Our findings reveal that apparently healthy, obese adults of comparable adiposity, but who represented extremes of insulin resistance and sensitivity, differ in that presence of insulin resistance is associated with significantly increased risk for OSA. These results extend previous findings in OSA and altered glucose metabolism by using rigorous methods to assess insulin action, as well as underscoring the validity of this independent relationship by selecting obese individuals of a specific BMI range to eliminate BMI per se
as a potential confounder. Prior studies have used surrogate estimates of insulin resistance (e.g. impaired fasting glucose or glucose intolerance in response to oral glucose challenge) to demonstrate an association with OSA after adjustments were made to account for variable adiposity in these population-based studies [20
]. The present data provide persuasive evidence of an association between insulin resistance and risk for OSA. Traditionally it has been suggested that insulin resistance occurs as a consequence of OSA via obesity as a shared causal link; recently, alternate pathways underlying OSA physiology have been postulated to trigger disturbances in glucose regulation [7
]. These mechanisms may include sleep fragmentation and/ or intermittent hypoxia in potentiating insulin resistance, possibilities supported by epidemiologic evidence as well as small studies conducted under short-term, experimentally-induced conditions [7
]. The contribution to altered glucose metabolism of other processes that may be activated by OSA, e.g. inflammation and/or adipocytokines, are less defined and require further investigation [22
]. Given the dearth of experimental evidence, it would also be remiss not to consider the less conventional hypothesis that insulin resistance could increase one's risk for OSA. Indeed, this cross-sectional analysis leaves open for interpretation the possibility that being insulin-sensitive might, in fact, render it less likely for an overweight/ obese individual to have OSA. Although there is less evidence in the literature to support this line of reasoning, it should be noted that a prospective study demonstrated an association between high baseline insulin levels and incident observed apnea [23
]. Ultimately, as cross-sectional studies can only provide evidence of association, further prospective or interventional studies are necessary to ascertain direction of causality.
The other main result of the present study is that insulin-resistant individuals reported increased daytime sleepiness and were more likely to exhibit excessive daytime sleepiness as compared to equally obese, insulin-sensitive individuals. These results are especially provocative in light of a recent study demonstrating that an independent relationship between OSA and type 2 diabetes was confined to patients with severe OSA who reported excessive sleepiness [24
]; on the contrary, severe OSA in non-sleepy patients was not associated with prevalent diabetes mellitus. These findings are also consistent with previous results demonstrating that excessive daytime sleepiness is associated with the Homeostasis Model Assessment index (a surrogate index of insulin sensitivity) among patients with OSA [25
]. Taken together, these data suggest that sleepiness may be a necessary component in the pathogenic link between insulin resistance and OSA. Indeed, it has been postulated that sleepiness in patients with OSA may confer a different metabolic risk profile from non-sleepy patients with OSA [27
]. It should be cautioned that while daytime sleepiness is a hallmark feature of OSA, high ESS scores are not necessarily specific for OSA. Nonetheless, that ESS scores were concordant with results of the Berlin and STOP questionnaires in our study affirms that obese, insulin-resistant individuals are at high risk for OSA, characterized by greater degree of daytime sleepiness.
To the best of our knowledge, this is the first study to provide evidence of the efficacy of the Berlin, STOP, and ESS questionnaires in identifying an association between OSA risk and/ or daytime sleepiness with insulin resistance. These findings thereby lend support to use of these questionnaires in areas where cost and/or limited resources preclude offering polysomnography to all patients, as an efficacious screening tool to help identify obese, insulin-resistant individuals at highest risk for OSA. While confirmation of these results with polysomnography would have been preferable, it is reasonable to expect that these questionnaires are reliable indicators of OSA risk. The Berlin questionnaire has been widely used in large epidemiologic studies [2
] and validated against polysomnography [9
] in primary care populations/ communities similar to ours. While the STOP questionnaire was developed for use in pre-surgical patients, it was incorporated in the study because unlike Berlin, the STOP does not include BMI as one of its criteria. As anticipated in our overweight/ obese study population, the Berlin questionnaire identified a greater number of individuals at high risk for OSA as compared with the STOP. Nevertheless, the two questionnaires were concordant in identifying a preponderance of insulin-resistant individuals at high risk for OSA. Use of ESS in addition to the STOP and Berlin questionnaires provided further evidence in support of our hypothesis. These results also support use of the STOP questionnaire as an alternative to Berlin in a primary care setting, particularly when rapid screening is desirable due to its simplicity and ease of administration. Finally, that these screening tools were able to detect disparate responses between the two groups of equally obese, but metabolically very different individuals suggests that insulin resistance modulates OSA risk, independent of adiposity, in a substantial manner.
These findings raise the question how best to apply this information in a primary care practice. Given the rising prevalence of obesity, including these questionnaires in routine evaluation of all overweight subjects may not be feasible. However, our results suggest that considerable clinical benefit might be gained by administering these questionnaires to overweight/obese individuals who are insulin-resistant, and therefore at highest risk for OSA. What then is the best way to identify those overweight/obese individuals who are insulin-resistant? While there is no simple way to accomplish this task in a clinical setting, there are at least two surrogate estimates of insulin resistance to consider. The data in indicate that both FPI and TG/HDL-C ratio were 2-fold higher in insulin-resistant individuals. Indeed, FPI is a significant predictor of insulin resistance, and individuals whose FPI fall in the upper quartile of an apparently healthy population are likely to be insulin-resistant [15
]. Another approach is to use the plasma TG/HDL-C concentration ratio. When this method was applied to a group of overweight/obese individuals [18
], a ratio ≥ 3.0 (in traditional units, ≥ 1.3 in SI units) was relatively successful in identifying individuals who were insulin-resistant. There is evidence that this value is a useful indicator for hyperinsulinemia regardless of race/ethnicity [28
]. The higher the FPI concentration and/or the TG/HDL-C ratio, the more likely the overweight/obese individual is to be insulin-resistant. Overweight/ obese individuals considered to be insulin-resistant by either or both of these approaches can be further evaluated with the screening questionnaires. Based on their scores, those deemed at highest risk of OSA could be referred for polysomnography. This approach provides clinicians with a reasonably cost-effective way to identify individuals at enhanced risk of OSA, thereby providing a means for early treatment and/or life-style intervention to prevent complications associated with OSA.
This study was limited by its small size. Extremely obese individuals were also excluded from this study. Prevalence estimates for OSA among Americans with BMI > 35 kg/m2
are even higher [2
] than that of the present BMI distribution, and a case could be made to screen most individuals within this category of obesity especially since these individuals as of yet comprise a minority of Americans. We felt it important rather to focus on overweight to moderately obese individuals which make up nearly half of the U.S. population. Regardless, these study findings may not be applicable to adults who are extremely obese. While use of screening questionnaires to assess OSA risk has its advantages as discussed above, it would have been optimal to confirm our study findings with polysomnography. Nonetheless, the robustness of our results lends strength to our conclusions.
In summary, overweight to moderately obese, non-diabetic adults vary remarkably in OSA risk detectable by conventional questionnaires, and is associated with insulin resistance status. High risk for OSA and excessive daytime sleepiness is prevalent among insulin-resistant individuals, features that are relatively spared in their weight-matched insulin-sensitive counterparts. It is suggested that administration of screening questionnaires to apparently healthy, obese individuals, classified as being insulin-resistant, provides a clinically effective way to identify individuals who are likely to have undiagnosed OSA, or who are at risk for developing the syndrome.