Abstract
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.
Highlights
Lead exposure has adverse health impacts on children’s mental and physical growth and development
The spatial negative binomial Hurdle model best fitted the number of children with lead poisoning and provided better predictions over other models
The results showed that the negative binomial Hurdle model with random effects (RE) had the smallest χ2 deviance from the observed frequencies (Table 5), which confirmed that the negative binomial Hurdle model handled both issues of overdispersion and excessive zeros effectively and improved both model fitting and prediction
Summary
Lead exposure has adverse health impacts on children’s mental and physical growth and development. Pediatric lead poisoning is completely preventable through an intervention such as proactively identifying the lead sources in the environment and educating parents and guardians on how to reduce exposure to these environmental sources [3]. In order to prevent pediatric lead poisoning, public health service agencies decided that it is important to shift from case identification and management to primary prevention. These service agencies are interested in developing analytical methods to identify high-risk areas of lead poisoning
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