The OMEGA-NET International Inventory of Occupational Cohorts

Worldwide cohort studies to support healthy ageing research: data availabilities and gaps

BACKGROUND

Population ageing is a transforming demographic force. To support evidence-based efforts for promoting healthy ageing, a summary of data availabilities and gaps to study ageing is needed.

METHOD

Through a multifaceted search strategy, we identified relevant cohort studies worldwide to studying ageing and provided a summary of available pertinent measurements. Following the World Health Organization's definition of healthy ageing, we extracted information on intrinsic capacity domains and sociodemographic, social, and environmental factors.

RESULTS

We identified 287 cohort studies. South America, the Middle East, and Africa had a limited number of cohort studies to study ageing compared to Europe, Oceania, Asia, and North America. Data availabilities of different measures varied substantially by location and study aim. Using the information collected, we developed a web-based Healthy Ageing Toolkit to facilitate healthy ageing research.

CONCLUSIONS

The comprehensive summary of data availability enables timely evidence to contribute to the United Nations Decades of Healthy Ageing goals of promoting healthy ageing for all. Highlighted gaps guide strategies for increased data collection in regions with limited cohort studies. Comprehensive data, encompassing intrinsic capacity and various sociodemographic, social, and environmental factors, is crucial for advancing our understanding of healthy ageing and its underlying pathways.

FAIR environmental and health registry (FAIREHR)- supporting the science to policy interface and life science research, development and innovation

The environmental impact on health is an inevitable by-product of human activity. Environmental health sciences is a multidisciplinary field addressing complex issues on how people are exposed to hazardous chemicals that can potentially affect adversely the health of present and future generations. Exposure sciences and environmental epidemiology are becoming increasingly data-driven and their efficiency and effectiveness can significantly improve by implementing the FAIR (findable, accessible, interoperable, reusable) principles for scientific data management and stewardship. This will enable data integration, interoperability and (re)use while also facilitating the use of new and powerful analytical tools such as artificial intelligence and machine learning in the benefit of public health policy, and research, development and innovation (RDI). Early research planning is critical to ensuring data is FAIR at the outset. This entails a well-informed and planned strategy concerning the identification of appropriate data and metadata to be gathered, along with established procedures for their collection, documentation, and management. Furthermore, suitable approaches must be implemented to evaluate and ensure the quality of the data. Therefore, the 'Europe Regional Chapter of the International Society of Exposure Science' (ISES Europe) human biomonitoring working group (ISES Europe HBM WG) proposes the development of a FAIR Environment and health registry (FAIREHR) (hereafter FAIREHR). FAIR Environment and health registry offers preregistration of studies on exposure sciences and environmental epidemiology using HBM (as a starting point) across all areas of environmental and occupational health globally. The registry is proposed to receive a dedicated web-based interface, to be electronically searchable and to be available to all relevant data providers, users and stakeholders. Planned Human biomonitoring studies would ideally be registered before formal recruitment of study participants. The resulting FAIREHR would contain public records of metadata such as study design, data management, an audit trail of major changes to planned methods, details of when the study will be completed, and links to resulting publications and data repositories when provided by the authors. The FAIREHR would function as an integrated platform designed to cater to the needs of scientists, companies, publishers, and policymakers by providing user-friendly features. The implementation of FAIREHR is expected to yield significant benefits in terms of enabling more effective utilization of human biomonitoring (HBM) data.

Automated Coding of Job Descriptions From a General Population Study: Overview of Existing Tools, Their Application and Comparison

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.

Applying the exposome concept to working life health

Exposures at work have a major impact on noncommunicable diseases (NCDs). Current risk reduction policies and strategies are informed by existing scientific evidence, which is limited due to the challenges of studying the complex relationship between exposure at work and outside work and health. We define the working life exposome as all occupational and related nonoccupational exposures. The latter includes nonoccupational exposures that may be directly or indirectly influenced by or interact with the working life of the individual in their relation to health. The Exposome Project for Health and Occupational Research aims to advance knowledge on the complex working life exposures in relation to disease beyond the single high exposure–single health outcome paradigm, mapping and relating interrelated exposures to inherent biological pathways, key body functions, and health. This will be achieved by combining (1) large-scale harmonization and pooling of existing European cohorts systematically looking at multiple exposures and diseases, with (2) the collection of new high-resolution external and internal exposure data. Methods and tools to characterize the working life exposome will be developed and applied, including sensors, wearables, a harmonized job exposure matrix (EuroJEM), noninvasive biomonitoring, omics, data mining, and (bio)statistics. The toolbox of developed methods and knowledge will be made available to policy makers, occupational health practitioners, and scientists. Advanced knowledge on working life exposures in relation to NCDs will serve as a basis for evidence-based and cost-effective preventive policies and actions. The toolbox will also enable future scientists to further expand the working life exposome knowledge base.

Occupational Exposure Assessment Tools in Europe: A Comprehensive Inventory Overview

OBJECTIVES

The Network on the Coordination and Harmonisation of European Occupational Cohorts (OMEGA-NET) was set up to enable optimization of the use of industrial and general population cohorts across Europe to advance aetiological research. High-quality harmonized exposure assessment is crucial to derive comparable results and to enable pooled analyses. To facilitate a harmonized research strategy, a concerted effort is needed to catalogue available occupational exposure information. We here aim to provide a first comprehensive overview of exposure assessment tools that could be used for occupational epidemiological studies.

METHODS

An online inventory was set up to collect meta-data on exposure assessment tools. Occupational health researchers were invited via newsletters, editorials, and individual e-mails to provide details of job-exposure matrices (JEMs), exposure databases, and occupational coding systems and their associated crosswalks to translate codes between different systems, with a focus on Europe.

RESULTS

Meta-data on 36 general population JEMs, 11 exposure databases, and 29 occupational coding systems from more than 10 countries have been collected up to August 2021. A wide variety of exposures were covered in the JEMs on which data were entered, with dusts and fibres (in 14 JEMs) being the most common types. Fewer JEMs covered organization of work (5) and biological factors (4). Dusts and fibres were also the most common exposures included in the databases (7 out of 11), followed by solvents and pesticides (both in 6 databases).

CONCLUSIONS

This inventory forms the basis for a searchable web-based database of meta-data on existing occupational exposure information, to support researchers in finding the available tools for assessing occupational exposures in their cohorts, and future efforts for harmonization of exposure assessment. This inventory remains open for further additions, to enlarge its coverage and include newly developed tools.