Given Moonga1, Moses N Chisola2, Ursula Berger3, Dennis Nowak4, John Yabe5, Hokuto Nakata6, Shouta Nakayama6, Mayumi Ishizuka6, Stephan Bose-O'Reilly7. 1. Institute and Clinic for Occupational-, Social- and Environmental Medicine, LMU University Hospital Munich, Ziemssenstr. 1, D-80336, Munich, Germany; CIH(LMU) Center for International Health, LMU University Hospital, Munich, Germany; Department of Epidemiology and Biostatistics, University of Zambia, Lusaka, Zambia; Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT (Private University for Health Sciences, Medical Informatics and Technology), Hall i.T, Austria. Electronic address: Given.Moonga@lrz.uni-muenchen.de. 2. Department of Geography and Environmental Studies, University of Zambia, Lusaka, Zambia. 3. Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilian University Munich, Munich, Germany. 4. Institute and Clinic for Occupational-, Social- and Environmental Medicine, LMU University Hospital Munich, Ziemssenstr. 1, D-80336, Munich, Germany. 5. School of Veterinary Medicine, University of Zambia, Lusaka, Zambia. 6. Laboratory of Toxicology, Department of Environmental Veterinary Sciences, Faculty of Veterinary Medicine, Hokkaido University, Sapporo, Japan. 7. Institute and Clinic for Occupational-, Social- and Environmental Medicine, LMU University Hospital Munich, Ziemssenstr. 1, D-80336, Munich, Germany; Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT (Private University for Health Sciences, Medical Informatics and Technology), Hall i.T, Austria; University Children's Hospital Regensburg (KUNO-Clinics), University of Regensburg, Clinic St. Hedwig, Regensburg, Germany.
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 < 0.001). We found distinct hotspots (mean 51.9 μg/dL) in communities close to the old lead and zinc-mining site, lying on its western side. Whereas coldspots (mean 7 μg/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.
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 < 0.001). We found distinct hotspots (mean 51.9 μg/dL) in communities close to the old lead and zinc-mining site, lying on its western side. Whereas coldspots (mean 7 μg/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.
Authors: Jens Bertram; Christian Ramolla; André Esser; Thomas Schettgen; Nina Fohn; Thomas Kraus Journal: Int J Environ Res Public Health Date: 2022-05-17 Impact factor: 4.614