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Volume 13 No. 04
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Scientific Investigations

Prevalence and Associations of Obstructive Sleep Apnea in South Asians and White Europeans with Type 2 Diabetes: A Cross-Sectional Study

Amin Amin, MRCS1; Asad Ali, FRCP2; Quratul A. Altaf, MRCP3; Milan K. Piya, MRCP, PhD4,5; Anthony H. Barnett, FRCP, MD1,3; Neil T. Raymond, MSc6; Abd A. Tahrani, MRCP, PhD1,3
1Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom; 2Department of Respiratory Medicine, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom; 3Department of Diabetes and Endocrinology, Heart of England NHS Foundation Trust, Birmingham, United Kingdom; 4Department of Diabetes, Derby Teaching Hospitals NHS Foundation NHS Trust, Derby, United Kingdom; 5Warwick Medical School, University of Warwick, Coventry, United Kingdom; 6Independent Epidemiology and Statistical Consultant, Epidemiology, Research Design and Statistical Consulting (ERDASC), Leicestershire, United Kingdom; 7Centre of Endocrinology, Diabetes and Metabolism, Birmingham Health Partners, Birmingham, United Kingdom

ABSTRACT

Study Objectives:

To assess and compare obstructive sleep apnea (OSA) prevalence in South Asians and White Europeans with type 2 diabetes mellitus (T2DM). Secondary aims included exploring possible causes for observed ethnic differences.

Methods:

A cross-sectional study of patients with T2DM recruited from secondary care diabetes clinics. OSA was defined as an apnea-hypopnea index (AHI) ≥ 5 events/h using home-based, multi-channel respiratory monitoring.

Results:

Two hundred thirty-four patients (105 South Asian and 129 White Europeans) were studied. The prevalence of mild, moderate, and severe OSA in South Asians was 36.2% (n = 38/105), 9.5% (n = 10/105), and 5.7% (n = 6/105) respectively. After adjustment, OSA was associated with a higher body mass index in South Asians. OSA was significantly less common in South Asians compared to White Europeans (51.4% [54/105] versus 75.2% [97/129], P < .001). OSA was also less severe in South Asians compared to White Europeans (median [interquartile range]: AHI 5.1 [1.4–11.5] versus 8.5 [5.0–20.7] events/h, P < .001; time spent with oxygen saturations < 90% 0.5 [0.0–2.9]% versus 4.0 [0.7–14.4]%, P < .001). Logistic regression showed that only obesity measures explained the ethnic differences in OSA.

Conclusions:

South Asians with T2DM are at considerable risk of OSA. OSA in South Asians was associated with obesity. However, OSA prevalence was lower in South Asians than in White Europeans. Obesity measures accounted for the observed ethnic differences. Examining factors contributing to ethnic differences will be important to inform screening and treatment strategies.

Citation:

Amin A, Ali A, Altaf QA, Piya MK, Barnett AH, Raymond NT, Tahrani AA. Prevalence and associations of obstructive sleep apnea in South Asians and White Europeans with type 2 diabetes: a cross-sectional study. J Clin Sleep Med. 2017;13(4):583–589.


INTRODUCTION

Obstructive sleep apnea (OSA) is very common in patients with and without type 2 diabetes mellitus (T2DM).13 The coexistence of OSA and T2DM is not surprising, considering that the two conditions share common risk factors such as obesity and age,4,5 and that OSA has been identified as an independent risk factor for the development of incident diabetes.6,7 In addition, longitudinal studies have shown that insulin resistance is an independent predictor of reported witnessed apnea.8

The reported prevalence of OSA in patients with T2DM varies considerably between studies (8.5% to 86%).921 These discrepancies may reflect differences in the population examined (such as the setting of care, sex, ethnicities, degree of obesity, etc.), the methods used to diagnose OSA (such as questionnaires, portable home-based devices, polysomnography), and the parameters and definitions used to diagnose OSA (the apnea-hypopnea index (AHI) versus oxygen desaturation index (ODI), cutoffs of 5, 10 or 15 events/h).1,22,23

BRIEF SUMMARY

Current Knowledge/Study Rationale: Obstructive sleep apnea (OSA) is known to be common in patients with type 2 diabetes mellitus (T2DM) but the prevalence of OSA in South Asians with T2DM is unknown.

Study Impact: We found that OSA is common in South Asians with T2DM, although less common than in White Europeans. Ethnic differences in OSA prevalence were mainly due to differences in obesity and fat distribution. Other factors contributing to ethnic differences, such as upper airway structure and anatomy, need to be examined to aid screening and treatment strategies.

