The investigation of disease risks in small areas is complicated by many issues including data quality, the retrospective nature of the statistical testing, the problems of boundary definitions in time and space around a putative disease cluster, and the lack of generally accepted definitions of the key terminology.
Routine data systems have revolutionised the initial investigation of disease risks near sources of environmental pollution, although problems of data analysis and interpretation remain.
This is especially true of unmeasured socioeconomic confounding, which could generate apparent positive results near a pollution source.
Mots-clés Pascal : Santé et environnement, Analyse risque, Echelle petite, Géographie, Pollution, Analyse amas, Méthodologie, Analyse statistique, Royaume Uni, Homme, Europe
Mots-clés Pascal anglais : Health and environment, Risk analysis, Small scale, Geography, Pollution, Cluster analysis, Methodology, Statistical analysis, United Kingdom, Human, Europe
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 96-0050899
Code Inist : 002B30A02A. Création : 199608.