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Background: Engagement in before-school physical activity can potentially enhance health and learning-related outcomes for children and adolescents. However, influencing factors and stakeholder perceptions of before-school physical activity remain under-researched. This qualitative study aimed to examine stakeholder perceptions of: a) the suitability of the before-school segment for physical activity, b) barriers and facilitators associated with before-school physical activity, and c) strategies for schools to support before-school physical activity., Methods: Twelve focus groups and one interview were conducted with 38 participants from a range of school stakeholder groups-students, parents, teachers, school leaders, external physical activity providers, and school health and physical activity experts. Focus groups were analysed using template analysis, guided by a social-ecological model., Results: Stakeholders perceived before-school physical activity as valuable, for reasons including perceptions of meaningful contributions to students' cognitive functioning, classroom behaviours, and wellbeing. Factors influencing before-school physical activity were identified across multiple social-ecological levels, including the critical role of school leadership support, availability of facilities, and provision of qualified supervision. Proposed strategies highlighted the need for sustainable design, contextual relevance, and community engagement in before-school initiatives. Additionally, communication of the manifold benefits identified by stakeholders was suggested as a means to drive support and engagement in before-school physical activity., Conclusions: This study provides insight for schools seeking to enhance opportunities for physical activity in the before-school hours and may inform future intervention research on the subject, taking into account its multi-faceted influences and the need for context-specific strategies., (© 2024. The Author(s).)

Background: Understanding the early roots of physical activity and sedentary behaviors is critical to developing intervention programs that promote healthy lifestyle habits in infants and children. There is, however, no evidence on how these behaviors cluster and develop together during early childhood. The aim of this study was to identify single and joint longitudinal trajectories in physical activity and screen time amongst children aged 0 to 9 years, their social-demographic predictors and their prospective health-related quality-of-life and socio-emotional outcomes., Methods: Three waves of data from The Longitudinal Study of Australian Children, a national study tracking two cohorts every 2 years (B-cohort, 0-5 years, n = 4,164; K-cohort, 4-9 years, n = 3,974) were analysed. Growth mixture modelling was applied to longitudinal time-use diary data to identify joint trajectories in children's physical activity and screen time over Waves 1-3. Key socio-demographic variables measured at Wave 1 were used to predict membership in different trajectories. The prospective consequences (at Wave 3) of time-use trajectories on health-related quality-of-life and socio-emotional outcomes were assessed., Results: Three physical-activity/screen-time trajectories were identified for both cohorts: Cluster-A-children who maintained low levels of physical activity and screen time (∽50% of the sample), Cluster-B-children who progressively increased physical activity and maintained low screen-time levels (∽25%), and Cluster-C-children who maintained low physical-activity levels and increased screen time (∽25%). Children in Cluster-B experienced the best health-related quality-of-life and socio-emotional outcomes, while those in Cluster-C experienced the worst. Children who were female, Indigenous, from non-English-speaking backgrounds, not living with two biological parents, in more affluent households and neighbourhoods, without siblings and with parents with poor mental health were at greater risk of falling into Cluster-A or Cluster-C., Conclusion: Our findings identified which children are most at-risk of falling into time-use trajectories that lead to poor health-related quality-of-life and socio-emotional outcomes later in life, increasing our ability to monitor, detect and prevent these suboptimal behaviours prior to their onset.

Background: Increased mammographic breast density is a moderate risk factor for breast cancer. Different scales have been proposed for classifying mammographic density. This study sought to assess intra-rater agreement for the most widely used scales (Wolfe, Tabár, BI-RADS and Boyd) and compare them in terms of classifying mammograms as high- or low-density., Methods: The study covered 3572 mammograms drawn from women included in the DDM-Spain study, carried-out in seven Spanish Autonomous Regions. Each mammogram was read by an expert radiologist and classified using the Wolfe, Tabár, BI-RADS and Boyd scales. In addition, 375 mammograms randomly selected were read a second time to estimate intra-rater agreement for each scale using the kappa statistic. Owing to the ordinal nature of the scales, weighted kappa was computed. The entire set of mammograms (3572) was used to calculate agreement among the different scales in classifying high/low-density patterns, with the kappa statistic being computed on a pair-wise basis. High density was defined as follows: percentage of dense tissue greater than 50% for the Boyd, "heterogeneously dense and extremely dense" categories for the BI-RADS, categories P2 and DY for the Wolfe, and categories IV and V for the Tabár scales., Results: There was good agreement between the first and second reading, with weighted kappa values of 0.84 for Wolfe, 0.71 for Tabár, 0.90 for BI-RADS, and 0.92 for Boyd scale. Furthermore, there was substantial agreement among the different scales in classifying high- versus low-density patterns. Agreement was almost perfect between the quantitative scales, Boyd and BI-RADS, and good for those based on the observed pattern, i.e., Tabár and Wolfe (kappa 0.81). Agreement was lower when comparing a pattern-based (Wolfe or Tabár) versus a quantitative-based (BI-RADS or Boyd) scale. Moreover, the Wolfe and Tabár scales classified more mammograms in the high-risk group, 46.61 and 37.32% respectively, while this percentage was lower for the quantitative scales (21.89% for BI-RADS and 21.86% for Boyd)., Conclusions: Visual scales of mammographic density show a high reproducibility when appropriate training is provided. Their ability to distinguish between high and low risk render them useful for routine use by breast cancer screening programs. Quantitative-based scales are more specific than pattern-based scales in classifying populations in the high-risk group.