Table III.

Elements of a Cumulative Risk Characterization

Characterization Element	Special Emphases for CRAs
Assessment goals	Clearly state the CRA goals, including the initiating factor/s (or impetus) for the assessment.
	Identify anticipated uses of the CRA (e.g., guiding consideration of alternate risk management actions).
Type of CRA	Identify whether the CRA is qualitative, semi-quantitative, or quantitative. (When the type of CRA is determined prior to identifying specific goals and risk management decisions, this element may be combined with the preceding one.)
	Ensure that the level of analysis matches the CRA type (e.g., screening vs. full risk) and is consistent throughout.
Exposures to combined stressors	Identify the population and geographic areas of interest.
	Describe the environmental conditions and exposure scenarios, considering the stressors, pathways, population characteristics, and additional factors that could affect exposures (i.e., exposure modifying factors) and health outcomes (i.e., effect measure modifiers including susceptibilities, vulnerabilities, buffers). Develop the population profile.
	Describe the models used to assess exposures, accounting for the time frames of interest (including any critical exposure windows), and considering interactions that can affect fate and transport.
Joint toxicity and health effects from combined stressors	Describe the data and models used to assess joint toxicity and effects from the relevant stressors considered (including effect measure modifiers), and provide context for the baseline health status of the population of interest.
	Provide estimates of the cumulative risk predicted from combined stressors across relevant exposure routes and durations, accounting for population-level characteristics.
Uncertainty characterization, sensitivity analysis	Examine the influences of study assumptions and limitations on the CRA results, such as the use of alternative toxicity values or different approaches for quantifying exposure levels for nonchemical stressors. Identify the strength of evidence for interactions (including toxicological) and for the relevance of those interactions to the population(s) of concern.
	Describe (either qualitatively or quantitatively) the quality of the data used to assess the relationships between the stressors (and their combinations) and the predicted health effects, including whether risks are suspected to vary among different populations. In addition to performing quantitative sensitivity analyses, this uncertainty characterization could discuss the influence of chemical or nonchemical stressors that may be difficult to quantify or that cannot be integrated into the main analysis due to limited data, but that should still be included as part of a qualitative judgment of potential hazard.