title: Using additional information on working hours to predict coronary heart disease: a cohort study.
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.
  
  
  METHODS
  Cohort study with baseline medical examination performed between 1991 and 1993 and prospective follow-up for incident CHD performed until 2004.
  
  
  METHODS
  Civil service departments in London (the Whitehall II study).
  
  
  METHODS
  7095 adults (2109 women and 4986 men) aged 39 to 62 years working full-time without CHD at baseline.
  
  
  METHODS
  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).
  
  
  CONCLUSIONS
  The findings may not be generalizable to populations with a larger proportion of high-risk persons and were not validated in an independent cohort.
  
  
  CONCLUSIONS
  Information on working hours may improve risk prediction of CHD on the basis of the Framingham risk score in low-risk, working populations.
  
  
  BACKGROUND
  Medical Research Council; British Heart Foundation; Bupa Foundation; and the National Heart, Lung, and Blood Institute and National Institute on Aging of the National Institutes of Health.
authors.affiliation: Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E 6BT, United Kingdom. m.kivimaki@ucl.ac.uk
authors.forename: Mika
authors.initials: M
authors.lastname: Kivimäki
authors.forename: G David
authors.initials: GD
authors.lastname: Batty
authors.forename: Mark
authors.initials: M
authors.lastname: Hamer
authors.forename: Jane E
authors.initials: JE
authors.lastname: Ferrie
authors.forename: Jussi
authors.initials: J
authors.lastname: Vahtera
authors.forename: Marianna
authors.initials: M
authors.lastname: Virtanen
authors.forename: Michael G
authors.initials: MG
authors.lastname: Marmot
authors.forename: Archana
authors.initials: A
authors.lastname: Singh-Manoux
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Shipley
mesh_terms: D000328:Adult; D003327:Coronary Disease / Q000453:epidemiology* / Q000401:mortality; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D012307:Risk Factors; D014940:Work Schedule Tolerance