Farming activities and risk of inflammatory bowel disease: a French nationwide population-based cohort study.

BACKGROUND AND AIMS: Epidemiological data regarding inflammatory bowel disease (IBD) are lacking, in particular for occupationally exposed populations. We investigated whether, among the entire French farm manager (FM) workforce, certain agricultural activities are more strongly associated with IBD than others. METHODS: Nationwide population-based insurance claims and electronic health records from all FMs that worked at least once over the period 2002-2016 were used (n=1088561, 69% males). The outcome measure was the association between 26 farming activities and the risk of IBD, Crohn's disease (CD), and ulcerative colitis (UC), measured as hazard ratios (HRs), after adjusting for age, sex, pre-existing medical comorbidities, and farm location. The time to first chronic disease declaration was used as the underlying timescale. A model was generated for every activity and disease, utilizing a reference group comprising all FMs who abstained from the specified activity from 2002 to 2016. RESULTS: There were 1752 IBD cases, with 704 CD (40.2%) and 1048 UC (59.8%) cases, respectively. Elevated HRs were observed for fruit arboriculture (HR from 1.17 to 1.52) and dairy farming (HR from 1.22 to 1.46) for all IBD, in crop farming for CD only (HR=1.26 [95CI%: 1.06-1.49]), and in shellfish farming (HR from 2.12 to 2.51) for both CD and IBD. CONCLUSIONS: Further research regarding specific farming activities and exposures likely to modify the microbiota (e.g., pesticides, pathogens) is required to identify potential occupational risk factors (agricultural exposome) for IBD. Exposure to Mycobacterium avium subspecies paratuberculosis, cryptosporidium, environmental toxins, micro/nanoplastics, and pesticides represents promising research avenues.

Farming activity and risk of treated thyroid disorders: Insights from the TRACTOR project, a nationwide cohort study.

BACKGROUND: Epidemiological data regarding thyroid diseases are lacking, in particular for occupationally exposed populations. OBJECTIVES: To compare the risk of hypothyroidism and hyperthyroidism between farming activities within the complete population of French farm managers (FMs). METHODS: Digital health data from retrospective administrative databases, including insurance claims and electronic health/medical records, was employed. This cohort data spanned the entirety of French farm managers (FMs) who had undertaken work at least once from 2002 to 2016. Survival analysis with the time to initial medication reimbursement as timescale was used to examine the association (hazard ratio, HR) between 26 specific farming activities and both treated hypothyroidism and hyperthyroidism. A distinct model was developed for each farming activity, comparing FMs who had never engaged in the specific farming activity between 2002 and 2016 with those who had. All analyses were adjusted for potential confounders (e.g., age), and sensitivity analyses were conducted. RESULTS: Among 1088561 FMs (mean age 46.6 [SD 14.1]; 31% females), there were 31834 hypothyroidism cases (75% females) and 620 hyperthyroidism cases (67% females), respectively. The highest risks were observed for cattle activities for both hyperthyroidism (HR ranging from 1.75 to 2.42) and hypothyroidism (HR ranging from 1.41 to 1.44). For hypothyroidism, higher risks were also observed for several animal farming activities (pig, poultry, and rabbit), as well as fruit arboriculture (HR = 1.22 [1.14-1.31]). The lowest risks were observed for activities involving horses. Sex differences in the risk of hypothyroidism were observed for eight activities, with the risk being higher for males (HR = 1.09 [1.01-1.20]) than females in viticulture (HR = 0.97 [0.93-1.00]). The risk of hyperthyroidism was two times higher for male dairy farmers than females. DISCUSSION: Our findings offer a comprehensive overview of thyroid disease risks within the FM community. Thyroid ailments might not stem from a single cause but likely arise from the combined effects of various causal agents and triggering factors (agricultural exposome). Further investigation into distinct farming activities-especially those involving cattle-is essential to pinpoint potential risk factors that could enhance thyroid disease monitoring in agriculture.

Agricultural activities and risk of Alzheimer's disease: the TRACTOR project, a nationwide retrospective cohort study.

