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Volume 13 No. 09
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Scientific Investigations
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The National Healthy Sleep Awareness Project Sleep Health Surveillance Questionnaire as an Obstructive Sleep Apnea Surveillance Tool

Youngsin Jung, MD, PhD1,2; Mithri R. Junna, MD1,2; Jayawant N. Mandrekar, PhD3; Timothy I. Morgenthaler, MD1,4
1Center for Sleep Medicine, Mayo Clinic, Rochester, Minnesota; 2Department of Neurology, Mayo Clinic, Rochester, Minnesota; 3Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota; 4Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota

ABSTRACT

Study Objectives:

To validate the previously published National Healthy Sleep Awareness Project (NHSAP) Surveillance and Epidemiology Workgroup questionnaire for ability to determine risk for moderate to severe obstructive sleep apnea (OSA).

Methods:

The NHSAP sleep questions, part of the next Behavioral Risk Factor Surveillance System (BRFSS), were constructed to mimic elements of the STOP sleep apnea questionnaire, and included number of days with sleep disruption and unintentional dozing and a history of snoring and apneas. The responses to four sleep questions from the BRFSS were collected from 352 adults undergoing in-laboratory polysomnography at Mayo Clinic, Rochester, Minnesota. Demographic and clinical information, including sex, age, body mass index (BMI), and presence of hypertension, which will be available in other parts of the complete BRFSS, were obtained by chart review. Univariate and logistic regression analyses were performed, and values of P < .05 were considered to be statistically significant.

Results:

Fifty-five percent of subjects were men and 45% were women with a median age of 58 years and BMI 32.2 kg/m2. Sixty percent had no or mild OSA, and 40% had moderate to severe OSA. No single question was superior in screening for moderate to severe OSA, although a history of snoring and witnessed apneas was more likely to predict moderate to severe OSA. Male sex, age ≥ 50 years, BMI ≥ 30 kg/m2, presence of hypertension, and a history of snoring and witnessed apneas were the most highly weighted factors in predicting moderate to severe OSA. When each variable was dichotomized to a single point, a cutoff of 5 points significantly predicted a high risk of moderate to severe OSA with an odds ratio of 3.87 (2.39–6.27).

Conclusions:

Although many variables were positively associated with the apnea-hypopnea index, no single factor was superior in predicting moderate to severe OSA. Male sex, increased age, higher BMI, hypertension, and a history of snoring and witnessed apneas are the most highly predictive of moderate to severe OSA. Combined use of the NHSAP questionnaire and demographic and clinical characteristics could be considered for screening for moderate to severe OSA.

Citation:

Jung Y, Junna MR, Mandrekar JN, Morgenthaler TI. The National Healthy Sleep Awareness Project sleep health surveillance questionnaire as an obstructive sleep apnea surveillance tool. J Clin Sleep Med. 2017;13(9):1067–1074.


INTRODUCTION

Obstructive sleep apnea (OSA) is a significant health concern. It has been associated with various cardiovascular and cerebrovascular diseases, including hypertension, atrial fibrillation, coronary artery disease, congestive heart failure, and stroke, as well as increased all-cause mortality.13 Over the past 20 years, the prevalence has increased by 14% to 50% depending upon age and sex.4 Moderate to severe OSA, defined by an apneahypopnea index (AHI) ≥ 15, is estimated to occur in 10% to 17% of men and 3% to 9% of women, depending on their age.4

Given the implications of untreated OSA on cardiovascular and cerebrovascular health, Healthy People 2020, a nationwide health-promoting program launched by the Department of Health and Human Services, includes topics on sleep health.5 The main objectives are to increase OSA evaluation in individuals with symptoms concerning for sleep-disordered breathing and decrease motor vehicle accidents associated with drowsy driving.5 To accomplish these goals, the National Healthy Sleep Awareness Project (NHSAP) was created by the Centers for Disease Control and Prevention (CDC), the American Academy of Sleep Medicine (AASM), and the Sleep Research Society.6 The NHSAP Surveillance and Epidemiology Work-group has created a bank of questions that will be included in the sleep section of the next Behavioral Risk Factor Surveillance System (BRFSS), a well-established government supported annual surveillance tool, and published the design and development of the question bank in an effort to improve sleep health surveillance.7,8

BRIEF SUMMARY

Current Knowledge/Study Rationale: Untreated obstructive sleep apnea (OSA) is associated with significant cardiovascular and cerebrovascular comorbidities. This study assesses the National Healthy Sleep Awareness Project (NHSAP) Surveillance and Epidemiology Workgroup questionnaire as a risk stratification tool for clinically significant OSA.

