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ORIGINAL ARTICLE
Year : 2021  |  Volume : 20  |  Issue : 3  |  Page : 206-211  

Prevalence of obstructive sleep apnea in diabetic patients


1 Department of Medicine, KGMU, Lucknow, Uttar Pradesh, India
2 Department of ENT, KGMU, Lucknow, Uttar Pradesh, India
3 Department of Respiratory Medicine, KGMU, Lucknow, Uttar Pradesh, India

Date of Submission21-May-2020
Date of Acceptance29-Sep-2020
Date of Web Publication17-Sep-2021

Correspondence Address:
Dr. Shyam Chand Chaudhary
Department of Medicine, KGMU, Lucknow - 226 003, Uttar Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/aam.aam_43_20

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   Abstract 


Context: Obstructive sleep apnea (OSA)-related hypoxemia stimulates release of acute-phase proteins and reactive oxygen species that exacerbate insulin resistance and lipolysis and cause an augmented prothrombotic and proinflammatory state which can leads to premature death. Aims: This study aims to study the prevalence of OSA in diabetic patients. Setting and Design: It was a cross-sectional study, done over a period of 1 year in a tertiary care hospital. Materials and Methods: A total of 149 type 2 diabetic patients were enrolled after taking written consent. All patients were subjected to STOP BANG questionnaire and patients falling in intermediate-high risk (score 3–8), were taken for overnight polysomnography to confirm the diagnosis of OSA (apnea hypopnea index ≥ 5). Statistical Analysis Used: Statistical Package for Social Sciences (SPSS) Version 21.0 statistical analysis software. Results: Fifty-five percent of our diabetic population were having OSA. The age of patients enrolled in the study ranged between 30 and 86 years and prevalence increases with an increase in age groups. Majority (61.7%) of our cases were males. Incremental trend in weight, body mass index (BMI), neck circumference, and waist circumference of OSA cases were found with increasing in severity of OSA. Mean levels of raised blood sugar and HbA1c were higher in severe OSA cases. Conclusions: OSA has a high prevalence in patients with type 2 diabetes mellitus. Patients with type 2 diabetes should be screened for OSA, even in the absence of symptoms, especially in individuals with higher waist circumference and BMI.

   Abstract in French 

Résumé
Contexte: L'hypoxémie liée à l'apnée obstructive du sommeil (AOS) stimule la libération de protéines de phase aiguë et d'espèces réactives de l'oxygène qui exacerber la résistance à l'insuline et la lipolyse et provoquer un état prothrombotique et pro-inflammatoire accru qui peut conduire à un décès. Objectifs: Cette étude vise à étudier la prévalence de l'AOS chez les patients diabétiques. Cadre et conception: il s'agissait d'une étude transversale, réalisée sur une période d'un an dans un hôpital de soins tertiaires. Matériels et méthodes: Un total de 149 patients diabétiques de type 2 ont été recrutés après avoir pris consentement écrit. Tous les patients ont été soumis au questionnaire STOP BANG et les patients à risque intermédiaire-élevé (score 3-8), ont été prise pour une polysomnographie nocturne pour confirmer le diagnostic d'AOS (index d'apnée hypopnée ≥ 5). Analyse statistique utilisée: statistique Package for Social Sciences (SPSS) Version 21.0 du logiciel d'analyse statistique. Résultats: Cinquante-cinq pour cent de notre population diabétique étaient souffrant d'AOS. L'âge des patients inclus dans l'étude variait entre 30 et 86 ans et la prévalence augmente avec l'augmentation des tranches d'âge. La majorité (61,7 %) de nos cas étaient des hommes. Tendance progressive du poids, de l'indice de masse corporelle (IMC), du tour de cou et du tour de taille des cas d'AOS ont été trouvés avec une augmentation de la sévérité de l'AOS. Les taux moyens de glycémie élevée et d'HbA1c étaient plus élevés dans les cas graves d'AOS. Conclusions: L'AOS a une prévalence élevée chez les patients atteints de diabète de type 2. Les patients atteints de diabète de type 2 doivent subir un dépistage de l'AOS, même en l'absence de symptômes, en particulier chez les personnes ayant un tour de taille et un IMC plus élevés.

