Effects of Gender and Obesity on Daytime Sleepiness in Obstructive Sleep Apnoea Patients

Objective: Identify factors associated with excessive day time sleepiness (EDS) in individuals with obstructive sleep apnea (OSA), and analyze the effects that obesity and gender have on excessive daytime sleepiness in such individuals. Methods: A total of 160 people were selected for this study. All the people have completed a clinical evaluation, and whose apneahypopnea index (AHI) > 10 events/hour of sleep on polysomnography were included in the study from the Department of otolaryngology. Results: The Mean age was 43.87±11.34 years, mean EDS score was 14.09± 4.91, and mean AHI was 43.88±20.66 events/hour of sleep. Male presented lower mean age, higher EDS scores, and more time in apnoea, whereas females presented with higher mean age, lower EDS scores, and less time in sleep apnea. The EDS score showed best correlation with duration of apnoea (r = 0.448; p < 0.01), peripheral oxygen saturation (SpO2; r = -0.458; p < 0.01) and AHI (r = 0.484; p < 0.01). The mean body mass index (BMI) was 27.41±3.86 kg/m2. Normal, Overweight, obese, and morbidly obese were observed in 20%, 61%, 18%, and 0.6% of cases, respectively. Severity of the disease best correlated with BMI (r = 0.421; p < 0.01). Conclusions: OSA is predominant in males (M/F 5:1), and obese population. Females diagnosed with OSA have higher mean age. However, EDS scores and time spent in sleep apnoea is lower in females. Higher BMI is associated with EDS, irrespective of gender.


Introduction
Excessive day time sleepiness (EDS), or hypersomnolence is today's rising concern in many societies. It is associated with obesity and is common in patients with obstructive sleep apnoea (OSA). Obesity and overweight prevalence have grown around the world, according to the World Health Organization says the worldwide percentage has tripled since 1975. The world's most populous country, China, the rate of overweight and obesity increases is even higher. [1] Obstructive sleep apnoea (OSA) is a disorder characterized by repeated events of impaired ventilation during sleep, caused by obstruction of the upper airways. [2] These events can be total (apnoeas) or partial (hypopneas) and are often associated with episodes of decreased arterial blood oxygenation level (i.e., desaturations) and brief arousals from sleep. The term OSA syndrome (OSAS) is often used to denote symptomatic OSA, e.g., OSA with daytime sleepiness. The diagnosis is made based on a polysomnographic recording of physiological signals related to breathing (e.g., nasal airflow, chest, and abdominal movement, heart rate, and blood oxygen saturation) during sleep. Sleep can be assessed by Electrophysiological technology such as direct polysomnography (PSG), consisting of electroencephalography (EEG), surface electromyography (EMG), and electrooculography (EOG), heart rate, or actigraphy or sleep diary. [3][4] OSA severity is often based on the number of apneas and hypopneas per hour of sleep (the Apnoea Hypopnea Index, AHI) and the number of oxygen desaturation events per hour of sleep (the Oxygen Desaturation Index, ODI). OSA has been associated with hypertension, cardiovascular disease, [5] traffic accidents, [6] obesity, and hyperglycemia/type II diabetes mellitus. [7] The reasons are not completely clear, although several factors have been identified that are associated with treatment adherence. The most commonly reported symptom of OSAS is daytime sleepiness, which is often measured using the Epworth Sleepiness Scale. [8] Both OSA and EDS are a public health problem. It not only leads to cognitive impairment but also reduced reflexes, resulting in an increased risk of traffic accidents and other mishaps. Also, EDS can have significant repercussions for work, social life, and quality of life. [9] The objective of this study was to evaluate the impact of gender and obesity in patients with OSA.

Equipment
Polysomnographic tests were performed using the standard method, with an electroencephalogram, electrooculogram (left eye and right eye), electromyogram (chin and anterior tibia), and electrocardiogram. All of the equipment employed was manufactured by Beijing Xin Yang Sheng poly Technology (China). Airflow was measured using a nasal cannula connected to a pressure transducer, and peripheral oxygen saturation (SpO2) was measured using a pulse oximeter (China).

Study Design and Sample Population
All of the patients were examined retrospectively. Patients with OSA of the 4th affiliated hospital of the Hubei University of Medicine and the sample population were the patients who were admitted into the 4th Affiliated Hospital of Hubei University of medicine from January 2016 to July 2017.

Ethical consideration and approval of informed consent
By using a pre-established protocol patient were included in the study, the patients have explained the purpose of the study and Once the verbal consent was obtained with the presence of a Nurse especially trained in Otolaryngology, a written form has given both in English and Chinese language to get the written informed consents.

