A cluster analysis of device-measured physical activity behaviours and the association with chronic conditions, multi-morbidity and healthcare utilisation in adults aged 45 years and older

•Device measured physical activity data was used to categorise physical activity behaviour.•Mental health, chronic lung disease and BMI were significantly associated with cluster.•The least-active sedentary cluster had the highest level of morbidity.•This least-active sedentary cluster also had the...

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Veröffentlicht in:Preventive medicine reports 2021-12, Vol.24, p.101641-101641, Article 101641
Hauptverfasser: O'Regan, Andrew, Hannigan, Ailish, Glynn, Liam, Garcia Bengoechea, Enrique, Donnelly, Alan, Hayes, Grainne, Murphy, Andrew W., Clifford, Amanda M., Gallagher, Stephen, Woods, Catherine B.
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Sprache:eng
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Zusammenfassung:•Device measured physical activity data was used to categorise physical activity behaviour.•Mental health, chronic lung disease and BMI were significantly associated with cluster.•The least-active sedentary cluster had the highest level of morbidity.•This least-active sedentary cluster also had the highest level of healthcare use. Most adults do not meet physical activity guidelines with negative implications for health. The aim of this study was to profile adults using multiple physical activity behaviours and to investigate associations with chronic conditions, multi-morbidity and healthcare utilisation. The study used data generated from a sample of adults aged 45 years and older (N = 485), recruited to the Move for Life randomised control trial. Participants wore an accelerometer for eight consecutive days. Hierarchical cluster analysis was conducted using the variables: moderate to vigorous intensity physical activity, light intensity physical activity, step count, waking sedentary time, standing time and bed hours. Descriptive statistics were used to investigate associations with self-reported number of chronic illnesses, multi-morbidity and healthcare utilisation. Four distinct physical activity behaviour profiles were identified: inactive-sedentary (n = 50, 10.3%), low activity (n = 295, 60.8%), active (n = 111, 22.9%) and very active (n = 29, 6%). The inactive-sedentary cluster had the highest prevalence of chronic illnesses, in particular, mental illness (p = 0.006) and chronic lung disease (p = 0.032), as well as multi-morbidity, complex multi-morbidity and healthcare utilisation. The prevalence of any practice nurse visit (p = 0.033), outpatient attendances (p = 0.04) and hospital admission (p = 0.034) were higher in less active clusters. The results have provided an insight into how physical activity behaviour is associated with chronic illness and healthcare utilisation. A group within the group has been identified that is more likely to be unwell. Provisions need to be made to reduce barriers for participation in physical activity for adults with complex multi-morbidity and very low physical activity.
ISSN:2211-3355
2211-3355
DOI:10.1016/j.pmedr.2021.101641