249913
Geography, isolation, and pneumonia and influenza mortality in elderly populations
Tuesday, November 1, 2011
Joseph Sepulveda
,
Department of Geography, Northern Illinois University, DeKalb, IL
Ryan Coomer
,
Department of Geography, Northern Illinois University, DeKalb, IL
Background. Elderly populations (65+ years) in the US are at the highest risk of death from pneumonia and influenza (PI). Geographic patterns of PI mortality in the elderly are not as readily discernible as other leading causes of death. However, county rural/urban typologies can reveal an underlying association among geographic categories and PI mortality rates in this population. Objectives/Purpose. To evaluate critically the NCHS Urban/Rural county typology on PI mortality calculations in the elderly and differentiating place effects on the general 65+ year population and its sub-populations of 65-74 years, 75-84 years, and 85+ years. Methods. PI mortality, population, and the NCHS county typology were obtained from the CDC WONDER website. Crude rates for each elderly age group were calculated for each of the county typology categories large central metropolitan, large fringe metropolitan, medium metropolitan, small metropolitan, micropolitan-non-metro, and non-core-non-metro, and mapped and compared statistically. Results. The highest mortality rates (per 100,000) for nearly all elderly age groups were found in large central metropolitan counties and non-core-non-metro counties, with the exception of the 85+ year population whose highest rates were found in micropolitan-non-metro and non-core-non-metro counties. Discussion/Conclusions. The expectation was that isolated counties would possess the highest PI mortality rates for elderly populations. This expectation was borne out, but an unexpected result was the higher PI mortality found in large central metropolitan counties. This suggests that isolation effects are not just geographic but also attributable place specific socio-economic characteristics that must be considered in developing explanatory models.
Learning Areas:
Communication and informatics
Public health or related research
Social and behavioral sciences
Systems thinking models (conceptual and theoretical models), applications related to public health
Learning Objectives: The participant will be able to describe the effect of county typology categories on pneumonia and influenza mortality rate calculations.
The participant will be able to compare regional differences in pneumonia and influenza mortality patterns of elderly populations.
Keywords: Mortality, Geographic Information Systems
Presenting author's disclosure statement:Qualified on the content I am responsible for because: I am qualified to present because I teach and conduct research in areas of medical geography, GIS, and vital statistics.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines,
and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed
in my presentation.
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