A spatial analysis of the determinants of pneumonia and influenza hospitalizations in Ontario (1992-2001).

Department of Geography, University of Ottawa, 60 University Avenue, Simard Hall Room 06, Ottawa, Ont., Canada K1N 6N5.
Social Science [?] Medicine (Impact Factor: 2.73). 05/2007; 64(8):1636-50. DOI: 10.1016/j.socscimed.2006.12.001
Source: PubMed

ABSTRACT Previous research on the determinants of pneumonia and influenza has focused primarily on the role of individual level biological and behavioural risk factors resulting in partial explanations and largely curative approaches to reducing the disease burden. This study examines the geographic patterns of pneumonia and influenza hospitalizations and the role that broad ecologic-level factors may have in determining them. We conducted a county level, retrospective, ecologic study of pneumonia and influenza hospitalizations in the province of Ontario, Canada, between 1992 and 2001 (N=241,803), controlling for spatial dependence in the data. Non-spatial and spatial regression models were estimated using a range of environmental, social, economic, behavioural, and health care predictors. Results revealed low education to be positively associated with hospitalization rates over all age groups and both genders. The Aboriginal population variable was also positively associated in most models except for the 65+-year age group. Behavioural factors (daily smoking and heavy drinking), environmental factors (passive smoking, poor housing, temperature), and health care factors (influenza vaccination) were all significantly associated in different age and gender-specific models. The use of spatial error regression models allowed for unbiased estimation of regression parameters and their significance levels. These findings demonstrate the importance of broad age and gender-specific population-level factors in determining pneumonia and influenza hospitalizations, and illustrate the need for place and population-specific policies that take these factors into consideration.

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    ABSTRACT: Background: The Arctic and subarctic area are likely to be highly affected by climate change, with possible impacts on human health due to effects on food security and infectious diseases. Objectives: To investigate the evidence for an association between climatic factors and infectious diseases, and to identify the most climate-sensitive diseases and vulnerable populations in the Arctic and subarctic region. Methods: A systematic review was conducted. A search was made in PubMed, with the last update in May 2013. Inclusion criteria included human cases of infectious disease as outcome, climate or weather factor as exposure, and Arctic or subarctic areas as study origin. Narrative reviews, case reports, and projection studies were excluded. Abstracts and selected full texts were read and evaluated by two independent readers. A data collection sheet and an adjusted version of the SIGN methodology checklist were used to assess the quality grade of each article. Results: In total, 1953 abstracts were initially found, of which finally 29 articles were included. Almost half of the studies were carried out in Canada (n=14), the rest from Sweden (n=6), Finland (n=4), Norway (n=2), Russia (n=2), and Alaska, US (n=1). Articles were analyzed by disease group: food- and waterborne diseases, vector-borne diseases, airborne viral- and airborne bacterial diseases. Strong evidence was found in our review for an association between climatic factors and food- and waterborne diseases. The scientific evidence for a link between climate and specific vector- and rodent-borne diseases was weak due to that only a few diseases being addressed in more than one publication, although several articles were of very high quality. Air temperature and humidity seem to be important climatic factors to investigate further for viral- and bacterial airborne diseases, but from our results no conclusion about a causal relationship could be drawn. Conclusions: More studies of high quality are needed to investigate the adverse health impacts of weather and climatic factors in the Arctic and subarctic region. No studies from Greenland or Iceland were found, and only a few from Siberia and Alaska. Disease and syndromic surveillance should be part of climate change adaptation measures in the Arctic and subarctic regions, with monitoring of extreme weather events known to pose a risk for certain infectious diseases implemented at the community level.
    Global Health Action 01/2014; 7:24161. · 2.06 Impact Factor
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    ABSTRACT: Pneumonia and influenza represent a significant public health and health care system burden that is expected to increase with the aging of developed nations' populations. The burden of these illnesses is far from uniform however, with recent studies showing that they are both highly spatially and temporally variable. We have combined spatial and time-series analysis techniques to examine pneumonia and influenza hospitalizations in the province of Ontario, Canada, to determine how temporal patterns vary over space, and how spatial patterns of hospitalizations vary over time. Knowledge of these patterns can provide clues to disease aetiology and inform the effective management of health care system resources. Spatial analysis revealed significant clusters of high hospitalization rates in northern and rural counties (Moran's I = 0.186; P <0.05), while county level time series analysis demonstrated significant upward trends in rates in almost a quarter of the counties (P <0.05), and significant seasonality in all but one county (Fisher-Kappa and Barlett Kolmogorov Smirnov tests significant at the level P <0.01). Areas of weak seasonality were typically seen in rural areas with high rates of hospitalizations. The highest levels of spatial clustering of pneumonia and influenza hospitalizations were found to occur in months when rates were lowest. The findings provide evidence of spatio-temporal interaction over the study period, with marked spatial variability in temporal patterns, and temporal variability in spatial patterns. Results point to the need for the effective allocation of services and resources based on regional and seasonal demands, and more regionally focused prevention strategies. This research represents an important step towards understanding the dynamic nature of these illnesses, and sets the stage for the application of spatio-temporal modelling techniques to explain them.
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