Hostname: page-component-8448b6f56d-wq2xx Total loading time: 0 Render date: 2024-04-19T20:20:04.296Z Has data issue: false hasContentIssue false

An exploratory spatial analysis of pneumonia and influenza hospitalizations in Ontario by age and gender

Published online by Cambridge University Press:  07 July 2006

E. J. CRIGHTON
Affiliation:
Department of Geography, Environmental Studies Program, University of Ottawa, Ottawa, ON, Canada
S. J. ELLIOTT
Affiliation:
School of Geography and Geology, McMaster University, Hamilton, ON, Canada
R. MOINEDDIN
Affiliation:
Department of Public Health Sciences, University of Toronto, Toronto, ON, Canada Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada
P. KANAROGLOU
Affiliation:
School of Geography and Geology, McMaster University, Hamilton, ON, Canada
R. E. G. UPSHUR
Affiliation:
School of Geography and Geology, McMaster University, Hamilton, ON, Canada Department of Public Health Sciences, University of Toronto, Toronto, ON, Canada Primary Care Research Unit, Sunnybrook and Women's College Health Sciences Centre, Toronto, ON, Canada
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Pneumonia and influenza represent a significant public health burden in Canada and abroad. Knowledge of how this burden varies geographically provides clues to understanding the determinants of these illnesses, and insight into the effective management of health-care resources. We conducted a retrospective, population-based, ecological-level study to assess age- and gender-specific spatial patterns of pneumonia and influenza hospitalizations in the province of Ontario, Canada from 1992 to 2001. Results revealed marked variability in hospitalization rates by age, as well as clear and statistically significant patterns of high rates in northern rural counties and low rates in southern urban counties. A moderate yet significant level of positive spatial autocorrelation (Moran's I=0·21, P<0·05) was found in the global data, with significant, age-specific clusters of high values or ‘hot spots’ identified in several northern counties. Findings illustrate the need for geographically focused prevention strategies, and resource and service allocation policies informed by regional and population-specific demands.

Type
Research Article
Copyright
2006 Cambridge University Press