BackgroundBiomarkers are considered the method of choice for determining exposure to environmental contaminants and relating such exposures to health outcomes. However, the association between many biomarkers and outcome is not direct because of variability in sensitivity and susceptibility in the individual.ObjectivesWe explore the relationship between environmental exposures and health outcomes as mitigated by differential susceptibility in individuals or populations and address the question “Can biomarkers enable us to understand and quantify better the population burden of disease and health effects attributable to environmental exposures?”MethodsWe use a case–study approach to develop the thesis that biomarkers offer a pathway to disaggregation of health effects into specific, if multiple, risk factors. We offer the point of view that a series or array of biomarkers, including biomarkers of exposure, biomarkers of susceptibility, and biomarkers of effect, used in concert offer the best means by which to effect this disaggregation. We commence our discussion by developing the characteristics of an ideal biomarker, then give some examples of commonly used biomarkers to show the strengths and weaknesses of current usage. We follow this by more detailed case-study assessment outlining the state-of-the-science in specific cases. We complete our work with recommendations regarding the future use of biomarkers and areas for continued development.ConclusionsThe case studies provide examples of when and how biomarkers can be used to infer the source and magnitude of exposure among a set of competing sources and pathways. The answer to this question is chemical specific and relates to how well the biomarker matches the characteristics of an “ideal” biomarker–in particular ease of collection and persistence. The use of biomarkers in combination provides a better opportunity to disaggregate both source and pathway contributions.
This paper addresses interactions among foraging behavior, habitat preferences, site characteristics, and spatial distribution of contaminants in developing PCB exposure estimates for winter flounder at a hypothetical open water dredged material disposal site in the coastal waters of New York and New Jersey (NY-NJ). The implications of these interactions for human health risk estimates for local recreational anglers who fish for and eat flounder are described. The models implemented in this study include a spatial submodel to account for spatial and temporal characteristics of fish exposures and a probabilistic adaptation of the Gobas bioaccumulation model that accounts for temporal variation in concentrations of hydrophobic contaminants in sediment and water. We estimated the geographic distribution of a winter flounder subpopulation offshore of NY-NJ based on species biology and its vulnerability to local recreational fishing, the foraging area of individual fish, and their migration patterns. We incorporated these parameters and an estimate of differential attraction to a management site into a spatially explicit model to assess the range of exposures within the population. The output of this modeling effort, flounder PCB tissue concentrations, provided exposure point concentrations for an estimate of human health risk through ingestion of locally caught flounder. The risks obtained for the spatially nonexplicit case are as much as 1 order of magnitude higher than those obtained with explicit consideration of spatial and temporal characteristics of winter flounder foraging and seasonal migration. This practice of "defaulting" to extremely conservative estimates for exposure parameters in the face of uncertainty ill serves the decision-making process for management of contaminated sediments in general and specifically for disposal of dredged materials. Consideration of realistic spatial and temporal scales in food chain models can help support sediment management decisions by providing a quantitative expression of the confidence in risk estimates.
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