Physical activity (PA) and sedentary behaviour (SB) of pre-school aged children are associated with important health and developmental outcomes. Accurate measurement of these behaviours in young children is critical for research and practice in this area. The aim of this review was to examine the validity, reliability, and feasibility of measurement tools used to assess PA and SB of pre-school aged children.Searches of electronic databases, and manual searching, were conducted to identify articles that examined the measurement properties (validity, reliability or feasibility) of measurement tools used to examine PA and/or SB of pre-school aged children (3–7 years old). Following screening, data were extracted and risk of bias assessment completed on all included articles.A total of 69 articles, describing 75 individual studies were included. Studies assessed measurement tools for PA (n = 27), SB (n = 5), and both PA and SB (n = 43). Outcome measures of PA and SB differed between studies (e.g. moderate to vigorous activity, step count, posture allocation). Most studies examined the measurement properties of one measurement tool only (n = 65). Measurement tools examined included: calorimetry, direct observation, combined heart rate and accelerometry, heart rate monitors, accelerometers, pedometers, and proxy report (parent, carer or teacher reported) measures (questionnaires or diaries). Studies most frequently assessed the validity (criterion and convergent) (n = 65), face and content validity (n = 2), test-retest reliability (n = 10) and intra-instrument reliability (n = 1) of the measurement tools. Feasibility data was abstracted from 41 studies.Multiple measurement tools used to measure PA and SB in pre-school aged children showed some degree of validity, reliability and feasibility, but often for different purposes. Accelerometers, including the Actigraph (in particular GT3X versions), Actical, ActivPAL and Fitbit (Flex and Zip), and proxy reported measurement tools used in combination may be useful for a range of outcome measures, to measure intensity alongside contextual information.

Background The COVID-19 pandemic has asked unprecedented questions of governments around the world. Policy responses have disrupted usual patterns of movement in society, locally and globally, with resultant impacts on national economies and human well-being. These interventions have primarily centred on enforcing lockdowns and introducing social distancing recommendations, leading to questions of trust and competency around the role of institutions and the administrative apparatus of state. This study demonstrates the unequal societal impacts in population movement during a national ‘lockdown’. Methods We use nationwide mobile phone movement data to quantify the effect of an enforced lockdown on population mobility by neighbourhood deprivation using an ecological study design. We then derive a mobility index using anonymised aggregated population counts for each neighbourhood (2253 Census Statistical Areas; mean population n=2086) of national hourly mobile phone location data (7.45 million records, 1 March 2020–20 July 2020) for New Zealand (NZ). Results Curtailing movement has highlighted and exacerbated underlying social and spatial inequalities. Our analysis reveals the unequal movements during ‘lockdown’ by neighbourhood socioeconomic status in NZ. Conclusion In understanding inequalities in neighbourhood movements, we are contributing critical new evidence to the policy debate about the impact(s) and efficacy of national, regional or local lockdowns which have sparked such controversy.

Public health is increasingly engaging with multi-faceted obesity prevention efforts. Although parks represent key community assets for broader public health, they may not be distributed equitably and associations with obesity are equivocal. We investigated park access and quality relative to deprivation and obesity with individual-level data from the Yorkshire Health Study. Compared to the least deprived areas, the moderately and most deprived areas had a greater park access and park quality in terms of features and amenities. However, parks in the moderately and most deprived areas also had the most safety concerns and incivilities. Although deprivation was associated with obesity, contrary to current policy guidance, both park access and quality appear less important for understanding variations in obesity within this study. Although sub-group analyses by deprivation tertile revealed that low quality park amenities in highly and moderately deprived areas may be important for understanding obesity prevalence, all other associations were non-significant.

Background Children residing in neighbourhoods of high deprivation are more likely to have poorer health, including excess body size. While the availability of unhealthy food outlets are increasingly considered important for excess child body size, less is known about how neighbourhood deprivation, unhealthy food outlets and unhealthy dietary behaviours are interlinked. Methods This study involves children aged 8–13 years (n=1029) and resided in Auckland, New Zealand. Unhealthy dietary behaviours (frequency of consumption of unhealthy snacks and drinks) and food purchasing behaviour on the route to and from school were self-reported. Height and waist circumference were measured to calculate waist-to-height ratio (WtHR). Geographic Information Systems mapped neighbourhood deprivation and unhealthy food outlets within individual, child-specific neighbourhood buffer boundaries (800 m around the home and school). Associations between neighbourhood deprivation (calculated using the New Zealand Index of Deprivation 2013), unhealthy food outlets, unhealthy dietary behaviours and WtHR were investigated using structural equation modelling in Mplus V.8.0. Age, sex and ethnicity were included as covariates, and clustering was accounted for at the school level. Results Structural equation models showed that unhealthy food outlets were unrelated to unhealthy dietary behaviours (estimate 0.029, p=0.416) and excess body size (estimate −0.038, p=0.400). However, greater neighbourhood deprivation and poorer dietary behaviours (estimate −0.134, p=0.001) were associated with greater WtHR (estimate 0.169, p<0.001). Conclusion Excess child body size is associated with neighbourhood deprivation and unhealthy dietary behaviours but not unhealthy outlet density or location of these outlets near home and school.

Little research has investigated associations between a combined measure of the food and physical activity (PA) environment, BMI (body-mass-index) and obesity. Cross-sectional data (n=22,889, age 18-86years) from the Yorkshire Health Study were used [2010-2013]. BMI was calculated using self-reported height and weight; obesity=BMI≥30. Neighbourhood was defined as a 2km radial buffer. Food outlets and PA facilities were sourced from Ordnance Survey Points of Interest (PoI) and categorised into 'fast-food', 'large supermarkets', 'convenience and other food retail outlets' and 'physical activity facilities'. Parks were sourced from Open Street Map. Latent class analysis was conducted on these five environmental variables and availability was defined by quartiles of exposure. Linear and logistic regressions were then conducted for BMI and obesity respectively for different neighbourhood types. Models adjusted for age, gender, ethnicity, area-level deprivation, and rural/urban classification. A five-class solution demonstrated best fit and was interpretable. Neighbourhood typologies were defined as; 'low availability', 'moderate availability', 'moderate PA, limited food', 'saturated' and 'moderate PA, ample food'. Compared to low availability, one typology demonstrated lower BMI (saturated, b=-0.50, [95% CI=-0.76, -0.23]), while three showed higher BMI (moderate availability, b=0.49 [0.27, 0.72]; moderate PA, limited food, b=0.30 [0.01, 0.59]; moderate PA, ample food, b=0.32 [0.08, 0.57]). Furthermore, compared to the low availability, saturated neighbourhoods showed lower odds of obesity (OR=0.86 [0.75, 0.99]) while moderate availability showed greater odds of obesity (OR=1.18 [1.05, 1.32]). This study supports population-level approaches to tackling obesity however neighbourhoods contained features that were health-promoting and -constraining.