Integration of probabilistic exposure assessment and probabilistic hazard characterization

Guidance on risk-benefit assessment of foods

The EFSA Scientific Committee has updated its 2010 Guidance on risk-benefit assessment (RBA) of foods. The update addresses methodological developments and regulatory needs. While it retains the stepwise RBA approach, it provides additional methods for complex assessments, such as multiple chemical hazards and all relevant health effects impacting different population subgroups. The updated guidance includes approaches for systematic identification, prioritisation and selection of hazardous and beneficial food components. It also offers updates relevant to characterising adverse and beneficial effects, such as measures of effect size and dose-response modelling. The guidance expands options for characterising risks and benefits, incorporating variability, uncertainty, severity categorisation and ranking of different (beneficial or adverse) effects. The impact of different types of health effects is assessed qualitatively or quantitatively, depending on the problem formulation, scope of the RBA question and data availability. The integration of risks and benefits often involves value-based judgements and should ideally be performed with the risk-benefit manager. Metrics such as Disability-Adjusted Life Years (DALYs) and Quality-Adjusted Life Years (QALYs) can be used. Additional approaches are presented, such as probability of all relevant effects and/or effects of given severities and their integration using severity weight functions. The update includes practical guidance on reporting results, interpreting outcomes and communicating the outcome of an RBA, considering consumer perspectives and responses to advice.

Advancing probabilistic risk assessment by integrating human biomonitoring, new approach methods, and Bayesian modeling: A case study with the mycotoxin deoxynivalenol

Deoxynivalenol (DON) is a mycotoxin frequently observed in cereals and cereal-based foods, with reported toxicological effects including reduced body weight, immunotoxicity and reproductive defects. The European Food Safety Authority used traditional risk assessment approaches to derive a deterministic Tolerable Daily Intake (TDI) of 1 μg/kg-day, however data from human biomarkers studies indicate widespread and variable exposure worldwide, necessitating more sophisticated and advanced methods to quantify population risk. The World Health Organization/International Programme on Chemical Safety (WHO/IPCS) has previously used DON as a case example in replacing the TDI with a probabilistic toxicity value, using default uncertainty and variability distributions to derive the Human Dose corresponding to an effect size M in the Ith percentile of the population (HDMI) for M = 5 % decrease in body weight and I = 1 %. In this study, we extend this case study by incorporating (1) Bayesian modeling approaches, (2) using both in vivo data and in vitro population new approach methods to replace default distributions for interspecies toxicokinetic (TK) differences and intraspecies TK and toxicodynamic (TD) variability, and (3) integrating biomonitoring data and probabilistic dose-response functions to characterize population risk distributions. We first derive an HDMI of 5.5 [1.4-24] μg/kg-day, also using TK modeling to converted the HDMI to Biomonitoring Equivalents, BEMI for comparison with biomonitoring data, with a blood BEMI of 0.53 [0.17-1.6] μg/L and a urinary excretion BEMI of 3.9 [1.0-16] μg/kg-day. We then illustrate how this integrative approach can advance quantitative risk characterization using two human biomonitoring datasets, estimating both the fraction of population with an effect size M ≥ 5 % as well as the distribution of effect sizes. Overall, we demonstrate that integration of Bayesian modeling, human biomonitoring data, and in vitro population-based TD data within the WHO/IPCS probabilistic framework yields more accurate, precise, and comprehensive risk characterization.

Trends of caffeine intake from food and beverage among Chinese adults: 2004-2018

Caffeine is a kind of psychostimulant that naturally exist in foods. The benefits and risks of caffeine depend on the dose. Moreover, the intake of caffeine from dietary sources in China has seldom been assessed. We calculated the dietary caffeine intake of Chinese adult consumers from 2004 to 2018 and analyzed its consumption trends by using data from the China Health and Nutrition Survey and the National Food and Beverage Consumption Survey. Caffeine contents in different dietary items were determined by HPLC. Monte Carlo simulations were applied to estimate caffeine intake. Mann-Kendall trend test and linear regression were used to analyze the trend of caffeine consumption. Among 79,173 individuals, 3972 (5%) of the adult Chinese population consumed caffeine between 2004 and 2018. The average caffeine intake was 123 mg/day for male consumers and 116 mg/day for female consumers. The median and P75 caffeine intake raised over the 14 years. Traditional tea leaves, coffee and sodas are the main sources of caffeine intake. Our findings indicate that most Chinese adults consumed caffeine within the safe level (400 mg/day), but the caffeine consumption has shown an increasing trend in recent 14 years.

Quantitative probabilistic assessment of caffeine intake from tea in Chinese adult consumers based on nationwide caffeine content determination and tea consumption survey

Caffeine has known effects on the central nervous and cardiovascular systems. An intake up to 400 mg/day does not give rise to health concerns. Tea, a major source of caffeine, is highly consumed in China. However, the potential health risk of caffeine from tea has not been well evaluated. The present study assessed caffeine intake levels from tea for Chinese adult consumers. We collected 1,398 samples of green, black, dark, jasmine, oolong, white, and yellow tea from 17 provinces. The caffeine content was determined by HPLC. The average contents were 27 (oolong tea) - 43 (yellow tea) mg/g. The leaching rate of caffeine into the water was about 100%. Tea consumption data were from the National Beverage Consumption Survey 2013-2014. Monte Carlo simulations were applied to estimate the distribution of caffeine intake. The average caffeine intake from tea was 180 mg/day of all consumers. Green, dark, and black tea were the primary sources. Males (197 mg/day) consumed more caffeine than females (136 mg/day) on average, but females older than 71 years had the highest intake level (259 mg/day) among all subgroups. Over 90% of Chinese adult tea drinkers have caffeine intake under 400 mg/day.