Data regarding Alzheimer's disease (AD) occurrence in farming populations is lacking. This study aimed to investigate whether, among the entire French farm manager (FM) workforce, certain agricultural activities are more strongly associated with AD than others, using nationwide data from the TRACTOR (Tracking and monitoring occupational risks in agriculture) project. Administrative health insurance data (digital electronic health/medical records and insurance claims) for the entire French agricultural workforce, over the period 2002-2016, on the entire mainland France were used to estimate the risk of AD for 26 agricultural activities with Cox proportional hazards model. For each analysis (one for each activity), the exposed group included all FMs that performed the activity of interest (e.g. crop farming), while the reference group included all FMs who did not carry out the activity of interest (e.g. FMs that never farmed crops between 2002 and 2016). There were 5067 cases among 1,036,069 FMs who worked at least one year between 2002 and 2016. Analyses showed higher risks of AD for crop farming (hazard ratio (HR) = 3.72 [3.47-3.98]), viticulture (HR = 1.29 [1.18-1.42]), and fruit arboriculture (HR = 1.36 [1.15-1.62]). By contrast, lower risks of AD were found for several animal farming types, in particular for poultry and rabbit farming (HR = 0.29 [0.20-0.44]), ovine and caprine farming (HR = 0.50 [0.41-0.61]), mixed dairy and cow farming (HR = 0.46 [0.37-0.57]), dairy farming (HR = 0.67 [0.61-0.73]), and pig farming (HR = 0.30 [0.18-0.52]). This study shed some light on the association between a wide range of agricultural activities and AD in the entire French FMs population.

Prediction of the acceptance of telemedicine among rheumatic patients: a machine learning-powered secondary analysis of German survey data.

Telemedicine (TM) has augmented healthcare by enabling remote consultations, diagnosis, treatment, and monitoring of patients, thereby improving healthcare access and patient outcomes. However, successful adoption of TM depends on user acceptance, which is influenced by technical, socioeconomic, and health-related factors. Leveraging machine learning (ML) to accurately predict these adoption factors can greatly contribute to the effective utilization of TM in healthcare. The objective of the study was to compare 12 ML algorithms for predicting willingness to use TM (TM try) among patients with rheumatic and musculoskeletal diseases (RMDs) and identify key contributing features. We conducted a secondary analysis of RMD patient data from a German nationwide cross-sectional survey. Twelve ML algorithms, including logistic regression, random forest, extreme gradient boosting (XGBoost), and neural network (deep learning) were tested on a subset of the dataset, with the inclusion of only RMD patients who answered "yes" or "no" to TM try. Nested cross-validation was used for each model. The best-performing model was selected based on area under the receiver operator characteristic (AUROC). For the best-performing model, a multinomial/multiclass ML approach was undertaken with the consideration of the three following classes: "yes", "no", "do not know/not answered". Both one-vs-one and one-vs-rest strategies were considered. The feature importance was investigated using Shapley additive explanation (SHAP). A total of 438 RMD patients were included, with 26.5% of them willing to try TM, 40.6% not willing, and 32.9% undecided (missing answer or "do not know answer"). This dataset was used to train and test ML models. The mean accuracy of the 12 ML models ranged from 0.69 to 0.83, while the mean AUROC ranged from 0.79 to 0.90. The XGBoost model produced better results compared with the other models, with a sensitivity of 70%, specificity of 91% and positive predictive value of 84%. The most important predictors of TM try were the possibility that TM services were offered by a rheumatologist, prior TM knowledge, age, self-reported health status, Internet access at home and type of RMD diseases. For instance, for the yes vs. no classification, not wishing that TM services were offered by a rheumatologist, self-reporting a bad health status and being aged 60-69 years directed the model toward not wanting to try TM. By contrast, having Internet access at home and wishing that TM services were offered by a rheumatologist directed toward TM try. Our findings have significant implications for primary care, in particular for healthcare professionals aiming to implement TM effectively in their clinical routine. By understanding the key factors influencing patients' acceptance of TM, such as their expressed desire for TM services provided by a rheumatologist, self-reported health status, availability of home Internet access, and age, healthcare professionals can tailor their strategies to maximize the adoption and utilization of TM, ultimately improving healthcare outcomes for RMD patients. Our findings are of high interest for both clinical and medical teaching practice to fit changing health needs caused by the growing number of complex and chronically ill patients.

Does prenatal exposure to multiple airborne and tap-water pollutants increase neonatal thyroid-stimulating hormone concentrations? Data from the Picardy region, France.

