© Borgis - Postępy Nauk Medycznych 4/2013, s. 281-289
*Monika Kuźmińska, Ewa Marcinowska-Suchowierska
Współistnienie otyłości i zaburzeń oddychania w czasie snu (ZOCS) u pacjentów kierowanych z podejrzeniem ZOCS
Coexistence of obesity and sleep-disordered breathing in patients with suspected sleep apnea syndrome polysomnography referred by physicians of different specialties
Internal, Family Medicine and Metabolic Bone Disease Department, Medical Centre of Postgraduate Education, Warsaw
Head of Department: prof. Ewa Marcinowska-Suchowierska, MD, PhD
Zaburzenia oddychania podczas snu (ZOCS), zwłaszcza w postaci obturacyjnego bezdechu sennego (OBS), są bardzo rozpowszechnione w populacji ogólnej. Otyłość to główny czynnik ryzyka. Najczęściej stosowanym wskaźnikiem oceny wielkości otyłości jest BMI (Body Mass Index). Celem tego badania było określenie związku między występowaniem zaburzeń oddychałnia w czasie snu a otyłością na podstawie oceny BMI i AHI u pacjentów, kierowanych do pracowni polisomnograficznej przez lekarzy różnych specjalności z powodu podejrzenia ZOCS. Poddano ocenie polisomnograficznej 960 pacjentów. Średnie BMI dla grupy z AHI < 5 (zdrowi): 29,96 kg/m2 – mężczyźni; 33,63 kg/m2 – kobiet, dla grupy z AHI ≥ 5 (chorzy): 32,05 kg/m2 – mężczyźni, 36,38 kg/m2 – kobiety. Różnice w BMI między zdrowymi a grupą pacjentów były istotne statystycznie dla obu płci (kobiety p = 0,03, p = 0,00036 mężczyźni). Istotną dodatnią korelację pomiędzy AHI i BMI stwierdzono w grupie kobiet chorych (r = 0,168, p = 0,029) i grupie chorych mężczyzn (r = 0,2571, p < 0,001). Nie wykazano natomiast istotnych statystycznie korelacji między AHI i BMI u zdrowych kobiet i mężczyzn. Dodatkowo podzielono pacjentów na trzy grupy wiekowe: 35 lat ≤ wiek ≤ 45 lat; 45 lat <wiek ≤ 55 lat, wiek> 55 lat. U kobiet chorych jedynie w grupie 35 lat ≤ wiek ≤ 45 lat stwierdzono statystycznie istotną dodatnią korelację między BMI i AHI (r = 0,369 p = 0,049), wśród mężczyzn korelacje te stwierdzono we wszystkich grupach wiekowych (35 lat ≤ wiek ≤ 45 lat: r = 0,27, p = 0,02; 45 lat <wiek ≤ 55 lat: r = 0,28, p = 0,004; wiek> 55 lat: r = 0,166, p = 0,015). Możemy stwierdzić, że w ogólnej populacji pacjentów z podejrzeniem zaburzeń oddychania w czasie snu o charakterze bezdechu sennego wyższe AHI jest skorelowane z wyższym BMI będącym wskaźnikiem otyłości.
