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Article Abstract

The motor-vehicle is accountable for emitting a substantial concoction of air quality objective pollutants and carcinogenic hydrocarbons within close proximity to urbanised residential districts. The spatial extent of health impacts associated with road-transport pollutants have traditionally been explored through the examination of artificially created buffers, defined by subjective distances from specified major road links. Within this paper an alternative approach is presented using boundary statistics, which describe naturally occurring shifts of magnitude in socio-environmental and health outcomes across the wider urban area. In contrast, previous distance-threshold investigations have used arbitrarily sized buffers placed upon predetermined locations in response to environmental attributes, without considering the combined influence of additional social burdens. The demographically diverse City of Leicester, situated within the heart of the United Kingdom's major road-transport network, was selected to showcase such methods. Descriptive multilevel modelling strategies accommodating for generalised spatial structures across Leicester, globally associated issues of deprivation, road-transport emissions and ethnic minorities with increased respiratory risks. Getis-Ord Gi* spatial pattern recognition statistics identified the existence of localised variations, with inner city neighbourhoods tending to house children of ethnic minority groups whom experience disproportionately large environmental and respiratory health burdens. Crisp polygon wombling boundary detection across Leicester appeared to broadly complement the Gi* statistics, identifying naturally occurring boundaries in road-transport emissions to result in elevated children's respiratory admissions within a distance of 283 m (P < 0.05). The designated threshold was identified to reduce in relation to certain ethnic groups, thus suggesting environmental injustices likely prevail within the model British multicultural City of Leicester. The study's findings have applications within healthcare management and urban planning for locating vulnerable populaces and for minimising health risks in future road network designs.

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http://dx.doi.org/10.1016/j.socscimed.2013.01.030DOI Listing

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