|Year : | Volume
| Issue : | Page :
Prevalence of risk for obstructive sleep apnea in patients with bipolar disorder
Natarajan Varadharajan, Sandeep Grover
Department of Psychiatry, Post Graduate Institute of Medical Education and Research, Chandigarh, India
|Date of Submission||10-Dec-2019|
|Date of Acceptance||08-Jun-2021|
|Date of Web Publication||19-Aug-2021|
Department of Psychiatry, Postgraduate Institute of Medical Education and Research, Chandigarh - 160 012
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Aim: To evaluate the prevalence of risk for obstructive sleep apnea (OSA) among patients with bipolar disorder (BD). Methodology: Eighty-seven patients with BD and 50 matched controls were assessed by using the Berlin questionnaire. Results: One-fifth of the patients with BD was found to be at high risk for OSA, compared to the 6% prevalence in the control group. Patients in high risk for OSA were more often females, had significantly higher body mass index, high waist circumference, and comorbid physical illnesses. In terms of pharmacotherapy, there was association of use of antipsychotics with higher risk of OSA at the trend level (p=0.052). Conclusion: The prevalence of high risk for OSA is significantly higher among patients with BD and higher prevalence is related to obesity and comorbid physical illnesses.
Keywords: Bipolar disorder, obstructive sleep apnea obesity, prevalence
Bipolar disorder (BD) is one of the leading causes of disabilities among the mental disorders, accounting for 9.9 million disability adjusted life years (DALYs) in 2013, explaining overall 0.4% of total DALYs and 1.3% of total years lost due to disability. Patients with BD have a higher prevalence of medical comorbidities such as diabetes mellitus, cardiovascular disorders, obesity, metabolic syndrome, and obstructive sleep apnea (OSA) when compared with the general population.,,,,,
Although a vast literature is available for insomnia, daytime sleepiness, circadian rhythm disturbances in patients with BD and how these contribute to poor quality of life, frequent relapses, and have adverse consequences for affective functioning, [8,9] relatively less is understood about OSA in patients with BD. A systematic review reported the prevalence of OSA to vary from 2.9% to 69%, with a median of 19.8% in clinical-based studies and a median of 6.9% in population-based studies. However, this review was limited to studies which assessed OSA using polysomnography (PSG). A recent meta-analysis reported a pooled prevalence of OSA in patients with BD in the clinical settings to be 24.5%, and this prevalence figure is comparable to clinical studies in the general population. However, it is important to note that most of these studies have been carried out in Western countries, which have a high prevalence of obesity, which can possibly influence the prevalence of OSA among patients with BD. There is a paucity of research in the Indian context with respect to the prevalence of risk for OSA among patients with BD. In this background, this study attempted to evaluate the prevalence of risk for OSA and its correlates among patients with BD.
| Methodology|| |
This cross-sectional study was carried out in the outpatient department of a tertiary care teaching hospital. To be included in the study, the patients with BD were required to be in clinical remission, i.e., Hamilton Depression Rating Scale (HDRS) and Young's Mania Rating Scale Patients (YMRS) score ≤7 and provided written informed consent.
Patients were excluded if they had comorbid psychiatric syndromes including intellectual disability and organic brain syndromes, sleep disorders before onset of BD, uncontrolled physical illnesses despite treatment, substance abuse or dependence (other than tobacco), on shift duties and irregular daytime work schedules, with recent (within 2 months prior to the study) international travel, pregnancy, childbirth, and bereavement.
Sociodemographic, clinical, and treatment details were obtained from the patients and their relatives, as well as the medical records. The severity of mood was assessed using YMRS and HDRS. Patients were asked to complete the Berlin Sleep Questionnaire Hindi version and Epworth Sleepiness Scale (ESS). Hypertension was defined as the systolic blood pressure (BP) of >140 mmHg or diastolic BP of 90 mmHg of OSA were compared or when the participants were on antihypertensive medications.