People of South Asian origin are at increased risk of T2DM and cardiovascular disease compared with White Europeans. Diabetes in these individuals tends to develop at a younger age and at lower body mass index (BMI), probably related to the presence of more visceral fat compared to White Europeans with similar BMI.2426 These ethnic differences, as well as differences in genetics and craniofacial features,27 suggest that OSA prevalence might differ between these ethnicities. Although several studies examined the prevalence of OSA in White Europeans and Blacks with T2DM,9,10,13,15,18 the prevalence of OSA in South Asians with T2DM remains unknown. In addition, it is important to ascertain the prevalence of OSA in South Asians with T2DM considering that South Asians are at increased risk of cardiovascular disease.24

Because of the differences in obesity and fat distribution, we hypothesized that OSA prevalence will differ between South Asians and White Europeans with T2DM. It is difficult to predict the nature of these differences, however, as White Europeans generally have higher BMI than South Asians and South Asians are more prone to obesity-related metabolic consequences (such as dysglycemia and dyslipidemia) at a much lower BMI than White Europeans.25 In this study, the goal was to assess OSA prevalence in South Asians with T2DM and to compare this finding with White Europeans with T2DM. A secondary goal was to explore possible causes for observed ethnic differences.

METHODS

We conducted an observational cross-sectional study in South Asian and White European adults with T2DM, utilizing the population of our previously published study.17 Patients with respiratory disease (including previously diagnosed OSA [n = 8]) or end-stage renal disease, or any diagnosis of cancer were excluded. Patients were recruited consecutively from the outpatient general diabetes clinics of two United Kingdom hospitals (Birmingham Heartlands Hospital and Royal Stoke University Hospital) between 2009 and 2011. Patients are typically referred to the hospital clinics by their primary care physicians if glycemic targets are not achieved despite the use of multiple glucose lowering agents, or if recurrent hypoglycemia or advanced diabetes-related complications developed. The criteria used by primary care physicians to refer to the diabetes clinic were the same in South Asians and White Europeans.

Patients were approached in the waiting area before their appointment, with no prior knowledge of their medical condition(s) and regardless of whether they were newly referred or under long-term follow-up at the hospital clinic. We avoided any reference to snoring or sleeping disturbances during the recruitment process. Consent was obtained and self-determined ethnicity was collected using United Kingdom decennial census categories; South Asian patients had their family origins from India, Pakistan, or Bangladesh. Both the South Asians and White Europeans were recruited from the same diabetes centers. The project was approved by the Warwickshire Research Ethics Committee (REC number 08/H1211/145), and all patients provided written informed consent.

OSA was assessed by a single overnight home-based cardiorespiratory sleep study using a portable multi-channel device (Alice PDX, Philips Respironics, Netherlands) and scored manually in accordance with the American Academy of Sleep Medicine guidelines.28 AHI ≥ 5 events/h was consistent with the diagnosis of OSA.29 AHI ≥ 15 and ≥ 30 events/h was considered consistent with moderate and severe OSA, respectively. Hypopneas were defined as a drop in oxygen saturation by ≥ 4% and a signal drop by ≥ 30% in the airflow excursions obtained from the nasal cannula. OSA severity was also assessed based on the AHI, ODI (the number of oxygen desaturations of ≥ 4% per hour), the time spent with oxygen saturations < 90%, and the nadir oxygen levels during sleep. Sleep studies with fewer than 4 hours of adequate recordings were repeated and excluded if adequate recordings were not obtained (n = 30). Patients with predominantly central sleep apnea were excluded (2 patients). Epworth Sleepiness Scale (ESS) score ≥ 11 was consistent with excessive daytime sleepiness.30

Data analysis was performed using SPSS 21.0 software (SPSS Inc., Chicago, Illinois, United States). Data are presented as mean (standard deviation) or median (interquartile range). Independent continuous variables were compared using the Student t test or the Mann-Whitney U test. Categorical variables were compared using the chi-square test. To assess the associations between OSA (dichotomous categorical variable) or AHI (scale variable) (the dependent variables) and covariates, binary logistic and multiple linear regressions were used. To explore the possible underlying reasons for ethnic differences in OSA prevalence, logistic regression was used where OSA was the outcome measure, and ethnicity was one of the predictor variables in addition to other biologically plausible and relevant variables (such as age, sex, ethnicity, an adiposity measure, duration of diabetes, alcohol intake, and smoking). A similar model with AHI as the outcome measure instead of OSA and utilizing multiple linear regression was used. The AHI was used in the linear regression after the addition of a value of 1 (due to multiple values of 0), and then log-transformation to normalize data distribution as much as possible. In all the regression models, the Enter method was used. We assessed multicollinearity in both multiple linear and logistic regression models using simple correlations between variables plus the tolerance values, variance inflation factor, and the condition indices, and there was no evidence of multicollinearity in any of the models used. A value of P < .05 was considered significant.

