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Development and application of a comparative risk assessment method for ranking chemical hazards in food.

Ying LiGuoxin LiangLei ZhangZhaoping LiuDajin YangJianwen LiGui-Ju SunPingping Zhou
Published in: Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment (2020)
The aim of this study was to develop a comparative risk assessment method to prioritise the public health risks posed by chemical hazards in food. Through a literature review, and in light of expert opinions, a bottom-up, semi-quantitative scoring method was applied to screen the ranking metrics and assign a score. In addition, a metrics system and a ranking model were constructed. The fuzzy comprehensive analysis model was used to assess typical chemical hazards in a specific food, as well as to rank risks in many foods. Data were collected from the National Food Surveillance System in China, the Food Consumption of Chinese Residents Database, government reports, public websites and databases of authoritative organisations. The comparative risk assessment method was applied to case studies on ranking chemical hazards in different kinds of food. According to application testing, the method truly reflects the overall risk and ranking of chemical hazards in food.
Keyphrases
  • human health
  • risk assessment
  • healthcare
  • public health
  • climate change
  • quality improvement
  • big data
  • deep learning
  • machine learning
  • drug induced