Self-Reported Modifiable Risk Factors of Cardiovascular Disease among Seafarers: A Cross-Sectional Study of Prevalence and Clustering

Background: Cardiovascular diseases (CVD) are the major cause of work-related mortality from diseases onboard ships in seafarers. CVD burden derives mainly from modifiable risk factors. To reduce the risk factors and the burden of CVD onboard ships in seafarers, it is important to understand the up-to-date prevalence of modifiable risk factors. The primary purpose of this study was to assess the prevalence and clustering of self-reported modifiable CVD risk factors among seafarers. We have also explored the association between socio-demographic and occupational characteristics and reported modifiable CVD risk factor clustering. Materials and methods: A cross-sectional study was conducted among seafarers from November to December 2020 on board ships. In total, 8125 seafarers aged 18 to 70 were selected from 400 ships. Data were collected using a standardized and anonymous self-reported questionnaire. The prevalence value for categorical variables and mean differences for continuous variables were compared using chi-square and independent sample t-tests. Multinomial logistic regression models were performed to identify independent predictors for modifiable CVD risk factor clustering. Results: Out of a total of 8125 seafarers aged ≥18 years on selected vessels, 4648 seafarers volunteered to participate in the survey, with a response rate of 57.2%. Out of 4318 participants included in analysis, 44.7% and 55.3% were officers and non-officers, respectively. The prevalence of reported hypertension, diabetes, current smoking and overweight or obesity were 20.8%, 8.5%, 32.5%, and 44.7%, respectively. Overall, 40%, 20.9%, 6% and 1.3% of the study participants respectively had one, two, three and four modifiable CVD risk factors. Older age (51+ years) (odds ratio (OR): 3.92, 95% confidence interval (CI): 2.44–6.29), being non-officers (OR: 1.36, 95% CI: 1.09–1.70), job duration (10–20 years) (OR: 2.73, 95% CI: 2.09–3.57), job duration (21+ years) (OR: 2.60, 95% CI: 1.79–3.78), working 57–70 h per week (OR: 2.03, 95% CI: 1.65–2.49) and working 71+ h per week (OR: 3.08, 95% CI: 2.42–3.92) were independent predictors for at least two self-reported modifiable CVD risk factor clustering. Conclusion: The results of our study demonstrate that more than four in six (68.5%) seafarers aged between 19 and 70 years have at least one of the modifiable CVD risk factors. Therefore, CVD prevention and modifiable risk factors reduction strategies targeting high-risk groups should be designed and implemented on board ships.

JOB DURATION AND HISTORY-DEPENDENT UNEMPLOYMENT INSURANCE

Unemployment insurance schemes typically include eligibility conditions comprising the employment history prior to becoming unemployed, an aspect largely neglected in the literature. We develop an analytically tractable matching model including such contingencies. Unemployed determine reservation durations for jobs to be acceptable, and stronger employment histories increase reservation durations. This creates a stratification among unemployed; unemployed with short employment histories accept short-term jobs, while those with a strong employment history aims for jobs with a longer duration. A trade-off arises between the employment level and the matching quality in terms of job duration; a stronger reward to employment histories reduces employment, but improves match quality (more long-term jobs). Numerical simulations show that the distribution between short- and long-term jobs is significantly affected by history dependencies in benefits levels and duration. The optimal utilitarian policy is shown to include contingencies based on employment histories of the unemployed.

A Generalized MILP Formulation for the Period-Aggregated Resource Leveling Problem with Variable Job Duration

We study a resource leveling problem with variable job duration. The considered problem includes both scheduling and resource management decisions. The planning horizon is fixed and separated into a set of time periods of equal length. There are several types of resources and their amount varies from one period to another. There is a set of jobs. For each job, a fixed volume of work has to be completed without any preemption while using different resources. If necessary, extra resources can be used at additional costs during each time period. The optimization goal is to minimize the total overload costs required for the execution of all jobs by the given deadline. The decision variables specify the starting time of each job, the duration of the job and the resource amount assigned to the job during each period (it may vary over periods). We propose a new generalized mathematical formulation for this optimization problem. The formulation is compared with existing approaches from the literature. Theoretical study and computational experiments show that our approach provides more flexible resource allocation resulting in better final solutions.

Two-Machine Job-Shop Scheduling Problem to Minimize the Makespan with Uncertain Job Durations

We study two-machine shop-scheduling problems provided that lower and upper bounds on durations of n jobs are given before scheduling. An exact value of the job duration remains unknown until completing the job. The objective is to minimize the makespan (schedule length). We address the issue of how to best execute a schedule if the job duration may take any real value from the given segment. Scheduling decisions may consist of two phases: an off-line phase and an on-line phase. Using information on the lower and upper bounds for each job duration available at the off-line phase, a scheduler can determine a minimal dominant set of schedules (DS) based on sufficient conditions for schedule domination. The DS optimally covers all possible realizations (scenarios) of the uncertain job durations in the sense that, for each possible scenario, there exists at least one schedule in the DS which is optimal. The DS enables a scheduler to quickly make an on-line scheduling decision whenever additional information on completing jobs is available. A scheduler can choose a schedule which is optimal for the most possible scenarios. We developed algorithms for testing a set of conditions for a schedule dominance. These algorithms are polynomial in the number of jobs. Their time complexity does not exceed O ( n 2 ) . Computational experiments have shown the effectiveness of the developed algorithms. If there were no more than 600 jobs, then all 1000 instances in each tested series were solved in one second at most. An instance with 10,000 jobs was solved in 0.4 s on average. The most instances from nine tested classes were optimally solved. If the maximum relative error of the job duration was not greater than 20 % , then more than 80 % of the tested instances were optimally solved. If the maximum relative error was equal to 50 % , then 45 % of the tested instances from the nine classes were optimally solved.

The influence of organizational and technological complexity on the period of job execution

Introduction. An essential index of the efficiency of the construction organization is its building period, which depends on the timing of individual work items. It is especially significant for large projects of public buildings including ones of medical establishments being complicated installations regarding their space-and-planning and technological aspects. It is known that the job duration is influenced by its complexity and number of workers assigned for it. However, the influence of the job complexity remains unexplored. It can be expressed by the average job grade and quantity of requirements for the job results. In addition to this, the nonlinear feature of the dependencies is not studied. Materials and methods. A statistical study was conducted to examine the feature of the processes and the reason for managing requirements. It was based on the data of the job labor content, complexity and duration, the number of workers during the construction of the Research Institute of Pediatric Oncology and Hematology building of the Scientific Medicine Centre of Oncology named after N.N. Blokhin in Moscow. The analysis showed the regression equation, the correlation, and determination coefficients. The significance of the coefficients was estimated using the Student’s criterion. Results. The study demonstrated a nonlinear dependence on the factors considered on the job duration. However, the average job grade is of a minor effect and can be excluded from the influencing factors. On the contrary, the quantity of requirements has a significant impact, which indicates the need to manage the requirements in the course of construction. Conclusions. To reduce the job duration, it is necessary to create a requirements management system that will also improve the quality of the performed work. In the future, it is expedient to conduct research on other construction projects.