Probabilistic risk assessment - the keystone for the future of toxicology

Safety sciences must cope with uncertainty of models and results as well as information gaps. Acknowledging this uncer-tainty necessitates embracing probabilities and accepting the remaining risk. Every toxicological tool delivers only probable results. Traditionally, this is taken into account by using uncertainty / assessment factors and worst-case / precautionary approaches and thresholds. Probabilistic methods and Bayesian approaches seek to characterize these uncertainties and promise to support better risk assessment and, thereby, improve risk management decisions. Actual assessments of uncertainty can be more realistic than worst-case scenarios and may allow less conservative safety margins. Most importantly, as soon as we agree on uncertainty, this defines room for improvement and allows a transition from traditional to new approach methods as an engineering exercise. The objective nature of these mathematical tools allows to assign each methodology its fair place in evidence integration, whether in the context of risk assessment, sys-tematic reviews, or in the definition of an integrated testing strategy (ITS) / defined approach (DA) / integrated approach to testing and assessment (IATA). This article gives an overview of methods for probabilistic risk assessment and their application for exposure assessment, physiologically-based kinetic modelling, probability of hazard assessment (based on quantitative and read-across based structure-activity relationships, and mechanistic alerts from in vitro studies), indi-vidual susceptibility assessment, and evidence integration. Additional aspects are opportunities for uncertainty analysis of adverse outcome pathways and their relation to thresholds of toxicological concern. In conclusion, probabilistic risk assessment will be key for constructing a new toxicology paradigm - probably!

Risk assessment approaches for evaluating cumulative exposures to multiple pesticide residues in agro-products using seasonal vegetable monitoring data from Hainan, China: a case study

Risks from combined exposure to multiple chemicals in food have prompted a growing concern for their effect on human health. Risk management of chemical mixtures should be based on developing and harmonizing methodologies to scientifically evaluate their cumulative adverse effects. In this study, a simplified tiered approach of cumulative exposure assessment is described along with a case study of vegetables in China's Hainan province during 2012-2014. This case study could be a reference for the Chinese National Risk Assessment Programs for vegetable and fruit products. In the proposed assessment approach, Tier 1 acts as a screening tier to categorize and evaluate chemicals under a conservative scenario, and it prioritizes the pesticides of most concern. Tier 2 refines the grouping of substances from Tier 1 and normalizes the toxic potency of the chemicals to sum the exposure of chemical mixtures in a given assessment group. Tier 3 applies the refined exposure model and the input parameter distribution to create probabilistic models using Monte Carlo simulation. This approach will be helpful in the cumulative exposure assessment where data on pesticide residues are sufficient, but the individual dietary consumption is inadequate.

Human health risk-benefit assessment of fish and other seafood: a scoping review

Fish and other seafood are important sources of nutrients, but they are also sources of chemical contaminants that may cause adverse health effects. This article aimed to identify existing risk-benefit assessments (RBA) of fish, shellfish, and other seafood, compare methodologies, discuss differences and commonalities in findings, and identify limitations and ways forward for future studies. We conducted a scoping review of the scientific literature of studies in all languages published from 2000 through April 2019. We identified 106 RBA of fish and other seafood across Europe, Asia, North America, Africa, and at the global level. Studies were heterogeneous in terms of types of fish and other seafood considered, beneficial and adverse compounds assessed, and overall methodology. Collected data showed that a diet consisting of a variety of lean and fatty fish and other seafood is recommended for the overall population and that women of childbearing age and children should limit the consumption of fish and other seafood types that have a high likelihood of contamination. Our review emphasizes the need for evidence-based, up-to-date, and harmonized approaches in RBA in general.

Development of a quantitative chemical risk assessment (QCRA) procedure for contaminants of emerging concern in drinking water supply

The uncertainties on the occurrence, fate and hazard of Contaminants of Emerging Concern (CECs) increasingly challenge drinking water (DW) utilities whether additional measures should be taken to reduce the health risk. This has led to the development and evaluation of risk-based approaches by the scientific community. DW guideline values are commonly derived based on deterministic chemical risk assessment (CRA). Here, we propose a new probabilistic procedure, that is a quantitative chemical risk assessment (QCRA), to assess potential health risk related to the occurrence of CECs in DW. The QCRA includes uncertainties in risk calculation in both exposure and hazard assessments. To quantify the health risk in terms of the benchmark quotient probabilistic distribution, the QCRA estimates the probabilistic distribution of CECs concentration in DW based on their concentration in source water and simulating the breakthrough curves of a granular activated carbon (GAC) treatment process. The model inputs and output uncertainties were evaluated by sensitivity and uncertainty analyses for each step of the risk assessment to identify the most relevant factors affecting risk estimation. Dominant factors resulted to be the concentration of CECs in water sources, GAC isotherm parameters and toxicological data. To stress the potential of this new QCRA approach, several case studies are considered with focus on bisphenol A as an example CEC and various GAC management options. QCRA quantifies the probabilistic risk, providing more insight compared to CRA. QCRA proved to be more effective in supporting the intervention prioritization for treatment optimization to pursue health risk minimization.

A Probabilistic Approach to Evaluate the Risk of Decreased Total Triiodothyronine Hormone Levels following Chronic Exposure to PFOS and PFHxS via Contaminated Drinking Water

BACKGROUND

Extensive exposure to per- and polyfluoroalkyl substances (PFAS) have been observed in many countries. Current deterministic frameworks for risk assessment lack the ability to predict the likelihood of effects and to assess uncertainty. When exposure exceeds tolerable intake levels, these shortcomings hamper risk management and communication.

OBJECTIVE

The integrated probabilistic risk assessment (IPRA) combines dose-response and exposure data to estimate the likelihood of adverse effects. We evaluated the usefulness of the IPRA for risk characterization related to decreased levels of total triiodothyronine (T 3 ) in humans following a real case of high exposure to PFAS via drinking water.

METHODS

PFAS exposure was defined as serum levels from residents of a contaminated area in Ronneby, Sweden. Median levels were 270  ng / mL [perfluorooctane sulfonic acid (PFOS)] and 229  ng / mL [perfluorohexane sulfonic acid (PFHxS)] for individuals who resided in Ronneby 1 y before the exposure termination. This data was integrated with data from a subchronic toxicity study in monkeys exposed daily to PFOS. Benchmark dose modeling was employed to describe separate dose-effect relationship for males and females, and extrapolation factor distributions were used to estimate the corresponding human benchmark dose. The critical effect level was defined as a 10% decrease in total T 3 .

RESULTS

The median probability of critical exposure, following a combined exposure to PFOS and PFHxS, was estimated to be [2.1% (90% CI: 0.4 % - 13.1 % )]. Gender-based analysis showed that this risk was almost entirely distributed among women, namely [3.9% (90% CI: 0.8 % - 21.6 % )].