Study population
A total of 160 patients diagnosed with OSA, who had been submitted polysomnography, were eligible for inclusion in the study. Of those, 160 patients were selected and subsequently evaluated over a one and half year's period. Patients were selected based on the following criteria: clinical chart data being complete; being over 16 years of age; and having received a diagnosis of OSA confirmed through polysomnography, apnoea-hypopnea index (AHI) being >10 events/hour of sleep. Clinical data were obtained through history and physical examination. Upon history, conducted with the patient and their family member, questions were asked regarding snoring, sleep apnea, and daytime sleepiness, including the patient history of traffic accidents. We investigated EDS using the criteria proposed by Johns MW. [10] The patients were asked how often they fell dozing in different situations, such as sitting and reading, watching television, meeting or theatre, traveling as a passenger, lying down in the afternoon, sitting and talking, sitting quietly after lunch, in a car while stopped in traffic. (Possible responses: never; slight; mild; moderate; and high). A score was attributed to each answer, ranging from 0 to 3, in which 0 corresponded to never and 3 corresponded to high. Therefore, the overall EDS score ranged from 0 to 24. [10] The body mass index (BMI) for each patient was obtained by dividing weight in kilograms by height in meters squared. Patients were categorized by weight status based on their BMI: normal (between 20 and 24.9 kg/m 2 ), overweight (BMI between 25 and 29.9 kg/m 2 ), obese (BMI between 30 and 39.9 kg/m 2 ), or morbidly obese (BMI ≥ 40 kg/m 2 ). Sleep stages were classified according to the criteria established by U. Rajendra Acharya, Yildirim O, and Baloglu UB. [10] Apnoea was defined as a reduction in airflow to ≤10% of the baseline value for 10 seconds or more, and hypopnea was defined as reductions in airflow of ≥50% accompanied by awakening and a ≥4% drop in SpO2. The AHI was calculated by dividing the total number of apnoea-hypopnea episodes by the number of hours of sleep. Based on AHI, OSA was classified as Mild (<15), moderate (15-30), or severe (>30). [11][12]

Data analysis
Data were stored and analyzed using the program Statistical Package for Social Sciences, version 22.0 (SPSS Inc, Chicago, IL, USA). Results are expressed as many cases, percentages, mean and standard deviation, or standard error. To analyze the correlations among variables with normal distribution, Pearson's linear correlation test was used, whereas Spearman's correlation coefficient was used for variables with non-normal distribution. All of the tests were two-tailed. Values of p < 0.05 were considered statistically significant.

Results
A total of 160 patients with OSA, 134 were male and 26 were female. The mean age was 43.87±11.34 years, varying from 16 to 77 years. Mode age was in between 41 to 50 years in both males and females. Clinical and polysomnographic data are shown, by gender (see Table 1). There was no difference in terms of reported snoring or apnoea with gender (chi-square; p > 0.05). Significant differences were observed between males and females in relation to the following: mean age (41.64 ± 9.74 years vs. 46.54 ± 12.30 years; p = 0.031); mean EDS score (14.17 ± 4.95 vs. 13.37 ± 4.92; p = 0.000); and meantime spent in sleep apnoea (167.96± 97.61 min vs. 124.25± 83.16 min; p = 0.041). There were no statistically significant differences between genders in terms of the remaining clinical and polysomnographic variables. The mean EDS score for the sample as a whole was 14.09±4.91. We found that EDS score correlated positively and significantly with the following variables: BMI; total sleep time; sleep efficiency; a percentage of total sleep time spent in REM sleep; the total number of minutes spent in sleep apnoea; and percentage of total sleep time spent in apnoea statistically significant. Although negative, correlations were observed between the EDS score and the following variables: age; sleep latency; mean SpO2; (see Table 2).
The mean BMI in the sample as a whole was 27.41±3.86. Of the 160 patients evaluated, 128 (80%) presented a BMI ≥ 25 kg/m 2 . There were 98 patients (61%) who were classified as overweight, 29 (18%) who were classified as obese, and 1(0.6%) who were classified as morbidly obese. Figure 2. Shows the AHI, total sleep time spent in apnoea in percentage, and the minimum SpO2 after the categorization of the patients by BMI. There were simultaneous increases in AHI and in the percentage of time spent in sleep apnea as increases in the degree of obesity. In obese patients both the AHI and percentage of time spent in sleep apnoea is almost similar to the lowest minimum SpO2. SpO2 is in all the variables normal, overweight, and obese patients have not much difference. We found that BMI correlated more strongly with the EDS score (r = 0.701; p < 0.001) than with any other clinical variable. (see figure  1b) The polysomnographic variables with which BMI correlated most strongly were AHI (r = 0421. p < 0.001), minimum SpO2 (r=-0.370; p<0.001) and sleep efficiency (r=0.214; p<0.001).
The OSA was mild (AHI < 15) in 10 patients, moderate (AHI between 15 and 30) in 36 patients, and severe (AHI > 30) in 113 patients. The mean EDS score was 12.72 ± 1.77 in the group with mild disease, 20.84 ± 3.96 in the group with moderate disease, and 54.42 ± 15.82 in the group with severe disease (p < 0.01). There were no differences among the groups in terms of age (p = 0.37). There were significant differences among the three OSA severity groups in terms of mean BMI (mild OSA: 27.40 ± 3.20kg/m 2 ; moderate OSA: 32.01 ± 1.25 kg/m 2 ; and severe OSA: 48.25 ±9.68 kg/m 2 . We also found AHI to correlate better with BMI and EDS scores than with any other clinical variables ( Figure 3a). As for the polysomnographic variables. AHI best correlate with body mass index (r=0.421; p<0.001). There is a negative correlation found with minimum SpO2 (r= -0.458; p<0.00). We also found AHI correlates better with BMI and EDS scores than with any other clinical variables (Figure 3a and b). As for the polysomnographic variables. AHI best correlate with body mass index (r=0.421; p<0.001).

