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Chemical exposures are an important environmental health concern. The general population can be exposed to chemicals in food and consumer products, cleaning supplies, industrial and manufacturing activities, or agricultural applications on a regular basis. Conducting systematic reviews of these exposures can be challenging due to the sheer number of chemicals as well as the lack of available data in many contexts. Only a small percentage of chemicals will have undergone toxicologic evaluation, human exposure characterization, and epidemiologic analysis.
Systematic evidence maps (SEMs) provide a comprehensive summary of the characteristics and availability of data. While the objective is not to synthesize evidence, SEMs can help reveal gaps in the literature and formulate research questions. By using a systematic process to document what is available, SEMs can aid in decision-making in various contexts, both regulatory and non-regulatory. For example, the U.S. Environmental Protection Agency can use SEMs to identify data gaps, understand the resources that would be needed for a full assessment, or prioritize key features for evaluation.
This presentation will illustrate how SEM methods were applied to a broad group of over 150 data poor per- and poly-fluoroalkyl substances (PFAS) to narrow search results and identify relevant epidemiology studies that support human health assessment. Starting with a literature search resulting in over 10,000 studies, different levels of screening, including the application of machine learning, were employed to identify approximately 90 epidemiology studies that could then undergo detailed study evaluation and data extraction. In addition, visualization techniques will be demonstrated to show how to effectively explore datasets and how results can be presented to support different research or assessment needs.