DISCUSSION

The IPRA was compared with the traditional deterministic Margin of Exposure (MoE) approach. We conclude that probabilistic risk characterization represents an important step forward in the ability to adequately analyze group-specific health risks. Moreover, quantifying the sources of uncertainty is desirable, as it improves the awareness among stakeholders and will guide future efforts to improve accuracy. https://doi.org/10.1289/EHP6654.

A retain and refine approach to cumulative risk assessment

Mixtures of substances to which humans are exposed may lead to cumulative exposure and health effects. To study their effects, it is first necessary to identify a cumulative assessment group (CAG) of substances for risk assessment or hazard testing. Excluding substances from consideration before there is sufficient evidence may underestimate the risk. Conversely, including everything and treating the inevitable uncertainties using conservative assumptions is inefficient and may overestimate the risk, with an unknown level of protection. An efficient, transparent strategy is described to retain a large group, quantifying the uncertainty of group membership and other uncertainties. Iterative refinement of the CAG then focuses on adding information for the substances with high probability of contributing significantly to the risk. Probabilities can be estimated using expert opinion or derived from data on substance properties. An example is presented with 100 pesticides, in which the retain step identified a single substance to target refinement. Using an updated hazard characterisation for this substance reduced the mean exposure estimate from 0.43 to 0.28 μg kg-bw^-1 day^-1 and reduced the 99.99th percentile exposure from 24.9 to 5.1 μg kg-bw^-1 day^-1. Other retained substances contributed little to the risk estimates, even after accounting for uncertainty.

A common approach for ranking of microbiological and chemical hazards in foods based on risk assessment - useful but is it possible?

This article compares and contrasts microbial and chemical risk assessment methodologies in order to evaluate the potential for a common framework for ranking of risk of chemical and microbiological hazards, and developments needed for such a framework. An overview of microbial (MRA) and chemical (CRA) risk assessment is presented and important differences are highlighted. Two microbiological and two chemical hazard-food combinations were ranked based on both a margin of exposure and a risk assessment approach. The comparisons illustrated that it is possible to rank chemical and microbiological hazard-food combinations with traditional approaches from each domain and indicated that the rank order but not the absolute measures is similar using either approach. Including severity in the assessment using DALY reduced differences between hazards and affected the outcome more than which approach was used. Ranking frameworks should include assessment of uncertainty as an integral part of the ranking, and be based on assessment of risk, not safety, and expressed in a common health metric such as disease burden. Necessary simplifications to address data gaps can involve the use of default scenarios. Challenges include comparisons of case-based vs. non-case-based health-endpoints, e.g. biomarker concentration, and integration of the severity of health effects into ranking.

Probabilistic approach for assessing cancer risk due to benzo[a]pyrene in barbecued meat: Informing advice for population groups

BACKGROUND

Consumption of meat prepared by barbecuing is associated with risk of cancer due to formation of carcinogenic compounds including benzo[a]pyrene (BaP). Assessment of a population's risk of disease and people's individual probability of disease given specific consumer attributes may direct food safety strategies to where impact on public health is largest. The aim of this study was to propose a model that estimates the risk of cancer caused by exposure to BaP from barbecued meat in Denmark, and to estimate the probability of developing cancer in subgroups of the population given different barbecuing frequencies.

METHODS

We developed probabilistic models applying two dimensional Monte Carlo simulation to take into account the variation in exposure given age and sex and in the individuals' sensitivity to develop cancer after exposure to BaP, and the uncertainty in the dose response model. We used the Danish dietary consumption survey, monitoring data of chemical concentrations, data on consumer behavior of frequency of barbecuing, and animal dose response data.

FINDINGS

We estimated an average extra lifetime risk of cancer due to BaP from barbecued meat of 6.8 × 10-5 (95% uncertainty interval 2.6 × 10-7 - 7.0 × 10-4) in the Danish population. This corresponds to approximately one to 4,074 extra cancer cases over a lifetime, reflecting wide uncertainty. The impact per barbecuing event on the risk of cancer for men and women of low body weight was higher compared to higher bodyweight. However, the difference due to sex and bodyweight between subgroups are dwarfed by the uncertainty.

INTERPRETATION

This study proposes a model that can be applied to other substances and routes of exposure, and allows for deriving the change in risk following a specific change in behaviour. The presented methodology can serve as a valuable tool for risk management, allowing for the formulation of behaviour advice targeted to specific sub-groups in the population.

Risk Benefit Assessment of foods: Key findings from an international workshop

Whilst risk management measures, including food policy, are developed for the protection of public health and the environment, they may also lead to a reduction in health benefits. Policy decisions require then consideration of these necessary trade-offs, which leads to an increasing need to apply formal risk-benefit assessment (RBA) of foods. In this context, the European Food Safety Authority sponsored a Risk-Benefit Assessment Workshop on "past, current and future developments within the risk-benefit assessment of foods (RBA)" held in May 2017. The overall aims of the RBA Workshop were to discuss existing methods, challenges and needs within RBA, and to draft a roadmap for future development of RBA. The specific objectives were to i) identify RBA activities in Europe and globally; ii) discuss how to further develop and optimize RBA methodology; iii) identify challenges and opportunities within RBA; and iv) increase collaboration internationally. The two-day workshop gathered 28 participants from 16 institutions in 11 countries. It included technical presentations of RBA methods and case studies, and two break-out sessions for group discussions. All participants agreed that RBA has substantial potential to inform risk-management decisions in the areas of food safety, nutrition and public health. Several activities to optimize further developments within RBA were suggested. This paper provides a summary of workshop presentations, a discussion of challenges that limit progress in this area, and suggestions of next steps for this promising approach supporting a science-based decision process in the area of risk-benefit management of foods.

