Search Results

Background : Little is known about the influence of 24-hour movement behaviors on children’s psychosocial health when transitioning from primary to secondary school. This study described changes in 24-hour domain-specific movement behavior composition and explored their associations with changes in psychosocial health during this transition. Methods : Data were drawn from the Longitudinal Study of Australian Children. The analytical sample (n = 909) included children who were enrolled in primary school at baseline (2010) and in secondary school at follow-up (2012). Time spent in 8 domains of movement behaviors was derived from the child-completed time-use diaries. Psychosocial health was examined using the self-report version of the Strengths and Difficulties Questionnaires. Analyses included repeated-measures multivariate analysis of variance and compositional regression. Results : Children reported engaging in more social activities and sleeping less over the transition period. Increased time spent in social activities (β _ilr  = −0.06, P = .014) and recreational screen use (β _ilr  = −0.17, P = .003) (relative to other domains) were associated with decreased prosocial behavior in boys. Changes in movement behavior composition were not associated with changes in girls’ psychosocial health. Conclusion : This study found considerable changes in children’s 24-hour movement behavior composition, but a lack of consistent association with changes in psychosocial health during the primary to secondary school transition.

Background: Tummy time is recommended by the World Health Organization as part of its global movement guidelines for infant physical activity. To enable objective measurement of tummy time, accelerometer wear and nonwear time requires validation. The purpose of this study was to validate GENEActiv wear and nonwear time for use in infants. Methods: The analysis was conducted on accelerometer data from 32 healthy infants (4–25 wk) wearing a GENEActiv (right hip) while completing a positioning protocol (3 min each position). Direct observation (video) was compared with the accelerometer data. The accelerometer data were analyzed by receiver operating characteristic curves to identify optimal cut points for second-by-second wear and nonwear time. Cut points (accelerometer data) were tested against direct observation to determine performance. Statistical analysis was conducted using leave-one-out validation and Bland–Altman plots. Results: Mean temperature (0.941) and z-axis (0.889) had the greatest area under the receiver operating characteristic curve. Cut points were 25.6°C (temperature) and −0.812g (z-axis) and had high sensitivity (0.84, 95% confidence interval, 0.838–0.842) and specificity (0.948, 95% confidence interval, 0.944–0.948). Conclusions: Analyzing GENEActiv data using temperature (>25.6°C) and z-axis (greater than −0.812g) cut points can be used to determine wear time among infants for the purpose of measuring tummy time.

Background: This study examined the associations between environmental characteristics of early childhood education and care (ECEC) centers and 1-year change in toddlers’ physical activity and sedentary behavior while at the centers. Methods: Data from 292 toddlers from the GET-UP! study were analyzed. Environmental characteristics of ECEC centers were rated using the Infant/Toddler Environment Rating Scale-revised edition at baseline. Children’s physical activity and sedentary behavior in the centers were assessed using activPAL devices, at baseline and at 1-year follow-up. Linear mixed models were performed to examine the associations between the environmental characteristics and change in the proportion of time spent in physical activity and sedentary behavior. Results: Compared with baseline, children spent a higher proportion of time in sedentary behavior (sitting) but a lower proportion of time in standing and physical activity (stepping) while at ECEC centers, at 1-year follow-up. The environmental characteristics “interaction” (B = −1.39; P = .01) and “program structure” (B = −1.15; P = .04) were negatively associated with change in the proportion of time spent in physical activity. Conclusion: Better “interaction” and “program structure” may preclude children’s physical activity from declining over time and may be considered important features to target in future interventions in ECEC centers aiming at promoting active lifestyles.

