Abstract
Background:
The metabolic syndrome (MetS), a cluster of cardiovascular risk factors, is associated with obstructive sleep apnea (OSA). OSA is a major contributor to cardiac, cerebrovascular, and metabolic disorders as well as to premature death.
Materials and Methods:
This cross-sectional study was done for 1 year in 103 patients of MetS diagnosed by the International Diabetes Federation criteria. All patients were subjected to the STOP-Bang questionnaire, and they were classified into low, intermediate, and high risks depending on the score. Patients falling in intermediate-high risk (score 3–8) were taken for overnight polysomnography to confirm the diagnosis of OSA (apnea–hypopnea index [AHI] ≥5) and were considered Group I. Patients with STOP-Bang score ≤2 or score ≥3 with AHI <5 were considered Group II (non-OSA).
Results:
Out of 103 MetS patients enrolled in the study, only 70 (68.0%) were diagnosed with OSA, so the prevalence of OSA in MetS patients was 68%. The majority of the OSA cases had moderate-to-severe OSA (68.5%), and only 31.4% had mild OSA. The age of patients enrolled in the study ranged between 29 and 78 years, and the mean age of patients was 54.8 ± 9.4 years. Out of 103 MetS enrolled in the study, 59 (57.3%) were male and the rest were female, so the prevalence of severe OSA was higher in males than in females. The prevalence increases with an increase in age groups. Weight, body mass index (BMI), circumference, and waist circumference (WC) of cases of OSA were found to be significantly higher as compared to that of non-OSA. An incremental trend of increase in weight, BMI, neck circumference, and WC was observed with the increase in the severity of OSA. Patients of OSA as compared to non-OSA had significantly increased WC, blood pressure (BP), fasting, postprandial, random blood sugar, and triglyceride (TG) levels. A trend of increase in WC, BP fasting, postprandial, random blood sugar, and TG levels was associated with an increase in the severity of OSA. Snoring and daytime sleepiness were observed in a significantly higher proportion of OSA cases as compared to non-OSA cases.
Conclusions:
This study shows that OSA has a high prevalence in subjects with MetS. A high index of clinical suspicion is required for early diagnosis.
Keywords: Apnea–hypopnea index, body mass index, metabolic syndrome, obstructive sleep apnea
Résumé
Contexte:
Le syndrome métabolique (MetS), un ensemble de facteurs de risque cardiovasculaire, est associé à l’apnée obstructive du sommeil (AOS). L’AOS est un contributeur majeur aux troubles cardiaques, cérébrovasculaires et métaboliques ainsi qu’aux décès prématurés.
Matériels et méthodes:
ce Une étude transversale a été réalisée pendant 1 an chez 103 patients atteints de MetS diagnostiqués selon les critères de la Fédération internationale du diabète. Tous les patients étaient soumis au questionnaire STOP-Bang, et ils ont été classés en risques faibles, intermédiaires et élevés en fonction du score. Patients présentant un risque intermédiaire-élevé (score 3 à 8) ont été soumis à une polysomnographie nocturne pour confirmer le diagnostic d’AOS (apnée-hypopnée). [AHI] ≥5) et ont été considérés comme le groupe I. Les patients avec un score STOP-Bang ≤2 ou un score ≥3 avec un AHI <5 ont été considérés comme le groupe II (non-AOS).
