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Original Research: SLEEP MEDICINE |

Predictors of Habitual Snoring and Obstructive Sleep Apnea Risk in Patients With Asthma FREE TO VIEW

Mihaela Teodorescu, MD, MS; Flavia B. Consens, MD; William F. Bria, MD; Michael J. Coffey, MD; Marc S. McMorris, MD; Kevin J. Weatherwax, BS; John Palmisano, MA; Carolyn M. Senger, BS; Yining Ye, PhD; Jack D. Kalbfleisch, PhD; Ronald D. Chervin, MD, MS
Author and Funding Information

*From the Department of Medicine and Wisconsin Sleep Institute (Dr. Teodorescu), University of Wisconsin, Madison, WI; the Medical Service and Sleep Disorders Center (Dr. Teodorescu), William S. Middleton Veterans Hospital, Madison, WI; the Department of Neurology and Sleep Disorders Center (Drs. Consens and Chervin, Mr. Palmisano, and Ms. Senger) and the Department of Medicine (Drs. Bria and Coffey), University of Michigan Health System, Ann Arbor, MI; the Department of Biostatistics (Drs. McMorris, Ye, and Kalbfleisch), University of Michigan School of Public Health, Ann Arbor, MI; and Michigan Institute for Clinical and Health Research (Mr. Weatherwax), University of Michigan Health System, Ann Arbor, MI.

Correspondence to: Mihaela Teodorescu, MD, MS, University of Wisconsin School of Medicine and Public Health, K4/910 CSC 9988, 600 Highland Ave, Madison, WI 53792-9988; e-mail: mt3@medicine.wisc.edu


This work was performed at the University of Michigan Health System, Ann Arbor, MI.

This research was supported by University of Michigan General Clinical Research Center grant MO1 RR00042 (to M.T.) and University of Michigan Department of Neurology Training Grant T32 NS007222 (to M.T.).

Dr. Teodorescu has received funding from the University of Wisconsin School of Medicine and Public Health, Department of Medicine and from Medical Education and Research Committee New Investigator Award to continue asthma-sleep apnea research. Dr. Coffey has received research funds from the University of Michigan. Dr. Chervin has consulted on the subjects of sleep or sleep apnea for Respironics, Inc, Pavad Medical, Inc, Alexa Pharmaceuticals, Inc, several legal firms, and US District Attorney (each for under $10,000). He is named in a University of Michigan patent on a sleep apnea-related signal analysis algorithm. The other authors have no conflicts of interest to disclose.

For editorial comment see page 1115


© 2009 American College of Chest Physicians


Chest. 2009;135(5):1125-1132. doi:10.1378/chest.08-1273
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Background:  A high prevalence of obstructive sleep apnea (OSA) symptoms was reported in patients with asthma. Our goal was to evaluate factors associated with habitual snoring and OSA risk in these patients.

Methods:  Patients with asthma were surveyed at specialty clinics with the Sleep Apnea scale of the Sleep Disorders Questionnaire (SA-SDQ) and questions about the frequency of asthma symptoms (National Asthma Education and Prevention Program guidelines), followed by medical record review. SA-SDQ scores ≥ 36 for men and ≥ 32 for women defined high OSA risk. Logistic regression was used to model associations with habitual snoring and high OSA risk.

Results:  Among 244 patients, 37% snored habitually and 40% demonstrated high OSA risk. Independent predictors of habitual snoring included gastroesophageal reflux disease (GERD) [odds ratio (OR), 2.19; 95% confidence interval (CI), 1.19 to 4.02] and use of an inhaled corticosteroid (ICS) [OR, 2.66; 95% CI, 1.05 to 6.72]. High OSA risk was predicted by asthma severity step (OR, 1.59; 95% CI, 1.23 to 2.06), GERD (OR, 2.70; 95% CI, 1.51 to 4.83), and ICS use (OR, 4.05; 95% CI, 1.56 to 10.53). Linear, dose-dependent relationships of ICS with habitual snoring and high OSA risk were seen (p = 0.004 and p = 0.0006, respectively). Women demonstrated a 2.11 times greater odds for high OSA risk (95% CI, 1.10 to 4.09) when controlling for the above covariates.

Conclusions:  Symptoms of OSA in patients with asthma are predicted by asthma severity, coexistent GERD, and use of an ICS in a dose-dependent fashion. The well-recognized male gender predominance for OSA symptoms is not apparent in these patients. Further exploration of these relationships may help to explain the increased prevalence of OSA in asthma and provide new insights into the reported female predominance of asthma morbidity.

Figures in this Article

Asthma and obstructive sleep apnea (OSA) are common disorders, estimated to afflict approximately 8% and 4%, respectively, of the US population.1,2 OSA is the most severe form of obstructive sleep-disordered breathing (SDB); snoring, at the other end of the spectrum, is even more common. Traditional risk factors for OSA include male gender, age, obesity, and nocturnal nasal congestion.3

Patients with asthma appear to have an increased risk for OSA. Large epidemiologic studies demonstrate that asthma patients more frequently report snoring.46 In a longitudinal study, asthma was an independent risk factor for development of snoring.7 OSA symptoms are highly prevalent in clinic-based populations of well-characterized asthma patients.8,9 Polysomnography revealed high frequencies of OSA (88% and 95.5%) in patients with difficult-to-control asthma.10,11 Conversely, OSA could worsen asthma. Treatment for OSA improves asthma symptoms,1214 use of rescue bronchodilator, peak expiratory flow rates,12 and disease-specific quality of life.15 The National Asthma Education and Prevention Program Expert Panel Report16 recommends evaluating for OSA as a potential contributor to poor asthma control. In short, OSA and asthma may have a bidirectional relationship in which each can exacerbate the other.

In this setting, a more specific understanding of what increases predisposition for OSA in asthma could be useful. It has been suggested that asthma comorbidities such as GERD and rhinitis, and medications (ie, systemic steroids) may each contribute to the development of OSA,10,1719 but their roles have not been studied. This investigation aimed to assess factors associated with habitual snoring and OSA risk in well-characterized patients with asthma. Our hypothesis was that asthma severity, coexistent disorders (GERD, nasal diseases), and medications (corticosteroids) would be associated with OSA symptoms, aside from traditional OSA risk factors such as excess weight, age, and male gender. A preliminary analysis was presented in abstract form20 and part of this sample was used for an analysis of daytime sleepiness in asthma.8

Participants

The population included asthma patients returning for routine visits at the University of Michigan Pulmonary Clinics and Asthma-Airways Center. Patients 18 to 75 years old, able, and willing to provide informed consent and complete our survey were included. Those at urgent asthma-related visits and pregnant women were not enrolled. This study was approved by the University of Michigan Institutional Review Board and conducted between May 2004 and April 2006.

Survey Content

The self-administered survey included the Sleep Apnea scale of the Sleep Disorders Questionnaire (SA-SDQ) which assesses OSA risk.21 This scale consists of eight symptom-items that ask about loud snoring disruptive to the bed partner, cessation of breathing in sleep, sudden gasping-arousals, worsening of snoring while supine or after alcohol, nocturnal sweating and nasal congestion, and history of hypertension. Responses are recorded on a 5-point Likert scale (“never” to “always”). Among these symptom-items, the report of loud snoring best correlated with polysomnography-diagnosed OSA.22 Data on weight, age, smoking, and body mass index (BMI) are rated on a 1 to 5 scale. The SA-SDQ was validated in a large sample of patients.21 We used the previously validated cutoff scores of ≥ 36 for men and ≥ 32 for women to define high OSA risk.21

A second instrument asked about frequency of daytime and nighttime asthma symptoms following the National Asthma Education and Prevention Program classification of asthma severity based on clinical features.23 This approach was specifically chosen to allow separate evaluation of associations between OSA symptoms with both clinical features of asthma and asthma medications. Attempts were made to obtain diaries of peak expiratory flow rates from patients or their medical records. Since their availability was limited, for uniformity, the peak flow variability was not used in asthma step assessment.

Medical Records Review

Records were reviewed to identify established diagnoses of lung and other comorbidities (eg, GERD, rhinitis, chronic sinusitis, and nasal polyps), SDB and its treatment, and current the asthma medications. The most recent spirometry data, obtained as requested by the evaluating physician, was collected to assess asthma severity step.23

Statistical Analysis

BMI was classified by the criteria of the Centers for Disease Control. Age ≥ 30 years was stratified into decades, using the 18- to 29-year-old group as the referent category. On the SA-SDQ, responses of 4 or 5 (“usually” or “always,” respectively) defined habitual symptoms. Doses of ICSs were classified as: low (category 1), medium (category 2) and high (category 3), per National Asthma Education and Prevention Program guidelines for adults.24 A dummy variable was created for each ICS dose category and compared with the “no ICS use” (category 0), as the reference. To test for linear trends, the ordinal (0 to 3) ICS dose variable was used.

Statistical software (SAS 9.1.3; SAS Institute; Cary, NC) was used for statistical analysis. Two-sample t test, χ2 test, or Fisher exact test was used as appropriate to test for gender differences in baseline variables (including natural logarithm-transformed BMI). Logistic regression was used to assess univariate relationships. Variables included in the SA-SDQ (such as categorized age, weight, BMI, and nocturnal nasal congestion) could not be analyzed for associations with the full SA-SDQ, but could be studied for associations with habitual snoring as a key symptom extracted from the SA-SDQ. A multivariate logistic regression model was fitted for habitual snoring as the outcome, having as predictors traditional risk factors for snoring (age, gender, overweight and obesity, nocturnal nasal congestion) and other covariates that demonstrated statistically significant univariate relationships. Multivariate models were constructed for high OSA risk on the SA-SDQ, with predictors that demonstrated statistically significant univariate associations. Linear relationships were tested in the same multivariate models, using the ordinal ICS dose variable. Two-sided p values <0.05 were considered to indicate statistical significance.

Patient Characteristics

Of the 325 patients approached, 303 (93%) completed this survey. Nineteen patients with lung comorbidities (eg, COPD, interstitial lung diseases) were excluded from the analysis.

Among the 284 patients, 143 (50%) had a diagnosis of SDB or met the criteria for high OSA risk. Of the 75 patients (26%) with a known history of OSA and recommended treatment, 40 patients (25 of 49 women [51%] and 15 of 26 men [58%], p = 0.58) were receiving treatment with CPAP. As CPAP could influence asthma control,1214 these 40 patients were excluded from further analyses.

The characteristics of the remaining 244 patients are presented in Table 1. BMI tended to be higher in females than in males (30 ± 8 vs 29 ± 6, respectively; p = 0.05). Among these patients, 27 (11%) were African-American, a group that may have particular vulnerability to OSA, 208 were white (85%), 5 (2%) Asian, 2 (1%) Hawaiian/Pacific Islander, and 2 (1%) American Indians/Alaskans. Of the 65 patients with asthma step 1, 13 (20%) were receiving high ICS doses and 20 (31%) were not receiving ICSs. Among 77 patients with asthma step 4, 12 (16%) were not taking ICSs and 43 (56%) were on high ICS doses. Habitual nocturnal nasal congestion was reported by 61 (25%) of the patients.

Table Graphic Jump Location
Table 1 Demographic and Physiologic Characteristics, Medical History, and Medication Use for 244 Asthma Patients*

*Data are presented as mean ± SD, No. (%), or No. unless otherwise indicated. FEF25–75 = forced expiratory flow between 25% and 75% of vital capacity.

Self-Reported OSA Symptoms

Snoring and witnessed apnea occurring with any frequency were reported by 204 patients (84%) and 78 patients (32%), respectively, without gender differences noted (both p > 0.10). Habitual snoring was reported by 90 of these patients (37%). The mean SA-SDQ score was 30 ± 8, and 77 women (45%) and 20 men (28%) showed high OSA risk. The SA-SDQ scores did not differ between previously diagnosed but untreated OSA patients and patients without known OSA history but high OSA risk (38 ± 5 vs 37 ± 4, respectively; p = 0.38).

Predictors of Habitual Snoring

Table 2 presents variables significantly associated with habitual snoring in univariate analyses, which were included in the multivariate model. Independent predictors of habitual snoring included GERD and ICS use, in addition to overweight and obesity, and habitual nasal congestion. Analysis of the association between habitual snoring and ICS doses, adjusted for the above covariates, demonstrated a linear dose-dependent relationship (p = 0.004 for the linear model). Compared to no ICS use, the odds of self-reported habitual snoring were on average 11% higher (odds ratio [OR], 1.11; 95% confidence interval [CI], 0.31 to 4.03) with low-dose ICS use, 159% higher (OR, 2.59; 95% CI, 0.96 to 6.97) with medium-dose use, and 267% higher (OR, 3.67; 95% CI, 1.34 to 10.01) with high-dose use (Fig 1). No univariate relationships were found with African-American race (vs all other races), history of rhinitis, chronic sinusitis, nasal polyps, and use of oral corticosteroids (all p > 0.10).

Table Graphic Jump Location
Table 2 Predictors of Habitual Snoring in 244 Asthma Patients

*Adjusted for all variables shown.

†Age 18 to 29 years was the reference category.

‡BMI < 25 kg/m2 was the reference category.

Figure Jump LinkFigure 1 The dose-dependent relationship between habitual snoring and ICS dose (overall p = 0.004 for the linear trend). The multivariate models included age (in decades), gender, overweight, obesity, habitual nasal congestion, GERD, and asthma severity step.Grahic Jump Location
Predictors of High OSA Risk

Variables associated with high OSA risk in both univariate and multivariate analyses are shown in Table 3. Female gender, GERD, asthma severity step, and ICS use were all predictive of OSA risk, independent of each other. The estimated odds that a woman with asthma would have a high risk for OSA were 111% greater (OR, 2.11; 95% CI, 1.10 to 4.05) in comparison to a man with asthma. A similar linear dose-dependent relationship was observed with ICS use (overall p = 0.0006 for the linear model), when adjusting for these covariates. When compared to no ICS use, the odds for high OSA risk were on average 129% higher (OR, 2.29; 95% CI, 0.66 to 7.96) for low-dose ICS, 267% higher (OR, 3.67; 95% CI, 1.34 to 10.03) for medium-dose ICS, and 443% higher (OR, 5.43; 95% CI 1.96 to 15.05) for high-dose ICS (Fig 2). A statistically significant univariate association between high OSA risk and African-American race (OR, 2.44; 95% CI, 1.08 to 5.52) was seen but this did not persist (OR, 1.74; 95% CI, 0.72 to 4.22) after adjusting for the other predictors shown in Table 3. No univariate associations were seen with a history of rhinitis, chronic sinusitis, nasal polyps, and use of oral corticosteroids (all p > 0.10).

Table Graphic Jump Location
Table 3 Predictors of High OSA Risk in 244 Asthma Patients

*Adjusted for all variables shown.

Figure Jump LinkFigure 2 The dose-dependent relationship between high OSA risk and ICS dose (overall p = 0.0006 for the linear trend). The multivariate models included gender, GERD, and asthma severity step.Grahic Jump Location

Because of the possibility of asthma severity confounding this relationship, multivariate models of ICS doses as predictors were created without and with inclusion of asthma severity step (Table 4). Inclusion of asthma step slightly attenuated the estimates of ORs but the statistical significance of the independent relationships of high OSA risk with medium and high ICS doses was maintained.

Table Graphic Jump Location
Table 4 Multivariate Models of High OSA Risk and ICS Dose Relationships With and Without Inclusion of Asthma Severity Step

*Gender and GERD were included in each model.

Associations of High OSA Risk With Asthma Step Components

In univariate analyses, high OSA risk showed similar associations with asthma symptoms in the daytime (OR, 1.65; 95% CI, 1.29 to 2.12]; p < 0.0001) and nighttime (OR, 1.45; 95% CI, 1.17 to 1.79; p = 0.0006), and a significant inverse association with FEV1 percent predicted (OR, 0.98; 95% CI, 0.97 to 0.99; p = 0.002). Replacement of asthma step with either daytime symptoms, nighttime symptoms, or FEV1 percent predicted in the multivariable model shown in Table 3 did not alter the magnitude or statistical significance of these relationships (Table 5).

Table Graphic Jump Location
Table 5 Associations of High OSA Risk With Components of Asthma Severity Step

*Each multivariate logistic regression model included gender, history of GERD, and use of an ICS as covariates.

This study identifies, for the first time, several factors that may help to explain an increased predisposition for OSA in asthma. Independent predictors of OSA symptoms included more severe asthma, history of GERD, and use of larger doses of ICSs, aside from traditional OSA risk factors such as excess weight and nocturnal nasal congestion. Additionally, these data suggest a reversal of male gender predominance for OSA symptoms in patients with asthma.

This specialty clinic-based, large sample of patients with asthma, well-characterized by clinical assessments and objective measures, should be representative of asthma patients with previously unidentified or untreated OSA followed routinely at many specialty clinics. Most of the patients (93%) invited to participate agreed to do so. In the final sample of 244 patients, a large proportion (71%) were women, consistent with the known female-gender predominance of asthma.25 Distribution of asthma severity was skewed toward more severe cases, as expected for this tertiary clinical setting. The prevalence of comorbidities was similar to that in prior reports.2629

Our results add to the evidence that asthma itself may lead to SDB,46 though these previous studies adjusted for few of the potential confounders that we assessed. In the European Community Respiratory Health Survey, among 2,661 patients of whom 267 had asthma, asthma patients more often reported habitual snoring (OR, 1.7; 95% CI, 1.2 to 2.5) and apnea, after adjustment for confounders, including BMI.5 In a 14-year longitudinal study conducted in Busselton, Australia, development of asthma emerged as a risk factor for incident habitual snoring (OR, 2.84; 95% CI, 1.44 to 5.58), independent of baseline BMI, BMI change during the time interval, and other confounders.7 In our study, daytime and nighttime asthma symptoms were comparable predictors of OSA risk, and a significant association with FEV1 percent predicted was also observed. Theoretically, asthma could deleteriously impact the patency of the upper airway (UAW) through effects of sleep loss and fragmentation30,31; greater reduction in lung volumes during sleep, particularly during REM sleep32,33; decreased pharyngeal transmural pressure related to nocturnal increase in air speed18; and systemic inflammation-related weakening of respiratory muscles,34,35 which could include the UAW dilators. Our data suggest that some of these mechanisms, probably involving systemic inflammatory pathways are operational during the day as well.

Another independent predictor of OSA symptoms was GERD. Epidemiologic studies report an association of GERD with OSA symptoms in the general population, independent of other confounders.36,37 Effective treatment for GERD improves the apnea-hypopnea index (AHI) to some extent.38 GERD is a common comorbid condition of asthma.28 Particularly, in obese patients with asthma, omental fat weight, subsequent loss of angulation of the gastroesophageal junction, and an increased transdiaphragmatic pressure gradient could predispose these patients to GERD.28 The proximal migration of gastric acid combined with prolonged acid clearance during sleep39 could trigger pharyngeal spasm, and cause UAW mucosal exudative neurogenic inflammation,28,40 setting the stage for OSA.

A novel finding from our study is the linear, dose-dependent association between ICS use and OSA risk, independent of asthma severity and other covariates. Yigla et al10 observed higher respiratory disturbance indices in patients with difficult-to-control asthma requiring continuous therapy with oral corticosteroids compared to those requiring bursts. All 22 patients were concomitantly on high dose of ICSs, precluding analysis of their potential association with the respiratory disturbance index. Based on the known effects of corticosteroids, our observation of independent associations of ICS dose with both snoring and OSA risk, but stronger with OSA risk (which includes information on weight and BMI), suggests that fat accumulation around the UAW may be one, but not the only, potential mechanism involved. Local myopathic effects of ICSs seem to occur in the larynx. In fact, dysphonia, the most common adverse effect of ICSs, is believed to be predominantly a myopathy of the vocal cords adductors,41,42 and it also occurs in a dose-dependent fashion.42 Thus, ICSs could potentially exert a local myopathic effect on the UAW dilators, impairing their compensatory response to anatomic compromise by fat. Additionally, ICS-related laryngeal candidiasis and inflammatory changes can cause dysphonia in some cases,41,42 and could represent another explanation for UAW dysfunction. Laryngeal inflammation is linked to OSA severity in OSA patients without asthma.43 The observed dose-dependent relationships of ICSs and OSA symptoms theoretically could reflect a relationship of asthma severity with OSA, with ICS doses as a mere surrogate of asthma severity. However, we had enough variability of ICS doses within each asthma severity step to argue against colinearity of these variables. Additionally, the independent relationships between ICS doses and OSA risk were maintained even with inclusion of asthma step in our multivariate model (Table 4). Similarly, it is possible that the relationship of ICS dose with OSA symptoms could be confounded by systemic steroid use among patients who use ICSs. However, we did not identify an association between oral corticosteroid use and OSA symptoms in this sample. Myopathic effects of corticosteroids occur more often with halogenated and, especially, fluorinated compounds.44 The ICSs are all halogenated compounds, raising the possibility that they may exert a more potent local UAW effect than systemic corticosteroids.

We found a two times higher likelihood for high OSA risk in women than in men with asthma, and there was no gender difference in habitual snoring, the latter independent of stratified BMI. These findings contrast with reports from general populations, where the male/female ratio typically is 2 to 3:1,2,4548 and could have important clinical implications, as asthma morbidity is higher in women1,49 despite their more frequent use of ICSs and better knowledge about asthma.49

Excess weight was found to be a strong predictor of habitual snoring, as in the general population.3 The rampant epidemic of obesity, particularly observed in asthma patients,50 is likely to promote OSA directly through anatomic effects on the upper airway or more indirectly through effects on lung volumes.50,51 Relationships among obesity, OSA, and asthma are likely to be bidirectional and more complex than can be dissected in our correlational study.

One limitation of this study is that polysomnography was not used to confirm OSA. Symptoms of asthma and OSA may overlap and create misleading associations if the overlap arises despite absence of any true biological interaction. However, questionnaire-based methodology using validated instruments represents a well-accepted approach of collecting hypothesis-generating data to justify further use of expensive tools. While currently still there are no OSA screening instruments validated specifically in asthma patients, the SA-SDQ has been validated for OSA (AHI ≥ 5 events/h) in a large sample of sleep patients with high internal validity, good sensitivity and specificity.21 A validation study of the SA-SDQ specifically in asthma patients is in progress. Lack of a strong enough association between OSA symptoms such as snoring and polysomnographic evidence for OSA to justify use of the symptom-based score in correlative research would be a most unusual finding based on published data from other medical conditions,22,52,53 as would the finding that symptoms completely reproduced objective findings. Research in both adults54 and children55 shows that symptom-based OSA measures may predict outcomes as well as, or above and beyond those predicted by objective measures. Additionally, in specific patient populations the SA-SDQ was found to be a good predictor for OSA22,53 such that cutoff scores lower than those used herein were proposed.22 If for some reason, published gender-specific SA-SDQ cutoffs are not accurate for asthma patients, then our observation of gender differences in OSA risk, but not habitual snoring, could be affected.

A second limitation of this study relates to its cross-sectional design, which restricts our ability to draw conclusions about causal pathways. However, the relationships we found with ICSs were robust, occurred in a dose-dependent fashion and independent of other alternative factors, and hold biological plausibility. As these agents have a central role in the management of asthma,16 our data identify a need for more research into the possibility that these medications could promote OSA.

Comorbidities such as GERD and nasal diseases may still have been missed in some patients, as the study design did not include their prospective evaluation. Additionally, these conditions were often treated, potentially reducing their contribution to OSA risk, since effective treatment of GERD with proton pump inhibitors improves the AHI in some patients38 and nasal steroids reduce the AHI in patients with rhinitis.56 Thus, the observed associations may actually represent underestimations of their true relationships with OSA.

In summary, to our knowledge this is the first detailed report of factors associated with OSA symptoms in a large sample of well-characterized asthma patients. Asthma severity, GERD and ICSs in higher doses were identified as independent predictors of OSA symptoms, when controlling for traditional OSA risk factors. Women appear to have a higher predisposition for OSA than men do, which may provide further insight into the female predominance of asthma morbidity. A large proportion of patients at this tertiary referral clinic screened high for OSA, emphasizing the need for better understanding of the pathophysiology that may connect asthma and OSA. This study raises important questions, as some of the associations observed may represent causal pathways and additional research will be needed to clarify them. Meanwhile, these results could guide clinicians in identifying asthma patients who might benefit from OSA screening.

AHI

apnea-hypopnea index

BMI

body mass index

CI

confidence interval

GERD

gastroesophageal reflux disease

ICS

inhaled corticosteroid

OR

odds ratio

OSA

obstructive sleep apnea

SA-SDQ

Sleep Apnea scale of the Sleep Disorders Questionnaire

SDB

sleep-disordered breathing

UAW

upper airway

We thank Ashley S. Holland, MPH, Radu C. Nistor, and Jesica M. Pedroza, BS for assistance with administration of screening questionnaires in clinics and data entry. We recognize the help from the physicians at the University of Michigan Pulmonary Clinics and Briarwood Asthma-Airways Center in recruiting patients for this study.

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Harrison BD. Psychosocial aspects of asthma in adults. Thorax. 1998;53:519-525. [PubMed]
 
Harding SM. Gastroesophageal reflux: a potential asthma trigger. Immunol Allergy Clin North Am. 2005;25:131-148. [PubMed]
 
Carr RE. Panic disorder and asthma: causes, effects and research implications. J Psychosom Res. 1998;44:43-52. [PubMed]
 
Leiter JC, Knuth SL, Bartlett D Jr. The effect of sleep deprivation on activity of the genioglossus muscle. Am Rev Respir Dis. 1985;132:1242-1245. [PubMed]
 
Series F, Roy N, Marc I. Effects of sleep deprivation and sleep fragmentation on upper airway collapsibility in normal subjects. Am J Respir Crit Care Med. 1994;150:481-485. [PubMed]
 
Ballard RD, Irvin CG, Martin RJ, et al. Influence of sleep on lung volume in asthmatic patients and normal subjects. J Appl Physiol. 1990;68:2034-2041. [PubMed]
 
Van de Graaff WB. Thoracic influence on upper airway patency. J Appl Physiol. 1988;65:2124-2131. [PubMed]
 
Silvestri M, Bontempelli M, Giacomelli M, et al. High serum levels of tumour necrosis factor-alpha and interleukin-8 in severe asthma: markers of systemic inflammation? Clin Exp Allergy. 2006;36:1373-1381. [PubMed]
 
Reid MB, Lannergren J, Westerblad H. Respiratory and limb muscle weakness induced by tumor necrosis factor-alpha: involvement of muscle myofilaments. Am J Respir Crit Care Med. 2002;166:479-484. [PubMed]
 
Janson C, Gislason T, De Backer W, et al. Prevalence of sleep disturbances among young adults in three European countries. Sleep. 1995;18:589-597. [PubMed]
 
Gislason T, Janson C, Vermeire P, et al. Respiratory symptoms and nocturnal gastroesophageal reflux: a population-based study of young adults in three European countries. Chest. 2002;121:158-163. [PubMed]
 
Senior BA, Khan M, Schwimmer C, et al. Gastroesophageal reflux and obstructive sleep apnea. Laryngoscope. 2001;111:2144-2146. [PubMed]
 
Orr WC, Elsenbruch S, Harnish MJ, et al. Proximal migration of esophageal acid perfusions during waking and sleep. Am J Gastroenterol. 2000;95:37-42. [PubMed]
 
Demeter P, Pap A. The relationship between gastroesophageal reflux disease and obstructive sleep apnea. J Gastroenterol. 2004;39:815-820. [PubMed]
 
Williams AJ, Baghat MS, Stableforth DE, et al. Dysphonia caused by inhaled steroids: recognition of a characteristic laryngeal abnormality. Thorax. 1983;38:813-821. [PubMed]
 
DelGaudio JM. Steroid inhaler laryngitis: dysphonia caused by inhaled fluticasone therapy. Arch Otolaryngol Head Neck Surg. 2002;128:677-681. [PubMed]
 
Payne RJ, Kost KM, Frenkiel S, et al. Laryngeal inflammation assessed using the reflux finding score in obstructive sleep apnea. Otolaryngol Head Neck Surg. 2006;134:836-842. [PubMed]
 
Dekhuijzen PN, Decramer M. Steroid-induced myopathy and its significance to respiratory disease: a known disease rediscovered. Eur Respir J. 1992;5:997-1003. [PubMed]
 
Larsson LG, Lindberg A, Franklin KA, et al. Gender differences in symptoms related to sleep apnea in a general population and in relation to referral to sleep clinic. Chest. 2003;124:204-211. [PubMed]
 
Kim J, In K, Kim J, et al. Prevalence of sleep-disordered breathing in middle-aged Korean men and women. Am J Respir Crit Care Med. 2004;170:1108-1113. [PubMed]
 
Honsberg AE, Dodge RR, Cline MG, et al. Incidence and remission of habitual snoring over a 5- to 6-year period. Chest. 1995;108:604-609. [PubMed]
 
Baldwin CM, Griffith KA, Nieto FJ, et al. The association of sleep-disordered breathing and sleep symptoms with quality of life in the Sleep Heart Health Study. Sleep. 2001;24:96-105. [PubMed]
 
Day A, Ernst P, Glick L, et al. Women and asthma: lessons from a gender analysis of the asthma in Canada survey. J Asthma. 2006;43:169-173. [PubMed]
 
Shore SA. Obesity and asthma: possible mechanisms. J Allergy Clin Immunol. 2008;121:1087-1093 quiz 1094–1085.. [PubMed]
 
White DP. Pathogenesis of obstructive and central sleep apnea. Am J Respir Crit Care Med. 2005;172:1363-1370. [PubMed]
 
Chung F, Ward B, Ho J, et al. Preoperative identification of sleep apnea risk in elective surgical patients, using the Berlin questionnaire. J Clin Anesth. 2007;19:130-134. [PubMed]
 
Bassetti C, Aldrich MS, Quint D. Sleep-disordered breathing in patients with acute supra- and infratentorial strokes: a prospective study of 39 patients. Stroke. 1997;28:1765-1772. [PubMed]
 
Gottlieb DJ, Yao Q, Redline S, et al. Does snoring predict sleepiness independently of apnea and hypopnea frequency? Am J Respir Crit Care Med. 2000;162:1512-1517. [PubMed]
 
Chervin RD, Weatherly RA, Garetz SL, et al. Pediatric sleep questionnaire: prediction of sleep apnea and outcomes. Arch Otolaryngol Head Neck Surg. 2007;133:216-222. [PubMed]
 
Kiely JL, Nolan P, McNicholas WT. Intranasal corticosteroid therapy for obstructive sleep apnoea in patients with co-existing rhinitis. Thorax. 2004;59:50-55. [PubMed]
 

Figures

Figure Jump LinkFigure 1 The dose-dependent relationship between habitual snoring and ICS dose (overall p = 0.004 for the linear trend). The multivariate models included age (in decades), gender, overweight, obesity, habitual nasal congestion, GERD, and asthma severity step.Grahic Jump Location
Figure Jump LinkFigure 2 The dose-dependent relationship between high OSA risk and ICS dose (overall p = 0.0006 for the linear trend). The multivariate models included gender, GERD, and asthma severity step.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 Demographic and Physiologic Characteristics, Medical History, and Medication Use for 244 Asthma Patients*

*Data are presented as mean ± SD, No. (%), or No. unless otherwise indicated. FEF25–75 = forced expiratory flow between 25% and 75% of vital capacity.

Table Graphic Jump Location
Table 2 Predictors of Habitual Snoring in 244 Asthma Patients

*Adjusted for all variables shown.

†Age 18 to 29 years was the reference category.

‡BMI < 25 kg/m2 was the reference category.

Table Graphic Jump Location
Table 3 Predictors of High OSA Risk in 244 Asthma Patients

*Adjusted for all variables shown.

Table Graphic Jump Location
Table 4 Multivariate Models of High OSA Risk and ICS Dose Relationships With and Without Inclusion of Asthma Severity Step

*Gender and GERD were included in each model.

Table Graphic Jump Location
Table 5 Associations of High OSA Risk With Components of Asthma Severity Step

*Each multivariate logistic regression model included gender, history of GERD, and use of an ICS as covariates.

References

Centers for Disease Control and Prevention, National Center for Health Statistics, US Department of Health and Human Services Fast stats A to Z: asthma prevalence, health care use and mortality; United States 2003–2005.Accessed February 20, 2009 Available athttp://www.cdc.gov/nchs/products/pubs/pubd/hestats/ashtma03-05/asthma03-05.htm.
 
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Janson C, De Backer W, Gislason T, et al. Increased prevalence of sleep disturbances and daytime sleepiness in subjects with bronchial asthma: a population study of young adults in three European countries. Eur Respir J. 1996;9:2132-2138. [PubMed]
 
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Teodorescu M, Consens FB, Bria WF, et al. Correlates of daytime sleepiness in patients with asthma. Sleep Med. 2006;7:607-613. [PubMed]
 
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Yigla M, Tov N, Solomonov A, et al. Difficult-to-control asthma and obstructive sleep apnea. J Asthma. 2003;40:865-871. [PubMed]
 
Boulet LP, Hamid Q, Bacon SL, et al. Symposium on obesity and asthma - November 2, 2006. Can Respir J. 2007;14:201-208. [PubMed]
 
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Guilleminault C, Quera-Salva MA, Powell N, et al. Nocturnal asthma: snoring, small pharynx and nasal CPAP. Eur Respir J. 1988;1:902-907. [PubMed]
 
Ciftci TU, Ciftci B, Guven SF, et al. Effect of nasal continuous positive airway pressure in uncontrolled nocturnal asthmatic patients with obstructive sleep apnea syndrome. Respir Med. 2005;99:529-534. [PubMed]
 
Lafond C, Series F, Lemiere C. Impact of CPAP on asthmatic patients with obstructive sleep apnoea. Eur Respir J. 2007;29:307-311. [PubMed]
 
National Asthma Education and Prevention Program Expert Panel Report 3 (EPR-3): Guidelines for the Diagnosis and Management of Asthma-Summary Report 2007. J Allergy Clin Immunol. 2007;120suppl:S94-S138. [PubMed]
 
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Bohadana AB, Hannhart B, Teculescu DB. Nocturnal worsening of asthma and sleep-disordered breathing. J Asthma. 2002;39:85-100. [PubMed]
 
Kasasbeh A, Kasasbeh E, Krishnaswamy G. Potential mechanisms connecting asthma, esophageal reflux, and obesity/sleep apnea complex: a hypothetical review. Sleep Med Rev. 2007;11:47-58. [PubMed]
 
Teodorescu M, Consens FB, Bria WF, et al. Screening for symptoms of sleep-disordered breathing (SDB) among asthmatics. Sleep. 2005;28S:A164
 
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Weatherwax KJ, Lin X, Marzec ML, et al. Obstructive sleep apnea in epilepsy patients: the Sleep Apnea scale of the Sleep Disorders Questionnaire (SA-SDQ) is a useful screening instrument for obstructive sleep apnea in a disease-specific population. Sleep Med. 2003;4:517-521. [PubMed]
 
US Department of Health and Human Services, National Institute of Health, National Heart, Lung and Blood Institute National asthma education and prevention program: practical guide for the diagnosis and management of asthma; expert panel report 2.Accessed February 20, 2009 Available at:http://www.nhlbi.nih.gov/guidelines/archives/epr-2/index.htm.
 
US Department of Health and Human Services, National Institute of Health, National Heart, Lung and Blood Institute National asthma education and prevention program: expert panel report: guidelines for the diagnosis and management of asthma; update on selected topics. 2002;Accessed February 20, 2009 Available at:http://www.nhlbi.gov/guidelines/archives/epr-2_upd/index.htm.
 
Ohga E, Nagase T, Tomita T, et al. Increased levels of circulating ICAM-1, VCAM-1, and L-selectin in obstructive sleep apnea syndrome. J Appl Physiol. 1999;87:10-14. [PubMed]
 
Nayak AS. The asthma and allergic rhinitis link. Allergy Asthma Proc. 2003;24:395-402. [PubMed]
 
Harrison BD. Psychosocial aspects of asthma in adults. Thorax. 1998;53:519-525. [PubMed]
 
Harding SM. Gastroesophageal reflux: a potential asthma trigger. Immunol Allergy Clin North Am. 2005;25:131-148. [PubMed]
 
Carr RE. Panic disorder and asthma: causes, effects and research implications. J Psychosom Res. 1998;44:43-52. [PubMed]
 
Leiter JC, Knuth SL, Bartlett D Jr. The effect of sleep deprivation on activity of the genioglossus muscle. Am Rev Respir Dis. 1985;132:1242-1245. [PubMed]
 
Series F, Roy N, Marc I. Effects of sleep deprivation and sleep fragmentation on upper airway collapsibility in normal subjects. Am J Respir Crit Care Med. 1994;150:481-485. [PubMed]
 
Ballard RD, Irvin CG, Martin RJ, et al. Influence of sleep on lung volume in asthmatic patients and normal subjects. J Appl Physiol. 1990;68:2034-2041. [PubMed]
 
Van de Graaff WB. Thoracic influence on upper airway patency. J Appl Physiol. 1988;65:2124-2131. [PubMed]
 
Silvestri M, Bontempelli M, Giacomelli M, et al. High serum levels of tumour necrosis factor-alpha and interleukin-8 in severe asthma: markers of systemic inflammation? Clin Exp Allergy. 2006;36:1373-1381. [PubMed]
 
Reid MB, Lannergren J, Westerblad H. Respiratory and limb muscle weakness induced by tumor necrosis factor-alpha: involvement of muscle myofilaments. Am J Respir Crit Care Med. 2002;166:479-484. [PubMed]
 
Janson C, Gislason T, De Backer W, et al. Prevalence of sleep disturbances among young adults in three European countries. Sleep. 1995;18:589-597. [PubMed]
 
Gislason T, Janson C, Vermeire P, et al. Respiratory symptoms and nocturnal gastroesophageal reflux: a population-based study of young adults in three European countries. Chest. 2002;121:158-163. [PubMed]
 
Senior BA, Khan M, Schwimmer C, et al. Gastroesophageal reflux and obstructive sleep apnea. Laryngoscope. 2001;111:2144-2146. [PubMed]
 
Orr WC, Elsenbruch S, Harnish MJ, et al. Proximal migration of esophageal acid perfusions during waking and sleep. Am J Gastroenterol. 2000;95:37-42. [PubMed]
 
Demeter P, Pap A. The relationship between gastroesophageal reflux disease and obstructive sleep apnea. J Gastroenterol. 2004;39:815-820. [PubMed]
 
Williams AJ, Baghat MS, Stableforth DE, et al. Dysphonia caused by inhaled steroids: recognition of a characteristic laryngeal abnormality. Thorax. 1983;38:813-821. [PubMed]
 
DelGaudio JM. Steroid inhaler laryngitis: dysphonia caused by inhaled fluticasone therapy. Arch Otolaryngol Head Neck Surg. 2002;128:677-681. [PubMed]
 
Payne RJ, Kost KM, Frenkiel S, et al. Laryngeal inflammation assessed using the reflux finding score in obstructive sleep apnea. Otolaryngol Head Neck Surg. 2006;134:836-842. [PubMed]
 
Dekhuijzen PN, Decramer M. Steroid-induced myopathy and its significance to respiratory disease: a known disease rediscovered. Eur Respir J. 1992;5:997-1003. [PubMed]
 
Larsson LG, Lindberg A, Franklin KA, et al. Gender differences in symptoms related to sleep apnea in a general population and in relation to referral to sleep clinic. Chest. 2003;124:204-211. [PubMed]
 
Kim J, In K, Kim J, et al. Prevalence of sleep-disordered breathing in middle-aged Korean men and women. Am J Respir Crit Care Med. 2004;170:1108-1113. [PubMed]
 
Honsberg AE, Dodge RR, Cline MG, et al. Incidence and remission of habitual snoring over a 5- to 6-year period. Chest. 1995;108:604-609. [PubMed]
 
Baldwin CM, Griffith KA, Nieto FJ, et al. The association of sleep-disordered breathing and sleep symptoms with quality of life in the Sleep Heart Health Study. Sleep. 2001;24:96-105. [PubMed]
 
Day A, Ernst P, Glick L, et al. Women and asthma: lessons from a gender analysis of the asthma in Canada survey. J Asthma. 2006;43:169-173. [PubMed]
 
Shore SA. Obesity and asthma: possible mechanisms. J Allergy Clin Immunol. 2008;121:1087-1093 quiz 1094–1085.. [PubMed]
 
White DP. Pathogenesis of obstructive and central sleep apnea. Am J Respir Crit Care Med. 2005;172:1363-1370. [PubMed]
 
Chung F, Ward B, Ho J, et al. Preoperative identification of sleep apnea risk in elective surgical patients, using the Berlin questionnaire. J Clin Anesth. 2007;19:130-134. [PubMed]
 
Bassetti C, Aldrich MS, Quint D. Sleep-disordered breathing in patients with acute supra- and infratentorial strokes: a prospective study of 39 patients. Stroke. 1997;28:1765-1772. [PubMed]
 
Gottlieb DJ, Yao Q, Redline S, et al. Does snoring predict sleepiness independently of apnea and hypopnea frequency? Am J Respir Crit Care Med. 2000;162:1512-1517. [PubMed]
 
Chervin RD, Weatherly RA, Garetz SL, et al. Pediatric sleep questionnaire: prediction of sleep apnea and outcomes. Arch Otolaryngol Head Neck Surg. 2007;133:216-222. [PubMed]
 
Kiely JL, Nolan P, McNicholas WT. Intranasal corticosteroid therapy for obstructive sleep apnoea in patients with co-existing rhinitis. Thorax. 2004;59:50-55. [PubMed]
 
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