Student Research: Stephen Cho

MPH, Occupational and Environmental Medicine (OEM), 2015
Faculty Advisor: Debra Cherry

Correlation Analysis of Sleep Study Variables in Obese v. Non-obese Military Personnel Diagnosed with Obstructive Sleep Apnea


Abstract: Background/Introduction: Several studies have established an association between obesity and Obstructive Sleep Apnea (OSA), but the exact mechanism of interactions remains unknown. Military records offer an opportunity to compare OSA in obese and non-obese patients in order to further characterize the relationship between obesity and OSA, since high number of non-obese soldiers undergoes sleep studies due to unique culture of military medicine.

Methods: Our cross-sectional study explores different associations of diagnostic markers of OSA with selected physiologic sleep disturbances among obese (body mass index (BMI) ≥ 30 kg/ m2) and non-obese (BMI < 30 kg/ m2) patients with OSA. We reviewed and analyzed a database of OSA cases (N=342) comprised of soldiers diagnosed with OSA who underwent polysomnography (PSG) at a major military medical center in 2010. The cases were divided into obese (n= 176; body mass index (BMI) ≥ 30kg/m2) and non-obese (n=166; BMI <30kg/m2). Pearson correlations (r) were calculated for Apnea Hypopnea Index (AHI) among patients with mild OSA (5 ≤ AHI < 15), moderate/severe OSA (AHI ≥ 15), and both groups combined. PSG variables (arousal index, minimum oxygen saturation (O2 Sat)) were compared between the obese and non-obese groups.

Results: A statistically significant correlation between AHI and AI was only seen in moderate-severe OSA for obese patients (r = 0.55, p < 0.01) while significant correlations were seen in both mild (r=0.20, p=0.02) and moderate-severe OSA (r = 0.45, p < 0.01) for non-obese patients. On the other hand, statistically significant correlations between AHI and min O2 were found in both mild (r=-0.37, p<0.01) and moderate-severe (r = -0.38, p < 0.01) OSA for obese patients while the correlation was only found in mild(r = -0.26, p = 0.01) OSA for non-obese patients. Furthermore, the correlation between AHI (≥5, without a disease severity stratification) and min O2 sat was significantly (more than twofold) stronger for obese (r = -0.56, p < .01) than for non-obese patients (r = -0.27, p < 0.01) and the difference was also statistically significant (p < 0.01).

Conclusions: Results suggest that obstructive events during sleep in non-obese and obese patients with OSA might involve and even trigger different cascades of pathophysiologic events. The correlation between frequency of arousal (AI) and number of obstructive events (AHI) increases as the disease progresses and the depth of hypoxia was consistently associated with the number of obstructive events throughout the disease severity for obese OSA patients. However, although, the correlations between frequency of arousal and number of obstructive events also increases as the disease gets more severe, they were losing association between the number of obstructive events and the depth of hypoxia as disease gets worse. Given that physiologic disturbances from the primary pathologic event of OSA may differ as a function of obesity, future study should focus on clarifying the different clinical manifestations of OSA in obese and non-obese patients and may further consider comparing the efficacy of treatment(s) for OSA between obese and non-obese patient groups.