It is well known that engaging in physical activity is associated with health benefits (e.g. cognitive health, sleep etc) and does mitigate health risks such as reduced risk of all-cause mortality, cardiovascular disease mortality, incident hypertension, cancer, etc (5, 6). The 2020 guidelines of physical activity and sedentary behaviour emphasizes that adults should undertake 150–300min of moderate-intensity, or 75–150min of vigorous-intensity physical activity, or some equivalent combination of moderate-intensity and vigorous-intensity aerobic physical activity, per week (7). The guideline also emphasizes that ”some physical activity is better than none” and “adults should limit the amount of time spent being sedentary” are the main messages.
The 2020 guidelines of physical activity and sedentary behaviour (now called “2020 guidelines of PA and SB”) refers to absolute time, while disregarding a recommendation based on relative time. There are also 24-hours guidelines based on physical activity, sedentary behaviour and sleep, such as the Canadian 24-Hour Movement Guidelines for Adults (8) and the Australian 24-Hour Movement Guidelines for Children and Young People (9). Although these provide 24-hour guidelines, these recommendations do not provide guidelines based on relative values. As the relative time is affected by the time in all behaviours it is more difficult to provide an optimal composition about how an individual should spend their day from a health perspective. In addition, there are far more publications on absolute time of physical activity, compared to relative time (10). Applying CoDA, leads normally to an output of relative time for a specific behaviour, which is often quite difficult to interpret relative to the 2020 guidelines of PA and SB. Even if percent could be transformed to absolute time, and rescaled to sum up to 24 hours (11), identifying reference values associated with the 2020 guidelines of PA and SB may help in interpreting which values correspond to the strongest health benefits. It might also help when visualizing diagrams, e.g. ternary plots (12), where relative values are depicted.
If data on complete 24 hours is available, the recommended guidelines of 150–300 min should correspond to that an adult individual should spend between 1.5-3.0% of total time in MVPA. However, in most cases, data on sleep is not recorded and only time in awaken behaviours can be modelled. If not 24 hours of data is recorded, the fraction of MVPA may vary depending on how large part of the day in awaken behaviours is recorded. Considering that most guidelines recommend including days with at least 10 hours of valid data (13), it is important to estimate how this could influence the relative time of MVPA that corresponds to the 2020 guidelines of PA and SB. For instance, if sleep time is ignored and an individual spend 30 min of time in MVPA, the proportion of time will vary between 3.1–6.3% if awaken time is between 8–16 hours.
Please insert Fig. 1 here
If time in different behaviours is unbiased, estimates of relative time will be correct as well. However, if time is classified as non-wear time that corresponds to time in a behaviour, the estimates of relative time will be inaccurate. This pattern could be explored in a scatter plot with wear time against the relative time in a specific behaviour. If the relative time of a behaviour deviates across wear time it could be suspected that the time in a behaviour is biased. In Fig. 1A, based on publicly available data from NHANES 2003–2006, the proportion of time spent in MVPA and reaching the recommended level of the 2020 guidelines of PA and SB across wear time were rather constant. In Fig. 1B, based on randomly generated data, the individuals that reached the recommended level of the 2020 guidelines of PA and SB had the lowest amount of wear time, illustrating that time in at least one behaviour is not accurately estimated. The figure also highlights that the proportion of individuals reaching the recommended level of the 2020 guidelines of PA and SB should be rather constant across wear time. Since individuals often have different wear time it is important to estimate which cut-off value can identify the majority of individuals reaching the recommendation (sensitivity) and distinguish between the ones that do not achieve the recommendation (specificity).