RESULTS

A total of 266 patients with T2DM were recruited and had overnight sleep studies. Thirty-two patients were excluded (30 poor sleep study recordings and 2 patients with central sleep apnea), leaving 234 patients (105 South Asians and 129 White Europeans) for this analysis. The baseline characteristics of the South Asians and White Europeans included in the analysis are summarized in Table 1. White Europeans were older, weighed more, and had more smoking and alcohol intake than South Asians. In addition, the prescription of incretin-based therapy and some antihypertensive medications was greater in White Europeans than in South Asians. The differences outlined in Table 1 informed the selection of variables for the multivariable analysis.

Characteristics of the study population.

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Table 1

Characteristics of the study population.

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OSA Prevalence in South Asians and White Europeans T2DM

One hundred five South Asian patients with T2DM were included. The prevalence of OSA (AHI ≥ 5) was 51.4% (n = 54 of 105), with 15.2% (16 of 105) having moderate to severe OSA (Table 2). OSA was more common in White Europeans compared to South Asians with T2DM (75.2% [97 of 129] 95% confidence interval [CI] 67.8–82.7% versus 51.4% [54 of 105] 95% CI 41.8–61.0%, P < .001), mainly due to the very high prevalence of OSA in White European men compared to South Asian men with T2DM (Table 2). The difference in OSA prevalence between White Europeans and South Asians with T2DM was 23.8% (95% CI for difference 14.2 to 33.4%), indicating a substantial and significant difference despite having similar diabetes duration.

Comparison of obstructive sleep apnea parameters between South Asians and White Europeans with type 2 diabetes mellitus.

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Table 2

Comparison of obstructive sleep apnea parameters between South Asians and White Europeans with type 2 diabetes mellitus.

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OSA was more severe in White Europeans compared to South Asians with T2DM, as White Europeans had higher AHI, higher ODI, lower nadir oxygen saturation, higher ESS, and a higher proportion of time with oxygen saturation < 90% compared to South Asians (Table 2).

The prevalence of OSA (AHI ≥ 5) and moderate to severe OSA (AHI ≥ 15) was similar between South Asian men and women with T2DM (OSA: 54.1% [33 of 61] versus 47.7% [21 of 44], P = .52; moderate to severe OSA: 18% [11 of 61] versus 11.4% [5 of 44], P = .56 for men versus women, respectively). However, South Asian women had significantly higher BMI (32.6 ± 5.9 versus 29.2 ± 4.9 kg/m2, P = .002) and nonsignificantly higher waist circumference (107.4 ± 13.8 versus 104.6 ± 12.1 cm, P = .27) than South Asian men; South Asian men were older than South Asian women (56.8 ± 12.6 versus 51.4 ± 11.8 years, P = .028). These differences might contribute to the lack of higher prevalence of OSA in South Asian men than in South Asian women with T2DM.

The comparison of South Asian patients with and without OSA is summarized in Table 3. Patients with OSA had longer diabetes duration, higher ESS score, and were more obese than patients without OSA. Patients with and without OSA had similar glycemic control and blood pressure despite prescribing differences; patients with OSA were prescribed more antihypertensive medications and insulin compared to those without OSA. Lipid profile and cardiovascular disease was similar between groups, but patients with OSA had more past history of stroke/transient ischemic attacks.

Characteristics of South Asians with type 2 diabetes mellitus with and without obstructive sleep apnea.

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Table 3

Characteristics of South Asians with type 2 diabetes mellitus with and without obstructive sleep apnea.

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The effect of sex on OSA prevalence in South Asians and White Europeans is detailed in the supplemental material.

Possible Explanations for Ethnic Differences

After adjustment for age, sex, ethnicity, diabetes duration, alcohol intake, and smoking status (Nagelkerke R2 for the model 0.22), White European ethnicity remained associated with OSA (odds ratio 3.1, 95% CI 1.6–6.1, P = .001). After adding BMI to the model (Nagelkerke R2 for the model 0.31), the association between OSA and ethnicity was lost (odds ratio 1.5, 95% CI 0.7–3.3, P = .3) (Table 4). Similar results were obtained when waist circumference or neck circumference were added to the model instead of BMI (data not shown).

Binary logistic regression examining the effect of obesity on the relationship between ethnicity and obstructive sleep apnea.

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Table 4

Binary logistic regression examining the effect of obesity on the relationship between ethnicity and obstructive sleep apnea.