It is a screening instrument to ascertain the risk of having OSA and comprises of three categories of symptoms related to the risk of having OSA: Five questions are related to snoring and cessation of breathing in category 1, four questions are related to daytime sleepiness in category 2; there is a question about high BP and also a question about the body mass index (BMI) in category 3. Category 1/Category 2 is positive if the person scores 2 or more points for each category. Category 3 is positive if there is presence of hypertension (>140/90 mmHg or use of medication) or a BMI >30 kg/m2. Patients are classified as having a high risk for OSA if scores are positive on two or more categories. The Hindi version of the scale has a sensitivity of 89% and specificity of 58%. Positive predictive value of the instrument was 0.87, whereas the negative predictive value was 0.63. [13,15]
Epworth sleepiness scale
The ESS is an 8-item questionnaire which assesses daytime sleepiness. Patients are asked to rate their likelihood of falling asleep in a variety of situations on a 4-point scale (0–3). Total scores range from 0 to 24. A score >10 indicates clinically “significant daytime sleepiness.”
Data were analyzed using the Statistical Package for Social Sciences, Sixteenth version (SPSS-16). (SPSS Inc. Released 2007. SPSS for Windows, Version 16.0. Chicago, SPSS Inc.). The data were analyzed in the form of frequencies, percentage, mean, and standard deviation. Comparisons were done using the Chi-Square test and t-test.
| Results|| |
The present study included 87 patients of BD and 50 healthy controls. There was no significant difference between the two groups, in terms of demographic variables, except that, significantly higher proportion of those in the control group were educated beyond matric. In terms of anthropometric measures, compared to the healthy control group, patients of BD had significantly higher BMI [Table 1].
|Table 1: Demographic, clinical and anthropometric profiles of study groups|
Click here to view
Compared to the healthy controls, significantly higher proportions of patients with BD were considered to be at high risk for OSA [Table 1].
Demographic, clinical, and anthropometric variables associated with high risk of obstructive sleep apnea
When the patients of BD, at low and high risk were of OSA were compared, it was seen that patients at high risk were significantly more often females, had higher BMI, higher proportion of them had BMI ≥25, were shorter in height, were heavier in weight, had higher waist circumference, and had higher prevalence of comorbid physical illnesses [Table 2].
|Table 2: Comparison of demographic, clinical and anthropometric variables of patients at high and low risk of obstructive sleep apnea|
Click here to view
| Discussion|| |
This study aimed to evaluate the prevalence of risk for OSA among patients with BD and evaluate the factors associated with high risk for OSA.
In the present study, about one-fifth of the patients were found to be at high risk for OSA, and this was significantly higher than that observed in a matched healthy control group. Studies from the different parts of the world which have evaluated the risk using self-rated questionnaires in clinic based settings have reported prevalence to vary from 22% to 54.1%,,, whereas studies which have additionally used PSG to ascertain OSA, have reported prevalence of about 22%. [18,19] The findings of the present study are close to the lower end of the reported rates in the literature. This could be possibly due to the relatively lower BMI in our sample, compared to some of the previous studies, which have reported mean BMI of the study sample to range from 29.18 to 36.80 kg/m2,,, which is one of the important predictor of OSA.
In terms of risk factors, the present study suggests that female gender, higher BMI, higher body weight, higher waist circumference, and presence of comorbid physical illnesses are associated with high risk of OSA. Previous studies which have evaluated the factors associated with high risk of OSA have come up with inconsistent association with gender, with some reporting higher prevalence of high risk among females,,,,, whereas others have reported higher prevalence among males. The association of high risk for OSA with higher BMI is a well-known fact, with majority of the literature supporting the same.,,, This association suggests that clinicians managing patients with BD should routinely measure anthropometric measures in their patients and encourage them to lose weight by following dietary restrictions and regular physical exercises.
