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Non-Clinical Medicine - Physiology - Public Health and Epidemiology - Respiratory Medicine

Predicting Daily Physical Activity in Patients with Chronic Obstructive Pulmonary Disease
Published: Friday, November 02, 2012
Author: Arnoldus J. R. van Gestel et al.

by Arnoldus J. R. van Gestel, Christian F. Clarenbach, Anne C. Stöwhas, Valentina A. Rossi, Noriane A. Sievi, Giovanni Camen, Erich W. Russi, Malcolm Kohler


Objectively measuring daily physical activity (PA) using an accelerometer is a relatively expensive and time-consuming undertaking. In routine clinical practice it would be useful to estimate PA in patients with chronic obstructive pulmonary disease (COPD) with more simple methods.


To evaluate whether PA can be estimated by simple tests commonly used in clinical practice in patients with COPD.


The average number of steps per day was measured for 7 days with a SenseWear Pro™ accelerometer and used as gold standard for PA. A physical activity level (PAL) of <1.4 was considered very inactive. Univariate and multivariate analyses were used to examine the relationship between the 6-minute walking distance (6MWD), the number of stands in the Sit-to-Stand Test (STST), hand-grip strength and the total energy expenditure as assessed by the Zutphen Physical Activity Questionnaire (TEEZPAQ). ROC curve analysis was used to identify patients with an extremely inactive lifestyle (PAL<1.4).


In 70 patients with COPD (21 females) with a mean [SD] FEV1 of 43.0 [22.0] %predicted, PA was found to be significantly and independently associated with the 6MWD (r?=?0.69, 95% CI 0.54 to 0.80, p<0.001), STST (r?=?0.51, 95% CI 0.31 to 0.66, p?=?0.001) and TEEZPAQ (r?=?0.50, 95% CI 0.30 to 0.66, p<0.001) but not with hand-grip strength. However, ROC curve analysis demonstrated that these tests cannot be used to reliably identify patients with an extremely inactive lifestyle.


In patients with COPD simple tests such as the 6-Minute Walk Test, the Sit-to-Stand Test and the Zutphen Physical Activity Questionnaire cannot be used to reliably predict physical inactivity.