The aim of this study was to assess subjective sleep characteristics in adult patients with long-standing type 1 diabetes, and to relate sleep variables to HbA1c values. Although sleep duration did not differ between patients and controls, more patients had poor sleep quality compared with non-diabetic, age-, sex- and BMI-matched controls. Patients with type 1 diabetes reported more sleep disturbances and daytime dysfunction. A higher proportion of the patients with type 1 diabetes were at increased risk for OSA. There was no association between subjective sleep characteristics and impaired glucoregulation. These observations indicate that type 1 diabetes is associated with an increased prevalence of disturbed subjective sleep characteristics, which do not relate to glucoregulation.
Previous studies on the relation between diabetes and sleep characteristics mainly focussed on patients with type 2 diabetes [1
]. Only a few studies have assessed sleep characteristics in patients with type 1 diabetes [9
]. Those studies investigated relatively few individuals and children [10
] with type 1 diabetes. The present study extends those observations in showing that in a large group of adult patients with a long history of type 1 diabetes subjective sleep characteristics are impaired, compared with a carefully matched control group, controlling for potential confounding factors such as age, sex and BMI.
This decrease in sleep quality and increased prevalence of sleep disturbances in patients with long-standing type 1 diabetes may have important implications, as previous studies showed that reduction of sleep duration and/or decreased sleep quality impair glucose tolerance and reduce insulin sensitivity in healthy controls [6
]. Sleep disturbances might have a similar negative effect on glucose metabolism in patients with type 1 diabetes, resulting in worse diabetic control. However, this presumed relationship between sleep disturbances and impaired glucose metabolism, assessed by HbA1c
values, was not detectable in the current study. Nonetheless, it is still possible that disturbed sleep characteristics influence glucose metabolism in these patients. However, the effects of impaired sleep characteristics may not simply be reflected in HbA1c
values because intensive glucose control and frequent, appropriate adjustments of insulin doses in patients at risk might have obtunded the effects of impaired sleep characteristics on glucoregulation.
Various aspects of diabetes could be linked to disturbed sleep quality, including physical complications of the disease, psychological factors, metabolic fluctuations and high prevalence of sleep disorders. In the patients with type 1 diabetes in our study, disturbed sleep quality was independently associated with habitual snoring, higher depression scores according to the HADS questionnaire, presence of polyneuropathy and other sleep disturbances, mainly by hypoglycaemia.
Previous studies showed a high prevalence of depression in diabetes [20
] and chronic pain conditions [21
]. Although we excluded patients with a known depression, use of psychotropic drugs, and co-morbid disorders (other than neuropathy) associated with pain, in our study higher depression scores were independently associated with impaired sleep quality.
Many patients with type 1 diabetes in our study used ACE inhibitors, statins and/or beta-blockers, which might interfere with sleep characteristics. The effects of beta-blockers on sleep are not equivocal. A previous study showed that the use of beta-blockers could positively or negatively affect sleep [22
]. A case report by Cicolin et al. suggested that ACE inhibitors may contribute to OSA by inducing upper airway inflammation [23
]. Therefore, we have considered that the use of beta-blockers and/or ACE inhibitors might affect sleep quality in patients with type 1 diabetes. However, in univariate logistic regression analysis we did not find an association between the use of beta-blockers or ACE inhibitors and impaired sleep quality. In univariate logistic regression analysis there was an association between the use of ACE inhibitors and high risk of OSA. However, this association was no longer significant after correction for the confounders age, sex, BMI and hypertension. There are conflicting data on sleep disturbances in patients treated with statins. Some studies reported higher prevalence of sleep disturbances in patients treated with lipophilic statins than with pravastatin [24
] whereas other studies did not find an increased prevalence of sleep disturbances in patients treated with different statins compared with placebo [26
]. In the present study, there was no difference in the use of statins between patients with a poor sleep quality (PSQI
5) and patients with a good sleep quality (PSQI
5). The use of statins was even higher in the group with good sleep quality. In accordance, in univariate analysis, use of statins was not associated with impaired sleep quality. Therefore, our conclusions are not likely to be merely explained by the use of medications in our patients.
