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      Physical activity patterns and clusters in 1001 patients with COPD

      research-article
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      Chronic Respiratory Disease
      SAGE Publications
      Chronic obstructive pulmonary disease, physical activity, outcome assessment (healthcare), principal component analysis, cluster analysis

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          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 [FEV 1], 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 FEV 1, 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.

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          Most cited references41

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          Physical activity in patients with COPD.

          The present study aimed to measure physical activity in patients with chronic obstructive pulmonary disease (COPD) to: 1) identify the disease stage at which physical activity becomes limited; 2) investigate the relationship of clinical characteristics with physical activity; 3) evaluate the predictive power of clinical characteristics identifying very inactive patients; and 4) analyse the reliability of physical activity measurements. In total, 163 patients with COPD (Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage I-IV; BODE (body mass index, airway obstruction, dyspnoea, exercise capacity) index score 0-10) and 29 patients with chronic bronchitis (normal spirometry; former GOLD stage 0) wore activity monitors that recorded steps per day, minutes of at least moderate activity, and physical activity levels for 5 days (3 weekdays plus Saturday and Sunday). Compared with patients with chronic bronchitis, steps per day, minutes of at least moderate activity and physical activity levels were reduced from GOLD stage II/BODE score 1, GOLD stage III/BODE score 3/4 and from GOLD stage III/BODE score 1, respectively. Reliability of physical activity measurements improved with the number of measured days and with higher GOLD stages. Moderate relationships were observed between clinical characteristics and physical activity. GOLD stages III and IV best predicted very inactive patients. Physical activity is reduced in patients with chronic obstructive pulmonary disease from Global Initiative for Chronic Obstructive Lung Disease stage II/ body mass index, airway obstruction, dyspnoea, exercise capacity score 1. Clinical characteristics of patients with chronic obstructive pulmonary disease only incompletely reflect their physical activity.
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            Television time and continuous metabolic risk in physically active adults.

            Among Australian adults who met the public health guideline for the minimum health-enhancing levels of physical activity, we examined the dose-response associations of television-viewing time with continuous metabolic risk variables. Data were analyzed on 2031 men and 2033 women aged > or = 25 yr from the 1999-2000 Australian Diabetes, Obesity and Lifestyle study without clinically diagnosed diabetes or heart disease, who reported at least 2.5 h.wk of moderate- to vigorous-intensity physical activity. Waist circumference, resting blood pressure, and fasting and 2-h plasma glucose, triglycerides, and high-density-lipoprotein cholesterol (HDL-C) were measured. The cross-sectional associations of these metabolic variables with quartiles and hours per day of self-reported television-viewing time were examined separately for men and for women. Analyses were adjusted for age, education, income, smoking, diet quality, alcohol intake, parental history of diabetes, and total physical activity time, as well as menopausal status and current use of postmenopausal hormones for women. Significant, detrimental dose-response associations of television-viewing time were observed with waist circumference, systolic blood pressure, and 2-h plasma glucose in men and women, and with fasting plasma glucose, triglycerides, and HDL-C in women. The associations were stronger in women than in men, with significant gender interactions observed for triglycerides and HDL-C. Though waist circumference attenuated the associations, they remained statistically significant for 2-h plasma glucose in men and women, and for triglycerides and HDL-C in women. In a population of healthy Australian adults who met the public health guideline for physical activity, television-viewing time was positively associated with a number of metabolic risk variables. These findings support the case for a concurrent sedentary behavior and health guideline for adults, which is in addition to the public health guideline on physical activity.
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              Pulmonary Rehabilitation and Physical Activity in Patients with Chronic Obstructive Pulmonary Disease.

              Physical inactivity is common in patients with chronic obstructive pulmonary disease (COPD) compared with age-matched healthy individuals or patients with other chronic diseases. Physical inactivity independently predicts poor outcomes across several aspects of this disease, but it is (at least in principle) treatable in patients with COPD. Pulmonary rehabilitation has arguably the greatest positive effect of any current therapy on exercise capacity in COPD; as such, gains in this area should facilitate increases in physical activity. Furthermore, because pulmonary rehabilitation also emphasizes behavior change through collaborative self-management, it may aid in the translation of increased exercise capacity to greater participation in activities involving physical activity. Both increased exercise capacity and adaptive behavior change are necessary to achieve significant and lasting increases in physical activity in patients with COPD. Unfortunately, it is readily assumed that this translation occurs naturally. This concise clinical review will focus on the effects of a comprehensive pulmonary rehabilitation program on physical activity in patients with COPD. Changing physical activity behavior in patients with COPD needs an interdisciplinary approach, bringing together respiratory medicine, rehabilitation sciences, social sciences, and behavioral sciences.
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                Author and article information

