Variability exists in children's activity patterns due to the association with environmental, social, demographic, and inter-individual factors. This study described accelerometer assessed physical ...activity patterns of high and low active children during segmented school week days whilst controlling for potential correlates.
Two hundred and twenty-three children (mean age: 10.7 ± 0.3 yrs, 55.6% girls, 18.9% overweight/obese) from 8 north-west England primary schools wore ActiGraph GT1M accelerometers for 7 consecutive days during autumn of 2009. ActiGraph counts were converted to minutes of moderate (MPA), vigorous (VPA) and moderate-to-vigorous (MVPA) physical activity. Children were classified as high active (HIGH) or low active (LOW) depending on the percentage of week days they accumulated at least 60 minutes of MVPA. Minutes spent in MPA and VPA were calculated for school time and non-school time and for five discrete school day segments (before-school, class time, recess, lunchtime, and after-school). Data were analysed using multi-level modelling.
The HIGH group spent significantly longer in MPA and/or VPA before-school, during class time, lunchtime, and after-school (P < .05), independent of child and school level factors. The greatest differences occurred after-school (MPA = 5.5 minutes, VPA = 3.8 minutes, P < 0.001). MPA and VPA were also associated with gender, BMI z-score, number of enrolled children, playground area per student, and temperature, depending on the segment analysed.The additive effect of the segment differences was that the HIGH group accumulated 12.5 minutes per day more MVPA than the LOW group.
HIGH active children achieved significantly more MPA and VPA than LOW active during four of the five segments of the school day when analyses were adjusted for potential correlates. Physical activity promotion strategies targeting low active children during discretionary physical activity segments of the day, and particularly via structured afterschool physical activity programs may be beneficial.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
PURPOSEThis study aimed to 1) explore children’s compliance to wearing wrist- and hip-mounted accelerometers, 2) compare children’s physical activity (PA) derived from raw accelerations of wrist and ...hip, and 3) examine differences in raw and counts PA measured by hip-worn accelerometry.
METHODSOne hundred and twenty-nine 9- to 10-yr-old children wore a wrist-mounted GENEActiv accelerometer (GAwrist) and a hip-mounted ActiGraph GT3X+ accelerometer (AGhip) for 7 d. Both devices measured raw accelerations, and the AGhip also provided count-based data.
RESULTSMore children wore the GAwrist than those from the AGhip regardless of wear time criteria applied (P < 0.001–0.035). Raw data signal vector magnitude (r = 0.68), moderate PA (MPA) (r = 0.81), vigorous PA (VPA) (r = 0.85), and moderate-to-vigorous PA (MVPA) (r = 0.83) were strongly associated between devices (P < 0.001). GAwrist signal vector magnitude (P = 0.001), MPA (P = 0.037), VPA (P = 0.002), and MVPA (P = 0.016) were significantly greater than those from the AGhip. According to GAwrist raw data, 86.9% of children engaged in at least 60 min·d of MVPA, compared with 19% for AGhip. ActiGraph MPA (raw) was 42.00 ± 1.61 min·d compared with 35.05 ± 0.99 min·d (counts) (P = 0.02). ActiGraph VPA was 7.59 ± 0.46 min·d (raw) and 37.06 ± 1.85 min·d (counts; P = 0.19).
CONCLUSIONSIn children, accelerometer wrist placement promotes superior compliance than the hip. Raw accelerations were significantly higher for GAwrist compared with those for AGhip possibly because of placement location and technical differences between devices. AGhip PA calculated from raw accelerations and counts differed substantially, demonstrating that PA outcomes derived from cut points for raw output and counts cannot be directly compared.
Movement behaviours performed over a finite period such as a 24 h day are compositional data. Compositional data exist in a constrained simplex geometry that is incongruent with traditional ...multivariate analytical techniques. However, the expression of compositional data as log-ratio co-ordinate systems transfers them to the unconstrained real space, where standard multivariate statistics can be used. This study aimed to use a compositional data analysis approach to examine the adiposity and cardiorespiratory fitness predictions of time reallocations between children's daily movement behaviours.
This study used cross-sectional data from the Active Schools: Skelmersdale study, which involved Year 5 children from a low-income community in northwest England (n = 169). Measures included accelerometer-derived 24 h activity (sedentary time ST, light physical activity LPA, moderate-to-vigorous physical activity MVPA, and sleep), cardiorespiratory fitness determined by the 20 m shuttle run test, objectively measured height, weight and waist circumference (from which zBMI and percent waist circumference-to-height ratio (%WHtR) were derived) and sociodemographic covariates. Log-ratio multiple linear regression models were used to predict adiposity and fitness for the mean movement behaviour composition, and for new compositions where fixed durations of time had been reallocated from one behaviour to another, while the remaining behaviours were unchanged. Predictions were also made for reallocations of fixed durations of time using the mean composition of three different weight status categories (underweight, normal-weight, and overweight/obese) as the starting point.
