Excessive daytime sleepiness among patients with metabolic syndrome

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ORIGINAL ARTICLE

Excessive daytime sleepiness among patients with metabolic syndrome

Adel Salah Bediwy

^a,^*

, Yousuf M. Mansour

^a

, Ehab A. Abo Ali

^b

aChest Department, Faculty of Medicine, Tanta University, Egypt

bPublic Health and Community Medicine Department, Faculty of Medicine, Tanta University, Egypt

Received 23 July 2015; accepted 9 August 2015 Available online 21 August 2015

KEYWORDS

Excessive day time sleepiness;

Metabolic syndrome;

Sleep apnea

Abstract Background: Metabolic syndrome is a medical disorder that predisposes to cardiovascular diseases. Excessive daytime sleepiness (EDS) is a common finding in patients with metabolic syndrome.

Aim: To assess the presence of EDS among subjects with metabolic syndrome and to find its correlations with apnea hypopnea index (AHI), Hamilton depression rating score (HDRS), body mass index (BMI), age and fasting plasma glucose (FPG).

Method: 76 patients with metabolic syndrome were evaluated for EDS by Epworth sleepiness score (ESS) and for sleep apnea by polysomnography.

Results: 22 subjects (28.9%) had EDS, 37 subjects (48.7%) had sleep apnea and 28 subjects (36.8%) had depression. ESS showed no significant association with AHI while it showed significant associations with each of HDRS, BMI, age and FPG.

Conclusions: Other explanations of EDS in subjects with metabolic syndrome can be related to obesity, depression, or diabetes rather than to sleep apnea. Subjects with metabolic syndrome should be screened for EDS regardless of sleep apnea.

Ó2015 The Authors. Production and hosting by Elsevier B.V. on behalf of The Egyptian Society of Chest Diseases and Tuberculosis. This is an open access article under the CC BY-NC-ND license (http://

creativecommons.org/licenses/by-nc-nd/4.0/).

Introduction

Metabolic syndrome is a combination of the medical disorders that, when present together, increase the risk of developing cardiovascular disease and diabetes. Some studies have shown the prevalence in the USA to be an estimated 25% of the population, and prevalence increases with age[1].

Metabolic syndrome, also known as insulin resistance syndrome or syndrome X, is recognized as a constellation of obesity, glucose intolerance, dyslipidemia, and hypertension. Over the past several decades, there has been a substantial increase in the prevalence of metabolic syndrome, coinciding with the increased prevalence of obesity[2].

Obstructive sleep apnea (OSA) is a clinical condition char- acterized by recurrent episodes of complete obstruction (apnea) or partial obstruction (hypopnea) of the upper airway, leading to increased negative intrathoracic pressure, sleep fragmentation, and intermittent hypoxia during sleep[3].

* Corresponding author.

E-mail address:[email protected](A.S. Bediwy).

Peer review under responsibility of The Egyptian Society of Chest Diseases and Tuberculosis.

H O S T E D BY

The Egyptian Society of Chest Diseases and Tuberculosis

Egyptian Journal of Chest Diseases and Tuberculosis

www.elsevier.com/locate/ejcdt www.sciencedirect.com

http://dx.doi.org/10.1016/j.ejcdt.2015.08.010

0422-7638Ó2015 The Authors. Production and hosting by Elsevier B.V. on behalf of The Egyptian Society of Chest Diseases and Tuberculosis.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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In the United States, the prevalence of OSA is estimated to be 3–7% in men and 2–5% in women. Among patients with a body mass index greater than 28, OSA is present in 41%[4,5].

OSA has implications beyond disrupted sleep. It is increas- ingly recognized as an independent risk factor for cardiac, neu- rologic, and peri-operative morbidities[6]. It is also associated with high incidence of some psychiatric disturbances such as depression[7].

Some studies showed that 50–60% of people who are obese and patients with the metabolic syndrome have OSA[8]. The prevalence of OSA is even higher in obese patients with diabetes mellitus[9].

Excessive daytime sleepiness may be related to the extent of adiposity, the distribution of adiposity, or metabolic, inflammatory, physical, mental, or psychological disturbances expe- rienced by obese subjects. It may be also related to the increased incidence of OSA in these patients[10].

