Conducting evaluations of evidence that are transparent, timely and can lead to health-protective actions

ENVIRONMENTAL HEALTH(2022)

引用 0|浏览15
暂无评分
摘要
Background In February 2021, over one hundred scientists and policy experts participated in a web-based Workshop to discuss the ways that divergent evaluations of evidence and scientific uncertainties are used to delay timely protection of human health and the environment from exposures to hazardous agents. The Workshop arose from a previous workshop organized by the European Environment Agency (EEA) in 2008 and which also drew on case studies from the EEA reports on ‘Late Lessons from Early Warnings’ (2001, 2013). These reports documented dozens of hazardous agents including many chemicals, for which risk reduction measures were delayed for decades after scientists and others had issued early and later warnings about the harm likely to be caused by those agents. Results Workshop participants used recent case studies including Perfluorooctanoic acid (PFOA), Extremely Low Frequency – Electrical Magnetic Fields (ELF-EMF fields), glyphosate, and Bisphenol A (BPA) to explore myriad reasons for divergent outcomes of evaluations, which has led to delayed and inadequate protection of the public’s health. Strategies to overcome these barriers must, therefore, at a minimum include approaches that 1) Make better use of existing data and information, 2) Ensure timeliness, 3) Increase transparency, consistency and minimize bias in evidence evaluations, and 4) Minimize the influence of financial conflicts of interest. Conclusion The recommendations should enhance the production of “actionable evidence,” that is, reliable evaluations of the scientific evidence to support timely actions to protect health and environments from exposures to hazardous agents. The recommendations are applicable to policy and regulatory settings at the local, state, federal and international levels.
更多
查看译文
关键词
Conflicts of interest,Industry sponsorship,Environmental justice,Cumulative impacts,Non-chemical stressors,Precautionary principle,Risk of bias,Systematic review,Transparency
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要