Comparison of two sets of accelerometer cut-off points for calculating moderate-to-vigorous physical activity in young children.

Child Obesity Research Centre, Faculty of Education, University of Wollongong, NSW 2522, Australia.
Journal of physical activity & health (Impact Factor: 1.95). 11/2007; 4(4):509-13.
Source: PubMed
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    ABSTRACT: No universally accepted ActiGraph accelerometer cutpoints for quantifying moderate-to-vigorous physical activity (MVPA) exist. Estimates of MVPA from one set of cutpoints cannot be directly compared to MVPA estimates using different cutpoints, even when the same outcome units are reported (MVPA min d –1). The purpose of this study was to illustrate the utility of an equating system that translates reported MVPA estimates from one set of cutpoints into another, to better inform public health policy. Secondary data analysis. ActiGraph data from a large preschool project (N = 419, 3–6-yr-olds, CHAMPS) was used to conduct the analyses. Conversions were made among five different published MVPA cutpoints for children: Pate (PT), Sirard (SR), Puyau (PY), Van Cauwengerghe (VC), and Freedson Equation (FR). A 10-fold cross-validation procedure was used to develop prediction equations using MVPA estimated from each of the five sets of cutpoints as the dependent variable, with estimated MVPA from one of the other four sets of cutpoints (e.g., PT MVPA predicted from FR MVPA). The mean levels of MVPA for the total sample ranged from 22.5 (PY) to 269.0 (FR) min d −1 . Across the prediction models (5 total), the median proportion of variance explained (R 2) was 0.76 (range 0.48–0.97). The median absolute percent error was 17.2% (range 6.3–38.4%). The prediction equations developed here allow for direct comparisons between studies employing different ActiGraph cutpoints in preschool-age children. These prediction equations give public health researchers and policy makers a more concise picture of physical activity levels of preschool-aged children.
    Journal of Science and Medicine in Sport 01/2011; 14:404-410. · 3.08 Impact Factor
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    ABSTRACT: Evaluate the predictive validity of ActiGraph energy expenditure equations and the classification accuracy of physical activity intensity cut-points in preschoolers. Forty children aged 4-6 years (5.3±1.0 years) completed a ∼150-min room calorimeter protocol involving age-appropriate sedentary, light and moderate-to vigorous-intensity physical activities. Children wore an ActiGraph GT3X on the right mid-axillary line of the hip. Energy expenditure measured by room calorimetry and physical activity intensity classified using direct observation were the criterion methods. Energy expenditure was predicted using Pate and Puyau equations. Physical activity intensity was classified using Evenson, Sirard, Van Cauwenberghe, Pate, Puyau, and Reilly, ActiGraph cut-points. The Pate equation significantly overestimated VO2 during sedentary behaviors, light physical activities and total VO2 (P<0.001). No difference was found between measured and predicted VO2 during moderate-to vigorous-intensity physical activities (P = 0.072). The Puyau equation significantly underestimated activity energy expenditure during moderate-to vigorous-intensity physical activities, light-intensity physical activities and total activity energy expenditure (P<0.0125). However, no overestimation of activity energy expenditure during sedentary behavior was found. The Evenson cut-point demonstrated significantly higher accuracy for classifying sedentary behaviors and light-intensity physical activities than others. Classification accuracy for moderate-to vigorous-intensity physical activities was significantly higher for Pate than others. Available ActiGraph equations do not provide accurate estimates of energy expenditure across physical activity intensities in preschoolers. Cut-points of ≤25counts⋅15 s(-1) and ≥420 counts⋅15 s(-1) for classifying sedentary behaviors and moderate-to vigorous-intensity physical activities, respectively, are recommended.
    PLoS ONE 11/2013; 8(11):e79124. DOI:10.1371/journal.pone.0079124 · 3.53 Impact Factor
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    ABSTRACT: It is unknown whether relationships detected between physical activity intensity and health differ according to accelerometer thresholds used [sample-specific thresholds (SSTs), published thresholds (PTs) or the individualized activity-related time equivalent (ArteACC)]. SSTs were developed through ActiGraph calibration in 52 boys, aged 8-10 years. The boys subsequently wore an ActiGraph for seven days. SSTs, PTs and ArteACC for moderate (MPA) and vigorous (VPA) activity were applied. Waist circumference (WC), peak oxygen consumption (VO2peak) and blood pressure were assessed. After applying SSTs, 48.9% of boys achieved 60+ minutes of daily MVPA, compared with 8.5% with PTs and 100% with ArteACC. MPA and VPA were correlated with WC and VO2peak, regardless of whether PTs or SSTs were used (WC: MPA r = -0.37 to -0.43; VO2peak: r = 0.34 to 0.39, p < 0.05). With ArteACC, only VPA was correlated with WC (r = -0.39, p < 0.01) and VO2peak (r = 0.35, p < 0.05). Relationships with blood pressure were statistically non-significant. Although estimates of the quantity of activity differed according to thresholds used, relationships detected with health were consistent regardless of whether SSTs or PTs were employed. There was no advantage of using SSTs or individualized thresholds. Researchers are encouraged to use PTs to ensure greater comparability between studies. Key pointsStandardized accelerometer intensity thresholds for evaluating children's physical activity do not exist, therefore determining whether relationships between activity and health differ when using different thresholds is of interest.Although prevalence estimates differ according to the choice of accelerometer intensity threshold, relationships detected between activity and various health outcomes in boys are similar, providing the moderate threshold is at least equivalent to an average brisk walk (i.e., ≥ 4 METs).Standardization of thresholds between samples should not impact on relationships determined with health and would allow comparability of prevalence estimates.
    Journal of sports science & medicine 01/2009; 8(1):136-43. · 0.90 Impact Factor