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European Journal of Heart Failure 2007 9(2):184-190; doi:10.1016/j.ejheart.2006.05.012
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© 2007 European Society of Cardiology

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

Erik Ingelssona,*, Lars Lindb,c, Johan Ärnlöva and Johan Sundströma,b

a Department of Public Health and Caring Sciences, Section of Geriatrics, Uppsala University Uppsala Science Park, SE-751 85 Uppsala, Sweden
b Department of Medical Sciences, Uppsala University Uppsala, Sweden
c Astra Zeneca R&D Mölndal, Sweden

* Corresponding author. Visiting address: Dag Hammarskjölds väg 14B, Uppsala, Sweden. Tel.: +46 18 6117662; fax: +46 18 6117976. E-mail address: erik.ingelsson{at}pubcare.uu.se


   Abstract
Top
 Notes
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 
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≤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.

Key Words: Heart failure • Sleep disorders • Epidemiology • Risk factors

Received February 2, 2006; Revised April 24, 2006; Accepted May 22, 2006


   1. Introduction
Top
 Notes
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 References
 
Heart failure (HF) is a major cause of morbidity and mortality. Although survival after onset of HF has improved in recent years [1], mortality remains high, and greater efforts should be made in primary prevention of the disease [2]. The predominant causes of HF are hypertension and coronary heart disease. Other established risk factors for HF include left ventricular hypertrophy, valvular heart disease, diabetes, cigarette smoking and obesity [3-6].

There is evidence of an association between sleep disturbances and coronary heart disease [7,8], and obstructive sleep apnoea has been demonstrated to increase the risk of coronary heart disease and stroke [9]. Although coronary heart disease is a major risk factor for HF, the majority of HF cases are not preceded by a coronary event [6]. Sleep disturbances [10,11] and sleep-disordered breathing [12,13] are associated with manifest HF. However, the relationship between sleep disturbances and incident HF has been less studied.

Since the presence of sleep disturbances has a predictive value for the development of coronary heart disease and is known to be associated with established HF, we hypothesized that sleep disturbances would also predict incident HF. This is important, since sleep disorders are potentially modifiable. Thus, the aim of the study was to analyze self-reported sleep disturbances as possible risk factors for the development of heart failure during a median follow-up period of 30 years, in a community-based sample of middle-aged men free from HF, valvular disease and myocardial infarction at baseline, accounting for established risk factors for HF.


   2. Methods
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 References
 
2.1. Study sample
The study utilizes the ULSAM (Uppsala Longitudinal Study of Adult Men) cohort, to which all 50-year-old men living in Uppsala County in 1970-1974 were invited. Of the 2841 invited men, 82% (2322 men) participated in the investigation [14]. The ULSAM study is described in detail on the Internet (http://www.pubcare.uu.se/ULSAM/). None of the participants had been diagnosed with HF in the hospital discharge register before baseline. Seven participants were excluded due to prior myocardial infarction, and one participant due to valvular disease at baseline, thus 2314 men were eligible to participate. A sub-sample (n=1903) excluding all participants who suffered from a myocardial infarction during the follow-up time (n=411) was also examined. All participants gave written consent and the Ethics Committee of Uppsala University approved the study.

2.2. Examinations at baseline
Examinations performed at baseline when the participants were 50 years old [14] included a structured interview; a self-administered questionnaire including questions about sleep disturbances; blood sampling (after an overnight fast) for glucose determinations; electrocardiogram; and a physical examination with determinations of supine blood pressure and anthropometric measurements.

The questionnaire regarding sleep disturbances included three questions which could be answered as "no" (absent, 0) or "yes" (present, 1):

  1. "Do you have difficulties falling to sleep at night?" (variable denoted "insomnia");
  2. "Do you often wake up in the early hours unable to get back to sleep?" (variable denoted "restless sleep");
  3. "Do you take sleeping pills more than 3 times per week?" (variable denoted "sleeping pills"). As the number of participants with sleep disturbances was quite small, the three questions were also combined into one variable (denoted "any sleep disturbance"), which was given the value of 1 (present) if any of the three questions were answered as "yes" and 0 (absent) otherwise. No established standardized questionnaires about sleep disturbances were available at the time of the baseline examination.

