Summary Background Measures during the COVID‐19 pandemic, including the closure of schools and sports facilities, may have lasting impact on the physical activity (PA) of children that persists for a long time. Objective To investigate the effect of COVID‐19 measures on screen time and PA in Dutch children pre‐, during‐ and post‐school closures. Methods In cohort A (n = 102, 10.5 ± 3.6 years, 42.4% boys), data on PA and screen time during the lockdown were collected using a questionnaire. In cohort B (n = 131, 10.2 ± 0.9 years, 43.5% boys), data on PA and screen time were collected using a questionnaire and accelerometry 1 year before and after school closure. Results In cohort A, 62% reported less total PA. Self‐reported screen time on week days increased 34 ± 105 min/d during the lockdown. In cohort B, sedentary time as measured by accelerometry, increased by 45 ± 67 min/d and only 20% reached PA levels of 60 min/d compared to 64% in May 2019. Self‐reported screen time increased by 59 ± 112 min/d and 62 ± 130 min/d during week and weekend days, respectively. Conclusions Children were less physically active, and screen time was higher during and after the school closures due to the COVID‐19 lockdown. This is alarming as an active lifestyle in children is crucial in preventing chronic diseases such as obesity.

There is not a 'one-size-fits-all' treatment approach, and matched care to personal needs is preferable. The integration of a chronic care approach is critical for the successful adaption of sustainable health behaviours.

In this work, we propose to use pattern recognition methods to determine submaximal heart rate (HR) during specific contexts, such as walking at a certain speed, using wearable sensors in free living, and using context-specific HR to estimate cardiorespiratory fitness (CRF). CRF of 51 participants was assessed by a maximal exertion test (V̇o2 max). Participants wore a combined accelerometer and HR monitor during a laboratory-based simulation of activities of daily living and for 2 wk in free living. Anthropometrics, HR while lying down, and walking at predefined speeds in laboratory settings were used to estimate CRF. Explained variance (R(2)) was 0.64 for anthropometrics, and increased up to 0.74 for context-specific HR (0.73-0.78 when including fat-free mass). Next, we developed activity recognition and walking speed estimation algorithms to determine the same contexts (i.e., lying down and walking) in free living. Context-specific HR in free living was highly correlated with laboratory measurements (Pearson's r = 0.71-0.75). R(2) for CRF estimation was 0.65 when anthropometrics were used as predictors, and increased up to 0.77 when including free-living context-specific HR (i.e., HR while walking at 5.5 km/h). R(2) varied between 0.73 and 0.80 when including fat-free mass among the predictors. Root mean-square error was reduced from 354.7 to 281.0 ml/min by the inclusion of context-specific HR parameters (21% error reduction). We conclude that pattern recognition techniques can be used to contextualize HR in free living and estimated CRF with accuracy comparable to what can be obtained with laboratory measurements of HR response to walking.

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Introduction Physical activity (PA) plays an important role in the prevention of cardiovascular diseases, especially in children. Previous studies which investigated the role of PA and sedentary time (ST) in cardiovascular disease used different measurements and found inconsistent results. The current study used recommended standardized measures and provides an overview of PA and ST among Dutch primary school children and their associations with cardiovascular risk factors. Methods 503 children (55% girls, mean age (± SD) 10 ± 1y) were included. PA (total PA, lightPA and moderate to vigorous PA (MVPA)) and ST were measured with the Actigraph GT3X accelerometer. PA in different domains was measured with the BAECKE questionnaire. Cardiovascular risk factors included BMI z-score, waist circumference, blood pressure (z-score) and estimated cardiorespiratory fitness (CRF) as measured with the 20 meter shuttle run test. Results Children spent 57 ± 20 min/day (8%) on MVPA and 42% of the children reached the MVPA guideline of 60 min/day. Total PA and MVPA (h/day) were negatively associated with BMI z-score (B = -0.452, p = 0.011) and waist circumference (B = -3.553, p = 0.011) and positively associated with CRF (B = 2.527, p = <0.001). ST was positively associated with BMI z-score (B = 0.108, p = 0.048) and waist circumference (B = 0.920, p = 0.033). No significant associations were found between total PA or PA intensities and blood pressure. Conclusion This study used standardized measures of PA and therefore created an accurate overview of PA, ST and their associations with cardiovascular risk factors. PA and ST were associated with BMI z-score, waist circumference and CRF. The findings emphasize the importance of promoting MVPA in children, but also highlight the potential benefits of reducing ST to improve cardiovascular risk factors. Trial registration ClinicalTrials.gov NCT03440580.