Indan Journal of Medical Research Indan Journal of Medical Research Indan Journal of Medical Research Indan Journal of Medical Research
  Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login  
  Home Print this page Email this page Small font sizeDefault font sizeIncrease font size Users Online: 5134       

   Table of Contents      
Year : 2011  |  Volume : 134  |  Issue : 5  |  Page : 639-644

Prevalence of metabolic syndrome in a north Indian hospital-based population with obstructive sleep apnoea

1 Department of Medicine, All India Institute of Medical Sciences, New Delhi, India
2 Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India
3 Department of Cardiac Biochemistry, All India Institute of Medical Sciences, New Delhi, India

Date of Submission25-Oct-2010
Date of Web Publication20-Dec-2011

Correspondence Address:
Surendra K Sharma
Department of Medicine, All India Institute of Medical Sciences, New Delhi 110 029
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0971-5916.90988

Rights and Permissions

Background & objectives: Obstructive sleep apnoea (OSA) is known to be associated with cardiovascular risk factors and metabolic syndrome (MS). The burden of MS in patients with OSA in India is unknown. We investigated the prevalence of MS and its components in a cross-sectional study in patients with and without OSA in a hospital-based population of a tertiary health care centre in New Delhi, India.
Methods: Consecutive patients undergoing overnight polysomnography in the Sleep Laboratory of the Department of Internal Medicine of All India Institute of Medical Sciences (AIIMS) hospital, New Delhi, were studied. Anthropometry and body composition analysis, blood pressure (BP), fasting blood glucose, insulin resistance by homeostasis model assessment (HOMA-IR) and fasting blood lipid profile were measured. MS was defined using the National Cholesterol Education Program Adult treatment panel III criteria, with Asian cut-off values for abdominal obesity.
Results: Of the 272 subjects recruited, 187 (82%) had OSA [apnoea-hypopnoea index (AHI)>5 events/h] while 40 (18%) had a normal sleep study. Prevalence of MS in OSA patients was 79 per cent compared to 48 per cent in non-OSA individuals [OR 4.15, (2.05-8.56), P<0.001]. Prevalence of OSA in mild, moderate and severe OSA was 66, 72 and 86 per cent, respectively (P<0.001). Patients with OSA were more likely to have higher BP [OR: 1.06 (1.02-1.11)], fasting insulin [OR: 1.18 (1.05-1.32)], HOMA-IR [OR: 1.61 (1.11-2.33)] and waist circumference [OR: 1.20 (1.13-1.27)].
Interpretation & conclusions: Our findings suggest that OSA is associated with a 4-fold higher occurrence of MS than patients without OSA. The prevalence of MS increases with increasing severity of OSA, therefore, early detection will be beneficial.

Keywords: Metabolic syndrome - obstructive sleep apnoea - prevalence - risk factors - South Asians - urban Indians

How to cite this article:
Agrawal S, Sharma SK, Sreenivas V, Lakshmy R. Prevalence of metabolic syndrome in a north Indian hospital-based population with obstructive sleep apnoea. Indian J Med Res 2011;134:639-44

How to cite this URL:
Agrawal S, Sharma SK, Sreenivas V, Lakshmy R. Prevalence of metabolic syndrome in a north Indian hospital-based population with obstructive sleep apnoea. Indian J Med Res [serial online] 2011 [cited 2020 Aug 5];134:639-44. Available from:

Obstructive sleep apnoea (OSA) is a condition in which there is collapse of the upper airway during sleep, as a result of which there is a decrease or complete cessation of airflow. [1] A population-based study in Delhi reported the prevalence of OSA to be as high as 9.3 per cent [2] . The association of OSA with increased cardiovascular morbidity and mortality [3] and various cardiovascular risk factors [4] is known for a long time. Various metabolic and morphological risk factors for cardiovascular disease such as obesity, hypertension, dyslipidaemia and insulin resistance are found to be co-existent in patients more often than explained by chance alone. This clustering of risk factors is called metabolic syndrome (MS) [5] . OSA has been shown to be associated with these risk factors including hypertension [6],[7] , insulin resistance [8],[9] and dyslipidaemia [10] . Given this association of both OSA and MS with cardiovascular disease it is logical to expect a relationship between the two. It has subsequently been shown that OSA is associated with MS [11] . A UK based study [10] showed the prevalence of MS in patient with OSA to be 85 per cent compared with 37 per cent in normal controls. In a Chinese study [12] it was 58 and 21 per cent, respectively. A north Indian population-based study [13] found the prevalence to be 77 and 40 per cent, respectively. OSA and MS are believed to act synergistically to increase cardiovascular risk and the co-occurrence of these conditions has been termed syndrome Z [14] . However, the data on the relationship between OSA and MS are conflicting with obesity being considered as an important confounder due to its independent association with OSA and other cardiovascular risk factors [15],[16],[17] .

