OSA and T2DM
OSA and incident T2DM
Several studies have examined whether having OSA increases the individual’s risk of developing T2DM, in particular whether obesity is a major risk factor for both conditions and whether OSA has been associated with IR and prediabetes as described earlier. Several cross-sectional studies found a higher prevalence of T2DM in patients with OSA despite adjusting for confounders, particularly age and obesity; these studies are reviewed in . Whether OSA is a predictor of T2DM has been examined in a small number of longitudinal studies that used a variety of methods to diagnose OSA (from symptoms to polysomnography), and to diagnose T2DM (from self-reported to OGTT); these studies are summarized in Table 22.2. A recent meta-analysis of studies that used objective measures to diagnose OSA found that moderate to severe OSA was associated with increased risk of developing T2DM (RR 1.63;95% CI 1.09–2.45) .
OSA prevalence in T2DM
Given the high prevalence of glycemic abnormalities in patients with OSA, it is not surprising that OSA is very common in patients with T2DM. However, there is significant variation in OSA prevalence between studies due to differences in population characteristics (primary vs. secondary care, long vs. short diabetes duration, ethnicity, obesity, and so on), and differences in the methods and criteria used to diagnose OSA. These studies are summarized in Table 22.3.
As a result of the high prevalence of OSA in patients with T2DM, the International Diabetes Federation (IDF) recommended screening for OSA in this high-risk population , although appropriate validated screening methods in patients with T2DM are still lacking.
OSA and glycemic control in T2DM
Since OSA is associated with IR and possibly β-cell dysfunction, and increased inflammation and oxidative stress (see later for more details), it is logical to hypothesize that OSA leads to worsening glycemic control in patients with T2DM. The main difficulty in OSA-related research is to differentiate the impact of OSA from that of obesity. A small number of studies assessed this issue, and they demonstrated that OSA and OSA severity are associated with poorer glycemic control (both HbA1c and fasting plasma glucose) and glycemic variability after multivariable adjustments for several confounders, such as age, sex, race, BMI, number of diabetes medications, level of exercise, years of diabetes and total sleep time in some studies [117,120–123]. These studies were relatively small (n=31–92). The adjusted mean increase in HbA1c between patients with and without OSA varied from 0.7% to 3.69% depending on the OSA severity. One study, however, did not show an association between OSA and glycemic control ; but in this study only 22% of participants had full polysomnography and the duration of the sleep study was just 4 hours . A recent study showed that following adjustment for age, gender, obesity, smoking status, hypertension and antihypertensives, AHI correlated with HbA1c in patients with prediabetes but not in those with T2DM or normoglycemia, whilst the lowest oxygen saturation correlated with HbA1c across all groups .
Despite the constant finding of an association between OSA and glycemic control in patients with T2DM, the impact of CPAP on glycemic control has not been evaluated widely and the results were not consistent (Table 22.4). Several studies [71,109,125–129] have evaluated CPAP treatment; of these, only one is a randomized clinical trial , with the rest being uncontrolled pre/post assessments (Table 22.4). The one controlled study showed no change in HbA1c after CPAP therapy for 3 months. The lack of positive effect could be attributed to the small study sample, the limited duration of follow-up, the suboptimal adherence to CPAP (3.6 hours per night) or a true lack of effect. In marked contrast, uncontrolled studies have shown improvements in insulin sensitivity [109,125], postprandial hyperglycemia , glycemic variability , or HbA1c [126,127] (Table 22.4). A recent meta-analysis found that CPAP treatment did not result in significant reductions in HbA1c (0.08 %; 95 % CI -0.26–0.42) in patients with T2DM . However, new data showing that AHI only correlated with REM AHI and not non-REM AHI suggest that longer usage of CPAP beyond 4 hours is needed as most REM sleep occurs in the latter half of the night . Indeed recent preliminary results showed that 1 week of in-laboratory (8 hours of sleep) CPAP treatment resulted in a decrease of 11.2 and 19.8mg dL−1 in the average 24-hour and post-breakfast glucose levels, respectively, with a 45% decrease in the dawn phenomenon as well . However, enforcing 7–8 hours per night of CPAP usage in real life is a huge challenge. In addition, it is important to note that the diabetes duration of patients in this study was relatively short (3.2 years) unlike in previous studies; this is important as IR and β-cell dysfunction may be more reversible in such a Population.