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  • 标题:Expert Review for GHS Classification of Chemicals on Health Effects
  • 本地全文:下载
  • 作者:Takeshi MORITA ; Kaoru MORIKAWA
  • 期刊名称:Industrial Health
  • 印刷版ISSN:0019-8366
  • 电子版ISSN:1880-8026
  • 出版年度:2011
  • 卷号:49
  • 期号:5
  • 页码:559-565
  • DOI:10.2486/indhealth.MS1267
  • 出版社:National Institute of Occupational Safety and Health
  • 摘要:Intoxication as a result of chemical accidents is a major issue in industrial health. The Globally Harmonized System of Classification and Labelling of Chemicals (GHS) provides a framework for hazard communication on chemicals using labelling or safety data sheets. The GHS will be expected to reduce the number of chemical accidents by communicating the hazards posed and prompting safety measures to be taken. One of the issues which may be a barrier to effective implementation of the GHS results from discrepancies in GHS classifications of chemicals across countries/regions. The main reasons are the differences in information sources used and in the expertise of people making the classification (Classifiers). The GHS requests expert judgment in a weight of evidence (WOE) approach in the application of the criteria of classification. A WOE approach is an assessment method that considers all available information bearing on the determination of toxicity. The quality and consistency of the data, study design, mechanism or mode of action, dose-effect relationships and biological relevance should be taken into account. Therefore, expert review should be necessary to classify chemicals accurately. However, the GHS does not provide any information on the required level of expertise of the Classifiers, definition of who qualifies as an expert, evaluation methods of WOE or data quality, and the timing of expert judgment and the need for updating/re-classification as new information becomes available. In this paper, key methods and issues in expert reviews are discussed. Examples of expert reviews and recommendations for harmonized classification are also presented.
  • 关键词:GHS;Expert review;Weight of evidence;Data quality;Classification;Health effects
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