Roslyn Cheasley1, C Peter Keller1, Eleanor Setton2. 1. Department of Geography, University of Victoria, PO Box 3060, Ring Road, Victoria, BC, V8N 1V3, Canada. 2. Department of Geography, University of Victoria, PO Box 3060, Ring Road, Victoria, BC, V8N 1V3, Canada. elsetton@uvic.ca.
Abstract
OBJECTIVES: To explore differences in urban versus rural lifetime excess risk of cancer from five specific contaminants found in food and beverages. METHODS: Probable contaminant intake is estimated using Monte Carlo simulations of contaminant concentrations in combination with dietary patterns. Contaminant concentrations for arsenic, benzene, lead, polychlorinated biphenyls (PCBs) and tetrachloroethylene (PERC) were derived from government dietary studies. The dietary patterns of 34 944 Canadians from 10 provinces were available from Health Canada's Canadian Community Health Survey, Cycle 2.2, Nutrition (2004). Associated lifetime excess cancer risk (LECR) was subsequently calculated from the results of the simulations. RESULTS: In the calculation of LECR from food and beverages for the five selected substances, two (lead and PERC) were shown to have excess risk below 10 per million; whereas for the remaining three (arsenic, benzene and PCBs), it was shown that at least 50% of the population were above 10 per million excess cancers. Arsenic residues, ingested via rice and rice cereal, registered the greatest disparity between urban and rural intake, with LECR per million levels well above 1000 per million at the upper bound. The majority of PCBs ingestion comes from meat, with values slightly higher for urban populations and LECR per million estimates between 50 and 400. Drinking water is the primary contributor of benzene intake in both urban and rural populations, with LECR per million estimates of 35 extra cancers in the top 1% of sampled population. CONCLUSION: Overall, there are few disparities between urban and rural lifetime excess cancer risk from contaminants found in food and beverages. Estimates could be improved with more complete Canadian dietary intake and concentration data in support of detailed exposure assessments in estimating LECR.
OBJECTIVES: To explore differences in urban versus rural lifetime excess risk of cancer from five specific contaminants found in food and beverages. METHODS: Probable contaminant intake is estimated using Monte Carlo simulations of contaminant concentrations in combination with dietary patterns. Contaminant concentrations for arsenic, benzene, lead, polychlorinated biphenyls (PCBs) and tetrachloroethylene (PERC) were derived from government dietary studies. The dietary patterns of 34 944 Canadians from 10 provinces were available from Health Canada's Canadian Community Health Survey, Cycle 2.2, Nutrition (2004). Associated lifetime excess cancer risk (LECR) was subsequently calculated from the results of the simulations. RESULTS: In the calculation of LECR from food and beverages for the five selected substances, two (lead and PERC) were shown to have excess risk below 10 per million; whereas for the remaining three (arsenic, benzene and PCBs), it was shown that at least 50% of the population were above 10 per million excess cancers. Arsenic residues, ingested via rice and rice cereal, registered the greatest disparity between urban and rural intake, with LECR per million levels well above 1000 per million at the upper bound. The majority of PCBs ingestion comes from meat, with values slightly higher for urban populations and LECR per million estimates between 50 and 400. Drinking water is the primary contributor of benzene intake in both urban and rural populations, with LECR per million estimates of 35 extra cancers in the top 1% of sampled population. CONCLUSION: Overall, there are few disparities between urban and rural lifetime excess cancer risk from contaminants found in food and beverages. Estimates could be improved with more complete Canadian dietary intake and concentration data in support of detailed exposure assessments in estimating LECR.
Authors: Linda Sharp; David Donnelly; Avril Hegarty; Anne-Elie Carsin; Sandra Deady; Neil McCluskey; Anna Gavin; Harry Comber Journal: J Urban Health Date: 2014-06 Impact factor: 3.671
Authors: Noelle Liao; Edmund Seto; Brenda Eskenazi; May Wang; Yan Li; Jenna Hua Journal: Int J Environ Res Public Health Date: 2018-10-08 Impact factor: 3.390