Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search

  • Carlos Mena | cmena@utalca.cl Geomatics Centre, Faculty of Forestry Sciences, University of Talca, Chile.
  • Cesar Sepúlveda Thrombosis Research Center, Department of Clinical Biochemistry and Immunohematology, Faculty of Health Sciences, Interdisciplinary Excellence Research Program on Healthy Aging (PIEI-ES), University of Talca, Chile.
  • Eduardo Fuentes Thrombosis Research Center, Department of Clinical Biochemistry and Immunohematology, Faculty of Health Sciences, Interdisciplinary Excellence Research Program on Healthy Aging (PIEI-ES); Multidisciplinary Scientific Nucleus, University of Talca, Chile.
  • Yony Ormazábal Geomatics Centre, Faculty of Forestry Sciences, University of Talca, Chile.
  • Iván Palomo Thrombosis Research Center, Department of Clinical Biochemistry and Immunohematology, Faculty of Health Sciences, Interdisciplinary Excellence Research Program on Healthy Aging (PIEI-ES), University of Talca, Chile.

Abstract

Cardiovascular diseases (CVDs) are the primary cause of death and disability in de world, and the detection of populations at risk as well as localization of vulnerable areas is essential for adequate epidemiological management. Techniques developed for spatial analysis, among them geographical information systems and spatial statistics, such as cluster detection and spatial correlation, are useful for the study of the distribution of the CVDs. These techniques, enabling recognition of events at different geographical levels of study (e.g., rural, deprived neighbourhoods, etc.), make it possible to relate CVDs to factors present in the immediate environment. The systemic literature presented here shows that this group of diseases is clustered with regard to incidence, mortality and hospitalization as well as obesity, smoking, increased glycated haemoglobin levels, hypertension physical activity and age. In addition, acquired variables such as income, residency (rural or urban) and education, contribute to CVD clustering. Both local cluster detection and spatial regression techniques give statistical weight to the findings providing valuable information that can influence response mechanisms in the health services by indicating locations in need of intervention and assignment of available resources.

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Published
2018-05-07
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Issue
Section
Reviews
Keywords:
Spatial analysis, Cluster, Cardiovascular diseases.
Statistics
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How to Cite
Mena, C., Sepúlveda, C., Fuentes, E., Ormazábal, Y., & Palomo, I. (2018). Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search. Geospatial Health, 13(1). https://doi.org/10.4081/gh.2018.587

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