Sleep-disordered breathing (SBD), particularly in the form of obstructive sleep apnea (OSAS), is highly prevalent in the general population. Obesity is a major risk factor for OSAS. BMI is the most frequently used obesity indicator. The aim of this study was to describe correlation between BMI and AHI in patients referred to sleep laboratory by physicians of different specialties because of suspicion of OSAS. 960 patients were included, all of them underwent polysomnographic evaluation. Polysomnographic parameters were judged in accordance with the recommendations. Mean BMI for the group with AHI < 5: 29.96 kg/m2 – men; 33.63 kg/m2 – women; for the group with AHI ≥ 5: 32.05 kg/m2 – men; 36.38 kg/m2 – women. The differences in BMI between healthy and patients groups were statistically significant for both sexes (women p = 0.03, men p = 0.00036). A significant positive correlation between AHI and BMI was found in women’s groups of patients (r = 0.168, p = 0.029) and men’s groups of patients (r = 0.2571, p < 0.001). No statistically significant correlations between AHI and BMI in healthy women and men were shown. We used also a division into three age ranges of patients: 35 y ≤ age ≤ 45 y; 45 y < age ≤ 55 y; age > 55 years. In both sex groups statistically significant positive correlation between BMI and AHI women (r = 0.375, p = 0.007) and (r = 0.17; p = 0.041) men (r = 0.296, p = 0.0008) and respectively for men patients in all age groups (35 y ≤ age ≤ 45 y: r=0.27, p = 0.02; 45 y < age ≤ 55 y: r = 0.28, p = 0.004; age > 55 y: r = 0.166; p=0.015). No statistically significant correlation between BMI and AHI for women in groups 45 y < age ≤ 55 y and above 55 y. We conclude that in the general patients population with suspected SBD higher AHI is correlated with also higher BMI which is obesity indicator.
Sleep-disordered breathing (SBD), particularly in the form of obstructive sleep apnea (OSAS), is highly prevalent in the general population. The term SBD has traditionally encompassed obstructive sleep apnea – OSAS.
Sleep-disordered breathing is characterized by repetitive periods of cessation in breathing (apneas) or reductions in the amplitude of a breath (hypopneas) that occur during sleep. These events are frequently associated with fragmentation of sleep, desaturations, and sympathetic nervous system activation with heart rate and blood pressure elevation. Obstructive sleep apnea, which represents cessation of airflow, develops because of factors such as anatomic obstruction of the upper airway related to obesity, excess tissue bulk in the pharynx, and changes in muscle tone and nerve activity during sleep. Repeated episodes of upper airway obstruction during sleep lead to significant hypoxemia.
Central sleep apnea represents cessation of airflow along with absence or significant reduction in respiratory effort during sleep and is more commonly present in case of congestive heart failure, neurologic disorders, or cardiopulmonary disease.
Mixed sleep apnea is a polysomnographic diagnosed type of apnea composed of central apnea in the beginning which changes to obstructive sleep apnea.
Obstructive sleep apnea syndrome (OSAS) is very prevalent especially amongst middle-aged men population, although increased recognition of the disease is observed also in women. According to epidemiological studies 2% of female and 4% men population are affected by OSAS (1).
Obesity is a major risk factor for OSAS, occurring in up to 50% of obese men (2-4) and this relationship has been confirmed in numerous studies in the world as well as performed at our institution (5).
As shown in epidemiological studies 70% of people who were diagnosed with OSA are obese (6). It is also specified that a weight gain by 10% increases the risk of developing OSAS 6 times. Weight loss in obese patients with OSAS were found to be part of OSAS reduction (7).
AIM OF STUDY
The aim of our study is to show how often diagnosis of sleep-disordered breathing coexists with obesity in male and female population diagnosed in our sleep laboratory.
MATERIAL AND METHODS
We examined retrospectively 960 (n = 960) polysomnograms recruited from patients (both sexes) referred to sleep laboratory for suspected sleep apnea. We included bariatric patients, patients before laryngological procedures, and patients who snored regularly. Patients were referred to sleep laboratory by physicians of many specialties: family doctors, surgeons, internists, otolaryngologists.
BMI (Body Mass Index) was used as the obesity indicator. BMI was calculated as weight in kilograms divided by the square of the height.
Using BMI value we describe as follows: overweight – BMI = 25 ÷ 29.9 kg/m2; obesity of first degree BMI = 30 ÷ 34.9 kg/m2; obesity of second degree BMI = 35 ÷ 39.9 kg/m2 and obesity of third degree BMI > 40 kg/m2.
Because of retrospective character of the study no written informed consent was needed, anyway we had ethical committee approval at The Centre of Postgraduate Medical Education.
Overnight polysomnography (PSG) study was performed in all patients by computerized systems (SOMNOmedics and NICOLET systems).
