From secondary school to university: associations between sport participation and total and domain-specific sedentary behaviours in Spanish students

Socioeconomic position as a predictor of youth's movement trajectory profiles between ages 10 and 14 years

BACKGROUND

Combinations of movement behaviors (i.e., physical activity, sedentary behavior, sleep) are associated with health and developmental outcomes in youth. Youth vary in how they accumulate these behaviors, both in volume and specific domains (e.g., sedentary time spent on recreational screen activities vs homework). The aim of this study was to examine how youth's combined general and domain-specific movement trajectories differ by socioeconomic position.

METHODS

We conducted a longitudinal, group-based multi-trajectory analysis to identify general and domain-specific movement trajectory profiles for 2457 youth from age 10 to 14 years from the Longitudinal Study of Australian Children from 2014-2018. We used multinomial logistic regression to test if socioeconomic position predicted profile membership.

RESULTS

We identified three general movement trajectory profiles for both sexes, four domain-specific profiles for males, and five for females. For general movement trajectories, females from lower socioeconomic positions were more likely to be a combination of less active and more sedentary than females from higher socioeconomic positions. Males across socioeconomic positions spend similar amounts of time in physical activity, sedentary time, and sleep. For domain-specific movement trajectories, youth from lower socioeconomic positions were likely to spend a combination of less time in education-based sedentary behavior and more time in recreational screen activities than their higher socioeconomic position peers.

CONCLUSION

Our results indicate that socioeconomic position predicted in which domains youth accumulate their movements. Future observational research and interventions targeting different socioeconomic groups should therefore consider domain-specific movement trajectories.

Sedentary behaviour profiles and longitudinal associations with academic performance in youth: The UP&DOWN study

The current study evaluated longitudinal associations between profile transitions of context-specific sedentary behaviour (SB) and changes in academic performance (AP) among school-aged youth. Participants were 466 children and 717 adolescents (50.8% males) aged 8-18 years (children = 7.92 ± 0.41 years; adolescents = 11.85 ± 1.53 years). Non-school SBs and AP were evaluated at baseline and two years later. General linear mixed models were implemented, controlling for age, region, parental education, body mass index, and cardiorespiratory fitness. Cross-sectionally, participants with an Educative-profile (i.e., highest scores in doing homework with/without computer and reading for fun) had higher AP when compared to other profiles. Longitudinally, males who changed from a Screen- to an Educative-profile had higher AP than males who changed from an Educative- to a Social- or Screen-SB profile (p < 0.01). No significant differences were found in females. These findings show the importance of analysing SB patterns from a qualitative perspective (i.e., context-specific for boosting school children AP) and highlighting time spent in educative as the most positive for AP, as well the need to implement interventions to reduce time on screen and social behaviours, especially targeting males.

Are There Common Correlates of Adolescents' Sport Participation and Screen Time?

Objective: This study aimed to identify intrapersonal, interpersonal, and environmental correlates of leisure-time participation in sports and examine whether they are also associated with screen-time among adolescents. Methods: Adolescents from eight schools in Victoria, Australia were recruited for this study. Participants (n = 400) comprised of an even distribution of boys (51%) and girls (49%) aged 12-16 years. Their engagement in leisure-time activities (including sports and screen-time) and 13 potential correlates were self-reported. Multinomial logistic regression analyses examined correlates of sports and screen-time participation categories, accounting for clustering by school and adjusting for significant sociodemographic characteristics. Results: The majority (76%) participated in leisure-time sports and exceeded screen-time recommendations (<2 h/day) on both weekdays (69%) and weekend days (85%). Greater internal motivation for sports was positively associated with sports participation and inversely associated with screen-time on weekend days, respectively. Fewer barriers, positive family and coach support and more neighborhood sporting opportunities were significantly associated with greater sports participation. Neighborhood social norms were inversely associated with sports participation. Preference for sports was associated with less weekday and weekend screen-time. Friend support for sports was inversely associated with weekday screen-time. Access to sports facilities in the local neighborhood was associated with more weekday and weekend screen-time. Conclusion: Internal motivation for sports was associated with both sports participation and less screen-time. Preference for leisure-time sports and friend support for sports were associated with less screen-time. Future research should continue to explore common correlates of multiple leisure-time behaviors to inform the development of effective intervention strategies.

