Low-Dose Arsenic: In Search of a Risk Threshold
Low-Dose Arsenic: In Search of a Risk Threshold
Meanwhile the debate over low-dose health risks from arsenic will likely continue on two fronts: how to apply mechanistic findings from animal and in vitro research to human responses, and how to address fundamental uncertainties in the human data.
A key question is whether the recent epidemiological literature supports estimates of cancer risk predicted from linear dose–response models. Dozens of studies over the last 15 years have investigated human cancer risk from arsenic exposure at sites around the world. According to a 2011 review published by Herman Gibb, president of environmental consulting firm Tetra Tech Sciences, these studies provide conflicting evidence, in part because the sample sizes needed to quantify risks at drinking water doses less than 100 ppb are larger than what's ordinarily achievable.
Steinmaus argues that the high-dose epidemiology data may ultimately be most suitable for risk assessment, "but when you extrapolate down from those doses, the risks are huge." He adds, "This raises the question of whether linear extrapolations are suitable, and herein lies the big controversy."
Continued Debate
Meanwhile the debate over low-dose health risks from arsenic will likely continue on two fronts: how to apply mechanistic findings from animal and in vitro research to human responses, and how to address fundamental uncertainties in the human data.
A key question is whether the recent epidemiological literature supports estimates of cancer risk predicted from linear dose–response models. Dozens of studies over the last 15 years have investigated human cancer risk from arsenic exposure at sites around the world. According to a 2011 review published by Herman Gibb, president of environmental consulting firm Tetra Tech Sciences, these studies provide conflicting evidence, in part because the sample sizes needed to quantify risks at drinking water doses less than 100 ppb are larger than what's ordinarily achievable.
Steinmaus argues that the high-dose epidemiology data may ultimately be most suitable for risk assessment, "but when you extrapolate down from those doses, the risks are huge." He adds, "This raises the question of whether linear extrapolations are suitable, and herein lies the big controversy."
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