Objective measures of the built environment and physical activity in children: from walkability to moveability.

Features of the built environment that may influence physical activity (PA) levels are commonly captured using a so-called walkability index. Since such indices typically describe opportunities for walking in everyday life of adults, they might not be applicable to assess urban opportunities for PA in children. Particularly, the spatial availability of recreational facilities may have an impact on PA in children and should be additionally considered. We linked individual data of 400 2- to 9-year-old children recruited in the European IDEFICS study to geographic data of one German study region, based on individual network-dependent neighborhoods. Environmental features of the walkability concept and the availability of recreational facilities, i.e. playgrounds, green spaces, and parks, were measured. Relevant features were combined to a moveability index that should capture urban opportunities for PA in children. A gamma log-regression model was used to model linear and non-linear effects of individual variables on accelerometer-based moderate-to-vigorous physical activity (MVPA) stratified by pre-school children (<6 years) and school children (≥6 years). Single environmental features and the resulting indices were separately included into the model to investigate the effect of each variable on MVPA. In school children, commonly used features such as residential density [Formula: see text], intersection density [Formula: see text], and public transit density [Formula: see text] showed a positive effect on MVPA, while land use mix revealed a negative effect on MVPA [Formula: see text]. In particular, playground density [Formula: see text] and density of public open spaces, i.e., playgrounds and parks combined [Formula: see text], showed positive effects on MVPA. However, availability of green spaces showed no effect on MVPA. Different moveability indices were constructed based on the walkability index accounting for the negative impact of land use mix. Moveability indices showed also strong effects on MVPA in school children for both components, expanded by playground density [Formula: see text] or by public open space density [Formula: see text], but no effects of urban measures and moveability indices were found in pre-school children. The final moveability indices capture relevant opportunities for PA in school children. Particularly, availability of public open spaces seems to be a strong predictor of MVPA. Future studies involving children should consider quantitative assessment of public recreational facilities in larger cities or urban sprawls in order to investigate the influence of the moveability on childhood PA in a broader sample.

Assessing opportunities for physical activity in the built environment of children: interrelation between kernel density and neighborhood scale.

BACKGROUND: Built environment studies provide broad evidence that urban characteristics influence physical activity (PA). However, findings are still difficult to compare, due to inconsistent measures assessing urban point characteristics and varying definitions of spatial scale. Both were found to influence the strength of the association between the built environment and PA. METHODS: We simultaneously evaluated the effect of kernel approaches and network-distances to investigate the association between urban characteristics and physical activity depending on spatial scale and intensity measure. We assessed urban measures of point characteristics such as intersections, public transit stations, and public open spaces in ego-centered network-dependent neighborhoods based on geographical data of one German study region of the IDEFICS study. We calculated point intensities using the simple intensity and kernel approaches based on fixed bandwidths, cross-validated bandwidths including isotropic and anisotropic kernel functions and considering adaptive bandwidths that adjust for residential density. We distinguished six network-distances from 500 m up to 2 km to calculate each intensity measure. A log-gamma regression model was used to investigate the effect of each urban measure on moderate-to-vigorous physical activity (MVPA) of 400 2- to 9.9-year old children who participated in the IDEFICS study. Models were stratified by sex and age groups, i.e. pre-school children (2 to <6 years) and school children (6-9.9 years), and were adjusted for age, body mass index (BMI), education and safety concerns of parents, season and valid weartime of accelerometers. RESULTS: Association between intensity measures and MVPA strongly differed by network-distance, with stronger effects found for larger network-distances. Simple intensity revealed smaller effect estimates and smaller goodness-of-fit compared to kernel approaches. Smallest variation in effect estimates over network-distances was found for kernel intensity measures based on isotropic and anisotropic cross-validated bandwidth selection. CONCLUSION: We found a strong variation in the association between the built environment and PA of children based on the choice of intensity measure and network-distance. Kernel intensity measures provided stable results over various scales and improved the assessment compared to the simple intensity measure. Considering different spatial scales and kernel intensity methods might reduce methodological limitations in assessing opportunities for PA in the built environment.