OBJECTIVE: Systematic screening for congenital hypothyroidism by heel-stick sampling has revealed unexpected heterogeneity in the geographic distribution of newborn thyroid-stimulating hormone concentrations in Picardy, France. We explored a possible relationship with environmental pollutants. METHODS: Zip code geolocation data from mothers of newborns without congenital hypothyroidism born in 2021 were linked to ecological data for a set of airborne (particulate matter with a diameter of 2.5 µm or less [PM2.5] or 10 µm or less [PM10]) and tap-water (nitrate and perchlorate ions and atrazine) pollutants. Statistical associations between mean exposure levels during the third trimester of pregnancy and Thyroid-stimulating hormone (TSH) concentrations in 6249 newborns (51 % male) were investigated using linear regression models. RESULTS: Median neonatal TSH concentration (interquartile range, IQR) was 1.7 (1-2.8) mIU/L. An increase of one IQR in prenatal exposure to perchlorate ions (3.6 µg/L), nitrate ions (19.2 mg/L), PM2.5 (3.7 µg/m3) and PM10 (3.4 µg/m3), were associated with increases in TSH concentrations of 2.30 % (95 % CI: 0.95-3.66), 5.84 % (95 % CI: 2.81-8.87), 13.44 % (95 % CI: 9.65-17.28) and 6.26 % (95 % CI: 3.01-9.56), respectively. CONCLUSIONS: Prenatal exposure to perchlorate and nitrate ions in tap water and to airborne PM over the third trimester of pregnancy was significantly associated with increased neonatal TSH concentrations.

Agricultural activities and risk of treatment for depressive disorders among the entire French agricultural workforce: the TRACTOR project, a nationwide retrospective cohort study.

Background: Although depression is a major issue among farming population, to date, there have been few studies on specific agricultural activities. We aimed to investigate whether, among the entire French farm manager (FM) workforce, certain agricultural activities are more strongly associated with depression than others. Methods: This nationwide retrospective cohort study used data from an administrative health database available to the TRACTOR project. This database pertains to the entire French agricultural workforce (overseas workers not included). Data were analyzed from January 2021 to December 2022. All FMs that worked at least once over the period 2002-2016 were included. The outcome measure was the association between 26 agricultural activities and the risk of depression measured as hazard ratios (HRs) after adjusting for age, sex, and pre-existing medical comorbidities. The time to first depression insurance declaration, or first antidepressant prescription claim was used as the underlying timescale. For each activity, the reference/control group included all FMs that never performed the considered activity between 2002 and 2016, while the exposed group included FMs that performed the considered activity at least once from 2002 to 2016. Four sensitivity analyses were conducted to test hypotheses, and to address potential sources of bias. Findings: There were 84,507 (7.76%; 28.2 cases per 1000 person-years) depression cases among 1,088,561 FMs (mean age 46.6 [SD 14.1]). Compared to other activities, dairy farming (HR = 1.37, 95% confidence interval: 1.32-1.42), cow farming (HR = 1.53 [1.47-1.59]), poultry and rabbit farming (HR = 1.37 [1.27-1.50]), and mixed farming (HR = 1.30 [1.24-1.36]) were more strongly associated with depression. Sex differences were observed, with most of the time, risks higher for females than for males. Interpretation: Agricultural activities at risk of depression among the entire French agricultural workforce were identified. These findings do represent a crucial first step on the road to implement effective preventive measures against depression to determine where additional resources should be allocated to screen for depression, along with intervention. Funding: MIAI@Grenoble Alpes, and Mutualité Sociale Agricole.

Factors Associated With Telemedicine Use Among Patients With Rheumatic and Musculoskeletal Disease: Secondary Analysis of Data From a German Nationwide Survey.