In the present study, continuation of an antipsychotic during the remission phase was associated with high risk of OSA. This association can be understood in light of the fact that atypical antipsychotics are associated with significant weight gain. Previous studies have also reported similar associations.,, Over the years, various treatment guidelines have started recommending atypical antipsychotics as pharmaco-prophylactic agents in the management of BD.,, However, these recommendations are based on the efficacy of the various antipsychotics, without considering the long term negative effect of the same on other outcomes. Association of ongoing antipsychotics (at the trend level) with higher risk of OSA suggests that a caution must be practiced while using antipsychotics in the maintenance phase in patients with BD and the same should be based on weighing all the pros and cons of the same.
Available data suggest association of higher residual depressive symptoms to be an important predictor for OSA. However, the present study do not support the same.
Our study had certain limitations. First, it was based on the convenient sample of patients attending our outpatient services. The present study was based on a screening instrument and the patients who were screened to be at high risk were not subjected to PSG, which is the gold standard for diagnosing OSA. As it was cross-sectional study, it is difficult to ascertain whether OSA predisposed to BD by altering sleep or vice versa, given the bidirectional relationship between OSA and depression. Although Berlin questionnaire is an effective tool among other screening tools in the clinical settings in which the benefit of high sensitivity outweighs the disadvantage of low specificity, it is inferior to the gold standard diagnostic strategy, i.e., PSG. The study group and the control group were not matched for BMI and obesity. Future studies must attempt to overcome these limitations.
| Conclusion|| |
The present study suggests that about one-fifth of the patients with BD are at high risk for OSA, which is significantly higher than that seen in the healthy control group. In terms of risk factors, female gender, higher BMI, higher body weight, higher waist circumference, and presence of comorbid physical illnesses and continuation of antipsychotics in the maintenance phase are associated with high risk of OSA.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Ferrari AJ, Stockings E, Khoo JP, Erskine HE, Degenhardt L, Vos T, et al.
The prevalence and burden of bipolar disorder: Findings from the Global Burden of Disease Study 2013. Bipolar Disord 2016;18:440-50.
Forty L, Ulanova A, Jones L, Jones I, Gordon-Smith K, Fraser C, et al.
Comorbid medical illness in bipolar disorder. Br J Psychiatry 2014;205:465-72.
Grover S, Malhotra N, Chakrabarti S, Kulhara P. Metabolic syndrome in bipolar disorders. Indian J Psychol Med 2012;34:110-8.
] [Full text]
Grover S, Nebhinani N, Chakrabarti S, Avasthi A, Basu D, Kulhara P, et al.
Cardiovascular risk factors among bipolar disorder patients admitted to an inpatient unit of a tertiary care hospital in India. Asian J Psychiatr 2014;10:51-5.
McElroy SL, Keck PE Jr. Obesity in bipolar disorder: An overview. Curr Psychiatry Rep 2012;14:650-8.
Kemp DE, Gao K, Chan PK, Ganocy SJ, Findling RL, Calabrese JR. Medical comorbidity in bipolar disorder: Relationship between illnesses of the endocrine/metabolic system and treatment outcome. Bipolar Disord 2010;12:404-13.
Stubbs B, Vancampfort D, Veronese N, Solmi M, Gaughran F, Manu P, et al.
The prevalence and predictors of obstructive sleep apnea in major depressive disorder, bipolar disorder and schizophrenia: A systematic review and meta-analysis. J Affect Disord 2016;197:259-67.
Harvey AG. Sleep and circadian rhythms in bipolar disorder: Seeking synchrony, harmony, and regulation. Am J Psychiatry 2008;165:820-9.
Gold AK, Sylvia LG. The role of sleep in bipolar disorder. Nat Sci Sleep 2016;8:207-14.
Gupta MA, Simpson FC. Obstructive sleep apnea and psychiatric disorders: A systematic review. J Clin Sleep Med 2015;11:165-75.
Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56-62.
Young RC, Biggs JT, Ziegler VE, Meyer DA. A rating scale for mania: Reliability, validity and sensitivity. Br J Psychiatry 1978;133:429-35.
