Physical activity patterns and clusters in 1001 patients with COPD. (August 2017)

• Record Type: Journal Article
• Authors: Mesquita, Rafael; Spina, Gabriele; Pitta, Fabio; Donaire-Gonzalez, David; Deering, Brenda M; Patel, Mehul S; Mitchell, Katy E; Alison, Jennifer; van Gestel, Arnoldus JR; Zogg, Stefanie; Gagnon, Philippe; Abascal-Bolado, Beatriz; Vagaggini, Barbara; Garcia-Aymerich, Judith; Jenkins, Sue C; Romme, Elisabeth APM; Kon, Samantha SC; Albert, Paul S; Waschki, Benjamin; Shrikrishna, Dinesh; Singh, Sally J; Hopkinson, Nicholas S; Miedinger, David; Benzo, Roberto P; Maltais, François; Paggiaro, Pierluigi; McKeough, Zoe J; Polkey, Michael I; Hill, Kylie; Man, William D-C; Clarenbach, Christian F; Hernandes, Nidia A; Savi, Daniela; Wootton, Sally; Furlanetto, Karina C; Cindy Ng, Li W; Vaes, Anouk W; Jenkins, Christine; Eastwood, Peter R; Jarreta, Diana; Kirsten, Anne; Brooks, Dina; Hillman, David R; Sant'Anna, Thaís; Meijer, Kenneth; Dürr, Selina; Rutten, Erica PA; Kohler, Malcolm; Probst, Vanessa S; Tal-Singer, Ruth; Gil, Esther Garcia; den Brinker, Albertus C; Leuppi, Jörg D; Calverley, Peter MA; Smeenk, Frank WJM; Costello, Richard W; Gramm, Marco; Goldstein, Roger; Groenen, Miriam TJ; Magnussen, Helgo; Wouters, Emiel FM; ZuWallack, Richard L; Amft, Oliver; Watz, Henrik; Spruit, Martijn A;
• Is Part Of: Chronic respiratory disease. Volume 14:Number 3(2017)
• Page Start: 256
• Page End: 269
• Publication Date: 2017-08
• Subjects: Chronic obstructive pulmonary disease -- physical activity -- outcome assessment (healthcare) -- principal component analysis -- cluster analysis; Respiratory organs -- Diseases -- Periodicals; 616.2005
• DOI: 10.1177/1479972316687207
• Languages: English
• ISSNs: 1479-9723

Abstract

We described physical activity measures and hourly patterns in patients with chronic obstructive pulmonary disease (COPD) after stratification for generic and COPD-specific characteristics and, based on multiple physical activity measures, we identified clusters of patients. In total, 1001 patients with COPD (65% men; age, 67 years; forced expiratory volume in the first second [FEV1 ], 49% predicted) were studied cross-sectionally. Demographics, anthropometrics, lung function and clinical data were assessed. Daily physical activity measures and hourly patterns were analysed based on data from a multisensor armband. Principal component analysis (PCA) and cluster analysis were applied to physical activity measures to identify clusters. Age, body mass index (BMI), dyspnoea grade and ADO index (including age, dyspnoea and airflow obstruction) were associated with physical activity measures and hourly patterns. Five clusters were identified based on three PCA components, which accounted for 60% of variance of the data. Importantly, couch potatoes (i.e. the most inactive cluster) were characterised by higher BMI, lower FEV1, worse dyspnoea and higher ADO index compared to other clusters ( p < 0.05 for all). Daily physical activity measures and hourly patterns are heterogeneous in COPD. Clusters of patients were identified solely based on physical activity data. These findings may be useful to develop interventions aiming to promote physical activity in COPD.