Background: Although there is increasing evidence regarding children’s screen time, little is known about children’s sitting. This study aimed to determine the correlates of screen time and sitting in 6- to 8-year-old children. Methods: In 2011–2012, parents in the Healthy Active Preschool and Primary Years (HAPPY) study (n = 498) reported their child’s week/weekend day recreational screen time and potential correlates. ActivPALs^™ measured children’s nonschool sitting. In model 1, linear regression analyses were performed, stratified by sex and week/weekend day and controlling for age, clustered recruitment, and activPAL^™ wear time (for sitting analyses). Correlates significantly associated with screen time or sitting (P < .05) were included in model 2. Results: Children (age 7.6 y) spent 99.6 and 119.3 minutes per day on week and weekend days engaging in screen time and sat for 119.3 and 374.6 minutes per day on week and weekend days, respectively. There were no common correlates for the 2 behaviors. Correlates largely differed by sex and week/weekend day. Modifiable correlates of screen time included television in the child’s bedroom and parental logistic support for, encouragement of, and coparticipation in screen time. Modifiable correlates of sitting included encouragement of and coparticipation in physical activity and provision of toys/equipment for physical activity. Conclusions: Interventions may benefit from including a range of strategies to ensure that all identified correlates are targeted.

Background: In 2018, South Africa developed 24-hour movement behavior guidelines for children from birth to 5 years. This study reports on the stakeholder consultation as part of this development process. Methods: An online survey was completed by 197 participants; 9 focus groups (with parents/caregivers, early childhood development practitioners, and community health workers, total n = 70) were conducted, and a meeting with stakeholders from government and nongovernment organizations (n = 15) was held. Results: In the online survey, stakeholders overwhelmingly agreed with the guidelines (97.0%) and recognized the benefit of putting the guidelines into practice (88.8%). Most online survey respondents (88.3%) reported that the guidelines would benefit all South African children equally. Responses to open-ended questions in the online survey and focus group discussions revealed issues including safety and nutrition of children, perceived parental barriers to using the guidelines, and education. Training and provision of educational materials were identified from all stakeholders as key in the dissemination and implementation of the guidelines. Conclusions: The findings informed the development of the South African 24-hour movement behavior guidelines and revealed several important factors to address in the dissemination and implementation of the guidelines to ensure that they are applicable and equitable in South Africa.

Background: This article summarizes the approach taken to develop UK Chief Medical Officers’ physical activity guidelines for the Under 5s, 2019. Methods: The Grading of Recommendations Assessment, Development and Evaluation (GRADE)-Adaptation, Adoption, De Novo Development (ADOLOPMENT) approach was used, based on the guidelines from Canada and Australia, with evidence updated to February 2018. Recommendations were based on the associations between (1) time spent in sleep, sedentary time, physical activity, and 10 health outcomes and (2) time spent in physical activity and sedentary behavior on sleep outcomes (duration and latency). Results: For many outcomes, more time spent in physical activity and sleep (up to a point) was beneficial, as was less time spent in sedentary behavior. The authors present, for the first time, evidence in GRADE format on behavior type–outcome associations for infants, toddlers, and preschoolers. Stakeholders supported all recommendations, but recommendations on sleep and screen time were not accepted by the Chief Medical Officers; UK guidelines will refer only to physical activity. Conclusions: This is the first European use of GRADE-ADOLOPMENT to develop physical activity guidelines. The process is robust, rapid, and inexpensive, but the UK experience illustrates a number of challenges that should help development of physical activity guidelines in future.

This study examined the classification accuracy of the activPAL, including total time spent sedentary and total number of breaks in sedentary behavior (SB) in 4- to 6-year-old children. Forty children aged 4–6 years (5.3 ± 1.0 years) completed a ~150-min laboratory protocol involving sedentary, light, and moderate- to vigorous-intensity activities. Posture was coded as sit/lie, stand, walk, or other using direct observation. Posture was classified using the activPAL software. Classification accuracy was evaluated using sensitivity, specificity and area under the receiver operating characteristic curve (ROC-AUC). Time spent in each posture and total number of breaks in SB were compared using paired sample t-tests. The activPAL showed good classification accuracy for sitting (ROC-AUC = 0.84) and fair classification accuracy for standing and walking (0.76 and 0.73, respectively). Time spent in sit/lie and stand was overestimated by 5.9% (95% CI = 0.6−11.1%) and 14.8% (11.6−17.9%), respectively; walking was underestimated by 10.0% (−12.9−7.0%). Total number of breaks in SB were significantly overestimated (55 ± 27 over the course of the protocol; p < .01). The activPAL performed well when classifying postures in young children. However, the activPAL has difficulty classifying other postures, such as kneeling. In addition, when predicting time spent in different postures and total number of breaks in SB the activPAL appeared not to be accurate.