Background: It remains unclear if schoolyard interventions “just” provide more opportunities for those children who are already active. The authors wanted to investigate schoolyard use and physical activity (PA) among the least-active children during recess following schoolyard renewals. Methods: An intervention study design with preresults and postresults comparison was used. Accelerometer and global positioning system data were collected at 6 Danish schools from 553 children at baseline and 439 after renewals (grades 4–9). Based on mean minutes of recess moderate to vigorous PA per child per school, the least-active children were defined as all children in the lowest activity quartile at baseline and follow-up, respectively. Results: One hundred and thirty-five children (70% girls) at baseline and 108 (76% girls) at follow-up were categorized as the least-active children. At follow-up they accumulated more time (12.1 min/d) and PA (4.4 min/d) in the schoolyard during recess compared with baseline. The difference in schoolyard PA found for the least-active children was relatively small compared with the difference for all children. Conclusions: Solely improving the physical schoolyard environment seemed to have limited impact on the least-active children’s PA. Future studies should investigate the complex interrelations between the least-active children and the entire schoolyard environment.
Charlotte Skau Pawlowski, Henriette Bondo Andersen, and Jasper Schipperijn
Sanne L.C. Veldman, Rachel A. Jones, Rebecca M. Stanley, Dylan P. Cliff, Stewart A. Vella, Steven J. Howard, Anne-Maree Parrish, and Anthony D. Okely
Background: The aim of this study was to examine the efficacy of an embedded after-school intervention, on promoting physical activity and academic achievement in primary-school-aged children. Methods: This 6-month, 2-arm cluster randomized controlled trial involved 4 after-school centers. Two centers were randomly assigned to the intervention, which involved training the center staff on and implementing structured physical activity (team sports and physical activity sessions for 75 min) and academic enrichment activities (45 min). The activities were implemented 3 afternoons per week for 2.5 hours. The control centers continued their usual after-school care practice. After-school physical activity (accelerometry) and executive functions (working memory, inhibition, and cognitive flexibility) were assessed pre- and postintervention. Results: A total of 60 children were assessed (7.7 [1.8] y; 50% girls) preintervention and postintervention (77% retention rate). Children in the intervention centers spent significantly more time in moderate to vigorous physical activity (adjusted difference = 2.4%; 95% confidence interval, 0.6 to 4.2; P = .026) and scored higher on cognitive flexibility (adjusted difference = 1.9 units; 95% confidence interval, 0.9 to 3.0; P = .009). About 92% of the intervention sessions were implemented. The participation rates varied between 51% and 94%. Conclusion: This after-school intervention was successful at increasing moderate to vigorous physical activity and enhancing cognitive flexibility in children. As the intervention was implemented by the center staff and local university students, further testing for effectiveness and scalability in a larger trial is required.
Tatiana Plekhanova, Alex V. Rowlands, Tom Yates, Andrew Hall, Emer M. Brady, Melanie Davies, Kamlesh Khunti, and Charlotte L. Edwardson
Introduction: This study examined the equivalency of sleep estimates from Axivity, GENEActiv, and ActiGraph accelerometers worn on the nondominant and dominant wrists and with and without using a sleep log to guide the algorithm. Methods: 47 young adults wore an Axivity, GENEActiv, and ActiGraph accelerometer continuously on both wrists for 4–7 days. Sleep time, sleep window, sleep efficiency, sleep onset, and wake time were produced using the open-source software (GGIR). For each outcome, agreement between accelerometer brands, dominant and nondominant wrists, and with and without use of a sleep log, was examined using pairwise 95% equivalence tests (±10% equivalence zone) and intraclass correlation coefficients (ICCs), with 95% confidence intervals and limits of agreement. Results: All sleep outcomes were within a 10% equivalence zone irrespective of brand, wrist, or use of a sleep log. ICCs were poor to good for sleep time (ICCs ≥ .66) and sleep window (ICCs ≥ .56). Most ICCs were good to excellent for sleep efficiency (ICCs ≥ .73), sleep onset (ICCs ≥ .88), and wake time (ICCs ≥ .87). There were low levels of mean bias; however, there were wide 95% limits of agreement for sleep time, sleep window, sleep onset, and wake time outcomes. Sleep time (up to 25 min) and sleep window (up to 29 min) outcomes were higher when use of the sleep log was not used. Conclusion: The present findings suggest that sleep outcomes from the Axivity, GENEActiv, and ActiGraph, when analyzed identically, are comparable across studies with different accelerometer brands and wear protocols at a group level. However, caution is advised when comparing studies that differ on sleep log availability.
Jeffrey Sallen, Christian Andrä, Sebastian Ludyga, Manuel Mücke, and Christian Herrmann
Background: The relationship between engagement in physical activity and the development of motor competence (MC) is considered to be reciprocal and dynamic throughout childhood and adolescence. The 10-month follow-up study aimed to explore this reciprocal relationship and investigated whether the relationship is mediated by the corresponding self-perception of MC (PMC). Methods: A total of 51 children aged between 10 and 11 years (M = 10.27 [0.45]) participated in the study (52.9% boys, 47.1% girls). As an indicator for physical activity, the average vigorous physical activity (VPA) per day was measured by ActiGraph accelerometers. Two aspects of MC and PMC were recorded: self-movement and object movement. Saturated pathway models in a cross-lagged panel design with 2 measurement points were analyzed. Results: Reciprocal and direct relationships between VPA and MC object movement respectively MC self-movement were not found in longitudinal analyses with PMC as a mediator. Indirect effects of MC at t1 on VPA at t2 via PMC were identified (self-movement: β = 0.13, 95% confidence interval, 0.04 to 0.26; object movement: β = 0.14, 95% confidence interval, 0.01 to 0.49). Conclusion: The results highlight the importance of MC and PMC in promoting children’s VPA. However, VPA does not drive the development of MC.
