van der Fels-Klerx H.J.,Wageningen University |
Edwards S.G.,Harper Adams University College |
Kennedy M.C.,UK Environment Agency |
O'Hagan S.,PepsiCo |
And 4 more authors.
Food and Chemical Toxicology | Year: 2014
In order to ensure the food safety, risk managers may implement measures to reduce human exposure to contaminants via food consumption. The evaluation of the effect of a measure is often an overlooked step in risk analysis process. The aim of this study was to develop a systematic approach for determining the effectiveness of mitigation measures to reduce dietary exposure to chemical contaminants. Based on expert opinion, a general framework for evaluation of the effectiveness of measures to reduce human exposure to food contaminants was developed. The general outline was refined by application to three different cases: 1) methyl mercury in fish and fish products, 2) deoxynivalenol in cereal grains, and 3) furan in heated products. It was found that many uncertainties and natural variations exist, which make it difficult to assess the impact of the mitigation measure. Whenever possible, quantitative methods should be used to describe the current variation and uncertainty. Additional data should be collected to cover natural variability and reduce uncertainty. For the time being, it is always better for the risk manager to have access to all available information, including an assessment of uncertainty; however, the proposed methodology provides a conceptual framework for addressing these systematically. © 2014 The Authors.
Ross J.,Risksciences.net LLC |
Driver J.,Risksciences.net LLC |
Lunchick C.,Bayer Crop Science Human Safety |
O'Mahony C.,Trinity Technology and Enterprise Campus
Outlooks on Pest Management | Year: 2015
Any quantitative understanding of human risk from exposure to pesticides requires knowledge of both hazard (the intrinsic ability of a pesticide to cause harm) and exposure (absorbed dose), i.e., risk is directly proportional to the product of hazard and exposure. Thus, regardless of potential high hazard, risk may be insignificant if exposure is very low, and exposure-driven risk assessment is increasingly being recognized as being the best path forward for the protection of human health. In fact, regulatory agencies did not start doing quantitative risk assessments for pesticides using endpoints other than lethality until the 1970s in part because the analytical tools to sensitively measure exposure were lacking. Quantifying exposure to pesticides required analytical methods such as gas chromatography and liquid chromatography that weren?t commercially available until the mid-1960s to early 1970s, respectively. With the advent of quadrapole mass spectroscopy in the early 1970s the ability to quantify sub milligram per kilogram bodyweight exposures to a wide variety of pesticides with confidence became commonplace. Analytical capability has continued to improve, and it is now possible to measure exposures in the nanogram and sometimes pictogram per kilogram range. As our quantitative knowledge of human exposure matured, it was desirable to extrapolate the knowledge from one chemical that had been measured to others that had not. Indeed, by the early 1980s it became evident that handler exposure to conventional pesticides was generic and not chemical specific. Part of the driving factor to do this modeling was that definitive exposure measurements for one chemical under one set of conditions was costly (>?100,000) and time consuming (months), and the combinations and permutations of exposure scenarios and pesticides are staggering. Models allow us to estimate the exposure to a new active substance or rank exposure of one pesticide to others used in similar conditions. The objective of this paper is to present a brief overview of the range of human exposure models that are available, and the route or pathway of exposure for which they estimate dose with the hope that it provides an appreciation of the basic approaches, chronology and effort expended in developing them. © 2015 Research Information Ltd. All rights reserved.
Oldring P.K.T.,Valspar Corporation |
O'Mahony C.,Trinity Technology and Enterprise Campus |
Dixon J.,FIG Consultant |
Vints M.,Amcor Flexibles Europe and Americas |
And 3 more authors.
Food Additives and Contaminants - Part A Chemistry, Analysis, Control, Exposure and Risk Assessment | Year: 2014
The approach used to obtain European Union-wide data on the usage and concentration of substances in different food packaging materials is described. Statistics were collected on pack sizes and market shares for the different materials used to package different food groups. The packaging materials covered were plastics (both flexible and rigid), metal containers, light metal packaging, paper and board, as well as the adhesives and inks used on them. An explanation as to how these data are linked in various ways in the FACET exposure modelling tool is given as well as an overview of the software along with examples of the intermediate tables of data. The example of bisphenol A (BPA), used in resins that may be incorporated into some coatings for canned foodstuffs, is used to illustrate how the data in FACET are combined to produce concentration distributions. Such concentration distributions are then linked probabilistically to the amounts of each food item consumed, as recorded in national food consumption survey diaries, in order to estimate exposure to packaging migrants. Estimates of exposure are at the level of the individual consumer and thus can be expressed for various percentiles of different populations and subpopulations covered by the national dietary surveys. © 2014 Taylor & Francis.
Moore A.,Trinity College Dublin |
Wesiak G.,Graz University of Technology |
Steiner C.M.,Graz University of Technology |
Hauff C.,Technical University of Delft |
And 3 more authors.
CEUR Workshop Proceedings | Year: 2013
Research on user modeling based on social network information has shown that some user characteristics can be accurately inferred from users' digital traces. This kind of information can be used to inform user models of adaptive systems for personalizing the system. This paper addresses a crucial question for practical application of this approach: Are users actually willing to provide their social Web profiles and how do they perceive this? An empirical study conducted with medical students shows that although participants are using social networks, they are reluctant about providing their identities and consider these portals rather private. The outcomes of the study uncover a clear need for further research on enhanced privacy and enhanced trust.
McNamara C.,Trinity Technology and Enterprise Campus |
Mehegan J.,Trinity Technology and Enterprise Campus |
O'Mahony C.,Trinity Technology and Enterprise Campus |
Safford B.,Unilever |
And 8 more authors.
Food Additives and Contaminants - Part A Chemistry, Analysis, Control, Exposure and Risk Assessment | Year: 2011
The feasibility of using a retailer fidelity card scheme to estimate food additive intake was investigated in an earlier study. Fidelity card survey information was combined with information provided by the retailer on levels of the food colour Sunset Yellow (E110) in the foods to estimate a daily exposure to the additive in the Swiss population. As with any dietary exposure method the fidelity card scheme is subject to uncertainties and in this paper the impact of uncertainties associated with input variables including the amounts of food purchased, the levels of E110 in food, the proportion of food purchased at the retailer, the rate of fidelity card usage, the proportion of foods consumed outside of the home and bodyweights and with systematic uncertainties was assessed using a qualitative, deterministic and probabilistic approach. An analysis of the sensitivity of the results to each of the probabilistic inputs was also undertaken. The analysis identified the key factors responsible for uncertainty within the model and demonstrated how the application of some simple probabilistic approaches can be used quantitatively to assess uncertainty. © 2011 Copyright Taylor and Francis Group, LLC.