点击次数：

影响因子：3.39

DOI码：10.3390/ijerph15091792

发表刊物：International Journal of Environmental Research and Public Health

关键字：overdispersion; zero-inflated count data; negative binomial Hurdle model; generalized linear mixed models; random effects; spatial effects

摘要：Objective The purpose of this study is to identify the high-risk areas of children’s lead poisoning in Syracuse, NY, USA, using spatial modeling techniques. The relationships between the number of children’s lead poisoning cases and three socio-economic and environmental factors (i.e., building year and town taxable value of houses, and soil lead concentration) were investigated. Methods Spatial generalized linear models (including Poisson, negative binomial, Poisson Hurdle, and negative binomial Hurdle models) were used to model the number of children’s lead poisoning cases using the three predictor variables at the census block level in the inner city of Syracuse. Results The building year and town taxable value were strongly and positively associated with the elevated risk for lead poisoning, while soil lead concentration showed a weak relationship with lead poisoning. The negative binomial Hurdle model with spatial random effects was the appropriate model for the disease count data across the city neighborhood. Conclusions The spatial negative binomial Hurdle model best fitted the number of children with lead poisoning and provided better predictions over other models. It could be used to deal with complex spatial data of children with lead poisoning, and may be generalized to other cities.

合写作者：Liyang Shao

第一作者：Q1, Zhen Zhen

论文类型：期刊论文

通讯作者：Lianjun Zhang*

卷号：15

期号：9

页面范围：1792

ISSN号：1660-4601

是否译文：否

发表时间：2018-01-01

收录刊物：SCI、SSCI