Study Impact: Identification of individuals at risk for OSA is important for appropriate evaluation and treatment. The NHSAP questionnaire provides similar accuracy to other commonly used screening tools and can be useful for determining risk for moderate to severe OSA.

The NHSAP sleep health question bank is designed to address sleep quality, satisfaction, alertness, and OSA risk.8 The content and construct validity of the questions in the bank related to sleep quality, satisfaction, and alertness have been previously established, although they have not been grouped to describe “sleep health.”9,10 The questions designed to assess for the risk of OSA have been constructed to mimic “snoring,” “tired,” and “observed apnea” elements of the STOP sleep apnea questionnaire with subtle differences in wording of the questions.8 Although the NHSAP sleep questions themselves do not address demographic or clinical factors that may affect the risk of OSA, information regarding age, sex, body mass index (BMI), and blood pressure can be gleaned from other sections of the BRFSS. Combining the sleep questions and demographic and clinical factors addresses 7 of the 8 components of the STOP-BANG (snoring, tired, observed apneas, blood pressure, BMI, age, neck circumference, gender) questionnaire, which, depending upon cutoff points selected, has 93% and 100% sensitivity and 43% and 37% specificity for moderate and severe OSA, respectively, and shows positive predictability of OSA severity with an increasing score.1114 Neck circumference is not addressed in the BRFSS.

The previous version of the BRFSS sleep questions has been validated, although the focus was placed on predicting sleep/ wake disturbance.15 It is unclear whether the new NHSAP/ BRFSS sleep question bank in combination with demographic and clinical factors can be utilized as an effective risk stratification tool for OSA in population-based surveys. Here, we examined the criterion validity of the sleep question bank in predicting the presence of moderate to severe OSA, as these questions will be utilized in the next BRFSS to promote sleep health surveillance of America.

METHODS

A revised 2016 NHSAP/BRFSS sleep questionnaire contained 4 questions addressing sleep quality and satisfaction, alertness, and OSA risk (Table 1). The number of days with sleep initiation or maintenance insomnia or hypersomnia was used to measure sleep quality and satisfaction. The number of days with unintentional dozing during the day was used to assess daytime alertness. Witnessed snoring and apneic episodes were intended to add information regarding OSA risk.

The revised NHSAP/BRFSS sleep questionnaire.

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Table 1

The revised NHSAP/BRFSS sleep questionnaire.

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The sample size was calculated based on an estimated sensitivity (0.5–0.9), precision of the sensitivity (95% confidence interval width), power of 0.8, type I error of 0.05, and estimated prevalence of 0.67, similar to the sample size estimation for the STOP-BANG validation.11 This suggested that a sample size of 350 would be suitable. The questionnaire was distributed to 678 English-speaking patients who were 18 years or older and undergoing overnight polysomnography (PSG) for various clinical indications in the Center for Sleep Medicine at Mayo Clinic, Rochester, Minnesota between October 12, 2015 and January 8, 2016. Patients had to provide written consent, complete the questionnaire, and undergo split-night or full-night diagnostic in-laboratory PSG to be included in the study (Figure 1). Of 678 recruits, 352 patients (52%) met the inclusion criteria. Of 326 patients excluded, 295 did not provide written consent, 8 did not complete the questionnaire, and 23 did not undergo diagnostic PSG. As the complete BRFSS was not administered to the patients, demographic and clinical characteristics of these patients, including age, sex, BMI, and presence of hypertension, were obtained by chart review. In addition, Epworth Sleepiness Scale (ESS) was collected by chart review. ESS was available for 318 patients (90%). PSG was scored by certified technologists and reviewed by board-certified sleep medicine physicians according to the AASM scoring criteria.16 Diagnostic AHI was used to divide the patients into no apnea (AHI < 5), mild apnea (5 ≤ AHI < 15), or moderate to severe apnea (AHI ≥ 15) groups.17 This study was approved by the Mayo Clinic Institutional Review Board.

