Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA)

Abstract

<jats:title>Abstract</jats:title> <jats:p>Data on the use of time in different exposures, behaviors, and work tasks are common in occupational research. Such data are most often expressed in hours, minutes, or percentage of work time. Thus, they are constrained or ‘compositional’, in that they add up to a finite sum (e.g. 8 h of work or 100% work time). Due to their properties, compositional data need to be processed and analyzed using specifically adapted methods. Compositional data analysis (CoDA) has become a particularly established framework to handle such data in various scientific fields such as nutritional epidemiology, geology, and chemistry, but has only recently gained attention in public and occupational health sciences. In this paper, we introduce the reader to CoDA by explaining why CoDA should be used when dealing with compositional time-use data, showing how to perform CoDA, including a worked example, and pointing at some remaining challenges in CoDA. The paper concludes by emphasizing that CoDA in occupational research is still in its infancy, and stresses the need for further development and experience in the use of CoDA for time-based occupational exposures. We hope that the paper will encourage researchers to adopt and apply CoDA in studies of work exposures and health.</jats:p>

Can Childcare Work Be Designed to Promote High Intensity Physical Activity for Improved Fitness and Health? A Proof of Concept Study of the Goldilocks Principle

“…Further processing and comparisons were done using compositional data analysis [ 51 , 52 ]. Using procedures in Rstudio v. 1.2.5033 [ 51 ] and the compositions [ 53 ] package, we expressed the central tendency of the data in terms of the geometric means of time ≥60%HRR and <60%HRR for the two periods [ 54 ].…”

Effects of Two Randomized and Controlled Multi-Component Interventions Focusing On 24-Hour Movement Behavior among Office Workers: A Compositional Data Analysis

“…Several systematic reviews on workplace PA and SED interventions have pointed out that it is important to understand that changes in time spent in one behavior necessarily lead to changes in one or more other behaviors [ 9 , 20 ] because a day is constrained to 24 h However, previous studies have traditionally investigated effects of movement behavior interventions without taking the compositional nature of time-use data into account [ 9 , 20 ]. Even if an intervention targets only one behavior, this behavior has to be understood relative to all other behaviors, i.e., as part of a composition [ 21 ]. Treating time-use variables as absolute rather than relative data in regression analyses can potentially lead to misleading estimates of effect sizes (ES) [ 22 ].…”

“…Compositional data analysis (CoDA) is one statistical approach for handling time-use data [ 21 , 23 , 24 ]. Thus, CoDA allows analyses of intervention effects on the entire composition of different movement behaviors, such as SED, light-intensity physical activity (LIPA), moderate physical activity (MPA), vigorous physical activity (VPA) and time in bed [ 25 ].…”

Associations of Meeting 24-hour Movement Guidelines with Stress and Self-rated Health among Adults: Is Meeting more Guidelines Associated with Greater Benefits?

“…There has been a recent shift from studying the effects of each movement behaviour separately to simultaneously examining the effects of all movement behaviours that occur in a 24-hour day (1)(2)(3)(4)(5)(6). This paradigm was motivated by the ndings that sleep, sedentary behaviour (SB), and physical activity are associated with health (7,8) and that the amounts of time spent in these behaviours are perfectly collinear parts of the 24-hour day -more time spent in one movement behaviour inevitably leads to less time spent in the remaining ones.…”