Samuel R. Nyman
Despite interest as to the benefits of Tai Chi, there remains a controversy over its effectiveness as an exercise intervention for preventing falls among older adults. This review synthesizes the evidence base with a focus on meta-analyses and randomized controlled trials with community-dwelling older adults. It provides a critical lens on the evidence and quality of the trials. High-quality evidence suggests that Tai Chi is an effective intervention for preventing falls in community settings; however, there is unclear evidence for long-term care facilities and an absence of evidence for hospital settings. When compared directly with other exercise interventions, Tai Chi may offer a superior strategy for reducing falls through its benefits on cognitive functioning. Using data from the current Cochrane review, a new synthesis is presented suggesting that 71–81% of community-dwelling older adults are adherent to class-based Tai Chi interventions. The practical opportunities and challenges for practitioners are discussed.
Pazit Levinger and Keith D. Hill
Juliana S. Oliveira, Marina B. Pinheiro, Nicola Fairhall, Sarah Walsh, Tristan Chesterfield Franks, Wing Kwok, Adrian Bauman, and Catherine Sherrington
Background: Frailty and sarcopenia are common age-related conditions associated with adverse outcomes. Physical activity has been identified as a potential preventive strategy for both frailty and sarcopenia. The authors aimed to investigate the association between physical activity and prevention of frailty and sarcopenia in people aged 65 years and older. Methods: The authors searched for systematic reviews (January 2008 to November 2019) and individual studies (January 2010 to March 2020) in PubMed. Eligible studies were randomized controlled trials and longitudinal studies that investigated the effect of physical activity on frailty and/or sarcopenia in people aged 65 years and older. The Grading of Recommendations Assessment, Development and Evaluation approach was used to rate certainty of evidence. Results: Meta-analysis showed that physical activity probably prevents frailty (4 studies; frailty score pooled standardized mean difference, 0.24; 95% confidence interval, 0.04–0.43; P = .017, I 2 = 57%, moderate certainty evidence). Only one trial investigated physical activity for sarcopenia prevention and did not provide conclusive evidence (risk ratio 1.08; 95% confidence interval, 0.10–12.19). Five observational studies showed positive associations between physical activity and frailty or sarcopenia prevention. Conclusions: Physical activity probably prevents frailty among people aged 65 years and older. The impact of physical activity on the prevention of sarcopenia remains unknown, but observational studies indicate the preventive role of physical activity.
Kristin Suorsa, Anna Pulakka, Tuija Leskinen, Jaana Pentti, Andreas Holtermann, Olli J. Heinonen, Juha Sunikka, Jussi Vahtera, and Sari Stenholm
Background: The accuracy of wrist-worn accelerometers in identifying sedentary time has been scarcely studied in free-living conditions. The aim of this study was to compare daily sedentary time estimates between a thigh-worn accelerometer, which measured sitting and lying postures, and a wrist-worn accelerometer, which measured low levels of movement. Methods: The study population consisted of 259 participants (Mage = 62.8 years, SD = 0.9) from the Finnish Retirement and Aging Study (FIREA). Participants wore an Axivity AX3 accelerometer on their mid-thigh and an Actigraph wActiSleep-BT accelerometer on their non-dominant wrist simultaneously for a minimum of 4 days in free-living conditions. Two definitions to estimate daily sedentary time were used for data from the wrist-worn accelerometer: 1) the count cutpoint, ≤1853 counts per minute; and 2) the Euclidean Norm Minus One (ENMO) cutpoint, <30 mg. Results: Compared to the thigh-worn accelerometer, daily sedentary time estimate was 63 min (95% confidence interval [CI] = −53 to −73) lower by the count cutpoint and 50 min (95% CI = 34 to 67) lower by the ENMO cutpoint. The limits of agreement in daily sedentary time estimates between the thigh- and cutpoint methods for wrist-worn accelerometers were wide (the count cutpoint: −117 to 243, the ENMO cutpoint: −212 to 313 min). Conclusions: Currently established cutpoint-based methods to estimate sedentary time from wrist-worn accelerometers result in underestimation of daily sedentary time compared to posture-based estimates of thigh-worn accelerometers. Thus, sedentary time estimates obtained from wrist-worn accelerometers using currently available cutpoint-based methods should be interpreted with caution and future work is needed to improve their accuracy.
Daniel H. Aslan, Joshua M. Collette, and Justus D. Ortega
The decline of walking performance is a key determinant of morbidity among older adults. Healthy older adults have been shown to have a 15–20% lower walking economy compared with young adults. However, older adults who run for exercise have a higher walking economy compared with older adults who walk for exercise. Yet, it remains unclear if other aerobic exercises yield similar improvements on walking economy. The purpose of this study was to determine if regular bicycling exercise affects walking economy in older adults. We measured metabolic rate while 33 older adult “bicyclists” or “walkers” and 16 young adults walked on a level treadmill at four speeds between (0.75–1.75 m/s). Across the range of speeds, older bicyclists had a 9–17% greater walking economy compared with older walkers (p = .009). In conclusion, bicycling exercise mitigates the age-related deterioration of walking economy, whereas walking for exercise has a minimal effect on improving walking economy.