Challenges in Standardizing Exposure Assessment Studies

Dear Colleagues,

It is well known that food may trigger various health issues mainly caused by chemical, microbial or physical hazards. To understand the consequences of consuming contaminated food, one accepted approach is to perform exposure assessment studies combining data from two main sources: consumption studies and food analyses. Despite a vast number of publications covering this matter, there are still some doubts about standardizing the approach and enable benchmarking throughout different countries, demographic characteristics, foods and contaminants.

In this Special issue, we encourage authors to submit original research manuscripts or reviews related, but not limited, to standardizing the following topics: consumption studies, predictive models, Monte Carlo analysis, measuring the magnitude, frequency and the duration of exposure, food analysis, food sampling, dietary habits, food safety hazards, risk–benefit food studies, and exposure assessments models and approaches.

Prof. Dr. Ilija Djekic
Dr. Božidar Udovički
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Standards is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• exposure assessment
• food contaminants
• food safety hazards
• dietary patterns
• monte carlo simulation
• predictive modeling
• exposed population
• magnitude, frequency and duration of exposure