Résultats:
Sur 103 patients atteints du MetS inclus dans l’étude, seuls 70 (68,0 %) ont reçu un diagnostic d’AOS, d’où la prévalence de l’AOS dans le MetS. les patients étaient de 68%. La majorité des cas d’AOS présentaient une AOS modérée à sévère (68,5 %), et seulement 31,4 % présentaient une AOS légère. L’âge des patients les patients inscrits à l’étude étaient âgés de 29 à 78 ans et l’âge moyen des patients était de 54,8 ± 9,4 ans. Sur 103 MetS inscrits au Dans l’étude, 59 (57,3 %) étaient des hommes et les autres étaient des femmes, de sorte que la prévalence de l’AOS sévère était plus élevée chez les hommes que chez les femmes. La prévalence augmente avec l’augmentation des tranches d’âge. Le poids, l’indice de masse corporelle (IMC), la circonférence et le tour de taille (WC) des cas d’AOS ont été s’avère significativement plus élevé que celui des personnes non atteintes d’AOS. Une tendance progressive à l’augmentation du poids, de l’IMC, de la circonférence du cou et Le WC a été observé avec l’augmentation de la gravité de l’AOS. Les patients atteints d’AOS par rapport aux patients non atteints d’AOS présentaient une augmentation significative du WC, du sang pression artérielle (TA), niveaux de glycémie à jeun, postprandiaux, aléatoires et de triglycérides (TG). Une tendance à l’augmentation des WC, de la TA à jeun, postprandiale, la glycémie aléatoire et les taux de TG étaient associés à une augmentation de la gravité de l’AOS. Des ronflements et une somnolence diurne ont été observés chez une proportion significativement plus élevée de cas d’AOS par rapport aux cas non AOS.
Conclusions:
Cette étude montre que l’AOS a une prévalence élevée chez les sujets atteints de MetS. Un indice élevé de suspicion clinique est nécessaire pour un diagnostic précoce.
Mots-clés: Apnée obstructive du sommeil, indice d’apnée-hypopnée, indice de masse corporelle, syndrome métabolique
INTRODUCTION
Metabolic syndrome (MetS) and obstructive sleep apnea (OSA) are relatively common diseases worldwide. MetS is a combination of medical disorders that include abdominal obesity, insulin resistance, dyslipidemia, and elevated blood pressure (BP). This syndrome increases the risk of developing cardiovascular disease and OSA. In addition, it is associated with an immense number of other comorbidities.[1,2] As the term syndrome implies, a single specific causative etiology to MetS is not clear. Nevertheless, abdominal adiposity and insulin resistance appear to be at the core of the pathophysiology of MetS and its individual components.[3] Although the incidence of MetS in India is on the rise, there is a paucity of Indian data on its correlation with obstructive sleep apnea.[2]
OSA is characterized by recurrent upper airway obstruction during sleep, causing recurrent apneas and arousals. It is identified as the cessation of airflow ≥10 s, with continued chest and abdominal movements. Hypopnea is identified as a ≥30% reduction in airflow accompanied by a 4% decrease in oxygen saturation and/or followed by arousal, with continued chest and abdominal movement.[4] Risk factors of OSA are type 2 diabetes mellitus (DM), alcohol use, drug abuse, coronary artery disease (CAD), hypertension, congestive heart failure (CHF), hyperlipidemia, asthma, chronic obstructive pulmonary disease, liver disease, AIDS, end-stage renal disease (ESRD), hypothyroidism, depression, etc.[5]
OSA has been shown to be an independent risk factor for hypertension and insulin resistance.[6,7] Patients with OSA have abnormalities in each of the “core” components of the MetS-high BP, high fasting glucose, increased waist circumference (WC), low high-density lipoprotein cholesterol (HDL-C), and high triglycerides (TGs) as well as in many of its other features, including sympathetic activation, endothelial dysfunction, systemic inflammation, hypercoagulability, and insulin resistance. OSA also promotes metabolic dysfunction and increases the incidence of MetS overall, as well as its individual components. Therefore, OSA seems to be more than an epiphenomenon in the MetS. Early treatment of OSA in patients with MetS has produced some beneficial effects on individual components of MetS; hence, early identification and treatment of OSA in patients with MetS is essential.
MATERIALS AND METHODS
This cross-sectional study was conducted in the Department of Medicine in collaboration with the Department of Respiratory Medicine, the Department of Physiology, and the Department of ENT, Head and Neck Surgery. After approval of the Institutional Ethics Committee, all subjects were enrolled on the basis of inclusion and exclusion criteria from outdoor and indoor patients of the Departments of Medicine and Pulmonary Medicine.