Keywords: Apnea hypopnea index, body mass index, diabetes mellitus, obstructive sleep apnea, polysomnography, STOP-BANG questionnaire
Mots-clés: indice d'apnée hypopnée, indice de masse corporelle, diabète sucré, apnée obstructive du sommeil, polysomnographie, STOP BANG questionnaire


How to cite this article:
Singh A, Chaudhary SC, Gupta KK, Sawlani KK, Singh A, Singh AB, Verma AK. Prevalence of obstructive sleep apnea in diabetic patients. Ann Afr Med 2021;20:206-11

How to cite this URL:
Singh A, Chaudhary SC, Gupta KK, Sawlani KK, Singh A, Singh AB, Verma AK. Prevalence of obstructive sleep apnea in diabetic patients. Ann Afr Med [serial online] 2021 [cited 2021 Nov 29];20:206-11. Available from: https://www.annalsafrmed.org/text.asp?2021/20/3/206/326198




   Introduction Top


Diabetes mellitus (DM) and obstructive sleep apnea (OSA) syndrome share high prevalence in industrialized nations. Both are associated with obesity and other manifestations of metabolic syndrome, which partially explains the high coincidence. Patients with OSA are more often involved in accidents, the social life might be impaired, depression occurs, and cardiovascular mortality is independently increased from other known risk factors such as obesity. In a hospital-based study of urban men between 35 and 65 years from western India, the prevalence of OSA was 19.5%.[1]

Polysomonography is the gold standard noninvasive technique for the assessment of sleep apnea.[2],[3] However, recent studies showed a screening device can be used with excellent diagnostic accuracy in terms of high sensitivity and specificity. Treatment with continuous positive airway pressure lowers the number of nocturnal apneas and hypopneas and may decrease the morbidity and mortality.[4],[5] Several studies demonstrated an increased insulin resistance in patients with OSA and proposed that sleep disordered breathing is independently associated with type 2 DM (T2DM), a condition that is in part driven by insulin resistance. The presence of OSA seems to promote the development of DM and vice versa.[6]


   Materials and Methods Top


This cross-sectional study was conducted in the Department of Medicine in collaboration with Respiratory Medicine, Physiology and Department of ENT at a tertiary care hospital in Northern India over a period of 1 year from September 2018 to August 2019. After taking written consent, 149 patients having age > 18 years with T2DM, attending OPD or admitted to indoor medical wards were enrolled in the study. Exclusion criteria: Patients with any of the following conditions were excluded from the study; acute and unstable medical condition, for example- congestive heart failure, chronic renal failure, recent stroke, acute coronary syndrome, hypertension, liver disease, chronic obstructive pulmonary disease, asthma, acquired immune deficiency syndrome, hypothyroidism, depression, alcohol use, drug abuse, patient ≤18 years age, pregnancy, diagnosed neuromuscular disease, obvious airway disease, and history of maxillofacial and neck trauma surgery.

Methodology

All enrolled patients underwent detailed history (age, sex, underlying diseases, smoking, drinking, and exercise) and physical examination. We also measured the height, weight, neck circumference and waist circumference. Body mass index (BMI) was calculated and a BMI > 25 kg/m2 was used as a cut off for obesity. After clinical evaluation, all patients were advised for routine investigations including, complete hemogram, serum electrolytes (sodium and potassium), serum urea and creatinine, fasting lipid profile, blood sugar fasting and postprandial, HbA1c, thyroid profile, urine microalbumin, abdominal ultrasonography, and fundus examination. To assess the prevalence of OSA, STOP-BANG Questionnaire was used for screening purpose in each and every diabetic patients enrolled in the study. The STOP-BANG questionnaire is an 8-item questionnaire, each item scored as 1. STOP-BANG questionnaire includes Snoring, Tiredness during day time, Observed apnea, high blood Pressure, BMI, Age, Neck circumference and Gender (male). It has been shown that with a stepwise increase of the STOP-BANG score, the probability of OSA increases. The STOP-BANG questionnaire with a score ≥ 3 consistently demonstrated high sensitivity to detect OSA in different populations. In accordance with previous studies, we used a cut off value of 3. Diabetic patients with STOP-BANG score ≥3 were subjected for full night polysomnography.

