Exposure Monitoring Strategies for Applying Low-Cost PM Sensors to Assess Flour Dust in Industrial Bakeries.

Low-cost particulate matter (PM) sensors provide new methods for monitoring occupational exposure to hazardous substances, such as flour dust. These devices have many possible benefits, but much remains unknown about their performance for different exposure monitoring strategies in the workplace. We explored the performance of PM sensors for four different monitoring strategies (time-weighted average and high time resolution, each quantitative and semi-quantitative) for assessing occupational exposure using low-cost PM sensors in a field study in the industrial bakery sector. Measurements were collected using four types of sensor (PATS+, Isensit, Airbeam2, and Munisense) and two reference devices (respirable gravimetric samplers and an established time-resolved device) at two large-scale bakeries, spread over 11 participants and 6 measurement days. Average PM2.5 concentrations of the low-cost sensors were compared with gravimetric respirable concentrations for 8-h shift periods and 1-min PM2.5 concentrations of the low-cost sensors were compared with time-resolved PM2.5 data from the reference device (quantitative monitoring strategy). Low-cost sensors were also ranked in terms of exposure for 8-h shifts and for 15-min periods with a shift (semi-quantitative monitoring strategy). Environmental factors and methodological variables, which can affect sensor performance, were investigated. Semi-quantitative monitoring strategies only showed more accurate results compared with quantitative strategies when these were based on shift-average exposures. The main factors that influenced sensor performance were the type of placement (positioning the devices stationary versus personal) and the company or workstation where measurements were collected. Together, these findings provide an overview of common strengths and drawbacks of low-cost sensors and different ways these can be applied in the workplace. This can be used as a starting point for further investigations and the development of guidance documents and data analysis methods.

Response Letter to Koivisto et al. 'Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool'.

In this article, we have responded to the key statements in the article by Koivisto et al. (2022) that were incorrect and considered to be a biased critique on a subset of the exposure models used in Europe (i.e. ART and Stoffenmanager®) used for regulatory exposure assessment. We welcome scientific discussions on exposure modelling (as was done during the ISES Europe workshop) and criticism based on scientific evidence to contribute to the advancement of occupational exposure estimation tools. The tiered approach to risk assessment allows various exposure assessment models from screening tools (control/hazard banding) through to higher-tiered approaches. There is a place for every type of model, but we do need to recognize the cost and data requirements of highly bespoke assessments. That is why model developers have taken pragmatic approaches to develop tools for exposure assessments based on imperfect data. We encourage Koivisto et al. to focus on further scientifically robust work to develop mass-balance models and by independent external validations studies, compare these models with alternative model tools such as ART and Stoffenmanager®.

The Dermal Advanced REACH Tool (dART): A Bayesian Model for Dermal Exposure Assessment.

The dermal Advanced REACH Tool (dART) is a tier 2 exposure model for estimating dermal exposure to the hands (mg min-1) for non-volatile liquid and solid-in-liquid products. The dART builds upon the existing ART framework and describes three mass transport processes (deposition (Dhands), direct emission and direct contact (Ehands), and contact transfer (Thands)) that may each contribute to dermal exposure. The mechanistic model that underpins the dART and calibration of the mechanistic model, such that the dimensionless score that results from encoding contextual information about a task into the determinants of the dART can be converted into a prediction of exposure (mg min-1), have been described in previous work. This paper completes the methodological framework of the dART model through placing the mechanistic model within a wider statistical modelling framework. A mixed-effects model, within a Bayesian framework, is presented for modelling the rate of dermal exposure per minute of activity. The central estimate of exposure for a particular task is provided by a calibrated mechanistic model (and thus based upon contextual information about a task). The model also describes between- and within-worker sources of variability in dermal exposure, with prior distributions for variance components based upon the literature. Estimates of exposure based upon informative prior distributions may be updated using measurement data associated with the task. The dART model is demonstrated using three worked examples, where estimates are initially obtained based upon the prior distributions alone, and then refined through accommodating measurement data on the tasks.

