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Background: Spain shows the highest bladder cancer incidence rates in men among European countries. The most important risk factors are tobacco smoking and occupational exposure to a range of different chemical substances, such as aromatic amines. Methods: This paper describes the municipal distribution of bladder cancer mortality and attempts to "adjust" this spatial pattern for the prevalence of smokers, using the autoregressive spatial model proposed by Besag, York and Molliè, with relative risk of lung cancer mortality as a surrogate. Results: It has been possible to compile and ascertain the posterior distribution of relative risk for bladder cancer adjusted for lung cancer mortality, on the basis of a single Bayesian spatial model covering all of Spain's 8077 towns. Maps were plotted depicting smoothed relative risk (RR) estimates, and the distribution of the posterior probability of RR>1 by sex. Towns that registered the highest relative risks for both sexes were mostly located in the Provinces of Cadiz, Seville, Huelva, Barcelona and Almería. The highest-risk area in Barcelona Province corresponded to very specific municipal areas in the Bages district, e.g., Suría, Sallent, Balsareny, Manresa and Cardona. Conclusion: Mining/industrial pollution and the risk entailed in certain occupational exposures could in part be dictating the pattern of municipal bladder cancer mortality in Spain. Population exposure to arsenic is a matter that calls for attention. It would be of great interest if the relationship between the chemical quality of drinking water and the frequency of bladder cancer could be studied. [ABSTRACT FROM AUTHOR]

Presents a mortality study on the solid-tumor in the vicinity of uranium cycle facilities and nuclear power plants (NPP) in Spain. Differences between mortality patterns in NPP and nuclear fuel facilities; Effect of residential exposure on radon; Comparison of cause-specific mortality.

Background: Aetiologically, genetic and environmental factors having an uneven spatial distribution may underlie Parkinson's disease (PD). Undiagnosis of PD in selected regions might have limited access to treatment with levodopa and simultaneously, if present at death, determined PD underreporting at the death record. The purpose of this study was to describe and analyse municipal mortality due to PD in Spain in aetiological and interventional perspective. Methods: PD mortality at a municipal level was modelled using the Besag-York- Molliè autoregressive spatial model, combining demographic information with cause-of-death diagnostic data (International Classification of Diseases 9th Revision (ICD-9) code 332.0). Municipal relative risks (RRs) were independently estimated for women, men and both sexes, and plotted on maps depicting smoothed RR estimates and the distribution of the posterior probability of RR>1. Results: A south-north gradient, with large geographical areas suggesting clustered towns with high mortality, was seen in Asturias, the Basque Country, Balearic Islands and, particularly, in the Lower Ebro valley around Tarragona. Similarly, there was a suggestion that lowest mortality was clustered in the south-east and south-west. We identified some isolated or clustered municipalities with high mortality that were situated near industrial plants reported to be associated with environmental xenobiotic emissions. However, the same pattern was also observed for some cities with low mortality. Conclusion: Municipal PD mortality in Spain was unevenly distributed. Patterns were roughly similar to reported provincial PD mortality and use of levodopa. While the overall pattern appears to result from spatially selective PD undiagnosis, and can not be ascribed to industrial emissions, it can not be excluded that selected "hot spots" reflect genetic factors and/or environmental exposures inducing parkinsonism. A few municipal populations, located in low-mortality-risk areas in the vicinity of polluting plants or registering high excess PD mortality, might constitute a priority for conducting direct etiological studies. Additionally, interventions aimed to reduce potential PD undiagnosis might be most appropriate in the South. [ABSTRACT FROM AUTHOR]

Spatial aggregation of different industrial facilities leads to simultaneous release of pollutant emissions. Our objective is to study cancer mortality risk associated with residence in the vicinity of pollutant factories. We used data on industries for year 2007 (3458 facilities). For the 8,098 Spanish towns, we defined a factor with 4 levels based on the number of factories in a radius of 2.5 km from the centroid of each town (industrial factor).We also used data of land cover use to approximate the percentage of municipal land used for industrial activities in each Spanish town (land-used variable). For both variables we fitted Poisson models with random terms to account for spatial variation. We estimated risk trends related with increasing number of factories or percentage of land used for industrial activities. We studied 33 cancer causes. For the industrial factor, 11 causes showed trend associated with increasing factor level. For the land use variable, 8 causes showed statistically significant risks. Almost all tumours related to the digestive system and the respiratory system showed increased risks. Thus mortality by these tumours could be associated to residence in towns nearby industrial areas with positive trend linked to increasing levels of industrial activity. [ABSTRACT FROM AUTHOR]

Spatial aggregation of different industrial facilities leads to simultaneous release of pollutant emissions. Our objective is to study cancer mortality risk associated with residence in the vicinity of pollutant factories. We used data on industries for year 2007 (3458 facilities). For the 8,098 Spanish towns, we defined a factor with 4 levels based on the number of factories in a radius of 2.5 km from the centroid of each town (industrial factor).We also used data of land cover use to approximate the percentage of municipal land used for industrial activities in each Spanish town (land-used variable). For both variables we fitted Poisson models with random terms to account for spatial variation. We estimated risk trends related with increasing number of factories or percentage of land used for industrial activities. We studied 33 cancer causes. For the industrial factor, 11 causes showed trend associated with increasing factor level. For the land use variable, 8 causes showed statistically significant risks. Almost all tumours related to the digestive system and the respiratory system showed increased risks. Thus mortality by these tumours could be associated to residence in towns nearby industrial areas with positive trend linked to increasing levels of industrial activity. [ABSTRACT FROM AUTHOR]