Objective:The Delphi method was used to propose health effect evaluation indicators to assess foods for special medical purposes(FSMPs).This lays the foundation for the formation of a big data model for human health t...Objective:The Delphi method was used to propose health effect evaluation indicators to assess foods for special medical purposes(FSMPs).This lays the foundation for the formation of a big data model for human health testing,as well as a big data platform for the health and safety evaluation of special medical foods.Methods:The Delphi method was used to conduct two rounds of expert consultation on the constructed FSMP health effect evaluation indicators.Results:Ten major items were identified after two rounds of expert consultation.Among these,there were 10 primary entries,32 secondary entries,50 tertiary entries,and 28 quaternary entries.Conclusion:The complete list of evaluation indicators contains 10 entries,which can comprehensively and systematically monitor adverse reactions to the use of FSMPs.The present findings lay the foundation for a big data platform to evaluate the health and safety of special foods.展开更多
基金This research was supported by the National Key Research and Development Program of China(2019YFC1606400).
文摘Objective:The Delphi method was used to propose health effect evaluation indicators to assess foods for special medical purposes(FSMPs).This lays the foundation for the formation of a big data model for human health testing,as well as a big data platform for the health and safety evaluation of special medical foods.Methods:The Delphi method was used to conduct two rounds of expert consultation on the constructed FSMP health effect evaluation indicators.Results:Ten major items were identified after two rounds of expert consultation.Among these,there were 10 primary entries,32 secondary entries,50 tertiary entries,and 28 quaternary entries.Conclusion:The complete list of evaluation indicators contains 10 entries,which can comprehensively and systematically monitor adverse reactions to the use of FSMPs.The present findings lay the foundation for a big data platform to evaluate the health and safety of special foods.
