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Physical activity level and its clinical correlates in chronic obstructive pulmonary disease: a cross-sectional study

Mikael Andersson12*, Frode Slinde3, Anne Marie Grönberg3, Ulla Svantesson4, Christer Janson2 and Margareta Emtner12

Author Affiliations

1 Department of Neuroscience, Physiotherapy, Uppsala University, Box 593/BMC, SE-751 24, Uppsala, Sweden

2 Department of Medical Science, Respiratory Medicine and Allergology, Uppsala University, Uppsala, Sweden

3 Department of Internal medicine and Clinical Nutrition, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

4 Department of Clinical Neuroscience and Rehabilitation, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

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Respiratory Research 2013, 14:128  doi:10.1186/1465-9921-14-128

Published: 15 November 2013



Decreased physical activity is associated with higher mortality in subjects with COPD. The aim of this study was to assess clinical characteristics and physical activity levels (PALs) in subjects with COPD.


Seventy-three subjects with COPD (67 ± 7 yrs, 44 female) with one-second forced expiratory volume percentage (FEV1%) predicted values of 43 ± 16 were included. The ratio of total energy expenditure (TEE) and resting metabolic rate (RMR) was used to define the physical activity level (PAL) (PAL = TEE/RMR). TEE was assessed with an activity monitor (ActiReg), and RMR was measured by indirect calorimetry. Walking speed (measured over 30-meters), maximal quadriceps muscle strength, fat-free mass and systemic inflammation were measured as clinical characteristics. Hierarchical linear regression was applied to investigate the explanatory values of the clinical correlates to PAL.


The mean PAL was 1.47 ± 0.19, and 92% of subjects were classified as physically very inactive or sedentary. The walking speed was 1.02 ± 0.23 m/s, the quadriceps strength was 31.3 ± 11.2 kg, and the fat-free mass index (FFMI) was 15.7 ± 2.3 kg/m2, identifying 42% of subjects as slow walkers, 21% as muscle-weak and 49% as FFM-depleted. The regression model explained 45.5% (p < 0.001) of the variance in PAL. The FEV1% predicted explained the largest proportion (22.5%), with further improvements in the model from walking speed (10.1%), muscle strength (7.0%) and FFMI (3.0%). Neither age, gender nor systemic inflammation contributed to the model.


Apart from lung function, walking speed and muscle strength are important correlates of physical activity. Further explorations of the longitudinal effects of the factors characterizing the most inactive subjects are warranted.

Physical activity; Activity monitor; COPD; Physical function; Body composition