Validation of the activPAL3 micro Introduction

Validation of the activPAL3 micro Cormac Powell, Brian P. Carson, Kieran P. Dowd & Alan E. Donnelly Department of Physical Education and Sport Sciences and Centre for Physical Activity and Health Research, University of Limerick, Limerick, Ireland ([email protected])

Introduction

Results

The uniaxial activPAL has been identified as a valid measure of physical activity (PA) in adolescents (Dowd et al., 2011) and as an accurate measure of step count in older adults (Grant et al., 2008). This device has also been shown to accurately differentiate between sitting/lying, standing and stepping in adults (Godfrey et al., 2007). To date, there is no information on the use of the new activPAL3 micro’s (APm) count function to classify PA intensities in adults. The purpose of this study was to examine the relationship between activity counts and energy expenditure, measured by indirect calorimetry. This study also aimed to develop and validate counts to activity thresholds for moderate physical activity (MPA) and vigorous physical activity (VPA) in an adult population for the APm.

The median counts·15 s-1 and the energy expenditure data for each activity are presented in table 1. An increase in counts·15 s-1 was observed with an increase in energy expenditure. An AUC of 0.992 for MPA and 0.999 for VPA was observed for the development group. For MPA, a threshold of 5149 counts·15 s-1 optimized sensitivity (0.937) and specificity (0.939), while for VPA, a threshold of 12346 counts·15 s-1 optimized sensitivity (0.982) and specificity (0.980).

Methods • Fifty participants performed three activities of daily living, two walking activities and one running activity (Figure 1) while wearing an APm and a CosMED K4B2 (Figure 2). • Prior to performing the activities, participants had their resting metabolic rate (RMR) measured for 15 minutes. The final two minutes of each activity were used in the analysis to ensure that the participants were in a steady state Thirty participants were randomly assigned to the development group, with the remaining 20 assigned to the cross-validation group. Receiver Operating Characteristics (ROC) curves and analysis were used to calculate an Area Under the Curve (AUC) and define thresholds with optimal sensitivity and specificity for moderate physical activity (MPA) and vigorous physical activity (VPA) in the development group. • The thresholds for MPA and VPA were then cross-validated in the independent group of 20 participants. Activity Time (Minutes) RMR 15 Sitting 5 Standing 5 Handling dishes 5 Slow walking 7 Fast walking 7 Jogging 7

RMR

Sitting

Standing

Handling dishes

Slow walking

Participant characteristics N

50

Age

39.3 (11.9)

Mass

73.46 (11.71)

Height

1.72 (0.09)

BMI

24.98 (3.64)

Sex

46% male

(2.5-4.5km/h)

Table 1 - Median (interquartile range) for APm counts and energy expenditure for each activity

Activity

Counts (·15 s-1)

Sitting 0.6250 (14.06) Standing 0.5000 (8.06) Handling dishes 50.8750 (87.50) Slow walking 6200.1250 (2225.06) Fast walking 9566.2500 (2153.19) Jogging 16858.5000 (3041.50)

Energy Expenditure (METs) 1.0305 (0.1885) 1.1206 (0.1783) 1.5226 (0.3072) 3.1804 (0.7151) 4.1018 (1.2038) 9.8614 (2.1941)

The counts from the ROC analysis were cross-validated with the cross-validation group. The results are presented in table 2. The MPA and VPA thresholds demonstrated high levels of sensitivity and specificity when cross-validated. Table 2 - Cross-validation results for sensitivity and specificity values for activity intensity thresholds counts·15 s-1

Counts·15 s-1 Sensitivity Specificity

MPA 5149 0.934 0.902

VPA 12346 0.971 1.000

Discussion and Conclusions • Thresholds of 5149 count·15 s-1 and 12346 count·15 s-1 were developed for MPA and VPA respectively. These thresholds were shown to have high levels of sensitivity and specificity when cross-validated in the independent sample. • The activPAL has previously been shown to be the “gold standard objective measure” of sedentary time (Kozey-Keadle et al., 2011). These findings suggest that the new APm provides valid estimates of MPA and VPA in an adult population and may be used as a dual monitor of both physical activity and sedentary behaviour. • These thresholds may only be suitable for stationary and ambulatory activities in an adult population and may be less well suited for activities which have a high metabolic cost but low levels of recorded acceleration (e.g. cycling, resistance training).

Fast walking

References

(4.5-6.5km/h)

Figure 1 – Sequence and duration of activities

Jogging (6.5-8.5km/h)

1. Dowd KP, Harrington DM, Donnelly AE. Criterion and concurrent validity of the activPAL professional physical activity monitor in adolescent females. PLoS One 2012;7(10):e4763 2. Godfrey A, Culhane KM, Lyons GM. Comparison of the performance of the activPAL Professional physical activity logger to a discrete accelerometer-based activity monitor. Med Eng Phys 2007;29(8):930-4. 3. Grant PM, Dall PM, Mitchell SL, Granat MH. Activity-monitor accuracy in measuring step number and cadence in community-dwelling older adults. J Aging Phys Act 2008;16(2):201-14. 4. Kozey-Keadle S, Libertine A, Lyden K, et al. Validation of wearable monitors for assessing sedentary behaviour. Med Sci Sports Exerc 2011;43(8):1561-67.

Acknowledgements This research project was supported by a Physical Education and Sport Sciences Postgraduate Scholarship from the University of Limerick.

Figure 2 –CosMED K4B2 (right) and APm (left) set up

International Conference on Ambulatory Monitoring of Physical Activity and Movement Limerick, Ireland June 2015