Thursday 16 October Papers / Journal of Science and Medicine in Sport 18S (2014) e23–e71 e37

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Predictive validity of the BodyMedia SenseWearArmband in children with cerebral palsy

B. Joschtel 1,∗, M. Neil 2, M. Fragala-Pinkham 3,S. Trost 1

1 School of Human Movement Studies, The Universityof Queensland, Brisbane, Australia2 Department of Physical Therapy and RehabilitationSciences, Drexel University, Philadelphia, PA, UnitedStates3 Research Center, Franciscan Hospital for Children,Brighton, MA, United States

Introduction: Cerebral palsy (CP) is the most common physicaldisability of childhood with a prevalence of 2.5–3.6 cases per 1000live births. Children with CP perform significantly less PA than typ-ically developing children, indicating that interventions to increasePA are necessary. To evaluate their effectiveness, valid measures ofPA intensity are required. The BodyMedia SenseWear Armband MFmonitor (Armband) provides estimates of PA energy expenditure(METs); however, the validity of this estimate among children withCP has not been previously investigated. The purpose of this studywas to determine if the MET values produced by the Armband arevalid for use among children with CP.

Method: 57 children and youth (mean age 12.5 ± 3.3 y, 49.1%hemiplegia, GMFCS level I–III) completed the following 9 standard-ised activity trials while wearing a BodyMedia SenseWear Armband(Software Version 7.0): Supine rest, seated writing, table cleaning,laundry task, active video game 1, active video game 2, comfort-able walk, brisk walk, fast walk. VO2 was measured concurrentlyusing the Cosmed K4b2. Differences between measured and pre-dicted METs were assessed using dependent t-tests. Classificationaccuracy was evaluated using percent agreement, sensitivity, speci-ficity, and area under the receiver operating characteristic (ROC)curve.

Results: Armband predicted METs were significantly higherthan measured METs for all activity trials (P < .05), with theexception of lying down trial and the two active gaming trials.Accuracy for categorising Armband predicted METs as either SED,LPA, or MVPA was modest (percent agreement = 66%; WeightedKappa = 0.52, 95% CI = 0.45–0.58). For SED, classification accuracywas good (ROC-AUC = 0.82, 95% CI = 0.77–0.87), with low sensitiv-ity (Se = 66.0%, Sp = 97.8%). For LPA, classification accuracy was poor(ROC-AUC = 0.61, 95% CI = 0.57–0.66), primarily the result of poorsensitivity or a inflated false negative rate (Se = 39.0%, Sp = 83.8%).For MVPA, classification accuracy was fair (ROC-AUC = 0.74, 95%CI = 0.70–0.78), primarily the result of poor specificity (Se = 87.2%,Sp = 60.8%).

Discussion: The BodyMedia SenseWear Armband overesti-mated the intensity of PA in children with CP. The Armband’sproprietary algorithms for prediction of energy expenditure maynot be valid among children with CP.

http://dx.doi.org/10.1016/j.jsams.2014.11.226

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Promoting physical activity in early childhood –Current challenges and future opportunities

J. Hnatiuk

Centre for Physical Activity & Nutrition Research,Deakin University, Australia

The early childhood period (0–5 years) has been identified asa key period for the development of optimal physical activity lev-els in children. As gatekeepers of their children’s health behaviours,parents play a central role in this process and have recently becomethe target of intervention strategies aiming to positively impact onyoung children’s physical activity. However, very little evidence-based information exists about how parents shape their children’sphysical activity early in life. Research in this field has been limitedby challenges of assessing young children’s physical activity aswell perceptions that children are naturally active. Additionally, theexamination of parental influences on children’s physical activityhas traditionally focused on assessing physical activity across thefull day, rather than identifying specific times of the day (active andinactive periods) in which to intervene. Identifying key influenceson young children’s physical activity within the family environ-ment and across different periods of the day may provide greaterdirection for future intervention strategies developed in this agegroup.

http://dx.doi.org/10.1016/j.jsams.2014.11.227

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Maternal facilitation of physical activity andyoung children’s physical activity levels acrossthe day

J. Hnatiuk ∗, N. Ridgers, J. Salmon, K. Hesketh

Deakin University, Australia

Background: The promotion of physical activity in early child-hood has become a focus of research in recent years with emergingevidence that many preschool children do not meet current phys-ical activity recommendations. The family environment has beenidentified as an important influence on young children’s physicalactivity behaviors, yet identifying how parents contribute to chil-dren’s activity patterns across the day remains unknown. This studyaimed to identify maternal correlates of physical activity in youngchildren across the day.

Methods: Participants were 145 mothers and their 1–3.5 yearold children taking part in the Mother and Child Physical Activity(MACPAC) Study. Mothers completed a 20-item survey compris-ing 6 constructs that assessed the time they spent facilitating orrestricting their child’s engagement in physical activity during themorning (6 am–11 am), afternoon (11 am–4 pm) and evening (4pm–9 pm) periods. Children wore ActiGraph GT3X+ accelerometersfor at least 3 weekdays and 1 weekend day to determine the timespent in light, moderate and vigorous-intensity physical activity(LMVPA) in the various periods. Data were analysed using multi-level modelling to control for clustering at the recruitment andfamily level and were adjusted for accelerometer wear time andage the child began walking.

Results: Children engaged in an average of 99.5 (SD = 21.6) minof LMVPA during the morning, 121.3 (SD = 30.1) min during theafternoon and 103.9 (SD = 25.5) min during the evening. Childrenof mothers who provided more opportunities for physical activityin the afternoon had children with higher physical activity levelsduring that period (ˇ = 0.03, 95% CI = 0.01, 0.05), while children of