Estimating small area health-related characteristics of populations: a methodological review

Submitted: 20 July 2016
Accepted: 21 November 2016
Published: 8 May 2017
Abstract Views: 3613
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Estimation of health-related characteristics at a fine local geographic level is vital for effective health promotion programmes, provision of better health services and population-specific health planning and management. Lack of a micro-dataset readily available for attributes of individuals at small areas negatively impacts the ability of local and national agencies to manage serious health issues and related risks in the community. A solution to this challenge would be to develop a method that simulates reliable small-area statistics. This paper provides a significant appraisal of the methodologies for estimating health-related characteristics of populations at geographical limited areas. Findings reveal that a range of methodologies are in use, which can be classified as three distinct set of approaches: i) indirect standardisation and individual level modelling; ii) multilevel statistical modelling; and iii) micro-simulation modelling. Although each approach has its own strengths and weaknesses, it appears that microsimulation- based spatial models have significant robustness over the other methods and also represent a more precise means of estimating health-related population characteristics over small areas.

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Supporting Agencies

Charles Sturt University
Azizur Rahman, School of Computing and Mathematics, Charles Sturt University, Wagga Wagga

Senior Lecturer

School of Computing and Mathematics

How to Cite

Rahman, A. (2017). Estimating small area health-related characteristics of populations: a methodological review. Geospatial Health, 12(1). https://doi.org/10.4081/gh.2017.495

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