Inclusion criteria
After taking written informed consent, 103 patients of any gender of age ≥18 years who fulfilled the 2005 International Diabetes Federation (IDF) criteria for MetS, were included in this study. According to the 2005 IDF criteria, MetS was diagnosed in a patient having central obesity (WC ≥90 cm in males and ≥80 cm in females) plus any two of the following: (1) Serum TGs ≥150 mg/dL or specific treatment for lipid abnormality. (2) Serum HDL-C <40 mg/dL in males and <50 mg/dL in females, or specific treatment for lipid abnormality. (3) Blood Pressure in supine position (after 10 min rest)- systolic BP (SBP) ≥130 mmHg or diastolic BP (DBP) ≥85 mmHg, or on the treatment of previously diagnosed hypertension. (4) Fasting blood sugar (FBS) ≥100 mg/dL, or previously diagnosed type 2 DM.
Exclusion criteria
Patients with chronic respiratory problems, congestive heart failure, cognitive impairment, history of cerebrovascular accident within the preceding 30 days, patient on sedatives, antipsychotics, or anti-obesity drugs, hypothyroidism, any structural and physical problem in airway, end stage renal disease, chronic liver disease, coronary artery disease, acquired immunodeficiency syndrome patients, drug abuser, depressive patients, pregnancy, and history of maxillofacial neck trauma and surgery were excluded from the study.
Methodology
Patient evaluation
A detailed clinical history including past history regarding diabetes mellitus including its duration, treatment taken-OHA or insulin, controlled or uncontrolled on medications and hypertension regarding duration, treatment taken, and controlled or uncontrolled on medications and complete general and systemic examinations were done in all cases. Anthropometric measurements (height, weight, and neck circumference) were taken in all cases. All the patients had been seen by ENT specialists before they underwent polysomnography (PSG). There was no reason of snoring and sleep apnea from the nose, throat, and larynx. Respiratory medicine consultants also evaluated for any lower respiratory tract impairments. All patients were subjected to complete blood count, kidney function test with serum electrolytes, liver function test, fasting and postprandial blood sugar, HbA1c, thyroid function test, and fasting lipids profile. Patients were screened for OSA with the help of the STOP-Bang questionnaire. Those patients who scored ≥3 were subjected to overnight PSG to confirm the diagnosis of OSA.
Polysomnography
PSG was done with the help of machines in the Department of Medicine and in the Department of Pulmonary Medicine. Apnea–hypopnea index (AHI) was calculated and accordingly patients were classified into mild, moderate, and severe OSA (mild: AHI = 5–14, moderate: AHI = 15–30, severe: AHI = >30).
The key physiological information collected during a sleep study for OSA-hypopnea syndrome assessment included measurement of breathing (changes in airflow, respiratory excursion), oxygenation (hemoglobin oxygen saturation), body position, and cardiac rhythm. In addition, PSG measured sleep continuity and sleep stages (by electroencephalography, chin electromyography, electro-oculography, and actigraphy), limb movements (by leg sensors), and snoring intensity. This information was used to quantify the frequency and subtypes of abnormal respiratory movement’s events during sleep as well as associated changes in oxygen hemoglobin saturation, arousals, and sleep stage distributions. The sleep study report provided quantitative data such as the AHI and the profile of oxygen saturation over the night (mean, nadir, and time at low levels). Reports also included the respiratory disturbance index, which included the number of respiratory effort-related arousals in addition to the number of apneas plus hypopneas.
Statistical analysis
The statistical analysis was done using SPSS (Statistical Package for the Social Sciences) version 21.0 statistical analysis software (IBM Corp, Illinois, Chicago, USA). The values were represented in number (%) and mean ± standard deviation (SD). The group of the continuous variable was compared by the Student’s t-test, and while discrete data were analyzed by the Chi-square test. The level of significance “P” mentioned in the results was considered significant if P < 0.05.
Ethical clearance and funding
This study was approved by the institutional ethical committee and was not supported by any funding agency.
