The COVID-19 pandemic forced governments to implement measures that disrupted the daily routines of many families worldwide. We studied how the COVID-19 lockdown affected children’s routines in Portugal (PT), Brazil (BR), and Italy (IT) to determine if children’s age and country impacted their physical activity (PA) and sedentary time. We launched an anonymous online survey to assess how 3–12 years old children adjusted their daily routines to this situation. Parents reported the times each child was engaged in different activities throughout the day, and we used these data to calculate separately overall sedentary and physical activity time. We conducted separate analyses of variance for age and country on the percentage of time spent in the different activities. Results, based on the data from 3045 children in these three countries (PT n = 2044; BR n = 836; IT n = 165), showed that, during lockdown, most children spent most of their awake daily hours in sedentary activities. There was a clear age effect on the way their routines were organized. Percentages of time spent in intellectual activity, playful screen activity, and overall sedentary time were greater in the older age groups, whereas percentages of time spent in play (with and without PA) and in overall PA were greater in the younger groups. We found a main effect of country for all variables except play without PA. The country effect was mainly due to the difference between the routines in BR when compared to PT and IT. Values of playful screen time and overall sedentary activity were higher in BR than in the two European countries. Conversely, values for play with PA, PA, and overall PA (except in the older group) were lower in BR. Patterns of time spent in these activities were similar in IT and PT, but PA and overall PA times were higher in the two younger age groups in IT. In summary, percentage of PA time of confined children was low and decreased with age across all three countries and was particularly low for children in BR relative to those in PT and IT.

Aging process is accompanied by a gradual and sustained loss of physical abilities which leads to a progressive muscle weakness with important consequences for daily living especially in women. This study aimed was to analyze the differences by ages in dynamic balance and lower limb strength in community-dwelling women, and secondly to assess the differences in dynamic balance scores and lower limb strength between fallers and non-fallers in community-dwelling women. A total of 1025 community-dwelling women were recruited for the study. The sample were divided into six groups based on age: G1, from 60-65 yrs. (n=282); G2, from 66-70 yrs. (n=178); G3, from 71-75 yrs. (n=108); G4 from 76-80 yrs. (n=397); G5 from 81-85 yrs. (n=51) and G6, from 86-90 yrs. (n=9). The number of falls during the last year were also recorded. Significant differences were found in Sit to stand test (STS) and Timed up and go test (TUG) scores among age groups (p≤0.05). Additionally, poorer scores were found between fallers than non-fallers group (p≤0.05) both in STS and TUG test. Physical fitness performance decline as age group increase, and this decline is more striking after 70 years in community dwelling elderly women. In addition, faller elderly women show poorer scores in TUG and STS than non-fallers, reinforcing the idea that lower limb muscle strength and dynamic balance play an important role in falls in elderly women. Key words: Aging, Functional mobility, Falls, timed up and go, sit to stand  

Abstract Objective: Verify whether the practice of physical activity, before the social distancing imposed by COVID-19, influences children’s routines during this period, in children of different ages. Methods: Descriptive cross-sectional study carried out with an online questionnaire from LimeSurvey and disseminated for four months during social distancing. The questionnaire contained questions about family composition, household characteristics, household and children’s routines, including habits such as sleeping, physical activity, intellectual activity, playing with and without physical activity, and screen time. The final sample consisted of 916 participating families that answered about the physical activity habits of their respective children before the pandemic. Children were divided into three age groups (three to five years, six to nine years, and ten to twelve years). Independent Student’s t-tests were performed to investigate whether the previous practice of scheduled physical activity group and the no physical activity group differed as to the time dedicated to children’s activities and routines (intellectual activity, sleeping, screen time, playing with and without physical activity), by age groups, during social distancing. Results: There was a decrease in the levels of physical activity undertaken by Brazilian children during social distancing. There was no difference when both groups. The children with previous practice of scheduled physical activity did not display different habits from the children who did not adopt this practice. Conclusions: The practice of physical activity before social distancing did not influence the level of physical activity and other habits during social distancing. Healthy habits should be encouraged and targeted for all children during the pandemic. These findings can contribute to the formulation of public policies for children during pandemic times.

Children’s motor competence (MC) was negatively affected by the COVID-19 pandemic; however, possible chronic effects have not been studied. Therefore, the aim of this study was to examine the possible impact of the forced lack of physical activity (PA) during the COVID-19 lockdown on children’s MC two years later. The motor competence of sixty-seven healthy children (7.4–12.2 years old) was assessed using the Motor Competence Assessment (MCA). All participants completed the MCA tests at two different moments (before and after the COVID-19 lockdown), four years apart. The mean values after the COVID-19 lockdown for all participants on the subscales and on the Total MCA are lower, but no significant changes were found when controlling for gender and age (p > 0.05 in all analyses). However, a significant decrease was found in the Locomotor subscale in boys (p = 0.003). After dividing the participants into three age groups, the youngest also suffered a decrease in the Locomotor subscale (p < 0.001) and their Total MCA (p = 0.04). In addition, those participants who had a higher MC at baseline decreased their scores for the Locomotor (p < 0.001) and Manipulative (p < 0.001) subscales, and for the Total MCA (p < 0.001). In conclusion, the younger children and the more motor proficient did not fully recover from the negative effects of the pandemic lockdown after two years.

The Motor Competence Assessment (MCA) is a quantitative test battery that assesses motor competence across the whole lifespan. It is composed of three sub-scales: locomotor, stability, and manipulative, each of them assessed by two different objectively measured tests. The MCA construct validity for children and adolescents, having normative values from 3 to 23 years of age, and the configural invariance between age groups, were recently established. The aim of this study is to expand the MCA’s development and validation by defining the best and leanest method to score and classify MCA sub-scales and total score. One thousand participants from 3 to 22 years of age, randomly selected from the Portuguese database on MC, participated in the study. Three different procedures to calculate the sub-scales and total MCA values were tested according to alternative models. Results were compared to the reference method, and Intraclass Correlation Coefficient, Cronbach’s Alpha, and Bland–Altman statistics were used to describe agreement between the three methods. The analysis showed no substantial differences between the three methods. Reliability values were perfect (0.999 to 1.000) for all models, implying that all the methods were able to classify everyone in the same way. We recommend implementing the most economic and efficient algorithm, i.e., the configural model algorithm, averaging the percentile scores of the two tests to assess each MCA sub-scale and total scores.