Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium.

BACKGROUND AND AIMS: Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers. METHODS: Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours. RESULTS: The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with -0.63 (95% confidence interval -0.48, -0.79), -0.43 (-0.25, -0.59), -0.40 (-0.25, -0.56), and -0.15 (0.05, -0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day. CONCLUSIONS: Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity.

Relationship of device measured physical activity type and posture with cardiometabolic health markers: pooled dose-response associations from the Prospective Physical Activity, Sitting and Sleep Consortium.

AIMS/HYPOTHESIS: The aim of this study was to examine the dose-response associations of device-measured physical activity types and postures (sitting and standing time) with cardiometabolic health. METHODS: We conducted an individual participant harmonised meta-analysis of 12,095 adults (mean ± SD age 54.5±9.6 years; female participants 54.8%) from six cohorts with thigh-worn accelerometry data from the Prospective Physical Activity, Sitting and Sleep (ProPASS) Consortium. Associations of daily walking, stair climbing, running, standing and sitting time with a composite cardiometabolic health score (based on standardised z scores) and individual cardiometabolic markers (BMI, waist circumference, triglycerides, HDL-cholesterol, HbA1c and total cholesterol) were examined cross-sectionally using generalised linear modelling and cubic splines. RESULTS: We observed more favourable composite cardiometabolic health (i.e. z score <0) with approximately 64 min/day walking (z score [95% CI] -0.14 [-0.25, -0.02]) and 5 min/day stair climbing (-0.14 [-0.24, -0.03]). We observed an equivalent magnitude of association at 2.6 h/day standing. Any amount of running was associated with better composite cardiometabolic health. We did not observe an upper limit to the magnitude of the dose-response associations for any activity type or standing. There was an inverse dose-response association between sitting time and composite cardiometabolic health that became markedly less favourable when daily durations exceeded 12.1 h/day. Associations for sitting time were no longer significant after excluding participants with prevalent CVD or medication use. The dose-response pattern was generally consistent between activity and posture types and individual cardiometabolic health markers. CONCLUSIONS/INTERPRETATION: In this first activity type-specific analysis of device-based physical activity, ~64 min/day of walking and ~5.0 min/day of stair climbing were associated with a favourable cardiometabolic risk profile. The deleterious associations of sitting time were fully attenuated after exclusion of participants with prevalent CVD and medication use. Our findings on cardiometabolic health and durations of different activities of daily living and posture may guide future interventions involving lifestyle modification.

Accelerometer and Survey Assessed Physical Activity in Children With Epilepsy: A Case-Controlled Study.

PURPOSE: Anecdotal evidence suggests that children with epilepsy (CWE) are limited in the frequency of their daily physical activity (PA). However, there is limited research utilizing device-based measures of PA. We compared levels of PA and sedentary behavior in CWE (11-15 y) and age- and gender-matched healthy controls. METHOD: Participants (n = 60 CWE [25 males, 35 females] and n = 49 controls [25 males, 24 females]) wore a Actigraph accelerometer (GT3X or GT3X+) for 7 consecutive days during waking hours and self-reported their PA and sedentary behaviors. CWE were compared with control children on time spent in different intensities of PA and on self-reported PA and sedentary behavior. Factors associated with PA were analyzed using linear regression. RESULTS: CWE spent less time in accelerometer assessed light (189.15 vs 215.01 min/d, P < .05) and vigorous PA (35.14 vs 44.28 min/d, P < .05) on weekdays compared with controls. There were no significant differences between CWE and control participants in accelerometer assessed time spent sedentary or time spent in PA on weekends. Among CWE, older children engaged in more reported sedentary behavior and younger children spent more time in most domains of PA (P < .05). Furthermore, CWE reported less PA than controls (P = .006). Sixteen percent of controls met World Health Organization PA guidelines compared with 10% of CWE. There was a positive relationship between accelerometer assessed PA and quality of life for CWE. CONCLUSION: CWE spent less time in light and moderate to vigorous PA on weekdays. Further research is needed to understand reasons for these differences.

The impact of selected methodological factors on data collection outcomes in observational studies of device-measured physical behaviour in adults: A systematic review.

