Predictors and Prevalence of Severe Obstructive Sleep Apnea: A Cross-Sectional Study in Erbil, Kurdistan Region, Iraq.

Background Obstructive sleep apnea (OSA) is a common sleep disorder that's characterized by episodes of a complete or partial collapse of the upper airway with an associated decrease in oxygen saturation or arousal from sleep. According to the American Academy of Sleep Medicine (AASM), OSA is categorized based on polysomnography findings into mild, moderate, and severe. Objectives This study aims at determining the prevalence of the severities of OSA in Erbil, Kurdistan Region of Iraq, as well as discovering the predictors for severe OSA. Methods This was a cross-sectional study that was carried out from December 2021 to July 2023 on patients displaying OSA symptoms in a sleep study section of a private clinic in Erbil, Kurdistan Region of Iraq. A detailed questionnaire was designed to collect the data, and IBM SPSS Statistics for Windows, Version 26 (Released 2019; IBM Corp., Armonk, New York, United States) was used to analyze it. The polysomnography device used for the diagnosis of OSA was a Philips Respironics Alice NightOne home device, and Philips Respironics Sleepware G3 (Koninklijke Philips N.V., Amsterdam, Netherlands) was used to analyze the sleep data. Results A sample size of 328 OSA cases was analyzed. The results revealed a prevalence of 47% (155) for severe OSA. Apnea-hypopnea index (AHI) was negatively correlated with lowest and average oxygen saturation, while it was positively correlated with time spent with oxygen saturation under 89%, body mass index (BMI), and weight of the participants. Furthermore, stepwise multiple regression tests revealed BMI, age, gender, and heart failure as independent predictors for AHI. Conclusion This study highlights the links between OSA and various chronic health conditions. Furthermore, it underscores the importance of factors like age, obesity, and gender in influencing OSA severity. The identification of predictors for OSA severity can assist in risk assessment and personalized interventions.