Toxicity Weighting for Human Biomonitoring Mixture Risk Assessment: A Proof of Concept.

Chemical mixture risk assessment has, in the past, primarily focused on exposures quantified in the external environment. Assessing health risks using human biomonitoring (HBM) data provides information on the internal concentration, from which a dose can be derived, of chemicals to which human populations are exposed. This study describes a proof of concept for conducting mixture risk assessment with HBM data, using the population-representative German Environmental Survey (GerES) V as a case study. We first attempted to identify groups of correlated biomarkers (also known as 'communities', reflecting co-occurrence patterns of chemicals) using a network analysis approach (n = 515 individuals) on 51 chemical substances in urine. The underlying question is whether the combined body burden of multiple chemicals is of potential health concern. If so, subsequent questions are which chemicals and which co-occurrence patterns are driving the potential health risks. To address this, a biomonitoring hazard index was developed by summing over hazard quotients, where each biomarker concentration was weighted (divided) by the associated HBM health-based guidance value (HBM-HBGV, HBM value or equivalent). Altogether, for 17 out of the 51 substances, health-based guidance values were available. If the hazard index was higher than 1, then the community was considered of potential health concern and should be evaluated further. Overall, seven communities were identified in the GerES V data. Of the five mixture communities where a hazard index was calculated, the highest hazard community contained N-Acetyl-S-(2-carbamoyl-ethyl)cysteine (AAMA), but this was the only biomarker for which a guidance value was available. Of the other four communities, one included the phthalate metabolites mono-isobutyl phthalate (MiBP) and mono-n-butyl phthalate (MnBP) with high hazard quotients, which led to hazard indices that exceed the value of one in 5.8% of the participants included in the GerES V study. This biological index method can put forward communities of co-occurrence patterns of chemicals on a population level that need further assessment in toxicology or health effects studies. Future mixture risk assessment using HBM data will benefit from additional HBM health-based guidance values based on population studies. Additionally, accounting for different biomonitoring matrices would provide a wider range of exposures. Future hazard index analyses could also take a common mode of action approach, rather than the more agnostic and non-specific approach we have taken in this proof of concept.

A Review of Workplace Risk Management Measures for Nanomaterials to Mitigate Inhalation and Dermal Exposure.

This review describes an evaluation of the effectiveness of Risk Management Measures (RMM) for nanomaterials in the workplace. Our aim was to review the effectiveness of workplace RMM for nanomaterials and to determine whether established effectiveness values of conventional chemical substances applied for modelling purposes should be adopted or revised based on available evidence. A literature review was conducted to collate nano-specific data on workplace RMM. Besides the quantitative efficacy values, the library was populated with important covariables such as the study design, measurement type, size of particles or agglomerates/aggregates, and metrics applied. In total 770 records were retrieved from 41 studies for three general types of RMM (engineering controls, respiratory equipment and skin protective equipment: gloves and clothing). Records were found for various sub-categories of the different types of RMM although the number of records for each was generally limited. Significant variation in efficacy values was observed within RMM categories while also considering the respective covariables. Based on a comparative evaluation with efficacy values applied for conventional substances, adapted efficacy values are proposed for various RMM sub-categories (e.g. containment, fume cupboards, FFP2 respirators). It is concluded that RMM efficacy data for nanomaterials are limited and often inconclusive to propose effectiveness values. This review also shed some light on the current knowledge gaps for nanomaterials related to RMM effectiveness (e.g. ventilated walk-in enclosures and clean rooms) and the challenges foreseen to derive reliable RMM efficacy values from aggregated data in the future.

Work-related factors associated with occupational exposure to static magnetic stray fields from MRI scanners.