Body mass index (BMI) at baseline was calculated as weight (in kg) divided by height (in meters) squared (kg/m2). The presence of elevated blood pressure at baseline was defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg, and/or use of anti-hypertensive medication. The presence of diabetes at baseline was defined as fasting blood glucose ≥6.1 mmol/l and/or use of oral hypoglycaemic agents or insulin. Electrocardiographic left ventricular hypertrophy was defined as high amplitude R-waves according to the revised Minnesota code [15] together with a left ventricular strain pattern [6]. The presence of valvular disease (International Classification of Diseases [ICD]-8 codes 394-396 and 424, ICD-9 codes 394-397 and 424 or ICD-10 codes I05-I08 and I34-I37) and prior myocardial infarction (ICD-8 code 410, ICD-9 code 410 or ICD-10 code I21) were assessed from the hospital discharge register. The diagnosis of acute myocardial infarction was chosen as a proxy for coronary heart disease, as the precision of the myocardial infarction diagnosis in the Swedish hospital discharge register is high [16,17]. Furthermore, adjusting for, or excluding, interim myocardial infarction is an established method for examining "non-ischaemic" HF [18,19].

2.3. Follow-up and outcome parameter
The participants had a median follow-up time of 29.6 years (range 0.04 to 32.7 years), contributing to 59,122 person-years at risk. The possible HF cases were selected by linking the ULSAM participants to the hospital discharge register using the Swedish unique personal identification numbers. As a possible diagnosis of heart failure, we considered International Classification of Disease (ICD) heart failure codes 427.00, 427.10, 428.99 (ICD-8), 428 (ICD-9), I50 (ICD-10) and hypertensive heart disease with heart failure, I11.0 (ICD-10), allowed in any of the six possible diagnosis positions. Three hundred and forty-six men had a hospital discharge register diagnosis of heart failure between entry into the ULSAM study and the end of 2002. The medical records from the relevant hospitalisation were reviewed by two physicians (E.I. and L.L.), who classified the cases as definite, questionable or miscoded, blinded to the baseline data. The classification relied on the definition proposed by the European Society of Cardiology [20]. Thus, to be classified as a definite HF case, there had to be symptoms and signs of HF and objective evidence of cardiac dysfunction at rest. In cases of doubt, the response to treatment directed towards HF was a useful check of the diagnosis. The use of echocardiography was more common in the later part of the follow-up period, but the validity of the heart failure diagnoses did not increase over time, as described previously together with extensive information about the validation process [21]. After this validation, 282 cases of definite HF were included in the present study. None of the participants were lost to follow-up.

2.4. Statistical methods
Data are given as means±standard deviations and percent. The prognostic values of presence vs. absence for the variables reflecting sleep disturbances for HF incidence were investigated with Cox proportional hazards analyses. Proportional hazards assumptions were confirmed graphically and by Schoenfeld's tests. The analyses were performed unadjusted and multivariable-adjusted including established risk factors for HF (elevated blood pressure, diabetes, electrocardiographic left ventricular hypertrophy, smoking and BMI) as baseline covariates. The models were repeated in a sub-sample (n=1903) without myocardial infarction at baseline or during follow-up. Interaction terms between the variables reflecting sleep disturbances and all baseline covariates were examined. Evidence of effect modifications between BMI and the four variables reflecting sleep disturbances were found (p<0.001 in tests for heterogeneity). Thus, in addition to the analyses in the total sample, the study sample was stratified into two parts; one stratum with normal-weight participants (BMI at 25.0 or less; n=1232), and one with overweight participants (BMI over 25; n=1082), and all analyses were performed also in these two BMI-strata separately. Two-tailed 95% confidence intervals and p-values were given, with p<0.05 regarded as significant. Statistical software package STATA 8.2 (Stata Corporation, College Station, USA) was used.


   3. Results
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 References
 
During a median follow-up time of 29.6 years, 282 of the participants were hospitalized with HF (102 cases in the normal-weight sample and 180 cases in the overweight sample). The overall incidence rate for HF during the follow-up period was 4.8/1000 person-years at risk (PYAR; 3.2/1000 PYAR in the normal-weight sample and 6.7/1000 PYAR in the overweight sample). The incidence rate increased considerably over time (0.31/1000 PYAR at age 50-60, 4.6/1000 PYAR at age 60-70, 10.9/1000 PYAR at age 70-80 and 20.9/1000 PYAR over 80 years of age). Table 1 shows the participant characteristics at baseline.


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  		Table 1 Baseline characteristics of the cohort

 
In the total cohort, insomnia, use of sleeping pills and the combined "any sleep disturbance" variable were significant predictors for HF in unadjusted analyses (Table 2, second column). When adjusting for established risk factors for HF (elevated blood pressure, diabetes, electrocardiographic left ventricular hypertrophy, smoking and BMI), all three variables remained significant predictors of HF (Table 2, third column). In unadjusted analyses in the sub-sample without myocardial infarction during follow-up, the use of sleeping pills was a significant predictor for HF (Table 2, fourth column). Adjusting for established risk factors, use of sleeping pills and the combined "any sleep disturbance" variable were significant predictors for HF (Table 2, fifth column). In order to examine why the combined "any sleep disturbance" variable was significant only in the adjusted analyses in this sub-sample, but not in the unadjusted, a post hoc analysis including only the "any sleep disturbance" variable and BMI in a Cox regression model was performed. In this model, the combined "any sleep disturbance" variable was a significant predictor of HF (hazard ratio, 1.43; 95% confidence interval, 1.01-2.03; p=0.046), implying that BMI was a negative confounder in the association between the "any sleep disturbance" variable and HF.


