当前位置： SCI文献检索 > ANNALS OF EPIDEMIOLOGY期刊下所有文献 > Spatiotemporal analysis and mapping of oral cancer risk in changhua county (taiwan): an application of generalized bayesian maximum entropy method.

Spatiotemporal analysis and mapping of oral cancer risk in changhua county (taiwan): an application of generalized bayesian maximum entropy method.

Abstract：

PURPOSE:Incidence rate of oral cancer in Changhua County is the highest among the 23 counties of Taiwan during 2001. However, in health data analysis, crude or adjusted incidence rates of a rare event (e.g., cancer) for small populations often exhibit high variances and are, thus, less reliable. METHODS:We proposed a generalized Bayesian Maximum Entropy (GBME) analysis of spatiotemporal disease mapping under conditions of considerable data uncertainty. GBME was used to study the oral cancer population incidence in Changhua County (Taiwan). Methodologically, GBME is based on an epistematics principles framework and generates spatiotemporal estimates of oral cancer incidence rates. In a way, it accounts for the multi-sourced uncertainty of rates, including small population effects, and the composite space-time dependence of rare events in terms of an extended Poisson-based semivariogram. RESULTS:The results showed that GBME analysis alleviates the noises of oral cancer data from population size effect. Comparing to the raw incidence data, the maps of GBME-estimated results can identify high risk oral cancer regions in Changhua County, where the prevalence of betel quid chewing and cigarette smoking is relatively higher than the rest of the areas. CONCLUSIONS:GBME method is a valuable tool for spatiotemporal disease mapping under conditions of uncertainty.

journal_name

Ann Epidemiol

journal_title

Annals of epidemiology

authors

Yu HL,Chiang CT,Lin SD,Chang TK

doi

10.1016/j.annepidem.2009.10.005

subject

Has Abstract

pub_date

2010-02-01 00:00:00

pages

99-107

issue

2

eissn

1047-2797

issn

1873-2585

pii

S1047-2797(09)00342-1

journal_volume

20

pub_type

杂志文章

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