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Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach


Nichols, LJ and Gall, S and Stirling, C, Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach, Journal of Neurosciences in Rural Practice, 7, (4) pp. 559-565. ISSN 0976-3147 (2016) [Refereed Article]


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Copyright 2016 Journal of Neurosciences in Rural Practice. Licensed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)

DOI: doi:10.4103/0976-3147.188627


An aneurysmal subarachnoid hemorrhage (aSAH) carries a high disability burden. The true impact of rurality as a predictor of outcome severity is unknown. Our aim is to clarify the relationship between the proposed explanations of regional and rural health disparities linked to severity of outcome following an aSAH. An initial literature search identified limited data directly linking geographical location, rurality, rural vulnerability, and aSAH. A further search noting parallels with ischemic stroke and acute myocardial infarct literature presented a number of diverse and interrelated predictors. This a priori knowledge informed the development of a conceptual framework that proposes the relationship between rurality and severity of outcome following an aSAH utilizing structural equation modeling. The presented conceptual framework explores a number of system, environmental, and modifiable risk factors. Socioeconomic characteristics, modifiable risk factors, and timely treatment that were identified as predictors of severity of outcome following an aSAH and within each of these defined predictors a number of contributing specific individual predictors are proposed. There are considerable gaps in the current knowledge pertaining to the impact of rurality on the severity of outcome following an aSAH. Absent from the literature is any investigation of the cumulative impact and multiplicity of risk factors associated with rurality. The proposed conceptual framework hypothesizes a number of relationships between both individual level and system level predictors, acknowledging that intervening predictors may mediate the effect of one variable on another.

Item Details

Item Type:Refereed Article
Keywords:aneurysmal subarachnoid hemorrhage, rural vulnerability, structural equation modeling
Research Division:Health Sciences
Research Group:Epidemiology
Research Field:Epidemiology not elsewhere classified
Objective Division:Health
Objective Group:Evaluation of health and support services
Objective Field:Evaluation of health outcomes
UTAS Author:Nichols, LJ (Mrs Linda Nichols)
UTAS Author:Gall, S (Associate Professor Seana Gall)
UTAS Author:Stirling, C (Professor Christine Stirling)
ID Code:110866
Year Published:2016
Deposited By:Health Sciences
Deposited On:2016-08-19
Last Modified:2017-11-06
Downloads:220 View Download Statistics

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