Job-exposure Matrices Research Articles

Association between ocular diseases and screen time and sedentary time derived from job-exposure matrices

After developing job-exposure matrices (JEMs) for screen and sedentary time, we aimed to assess the associations between the JEM-derived exposures and various ocular diseases. We collected data from patients hospitalized from 2005 to 2021. JEMs were developed from 41,718 patients with occupational information and screen and sedentary times. The adjusted means of screen and sedentary time were calculated for 143 occupational groups and categorized into three classes based on the tertiles. The associations between ocular diseases and these JEM-derived exposures were examined using multivariable conditional logistic regression for 727,589 patients. The odds ratios of the class with highest screen time were 1.05 (95% confidence interval, 1.01–1.09) for cataract, 1.24 (1.06–1.45) for primary open-angle glaucoma (POAG), 1.26 (1.06–1.49) for rhegmatogenous retinal detachment (RRD), 1.49 (1.26–1.76) for ptosis, and 0.39 (0.27–0.57) for pterygium. The odds ratios of the class with highest sedentary time were 1.05 (1.01–1.09) for cataract, 1.24 (1.05–1.46) for RRD, 1.68 (1.42–1.99) for ptosis, and 0.60 (0.42–0.84) for pterygium. Both screen and sedentary time were positively associated with cataract, RRD and ptosis. Interestingly, POAG had a positive association with only screen time. Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary."I have confirmed that the content is correct. No amendments are necessary.Please check article title if captured correctly."?>"I have confirmed that the content is correct. No amendments are necessary.

Workplace Exposures Vary Across Neighborhoods in the US: Implications on Social Vulnerability and Racial/Ethnic Health Disparities.

Ignoring workplace exposures that occur beyond the local residential context in place-based risk indices like the CDC's Social Vulnerability Index (SVI) likely misclassifies community exposure by under-counting risks and obscuring true drivers of racial/ethnic health disparities. To investigate this hypothesis, we developed several place-based indicators of occupational exposure and examined their relationships with race/ethnicity, SVI, and health inequities. We used publicly available job exposure matrices and employment estimates from the United States (US) Census to create and map six indicators of occupational hazards for every census tract in the US. We characterized census tracts with high workplace-low SVI scores. We used natural cubic splines to examine tract level associations between the percentage of racial/ethnic minorities (individuals who are not non-Hispanic White) and the occupational indicators. Lastly, we stratified each census tract into high/low occupational noise, chemical pollutant, and disease/infection exposure to examine racial/ethnic health disparities to diabetes, asthma, and high blood pressure, respectively, as a consequence of occupational exposure inequities. Our results show that racial/ethnic minority communities, particularly those that are also low-income, experience a disproportionate burden of workplace exposures that may be contributing to racial/ethnic health disparities. When composite risk measures, such as SVI, are calculated using only information from the local residential neighborhood, they may systematically under-count occupational risks experienced by the most vulnerable communities. There is a need to consider the role of occupational justice on nationwide, racial/ethnic health disparities.

Validity of an expert-based job exposure matrix of hand-wrist physical exposures and their prospective associations with carpal tunnel syndrome.

Epidemiological studies of occupational risk factors for rare disorders require large study populations with adequate exposure estimates. Job exposure matrices (JEMs) linked to national information on standardized job titles may enable such large studies. We aimed to establish and validate a JEM for occupational hand-wrist exposures that could be linked to Danish national register data on job titles and hand-wrist disorders. We developed a JEM for hand-wrist repetition, force, vibration, and computer work in 96 job groups covering 91% of the 2227 occupational titles in the Danish version of the International Standard Classification of Occupation-88, and examined inter-rater reliability of five expert ratings. Poisson regression models were used to estimate incidence rate ratios for the association of carpal tunnel syndrome (CTS) with the level of repetitive movements, force, vibration, and hours of computer work described by the JEM, adjusted for relevant confounders. The JEM based on expert ratings had fair to good interrater reliability. The incidence of CTS increased with increasing levels of force, hand-wrist repetition, and vibration, Exposure-response patterns for repetition and vibration became less consistent after adjustment for force. The interaction between repetition and force was complex and did not support an overall positive interaction. Computer work was negatively associated with incident CTS. The JEM was able to identify known risk factors for CTS consistent with current evidence, and provided further associations on exposure-response patterns, mutual exposure adjustment, and interaction effects between repetition and force. The reliability of expert assessments of hand-wrist physical exposures was fair to good.

