Issue Navigator

Volume 14 No. 09
Earn CME
Accepted Papers


Obstructive Sleep Apnea and Atrial Fibrillation: Honing in on Race-Specific Susceptibilities

Younghoon Kwon, MD1; Reena Mehra, MD, MS2
1Cardiovascular Division, University of Virginia, Charlottesville, Virginia; 2Sleep Disorders Center, Neurologic Institute, Respiratory Institute, Heart and Vascular Institute and Molecular Cardiology Department of the Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio

Atrial fibrillation (AF) is one of the most common cardiac arrhythmias affecting millions in the United States alone.1 Adverse consequences of AF such as ischemic stroke, heart failure and mortality coupled with its rising epidemic is of significant public health concern.2 Common cardiovascular risk factors such as aging, hypertension, obesity and metabolic syndrome are major predisposing factors for AF in patients without structural heart disease. Not surprisingly, sleep-disordered breathing (SDB), which is also commonly associated with these factors, has also been implicated as one of the pieces of the pathophysiologic puzzle of AF. Indeed, obstructive sleep apnea (OSA), the most common type of SDB, in patients without heart failure is highly prevalent in patients with AF and is associated with a higher recurrence of AF after electrical cardioversion or catheter-based AF ablation.35 On the other hand, such shared common risk factors can confound the independent role of SDB on the pathogenesis of AF. In fact, while the association between SDB and AF, including nocturnal AF, has been shown in many clinic and community-based studies, careful inspection of the results of the available studies reveals that the relationship is more complex than how it is generally perceived.610 Specifically, the association between OSA and AF has not been consistent as highlighted by recently reported prospective studies.1113 Inconsistent results or absence of significant findings often prompt us to consider potential effect modification by characteristics to identify subgroup susceptibilities. For example, age appears to be an important effect modifier. In one study, OSA was predictive of incident AF in younger subjects (< 65 years) but not in the older age group.6 In another study of older men, central sleep apnea was associated with incident AF in older patients (> 76 years) but not in younger patients.11 Sex is another important effect modifier. Although lacking SDB-AF specific studies, an emerging body of evidence suggests a differential cardiovascular effect of OSA by sex.14 On the contrary, there has been a paucity of cross-race/ethnicity examinations of race in explaining the association of SDB with cardiovascular outcomes including AF.

In this issue of the Journal of Clinical Sleep Medicine, a study by Ghazi et al. raises the important question of how race/ethnicity, sex, age and regional difference may influence the relationship between OSA and AF.15 Using the large biracial cohort of the REasons for Geographic And Racial Differences in Stroke (REGARDS) study, the investigators attempted to address this question by examining the association between “OSA risk,” a surrogate for OSA, and prevalent AF. They found that high OSA risk as determined by Berlin Questionnaire (BQ) was associated with a higher odds of having AF. Although the results did not differ by sex, age or region, there was significant effect modification by race. Race-specific analysis revealed more pronounced results (58% increased odds of AF) in blacks; however, the association was no longer present in whites. This finding adds to the emerging notion of differential association of common AF risk factors by race.16 A previous analysis in the same cohort found that although risk factors for AF were similar between blacks and whites, impact of certain risk factors such as smoking, obesity and hypertension as measured by population attributable fraction (PAF) was higher for blacks than whites.17 This study by Ghazi et al. raises a possibility that OSA is another modifiable risk factor that may have relatively higher implication in the risk of AF in blacks than whites.

A major limitation of the study by Ghazi et al., as acknowledged by the authors, is the lack of objective sleep monitoring. Instead, OSA risk was classified as “high” versus “low” risk based on BQ. BQ consists of questions classified into three categories; (1) snoring, (2) sleepiness/fatigue and (3) comorbid risks (hypertension or high body mass index [BMI > 30 kg/m2]).18 Although this survey tool has been validated in primary care setting and is generally considered a useful screening tool for OSA in various settings including general population, positive predictive value is typically low (versus high negative predictive value) when tested against gold-standard polysomnography.19,20 This is not surprising as all three components of the survey tool, in particular the item about the comorbid risks such as hypertension and obesity, are not so specific to OSA. Therefore, high OSA risk by BQ likely overestimates the true risk of OSA. Moreover, there is a possibility that the accuracy of the tool differs by race/ethnicity. In general, blacks appear to more likely endorse daytime sleepiness and poor sleep quality than whites.21 Another obvious challenge was the inability to adjust for BMI as it was already incorporated in the prediction of high versus low OSA risk as a part of BQ. The challenge of the methodological approach was evidenced by inconsistent results shown in sensitivity analysis in which the association based on the BMI category was examined. While high OSA risk group conferred higher AF risk in participants with low BMI strata, the same did not hold true for those with high BMI strata. This suggests the very association (high risk OSA-AF) may be BMI-dependent. Further insights into this issue in the context of racial difference cannot be given as race-stratified results was not provided. Since hypertension and obesity are one of the most potent confounders in any OSA-cardiovascular association and their contribution to AF risk may be stronger in blacks than in whites, it is possible that the findings of this study may have been driven by uneven distribution of these risk factors between high versus low OSA risk in blacks (rather than by true impact of race). Separate analysis based on each component of BQ may have shed more light on this question. Finally, we need to recognize that the cross-sectional design of the study does not allow us to derive a causality. In fact, the timing of AF ascertainment based on either self-report or home visit electrocardiography preceded that of sleep survey by up to maximum of 7 years. Thus, it is very possible that new AF cases that have occurred after the initial AF survey period, not included in the analysis, may have impacted the study results.

