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Spatial distribution of fluoride in drinking-water in Shandong Province based on a geographic information system / 中华地方病学杂志
Chinese Journal of Endemiology ; (12): 283-286, 2018.
Article in Zh | WPRIM | ID: wpr-701315
Responsible library: WPRO
ABSTRACT
Objective To detect the spatial distribution characteristics of water fluoride in Shandong Province.Methods The county-based study set Shandong Province as a research site.The county level fluoride database was matched with electronic maps to build geographic information system (GIS) spatial data platform.Global Moran's I and Local Moran's I index were calculated,respectively,and the cluster range of water fluoride distribution in Shandong Province was studied through SaTScan software.Results The water fluoride was normal (≤ 1.0 mg/L) in 54 counties in Shandong Province,mainly located in Weihai and Yantai in the eastern,Dongying in northern,and vast region in middle and southeastern of Shandong Province.Eighty-six counties were high water fluoride counties (> 1.0 mg/L),mainly distributed in the southwest,northwest and north-central of Shandong Province,showing a significant geographical feature.Global spatial autocorrelation analysis showed that the distribution of water fluoride content in Shandong Province showed significant positive spatial autocorrelation (Moran's I =0.44,Z =6.83,P < 0.01).Local Moran's I analysis showed water fluoride in 13 counties had local spatial autocorrelation,being all high-high clusters.And these results were statistically significant (P < 0.05).A cluster area was detected through SaTScan spatial analysis software,including 15 counties.The center was located in Dongming County of Heze City,with radius of 130.08 km.The results and the local spatial autocorrelation results were basically consistent.Conclusions There are apparent spatial autocorrelation and spatial cluster in water fluoridation in Shandong Province.Spatial autocorrelation and SaTScan software can be combined in exploring the spatial distribution of water fluoride.
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Full text: 1 Database: WPRIM Language: Zh Journal: Chinese Journal of Endemiology Year: 2018 Document type: Article
Full text: 1 Database: WPRIM Language: Zh Journal: Chinese Journal of Endemiology Year: 2018 Document type: Article