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http://dx.doi.org/10.7465/jkdi.2016.27.5.1203

Bayesian spatial analysis of obesity proportion data  

Choi, Jungsoon (Department of Mathematics, Hanyang University and Research Institute for Natural Sciences)
Publication Information
Journal of the Korean Data and Information Science Society / v.27, no.5, 2016 , pp. 1203-1214 More about this Journal
Abstract
Obesity is a risk factor for various diseases as well as itself a disease and associated with socioeconomic factors. The obesity proportion has been increasing in Korea over about 15 years so that investigation of the socioeconomic factors related with obesity is important in terms of preventation of obesity. In particular, the association between obesity and socioeconomic status varies with gender and has spatial dependency. In the paper, we estimate the effects of socioeconomic factors on obesity proportion by gender, considering the spatial correlation. Here, a conditional autoregressive model under the Bayesian framework is used in order to take into account the spatial dependency. For the real applicaiton, we use the obestiy proportion dataset at 25 districts of Seoul in 2010. We compare the proposed spatial model with a non-spatial model in terms of the goodness-of-fit and prediction measures so the spatial model performs well.
Keywords
Bayesian inference; conditionally autoregressive model; obesity; socioeconomic status; spatial analysis;
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Times Cited By KSCI : 3  (Citation Analysis)
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