already well explored but there are hardly any studies about its effects in the normal or elderly population. Unfortunately knowledge about the differences between AS and XCS in the physiological adaptation processes in the elderly population is also lacking.
Aims and hypotheses of the pre-study In order to standardize training interventions, the present pre-study aims at comparing physiological and metabolic parameters between AS, XCS and IT. Therefore, the results of the pre-study serve as determinants for the training parameters of the above mentioned main study.
We postulate that, based on the results of the present study, it is possible to set up comparable isocaloric training sessions for AS, XCS and IT for elderly and unfit persons.
Furthermore, we assume that elderly and unfit subjects are able to perform a full spectrum of intensities and techniques necessary to set appropriate stimuli for isocaloric comparison.
We hypothesize arterial stiffness indices and circulating microRNA (miRNA) patterns to change due to one bout of physical activity of AS, XCS, and IT with variations depending on the kind of sport.
|Condition or disease||Intervention/treatment|
|Healthy||Other: Alpine skiing Other: cross country skiing Other: Indoor training (cycling)|
|Study Type :||Observational|
|Actual Enrollment :||21 participants|
|Official Title:||Metabolic and Physiological Stress During Alpine Skiing, Cross-country Skiing and Indoor Training in Untrained and Trained Persons.|
|Study Start Date :||January 2014|
|Actual Primary Completion Date :||May 2014|
|Actual Study Completion Date :||May 2014|
Participants should be capable of alpine skiing and cross country skiing.
Other: Alpine skiing
Other: cross country skiing
Other: Indoor training (cycling)
- Oxygen consumption (VO2) [ Time Frame: 12 weeks ]VO2 will be measured during during physical examination, indoor training, Alpine Skiing, and Cross Country Skiing. VO2 will be transformed into metabolic equivalents to calculate isocaloric training parameters for the different kind of sport.
- Pulse wave analysis (PWA) [ Time Frame: 12 weeks ]PWA will be measured before/after physical examination, indoor training, Alpine Skiing, and Cross Country Skiing. PWA will be done by oscillometric measurement to calculate influence of acute exercise and training status on several pulse wave parameters.
- RNA [ Time Frame: 12 weeks ]Total RNA will be isolated from stored plasma and blood cell samples. All samples will be screened for influence of acute exercise (before/after physical examination and indoor training).
- Nitric oxide (NO) [ Time Frame: 12 weeks ]NO will be quantified out of stored blood samples and serves as a possible surrogate parameter of pulse wave analysis.
- Metabolic screening [ Time Frame: 12 weeks ]Metabolic parameters (e.g. glucose, lactate) will be quantified out of stored blood samples: These parameters serve as determinants of the different exercises.
Biospecimen Retention: Samples With DNA
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02082106
|University Institute of Sports Medicine, Prevention and Rehabilitation|
|Salzburg, Austria, A-5020|
|Principal Investigator:||Josef Niebauer, MBA, Prof. Dr.Dr.||Paracelsus Medical University|
|Study Chair:||Martin Schoenfelder, Dr.||Research Institute of Moleclar Sport and Rehabilitation Medicine, Paracelsus Medical University Salzburg, Austria|
|Study Chair:||Thomas Stoeggl, Prof. Dr.||Department of Sport Sciency and Kinesiology - University of Salzburg|