基于海员社会人口学、职业和与健康相关特征的自我报告高血压远程医疗风险预测模型：一项横断面流行病学研究。

Risk prediction model of self-reported hypertension for telemedicine based on the sociodemographic, occupational and health-related characteristics of seafarers: a cross-sectional epidemiological study.

机构信息

School of Medicinal and Health Products Sciences, University of Camerino, Camerino, Marche, Italy

School of Public Health, College of Health Sciences and Medicine, Wolaita Sodo University, Sodo, Ethiopia.

出版信息

BMJ Open. 2023 Oct 4;13(10):e070146. doi: 10.1136/bmjopen-2022-070146.

DOI:10.1136/bmjopen-2022-070146

PMID:37793918

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10551994/

Abstract

OBJECTIVES

High blood pressure is a common health concern among seafarers. However, due to the remote nature of their work, it can be difficult for them to access regular monitoring of their blood pressure. Therefore, the development of a risk prediction model for hypertension in seafarers is important for early detection and prevention. This study developed a risk prediction model of self-reported hypertension for telemedicine.

DESIGN

A cross-sectional epidemiological study was employed.

SETTING

This study was conducted among seafarers aboard ships. Data on sociodemographic, occupational and health-related characteristics were collected using anonymous, standardised questionnaires.

PARTICIPANTS

This study involved 8125 seafarers aged 18-70 aboard 400 vessels between November 2020 and December 2020. 4318 study subjects were included in the analysis. Seafarers over 18 years of age, active (on duty) during the study and willing to give informed consent were the inclusion criteria.

OUTCOME MEASURES

We calculated the adjusted OR (AOR) with 95% CIs using multiple logistic regression models to estimate the associations between sociodemographic, occupational and health-related characteristics and self-reported hypertension. We also developed a risk prediction model for self-reported hypertension for telemedicine based on seafarers' characteristics.

RESULTS

Among the 4318 participants, 55.3% and 44.7% were non-officers and officers, respectively. 20.8% (900) of the participants reported having hypertension. Multivariable analysis showed that age (AOR: 1.08, 95% CI 1.07 to 1.10), working long hours per week (AOR: 1.02, 95% CI 1.01 to 1.03), work experience at sea (10+ years) (AOR: 1.79, 95% CI 1.33 to 2.42), being a non-officer (AOR: 1.75, 95% CI 1.44 to 2.13), snoring (AOR: 3.58, 95% CI 2.96 to 4.34) and other health-related variables were independent predictors of self-reported hypertension, which were included in the final risk prediction model. The sensitivity, specificity and accuracy of the predictive model were 56.4%, 94.4% and 86.5%, respectively.

CONCLUSION

A risk prediction model developed in the present study is accurate in predicting self-reported hypertension in seafarers' onboard ships.

摘要

目的

高血压是海员常见的健康问题。然而，由于他们工作的偏远性质，他们很难定期监测血压。因此，为了早期发现和预防，开发一种海员高血压风险预测模型很重要。本研究开发了一种用于远程医疗的自我报告高血压风险预测模型。

设计

采用横断面流行病学研究。

地点

本研究在船舶上的海员中进行。使用匿名的、标准化的问卷收集社会人口学、职业和与健康相关的特征数据。

参与者

这项研究涉及 2020 年 11 月至 12 月期间，400 艘船舶上的 8125 名 18-70 岁的海员。4318 名研究对象被纳入分析。纳入标准为 18 岁以上、研究期间（值班）活跃且愿意知情同意的海员。

结果

在 4318 名参与者中，非军官和军官分别占 55.3%和 44.7%。20.8%（900）的参与者报告患有高血压。多变量分析显示，年龄（OR：1.08，95%CI 1.07-1.10）、每周工作时间长（OR：1.02，95%CI 1.01-1.03）、海上工作经验（10 年以上）（OR：1.79，95%CI 1.33-2.42）、非军官（OR：1.75，95%CI 1.44-2.13）、打鼾（OR：3.58，95%CI 2.96-4.34）和其他健康相关变量是自我报告高血压的独立预测因素，这些因素被纳入最终风险预测模型。预测模型的灵敏度、特异性和准确性分别为 56.4%、94.4%和 86.5%。