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Moonga, Given; Chisola, Moses N.; Berger, Ursula; Nowak, Dennis; Yabe, John; Nakata, Hokuto; Nakayama, Shouta; Ishizuka, Mayumi and Bose-O'Reilly, Stephan (2021): Geospatial approach to investigate spatial clustering and hotspots of blood lead levels in children within Kabwe, Zambia. In: Environmental Research, Vol. 207, 112646

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Abstract

BACKGROUND Communities around Kabwe, Zambia are exposed to lead due to deposits from an old lead (Pb) and zinc (Zn) mining site. Children are particularly more vulnerable than adults, presenting with greatest risk of health complications. They have increased oral uptake due to their hand to mouth activities. Spatial analysis of childhood lead exposure is useful in identifying specific areas with highest risk of pollution. The objective of the current study was to use a geospatial approach to investigate spatial clustering and hotspots of blood lead levels in children within Kabwe. METHODS We analysed existing data on blood lead levels (BLL) for 362 children below the age of 15 from Kabwe town. We used spatial autocorrelation methods involving the global Moran's I and local Getis-Ord Gi*statistic in ArcMap 10.5.1, to test for spatial dependency among the blood lead levels in children using the household geolocations. RESULTS BLL in children from Kabwe are spatially autocorrelated with a Moran's Index of 0.62 (p~\textless~0.001). We found distinct hotspots (mean 51.9~\textgreekmg/dL) in communities close to the old lead and zinc-mining site, lying on its western side. Whereas coldspots (mean 7~\textgreekmg/dL) where observed in areas distant to the mine and traced on the eastern side. This pattern suggests a possible association between observed BLL and distance from the abandoned lead and zinc mine, and prevailing winds. CONCLUSION Using geocoded data for households, we found clustering of childhood blood lead and identified distinct hotspot areas with high lead levels for Kabwe town. The geospatial approach used is especially valuable in resource-constrained settings like Zambia, where the precise identification of high risk locations allows for the initiation of targeted remedial and treatment programs.

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