Health impact assessment of a skin sensitizer: Analysis of potential policy measures aimed at reducing geraniol concentrations in personal care products and household cleaning products

A methodology to assess the health impact of skin sensitizers is introduced, which consists of the comparison of the probabilistic aggregated exposure with a probabilistic (individual) human sensitization or elicitation induction dose. The health impact of potential policy measures aimed at reducing the concentration of a fragrance allergen, geraniol, in consumer products is analysed in a simulated population derived from multiple product use surveys. Our analysis shows that current dermal exposure to geraniol from personal care and household cleaning products lead to new cases of contact allergy and induce clinical symptoms for those already sensitized. We estimate that this exposure results yearly in 34 new cases of geraniol contact allergy per million consumers in Western and Northern Europe, mainly due to exposure to household cleaning products. About twice as many consumers (60 per million) are projected to suffer from clinical symptoms due to re-exposure to geraniol. Policy measures restricting geraniol concentrations to <0.01% will noticeably reduce new cases of sensitization and decrease the number of people with clinical symptoms as well as the frequency of occurrence of these clinical symptoms. The estimated numbers should be interpreted with caution and provide only a rough indication of the health impact.

Probabilistic risk assessment of nitrate groundwater contamination from greenhouses in Albenga plain (Liguria, Italy) using lysimeters

The use of fertilizers in greenhouse-grown crops can pose a threat to groundwater quality and, consequently, to human beings and subterranean ecosystem, where intensive farming produces pollutants leaching. Albenga plain (Liguria, Italy) is an alluvial area of about 45km² historically devoted to farming. Recently the crops have evolved to greenhouses horticulture and floriculture production. In the area high levels of nitrates in groundwater have been detected. Lysimeters with three types of reconstituted soils (loamy sand, sandy clay loam and sandy loam) collected from different areas of Albenga plain were used in this study to evaluate the leaching loss of nitrate (NO₃^-) over a period of 12weeks. Leaf lettuce (Lactuca sativa L.) was selected as a representative green-grown crop. Each of the soil samples was treated with a slow release fertilizer, simulating the real fertilizing strategy of the tillage. In order to estimate the potential risk for aquifers as well as for organisms exposed via pore water, nitrate concentrations in groundwater were evaluated by applying a simplified attenuation model to the experimental data. Results were refined and extended from comparison of single effects and exposure values (Tier I level) up to the evaluation of probabilistic distributions of exposure and related effects (Tier II, III IV levels). HHRA suggested HI >1 and about 20% probability of exceeding RfD for all the greenhouses, regardless of the soil. ERA suggested HQ>100 for all the greenhouses; 93% probability of PNEC exceedance for greenhouses containing sand clay loam. The probability of exceeding LC50 for 5% of the species was about 40% and the probability corresponding to DBQ of DEC/EC50>0.001 was >90% for all the greenhouses. The significantly high risk, related to the detected nitrate leaching loss, can be attributed to excessive and inappropriate fertigation strategies.

Quantitative human health risk assessment along the lifecycle of nano-scale copper-based wood preservatives

The use of nano-scale copper oxide (CuO) and basic copper carbonate (Cu₂(OH)₂CO₃) in both ionic and micronized wood preservatives has raised concerns about the potential of these substances to cause adverse humans health effects. To address these concerns, we performed quantitative (probabilistic) human health risk assessment (HHRA) along the lifecycles of these formulations used in antibacterial and antifungal wood coatings and impregnations by means of the EU FP7 SUN project's Decision Support System (SUNDS, www.sunds.gd). The results from the risk analysis revealed inhalation risks from CuO in exposure scenarios involving workers handling dry powders and performing sanding operations as well as potential ingestion risks for children exposed to nano Cu₂(OH)₂CO₃ in a scenario involving hand-to-mouth transfer of the substance released from impregnated wood. There are, however, substantial uncertainties in these results, so some of the identified risks may stem from the safety margin of extrapolation to fill data gaps and might be resolved by additional testing. Our stochastic approach successfully communicated the contribution of different sources of uncertainty in the risk assessment. The main source of uncertainty was the extrapolation from short to long-term exposure, which was necessary due to the lack of (sub)chronic in vivo studies with CuO and Cu₂(OH)₂CO₃. Considerable uncertainties also stemmed from the use of default inter- and intra-species extrapolation factors.

Beyond the RfD: Broad Application of a Probabilistic Approach to Improve Chemical Dose-Response Assessments for Noncancer Effects

BACKGROUND

The National Academies recommended risk assessments redefine the traditional noncancer Reference Dose (RfD) as a probabilistically derived risk-specific dose, a framework for which was recently developed by the World Health Organization (WHO).

OBJECTIVES

Our aim was to assess the feasibility and implications of replacing traditional RfDs with probabilistic estimates of the human dose associated with an effect magnitude M and population incidence I (HD_MI).

METHODS

We created a comprehensive, curated database of RfDs derived from animal data and developed a standardized, automated, web-accessible probabilistic dose-response workflow implementing the WHO framework.

RESULTS

We identified 1,464 RfDs and associated endpoints, representing 608 chemicals across many types of effects. Applying our standardized workflow resulted in 1,522 HD_MI values. Traditional RfDs are generally within an order of magnitude of the HD_MI lower confidence bound for I=1% and M values commonly used for benchmark doses. The greatest contributor to uncertainty was lack of benchmark dose estimates, followed by uncertainty in the extent of human variability. Exposure at the traditional RfD frequently implies an upper 95% confidence bound of several percent of the population affected. Whether such incidences are considered acceptable is likely to vary by chemical and risk context, especially given the wide range of severity of the associated effects, from clinical chemistry to mortality.

CONCLUSIONS

Overall, replacing RfDs with HD_MI estimates can provide a more consistent, scientifically rigorous, and transparent basis for risk management decisions, as well as support additional decision contexts such as economic benefit-cost analysis, risk-risk tradeoffs, life-cycle impact analysis, and emergency response. https://doi.org/10.1289/EHP3368.

APROBA-Plus: A probabilistic tool to evaluate and express uncertainty in hazard characterization and exposure assessment of substances

To facilitate the application of probabilistic risk assessment, the WHO released the APROBA tool. This tool applies lognormal uncertainty distributions to the different aspects of the hazard characterization, resulting in a probabilistic health-based guidance value. The current paper describes an extension, APROBA-Plus, which combines the output from the probabilistic hazard characterization with the probabilistic exposure to rapidly characterize risk and its uncertainty. The uncertainty in exposure is graphically compared with the uncertainty in the target human dose, i.e. the dose that complies with the specified protection goals. APROBA-Plus is applied to several case studies, resulting in distinct outcomes and illustrating that APROBA-Plus could serve as a standard extension of routine risk assessments. By visualizing the uncertainties, APROBA-Plus provides a more transparent and informative outcome than the more usual deterministic approaches, so that risk managers can make better informed decisions. For example, APROBA-Plus can help in deciding whether risk-reducing measures are warranted or that a refined risk assessment would first be needed. If the latter, the tool can be used to prioritize possible refinements. APROBA-Plus may also be used to rank substances into different risk categories, based on potential health risks without being compromised by different levels of conservatism that may be associated with point estimates of risk.