Parent-identified strengths of autistic youth.

LAY ABSTRACT: Autism is a condition frequently characterized by social and communication challenges. Because most research focuses on understanding and reducing challenges, less is known about the strengths of autistic individuals. This is especially true of those who are transitioning into adulthood. We designed this research study to provide information about how parents perceive the strengths of their autistic adolescent children prior to the transition. We reviewed 39 parent interviews from previous research about how they prepare their autistic sons and daughters for adulthood. Without prompting, parents identified many strengths of their autistic children. Diverse strengths and skills they identified included intelligence, creativity, physical abilities, and self-care skills. These strengths are interesting, as they cover traits that are often thought of as areas of difficulty for autistic youth. However, parents also talked about strengths alongside challenges, and how specific supports would be needed to help their sons and daughters fully realize their strengths. These findings are important, as they help us know more about the strengths of autistic youth and how strengths can be supported when preparing for adulthood. Our findings also help reveal strengths that are particularly apparent during the transition to adulthood.

Exploring Evaluation Variables for Low-Cost Particulate Matter Monitors to Assess Occupational Exposure.

(1) Background: Small, lightweight, low-cost optical particulate matter (PM) monitors are becoming popular in the field of occupational exposure monitoring, because these devices allow for real-time static measurements to be collected at multiple locations throughout a work site as well as being used as wearables providing personal exposure estimates. Prior to deployment, devices should be evaluated to optimize and quantify measurement accuracy. However, this can turn out to be difficult, as no standardized methods are yet available and different deployments may require different evaluation procedures. To gain insight in the relevance of different variables that may affect the monitor readings, six PM monitors were selected based on current availability and evaluated in the laboratory; (2) Methods: Existing strategies that were judged appropriate for the evaluation of PM monitors were reviewed and seven evaluation variables were selected, namely the type of dust, within- and between-device variations, nature of the power supply, temperature, relative humidity, and exposure pattern (peak and constant). Each variable was tested and analyzed individually and, if found to affect the readings significantly, included in a final correction model specific to each monitor. Finally, the accuracy for each monitor after correction was calculated; (3) Results: The reference materials and exposure patterns were found to be main factors needing correction for most monitors. One PM monitor was found to be sufficiently accurate at concentrations up to 2000 µg/m3 PM2.5, with other monitors appropriate at lower concentrations. The average accuracy increased by up to three-fold compared to when the correction model did not include evaluation variables; (4) Conclusions: Laboratory evaluation and readings correction can greatly increase the accuracy of PM monitors and set boundaries for appropriate use. However, this requires identifying the relevant evaluation variables, which are heavily reliant on how the monitors are used in the workplace. This, together with the lack of current consensus on standardized procedures, shows the need for harmonized PM monitor evaluation methods for occupational exposure monitoring.

Calibration of the Dermal Advanced REACH Tool (dART) Mechanistic Model.

