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Titre : | Submaximal ExerciseBased Equations to Predict Maximal Oxygen Uptake in Older Adults: A Systematic Review (2016) |
Auteurs : | Ashleigh E. Smith ; Harrison Evans ; Gaynor Parfitt |
Type de document : | Article |
Dans : | Archives of Physical Medicine and Rehabilitation (2016/6, 2016) |
Article en page(s) : | pp. 10031012 |
Langues: | Anglais |
Descripteurs : |
HE Vinci Epreuve d'effort ; Rééducation et réadaptation ; Vieillissement |
Mots-clés: | Aging ; Exercise test ; Forecasting ; Prévision ; Oxygen consumption ; Consommation d'oxygène ; Physical fitness ; Aptitude physique |
Résumé : |
Objective To evaluate and discuss the accuracy of submaximal exercisebased equations to predict maximum oxygen uptake (View the MathML sourceV˙o2max), validated using direct gas analysis, in older apparently healthy adults. Data Sources Studies were identified by searching 5 electronic databases and manually scanning reference lists of included articles from the respective inception of each database through April 2015. Study Selection Studies were included if they used at least 1 submaximal exercisebased variable in the prediction, the actual View the MathML sourceV˙o2max was directly measured using a gas analysis device, and if participants were apparently healthy older adults (mean age ≥65y). Eligible studies were required to report at least 1 validity statistic (eg, Pearson product-moment correlation [r ]) and either a predicted and measured View the MathML sourceV˙o2max value or a directional significant difference between the measured and predicted View the MathML sourceV˙o2max values. No limits were placed on year of publication, but only full-text, published articles in the English language were included. Data Extraction Nine articles and 13 equations were retained from the systematic search strategy. If the same prediction equation was used across multiple trials, data from the most accurate trial were reported. Data Synthesis Submaximal equations predicted directly measured View the MathML sourceV˙o2max with a moderate to strong correlation strength (r range, 0.40.9). Predicted View the MathML sourceV˙o2max significantly differed from directly measured in 2 of the 13 equations. The preferred mode of ergometry was walking or running (7 equations); a stepping protocol was the most accurate (R2=0.9, not significant between predicted and measured View the MathML sourceV˙o2max). Conclusions Factors to consider when choosing a submaximal exercisebased equation are the accuracy of the equation, the population tested, the mode of ergometry, the equipment availability, and the time needed to conduct familiarization sessions. |
Disponible en ligne : | Oui |
En ligne : | https://login.ezproxy.vinci.be/login?url=https://www.sciencedirect.com/science/article/pii/S0003999315013246 |