PURPOSE: This study aims to identify work-related and personal factors associated with workers' exposure to static magnetic fields (SMF) and motion-induced time-varying magnetic fields (TVMF) from MRI scanners. METHODS: Measurements of personal exposure to SMF and TVMF were performed among MRI staff during 439 work shifts at 14 different workplaces using portable magnetic field dosimeters. These data were coupled with contextual workplace and worker information. After data cleanup, 324 remaining observations were used to develop linear mixed effects models for various measures of peak and time-weighted average (TWA) exposure. RESULTS: Exposure levels near whole-body closed-bore scanners increased by 30% to 76% for each additional tesla of scanner strength, depending on exposure metric. Small-bore animal scanners, on the other hand, showed a reversed association with scanner strength. Measures of peak and TWA exposure were differently associated with specific tasks and scan procedures. In addition, body height of the worker was negatively associated with measured exposure levels. CONCLUSION: The study revealed workplace characteristics, scan activities, and personal characteristics associated with SMF and TVMF exposure levels of MRI staff and was able to quantify the unique contribution of each of these factors while adjusting for the presence of others.

Does assessment of personal exposure matter during experimental neurocognitive testing in MRI-related magnetic fields?

PURPOSE: To determine whether the use of quantitative personal exposure measurements in experimental research would result in better estimates of the associations between static and time-varying magnetic field exposure and neurocognitive test performance than when exposure categories were based solely on distance to the magnetic field source. METHODS: In our original analysis, based on distance to the magnet of a 7 T MRI scanner, an effect of exposure to static magnetic fields was observed. We performed a sensitivity analysis of test performance on a reaction task and line bisection task with different exposure measures that were derived from personal real-time measurements. RESULTS: The exposure measures were highly comparable, and almost all models resulted in significant associations between exposure to time-varying magnetic fields within a static magnetic field and performance on a reaction and line bisection task. CONCLUSION: In a controlled experimental setup, distance to the bore is a good proxy for personal exposure when placing subjects at fixed positions with standardized head movements in the magnetic stray fields of a 7 T MRI. Use of a magnetic field dosimeter is, however, important for estimating quantitative exposure response associations.

Exposure to static and time-varying magnetic fields from working in the static magnetic stray fields of MRI scanners: a comprehensive survey in the Netherlands.

Clinical and research staff who work around magnetic resonance imaging (MRI) scanners are exposed to the static magnetic stray fields of these scanners. Although the past decade has seen strong developments in the assessment of occupational exposure to electromagnetic fields from MRI scanners, there is insufficient insight into the exposure variability that characterizes routine MRI work practice. However, this is an essential component of risk assessment and epidemiological studies. This paper describes the results of a measurement survey of shift-based personal exposure to static magnetic fields (SMF) (B) and motion-induced time-varying magnetic fields (dB/dt) among workers at 15 MRI facilities in the Netherlands. With the use of portable magnetic field dosimeters, >400 full-shift and partial shift exposure measurements were collected among various jobs involved in clinical and research MRI. Various full-shift exposure metrics for B and motion-induced dB/dt exposure were calculated from the measurements, including instantaneous peak exposure and time-weighted average (TWA) exposures. We found strong correlations between levels of static (B) and time-varying (dB/dt) exposure (r = 0.88-0.92) and between different metrics (i.e. peak exposure, TWA exposure) to express full-shift exposure (r = 0.69-0.78). On average, participants were exposed to MRI-related SMFs during only 3.7% of their work shift. Average and peak B and dB/dt exposure levels during the work inside the MRI scanner room were highest among technical staff, research staff, and radiographers. Average and peak B exposure levels were lowest among cleaners, while dB/dt levels were lowest among anaesthesiology staff. Although modest exposure variability between workplaces and occupations was observed, variation between individuals of the same occupation was substantial, especially among research staff. This relatively large variability between workers with the same job suggests that exposure classification based solely on job title may not be an optimal grouping strategy for epidemiological purposes.

Occupational exposure of healthcare and research staff to static magnetic stray fields from 1.5-7 Tesla MRI scanners is associated with reporting of transient symptoms.