BACKGROUND: Accelerometer measures of physical behaviours (physical activity, sedentary behaviour and sleep) in observational studies offer detailed insight into associations with health and disease. Maximising recruitment and accelerometer wear, and minimising data loss remain key challenges. How varying methods used to collect accelerometer data influence data collection outcomes is poorly understood. We examined the influence of accelerometer placement and other methodological factors on participant recruitment, adherence and data loss in observational studies of adult physical behaviours. METHODS: The review was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA). Observational studies of adults including accelerometer measurement of physical behaviours were identified using database (MEDLINE (Ovid), Embase, PsychINFO, Health Management Information Consortium, Web of Science, SPORTDiscus and Cumulative Index to Nursing & Allied Health Literature) and supplementary searches to May 2022. Information regarding study design, accelerometer data collection methods and outcomes were extracted for each accelerometer measurement (study wave). Random effects meta-analyses and narrative syntheses were used to examine associations of methodological factors with participant recruitment, adherence and data loss. RESULTS: 123 accelerometer data collection waves were identified from 95 studies (92.5% from high-income countries). In-person distribution of accelerometers was associated with a greater proportion of invited participants consenting to wear an accelerometer (+ 30% [95% CI 18%, 42%] compared to postal distribution), and adhering to minimum wear criteria (+ 15% [4%, 25%]). The proportion of participants meeting minimum wear criteria was higher when accelerometers were worn at the wrist (+ 14% [ 5%, 23%]) compared to waist. Daily wear-time tended to be higher in studies using wrist-worn accelerometers compared to other wear locations. Reporting of information regarding data collection was inconsistent. CONCLUSION: Methodological decisions including accelerometer wear-location and method of distribution may influence important data collection outcomes including recruitment and accelerometer wear-time. Consistent and comprehensive reporting of accelerometer data collection methods and outcomes is needed to support development of future studies and international consortia. Review supported by the British Heart Foundation (SP/F/20/150002) and registered (Prospero CRD42020213465).

Clustering of diet, physical activity and sedentary behaviour and related physical and mental health outcomes: a systematic review.

BACKGROUND: Physical activity (PA), sedentary behaviour (SB) and diet play an important role in the physical and mental health of young people. Understanding how these behaviours cluster, and the impact of clusters on health is important for the development of public health interventions. This review examines the prevalence of clusters of PA, sedentary time, and dietary behaviours, and how clusters relate to physical and mental health indicators among children, adolescents and young adults. METHODS: Electronic (PubMed, Web of Science and Scopus) and manual searches were conducted for articles that were (i) observational studies including children, adolescents and/or young adults aged 5-24 years, (ii) examined the 'patterning', 'clustering', or 'co-existence' of each of PA, dietary behaviour and SB, and (iii) published in English up to and including July 2022. In addition to information on clustering, data on physical and mental health outcomes were extracted where reported. Included studies were assessed using the Cochrane risk of bias for observational studies. A narrative synthesis was conducted due to high heterogeneity. This review was registered with PROSPERO (CRD42021230976). RESULTS: Forty-nine cross-sectional studies and four prospective cohort studies from eighteen countries reporting data from 778,415 individual participants were included. A broad range of clusters (n = 172) were found (healthy, unhealthy, and mixed). Mixed clusters were common (n = 98), and clusters of high diet quality, low PA and high SB were more prevalent in girls, while mixed clusters of high PA, high SB and low diet quality were more prevalent in boys. Unhealthy clusters comprising low moderate to vigorous PA, low consumption of fruits and vegetables, and high screen time were prevalent, particularly in those from lower socioeconomic status families. Compared to those with healthy behavioural clusters, those with unhealthy and mixed clusters had a higher adiposity, higher risk of cardiovascular disease, poorer mental health scores, and lower cardiorespiratory fitness. CONCLUSIONS: PA, SB and diet cluster in healthy, unhealthy and mixed patterns in young people that differ across sociodemographic characteristics. Unhealthy clusters are associated with poorer health outcomes. Intervention strategies targeting un-clustering multiple unhealthy behaviours should be developed and evaluated for their impact on health outcomes.

Body Size, Fatness and Skeletal Age in Female Youth Soccer Players.

Growth and maturation are central concerns in the organization of training and competitions in youth sports. This study examined maturity-associated variation in body size and adiposity among adolescent girls participating in competitive age group youth soccer. The sample included 441 players 10.08-16.73 years of age. Stature and body mass were measured and body composition was predicted. The Fels method was used to estimate skeletal age. Skeletally maturity status (late, average or early maturing) was based on the difference between chronological and skeletal age for each player. Mean stature approximated the 50th percentiles of the general population in all competitive age groups, while mean weight fluctuated between 50th and 75th percentiles. Age- and maturity-specific means for estimated fat mass ranged between 18.0% and 28.2%. The number of players classified as skeletally mature increased with competitive age groups (under-13: 0%; under-15: 8%; under-17: 49%). In general, early maturing girls tended to be heavier than their age group peers and especially when compared to late maturing players.