RESULTS
A total of 103 patients with MetS fulfilling the inclusion criteria were enrolled in the present study. All patients were screened for OSA by the STOP-Bang questionnaire. Out of 103 patients, 87 (84.5%) cases had a score of ≥3 and the rest 16 (15.5%) cases had a score of <3 [Table 1]. Patients who had a score of ≥3 were subjected to PSG as they had a moderate-to-high risk for OSA, whereas those who had a score of <3 had a low risk of OSA and were not subjected to PSG.
Table 1.
STOP-Bang score of the study population obstructive sleep apnea (n=103)
| STOP-Bang score | Number of cases (n=103; 100%), n (%) |
|---|---|
| Score 0–2 | 16 (15.5) |
| Score 3–4 | 38 (36.9) |
| Score 5–8 | 49 (47.6) |
Eighty-seven patients whose STOP-Bang score was ≥3 underwent PSG. Out of 87 patients, 70 had AHI score ≥5 on PSG were diagnosed with OSA, and the rest 17 had AHI score <5 were considered to be non-OSA cases [Table 2].
Table 2.
Polysomnography of study population with STOP-Bang score ≥3
| AHI | Number of cases (n=87; 100%), n (%) |
|---|---|
| ≥5.0 | 70 (80.5) |
| <5.0 | 17 (19.5) |
AHI=Apnea–hypopnea index
Out of 103 MetS patients enrolled in the study, 70 were diagnosed with OSA (Group I). Hence, a prevalence of 68% (95% confidence interval: 58.9%–77.0%) was observed in the study. The MetS patients with AHI <5.0 (17) and those with STOP-Bang score <3 (16) were considered non-OSA (Group II) [Table 3]. The majority of the OSA cases had moderate-to-severe levels of OSA (68.6%), and only 31.4% had mild levels of OSA [Table 4].
Table 3.
Prevalence of obstructive sleep apnea in metabolic syndrome (n=103)
| Group | Description | Number of patients (%) |
|---|---|---|
| Group I (OSA) | MetS patients with AHI ≥5 | 70 (68.0) |
| Group II (Non-OSA) | MetS patients with AHI <5.0 (17) + MetS patients with STOP-Bang score <3 (16) | 33 (32.0) |
MetS=Metabolic syndrome, AHI=Apnea–hypopnea index, OSA=Obstructive sleep apnea
Table 4.
Severity of obstructive sleep apnea cases (n=70)
| Severity | Number of patients (%) |
|---|---|
| Mild OSA (AHI 5–14) | 22 (31.4) |
| Moderate OSA (AHI 15–30) | 19 (27.2) |
| Severe OSA (AHI >30) | 29 (41.4) |
AHI=Apnea–hypopnea index, OSA=Obstructive sleep apnea
The proportion of OSA was higher among the cases of higher age groups compared to lower age groups, but the difference was not found to be significant statistically (P = 0.603). The mean age of the study population was 54.8 ± 9.4 years. The mean age of patients with OSA (Group I) was 55.4 ± 8.80 years and that of non-OSA (Group II) was 53.5 ± 10.5 years. The proportion of OSA was higher among females compared to males, the male: female ratio was 1:1.8, but the difference was not found to be significant statistically (P = 0.371). The proportion of severe OSA was highest among the cases of age 35–50 years compared to higher age groups, but the difference was not found to be significant statistically (P = 0.638). The proportion of severe OSA was higher in males compared to females, and the difference was found to be significant statistically (P = 0.015).
The central obesity and DM were present in all the subjects. Hypertension was more common in Group I as compared to Group II, and the difference was found to be significant statistically (P < 0.001). Raised TG and low high-density lipoprotein (HDL) were also more commonly seen in Group I cases; however, these differences were not found statistically [Table 5].
Table 5.
