Participation in physical activity for adolescents with disabilities: Parents' perspective

This study is to describe the role of parents in promoting the physical activity of adolescents with disabilities and to describe their perceptions of participation. This study used a qualitative descriptive design. Sample procedure using convenience sampling. A total of 28 parents of youth with disabilities aged twelve - sixteen years. Data analysis used content analysis, with the development of inductive categories using Nvivo 11 software. For eight weeks, data were collected from January to February 2020. All samples explained how many challenges involved participating in physical activities of adolescents with disabilities. After all, parents would like to see their children participating in more physical activity, but consider the promotion of physical activity to be a very demanding task that is difficult to handle alone. The finding is that the promotion of physical activity habits among adolescents with disabilities needs to be prioritized, that the support provided needs to be tailored to the needs of adolescents and their families as well as collaborative efforts and support from all partiesKeywords: adolescent, physical activity, parents, persons with disabilities

The school policy, social, and physical environment and change in adolescent physical activity: An exploratory analysis using the LASSO

Purpose We examined the association between the school policy, social and physical environment and change in adolescent physical activity (PA) and explored how sex and socioeconomic status modified potential associations. Methods Data from the GoActive study were used for these analyses. Participants were adolescents (n = 1765, mean age±SD 13.2±0.4y) from the East of England, UK. Change in longitudinal accelerometer assessed moderate-to-vigorous physical activity (MVPA) was the outcome. School policy, social and physical environment features (n = 267) were exposures. The least absolute shrinkage and selection operator variable selection method (LASSO) was used to determine exposures most relevant to the outcome. Exposures selected by the LASSO were added to a multiple linear regression model with estimates of change in min/day of MVPA per 1-unit change in each exposure reported. Post-hoc analyses, exploring associations between change in variables selected by the LASSO and change in MVPA, were undertaken to further explain findings. Findings No school policy or physical environment features were selected by the LASSO as predictors of change in MVPA. The LASSO selected two school social environment variables (participants asking a friend to do physical activity; friend asking a participant to do physical activity) as potential predictors of change in MVPA but no significant associations were found in subsequent linear regression models for all participants (β [95%CI] -1.01 [-2.73;0.71] and 0.65 [-2.17;0.87] min/day respectively). In the post-hoc analyses, for every unit increase in change in participants asking a friend to do PA and change in a friend asking participants to do PA, an increase in MVPA of 2.78 (1.55;4.02) and 1.80 (0.48;3.11) min/day was predicted respectively. Conclusions The school social environment is associated with PA during adolescence. Further exploration of how friendships during adolescence may be leveraged to support effective PA promotion in schools is warranted.

Adaptive mHealth Intervention for Adolescent Physical Activity Promotion

Objective The present nonrandomized controlled trial aimed to evaluate feasibility, acceptability, and preliminary efficacy of a tailored text message intervention for increasing adolescent physical activity, as compared with passive monitoring. Methods Forty adolescents (13–18 years old) received either a tailored text messaging intervention (Network Underwritten Dynamic Goals Engine [NUDGE]; N = 20), or participated in an attention-control condition (N = 20), for 20 days. Physical activity was measured for all participants via continuous accelerometry. Frequency analyses were conducted on program usage and satisfaction ratings to evaluate feasibility and acceptability, and multilevel models were used to evaluate the efficacy hypotheses. Results The vast majority of participants (90%) reported being very or mostly satisfied with the NUDGE program and rated their enjoyment as above average. The intervention group was estimated to spend an average of 20.84 more minutes per day in moderate-to-vigorous physical activity relative to the attention-control group (β = 20.84, SE = 8.19). Exploratory analyses revealed that the intervention group also engaged in 82 fewer minutes of sedentary time per day on average, although this effect was not significant due to the large variability in sedentary time (β = −81.98, SE = 46.86). Conclusions The NUDGE tailored text messaging intervention was feasible, acceptable, and efficacious in increasing physical activity in this sample. Findings warrant additional evaluation of NUDGE as both a standalone physical activity intervention or as part of a multicomponent package.