OBJECTIVES: Limited data is available about incidence of acute transient symptoms associated with occupational exposure to static magnetic stray fields from MRI scanners. We aimed to assess the incidence of these symptoms among healthcare and research staff working with MRI scanners, and their association with static magnetic field exposure. METHODS: We performed an observational study among 361 employees of 14 clinical and research MRI facilities in The Netherlands. Each participant completed a diary during one or more work shifts inside and/or outside the MRI facility, reporting work activities and symptoms (from a list of potentially MRI-related symptoms, complemented with unrelated symptoms) experienced during a working day. We analysed 633 diaries. Exposure categories were defined by strength and type of MRI scanner, using non-MRI shifts as the reference category for statistical analysis. Non-MRI shifts originated from MRI staff who also participated on MRI days, as well as CT radiographers who never worked with MRI. RESULTS: Varying per exposure category, symptoms were reported during 16-39% of the MRI work shifts. We observed a positive association between scanner strength and reported symptoms among healthcare and research staff working with closed-bore MRI scanners of 1.5 Tesla (T) and higher (1.5 T OR=1.88; 3.0 T OR=2.14; 7.0 T OR=4.17). This finding was mainly driven by reporting of vertigo and metallic taste. CONCLUSIONS: The results suggest an exposure-response association between exposure to strong static magnetic fields (and associated motion-induced time-varying magnetic fields) and reporting of transient symptoms on the same day of exposure. TRIAL REGISTRATION NUMBER: 11-032/C.

Inventory of MRI applications and workers exposed to MRI-related electromagnetic fields in the Netherlands.

OBJECTIVE: This study aims to characterise and quantify the population that is occupationally exposed to electromagnetic fields (EMF) from magnetic resonance imaging (MRI) devices and to identify factors that determine the probability and type of exposure. MATERIALS AND METHODS: A questionnaire survey was used to collect information about scanners, procedures, historical developments and employees working with or near MRI scanners in clinical and research MRI departments in the Netherlands. RESULTS: Data were obtained from 145 MRI departments. A rapid increase in the use of MRI and field strength of the scanners was observed and quantified. The strongest magnets were employed by academic hospitals and research departments. Approximately 7000 individuals were reported to be working inside an MRI scanner room and were thus considered to have high probability of occupational exposure to static magnetic fields (SMF). Fifty-four per cent was exposed to SMF at least one day per month. The largest occupationally exposed group were radiographers (n ~ 1700). Nine per cent of the 7000 involved workers were regularly present inside a scanner room during image acquisition, when exposure to additional types of EMF is considered a possibility. This practice was most prevalent among workers involved in scanning animals. CONCLUSION: The data illustrate recent trends and historical developments in magnetic resonance imaging and provide an extensive characterisation of the occupationally exposed population. A considerable number of workers are potentially exposed to MRI-related EMF. Type and frequency of potential exposure depend on the job performed, as well as the type of workplace.

JEMs and incompatible occupational coding systems: effect of manual and automatic recoding of job codes on exposure assignment.

BACKGROUND: In epidemiological studies, occupational exposure estimates are often assigned through linkage of job histories to job-exposure matrices (JEMs). However, available JEMs may have a coding system incompatible with the coding system used to code the job histories, necessitating a translation of the originally assigned job codes. Since manual recoding is usually not feasible in large studies, this is often done by use of automated crosswalks translating job codes from one system to another. We set out to investigate whether automatically translating job codes led to different exposure estimates compared with those resulting from manual recoding using the original job descriptions. METHODS: One hundred job histories were randomly drawn from the Netherlands Cohort Study on diet and cancer (NLCS), using a sampling strategy designed to oversample potentially exposed jobs. This resulted in 220 job codes that were automatically translated from the original Dutch coding system to the International Standard Classification of Occupations (ISCO)-68 and ISCO-88 as well as manually recoded from the job descriptions in the original questionnaire by two coders. Exposure to several agents (i.e. chromium, asbestos, silica, pesticides, aromatic solvents, and extremely low-frequency magnetic fields) was assigned by JEMs based on job codes resulting from automatic and manual recodings. RESULTS: The agreement between occupational exposure estimates based on the crosswalk versus those based on manual recoding reached a Cohen's Kappa (κ) of 0.66 or higher and were similar to the agreements between the two coders. CONCLUSIONS: Results of this study indicate that using automated crosswalks to recode job codes from one occupational classification system to another results only in a limited loss in agreement in assigned occupational exposure estimates compared with direct manual recoding. Therefore, in this case, crosswalks provide an efficient alternative to the costly and time-consuming direct manual recoding from job history descriptions from questionnaires.