Human health risk assessments provide the basis for public health decision-making and chemical regulation in the United States. Three evidence streams generally support the development of human health risk assessments - epidemiology, toxicology, and mechanistic information. Epidemiologic studies are generally the preferred evidence stream for assessing causal relationships during hazard identification. However, the available studies may be limited in scope, subject to bias, or otherwise inadequate to inform causal inferences. In addition, there are challenges in assessing coherence, validity, and reliability during synthesis of individual epidemiological studies with different designs, which in turn affects conclusions on causation.
Triangulation aims to address the challenge of synthesizing evidence from diverse studies with distinct sources of bias. Bias is a systematic error that leads to inaccurate study results. Tools for assessing risk of bias provide a structured list of questions for systematic consideration of different domains (such as confounding, selective reporting, and conflict of interest). These tools also provide a structured framework for identifying potential sources of bias and informing judgments on individual studies. The National Academies of Sciences, Engineering, and Medicine convened a workshop to understand and explore triangulation and opportunities to use the practice to enhance the EPA's human health assessments. The workshop was held virtually on May 9 and 11, 2022. This publication summarizes the key presentations and discussions conducted during the workshop.
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