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      The burden of chronic mercury intoxication in artisanal small-scale gold mining in Zimbabwe: data availability and preliminary estimates

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          Abstract

          Background

          Artisanal small-scale gold mining (ASGM) is a poverty-driven activity practiced in over 70 countries worldwide. Zimbabwe is amongst the top ten countries using large quantities of mercury to extract gold from ore. This analysis was performed to check data availability and derive a preliminary estimate of disability-adjusted life years (DALYs) due to mercury use in ASGM in Zimbabwe.

          Methods

          Cases of chronic mercury intoxication were identified following an algorithm using mercury-related health effects and mercury in human specimens. The sample prevalence amongst miners and controls (surveyed by the United Nations Industrial Development Organization in 2004 and the University of Munich in 2006) was determined and extrapolated to the entire population of Zimbabwe. Further epidemiological and demographic data were taken from the literature and missing data modeled with DisMod II to quantify DALYs using the methods from the Global Burden of Disease (GBD) 2004 update published by the World Health Organization (WHO). While there was no disability weight (DW) available indicating the relative disease severity of chronic mercury intoxication, the DW of a comparable disease was assigned by following the criteria 1) chronic condition, 2) triggered by a substance, and 3) causing similar health symptoms.

          Results

          Miners showed a sample prevalence of 72% while controls showed no cases of chronic mercury intoxication. Data availability is very limited why it was necessary to model data and make assumptions about the number of exposed population, the definition of chronic mercury intoxication, DW, and epidemiology. If these assumptions hold, the extrapolation would result in around 95,400 DALYs in Zimbabwe’s total population in 2004.

          Conclusions

          This analysis provides a preliminary quantification of the mercury-related health burden from ASGM based on the limited data available. If the determined assumptions hold, chronic mercury intoxication is likely to have been one of the top 20 hazards for population health in Zimbabwe in 2004 when comparing with more than 130 categories of diseases and injuries quantified in the WHO’s GBD 2004 update. Improving data quality would allow more accurate estimates. However, the results highlight the need to reduce a burden which could be entirely avoided.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1476-069X-13-111) contains supplementary material, which is available to authorized users.

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          Most cited references150

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          A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

          The Lancet, 380(9859), 2224-2260
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            The global burden for disease: A comprehensive assessment of mortality and disability from diseases, injuries and risk factors in 1990 and projected to 2020

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              A generic model for the assessment of disease epidemiology: the computational basis of DisMod II

              Epidemiology as an empirical science has developed sophisticated methods to measure the causes and patterns of disease in populations. Nevertheless, for many diseases in many countries only partial data are available. When the partial data are insufficient, but data collection is not an option, it is possible to supplement the data by exploiting the causal relations between the various variables that describe a disease process. We present a simple generic disease model with incidence, one prevalent state, and case fatality and remission. We derive a set of equations that describes this disease process and allows calculation of the complete epidemiology of a disease given a minimum of three input variables. We give the example of asthma with age-specific prevalence, remission, and mortality as inputs. Outputs are incidence and case fatality, among others. The set of equations is embedded in a software package called 'DisMod II', which is made available to the public domain by the World Health Organization.
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                Author and article information

                Contributors
                nadine.steckling@uni-bielefeld.de
                stephan.boeseoreilly@med.uni-muenchen.de
                paulo.pinheiro@uni-bielefeld.de
                dietrich.plass@uba.de
                dennis.shoko@gmail.com
                drasch@allacher-apotheke.de
                l.bernaudat@unido.org
                uwe.siebert@umit.at
                claudia.hornberg@uni-bielefeld.de
                Journal
                Environ Health
                Environ Health
                Environmental Health
                BioMed Central (London )
                1476-069X
                13 December 2014
                13 December 2014
                2014
                : 13
                : 1
                : 111
                Affiliations
                [ ]Department Environment & Health, Bielefeld University, School of Public Health, Universitätsstraße 25, D-33615 Bielefeld, Germany
                [ ]University Hospital Munich, Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, WHO Collaborating Centre for Occupational Health, Workgroup Paediatric Environmental Epidemiology, Ziemssenstr. 1, D-80336 Munich, Germany
                [ ]UMIT - University for Health Sciences, Medical Informatics and Technology, Department of Public Health and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, Eduard Wallnoefer Center I, A-6060 Hall i.T, Austria
                [ ]Bielefeld University, Faculty of Educational Sciences, Universitätsstraße 25, D-33615 Bielefeld, Germany
                [ ]Federal Environment Agency, Section Exposure Assessment and Environmental Health Indicators, Corrensplatz 1, D-14195 Berlin, Germany
                [ ]Tailjet Consultancy Services, 4 Tor Road, Vainona, Borrowdale Harare, Zimbabwe
                [ ]Institute of Forensic Medicine, Department of Forensic Toxicology, University of Munich - LMU, Nussbaumstr. 26, D-80336 Munich, Germany
                [ ]United Nations Industrial Development Organization, Vienna International Centre, P.O. Box 300, A-1400 Vienna, Austria
                [ ]Harvard Medical School, Massachusetts General Hospital, Institute for Technology Assessment and Department of Radiology, Boston, USA
                [ ]Harvard School of Public Health, Department of Health Policy and Management, Center for Health Decision Science, Boston, USA
                Article
                818
                10.1186/1476-069X-13-111
                4290131
                25495641
                2b2c8c7d-7475-48e5-9593-02732d863bfc
                © Steckling et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 11 March 2014
                : 4 December 2014
                Categories
                Research
                Custom metadata
                © The Author(s) 2014

                Public health
                environmental burden of disease,disability-adjusted life years,artisanal small-scale gold mining,mercury,occupational health,zimbabwe

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