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Using Additional Information on Working Hours to Predict Coronary Heart Disease.
- Source :
- Annals of Internal Medicine; 4/5/2011, Vol. 154 Issue 7, p457-W.153, 9p, 1 Diagram, 6 Charts
- Publication Year :
- 2011
-
Abstract
- Background: Long working hours are associated with increased risk for coronary heart disease (CHD). Adding information on long hours to traditional risk factors for CHD may help to improve risk prediction for this condition. Objective: To examine whether information on long working hours improves the ability of the Framingham risk model to predict CHD in a low-risk, employed population. Design: Cohort study with baseline medical examination performed between 1991 and 1993 and prospective follow-up for incident CHD performed until 2004. Setting: Civil service departments in London (the Whitehall II study). Participants: 7095 adults (2109 women and 4986 men) aged 39 to 62 years working full-time without CHD at baseline. Measurements: Working hours and the Framingham risk score were measured at baseline. Coronary death and nonfatal myocardial infarction were ascertained from medical screenings every 5 years, hospital data, and registry linkage. Results: 192 participants had incident CHD during a median 12.3- year follow-up. After adjustment for their Framingham risk score, participants working 11 hours or more per day had a 1.67-fold (95% CI, 1.10- to 2.55-fold) increased risk for CHD compared with participants working 7 to 8 hours per day. Adding working hours to the Framingham risk score led to a net reclassification improvement of 4.7% (P = 0.034) due to better identification of persons who later developed CHD (sensitivity gain). Limitation: The findings may not be generalizable to populations with a larger proportion of high-risk persons and were not validated in an independent cohort. Conclusion: Information on working hours may improve risk prediction of CHD on the basis of the Framingham risk score in low-risk, working populations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00034819
- Volume :
- 154
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Annals of Internal Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 60001509
- Full Text :
- https://doi.org/10.7326/0003-4819-154-7-201104050-00003