Use of a job exposure matrix to predict the risk of work disability in individuals with back pain: An inception cohort study.

Low back pain has a high economic burden in Germany due to back pain-related sick leave, disability pensions, and health care utilization. Work-related factors can predict disabling back pain. Job exposure matrices can be used to consider job demands and occupational characteristics in routine data analysis. This longitudinal analysis tested whether rehabilitation utilization due to musculoskeletal disorders is associated with occupation-linked job exposures in employees with back pain. Data from a German cohort study were used, including employees aged 45 to 59 years with self-reported back pain in the last three months. Individuals' job titles were assessed in the baseline survey in 2017 and matched with parameters of aggregated job exposure indices. Administrative data from the German Pension Insurance were used to extract information on rehabilitation utilization. Proportional hazard models tested the associations. We considered data of 6,569 participants (mean age: 52.3 years; 57.7% women). During follow-up, with a maximum of 21 months, 296 individuals (4.5%) utilized medical rehabilitation due to musculoskeletal disorders. Adjusted analyses showed that high physical (HR = 2.87; 95% CI 1.74; 4.75) and overall (HR = 2.34; 95% CI 1.44; 3.80) job exposures were associated with a higher risk of rehabilitation utilization. Individuals with back pain working in occupations with high physical job exposures have a higher risk for rehabilitation utilization. To prevent work disability in individuals with back pain, occupational groups with high physical job exposures should be actively informed about tailored intervention options.

Exposure to fibres and risk of pleural mesothelioma in the Norwegian Offshore Petroleum Workers cohort

ObjectivesPleural mesothelioma is a rare respiratory cancer, mainly caused by inhalation of asbestos fibres. Other inorganic fibres are also suggested risk factors. We aimed to investigate the association between exposure...

Exposure and Illness Among Workers Filing for COVID-19-Related Workers' Compensation-California, 2020.

The aim of the study is to characterize the incidence of SARS-CoV-2 exposure and COVID-19 infection among California workers' compensation claims in 2020 and examine risk factors for exposure. Using a case-control approach, we combined machine learning techniques and job exposure matrices to assess associations between exposures and illness claims and clusters of claims within specific worksites over a 3-week period. Of the 117,125 COVID-19 claims, most were primarily among younger groups, of shorter tenure, and from health care occupations. Illness claims were among older groups with longer tenure. Jobs with very close physical proximity and high physical activity, along with transportation and warehousing industries, were associated with being part of a cluster of claims. The findings merit further study but indicate respiratory viral transmission and support efforts to systematically incorporate work-related variables into other California data sources.

Development of a crosswalk to convert French PCS2003 into international ISCO88 occupational classifications. Application to the Occupational Asthma-specific Job-Exposure Matrix (OAsJEM).