Comparative Human Health Impact Assessment of Engineered Nanomaterials in the Framework of Life Cycle Assessment

For safe innovation, knowledge on potential human health impacts is essential. Ideally, these impacts are considered within a larger life-cycle-based context to support sustainable development of new applications and products. A methodological framework that accounts for human health impacts caused by inhalation of engineered nanomaterials (ENMs) in an indoor air environment has been previously developed. The objectives of this study are as follows: (i) evaluate the feasibility of applying the CF framework for NP exposure in the workplace based on currently available data; and (ii) supplement any resulting knowledge gaps with methods and data from the life cycle approach and human risk assessment (LICARA) project to develop a modified case-specific version of the framework that will enable near-term inclusion of NP human health impacts in life cycle assessment (LCA) using a case study involving nanoscale titanium dioxide (nanoTiO₂ ). The intent is to enhance typical LCA with elements of regulatory risk assessment, including its more detailed measure of uncertainty. The proof-of-principle demonstration of the framework highlighted the lack of available data for both the workplace emissions and human health effects of ENMs that is needed to calculate generalizable characterization factors using common human health impact assessment practices in LCA. The alternative approach of using intake fractions derived from workplace air concentration measurements and effect factors based on best-available toxicity data supported the current case-by-case approach for assessing the human health life cycle impacts of ENMs. Ultimately, the proposed framework and calculations demonstrate the potential utility of integrating elements of risk assessment with LCA for ENMs once the data are available.

Comparison of methods for calculating the health costs of endocrine disrupters: a case study on triclosan

BACKGROUND

Socioeconomic analysis is currently used in the Europe Union as part of the regulatory process in Regulation Registration, Evaluation and Authorisation of Chemicals (REACH), with the aim of assessing and managing risks from dangerous chemicals. The political impact of the socio-economic analysis is potentially high in the authorisation and restriction procedures, however, current socio-economic analysis dossiers submitted under REACH are very heterogeneous in terms of methodology used and quality. Furthermore, the economic literature is not very helpful for regulatory purposes, as most published calculations of health costs associated with chemical exposures use epidemiological studies as input data, but such studies are rarely available for most substances. The quasi-totality of the data used in the REACH dossiers comes from toxicological studies.

METHODS

This paper assesses the use of the integrated probabilistic risk assessment, based on toxicological data, for the calculation of health costs associated with endocrine disrupting effects of triclosan. The results are compared with those obtained using the population attributable fraction, based on epidemiological data.

RESULTS

The results based on the integrated probabilistic risk assessment indicated that 4894 men could have reproductive deficits based on the decreased vas deferens weights observed in rats, 0 cases of changed T₃ levels, and 0 cases of girls with early pubertal development. The results obtained with the Population Attributable Fraction method showed 7,199,228 cases of obesity per year, 281,923 girls per year with early pubertal development and 88,957 to 303,759 cases per year with increased total T₃ hormone levels. The economic costs associated with increased BMI due to TCS exposure could be calculated. Direct health costs were estimated at €5.8 billion per year.

CONCLUSIONS

The two methods give very different results for the same effects. The choice of a toxicological-based or an epidemiological-based method in the socio-economic analysis will therefore significantly impact the estimated health costs and consequently the political risk management decision. Additional work should be done for understanding the reasons of these significant differences.

Probabilistic approach for assessing infants' health risks due to ingestion of nanoscale silver released from consumer products

Silver nanoparticles (n-Ag) are widely used in consumer products and many medical applications because of their unique antibacterial properties. Their use is raising concern about potential human exposures and health effects. Therefore, it is informative to assess the potential human health risks of n-Ag in order to ensure that nanotechnology-based consumer products are deployed in a safe and sustainable way. Even though toxicity studies clearly show the potential hazard of n-Ag, there have been few attempts to integrate hazard and exposure assessments to evaluate risks. The underlying reason for this is the difficulty in characterizing exposure and the lack of toxicity studies essential for human health risk assessment (HHRA). Such data gaps introduce significant uncertainty into the risk assessment process. This study uses probabilistic methods to assess the relative uncertainty and potential risks of n-Ag exposure to infants. In this paper, we estimate the risks for infants potentially exposed to n-Ag through drinking juice or milk from sippy cups or licking baby blankets containing n-Ag. We explicitly evaluate uncertainty and variability contained in available dose-response and exposure data in order to make the risk characterization process transparent. Our results showed that individual margin of exposures for oral exposure to sippy cups and baby blankets containing n-Ag exhibited minimal risk.

Update: use of the benchmark dose approach in risk assessment

The Scientific Committee (SC) reconfirms that the benchmark dose (BMD) approach is a scientifically more advanced method compared to the NOAEL approach for deriving a Reference Point (RP). Most of the modifications made to the SC guidance of 2009 concern the section providing guidance on how to apply the BMD approach. Model averaging is recommended as the preferred method for calculating the BMD confidence interval, while acknowledging that the respective tools are still under development and may not be easily accessible to all. Therefore, selecting or rejecting models is still considered as a suboptimal alternative. The set of default models to be used for BMD analysis has been reviewed, and the Akaike information criterion (AIC) has been introduced instead of the log-likelihood to characterise the goodness of fit of different mathematical models to a dose-response data set. A flowchart has also been inserted in this update to guide the reader step-by-step when performing a BMD analysis, as well as a chapter on the distributional part of dose-response models and a template for reporting a BMD analysis in a complete and transparent manner. Finally, it is recommended to always report the BMD confidence interval rather than the value of the BMD. The lower bound (BMDL) is needed as a potential RP, and the upper bound (BMDU) is needed for establishing the BMDU/BMDL per ratio reflecting the uncertainty in the BMD estimate. This updated guidance does not call for a general re-evaluation of previous assessments where the NOAEL approach or the BMD approach as described in the 2009 SC guidance was used, in particular when the exposure is clearly smaller (e.g. more than one order of magnitude) than the health-based guidance value. Finally, the SC firmly reiterates to reconsider test guidelines given the expected wide application of the BMD approach.

