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Abstract
Nightshift work disturbs the circadian rhythm, which might contribute to the development of cardio-metabolic disorders. In this cross-sectional study, we aimed to gain insight into perturbations of disease relevant metabolic pathways due to nightshift work. We characterized the metabolic profiles of 237 female nurses and paramedic staff participating in the Klokwerk study using the Nightingale Health platform. We performed analyses on plasma levels of 225 metabolites, including cholesterol, triglycerides, fatty acids, and amino acids. Using both principal component- and univariate-regression, we compared metabolic profiles of nightshift workers to metabolic profiles from workers that did not work night shifts (defined as day workers). We also assessed whether differential effects were observed between recently started versus more experienced workers. Within the group of nightshift workers, we compared metabolic profiles measured right after a nightshift with metabolic profiles measured on a day when no nightshift work was conducted. We observed evidence for an impact of nightshift work on the presence of unfavorable fatty acid profiles in blood. Amongst the fatty acids, effects were most prominent for PUFA/FA ratios (consistently decreased) and SFA/FA ratios (consistently elevated). This pattern of less favorable fatty acid profiles was also observed in samples collected directly after a night shift. Amino acid levels (histidine, glutamine, isoleucine, and leucine) and lipoproteins (especially HDL-cholesterol, VLDL-cholesterol, and triglycerides) were elevated when comparing nightshift workers with day workers. Amino acid levels were decreased in the samples that were collected directly after working a nightshift (compared to levels in samples that were collected during a non-nightshift period). The observed effects were generally more pronounced in samples collected directly after the nightshift and among recently started compared to more experienced nightshift workers. Our finding of a suggested impact of shift work on impaired lipid metabolism is in line with evidence that links disruption of circadian rhythmicity to obesity and metabolic disorders.

Traffic-related air pollution (TRAP) is a complex mixture of compounds that contributes to the pathogenesis of many diseases including several types of cancer, pulmonary, cardiovascular and neurodegenerative diseases, and more recently also diabetes mellitus. In search of an early diagnostic biomarker for improved environmental health risk assessment, recent human studies have shown that certain extracellular miRNAs are altered upon exposure to TRAP. Here, we present a global circulating miRNA analysis in a human population exposed to different levels of TRAP. The cross-over study, with sampling taking place during resting and physical activity in two different exposure scenarios, included for each subject personal exposure measurements of PM10,PM2.5, NO, NO2, CO, CO2, BC and UFP. Next-generation sequencing technology was used to identify global circulating miRNA levels across all subjects. We identified 8 miRNAs to be associated with the mixture of TRAP and 27 miRNAs that were associated with the individual pollutants NO, NO2, CO, CO2, BC and UFP. We did not find significant associations between miRNA levels and PM10 or PM2.5. Integrated network analysis revealed that these circulating miRNAs are potentially involved in processes that are implicated in the development of air pollution-induced diseases. Altogether, this study demonstrates that signatures consisting of circulating miRNAs present a potential novel biomarker to be used in health risk assessment. ; This work has been supported by the European Union within the frame of the Exposomics (226756) project.

Several citizen science (CS) initiatives have been adopted in environmental science to monitor air and noise pollution, and water quality related to civic concerns. Nevertheless, CS projects in environmental epidemiology remain scarce. This is because little attention has been paid to evaluate associations of environmental exposures with health effects directly. This narrative review aims to promote the understanding and application of CS in environmental epidemiology. There are many commonalities between CS and other participatory approaches in environmental epidemiology. Yet, CS can foster the democratization of scientific governance and enhance the sustainability of research projects more effectively than other existing participatory approaches. This is especially the case in projects where citizens are invited to participate, engage and become involved throughout all the phases of a research project (co-created projects). This paper identifies various challenges and opportunities specific to the implementation of co-created CS projects in environmental epidemiology. The development of more locally relevant research designs, using local knowledge, obtaining medical ethical clearance, and co-analysing the association between exposure and health, are examples of opportunities and challenges that require epidemiologists to go beyond the traditional research framework and include more outreach activities. Continued efforts, particularly the sharing of information about projects' collaborative processes, are needed to make CS a more concrete and cohesive approach in environmental epidemiology.