Statistical analysis

The statistical analysis was done using SPSS Version 21.0 (IBM, Armonk, State-New York, Country-United States) statistical analysis software. The values were represented in number (%) and mean ± standard deviation. Group of the continuous variable was compared by student t-test for analysis of variance ANOVA and while discrete data were analyzed by Chi-square test. The level of significance “P” mentioned in the results were considered significant if P < 0.05. Ethical clearance and funding: This study was approved by institutional ethical committee and was not supported by any funding agency.


   Results Top


A total of 149 diabetic patients fulfilling the inclusion criteria were enrolled in the present study. All patients were screened through STOP-BANG questionnaire, and 100 patients who had score ≥ 3 were subjected to polysomnography and patients were divided into two groups based on apnea hypopnea index (AHI score) [Table 1].
Table 1: Polysomnography of diabetic patients with stopbang score ≥3

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Out of 100 patients who underwent polysomnography, 82 had AHI score ≥ 5 and diagnosed as OSA. Thus, the prevalence in our study population was 55%. OSA cases (82) were further classified in three subgroups based on their severity [Table 2].
Table 2: Severity of obstructive sleep apnea in our study population (n=82)

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The age of patients enrolled in the study ranged between 30 and 86 years and mean age was 63.42 ± 12.31 years. The difference in the mean age of OSA cases with different grades of severity was not found significant statistically. Proportion of diabetic patients with mild OSA was higher as compared to moderate and severe OSA in lower age groups, i.e., ≤50 years (19.2% vs. 17.6% and 12.8%) and 51–65 years (46.2% vs. 17.6% and 43.6%) while proportion of patients with moderate OSA was higher as compared to mild and severe OSA in the age group >65 years (64.7% vs. 34.6% and 43.6%) but this difference was not found to be statistically significant. Out of 149 diabetic patients enrolled in study 61.7% (92) were males and rest were females. Results demonstrate the high prevalence of OSA in diabetic males in comparison to females in all grades of severity. Although the proportion of male patients with severe OSA was higher as compared to that of mild OSA and moderate OSA (79.5% vs. 61.5% and 52.9%) this difference was not found to be significant statistically [Table 3].
Table 3: Association of demographic variables and severity of obstructive sleep apnea

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An incremental trend of increase in weight, BMI, neck circumference, and waist circumference was observed with an increase in severity of OSA, but this association was found to be statistically significant only for neck and waist circumference [Table 4].
Table 4: Association of anthropometric parameters and severity of obstructive sleep apnea

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The prevalence of OSA in subjects with BMI > 30 kg/m2 was 62.2% (51), 30.5% (25) with BMI 25–30 kg/m and 7.3% (6) with BMI < 25 kg/m2. Proportion of cases with mild OSA was higher as compared to moderate and severe OSA having normal BMI. Proportion of overweight was higher among moderate OSA as compared to mild and severe OSA and proportion of obese was higher among severe OSA as compared to mild and moderate OSA cases but this association was not found to be significant statistically. Although the proportion of diabetic patients with severe and moderate OSA was higher as compared to mild OSA having neck circumference >40 mm (46.2% vs. 29.4% and 15.3%) but this association was not found to be significant statistically [Table 5].
Table 5: Association of body mass index and neck circumference with severity of obstructive sleep apnea

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On comparing, the blood sugar and lipid levels among cases with different severity of OSA significant differences was observed for random blood sugar (RBS), hemoglobin A1C (HbA1c), and serum cholesterol levels, the rest of the parameters were found to be comparable. An increasing trend in RBS, HbA1c, and cholesterol levels was observed with an increase in severity of OSA [Table 6].
Table 6: Association of blood sugar and lipid levels with severity of obstructive sleep apnea

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Our study also showed that the patients who were taking treatment for diabetes either in the form of oral hypoglycemic agent/insulin, the grading of OSA was increased with the status of uncontrolled blood sugar [Table 7]. Nonproliferative diabetic retinopathy was significantly higher in severe OSA as compared to mild and moderate OSA [Table 8].
Table 7: Association of treatment history with severity of obstructive sleep apnea