The problem of transcoding is recurrent when researchers wish to link occupational data from cohorts to Job-Exposure Matrices (JEMs) which were not set up in the same classifications. The Occupational Asthma-specific JEM (OAsJEM) is a JEM developed for assessing exposure to agents known at risk for asthma for jobs coded with ISCO88 occupation classification. To apply the OAsJEM in the CONSTANCES cohort, in which jobs and industries were coded with French PCS2003 and NAF2008 classifications respectively, we developed a crosswalk to convert jobs from PCS2003 into ISCO88 classification. This work was carried out by 2 skilled coders and 1 novice coder who have worked independently by using different tools and transcoding strategies defined a priori. Consensus meetings were organized with skilled coders to define the final crosswalk. This work was elaborated in 2 steps: (i) for 38 ISCO88 codes classified as potentially exposed to cleaning and disinfection products by the OAsJEM, and (ii) for all jobs from the ISCO88 classification. A comparison between the 3 initial coder's crosswalk proposals and the final crosswalk was made for the 38 ISCO codes in step (i). The final crosswalk provided 998 matches between the 482 4-digit PCS2003 codes, 308 4-digit ISCO88 codes, and 31 3-digit ISCO88 codes. Information regarding the NAF2008 industry classification was also used in some cases to improve the final crosswalk. For the selected 38 ISCO88 codes, the final crosswalk provided 110 combinations, but the number of proposed ISCO88-PCS2003 couples by each of the 3 coders varied greatly from 68 to 153. In addition, an important variability between the 3 coders were observed among the number of common combinations between the initial coder's proposals and the final crosswalk (from 47% to 78%). We have developed a crosswalk specifically for an application of the OAsJEM in population-based surveys using the PCS2003 occupation classification. The development of this crosswalk is of great interest for the use of OAsJEM on the data of the CONSTANCES cohort and on any other survey with occupational data coded according to the French classifications. This OAsJEM crosswalk could be used by other teams to evaluate occupational exposures known to be at risk of asthma from occupational calendars coded with French classifications.

Risk of hypersensitivity pneumonitis and other interstitial lung diseases following organic dust exposure

BackgroundOrganic dust is associated with hypersensitivity pneumonitis, and associations with other types of interstitial lung disease (ILD) have been suggested. We examined the association between occupational organic dust exposure and...

Supporting the working life exposome: Annotating occupational exposure for enhanced literature search.

An individual's likelihood of developing non-communicable diseases is often influenced by the types, intensities and duration of exposures at work. Job exposure matrices provide exposure estimates associated with different occupations. However, due to their time-consuming expert curation process, job exposure matrices currently cover only a subset of possible workplace exposures and may not be regularly updated. Scientific literature articles describing exposure studies provide important supporting evidence for developing and updating job exposure matrices, since they report on exposures in a variety of occupational scenarios. However, the constant growth of scientific literature is increasing the challenges of efficiently identifying relevant articles and important content within them. Natural language processing methods emulate the human process of reading and understanding texts, but in a fraction of the time. Such methods can increase the efficiency of both finding relevant documents and pinpointing specific information within them, which could streamline the process of developing and updating job exposure matrices. Named entity recognition is a fundamental natural language processing method for language understanding, which automatically identifies mentions of domain-specific concepts (named entities) in documents, e.g., exposures, occupations and job tasks. State-of-the-art machine learning models typically use evidence from an annotated corpus, i.e., a set of documents in which named entities are manually marked up (annotated) by experts, to learn how to detect named entities automatically in new documents. We have developed a novel annotated corpus of scientific articles to support machine learning based named entity recognition relevant to occupational substance exposures. Through incremental refinements to the annotation process, we demonstrate that expert annotators can attain high levels of agreement, and that the corpus can be used to train high-performance named entity recognition models. The corpus thus constitutes an important foundation for the wider development of natural language processing tools to support the study of occupational exposures.

Benzene exposure and risk of lung cancer in the Norwegian Offshore Petroleum Worker cohort: a prospective case-cohort study

ObjectiveThe objective of our study was to examine whether occupational exposure to benzene is associated with lung cancer among males in the Norwegian Offshore Petroleum Workers cohort.MethodsAmong 25 347 male...

Return to work after cancer-the impact of working conditions: A Norwegian Register-based Study.