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Similarly, when a linear regression model was performed with log (AHI+1), ethnicity was not significantly associated with AHI when an obesity measure was added to the model (data not shown).

DISCUSSION

This is the first report to examine the prevalence of OSA in South Asians with T2DM and to compare the data with that in White Europeans from the same locality. We found that OSA was very common in South Asians with T2DM but less common and less severe in comparison with White Europeans. We also found that obesity was the major contributor to the higher OSA prevalence observed in White Europeans.

There are several reasons to support our belief that the study population is representative of the general South Asian and White European populations with T2DM attending secondary care. (1) Both ethnicities in our study live in the same compact geographical area and have similar deprivation scores. (2) The referral guidelines, agreed between diabetes specialists and primary care, are the same for both ethnicities. (3) We approached similar numbers of South Asians and White Europeans and the response rate was similar in the two ethnic groups (approximately 65%, excluding those who were not eligible to enter the study). (4) Our patients had characteristics (such as age, BMI, height, hemoglobin A1c level, history of cardiovascular disease, etc.) similar to those of patients in another report from a different region in the United Kingdom.31

This study is the first to report the prevalence of OSA in South Asians with T2DM; however, a small number of studies have examined the prevalence of OSA in the general population of South Asians and also in South Asians with metabolic syndrome. In South Asians without T2DM, the prevalence of OSA varied between 3.7% in a semiurban population to 19.5% in middle-aged urban men.3234 Although direct comparison with these studies is not possible because of differences in methodology and population characteristics, the higher prevalence of OSA in South Asians with T2DM in our study compared to the prevalence of OSA in the general South Asians population is consistent with many studies that showed a high prevalence of OSA in patients with T2DM.921

Two other studies compared the prevalence of OSA in South Asians and White Europeans in the context of the metabolic syndrome and/or obesity rather than diabetes, and the results were conflicting.35,36 In one, the prevalence of OSA was 28.3% and there was no difference between South Asians and White Europeans. This study was conducted in a primary care population, however, and utilized the Berlin Sleep questionnaire,36 whereas our study utilized home-based sleep studies offering more in-depth assessment of OSA. Another study reported a higher prevalence of OSA in South Asians compared to White Europeans (85% versus 66%), despite using the same methodology as ours in diagnosing OSA.35 There are several factors that may explain this discrepancy. The patients in this study were recruited from a weight management/bariatric clinic rather than a diabetes clinic. This is reflected by the higher BMI (mean BMI 46 kg/m2 and 49 kg/m2 for South Asians and White Europeans, respectively) compared with our study population who were recruited from a diabetes clinic. South Asians also formed a small proportion of the study population (13%) whereas in our study the South Asians and White Europeans populations were more balanced. In addition, the OSA data were collected as part of “routine care” and hence there is a possibility of “selection bias”; this is supported by the higher prevalence of T2DM in South Asians than in White Europeans in that study despite the fact that South Asians were only 13% of the study population (60% versus 33%). In addition, South Asians have been shown to have more visceral adiposity compared to White Europeans who have similar BMI,25,37 so the South Asians in the study by Leong et al.35 are likely to have more visceral adiposity than the White Europeans. It is not surprising that the OSA prevalence was higher in South Asians considering the strong association between OSA and visceral obesity.

When comparing the South Asians and White Europeans patients in our study, there were several differences in OSA-related risk factors, which might contribute to the ethnic differences observed. However, the regression models suggest that only differences in obesity were important in explaining the ethnic differences observed. In our study, in comparison with the South Asians, White Europeans were more obese based on BMI and waist circumference. Differences in obesity between the two ethnic groups are due to multiple factors relating to differences in genetics, physiology, culture, socioeconomic status, environment, and interactions between these variables as well as others that are not fully recognized.38 However, un-measured factors other than obesity might explain the ethnic differences observed in the study, such as differences in upper airway anatomy, or differences in the ventilator drive and chemosensitivity; such factors require further exploration.

