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)
The 24-hour 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 isotemporal substitution, compositional data analysis, and latent profile analysis 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 CASI item response theory (IRT) score, adjusting for other baseline characteristics. We highlight differences in assumptions and the scientific questions that can be addressed by each approach. ISM is easiest to apply and interpret; however, the typical ISM model assumes a linear association. CoDA specifies a non-linear relationship with time reallocation, through isometric log-ratio transformations that are more challenging to apply and interpret. LPA can serve as an exploratory data 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. Cross-sectional data 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 the applicability of each model’s assumptions. Further research is needed into the health implications of the distinct 24HAC patterns identified in this cohort.