The dermal Advanced REACH Tool (dART) is a Tier 2 exposure modelling tool currently in development for estimating dermal exposure to the hands (mg min-1) for non-volatile liquid and solids-in-liquid products. The dART builds upon the existing ART framework and describes three mass transport processes [deposition (Dhands), direct emission and direct contact (Ehands), and contact transfer (Thands)] that may each contribute to dermal exposure. The mechanistic model that underpins the dART and its applicability domain has already been described in previous work. This paper describes the process of calibrating the mechanistic model such that the dimensionless score that results from encoding contextual information about a task into the determinants of the dART can be converted into a prediction of exposure (mg min-1). Furthermore, as a consequence of calibration, the uncertainty in a dART prediction may be quantified via a confidence interval. Thirty-six experimental studies were identified that satisfied the conditions of: (i) high-quality contextual information that was sufficient to confidently code the dART mechanistic model determinants; (ii) reliable exposure measurement data sets were available. From these studies, 40 exposure scenarios were subsequently developed. A non-linear log-normal mixed-effect model was fitted to the data set of Dhands,   Ehands, and    Thands scores and corresponding measurement data. The dART model was shown to be consistent with activities covering a broad range of tasks [spray applications, activities involving open liquid surfaces (e.g. dipping, mixing), handling of contaminated objects, spreading of liquid products, and transfer of products (e.g. pouring of liquid)]. Exposures resulting from a particular task were each dominated by one or two of the identified mass transport processes. As a consequence of calibration, an estimate of the uncertainty associated with a mechanistic model estimate is available. A 90% multiplicative interval is approximately a factor of six. This represents poorer overall precision than the (inhalation) ART model for dusts and vapours, although better than the ART model for mists. Considering the complexity of the conceptual model compared with the ART, the wide variety of exposure scenarios considered with differing dominant routes, and the particular challenges that result from the consideration of measurement data both above and beneath a protective glove, the precision of the calibrated dART mechanistic model is reasonable for well-documented exposure scenarios coded by experts. However, as the inputs to the model are based upon user judgement, in practical use, the reliability of predictions will be dependent upon both the competence of users and the quality of contextual information available on an exposure scenario.

Dermal Advanced REACH Tool (dART)-Development of a Dermal Exposure Model for Low-Volatile Liquids.

This article describes the development of a mechanistic model for underpinning the dermal Advanced REACH Tool (dART), an extension of the existing ART model and its software platform. It was developed for hand exposure to low volatile liquids (vapour pressure ≤ 10 Pa at 20°C) including solids-in-liquid products. The model is based on an existing conceptual dermal source-receptor model that has been integrated into the ART framework. A structured taxonomy of workplace activities referred to as activity classes are adopted from ART. Three key processes involved in mass transport associated with dermal exposure are applied, i.e. deposition, direct emission and contact, and transfer. For deposition, the model adopts all the relevant modifying factors (MFs) applied in ART. In terms of direct emission and contact (e.g. splashes) and transfer (e.g. hand-surface contacts), the model defines independent principal MFs, i.e. substance-related factors, activity-related factors, localized- and dispersion control and exposed surface area of the hands. To address event-based exposures as much as possible, the model includes crucial events during an activity (e.g. hand immersions) and translates objective information on tools and equipment (manual or automated) to probable events (e.g. splashes) and worker behaviours (e.g. surface contacts). Based on an extensive review of peer-reviewed literature and unpublished field studies, multipliers were assigned to each determinant and provide an approximated (dimensionless) numerical value. In the absence of (sufficient) evidence, multipliers were assigned to determinants based on assumptions made during discussions by experts in the consortium. A worked example is presented to illustrate the calculation of hand exposure for a specific scenario. The dART model is not yet implemented in the ART software platform, and a robust validation of the model is necessary to determine its predictive ability. With advancing knowledge on dermal exposure and its determinants, this model will require periodic updates and refinements, in addition to further expansion of the applicability domain of the model.

A microsimulation model for the development and progression of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a chronic lung disease that is thought to affect over one million people in Great Britain. The main factor contributing to the development of COPD is tobacco smoke. This paper presents a microsimulation model for the development of COPD, incorporating population dynamics and trends in smoking. The model simulates a population longitudinally throughout their lifetimes, providing projections of future COPD prevalence and evaluation of the effects of changes in risk factor prevalence such as smoking. Sensitivity analysis provides information on the most influential model parameters. The model-predicted prevalence of COPD in 2040 was 17% in males over the age of 35 years (13% amongst non-smokers and 22% amongst smokers), and a modest decline over the next 25 years due to recent trends in smoking rates. The simulation model provides us with valuable information on current and future trends in COPD in Great Britain. It was developed primarily to enable easy extension to evaluate the effects of occupational and environmental exposures on lung function and the prevalence of COPD and to allow evaluation of interventions, such as introducing health surveillance or policy changes. As longitudinal studies for investigating COPD are difficult due to the lengthy follow-up time required and the potentially large number of drop-outs, we anticipate that the model will provide a valuable tool for health impact assessment. An extended model for occupational exposures is under development and will be presented in a subsequent paper.