The purpose of this study is to compare a cohort of cancer survivors with a cohort of cancer-free employees (1) with respect to employment prospects over a 15-year period and (2) with respect to the differential impact of working conditions on employment over this time period. The cancer cohort is retrieved from the Cancer Registry of Norway, while data on the non-cancer cohort are retrieved from register data managed by Statistics Norway. Job exposure matrices were used to remedy the lack of working-conditions information in the register data. We use nearest-neighbor matching to match the non-cancer cohort (the control group) to the cancer-survivor cohort (the treatment group). Cox regression analysis was applied to examine the relationships between working conditions, employment, and cancer. The results are reported separately for mechanical-job exposures and psychosocial exposures, as well as by gender. Cancer survivors are more likely to experience reduced employment as compared to individuals without a history of cancer. Male cancer survivors in physically demanding occupations have an increased risk of reduced employment after being diagnosed with cancer. This does not apply to female cancer survivors. Regarding the impact of psychosocial exposures on employment, we find no differences over time between cancer survivors and the non-cancer population. Male cancer survivors in physically demanding occupations have an increased risk of reduced employment after being diagnosed with cancer, whereas this is not the case for female cancer survivors. Psychosocial exposures do not impact the relative risk of reduced employment over time. We suggest that return to work after cancer should be considered a process rather than only the re-entry step of resuming work. Thus, it is important to provide long-term support for cancer survivors. We recommend providing more attention to working conditions, particularly in occupations that involve a high level of mechanical-job exposures.

Development of a job-exposure matrix-like exposure assessment method for the US general population based on Occupational Information Network (O*NET) job tasks.

Job-exposure matrices (JEMs) are often used for exposure assessment in occupational exposure and epidemiology studies. However, general population JEMs are difficult to find and access for workers in the United States of America. We aimed to use publicly available information to develop a JEM-like exposure assessment method to determine exposure to a wide range of occupational agents in a wide range of occupations for US general population studies. We used information from the US Department of Labor's Occupational Information Network database (O*NET) for 19,636 job tasks and 974 civilian occupations. We used automated keyword searches to identify 1,804 job tasks that involved exposure to 50 occupational agents. We had 2 reviewers determine whether each identified job task actually involved exposure to the 50 occupational agents. We had a third reviewer, a certified industrial hygienist, assess any job task and exposure for which the first 2 reviewers disagreed. For each U.S. Census 2010 occupation code, we used this information to derive 3 exposure variables for each occupational agent: ever exposure, number of job tasks of exposure, and frequency of exposure. Our keyword searches identified a median of 10 (interquartile range [IQR]: 43.75) job tasks for each occupational agent, and the maximum was 308. We determined job tasks actually involved exposure to 45 occupational agents, including solvents, air pollution, pesticides, radiation, metals, etc. We derived the 3 exposure variables for these 45 occupational agents for 516 U.S. Census 2010 occupation codes. The median percentage for ever exposure to individual occupational agents was 1.16% (IQR: 1.74%), and the maximum was 11.43%. Our JEM-like exposure assessment method based on O*NET information can be used to determine exposure to a wide range of occupational agents in a wide range of occupations for the US general population.

Occupational quantitative exposure to crystalline silica, solvents and pesticides and risk of clinical forms of systemic sclerosis

Abstract Objectives To estimate the association between SSc clinical phenotypes and quantitative occupational exposure to crystalline silica, chlorinated solvents, trichloroethylene and pesticides using job-exposure matrices. Methods In the VISS-EXPOSITION transversal study, data on declarative occupational exposure to crystalline silica, solvents and pesticides were retrieved. In parallel, the lifetime occupational history was evaluated using a questionnaire and cursus laboris for SSc patients followed at Bordeaux University Hospital (France). Using job-exposure matrices, we assessed patients’ occupational exposure in relation to relevant clinical phenotypic forms of the disease. Results Toxic exposure to crystalline silica and pesticides is underestimated by patients. Non-biased job-exposure matrices retrieved more exposed patients than the declarative assessment (10.1% of patients by job-exposure matrices vs 6.3% by declaration for crystalline silica and 25.9% vs 12.2% for pesticides). Patients overestimate their solvent exposure (7.9% for chlorinated solvents and 4.8% for trichlorethylene assessed by job-exposure matrices and 24.4% declarative exposure to solvents at large). Clinical form evaluation revealed a non-significant trend toward an increased risk of crystalline silica occupational exposure in the pulmonary fibrotic group of SSc patients [odds ratio (OR) 3.12 (95% CI 0.80, 12.15)]. We also observed a non-significant trend toward an elevated OR ([2.89 (95% CI 0.93, 8.95)] for chlorinated solvent occupational exposure and the vascular phenotype of SSc. Of note, pesticide occupational exposure evaluation represents one of the largest to date in SSc patients. Conclusion This study emphasizes that many exposed SSc patients are unaware of their occupational exposure. Job-exposure matrices allow better exposure screening for SSc secondary prevention and occupational exposure compensation. Clinical trial registration clinicaltrials.gov (https://www.clinicaltrials.gov), NCT03543956

