Criterion and Concurrent Validity of the activPAL™ Professional Physical Activity Monitor in Adolescent Females

Abstract

BackgroundThe activPAL has been identified as an accurate and reliable measure of sedentary behaviour. However, only limited information is available on the accuracy of the activPAL activity count function as a measure of physical activity, while no unit calibration of the activPAL has been completed to date. This study aimed to investigate the criterion validity of the activPAL, examine the concurrent validity of the activPAL, and perform and validate a value calibration of the activPAL in an adolescent female population. The performance of the activPAL in estimating posture was also compared with sedentary thresholds used with the ActiGraph accelerometer.MethodologiesThirty adolescent females (15 developmental; 15 cross-validation) aged 15–18 years performed 5 activities while wearing the activPAL, ActiGraph GT3X, and the Cosmed K4B2. A random coefficient statistics model examined the relationship between metabolic equivalent (MET) values and activPAL counts. Receiver operating characteristic analysis was used to determine activity thresholds and for cross-validation. The random coefficient statistics model showed a concordance correlation coefficient of 0.93 (standard error of the estimate = 1.13). An optimal moderate threshold of 2997 was determined using mixed regression, while an optimal vigorous threshold of 8229 was determined using receiver operating statistics. The activPAL count function demonstrated very high concurrent validity (r = 0.96, p<0.01) with the ActiGraph count function. Levels of agreement for sitting, standing, and stepping between direct observation and the activPAL and ActiGraph were 100%, 98.1%, 99.2% and 100%, 0%, 100%, respectively.ConclusionsThese findings suggest that the activPAL is a valid, objective measurement tool that can be used for both the measurement of physical activity and sedentary behaviours in an adolescent female population.

The Development of Activity Profiles in Adolescent Females and their Association with Adiposity

“…The activPAL is a valid and reliable measure of sitting/lying time, standing time, and MVPA in youths (3,7). A detailed description of the activPAL and the wear protocol have been described elsewhere (7).…”

“…Sitting/lying time and standing time were determined through postural position using the activPAL. MVPA was examined using a validated count to activity thresholds of 2997 counts/15-s epoch from the activPAL accelerometer count function (7). MVPA corresponded to activities which required an intensity of > 3 metabolic equivalents.…”

Concurrent Validity of the MOX Activity Monitor Compared to the ActiGraph GT3X

“…Another study also proved that the slope of prediction equations differs among different activities. 21 Also, in other studies the variance of the counts increased with speed, [22][23][24] and even the variance in volume of O 2 (in mL/kg/min) increased with speed. 25,26 However, within participants MOX counts increased consistently, and during daily life there was a merely consistent over-or underestimation of activity per participant.…”

Impact of Activity Monitors on Quantification of Physical Activity - A Systematic Review & Meta-Analysis (Preprint)

“…Majority of studies used mixed gender population (n=14), 1 study targeted only males and 1 of females. Most of the studies included participants aged between 18-60 years (n=10) [16], [17], [21], [23], [26], [31], [32], [33], [25], [28] while five studies included participants older than 60 years of age [22], [23], [24], [27], [30] For both qualitative and quantitative analysis seven studies usedactivPAL [9], [17], [22], [24], [25], [29], [33] as an assessment measure of PA whereas eight studies used actigraph [9], [16], [17], [21], [22], [25], [27], [29]. Studies also used step watch [21], AMP 331 [30], mobile phone technology [32] CosMed Kb42 [29], IPAQ [23] and LAPAQ [24] respectively Figure 2 shows the risk of bias in terms of percentages in the studies…”