Shapes and definitions of exposure-response curves: A comment on “A matrix for bridging the epidemiology and risk assessment gap”

Abstract A proposed matrix bridging between the results supplied by epidemiologists and those demanded by risk assessors proposes that a key piece of information sought by risk assessors is the shape of the exposure-response curve (e.g., linear vs. nonlinear, threshold vs. no threshold, etc.). This comment emphasizes that there are several different exposure-response curves, having different causal interpretations and risk management implications. Risk assessors and risk management decision makers and policy maker usually need to know how changes in exposures would change disease risks (given assumptions about levels of other variables). Epidemiologists typically provide conditional expected observed values of response variables for different observed levels of exposures, i.e., regression relationships. These are two different curves and may have quite different shapes. Current widespread epidemiological practice conflates them. Being clear about what is needed for risk assessment (usually the former) and what has been produced by epidemiologists (usually the latter) can help to identify mismatches and to build more useful bridges between these communities.