Despite these limitations, given race-based differences in risk, pathophysiology and social constructs, we applaud the investigators for addressing the important area of race-specific influences in OSA and AF within the limits of the study design. Specifically, there is clear evidence of the important role that race plays in the pathogenesis and the outcome of AF. Blacks are at a lower risk for developing AF than whites despite a higher prevalence of many of the traditional risk factors including hypertension and obesity known to increase the likelihood of AF.22,23 More importantly, racial disparities in vulnerability of AF related outcomes have been identified. In a recent investigation of Atherosclerosis Risk in Communities (ARIC) cohort, the outcome of AF on the rates of stroke, heart failure, coronary heart disease and mortality was considerably higher in black compared to white individuals.24 In OSA, race-specific differences have been identified as well with increased hypoxic ventilatory response, increased peripheral response to hypercapnia and differences in cephalometric and anthropometrics upper airway features in blacks versus whites.25 It is critical therefore for momentum to continue to identify the role of biologic, genomic and social constructs of race-specific differences in OSA and AF. These efforts will allow us to hone in on race-based susceptibilities in OSA and target interventions accordingly to mitigate AF-related adverse cardiovascular outcomes and mortality, ie, important outcomes recognized to be increased in blacks with AF.


Dr. Mehra reports that she is supported by NIH funding. Her institution has received positive airway pressure machines and equipment from Philips Respironics and ResMed for use in NIH-funded research. She has received honorarium from the American Academy of Sleep Medicine for speaking. She serves as an Associate Editor for the journal Chest. She has received royalties from Up to Date.

Dr. Kwon reports that he has received NIH funding for which he has served as Principal Investigator (R21HL140432).


Kwon Y, Mehra R. Obstructive sleep apnea and atrial fibrillation: honing in on race-specific susceptibilities. J Clin Sleep Med. 2018;14(9):1459–1461.



Chugh SS, Havmoeller R, Narayanan K, et al. Worldwide epidemiology of atrial fibrillation: a Global Burden of Disease 2010 Study. Circulation. 2014;129(8):837–847. [PubMed]


Morillo CA, Banerjee A, Perel P, Wood D, Jouven X. Atrial fibrillation: the current epidemic. J Geriatr Cardiol. 2017;14(3):195–203. [PubMed Central][PubMed]


Gami AS, Pressman G, Caples SM, et al. Association of atrial fibrillation and obstructive sleep apnea. Circulation. 2004;110(4):364–367. [PubMed]


Kanagala R, Murali NS, Friedman PA, et al. Obstructive sleep apnea and the recurrence of atrial fibrillation. Circulation. 2003;107(20):2589–2594. [PubMed]


Ng CY, Liu T, Shehata M, Stevens S, Chugh SS, Wang X. Meta-analysis of obstructive sleep apnea as predictor of atrial fibrillation recurrence after catheter ablation. Am J Cardiol. 2011;108(1):47–51. [PubMed]


Gami AS, Hodge DO, Herges RM, et al. Obstructive sleep apnea, obesity, and the risk of incident atrial fibrillation. J Am Coll Cardiol. 2007;49(5):565–571. [PubMed]


Kwon Y, Gharib SA, Biggs ML, et al. Association of sleep characteristics with atrial fibrillation: the Multi-Ethnic Study of Atherosclerosis. Thorax. 2015;70(9):873–879. [PubMed Central][PubMed]