BACKGROUND: Previous studies have demonstrated telemedicine (TM) to be an effective tool to complement rheumatology care and address workforce shortage. With the outbreak of the COVID-19 pandemic, TM experienced a massive upswing. A previous study revealed that physicians' willingness to use TM and actual use of TM are closely connected to their knowledge of TM. However, it remains unclear which factors are associated with patients' motivation to use TM. OBJECTIVE: This study aims to identify the factors that determine patients' willingness to try TM (TM try) and their wish that their rheumatologists offer TM services (TM wish). METHODS: We conducted a secondary analysis of data from a German nationwide cross-sectional survey among patients with rheumatic and musculoskeletal disease (RMD). Bayesian univariate and multivariate logistic regression analyses were applied to the data to determine which factors were associated with TM try and TM wish. The predictor variables (covariates) studied individually included sociodemographic factors (eg, age and sex) and health characteristics (eg, disease type and health status). All the variables positively or negatively associated with TM try or TM wish in the univariate analyses were then considered for the Bayesian model averaging analysis after a selection based on the variance inflation factor (≤2.5). All the analyses were stratified by sex. RESULTS: Of the total 102 variables, 59 (57.8%) and 45 (44.1%) variables were found to be positively or negatively associated (region of practical equivalence ≤5%) with TM try and TM wish, respectively. A total of 16 and 8 determinant factors were identified for TM try and TM wish, respectively. Wishing that TM services were offered by rheumatologists, having internet access at home, residing 5 to 10 km away from the general practitioner's office, owning an electronic device, and being aged 40 to 60 years were among the factors positively associated with TM try and TM wish. By contrast, not yet being diagnosed with an RMD, having no prior knowledge of TM, having a bad health status, living in a rural area, not documenting one's health status, not owning an electronic device, and being aged 60 to 80 years were negatively associated with TM try and TM wish. CONCLUSIONS: Our results suggest that health status, knowledge, age, and access to technical equipment and infrastructure influence the motivation of patients with RMD to use telehealth services. In particular, older patients with RMD living in rural areas, who could likely benefit from using TM, are currently not motivated to use TM and seem to need additional TM support.

Factors Associated With Telemedicine Use Among German General Practitioners and Rheumatologists: Secondary Analysis of Data From a Nationwide Survey.

BACKGROUND: Previous studies have demonstrated telemedicine (TM) to be an effective tool to complement rheumatology care and address workforce shortage. With the outbreak of the SARS-CoV-2 pandemic, TM experienced a massive upswing. However, in rheumatology care, the use of TM stagnated again shortly thereafter. Consequently, the factors associated with physicians' willingness to use TM (TM willingness) and actual use of TM (TM use) need to be thoroughly investigated. OBJECTIVE: This study aimed to identify the factors that determine TM use and TM willingness among German general practitioners and rheumatologists. METHODS: We conducted a secondary analysis of data from a German nationwide cross-sectional survey with general practitioners and rheumatologists. Bayesian univariate and multivariate logistic regression analyses were applied to the data to determine which factors were associated with TM use and TM willingness. The predictor variables (covariates) that were studied individually included sociodemographic factors (eg, age and sex), work characteristics (eg, practice location and medical specialty), and self-assessed knowledge of TM. All the variables positively and negatively associated with TM use and TM willingness in the univariate analysis were then considered for Bayesian model averaging analysis after a selection based on the variance inflation factor (≤2.5). All analyses were stratified by sex. RESULTS: Univariate analysis revealed that out of 83 variables, 36 (43%) and 34 (41%) variables were positively or negatively associated (region of practical equivalence≤5%) with TM use and TM willingness, respectively. The Bayesian model averaging analysis allowed us to identify 13 and 17 factors of TM use and TM willingness, respectively. Among these factors, being female, having very poor knowledge of TM, treating <500 patients per quarter, and not being willing to use TM were negatively associated with TM use, whereas having good knowledge of TM and treating >1000 patients per quarter were positively associated with TM use. In addition, being aged 51 to 60 years, thinking that TM is not important for current and future work, and not currently using TM were negatively associated with TM willingness, whereas owning a smart device and working in an urban area were positively associated with TM willingness. CONCLUSIONS: The results point to the close connection between health care professionals' knowledge of TM and actual TM use. These results lend support to the integration of digital competencies into medical education as well as hands-on training for health care professionals. Incentive programs for physicians aged >50 years and practicing in rural areas could further encourage TM willingness.

Toxicological and Exposure Database Inventory: A review.

