Individual Physical Activity



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p This list of considerations is aligned with the steps proposed by Strath et al. (see reference 3) and colleagues, but differs in some respects. An additional consideration of “Population” was added because issues with assessments vary greatly by age and other demographic factors. Several of the steps proposed by Strath and colleagues also were combined to facilitate interpretation.

q Assume that a certain activity monitor uses a cutpoint for MVPA of 2000 counts per minute. A child who is playing a tag game can accumulate 1200 counts in 30 seconds and then remain sitting or in a standing position for the other 30 seconds and therefore accumulate 0 counts during the remaining fraction of the minute. The aggregated counts for this entire minute (1200) would be less than the threshold (e.g. < 2000) and indicate that the child was not active during that minute even though half of the time was spent running. If the epoch was 30 seconds, the counts would exceed an adjusted threshold (e.g., 1000) and the same period would be categorized as active. The use of 1-minute epochs essentially “ignores” these shorter bouts of activity, resulting in underestimations of activity levels in children.

r Existing self-report measures tend to overlook important physical activity domains, such as activity associated with transportation, while monitor-based measures cannot provide direct information about context. In both cases, the measurement protocol
can be adapted to capture this information by either including additional items in a self-report (report-based measures) or by obtaining detailed schedule information (e.g., school time) and extract raw data during the period of interest.

s The use of measurement error models has helped to refine the precision of some self-report measures. This has been shown to strengthen the associations between physical activity and health outcomes such as obesity or diabetes by 30% to 50% (see Reference 88).