INTRODUCTION:
Estimation of physical activity intensity by translating accelerometry derived behaviors or counts to Metabolic Equivalence of Task (MET) values can be improved by accounting for the gradual changes, or slopes, in MET values that occur during transitions between different activities, rather than treating these transitions as abrupt, discrete shifts. This approach has the potential to better match the physiological response of different physical behaviors. This study aims to evaluate how adding exponential slopes to intensity classifications derived from thigh-worn accelerometer data influences the estimation of daily time spent in moderate and vigorous physical activities. The accuracy of these estimates will be validated using percentage heart rate reserve (HRR) as the criterion measure.
METHODS:
The analysis included data from 419 middle-aged adults as part of the Swedish CArdioPulmonary BioImage Study. Participants wore thigh-worn accelerometers and a portable electrocardiogram (ECG) for approximately 24h. Moderate-intensity (MPA) and vigorous-intensity physical activity (VPA) were estimated for each second by applying previously reported Metabolic Equivalents of Task (METs) values for various physical behaviors to thigh-worn accelerometry. Time spent in MPA and VPA were calculated using two acceleration processing methods: 1-second epochs and 90-second sloped METs. Time spent in MPA and VPA were also estimated using HRR and compared to each acceleration method.
RESULTS:
The HRR method estimated participants spent 27±36 minutes/day in MPA and 2.6±8.7 minutes/day in VPA. The 90-second sloped METs method overestimated participants spent 32±27 minutes/day in MPA, mean absolute error (MAE): 26±28 minutes/day; p<0.001) and 3.3±7.2 minutes/day in VPA (MAE: 4.3±9.8 minutes/day; p<0.001). The 1-second epoch METs method overestimated participants spent 45±25 minutes/day in MPA (MAE: 31±27 minutes/day; p<0.001) and 11±12 minutes/day in VPA (MAE: 10±12 minutes/day; p<0.001). Using Bland-Altman analyses, both acceleration processing methods demonstrated fixed and proportional biases compared to HRR (p<0.001).
CONCLUSION:
The findings highlight the impact of inclusion of exponential slopes into MET curves at behavior transitions on the accuracy of physical activity intensity estimates.