الملخص
<p><b>OBJECTIVE</b>To develop the dietary exposure evaluation model software accredited of Chinese intellectual property rights and to verify the rationality and accuracy of the results from the probabilistic model in Chinese dietary exposure evaluation model software according to international standards.</p><p><b>METHODS</b>The software of SAS was used to build various evaluation model based on the data from Chinese dietary survey and the chemical compound in food surveillance and to design an operation interface. The results from probabilistic dietary exposure model for children 2 - 7 years old were compared with that from duplicate portion study of 2-7 years children dietary exposure in Jinhu, Jiangsu province in order to analyze the rationality of model. The results from probabilistic model of dietary exposure were compared with the results from @Risk software to verify the correction of the probabilistic model by using the same data of randomly selected 10 000 study subjects from national dietary survey. While, the mean drift was used as an internal index to illustrate the accuracy of the computation.</p><p><b>RESULTS</b>Chinese dietary exposure evaluation software was developed successfully. On the rationality, the results from probabilistic model were lower than that from the point estimation (e.g., cucumber: the result of point estimation of acephate was 4.78 microg x kg(-1) x d(-1), while the results of probabilistic model which was 0.39 microg x kg(-1) x d(-1)). Meanwhile the results from probabilistic model were higher than the results of duplicate portion study (on the P95, the result of probabilistic model of Pb exposure in children was 11.08 microg x kg(-1) x d(-1), while the results of duplicate portion study was 5.75 microg x kg(-1) x d(-1)). On accuracy, the results from @Risk and the probabilistic model were highly consistent (on the P95, the result of probabilistic assessment of acephate diet exposure was 4.27 microg x kg(-1) x d(-1), while the results of duplicate portion study was 4.24 microg x kg(-1) x d(-1)), and the mean drift was of random distribution, the drift region varied from 0.05% to 11.9%.</p><p><b>CONCLUSION</b>The results computed by the software of Chinese dietary exposure evaluation model are reliable and reasonable, which is a meaningful step to improve the dietary exposure evaluation technique in China.</p>
الموضوعات
Child , Child, Preschool , Humans , China , Consumer Product Safety , Diet , Models, Statistical , Software Design , Software Validationالملخص
<p><b>OBJECTIVE</b>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.</p><p><b>METHODS</b>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.</p><p><b>RESULTS</b>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.</p><p><b>CONCLUSION</b>The non-parametric probabilistic model can quantify the variability and uncertainty of exposure assessment and improve the assessment accuracy.</p>