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  		Table 2 Incidence of heart failure in relation to self-reported sleep disturbances, in the total cohort and in a sub-sample excluding all individuals with an interim myocardial infarction, unadjusted and adjusted for established risk factors

 
As evidence of effect modifications between BMI and the four variables reflecting sleep disturbances were found, the analyses were also performed in a sample of normal-weight participants (BMI≤25.0; n=1232), and one with overweight participants (BMI>25; n=1082). In the normal-weight sample, no statistically significant associations between sleep disturbances and HF were found, either in the whole sample (Table 3, second and third columns), or the sub-sample without myocardial infarction during follow-up (Table 4, second and third columns). In the overweight sample, insomnia and the combined "any sleep disturbance" variable were both significant predictors for HF in unadjusted analyses (Table 3, fourth column). When adjusting for established risk factors for HF (elevated blood pressure, diabetes, electrocardiographic left ventricular hypertrophy, smoking and BMI), both variables remained significant predictors of HF (Table 3, fifth column). In unadjusted analyses in the sub-sample without myocardial infarction during follow-up, use of sleeping pills and the "any sleep disturbance" variable were significant predictors of HF in overweight persons (Table 4, fourth column). Adjusting for established risk factors, the "any sleep disturbance" variable remained a significant predictor of HF (Table 4, fifth column).


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  		Table 3 Incidence of heart failure in relation to self-reported sleep disturbances, in the total cohort according to weight, unadjusted and adjusted for established risk factors

 


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  		Table 4 Incidence of heart failure in relation to self-reported sleep disturbances, in a sub-sample excluding all individuals with an interim myocardial infarction, according to weight, unadjusted and adjusted for established risk factors

 

   4. Discussion
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
References
 
4.1. Principal findings
In this community-based cohort study of middle-aged men with a median follow-up time of 30 years, self-reported sleep disturbances were a risk factor for HF in middle-aged men, independently of established risk factors for HF at baseline. This association seems to be largely independent of interim myocardial infarction during the follow-up period. This study also demonstrated that the association between self-reported sleep disturbances and HF was present only in overweight subjects, indicating that obesity somehow is important in the mechanisms by which sleep disturbances increase the risk of HF. However, as the hazard ratios in the normal-weight and overweight groups were similar and the confidence intervals were overlapping, the difference between the groups might also be a chance finding. The combined "any sleep disturbance" variable had the most consistent effect throughout all models, possibly reflecting the highest statistical power for that variable. On the other hand, the "restless sleep" variable did not reach significance in any model, indicating that this question fails to capture the sleep disturbances that increase the risk of HF.

4.2. Previous studies
Sleep disturbances are common among patients with manifest HF [10,11]. Also sleep-disordered breathing, such as sleep apnoea, is known to be associated with manifest HF [12,13]. Furthermore, there is evidence of an association between sleep disturbances [7,8], obstructive sleep apnoea and subsequent coronary heart disease [9]. However, the relationship between sleep disturbances and incident HF have been less studied. In one previous study, daytime sleepiness at baseline predicted incident HF over a follow-up time of 5 years, but in that study, the adjustment for established risk factors for HF was not complete [22].

4.3. Possible mechanisms
One possible mechanism behind our observations is that sleep disturbances cause alterations in the growth hormone/insulin-like growth factor-1 (GH/IGF-1) system. In the experimental setting, sleep-deprived rats demonstrate depressed serum levels of GH and IGF-1, [23] and in humans, obstructive sleep apnoea syndrome is associated with impaired secretion of GH and IGF-1 [24]. Previous studies have shown that low serum levels of IGF-1 are predictive of future risk of developing HF [25,26]. There is an association between obesity and low GH levels [27], which could explain why sleep disturbances only predicted HF in overweight participants in this study. Since obese persons already have low GH levels, they might be more vulnerable to the effect of sleep disturbances.

Further, the presence of sleep disturbances might be an indicator of depression, which has been shown to be an independent risk factor for HF among older persons with hypertension [28]. Depression has also been associated with low GH levels in previous studies [29].