Article Number: 106470 ; Several citizen science (CS) initiatives have been adopted in environmental science to monitor air and noise pollution, and water quality related to civic concerns. Nevertheless, CS projects in environmental epidemiology remain scarce. This is because little attention has been paid to evaluate associations of environmental exposures with health effects directly. This narrative review aims to promote the understanding and application of CS in environmental epidemiology. There are many commonalities between CS and other participatory approaches in environmental epidemiology. Yet, CS can foster the democratization of scientific governance and enhance the sustainability of research projects more effectively than other existing participatory approaches. This is especially the case in projects where citizens are invited to participate, engage and become involved throughout all the phases of a research project (co-created projects). This paper identifies various challenges and opportunities specific to the implementation of co-created CS projects in environmental epidemiology. The development of more locally relevant research designs, using local knowledge, obtaining medical ethical clearance, and coanalysing the association between exposure and health, are examples of opportunities and challenges that require epidemiologists to go beyond the traditional research framework and include more outreach activities. Continued efforts, particularly the sharing of information about projects? collaborative processes, are needed to make CS a more concrete and cohesive approach in environmental epidemiology ; Aplinkotyros katedra ; Vytauto Didžiojo universitetas

Abstract

Background:
Generic job-exposure matrices (JEMs) are often used in population-based epidemiologic studies to assess occupational risk factors when only the job and industry information of each subject is available. JEM ratings are often based on professional judgment, are usually ordinal or semi-quantitative, and often do not account for changes in exposure over time. We present an empirical Bayesian framework that combines ordinal subjective JEM ratings with benzene measurements. Our aim was to better discriminate between job, industry, and time differences in exposure levels compared to using a JEM alone.


Methods:
We combined 63 221 short-term area air measurements of benzene exposure (1954–2000) collected during routine health and safety inspections in Shanghai, China, with independently developed JEM intensity ratings for each job and industry using a mixed-effects model. The fixed-effects terms included the JEM intensity ratings for job and industry (both ordinal, 0–3) and a time trend that we incorporated as a b-spline. The random-effects terms included job (n = 33) and industry nested within job (n = 399). We predicted the benzene concentration in two ways: (i) a calibrated JEM estimate was calculated using the fixed-effects model parameters for calendar year and JEM intensity ratings; (ii) a job-/industry-specific estimate was calculated using the fixed-effects model parameters and the best linear unbiased predictors from the random effects for job and industry using an empirical Bayes estimation procedure. Finally, we applied the predicted benzene exposures to a prospective population-based cohort of women in Shanghai, China (n = 74 942).


Results:
Exposure levels were 13 times higher in 1965 than in 2000 and declined at a rate that varied from 4 to 15% per year from 1965 to 1985, followed by a small peak in the mid-1990s. The job-/industry-specific estimates had greater differences between exposure levels than the calibrated JEM estimates (97.5th percentile/2.5th percentile exposure level, BGR95B: 20.4 versus 3.0, respectively). The calibrated JEM and job-/industry-specific estimates were moderately correlated in any given year (Pearson correlation, rp = 0.58). We classified only those jobs and industries with a job or industry JEM exposure probability rating of 3 (>50% of workers exposed) as exposed. As a result, 14.8% of the subjects and 8.7% of the employed person-years in the study population were classified as benzene exposed. The cumulative exposure metrics based on the calibrated JEM and job-/industry-specific estimates were highly correlated (rp = 0.88).


Conclusions:
We provide a useful framework for combining quantitative exposure data with expert-based exposure ratings in population-based studies that maximized the information from both sources. Our framework calibrated the ratings to a concentration scale between ratings and across time and provided a mechanism to estimate exposure when a job/industry group reported by a subject was not represented in the exposure database. It also allowed the job/industry groups' exposure levels to deviate from the pooled average for their respective JEM intensity ratings.

Several citizen science (CS) initiatives have been adopted in environmental science to monitor air and noise pollution, and water quality related to civic concerns. Nevertheless, CS projects in environmental epidemiology remain scarce. This is because little attention has been paid to evaluate associations of environmental exposures with health effects directly. This narrative review aims to promote the understanding and application of CS in environmental epidemiology. There are many commonalities between CS and other participatory approaches in environmental epidemiology. Yet, CS can foster the democratization of scientific governance and enhance the sustainability of research projects more effectively than other existing participatory approaches. This is especially the case in projects where citizens are invited to participate, engage and become involved throughout all the phases of a research project (co-created projects). This paper identifies various challenges and opportunities specific to the implementation of co-created CS projects in environmental epidemiology. The development of more locally relevant research designs, using local knowledge, obtaining medical ethical clearance, and co-analysing the association between exposure and health, are examples of opportunities and challenges that require epidemiologists to go beyond the traditional research framework and include more outreach activities. Continued efforts, particularly the sharing of information about projects' collaborative processes, are needed to make CS a more concrete and cohesive approach in environmental epidemiology. ; This paper has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 824484. The output reflects the authors' view. The European Commission is not responsible for any use that may be made from the information this paper contains. We acknowledge support from the Spanish Ministry of Science, Innovation and Universities through the "Centro de Excelencia Severo Ochoa 2019-2023" Program (CEX2018-000806-S), support from the Generalitat de Catalunya through the CERCA Program, and the support from EXPOSOME-NL (NWO grant number 024.004.017) and EXPANSE (EU-H2020 Grant number 874627).

