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Mass mortality events (MMEs) are defined as the death of large numbers of fish over a short period of time. These events can result in catastrophic losses to the Atlantic salmon aquaculture industry and the local economy. However, they are challenging to understand because of their relative infrequency and the high number of potential factors involved. As a result, the causes and consequences of MMEs in Atlantic salmon aquaculture are not well understood. In this study, we developed a structural network of causal risk factors for MMEs for aquaculture and the communities that depend on Atlantic salmon aquaculture. Using the Interpretive Structural Modeling (ISM) technique, we analysed the causes of Atlantic salmon mass mortalities due to environmental (abiotic), biological (biotic) and nutritional risk factors. The consequences of MMEs were also assessed for the occupational health and safety of aquaculture workers and their implications for the livelihoods of local communities. This structural network deepens our understanding of MMEs and points to management actions and interventions that can help mitigate mass mortalities. MMEs are typically not the result of a single risk factor but are caused by the systematic interaction of risk factors related to the environment, fish diseases, feeding/nutrition and cage‐site management. Results also indicate that considerations of health and safety risk, through pre‐ and post‐event risk assessments, may help to minimize workplace injuries and eliminate potential risks of human fatalities. Company and government‐assisted socio‐economic measures could help mitigate post‐mass mortality impacts. Appropriate and timely management actions may help reduce MMEs at Atlantic salmon cage sites and minimize the physical and social vulnerabilities of workers and local communities. [ABSTRACT FROM AUTHOR]

Objective: To review the publications of a Total Worker Health Center® of Excellence, the Harvard T.H. Chan School of Public Health Center for Work, Health, and Well-being, in order to identify research findings relevant to either organizational or public policies. Methods: Two researchers independently reviewed 57 publications from 2011 to 2019 to identify cross-cutting themes that focus on working conditions or related health outcomes and their organizational and public policy implications. Results: Twelve cross-cutting themes were identified with their respective organizational and public policy implications. Several policy implications cut across work-related themes. Conclusions: Policy implications of TWH® research will aid in setting priorities to translate this from research into practice in future studies and help identify gaps that we and others can use to plan future TWH® research. [ABSTRACT FROM AUTHOR]

Objective The aim of this study was to describe the application of latent class growth analysis (LCGA) to identify different working life trajectories (WLT) using employed working time by year as a repeated measure. Methods Trajectories are estimated using LCGA, which considers all individuals within a trajectory to be homogeneous. The methodology was applied to a subsample of the Spanish WORKing life Social Security (WORKss) cohort, limited to persons born 1956-1965 (N=247 475). The number of days worked per year is used as a repeated measure across 32 time points (1981-2013). Results According to the model-fit results and further guided by expert knowledge, a four WTL model was selected as the optimal approach: WLT1 or "high labor force participation" (N=99 591; 40.2%); WLT2 or "decreased labor force participation" (N= 22 846; 9.2%); WLT3 or "increased labor force participation" (N=59 213; 23.9%); and WLT4 or "low labor force participation" (N=65 827; 26.6%). WLT1 consisted mainly of men with more years of work experience (>19 years) while WLT4 was mainly composed by women with <9 years. The other two trajectories had opposite trends and no sex differences. The occupational category variable had little influence in the trajectories. Conclusions Longitudinal data that are regularly collected by administrative systems can benefit from LCGA approaches to identify different trajectory patterns that may be associated with an outcome of interest. In occupational epidemiology, this study represents a step forward by using this modeling approach to identify different WLT. [ABSTRACT FROM AUTHOR]

Objective: This study developed, implemented, and evaluated the feasibility of executing an organizational capacity building intervention to improve bus driver safety and well-being in a Chilean transportation company. Method: Through an implementation science lens and using a pre-experimental mixed methods study design, we assessed the feasibility of implementing a participatory organizational intervention designed to build organizational capacity. Result: We identified contextual factors that influenced the intervention mechanisms and intervention implementation and describe how the company adapted the approach for unexpected external factors during the COVID-19 pandemic and social and political unrest experienced in Chile. Conclusions: The intervention enabled the organization to create an agile organizational infrastructure that provided the organization's leadership with new ways to be nimbler and more responsive to workers' safety and well-being needs and was robust in responding to strong external forces that were undermining worker safety and well-being., Competing Interests: Conflict of interest: None declared., (Copyright © 2024 American College of Occupational and Environmental Medicine.)