Objectives To understand the role of household variables on the percentage of physical activity (%PA) during the COVID-19 confinement in Portugal. Study Design A Cross-sectional study design using an anonymous online survey was launched to assess how Portuguese families with children under 13 years of age adjusted their daily routines to the confinement. Methods Separate ANOVAs were performed to investigate how factors, such as the number of children, age, sex, the housing characteristics, and the adults’ job situation, can affect the percentage of time for physical activity (%PA). Results Findings, based on data from 2159 children, indicate that: I) Boys and girls did not differ in the %PA on any of the age groups; II) Children with an outdoor space and who had other children in the household were significantly more active (p<.001); III) Children from families with all adults working from home showed lower levels of %PA; IV) Being younger, having a big outdoor space, having other children in the household, and having at least one adult free from working from home, were significant positive predictors of children’s %PA, explaining 21% of the overall variance. Conclusion Time allocated for PA during this period is reduced compared to what is usually reported on normal days. It is necessary to find strategies to increase children's PA, especially in families where both parents are working and have no outdoor space.

a b s t r a c tObjectives: This study was aimed at developing a quantitative model to evaluate motor competence (MC) in children and adolescents, to be applicable in research, education, and clinical contexts. Design: Cross-sectional. Methods: A total of 584 children (boys n = 300) with ages between 6 and 14 years were assessed using nine well known quantitative motor tasks, divided into three major components (stability, locomotor and manipulative). Structural equation modelling through EQS 6.1 was used to find the best model for representing the structural and measurement validity of MC. Results: The final MC model was composed by three latent factors closely related with each other. Each factor was best represented by two of the initial three motor tasks chosen. The model was shown to give a very good overall fit ( 2 = 12.04, p = .061; NFI = .982; CFI = .991; RMSEA = .059). Conclusions: MC can be parsimoniously represented by six quantitative motor tasks, grouped into three interrelated factors. The developed model was shown to be robust when applied to different samples, demonstrating a good structural and measurement reliability. The use of a quantitative protocol with few, simple to administer and well known, motor tasks, is an important advantage of this model, since it can be used in several contexts with different objectives. We find it especially beneficial for physical educations teachers who have to regularly assess their students.

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