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Analysis of the 24-h activity cycle: An illustration examining the association with cognitive function in the Adult Changes in Thought study

Wu, Yinxiang ; Rosenberg, Dori E ; Greenwood-Hickman, Mikael Anne ; McCurry, Susan M ; Proust-Lima, Cécile ; Nelson, Jennifer C ; Crane, Paul K ; LaCroix, Andrea Z ; Larson, Eric B ; Shaw, Pamela A

Frontiers in psychology, 2023-03, Vol.14, p.1083344-1083344 [Periódico revisado por pares]

Switzerland: Frontiers Media S.A

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  • Título:
    Analysis of the 24-h activity cycle: An illustration examining the association with cognitive function in the Adult Changes in Thought study
  • Autor: Wu, Yinxiang ; Rosenberg, Dori E ; Greenwood-Hickman, Mikael Anne ; McCurry, Susan M ; Proust-Lima, Cécile ; Nelson, Jennifer C ; Crane, Paul K ; LaCroix, Andrea Z ; Larson, Eric B ; Shaw, Pamela A
  • Assuntos: cognition ; compositional data ; Life Sciences ; physical activity ; Psychology ; Santé publique et épidémiologie ; sedentary behavior ; sleep ; time use
  • É parte de: Frontiers in psychology, 2023-03, Vol.14, p.1083344-1083344
  • Notas: ObjectType-Article-2
    SourceType-Scholarly Journals-1
    ObjectType-Feature-3
    content type line 23
    ObjectType-Review-1
    This article was submitted to Quantitative Psychology and Measureme, a section of the journal Frontiers in Psychology
    Edited by: Ryan Falck, University of British Columbia, Canada
    Reviewed by: Charlotte Lund Rasmussen, Curtin University, Australia; Narlon C. Boa Sorte Silva, University of British Columbia, Canada
  • Descrição: The 24-h activity cycle (24HAC) is a new paradigm for studying activity behaviors in relation to health outcomes. This approach inherently captures the interrelatedness of the daily time spent in physical activity (PA), sedentary behavior (SB), and sleep. We describe three popular approaches for modeling outcome associations with the 24HAC exposure. We apply these approaches to assess an association with a cognitive outcome in a cohort of older adults, discuss statistical challenges, and provide guidance on interpretation and selecting an appropriate approach. We compare the use of the isotemporal substitution model (ISM), compositional data analysis (CoDA), and latent profile analysis (LPA) to analyze 24HAC. We illustrate each method by exploring cross-sectional associations with cognition in 1,034 older adults (Mean age = 77; Age range = 65-100; 55.8% female; 90% White) who were part of the Adult Changes in Thought (ACT) Activity Monitoring (ACT-AM) sub-study. PA and SB were assessed with thigh-worn activPAL accelerometers for 7-days. For each method, we fit a multivariable regression model to examine the cross-sectional association between the 24HAC and Cognitive Abilities Screening Instrument item response theory (CASI-IRT) score, adjusting for baseline characteristics. We highlight differences in assumptions and the scientific questions addressable by each approach. ISM is easiest to apply and interpret; however, the typical ISM assumes a linear association. CoDA uses an isometric log-ratio transformation to directly model the compositional exposure but can be more challenging to apply and interpret. LPA can serve as an exploratory analysis tool to classify individuals into groups with similar time-use patterns. Inference on associations of latent profiles with health outcomes need to account for the uncertainty of the LPA classifications, which is often ignored. Analyses using the three methods did not suggest that less time spent on SB and more in PA was associated with better cognitive function. The three standard analytical approaches for 24HAC each have advantages and limitations, and selection of the most appropriate method should be guided by the scientific questions of interest and applicability of each model's assumptions. Further research is needed into the health implications of the distinct 24HAC patterns identified in this cohort.
  • Editor: Switzerland: Frontiers Media S.A
  • Idioma: Inglês
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