Subject recruitment flow chart.

AHI = apnea-hypopnea index, PSG = polysomnography.

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Figure 1

Subject recruitment flow chart.

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Statistical Analysis

Descriptive summaries were reported as frequencies and percentages for categorical variables, and as median and inter-quartile ranges for continuous variables. Univariate analysis was used to determine factors that were strongly associated with the presence of moderate to severe OSA. Chi square test or Fisher exact test was used for categorical variables, and Wilcoxon rank-sum test or Kruskal-Wallis test was used for continuous variables due to non-normal distribution of the variables. Multivariable logistic regression models were utilized to generate prediction models for the NHSAP questionnaire and the demographic and clinical factors, including age, sex, BMI, and presence of hypertension. Receiver operating characteristic (ROC) curves were generated to determine a cutoff value for given scoring methods. An area under the ROC curve (AUC) estimate of 0.7–0.8 was regarded as acceptable, 0.8–0.9 was regarded as excellent, and more than 0.9 was regarded as outstanding. All tests were two-sided, and values of P < .05 were considered statistically significant. Analysis was performed using SAS version 9.4 (SAS Inc, Cary, North Carolina, United States).

RESULTS

The demographic and clinical characteristics of the patients and answers to the questionnaire are shown in Table 2. Fifty-five percent were men and 45% were women with a median age of 58 years. Most of the patients were obese with a median BMI of 32.2 kg/m2, although 12% had a BMI less than 25 kg/m2 and 23% had a BMI between 25 and 30 kg/m2. Hypertension was present in 48% of the patients. Eighty-one percent of the patients reported the presence of sleep initiation or maintenance difficulty or hypersomnia in the 2 weeks preceding their PSG with a median of 7 days of sleep disruption. However, most of the patients did not report decreased daytime alertness, which was also supported by separately measured ESS. Seventy-six percent of the patients reported snoring, and 54% of the patients reported witnessed apneic episodes. Based on AHI, 24% of the patients had no OSA, 36% had mild OSA, and 40% had moderate to severe OSA. Demographic and clinical characteristics of the 295 subjects that were excluded from the study could not be compared to the subjects that were included in the study, as they did not provide written consent for the study. The 31 subjects who provided written consent, but either did not complete the questionnaire or undergo diagnostic PSG, were older (a median age of 65 years with interquartile range 59–72 years; P = .01) than the subjects who were included, but did not differ in other demographic or clinical characteristics.

Demographic and clinical characteristics and the NHSAP/BRFSS sleep questionnaire.

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Table 2

Demographic and clinical characteristics and the NHSAP/BRFSS sleep questionnaire.

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Based on univariate analysis, male sex, age, BMI, and presence of hypertension were associated with AHI ≥ 15 (P ≤ .0002). In addition, report of snoring and witnessed apneas on the questionnaire was associated with AHI ≥ 15 (P < .0001). However, report of initiation or maintenance insomnia, hypersomnia, or decreased daytime alertness on the questionnaire, regardless of the number of days with the aforementioned symptoms in the two weeks preceding the PSG, and ESS did not correlate with AHI ≥ 15.

Male sex, an increase in age by 10 years, an increase in BMI by 5 kg/m2, and presence of hypertension had an odds ratio of 2.34, 1.29, 1.29, and 2.34 for moderate to severe OSA, respectively (Table 3). The presence of snoring and witnessed apneas reported on the questionnaire had an odds ratio of 2.30 and 2.02 for moderate to severe OSA, respectively (Table 3). However, the presence of initiation or maintenance insomnia, hypersomnia, or decreased daytime alertness on the questionnaire, and higher ESS did not significantly increase the odds ratio for moderate to severe OSA (Table 3).

Odds ratios of demographic, clinical, and questionnaire variables for moderate to severe obstructive sleep apnea.

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Table 3

Odds ratios of demographic, clinical, and questionnaire variables for moderate to severe obstructive sleep apnea.