The prevalence of MS in patients of OSA has not been studied in hospital-based populations in India so far. The population-based data available are insufficient to guide decision making in sleep clinic patients as these patients represent a much more symptomatic cohort with probably a higher burden of MS than discovered by community-based studies. The present study was carried out to determine prevalence of MS in a hospital-based urban north Indian population with OSA and to correlate components of MS with OSA in patients presenting to sleep clinic of a tertiary health care centre in New Delhi, India.

   Material & Methods Top

In this cross-sectional study consecutive patients undergoing polysomnography (PSG) in the Sleep Laboratory of the Department of Internal Medicine of All India Institute of Medical Sciences (AIIMS), New Delhi, between June 2008 and May 2010 were evaluated for enrolment. These patients were referred for PSG from the sleep related breathing disorders (SRBD) clinic of the Department of Internal Medicine, AIIMS hospital, New Delhi. Referral of patients for PSG was on discretion of physicians in the sleep clinic, usually for symptoms of excessive daytime somnolence or snoring. Males and females, aged 30-65 yr, and naïve to continuous positive airway pressure (CPAP) treatment were included. Patients having hypothyroidism, chronic renal failure, chronic liver disease and patients with coronary artery disease and left ventricular dysfunction were excluded from the study. Patients with history of chronic corticosteroid use or hormone replacement therapy were also excluded. Approval for study protocol was obtained from the AIIMS ethics committee and written informed consent was taken from each participant.

Sleep assessment: All subjects underwent overnight 16-channel polysomnography (PSG) conducted in Sleep Laboratory of the Department of Internal Medicine at AIIMS hospital, New Delhi, by trained technicians using a Rembrandt 7.3 version PSG machine (Medicare Technologies, USA) as described elsewhere [18] . Recorded sleep data were scored manually according to standard criteria [19] by experienced laboratory technicians blinded to clinical data. Apnoea and hypopnoea were defined according to the Chicago criteria as recommended by the American Academy of Sleep Medicine [20] . OSA was defined as apnoea-hypopnoea index (AHI)>5 events/h. Severity of OSA was graded as, mild OSA: AHI ≥5 and <15 events/h, moderate OSA: AHI ≥15 and <30 events/h, and severe OSA: AHI ≥30 events/h [21] . Patients without OSA were referred to as normal. Obstructive sleep apnoea syndrome (OSAS) was defined as the presence of OSA with excessive daytime sleepiness (EDS). EDS was assessed using the Epworth Sleepiness Scale (ESS) [22] based on the subject's response to eight questions regarding probability of dozing under specific situations with a 4-point scale. A score of 10 or more was considered suggestive of EDS.

Anthropometry, body composition analysis and blood pressure measurements: Blood pressure, body weight, body composition analysis, neck circumference (NC), neck length (NL), waist circumference (WC), hip circumference (HC) and biceps, triceps, subscapular and suprailiac skin-fold thicknesses were measured using standard methods as described earlier [23] . Percentage predicted neck circumference (PPNC) was computed using Davies and Strading formula as, PPNC = (1000 x NC) / [(0.55 x Height) +310] [24] . Body weight was measured to the nearest 0.5 kg in erect position without footwear, wearing light indoor clothes by a Tanita Body composition analyzer (model TBF 300 GS, Tanita corporation, Tokyo, Japan) along with fat mass, per cent body fat and fat-free mass.

