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Journal of Epidemiology and Community Health 2007;61:165-171; doi:10.1136/jech.2005.041491
Copyright © 2007 by the BMJ Publishing Group Ltd.

RESEARCH REPORT

Modelling of municipal mortality due to haematological neoplasias in Spain

Rebeca Ramis-Prieto, Javier García-Pérez, Marina Pollán, Nuria Aragonés, Beatriz Pérez-Gómez and Gonzalo López-Abente

Environmental and Cancer Epidemiology Unit, National Centre for Epidemiology, Carlos III Institute of Health, C/Sinesio Delgado, 6, 28029 Madrid, Spain

Correspondence to:
Correspondence to:
R Ramis-Prieto
Environmental and Cancer Epidemiology Unit, National Centre for Epidemiology, Carlos III Institute of Health, C/Sinesio Delgado, 6, 28029 Madrid, Spain; rramis{at}isciii.es

Objectives: To study the geographical pattern of mortality caused by haematological tumours in Spain at the municipal level using three Bayesian models and to compare their goodness of fit.

Methods: The fitted Bayesian hierarchical models were: (1) the Besag York and Molliè (BYM) model; (2) a model based on zero-inflated Poisson (ZIP) distribution, which allowed a large number of event-free areas; and (3) a mixture of distributions that enabled discontinuities (jumps in the pattern) to be modelled. The three models allow smoothed relative risk maps to be obtained for the all countries. The goodness of fit was evaluated using the deviance information criteria.

Results: The three models yielded similar results. The ZIP model plotted a pattern almost identical with the BYM model. The goodness-of-fit criteria indicate that the mixture model is the one that best fits our data. Haematological tumours display a geographical pattern that could be partly explained by environmental determinants, as many of the highest-risk towns are located in heavily industrialised areas.

Conclusions: The choice of one or another model has scant practical consequences. The pattern of distribution supports the hypothesis that differences in lifestyles, air/industrial pollution and migratory phenomena may determine the pattern of urban mortality due to these tumours.

Abbreviations: BYM, Besag York and Molliè; CAR, conditional autoregressive; DIC, Deviance Information Criterion; NHL, non-Hodgkin’s lymphomas; SMR, standard mortality ratio; ZIP, zero-inflated Poisson


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