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Of 141 patients with AHI ≥ 15, 68 had moderate OSA (15 ≤ AHI < 30), and 73 had severe OSA (AHI ≥ 30). There were no differences between the two groups in terms of their demographic or clinical characteristics or answers to the questionnaire (Table S1 in the supplemental material). None of the variables had a significant odds ratio for AHI ≥ 30 compared to 15 ≤ AHI < 30 (Table S2 in the supplemental material).

Of note, the number of days with decreased sleep quality and satisfaction (AUC 0.4) and alertness (AUC 0.5) had no significant effect on identifying patients with moderate to severe OSA. Therefore, further analyses were performed based on the presence or absence of these symptoms, rather than using the actual number of days reported on the questionnaire.

The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the individual questions are shown in Table 4. The most sensitive question was a history of snoring with a sensitivity of 84.4%. The most specific question was alertness with a specificity of 55.0%. All parameters provided PPV of almost 40%, whereas NPV ranged between 50.8 and 74.1%. No single question was superior than the others in screening for patients with moderate to severe OSA.

Predictive parameters of the NHSAP/BRFSS sleep questions for moderate to severe obstructive sleep apnea.

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Table 4

Predictive parameters of the NHSAP/BRFSS sleep questions for moderate to severe obstructive sleep apnea.

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To determine a cutoff value for predicting moderate to severe OSA, a single point was assigned to a positive answer (ie, # day > 0 or yes) to each question on the questionnaire. Based on the ROC curves for age and BMI, age 50 years or older and BMI ≥ 30 kg/m2 were found to be significantly associated with moderate to severe OSA. Therefore, an aggregate score was constructed, assigning one point for each sleep question, age 50 years or older, BMI ≥ 30 kg/m2, male sex, and presence of hypertension. The ROC curve based upon the sum of these parameters is shown in Figure 2. The AUC was 0.7. The sensitivity, specificity, PPV, and NPV of each point score is shown in Table 5. Based on the sensitivity and specificity, assuming both of equal importance, a score of 5 was the optimal threshold for predicting moderate to severe OSA, with an odds ratio of 3.87 (2.39–6.27).

Receiver operating characteristic curve of NHSAP/BRFSS questionnaire cutoffs for moderate to severe obstructive sleep apnea.

AUC = area under the receiver operating characteristic curve, BRFSS = Behavioral Risk Factor Surveillance System, NHSAP = National Healthy Sleep Awareness Project.

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Figure 2

Receiver operating characteristic curve of NHSAP/BRFSS questionnaire cutoffs for moderate to severe obstructive sleep apnea.

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Predictive parameters of different NHSAP/BRFSS sleep questionnaire cutoffs for moderate to severe obstructive sleep apnea.

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Table 5

Predictive parameters of different NHSAP/BRFSS sleep questionnaire cutoffs for moderate to severe obstructive sleep apnea.

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DISCUSSION

The results of the current study indicate that data derived from the NHSAP sleep questions, when combined with the answer to other questions in the BRFSS, provide accuracy in predicting the presence of moderate to severe OSA that is similar to other prediction rules specifically developed to stratify risk for having clinically significant OSA. Using our derived score with all possible results, the ROC had an acceptable AUC of 0.7, and the “optimized” threshold score of 5 provides an odds ratio estimate of 3.87. The comparability of the performance of the NHSAP sleep questions to other established clinical prediction rules, such as the STOP-BANG questionnaire, is important as the next BRFSS will be widely distributed to survey America's sleep health. In clinical populations referred to the Veterans Administration sleep facilities, the STOP-BANG questionnaire had an AUC of 0.66 (95% confidence interval [CI]: 0.64–0.69) for predicting at least moderately severe OSA.18 In another study, the AUC was calculated for the Berlin Questionnaire as 0.54 (95% CI: 0.33–0.75; P = .75), the Epworth Sleepiness Scale as 0.69 (95% CI: 0.47–0.86; P = .10), and the Sleep Apnea Clinical Score as 0.82 (95% CI: 0.61–0.94; P = .02).19 A recent meta-analysis found that in sleep clinic populations, the AUC for the STOP-BANG was consistently greater than 0.72 for all severities of OSA.20