Components of metabolic syndrome among the study population
| Component | Group I (OSA) (n=70), n (%) | Group II (Non-OSA) n=33, n (%) | Total (n=103), n (%) | χ 2 | P |
|---|---|---|---|---|---|
| Central obesity | 70 (100) | 33 (100.0) | 103 (100.0) | NA | NA |
| Diabetes mellitus | 70 (100) | 33 (100.0) | 103 (100.0) | NA | NA |
| Hypertension | 50 (71.4) | 6 (18.2) | 56 (54.4) | 25.63 | <0.001 |
| Hypertriglyceridemia | 63 (90) | 29 (87.9) | 92 (89.3) | 0.11 | 0.745 |
| Low HDL | 57 (81.4) | 25 (75.8) | 82 (79.6) | 0.44 | 0.505 |
OSA=Obstructive sleep apnea, HDL=High-density lipoprotein, NA=Not available
Patients of Group I (OSA) had a significantly higher value of waist circumference (WC),fasting blood sugar (FBS), blood pressure (SBP and DBP), and triglyceride as compared to Group II (non-OSA) [Table 6]. With increasing value of WC, FBS. SBP, DBP, and TG, the severity of OSA was found to be increased statistically (P < 0.05). Although the value of HDL was found to be low in moderate-to-severe OSA as compared to mild, this association was statistically insignificant (P = 0.326).
Table 6.
Association of metabolic syndrome parameters with obstructive sleep apnea
| OSA | Mean±SD |
Unpaired t-test |
||
|---|---|---|---|---|
| Group I (OSA) (n=70) | Group II (Non-OSA) (n=33) | t | P | |
| WC | 89.60±3.62 | 87.00±5.43 | 2.88 | 0.005 |
| FBS | 172.30±38.37 | 153.18±26.97 | −2.58 | 0.011 |
| SBP | 143.74±18.48 | 124.67±10.12 | 5.54 | <0.001 |
| DBP | 86.31±8.78 | 76.18±5.51 | 6.08 | <0.001 |
| TG | 187.10±33.06 | 173.48±26.50 | 2.07 | 0.041 |
| HDL | 36.56±6.49 | 38.64±7.28 | −1.46 | 0.148 |
OSA=Obstructive sleep apnea, HDL=High-density lipoprotein, SD=Standard deviation, WC=Waist circumference, FBS=Fasting blood glucose, SBP=Systolic blood pressure, DBP=Diastolic blood pressure, TG=Triglyceride
With increasing the number of components of MetS, the prevalence of OSA was found to be increased significantly (P = 0.001) [Table 7]. A higher number of components of MetS were associated with increasing severity of OSA (P < 0.249).
Table 7.
Association of components of metabolic syndrome with obstructive sleep apnea
| Component | Group I (OSA) (n=70), n (%) | Group II (Non-OSA) (n=33), n (%) | Total (n=103), n (%) | χ 2 | P |
|---|---|---|---|---|---|
| 3 MetS | 6 (8.6) | 11 (33.3) | 17 (16.5) | 16.43 | <0.001 |
| 4 MetS | 28 (40.0) | 17 (51.5) | 45 (43.7) | ||
| 5 MetS | 36 (51.4) | 5 (15.2) | 41 (39.8) |
MetS=Metabolic syndrome, OSA=Obstructive sleep apnea
Higher weight, body mass index (BMI), WC, and neck circumference increase the likelihood of developing OSA. These results were found to be statistically significant (<0.05). However, a statistically significant association was not found with height (P = 0.388) [Table 8]. With the increase in weight, BMI, WC, and neck circumference, the severity of OSA increases and result was statistically significant (<0.05).
Table 8.
Association of anthropometric parameters with obstructive sleep apnea (n=103)
| OSA | Mean±SD |
Unpaired t-test |
||
|---|---|---|---|---|
| Group I (OSA) (n=70) | Group II (Non-OSA) (n=33) | t | P | |
| Height | 157.06±8.15 | 158.61±9.09 | −0.87 | 0.388 |
| Weight | 82.93±12.34 | 77.67±11.19 | 2.08 | 0.040 |
| BMI | 34.61±4.69 | 31.60±5.48 | 2.88 | 0.005 |
| WC | 89.60±3.62 | 87.00±5.43 | 2.88 | 0.005 |
| Neck circumference | 40.79±4.04 | 39.15±3.11 | 2.06 | 0.042 |
BMI=Body mass index, WC=Waist circumference, SD=Standard deviation, OSA=Obstructive sleep apnea
The prevalence of OSA was found to be increased with an increase in BMI, neck circumference, presence of snoring and tiredness. It was found to be statistically significant with BMI, neck circumference, and presence of snoring (P = 0.05), however, the result of tiredness was not statistically significant (P = 0.113). It was observed that the severity of OSA increases with an increase in BMI, neck circumference, presence of snoring, and daytime tiredness, but the result was statistically significant only in case of neck circumference (P = 0.001). The results were not statistically significant for other parameters [Table 9].
