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      Children’s physical activity and sedentary time compared using assessments of accelerometry counts and muscle activity level

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          Abstract

          Background

          This research compared accelerometry (ACC)-derived and muscle electromyography (EMG)-based estimates of physical activity (PA) and sedentary time in typical PA tasks and during the daily lives of children.

          Methods

          Data was included from two exploratory studies. In Study I, 6–7-year-old children ( n = 11, 64% girls) were assessed for eight PA tasks (walking, stair negotiation, climbing, crawling, swinging, balancing, trampoline jumping and a game of tag). In Study II, 7–9-year-old children ( n = 14, 38% girls) were assessed for six PA tasks (walking, sitting, static squat, single leg hops, jump for height and standing long jump), and daily PA during one day with and one day without structured exercise. Quadriceps and hamstring muscle activity and inactivity using EMG shorts and acceleration by waist-mounted accelerometer were simultaneously measured and classified as sedentary, light, moderate and vigorous activity. Data from ACC was further analyzed using five different published cut-off points and varying time windows (1−60 s) for comparison with EMG.

          Results

          In the PA tasks ACC counts and EMG amplitude showed marked differences in swinging, trampoline jumping, crawling, static squat, single leg hops, standing long jump and jump for height, the difference being over 170% when signals were normalized to that during walking. Furthermore, in walking, swinging, trampoline jumping, stair negotiation and crawling ACC classified over 60% of the time as vigorous-intensity activity, while EMG indicated primarily light- and moderate-intensity activities. During both days with and without exercise, ACC resulted in greater proportion of light activity ( p < 0.01) and smaller proportion of moderate activity compared to EMG ( p < 0.05). The choice of cut-off points and epoch length in ACC analysis influenced the classification of PA level and sedentary time. In the analysis of daily activities the cut-off points by Evenson et al. (2008) with epochs of 7.5 s and 15 s yielded the smallest difference (less than 10% of recording time at each intensity) against EMG-derived PA levels.

          Discussion

          This research provides novel insight on muscle activity and thereby on neuromuscular loading of major locomotor muscles during normal daily activities of children. While EMG and ACC provided similar estimates of sedentary time in 13 typical PA tasks, duration of light, moderate and vigorous PA varied considerably between the methods especially during walking, stair negotiation, crawling, swinging and trampoline jumping. Evenson et al.’s ( 2008) cut-off points with ≤15 s epoch provided similar classification of PA than EMG during daily life. Compared to impacts recorded using ACC, EMG can provide understanding on children’s neuromuscular loading during motor tasks that is useful when studying effects of PA interventions on, and development of, motor competence and coordination.

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          Most cited references35

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          A Developmental Perspective on the Role of Motor Skill Competence in Physical Activity: An Emergent Relationship

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            Motor Competence and its Effect on Positive Developmental Trajectories of Health.

            In 2008, Stodden and colleagues took a unique developmental approach toward addressing the potential role of motor competence in promoting positive or negative trajectories of physical activity, health-related fitness, and weight status. The conceptual model proposed synergistic relationships among physical activity, motor competence, perceived motor competence, health-related physical fitness, and obesity with associations hypothesized to strengthen over time. At the time the model was proposed, limited evidence was available to support or refute the model hypotheses. Over the past 6 years, the number of investigations exploring these relationships has increased significantly. Thus, it is an appropriate time to examine published data that directly or indirectly relate to specific pathways noted in the conceptual model. Evidence indicates that motor competence is positively associated with perceived competence and multiple aspects of health (i.e., physical activity, cardiorespiratory fitness, muscular strength, muscular endurance, and a healthy weight status). However, questions related to the increased strength of associations across time and antecedent/consequent mechanisms remain. An individual's physical and psychological development is a complex and multifaceted process that synergistically evolves across time. Understanding the most salient factors that influence health and well-being and how relationships among these factors change across time is a critical need for future research in this area. This knowledge could aid in addressing the declining levels of physical activity and fitness along with the increasing rates of obesity across childhood and adolescence.
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              Validation of wearable monitors for assessing sedentary behavior.

              A primary barrier to elucidating the association between sedentary behavior (SB) and health outcomes is the lack of valid monitors to assess SB in a free-living environment. The purpose of this study was to examine the validity of commercially available monitors to assess SB. Twenty overweight (mean ± SD: body mass index = 33.7 ± 5.7 kg·m(-2)) inactive, office workers age 46.5 ± 10.7 yr were directly observed for two 6-h periods while wearing an activPAL (AP) and an ActiGraph GT3X (AG). During the second observation, participants were instructed to reduce sitting time. We assessed the validity of the commonly used cut point of 100 counts per minute (AG100) and several additional AG cut points for defining SB. We used direct observation (DO) using focal sampling with duration coding to record either sedentary (sitting/lying) or nonsedentary behavior. The accuracy and precision of the monitors and the sensitivity of the monitors to detect reductions in sitting time were assessed using mixed-model repeated-measures analyses. On average, the AP and the AG100 underestimated sitting time by 2.8% and 4.9%, respectively. The correlation between the AP and DO was R2 = 0.94, and the AG100 and DO sedentary minutes was R2 = 0.39. Only the AP was able to detect reductions in sitting time. The AG 150-counts-per-minute threshold demonstrated the lowest bias (1.8%) of the AG cut points. The AP was more precise and more sensitive to reductions in sitting time than the AG, and thus, studies designed to assess SB should consider using the AP. When the AG monitor is used, 150 counts per minute may be the most appropriate cut point to define SB.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                21 August 2018
                2018
                : 6
                : e5437
                Affiliations
                [1 ]Neuromuscular Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä , Jyväskylä, Finland
                [2 ]Active Life Lab, South-Eastern Finland University of Applied Sciences , Mikkeli, Finland
                [3 ]Faculty of Sport and Health Sciences, University of Jyväskylä , Jyväskylä, Finland
                Article
                5437
                10.7717/peerj.5437
                6108314
                679011b3-678e-4896-b2a3-7e0f050ffb72
                ©2018 Gao et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 16 March 2018
                : 24 July 2018
                Funding
                Funded by: Ministry of Education and Culture
                Award ID: OKM/59/626/2016
                This study is funded by Ministry of Education and Culture (OKM/59/626/2016), Finland. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Kinesiology
                Public Health

                electromyography,inactivity,young children,muscle activity,sedentary time,accelerometer

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