Effectiveness of interventions to increase device-measured physical activity in pregnant women: systematic review and meta-analysis of randomised controlled trials.

BACKGROUND: Interventions that provide pregnant women with opportunities to access and participate in physical activity have been shown to be beneficial to their health. Much of this evidence however has been based on self-reported physical activity data, which may be prone to inflated effects due to recall bias and social desirability bias. No previous synthesis of randomised controlled trials has assessed the effectiveness of these interventions using only device measured data, to assess their health benefits more accurately in pregnant women. This systematic review and meta-analysis aimed to address this evidence gap. DATA SOURCES: Cochrane Central Register of Controlled Trials, Medline, SportDiscus, APA PsycINFO, Embase and Web of Science databases were queried from inception up to December 2, 2021. An updated search of PubMed was conducted on May 16, 2022. STUDY ELIGIBILITY CRITERIA: Randomised controlled trials that recruited pregnant women, participating in any physical activity intervention (excluding interventions aimed entirely at body conditioning), compared with standard antenatal care (comparators), using device-measured total physical activity as an outcome were eligible for inclusion. METHODS: 3144 titles and abstracts were screened for eligibility, and 18 met the inclusion criteria. Data were analysed using random effect models, (standardised mean difference and mean difference), using data from baseline to last available follow-up (primary end point), and until between 24 to 30 weeks gestation. Gestational weight gain was also assessed at these timepoints in the included trials. RESULTS: No significant differences between the groups were found for total physical activity at last available follow-up or 24 to 30 weeks gestation (95% CI 0.03 to 0.27, p = 0.10: 95% CI -0.05 to 0.33, p = 0.15) respectively. On average, pregnant women randomised to a physical activity intervention completed 435 and 449 more steps per day than comparators at last available follow-up and at 24 to 30 weeks gestation (95% CI -0.5-870.6, p = 0.05: 95% CI 5.5-892.7, p = 0.05) respectively. Intervention participants also gained 0.69 kg less (95% CI -1.30 to -0.08, p = 0.03) weight than comparators. CONCLUSION: Based on device-measured data, interventions to promote physical activity during pregnancy have small but important effects on increasing physical activity and managing excessive gestational weight gain.

Cross-sectional and longitudinal associations of active travel, organised sport and physical education with accelerometer-assessed moderate-to-vigorous physical activity in young people: the International Children's Accelerometry Database.

BACKGROUND: Physical activity (PA) declines during childhood. Important sources of PA are active travel, organised sport and physical education (PE), but it is unclear how these domain-specific PA sources contribute to (changes in) daily moderate-to-vigorous PA (MVPA) in young people. This study aimed to examine (1) the cross-sectional association between domain-specific physical activity (i.e., active travel, organised sport and PE) and daily minutes in accelerometer-assessed MVPA; and (2) the longitudinal association between domain-specific physical activity at baseline and change in daily minutes in MVPA. METHODS: Participants (baseline age 11.3 ± .1.2 years) were drawn from three studies in the International Children's Accelerometry Database. The contribution of self-reported standardised active travel, organised sport and PE to accelerometer-measured daily minutes in MVPA was examined using linear regression. In cross-sectional analyses, MVPA was regressed on each PA domain in separate models, adjusted for study, age, sex, maternal education, season, and monitor wear time. In longitudinal analyses, change in MVPA was regressed on each of the baseline PA domains, additionally adjusting for changes in season and wear time, follow-up duration, and baseline MVPA. R-squared was used to compare variance explained by each PA domain. RESULTS: In the cross-sectional analyses (n = 3871), organised sport (standardised ß = 3.81, 95% confidence interval [95%CI] = 3.06, 4.56) and active travel (ß = 3.46, 95%CI = 2.73, 4.19) contributed more to daily MVPA than PE (ß = 0.82, 95%CI = -0.02, 1.66). Compared to the base model which included only covariates (R2 = 21.5%), organised sport (absolute change: + 1.9%) and active travel (+ 1.7%) models explained more of the variance than the PE model (± < 0.1%). Associations followed a similar pattern in the longitudinal analyses (n = 2302), but none of the PA domains predicted change in MVPA (organised sport: standardised ß = 0.85, 95%CI = -0.03, 1.72; active travel: ß = 0.68, 95%CI = -0.14, 1.50; PE: ß = 0.02, 95%CI = -0.87, 0.91). CONCLUSIONS: A multi-sectoral approach covering a wide range of PA domains should be promoted to minimise the age-related decline in MVPA during childhood.