Inter- and intra-individual variation in urinary biomarker concentrations over a 6-day sampling period. Part 1: metals.

The aim of the current HBM-study is to further the understanding of the impact of inter- and intra-individual variability in HBM surveys as it may have implications for the design and interpretation of the study outcomes. As spot samples only provide a snapshot in time of the concentrations of chemicals in an individual, it remains unclear to what extent intra-individual variability plays a role in the overall variability of population-wide HBM surveys. The current paper describes the results of an intensive biomonitoring study, in which all individual urine samples of 8 individuals were collected over a 6-day sampling period (a total of 352 unique samples). By analyzing different metals (As, Cd, Mn, Ni) in each individual sample, inter- and intra-individual variability for these four metals could be determined, and the relationships between exposure, internal dose, and sampling protocol assessed. Although the range of biomarker values for different metals was well within the normal range reported in large-scale population surveys, large intra-individual differences over a 6-day period could also be observed. Typically, measured biomarker values span at least an order of magnitude within an individual, and more if specific exposure episodes could be identified. Fish consumption for example caused a twenty- to thirty-fold increase in urinary As-levels over a period of 2-6h. Intra-class correlation coefficients (ICC) were typically low for uncorrected biomarker values (between 0.104 and 0.460 for the 4 metals), but improved when corrected for creatinine or specific gravity (SG). The results show that even though urine is a preferred matrix for HBM studies, there are certain methodological issues that need to be taken into account in the interpretation of urinary biomarker data, related to the intrinsic variability of the urination process itself, the relationship between exposure events and biomarker quantification, and the timing of sampling. When setting up HBM-projects, this expected relationship between individual exposure episode and urinary biomarker concentration needs to be taken into account.

Advanced REACH Tool (ART): overview of version 1.0 and research needs.

This paper provides an outline of the Advanced REACH Tool (ART) version 1.0 and a discussion of how it could be further developed. ART is a higher tier exposure assessment tool that combines mechanistically modelled inhalation exposure predictions with available exposure data using a Bayesian approach. ART assesses exposure for scenarios across different plants and sites. Estimates are provided for different percentiles of the exposure distribution and confidence intervals around the estimate. It also produces exposure estimates in the absence of data, but uncertainty of the estimates will decrease when results of exposure measurements are included. The tool has been calibrated using a broad range of exposure data and provides estimates for exposure to vapours, mists, and dusts. ART has a robust and stable conceptual basis but will be refined in the future and should therefore be considered an evolving system. High-priority areas for future research are identified in this paper and include the integration of partially analogous measurement series, inclusion of company and site-specific assessments, user decision strategies linked to ART predictions, evaluation of validity and reliability of ART, exploring the possibilities for incorporating the dermal route and integration of ART predictions with tools for modelling internal dose. ART is initially developed in the scope of REACH but is equally useful for exposure assessment in other areas.

Advanced Reach Tool (ART): development of the mechanistic model.

This paper describes the development of the mechanistic model within a collaborative project, referred to as the Advanced REACH Tool (ART) project, to develop a tool to model inhalation exposure for workers sharing similar operational conditions across different industries and locations in Europe. The ART mechanistic model is based on a conceptual framework that adopts a source receptor approach, which describes the transport of a contaminant from the source to the receptor and defines seven independent principal modifying factors: substance emission potential, activity emission potential, localized controls, segregation, personal enclosure, surface contamination, and dispersion. ART currently differentiates between three different exposure types: vapours, mists, and dust (fumes, fibres, and gases are presently excluded). Various sources were used to assign numerical values to the multipliers to each modifying factor. The evidence used to underpin this assessment procedure was based on chemical and physical laws. In addition, empirical data obtained from literature were used. Where this was not possible, expert elicitation was applied for the assessment procedure. Multipliers for all modifying factors were peer reviewed by leading experts from industry, research institutes, and public authorities across the globe. In addition, several workshops with experts were organized to discuss the proposed exposure multipliers. The mechanistic model is a central part of the ART tool and with advancing knowledge on exposure, determinants will require updates and refinements on a continuous basis, such as the effect of worker behaviour on personal exposure, 'best practice' values that describe the maximum achievable effectiveness of control measures, the intrinsic emission potential of various solid objects (e.g. metal, glass, plastics, etc.), and extending the applicability domain to certain types of exposures (e.g. gas, fume, and fibre exposure).

