[Establishment of Non-Parametric Probabilistic Model for Evaluation of Chinese Dietary Exposure]
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OBJECTIVE: To establish a non-parametric probabilistic model for evaluation of Chinese dietary exposure and to improve the assessment accuracy while integrating into the global risk assessment on food safety. METHODS: Contamination data was from the national food contamination monitoring program during 2000 - 2006, including heavy metals, pesticides and mycotoxins, amounting to 135 contaminants with 499 commodities and 487 819 samples. Food consumption data was obtained from the national diet and nutrition survey conducted in 2002 with three consecutive days by 24-hour recall method, and 66 172 consumers were included. Monte Carlo simulation was applied to derive the intake distribution, and the uncertainty of each percentile was estimated using the Bootstrap sampling. RESULTS: Different non-parametric probabilistic models for dietary exposure evaluation on heavy metals, pesticides and some of the toxins were established for Chinese people, and intake distributions with 95% confidence intervals of these contaminants were estimated. Taking acephate as an example, the results of its model shows that, for the 7 - 10 year-old children, the median dietary exposure in urban and rural areas were 1.77 microg x kg(-1) x d(-1) and 2.48 microg x kg(-1) x d(-1) respectively, with a 95% confidence interval of (1.59 - 2.06) microg x kg(-1) x d(-1) and (2.33 - 2.80) microg x kg(-1) x d(-1) respectively. CONCLUSION: The non-parametric probabilistic model can quantify the variability and uncertainty of exposure assessment and improve the assessment accuracy.
JOUR
Sun, Jinfang
Liu, Pei
Chen, Bingwei
Chen, Qiguang
Yu, Xiaojin
Wang, Cannan
Li, Jingxin
2010
Zhonghua Yu Fang Yi Xue Za Zhi
44
3
195-9
2010/05/11
0253-9624 (Print) 0253-9624 (Linking)
589