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Table 8: Association of fundus examination and severity of obstructive sleep apnea

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   Discussion Top


A population-based survey from North India had estimated the13.7% prevalence of OSA.[7] In another study from Delhi the prevalence rates of OSA and OSAS in males were 13.4 and 4% respectively whereas in females, these were 5.6 and 1.5%, respectively.[8] In a hospital-based study from north India revealed an estimated prevalence of OSA and OSAS to be 4.4 and 2.4% in males, whereas it was 2.5 and 1% in females.[9] The reported prevalence rate of OSA in diabetic population ranged from 23% to 86%.[10] Most of the studies from India were done in normal population. In our present hospital-based cross-sectional study conducted in 149 diabetic patients, we had estimated the 55% prevalence of OSA. Out of these 55% (82) OSA patients, the majority (68.3%) of the OSA cases had moderate to severe levels of OSA, only 31.7% had a mild level of OSA. Chasens et al. found a very high incidence (65%) of undetected OSA in patients with T2DM.[11] Elmasry et al. also found a prevalence rate of OSA of 36% in patients with diabetes in comparison with 14.5% in controlled glycemic or euglycemic patients.[12]

Results of our study demonstrate the higher prevalence of OSA with increasing age. Our findings seem to be consistent with the results in a prior study by Einhorn et al. and Reddy et al. They showed in their study that the prevalence of OSA increases with the age, though age is not an independent risk factor for OSA.[9],[13]

Out of 149 diabetic patients enrolled in the study, 92 (61.7%) were males and their proportion were high in all grades of severity of OSA. The proportion of male patients with severe OSA was higher as compared to that of mild and moderate OSA, though this difference was not found to be significant statistically. The above findings were also supported by the study of Einhorn et al.[13] and the study of Foster et al.[6] They showed that males had a higher AHI than females.

It can be appreciated from this study that the prevalence as well severity increases with increasing BMI. This was supported by the study done by Einhorn et al. which concluded that OSA is more common in the population with higher BMI.[13] The above association is also supported by Grunstein et al. and Young et al.[14],[15] Foster et al. also did study over 306 participants on the prevalence of OSA among obese patients with type 2 diabetic patients. They found that BMI was the only significant predictor of severe OSA (odds ratio 1.1; 95% confidence index 1.0–1.2; P < 0.03). Independent of other variables, a 1-unit increase in BMI was associated with a 10% increase in the predicted odds of severe OSA.[6]

We found that there is a significant increase in the prevalence of OSA with an increase in neck circumference. This association was found to be significant statistically. Pineda et al. correlated neck circumference with the severity of OSA. They concluded that the neck circumference can be used to differentiate mild from moderate-to-severe OSA.[16] Cross-sectional analysis of Sleep Heart Health Study data show that, in middle-aged and older adults, moderate-to-severe OSA, as defined as an AHI greater than or equal to 15 events per hours, is independently associated with BMI and neck circumference.

We have tried to show the relationship between blood sugar levels with the prevalence of OSA. The mean fasting blood sugar in mild OSA was 183 ± 49.26, in moderate OSA, it was 188 ± 40.69 and in severe OSA it was 208 ± 48.65. It was observed in the study that as the fasting blood sugar was increasing, so was the severity of OSA increasing. There is growing evidence in support of an independent association between OSA and impaired glucose metabolism by the study of Pamidi et al.[17] The above findings were also supported by the study of McNicholas et al.[18]

The mean HbA1C in mild OSA was 8.8 ± 1.7, in moderate OSA, it was 10.26 ± 1.59 and in severe OSA, it was 12.37 ± 1.84. We can clearly appreciate that as the higher the value of HbA1C, the severity of OSA increases. The following relation is supported by the study Bhimwal et al.[19] According to Aronsohn et al., the severity of OSA did not increase significantly with increased HbA1C which is contrary to the present study.[20]

In our study, an increasing trend in RBS, HbA1c, and cholesterol levels was observed with an increase in severity of OSA. Nonproliferative diabetic retinopathy was significantly higher in severe OSA as compared to mild and moderate OSA.