Abstract

Objectives
Automatic job coding tools were developed to reduce the laborious task of manually assigning job codes based on free-text job descriptions in census and survey data sources, including large occupational health studies. The objective of this study is to provide a case study of comparative performance of job coding and JEM (Job-Exposure Matrix)-assigned exposures agreement using existing coding tools.


Methods
We compared three automatic job coding tools [AUTONOC, CASCOT (Computer-Assisted Structured Coding Tool), and LabourR], which were selected based on availability, coding of English free-text into coding systems closely related to the 1988 version of the International Standard Classification of Occupations (ISCO-88), and capability to perform batch coding. We used manually coded job histories from the AsiaLymph case-control study that were translated into English prior to auto-coding to assess their performance. We applied two general population JEMs to assess agreement at exposure level. Percent agreement and PABAK (Prevalence-Adjusted Bias-Adjusted Kappa) were used to compare the agreement of results from manual coders and automatic coding tools.


Results
The coding per cent agreement among the three tools ranged from 17.7 to 26.0% for exact matches at the most detailed 4-digit ISCO-88 level. The agreement was better at a more general level of job coding (e.g. 43.8–58.1% in 1-digit ISCO-88), and in exposure assignments (median values of PABAK coefficient ranging 0.69–0.78 across 12 JEM-assigned exposures). Based on our testing data, CASCOT was found to outperform others in terms of better agreement in both job coding (26% 4-digit agreement) and exposure assignment (median kappa 0.61).


Conclusions
In this study, we observed that agreement on job coding was generally low for the three tools but noted a higher degree of agreement in assigned exposures. The results indicate the need for study-specific evaluations prior to their automatic use in general population studies, as well as improvements in the evaluated automatic coding tools.

By 2030, more than 80% of Europe's population will live in an urban environment. The urban exposome, consisting of factors such as where we live and work, where and what we eat, our social network, and what chemical and physical hazards we are exposed to, provides important targets to improve population health. The EXPANSE (EXposome Powered tools for healthy living in urbAN SEttings) project will study the impact of the urban exposome on the major contributors to Europe's burden of disease: Cardio-Metabolic and Pulmonary Disease. EXPANSE will address one of the most pertinent questions for urban planners, policy makers, and European citizens: "How to maximize one's health in a modern urban environment?" EXPANSE will take the next step in exposome research by (1) bringing together exposome and health data of more than 55 million adult Europeans and OMICS information for more than 2 million Europeans; (2) perform personalized exposome assessment for 5,000 individuals in five urban regions; (3) applying ultra-high-resolution mass-spectrometry to screen for chemicals in 10,000 blood samples; (4) evaluating the evolution of the exposome and health through the life course; and (5) evaluating the impact of changes in the urban exposome on the burden of cardiometabolic and pulmonary disease. EXPANSE will translate its insights and innovations into research and dissemination tools that will be openly accessible via the EXPANSE toolbox. By applying innovative ethics-by-design throughout the project, the social and ethical acceptability of these tools will be safeguarded. EXPANSE is part of the European Human Exposome Network.

