|Title||Steps per Day and Its Relationship to Energy Expenditures.|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Barreira, TV, Schuna, Jr, JM|
|Journal||Med Sci Sports Exerc|
Chomistek et al. (1) investigated the association between energy expenditure measured with doubly labeled water (DLW) and physical activity (PA) outputs derived from the ActiGraph GT3X in a sample of adults. The authors concluded that total activity counts per day, steps per day, and derived PA energy expenditure (PAEE) were more highly correlated with DLW-PAEE than moderate to vigorous PA. This study has a number of strengths, including the large number of participants, the use of DLW, and the large quantity of associations evaluated. However, we believe the authors missed an opportunity to feature the strengths of steps per day as an output metric related to PAEE.
Although steps and activity counts share some of the same weaknesses as output metrics (e.g., lack of consistency between device manufacturers and generations of the same device), in comparison to the latter, steps per day is a metric that both researchers and the general public can easily comprehend. Although steps per day outputs can differ between devices from various manufacturers because different algorithms are used to identify a “step,” a step is an observable action, and the accuracy of step measuring devices can be tested against a gold standard (i.e., direct observation). In addition, steps per day estimates from different devices tend to be highly correlated (2) and represent the primary metric used to track PA levels among millions of commercial activity tracker users. Activity counts metric, on the other hand, is not an intuitive unit of measure. There is no clear definition of what the metric ultimately represents, and each device manufacturer has its own output for activity counts. It is not an output in all research devices, and it is not found in many consumer devices either. Furthermore, the activity counts metric cannot be characterized by an observable action and does not have a comparable gold standard.
It should be noted that the authors tested numerous metrics related to activity counts, including different moderate to vigorous PA cut points and use of single-axis and triaxial values, whereas steps were only evaluated with a single metric (i.e., steps per day). It is possible that the evaluated steps per day derived using ActiGraph’s low-frequency extension filter is the step-based metric most highly correlated with DLW. However, as the authors noted (1), they could have easily evaluated associations between DLW and censored (when activity counts <500 counts per minute, steps are set to zero) steps per day (3). The authors could have also tested different step accumulation patterns or time spent at different cadence bands (4).
Lastly, the correlations between DLW-PAEE and steps per day were among the highest correlations observed and just as strong as correlations between DLW-PAEE and total activity counts per day. Because of the relative similarity in observed associations presented in this study between steps per day and other accelerometer-derived measures, we believe that it represents a potentially stronger metric for PA assessment than ActiGraph-defined activity counts because of its greater potential for comprehension and ubiquitous availability among scores of research-grade and commercially available PA measurement devices.
|Alternate Journal||Med Sci Sports Exerc|