The relationship between socio-economic status, parental support and adolescent physical activity

Aim: To examine: 1) the association between socio-economic status and adolescent physical activity; 2) to assess links between mothers' and fathers' social support and adolescents' physical activity. Methods: Participants were 326 urban adolescents and their parents. Physical activity was measured using a 7-d physical activity recall. Socio-economic status and parents' social support was assessed using questionnaires. Results: Boys were significantly more active than girls, and fathers' explicit modelling towards boys was higher compared to girls. In contrast, fathers' and mothers' logistic support was significantly higher towards their daughters. Social class and fathers' and mothers' social support were significantly related to adolescent self-reported physical activity. Fathers' explicit modelling was the strongest predictor of adolescent physical activity, predicting 13.5% of the total variance. Social class, fathers' logistic support and mothers' explicit modelling were also significant predictors, accounting for additional 14% of the variance in adolescents' weekly physical activity.
Conclusion: Parental support and social class are positively related to physical activity in Estonian adolescents.     

Evaluation of a smartphone nutrition and physical activity application to provide lifestyle advice to pregnant women: The SNAPP randomised trial

Our objective was to evaluate the impact of a smartphone application as an adjunct to face‐to‐face consultations in facilitating dietary and physical activity change among pregnant women. This multicentre, nested randomised trial involved pregnant women with a body mass index ≥18.5 kg/m², with a singleton pregnancy between 10 and 20 weeks' gestation, and participating in 2 pregnancy nutrition‐based randomised trials across metropolitan Adelaide, South Australia. All women participating in the SNAPP trial received a comprehensive dietary, physical activity, and behavioural intervention, as part of the GRoW or OPTIMISE randomised trials. Women were subsequently randomised to either the “Lifestyle Advice Only Group,” where women received the above intervention, or the “Lifestyle Advice plus Smartphone Application Group,” where women were additionally provided access to the smartphone application. The primary outcome was healthy eating index (HEI) assessed by maternal food frequency questionnaire completed at trial entry, and 28 and 36 weeks' gestation. Analyses were performed using intention‐to‐treat principles, with statistical significance at p = .05. One hundred sixty‐two women participated: 77 allocated to the Lifestyle Advice plus Smartphone Application Group and 85 to the Lifestyle Advice Only Group. Mean difference in HEI score at 28 weeks of pregnancy was 0.01 (CI [?2.29, 2.62]) and at 36 weeks of pregnancy ?1.16 (CI [?4.60, 2.28]). There was no significant additional benefit from the provision of the smartphone application in improving HEI score (p = .452). Although all women improved dietary quality across pregnancy, use of the smartphone application was poor. Our findings do not support addition of the smartphone application.     

Associations between physical activity, sedentary behavior, and glycemic control in a large cohort of adolescents with type 1 diabetes: the Hvidoere Study Group on Childhood Diabetes

Background: The Hvidoere Study Group on Childhood Diabetes has demonstrated persistent differences in metabolic outcomes between pediatric diabetes centers. These differences cannot be accounted for by differences in demographic, medical, or treatment variables. Therefore, we sought to explore whether differences in physical activity or sedentary behavior could explain the variation in metabolic outcomes between centers. Methods: An observational cross‐sectional international study in 21 centers, with demographic and clinical data obtained by questionnaire from participants. Hemoglobin A1c (HbA1c) levels were assayed in one central laboratory. All individuals with diabetes aged 11–18 yr (49.4% female), with duration of diabetes of at least 1 yr, were invited to participate. Individuals completed a self‐reported measure of quality of life (Diabetes Quality of Life ‐ Short Form [DQOL‐SF]), with well‐being and leisure time activity assessed using measures developed by Health Behaviour in School Children WHO Project. Results: Older participants (p < 0.001) and females (p < 0.001) reported less physical activity. Physical activity was associated with positive health perception (p < 0.001) but not with glycemic control, body mass index, frequency of hypoglycemia, or diabetic ketoacidosis. The more time spent on the computer (r = 0.06; p < 0.05) and less time spent doing school homework (r = ?0.09; p < 0.001) were associated with higher HbA1c. Between centers, there were significant differences in reported physical activity (p < 0.001) and sedentary behavior (p < 0.001), but these differences did not account for center differences in metabolic control. Conclusions: Physical activity is strongly associated with psychological well‐being but has weak associations with metabolic control. Leisure time activity is associated with individual differences in HbA1c but not with intercenter differences.     

One‐year longitudinal study found a bidirectional relationship between physical activity and sleep disturbance in teenage Estonian girls

Aim

Studies have shown that physical activity (PA) declines during adolescence, especially among girls. We examined the relationship between changes in PA and sleep disturbance over the school year, including any bidirectional relationship between these two factors.

Methods

This longitudinal study focused on teenage girls who had a mean age of 13.2 ± 0.2 years at baseline and were drawn from five randomly selected schools in the city of Tartu, Estonia. Sleep disturbance and PA were subjectively assessed using the self‐reported 3‐Day Physical Activity Recall and the Insomnia Severity Index, at four intervals throughout the school year. Latent growth curve analyses were used to evaluate longitudinal and bidirectional associations between PA and sleep disturbance.

Results

Assessments were carried out at three‐monthly intervals from September 2015 to June 2016. Sleep disturbance increased and PA decreased over the school year. At baseline, higher PA was related to lower sleep disturbance. Changes in PA corresponded with changes in sleep disturbance. A negative bidirectional relationship between sleep disturbance and PA over time was also found.

Conclusion

These results suggest that increasing PA may be an effective strategy for improving the quality of sleep in girls during early adolescence.