BACKGROUND: Knowledge of hazards and exposure data about chemical pollutants are essential for epidemiological studies for assessing health risks and preventing the development of diseases. Access to this type of information is clearly needed and although numerous databases (DBs) have been compiled, they are often extremely difficult to find and navigate. OBJECTIVES: This paper presents the creation of an online inventory of toxicological and exposure DBs to support human health risk assessment resulting from the chemical exposome. METHODS: A free searchable online inventory, called TEDI (Toxicological and Exposure Database Inventory), was set up to collect meta-data on toxicological and exposure DBs resulting from a review of the literature conducted on PubMed. Only chemical agents, including drugs, natural and manufactured/synthetic chemicals and air pollutants, were considered. Regarding exposure DBs, only human exposure to chemicals were included. Because of time and resource constraints, only an inventory was performed, and no effort was made to rate, assess or rank DBs on quality criteria. RESULTS: A total of 715 DBs were identified, catalogued, described and made available on TEDI. The number of chemicals ranged from one single chemical to 90 million for toxicological DBs and from 1 to 103,817 chemicals for exposure DBs. Some DBs were restricted to specific chemicals, with for instance 71 exposure DBs reporting polycyclic aromatic hydrocarbon measurements. Toxicological DBs (n = 362) provided a broad range of different information such as toxicity data (57%), physicochemical properties (38%), experimental study results (28%) or prediction data (16%). A total of 382 exposure DBs were found, including exposure measurements DBs (71%), web application/tool (21%), exposure and risk assessment models (19%) and epidemiological DBs (13%). DISCUSSION: TEDI is of value to the broader community and could support human health risk assessment to chemicals in various contexts. This inventory remains open for further additions, to enlarge its coverage, increase the meta-data collected and include newly developed DBs.

Agricultural activities and risk of central nervous system tumors among French farm managers: Results from the TRACTOR project.

The etiology of central nervous system (CNS) tumors is complex and involves many suspected risk factors. Scientific evidence remains insufficient, in particular in the agricultural field. The goal of our study was to investigate associations between agricultural activities and CNS tumors in the entire French farm manager workforce using data from the TRACTOR project. The TRACTOR project hold a large administrative health database covering the entire French agricultural workforce, over the period 2002-2016, on the whole French metropolitan territory. Associations were estimated for 26 activities and CNS tumors using Cox proportional hazards model, with time to first CNS tumor insurance declaration as the underlying timescale, adjusting for sex, age and geographical area. There were 1017 cases among 1 036 069 farm managers, including 317 meningiomas and 479 gliomas. Associations varied with tumor types, sex and types of crop and animal farming. Analyses showed several increased risks of CNS tumors, in particular for animal farming. The main increases in risk were observed for meningioma in mixed dairy and cow farming (hazard ratio [HR] = 1.75, 95% confidence interval [CI]: 1.09-2.81) and glioma in pig farming (HR = 2.28, 95% CI: 1.37-3.80). Our study brings new insights on the association of a wide range of agricultural activities and CNS tumor and subtype-specific risks in farm managers. Although these findings need to be corroborated in further studies and should be interpreted cautiously, they could have implications for enhancing CNS tumor surveillance in agriculture.

Air pollution and health impacts during the COVID-19 lockdowns in Grenoble, France.

It is undeniable that exposure to outdoor air pollution impacts the health of populations and therefore constitutes a public health problem. Any actions or events causing variations in air quality have repercussions on populations' health. Faced with the worldwide COVID-19 health crisis that began at the end of 2019, the governments of several countries were forced, in the beginning of 2020, to put in place very strict containment measures that could have led to changes in air quality. While many works in the literature have studied the issue of changes in the levels of air pollutants during the confinements in different countries, very few have focused on the impact of these changes on health risks. In this work, we compare the 2020 period, which includes two lockdowns (March 16 - May 10 and a partial shutdown Oct. 30 - Dec. 15) to a reference period 2015-2019 to determine how these government-mandated lockdowns affected concentrations of NO2, O3, PM2.5, and PM10, and how that affected human health factors, including low birth weight, lung cancer, mortality, asthma, non-accidental mortality, respiratory, and cardiovascular illnesses. To this end, we structured 2020 into four periods, alternating phases of freedom and lockdowns characterized by a stringency index. For each period, we calculated (1) the differences in pollutant levels between 2020 and a reference period (2015-2019) at both background and traffic stations; and (2) the resulting variations in the epidemiological based relative risks of health outcomes. As a result, we found that relative changes in pollutant levels during the 2020 restriction period were as follows: NO2 (-32%), PM2.5 (-22%), PM10 (-15%), and O3 (+10.6%). The pollutants associated with the highest health risk reductions in 2020 were PM2.5 and NO2, while PM10 and O3 changes had almost no effect on health outcomes. Reductions in short-term risks were related to reductions in PM2.5 (-3.2% in child emergency room visits for asthma during the second lockdown) and NO2 (-1.5% in hospitalizations for respiratory causes). Long-term risk reductions related to PM2.5 were low birth weight (-8%), mortality (-3.3%), and lung cancer (-2%), and to NO2 for mortality (-0.96%). Overall, our findings indicate that the confinement period in 2020 resulted in a substantial improvement in air quality in the Grenoble area.