PSG included the following variables: electroencephalograms, electrooculograms, electromyelograms of submental muscules, electrocardiogram, airflow (nasal and oral), chest and abdominal efforts, snoring (microphone) and arterial oxyhemoglobin saturation and pulse (finger probe).
Polysomnographic recordings were evaluated with respect to:
– amount of disordered breathing during sleep,
– type disorders: obstructive sleep apnea, mixed, central, hypopnea,
– AHI (Apnea hypopnea Index),
– disease severity based on AHI: (a mild form of 5 <= AHI <= 15, moderate 15 < AHI <= 30; severe AHI > 30),
– the number of desaturations,
– the average oxygen saturation (Sa av),
– minimum oxygen saturation (Sa min),
– the length of non REM (non-rapid eye movement) sleep composed of light sleep stages 1 and 2 (1 + 2), and composed of deep sleep stages 3 and 4 (3 + 4),
– the length of REM (ang. rapid eye movement).
Obstructive apnea was defined as a cessation of airflow for at least 10 seconds. The event is obstructive if during apnea there is effort to breathe.
Central apnea was defined as a cessation of airflow for at least 10 seconds. The event is central if during apnea there is no effort to breathe.
Hypopnea is an abnormal respiratory event with at least a 30% reduction in thoracoabdominal movement or airflow as compared to baseline lasting at least 10 seconds, and with ≥ 4% oxygen desaturation, or less than 50% reduction baseline in the breathing amplitude with oxygen desaturation of 3% or an arousal. Obstruction is often inferred from thoracoabdominal paradox (8).
Apnea Hypopnea Index (AHI) was defined as the number of apneas and hypopneas per hour of sleep.
Patients with AHI ≥ 5 were considered as sleep apnea (OSAS) patients (9-12).
All statistical analyses were carried out using statistical software STATISTIKA version 6.
Differences were considered significant at p < 0.05.
Based on polysomnography (AHI ≥ 5) sleep apnea syndrome was diagnosed in 61.46% of participants (n = 590), respectively in 63.1% (n = 424) of male and 57.65% (n = 166) of female adults targeted in this study (n = 960) by physicians of various specialties. In patients with AHI ≥ 5 the average age of men was 53.5 years, for women 55 years, in people without the disorder with AHI < 5, the average age was 49.3 years for men, 47.9 years for women.
The calculated mean BMI for the study population was as follows:
– The group with AHI < 5 (healthy female and male): 31.17 kg/m2.
– The group with AHI ≥ 5 (patients female and male): 33.27 kg/m2.
The statistically significant difference in BMI between healthy and patients was found (p = 0.000247):
– The group with AHI < 5 (healthy): 29.96 kg/m2 – men; 33.63 kg/m2 – women.
– The group with AHI ≥ 5: 32.05 kg/m2 – men; 36.38 kg/m2 – women.
We found statistically significant difference in BMI between healthy and women patients (p = 0.03) and in men group (p = 0.000363).
We found statistically significant positive correlations between AHI and BMI in women’s groups of patients (r = 0.168, p = 0.029) and men’s groups of patients (r = 0.2571, p < 0.001). See figure 2 and table 2 (women) and figure 4 and table 4 (men).
No statistically significant correlations were found between AHI and BMI in healthy women and men groups. See figure 1 and table 1 (women) and figure 3 and table 3 (men).
In addition in both groups of patients (women and men) we identified for which age range of patients correlation between BMI and AHI is the strongest and statistically significant.
We used a division into three age ranges of patients:
1. 35 years ≤ age ≤ 45 years;
2. 45 years < age ≤ 55 years;
3. age > 55 years.
In woman patients group we have found statistically significant positive correlation between BMI and AHI (r = 0.369, p = 0.049; see table 5 and figure 5) for group 35 y ≤ age ≤ 45 y.
No statistically significant correlation between BMI and AHI for the group 45 y < age ≤ 55 y and above 55 years (see table 6, 7 and figure 6, 7).
Slightly different correlations were observed in men patients groups.
