Levels of Physical Activity at Age 10 Years and Brain Morphology Changes From Ages 10 to 14 Years

Adherence to 24-hour activity cycle and a whole brain volumetric approach in adolescence: A cross-sectional study - The Cogni-Action project

BACKGROUND

While adherence to the WHO 24-hour movement guidelines has been linked to improved health outcomes, its relationship with brain morphology remains underexplored, particularly in understudied populations such as Latin American adolescents.

METHODS

This cross-sectional study examined brain morphology in 58 Chilean adolescents using structural T1-weighted magnetic resonance imaging. Brain volumes, including total gray matter, cortical, subcortical, hippocampal, and amygdala regions, were analyzed. Adherence to moderate-to-vigorous physical activity (MVPA) and sleep guidelines was assessed via accelerometry, while screen time was self-reported. Linear regression models were used to explore associations between guideline adherence and brain volumes, with p-values corrected using the FDR method.

RESULTS

Independently, most adolescents met only the screen time guideline (55 %), while fewer met sleep duration (12 %) or MVPA based on the sample-specific cutoff (27 %), with none meeting the international MVPA criterion. In combination, only 9 % adhered to both sleep and screen time recommendations, and no participants met all three guidelines. Notably, only adherence to screen time recommendations showed a trend-level association with lower total gray matter, cortical, subcortical, hippocampal, and amygdala volumes (FDR p-value < 0.100).

CONCLUSION

This study suggests that adolescents' daily habits-screen time, physical activity, and sleep-have complex relationships with brain development, which may sometimes diverge from expected patterns, as seen in the case of meeting screen time guidelines. As the first study conducted in Latin American adolescents, these suggests proposes that the relationship between these behaviors and brain development may differ from what has been reported in high-income countries, highlighting the need for further research in diverse socioeconomic and cultural contexts.

Sports participation & childhood neurocognitive development

Various psychosocial factors like collaboration inherent to team sports might provide a more dynamic environment for cognitive challenges that could foster enhanced neurocognitive development compared to individual sports. We investigated the impact of different organised sports on neurocognitive development in children (N = 11,878; aged 9-11) from the Adolescent Brain Cognitive Development (ABCD) study. Participants were classified into four categories based on their sports involvement at baseline and two years later: none, individual-based, team-based, or both. Cross-sectional and longitudinal analyses were conducted on 11 cognitive tests and neuroimaging metrics (i.e., resting-state functional connectivity and various grey matter (GM) and white matter (WM) measurements) between sport groups. A comparison between team and individual sports yielded no significant differences in cognitive measures at baseline and follow-up. Similarly, although WM microstructural differences were significant, the effect size was small. However, participation in any sport at baseline was associated with superior performance in various cognitive domains (i.e. inhibition, processing speed, and others), greater subcortical GM volume (i.e. cerebellum cortex, amygdala, hippocampus, and others), and whole-brain WM integrity compared to non-participants. Results suggest a positive association between organised sports participation, specifically individual and team-based sports, and neurocognitive development. However, further investigation is warranted to determine the nuanced effects of different sports on neurocognitive development.

Changes in Rest-Activity Rhythms in Adolescents as They Age: Associations With Brain and Behavioral Changes in the ABCD Study

OBJECTIVE

Adolescents with disrupted rest-activity rhythms (RARs), including shorter sleep duration, later sleep timing, and low physical activity levels, are at greater risk for mental health and behavioral problems. It remains unclear whether the same associations can be observed for within-subject changes in RARs.

METHOD

This longitudinal investigation on RARs used Fitbit data from the Adolescent Brain Cognitive Development (ABCD) Study at the 2-year follow-up (FL2) (ages 10-13 years) and 4-year follow-up (FL4) (ages 13-16 years). Good-quality Fitbit data were available for 963 youths at both time points. Changes in RARs from FL2 to FL4, their environmental and demographic contributors, and brain and behavioral correlates were examined.

RESULTS

From FL2 to FL4, adolescents showed decreases in sleep duration and physical activity as well as delayed sleep timing (Cohen d = 0.44-0.75). Contributions of environmental and demographic factors to RAR changes were greatest for sleep timing (explained 10% variance) and least for sleep duration (explained 1% variance). Delays in sleep timing had stronger correlations with behavioral problems including impulsivity and poor academic performance than reductions in sleep duration or physical activity. Additionally, the various brain measures differed in their sensitivity to RAR changes. Reductions in sleep duration were associated with decreased functional connectivity between subcortical regions and sensorimotor and cingulo-opercular networks and with enhanced functional connectivity between sensorimotor, visual, and auditory networks. Delays in sleep timing were mainly associated with gray matter changes in subcortical regions.

CONCLUSION

The current findings corroborate the importance of sleep and physical activity in brain neurodevelopment and behavioral problems in adolescents. RARs might serve as biomarkers for monitoring behavioral problems and be potential therapeutic targets for mental disorders in adolescents.

Monitoring Activity and Gait in Children (MAGIC) using digital health technologies

BACKGROUND

Digital health technologies (DHTs) can collect gait and physical activity in adults, but limited studies have validated these in children. This study compared gait and physical activity metrics collected using DHTs to those collected by reference comparators during in-clinic sessions, to collect a normative accelerometry dataset, and to evaluate participants' comfort and their compliance in wearing the DHTs at-home.

METHODS

The MAGIC (Monitoring Activity and Gait in Children) study was an analytical validation study which enrolled 40, generally healthy participants aged 3-17 years. Gait and physical activity were collected using DHTs in a clinical setting and continuously at-home.

RESULTS

Overall good to excellent agreement was observed between gait metrics extracted with a gait algorithm from a lumbar-worn DHT compared to ground truth reference systems. Majority of participants either "agreed" or "strongly agreed" that wrist and lumbar DHTs were comfortable to wear at home, respectively, with 86% (wrist-worn DHT) and 68% (lumbar-worn DHT) wear-time compliance. Significant differences across age groups were observed in multiple gait and activity metrics obtained at home.

CONCLUSIONS

Our findings suggest that gait and physical activity data can be collected from DHTs in pediatric populations with high reliability and wear compliance, in-clinic and in home environments.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT04823650 IMPACT: Digital health technologies (DHTs) have been used to collect gait and physical activity in adult populations, but limited studies have validated these metrics in children. The MAGIC study comprehensively validates the performance and feasibility of DHT-measured gait and physical activity in the pediatric population. Our findings suggest that reliable gait and physical activity data can be collected from DHTs in pediatric populations, with both high accuracy and wear compliance both in-clinic and in home environments. The identified across-age-group differences in gait and activity measurements highlighted their potential clinical value.