Combining exposure and effect modeling into an integrated probabilistic environmental risk assessment for nanoparticles

There is a growing need for good environmental risk assessment of engineered nanoparticles (ENPs). Environmental risk assessment of ENPs has been hampered by lack of data and knowledge about ENPs, their environmental fate, and their toxicity. This leads to uncertainty in the risk assessment. To deal with uncertainty in the risk assessment effectively, probabilistic methods are advantageous. In the present study, the authors developed a method to model both the variability and the uncertainty in environmental risk assessment of ENPs. This method is based on the concentration ratio and the ratio of the exposure concentration to the critical effect concentration, both considered to be random. In this method, variability and uncertainty are modeled separately so as to allow the user to see which part of the total variation in the concentration ratio is attributable to uncertainty and which part is attributable to variability. The authors illustrate the use of the method with a simplified aquatic risk assessment of nano-titanium dioxide. The authors' method allows a more transparent risk assessment and can also direct further environmental and toxicological research to the areas in which it is most needed. Environ Toxicol Chem 2016;35:2958-2967. © 2016 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Uncertainty and variability in human exposure limits - a chemical-specific approach for ciprofloxacin and methotrexate

Human exposure limits (HELs) for chemicals with a toxicological threshold are traditionally derived using default assessment factors that account for variations in exposure duration, species sensitivity and individual sensitivity. The present paper elaborates a probabilistic approach for human hazard characterization and the derivation of HELs. It extends the framework for evaluating and expressing uncertainty in hazard characterization recently proposed by WHO-IPCS, i.e. by the incorporation of chemical-specific data on human variability in toxicokinetics. The incorporation of human variability in toxicodynamics was based on the variation between adverse outcome pathways (AOPs). Furthermore, sources of interindividual variability and uncertainty are propagated separately throughout the derivation process. The outcome is a two-dimensional human dose distribution that quantifies the population fraction exceeding a pre-selected critical effect level with an estimate of the associated uncertainty. This enables policy makers to set separate standards for the fraction of the population to be protected and the confidence level of the assessment. The main sources of uncertainty in the human dose distribution can be identified in order to plan new research for reducing uncertainty. Additionally, the approach enables quantification of the relative risk for specific subpopulations. The approach is demonstrated for two pharmaceuticals, i.e. the antibiotic ciprofloxacin and the antineoplastic methotrexate. For both substances, the probabilistic HEL is mainly influenced by uncertainty originating from: (1) the point of departure (PoD), (2) extrapolation from sub-acute to chronic toxicity and (3) interspecies extrapolation. However, when assessing the tails of the two-dimensional human dose distributions, i.e. the section relevant for the derivation of human exposure limits, interindividual variability in toxicodynamics also becomes important.

World Health Organization estimates of the global and regional disease burden of four foodborne chemical toxins, 2010: a data synthesis

Background Chemical exposures have been associated with a variety of health effects; however, little is known about the global disease burden from foodborne chemicals. Food can be a major pathway for the general population's exposure to chemicals, and for some chemicals, it accounts for almost 100% of exposure.  Methods and Findings Groups of foodborne chemicals, both natural and anthropogenic, were evaluated for their ability to contribute to the burden of disease.  The results of the analyses on four chemicals are presented here - cyanide in cassava, peanut allergen, aflatoxin, and dioxin.  Systematic reviews of the literature were conducted to develop age- and sex-specific disease incidence and mortality estimates due to these chemicals.  From these estimates, the numbers of cases, deaths and disability adjusted life years (DALYs) were calculated.  For these four chemicals combined, the total number of illnesses, deaths, and DALYs in 2010 is estimated to be 339,000 (95% uncertainty interval [UI]: 186,000-1,239,000); 20,000 (95% UI: 8,000-52,000); and 1,012,000 (95% UI: 562,000-2,822,000), respectively.  Both cyanide in cassava and aflatoxin are associated with diseases with high case-fatality ratios.  Virtually all human exposure to these four chemicals is through the food supply.  Conclusion Chemicals in the food supply, as evidenced by the results for only four chemicals, can have a significant impact on the global burden of disease. The case-fatality rates for these four chemicals range from low (e.g., peanut allergen) to extremely high (aflatoxin and liver cancer).  The effects associated with these four chemicals are neurologic (cyanide in cassava), cancer (aflatoxin), allergic response (peanut allergen), endocrine (dioxin), and reproductive (dioxin).

A Unified Probabilistic Framework for Dose-Response Assessment of Human Health Effects

BACKGROUND

When chemical health hazards have been identified, probabilistic dose-response assessment ("hazard characterization") quantifies uncertainty and/or variability in toxicity as a function of human exposure. Existing probabilistic approaches differ for different types of endpoints or modes-of-action, lacking a unifying framework.

OBJECTIVES

We developed a unified framework for probabilistic dose-response assessment.

METHODS

We established a framework based on four principles: a) individual and population dose responses are distinct; b) dose-response relationships for all (including quantal) endpoints can be recast as relating to an underlying continuous measure of response at the individual level; c) for effects relevant to humans, "effect metrics" can be specified to define "toxicologically equivalent" sizes for this underlying individual response; and d) dose-response assessment requires making adjustments and accounting for uncertainty and variability. We then derived a step-by-step probabilistic approach for dose-response assessment of animal toxicology data similar to how nonprobabilistic reference doses are derived, illustrating the approach with example non-cancer and cancer datasets.

RESULTS

Probabilistically derived exposure limits are based on estimating a "target human dose" (HDMI), which requires risk management-informed choices for the magnitude (M) of individual effect being protected against, the remaining incidence (I) of individuals with effects ≥ M in the population, and the percent confidence. In the example datasets, probabilistically derived 90% confidence intervals for HDMI values span a 40- to 60-fold range, where I = 1% of the population experiences ≥ M = 1%-10% effect sizes.

CONCLUSIONS

Although some implementation challenges remain, this unified probabilistic framework can provide substantially more complete and transparent characterization of chemical hazards and support better-informed risk management decisions.