                Journal
                Chron Respir Dis
                Chron Respir Dis
                CRD
                spcrd
                Chronic Respiratory Disease
                SAGE Publications (Sage UK: London, England )
                1479-9723
                1479-9731
                24 February 2017
                August 2017
                : 14
                : 3
                : 256-269
                Affiliations
                [1 ]Department of Research & Education, CIRO, Horn, The Netherlands
                [2 ]Department of Respiratory Medicine, Maastricht University Medical Center+ (MUMC+), Maastricht, The Netherlands
                [3 ]Department of Signal Processing Systems, Technische Universiteit Eindhoven, Eindhoven, The Netherlands
                [4 ]Smart Professional Spaces Group, Philips Research, Eindhoven, The Netherlands
                [5 ]Laboratory of Research in Respiratory Physiotherapy, Department of Physiotherapy, State University of Londrina (UEL), Londrina, Brazil
                [6 ]Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
                [7 ]CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
                [8 ]Department of Respiratory Medicine, Beaumont Hospital, Dublin, Ireland
                [9 ]NIHR Respiratory Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust and Imperial College, London, UK
                [10 ]NIHR EM CLAHRC – Centre for Exercise and Rehabilitation Science, University Hospitals, Leicester, UK
                [11 ]Clinical and Rehabilitation Sciences, The University of Sydney, Sydney, NSW, Australia
                [12 ]Physiotherapy Department, Royal Prince Alfred Hospital, Sydney, NSW, Australia
                [13 ]Pulmonary Division, University Hospital of Zurich, Zurich, Switzerland
                [14 ]Medical University Clinic, Cantonal Hospital Baselland, Liestal and Medical Faculty, University of Basel, Basel, Switzerland
                [15 ]Centre de recherche, Institut Universitaire de cardiologie et de pneumologie de Québec, 2725 Chemin Ste-Foy Québec, Université Laval, Québec, Canada
                [16 ]Division of Pulmonary, Hospital U. Marqués de Valdecilla, IFIMAV, Santander, Spain
                [17 ]Mindful Breathing Laboratory, Mayo Clinic, Rochester, MN, USA
                [18 ]Cardio-Thoracic and Vascular Department, University of Pisa, Pisa, Italy
                [19 ]Universitat Pompeu Fabra (UPF), Barcelona, Spain
                [20 ]School of Physiotherapy and Exercise Science, Curtin University, Perth, WA, Australia
                [21 ]Department of Respiratory Medicine, Catharina Hospital, Eindhoven, The Netherlands
                [22 ]School of Ageing and Chronic Disease, University Hospital Aintree, Liverpool, UK
                [23 ]Pulmonary Research Institute at LungClinic Grosshansdorf, Airway Research Center North, Member of the German Centre for Lung Research, Grosshansdorf, Germany
                [24 ]Musgrove Park Hospital, Taunton and Somerset NHS Foundation Trust, Somerset, UK
                [25 ]Department of Pediatrics and Pediatric Neurology, Cystic Fibrosis Center, Sapienza University of Rome, Rome, Italy
                [26 ]Environmental Risk and Health, Flemish Institute for Technological Research (VITO), Mol, Belgium
                [27 ]Woolcock Institute of Medical Research, The University of Sydney, Camperdown, NSW, Australia
                [28 ]Department of Pulmonary Physiology, Sir Charles Gairdner Hospital, Perth, WA, Australia
                [29 ]AstraZeneca, Barcelona, Spain
                [30 ]Respiratory Medicine, West Park Healthcare Centre and Faculty of Medicine, University of Toronto, Toronto, Canada
                [31 ]Department of Human Movement Science, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
                [32 ]Center for Research in Health Sciences, University North of Paraná (UNOPAR), Londrina, Brazil
                [33 ]GlaxoSmithKline R&D, King of Prussia, PA, USA
                [34 ]Department of Pulmonary and Critical Care, Saint Francis Hospital and Medical Center, Hartford, CT, USA
                [35 ]ACTLab group, Chair of Sensor Technology, University Passau, Passau, Germany
                [36 ]REVAL - Rehabilitation Research Center, BIOMED - Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Diepenbeek, Belgium
                []Deceased 3 June 2016
                Author notes
                [*]Rafael Mesquita, Department of Research & Education, CIRO, Hornerheide 1, 6085 NM, Horn, The Netherlands. Email: rafaelmesquita14@ 123456ymail.com
                Article
                10.1177_1479972316687207
                10.1177/1479972316687207
                5720232
                28774199
                8ccc3faa-10b2-4c7c-8e31-ff4c423c768c
                © The Author(s) 2017

                This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License ( http://www.creativecommons.org/licenses/by-nc/3.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 17 February 2016
                : 15 October 2016
                Categories
                Original Papers

                Respiratory medicine
                chronic obstructive pulmonary disease,physical activity,outcome assessment (healthcare),principal component analysis,cluster analysis

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