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Informing environmental health policy on complex mixtures: What we need vs. what we (currently) get from machine learning methods
Citation:
Rappazzo, K., A. Krajewski, J. Stingone, J. Bobb, A. Keil, AND K. Thayer. Informing environmental health policy on complex mixtures: What we need vs. what we (currently) get from machine learning methods. International Society of Exposure Science Annual Meeting 2021, NA, NC, August 30 - September 02, 2021.
Impact/Purpose:
The purpose of this symposium is to connect the complex methods being used by academic researchers with the needs of environmental health policymakers. The speakers will provide an overview of methods currently being used in exposure science and epidemiology to analyze complex mixtures and a synopsis of what is needed in order to consider these research studies in creating environmental health policy.
Description:
While individuals are exposed to multiple, simultaneous exposures from their environment, the effects of these complex exposures are difficult to quantify. As a result, environmental health policies have often focused on individual exposures. In recent years, statistical methods for data reduction and assessment of complex environmental exposures on health outcomes has become a rapidly advancing area of research. Machine learning methods (Bayesian Kernel Machine Regression) and estimating algorithms (G computation) have become favored methods for handling big data and analyzing complex environmental mixtures in epidemiological studies, including in systematic review methodology. These methods are powerful when utilized in the right context and provide meaningful findings that advance our understanding of how complex mixtures from environmental exposures impact human health. Studies utilizing these methods can be used to facilitate health assessments with respect to identifying environmental epidemiology studies and summarizing information to aid with policy decisions. However, a careful understanding of underlying workings of these approaches, including clearly defining assumptions and limitations of the methods, and appropriate interpretations, are needed in research practice to be considered for incorporation in health assessments and public health policy. We propose this symposium in order to connect the complex methods being used by academic researchers with the needs of environmental health policymakers. The speakers will provide an overview of methods currently being used in exposure science and epidemiology to analyze complex mixtures and a synopsis of what is needed in order to consider these research studies in creating environmental health policy. The speaker presentations will be followed by a round table discussion of the advantages and disadvantages of these methods in environmental epidemiological research and policy. The views expressed in this symposium are those of the authors and do not necessarily reflect the views or policies of the US EPA.