Adolescent physical activity, sedentary behavior and sleep in relation to body composition at age 18 years in urban South Africa, Birth-to-Twenty+ Cohort

Background Adolescence is marked by a decline in physical activity, rapid physical growth and changes in body composition, which have been linked to body composition. Prospective data on these associations are rare, particularly in Africa. Aim The aim of this study was to examine the association of longitudinal patterns across adolescent in physical activity, sedentary behavior and sleep, with anthropometry and body composition at age 18 years in urban South Africa. Methods We analyzed data from the Birth-to-Twenty Plus Cohort (Bt20+), a longitudinal study of children born in 1990 in Soweto-Johannesburg, South Africa. We used general linear models to investigate the association of adolescent (ages 12 to 18 years) longitudinal trends in physical activity, sedentary behavior and schoolnight sleep and overall physical activity patterns, with body mass index (BMI), waist circumference, fat mass index (FMI), lean mass index (LMI) and percent body fat at age 18 years. Results The final study sample included 1337 participants with anthropometric measurements (52% female) and 958 participants with body composition measurements (53% female). Males who were consistently more active and consistently walked to school over adolescence had lower waist circumference (B = − 2.0, 95% CI: − 3.9 to − 0.2), FMI (B = − 0.8, 95%: CI: − 1.2 to − 0.1) and percent body fat (B = -2.9, 95% CI: − 4.9 to − 0.9) at age 18 years than those who decreased activity and did not walk to school. Consistently-sedentary females had higher waist circumference than those whose sedentary behavior increased over adolescence (B = 5.4, 95% CI: 0.2 to 10.6). Males who reported sleeping 9 h or more per night on schoolnights had significantly lower BMI (B = -1.0, 95% CI: − 1.4 to- 0.5), and percent body fat (B = -1.5, 95%CI − 2.8 to − 0.1) than those who reported sleeping 8 h or less per night. Conclusion Patterns of adolescent physical activity, sedentary behavior and sleep are related to young-adult body composition in urban South Africa. These modifiable behaviors may be paths for public health interventions to curb overweight and obesity in many low- or middle-income countries.

A multi-method exploration into the social networks of young teenagers and their physical activity behavior

Background There is a need for novel interventions to target inadequate levels of adolescent physical activity behavior. Previous research indicates that better understanding of the processes by which social networks influence physical activity behavior in adolescents may be useful to enhance intervention design. Methods This study used a multi-methods approach to aid our understanding about the role of social networks for adolescent physical activity behavior. The quantitative phase of data collection was analyzed using a three-step linear regression model using cross-sectional data from the WiSe study (n = 529 participants, 48.6% female, mean age 14.38 years (SD 0.32)). A demographically reflective sub-sample of schools were invited to take part in the qualitative phase, which involved focus group discussions. Thematic analysis was used to explore findings from the quantitative phase in greater depth, and identify other themes pertaining to the association between social networks and physical activity behavior. Results Males’ physical activity behavior was predicted by their friend group (0.46, p = 0.007) whereas females’ physical activity was predicted by their best friend (0.21, p = 0.03). The three main findings that were uncovered by the regression analysis were explored during the qualitative phase: 1) friends have similar physical activity behaviors; 2) friendship social networks may influence differently early adolescent male and female physical activity behavior; 3) popularity and sociability were not associated with physical activity behavior. Two additional themes emerged from the analysis of focus group data: 4) social norms and 5) external factors that may impact the relationship between adolescent physical activity behavior and social networks. Conclusions The investigation of the interplay between the findings from each phase of the inquiry indicated that social networks influence in different ways and to different degrees the physical activity of adolescent males and females. In turn, these insights point to the need for a systematic tailoring process for the development and implementation of physical activity behavior interventions.

Effect of early determinants on adolescent fat-free mass

OBJECTIVE: To analyze the effects of early determinants on adolescent fat-free mass. METHODS: A c ohort s tudy w ith 5 79 a dolescents e valuated a t b irth a nd a dolescence i n a birth cohort in São Luís, Maranhão. In the proposed model, estimated by structural equation modeling, socioeconomic status (SES) at birth, maternal age, pregestational body mass index (BMI), gestational smoking, gestational weight gain, type of delivery, gestational age, sex of the newborn, length and weight at birth, adolescent socioeconomic status, “neither study/nor work” generation, adolescent physical activity level and alcohol consumption were tested as early determinants of adolescent fat-free mass (FFM). RESULTS: A higher pregestational BMI resulted in higher FFM in adolescence (Standardized Coefficient, SC = 0.152; p < 0.001). Being female implied a lower FFM in adolescence (SC = -0.633; p < 0.001). The negative effect of gender on FFM was direct (SC = -0.523; p < 0.001), but there was an indirect negative effect via physical activity level (SC = -0.085; p < 0.001). Women were less active (p < 0.001). An increase of 0.5 kg (1 Standard Deviation, SD) in birth weight led to a gain of 0.25 kg/m2 (0.106 SD) in adolescent FFM index (p = 0.034). Not studying or working had a negative effect on the adolescent’s FFM (SC = -0.106; p = 0.015). Elevation of 1 SD in the adolescent’s physical activity level represented an increase of 0.5 kg/m2 (0.207 SD) in FFM index (p < 0.001). CONCLUSIONS: The early determinants with the greatest effects on adolescent FFM are gender, adolescent physical activity level, pregestational BMI, birth weight and belonging to the “neither-nor” generation.