Suchergebnisse

Abstract

Objectives
Methanogenic archaea have been found to make up part of the bioaerosols in pig, cattle, and poultry farms. So far no attempts have been made to determine how season, farm type, and farm characteristics may affect workers' exposure to archaea.


Methods
Personal filter samples from 327 farmers working on 89 Danish farms were analysed for the number of 16S rRNA gene copies from archaea and bacteria and for their dust and endotoxin content. The farms were visited during summer and winter. Information on farm type and stable characteristics were collected using self-reported activity diaries and walk-through surveys. Differences in archaea and bacteria levels with farm type and stable characteristics and correlations with dust and endotoxin levels were examined.


Results
Personal archaea exposure was documented in all farm types including, for the first time, during mink farming. At 7.3*104 gene copies m−3 the archaea levels were around two orders of magnitude lower than bacteria levels at 5.7*106 gene copies m−3. At 1.7*105 gene copies m−3 among pig farmers and 1.9*104 gene copies m−3 among cattle farmers the archaea levels differed with farm type (P < 0.0005). The archaea and bacteria levels correlated weakly with a Pearson correlation coefficient of 0.17. Neither archaea nor bacteria levels differed by season. In pig farms the archaea levels differed by type of ventilation and by wetness of the floor.


Conclusions
Archaea levels were not neglible and appeared to vary greatly between farm types. In pig farms they varied with some farm characteristics. Archaea levels appeared to depend on factors that differed from those of bacteria.

AbstractOccupational noise exposure is a known risk factor for hearing loss and also adverse cardiovascular effects have been suggested. A job exposure matrix (JEM) would enable studies of noise and health on a large scale. The objective of this study was to create a quantitative JEM for occupational noise exposure assessment of the general working population. Between 2001–2003 and 2009–2010, we recruited workers from companies within the 10 industries with the highest reporting of noise-induced hearing loss according to the Danish Working Environment Authority and in addition workers of financial services and children day care to optimize the range in exposure levels. We obtained 1343 personal occupational noise dosimeter measurements among 1140 workers representing 100 different jobs according to the Danish version of the International Standard Classification of Occupations 1988 (DISCO 88). Four experts used 35 of these jobs as benchmarks and rated noise levels for the remaining 337 jobs within DISCO 88. To estimate noise levels for all 372 jobs, we included expert ratings together with sex, age, occupational class, and calendar year as fixed effects, while job and worker were included as random effects in a linear mixed regression model. The fixed effects explained 40% of the total variance: 72% of the between-jobs variance, −6% of the between-workers variance and 4% of the within-worker variance. Modelled noise levels showed a monotonic increase with increasing expert score and a 20 dB difference between the highest and lowest exposed jobs. Based on the JEM estimates, metal wheel-grinders were among the highest and finance and sales professionals among the lowest exposed. This JEM of occupational noise exposure can be used to prioritize preventive efforts of occupational noise exposure and to provide quantitative estimates of contemporary exposure levels in epidemiological studies of health effects potentially associated with noise exposure.

Abstract

Background
Several measures of occupational exposure to pesticides have been used to study associations between exposure to pesticides and neurobehavioral outcomes. This study assessed the impact of different exposure measures for glyphosate and mancozeb on the association with neurobehavioral outcomes based on original and recalled self-reported data with 246 smallholder farmers in Uganda.


Methods
The association between the 6 exposure measures and 6 selected neurobehavioral test scores was investigated using linear multivariable regression models. Exposure measures included original exposure measures for the previous year in 2017: (i) application status (yes/no), (ii) number of application days, (iii) average exposure-intensity scores (EIS) of an application and (iv) number of EIS-weighted application days. Two additional measures were collected in 2019: (v) recalled application status and (vi) recalled EIS for the respective periods in 2017.


Results
Recalled applicator status and EIS were between 1.2 and 1.4 times more frequent and higher for both pesticides than the original application status and EIS. Adverse associations between the different original measures of exposure to glyphosate and 4 neurobehavioral tests were observed. Glyphosate exposure based on recalled information and all mancozeb exposure measures were not associated with the neurobehavioral outcomes.


