Investigating young children's physical activity through time and place.

BACKGROUND: Previous research indicates the start of primary school (4-5-year-old) as an essential period for the development of children's physical activity (PA) patterns, as from this point, the age-related decline of PA is most often observed. During this period, young children are exposed to a wider variety of environmental- and social contexts and therefore their PA is influenced by more diverse factors. However, in order to understand children's daily PA patterns and identify relevant opportunities for PA promotion, it is important to further unravel in which (social) contexts throughout the day, PA of young children takes place. METHODS: We included a cross-national sample of 21 primary schools from the Startvaardig study. In total, 248 children provided valid accelerometer and global positioning (GPS) data. Geospatial analyses were conducted to quantify PA in (social) environments based on their school and home. Transport-related PA was evaluated using GPS speed-algorithms. PA was analysed at different environments, time-periods and for week- and weekend days separately. RESULTS: Children accumulated an average of 60 min of moderate-to-vigorous PA (MVPA), both during week- and weekend days. Schools contributed to approximately half of daily MVPA during weekdays. During weekends, environments within 100 m from home were important, as well as locations outside the home-school neighbourhood. Pedestrian trips contributed to almost half of the daily MVPA. CONCLUSIONS: We identified several social contexts relevant for children's daily MVPA. Schools have the potential to significantly contribute to young children's PA patterns and are therefore encouraged to systematically evaluate and implement parts of the school-system that stimulate PA and potentially also learning processes. Pedestrian trips also have substantial contribution to daily MVPA of young children, which highlights the importance of daily active transport in school- and parental routines.

Applying an ecosystem approach to explore modifiable factors related to the risk for low motor competence in young children.

OBJECTIVES: Early childhood is a crucial phase for motor development in which differences between children can manifest. These differences might be related to factors in ecosystems in which children are raised, of which little is currently known. The current study's purpose was to explore which modifiable factors in children's ecosystems are associated with the odds for low versus higher motor competence (MC) in 4- to 6-year-old children. DESIGN: A cross-sectional study design was conducted to investigate which modifiable social and physical factors in the home environment and direct living environment were associated with differences in MC. METHODS: Children's MC was measured through the Athletic Skills Track in 612 4- to 6-year-olds, from 10 primary schools in Eindhoven, the Netherlands. Parenting practices, characteristics of the home environment, and perceptions of the direct living environment were assessed through parental questionnaires. Hierarchical logistic regression analyses were conducted to evaluate factors associated with low MC in children. RESULTS: The presence of a garden at home and higher perceived sports facilities in the direct living environment decreased the likelihood of children being classified as low MC. Moreover, stronger parental active transportation routines and more discouraging physical activity parenting practices resulted in lower odds of low MC. In addition, girls were more at risk for low MC. CONCLUSIONS: Characteristics of the social and physical home environment and direct living environment were associated with MC disparities during early childhood. Both parenting practices and parental physical activity-involved behaviours are relevant modifiable factors related to differences in children's MC.

Ventilation and air cleaning to limit aerosol particle concentrations in a gym during the COVID-19 pandemic.

SARS-CoV-2 can spread by close contact through large droplet spray and indirect contact via contaminated objects. There is mounting evidence that it can also be transmitted by inhalation of infected saliva aerosol particles. These particles are generated when breathing, talking, laughing, coughing or sneezing. It can be assumed that aerosol particle concentrations should be kept low in order to minimize the potential risk of airborne virus transmission. This paper presents measurements of aerosol particle concentrations in a gym, where saliva aerosol production is pronounced. 35 test persons performed physical exercise and aerosol particle concentrations, CO2 concentrations, air temperature and relative humidity were obtained in the room of 886 m³. A separate test was used to discriminate between human endogenous and exogenous aerosol particles. Aerosol particle removal by mechanical ventilation and mobile air cleaning units was measured. The gym test showed that ventilation with air-change rate ACH = 2.2 h-1, i.e. 4.5 times the minimum of the Dutch Building Code, was insufficient to stop the significant aerosol concentration rise over 30 min. Air cleaning alone with ACH = 1.39 h-1 had a similar effect as ventilation alone. Simplified mathematical models were engaged to provide further insight into ventilation, air cleaning and deposition. It was shown that combining the above-mentioned ventilation and air cleaning can reduce aerosol particle concentrations with 80 to 90% , depending on aerosol size. This combination of existing ventilation supplemented with air cleaning is energy efficient and can also be applied for other indoor environments.

