The Canadian Urban Environmental Health Research Consortium – a protocol for building a national environmental exposure data platform for integrated analyses of urban form and health

Abstract

BackgroundMultiple external environmental exposures related to residential location and urban form including, air pollutants, noise, greenness, and walkability have been linked to health impacts or benefits. The Canadian Urban Environmental Health Research Consortium (CANUE) was established to facilitate the linkage of extensive geospatial exposure data to existing Canadian cohorts and administrative health data holdings. We hypothesize that this linkage will enable investigators to test a variety of their own hypotheses related to the interdependent associations of built environment features with diverse health outcomes encompassed by the cohorts and administrative data.MethodsWe developed a protocol for compiling measures of built environment features that quantify exposure; vary spatially on the urban and suburban scale; and can be modified through changes in policy or individual behaviour to benefit health. These measures fall into six domains: air quality, noise, greenness, weather/climate, and transportation and neighbourhood factors; and will be indexed to six-digit postal codes to facilitate merging with health databases. Initial efforts focus on existing data and include estimates of air pollutants, greenness, temperature extremes, and neighbourhood walkability and socioeconomic characteristics. Key gaps will be addressed for noise exposure, with a new national model being developed, and for transportation-related exposures, with detailed estimates of truck volumes and diesel emissions now underway in selected cities. Improvements to existing exposure estimates are planned, primarily by increasing temporal and/or spatial resolution given new satellite-based sensors and more detailed national air quality modelling. Novel metrics are also planned for walkability and food environments, green space access and function and life-long climate-related exposures based on local climate zones. Critical challenges exist, for example, the quantity and quality of input data to many of the models and metrics has changed over time, making it difficult to develop and validate historical exposures.DiscussionCANUE represents a unique effort to coordinate and leverage substantial research investments and will enable a more focused effort on filling gaps in exposure information, improving the range of exposures quantified, their precision and mechanistic relevance to health. Epidemiological studies may be better able to explore the common theme of urban form and health in an integrated manner, ultimately contributing new knowledge informing policies that enhance healthy urban living.

Road proximity, air pollution, noise, green space and neurologic disease incidence: a population-based cohort study

“…Satellite-based PM 2.5 and NO 2 from a national land use regression model provided by the Canadian Urban Environmental Health Research Consortium (CANUE) were used in sensitivity analysis [59,60]. Ground-level PM 2.5 over North America was estimated by combining 0.01-degree × 0.01-degree resolution optimally estimated Aerosol Optical Depth (AOD) with simulated the aerosol vertical profile and scattering properties.…”

A User-Based Look at Visualization Tools for Environmental Data and Suggestions for Improvement—An Inventory among City Planners in Gothenburg

“…Notwithstanding, some authors have had a more systematic focus related to the creation of common databases or platforms. Within this group, Brook et al [22] developed a protocol for creating a national data platform for Canada related to environmental exposure, bringing together urban form analysis and health. Ibarra-Espinosa et al [23] developed an open-source Vehicular Emissions Inventory (VEIN) which is directed not only to sectoral studies on weather, climate and environmental health but is expected to be useful more generally for urban planning.…”

Characterizing community-wide housing attributes using georeferenced street-level photography

“…One strategy to enhance high-resolution data on the built environment is to use street-level imagery to assess certain neighborhood characteristics remotely, with greater ease and efficiency [23,24]. Especially with targeted data collection that goes beyond public databases or resources, a large amount of neighborhood-level information can be collected without surveys or other resident participation.…”