Can a deterministic spatial microsimulation model provide reliable small-area estimates of health behaviours? An example of smoking prevalence in New Zealand
Can a deterministic spatial microsimulation model provide reliable small-area estimates of health behaviours? An example of smoking prevalence in New Zealand
Models created to estimate neighbourhood level health outcomes and behaviours can be difficult to validate as prevalence is often unknown at the local level. This paper tests the reliability of a spatial microsimulation model, using a deterministic reweighting method, to predict smoking prevalence in small areas across New Zealand. The difference in the prevalence of smoking between those estimated by the model and those calculated from census data is less than 20% in 1745 out of 1760 areas. The accuracy of these results provides users with greater confidence to utilize similar approaches in countries where local-level smoking prevalence is unknown
synthetic estimation, smoking, new zealand, microsimulation, new zealand health survey
618-624
Smith, Dianna M.
e859097c-f9f5-4fd0-8b07-59218648e726
Pearce, Jamie R.
db47ec78-13d1-4340-b232-936398cd8e4e
Harland, Kirk
a0d6900c-1551-4075-a30d-215f965a84ec
March 2011
Smith, Dianna M.
e859097c-f9f5-4fd0-8b07-59218648e726
Pearce, Jamie R.
db47ec78-13d1-4340-b232-936398cd8e4e
Harland, Kirk
a0d6900c-1551-4075-a30d-215f965a84ec
Smith, Dianna M., Pearce, Jamie R. and Harland, Kirk
(2011)
Can a deterministic spatial microsimulation model provide reliable small-area estimates of health behaviours? An example of smoking prevalence in New Zealand.
Health & Place, 17 (2), .
(doi:10.1016/j.healthplace.2011.01.001).
(PMID:21257335)
Abstract
Models created to estimate neighbourhood level health outcomes and behaviours can be difficult to validate as prevalence is often unknown at the local level. This paper tests the reliability of a spatial microsimulation model, using a deterministic reweighting method, to predict smoking prevalence in small areas across New Zealand. The difference in the prevalence of smoking between those estimated by the model and those calculated from census data is less than 20% in 1745 out of 1760 areas. The accuracy of these results provides users with greater confidence to utilize similar approaches in countries where local-level smoking prevalence is unknown
This record has no associated files available for download.
More information
Accepted/In Press date: 5 January 2011
Published date: March 2011
Keywords:
synthetic estimation, smoking, new zealand, microsimulation, new zealand health survey
Organisations:
Population, Health & Wellbeing (PHeW)
Identifiers
Local EPrints ID: 382514
URI: http://eprints.soton.ac.uk/id/eprint/382514
ISSN: 1353-8292
PURE UUID: 07a93c5c-18ee-4111-94af-5ce4849c9a34
Catalogue record
Date deposited: 29 Oct 2015 12:03
Last modified: 15 Mar 2024 03:53
Export record
Altmetrics
Contributors
Author:
Jamie R. Pearce
Author:
Kirk Harland
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics
