Measurement of Sleep Apnea during Obesity Treatment

Linkage between obstructive sleep apnea and obesity is well known. Weight reduction is a commonly recommended treatment for sleep apnea. We would therefore expect weight loss to benefit those affected by apnea. Some measures of apnea have demonstrated such benefit, but whether such measures can be routinely used to assess the benefit of weight loss in an obese primary care population is less clear. While both obesity and sleep apnea are common conditions, evidence indicates that the risk of obstructive sleep apnea among the morbidly obese is greatly increased compared with non-obese individuals. A screening study of 602 people found that an increase of 1 SD in body mass index was accompanied by a more than 4-fold increase in likelihood of measures associated with apnea and hypoventilation (1). A prospective evaluation of 250 obese individuals with mean body mass index (BMI) of 45.3 kg/m2 found 40% of men and 3% of women had treatable sleep apnea, whereas no apnea was found in 128 non-obese people (2). Conversely, at least 60% to 70% of patients with obstructive sleep apnea are obese (3). There is evidence that the type or location of the fat, which is a key factor in determining the obesity-related metabolic risk associated with diabetes and heart disease, also plays an important role in the risk of sleep apnea among the obese. Visceral fat seems to convey a higher risk of apnea compared with other types or locations of fat. Visceral fat measures in 37 obese subjects were significantly associated with sleep apnea when controlled for age and lean body mass (4). A recent study matched obese sleep apnea patients with obese and non-obese controls, and found that apnea patients had greater visceral fat than controls, and that visceral fat, but not BMI, was correlated with apnea (5). Prevalence of sleep apnea in premenopausal women is much lower than in men (6), but obesity increases that risk substantially (2, 6). Women with polycystic ovary disorder were recently found to have a 30-fold increased risk of sleep-disordered breathing compared with premenopausal control women, perhaps because of insulin resistance and metabolic disturbance prominently associated with that syndrome (7). Several studies indicate that weight loss is associated with amelioration of sleep apnea symptoms. Improvement of apneic episodes by weight loss is so well recognized that weight loss forms one of the principal recommendations for management of obstructive sleep apnea (8). The best results have been found with surgical treatment of morbid obesity. Large weight losses associated with bariatric surgery greatly improved sleep apnea measurement scores when comparing preoperative and 1-year postoperative values (9). The Swedish Obese Subjects study has evidence of significant benefit in sleep apnea measures 2 years after obesity surgery (10). Another study found evidence of continued improvement in apnea measures 4.5 years after bariatric surgery (11). Weight loss produced by behavior, diet, and activity changes also seems to benefit sleep apnea, although the results are less robust. Losing ∼10 kg of weight significantly improved apnea measures in 15 individuals (12). Weight loss of a mean of 20.6 kg produced by a very-low-calorie diet in 12 patients with sleep apnea resulted in significant improvement in several measures associated with sleep apnea (13). Very-low-calorie-diet treatment in eight patients produced a drop of mean BMI from 153 to 132 kg/m2 while dropping apneic and hypopneic episodes from 106 to 52 (14). A recent trial of very-low-calorie diet among 15 obese people found that a reduction of mean weight from 114 to 105 kg significantly improved the oxygen desaturation index (a measure of apnea and hypopnea) (15). Improvement is not universal nor universally sustainable. Whereas mean apneic scores decreased by weight loss achieved by a very-low-calorie diet in one study, the heaviest individual and the person with least weight loss in the trial did not benefit (14). More disquieting was a re-evaluation of 24 patients apparently cured of apnea by weight loss. Six of 13 patients who maintained their weight loss had re-emergence of abnormal apnea measures, as did 8 of 11 who regained weight (16). One study of bariatric surgery efficacy that had demonstrated excellent effect of weight loss at 1 year revealed marked diminution of benefit by 7 years (9). The pathophysiology of obstructive sleep apnea is incompletely understood (17, 18), and in consequence, the means by which obesity contributes to the etiology of sleep apnea is not fully known (5, 18). One theorized mechanism whereby obesity contributes to sleep apnea development is enlargement of soft tissues surrounding the upper airway, thus exacerbating the risk for airway collapse during sleep. Whether other central mechanisms are also involved in the obesity contribution to sleep apnea has not been reliably established. The principle symptoms of obstructive sleep apnea are heavy snoring, interrupted nocturnal sleep, and excess daytime sleepiness. The consequences of excessive sleepiness are potentially serious, especially in tasks requiring alertness, such as driving. It should be noted that obese patients can have excess daytime sleepiness even without sleep apnea (19). Also in the Sleep Heart Health Study (SHHS), significantly increased sleepiness was found among those with increased measures of disordered breathing during sleep (20). In the SHHS, there was a modest-to-moderate increase in serious cardiovascular disease among patients with mild-to-moderate measures of disordered sleep breathing (21). Autonomic instability, manifested as heart rate and rhythm effects, may also be a consequence of sleep apnea (15, 22, 23). Hypertension was strongly associated with sleep apnea in the SHHS, although some of that association may have been because of obesity itself (24). The association of sleep apnea and hypertension is strong enough that some have hypothesized a specific syndrome, “Syndrome Z,” to recognize the clustering of nocturnal apnea with hypertension and cardiovascular risk factors (25). Considering the strong associations of