Consistency between air and biological monitoring for assessing polycyclic aromatic hydrocarbon exposure and cancer risk of workers.

BACKGROUND: Atmospheric levels of polycyclic aromatic hydrocarbons (PAHs) have been monitored in many companies since 1940. Because of the use of respiratory protective equipment (RPE) and cutaneous absorption, the measurement of urinary 1-hydroxypyrene (1-OHP), metabolite of pyrene (Pyr), and, more recently, 3-hydroxybenzo[a]pyrene (3-OHBaP), metabolite of benzo[a]pyrene (BaP), has been carried out to assess PAH exposure and estimate health risks. OBJECTIVES: This study aimed to investigate the agreement between 523 air and biological levels recorded in the Exporisq-HAP database by taking into account the effectiveness of RPE. METHODS: The agreement/consistency between 523 air and biological exposure levels was assessed by estimating and comparing the probability of exceeding French limit values (LVs) for both BaP and 3-OHBaP and ACGIH LV for 1-OHP, respectively. PAH airborne levels (wPAHs) were weighted by an assigned protection factor (APF) depending on the type of mask worn by workers, while urinary 1-OHP concentrations were adjusted with the wBaP/wPyr ratio of each industrial sector (wadj1-OHP). RESULTS: Within occupational groups, there was an overall agreement between airborne PAH levels and urinary biomarker concentrations. A clear dichotomy was found between "petroleum-derived" and "coal-derived" groups, with much higher exposures in the latest group despite the use of RPEs by two-thirds of the workers. The type of RPE varied from one plant to another, which underlines the importance of taking into account their effectiveness. The analysis of urinary 3-OHBaP was not relevant for low PAH exposure levels. In addition, this biomarker underdiagnosed the exceedance of LV relative to BaP levels for 6% of "coal-derived" groups. CONCLUSIONS: The use of urinary wadj1-OHP seemed to be more protective to assess the exceedance of LVs than those of urinary 3-OHBaP and air wBaP, but adjustment of the 1-OHP concentration by the BaP/Pyr ratio requires air sampling due to highly variable ratios observed in the studied occupational groups.

Health risk assessment with multiple reference indices.

BACKGROUND: Conducting a risk assessment can be challenging, especially when dealing with several reference indices, which could lead to conflicting conclusions between studies. The common approach is to use a reference index from a single source based on the risk assessor's preference. OBJECTIVES: To propose an approach for constructing a multi-reference index-based aggregated risk estimate using mathematical objectivity to reflect all of the available information. METHODS: The aggregated risk estimate based on multiple reference indices (AREMRI) results from the weighted linear combination of risk distributions that were obtained with each reference index available. The weights were calculated using the degree of agreement among the reference index-based risk distributions. The approach is illustrated through three practical cases of benzene inhalation cancer risk assessment using inhalation unit risks (IURs) from six different regulatory agencies. RESULTS: The degrees of agreement between the reference index-based risk distribution, obtained with the six IURs, ranged from 0.7 to 92%. The highest weights were attributed to reference index-based risk distributions that had the highest degree of agreement with the maximum number of other reference index-based risk distributions. Regardless of the practical case considered, the AREMRI risk distribution resulted in the third highest risk compared to the six single risk distributions. CONCLUSION: Our approach can be useful in the presence of several reference indices by providing useful insights, consistency and direct comparisons between studies to support better-informed risk assessment and management decisions. This approach can shed some light on some of the uncertainties associated with the toxicological reference values in a risk assessment associated with the toxicological reference values. If the uncertainty is large, more detailed evaluation of the toxicological reference values would be needed.

The TRACTOR Project: TRACking and MoniToring Occupational Risks in Agriculture Using French Insurance Health Data (MSA).

