International comparison of observation-specific spatial buffers: maximizing the ability to estimate physical activity.

BACKGROUND: Advancements in geographic information systems over the past two decades have increased the specificity by which an individual's neighborhood environment may be spatially defined for physical activity and health research. This study investigated how different types of street network buffering methods compared in measuring a set of commonly used built environment measures (BEMs) and tested their performance on associations with physical activity outcomes. METHODS: An internationally-developed set of objective BEMs using three different spatial buffering techniques were used to evaluate the relative differences in resulting explanatory power on self-reported physical activity outcomes. BEMs were developed in five countries using 'sausage,' 'detailed-trimmed,' and 'detailed,' network buffers at a distance of 1 km around participant household addresses (n = 5883). RESULTS: BEM values were significantly different (p < 0.05) for 96% of sausage versus detailed-trimmed buffer comparisons and 89% of sausage versus detailed network buffer comparisons. Results showed that BEM coefficients in physical activity models did not differ significantly across buffering methods, and in most cases BEM associations with physical activity outcomes had the same level of statistical significance across buffer types. However, BEM coefficients differed in significance for 9% of the sausage versus detailed models, which may warrant further investigation. CONCLUSIONS: Results of this study inform the selection of spatial buffering methods to estimate physical activity outcomes using an internationally consistent set of BEMs. Using three different network-based buffering methods, the findings indicate significant variation among BEM values, however associations with physical activity outcomes were similar across each buffering technique. The study advances knowledge by presenting consistently assessed relationships between three different network buffer types and utilitarian travel, sedentary behavior, and leisure-oriented physical activity outcomes.

Multiple health benefits of urban tree canopy: The mounting evidence for a green prescription.

The purpose of this study was to enhance the understanding of the health-promoting potential of trees in an urbanized region of the United States. This was done using high-resolution LiDAR and imagery data to quantify tree cover within 250m of the residence of 7910 adult participants in the California Health Interview Survey, then testing for main and mediating associations between tree cover and multiple health measures. The results indicated that more neighborhood tree cover, independent from green space access, was related to better overall health, primarily mediated by lower overweight/obesity and better social cohesion, and to a lesser extent by less type 2 diabetes, high blood pressure, and asthma. These findings suggest an important role for trees and nature in improving holistic population health in urban areas.

Application of an evidence-based tool to evaluate health impacts of changes to the built environment.

OBJECTIVES: To create and apply an empirically based health and greenhouse gas (GHG) impact assessment tool linking detailed measures of walkability and regional accessibility with travel, physical activity, health indicators and GHG emissions. METHODS: Parcel land use and transportation system characteristics were calculated within a kilometre network buffer around each Toronto postal code. Built environment measures were linked with health and demographic characteristics from the Canadian Community Health Survey and travel behaviour from the Transportation Tomorrow Survey. Results were incorporated into an existing software tool and used to predict health-related indicators and GHG emissions for the Toronto West Don Lands Redevelopment. RESULTS: Walkability, regional accessibility, sidewalks, bike facilities and recreation facility access were positively associated with physical activity and negatively related to body weight, high blood pressure and transportation impacts. When applied to the West Don Lands, the software tool predicted a substantial shift from automobile use to walking, biking and transit. Walking and biking trips more than doubled, and transit trips increased by one third. Per capita automobile trips decreased by half, and vehicle kilometres travelled and GHG emissions decreased by 15% and 29%, respectively. CONCLUSION: The results presented are novel and among the first to link health outcomes with detailed built environment features in Canada. The resulting tool is the first of its kind in Canada. This tool can help policy-makers, land use and transportation planners, and health practitioners to evaluate built environment influences on health-related indicators and GHG emissions resulting from contrasting land use and transportation policies and actions.