Another possible mechanism is that sleep disturbances could be related to increased inflammatory activity. A recent study has shown elevated CRP levels in sleep-deprived subjects [30]. Thus, inflammation might be a mechanism by which sleep disturbances lead to HF, since high levels of inflammatory markers are known to predict incident HF [31-33]. This could also be an explanation of why sleep disturbances only predicted HF in overweight persons, as recent research highlights the role of adipose tissue in the development of a systemic inflammatory state [34]. To assess this possible mechanism further, we performed secondary analyses including erythrocyte sedimentation rate (ESR) as a covariate in the models adjusting for established risk factors for HF. The results remained essentially the same as in the models without ESR. Thus, inflammation is likely not on the causal pathway between sleep disturbances and HF in the present study, as ESR has been demonstrated to be a good indicator of inflammation and risk for subsequent HF [33].

There is a growing evidence of an association between sleep restriction and increased insulin resistance [35]. Further, insulin resistance is associated with obesity, and it was recently demonstrated that insulin resistance is an independent risk factor for HF [36,37] To examine whether insulin resistance might mediate the reported relation between self-reported sleep disturbances and HF in middle-aged obese men, we performed secondary analyses including homeostasis model assessment (HOMA) insulin resistance index [37] as a covariate in the models adjusting for established risk factors for HF. The results were essentially the same in the models with and without HOMA, indicating that insulin resistance is unlikely to mediate the relationship between sleep disturbances and HF.

The self-reported sleep disturbances in the present study may reflect sleep apnoea-especially as this condition is strongly associated with overweight [38]-and that the nocturnal hypoxaemia might increase the risk for HF. However, the questions regarding sleep disturbances in the present study do not capture the cardinal symptoms of sleep apnoea, such as snoring, excessive daytime sleepiness and apnoeas. The self-reported sleep disturbances in the present study were as common in the normal-weight as in the overweight participants, which makes it unlikely that they reflect sleep apnoea, since this condition is much more common in over-weight persons [38]. Furthermore, it was insomnia and the use of sleeping pills that predicted HF, not restless sleep, which further supports that sleep apnoea was not the cause of our findings.

4.4. Strengths and limitations
The strengths of this study include the large population, the long follow-up period and the non-existent loss-to-follow-up. Furthermore, all HF cases were validated, limiting the inclusion of false positive cases. There are some limitations to this study. As we only examined men of the same age with a similar ethnic background, this study has an unknown generalizability to women and other age- and ethnic groups. Furthermore, since this study was initiated in the seventies and the HF diagnosis was based on a review of medical records, it was not possible to differentiate between systolic and diastolic heart failure as echocardiography was not available at the time of diagnosis for many of the cases. Milder, non-hospitalized cases of HF were not included in our endpoint, which would tend to underestimate the incidence rate, and bias the results towards the null hypothesis. Further, patients who are overweight are more likely to be hospitalised because of weight-associated problems. Thus, the ability to detect HF in overweight subjects might be higher. However, this still would not explain why sleep disturbances in overweight subjects increase the risk for HF. A possible limitation, which could explain the link between sleep disturbances and HF, could be that some subjects with sleep disturbances at baseline have undiagnosed HF with nocturnal dyspnoea. To rule out this reverse causation, we performed secondary analyses in which we included two questions from the questionnaire about dyspnoea ("Does climbing two flights of stairs or the equivalent at the same pace as others of your age leave you out of breath?" and "Do you usually get out of breath when you're walking on level ground?"). Inclusion of these baseline variables in multivariable models did not alter the results regarding sleep disturbances. It should also be noted that we have examined self-reported sleep disturbances, which may be different from objective presence of sleep disturbances. Another limitation is the lack of questions at baseline regarding depression and alcohol consumption, which might be considered potential confounders. However, irrespective of what the self-reported sleep disturbances reflect, and regardless of the underlying mechanisms behind our observations, they are important as they for the first time demonstrate an independent relationship between sleep disturbances and subsequent HF.

4.5. Conclusions
In conclusion, self-reported sleep disturbances imply an increased risk of subsequent HF in overweight subjects, independent of established risk factors for HF including an interim myocardial infarction, during three decades of follow-up in a population-based sample of middle-aged men. Further studies are needed in order to understand the mechanisms behind these associations.


   Acknowledgements
 
We thank Johan Lindbäck, Uppsala Clinical Research Center (UCR), Uppsala, Sweden for statistical advice. The work was supported by the Primary Health Care in Uppsala County and Thuréus Foundation. The funding source had no involvement in the work with the article.


   Notes
Top
 Notes
Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 
{star} Lars Lind is a part time employee at Astra Zeneca R&D, Mölndal, Sweden, and part time employed at Uppsala University. Astra Zeneca has no interests in this project and has not given any financial support. Thus, there are no conflicts of interest for any of the authors. Back


   References
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 

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A. W. Roberts, A. L. Clark, and K. K. Witte
Review article: Left ventricular dysfunction and heart failure in metabolic syndrome and diabetes without overt coronary artery disease -- do we need to screen our patients?
Diabetes and Vascular Disease Research, July 1, 2009; 6(3): 153 - 163.
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