Biochemical tests: At the end of the sleep study on the next morning, blood samples were taken from each subject and the following tests were done: fasting blood glucose (by glucose oxidase method) using Roche Hitachi 912 Chemistry Analyzer (Hitachi, Tokyo, Japan), fasting plasma insulin (by ELISA, R&D systems, Minneapolis, MN, USA), and lipid profile [total cholesterol, triglyceride (TG) and HDL-cholesterol were measured using immunocolorimetric assay, LDL cholesterol was calculated using Friedewald equation] [25] . Insulin resistance was calculated using the homeostasis model assessment (HOMA-IR) method using FBS and fasting plasma insulin, previously validated against the hyperinsulinaemic euglycaemic clamp [26] .

Metabolic syndrome: Metabolic syndrome was defined as per the National Cholesterol Education Program - Adult Treatment Panel III criteria [27] , with the cut-off for defining abdominal obesity taken as waist circumference ≥90cm in males and ≥80cm in females as recommended by the World Health Organization guidelines for South Asians [28] .

Sample size estimation: Assuming prevalence of MS to be 70 per cent in OSA, to estimate the prevalence of MS in patients of OSA with an absolute precision of ±10 per cent with a 2 sided 95% confidence interval, 84 subjects with OSA were required to be studied.

Statistical analysis: Statistical analyses were performed using a statistical software package (Stata 11.0 for Windows, Stata Corporation, College Station, TX, USA). Continuous variables were summarized as mean ± SD or median (range) and categorical variables as proportions, n (%). Comparison between groups was done by independent Student's t-test and Mann-Whitney test for parametric and non-parametric variables, respectively and Chi-square and Fisher's exact test for categorical variables. Chi square test was used to compare prevalence of MS in various categories of OSA with non-OSA using logistic regression to derive odds ratios. Trend for increase in prevalence of MS with increasing severity of OSA was assessed by Cuzick's test for trend for ordinal data [29] . P<0.05 was considered significant.

   Results Top

Of the 227 patients recruited, 187 (82%) had OSA defined by an AHI >5 events/h. Subjects with OSA were more likely to be male, older in age, had higher ESS, BMI, per cent body fat, fat mass, per cent predicted neck circumference and skin fold thicknesses [Table 1]. By definition, they had higher AHI and arousal index [Table 2]. There were more alcohol consumers and smokers in the OSA group, although it did not reach statistical significance.
Table 1: Comparison of demographic and anthropometric characteristics in apnoeics and non-apnoeics

Click here to view
Table 2: Comparison of polysomnographic characteristics in apnoeics and non-apnoeics

Click here to view

Diastolic blood pressure, fasting plasma insulin, HOMA-IR, waist circumference and waist-hip ratio were significantly higher in subjects with OSA compared to non-OSA individuals [Table 3]. There was a trend towards increased systolic blood pressure, fasting blood glucose, triglycerides and LDL cholesterol but did not reach statistical significance. There was no significant difference in total cholesterol, HDL cholesterol, non-HDL cholesterol and HDL:total cholesterol levels between the groups. Of the 187 patients with OSA, 148 (79%) had MS compared with 19 (48%) in the non-OSA group (OR= 4.19, 95% CI=2.05, 8.56) [Table 4]. Subgroup analysis showed an increasing prevalence of MS with increasing severity of OSA [66%, OR: 2.13 (0.87-5.21), 72% OR: 2.87 (1.10-7.49) and 86% OR: 7 (2.95-4.62) for mild, moderate and severe OSA, respectively compared to non-OSA group]. Cuzick's test for trend showed a significant (P<0.001) trend for increase in prevalence of MS with increasing severity of OSA [Table 4].
Table 3: Comparison of various components of metabolic syndrome in apnoeics and non-apnoeics

Click here to view
Table 4: Prevalence of metabolic syndrome in obstructive sleep apnoea

