The University of Southampton
University of Southampton Institutional Repository

Analysing spatially referenced public health data: a comparison of three methodological approaches

Analysing spatially referenced public health data: a comparison of three methodological approaches
Analysing spatially referenced public health data: a comparison of three methodological approaches
In the analysis of spatially referenced public health data, members of different disciplinary groups (geographers, epidemiologists and statisticians) tend to select different methodological approaches, usually those with which they are already familiar. This paper compares three such approaches in terms of their relative value and results. A single public health dataset, derived from a community survey, is analysed by using ‘traditional’ epidemiological methods, GIS and point pattern analysis. Since they adopt different ‘models’ for addressing the same research question, the three approaches produce some variation in the results for specific health-related variables. Taken overall, however, the results complement, rather than con or duplicate each other.
public health data, epidemiology, GIS, point pattern analysis tradict
1353-8292
1-12
Dunn, C.
2c23d09b-3bc6-4d42-ba65-3af8ceb81d48
Kingham, S.
4f8c942f-32dc-4240-8ba5-0a18f09b4da7
Rowlingson, B.
79ffeaa1-87e6-4bbc-a0bc-07c14f23bbf2
Bhopal, R.
830ac3cb-1e7c-4893-be10-efd090188614
Cockings, S.
53df26c2-454e-4e90-b45a-48eb8585e800
Foy, C.
f0927bac-894e-47a8-b5eb-7c1b4e40b9a6
Acquilla, S.
d6ba4ccd-9b0f-45fb-806d-b2a278c1c820
Halpin, J.
c8f57bbd-367c-4cd2-bd57-7a4af055c67b
Diggle, P.
958f3b35-5c71-408a-b244-ecb3acd10500
Walker, D.
26d59048-0785-4861-9c83-4bae3c33caad
Dunn, C.
2c23d09b-3bc6-4d42-ba65-3af8ceb81d48
Kingham, S.
4f8c942f-32dc-4240-8ba5-0a18f09b4da7
Rowlingson, B.
79ffeaa1-87e6-4bbc-a0bc-07c14f23bbf2
Bhopal, R.
830ac3cb-1e7c-4893-be10-efd090188614
Cockings, S.
53df26c2-454e-4e90-b45a-48eb8585e800
Foy, C.
f0927bac-894e-47a8-b5eb-7c1b4e40b9a6
Acquilla, S.
d6ba4ccd-9b0f-45fb-806d-b2a278c1c820
Halpin, J.
c8f57bbd-367c-4cd2-bd57-7a4af055c67b
Diggle, P.
958f3b35-5c71-408a-b244-ecb3acd10500
Walker, D.
26d59048-0785-4861-9c83-4bae3c33caad

Dunn, C., Kingham, S., Rowlingson, B., Bhopal, R., Cockings, S., Foy, C., Acquilla, S., Halpin, J., Diggle, P. and Walker, D. (2001) Analysing spatially referenced public health data: a comparison of three methodological approaches. Health & Place, 7 (1), 1-12. (doi:10.1016/S1353-8292(00)00033-2).

Record type: Article

Abstract

In the analysis of spatially referenced public health data, members of different disciplinary groups (geographers, epidemiologists and statisticians) tend to select different methodological approaches, usually those with which they are already familiar. This paper compares three such approaches in terms of their relative value and results. A single public health dataset, derived from a community survey, is analysed by using ‘traditional’ epidemiological methods, GIS and point pattern analysis. Since they adopt different ‘models’ for addressing the same research question, the three approaches produce some variation in the results for specific health-related variables. Taken overall, however, the results complement, rather than con or duplicate each other.

Full text not available from this repository.

More information

Submitted date: 12 September 1999
Published date: March 2001
Keywords: public health data, epidemiology, GIS, point pattern analysis tradict
Organisations: PHEW – P (Population Health), Remote Sensing & Spatial Analysis

Identifiers

Local EPrints ID: 16129
URI: https://eprints.soton.ac.uk/id/eprint/16129
ISSN: 1353-8292
PURE UUID: aca7b213-a9aa-4fc8-a73e-85aeae224b78

Catalogue record

Date deposited: 21 Jun 2005
Last modified: 15 Jul 2019 19:31

Export record

Altmetrics

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

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×