Computational protocol: Does school-based physical activity decrease overweight and obesity in children aged 6–9 years? A two-year non-randomized longitudinal intervention study in the Czech Republic

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Protocol publication

[…] Data were analysed using STATISTICA v.9 and SPSS v19. Four two-way (intervention and control group × 2 genders) analyses of variance (ANOVA) for repeated measures examined the PA programme and gender effects on PA levels, separately for the amount of steps and AEE. Schooldays, weekends, school and leisure times of working days were used as dependent variables to thoroughly examine the PA programme and gender effects on PA levels in each part of the monitored week. Tukey’s HSD post-hoc test identified differences in PA levels between control and intervention children at different times of week (schooldays × weekends), and time of day (school × leisure time). Data were adjusted only for clustering at school level due to the same design of PA intervention programme and also due to the similar PA-conducive environments at the selected intervention schools. When using ANOVA for repeated measures, clustering was controlled for employing the school attendance list and PA log book. T-test for dependent samples identified differences of the PA levels in each of the repetitive measures in participants of the same sex and group (i.e. either control or intervention). Logistic regression (Enter method) determined the obesity and overweight occurrence prospect over the course of implementation of the PA intervention. The model included independent variables such as affiliation with a group (intervention vs. control) and sex (girls vs. boys). The strength of the relationships between the independent (affiliation with a group, sex) and dependent (AEE and amount of steps) variables on schooldays, weekends, school time and leisure time was assessed by means of “effect size” d coefficient for repetitive measures [], where values d = 0.2, 0.5 and 0.8 may be interpreted as minor, middle and major effects [,]. […]

Pipeline specifications

Software tools Statistica, SPSS
Application Miscellaneous
Organisms Homo sapiens