Artificial intelligence exceeds humans in epidemiological job coding

BackgroundWork circumstances can substantially negatively impact health. To explore this, large occupational cohorts of free-text job descriptions are manually coded and linked to exposure. Although several automatic coding tools have been developed, accurate exposure assessment is only feasible with human intervention.MethodsWe developed OPERAS, a customizable decision support system for epidemiological job coding. Using 812,522 entries, we developed and tested classification models for the Professions et Catégories Socioprofessionnelles (PCS)2003, Nomenclature d’Activités Française (NAF)2008, International Standard Classifications of Occupation (ISCO)-88, and ISCO-68. Each code comes with an estimated correctness measure to identify instances potentially requiring expert review. Here, OPERAS’ decision support enables an increase in efficiency and accuracy of the coding process through code suggestions. Using the Formaldehyde, Silica, ALOHA, and DOM job-exposure matrices, we assessed the classification models’ exposure assessment accuracy.ResultsWe show that, using expert-coded job descriptions as gold standard, OPERAS realized a 0.66–0.84, 0.62–0.81, 0.60–0.79, and 0.57–0.78 inter-coder reliability (in Cohen’s Kappa) on the first, second, third, and fourth coding levels, respectively. These exceed the respective inter-coder reliability of expert coders ranging 0.59–0.76, 0.56–0.71, 0.46–0.63, 0.40–0.56 on the same levels, enabling a 75.0–98.4% exposure assessment accuracy and an estimated 19.7–55.7% minimum workload reduction.ConclusionsOPERAS secures a high degree of accuracy in occupational classification and exposure assessment of free-text job descriptions, substantially reducing workload. As such, OPERAS significantly outperforms both expert coders and other current coding tools. This enables large-scale, efficient, and effective exposure assessment securing healthy work conditions.

Association between psychosocial working conditions and well-being before retirement: a community-based study

ABSTRACT Psychosocial working conditions have been linked to mental health outcomes, but their association with well-being is poorly studied. We aimed to investigate the association between psychosocial working conditions and well-being before retirement, and to explore the role of gender and leisure activities in the association. From the Swedish National Study on Aging and Care in Kungsholmen, 598 community dwellers aged 60–65 years were included in the cross-sectional study. Lifelong occupational history was obtained through an interview. Job demands and job control in the longest-held occupation were graded with job exposure matrices. Psychosocial working conditions were classified into high strain (high demands, low control), low strain (low demands, high control), passive job (low demands, low control), and active job (high demands, high control). Well-being was assessed with the 10-item version of positive and negative affect schedule, and scored using confirmatory factor analysis. Engagement in leisure activities was categorized as low, moderate, and high. Data were analyzed using linear regression. Both high job control and high job demands were dose-dependently associated with higher well-being. Overall, compared to active jobs, passive jobs were associated with lower well-being (β −0.19, 95% CI −0.35 to −0.02, P = 0.028). Passive (β −0.28, 95% CI −0.51 to −0.04, P = 0.020) and high strain (β −0.31, 95% CI −0.52 to −0.10, P = 0.004) jobs were associated with lower well-being in men, but not in women. The association between passive jobs and well-being was attenuated by high leisure activities, while the association between high strain and well-being was magnified by low leisure activities. In conclusion, negative psychosocial working conditions are associated with poor well-being, especially in men. Leisure activities may modulate the association. Our study highlights that promoting favorable working conditions can be a target to improve well-being among employees and active participation in leisure activities is encouraged to cope with work-related stress for better well-being.

