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Background: Little is known on how the substitution of time spent in sedentary behavior (SB) patterns with time spent in physical activity impacts cardiovascular risk factors during adolescence. The study aimed to investigate how the substitution of time spent in SB and sedentary bouts with time spent in different physical activity intensities was associated with longitudinal changes in cardiovascular risk factors in analyses stratified by sex. Methods: This is a prospective cohort study with a mean follow-up period of 3.2 (±0.34) years, involving 109 (60 girls and 49 boys) Brazilian adolescents. Body mass index, waist circumference, and cardiorespiratory fitness were the cardiovascular risk factors considered. A cardiovascular risk score was calculated. Sedentary bouts, light physical activity (LPA), and moderate to vigorous physical activity (MVPA) were measured by accelerometers. Multivariate linear regression models adopting the isotemporal substitution were used to analyze the association between substitution of 10 minutes per day of sedentary bouts with LPA and MVPA and risk factors. All analyses considered 5% significance levels. Results: Substitutions of SB, short and long bouts, with MVPA were associated with higher cardiorespiratory fitness in boys (β = 0.077; 95% confidence interval, 0.001 to 0.55; β = 0.076; 95% confidence interval, 0.003 to 0.154; and β = 0.084; 95% confidence interval, 0.001 to 0.167, respectively). No associations were observed when analyses involved substitution of sedentary bouts with LPA, adiposity, cardiovascular risk score, and girls. Conclusions: Substituting SB bouts with MVPA appears to favorably influence changes of cardiorespiratory fitness in boys during adolescence. Greater benefits appear to occur when longer sedentary bouts are substituted by MVPA.

Standing is a solution to reduce or break-up sedentary time (sitting/reclining/lying while awake); however, the measurable health benefits of standing are conflicting. A recent article in the Journal for the Measurement of Physical Behaviour has demonstrated that the thigh-worn activPAL inclinometer can distinguish between passive (no movement) and active (structured micromovements) standing using a machine learning model in lab-based and free-living environments. The predictive model extends beyond previous research by considering three-dimensional aspects of movement into the decision tree model. The ability to characterize these distinct postures is increasingly important to understand the physiological difference between passive and active standing. Notably, active standing, when stepping is not feasible, may be superior to passive standing for improving metabolic activity, reducing fatigue, and enhancing blood flow. Applied to free-living settings, active standing could help mitigate or attenuate some adverse cardiometabolic effects of stationary activity, thereby yielding positive cardiovascular outcomes. As standing gains recognition as a potentially important health behavior, distinguishing between passive and active standing offers a unique opportunity to clarify the health impacts of standing time, contributing to the evidence base. This evidence may contribute to more detailed activity guidelines and support public health initiatives to promote active standing. These advancements have the potential to enhance our understanding of standing behaviors’ health impacts and the possible divergent physiological effects of active versus passive standing.

Humanity is facing a polycrisis, including climate change, loss of biodiversity, and economic inequalities. This commentary examines the role of physical activity (PA) research in the context of climate change, highlighting 3 perspectives: PA as a victim, as a perpetrator, and as part of the solution. The first perspective conceptualizes PA as a victim of climate change, as heat waves, extreme weather events, and high ozone levels pose a threat to health-enhancing PA and sports; adaptation strategies are needed and potentially lifesaving. The second perspective describes PA as a perpetrator to climate change due to the significant carbon footprint of some forms of PA and sport. The third perspective focuses on PA as a solution to climate change, as some forms of PA—such as active transport and urban gardening—have both individual and planetary health benefits. In addition, PA provides health benefits in extreme situations by reducing stress and maintaining health in times of crisis. Each of these 3 perspectives can guide future research in the field of PA and health.

Background: This study aimed to identify patterns of overall, team, and individual sport participation and examine the prospective associations between these patterns and loneliness in young people. Methods: We analyzed data from 4241 young people, from waves 3 (8–9 y) to 9 (20–21 y) of the Longitudinal Study of Australian Children. We conducted latent class analyses to identify overall and team versus individual sport participation trajectories and used adjusted log-Poisson regression models to examine the associations between these trajectories and loneliness at wave 9. Results: Latent class analyses identified 4 distinct overall sport participation classes which were labeled: nonparticipants (24%), dropouts (42%), initiators (7%), and consistent participants (27%). Compared with nonparticipants, consistent participants had a lower risk of loneliness (risk ratios = 0.69; 95% CIs, 0.59–0.81). Latent class analyses also identified 4 distinct team versus individual sport participation classes: team and individual sport nonparticipants (38%), individual sport participants (14%), moderate team sport participants (14%), and high team sport participants (34%). Compared with the team and individual sport nonparticipants, the high team sports participants had a lower risk of loneliness (risk ratios = 0.70; 95% CIs, 0.53–0.92). Conclusions: Young people who continued participating in sport in general, and particularly in team sport, had a reduced risk of loneliness. Continued participation in sports should be promoted to improve a range of physical, mental, and social health benefits. Furthermore, team-based sport can provide additional health and well-being benefits, including reduced loneliness due to the group nature of participation.

Background: Engaging in active transport will enable individuals across the life course to increase their habitual levels of physical activity. The aim of this study was to engage citizen scientists (CS) to identify factors that influence active transport in their community. Methods: The Our Voice citizen science methodology developed at Stanford University was employed. CS completed a “discovery walk,” taking photos of things that help or hinder active transport. Three groups were recruited: children aged 10–12 years (n = 11), adults (n = 12), and older adults >65 years (n = 10). CS rated each photo and provided a narrative explaining their reason for taking the photo. Once all CS in a specific age group had completed the walk, they met for a group discussion. The CS worked together to analyze the data, arranging them into themes and identifying priority actions. Two CS representatives from each age group presented their findings to the local council decision makers. Results: Children highlighted the need for safer crossings, especially from their school to the local park, and suggested zebra crossings as a solution. The adults highlighted that road signs prioritized vehicles, not pedestrians, and requested that this be reversed. Older adults noted that the poor condition of the pavements made it harder for people in wheelchairs to navigate. The CS recommendations have informed the council’s walking and cycling network program. Conclusion: Engaging with citizen science provided the community with an opportunity to advocate for meaningful yet realistic improvements in the built environment that could promote neighborhood active transport and physical activity across the lifespan.