Replacing MVPA with any other movement behaviour around the mean movement composition predicted higher adiposity and lower CRF. The log-ratio model predictions were asymmetrical: when time was reallocated to MVPA from sleep, ST, or LPA, the estimated detriments to fitness and adiposity were larger in magnitude than the estimated benefits of time reallocation from MVPA to sleep, ST or LPA. The greatest differences in fitness and fatness for reallocation of fixed duration of MVPA were predicted at the mean composition of overweight/obese children.
Findings reinforce the key role of MVPA for children's health. Reallocating time from ST and LPA to MVPA in children is advocated in school, home, and community settings.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Physical activity (PA) decreases during the transition from childhood to adolescence, with larger declines observed in girls. School-based interventions are considered the most promising approach for ...increasing adolescents' PA levels although, it is unclear which types of school-based interventions have the greatest impact. The objective of this systematic review is to assess the impact and design of school-based PA interventions targeting adolescent girls. A systematic search was conducted using four electronic databases (PubMed, Web of Science, SPORTDiscus and PsychInfo). This systematic review was registered with PROSPERO (Registration number: CRD42016037428) and PRISMA guidelines (2009) were followed throughout. Twenty studies were identified as meeting the inclusion criteria and were included in a narrative synthesis. Seventeen studies were eligible for inclusion in a meta-analysis. There was a significant small positive treatment effect for school-based PA interventions for adolescent girls (k=17, g=0.37, p<0.05). After an outlier was removed (residual z=7.61) the average treatment effect was significantly reduced, indicating a very small positive effect (k=16, g=0.07, p=0.05). Subgroup analysis revealed very small significant effects for multi-component interventions (k=7, g=0.09, p<0.05), interventions underpinned by theory (k=12, g=0.07, p<0.05), and studies with a higher risk of bias (k=13, g=0.09, p<0.05). Intervention effects were very small which indicates that changing PA behaviors in adolescent girls through school-based interventions is challenging. Multi-component interventions and interventions underpinned by theory may be the most effective approaches to positively change adolescent girls' PA.
•Interventions have a very small effect on adolescent girls' PA levels.•Multi-component school-based PA interventions show promise.•Interventions underpinned by theory may be more effective.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
UK and global policies recommend whole-school approaches to improve childrens' inadequate physical activity (PA) levels. Yet, recent meta-analyses establish current interventions as ineffective due ...to suboptimal implementation rates and poor sustainability. To create effective interventions, which recognise schools as complex adaptive sub-systems, multi-stakeholder input is necessary. Further, to ensure 'systems' change, a framework is required that identifies all components of a whole-school PA approach. The study's aim was to co-develop a whole-school PA framework using the double diamond design approach (DDDA).
Fifty stakeholders engaged in a six-phase DDDA workshop undertaking tasks within same stakeholder (n = 9; UK researchers, public health specialists, active schools coordinators, headteachers, teachers, active partner schools specialists, national organisations, Sport England local delivery pilot representatives and international researchers) and mixed (n = 6) stakeholder groupings. Six draft frameworks were created before stakeholders voted for one 'initial' framework. Next, stakeholders reviewed the 'initial' framework, proposing modifications. Following the workshop, stakeholders voted on eight modifications using an online questionnaire.
Following voting, the Creating Active Schools Framework (CAS) was designed. At the centre, ethos and practice drive school policy and vision, creating the physical and social environments in which five key stakeholder groups operate to deliver PA through seven opportunities both within and beyond school. At the top of the model, initial and in-service teacher training foster teachers' capability, opportunity and motivation (COM-B) to deliver whole-school PA. National policy and organisations drive top-down initiatives that support or hinder whole-school PA. To the authors' knowledge, this is the first time practitioners, policymakers and researchers have co-designed a whole-school PA framework from initial conception. The novelty of CAS resides in identifying the multitude of interconnecting components of a whole-school adaptive sub-system; exposing the complexity required to create systems change. The framework can be used to shape future policy, research and practice to embed sustainable PA interventions within schools. To enact such change, CAS presents a potential paradigm shift, providing a map and method to guide future co-production by multiple experts of PA initiatives 'with' schools, while abandoning outdated traditional approaches of implementing interventions 'on' schools.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Like many countries in sub-Saharan Africa, Kenya has experienced rapid urbanization in recent years. Despite the distinct socioeconomic and environmental differences, few studies have examined the ...adherence to movement guidelines in urban and rural areas. This cross-sectional study aimed at examining compliance to the 24-hour movement guidelines and their correlates among children from urban and rural Kenya.
Children (n = 539) aged 11.1 ± 0.8 years (52% female) were recruited from 8 urban and 8 rural private and public schools in Kenya. Physical activity (PA) and sleep duration were estimated using 24-h raw data from wrist-worn accelerometers. Screen time (ST) and potential correlates were self- reported. Multi-level logistic regression was applied to identify correlates of adherence to combined and individual movement guidelines.