As expected, positive answers to the questions of snoring and witnessed apneic episodes that were specifically aimed at assessing OSA risks were strongly associated with moderate to severe OSA. However, BRFSS sleep questions that were geared toward evaluating overall sleep quality and satisfaction and alertness failed to demonstrate strong correlations with the presence of moderate to severe OSA. Similar to prior findings, numeric quantification of sleep quality and satisfaction and alertness did not provide additional values for assessing the presence of OSA.21

Interestingly, no single question was superior in predicting the presence of moderate to severe OSA, which is consistent with previous studies showing that multiple questions are needed for OSA screening.11,15,22,23 The presence of certain demographic and clinical characteristics, such as male sex, age 50 years or older, BMI ≥ 30 kg/m2, and presence of hypertension, is not part of the sleep questions. However, sex, age, hypertension, height, and weight are self-reported in the BRFSS. When these were combined with the NHSAP/BRFSS sleep questions, the accuracy for predicting the presence of moderate to severe OSA substantially improved. Similar demographic and clinical factors have been shown to be highly associated with OSA.11

In our study, the BRFSS sleep question bank did not accurately differentiate patients with severe OSA from those with moderate OSA. Possibly, this may have been related to insufficient sample size to provide adequate statistical power. A further study with larger samples of moderate and severe OSA is indicated to address whether the BRFSS sleep question bank is a useful tool for separating patients with severe OSA from those with moderate OSA.

There are several potential limitations in our study. Subjects were recruited from patients who were referred to the Center for Sleep Medicine for evaluation of sleep-disordered breathing, and are therefore more likely to have significant sleep apnea and associated risk factors and comorbidities. We found a 76% prevalence for any severity of OSA, considerably higher than that found in the general population, and the BRFSS questionnaire is designed to be administered to a representative sample of the general population. Clearly our calculated predictive values would not apply to another population where prevalence of sleep apnea is much lower. In contrast, sensitivity, specificity, and odds ratios are not typically affected by the prevalence of the disease in question, as shown in a previous meta-analysis of the STOP-BANG questionnaire.20 In addition, the BRFSS is administered as a telephone interview, whereas our patients completed the survey in writing. It would be important to repeat our work in a more general population using telephone interview to ensure external validity.

Our score purposefully limited itself to the sleep question bank from the 2016 BRFSS, adding only pieces of information that would be available from other parts of the BRFSS and that are related to the STOP-BANG construct. Although answers regarding age and sex should yield accurate response in survey, we used measured BMI in our work, whereas the BRFSS would only supply self-reported height and weight. Although there is potential for random or systematic bias in self-report of BMI, studies generally show that BMI derived from self-report is reasonably accurate.2427 Self-report of high blood pressure has also been demonstrated to have moderate sensitivity.28

We did not evaluate other questions in the BRFSS for their potential contribution to the ability to stratify risk for OSA. This conceptually could be completed after administration of the entire BRFSS to the sample population as long as there was also the capability to provide testing for the presence or absence of OSA.

Untreated OSA can result in significant health consequences. Identifying patients at risk for OSA and triaging them for appropriate evaluation is crucial. The NHSAP/BRFSS perform in a fashion similar to other currently used clinical prediction rules for predicting OSA risk. Predicting the probability of moderate to severe OSA can be further improved by factoring in demographic and clinical characteristics. Therefore, combined use of the NHSAP/BRFSS sleep question bank and demographic and clinical variables may be recommended for screening of moderate to severe OSA.

DISCLOSURE STATEMENT

Drs. Jung, Junna, Mandrekar, and Morgenthaler have nothing to disclose.

ABBREVIATIONS

AASM

American Academy of Sleep Medicine

AHI

apnea-hypopnea index

AUC

area under the curve

BMI

body mass index

BRFSS

Behavioral Risk Factor Surveillance System

CDC

Centers for Disease Control and Prevention

CI

confidence interval

ESS

Epworth Sleepiness Scale

NHSAP

National Healthy Sleep Awareness Project

NPV

negative predictive value

OSA

obstructive sleep apnea

PPV

positive predictive value

PSG

polysomnography

ROC

receiver operating characteristic

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