Classification of occupational activities for assessment of inhalation exposure.

There is a large variety of activities in workplaces that can lead to emission of substances. Coding systems based on determinants of emission have so far not been developed. In this paper, a system of Activity Classes and Activity Subclasses is proposed for categorizing activities involving chemical use. Activity Classes share their so-called 'emission generation mechanisms' and physical state of the product handled and the underlying determinants of emission. A number of (industrial) stakeholders actively participated in testing and fine-tuning the system. With the help of these stakeholders, it was found to be relatively easy to allocate a large number of activities to the Activity Classes and Activity Subclasses. The system facilitates a more structured classification of activities in exposure databases, a structured analysis of the analogy of exposure activities, and a transparent quantification of the activity emission potential in (new) exposure assessment models. The first use of the system is in the Advanced REACH Tool.

What is the best strategy to reduce the burden of occupational asthma and allergy in bakers?

RATIONALE: Insight into the effectiveness of intervention strategies will help realise a decrease in the occupational disease burden from (allergic) respiratory diseases in the bakery population. OBJECTIVES: To use a simulation model to assess the impact of different intervention strategies on the disease burden of the bakery population over time. METHODS: A recently developed dynamic population based model was used to prospectively evaluate the impact on disease burden resulting from different intervention strategies. We distinguished interventions based on exposure reductions for flour dust and fungal α-amylase, health surveillance combined with reduction in exposure, and pre-employment screening. MAIN RESULTS: The impact of most interventions on disease burden was limited, generally less than 50% for lower respiratory symptoms and disabling occupational asthma. Only the rigorous health surveillance strategy, identifying workers who are sensitised or report upper respiratory symptoms and decreasing their individual exposures by 90% shortly after diagnosis, resulted in a decrease of almost 60% in disease burden after 20 years. CONCLUSIONS: This study demonstrates that different intervention strategies have substantially different impacts on the burden of disease. The time window during which changes occur differs considerably between strategies. This information can assist policy makers in their choice of intervention and gives guidance for achievable reductions in disease burden.

Variability of biomarkers in volunteer studies: The biological component.

Biological monitoring has become one of the methods to measure exposure, with the advantage that it gives information about the concentration of a substance that actually enters the body and reflects the inter-individual differences in uptake and metabolic variation. However, limited information is available on inter- and intra-individual variability of biomarkers. The aim of this study was to gather information about the biological component of inter-individual variation in biomarkers using results from volunteer studies. Open literature and other (internal) sources were searched to find human volunteer studies utilizing biological monitoring. Ultimately 41 studies were included in our analysis, with a total of 6747 observations for one or more biomarkers from 223 volunteers. The data from these studies were grouped on the basis of study, substance under investigation, exposure route, biological matrix, exposure duration, dose and number of exposure events to obtain 278 homogeneous groups (strata) for statistical analysis. Variability was assessed in two ways. Firstly, estimates of biomarker half-life were calculated for each individual, thereby allowing the estimation of inter-individual variability in half-lives within the homogeneous groups. Secondly, variation in biomarker concentrations at a given time point was estimated. For estimated half-lives the GSDs ranged from 1.0 to 6.8. The variability in estimated half-lives did not differ much for the different types of substances. For concentrations at a given time point the average GSDs within strata ranged from 1.0 to 5.6. Again, variability did not differ much for different groups (e.g., type of substance). The median variability component was 0.11 (range 0-3.0). In conclusion, volunteer studies enable the estimation of both variation in half-lives and variation in biomarker levels in the well-defined homogeneous groups. Comparison of our results with other studies indicates that variation due to biological differences within and between people is quite substantial in homogeneous exposure groups. The relative contribution of this biological component to the total variation will be smaller when variance components are estimated in less homogeneous groups, such as those in occupational and environmental settings.