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1. Bassiri AG, Gulleminault C: Clinical features and evaluation of obstructive sleep apnea-hypopnea syndrome. [In:] Krygier MH, Roth T, Dement WC: Sleep Medicine, ed 3., Saunders, Philadelphia 2000; 869-878.
2. Marik PE: Leptin, obesity and obstructive sleep apnea. Chest 2000; 118: 569-571.
3. Young T, Palta M, Dempsey J et al.: The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med 1993; 328: 1230-1235.
4. Vgontzas AN, Tan TL, Bixler EO et al.: Sleep apnea and sleep disruption in obese patients. Arch Intern Med 1994; 154: 1705-1711.
5. Levinson PD, McGarvey ST, Carlisle CC et al.: Adiposity and cardiovascular risk factors in men with obstructive sleep apnea. Eur Resp J 1992; 103: 1336-1342.
6. Krieger J: Clinical presentations of Sleep apnoea. [In:] McNicholas WT: Respiratory Disorders During Sleep. Eur Respir Mon 1998; 3: 75-105.
7. Peppard PE, Young T, Palta M et al.: Longitudinal study of moderate weight change and sleep-disordered breathing. JAMA 2000; 284: 3015-3021.
8. Practice Parameters for the Indications for polysomnography and Realted Procedures: An Update for 2005. Sleep; 28(4): 499-452.
9. American Academy of Sleep Medicine Task Force. Sleep-related breathing disorders in adults: recommendations for syndrome definition and measurement techniques in clinical research. Sleep 1997; 22: 667-668.
10. Practice Parameters for the use of portable recording in the assessment of obstructive sleep apnea. Standard of Practice Committee of the American Sleep Disorders Association. Sleep 1994; 17: 372-377.
11. American Sleep Disorders Association EEG arousals, scoring rules and examples: A preliminary report from the Sleep Disorders Atlas task Force of ASDA. Sleep; 15: 173-184.
12. Practice Parameters for the Indications for Polysomnography and Related Procedures: An Update for 2005. Sleep 2005; 28(4): 499-52.
13. Grunstein R, Wilcox L, Yang TS et al.: Snoring and sleep apnoea in men: association with central obesity and hypertension. Int J Obes Relat Metab Disord 1993; 17: 533-540.
14. Davies RJ, Stradling JR: The relationship between Neck circumference, radiographic laryngeal anatomy, and the obstructive Steep syndrome. Eur Respir J 1990; 3: 509-513.
15. Davies RJ, Ali NJ, Stradling JR: Neck circumference and other clinical features in the diagnosis of the obstructive sleep apnea syndrome. Thorax 1992; 47: 101-105.
16. Levinson PD, McGarvey ST, Carlisle CC et al.: Adiposity and cardiovascular risk factors in men with obstructive sleep apnea. Eur Resp J 1992; 103: 1336-1342.
17. Millman RP, Carlisle CC, McGarvey ST et al.: Body fat distribution and sleep apnea severity in women. Chest 1995; 107: 362-366.
18. Shinohara E, Kihara S, Yamashita S et al.: Visceral fat accumulation as an important risk factor for obstructive sleep apnea syndrome in obese subjects. J Intern Med 1997; 241: 11-18.
19. Solylu AC, Levent E, Sanman N et al.: Obstructive sleep apnea syndrome and anthropometric obesity indexes. Sleep Breath 2012; 16(4): 1151-1158.
20. Wang YJ, Yang Y, Liu YS et al.: Evaluation on the accuracy of obese indexes in predicting obstructive sleep apnea-hypopnea syndrome in male adults. Zhoghua Liu Xing Bing Xue Za Zhi 2007; 28(10): 1021-1025.
21. Namysłowski G, Ścierski W et al.: Sleep study in patients with overweight and obesity. J Physiol Pharmacol 2005 Dec; 56 (Suppl 6): 59-65.
22. Dreher A, Patscheider M, Braun T: Comparison of obstructive Steep apnea in normal weighted and obese patients. Laryngorhinootologie 2012; 91(3): 182-184.