Compliance with the combined movement guidelines was low overall (7%), and higher among rural (10%) than urban (5%) children. Seventy-six percent of rural children met the individual PA guidelines compared to 60% urban children while more rural children also met sleep guidelines (27% vs 14%). The odds of meeting the combined movement guidelines reduced with age (OR = 0.55, 95% CI = 0.35-0.87, p = 0.01), was greater among those who could swim (OR = 3.27, 95% CI = 1.09-9.83, p = 0.04), and among those who did not engage in ST before school (OR = 4.40, 95% CI = 1.81-10.68, p<0.01). The odds of meeting PA guidelines increased with the number of weekly physical education sessions provided at school (OR = 2.1, 95% CI = 1.36-3.21, p<0.01) and was greater among children who spent their lunch break walking (OR = 2.52, 95% CI = 1.15-5.55, p = 0.02) or running relative to those who spent it sitting (OR = 2.33, 95% CI = 1.27-4.27, p = 0.01).
Prevalence of meeting movement guidelines among Kenyan children is low and of greatest concern in urban areas. Several correlates were identified, particularly influential were features of the school day, School is thus a significant setting to promote a healthy balance between sleep, sedentary time, and PA.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Twenty-four-hour movement behaviours are gaining attention in the research community. However, no study has addressed how 24-h activity profiles vary between structured and less structured days and ...whether an unfavourable activity profile is associated with childhood obesity. We aimed to analyse differences between school day and weekend day 24-h activity profiles and their associations with adiposity indicators among children and adolescents.
Participants were 382 children and 338 adolescents who wore wrist accelerometers for 24 hours a day for seven consecutive days. The 24-h activity profile expressed by the average acceleration (AvAcc) and intensity gradient (IG) were estimated from multi-day raw accelerometer data. Adiposity indicators included body mass index (BMI) z-score, fat mass percentage (FM%), fat mass index (FMI), and visceral adipose tissue (VAT). Multiple linear regression of activity profile metrics and adiposity indicators was performed separately for school and weekend days.
Weekend days AvAcc and IG were lower compared to school days in both age groups (p <0.001 for all). Specifically, AvAcc was lower by 9.4% and 11.3% in children and adolescents, respectively. IG on weekend days was lower (more negative) by 3.4% in children and 3.1% in adolescents. Among children, on school days AvAcc and IG were negatively associated with FM%, FMI, and VAT, whilst on weekend days AvAcc was positively associated with BMI z-score, FMI, and VAT (p < 0.05 for all). Among adolescents, negative associations were found between weekend day AvAcc and IG and FM% and FMI (p < 0.05 for all), respectively.
This study confirms the importance of 24-h activity profile as a potentially protective factor against excess adiposity. The variability of movement behaviours during structured and less structured days should be considered when optimizing the 24-h movement behaviours to prevent childhood obesity.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background
It has been reported that boys’ and girls’ physical activity (PA) levels decline throughout adolescence. Boys are at risk of physical inactivity during adolescence; however, in ...intervention research, they are an under-represented group relative to girls. It is suggested that the school environment may be central to developing interventions that support adolescents in meeting the current PA guidelines. The aim of this systematic review and meta-analysis was to investigate the efficacy of school-based physical activity interventions for improving muscular fitness (MF) in adolescent males.
Methods
This systematic review and meta-analysis followed the preferred reporting systems for meta-analyses guidelines and was registered on PROSPERO (Registration number: CRD42018091023). Eligible studies were published in English within peer-reviewed articles. Searches were conducted in three databases, with an additional grey literature search in Google Scholar. Studies investigating MF outcomes were included.
Results
There were 43 data sets identified across 11 studies, from seven countries. Overall methodological quality of the studies was moderate-to-strong. Interventions targeting MF evidenced a small-to-medium effect (
g
= 0.32, CI 0.17, 0.48,
p
< 0.00). Subgroup analyses of MF delivery method resulted in small-to-medium effects: upper limb MF measures (
g
= 0.28, 95% CI − 0.02, 0.58,
p
= 0.07), lower limb MF measures (
g
= 0.28, 95% CI 0.09, 0.68,
p
= 0.03), combined MF activities (
g
= 0.24, 95% CI − 0.04 to 0.49,
p
= 0.05), plyometric activities (
g
= 0.39, 95% CI 0.09, 0.68,
p
= 0.01), body weight (
g
= 0.27, 95% CI − 0.10, 0.65,
p
= 0.15), and traditional MF methods (
g
= 0.43, 95% CI 0.09, 0.78,
p
= 0.01).
Conclusions
School-based interventions which aimed to increase MF outcomes in adolescent boys demonstrated small-to-moderate effects. Traditional and plyometric methods of resistance training appear to be the most effective form of PA delivery in adolescent males. More quality research is required to assess the impact of MF delivered in the school environment to inform future intervention design.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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