Geographic Variation in Cardiovascular Disease Mortality: A Study of Linking Risk Factors and Built Environment at a Local Health Unit in Canada

  • Lei Wang
  • Chris I. Ardern
  • Dongmei ChenEmail author
Part of the Global Perspectives on Health Geography book series (GPHG)


Cardiovascular disease (CVD) is one of the leading causes of death in Canada. CVD risk factors and outcome data are used to determine trends of disease risk to inform public health program planning for prevention and control of disease and risk reduction or elimination. Recent efforts to map CVD and its associated risk factors at the health region level have provided further insights into variation in determinants across populations. In this chapter, geographic information system (GIS) and spatial analysis were utilized to enhance CVD surveillance to identify the patterns and relationships between CVD mortality and its potential risk factors. Ordinary Least Squares (OLS) regression and Geographically Weighted Regression (GWR) approaches were used to explore geographical variation in the rate of CVD mortality. After consideration of potential environmental, epidemiological, demographic, and socioeconomic factors, spatial statistics analysis revealed geospatial clustering for CVD mortality and the “hot spots” or “cold spots.” Within a mixed rural-suburban setting in Ontario, Canada, there was an evidence of significant built environmental factors and immigrant time associated with the rate of CVD mortality. Moreover, this pilot work suggests that the integration of geospatial information with routinely collected surveillance data appears feasible within the structure and resources of local public health units as a means to assist in the identification of regional variation in the burden of CVD.


Cardiovascular disease (CVD) Geographic difference Built environment Spatial analysis GIS Canadian Community Health Survey (CCHS) 



This study was funded by the Public Health Agency of Canada and involved the collaboration of partners from the Regional Municipality of York (Public Health and Geomatics Branches), Queen’s University (Department of Geography), and York University (School of Kinesiology and Health Science) in the development of the current framework and conducting of the statistical and geospatial analysis. The authors would like to thank Dr. Eric Weir, Shelley Stalker, Bill Kou, and Shanna Hoetmer at York Region Public Health for their help on this research. Three anonymous reviewers and the book editors have provided constructive suggestions for improving the quality of this chapter.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Remote Sensing and Digital Earth, Chinese Academy of SciencesBeijingChina
  2. 2.Department of Geography and Planning, Queen’s UniversityKingstonCanada
  3. 3.School of Kinesiology and Health Science, York UniversityTorontoCanada

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