Assessment of skeletal age in youth female soccer players: Agreement between Greulich-Pyle and Fels protocols.

OBJECTIVE: The purpose of the study was to evaluate the agreement between the Fels and Greulich-Pyle methods for the assessment of skeletal age (SA) in female youth soccer players. METHODS: The sample included 441 Portuguese players 10.08-16.73 years of age who regularly participated in organized and competitive soccer. Standardized radiographs of the left hand-wrist were obtained and analyzed by an experienced examiner. SA was estimated with the Fels and Greulich-Pyle (GP) methods. Differences between SA and chronological age (CA) were used to define skeletal maturity groups: late, average and early maturing. In addition to descriptive statistics, Cohen's kappa and Lin concordance correlation coefficients were used to evaluate agreement between methods. RESULTS: Intraindividual differences in SA based on the two methods varied between 0.10 to 1.47 years among age groups with larger mean differences at older ages. Agreement of maturity classifications between methods was 74% at younger ages (under-13: kappa = 0.48; under-14: kappa = 0.39; Lin CCC = 0.68) and declined with increasing CA (under-17: 19% agreement; kappa = 0.001; Lin CCC = 0.11). About 19% of the total sample was skeletally mature with the Fels method and an SA was not assigned; in contrast, no players were skeletally mature with the GP method. CONCLUSIONS: GP SAs were systematically lower than Fels SAs among female soccer players. Intraindividual variability in SAs between methods was considerable. The findings highlight the impact of method on estimates of maturity status.

Cross-sectional associations between domain-specific sitting time and other lifestyle health behaviours: the Stormont study.

BACKGROUND: There is a dearth of literature on how different domains of sitting time relate to other health behaviours. Therefore, this study aimed to explore these associations in a sample of office workers. METHODS: 7170 Northern Irish Civil Servants completed an online survey which included information on workday and non-workday sitting time in five domains (travel, work, TV, computer-use, leisure-time), physical activity, fruit and vegetable intake, alcohol consumption and cigarette smoking. An unhealthy behaviour score was calculated by summing the number of health behaviours which did not meet the current guidelines. Multinomial regressions examined associations between unhealthy behaviour score and each domain of sitting time. RESULTS: ≥7 hours sitting at work and ≥2 hours TV viewing on a workday both more than doubled the odds of partaking in ≥3 unhealthy behaviours [Odds ratio, OR = 2.03, 95% CI, (1.59-2.61); OR = 2.19 (1.71-2.80)] and ≥3 hours of TV viewing on a non-workday nearly tripled the odds [OR = 2.96 (2.32-3.77)]. CONCLUSIONS: High sitting time at work and TV viewing on a workday and non-workday are associated with increased odds of partaking in multiple unhealthy behaviours. Interventions need to focus on these domains and public health policy should consider sitting time as an important health behaviour.

Global prevalence of physical activity for children and adolescents; inconsistencies, research gaps, and recommendations: a narrative review.

BACKGROUND: One of the strategic actions identified in the Global Action Plan on Physical Activity (PA) 2018-2030 is the enhancement of data systems and capabilities at national levels to support regular population surveillance of PA. Although national and international standardized surveillance of PA among children and adolescents has increased in recent years, challenges for the global surveillance of PA persist. The aims of this paper were to: (i) review, compare, and discuss the methodological inconsistencies in children and adolescents' physical activity prevalence estimates from intercontinental physical activity surveillance initiatives; (ii) identify methodological limitations, surveillance and research gaps. METHODS: Intercontinental physical activity surveillance initiatives for children and adolescents were identified by experts and through non-systematic literature searches. Prevalence of meeting PA guidelines by country, gender, and age were extracted when available. A tool was created to assess the quality of the included initiatives. Methods and PA prevalence were compared across data/studies and against the methodological/validity/translation differences. RESULTS: Eight intercontinental initiatives were identified as meeting the selection criteria. Methods and PA definition inconsistencies across and within included initiatives were observed, resulting in different estimated national prevalence of PA, and initiatives contradicting each other's cross-country comparisons. Three findings were consistent across all eight initiatives: insufficient level of PA of children and adolescents across the world; lower levels of PA among girls; and attenuation of PA levels with age. Resource-limited countries, younger children, children and adolescents not attending school, with disability or chronic conditions, and from rural areas were generally under/not represented. CONCLUSIONS: There are substantial inconsistencies across/within included initiatives, resulting in varying estimates of the PA situation of children and adolescents at the global, regional and national levels. The development of a new PA measurement instrument that would be globally accepted and harmonized is a global health priority to help improve the accuracy and reliability of global surveillance.