Excessive daytime sleepiness compromises quality of life due to the impairment it causes in work performance, interper- sonal relations, and cognitive and neuropsychological func- tions, in addition to causing a higher risk of car accidents, and metabolic and cardiovascular diseases[11–14].

So the presence of excessive daytime sleepiness in subjects with metabolic syndrome has to be assessed and explained.

The aim of this study was to assess excessive daytime sleepiness in subjects with metabolic syndrome and to find the correlation between daytime sleepiness as measured by the Epworth sleepiness scale and both apnea hypopnea index, Hamilton Depres- sion Rating Scale, body mass index, waist circumference, age and fasting plasma glucose (FPG).

Subjects and methods

Patients who presented to outpatient clinics in Tanta Univer- sity Hospitals and had the diagnostic criteria of the metabolic syndrome according to the International Diabetes Federation (IDF) consensus worldwide definition[15]and who agreed to share in the study were included. Study sample was taken with a convenient sample technique until recruitment of 76 subjects was achieved in a period of six months. The study protocol was approved by the local ethics committee of Tanta Faculty of Medicine and written consents were signed by all the participants.

The IDF consensus worldwide definition of the metabolic syndrome [15] 2006 is: Central obesity (defined as increased waist circumference with ethnicity-specific values) and any two of the following (NB: If BMI is >30 kg/m², central obesity can be assumed and waist circumference does not need to be measured):

Raised triglycerides: >150 mg/dL (1.7 mmol/L), or specific treatment for this lipid abnormality.

Reduced HDL cholesterol: <40 mg/dL (1.03 mmol/L) in males, <50 mg/dL (1.29 mmol/L) in females, or specific treatment for this lipid abnormality.

Raised blood pressure (BP): systolic BP > 130 or diastolic BP > 85 mmHg, or treatment of previously diagnosed hypertension.

Raised fasting plasma glucose (FPG): >100 mg/dL (5.6 mmol/L), or previously diagnosed type 2 diabetes.

Exclusion criteria: We excluded patients with thyroid or other endocrinal disorders other than diabetes mellitus, asthma, COPD, restrictive lung disease, lung cancer, sarcoido- sis, chronic liver or kidney diseases, and previous psychiatric diagnosis or who were on antidepressant medications. Patients with alcohol or drug addiction, cerebral infarction, unstable angina, myocardial infarction during the previous 3 months, and congestive heart failure were also excluded.

The followings were carried for all participants:

Thorough history taking: with special care to other co-morbidities, drug use, smoking status, substance and alcohol abuse.

Examination: general and chest examination to exclude patients with exclusion criteria, assess body mass index (BMI), vital signs, and waist circumference.

Routine laboratory tests: to help diagnosing metabolic syndrome, and to exclude patients with exclusion criteria.

Chest X ray postero–anterior view.

Epworth sleepiness scale: was used to assess daytime sleepiness. Patients rated the likelihood of falling asleep in eight specific situations on a 0–3 scale, with 0 meaning no chance at all of falling asleep, and 3 representing a high chance of falling asleep. Thus, the scale goes from 0 to 24. A score of ten suggests excessive daytime sleepiness[16].

The Hamilton Depression Rating Scale (HDRS): it is an inventory employed to detect and identify the intensity or severity of the signs and symptoms of depression; 17 questions are divided into two categories. The first category consists of nine questions scored on a five-point scale; the second category consists of eight questions rated on a three-point scale. The total score is computed reflecting the degree of symptom severity. A score of >10 indicates impairment[17].

All patients underwent overnight polysomnography using the AliceÒ5 Polysomnography System (Philips Respiron- ics, Murraysville, PA) with Alice Sleepware Software. This polysomnogram consisted of overnight recording of left and right electrooculogram, chin electromyogram, left and right tibialis anterior electromyogram, central and occipital EEG, electrocardiogram, airflow measurement, body posi- tion sensor, snoring sensor and microphone, respiratory effort belt (abdominal and thoracic), and pulse oximetry.

The sleep study began around 11 pm and the duration of the study was at least 5 h. The patients were instructed to avoid sleeping during the daytime before the study and to avoid alcohol, sedatives, hypnotics, and other medicines affecting sleep.

Statistical analysis: It was performed with the Statistical Package for Social Sciences (SPSS), version 16.0 (Chicago, IL, USA). Data are presented as mean (±SD) values. Appro- priate test of significance was used when needed. Significant statistical difference was considered whenp< 0.05.