Conclusions
The relation between the different original self-reported glyphosate exposure measures and neurobehavioral test scores appeared to be robust. When based on recalled exposure measures, associations observed with the original exposure measures were no longer present. Therefore, future epidemiological studies on self-reported exposure should critically evaluate the potential bias towards the null in observed exposure–response associations.

Abstract

Background
Occupational epidemiological studies on pesticide use commonly rely on self-reported questionnaire or interview data to assess exposure. Insight into recall accuracy is important, as misclassification of exposures due to imperfect recall can bias risk estimates.


Methods
We assessed the ability of workers in three UK cohorts (Prospective Investigation of Pesticide Applicators' Health [PIPAH], Pesticide Users' Health Study [PUHS], and Study of Health in Agricultural Work [SHAW]) to remember their working history related to pesticide exposure over time periods ranging from 3 to 14 years prior. During 2019–2020, cohort participants were re-surveyed using a similar questionnaire to that used previously. We compared recall of responses at follow-up to those reported at baseline related to crops/areas of work, use of personal protective equipment (PPE) items, hygiene habits, frequency of pesticide use, and application method. To assess the extent of recall, we used sensitivity, specificity, the percentage of overall agreement, and area under the curve (AUC) values. We also examined the presence of over or underestimation of recalled years, and days and hours per year, of working with pesticides using geometric mean ratios (GMR) and regression analysis to investigate any trends based on demographic characteristics.


Results
There were 643 individuals who completed both the baseline and follow-up surveys in the three cohorts with response rates ranging from 17 to 46%. There was a strong correlation (rho = 0.77) between the baseline and recalled years working with pesticides, though higher values were reported at follow-up (GMR = 1.18 [95% confidence interval: 1.07–1.30]) with no consistent differences by demographic characteristics. There was stronger agreement in the recalled days compared to hours per year in two of the cohorts. Recall for a number of exposure determinants across short and longer periods entailed overall agreement of &gt;70%, though with some differences: for example, sensitivity for long-term recall of crops was poor (&lt;43% in PUHS), whereas short-term recall of hygiene practices was good (AUC range = 0.65–1.00 in PIPAH).


Conclusion
Results indicate that recall ability may deteriorate over a longer period. Although low-response rates may require these findings to be interpreted with caution, recall for a number of exposure determinants appeared reliable, such as crops and hygiene practices within 3 years, as well as days per year working with pesticides.

Abstract
Tier 1 occupational exposure assessment tools recommended for use under the Registration, Evaluation, Authorization, and restriction of CHemicals (REACH) were evaluated using newly collected measurement data. Evaluated tools included the ECETOC TRAv2 and TRAv3, MEASEv1.02.01, and EMKG-EXPO-TOOL. Fifty-three exposure situations (ESs) based on tasks/chemicals were developed from National Institute for Occupational Safety and Health field surveys. During the field surveys, high quality contextual information required for evaluating the tools was also collected. For each ES, applicable tools were then used to generate exposure estimates using a consensus approach. Among 53 ESs, only those related to an exposure category of liquids with vapor pressure (VP) &gt; 10 Pa had sufficient numbers of exposure measurements (42 ESs with n = 251 for TRAv2 and TRAv3 and 40 ESs with n = 243 for EMKG-EXPO-TOOL) to be considered in detail. The results for other exposure categories (aqueous solutions, liquids with VP ≤ 10 Pa, metal processing, powders, and solid objects) had insufficient measurement to allow detailed analyses (results listed in the Supplementary File). Overall, EMKG-EXPO-TOOL generated more conservative results than TRAv2 and TRAv3 for liquids with high VP. This finding is at least partly due to the fact that the EMKG-EXPO-TOOL only considers pure substances and not mixtures of chemical agents. For 34 out of 40 ESs available for chemicals with VP &gt; 10 Pa, the liquid was a mixture rather than a pure substance. TRAv3 was less conservative than TRAv2, probably due to additional refinement of some input parameters. The percentages of exposure measurement results exceeding the corresponding tool estimates for liquids with VP &gt; 10 Pa by process category and by input parameters were always higher for TRAv3 compared to those for TRAv2. Although the conclusions of this study are limited to liquids with VP &gt; 10 Pa and few process categories, this study utilized the most transparent contextual information compared to previous studies, reducing uncertainty from assumptions for unknown input parameters. A further validation is recommended by collecting sufficient exposure data covering other exposure categories and all process categories under REACH.