'Snacktivity™' to increase physical activity: Time to try something different?

Evidence demonstrates that participation in regular physical activity (PA) reduces the risk of morbidity and mortality. However, current PA guidelines are focused on weekly accumulation of 150 min of moderate intensity PA as a threshold. Although recent developments of this guidance have discussed the merits of short bouts of physical activity, guidance that sets large behavioural goals for PA has not been successful in supporting the public to become sufficiently physically active and a 'one-size fits all' approach to PA guidelines may not be optimal. A complementary 'whole day' approach to PA promotion (i.e. incorporating PA throughout the day) that could motivate the population to be more physically active, is a concept we have called 'Snacktivity™'. The Snacktivity™ approach promotes small or 'bite' size bouts (e.g. 2-5 min) of PA accumulated throughout the whole day. Snacktivity™ is consistent with the small change approach which suggest that behaviour change and habit formation are best achieved through gradual building of task self-efficacy, celebrating small successes. Snacktivity™ also offers opportunities to "piggyback" on to existing behaviours/habits, using them as prompts for Snacktivity™. Moreover, small behaviour changes are easier to initiate and maintain than larger ones. A plethora of evidence supports the hypothesis that Snacktivity may be a more acceptable and effective way to help the public reach, or exceed current PA guidelines. This paper outlines the evidence to support the Snacktivity™ approach and the mechanisms by which it may increase population levels of physical activity. Future research directions for Snacktivity™ are also outlined.

Does adjusting for biological maturity when calculating child weight status improve the accuracy of predicting future health risk?

BACKGROUND: The aim of this study was to assess whether adjusting the weight categorisation of children for their biological maturity status could improve the accuracy of predicting weight status and cardiometabolic risk at age 17. METHODS: Data from 1525 participants (787 female) from the ALSPAC study were analysed. Participants' weight status at age 11 was estimated using first standard chronological age and sex adjusted BMI cut-offs, and again using maturity adjusted BMI cut-offs. Each BMI category at age 11 was regressed against cardiometabolic risk score and BMI category at age 17, controlling for sex, ethnicity and socio-economic status. RESULTS: At age 11 years, 22% of boys and 46% of girls who were categorised as overweight or having obesity based on chronological age were re-categorised into a lower BMI category after adjusting for biological maturity. Biologically adjusted BMI categories better predicted BMI category at age 17 compared with non-adjusted BMI categories (∆BIC = - 21.69); the odds of having obesity at age 17 were 18.28 times greater with each increase in BMI category at age 11. Adjusted and non-adjusted BMI status at 11 years showed equivalent accuracy in predicting cardiometabolic risk at age 17; the odds ratio of high cardiometabolic risk was 1.85, with heightened risk in boys, particularly early maturers. CONCLUSION: The traditional method of categorising adolescents into a BMI category may over-predict overweight and obesity, particularly in girls. Adjusting for biological maturity when estimating weight status through calculating adolescents' BMI classification was equivalent to standard approaches in predicting other cardiovascular risk at age 17.

A digital lifestyle behaviour change intervention for the prevention of type 2 diabetes: a qualitative study exploring intuitive engagement with real-time glucose and physical activity feedback.

