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Objective: To examine the association of 24-hour time-use compositions with mental health in a large, geographically diverse sample of UK adolescents. Design: Cross-sectional, secondary data analysis. Setting: Millennium Cohort Study (sixth survey), a UK-based prospective birth cohort. Participants: Data were available from 4642 adolescents aged 14 years. Analytical samples for weekday and weekend analyses were n=3485 and n=3468, respectively (45% boys, 85% white ethnicity). Primary and secondary outcome measures: Primary outcome measures were the Strengths and Difficulties Questionnaire (SDQ, socioemotional behaviour), Mood and Feelings Questionnaire (MFQ, depressive symptoms) and Rosenberg Self-Esteem Scale (RSE, self-esteem). Behavioural exposure data were derived from 24-hour time-use diaries. Results: On weekdays, participants spent approximately 54% of their time in sleep, 3% in physical activity, 9% in school-related activities, 6% in hobbies, 11% using electronic media and 16% in domestic activities. Predicted differences in SDQ, MFQ and RSE were statistically significant for all models (weekday and weekend) that simulated the addition or removal of 15 min physical activity, with an increase in activity being associated with improved mental health and vice versa. Predicted differences in RSE were also significant for simulated changes in electronic media use; an increase in electronic media use was associated with reduced self-esteem. Conclusion: Small but consistent associations were observed between physical activity, electronic media use and selected markers of mental health. Findings support the delivery of physical activity interventions to promote mental health during adolescence, without the need to specifically target or protect time spent in other activities.

Background: English youth typically do not sufficiently engage in the types and intensities of physical activity that develop muscular fitness. The aim of this study was to use a combination of qualitative techniques to explore adolescent boys’ understanding, perceptions, and experiences of physical activity and the role muscular fitness plays within boys’ physically active lifestyles. Methods: Focus group interviews with a write, draw, show, and tell activity were conducted with 32 adolescent boys aged 14–16 years from 3 secondary schools. Three separate sources of data (frequency counts, verbatim transcripts, and visual data) were generated and were pooled together and triangulated. Data were analysed deductively, first using the Youth Physical Activity Promotion model as a thematic framework, and then inductively. Results: Physical activity was frequently associated with organised sport, and most boys were unaware of current UK physical activity guidelines. Co-participation was frequently reported as a reinforcing factor to physical activity. Conclusions: There was a perceived lack of opportunity to participate in muscular fitness activities, particularly in school, and knowledge of how to conduct muscular fitness activities was limited. The contribution of physical education was highlighted as being key to facilitating exposure to muscular fitness activities.

This study used accelerometer and self-report measures of overall sedentary time (ST) and screen time behaviours to examine their respective associations with adiposity among UK youth. Participants (Year groups 5, 8, and 10; n=292, 148 girls) wore the SenseWear Armband Mini accelerometer for eight days and completed the Youth Activity Profile, an online report tool designed to estimate physical activity and ST.Stature, body mass and waist circumference were measured to classify adiposity outcomes (overweight/obese and central obesity). One-way between groups ANOVA and adjusted linear, logistic and multinomial logistic regression analyses were conducted. There was a significant main effect of age on total ST across the whole week (F(2, 289)=41.64, p≤0.001). ST increased monotonically across Year 5 (581.09±107.81 min·dˉ¹), 8 (671.96±112.59 min·dˉ¹) and 10 (725.80±115.20 min·dˉ¹), and all pairwise comparisons were significant at p≤0.001. A steep age-related gradient to mobile phone use was present (p≤0.001). ST was positively associated with adiposity outcomes independent of moderate-to-vigorous intensity physical activity (MVPA; p≤0.001). Engaging in >3 hours of video gaming daily was positively associated with central obesity (OR=2.12, p≤0.05) but not after adjustment for MVPA. Results further demonstrate the importance of reducing overall ST to maintain healthy weight status among UK youth.