Abstract

Objectives
A COVID-19 Job Exposure Matrix (COVID-19-JEM) has been developed, consisting of four dimensions on transmission, two on mitigation measures, and two on precarious work. This study aims to validate the COVID-19-JEM by (i) comparing risk scores assigned by the COVID-19-JEM with self-reported data, and (ii) estimating the associations between the COVID-19-JEM risk scores and self-reported COVID-19.


Methods
Data from measurements 2 (July 2020, n = 7690) and 4 (March 2021, n = 6794) of the Netherlands Working Conditions Survey-COVID-19 (NWCS-COVID-19) cohort study were used. Responses to questions related to the transmission risks and mitigation measures of Measurement 2 were used to calculate self-reported risk scores. These scores were compared with the COVID-19-JEM attributed risk scores, by assessing the percentage agreement and weighted kappa (κ). Based on Measurement 4, logistic regression analyses were conducted to estimate the associations between all COVID-19-JEM risk scores and self-reported COVID-19 (infection in general and infected at work).


Results
The agreement between the COVID-19-JEM and questionnaire-based risk scores was good (κ ≥ 0.70) for most dimensions, except work location (κ = 0.56), and face covering (κ = 0.41). Apart from the precarious work dimensions, higher COVID-19-JEM assigned risk scores had higher odds ratios (ORs; ranging between 1.28 and 1.80) on having had COVID-19. Associations were stronger when the infection were thought to have happened at work (ORs between 2.33 and 11.62).


Conclusions
Generally, the COVID-19-JEM showed a good agreement with self-reported infection risks and infection rates at work. The next step is to validate the COVID-19-JEM with objective data in the Netherlands and beyond.

Abstract
Wood dust is an established carcinogen also linked to several non malignant respiratory disorders. A major limitation in research on wood dust and its health effects is the lack of (historical) quantitative estimates of occupational exposure for use in general population-based case-control or cohort studies. The present study aimed to develop a multinational quantitative Job Exposure Matrix (JEM) for wood dust exposure using exposure data from several Northern and Central European countries. For this, an occupational exposure database containing 12653 personal wood dust measurements collected between 1978 and 2007 in Denmark, Finland, France, The Netherlands, Norway, and the United Kingdom (UK) was established. Measurement data were adjusted for differences in inhalable dust sampling efficiency resulting from the use of different dust samplers and analysed using linear mixed effect regression with job codes (ISCO-88) and country treated as random effects. Fixed effects were the year of measurement, the expert assessment of exposure intensity (no, low, and high exposure) for every ISCO-88 job code from an existing wood dust JEM and sampling duration. The results of the models suggest that wood dust exposure has declined annually by approximately 8%. Substantial differences in exposure levels between countries were observed with the highest levels in the United Kingdom and the lowest in Denmark and Norway, albeit with similar job rankings across countries. The jobs with the highest predicted exposure are floor layers and tile setters, wood-products machine operators, and building construction labourers with geometric mean levels for the year 1997 between 1.7 and 1.9 mg/m3. The predicted exposure estimates by the model are compared with the results of wood dust measurement data reported in the literature. The model predicted estimates for full-shift exposures were used to develop a time-dependent quantitative JEM for exposure to wood dust that can be used to estimate exposure for participants of general population studies in Northern European countries on the health effects from occupational exposure to wood dust.