obesity, sleep apnea, and many serious symptoms and clinical risk, it would not be surprising to find that sleep apnea is associated with inflated population health care costs. The database on this subject is not large and suffers from a variety of limitations, including some uncertainty about apnea prevalence. A Canadian study of 181 obstructive sleep apnea patients compared with age-, gender-, and geographically matched controls did address the issue of economic costs associated with sleep apnea (26). In 10 years before diagnosis of sleep apnea, the apnea patients had greater health costs ($3972/patient vs. $1969/patient) and hospital days (6.2 d/patient vs. 3.7 d/patient) than controls. The increased cost may include the effects of obesity and other obesity related comorbidities as well as the effects of sleep apnea itself. The gold standard for diagnosing and quantitating sleep apnea is polysomnography. The intent of this clinical test is to measure apneic and hypopneic episodes. The procedure requires an overnight stay in a sleep laboratory with electroencephalogram (EEG) and oxygen saturation metering. The resulting metric is the Apnea and Hypopnea Index (AHI), also known as the Respiratory Distress Index. Standards for quantifying these events exists. However, there continues to some controversy about how such events should be defined, particularly the standards characterizing hypopnea (27). With respect to results of obesity treatment, the formal sleep study–derived AHI has the advantage of recognized reproducibility. Many health management groups and third party payers require the AHI for formal diagnosis of sleep apnea. In these respects, the sleep study–generated AHI is “official.” However, there are real limitations to applying this test to the real-life situation of screening for disordered sleep breathing among obese patients. The requirement for an overnight stay poses limitations for the patient and cost liabilities for payers. The testing, with its constant monitoring of EEG and oxygen saturation, is expensive. The testing itself is labor intensive with respect to the monitoring, and further labor costs are incurred by the required interpretation. One response to these limitations has been the introduction of home polysomnography. This procedure has been used in the large SHHS (28, 29, 30). In this procedure, a portable device providing both EEG and oxygen data are brought to the home, set up, and calibrated by trained personnel in a home visit. Stored data are analyzed in a central facility and an AHI score can be generated. This procedure obviates some of the limitations of formal polysomnography but remains significantly cumbersome and expensive. Other attempts to measure sleep apnea have met with less acceptance. There had been hope that clinical history could be refined adequately to provide a diagnostic tool, but comparisons to polysomnography demonstrate serious inaccuracies in the history (31). One potential tool is measurement of oxygen saturation. This possibility had the advantages of easy and relatively inexpensive application to the outpatient setting, including during sleep. Lack of standards and sensitivity, as well as limitations of testing during sleep, has limited the application of this test (31). It might be possible to image and quantify fat in the neck, related to the notion that the problem with sleep apnea is caused by excess neck tissue. There is a correlation of neck fat with accepted apnea measures, but the correlation is not robust, and correlation of BMI with apnea measures is nearly as good (32). A similar test is airway collapsibility measures, with a rationale similar to the neck fat imaging (33). This could be an outpatient test, but it is cumbersome, and data on reproducibility and concordance with accepted measures are not available. An intriguing tool with potential clinical application is the Epworth Sleepiness Scale (34). This is a standardized instrument that questions how likely a person is to doze (0 = never; 1 = slight chance; 2 = moderate; 3 = highly likely) in the following situations: sitting and reading; watching TV; sitting inactive in public place; 1 hour car ride; lying down in afternoon; sitting and talking; sitting quietly after lunch without alcohol; and while stopped in traffic. Normal people have a score of 2–10, whereas sleep apnea patients have a score of 4–23. Whereas the results are not as accurate as polysomnography, the testing is cheap and easy and the result correlates in group measures with the sleep study–derived AHI (20). Correlation between the Epworth Scale and the AHI within an individual is not always reliable. When approaching the problem of what sleep apnea measure could be routinely used as part of the Task Force on Developing Obesity Outcomes and Learning Standards (TOOLS) package, it may be useful to consider the choices made by the Sleep Heart Health Study (29, 30). This trial faced some of the same questions, because the study designers needed to find testing procedures that could be applied to a large (∼6000) population. The chosen measures of sleep apnea for that trial were outpatient polysomnographic sleep studies and a Modified Epworth Sleep Scale in addition to weight, height, and neck circumference (21, 29, 30). The TOOLS panel considered the plan of including a sleep study–derived AHI, likely acquired by home polysomnography. While this proposal has merit, as outlined above, for the TOOLS application, the testing was thought to be too expensive for routine use. Another proposal was to use a version of the Epworth Sleepiness Scale, but as a stand-alone instrument, it was thought to suffer from limitations of accuracy that would limit its credibility. Given these data, the TOOLS panel did not recommend any routine application of a sleep apnea measure as part of the TOOLS package. Even so, the risk of sleep apnea in obese individuals must be recognized and screened for in the clinic on an individual basis. Among patients with known or suspected sleep apnea in the context of obesity, follow-up with the Epworth scale and polysomnography may help direct the clinical approach.

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