Aim: This study aimed to investigate the association between physical activity (PA), lifestyle, and symptoms of depression, anxiety, and stress. Methods: A cross-sectional study was carried out using an online questionnaire. PA (International Physical Activity Questionnaire), lifestyle (Short Multidimensional Inventory Lifestyle Evaluation), and mental health (Depression, Anxiety, and Stress Scale-21) were assessed. Mean scores were compared between groups of physically active and inactive participants, controlling for gender, education, and income. Furthermore, associations were made between the variables, and individual network analyses were carried out for each mental health domain. The sample consisted of 353 individuals (age = 33.8 [12.2], 59.2% women). Results: In network analyses, PA was indirectly related to depression and stress through the relationship with other lifestyle domains such as diet and nutrition or through stress management and social support. The same path was observed for anxiety; however, a direct partial correlation was also observed between PA and anxiety, suggesting that PA seems to intervene more directly in this aspect of mental health. Conclusion: It is concluded that PA is indirectly (via stress management, diet and nutrition, and social support) associated with depression and stress and has direct and indirect associations (via stress management and social support) with anxiety.

Background: University rankings often serve as benchmarks for excellence in academic evaluation. For example, ShanghaiRanking data from 2016 to 2023 for the Global Ranking of Sport Science Schools and Departments reveal consistent dominance by Australia (23.1%), Canada (18.0%), and the United States (12.0%), collectively counting over half of the top 50 universities worldwide. Nevertheless, there is uncertainty about how the methodology behind these rankings shapes a reality as much as it reflects one. Purpose: Our intention is to discuss the complexity of university rankings, using ShanghaiRanking as an example, to highlight how these rankings reflect academic excellence within the field of sport science. Current Evidence: When ranking universities in sport science, several aspects of academic excellence could be considered in addition to research metrics currently considered in ShanghaiRanking (publication, citation, citations per publication, top 25% journal publications, and internationally collaborated publications). These aspects may include (1) teaching quality, (2) practical training, (3) industry links and employability, (4) support services, (5) facilities and equipment, (6) international network, (7) community engagement, (8) sustainability and ethical practices, and (9) interdisciplinary approach. Altogether, they could provide a more comprehensive view of the quality and effectiveness of a sport-science program. Conclusions: The ranking of sport-science institutions poses a complex challenge due to diverse factors influencing academic excellence. Engaging in a broader dialogue and refining internationally relevant evaluation methodologies are crucial. These steps enable comparability between countries and provide a holistic understanding of the multidimensional nature of academic excellence in sport science.

Background: In high-performance sport, the support provided by sport scientists and other staff can be a valuable resource for coaches and athletes. Purpose: We propose and detail here the approach of “minimal, adequate, and accurate” sport-science support to ensure that programs of work and solutions are both economical and effective. Methods: Our support provision advocates for utilization of “minimal” resources (employing the least amount of time, tools, and funding) necessary to achieve the desired outcomes. We strive for “adequate” information that fulfills specific objectives without excess and with the requirement that methods and data used are “accurate” (valid and reliable). To illustrate the principles of this approach, we outline a real-world example of supporting 100-m track (athletics) sprinters preparing and competing in an international competition. The provision of performance support emphasizes an integrated approach, combining knowledge and insights from multiple sport-science disciplines. The key facets managed under this approach are (1) neuromuscular readiness, (2) wellness monitoring, (3) movement observation, (4) motivation, (5) biomechanics and performance analysis, and (6) qualitative feedback. These facets are based on the specific performance determinants and influencing factors of an event (100-m dash). Conclusions: Application of this quantitative and qualitative approach can enhance the ability to make informed decisions. Nevertheless, the approach must be planned, evaluated, and refined on a regular basis to enable effective decision making in sport-science support. The 3-element approach of “minimal, adequate, and accurate” should be codesigned and supported by the athletes, coaches, and staff to ensure successful implementation.

Background: The optimization of athlete training load is not a new concept; however in recent years, the concept of “load management” is one of the most widely studied and divisive topics in sports science and medicine. Purpose: Discuss the challenges faced by sports when utilizing training load monitoring and management, with a specific focus on the use of data to inform load management guidelines and policies/mandates, their consequences, and how we move this field forward. Challenges: While guidelines can theoretically help protect athletes, overzealous and overcautious guidelines may restrict an athlete’s preparedness, negatively influence performance, and increase injury risk. Poor methods, wrong interpretation of study findings, and faulty logic do not allow for systematic scientific evaluations to inform guidelines. Practical Solutions: Guidelines and mandates should be developed through a systematic research process with stronger research designs and clear research questions. Collaborating with statistical and epidemiological experts is essential. Implementing open science principles and sharing all sports training load data increase transparency and allow for more rapid and valid advancements in knowledge. Practitioners should incorporate multiple data streams and consider individual athlete responses, rather than applying broad guidelines based on average data. Conclusion: Many current training load guidelines and mandates in sports come from good intentions; however, they are arbitrary without sound knowledge of the underlying scientific principles or methods. Common sense guidelines are helpful when there is sparse literature, but they should be careful to avoid arbitrarily choosing findings from weak research. Without precise scientific inquiries, implementing training load interventions or guidelines can have negative implications.