Risk factors for obstructive sleep apnea in non-obese Korean patients: Significance of body weight

Abstract

The aim of this study is to evaluate if there is an association between body weight and obstructive sleep apnea even in patients who are not obese. From our hospital database, we identified 139 patients who underwent an overnight polysomnography. The inclusion criteria were patients (i) who visited our hospital with a chief complaint of snoring or apnea that was witnessed by a sleep partner, and (ii) with a body mass index <25 kg/m 2 . We compared the clinical variables, polysomnographic variables, and Epworth Sleepiness Scale scores in subjects with and without obstructive sleep apnea. Additionally, correlation analysis was performed between apnea-hypopnea index and age, body weight, and neck circumference. Of the 139 patients, 62 patients met the inclusion criteria for this study. Forty-two of the 62 patients were diagnosed with obstructive sleep apnea. Patients with obstructive sleep apnea were older, had higher body weight, larger neck circumference, and greater apnea-hypopnea index, longer time of pulse oxygen saturation <90%, and lower minimum pulse oxygen saturation compared to those without obstructive sleep apnea. In addition, apnea-hypopnea index was found to be positively correlated with age, body weight, and neck circumference. Multiple logistic regression analysis showed that old age, high body weight, and large neck circumference were independently associated with obstructive sleep apnea. We demonstrated that there was a significant association between body weight and obstructive sleep apnea in non-obese patients, and further prospective study is needed to evaluate the beneficial effect of weight loss on obstructive sleep apnea in non-obese patients.

Differences in Sleep Apnea Pattern According to Obesity: Clinical Study Using Polysomnographic Data

“…This is consistent with Park et al's results. 4) This study supports that nonobese patients with OSA can also benefit from weight loss, although this study did not demonstrate any direct evidence about a beneficial effect of weight loss on OSA in them.…”

“…Previous studies reported that neck circumference was one of the factors associated with the severity of OSA, even in nonobese. 4,5) Considering that neck circumference means the quantity of adipose tissue distribution around upper airway, our finding suggests that other pathogenic model is needed for nonobese patients with OSA, rather than earlier model (airway obstruction, especially at the level of oro and hypopharynx).…”

“…However, the latter is associated with neck adiposity and increased upper airway fat, resulting in OSA even in normal weight subjects. 3,4) Park et al 4) reported that OSA was diagnosed in 67.7% of Korean patients with BMI <25 kg/m 2 . They concluded that body weight was significantly correlated with OSA in nonobese Koreans.…”

Nasopharyngeal collapse can be identified on radiography in healthy male Beagle dogs without cardiopulmonary diseases

“…Similarly, obesity has been known as a main risk factor for obstructive sleep apnea in humans, where the deposition of fat around the airways is associated with apnea predisposition 3,21 . Furthermore, there was a significant association between body weight and obstructive sleep apnea in non‐obese patients, and the apnea‐hypopnea index was positively correlated with body weight and neck circumference 22 . However, another study reported that pharyngeal collapsibility during sleep and preferential fat deposition around the upper airways were independent of body mass index (calculated as weight divided by height in meters squared) 23,24 .…”

“…3,21 Furthermore, there was a significant association between body weight and obstructive sleep apnea in non-obese patients, and the apnea-hypopnea index was positively correlated with body weight and neck circumference. 22 However, another study reported that pharyngeal collapsibility during sleep and preferential fat deposition around the upper airways were independent of body mass index (calculated as weight divided by height in meters squared). 23,24 This may reflect different aspects between body mass index and BCS, which relies on visual and palpable characteristics to estimate the degree of obesity.…”