Physical activity on days with and without soccer practice in 12-13-year-old boys

Effectiveness of wearable technology to optimize youth soccer players' off-training behaviour and training responses: a parallel group randomized trial

BACKGROUND

Although youth soccer players meet and exceed the weekly physical activity (PA) guidelines also exhibit high off-training sedentary behaviour (SB) levels. Recent evidence indicated that low PA preceding training leads to decreased PA intensity in soccer practice and that SB impairs sports performance and recovery. Thus, a parallel group randomized trial examined the effect of activity wristbands on young players' off-training PA and SB profiles; assessed the added value of wearable wristbands with PA warnings; and investigated whether manipulating off-training PA can affect the players' training responses.

METHODS

Thirty-two adolescent soccer players (16.1 ± 0.9 years old) were monitored during weekdays for two weeks (interspersed with one week). Players were randomly assigned to a reminder to move (REM) and a non-reminder to move group (nREM). The REM wore an activity wristband (Fitbit Charge 2) with PA warnings in the last week of research, while the nREM wore identical monitors without PA feedback. Throughout the study, off-training PA was assessed using tri-axial accelerometers, and training responses were analysed using wearable inertial monitoring units. Gardner-Altman estimation plots and a Fisher's Exact Test of Independence estimated each group's off-training PA changes between the monitored weeks. Complementary, an analysis of covariance (ANCOVA) quantified the effect of Fitbit wristband configurations (with a reminder to move or without a reminder to move) on the off-training PA and soccer training external load variables. The independent variable group had two levels (REM and nREM). The off-training PA and training load values collected in the first week were introduced in the model as a covariate, the groups were designated fixed factors and the off-training PA and training load from the third week were the dependent variables. The team was also included as a covariate and the between-group differences post-intervention were adjusted for baseline and team.

RESULTS

Interestingly, results showed that different wearable wristbands did not influence the players' off-training PA profiles (p > 0.05). Concomitantly, no differences were observed in training responses (p > 0.05).

CONCLUSION

Findings emphasize the importance of health and youth sports organizations in developing newer approaches for promoting healthier lifestyles, beyond training practices, with potentially favourable implications for sports performance.

Off-training physical activity and training responses as determinants of sleep quality in young soccer players

This study aimed to quantify and assess the relationship of young soccer players' off-training physical activity (PA) and training responses on sleep quality. Eleven adolescent soccer players (13 ± 0.5 years old) were monitored during weekdays for four consecutive weeks, throughout soccer practice days. Off-training PA and sleep quality were assessed using 100 Hz tri-axial accelerometers and training responses analyzed using 20 Hz global positioning measurement units. A cluster analysis classified all cases into three different dimensions, (1) off-training PA, (2) training responses and (3) sleep quality. For each dimension, the most important variables for classifying the cases into clusters were sedentary PA and moderate-to-vigorous PA; total distance covered and impacts; and sleep onset latency and sleep fragmentation index, respectively. Afterwards, a correspondence analysis was used to identify whether off-training PA and training responses affected sleep quality. Results exposed that high to medium off-training PA combined with medium to high training responses may have decreased sleep quality. Conversely, no correspondence was observed between off-training PA and training responses, with higher sleep quality. This study emphasizes the importance of sports organizations adopting a holistic approach to youth soccer players' development, that appropriately considers the inter-relationship between lifestyle, performance and health-related information.

Sedentary behaviours and their relationship with body composition of athletes

During the recovery period, athletes present high sedentary behaviour (SB). In non-athletes, there is a direct relationship between SB and obesity. However, little is known about this relationship in athletes. We hypothesized that different types of SB entail different associations with body composition outcomes.We examined the associations between different types of SB and body composition outcomes in 135 athletes (70 males) aged 21.3 ± 3.9 years old. Dual-energy X-ray absorptiometry was performed to assess fat mass (FM), fat-free mass (FFM) and trunk fat mass (TFM). A validated SB questionnaire (PACE) was used to estimate total SB and specific sedentary pursuits on an average day. Multiple linear regression analyses were performed, adjusting for age, sex, weekly training time, years of sport practice, and sport type.A positive association was found for total SB and total screen time with %TFM (β = 0.220, p = 0.038 and β = 0.319, p = 0.040, respectively), while an inverse association was found for %FFM (β = -0.214, p = 0.042 and β = -0.310, p = 0.026). A higher total screen time was related with a higher %FM (β = 0.283, p = 0.035). With a much stronger effect size, cell phone screen time was positively related with %FM (β = 1.447, p = 0.001).There is still debate whether high levels of physical activity can fully counteract the harms of SB. These findings suggest that SB, particularly cell phone screen time, can compromise athletes' body composition, regardless of weekly training time. Sport federations and coaches may improve athletes' body composition by targeting specific sedentary pursuits, i.e. total screen time and cell phone screen time, during athletes' recovery time.Highlights Even in athletes, SB can compromise total and regional body composition regardless of high training time.Screen time, specifically cell phone screen time seems to be the sedentary pursuit to target in athletes.Sport federations and coaches must control SB during athletes' recovery time.

The Influence of Maturity Status on Anthropometric Profile and Body Composition of Youth Goalkeepers

The anthropometric profile assessment is an important aspect to consider during the growth stages of youth sport practitioners due to its usefulness in controlling maturity status and overall health. We performed an anthropometric profile evaluation in a sample of youth goalkeepers (n = 42) during a training camp, dividing them into three categories based on their years from peak height velocity (YPHV). We also checked if the selection of goalkeepers was associated with the birth quartile. The results showed that most of the participants' anthropometric parameters followed the normal trend according to the maturation stages. However, several subjects showed an overweight/obese condition and/or high waist circumference. Non-optimal values were found, mostly in the group of goalkeepers around the PHV. In addition, no selection based on birth quartile was seen. Therefore, the anthropometric profile and body composition of youth goalkeepers are physiologically affected by maturity status. However, several subjects were found to be overweight/obese and at cardiometabolic risk, suggesting that children and adolescents, although practicing sport, should pay attention to potentially contributing factors such as the attainment of the recommended levels of physical activity, lowering sedentary time, and adopt a healthy lifestyle.

Can Off-Training Physical Behaviors Influence Recovery in Athletes? A Scoping Review

Recently, the attention on recovery in sport increased enormously although there is lack of scientific evidence on the role of lifestyle in terms of movement [i.e., physical behaviors (PBs)], apart from sleep. Few studies assessed physical activity (PA) and sedentary behavior (SB) in athletes. The aims of this scoping review were to answer to the following scientific questions: (1) How active/inactive are competitive athletes out of training? (2) Do off-training PBs affect recovery, performance, and health? (3) What strategies can be implemented to improve recovery using off-training PBs, apart from sleep? From 1,116 potentially relevant articles, nine were eligible for inclusion in this review. The main issues identified were related to the heterogeneity concerning the types of sports, age category, gender, competitive level, sample size, and instruments/devices adopted, the paucity of studies investigating the effects of PBs while awake on recovery, and the lack of experimental designs manipulating PBs while awake to accelerate recovery. Furthermore, PA and SB domains were rarely investigated, while no research articles focused on the combined effect of 24-h PBs. Eight out of nine studies measured PA, seven SB, and two included sleep. Three studies included training practice into PA measurement by the means of accelerometry. Overall, almost the totality of the athletes achieved recommended PA levels although they sustained prolonged SB. In conclusion, more descriptive researches are needed in different athletic populations and settings. Furthermore, experimental designs aimed at investigating the effects of PBs manipulation on recovery and the putative mechanisms are encouraged.