Objectives: To examine the backward comparability of a range of wrist-worn accelerometer estimates of sedentary time (ST) with ActiGraph 100 count min −1 waist ST estimates. Design: Cross-sectional, secondary data analysis Methods: One hundred and eight 10–11-year-old children (65 girls) wore an ActiGraph GT3X+ accelerometer (AG) on their waist and a GENEActiv accelerometer (GA) on their non-dominant wrist for seven days. GA ST data were classified using a range of thresholds from 23 to 56 mg ST estimates were compared to AG ST 100 count min −1 data. Agreement between the AG and GA thresholds was examined using Cronbach's alpha, intraclass correlation coefficients (ICC), limits of agreement (LOA), Kappa values, percent agreement, mean absolute percent error (MAPE) and equivalency analysis. Results: Mean AG total ST was 492.4 min over the measurement period. Kappa values ranged from 0.31 to 0.39. Percent agreement ranged from 68 to 69.9%. Cronbach's alpha values ranged from 0.88 to 0.93. ICCs ranged from 0.59 to 0.86. LOA were wide for all comparisons. Only the 34 mg threshold produced estimates that were equivalent at the group level to the AG ST 100 count min −1 data though sensitivity and specificity values of ∼64% and ∼74% respectively were observed. Conclusions: Wrist-based estimates of ST generated using the 34 mg threshold are comparable with those derived from the AG waist mounted 100 count min −1 threshold at the group level. The 34 mg threshold could be applied to allow group-level comparisons of ST with evidence generated using the ActiGraph 100 count min −1 method though it is important to consider the observed sensitivity and specificity results when interpreting findings.

Self-reported youth physical activity (PA) is typically overestimated. We aimed to calibrate and validate a self-report tool among English youth. Four-hundred-and-two participants (aged 9-16 years; 212 boys) wore SenseWear Armband Mini devices (SWA) for eight days and completed the self-report Youth Activity Profile (YAP) on the eighth day. Calibration algorithms for temporally matched segments were generated from the YAP data using quantile regression. The algorithms were applied in an independent cross-validation sample, and student- and school-level agreement were assessed. The utility of the YAP algorithms to assess compliance to PA guidelines was also examined. The school-level bias for the YAP estimates of in-school, out-of-school, and weekend moderate-to-vigorous PA (MVPA) were 17.2 (34.4), 31.6 (14.0), and -4.9 (3.6) min·week-1, respectively. Out-of-school sedentary behaviour (SB) was over-predicted by 109.2 (11.8) min·week-1. Predicted YAP values were within 15%-20% equivalence of the SWA estimates. The classification accuracy of the YAP MVPA estimates for compliance to 60 min·day-1 and 30 min·school-day-1 MVPA recommendations were 91%/37% and 89%/57% sensitivity/specificity, respectively. The YAP generated robust school-level estimates of MVPA and SB and has potential for surveillance to monitor compliance with PA guidelines. The accuracy of the YAP may be further improved through research with more representative UK samples to enhance the calibration process and to refine the resultant algorithms.

Average acceleration (AvAcc) and intensity gradient (IG) have been proposed as standardised metrics describing physical activity (PA) volume and intensity, respectively. We examined hypothesised between-group PA differences in AvAcc and IG, and their associations with health and wellbeing indicators in children. ActiGraph GT9X wrist accelerometers were worn for 24-h·d−1 over seven days by 145 children aged 9-10. Raw accelerations were averaged per 5-s epoch to represent AvAcc over 24-h. IG represented the relationship between log values for intensity and time. Moderate-to-vigorous PA (MVPA) was estimated using youth cutpoints. BMI z-scores, waist-to-height ratio (WHtR), peak oxygen uptake (VO2peak), Metabolic Syndrome risk (MetS score), and wellbeing were assessed cross-sectionally, and 8-weeks later. Hypothesised between-group differences were consistently observed for IG only (p<.001). AvAcc was strongly correlated with MVPA (r=0.96), while moderate correlations were observed between IG and MVPA (r=0.50) and AvAcc (r=0.54). IG was significantly associated with health indicators, independent of AvAcc (p<.001). AvAcc was associated with wellbeing, independent of IG (p<.05). IG was significantly associated with WHtR (p<.01) and MetS score (p<.05) at 8-weeks follow-up. IG is sensitive as a gauge of PA intensity that is independent of total PA volume, and which relates to important health indicators in children.

