Patterns of Physical Activity Progression in Patients With COPD

Maria Koreny, Heleen Demeyer, Marta Benet, Ane Arbillaga-Etxarri, Eva Balcells, Anael Barberan-Garcia, Elena Gimeno-Santos, Nicholas S. Hopkinson, Corina De Jong, Niklas Karlsson, Zafeiris Louvaris, Michael I. Polkey, Milo A. Puhan, Roberto A. Rabinovich, Robert Rodríguez-Roisin, Pere Vall-Casas, Ioannis Vogiatzis, Thierry Troosters, Judith Garcia-Aymerich, Anna DelgadoJaume Torrent-Pallicer, Jordi Vilaró, Diego A.Rodríguez Chiaradía, Alicia Marín, Pilar Ortega, Nuria Celorrio, Mónica Mon teagudo, Nuria Montellà, Laura Muñoz, Pere Toran, Pere Simonet, Carme Jané, Carlos Martín-Cantera, Eulàlia Borrell, Pere Vall-Casasal, Nathalie Ivanoff, Solange Corriol-Rohou, Ian Jarrod, Damijen Erzen, Caterina Brindicci, Tim Higenbottam, Mario Scuri, Paul McBride, Nadia Kamel, Margaret Tabberer, Fabienne Dobbels, Pim de Boer, Karoly Kulich, Alastair Glendenning, Katja Rudell, Frederick J. Wilson, Enkeleida Nikai, Thys Van Der Molen, Bill MacNee, Anja Frei

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Introduction:
Although mean physical activity in COPD patients declines by 400–500 steps/day annually, it is unknown whether the natural progression is the same for all patients. We aimed to identify distinct physical activity progression patterns using a hypothesis-free approach and to assess their determinants.

Methods:
We pooled data from two cohorts (usual care arm of Urban Training [NCT01897298] and PROactive initial validation [NCT01388218] studies) measuring physical activity at baseline and 12 months (Dynaport MoveMonitor). We identified clusters (patterns) of physical activity progression (based on levels and changes of steps/day) using k-means, and compared baseline sociodemographic, interpersonal, environmental, clinical and psychological characteristics across patterns.

Results:
In 291 COPD patients (mean ± SD 68 ± 8 years, 81% male, FEV1 59 ± 19%pred) we identified three distinct physical activity progression patterns: Inactive (n = 173 [59%], baseline: 4621 ± 1757 steps/day, 12-month change (Δ): −487 ± 1201 steps/day), Active Improvers (n = 49 [17%], baseline: 7727 ± 3275 steps/day, Δ: + 3378 ± 2203 steps/day) and Active Decliners (n = 69 [24%], baseline: 11 267 ± 3009 steps/day, Δ: −2217 ± 2085 steps/day). After adjustment in a mixed multinomial logistic regression model using Active Decliners as reference pattern, a lower 6-min walking distance (RRR [95% CI] 0.94 [0.90–0.98] per 10 m, P = .001) and a higher mMRC dyspnea score (1.71 [1.12–2.60] per 1 point, P = .012) were independently related with being Inactive. No baseline variable was independently associated with being an Active Improver.

Conclusions:
The natural progression in physical activity over time in COPD patients is heterogeneous. While Inactive patients relate to worse scores for clinical COPD characteristics, Active Improvers and Decliners cannot be predicted at baseline.
Original languageEnglish
Pages (from-to)214-223
JournalArchivos de Bronconeumologia
Volume57
Issue number3
Early online date8 Oct 2020
DOIs
Publication statusPublished - 1 Mar 2021

Fingerprint

Dive into the research topics of 'Patterns of Physical Activity Progression in Patients With COPD'. Together they form a unique fingerprint.

Cite this