Multidisciplinary perspectives on cumulative impact assessment for vulnerable communities: expert elicitation using a Delphi method.

Prompted by a series of executive orders, the U.S. Environmental Protection Agency (USEPA) is promoting cumulative impact assessment (CIA) to integrate numerous factors that have the potential to impact community health, which include nonchemical stressors such as socioeconomic conditions, pre-existing health conditions, and many others that historically have not been addressed by USEPA's chemical risk assessment paradigm. Understanding the cumulative impact of all stressors on responses to environmental exposures requires multidisciplinary input from social scientists, economists, and others not traditionally involved in chemical risk assessments. To gather input from these disciplines, a group of 13 independent experts with perspectives on CIA as a social scientist, economist, public health expert, or decision analyst participated in a virtual workshop to obtain their perspectives regarding key aspects of CIA. The independent experts, who have decades of experience studying cumulative impacts in vulnerable population groups and environmental justice (EJ), responded anonymously to charge questions specific to their expertise and then were asked to review and comment on other's responses within and outside their discipline. The questions and responses were organized by the authors into general topics (e.g., screening tools and indexes, role of nonchemical stressors in cumulative impacts, uncertainties), and discussions across and within the four disciplines were summarized by the authors. The expert's opinions were used to frame a set of future research objectives to advance the development of CIA and improve its use in the EJ context. Specifically, the experts' recommendations addressed the need for regulatory impact analysis, the appropriate use of screening tool information and indexes, the role and measurement of nonchemical stressors, relevance of a risk modifier approach to CIA, inclusion of uncertainty and causality, metrics to assess effectiveness of interventions, and methods for community communication.