Long-term sickness absence among adults with ADHD: the role of psychosocial working conditions

Abstract Background Symptoms of Attention-deficit/hyperactivity disorder (ADHD) do not only occur during childhood but often persist into adulthood and affect individuals’ ability to work. Adults with ADHD compared to those without ADHD are at a higher risk of negative labour market outcomes, such as long-term sickness absence (LTSA). Identifying modifiable factors in the workplace such as psychosocial working conditions may be a plausible strategy to lower this risk. This study aimed to investigate the effect modification of job control and job demands on the risk of LTSA among adults with ADHD. Methods The study population consisted of around 3.7 million individuals aged 20-60 years in Sweden in 2009. Of them, 0.3% had a diagnosis of ADHD extracted from the national patient registers. LTSA was defined as having one sick-leave spell of 90 days or more between 2010-2020. Job control and job demands were measured using job exposure matrices. Multivariable Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of LTSA among adults with ADHD compared to those without. Stratified analysis was conducted to test the effect modification by job demand-control status. Results During the follow-up, 812,971 (22%) adults had LTSA. Both men and women with a diagnosis of ADHD were at a higher risk of LTSA (HR 1.75, 95% CI 1.68-1.82 and HR 1.61, 95% CI 1.55-1.68, respectively) compared to those without ADHD, after adjusting for demographics, previous LTSA, and other mental and somatic disorders. The increased risk of LTSA among adults with ADHD was present regardless of the levels of job control, job demands and job demand-control categories (HRs ranged from 1.55 to 2.10). Conclusions Adults with a diagnosis of ADHD have a higher risk of LTSA and job demand-control status does not seem to substantially modify this risk. Future studies identifying factors in the workplace that may potentially help prevent LTSA among adults with ADHD are highly warranted. Key messages • Adults with ADHD have a higher risk of LTSA regardless of the job demand-control status. • There is an urgent need to identify factors that may help improve the work ability of this population.

The role of working conditions in educational differences in ischemic heart disease mortality

Abstract Background The educational gradient in cardiovascular mortality is well established, but still not completely understood. One important mechanism may be working conditions. This study aims to investigate the extent to which job control and heavy physical workload explain educational differences in ischemic heart disease (IHD) mortality while also accounting for risk factors established in childhood and adolescence. Methods This register-based cohort study is based on men who completed their mandatory conscription (age 18-20) for the Swedish military in 1969/1970. This includes 37,419 men who also had a registered occupation in 2005. IHD mortality was measured in the cause of death register. Educational differences in IHD mortality, followed between 2006 and 2019, were measured using Cox proportional hazards regression models. Models were first adjusted for socioeconomic, cognitive, health and behavioral factors measured in childhood and during conscription. Models were further adjusted for physical workload and job control in 2005 (measured during mid-50s). These occupational exposures were measured using Job Exposure Matrices (JEM). Percent attenuation in hazard ratios (HR) after adjustment were calculated using the formula ((HR crude-HR adjusted)/(HRcrude-1))*100. Results Crude models showed a clear educational gradient regarding IHD mortality (HR 2.67, 95% confidence interval 2.08-3.42 for the lowest educated compared to the highest educated). Adjusting for earlier risk factors resulted in a 39-50% reduction in HR estimates. Further adjusting for physical workload and job control resulted in around 75% reductions compared to the crude model. Conclusions Physical workload and job control explained around 25% of the increased risk of IHD mortality in those with lower education. Improvement of the physical and psychosocial work environment could lead to a reduction in IHD mortality and smaller educational differences. Key messages • Physical workload and job control played an important role in educational differences in IHD even when accounting for a variety of early life risk factors. • Improving the physical and psychosocial work environment could lead to a lower incidence of IHD deaths and reduced educational inequalities.

