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Patterns of Time Use across the Chronic Obstructive Pulmonary Disease Severity Spectrum
Toby Hunt1, Marie T Williams2, Timothy S Olds3
1Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research, School of Health Sciences, University of South Australia, City East Campus, North Terrace, Adelaide 5000, Australia. toby.hunt@mymail.unisa.edu.au.
Abstract:
Descriptions of time use patterns in people with chronic obstructive pulmonary disease (COPD) are scarce and the relationship between use-of-time and COPD severity remains unclear. This study aimed to describe a typical day for people with COPD and to explore the differences in time-use patterns across the Body Mass-Index, Airflow Obstruction, Dyspnoea and Exercise Capacity (BODE) index using compositional analyses. Using a cross-sectional design, 141 adults with clinically stable COPD had their demographics, objective measures of function (pulmonary, exercise capacity and physical activity), and self-reported COPD-related impairment recorded. Daily time-use compositions were derived from 24-h accelerometry and 24-h use-of-time recall interviews. Compositional multiple linear regression models were used to explore the relationship between the BODE index and 24-h time-use compositions. These models were used to predict daily time (min/d) that is spent in time-use components across the BODE index. The BODE index score was clearly associated with 24-h accelerometry (p < 0.0001) and 24-h use-of-time recall (p < 0.0001) compositions. Relative to the remaining time-use components, higher BODE index scores were associated with greater sedentary behaviour (p < 0.0001), Quiet time (p < 0.0001), Screen time (p = 0.001) and Self-care (p = 0.022), and less daily Chores (p < 0.0001) and Household administration (p = 0.015) time. As the BODE index scores increased, time-use predictions were strongly associated with decreases in Chores (up to 206 min/d), and increases in Screen (up to 156 min/d) and Quiet time (up to 131 min/d). Time-use patterns may provide a basis for planning interventions relative to the severity of COPD.
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