Results

The study included 76 subjects with metabolic syndrome who agreed to share in the study. Demographic, anthropometric and clinical characteristics of the studied subjects are shown inTable 1.

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Epworth sleepiness score (ESS) values showed no significant association with apnea hypopnea index (AHI) while it showed significant association with both HDRS, BMI and waist circumference, age and fasting plasma glucose (FPG) (p< 0.05) (Table 2).

AHI showed significant positive correlations with HDRS, BMI and waist circumference, age and FPG (Table 3).

It was noticed that AHI values in subjects having excessive daytime sleepiness and those without excessive daytime sleepiness were 17.3 ± 15.8 and 12.1 ± 13.4 respectively without any statistically significant difference (t= 1.35 andp= 0.19).

Discussion

This study has shown that Epworth sleepiness score (ESS) in subjects with metabolic syndrome was 8.263 ± 5.7. The

normal community mean (±standard deviation) ESS is 4.6

± 2.8[10]. This means that subjects with metabolic syndrome have more excessive daytime sleepiness (EDS) than the general population. Also, we found that about half of subjects with metabolic syndrome have polysomnographic evidence of sleep apnea with a mean apnea hypopnea index (AHI) of 13.62 events per hour.

Table 1 Demographic, anthropometric and clinical characteristics of the studied group.

Characteristics Study group (n= 76)

No. %

Age in years 43.03 ± 14.32

18– 15 19.7

30– 15 19.7

40– 16 21.1

50– 17 22.4

P60 13 17.1

Gender

Males 40 52.6

Females 36 47.4

BMI

33.8 ± 1.9 kg/m²

30–34.9 44 57.9

P35 32 42.1

Waist circumference

High risk 44 57.9

Low risk 32 42.1

ESS 8.3 ± 5.7

Positive 22 28.9

Negative 54 71.1

AHI 13.62 ± 14.2

Nil 39 51.3

Mild (5-) 8 10.5

Moderate (15-) 16 21.1

Severe (P30) 13 17.1

HDRS 15.34 ± 13.77

Positive 28 36.8

Negative 58 63.2

FPG

158.89 ± 44.8 mg%

>100 mg/dL 45 59.2

6100 mg/dL 31 40.8

BMI: body mass index. ESS: Epworth sleepiness score. AHI:

Apnea hypopnea index. HDRS: Hamilton depression rating scale.

FPG: Fasting plasma glucose.

Table 2 Epworth sleepiness score (ESS) in relation to demographic, anthropometric and clinical characteristics of the studied group.

Characteristics Epworth sleepiness score (ESS) Test of significance Positive

(n= 22)

Negative (n= 54)

v² p

No. % No. %

Age in years

<40 4 18.2 26 48.1 5.875

P40 18 81.8 28 51.9 0.015^*

Gender

Males 12 54.5 28 51.9 0.045

Females 10 45.5 26 48.1 0.831

BMI

30–34.9 6 27.3 38 70.4 11.911

P35 16 72.7 16 29.6 0.001^*

Waist circumference

High risk 17 77.3 27 50 4.77

Low risk 5 22.7 27 50 0.029^*

AHI

Nil 10 45.5 29 53.7

Mild 2 9.1 6 11.1 0.88

Moderate 5 22.7 11 20.4 0.83

Severe 5 22.7 8 14.8

HDRS

Positive 13 59.1 15 27.8 6.587

Negative 9 40.9 39 72.2 0.010^*

FPG

>100 mg/dL 17 77.3 28 51.9 4.183

6100 mg/dL 5 22.7 26 48.1 0.041^*

BMI: body mass index. AHI: Apnea hypopnea index. HDRS:

Hamilton depression rating scale. FPG: Fasting plasma glucose.

* Significant statistical difference.

Table 3 Correlations between AHI and other studied parameters.

Correlations between AHI and r p

HDRS 0.47 <0.001^*

BMI 0.77 <0.001^*

Waist circumference 0.755 <0.001^*

Age 0.404 <0.001^*

FPG 0.364 0.001^*

BMI: body mass index. AHI: Apnea hypopnea index. HDRS:

Hamilton depression rating scale. FPG: fasting plasma glucose.

* Significant.