BACKGROUND Adolescent girls are more likely to be inactive than boys. A range of factors including multiple psychosocial aspects are thought to influence their engagement in physical activity (PA). This study aimed to explore adolescent girls’ perceptions and experiences of school-based PA to inform a subsequent intervention, the Girls Peer Activity (G-PACT) project. METHODS The Youth Activity Profile was used to assess adolescent girls’ current PA levels. Open-ended questions were used to investigate girls’ perceptions and experiences of school-based PA. Focus groups stratified by PA level were then conducted to explore their perceptions and experiences in depth. The focus group data were analysed using inductive thematic analysis. RESULTS The master themes emanating from the focus groups were non-competitive activities and after-school sport culture for lower active girls. Higher active girls’ master themes were PA perceptions and PE. Regardless of activity level, participants reported greater enjoyment from PA when participating with friends and having choice over activities provided within the school setting. CONCLUSIONS The findings highlight the importance of choice, peer groupings, non-competitive opportunities and PA competence to adolescent girls’ school-based PA behaviours. The school environment can support and restrict girls’ engagement in PA. The findings will be applied to the design, content and implementation of the G-PACT project.

This study used accelerometer and self-report measures of overall sedentary time (ST) and screen time behaviours to examine their respective associations with adiposity among UK youth. Participants (Year groups 5, 8, and 10; n=292, 148 girls) wore the SenseWear Armband Mini accelerometer for eight days and completed the Youth Activity Profile, an online report tool designed to estimate physical activity and ST.Stature, body mass and waist circumference were measured to classify adiposity outcomes (overweight/obese and central obesity). One-way between groups ANOVA and adjusted linear, logistic and multinomial logistic regression analyses were conducted. There was a significant main effect of age on total ST across the whole week (F(2, 289)=41.64, p≤0.001). ST increased monotonically across Year 5 (581.09±107.81 min·dˉ¹), 8 (671.96±112.59 min·dˉ¹) and 10 (725.80±115.20 min·dˉ¹), and all pairwise comparisons were significant at p≤0.001. A steep age-related gradient to mobile phone use was present (p≤0.001). ST was positively associated with adiposity outcomes independent of moderate-to-vigorous intensity physical activity (MVPA; p≤0.001). Engaging in >3 hours of video gaming daily was positively associated with central obesity (OR=2.12, p≤0.05) but not after adjustment for MVPA. Results further demonstrate the importance of reducing overall ST to maintain healthy weight status among UK youth.

Self-reported youth physical activity (PA) is typically overestimated. We aimed to calibrate and validate a self-report tool among English youth. Four-hundred-and-two participants (aged 9–16 years; 212 boys) wore SenseWear Armband Mini devices (SWA) for eight days and completed the self-report Youth Activity Profile (YAP) on the eighth day. Calibration algorithms for temporally matched segments were generated from the YAP data using quantile regression. The algorithms were applied in an independent cross-validation sample, and student- and school-level agreement were assessed. The utility of the YAP algorithms to assess compliance to PA guidelines was also examined. The school-level bias for the YAP estimates of in-school, out-of-school, and weekend moderate-to-vigorous PA (MVPA) were 17.2 (34.4), 31.6 (14.0), and -4.9 (3.6) min week, respectively. Out-of-school sedentary behaviour (SB) was over-predicted by 109.2 (11.8) min·week−1. Predicted YAP values were within 15%–20% equivalence of the SWA estimates. The classification accuracy of the YAP MVPA estimates for compliance to 60 min·day−1 and 30 min·school-day−1 MVPA recommendations were 91%/37% and 89%/57% sensitivity/specificity, respectively. The YAP generated robust school-level estimates of MVPA and SB and has potential for surveillance to monitor compliance with PA guidelines. The accuracy of the YAP may be further improved through research with more representative UK samples to enhance the calibration process and to refine the resultant algorithms