Conceptual model for assessment of inhalation exposure: defining modifying factors.

The present paper proposes a source-receptor model to schematically describe inhalation exposure to help understand the complex processes leading to inhalation of hazardous substances. The model considers a stepwise transfer of a contaminant from the source to the receptor. The conceptual model is constructed using three components, i.e. (i) the source, (ii) various transmission compartments and (iii) the receptor, and describes the contaminant's emission and its pattern of transport. Based on this conceptual model, a list of nine mutually independent principal modifying factors (MFs) is proposed: activity emission potential, substance emission potential, localized control, separation, segregation, dilution, worker behavior, surface contamination and respiratory protection. These MFs describe the exposure process at a high level of abstraction so that the model can be generically applicable. A list of exposure determinants underlying each of these principal MFs is proposed to describe the exposure process at a more detailed level. The presented conceptual model is developed in conjunction with an activity taxonomy as described in a separate paper. The proposed conceptual model and MFs should be seen as 'building blocks' for development of higher tier exposure models.

"Doing the heavy lifting: health care workers take back their backs".

Health care workers have the highest musculoskeletal disorder prevalence and incidence of any occupational/industry group, and patient handling tasks are so biomechanically demanding that they cannot be made safe through the commonly used, technique-oriented methods such as "back school" training programs. Although there is standard-setting activity for "no-lift" programs in some states, there is still no federal standard. Health care worker unions and nurses' associations have begun to take action through training members in equipment need, use, and acceptance in programs to encourage adoption of no-lifting programs. Acceptance of lifting equipment is increasing due to recognition of the high human and economic costs of MSD, consistent documentation of cost savings from no-lift programs, major improvements in lifting equipment, and shortages of health care staff. An action-oriented training program for health care workers is described that provides knowledge about the 1) Scope of the current problem of back injuries in health care, 2) Costs of injuries, both to workers and to the hospital, 3) Elements of a safe patient-handling program, and 4) Success stories. The program also builds skills through: 1) Hands-on experience with safe lifting equipment, and 2) Assessing organizational and union readiness and planning for action at the workplace.

Tools for regulatory assessment of occupational exposure: development and challenges.

REACH (Registration, Evaluation and Authorization of CHemicals) requires improved exposure models that can be incorporated into screening tools and refined assessment tools. These are referred to as tier 1 and 2 models, respectively. There are a number of candidate in tier 1 models that could be used with REACH. Tier 2 models, producing robust and realistic exposure assessments, are currently not available. A research programme is proposed in this paper that will result in a new, advanced exposure assessment tool for REACH. In addition, issues related to variability and uncertainty are discussed briefly, and some examples of tier 1 screening tools are presented. The proposed framework for the tier 2 tool is based on a Bayesian approach, and makes full use of mechanistically modelled estimates and any relevant measurements of exposure. The new approach will preclude the necessity to conduct of case-by-case exposure measurements for each chemical and scenario, since the system will allow for the use of analogous exposure data from relatively comparable scenarios. The development of the new approach requires substantial effort in the area of mechanistic modelling, database development and Bayesian statistical techniques. In this paper, the data gaps and areas for future research are identified to help realise and further improve this type of approach within REACH. A structured data collection and storage system is a central element of the research programme and the availability of this type of tool may also facilitate the sharing of exposure data down and up the supply chain. In addition, new data that are stored according to the proposed structure could enable the validation of any exposure model and thus this programme enhances the exposure assessment field as a whole.

Correlation of haemoglobin-acrylamide adducts with airborne exposure: an occupational survey.

