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Application of spatial statistics in studying the distribution of food contamination / 中华流行病学杂志
Chinese Journal of Epidemiology ; (12): 241-246, 2019.
Article in Chinese | WPRIM (Western Pacific) | ID: wpr-738247
Responsible library: WPRO
ABSTRACT
Objective Based on data related to arsenic contents in paddy rice,as part of the food safety monitoring programs in 2017,to discuss and explore the application of spatial analysis used for food safety risk assessment.Methods One province was chosen to study the spatial visualization,spatial point model estimation,and kernel density estimation.Moran's I statistic of spatial autocorrelation methods was used to analyze the spatial distribution at the county level.Results Data concerning the spatial point model estimation showed that the spatial distribution of pollution appeared relatively dispersive.From the kernel density estimation,we found that the hot spots of pollution were mainly located in the central and eastern regions.The global Moran's I values appeared as 0.11 which presented low spatial aggregation to the rice arsenic contamination and with statistically significant differences.One "high-high" and two typical "low-low" clustering were seen in this study.Conclusion Results from our study provided good visual demonstration,identification of pollution distribution rules,hot spots and aggregation areas for research on the distribution of food pollutants.Spatial statistics can provide technical support for the implementation of issue-based monitoring programs.

Full text: Available Database: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Epidemiology Year: 2019 Document type: Article
Full text: Available Database: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Epidemiology Year: 2019 Document type: Article
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