浦索港卫生所滨海区船舶工作人员高血压危险因素分析

Arjuman Asrun, None Wahiduddin, None Ansariadi, Ridwan Amiruddin, None Balqis, Andi Alfian Zainuddin, Anwar Mallongi
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Chi-square analysis was employed to assess the relationship between respondent characteristic variables and independent variables concerning the occurrence of hypertension. Multivariate analysis was conducted on variables that showed an association with hypertension to obtain independent risk values using logistic regression analysis. This research used a 95% confidence level. Results: The prevalence of hypertension in ship crew is 12.73%. Logistic regression results showed that the crew members had an overweight (AOR=15.93, 95%CI: 5.080-49.981, p=0.000) and moderate and heavy smokers among crew members (AOR=2.51, 95%CI: 1.038-6.066), p=0.021) were factors associated with the prevalence of hypertension in ships crew members of hypertension in ships crew members after controlled by aged over 45 years (AOR=22.94; 95% CI: 2.587-203.477, p=0.005) and family history of hypertension (AOR=6.01; 95% CI: 2.741-13.168, p=0.000). 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引用次数: 0

摘要

目标:作为海员在船上工作或受船舶所有人或经营人雇用以履行其职务后的职责的船员,在获得支持其保持健康的健康教育、设施和基础设施方面将受到限制。高血压是导致心血管疾病的非传染性疾病之一。本研究旨在探讨渤索港务卫生处本区海港工作范围内船员高血压患病率的相关危险因素。方法:采用横断面研究,385人参与数据分析。采用卡方分析评估被调查者高血压发生的特征变量与自变量之间的关系。对与高血压相关的变量进行多因素分析,采用logistic回归分析获得独立风险值。这项研究使用了95%的置信水平。结果:船员高血压患病率为12.73%。Logistic回归结果显示,船员中体重超标(AOR=15.93, 95%CI: 5.080 ~ 49.981, p=0.000)和中度重度吸烟者(AOR=2.51, 95%CI: 1.038 ~ 6.066), p=0.021)是与船舶船员高血压患病率相关的因素。95% CI: 2.587-203.477, p=0.005)和高血压家族史(AOR=6.01;95% CI: 2.741-13.168, p=0.000)。结论:本研究发现船舶船员的身体质量指数和吸烟行为是高血压的显著危险因素,而饮酒和工作场所相关的环境应激在本研究中未被发现是显著的危险因素。研究意义:本研究可为确定船上船员高血压预防和控制的健康计划和更具体的优先人群提供参考。原创性:本研究的对象是在船上执行操作任务的合法海员,而大多数类似研究使用的是在保健诊所的海员的健康数据。
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Analysis of Risk Factors for Hypertension in Ship Crews of Seaports Work Coverage for Poso Port Health Office, Bungku Working Area
Objective: Ship crew as seafarers who work or are employed on board the ship by the owner or operator of the ship to carry out their duties following their position will have limitations in accessing health education, facilities, and infrastructure that support them to maintain their health. One of the non-communicable diseases that contributes to cardiovascular diseases is hypertension. This study aims to determine the risk factors related to the prevalence of hypertension in ship crew at Seaport work coverage for Poso Port Health Office, Bungku Working Area. Methods: This was a cross-sectional study with a sample size of 385 participant involve in data analysis. Chi-square analysis was employed to assess the relationship between respondent characteristic variables and independent variables concerning the occurrence of hypertension. Multivariate analysis was conducted on variables that showed an association with hypertension to obtain independent risk values using logistic regression analysis. This research used a 95% confidence level. Results: The prevalence of hypertension in ship crew is 12.73%. Logistic regression results showed that the crew members had an overweight (AOR=15.93, 95%CI: 5.080-49.981, p=0.000) and moderate and heavy smokers among crew members (AOR=2.51, 95%CI: 1.038-6.066), p=0.021) were factors associated with the prevalence of hypertension in ships crew members of hypertension in ships crew members after controlled by aged over 45 years (AOR=22.94; 95% CI: 2.587-203.477, p=0.005) and family history of hypertension (AOR=6.01; 95% CI: 2.741-13.168, p=0.000). Conclusions: Body mass index and smoking behavior among ship crew members are significant risk factors for hypertension in this study, while alcohol consumption and workplace-related environmental stress were not found to be significant risk factors in this research Implication of the research: This research can serve as a reference for determining health programs and more specific priority groups targeted for the prevention and control of hypertension among ship crew members on board. Originality: This study was conducted on ship crew members, legally active seafarers in the operational tasks on ship, whereas most similar research uses the health data of seafarers in healthcare clinics.
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