Kwon Y, Koene RJ, Johnson AD, Lin GM, Ferguson JD. Sleep, sleep apnea and atrial fibrillation: questions and answers. Sleep Med Rev. 2018;39:134–142. [PubMed]


Mehra R, Benjamin EJ, Shahar E, et al. Association of nocturnal arrhythmias with sleep-disordered breathing: the Sleep Heart Health Study. Am J Respir Crit Care Med. 2006;173(8):910–916. [PubMed Central][PubMed]


Stevenson IH, Teichtahl H, Cunnington D, Ciavarella S, Gordon I, Kalman JM. Prevalence of sleep disordered breathing in paroxysmal and persistent atrial fibrillation patients with normal left ventricular function. Eur Heart J. 2008;29(13):1662–1669. [PubMed]


May AM, Blackwell T, Stone PH, et al. Central sleep-disordered breathing predicts incident atrial fibrillation in older men. Am J Respir Crit Care Med. 2016;193(7):783–791. [PubMed Central][PubMed]


Porthan KM, Melin JH, Kupila JT, Venho KK, Partinen MM. Prevalence of sleep apnea syndrome in lone atrial fibrillation: a case-control study. Chest. 2004;125(3):879–885. [PubMed]


Tung P, Levitzky YS, Wang R, et al. Obstructive and central sleep apnea and the risk of incident atrial fibrillation in a community cohort of men and women. J Am Heart Assoc. 2017;6(7):e004500[PubMed Central][PubMed]


Freitas LS, Drager LF. Gender and cardiovascular impact of obstructive sleep apnea: work in progress! J Thorac Dis. 2017;9(10):3579–3582. [PubMed Central][PubMed]


Ghazi L, Bennett A, Petrov ME, et al. Race, sex, age, and regional differences in the association of obstructive sleep apnea with atrial fibrillation: reasons for geographic and racial differences in stroke study. J Clin Sleep Med. 2018;14(9):1485–1493


Gbadebo TD, Okafor H, Darbar D. Differential impact of race and risk factors on incidence of atrial fibrillation. Am Heart J. 2011;162(1):31–37. [PubMed Central][PubMed]


O'Neal WT, Judd SE, Limdi NA, et al. Differential impact of risk factors in blacks and whites in the development of atrial fibrillation: the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. J Racial Ethn Health Disparities. 2017;4(4):718–724. [PubMed]


Netzer NC, Stoohs RA, Netzer CM, Clark K, Strohl KP. Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med. 1999;131(7):485–491. [PubMed]


Senaratna CV, Perret JL, Matheson MC, et al. Validity of the Berlin questionnaire in detecting obstructive sleep apnea: a systematic review and meta-analysis. Sleep Med Rev. 2017;36:116–124. [PubMed]


Tan A, Yin JD, Tan LW, van Dam RM, Cheung YY, Lee CH. Using the Berlin Questionnaire to predict obstructive sleep apnea in the general population. J Clin Sleep Med. 2017;13(3):427–432. [PubMed Central][PubMed]


Chen X, Wang R, Zee P, et al. Racial/ethnic differences in sleep disturbances: the Multi-Ethnic Study of Atherosclerosis (MESA). Sleep. 2015;38(6):877–888. [PubMed Central][PubMed]


Alonso A, Agarwal SK, Soliman EZ, et al. Incidence of atrial fibrillation in whites and African-Americans: the Atherosclerosis Risk in Communities (ARIC) study. Am Heart J. 2009;158(1):111–117. [PubMed Central][PubMed]


Rodriguez F, Stefanick ML, Greenland P, et al. Racial and ethnic differences in atrial fibrillation risk factors and predictors in women: findings from the Women's Health Initiative. Am Heart J. 2016;176:70–77. [PubMed]


Magnani JW, Norby FL, Agarwal SK, et al. Racial differences in atrial fibrillation-related cardiovascular disease and mortality: the Atherosclerosis Risk in Communities (ARIC) study. JAMA Cardiol. 2016;1(4):433–441. [PubMed Central][PubMed]


Pranathiageswaran S, Badr MS, Severson R, Rowley JA. The influence of race on the severity of sleep disordered breathing. J Clin Sleep Med. 2013;9(4):303–309. [PubMed Central][PubMed]


Rodriguez CJ, Soliman EZ, Alonso A, et al. Atrial fibrillation incidence and risk factors in relation to race-ethnicity and the population attributable fraction of atrial fibrillation risk factors: the Multi-Ethnic Study of Atherosclerosis. Ann Epidemiol. 2015;25(2):71–76. [PubMed]