BACKGROUND: Mobile health technologies have advanced to now allow monitoring of the acute physiological responses to lifestyle behaviours. Our aim was to explore how people engaged with real-time feedback on their physical activity and glucose levels over several weeks. METHODS: Semi-structured interviews with 26 participants (61.5% female, 56.6 years) at moderate-to-high risk of developing type 2 diabetes were conducted. Interviews were completed after participants took part in an intervention comprising a flash glucose monitor (Freestyle Libre) and a physical activity monitor (Fitbit Charge 2). Purposive sampling ensured representation of ages, genders and group allocations. RESULTS: Inductive thematic analysis revealed how individuals intuitively used, interpreted and acted on feedback from wearable technologies. Six key themes emerged: triggers of engagement with the technologies, links between behaviour and health, lack of confidence, changes to movement behaviours, changes to diet and barriers to lifestyle behaviour change. CONCLUSIONS: Our findings demonstrate that accessing behavioural and physiological feedback can increase self-awareness of how lifestyle impacts short-term health. Some participants noticed a link between the feedback presented by the two devices and changed their behaviour but many did not. Training and educational support, as well as efforts to optimize how feedback is presented to users, are needed to sustain engagement and behaviour change. Extensions of this work to involve people with diabetes are also warranted to explore whether behavioural and physiological feedback in parallel can encourage better diabetes self-management. TRIAL REGISTRATION: ISRCTN Registry, ISRCTN17545949 , 12/05/2017, prospectively registered.

Concurrent screen use and cross-sectional association with lifestyle behaviours and psychosocial health in adolescent females.

AIM: To describe concurrent screen use and any relationships with lifestyle behaviours and psychosocial health. METHODS: Participants wore an accelerometer for seven days to calculate physical activity sleep and sedentary time. Screen ownership and use and psychosocial variables were self-reported. Body mass index (BMI) was measured. Relationships were explored using mixed models accounting for school clustering and confounders. RESULTS: In 816 adolescent females (age: 12.8 SD 0.8 years; 20.4% non-white European) use of ≥2 screens concurrently was: 59% after school, 65% in evenings, 36% in bed and 68% at weekends. Compared to no screens those using: ≥1 screens at weekends had lower physical activity; ≥2 screens at the weekend or one/two screen at bed had lower weekend moderate-to-vigorous physical activity; one screen in the evening had lower moderate-to-vigorous physical activity in the after-school and evening period; ≥1 screens after school had higher BMI; and ≥3 screens at the weekend had higher weekend sedentary time. Compared to no screens those using: 1-3 after-school screens had shorter weekday sleep; ≥1 screens after-school had lower time in bed. CONCLUSION: Screen use is linked to lower physical activity, higher BMI and less sleep. These results can inform screen use guidelines.

Exploring Feelings of Pleasure and Purpose Associated With Older People's Activities Using Ecological Momentary Analysis: An Observational Study.

Momentary feelings of pleasure and purpose can be sources of intrinsic motivation, but momentary purpose is rarely studied. Activities, contexts, and feelings of retired/semiretired adults (n = 67, aged 50-78 years) were captured using ecological momentary assessment. Participants provided 2,065 valid responses to six daily smartphone surveys for 7 days. Physical activity was measured by waist-worn ActiGraph accelerometer. Pleasure (measured by affective happiness) and purpose outcomes were regressed on activities, context, and potential confounding variables. Interactions between activities and contexts were explored. Participants were highly active: 98.5% met physical activity guidelines. Sedentary activities were negatively associated with sense of purpose, especially when indoors. However, social sedentary activities were positively associated with feelings of happiness. Active, social outdoor activities were positively associated with both outcomes. Less sedentary participants experienced greater happiness and purpose during all their activities. Context matters: active, social, and outdoor activities seem to be more appealing to older adults.

Using a multi-stakeholder experience-based design process to co-develop the Creating Active Schools Framework.

BACKGROUND: 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). METHODOLOGY: 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. RESULTS: 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.

Reducing screen-time and unhealthy snacking in 9-11 year old children: the Kids FIRST pilot randomised controlled trial.

