Background. The occurrence and severity of excessive daytime sleepiness (EDS) vary considerably among obstructive sleep apnea (OSA) patients. This study was designed to investigate the characteristics of EDS and identify its contributing factors in OSA patients. Methods. This was a cross-sectional study from a tertiary medical center in China. A total of 874 consecutive patients with newly diagnosed OSA were included. Subjective daytime sleepiness was assessed with the Epworth Sleepiness Scale (ESS). The subjects were assigned to the non-EDS group (582 patients), mild to moderate EDS group (227 patients), and severe EDS group (65 patients) according to the ESS scores. The clinical features and polysomnographic parameters were acquired and analyzed to identify the differences between groups and the determinants of EDS. Results. The age of patients with severe EDS (49.5 ± 11.3) was slightly greater than that of patients with mild to moderate EDS (44.5 ± 10.2) (p<0.05) and non-EDS patients (45.2 ± 12.0) (p<0.05). Body mass index (BMI) was highest in the severe EDS group (29.1 ± 3.6 kg/m2) (p<0.0001), intermediate in the mild to moderate EDS group (27.9 ± 3.3 kg/m2), and lower in the non-EDS group (26.8 ± 3.3 kg/m2). Logistic regression analysis showed waist circumference, memory loss, work/commute disturbances, and sleep efficiency were independently associated with mild to moderate EDS, and the microarousal index, apnea-hypopnea index (AHI), and saturation impair time below 90% were independent contributing factors of mild to moderate EDS. Meanwhile, age, neck circumference, gasping/choking, memory loss, work/commute disturbances, and sleep latency were independently associated with severe EDS, and the AHI and mean SpO2 were independent contributing factors of severe EDS. Conclusions. OSA patients with various severities of EDS are more obese and have more comorbid symptoms compared to patients without EDS. Sleep fragmentation, respiratory events, and nocturnal hypoxia may be predictors of EDS. Comprehensive consideration of demographic, clinical, and polysomnographic factors is required when evaluating OSA patients.