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Title
A novel detection model for metabolic syndrome among seafarers on trade ships in the Red Sea: A cross-sectional observational study

ISSN printed: 1733-8670, ISSN on-line: 2392-0378
Abouelanin, Mohamed A.1; Mohamed, Mostafa M.2
URI: https://repository.pm.szczecin.pl/handle/123456789/2906
2026-03-31
This cross-sectional observational study evaluated the prevalence and determinants of metabolic syndrome (MetS) among 1432 seafarers aboard 76 trade vessels in the Red Sea. Data collection involved onboard examinations and remote or email-based protocols, encompassing anthropometric, biochemical, and lifestyle assessments. The prevalence of MetS was 27.8%, with higher rates among officers (33.5%) than among ratings (24.8%). Central obesity (81.3%) and elevated blood pressure (72.4%) were the most common components. Multivariate analysis identified age of 40 years or older, officer rank, and physical inactivity as significant predictors. Based on these findings, a novel three-phase maritime health framework is proposed, integrating digital screening, artificial intelligence (AI)-driven risk stratification, and continuous telemedicine monitoring. This model addresses operational challenges in surveillance compliance and aligns with the shipping sector’s digital transformation, providing a predictive and preventive approach to chronic disease management at sea.
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Title

A novel detection model for metabolic syndrome among seafarers on trade ships in the Red Sea: A cross-sectional observational study

Pages

Figures

4

Tables

2

ISSN printed

1733-8670

ISSN on-line

2392-0378

DOI

10.17402/680

Type

Original scientific article

Journal

85 Scientific Journals of the Maritime University of Szczecin, no. 85 / 2026

Publisher

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Politechniki Morskiej w Szczecinie

Copyright Holder

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Politechniki Morskiej w Szczecinie

Published

2026-03-31

Recieved

2025-08-14

Accepted

2026-03-09

Funding

No data

Keywords

metabolic syndrome, seafarers, maritime health, artificial intelligence, Red Sea, maritime safety

URI:

https://repository.pm.szczecin.pl/handle/123456789/2906

Language

English

Authors

Abouelanin, Mohamed A.1; Mohamed, Mostafa M.2

Affiliation

1 Faculty of Medicine, Menoufia University, Menoufia, Egypt H2F6+VR2, Al Ostaz Yassen Abd Al Ghafar, Qism Shebeen El-Kom, Shibin el Kom, Menofia Governorate 6132720, Egipt, mohamed.abouelanin2022@med.menofia.edu.eg
2 Faculty of Medicine, Menoufia University, Menoufia, Egypt H2F6+VR2, Al Ostaz Yassen Abd Al Ghafar, Qism Shebeen El-Kom, Shibin el Kom, Menofia Governorate 6132720, Egipt, mostafa_mahmoud@med.menofia.edu.eg

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