Epidemiological studies have reported that OSA prevalence is two to three times higher in men than women.39 It has been suggested that sex hormones might play a role in these sex differences because men receiving testosterone replacement are at higher risk of OSA. Also, the prevalence of OSA in post-menopausal women is higher than those who are premenopausal, but hormone replacement therapy lowers this risk.5 Furthermore, hyperandrogenemia in women is associated with higher risk of OSA, which is lowered by oral contraceptive use.40 Differences in fat distribution, upper airway size and collapsibility, and ventilatory control between men and women have also been implicated in sex difference in OSA prevalence.41,42 However, our studies in South Asians with T2DM do not show any sex difference in OSA prevalence. In our study, South Asian women were more obese (based on BMI and waist circumference) than South Asian men and this, together with differences in adiposity distribution, might have contributed to the lack of sex difference. Clearly, further studies need to be done to properly understand and clarify these findings. Our study has several limitations. We have used portable home-based multi-channel respiratory studies rather than the gold standard of inpatient overnight polysomnography. However, the use of this type of device is common and validated in OSA research.43 The cross-sectional design of the study allows us to only describe associations rather than causality. There were significant differences in the population characteristics of South Asians and White Europeans patients with T2DM, and among patients with and without OSA. However, we have used linear and logistic regression models to account for those differences. In addition, these differences represent real life as South Asians and White Europeans patients with T2DM differ significantly in many metabolic and nonmetabolic parameters. Using a different approach of matching for a wide range of variables between South Asians and White Europeans would have influenced the external validity of our findings. The sample size of our study does not allow for extensive adjustments, but even adjusting for one variable (for example, any adiposity measure), for which the sample size is adequate, removed the association between ethnicity and OSA. We also cannot rule out bias caused by self-selection (ie, patients who believe that they have OSA might be more inclined to participate in the study). Such a bias is a problem in many of the studies examining the prevalence of OSA and might result in a higher prevalence of OSA in the study population. We have tried to minimize this possibility by not describing the symptoms of OSA to the potential study participants when approached in the outpatient clinic waiting area. Finally, although we found that obesity accounted for the observed differences in OSA prevalence between South Asians and White Europeans, other possible contributors such as upper airway anatomy, structure and collapsibility were not measured in this study.

Our study has several strengths. We are the first to report the prevalence of OSA in South Asians with T2DM, a population that is has been found to have increased cardiovascular disease. Our study compared the OSA prevalence between South Asians and White Europeans who were recruited from the same diabetes clinic, received the same standard of care, and lived in the same geographical area. We have used a portable multi-channel respiratory device to diagnose OSA, which allowed us a more in-depth assessment than other studies that used questionnaires or single-channel devices such as pulse oximetry. Our study population was well characterized and a large number of variables were collected for each study participant.

In conclusion, South Asian men and women with T2DM are at a high risk of having OSA. OSA in South Asians with T2DM was associated with obesity. Compared to South Asians with T2DM, OSA prevalence was higher and OSA was more severe in White Europeans with T2DM. The ethnic differences in OSA prevalence were mainly due to differences in obesity between South Asians and White Europeans with T2DM.

Clinicians should have a high index of suspicion for OSA in South Asians and White Europeans with T2DM. Prospective studies examining the effect of ethnicity on the natural history of OSA and factors contributing to ethnic differences are important, as they could inform screening and treatment strategies and help to identify new treatment targets. Interventional studies assessing the effect of OSA treatment on blood pressure and cardiovascular disease in South Asians and White Europeans with T2DM are needed.

DISCLOSURE STATEMENT

Dr. Tahrani is a clinician scientist supported by the National Institute for Health Research in the United Kingdom. The views expressed in this publication are those of the authors and not necessarily those of the National Health Service, the National Institute for Health Research or the Department of Health. Dr. Tahrani is the guarantor of the study. This was not an industry supported study. This study was funded by the National Institute for Health Research United Kingdom, via a research training fellowship (RTF/01/094) and clinician scientist award (CS-2013-13-029) to Dr. Tahrani. This funding body had no role in the design or the interpretation or the reporting of this study. Dr. Barnett has consulted for and has participated in the speakers' bureau for Eli Lilly, Novo Nordisk, Boehringer Ingelheim, AstraZeneca, Novartis, Sanofi-Aventis, Janssen, and Merck. Dr. Piya has received research support from Novo Nordisk Research Foundation. Dr. Tahrani receives royalties from Eli Lilly, Novo Nordisk, Boehringer Ingelheim, Sanofi-Aventis, and Bristol-Myers Squibb; and has received research support from Novo Nordisk Research Foundation. The other authors have indicated no financial conflicts of interest.

ABBREVIATIONS

AHI

apnea-hypopnea index

BMI

body mass index

CI

confidence interval

eGFR

estimated glomerular filtration rate

ESS

Epworth Sleepiness Scale

HbA1c

hemoglobin A1c

ODI

oxygen desaturation index

OSA

obstructive sleep apnea

T2DM

type 2 diabetes mellitus

ACKNOWLEDGMENT

The authors thank Dr. Fahmy Hanna, Mrs. Helen Hodgson, and Mrs. Rebecca Barakam for their help in recruitment.

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Supplemental Material

Supplemental Material

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