The clinical assessment of peripheral polyneuropathy according to strict criteria in individuals with type 1 diabetes is a major strength of our study, as our study shows diabetic polyneuropathy was a major determinant of impaired sleep. Polyneuropathy contributes to impaired sleep via several potential mechanisms. First, neuropathic pain may lead to disturbed sleep [28
]. Second, polyneuropathy can impair thermoregulation. It has been proposed that autonomic changes in skin temperature modulate the neuronal activity of the thermosensitive neurons in the pre-optic area/anterior hypothalamus, which, in turn, regulate vigilance and sleepiness [29
]. This hypothesis is supported by a report showing that diabetic patients, even those without evidence of clinical neuropathy, show impaired thermoregulation during sleep [30
The relatively high prevalence of type 1 diabetic patients with a high risk for OSA, according to the BQ, suggests the potential of a high burden of unrecognised OSA in people with type 1 diabetes. This is a relatively new finding, in accordance with a recent pilot study of Borel et al., which observed a prevalence of OSA of 40% in 37 non-obese adult patients with type 1 diabetes [31
]. In accordance with our data, this observation is remarkable, as the BMI, which is a risk factor for OSA in the general population, of our patients with type 1 diabetes was matched to that of the healthy controls. Several studies in patients with type 2 diabetes have shown that OSA is associated with the presence of autonomic neuropathy [32
], which might also be involved in patients with type 1 diabetes. Unfortunately, our current study was not designed to elucidate underlying mechanisms of disturbed sleep, and we did not include assessments of autonomic neuropathy. Nonetheless, there was no association between poor glycaemic control (HbA1c
7.5%) and a ‘high’ risk for OSA in our study, despite the association between sleep-disordered breathing, glucose intolerance and insulin resistance in patients with type 2 diabetes [34
]. There was also no association between the occurrence of hypoglycaemia and the risk for OSA in our patients [36
Sleep characteristics were assessed by validated questionnaires in the present study. The PSQI and ESS have been developed to measure sleep quality and daytime sleepiness, respectively [14
], and reflect stable measures of sleep quality and sleepiness over the past year [37
]. The PSQI has a diagnostic sensitivity of 89.6% and a specificity of 86.5% for identifying cases with poor sleep quality, using a cut-off score of 5. This questionnaire has been validated by polysomnographic measurements [38
].The BQ is a screening tool widely used to differentiate between ‘high-’ and ‘low-risk’ groups for OSA. This risk grouping was useful in the prediction of respiratory disturbances in consecutive participants, who visited internists for any reason. For example, being in the ‘high-risk’ group defined by the BQ predicted more than five respiratory events per hour with a sensitivity of 86%, and a specificity of 77% [16
]. In view of the current data, polysomnography is required to objectively assess the sleep quality and OSA in patients with type 1 diabetes mellitus at high risk for OSA according to the BQ.
The current cross-sectional study was designed to assess subjective sleep variables in patients with type 1 diabetes mellitus and, therefore, we cannot elucidate from the data which chain(s) of events lead from type 1 diabetes to disturbed sleep. In particular, the links between peripheral polyneuropathy and disturbed sleep and between type 1 diabetes and the risk of OSA are not fully clear. Another matter is whether disturbed sleep leads to further impairment of glucose metabolism, with the effect that sleep disturbances and glycaemic control can interact in a vicious circle. Additional studies with objective sleep measurements are warranted to assess these relations in more detail.
In conclusion, the present study demonstrated that adult patients with long-standing type 1 diabetes mellitus have altered self-reported sleep characteristics compared with sex-, age- and BMI-matched non-diabetic controls. Therefore, disturbed subjective sleep characteristics are part of the complex syndrome of long-standing type 1 diabetes mellitus.