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

Abstract

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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Author Biography

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

Senior Lecturer

School of Computing and Mathematics

Published
2017-05-08
Section
Reviews
Keywords:
Health-related characteristics, Indirect standardisation, Micro-simulation modelling, Multilevel models, Small area estimates
Statistics
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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