Literature DB >> 16428258

Health-exposure modeling and the ecological fallacy.

Jon Wakefield1, Gavin Shaddick.   

Abstract

Recently, there has been an increased interest in modeling the association between aggregate disease counts and environmental exposures measured, for example via air pollution monitors, at point locations. This paper has two aims: first, we develop a model for such data in order to avoid ecological bias; second, we illustrate that modeling the exposure surface and estimating exposures may lead to bias in estimation of health effects. Design issues are also briefly considered, in particular the loss of information in moving from individual to ecological data, and the at-risk populations to consider in relation to the pollution monitor locations. The approach is investigated initially through simulations, and is then applied to a study of the association between mortality in those over 65 in the year 2000 and the previous year's SO2, in London. We conclude that the use of the proposed model can provide valid inference, but the use of estimated exposures should be carried out with great caution.

Mesh:

Substances:

Year:  2006        PMID: 16428258     DOI: 10.1093/biostatistics/kxj017

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


  24 in total

1.  Confounding and exposure measurement error in air pollution epidemiology.

Authors:  Lianne Sheppard; Richard T Burnett; Adam A Szpiro; Sun-Young Kim; Michael Jerrett; C Arden Pope; Bert Brunekreef
Journal:  Air Qual Atmos Health       Date:  2011-03-23       Impact factor: 3.763

2.  On ecological studies: a short communication.

Authors:  John Hart
Journal:  Dose Response       Date:  2011-01-07       Impact factor: 2.658

3.  Long-term associations of outdoor air pollution with mortality in Great Britain.

Authors:  Paul Elliott; Gavin Shaddick; Jonathan C Wakefield; Cornelis de Hoogh; David J Briggs
Journal:  Thorax       Date:  2007-07-31       Impact factor: 9.139

4.  Measurement error caused by spatial misalignment in environmental epidemiology.

Authors:  Alexandros Gryparis; Christopher J Paciorek; Ariana Zeka; Joel Schwartz; Brent A Coull
Journal:  Biostatistics       Date:  2008-10-16       Impact factor: 5.899

5.  Measurement error in two-stage analyses, with application to air pollution epidemiology.

Authors:  Adam A Szpiro; Christopher J Paciorek
Journal:  Environmetrics       Date:  2013-12-01       Impact factor: 1.900

6.  Incorporating spatial variability within epidemiological studies of environmental exposures.

Authors:  Gavin Shaddick; Duncan Lee; Jonathan Wakefield
Journal:  Int J Appl Earth Obs Geoinf       Date:  2013-06

7.  On the analysis of hybrid designs that combine group- and individual-level data.

Authors:  E Smoot; S Haneuse
Journal:  Biometrics       Date:  2014-09-22       Impact factor: 2.571

8.  A neighborhood wealth metric for use in health studies.

Authors:  Anne Vernez Moudon; Andrea J Cook; Jared Ulmer; Philip M Hurvitz; Adam Drewnowski
Journal:  Am J Prev Med       Date:  2011-07       Impact factor: 5.043

9.  Spatial Determinants of Ebola Virus Disease Risk for the West African Epidemic.

Authors:  Kate Zinszer; Kathryn Morrison; Aman Verma; John S Brownstein
Journal:  PLoS Curr       Date:  2017-03-31

10.  Spatio-temporal trends of mortality in small areas of Southern Spain.

Authors:  Ricardo Ocaña-Riola; José María Mayoral-Cortés
Journal:  BMC Public Health       Date:  2010-01-20       Impact factor: 3.295

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