Sleep disturbances independently predict heart failure in overweight middle-aged men

Eur J Heart Fail. 2007 Feb;9(2):184-90. doi: 10.1016/j.ejheart.2006.05.012. Epub 2006 Aug 1.


Background: Sleep disturbances are associated with manifest heart failure (HF). However, the relationship between sleep disturbances and incident HF has been less studied.

Aims: To investigate self-reported sleep disturbances as predictors of HF in a longitudinal, community-based cohort of 2314 middle-aged men.

Methods and results: Data on self-reported sleep disturbances, as well as established risk factors for HF were collected and analyzed using Cox proportional hazards analyses. In multivariable Cox proportional hazards models adjusted for established risk factors for HF, the presence at baseline of sleep disturbances (hazard ratio [HR], 1.52; 95% confidence interval [CI], 1.16-1.99; p=0.002) was an independent risk factor for HF. There was evidence of effect modification between BMI and sleep disturbances. In multivariable-adjusted models, sleep disturbance (HR, 1.58; 95% CI, 1.13-2.21; p=0.008) was an independent risk factor for HF in overweight participants (BMI>25), but not in normal-weight participants (BMI< or =25). All results remained similar in a sub-sample excluding all participants suffering from a myocardial infarction during follow-up.

Conclusions: Self-reported sleep disturbances imply an increased risk of subsequent HF in overweight middle-aged men, via mechanisms largely independent of established risk factors for HF, including an interim myocardial infarction.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Heart Failure / epidemiology
  • Heart Failure / etiology*
  • Heart Failure / physiopathology
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Obesity / complications*
  • Obesity / physiopathology
  • Overweight*
  • Prognosis
  • Proportional Hazards Models
  • Prospective Studies
  • Risk Assessment
  • Risk Factors
  • Sleep Wake Disorders / complications*
  • Sweden / epidemiology