A framework for using epidemiological data for risk assessment.
Data on health effects from human exposure to chemicals provide the most direct information for risk assessment. Despite their clear relevance for risk assessment and despite the frequently made statements by regulatory bodies to use epidemiological data whenever deemed appropriate, they are not always optimally used. In this article, a framework for using epidemiological data in risk assessment is presented. Before using an epidemiologic study as the basis for risk assessment, its quality must be evaluated. The quality criteria for such a study strongly depends on the type of association between the chemical and health effect in terms of its specificity and latency period. The framework is built on the type of health effect under consideration, whether it is a specific or non-specific effect and time window of the effect, whether it is an acute, sub-acute or long-term effect. Specificity and latency are aspects that have a great impact on the choice of research design and quality criteria that must be met in order to produce reliable results appropriate for risk assessment purposes. Although expert judgement will always play an important role, the framework can help to assess if a set of epidemiological data are sufficiently reliable to serve as the basis for the derivation of health-based exposure limits. The limitations and suitability to use for risk assessment of epidemiologic studies is more likely to be the result of poor or insufficient exposure data than of poor or unreliable health effect information. It is concluded that the value of epidemiologic data not only depends on its intrinsic quality, but also on the type of health effects under consideration. In this respect, the specificity and latency play an important role.
Swaen
G M H
GM
Department of Epidemiology, Maastricht University, The Netherlands. g.swaen@epid.unimaas.nl
D003627:Data Interpretation, Statistical; D004812:Epidemiologic Methods; D006801:Humans; D011786:Quality Control; D012107:Research Design; D018570:Risk Assessment / Q000706:statistics & numerical data*