Integrated probabilistic risk assessment for nanoparticles: the case of nanosilica in food

Insight into risks of nanotechnology and the use of nanoparticles is an essential condition for the social acceptance and safe use of nanotechnology. One of the problems with which the risk assessment of nanoparticles is faced is the lack of data, resulting in uncertainty in the risk assessment. We attempt to quantify some of this uncertainty by expanding a previous deterministic study on nanosilica (5-200 nm) in food into a fully integrated probabilistic risk assessment. We use the integrated probabilistic risk assessment method in which statistical distributions and bootstrap methods are used to quantify uncertainty and variability in the risk assessment. Due to the large amount of uncertainty present, this probabilistic method, which separates variability from uncertainty, contributed to a better understandable risk assessment. We found that quantifying the uncertainties did not increase the perceived risk relative to the outcome of the deterministic study. We pinpointed particular aspects of the hazard characterization that contributed most to the total uncertainty in the risk assessment, suggesting that further research would benefit most from obtaining more reliable data on those aspects.

Exploring the uncertainties in cancer risk assessment using the integrated probabilistic risk assessment (IPRA) approach

Current methods for cancer risk assessment result in single values, without any quantitative information on the uncertainties in these values. Therefore, single risk values could easily be overinterpreted. In this study, we discuss a full probabilistic cancer risk assessment approach in which all the generally recognized uncertainties in both exposure and hazard assessment are quantitatively characterized and probabilistically evaluated, resulting in a confidence interval for the final risk estimate. The methodology is applied to three example chemicals (aflatoxin, N-nitrosodimethylamine, and methyleugenol). These examples illustrate that the uncertainty in a cancer risk estimate may be huge, making single value estimates of cancer risk meaningless. Further, a risk based on linear extrapolation tends to be lower than the upper 95% confidence limit of a probabilistic risk estimate, and in that sense it is not conservative. Our conceptual analysis showed that there are two possible basic approaches for cancer risk assessment, depending on the interpretation of the dose-incidence data measured in animals. However, it remains unclear which of the two interpretations is the more adequate one, adding an additional uncertainty to the already huge confidence intervals for cancer risk estimates.

Dietary exposure and risk assessment to lead of the population of Jiangsu province, China

The paper's main purpose is to estimate the dietary exposure to lead for the inhabitants of Jiangsu province, China. Lead concentration data were obtained from the national food contamination monitoring programme during 2007-10. Food samples (n = 2077) were collected from 23 food categories in Jiangsu province. Consumption data were derived from Chinese national nutrition and health survey in 2002, which included 3938 inhabitants from 1451 households in Jiangsu province. Concentration data were combined with consumption data to estimate the dietary intake for the inhabitants of 2-6, 7-17 and 18-80 years, respectively. The β-binomial-normal (BBN) model was used to estimate the long-term intake for the population in Jiangsu province. The distribution of individual margin of exposure (IMoE) was introduced to assess the health effect. Uncertainty of IMoE was quantified by Monte Carlo and bootstrap methods. The mean levels of dietary exposure to lead were estimated at 3.019 µg kg(-1) bw day(-1) for children aged 2-6 years, 2.104 µg kg(-1) bw day(-1) for teenagers aged 7-17 years, and 1.601 µg kg(-1) bw day(-1) for adults aged 18-80 years. The mean intakes for the urban and rural populations were 1.494 and 1.822 µg kg(-1) bw day(-1), respectively. From the 25th to 99.9th percentiles, IMoE was 0.125-2.057 for 2-6 years and 0.473-7.998 for 18-80 years, respectively. The distribution of IMoE could indicate a public health concern on lead for the Chinese population in Jiangsu. Control measures should be taken to reduce lead exposure in Jiangsu province.

Integrated testing strategies for safety assessments

Despite the fact that toxicology uses many stand-alone tests, a systematic combination of several information sources very often is required: Examples include: when not all possible outcomes of interest (e.g., modes of action), classes of test substances (applicability domains), or severity classes of effect are covered in a single test; when the positive test result is rare (low prevalence leading to excessive false-positive results); when the gold standard test is too costly or uses too many animals, creating a need for prioritization by screening. Similarly, tests are combined when the human predictivity of a single test is not satisfactory or when existing data and evidence from various tests will be integrated. Increasingly, kinetic information also will be integrated to make an in vivo extrapolation from in vitro data. Integrated Testing Strategies (ITS) offer the solution to these problems. ITS have been discussed for more than a decade, and some attempts have been made in test guidance for regulations. Despite their obvious potential for revamping regulatory toxicology, however, we still have little guidance on the composition, validation, and adaptation of ITS for different purposes. Similarly, Weight of Evidence and Evidence-based Toxicology approaches require different pieces of evidence and test data to be weighed and combined. ITS also represent the logical way of combining pathway-based tests, as suggested in Toxicology for the 21st Century. This paper describes the state of the art of ITS and makes suggestions as to the definition, systematic combination, and quality assurance of ITS.

Qalibra: a general model for food risk-benefit assessment that quantifies variability and uncertainty

The EU project BRAFO proposed a framework for risk-benefit assessment of foods, or changes in diet, that present both potential risks and potential benefits to consumers (Hoekstra et al., 2012a). In higher tiers of the BRAFO framework, risks and benefits are integrated quantitatively to estimate net health impact measured in DALYs or QALYs (disability- or quality-adjusted life years). This paper describes a general model that was developed by a second EU project, Qalibra, to assist users in conducting these assessments. Its flexible design makes it applicable to a wide range of dietary questions involving different nutrients, contaminants and health effects. Account can be taken of variation between consumers in their diets and also other characteristics relevant to the estimation of risk and benefit, such as body weight, gender and age. Uncertainty in any input parameter may be quantified probabilistically, using probability distributions, or deterministically by repeating the assessment with alternative assumptions. Uncertainties that are not quantified should be evaluated qualitatively. Outputs produced by the model are illustrated using results from a simple assessment of fish consumption. More detailed case studies on oily fish and phytosterols are presented in companion papers. The model can be accessed as web-based software at www.qalibra.eu.