Psychosocial work factors and sickness absence among young Danish workers with a disease history

Abstract Background Young workers with a disease history may be more sensitive to adverse work environment, which could lead to increased rates of sickness absence (SA). This study investigates the association between psychosocial work factors and SA among young Danish workers with a history of somatic or mental disorders (N = 39,772). Methods We included young workers (aged 15-30) with a history of hospital-diagnosed somatic or mental disorders before labor market entry (between 2010 and 2018). SA spells of any length (≥1 day) were measured in registers and psychosocial work factors were estimated on the occupational level using job exposure matrices. We separately estimated adjusted rate ratios (RR) and 95% confidence intervals (95% CI) for women and men using Poisson regressions. Results Among women, employment in occupations with high quantitative demands, low decision authority, high job strain, high emotional demands, or high work-related physical violence was associated with higher rates of SA. Employment in occupations with high vs. low emotional demands showed the strongest association with a RR of 1.56 (95% CI: 1.48-1.65). Among men, employment in occupations with low decision authority showed the strongest association (1.40 [1.32-1.48]). In contrast, employment in occupations with high quantitative demands or high job strain was associated with lower rates of SA. Conclusions In a large nationwide sample of young workers with a history of somatic or mental disorders, we found several psychosocial work factors associated with SA at the job group level. Associations were overall similar to previously published results on all young workers. The results indicate that young workers with a history of somatic or mental disorders may not be more sensitive to adverse working conditions concerning the risk of SA and that preventive interventions, toward reducing SA, may have a similar impact regardless of disease history. Key messages • Several psychosocial working conditions were associated at the job group level with sickness absence in a nationwide sample of young workers with a disease history. • Associations were similar to previous results indicating that young workers with a disease history may not be more sensitive to adverse working conditions compared to the overall workforce.

Impact of occupational pesticide exposure on the human gut microbiome.

The rising use of pesticides in modern agriculture has led to a shift in disease burden in which exposure to these chemicals plays an increasingly important role. The human gut microbiome, which is partially responsible for the biotransformation of xenobiotics, is also known to promote biotransformation of environmental pollutants. Understanding the effects of occupational pesticide exposure on the gut microbiome can thus provide valuable insights into the mechanisms underlying the impact of pesticide exposure on health. Here we investigate the impact of occupational pesticide exposure on human gut microbiome composition in 7198 participants from the Dutch Microbiome Project of the Lifelines Study. We used job-exposure matrices in combination with occupational codes to retrieve categorical and cumulative estimates of occupational exposures to general pesticides, herbicides, insecticides and fungicides. Approximately 4% of our cohort was occupationally exposed to at least one class of pesticides, with predominant exposure to multiple pesticide classes. Most participants reported long-term employment, suggesting a cumulative profile of exposure. We demonstrate that contact with insecticides, fungicides and a general "all pesticides" class was consistently associated with changes in the gut microbiome, showing significant associations with decreased alpha diversity and a differing beta diversity. We also report changes in the abundance of 39 different bacterial taxa upon exposure to the different pesticide classes included in this study. Together, the extent of statistically relevant associations between gut microbial changes and pesticide exposure in our findings highlights the impact of these compounds on the human gut microbiome.

Trajectories of psychosocial working conditions and all-cause and cause-specific mortality: a Swedish register-based cohort study.

While psychosocial working conditions have been associated with morbidity, their associations with mortality, especially cause-specific mortality, have been less studied. Additionally, few studies considered the time-varying aspect of exposures. We aimed to examine trajectories of job demand-control status in relation to all-cause and cause-specific mortality, including cardiovascular diseases (CVD), suicide, and alcohol-related mortality. The study population consisted of around 4.5 million individuals aged 16-60 years in Sweden in 2005. Job control and demands were respectively measured using job exposure matrices (JEM). Trajectories of job control and demands throughout 2005-2009 were identified using group-based trajectory modelling, and job demand-control categories were subsequently classified. Deaths in 2010-2019 were recorded in the national cause of death register. Cox regression models were used. A total of 116 242 individuals died in 2010-2019. For both job control and demands, we identified four trajectories, which were parallel to each other and represented four levels of exposures. Low control and passive jobs were associated with higher all-cause, CVD, and suicide mortality among both men and women. High strain jobs were associated with higher all-cause and CVD mortality among men, while low control, passive jobs, and high strain jobs were associated with higher alcohol-related mortality among women. The trajectories identified may suggest stable levels of job control and demands over time. Poor psychosocial working conditions are related to all-cause and cause-specific mortality, and these patterns vary to some extent between men and women.