Gupta R, Ali R, Dhyani M, Das S, Pundir A. Hindi translation of Berlin questionnaire and its validation as a screening instrument for obstructive sleep apnea. J Neurosci Rural Pract 2016;7:244-9.
] [Full text]
Johns MW. A new method for measuring daytime sleepiness: The Epworth sleepiness scale. Sleep 1991;14:540-5.
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;131:485-91.
Geoffroy PA, Micoulaud Franchi JA, Maruani J, Philip P, Boudebesse C, Benizri C, et al.
Clinical characteristics of obstructive sleep apnea in bipolar disorders. J Affect Disord 2019;245:1-7.
Soreca I, Levenson J, Lotz M, Frank E, Kupfer DJ. Sleep apnea risk and clinical correlates in patients with bipolar disorder. Bipolar Disord 2012;14:672-6.
Kelly T, Douglas L, Denmark L, Brasuell G, Lieberman DZ. The high prevalence of obstructive sleep apnea among patients with bipolar disorders. J Affect Disord 2013;151:54-8.
Mieczkowski BP, Oduguwa A, Kowatch RA, Splaingard M. Risk factors for sleep apnea in children with bipolar disorder. J Affect Disord 2014;167:20-4.
Soreca I, Buttenfield JA, Hall MH, Kupfer DJ. Screening for obstructive sleep apnea in patients with bipolar I disorder: Comparison between subjective and objective measures. Bipolar Disord 2015;17:345-8.
Geoffroy PA, Boudebesse C, Bellivier F, Lajnef M, Henry C, Leboyer M, et al.
Sleep in remitted bipolar disorder: A naturalistic case-control study using actigraphy. J Affect Disord 2014;158:1-7.
Chang ET, Chen SF, Chiang JH, Wang LY, Hsu CY, Shen YC. Risk of obstructive sleep apnea in patients with bipolar disorder: A nationwide population-based cohort study in Taiwan. Psychiatry Clin Neurosci 2019;73:163-8.
Romero-Corral A, Caples SM, Lopez-Jimenez F, Somers VK. Interactions between obesity and obstructive sleep apnea: Implications for treatment. Chest 2010;137:711-9.
Schwartz AR, Patil SP, Laffan AM, Polotsky V, Schneider H, Smith PL. Obesity and obstructive sleep apnea: Pathogenic mechanisms and therapeutic approaches. Proc Am Thorac Soc 2008;5:185-92.
Young T, Peppard PE, Taheri S. Excess weight and sleep-disordered breathing. J Appl Physiol (1985) 2005;99:1592-9.
Peppard PE, Young T, Palta M, Dempsey J, Skatrud J. Longitudinal study of moderate weight change and sleep-disordered breathing. JAMA 2000;284:3015-21.
Rohatgi R, Gupta R, Ray R, Kalra V. Is obstructive sleep apnea the missing link between metabolic syndrome and second-generation antipsychotics: Preliminary study. Indian J Psychiatry 2018;60:478-84.
] [Full text]
Wirshing DA, Pierre JM, Wirshing WC. Sleep apnea associated with antipsychotic-induced obesity. J Clin Psychiatry 2002;63:369-70.
Knechtle B, Economou NT, Nikolaidis PT, Velentza L, Kallianos A, Steiropoulos P, et al.
Clinical characteristics of obstructive sleep apnea in psychiatric disease. J Clin Med 2019;8:534.
Yatham LN, Kennedy SH, Parikh SV, Schaffer A, Bond DJ, Frey BN, et al.
Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) 2018 guidelines for the management of patients with bipolar disorder. Bipolar Disord 2018;20:97-170.
American Psychiatric Association. Guideline Watch: Practice Guideline for the Treatment of Patients with Bipolar Disorder. 2nd
ed. Washington DC: American Psychiatric Association; 2005.
Shah N, Grover S, Rao GP. Clinical practice guidelines for management of bipolar disorder. Indian J Psychiatry 2017;59:S51-66.
[Table 1], [Table 2]