Independence and Sex Differences in Physical Activity and Sedentary Behavior Trends from Middle Adolescence to Emerging Adulthood: A Latent Class Growth Curve Analysis

The purpose of this study was to examine the relationship and sex differences in the growth patterns of moderate-to-vigorous physical activity (MVPA) and sedentary behavior (SB) from middle adolescence (around age 15) to emerging adulthood (18–29 years old). We used the secondary data from the National Longitudinal Study of Adolescent Health’s (Add Health) publicly accessible database. MVPA and SB were assessed four times (1995, 1996, 2000–2001, and 2008–2009) for a total of 681 individuals from middle adolescence to emerging adulthood. Latent class growth modeling was utilized to identify heterogeneous growth patterns in MVPA and SB. Chi-square tests were used to assess group dependence and sex differences in MVPA and SB growth patterns. Seven quadratic growth patterns for MVPA and two linear growth patterns for SB were found. Both MVPA and SB growth patterns exhibited slow or rapid rate of change at different periods of adolescence and emerging adulthood. MVPA growth patterns included: decline (slow)-and-rise (rapid), rise-and-decline (both rapid), decline-and-rise (both rapid), consistently low, consistently high, decline (rapid)-and-decline (slow), and decline (rapid)-and-rise (slow). SB growth patterns included: consistently low (slow decline) and consistently high (rapid decline). While women were more likely to be involved in consistently low group for MVPA and consistently low (slow decline) group for SB, men were more likely to be involved in rise-and-decline (both rapid) group, consistently high group, and decline (rapid)-and-rise (slow) group for MVPA and consistently high (rapid decline) group for SB. SB growth patterns were independent of MVPA growth patterns. SB should not be assumed to decrease as a result of MVPA intervention. Treatment of MVPA should prioritize adolescence over emerging adulthood, with an emphasis on preventing men’s MVPA levels from decreasing in emerging adulthood and increasing women’s overall MVPA levels.

From Secondary School to University: Associations Between Domain-Specific Sedentary Behaviors and Lifestyle Risk Behaviors

This study examined associations between changes in domain-specific sedentary behaviors and changes in health-related lifestyles of Spanish secondary school students (n = 113) to their first year of university. During the transitions from the end of high school to the beginning of university, engagement in sedentary behaviors have emerged as potential additional behavioral risk factors. Understanding how sedentary behaviors interconnect with other (un)healthy behaviors will inform interventions on multiple risk behaviors across this critical life period. A 3-year longitudinal survey assessed associations between domain-specific sedentary behaviors and leisure time physical activity (IPAQ), alcohol and tobacco consumption, and fruit and vegetable intake (24-h dietary recall), using Generalized Estimating Equations. Spending time on sedentary transportation was associated with a greater likelihood of smoking, whereas sedentary weekend homework was associated with a reduced likelihood of consuming alcohol. The lowest and highest tertiles for sedentary screen use and leisure-time PA were also less likely not to meet the recommendations for fruit and vegetable consumption. For specific sedentary behaviors, associations were gender-based or affected by leisure time physical activity. From secondary school to university, specific sedentary behaviors are linked to lifestyle risk factors. Over this transitional period, public health interventions targeting reduced sedentary behaviors may bring multiple benefits by also preventing other harmful behaviors.

Sport Injuries among Amateur Women and Young Intermediate Level Female Handball Players: A Preliminary Investigation

Background and objectives: Handball is a popular sport among women whose practice can lead to marked health benefits but could also show a high injury risk. There is a lack of research on intermediate level female players. We aimed to identify the prevalence of sport injuries in amateur and young intermediate level female handball players and the potential influence of the sport category. Materials and Methods: A group of cadets, juvenile and senior female players of three handball clubs participating in the Spanish regional league were followed throughout the 2018–2019 season. Information on injuries and exposure was collected via questionnaires. Results: Out of 114 players (34 seniors, 33 juvenile and 47 cadets), 77 of them sustained at least one injury. Most of the injuries were either moderate or severe, regardless of the category. A total of 7.93, 5.93 and 4.16 injuries per 1000 h of exposure were registered in the senior, juvenile and cadet categories respectively. The risk of sustaining an injury was 2.14 times higher for senior players Confidence Interval (CI 95%: 1.51–3.03) and 1.92 higher for juvenile players (CI 95%: 1.32–2.78) when compared with cadets. Conclusions: Senior and young female handball athletes playing at an amateur and intermediate level, are exposed to a substantial risk of sustaining a moderate or severe injury. The players’ category does not seem to have a great impact on the injury rate and on the characteristics of the sport injuries registered.