This paper reports an occupational hygiene survey of exposure to acrylamide comparing acrylamide haemoglobin adduct measurements with personal air monitoring and glove liner analysis. The air monitoring data showed that exposure to acrylamide was well-controlled with all samples below the UK maximum exposure limit (MEL) of 300 microg/m(3) with mean exposure about one tenth of the MEL. Each worker provided two blood samples approximately 3 months apart. These samples were well correlated (r=0.61) with a slope of 0.74, indicating that exposure was reasonably constant. Mean personal airborne acrylamide levels and mean acrylamide haemoglobin adduct levels were well correlated (r=0.72, N=46) and using the calculated linear correlation, exposure at the MEL would be expected to give rise to a haemoglobin adduct level of 1,550 pmol/g globin. Smoking status did not affect the correlation. There was also a correlation between levels of acrylamide detected on gloves and haemoglobin adduct levels. A combined regression model between haemoglobin adducts, airborne acrylamide and acrylamide glove contamination was significant for both airborne acrylamide and gloves with a regression coefficient of 0.89. The study showed that haemoglobin adduct level was a good biomarker of acrylamide exposure which correlated to both inhaled and potentially skin absorbed acrylamide estimates. There was excellent discrimination between well-controlled occupational levels and environmental levels from diet and smoking, allowing haemoglobin adduct measurement to be used to determine even low level exposures. Due to the complexity of the current methodology, new techniques would be useful in making haemoglobin adducts more widely applicable.

Violence in healthcare facilities: lessons from the Veterans Health Administration.

GOALS: The authors examined assault frequency and risk factors in health care. METHODS: The authors conducted a cross-sectional questionnaire survey in 142 hospitals. Analyses are presented at the level of the individual and aggregated by facility. RESULTS: Thirteen percent of employees described at least 1 assault in the last year; the proportion assaulted per facility ranged from 1% to 26%. Patients were the most common assaulters. Working in geriatrics, mental health, and rehabilitation or in nursing represented a high risk for assault. Hours of work and work patterns represented major risk factors for assault, as were higher measures of organizational stress. The penetration of training in alternate dispute resolution strategies was associated with lower rates of assaults. CONCLUSIONS: Although work in health care is associated with high rates of assaults, closer scrutiny suggests specific possible intervention strategies.

Vibration exposure and disease in a shipyard: a 13-year revisit.

BACKGROUND: In a 1988 study of shipyard workers, a progressive association was observed between cumulative exposure to vibration and the vascular and neurological symptoms of the hand-arm vibration syndrome (HAVS). In 2001, after a decade of exposure reduction and ageing of the workforce, a second study at the same site was initiated. METHODS: In 2001, 214 subjects were selected; they represented four current weekly vibration exposure time intervals--0 hr, >0 < 5 hr, > or =5 < 20 hr, > or =20 hr. The 1988 and 2000 cross-sectional populations were compared on the basis of exposure duration and current symptoms. RESULTS: In 2001, the study population was 9.6 years older than the 1988 group. Current weekly exposure hours were similar in the low and medium exposure groups 2001 and 1988, but exposure was reduced by an average of 9.7 hr per week in the highest exposure group (> or =20 hr) in 2001. Symptom severity was regressed polychotomously on estimated exposure (log cumulative hours); the OR was weaker in 2001 than in 1988 for sensorineural symptoms-1.44 [CI 1.04-1.98] versus 2.35 [CI 1.48-3.73]. This was also true for vascular symptoms-1.70 [CI 1.06-2.71] versus 3.99 [CI 2.27-7.01]. Vascular symptoms were more prevalent in the highest lifetime vibration exposure group in 1988 (68.7 vs. 43.2% in 2001); sensorineural symptoms were more prevalent in the least vibration exposed group in 2001 (52.6 vs. 20.7% in 1988). CONCLUSIONS: The prevalence of vascular symptoms associated with cumulative vibratory exposure was significantly greater in 1988, but neurological symptoms were more common at lower exposure levels in 2001. The presumption that reducing exposure duration alone is sufficient, in the absence of change in vibration magnitude, is not supported by the results of this study.