OBJECTIVES: A vast data mining project called 'TRACking and moniToring Occupational Risks in agriculture' (TRACTOR) was initiated in 2017 to investigate work-related health events among the entire French agricultural workforce. The goal of this work is to present the TRACTOR project, the challenges faced during its implementation, to discuss its strengths and limitations and to address its potential impact for health surveillance. METHODS: Three routinely collected administrative health databases from the National Health Insurance Fund for Agricultural Workers and Farmers (MSA) were made available for the TRACTOR project. Data management was required to properly clean and prepare the data before linking together all available databases. RESULTS: After removing few missing and aberrant data (4.6% values), all available databases were fully linked together. The TRACTOR project is an exhaustive database of agricultural workforce (active and retired) from 2002 to 2016, with around 10.5 million individuals including seasonal workers and farm managers. From 2012 to 2016, a total of 6 906 290 individuals were recorded. Half of these individuals were active and 46% had at least one health event (e.g. declared chronic disease, reimbursed drug prescription) during this 5-year period. CONCLUSIONS: The assembled MSA databases available in the TRACTOR project are regularly updated and represent a promising and unprecedent dataset for data mining analysis dedicated to the early identification of current and emerging work-related illnesses and hypothesis generation. As a result, this project could help building a prospective integrated health surveillance system for the benefit of agricultural workers.

A consensus approach for estimating health risk: Application to inhalation cancer risks.

Conducting a risk assessment is challenging because various and contrasting risk indicators are available, which can lead to discrepancies and, sometimes, conflicting conclusions. Constructing and using a consensus risk indicator (CRI) could provide a reliable alternative that is consistent and supports direct comparisons. The goal of this study is to propose a structured and pragmatic approach for constructing a CRI distribution and demonstrate its feasibility and easy implementation when conducting risk assessments. A CRI distribution is constructed as a weighted combination of existing indicators where the weights are obtained by using the overlapping areas of an individual indicator's distribution and an aggregated reference distribution. The approach is illustrated through an assessment of human cancer risk following inhalation exposure. The CRI is constructed using eight risk indicators. The CRI distribution parameters for 199 human carcinogenic chemicals associated with inhalation exposure were determined and are presented in an interactive table. To aid the wider implementation of the CRI approach, a user-friendly and interactive web application, named InCaRisk, was created to facilitate the cancer risk estimation following inhalation exposure. Our approach could be useful for enhancing the quality of regulatory decisions and protecting human health from environmental pollutants; our approach can be applied for a given health outcome, route of exposure and exposure setting.

Towards a recommended biomonitoring strategy for assessing the occupational exposure of roofers to PAHs.

The aims of this work were to assess the PAH exposure among roofers and to identify relevant biomarkers for monitoring occupational exposure. Several campaigns were conducted between 2004 and 2017, with 28 individual air samples and 240 urinary samples collected from 73 roofers. Seventeen parent PAHs and 14 urinary biomarkers, metabolites of pyrene (1-OHP), benzo(a)pyrene (3-OHBaP and TetraolBaP), naphthalene (1- and 2-naphtols), fluorene (1- 2- 3- 9-fluorenols) and phenanthrene (1- 2- 3- 4- 9-phenanthrols), were analysed. Three exposure groups were considered: soft-applied roofing using polymer-modified bitumen ("PMB"), hot-applied roofing using oxidized bitumen ("OB") and the tearing off of old roof coatings containing coal tar ("CT"). The PAHs containing 2-3 rings were much more abundant, and the highest airborne levels were observed in the "CT" group. The biomonitoring results were consistent with these results, with a large predominance of 2-3 ring PAH metabolites. 1-OHP, 3-fluorenol and 2-phenanthrol were better correlated with airborne levels and less influenced by smoking than the other metabolites. Conversely, 1-/2-naphtol levels were heavily influenced by smoking and not correlated with airborne naphthalene levels. Moreover, 3-OHBaP and TetraolBaP levels were very low when applying bitumen membranes, and much higher exposures were observed during tear-off activities. In this context, the recommended strategy for roofer biomonitoring should include 1-OHP, fluorenols and phenanthrols, as well as carcinogenic BaP metabolites (3-OHBaP or TetraolBaP) when evaluating the occupational exposure of roofers that are tearing off old roof coatings.

Lung cancer risk assessment for workers exposed to polycyclic aromatic hydrocarbons in various industries.

