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1.
Front Psychol ; 12: 614628, 2021.
Article in English | MEDLINE | ID: mdl-33679529

ABSTRACT

Schools have been the main context for physical activity (PA) and sedentary behavior (SB) interventions among adolescents, but there is inconsistent evidence on whether they also improve dimensions of the health-related quality of life (HRQoL). The aim of this study was to evaluate the effects of a school-based active lifestyle intervention on dimensions of HRQoL. A secondary aim was to verify whether sex, age, and HRQoL at baseline were moderators of the intervention effect. A cluster-randomized controlled trial was conducted at three control and three intervention schools in Florianopolis, Brazil. All students from 7th to 9th grade were invited to participate. A school year intervention, designed primarily to increase PA and reduce SB, included strategies focused on (i) teacher training on PA, SB, and nutrition, and availability of teaching materials related to these contents; (ii) environmental improvements (i.e., creation and revitalization of spaces for the practice of PA in school); and (iii) education strategies, with the availability of folders and posters regarding PA, SB, and nutrition. Participants and the research staffs were not blinded to group assignment, but a standardized evaluation protocol was applied at baseline and after the intervention (March and November 2017) using the KIDSCREEN-27 to assess HRQoL across five dimensions. Mixed linear models were performed to evaluate the effect of the Movimente intervention on the five HRQoL dimensions. Of the 921 students who answered the questionnaire at baseline, 300 and 434 completed the study in control and intervention groups, respectively (dropouts: 20%). The results revealed no significant effects of the intervention on any HRQoL dimensions. A reduction of the school environment dimension was observed in both the control (-2.44; 95% CI: -3.41 to -1.48) and intervention groups (-2.09; 95% CI: -2.89 to -1.30). Sensitivity analyses showed that students in the highest baseline tertiles of HRQoL in any dimension had a reduction in their respective scores from pre- to post-intervention in both school groups. In conclusion, our results demonstrated no intervention effect on HRQoL dimensions and those students with the highest levels of HRQoL at baseline on all dimensions reduced from pre to post-intervention. CLINICAL TRIAL REGISTRATION: The trial is registered at the Clinical Trial Registry (Trial ID: NCT02944318; date of registration: October 18, 2016).

2.
Int J Behav Nutr Phys Act ; 17(1): 160, 2020 12 04.
Article in English | MEDLINE | ID: mdl-33276782

ABSTRACT

BACKGROUND: Structured settings, such as school, childcare, afterschool programs, summer camps, and physical activity/sport programs are crucial to promoting physical activity (PA) opportunities and reducing sedentary (ST) for children and adolescents. However, little is known about how much PA and ST children and adolescents accumulate in structured settings. The aim of this study is to conduct a systematic review and meta-analysis of the absolute amount of time youth spend physically active and sedentary in different structured settings (Prospero number: 42018111804). METHODS: Observational and experimental/quasi-experimental studies (baseline data only) with full-text available, written in English and published in a peer-reviewed journal, reporting the total amount of objectively measured PA (light, moderate, vigorous, and/or total physical activity) and/or time spent ST during structured settings among youth (3 to 18 years) were eligible. Adjusted meta-analysis was conducted to estimate the pooled mean of time spent in PA and ST, by settings and sex. RESULTS: A total of 187 studies (childcare n=60; school n=91; afterschool programs n=14; summer camp n=4; and Physical activity/ sport programs n=18) from 30 countries (47.9% United States), representing 74,870 youth (mean age 8.6 years old) were included. Overall, there was a high variation between studies in outcomes and settings. The meta-analyses revealed, on average, youth spend 221.8 minutes (36.7 min/hour) in ST and 32.1 minutes (5.1 min/hour) in MVPA during childcare hours, and 223.9 minutes (36.7min/hour) in ST and 27.8 min (4.4 min/hour) in MVPA at school. Relatively, youth are engaged in more MVPA in afterschool programs (11.7 min/hour), PA/ sport programs (20.9 min/hour), and summer camps (6.4 min/hour), when compared to childcare and school. CONCLUSION: Total PA accumulated during childcare and MVPA accumulated during schools hours were close to recommendations, despite high proportion of ST. Afterschool programs, summer camp and PA/ sport programs are important settings that can contribute to daily PA and reduced ST. Ensuring all youth have access to these structured settings may be an important step forward for public health.


Subject(s)
Exercise , Sedentary Behavior , Accelerometry , Adolescent , Child , Child Care , Child, Preschool , Exercise/physiology , Female , Health Promotion , Humans , Male , Schools , Sports
3.
Int J Public Health ; 65(6): 881-891, 2020 Jul.
Article in English | MEDLINE | ID: mdl-32632457

ABSTRACT

OBJECTIVES: To identify patterns of non-dietary obesogenic behaviors, and social and environmental factors associated with overweight and obesity (OWOB). METHODS: A representative sample (n = 5520) of high school students (55.4% girls, 16.3 ± 1.0 years) from Pernambuco State, Brazil. Latent profile analyses were performed using self-reported daily sleep duration, television use, computer use, videogame use, seated time during the week and weekend days, physical activity, and active commuting to school during the week. Social and environmental factors and body mass index were included to identify classes. Multinomial analysis explored differences in social, environmental factors, and BMI by classes. RESULTS: Five patterns were identified [Computer users (C1), Short sleepers (C2), Typical behaviors (C3), Techno-active-gamers (C4), and Lower screen engagement (C5)]. Three groups (C1, C3 and C4) included students from better social conditions and a more urbanized environments. The prevalence of OWOB was higher in C1 (34.5%; 95% CI 31.1-38.0) and in C2 (29.7%; 95% CI 26.1-33.5) compared to C5 (23.3% 95% CI 21.3-25.3). CONCLUSIONS: In one of the poorest regions of Brazil, different groups of social/environmental factors and behavior patterns emerged associated with OWOB.


Subject(s)
Adolescent Behavior/psychology , Computers/statistics & numerical data , Exercise/psychology , Students/psychology , Television/statistics & numerical data , Video Games/psychology , Video Games/statistics & numerical data , Adolescent , Body Mass Index , Brazil/epidemiology , Female , Humans , Male , Overweight/epidemiology , Self Report , Surveys and Questionnaires
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