Polycyclic aromatic hydrocarbons in the Chinese diet: contamination characteristics, indicator screening, and health risk assessment.

Polycyclic aromatics hydrocarbons (PAHs) are ubiquitous in foods and environment and possess carcinogenic and mutagenic potential. Foods are the main source of exposure to PAHs in the general population. In this study, we determined the concentrations of 16 European Union priority PAHs in 1,564 foodstuffs acquired from nine provinces and commonly consumed by the Chinese population. The most predominant PAH was chrysene (16.7%), followed by benz[a]anthracene (12.4%) and benzo[b]fluoranthene (11.7%). Edible vegetable oils (17.89 µg/kg) and fruits (1.97 µg/kg) had the highest and lowest concentrations of total PAHs, respectively. Suitable indicators of PAH contamination in foods were assessed based on the occurrence of other PAHs in samples negative for benzo[a]pyrene and the correlation for the PAHs and their combinations. According to our results, PAH4 was a suitable indicator, better than PAH8 and benzo[a]pyrene alone. PAH exposure in the Chinese population was estimated by combining contamination data with national individual food consumption data, based on the middle bound approach. The overall average dietary exposures for BaP and PAH4 were 3.08 and 17.61 ng/kg bw/day, respectively. The major contributors to the total dietary exposure of PAHs were cereals (39%), edible vegetable oils (28%), and vegetables (20%). We used the margin of exposure (MOE) approach to assess health risk for consumers. MOEs of the mean estimated dietary exposures were >10,000, indicating a low concern for the health of the general population and of consumers of smoked, grilled, or barbecued foods. For high consumers and children, the MOEs were <10,000, indicating potential concerns.

Analysis of furan and its major furan derivatives in coffee products on the Chinese market using HS-GC-MS and the estimated exposure of the Chinese population.

The current study analysed concentrations of furan and its derivatives in coffee products commercially available in China based on an improved headspace gas chromatography-mass spectrometry (HS-GC-MS) method and estimated health risks. A total of 101 samples of coffee products on the Chinese market was analysed. Furan (98%, ND-6569 µg/kg) and 2-methylfuran (100%, 2-29639 µg/kg) were the compounds with the highest concentrations and detection rates in coffee products. The mean dietary exposure of Chinese consumers to furan and the sum of furan, 2-methylfuran and 3-methylfuran in coffee products was 0.09 and 0.46 µg/kg bw/day, respectively. For the neoplastic effects of furan, the margin of exposure (MOE) was 14,556 for the mean dietary exposure of consumers. For the non-neoplastic effects of furan, MOEs were 711 and 139 for furan and the sum of furan, 2-methylfuran and 3-methylfuran, respectively. Overall, a health concern is indicated for coffee consumers with MOEs below 10000.

A Bayesian Approach to Real-Time Monitoring and Forecasting of Chinese Foodborne Diseases.

Foodborne diseases have a big impact on public health and are often underreported. This is because a lot of patients delay treatment when they suffer from foodborne diseases. In Hunan Province (China), a total of 21,226 confirmed foodborne disease cases were reported from 1 March 2015 to 28 February 2016 by the Foodborne Surveillance Database (FSD) of the China National Centre for Food Safety Risk Assessment (CFSA). The purpose of this study was to make use of the daily number of visiting patients to forecast the daily true number of patients. Our main contribution is that we take the reporting delays into consideration and propose a Bayesian hierarchical model for this forecast problem. The data shows that there were 21,226 confirmed cases reported among 21,866 visiting patients, a proportion as high as 97%. Given this observation, the Bayesian hierarchical model was established to predict the daily true number of patients using the number of visiting patients. We propose several scoring rules to assess the performance of different nowcasting procedures. We conclude that Bayesian nowcasting with consideration of right truncation of the reporting delays has a good performance for short-term forecasting, and could effectively predict the epidemic trends of foodborne diseases. Meanwhile, this approach could provide a methodological basis for future foodborne disease monitoring and control strategies, which are crucial for public health.