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In a study done by Parish et al. metabolic syndrome was found in 60% of obstructive sleep apnea (OSA) patients[18], while it was found in 51.2% of OSA patients by Bonsignore et al.[19]. Drager et al. found the prevalence of sleep apnea among metabolic syndrome subjects to be 60%[8].

Visceral obesity/insulin resistance may be the principal culprit leading to sleep apnea, which, in turn, may accelerate these metabolic abnormalities, possibly through progressive elevation of stress hormones and cytokines. Furthermore, daytime sleepiness is frequently associated with obesity, diabetes type 2, and insulin resistance independent of sleep-disordered breathing[20].

Both metabolic syndrome and sleep apnea may be mecha- nistically linked through a number of possible pathways.

OSA is associated with alterations in the hypothalamic–pitui tary–adrenal axis that may promote the metabolic syndrome.

The hypoxia associated with sleep apnea triggers an oxidative stress that may promote development of metabolic syndrome.

Multiple inflammatory markers and mediators, including nuclear factor kappa B (NF-jB), C-reactive protein (CRP), tumor necrosis factor a (TNF-a), and interleukin 6 (IL-6), are elevated in patients with OSA and may play a role in the development of metabolic syndrome[21].

In our study, ESS showed no significant association with AHI. Also, AHI showed no significant difference between subjects having EDS and those without. These findings may sug- gest that EDS in subjects with metabolic syndrome may not be caused by sleep apnea and other factors may cause it.

Daytime sleepiness is a critical symptom of sleep apnea but is not pathognomonic. A number of sleep, medical, and mental diseases and disorders include this symptom[20]. It is known also that traditional risk factors for OSA such as EDS may not be present in a significant proportion of obese patients[22].

Bixler et al. reported that when diagnosing a case with a complaint of EDS, sleep disturbance (e.g., due to sleep apnea) should not be considered the only cause. It appears that EDS is more strongly associated with mood factors as well as metabolic factors rather than with sleep-disordered breathing[23].

Dixon et al. found that there was no significant relationship between ESS score and AHI in obese individuals[10]. They concluded that EDS and obstructive sleep apnea are common disorders in obese subjects but seem to be largely unrelated. On the other hand, Bonsignore et al. found no difference in EDS between patients with and without metabolic syndrome[19].

In a trial to find an alternative cause of EDS in our studied subjects, we tried to find an association between both ESS and AHI and the other studied parameters. We found that both ESS and AHI independently had significant associations with BMI, waist circumference, FPG and age. So we can attribute EDS in subjects with metabolic syndrome to one or more of the following factors: obesity, depression, advanced age and presence of diabetes rather than having sleep apnea.

Metabolic syndrome, insulin resistance, and obesity were found to be stronger determinants of sleepiness compared to apnea/hypopnea index[20].

Bixler et al. found that depression was the most significant risk factor for EDS followed by BMI, age, typical sleep duration, diabetes, smoking, and finally sleep apnea[23]. They suggested that patients with a complaint of EDS should be thoroughly assessed for depression and obesity/diabetes independent of whether sleep-disordered breathing is present.

Barcelo et al. found that OSA patients with EDS had higher plasma levels of glucose and evidence of insulin resistance compared with patients without EDS or healthy controls[24].

Dixon et al. reported that EDS was related to older age, male gender, smoking, type 2 diabetes, symptoms of depression, and poor quality of life [19]. Depression is a common finding in patients with OSA who should be screened carefully for depressive disorders[7].

The inflammatory cytokines TNF-a, interleukin-1b (IL-1b), and IL-6 are involved in physiological sleep regulation, and that their increased secretion or exogenous administration to humans is associated with sleepiness and fatigue[25,26].

Limitations of the study

ESS does not assess sleepiness objectively, and lack of multiple sleep latency test data is a limitation of our study. Any- way, the widespread use of ESS and its strong validation through many published studies encouraged us to use it.

This study is cross-sectional, and thus, causation cannot be directly tested.

Conclusions and recommendations

Lack of association between excessive daytime sleepiness (EDS) and AHI in subjects with metabolic syndrome was noticed in our study, so other explanations of EDS in this category of patients can be related to obesity, depression, or diabetes rather than to sleep apnea. Subjects with metabolic syndrome should be screened for EDS regardless of sleep apnea. Weight reduction and proper blood glucose control can reduce the occurrence of EDS in patients with metabolic syndrome.

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