Disease risk near point sources

Statistical issues for analyses using individual or spatially aggregated data

Peter Diggle, Paul Elliott

Research output: Contribution to journalArticle

Abstract

Study objective - To examine the statistical issues involved in the analysis of disease risk near point sources of environmental pollution, where data are held at both the individual and group (areal) level. To explore these issues with reference to possible socioeconomic confounding. Design - Statistical review. Setting - Point sources of environmental pollution. Main results - Except in very specific circumstances unlikely to hold in practice, aggregation of data to the areal level will lead to bias in the estimation of disease risk. Conclusions - There is no easy solution to the analysis of spatial data when some covariates (for example, age and sex of cases) are known at individual level, whereas others (for example, populations, age-sex distributions, small area deprivation indices) are known only at the areal (ecological) level. The underlying assumptions inherent in the analysis of these data need to be explicitly recognised in order to understand better the limitations of the available methodology as well as to inform interpretation of results. Ideally, the data should be kept as disaggregated as possible, to maximise the information available and minimise potential for bias.

Original languageEnglish (US)
JournalJournal of Epidemiology and Community Health
Volume49
Issue numberSUPPL. 2
DOIs
StatePublished - 1995
Externally publishedYes

Fingerprint

Environmental Pollution
Sex Distribution
Spatial Analysis
Age Distribution
Population

ASJC Scopus subject areas

  • Dermatology
  • Infectious Diseases
  • Public Health, Environmental and Occupational Health

Cite this

Disease risk near point sources : Statistical issues for analyses using individual or spatially aggregated data. / Diggle, Peter; Elliott, Paul.

In: Journal of Epidemiology and Community Health, Vol. 49, No. SUPPL. 2, 1995.

Research output: Contribution to journalArticle

@article{fa2e7fed8b894068a4ff4c04c6198e19,
title = "Disease risk near point sources: Statistical issues for analyses using individual or spatially aggregated data",
abstract = "Study objective - To examine the statistical issues involved in the analysis of disease risk near point sources of environmental pollution, where data are held at both the individual and group (areal) level. To explore these issues with reference to possible socioeconomic confounding. Design - Statistical review. Setting - Point sources of environmental pollution. Main results - Except in very specific circumstances unlikely to hold in practice, aggregation of data to the areal level will lead to bias in the estimation of disease risk. Conclusions - There is no easy solution to the analysis of spatial data when some covariates (for example, age and sex of cases) are known at individual level, whereas others (for example, populations, age-sex distributions, small area deprivation indices) are known only at the areal (ecological) level. The underlying assumptions inherent in the analysis of these data need to be explicitly recognised in order to understand better the limitations of the available methodology as well as to inform interpretation of results. Ideally, the data should be kept as disaggregated as possible, to maximise the information available and minimise potential for bias.",
author = "Peter Diggle and Paul Elliott",
year = "1995",
doi = "10.1136/jech.49.Suppl_2.S20",
language = "English (US)",
volume = "49",
journal = "Journal of Epidemiology and Community Health",
issn = "0143-005X",
publisher = "BMJ Publishing Group",
number = "SUPPL. 2",

}

TY - JOUR

T1 - Disease risk near point sources

T2 - Statistical issues for analyses using individual or spatially aggregated data

AU - Diggle, Peter

AU - Elliott, Paul

PY - 1995

Y1 - 1995

N2 - Study objective - To examine the statistical issues involved in the analysis of disease risk near point sources of environmental pollution, where data are held at both the individual and group (areal) level. To explore these issues with reference to possible socioeconomic confounding. Design - Statistical review. Setting - Point sources of environmental pollution. Main results - Except in very specific circumstances unlikely to hold in practice, aggregation of data to the areal level will lead to bias in the estimation of disease risk. Conclusions - There is no easy solution to the analysis of spatial data when some covariates (for example, age and sex of cases) are known at individual level, whereas others (for example, populations, age-sex distributions, small area deprivation indices) are known only at the areal (ecological) level. The underlying assumptions inherent in the analysis of these data need to be explicitly recognised in order to understand better the limitations of the available methodology as well as to inform interpretation of results. Ideally, the data should be kept as disaggregated as possible, to maximise the information available and minimise potential for bias.

AB - Study objective - To examine the statistical issues involved in the analysis of disease risk near point sources of environmental pollution, where data are held at both the individual and group (areal) level. To explore these issues with reference to possible socioeconomic confounding. Design - Statistical review. Setting - Point sources of environmental pollution. Main results - Except in very specific circumstances unlikely to hold in practice, aggregation of data to the areal level will lead to bias in the estimation of disease risk. Conclusions - There is no easy solution to the analysis of spatial data when some covariates (for example, age and sex of cases) are known at individual level, whereas others (for example, populations, age-sex distributions, small area deprivation indices) are known only at the areal (ecological) level. The underlying assumptions inherent in the analysis of these data need to be explicitly recognised in order to understand better the limitations of the available methodology as well as to inform interpretation of results. Ideally, the data should be kept as disaggregated as possible, to maximise the information available and minimise potential for bias.

UR - http://www.scopus.com/inward/record.url?scp=0029616115&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0029616115&partnerID=8YFLogxK

U2 - 10.1136/jech.49.Suppl_2.S20

DO - 10.1136/jech.49.Suppl_2.S20

M3 - Article

VL - 49

JO - Journal of Epidemiology and Community Health

JF - Journal of Epidemiology and Community Health

SN - 0143-005X

IS - SUPPL. 2

ER -