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Titolo:
Ecological regression analysis of environmental benzene exposure and childhood leukaemia: sensitivity to data inaccuracies, geographical scale and ecological bias
Autore:
Best, N; Cockings, S; Bennett, J; Wakefield, J; Elliott, P;
Indirizzi:
Imperial Coll Sch Med, Dept Epidemiol & Publ Hlth, London W2 1PG, England Imperial Coll Sch Med London England W2 1PG Hlth, London W2 1PG, England
Titolo Testata:
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY
, volume: 164, anno: 2001,
parte:, 1
pagine: 155 - 174
SICI:
0964-1998(2001)164:<155:ERAOEB>2.0.ZU;2-X
Fonte:
ISI
Lingua:
ENG
Soggetto:
DISEASE; CANCER; RISK; LEUKEMIA;
Keywords:
Bayesian hierarchical models; benzene; childhood leukaemia; ecological regression; environmental epidemiology; Markov random fields;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Social & Behavioral Sciences
Citazioni:
43
Recensione:
Indirizzi per estratti:
Indirizzo: Best, N Imperial Coll Sch Med, Dept Epidemiol & Publ Hlth, Norfolk Pl, London W2 1PG, England Imperial Coll Sch Med Norfolk Pl London England W2 1PGG, England
Citazione:
N. Best et al., "Ecological regression analysis of environmental benzene exposure and childhood leukaemia: sensitivity to data inaccuracies, geographical scale and ecological bias", J ROY STA A, 164, 2001, pp. 155-174

Abstract

Benzene is classified as a group 1 human carcinogen by the International Agency for Research on Cancer, and it is now accepted that occupational exposure is associated with an increased risk of various leukaemias. However. occupational exposure accounts for less than 1% of all benzene exposures, the major sources being cigarette smoking and vehicle exhaust emissions. Whether such low level exposures to environmental benzene are also associated with the risk of leukaemia is currently not known. In this study, we investigate the relationship between benzene emissions arising from outdoor sources (predominantly road traffic and petrol stations) and the incidence of childhood leukaemia in Greater London. An ecological design was used because of the rarity of the disease, the difficulty of obtaining individual level measurements of benzene exposure and the availability of data. However, somemethodological difficulties were encountered, including problems of case registration errors, the choice of geographical areas for analysis, exposuremeasurement errors and ecological bias. We use a Bayesian hierarchical modelling framework to address these issues, and we investigate the sensitivity of our inference to various modelling assumptions.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 23/01/21 alle ore 02:38:55