Discussion
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 16 September 2020 doi:10.20944/preprints202009.0354.v1 Sleep disorders have been always a disturbing public health issue that affects the quality of life [13]. Therefore, we conducted a cross-sectional study involving patients with OSAHS. Gender-related characteristics were compared and the effects of obesity on the disease were analyzed. Our study identified the predominance of the disease in males. The severity of the disease was similar in both genders. Females presented higher mean age, lower EDS scores, and less time spent in sleep apnoea. Among the patients in our study, the mean age at diagnosis was similar to that reported in other studies. [14][15] Cases of OSA can occur from adolescence to old age. The fact that the incidence of the disease peaks the same decade both in females and males but in males it begins the first half of the decade whereas in the female latter half of the decade, as found in this and other studies. In females, it has been attributed to the effect of hormonal protection of premenopausal females against OSA. [16] A 5:1 male/female ratio was found in our sample of patients, whereas one of the most often cited articles on the prevalence of OSA in the literature reported a 2:1 ratio. [17][18] The lower proportion of females in the present study can be explained by the different presentation of the disease in females and by the fact that diagnosing OSA in females continues to be difficult.
[16] Also, the females in our study presented less EDS and remained less time in sleep apnoea, although disease severity in females was comparable to that observed in males. Various factors associated with EDS, such as obesity, alterations in sleep architecture, were identified in our study. However, the correlations between the EDS score and the remaining variables, although significant and ranged from weak to moderate, which suggests that other factors can be associated with EDS. Factors such as fragmented sleep due to respiratory events have previously been related to EDS. [19] EDS is one of the major consequences of OSA. EDS has a greater frequency of traffic accidents due to drivers falling asleep at the wheel. [20][21][22] Of the patients studied, 16% to 20% reported having accidents or near accidents due to falling asleep at the wheel. This is slightly lesser than the 29% previously reported. [21] Work accident was found to be nearly double in workers with OSA (OR = 2.18; 95% CI = 1.53-3.10). Occupational driving was associated with a higher effect size. [22][23][24] It has been shown that a higher frequency of traffic accidents is also associated with factors other than OSA: the use of alcohol, chronic sleep deprivation, and narcolepsy, restless legs syndrome, and periodic limb movements, circadian rhythm sleep disorders, and the use of medication. [23] Of the 160 patients, 80.0% were considered overweight or obese. In male BMI>25 is 85% whereas, in females, it is only 66%. In addition to being associated with OSA severity, obesity is one of the risk factors for cardiovascular diseases. [25] OSA and hypertension coexist, the prevalence of the OSA in hypertensive people has markedly increased.
[26] In our study, 51% of patients were found hypertensive.
We consider that our sample size was adequate to identify the effects of gender and obesity on excessive day time sleepiness in OSA patients. There were few major limitations of the present study such as the lack of a control group composed of gender-and age-matched individuals, lack of a wellequipped polysomnographic machine. Another limitation, in terms of our ability to evaluate differences related to gender and disease severity, was the heterogeneity of the sample; only 26 patients (16.25%) were female, 134 were male (83.75%), and 113 (70.62%) presented severe OSA.

Conclusion
OSA is considered as a male predominant (M/F 5:1), and common in the obese population. Females diagnosed with OSA have higher mean age. However, EDS scores and time spent in sleep apnoea are lower in females. Higher BMI is associated with EDS, irrespective of gender. Other elements such as fragmented sleep, minimum SpO2 levels, and degree of obesity were associated with EDS.

Conflicts of Interest: None to declare
Author Contributions: SKS: concept and protocol development, review plan, data collection, data analysis, manuscript writing, statistical analysis, review, and editing of the manuscript. ZHT, JF, SY: review, and manuscript supervision. YHZ: data and consent collection. AKS: editing of the manuscript.