Click here to view

   Discussion Top

In this study we found a 79 per cent prevalence of MS in OSA patients compared with 48 per cent in the control group. These values are higher than those seen in previous studies [12],[13] . This is probably due to the fact that these were community-based studies and participants had a lower BMI compared to the present study. Our study being hospital-based is expected to have a higher prevalence of MS due to a referral bias. Compared to the only previous hospital-based study reporting prevalence of MS in OSA [10] the present study has lower values, probably due to ethnic differences in the patient populations and a much higher BMI of participants in the study by Coughlin et al[10] . Diastolic blood pressure, fasting plasma insulin, HOMA-IR, waist circumference and WHR were also higher in patients with OSA, with a trend towards higher systolic blood pressure, fasting blood glucose, triglycerides and LDL cholesterol. Body composition analysis showed higher fat mass, per cent body fat and skin fold thicknesses in patients of OSA. These findings are in concordance with previous studies showing OSA to be associated with higher BP [30] , insulin resistance [8] and deranged lipid profile and body composition [31] . While all studies are in agreement with the higher prevalence of MS in OSA, the data on association of individual components of MS are conflicting [8],[9],[10],[16],[17] due to differences in ethnicities, source of recruitment of the study population and power of the studies.

The increasing prevalence of MS with increasing severity of OSA suggests an association of OSA with MS. However, a causative role cannot be inferred from these data alone, since obesity is a significant confounder in studies involving OSA and MS, as it is a major risk factor for both conditions; 40-90 per cent obese individuals have OSA and about 70 per cent of OSA patients have obesity [32],[33],[34] . Only a longitudinal study would be able to definitely prove whether OSA precedes and causes MS or vice versa, and whether obesity is the predisposing factor for both these conditions.

The clinical implications are that there is a high prevalence of MS in patients presenting to sleep clinics with symptoms suggestive of OSA, irrespective of whether they have OSA or not. The prevalence of MS is even higher if they actually have OSA. MS as a whole and its components individually are very likely to be present in patients with OSA and this risk increases with the severity of metabolic syndrome. Screening for MS components along with the work up of OSA will allow early detection of these cases. This relationship of MS with OSA can also explain the mechanism for increased mortality in patients with OSA.

The present study has some limitations. Being a hospital-based study there was referral bias with more symptomatic patients likely to be referred to our hospital. The non-OSA group did not reflect absolutely normal individuals and they were more likely to have hypertension, diabetes, dyslipidaemia and obesity than healthy volunteers. However, this would serve to decrease the difference found between the two groups rather than increase it. Matching for obesity, an important potential confounder was not done. An ideal study design would have been to use BMI and per cent body fat matched controls to eliminate confounding. However, this would have substantially decreased the sample size of the control group and hence the statistical power of the study.

The strengths of the present study include (i) a large sample size of 227 patients with 187 of them being apnoeics with a resultant power of 97% to detect a significant difference between the groups for the prevalence of MS at the values found in this population; (ii) exclusion of OSA in control group by performing a full overnight PSG study in each one of them; (iii) diagnosis of OSA by full overnight, supervised, in-hospital PSG study; (iv) use of AHI cut-off of ≥5 events/h in accordance with the results of the Sleep Heart Health Study which reported association of hypertension with OSA at these cut-off values; (v) inclusion of both males and females in the study allowing extrapolation of these results to both these groups.

This is perhaps the first hospital-based study to investigate the prevalence of MS in patients with OSA from India. It differs from previous community-based studies from India and China [12],[13] . In conclusion, our study showed that the prevalence of MS was four times higher in patients of OSA than controls and the prevalence increased with increasing severity of OSA. Therefore, patients with MS should be investigated for OSA and vice versa, as early detection and correction of these conditions may result in significant decrease in morbidity and mortality.

   Acknowledgment Top

Authors thank sleep lab technicians Shriyut Jitender Sharma, Jitender Kumar and Amit Solomon for performing the polysomnographies and for their assistance in data collection, and also the sponsors of the study, Pfizer Ltd., Mumbai. The sponsors had no role in study design, data analysis and in writing the manuscript.