Water pollution risk associated with natural gas extraction from the Marcellus Shale

In recent years, shale gas formations have become economically viable through the use of horizontal drilling and hydraulic fracturing. These techniques carry potential environmental risk due to their high water use and substantial risk for water pollution. Using probability bounds analysis, we assessed the likelihood of water contamination from natural gas extraction in the Marcellus Shale. Probability bounds analysis is well suited when data are sparse and parameters highly uncertain. The study model identified five pathways of water contamination: transportation spills, well casing leaks, leaks through fractured rock, drilling site discharge, and wastewater disposal. Probability boxes were generated for each pathway. The potential contamination risk and epistemic uncertainty associated with hydraulic fracturing wastewater disposal was several orders of magnitude larger than the other pathways. Even in a best-case scenario, it was very likely that an individual well would release at least 200 m³ of contaminated fluids. Because the total number of wells in the Marcellus Shale region could range into the tens of thousands, this substantial potential risk suggested that additional steps be taken to reduce the potential for contaminated fluid leaks. To reduce the considerable epistemic uncertainty, more data should be collected on the ability of industrial and municipal wastewater treatment facilities to remove contaminants from used hydraulic fracturing fluid.

Fish, contaminants and human health: quantifying and weighing benefits and risks

This paper describes a quantitative risk-benefit assessment of fish consumption. We compare the net health effect expressed in DALYs of two scenarios. The reference scenario is the current fish intake of the Dutch population, which is less than what is recommended by the health authorities. The alternative scenario describes the health effects if the population consumes 200g of fish per week, which is close to the recommendation. All health effects due to fish consumption for which there is convincing evidence are incorporated in the assessment. The QALIBRA software (www.qalibra.eu) is used to simulate the two scenarios. The results show there is a net benefit for the population if it consumes 200g of fish each week.

State of the art in benefit-risk analysis: food and nutrition

Benefit-risk assessment in food and nutrition is relatively new. It weighs the beneficial and adverse effects that a food (component) may have, in order to facilitate more informed management decisions regarding public health issues. It is rooted in the recognition that good food and nutrition can improve health and that some risk may be acceptable if benefit is expected to outweigh it. This paper presents an overview of current concepts and practices in benefit-risk analysis for food and nutrition. It aims to facilitate scientists and policy makers in performing, interpreting and evaluating benefit-risk assessments. Historically, the assessments of risks and benefits have been separate processes. Risk assessment is mainly addressed by toxicology, as demanded by regulation. It traditionally assumes that a maximum safe dose can be determined from experimental studies (usually in animals) and that applying appropriate uncertainty factors then defines the 'safe' intake for human populations. There is a minor role for other research traditions in risk assessment, such as epidemiology, which quantifies associations between determinants and health effects in humans. These effects can be both adverse and beneficial. Benefit assessment is newly developing in regulatory terms, but has been the subject of research for a long time within nutrition and epidemiology. The exact scope is yet to be defined. Reductions in risk can be termed benefits, but also states rising above 'the average health' are explored as benefits. In nutrition, current interest is in 'optimal' intake; from a population perspective, but also from a more individualised perspective. In current approaches to combine benefit and risk assessment, benefit assessment mirrors the traditional risk assessment paradigm of hazard identification, hazard characterization, exposure assessment and risk characterization. Benefit-risk comparison can be qualitative and quantitative. In a quantitative comparison, benefits and risks are expressed in a common currency, for which the input may be deterministic or (increasingly more) probabilistic. A tiered approach is advocated, as this allows for transparency, an early stop in the analysis and interim interaction with the decision-maker. A general problem in the disciplines underlying benefit-risk assessment is that good dose-response data, i.e. at relevant intake levels and suitable for the target population, are scarce. It is concluded that, provided it is clearly explained, benefit-risk assessment is a valuable approach to systematically show current knowledge and its gaps and to transparently provide the best possible science-based answer to complicated questions with a large potential impact on public health.

State of the art in benefit-risk analysis: food microbiology

Over the past years benefit-risk analysis (BRA) in relation to foods and food ingredients has gained much attention; in Europe and worldwide. BRA relating to food microbiology is however a relatively new field of research. Microbiological risk assessment is well defined but assessment of microbial benefits and the weighing of benefits and risk has not been systematically addressed. In this paper the state of the art in benefit-risk analysis in food microbiology is presented, with a brief overview of microbiological food safety practices. The quality and safety of foods is commonly best preserved by delaying the growth of spoilage bacteria and contamination by bacterial pathogens. However, microorganisms in food can be both harmful and beneficial. Many microorganisms are integral to various food production processes e.g. the production of beer, wine and various dairy products. Moreover, the use of some microorganisms in the production of fermented foods are often claimed to have beneficial effects on food nutrition and consumer health. Furthermore, food safety interventions leading to reduced public exposure to foodborne pathogens can be regarded as benefits. The BRA approach integrates an independent assessment of both risks and benefits and weighs the two using a common currency. Recently, a number of initiatives have been launched in the field of food and nutrition to address the formulation of the benefit-risk assessment approach. BRA has recently been advocated by EFSA for the public health management of food and food ingredients; as beneficial and adverse chemicals can often be found within the same foods and even the same ingredients. These recent developments in the scoping of BRA could be very relevant for food microbiological issues. BRA could become a valuable methodology to support evaluations and decision making regarding microbiological food safety and public health, supplementing other presently available policy making and administrative tools for microbiological food safety management.

Assessment of rare dietary risks based on analysis of food combinations

Probabilistic methods, in particular Monte Carlo methods, have become widely used in assessment of dietary risks from plant protection products. However, if the critical exposure occurs rarely, estimating its probability with commonly used Monte Carlo approaches can require an unrealistically big number of iterations. A simple method proposed in this paper, referred to as food combination analysis (FCA), finds out subsets of input values necessary for occurrence of a critical exposure event. In particular, for a critical event to occur consumption of a certain combination of contaminated foods could be required. Sometimes by finding the probability that such a food combination is consumed one could directly get an acceptable estimate of the risk, without Monte Carlo simulations. The method performs especially well if available data sets of consumed amounts of foods and residue concentrations of a chemical contain a large fraction of zeros. Based on a literature example, it is shown that the probability of the critical exposure estimated with the FCA could be more than 10 times lower than the estimate of a Monte Carlo approach with 50,000 iterations. The present approach also provides a platform for adaptation and development of more sophisticated methods to estimate low dietary risks.