Occupational injury rates among Norwegian farmers: A sociotechnical perspective

The impact of Industry 4.0 on occupational health and safety: A systematic literature review

INTRODUCTION

Industry 4.0 has brought new paradigms to businesses based on high levels of automation and interconnectivity and the use of technologies. This new context has an impact on the work environment and workers. Nevertheless, these impacts are still inconclusive and controversial, requiring new investigative perspectives. This study aimed to investigate the requirements sought, the risk factors identified, and the adverse effects on workers caused by the characteristics of I4.0.

METHOD

The methodology was based on a systematic literature review utilizing the PRISMA protocol, and 30 articles were found eligible. A descriptive and bibliometric analysis of these studies was performed.

RESULTS

The results identified the main topics that emerged and have implications for workers' Occupational Health and Safety (OHS) and divided them into categories. The requirements are related mainly to cognitive, organizational, and technological demands. The most significant risk factors generated were associated with the psychosocial ones, but organizational, technological, and occupational factors were also identified. The adverse effects cited were categorized as psychic, cognitive, physical, and organizational; stress was the most cited effect. An explanatory theoretical model of interaction was proposed to represent the pathway of causal relations between the requirements and risk factors for the effects caused by I4.0.

CONCLUSIONS AND PRACTICAL APPLICATIONS

This review has found just how complex the relationships between the principles of Industry 4.0 are (e.g., requirements, risk factors, and effects) and the human factors. It also suggests a pathway for how these relationships occur, bridging the gap left by the limited studies focused on connecting these topics. These results can help organizational managers understand the impacts of I4.0 on workers' safety and health.

Profile and risk factors in farmer injuries: a review based on Haddon matrix and 5 E's risk reduction strategy

Farmers are considered a high-risk group for intentional and unintentional injuries. This review identified significant risk factors for agricultural injuries in farmers and explored injury prevention countermeasures based on the literature. Therefore, CiteSpace software was used to analyze the relevant literature in this field. Additionally, we identified both key risk factors and countermeasures using the Haddon matrix and the 5 E's risk reduction strategies conceptual framework, respectively. The risk factors were identified from four categories (host, agent, physical environment, and social environment) corresponding to three phases (pre-event, event, and post-event). Interventions of 5 E's risk reduction strategies including education, engineering, enforcement, economic, and emergency response have been proven effective in preventing injuries or reducing their severity. Our findings provide a comprehensive foundation and research direction for the study and prevention of injuries among farmers.

Latin American Agricultural Workers' Job Demands and Resources and the Association With Health Behaviors at Work and Overall Health

In the present study, we describe the job demands and job resources (JD-R) experienced by agricultural workers in three Latin American countries and their relationship to proactive health behaviors at work and overall health. Following previous research on the JD-R model, we hypothesized that job demands (H1) would be negatively related to agricultural workers' self-reported overall health. On the other hand, we hypothesized that job resources (H2) would be positively related to agricultural workers' overall health. Furthermore, we hypothesized (H3) that workers' engagement in jobsite health promotion practices via their proactive health behaviors at work would partially mediate the relationship between workers' job resources and job demands and overall health. We also had a research question (R1) about whether there were differences by type of job held. The sample of workers who participated in this study (N = 1,861) worked in Mexico, Guatemala, and Nicaragua for one large agribusiness that produces sugar cane. They worked in two distinct areas: company administration and agricultural operations. We administered employee health and safety culture surveys using survey methods tailored to meet the needs of both types of workers. Stratified path analysis models were used to test study hypotheses. In general, we found support for hypotheses 1 and 2. For example, operations workers reported more physically demanding jobs and administrative workers reported more work-related stress. Regardless, the existence of high job demands was associated with poorer overall health amongst both types of workers. We found that workers in more health-supportive work environments perform more proactive health behaviors at work, regardless of their role within the organization. However, hypothesis 3 was not supported as proactive health behaviors at work was not associated with overall health. We discuss future research needs in terms of evaluating these hypotheses amongst workers employed by small- and medium-sized agribusinesses as well as those in the informal economy in Latin America. We also discuss important implications for agribusinesses seeking to develop health promotion programs that meet the needs of all workers.

Towards a software architecture to manage occupational safety at grain handling and storage facilities

The study had as objective to evaluate occupational hazards on grain storage unit to define a conceptual model, implemented in an algorithm to manage the grains storage facilities safety standards compliance. Sampling points location were defined for static quantification of noise, dust and heat stress hazards in grains pre-processing operations to indicate the effectiveness of the control measures implemented. Safety standards applied to grain handling and storage facilities were identified and selected. Chart flows were elaborated to the algorithm logics and conceptual modeling. The highest level of noise was present in the grain cleaning operation (99.1 dB), while the expedition operation has the highest level of dust (20.27%). The heat stress was present in the grain drying operation (43.64 WBGT). Noise analysis did not show a difference between grains, only between operations. The flow of corn grain mass caused higher dust concentrations in the expedition operation. The method applied to characterize and quantify the hazards in grain storage units was satisfactory, and it is recommended as standard, for use in corn and soybean grains handling and storage units. The algorithm to manage occupational safety at storage facilities collaborates to monitor the safety compliance on postharvest operations.