Xanne Janssen1, Dylan P Cliff2, John J Reilly3, Trina Hinkley4, Rachel A Jones2, Marijka Batterham5, Ulf Ekelund6, Søren Brage7, Anthony D Okely2. 1. Interdisciplinary Educational Research Institute, University of Wollongong, Australia. Electronic address: xj512@uowmail.edu.au. 2. Interdisciplinary Educational Research Institute, University of Wollongong, Australia. 3. School of Psychology and Health, University of Strathclyde, United Kingdom. 4. Centre for Physical Activity and Nutrition Research (C-PAN), Deakin University, Australia. 5. Centre for Statistical and Survey Methodology, University of Wollongong, Australia. 6. Department of Sport Medicine, Norwegian School of Sport Sciences, Norway; MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, United Kingdom. 7. MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, United Kingdom.
Abstract
OBJECTIVES: Examine the predictive validity of the activPAL™ metabolic equivalents equation, develop an activPAL™ threshold value to define moderate-to vigorous-intensity physical activities, and examine the classification accuracy of the developed moderate-to vigorous-intensity physical activities threshold value in 4- to 6-year-old children. DESIGN: A sample of forty 4- to 6-year-old children from the Illawarra region in New South Wales, Australia were included in data analysis. METHODS: Participants completed a ∼ 150-min room calorimeter protocol involving age-appropriate sedentary behaviors, light-intensity physical activities and moderate-to vigorous-intensity physical activities. activPAL™ accelerometer counts were collected over 15s epochs. Energy expenditure measured by room calorimetry and direct observation were used as the criterion measure. Predicted metabolic equivalents were calculated using the activPAL™ metabolic equivalents equation (activPAL™ software version 5.8.0). Predictive validity was evaluated using dependent-samples t-tests. Participants were randomly allocated into two groups to develop and cross-validate an intensity threshold for moderate-to vigorous-intensity physical activities. Receiver operating characteristic curve analysis was used to determine moderate-to vigorous-intensity physical activities threshold. The classification accuracy of the developed threshold was cross-validated using sensitivity, specificity, and area under the receiver operating characteristic-curve. RESULTS: The activPAL™ metabolic equivalents equation significantly overestimated metabolic equivalents during sedentary behaviors and significantly underestimated metabolic equivalents for light-intensity physical activities, moderate-to vigorous-intensity physical activities and total metabolic equivalents compared to measured metabolic equivalents (all P<0.001). The developed threshold of ≥1418 counts per 15s resulted in good classification accuracy for moderate-to vigorous-intensity physical activities. CONCLUSION: The current activPAL™ metabolic equivalents equation requires further development before it can be used to accurately estimate metabolic equivalents in preschoolers. The developed threshold exhibited acceptable classification accuracy for moderate-to vigorous-intensity physical activities; however studies cross-validating this moderate-to vigorous-intensity physical activities threshold in free-living preschool-aged children are recommended.
OBJECTIVES: Examine the predictive validity of the activPAL™ metabolic equivalents equation, develop an activPAL™ threshold value to define moderate-to vigorous-intensity physical activities, and examine the classification accuracy of the developed moderate-to vigorous-intensity physical activities threshold value in 4- to 6-year-old children. DESIGN: A sample of forty 4- to 6-year-old children from the Illawarra region in New South Wales, Australia were included in data analysis. METHODS: Participants completed a ∼ 150-min room calorimeter protocol involving age-appropriate sedentary behaviors, light-intensity physical activities and moderate-to vigorous-intensity physical activities. activPAL™ accelerometer counts were collected over 15s epochs. Energy expenditure measured by room calorimetry and direct observation were used as the criterion measure. Predicted metabolic equivalents were calculated using the activPAL™ metabolic equivalents equation (activPAL™ software version 5.8.0). Predictive validity was evaluated using dependent-samples t-tests. Participants were randomly allocated into two groups to develop and cross-validate an intensity threshold for moderate-to vigorous-intensity physical activities. Receiver operating characteristic curve analysis was used to determine moderate-to vigorous-intensity physical activities threshold. The classification accuracy of the developed threshold was cross-validated using sensitivity, specificity, and area under the receiver operating characteristic-curve. RESULTS: The activPAL™ metabolic equivalents equation significantly overestimated metabolic equivalents during sedentary behaviors and significantly underestimated metabolic equivalents for light-intensity physical activities, moderate-to vigorous-intensity physical activities and total metabolic equivalents compared to measured metabolic equivalents (all P<0.001). The developed threshold of ≥1418 counts per 15s resulted in good classification accuracy for moderate-to vigorous-intensity physical activities. CONCLUSION: The current activPAL™ metabolic equivalents equation requires further development before it can be used to accurately estimate metabolic equivalents in preschoolers. The developed threshold exhibited acceptable classification accuracy for moderate-to vigorous-intensity physical activities; however studies cross-validating this moderate-to vigorous-intensity physical activities threshold in free-living preschool-aged children are recommended.
Authors: Christiana M van Loo; Anthony D Okely; Marijka Batterham; Tina Hinkley; Ulf Ekelund; Soren Brage; John J Reilly; Gregory E Peoples; Rachel Jones; Xanne Janssen; Dylan P Cliff Journal: J Phys Act Health Date: 2016-06
Authors: Dale E Rae; Simone A Tomaz; Rachel A Jones; Trina Hinkley; Rhian Twine; Kathleen Kahn; Shane A Norris; Catherine E Draper Journal: BMC Public Health Date: 2021-03-23 Impact factor: 3.295
Authors: Marieke De Craemer; Duncan McGregor; Odysseas Androutsos; Yannis Manios; Greet Cardon Journal: Int J Environ Res Public Health Date: 2018-10-03 Impact factor: 3.390