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The Contribution of Systematic Review and Meta-Analysis Methods to Human Health Risk Assessment: Neurobehavioral Effects of Manganese
Current methods of human health risk assessment may lack transparency in respect of identification, review, and synthesis of potentially relevant human and animal evidence. The nature, degree, and source of uncertainties are often unclear. This article aims to demonstrate the contribution that syste...
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Published in: | Human and ecological risk assessment 2008-11, Vol.14 (6), p.1250-1272 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Current methods of human health risk assessment may lack transparency in respect of identification, review, and synthesis of potentially relevant human and animal evidence. The nature, degree, and source of uncertainties are often unclear. This article aims to demonstrate the contribution that systematic review and meta-analysis methods can make to providing more structured, transparent, and systematic risk assessments. We focus on disparities between five risk assessments for neurobehavioral effects of manganese, and then illustrate advantages of a systematic approach. Fifty-five human epidemiological studies and 37 animal experiments were identified. Where appropriate, meta-analysis methods demonstrated consistent adverse effects associated with manganese exposure across species. In particular, there was reduced activity in subjects exposed to manganese, although exposed rats tended to be more active than controls. Limitations of exposure measurement and reporting restricted use of more quantitative methods of evidence synthesis. From a methodological viewpoint, we conclude that systematic review and meta-analysis methods can contribute to a more systematic and transparent human health risk assessment making more efficient use of available evidence, compared to current methods of risk assessment. More complex methods could encompass further differences between relevant studies and so further improve the risk assessment process. |
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ISSN: | 1080-7039 1549-7860 |
DOI: | 10.1080/10807030802494592 |