BACKGROUND: Millions of workers are exposed to carcinogenic polycyclic aromatic hydrocarbon (PAH) mixtures. The toxicity of PAH mixtures is variable and depends on the composition of the mixture, which is related to the emission sources. Although several indicators exist, the cancer risk estimation associated with occupational exposure to PAHs is poorly known. OBJECTIVES: To assess the risk of lung cancer associated with PAHs in several industries using the atmospheric concentrations of benzo[a]pyrene (BaP) as a proxy. METHODS: A total of 93 exposure groups belonging to 9 industries were investigated. Eight indicators found in the literature were compared to assess risks. A consensual indicator was used to estimate lung cancer risks. RESULTS: Approximately 30% of the exposure groups were above the maximal risk level of the European Union (10-4). The risk probabilities were >10-3 for coke and silicon production; >10-4 for the manufacturing of carbon products and aluminum production; >10-5 for foundries and combustion processes; >10-6 for the use of lubricating oils and engine exhaust emissions; and >10-7 for bitumen. The risk probabilities were highly variable within industries (from 1 to 1000 likelihood). A total of 27 (95% CI: 0.1-54) contemporary additional lung cancer cases could be expected per year in the French exposed population based on estimations using published data. CONCLUSION: This study provides an overview of cancer risk estimation in many industries. Despite efforts and changes that had been made to decrease risks, PAHs remain a sanitary threat for people exposed to these pollutants in occupational environments.

Exporisq-HAP database: 20 years of monitoring French occupational exposure to polycyclic aromatic hydrocarbon mixtures and identification of exposure determinants.

BACKGROUND: Millions of workers are exposed to polycyclic aromatic hydrocarbons (PAHs), a well-known family of carcinogens, but occupational exposure data about PAH mixture compositions are scarce. OBJECTIVES: To provide a detailed picture of airborne PAH exposures encountered in the French industrial landscape over the previous 20 years and to identify determinants driving exposures. METHODS: Results from 1643 airborne samples of 16 gaseous and particulate PAHs implemented into the Exporisq HAP database from 1995 to 2014 were used to describe exposure levels and aerosol chemical composition in many industries and activities. Compliance of benzo[a]pyrene (BaP) levels with several existing occupational exposure limits for long-term exposure was assessed. RESULTS: BaP levels were lower than those reported in the literature, but the level and composition of PAH mixtures were highly variable between and within industries. Numerous exposure determinants (e.g., product composition, type and temperature of process, ventilation and confinement) were assumed to explain these differences. The highest levels were found in industries using products derived from coal (aluminum, silicon, and coke production, manufacturing of carbon products and foundries), with mean BaP levels up to 23 times higher than the French recommended value of 150 ng/m3. Forty-seven percent of the occupational activities exceeded this value. Conversely, exposures resulting from petroleum-derived products were relatively low. CONCLUSIONS: As health effects depend on PAH levels but also on the composition of the mixture, exposure assessments must characterize the entire mixtures and record specific determinants to define homogeneous exposure groups and to accurately assess health risks.

Constructing a Database of Similar Exposure Groups: The Application of the Exporisq-HAP Database from 1995 to 2015.

Background: Similar exposure groups (SEGs) are needed to reliably assess occupational exposures and health risks. However, the construction of SEGs can turn out to be rather challenging because of the multifactorial variability of exposures. Objectives: The objective of this study is to put forward a semi-empirical approach developed to construct and implement a SEG database for exposure assessments. An occupational database of airborne levels of polycyclic aromatic hydrocarbons (PAHs) was used as an illustrative and working example. Methods: The approach that was developed consisted of four steps. The first three steps addressed the construction and implementation of the occupational Exporisq-HAP database (E-HAP). E-HAP was structured into three hierarchical levels of exposure groups, each of which was based on exposure determinants, along 16 dimensions that represented the sampled PAHs. A fourth step was implemented to identify and generate SEGs using the geometric standard deviation (GSD) of PAH concentrations. Results: E-HAP was restructured into 16 (for 16 sampled PAHs) 3 × 3 matrices: three hierarchical levels of description versus three degrees of dispersion, which included low (the SEG database: GSD ≤ 3), medium (3 < GSD ≤ 6), and high (GSD > 6). Benzo[a]pyrene (BaP) was the least dispersed particulate PAH with 41.5% of groups that could be considered as SEGs, 48.5% of groups of medium dispersion, and only 8% with high dispersion. These results were comparable for BaP, BaP equivalent toxic, or the sum of all carcinogenic PAHs but were different when individual gaseous PAHs or ∑PAHG were chosen. Conclusion: Within the framework of risk assessment, such an approach, based on groundwork studies, allows for both the construction of an SEG database and the identification of exposure groups that require improvements in either the description level or the homogeneity degree toward SEG.