FLAIR-only joint volumetric analysis of brain lesions and atrophy in clinically isolated syndrome (CIS) suggestive of multiple sclerosis.

BACKGROUND: MRI assessment in multiple sclerosis (MS) focuses on the presence of typical white matter (WM) lesions. Neurodegeneration characterised by brain atrophy is recognised in the research field as an important prognostic factor. It is not routinely reported clinically, in part due to difficulty in achieving reproducible measurements. Automated MRI quantification of WM lesions and brain volume could provide important clinical monitoring data. In general, lesion quantification relies on both T1 and FLAIR input images, while tissue volumetry relies on T1. However, T1-weighted scans are not routinely included in the clinical MS protocol, limiting the utility of automated quantification. OBJECTIVES: We address an aspect of this important translational challenge by assessing the performance of FLAIR-only lesion and brain segmentation, against a conventional approach requiring multi-contrast acquisition. We explore whether FLAIR-only grey matter (GM) segmentation yields more variability in performance compared with two-channel segmentation; whether this is related to field strength; and whether the results meet a level of clinical acceptability demonstrated by the ability to reproduce established biological associations. METHODS: We used a multicentre dataset of subjects with a CIS suggestive of MS scanned at 1.5T and 3T in the same week. WM lesions were manually segmented by two raters, 'manual 1' guided by consensus reading of CIS-specific lesions and 'manual 2' by any WM hyperintensity. An existing brain segmentation method was adapted for FLAIR-only input. Automated segmentation of WM hyperintensity and brain volumes were performed with conventional (T1/T1 + FLAIR) and FLAIR-only methods. RESULTS: WM lesion volumes were comparable at 1.5T between 'manual 2' and FLAIR-only methods and at 3T between 'manual 2', T1 + FLAIR and FLAIR-only methods. For cortical GM volume, linear regression measures between conventional and FLAIR-only segmentation were high (1.5T: α = 1.029, R2 = 0.997, standard error (SE) = 0.007; 3T: α = 1.019, R2 = 0.998, SE = 0.006). Age-associated change in cortical GM volume was a significant covariate in both T1 (p = 0.001) and FLAIR-only (p = 0.005) methods, confirming the expected relationship between age and GM volume for FLAIR-only segmentations. CONCLUSIONS: FLAIR-only automated segmentation of WM lesions and brain volumes were consistent with results obtained through conventional methods and had the ability to demonstrate biological effects in our study population. Imaging protocol harmonisation and validation with other MS phenotypes could facilitate the integration of automated WM lesion volume and brain atrophy analysis as clinical tools in radiological MS reporting.

T2 mapping outperforms normalised FLAIR in identifying hippocampal sclerosis.

RATIONALE: Qualitatively, FLAIR MR imaging is sensitive to the detection of hippocampal sclerosis (HS). Quantitative analysis of T2 maps provides a useful objective measure and increased sensitivity over visual inspection of T2-weighted scans. We aimed to determine whether quantification of normalised FLAIR is as sensitive as T2 mapping in detection of HS. METHOD: Dual echo T2 and FLAIR MR images were retrospectively analysed in 27 patients with histologically confirmed HS and increased T2 signal in ipsilateral hippocampus and 14 healthy controls. Regions of interest were manually segmented in all hippocampi aiming to avoid inclusion of CSF. Hippocampal T2 values and measures of normalised FLAIR Signal Intensity (nFSI) were compared in healthy and sclerotic hippocampi. RESULTS: HS was identified on T2 values with 100% sensitivity and 100% specificity. HS was identified on nFSI measures with 60% sensitivity and 93% specificity. CONCLUSION: T2 mapping is superior to nFSI for identification of HS.