Patterns of physical activity and sedentary behavior in child and adolescent cancer survivors assessed using wrist accelerometry: A cluster analysis approach

  • Lauren Ha
  • , Claire E. Wakefield
  • , Claudio Diaz
  • , David Mizrahi
  • , Christina Signorelli
  • , Kalina Yacef
  • , David Simar

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Physical activity levels among childhood cancer survivors are typically quantified as a total amount using time spent in various intensities. Yet, most analyses do not consider the transitory nature of children’s behaviors and a more detailed approach could provide complimentary information. We aimed to explore various behavior profiles of survivors’ daily and hourly physical activity patterns. We measured 8-18-year-old survivors’ activity levels over 7 days using wrist accelerometry and cluster analysis. Of the 37 participant datasets, survivors engaged in mean (SD) 36.3 (19.0) min/day of MVPA and 4.1 (1.9) hrs/day of sedentary activity. The cluster analysis revealed five daily movement patterns: ‘most active’ (prevalence 11%), ‘active’ (22%), ‘moderately active + moderately sedentary’ (35%), ‘moderately active + high sedentary’ (5%) and ‘least active’ (27%). Younger survivors and those with less time since treatment completion were more likely to be in the active clusters. Hourly behaviors were characterized by short bursts of MVPA and moderate bouts of sedentary activity. Our approach provides an insightful analysis into the nature and timing of childhood cancer survivors’ movement behaviours. Our findings may assist in the development of targeted interventions to improve physical activity levels.

Original languageEnglish
JournalHealth Informatics Journal
Volume29
Issue number4
DOIs
StatePublished - 1 Oct 2023
Externally publishedYes

Keywords

  • accelerometry
  • childhood cancer
  • cluster analysis
  • data mining
  • movement behaviors
  • physical activity

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