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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 Mollie (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.

Introduction Our objective is to study the relation between industrial pollution and cancer in Spain by defining a simple industrialisation index (town level), using the information from the European Pollutant Release and Transfer Register (E-PRTR). Materials and Methods We used data on industries from the PRTR-Spain for year 2007. We selected the 3458 facilities with positively validated co-ordinates. For the 8098 Spanish towns we defined the index as a factor with four levels based on the number of factories in a radius of 2.5 km from the centroid of each town: Value 0 for towns with no factory within the radius; 1 for those with 1 factory; 2 for those with 2, 3 or 4; and 3 for those with more than four factories. The index, along with socio-demographic indicators (potential confounders), was included in a spatial Poisson model (BYM) to estimate the cancer mortality risk associated with the index levels. We fitted models for 33 cancer causes. Also trend tests were computed. Results Many causes, 19, showed statistical association with at least one level of the factor. Almost all tumours related to the digestive system and the respiratory system showed excess of risk and/or trend linked with the index. Conclusions The proposed index is a useful tool to explore possible associations between the level of industrialisation of residential areas and its health outcomes, despite of its limitations. Digestive and respiratory system tumours could be associated to residence near to industrial areas.

The European Pollutant Release and Transfer Register (PRTR) constitute a valuable resource for monitoring health effects of industrial pollution. Our objective is to ascertain whether there might be excess colorectal cancer (CRC) mortality among populations residing in the vicinity of Spanish industrial installations governed by the PRTR. Methods An ecological study of CRC mortality at a municipal level (8098 towns), over the period 1997–2006. We conducted an exploratory “near vs far” analysis to estimate the RRs of towns at a distance of Results Statistically significant RR were detected in the vicinity of metal production and processing (RR 1.07; 95% CI 1.01 to 1.12), mining (RR 1.26; 95% CI 1.08 to 1.46), paper, pulp and board manufacture (RR 1.07; 95% CI 1.01 to 1.14), ceramic factories (RR 1.05; 95% CI 1.00 to 1.10) and food and beverage production (RR 1.07; 95% CI 1.03 to 1.11). Conclusions Residing in the vicinity of PRTR-registered industries may constitute a risk factor for CRC, since a higher mortality was detected in both men and women residing in towns with such industries nearby. Some of the differences between men and women suggest that there may be a strong, little-studied component of occupational exposure.