XXXX incidence mapping in golestan province, iran: using bayesian-gibbs sampling.

@entity5 @entity1820 @entity356 @entity418
OBJECTIVES: Recent studies of @entity418 ( @entity418 ) and @entity356 ( @entity356 ) have been reported to have high incidence rates of these @entity5 in Golestan Province of Iran. The present study describes the geographical patterns of @entity418 and @entity356 incidence based on @entity5 registry data and display statistically significant regions within this province. METHODS: In order to map the distribution of upper @entity1820 , relative risk (RR) were calculated. Therefore, to estimate a more reliable RR, Poisson regression models were used. The adjusted models (adjusted to urban-rural area, sex, and grouped age proportion) were utilized. We considered two-component random effects for each observation, an unstructured (noncorrelated) and a group of "neighbor" (correlated) heterogeneities. We estimated the model parameters using Gibbs sampling and empirical Bayes method. We used @entity418 and @entity356 data that were registered with Golestan Research Center of Gastroenterology and Hepatology in the years 2004-2008. RESULTS: The @entity418 and @entity356 maps were drawn for 2004-2008 in the province. Kalaleh and Minoodasht counties have a high RR of @entity418 and @entity356 in the years of study. In almost all years, the areas with a high RR were steady. CONCLUSION: The @entity418 and @entity356 maps showed significant spatial patterns of risk in Golestan province of Iran. Further study is needed to multivariate clustering and mapping of @entity5 RRs with considering diet and socioeconomic factors.
