Poor Sleep, Anxiety, Depression and Other Occupational Health Risks in Seafaring Population
Journal Title: TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation - Year 2016, Vol 10, Issue 1
Abstract
Background: seafaring is an occupation with specific work-related risks, causing increased morbidity and mortality. Nevertheless, the research in the area of marine students ‘sleep quality and mental health is lacking in Lithuania, as well as other European countries. The aim was to overview scientific findings, related with occupational health risks in a seafaring population and asses the frequency of poor sleep and the relations among poor sleep, anxiety and depression in the sample of maritime students. Methods and contingent. The scientific literature review, based on PubMed sources analysis, related to occupational health risks in seafaring population, was performed. Questionnaire survey was conducted in 2014 at The Lithuanian Maritime Academy, 393 (78.9 % of them males) students participated. Sleep quality was evaluated by Pittsburg Sleep Quality Index. Anxiety and depression were assessed by Hospital Anxiety and Depression scale. Sociodemographic questions were used. The Chi-square test r Fisher exact test was used to estimate association between categorical variables. P- Values less than 0.05 were interpreted as statistically significant. Results. Scientific literature review indicate that highly stressful and exhausting working conditions on ships can lead to depression, insomnia, various types of cancer, cardiovascular, communicable, blood-born and sexually transmitted diseases. Poor sleep was found in 45.0 % of the students. Mild depression was established in 6.9 %, moderate in 2.3 %, Severe in 0.8 % of the students. Mild anxiety was found in 19.1 %, moderate in 14.8 % and Severe in 7.9 % of the students. Depression (score ?8) was significantly more frequent among third (fourth) year students (22.2 %) with poor sleep, as compared to the students demonstrating good sleep (2.7 %). Marine engineering programme students whose sleep was poor more often had depression (22.0 %), as compared to the students whose sleep was good (5.7 %). Conclusions. Seafarers have higher hospitalization and mortality rates than age-matched peers, due to exposure to unique occupational health risk factors. Maritime students had poor sleep more than anxiety or depression. Anxiety and depression were more common among the students demonstrating poor sleep rather than good sleep. Key words: Maritime students, Sleep quality, Anxiety, Depression, Occupational health.
Authors and Affiliations
Jurgita Andruškienė, Šarūnė Barsevičienė, Giedrius Varoneckas
Keywords
Related Articles
- EP ID EP193317
- DOI 10.12716/1001.10.01.01
- Views 161
- Downloads 0
Study of Estonian Maritime Education Institutions Alumni
From November 2015 to June 2016 Research and Development Centre of the Estonian Maritime Academy (hereinafter R&D Centre of EMARA) carried out a survey among the alumni of maritime institutions in Estonia. The survey bas...
Application of Ship Motion Simulation in Reliability Assessment of Ship Entrance into the Port
The growing number of large container vessels is the reason of port infrastructure modernization necessity and changes of local bylaws in ports. The accessibility studies based on ship motion simulation allow for the ass...
Improving MET Quality: Relationship Between Motives of Choosing Maritime Professions and Students’ Approaches to Learning
Question of improvement quality of studies is a continual hot issue in every educational envi-ronment. In maritime education and training, this question is especially important because of international regulations of mar...
Shared Mental Models of Challenging Maritime Situations: Comparisons of Ship and Shore Personnel in the Straits of Malacca and Singapore
Shared mental models, measured as similar perceptions and understandings of the components of a work task or an operative environment, is a key characteristic for high performing teams. Identifying and addressing differe...
Towards use of Dijkstra Algorithm for Optimal Navigation of an Unmanned Surface Vehicle in a Real-Time Marine Environment with results from Artificial Potential Field
The growing need of ocean surveying and exploration for scientific and industrial application has led to the requirement of routing strategies for ocean vehicles which are optimal in nature. Most of the op-timal path pla...