   References Top

1.Vecchierini MF. Obstructive sleep apnoea-hypopnoea syndrome: evolution of an old concept. Neurochirurgie 2006; 52 : 432-42.  Back to cited text no. 1
2.Reddy EV, Kadhiravan T, Mishra HK, Sreenivas V, Handa KK, Sinha S, et al. Prevalence and risk factors of obstructive sleep apnea among middle-aged urban Indians: A community-based study. Sleep Med 2009; 10 : 913-8.  Back to cited text no. 2
3.Shahar E, Whitney C, Redline S, Lee ET, Newman AB, Javier Nieto F, et al. Sleep-disordered breathing and cardiovascular disease: cross-sectional results of the Sleep Heart Health Study. Am J Respir Crit Care Med 2001; 163 : 19-25.  Back to cited text no. 3
4.Wilcox I, McNamara SG, Collins FL, Grunstein RR, Sullivan CE. ''Syndrome Z'': the interaction of sleep apnoea, vascular risk factors and heart disease. Thorax 1998; 53 (Suppl): S25-8.  Back to cited text no. 4
5.Reaven G. metabolic syndrome: pathophysiology and implications for management of cardiovascular disease. Circulation 2002; 106 : 286-8.  Back to cited text no. 5
6.Peppard PE, Young T, Palta M, Skaturd J. Prospective study of the association between sleep-disordered breathing and hypertension. N Eng J Med 2000; 342 : 1378-84.  Back to cited text no. 6
7.Wolk R, Shamsuzzaman AS, Somers VK. Obesity, sleep apnea, and hypertension. Hypertension 2003; 42 : 1067-74.  Back to cited text no. 7
8.Ip MS, Lam B, Ng MM, Lam WK, Tsang KW, Lam KS. Obstructive sleep apnea is independently associated with insulin resistance. Am J Respir Crit Care Med 2002; 165 : 670-6.  Back to cited text no. 8
9.Punjabi N, Sorkin J, Katzel L, Goldberg AP, Schwartz AR, Smith PL. Sleep-disordered breathing and insulin resistance in middle-aged and overweight men. Am J Respir Crit Care Med 2002; 165 : 677-82.  Back to cited text no. 9
10.Coughlin SR, Mawdsley L, Mugarza JA, Calverley PM, Wilding JP. Obstructive sleep apnoea is independently associated with an increased prevalence of metabolic syndrome. Eur Heart J 2004; 25 : 735-41.  Back to cited text no. 10
11.Basta M, Vgontzas A. Metabolic abnormalities in obesity and sleep apnea are in a continuum. Sleep Med 2007; 8 : 5-7.  Back to cited text no. 11
12.Lam JC, Lam B, Lam CL, Fong D, Wang JK, Tse HF, et al. Obstructive sleep apnea and the metabolic syndrome in community-based Chinese adults in Hong Kong. Respir Med 2006; 100 : 980-7.  Back to cited text no. 12
13.Sharma SK, Reddy EV, Sharma A, Kadhiravan T, Mishra HK, Sreenivas V, et al. Prevalence and risk factors of syndrome Z in urban Indians. Sleep Med 2010; 11 : 562-8.  Back to cited text no. 13
14.Nock NL, Li L, Larkin EK, Patel SR, Redline S. Empirical evidence for "syndrome Z": a hierarchical 5-factor model of the metabolic syndrome incorporating sleep disturbance measures. Sleep 2009; 32 : 615-22.  Back to cited text no. 14
15.Stoohs RA, Facchini F, Guilleminault C. Insulin resistance and sleep-disordered breathing in healthy humans. Am J Respir Crit Care Med 1996; 154 : 170-4.  Back to cited text no. 15
16.Gruber A, Horwood F, Sithole J, Ali NJ, Idris I. Obstructive sleep apnoea is independently associated with the metabolic syndrome but not insulin resistance state. Cardiovasc Diabetol 2006; 5 : 22.  Back to cited text no. 16
17.Sharma SK, Kumpawat S, Goel A, Banga A, Ramkrishnan L, Chaturvedi P. Obesity and not obstructive sleep apnea is responsible for metabolic abnormalities in a cohort with sleep disordered breathing. Sleep Med 2007; 8 : 12-7.  Back to cited text no. 17