Table 9.
Association of body mass index, neck circumference, snoring, and tiredness with obstructive sleep apnea (n=103)
| Variable | Group I (OSA) (n=70), n (%) | Group II (Non-OSA) (n=33), n (%) | χ 2 | P |
|---|---|---|---|---|
| BMI (kg/m2) | ||||
| 18.5–22.9 | 0 | 3 (100.0) | 9.16 | 0.027 |
| 23.0–24.9 | 1 (50.0) | 1 (50.0) | ||
| 25.0–29.9 | 10 (55.6) | 8 (44.4) | ||
| ≥30 | 59 (73.8) | 21 (26.3) | ||
| Neck circumference | ||||
| ≥40 | 36 (57.1) | 27 (42.9) | 9.45 | 0.009 |
| 41–46 | 28 (82.4) | 6 (17.6) | ||
| >46 | 6 (100.0) | 0 | ||
| Snoring | ||||
| No | 4 (21.1) | 15 (78.9) | 23.54 | <0.001 |
| Yes | 66 (78.6) | 18 (21.4) | ||
| Tiredness | ||||
| No | 10 (52.6) | 9 (47.4) | 2.51 | 0.113 |
| Yes | 60 (71.4) | 24 (28.6) |
BMI=Body mass index, OSA=Obstructive sleep apnea
DISCUSSION
In the present study, the prevalence of OSA in MetS was 68%, and in the previous study, Soin et al. showed similar results. This cross-sectional analytical study was conducted on 100 subjects aged 30–60 years, comprising 50 cases of MetS and 50 controls without MetS. Overnight PSG was done in all the subjects. The prevalence and severity of OSA were assessed and compared between the two groups. The prevalence of OSA was significantly higher (66%) in patients with MetS than in subjects without MetS (12%). Out of 33 (66%) OSA patients with MetS, 8 (16%) had mild OSA, 11 (22%) had moderate OSA, and 14 (28%) had severe OSA. Increasing severity of OSA was associated with higher mean levels of all the MetS.[8] Barreiro et al. reported the highest prevalence of up to 81% of OSA with MetS.[9] Coughlin et al. showed the overall association of OSA with MetS. MetS was 9.1 times more likely to be present in subjects with OSA.[10] Out of 103 MetS cases enrolled in the study, 59 (57.3%) were male and the rest were female (44%). The proportion of OSA was higher in females as compared to males. The difference was not found to be statistically significant (P = 0.371), but the proportion of severe OSA was higher in males compared to females, and the difference was found to be significant statically (P = 0.015). The above findings were supported by the study of Parish et al. and Bonsignore et al.[11,12]
The age of patients enrolled in the study ranged between 29 and 78 years, with the mean age of the study population being 54.8 ± 9.4 years. The mean age of Group I (OSA) cases was 55.4 ± 8.8 years, whereas that of Group II (non-OSA) cases was 53.5 ± 10.5 years. The prevalence of OSA was highest in the age group > 65 years which was 73%, followed by 68% in the age group 51–65 years, 67.9% in the age group 35–50 years, and 33.3% in the age group < 35 years. Results demonstrated a high prevalence of OSA in MetS in males and females of all ages, especially in older age groups. The proportion of OSA was higher among the cases of higher age compared to lower age groups, but the difference was not found to be significant statistically (P = 0.603). Our findings seem to be consistent with the results in a prior study supported by Bonsignore et al. and Barrino et al.[9,12]
In the present study, the incremental trend of OSA was found with higher BMI. The prevalence of OSA in subjects with BMI >30 kg/m2 was 59 (73.8%), followed by 10 (56.6%) with BMI 25–29.9 kg/m2 and 1 (50%) with the subjects of BMI 23.0–24.9 kg/m2. The prevalence of OSA was found to be increased with an increase in BMI. The result of BMI was statistically significant (P = 0.05) supported by Parish et al.[11] It can be appreciated from this study that the prevalence as well as severity increases with increasing BMI. This was supported by the study done by Bonsignore et al., which concluded that OSA is more common in the population with higher BMI.[12]
