Abstract:
PURPOSE:To investigate the distribution of mesothelioma in Flanders using Bayesian disease mapping models that account for both an excess of zeros and overdispersion. METHODS:The numbers of newly diagnosed mesothelioma cases within all Flemish municipalities between 1999 and 2008 were obtained from the Belgian Cancer Registry. To deal with overdispersion, zero inflation, and geographical association, the hurdle combined model was proposed, which has three components: a Bernoulli zero-inflation mixture component to account for excess zeros, a gamma random effect to adjust for overdispersion, and a normal conditional autoregressive random effect to attribute spatial association. This model was compared with other existing methods in literature. RESULTS:The results indicate that hurdle models with a random effects term accounting for extra variance in the Bernoulli zero-inflation component fit the data better than hurdle models that do not take overdispersion in the occurrence of zeros into account. Furthermore, traditional models that do not take into account excessive zeros but contain at least one random effects term that models extra variance in the counts have better fits compared to their hurdle counterparts. In other words, the extra variability, due to an excess of zeros, can be accommodated by spatially structured and/or unstructured random effects in a Poisson model such that the hurdle mixture model is not necessary. CONCLUSIONS:Models taking into account zero inflation do not always provide better fits to data with excessive zeros than less complex models. In this study, a simple conditional autoregressive model identified a cluster in mesothelioma cases near a former asbestos processing plant (Kapelle-op-den-Bos). This observation is likely linked with historical local asbestos exposures. Future research will clarify this.
journal_name
Ann Epidemioljournal_title
Annals of epidemiologyauthors
Neyens T,Lawson AB,Kirby RS,Nuyts V,Watjou K,Aregay M,Carroll R,Nawrot TS,Faes Cdoi
10.1016/j.annepidem.2016.10.006subject
Has Abstractpub_date
2017-01-01 00:00:00pages
59-66.e3issue
1eissn
1047-2797issn
1873-2585pii
S1047-2797(16)30418-5journal_volume
27pub_type
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journal_title:Annals of epidemiology
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更新日期:2014-06-01 00:00:00
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journal_title:Annals of epidemiology
pub_type: 杂志文章
doi:10.1016/j.annepidem.2004.08.006
更新日期:2005-04-01 00:00:00
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更新日期:2009-10-01 00:00:00
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更新日期:1996-03-01 00:00:00