Built Environment Exposures Research Articles

Associations between BMI and home, school and route environmental exposures estimated using GPS and GIS: do we see evidence of selective daily mobility bias in children?

BackgroundThis study examined whether objective measures of food, physical activity and built environment exposures, in home and non-home settings, contribute to children’s body weight. Further, comparing GPS and GIS measures of environmental exposures along routes to and from school, we tested for evidence of selective daily mobility bias when using GPS data.MethodsThis study is a cross-sectional analysis, using objective assessments of body weight in relation to multiple environmental exposures. Data presented are from a sample of 94 school-aged children, aged 5–11 years. Children’s heights and weights were measured by trained researchers, and used to calculate BMI z-scores. Participants wore a GPS device for one full week. Environmental exposures were estimated within home and school neighbourhoods, and along GIS (modelled) and GPS (actual) routes from home to school. We directly compared associations between BMI and GIS-modelled versus GPS-derived environmental exposures. The study was conducted in Mebane and Mount Airy, North Carolina, USA, in 2011.ResultsIn adjusted regression models, greater school walkability was associated with significantly lower mean BMI. Greater home walkability was associated with increased BMI, as was greater school access to green space. Adjusted associations between BMI and route exposure characteristics were null. The use of GPS-actual route exposures did not appear to confound associations between environmental exposures and BMI in this sample.ConclusionsThis study found few associations between environmental exposures in home, school and commuting domains and body weight in children. However, walkability of the school neighbourhood may be important. Of the other significant associations observed, some were in unexpected directions. Importantly, we found no evidence of selective daily mobility bias in this sample, although our study design is in need of replication in a free-living adult sample.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-072X-14-8) contains supplementary material, which is available to authorized users.

Adolescent self-defined neighborhoods and activity spaces: Spatial overlap and relations to physical activity and obesity

Defining the proper geographic scale for built environment exposures continues to present challenges. In this study, size attributes and exposure calculations from two commonly used neighborhood boundaries were compared to those from neighborhoods that were self-defined by a sample of 145 urban minority adolescents living in subsidized housing estates. Associations between five built environment exposures and physical activity, overweight and obesity were also examined across the three neighborhood definitions. Limited spatial overlap was observed across the various neighborhood definitions. Further, many places where adolescents were active were not within the participants׳ neighborhoods. No statistically significant associations were found between counts of facilities and the outcomes based on exposure calculations using the self-defined boundaries; however, a few associations were evident for exposures using the 0.75mile network buffer and census tract boundaries. Future investigation of the relationship between the built environment, physical activity and obesity will require practical and theoretically-based methods for capturing salient environmental exposures.

Comparative analyses of built environment exposures relevant to health of greenhouse gas emissions reduction strategies in Serbia

Paper presents comparative analysis of residential indoor air pollutant concentration change over future specified time horizon, implementing building physical and thermal retrofit measures, thus creating pollution mitigation scenarios for existing Belgrade and Nis housing stock followed by greenhouse gas emission reduction scenarios up to 2050. Regarding specified mitigation scenarios, the set of typical housing unit models has been generated which define existing housing stock of Belgrade and Nis. Extensive monitoring of physical and thermal parameters as well as detailed socio-technical survey of selected households was performed and used as an initial modeling input. Relationship between environment pollution and building performances was investigated, with respect to indooroutdoor sources of pollution, thermal and physical properties of the stock samples and occupant?s behavior. As a final output, indoor pollutant concentrations for each of the modelled cases was obtained and validated against the available data. This housing modelling framework has been created in order to develop an assessment of present and future exposure and health impact quantity regarding single/multiple scenario interventions introduced to the housing stock. This paper provides each strategy guidelines for taking measures towards achieving the healthier indoor environments.

Home Versus Nonhome Neighborhood: Quantifying Differences in Exposure to the Built Environment

Built environment and health research have focused on characteristics of home neighborhoods, whereas overall environmental exposures occur over larger spatial ranges. Differences in built environment characteristics were analyzed for home and nonhome locations using GPS data. GPS data collected in 2007-2008 were analyzed for 41 subjects in the Seattle area in 2010. Environmental characteristics for 3.8 million locations were measured using novel GIS data sets called SmartMaps, representing spatially continuous values of local built environment variables in the domains of neighborhood composition, utilitarian destinations, transportation infrastructure, and traffic conditions. Using bootstrap sampling, CIs were estimated for differences in built environment values for home (<833 m of home address) and nonhome (>1666 m) GPS locations. Home and nonhome built environment values were significantly different for more than 90% of variables across subjects (p<0.001). Only 51% of subjects had higher counts of supermarkets near than away from home. Different measures of neighborhood parks yielded varying results. SmartMaps helped measure local built environment characteristics for a large set of GPS locations. Most subjects had significantly different home and nonhome built environment exposures. Considering the full range of individuals' environmental exposures may improve understanding of effects of the built environment on behavior and health outcomes.

The Built Environment and Location-Based Physical Activity

Studies of the built environment and physical activity have implicitly assumed that a substantial amount of activity occurs near home, but in fact the location is unknown. This study aims to examine associations between built environment variables within home and work buffers and moderate-to-vigorous physical activity (MVPA) occurring within these locations. Adults (n=148) from Massachusetts wore an accelerometer and GPS unit for up to 4 days. Levels of MVPA were quantified within 50-m and 1-km home and work buffers. Multiple regression models were used to examine associations between five objective built environment variables within 1-km home and work buffers (intersection density, land use mix, population and housing unit density, vegetation index) and MVPA within those areas. The mean daily minutes of MVPA accumulated in all locations=61.1+/-32.8, whereas duration within the 1-km home buffers=14.0+/-16.4 minutes. Intersection density, land use mix, and population and housing unit density within 1-km home buffers were positively associated with MVPA in the buffer, whereas a vegetation index showed an inverse relationship (all p<0.05). None of these variables showed associations with total MVPA. Within 1 km of work, only population and housing unit density were significantly associated with MVPA within the buffer. Findings are consistent with studies showing that certain attributes of the built environment around homes are positively related to physical activity, but in this case only when the outcome was location-based. Simultaneous accelerometer-GPS monitoring shows promise as a method to improve understanding of how the built environment influences physical activity behaviors by allowing activity to be quantified in a range of physical contexts and thereby provide a more explicit link between physical activity outcomes and built environment exposures.