Abd El-Nabi, A., Charl Fahmy, F., Sherif, A., Hassab, A., Kassem, A., Mohamed, A. (2008). Risk Prediction of Coronary Artery Disease among Naval Forces. Journal of High Institute of Public Health, 38(3), 637-648. doi: 10.21608/jhiph.2008.20910
Ashraf Farouk Abd El-Nabi; Fahmy Charl Fahmy; Aida Ali Reda Sherif; Ali Abd El-Halim Hassab; Ali Nasrat Mohamed Kassem; Ashry Gad Mohamed. "Risk Prediction of Coronary Artery Disease among Naval Forces". Journal of High Institute of Public Health, 38, 3, 2008, 637-648. doi: 10.21608/jhiph.2008.20910
Abd El-Nabi, A., Charl Fahmy, F., Sherif, A., Hassab, A., Kassem, A., Mohamed, A. (2008). 'Risk Prediction of Coronary Artery Disease among Naval Forces', Journal of High Institute of Public Health, 38(3), pp. 637-648. doi: 10.21608/jhiph.2008.20910
Abd El-Nabi, A., Charl Fahmy, F., Sherif, A., Hassab, A., Kassem, A., Mohamed, A. Risk Prediction of Coronary Artery Disease among Naval Forces. Journal of High Institute of Public Health, 2008; 38(3): 637-648. doi: 10.21608/jhiph.2008.20910
Risk Prediction of Coronary Artery Disease among Naval Forces
1Head of Preventive Medicine Department, Egyptian Navy
2Department of Occupational Health and Air Pollution (Division of Occupational Health and Industrial Medicine), High Institute of Public Health, Alexandria University, Alexandria, Egypt
3Department of Epidemiology, High Institute of Public Health, Alexandria University, Alexandria, Egypt
4Department of Internal Medicine, Faculty of Medicine, Alexandria University, Alexandria, Egypt
Abstract
Background: Coronary artery disease (CAD) risk factors seem to cluster in some occupational groups. Objective: The present study was designed to investigate CAD risk factors among naval forces as an example of a high risk sector and to construct a risk prediction model for the disease. Methods: A case control study was carried out at the general naval hospital (GNH) in Alexandria. The study included 250 male consecutive naval CAD cases with a control group of 250 males matches for age, occupational level, sociodemographic characteristics and, free from CAD. All participants were subjected to a questionnaire about personal data, occupational history and exposures, occupational and leisure physical activity, dietary habits, smoking, and medical history. Anthropometric measurements, sitting blood pressure, and lipid profile were determined by the standard methods. Results: revealed that occupational sedentary activity and perceived occupational noise were the significantly reported special occupational characteristics together with other conventional risk factors among CAD naval cases verses controls (p<0.0001 & <0.009 respectively). Logistic regression analysis with the dependent variable as being a CAD case showed independently significant effects for family history of premature CAD, history of hypertension, smoking, history of diabetes mellitus, body mass index (BMI), leisure physical activity, fish consumption, and HDL-cholesterol. A risk prediction model utilizing these variables was constructed with an overall correct percent of 74.6%. Conclusions: Application of the model expresses the risk of having CAD in an individual eligible with criteria of the study population. These results are of special importance for design of preventive programs for CAD in similar high risk occupational groups.
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