18.Sharma SK, Kurian S, Malik V, Mohan A, Banga A, Pandey RM, et al. A stepped approach for prediction of obstructive sleep apnea in overtly asymptomatic obese subjects: a hospital based study. Sleep Med 2004; 5 : 351-7.  Back to cited text no. 18
19.Rechtschaffen A, Kales AA, editors. A manual of standardized terminology, techniques and scoring for sleep stages of human subjects. Washington, DC: Government Printing Office. NIH Publication No. 204; 1968.  Back to cited text no. 19
20.Iber C, Ancoli-Israel S, Chesson A, Quan SF for the American Academy of Sleep Medicine. The AASM manual for the scoring of sleep and associated events: Rules, terminology and technical ehaviortions. Westchester: American Academy of Sleep Medicine; 2007.  Back to cited text no. 20
21.Epstein LJ, Kristo D, Strollo PJ Jr, Friedman N, Malhotra A, Patil SP, et al. Adult Obstructive Sleep Apnea Task Force of the American Academy of Sleep Medicine. Clinical guideline for the evaluation, management and long-term care of obstructive sleep apnea in adults. J Clin Sleep Med 2009; 5 : 263-76.  Back to cited text no. 21
22.Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 1991; 14 : 540-5.  Back to cited text no. 22
23.Sharma SK, Kumpawat S, Banga A, Goel A. Prevalence and risk factors of obstructive sleep apnea syndrome in a population of Delhi, India. Chest 2006; 130 : 149-56.  Back to cited text no. 23
24.Davies RJ, Stradling JR. The relationship between neck circumference, radiographic pharyngeal anatomy and obstructive sleep apnoea. Eur Respir J 1990; 3 : 504-9.  Back to cited text no. 24
25.Bairaktari E, Hatzidimou K, Tzallas C, Vini M, Katsaraki A, Tselepis A, et al. Estimation of LDL cholesterol based on the Friedewald formula and on apo B levels. Clin Biochem 2000; 33 : 549-55.  Back to cited text no. 25
26.Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28 : 412-9.  Back to cited text no. 26
27.Expert panel on Detection, Evaluation and Treatment of high blood cholesterol in adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on Detection, Evaluation and Treatment of high blood cholesterol in adults (Adult treatment panel III). JAMA 2001; 285 : 2486-97.  Back to cited text no. 27
28.WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363 : 157-63.  Back to cited text no. 28
29.Cuzick J. A Wilcoxon-Type test for trend. Stat Med 1985; 4 : 87-9.  Back to cited text no. 29
30.Davies CW, Crosby JH, Mullins RL, Barbour C, Davies RJ, Stradling JR. Case-control study of 24 hour ambulatory blood pressure in patients with obstructive sleep apnoea and normal matched control subjects. Thorax 2000; 55 : 736-40.   Back to cited text no. 30
31.Ip MS, Lam KS, Ho C, Tsang KW, Lam W. Serum leptin and vascular risk factors in obstructive sleep apnea. Chest 2000; 118 : 580-6.  Back to cited text no. 31
32.Daltro C, Gregorio PB, Alves E, Abreu M, Bomfim D, Chicourel MH, et al. Prevalence and severity of sleep apnea in a group of morbidly obese patients. Obes Surg 2007; 17 : 809-14.  Back to cited text no. 32
33.Young T, Palta M, Dempsey J, Skatrud J, Weber S, Badr S. The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med 1993; 328 : 1230-5.  Back to cited text no. 33
34.Young T, Peppard PE, Gottlieb DJ. Epidemiology of obstructive sleep apnea: a population health perspective. Am J Respir Crit Care Med 2002; 165 : 1217-39.  Back to cited text no. 34