In the present study, the mean neck circumference in OSA patients was 40.79 ± 4.0 cm. We found that there is a significant increase in the prevalence of OSA with an increase in neck circumference. This difference was found to be significant statistically (P = 0.042). These findings are supported by the study conducted by Laldayal et al. They also correlated neck circumference with the severity of OSA. They concluded that the neck circumference can be used to differentiate mild OSA from moderate-to-severe OSA.[13]
We tried to show the relationship between blood sugar levels with the prevalence of OSA. In our study, the mean FBS was 172.30 ± 38.37 mg/dl. The mean FBS in mild OSA was 160 ± 29.18, in moderate OSA, it was 168 ± 37.66, and in severe OSA, it was 187 ± 45.02. It was observed that the severity of OSA increases with an increase in the FBS. There is growing evidence in support of an independent association between OSA and impaired glucose metabolism by the study of Lam et al.[14]
The present study showed mean TGs in the OSA group as 187.10 ± 33.06. The mean TG in mild OSA was 173 ± 26.03, in moderate, it was 185.11 ± 35.83, and in severe, it was 198.14 ± 32.84. It was observed that the grading of OSA increases with an increase in TG levels. The above findings were also supported by Tanner et al.[15]
In this study, it was observed that with the increasing WC, FBS, SBP, DBP, and TG, the severity of OSA increased, and the result was statistically significant (<0.05). A higher number of components of MetS were significantly associated with OSA (P < 0.001). These findings were supported by the study conducted by Kono et al. They observed that obesity, hypertension, dyslipidemia, and hyperglycemia are prevalent in OSA syndrome (OSAS). We investigated the occurrence of hypertension, dyslipidemia, and hyperglycemia in 42 men with OSAS and 52 men without OSAS matched for age, BMI, and visceral fat accumulation. Although serum levels of TGs, HDL-C, and DBP did not differ significantly between the two groups, fasting blood glucose (111 ± 6 mg/dL vs. 93 ± 3 mg/dL) (mean ± SD) and the percentage of hypertensive patients (45% vs. 15%) were significantly higher in the group with OSAS. In addition, a significantly higher percentage of patients with OSAS (19% vs. 4%) had at least two of the following: hypertension, hyperglycemia, and dyslipidemia. Logistic regression analysis done by Kono M et al. showed that the AHI value was the predictor of the number of MetS parameters such as hypertension, hyperglycemia, and dyslipidemia, whereas BMI and lowest arterial oxygen saturation during sleep did not. Independent of visceral fat obesity, OSAS was associated with hypertension, dyslipidemia, and hyperglycemia. It is possible that OSAS may predispose even nonobese patients to the development of MetS.[16]
CONCLUSIONS
OSA is highly prevalent in the MetS population. It is related to age and obesity. The prevalence of OSA and OSAS has increased in epidemiological studies over time. Differences and increase in the prevalence of sleep apnea are probably due to different diagnostic equipment, definition, study design, and characteristics of included subjects. This study showed that OSA had a high prevalence in subjects with MetS and identified several factors that may be associated with its presence in the MetS population. Most of the clinicians do not suspect this important comorbidity of MetS, in the beginning, resulting in delayed diagnosis.
Limitations
Small sample size is the main limitation of our study as this prevalence study should be conducted over a large population size. Another limitation is the cross-sectional design of our study. As the patients were not followed up, the effect of treatment of MetS on the resolution of OSA could not be established. Obesity is itself a risk factor for the OSA, and insulin resistant can lead to obesity, so obesity acts as a confounding factor in our study. Further studies are required to strengthen the association of MetS with OSA.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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