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An exposure-response curve for copper excess and deficiency.

There is a need to define exposure-response curves for both Cu excess and deficiency to assist in determining the acceptable range of oral intake. A comprehensive database has been developed where different health outcomes from elevated and deficient Cu intakes were assigned ordinal severity scores to create common measures of response. A generalized linear model for ordinal data was used to estimate the probability of response associated with dose, duration and severity. The model can account for differences in animal species, the exposure medium (drinking water and feed), age, sex, and solubility. Using this model, an optimal intake level of 2.6 mg Cu/d was determined. This value is higher than the current U.S. recommended dietary intake (RDI; 0.9 mg/d) that protects against toxicity from Cu deficiency. It is also lower than the current tolerable upper intake level (UL; 10 mg/d) that protects against toxicity from Cu excess. Compared to traditional risk assessment approaches, categorical regression can provide risk managers with more information, including a range of intake levels associated with different levels of severity and probability of response. To weigh the relative harms of deficiency and excess, it is important that the results be interpreted along with the available information on the nature of the responses that were assigned to each severity score.

Authors

  • Chambers, Andrea, Chambers A, Institute of Population Health, McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Ontario, Canada. acham035@uottawa.ca

  • Krewski, Daniel, Krewski D,

  • Birkett, Nicholas, Birkett N,

  • Plunkett, Laura, Plunkett L,

  • Hertzberg, Richard, Hertzberg R,

  • Danzeisen, Ruth, Danzeisen R,

  • Aggett, Peter J, Aggett PJ,

  • Starr, Thomas B, Starr TB,

  • Baker, Scott, Baker S,

  • Dourson, Michael, Dourson M,

  • Jones, Paul, Jones P,

  • Keen, Carl L, Keen CL,

  • Meek, Bette, Meek B,

  • Schoeny, Rita, Schoeny R,

  • Slob, Wout, Slob W,

YEAR OF PUBLICATION: 2010
SOURCE: J Toxicol Environ Health B Crit Rev. 2010 Oct;13(7-8):546-78. doi: 10.1080/10937404.2010.538657.
JOURNAL TITLE ABBREVIATION: J Toxicol Environ Health B Crit Rev
JOURNAL TITLE: Journal of toxicology and environmental health. Part B, Critical reviews
ISSN: 1521-6950 (Electronic) 1093-7404 (Linking)
VOLUME: 13
ISSUE: 7-8
PAGES: 546-78
PLACE OF PUBLICATION: England
ABSTRACT:
There is a need to define exposure-response curves for both Cu excess and deficiency to assist in determining the acceptable range of oral intake. A comprehensive database has been developed where different health outcomes from elevated and deficient Cu intakes were assigned ordinal severity scores to create common measures of response. A generalized linear model for ordinal data was used to estimate the probability of response associated with dose, duration and severity. The model can account for differences in animal species, the exposure medium (drinking water and feed), age, sex, and solubility. Using this model, an optimal intake level of 2.6 mg Cu/d was determined. This value is higher than the current U.S. recommended dietary intake (RDI; 0.9 mg/d) that protects against toxicity from Cu deficiency. It is also lower than the current tolerable upper intake level (UL; 10 mg/d) that protects against toxicity from Cu excess. Compared to traditional risk assessment approaches, categorical regression can provide risk managers with more information, including a range of intake levels associated with different levels of severity and probability of response. To weigh the relative harms of deficiency and excess, it is important that the results be interpreted along with the available information on the nature of the responses that were assigned to each severity score.
LANGUAGE: eng
DATE OF PUBLICATION: 2010 Oct
DATE COMPLETED: 20110114
DATE REVISED: 20201216
MESH DATE: 2011/01/15 06:00
EDAT: 2010/12/21 06:00
STATUS: MEDLINE
PUBLICATION STATUS: ppublish
LOCATION IDENTIFIER: 10.1080/10937404.2010.538657 [doi]
OWNER: NLM

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Daniel Krewski

Chief Risk Scientist

Dr. Daniel Krewski is Chief Risk Scientist and co-founder of Risk Sciences International (RSI), a firm established in 2006 to bring evidence-based, multidisciplinary expertise to the challenge of understanding, managing, and communicating risk. As RSI’s inaugural CEO and long-time scientific...
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