A high body mass (BMI) index has repeatedly been associated with non-atopic asthma, but the biological mechanism linking obesity to asthma is still poorly understood. We aimed to test the hypothesis that inflammation and/or innate immunity plays a role in the obesity-asthma link. DNA methylome was measured in blood samples of 61 non-atopic participants with asthma and 146 non-atopic participants without asthma (non-smokers for at least 10 years) taking part in the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) study. Modification by DNA methylation of the association of BMI or BMI change over 10 years with adult-onset asthma was examined at each CpG site and differentially methylated region. Pathway enrichment tests were conducted for genes in a priori curated inflammatory pathways and the NLRP3-IL1B-IL17 axis. The latter was chosen on the basis of previous work in mice. Inflammatory pathways including glucocorticoid/PPAR signaling (p = 0.0023), MAPK signaling (p = 0.013), NF-κB signaling (p = 0.031), and PI3K/AKT signaling (p = 0.031) were enriched for the effect modification of BMI, while NLRP3-IL1B-IL17 axis was enriched for the effect modification of BMI change over 10 years (p = 0.046). DNA methylation measured in peripheral blood is consistent with inflammation as a link between BMI and adult-onset asthma and with the NLRP3-IL1B-IL17 axis as a link between BMI change over 10 years and adult-onset asthma in non-atopic participants. ; This work was supported by the grant FP7 of the European Commission "Enhanced exposure 36 assessment and omic profiling for high priority environmental exposures in Europe" (EXPOsOMICS grant 308610 to PV). The SAPALDIA study is supported by the Swiss National Science Foundation [grants no 33CS30-148470/1&2, 33CSCO-134276/1, 33CSCO-108796, 324730_135673, 3247BO-104283, 3247BO-104288, 3247BO-104284, 3247-065896, 3100-059302, 3200-052720, 3200-042532, 4026-028099, PMPDP3_129021/1, PMPDP3_141671/1], the Federal Office for the Environment, the Federal Office of Public Health, the Federal Office of Roads and Transport, the canton's government of Aargau, Basel-Stadt, Basel-Land, Geneva, Luzern, Ticino, Valais, and Zürich, the Swiss Lung League, the canton's Lung League of Basel Stadt/Basel Landschaft, Geneva, Ticino, Valais, Graubünden and Zurich, Stiftung ehemals Bündner Heilstätten, SUVA, Freiwillige Akademische Gesellschaft, Klinik Barmelweid, Hirslanden Klinik Aarau, the European Commission [Grant 018996 GABRIEL to W. Cookson], and the Wellcome Trust [WT 084703MA to W. Cookson]. This work was conducted within the Ageing Lungs in European Cohorts (ALEC) project and has received funding from the European Union's Horizon 2020 research and innovation programm [grant agreement No 633212].

International audience ; The implementation of One Health/EcoHealth/Planetary Health approaches has been identified as key (i) to address the strong interconnections between risk for pandemics, climate change and biodiversity loss and (ii) to develop and implement solutions to these interlinked crises. As a response to the multiple calls from scientists on that subject, we have here proposed seven long-term research questions regarding COVID-19 and emerging infectious diseases (EIDs) that are based on effective integration of environmental, ecological, evolutionary, and social sciences to better anticipate and mitigate EIDs. Research needs cover the social ecology of infectious disease agents, their evolution, the determinants of susceptibility of humans and animals to infections, and the human and ecological factors accelerating infectious disease emergence. For comprehensive investigation, they include the development of nature-based solutions to interlinked global planetary crises, addressing ethical and philosophical questions regarding the relationship of humans to nature and regarding transformative changes to safeguard the environment and human health. In support of this research, we propose the implementation of innovative multidisciplinary facilities embedded in social ecosystems locally: ecological health observatories and living laboratories. This work was carried out in the frame of the European Community project HERA (www.HERAresearchEU.eu), which aims to set priorities for an environment, climate and health research agenda in the European Union by adopting a systemic approach in the face of global environmental change

The implementation of One Health/EcoHealth/Planetary Health approaches has been identified as key (i) to address the strong interconnections between risk for pandemics, climate change and biodiversity loss and (ii) to develop and implement solutions to these interlinked crises. As a response to the multiple calls from scientists on that subject, we have here proposed seven long-term research questions regarding COVID-19 and emerging infectious diseases (EIDs) that are based on effective integration of environmental, ecological, evolutionary, and social sciences to better anticipate and mitigate EIDs. Research needs cover the social ecology of infectious disease agents, their evolution, the determinants of susceptibility of humans and animals to infections, and the human and ecological factors accelerating infectious disease emergence. For comprehensive investigation, they include the development of nature-based solutions to interlinked global planetary crises, addressing ethical and philosophical questions regarding the relationship of humans to nature and regarding transformative changes to safeguard the environment and human health. In support of this research, we propose the implementation of innovative multidisciplinary facilities embedded in social ecosystems locally: ecological health observatories and living laboratories. This work was carried out in the frame of the European Community project HERA (www.HERAresearchEU.eu), which aims to set priorities for an environment, climate and health research agenda in the European Union by adopting a systemic approach in the face of global environmental change.