  [Table 1], [Table 2], [Table 3], [Table 4]

This article has been cited by
1 Prevalence of Obstructive Sleep Apnoea in Patients with Metabolic Syndrome: A Prospective Observational Study from a Tertiary Care Centre in North India
Pushpinder Nagpal,Sunil Sharma,R. S. Negi,Malay Sarkar,Surinder Thakur
Sleep and Vigilance. 2019;
[Pubmed] | [DOI]
2 25-hydroxyvitamin D status, light exposure and sleep quality in UK dwelling South Asian and Caucasian postmenopausal women
A.L. Darling,K.H. Hart,S. Arber,J.L. Berry,P.L. Morgan,B.A. Middleton,S. Lanham-New,D.J. Skene
The Journal of Steroid Biochemistry and Molecular Biology. 2019;
[Pubmed] | [DOI]
3 Prevalence and risk factors of moderate to severe obstructive sleep apnea syndrome in major depression: a observational and retrospective study on 703 subjects
Matthieu Hein,Jean-Pol Lanquart,Gwenolé Loas,Philippe Hubain,Paul Linkowski
BMC Pulmonary Medicine. 2017; 17(1)
[Pubmed] | [DOI]
4 Prevalence and severity of syndrome Z in women with metabolic syndrome on waiting list for bariatric surgery: a cross-sectional study
Eduardo Araujo Perez,Luis Vicente Franco Oliveira,Wilson Rodrigues Freitas,Carlos Alberto Malheiros,Elias Jirjoss Ilias,Anderson Soares Silva,Jessica Julioti Urbano,Patricia Clemente Oliveira,Felipe X. Cepeda,Luciana M. M. Sampaio,Ivani C. Trombetta,Humberto Delle,Daniel Gianella Neto,Sergio Roberto Nacif,Roberto Stirbulov
Diabetology & Metabolic Syndrome. 2017; 9(1)
[Pubmed] | [DOI]
5 Prevalence and risk factors of moderate to severe obstructive sleep apnea syndrome in insomnia sufferers: a study on 1311 subjects
Matthieu Hein,Jean-Pol Lanquart,Gwénolé Loas,Philippe Hubain,Paul Linkowski
Respiratory Research. 2017; 18(1)
[Pubmed] | [DOI]
6 Metabolic syndrome and risk of major coronary events among the urban diabetic patients: North Indian Diabetes and Cardiovascular Disease Study—NIDCVD-2
Gurjit Kaur Bhatti,Sanjay Kumar Bhadada,Rajesh Vijayvergiya,Sarabjit Singh Mastana,Jasvinder Singh Bhatti
Journal of Diabetes and its Complications. 2016; 30(1): 72
[Pubmed] | [DOI]
7 Prévalence du syndrome métabolique dans une population de patients apnéiques : étude prospective avec calcul du risque cardiovasculaire
R. Ben Jazia,H. Ben Salem,I. Gargouri,S. Aissa,A. Garrouche,A. Hayouni,M. Benzarti,M. Boussarsar,A. Abdelghani
Revue de Pneumologie Clinique. 2015; 71(5): 311
[Pubmed] | [DOI]
8 The association between obstructive sleep apnea and metabolic syndrome: a systematic review and meta-analysis
Shaoyong Xu,Yi Wan,Ming Xu,Jie Ming,Ying Xing,Fei An,Qiuhe Ji
BMC Pulmonary Medicine. 2015; 15(1)
[Pubmed] | [DOI]
9 Obstructive sleep apnea is an important predictor of hepatic fibrosis in patients with nonalcoholic fatty liver disease in a tertiary care center
Swastik Agrawal,Ajay Duseja,Ashutosh Aggarwal,Ashim Das,Manu Mehta,Radha K. Dhiman,Yogesh Chawla
Hepatology International. 2015;
[Pubmed] | [DOI]
10 Public Health Implications of Obstructive Sleep Apnea Burden
Ileana Baldi,Achal Gulati,Giulia Lorenzoni,Kiran Natarajan,Simonetta Ballali,Mohan Kameswaran,Ranjith Rajeswaran,Dario Gregori,Gulshan Sethi
The Indian Journal of Pediatrics. 2014;
[Pubmed] | [DOI]
11 Obstructive Sleep Apnea Therapy and Metabolic Outcomes
Harneet K. Walia,Reena Mehra
Sleep Medicine Clinics. 2013; 8(4): 433
[Pubmed] | [DOI]
12 Effects of Weight Reduction Therapy on Obstructive Sleep Apnea Syndrome and Arterial Stiffness in Patients with Obesity and Metabolic Syndrome
Azusa Iguchi,Hajime Yamakage,Mayu Tochiya,Kazuya Muranaka,Yousuke Sasaki,Shigeo Kono,Akira Shimatsu,Noriko Satoh-Asahara
Journal of Atherosclerosis and Thrombosis. 2013; 20(11): 807
[Pubmed] | [DOI]


    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

  In this article
   Material & Methods
    Article Tables

 Article Access Statistics
    PDF Downloaded557    
    Comments [Add]    
    Cited by others 12    

Recommend this journal