BACKGROUND: Many young people form unhealthy behavioural habits, such as low intake of fruit and vegetables, high intake of energy-dense snack foods, and excessive sedentary screen-based behaviours. However, there is a shortage of parent-and home-focused interventions to change multiple health behaviours in children. METHODS: Kids FIRST was a 12-week, home- and school-based pilot randomised controlled trial to reduce screen-time and unhealthy snacking with assessments at pre- (baseline) and post-intervention. Four UK schools were randomised to control or one of three interventions targeting reductions in (1) screen-time and unhealthy snacking (ST + Sn), (2) screen-time (ST only), (3) unhealthy snacking (Sn only), and parents with children aged 9-11 years were recruited via schools. Intervention group parents received four online 'sessions' and four packages of resources tailored to each group. Children received four 30-min lessons during school time. Children and parents reported their own screen-time behaviours, children reported their own snacking behaviours. Descriptive analyses were undertaken using principles of intention to treat. RESULTS: Initial feasibility was shown in that this study successfully recruited schools and families into all four study arms and retained them over a period of 13 weeks (retention rate ≥ 74%). Seventy-five children and 64 parents provided full baseline questionnaire data. Reductions in children's school day and weekend day TV/DVD viewing and computer game use were found in the ST + Sn and ST groups, while self-reported smartphone use increased in these groups. Similar results were found for parents' TV/DVD, computer and smartphone use in these groups. Little to no changes were found in reports of the dietary variables assessed in any intervention group for children or parents. CONCLUSIONS: These preliminary findings show some promise for the Kids FIRST intervention. Based on these findings, a future full trial should recruit a more diverse sample of families and optimise the intervention and intervention resources to more fully engage parents with the dietary-based components of the intervention programme, where fewer changes were seen. Although most parents reporting receiving the intervention resources, further development work is required to achieve higher levels of engagement. This might include greater parent and child engagement work early in the development of the project. TRIAL REGISTRATION: Retrospectively registered in June 21st 2019 with ClinicalTrials.gov (number NCT03993652).

Reproducibility and inter-observer agreement of Greulich-Pyle protocol to estimate skeletal age among female adolescent soccer players.

BACKGROUND: Skeletal age (SA) is considered the best method of assessing biological maturation. The aim of this study was to determine intra-observer (reproducibility) and inter-observer agreement of SA values obtained via the Greulich-Pyle (GP) method. In addition, the variation in calculated SAs by alternative GP protocols was examined. METHODS: The sample was composed of 100 Portuguese female soccer players aged 12.0-16.7 years. SAs were determined using the GP method by two observers (OB1: experience < 100 exams using GP; OB2: experience > 2000 exams using several methods). The radiographs were examined using alternative GP protocols: (wholeGP) the plate was matched to the atlas as an overall approach; (30-boneGP) bone-by-bone inspections of 30-bones; (GPpmb) bone-by-bone inspections of the pre-mature bones only. For the 30-boneGP and GPpmb approaches, SA was calculated via the mean (M) and the median (Md). RESULTS: Reproducibility ranged 82-100% and 88-100% for OB1 and OB2, respectively. Inter-observer agreement (100 participants multiplied by 30 bones) was 92.1%. For specific bones, agreement rates less than 90% were found for scaphoid (81%), medial phalange V (83%), trapezium (84%) and metacarpal V (87%). Differences in wholeGP SAs obtained by the two observers were moderate (d-cohen was 0.79). Mean differences between observers when using bone-by bone SAs were trivial (30-boneGP: d-cohen less than 0.05; GPpmb: d-cohen less than 0.10). The impact of using the mean or the median was negligible, particularly when analyses did not include bones scored as mature. CONCLUSION: The GP appeared to be a reasonably reproducible method to assess SA and inter-observer agreement was acceptable. There is evidence to support a recommendation of only scoring pre-mature bones during later adolescence. Further research is required to examine whether these findings are consistent in younger girls and in boys.

Scaling left ventricular mass in adolescent female soccer players.

BACKGROUND: The aim of the study was to examine the contribution of chronological age (CA), skeletal maturation, training experience and concurrent body size descriptors, to inter-individual variance in left ventricular mass (LVM) among female adolescent soccer players. METHODS: The sample included 228 female soccer players 11.8-17.1 years. Training experience defined as years of participation in competitive soccer (range 2-9 years), was obtained by interview. Stature, body mass and skinfolds (triceps, medial calf) were measured. Fat mass was estimated; Fat-free mass was derived. LVM was assessed by echocardiography. Skeletal maturity status was as the difference of skeletal age (SA, Fels method) minus CA. RESULTS: Fat-free mass was the most prominent single predictor of LVM (R2 = 36.6%). It was associated with an allometric coefficient close to linearity (k = 0.924, 95%CI: 0.737 to 1.112). A significant multiplicative allometric model including body mass, fat-free mass, CA, training experience and skeletal maturity status was also obtained (R = 0.684; R2 = 46.2%). CONCLUSION: Stature has limitations as a valid size descriptor of LVM. Body mass, fat-free mass, training experience, CA, body mass and skeletal maturity status were relevant factors contributing to inter-individual variability in LVM.