SAGE Journals Online
Advertisement
Sign In to gain access to subscriptions and/or personal tools.

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Advertisement

Sign In to gain access to subscriptions and/or personal tools.
Statistical Methods in Medical Research
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Elliott, P.
Right arrow Articles by Shaddick, G.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Elliott, P.
Right arrow Articles by Shaddick, G.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Spatial statistical methods in environmental epidemiology: a critique

Paul Elliott

London School of Hygiene and Tropical Medicine, London, UK

Marco Martuzzi

London School of Hygiene and Tropical Medicine, London, UK

Gavin Shaddick

London School of Hygiene and Tropical Medicine, London, UK

Despite recent advances in the available statistical methods for geographical analysis, there are many constraints to their application in environmental epidemiology. These include problems of data availability and quality, especially the lack in most situations of environmental exposure measurements. Methods for disease 'cluster' investigation, point source exposures, small-area disease mapping and ecological correlation studies are critically reviewed, with the emphasis on practical applications and epidemiological interpretation. It is shown that, unless dealing with rare diseases, high specificity exposures and high relative risks, cluster investigation is unlikely to be fruitful, and is often complicated by the post hoc nature of such studies. However, it is recognized that in these circumstances proper assessment of the available data is often required as part of the public health response. Newly availabe methods, particularly in Bayesian statistics, offer an appropriate framework for geographical analysis and disease mapping. Again, it is uncertain whether they will give important clues as to aetiology, although they do give valuable description. Perhaps the most satisfactory approach is to test a priori hypotheses using a geographical database, although problems of interpretation remain.

Statistical Methods in Medical Research, Vol. 4, No. 2, 137-159 (1995)
DOI: 10.1177/096228029500400204


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
J. Epidemiol. Community HealthHome page
N. Middleton, J. A C Sterne, and D. Gunnell
The geography of despair among 15-44-year-old men in England and Wales: putting suicide on the map.
J Epidemiol Community Health, December 1, 2006; 60(12): 1040 - 1047.
[Abstract] [Full Text] [PDF]


Home page
Am J EpidemiolHome page
P. Moayyedi
Invited Commentary: Clues to the Etiology of Inflammatory Bowel Disease--A Return to John Snow?
Am. J. Epidemiol., October 1, 2006; 164(7): 624 - 626.
[Full Text] [PDF]


Home page
NeurologyHome page
M. Pugliatti, G. Solinas, S. Sotgiu, P. Castiglia, and G. Rosati
Multiple sclerosis distribution in northern Sardinia: Spatial cluster analysis of prevalence
Neurology, January 22, 2002; 58(2): 277 - 282.
[Abstract] [Full Text] [PDF]


Home page
Occup. Environ. Med.Home page
E Kokki, J Ranta, A Penttinen, E Pukkala, and J Pekkanen
Small area estimation of incidence of cancer around a known source of exposure with fine resolution data
Occup. Environ. Med., May 1, 2001; 58(5): 315 - 320.
[Abstract] [Full Text]


Home page
Int J EpidemiolHome page
S. Q Muth, J. J Potterat, and R. B Rothenberg
Birds of a feather: using a rotational box plot to assess ascertainment bias
Int. J. Epidemiol., October 1, 2000; 29(5): 899 - 904.
[Abstract] [Full Text] [PDF]


Home page
Occup. Environ. Med.Home page
T. Pless-Mulloli, C. E Dunn, R. Bhopal, P. Phillimore, S. Moffatt, and J. Edwards
Is it feasible to construct a community profile of exposure to industrial air pollution?
Occup. Environ. Med., August 1, 2000; 57(8): 542 - 549.
[Abstract] [Full Text]



Advertisement