Limitations

Although the sensitivity of STOP BANG Questionnaire in screening of OSA is very high (90%, 94%, and 96% to detect any OSA [AHI ≥ 5], moderate-to-severe OSA [AHI ≥ 15], and severe OSA [AHI ≥ 30], respectively) but gold standard polysomnography should be done in all diabetic patients who fulfill the inclusion and exclusion criteria to generate more accurate data. Small sample size in our study can be the limitation since the prevalence study should be conducted over a large population size. Obesity is itself a risk factor for OSA and obesity leads to insulin resistance so, obesity acts as confounding factor in our study.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

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Vijayan VK, Patial K. Prevalence of obstructive sleep apnoea syndrome in Delhi, India. Chest 2006;130:92S.  Back to cited text no. 1
    
2.
Erman MK, Stewart D, Einhorn D, Gordon N, Casal E. Validation of the ApneaLink for the screening of sleep apnea: A novel and simple single-channel recording device. J Clin Sleep Med 2007;3:387-92.  Back to cited text no. 2
    
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Marin JM, Carrizo SJ, Vicente E, Agusti AG. Long-term cardiovascular outcomes in men with obstructive sleep apnoea-hypopnoea with or without treatment with continuous positive airway pressure: An observational study. Lancet 2005;365:1046-53.  Back to cited text no. 3
    
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Harsch IA, Schahin SP, Radespiel-Tröger M, Weintz O, Jahreiss H, Fuchs FS, et al. Continuous positive airway pressure treatment rapidly improves insulin sensitivity in patients with obstructive sleep apnea syndrome. Am J Respir Crit Care Med 2004;169:156-62.  Back to cited text no. 4
    
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Foster GD, Sanders MH, Millman R. Obstructive sleep apnoea among obese patients with type 2 diabetes. Diabetes Care 2009;32:1017-9.  Back to cited text no. 10
    
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Chasens ER, Weaver TE, Umlauf MG. Insulin resistance and obstructive sleep apnea: Is increased sympathetic stimulation the link? Biol Res Nurs 2003;5:87-96.  Back to cited text no. 11
    
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Elmasry A, Lindberg E, Berne C, Janson C, Gislason T, Awad Tageldin M, et al. Sleep-disordered breathing and glucose metabolism in hypertensive men: A population-based study. J Intern Med 2001;249:153-61.  Back to cited text no. 12
    
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Einhorn D, Stewart DA, Erman MK, Gordon N, Philis-Tsimikas A, Casal E. Prevalence of sleep apnea in a population of adults with type 2 diabetes mellitus. Endocr Pract 2007;13:355-62.  Back to cited text no. 13
    
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Grunstein R, Wilcox I, Yang TS, Gould Y, Hedner J. Snoring and sleep apnoea in men: Association with central obesity and hypertension. Int J Obes Relat Metab Disord 1993;17:533-40.  Back to cited text no. 14
    
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Pineda E, Fitelson D, Rahill J, O'Donnell A, Kuru T, Waldhorn R, et al. Assessing the adjusted neck circumference sleep apnea screening score in patients undergoing polysomnography for suspected sleep apnea. Chest 2011;140:812A.  Back to cited text no. 16
    
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Pamidi S, Aronsohn RS, Tasali E. Obstructive sleep apnea: Role in the risk and severity of diabetes. Best Pract Res Clin Endocrinol Metab 2010;24:703-15.  Back to cited text no. 17
    
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McNicholas WT, Bonsigore MR, Management Committee of EU COST ACTION B26. Sleep apnoea as an independent risk factor for cardiovascular disease: Current evidence, basic mechanisms and research priorities. Eur Respir J 2007;29:156-78.  Back to cited text no. 18
    
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Bhimwal RK, Makwana M, Jangid R, Bhati RL. To study the prevalence of obstructive sleep apnoea in type 2 diabetes patients in Western Rajasthan, India. Int J Adv Med 2017;4:894.  Back to cited text no. 19
    
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Aronsohn RS, Whitmore H, Van Cauter E, Tasali E. Impact of untreated obstructive sleep apnea on glucose control in type 2 diabetes. Am J Respir Crit Care Med 2010;181:507-13.  Back to cited text no. 20
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8]



 

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