Spatial analysis of designated outdoor smoking areas: accessibility and land use

Abstract

Smoking is the leading cause of premature death in Canada. Smoking also pollutes air and generates litter such as cigarette butts. The use of designated smoking areas (DSAs) is increasingly popular on university campuses and has the potential to influence smoking prevalence. It is however found that the related regulations and policies are largely unknown. This study systematically examines the spatial distribution of DSAs at 12 Canadian campuses using ArcGIS Pro, and predicts the required number of DSAs using regression analysis based on a number of climatic, and socio-economic factors identified by cluster analysis. The density of DSAs ranged from 0.119 to 0.739 DSA/10⁴ m², with an average of 0.354 DSA/10⁴ m². Results from the regression models suggested that climatic factors are important to the number of DSAs. The proposed spatial analytical approach is also applicable to the design and planning of other major health institutions or residential complexes.

Keywords:

• Designated smoking areas
• ArcGIS
• spatial analysis
• regression models
• cluster analysis

Acknowledgements

The research reported in this paper was supported by a grant from the Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-06154) to the corresponding author (K. T. W. Ng), using computing equipment funded by FEROF at the University of Regina. The lead author (Y. Chen) was also supported by a Mitacs Globalink research award. The authors are grateful for their support. The views expressed herein are those of the writers and not necessarily those of our research and funding partners.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The research reported in this paper was supported by a grant from the Natural Sciences and Engineering Research Council of Canada [RGPIN-2019-06154] to the corresponding author (K. T. W. Ng), using computing equipment funded by FEROF at the University of Regina. The lead author (Y. Chen) was also supported by a Mitacs Globalink research award.