Does School-Based Health Promotion Affect Physical Activity on Weekends? And, Does It Reach Those Students Most in Need of Health Promotion?

<div><p>Objective</p><p>To determine whether a school-based health promotion program affects children’s weekend physical activity and whether this effect varies according to socioeconomic-status.</p><p>Methods</p><p>This was a quasi-experimental trial of school-based programs on physical activity levels implemented in disadvantaged neighborhoods in Alberta, Canada. In 2009 and 2011, 7 full days of pedometer data were collected from cross-sectional samples of grade 5 students (age 10–11 years) from 10 intervention schools in low-socioeconomic neighbourhoods and 20 comparison schools in middle-socioeconomic neighbourhoods. Multilevel models assessed differences in step-counts between intervention and comparison groups over-time by weight (objectively measured) and socioeconomic status subgroups.</p><p>Results</p><p>In 2009, children from intervention schools were less active on weekends relative to comparison schools (9212 vs. 11186 steps/day p<0.01). Two years later, daily step-counts on weekend days among children in low socioeconomic intervention schools increased such that they approximated those of children from middle socioeconomic comparison schools (12148 vs. 12121 steps/day p = 0.96). The relative difference in steps between intervention and comparison schools on weekends reduced from -21.4% to 0.2% following the intervention. The normalization of weekend step counts was similar for normal weight (–21.4% to +2.0%) and overweight (-19.1 to +3.9%) children, and was balanced across socioeconomic subgroups.</p><p>Conclusions</p><p>These data suggest that school-based health promotion is effective for reducing inequities in physical activity levels outside school hours. Investments in school-based health promotion lead to behavior modification beyond the school environment.</p><p>Trial Registration</p><p>ClinicalTrials.gov <a href="http://www.clinicaltrials.gov/ct2/show/NCT01914185" target="_blank">NCT01914185</a></p></div

Description of enrollment of schools in the study and participation of grade 5 students in data collection, their pedometer usage, and analyses.

<p>Description of enrollment of schools in the study and participation of grade 5 students in data collection, their pedometer usage, and analyses.</p

Characteristics of grade 5 students attending APPLE Schools and comparison schools in 2009 and 2011.

<p>^a: APPLE Schools = Alberta Project Promoting active Living and healthy Eating Schools</p><p>Characteristics of grade 5 students attending APPLE Schools and comparison schools in 2009 and 2011.</p

Inequity in physical activity levels (steps/day) on school days (Monday-Friday) and weekend days (Saturday, Sunday, holidays) by grade 5 students attending APPLE Schools and comparison schools over a two-year interval (2009–2011) of a Comprehensive School Health intervention.

<p>^a; CI = Confidence interval</p><p>^b: |relative difference in 2009|+Relative difference in 2011</p><p>^c:adjustments for potential confounders included: gender, parental education, and household income</p><p>^d: adjustments for potential confounders included: gender</p><p>Note: bolded 95% CI indicate statistical significance at p<0.05.</p><p>Inequity in physical activity levels (steps/day) on school days (Monday-Friday) and weekend days (Saturday, Sunday, holidays) by grade 5 students attending APPLE Schools and comparison schools over a two-year interval (2009–2011) of a Comprehensive School Health intervention.</p

Mean number of steps taken among all students from APPLE Schools and comparison schools in 2009 and 2011 on a) school days; b) weekend days; c) school hours; and d) non-school hours.

<p>Mean number of steps taken among all students from APPLE Schools and comparison schools in 2009 and 2011 on a) school days; b) weekend days; c) school hours; and d) non-school hours.</p

Inequity in physical activity levels (steps/hour) during school (8:00am–3:59pm) and non-school hours (7:00–7:59am & 4:00–8:59pm) by grade 5 students attending APPLE Schools and comparison schools over a two-year interval (2009–2011) of a Comprehensive School Health intervention.

<p>^a; CI = Confidence interval</p><p>^b: |relative difference in 2009|+Relative difference in 2011</p><p>^c:adjustments for potential confounders included: gender, parental education, and household income</p><p>^d: adjustments for potential confounders included: gender</p><p>Note: bolded 95% CI indicate statistical significance at p<0.05.</p><p>Inequity in physical activity levels (steps/hour) during school (8:00am–3:59pm) and non-school hours (7:00–7:59am & 4:00–8:59pm) by grade 5 students attending APPLE Schools and comparison schools over a two-year interval (2009–2011) of a Comprehensive School Health intervention.</p

DataSheet1_Relationship Between Fruit and Vegetables Intake and Common Mental Disorders in Youth: A Systematic Review.docx

Objective: Recent evidence suggests that adequate fruit and vegetables intake (FVI) might be associated with lower risk of common mental disorders (CMDs) in adults, but studies in youth are also beginning to emerge and are synthesized in this systematic review.Methods: Online databases were searched from inception to 30 October 2020 to locate cross-sectional, cohort, and case-control studies focusing on the FVI and CMDs in youth (i.e., 10–18 years old). The risk of bias of studies was assessed using Joanna Briggs Institute Critical Appraisal Tool and the Newcastle-Ottawa quality assessment scale.Results: Among 3,944 records identified, 12 studies (8 cross-sectional, 1 case-control, and 3 prospective cohort studies) were included in the final synthesis. None of the prospective cohort studies identified a statistically significant association between FVI and CMDs in youth, although inconsistent associations were reported in cross-sectional and case-control studies.Conclusion: The lack of associations between FVI and CMDs in youth, along with consistent associations in adults, might be explained by the accumulation of risk theoretical model and methodological challenges.</p