Objectives: We wished to determine the independent contribution of craniofacial dimensions of the upper airway to sleep-disordered breathing (SDB) in subjects who spanned the entire continuum of SDB. We also determined the interactive effects of body mass index (BMI) and age on the relationship between airway dimensions and SDB.
Design and subjects: We studied 142 nonclinical male subjects in a working community population (average age, 47 years; average BMI, 29; average ± SD apnea/hypopnea index [AHI], 20 ± 20/h), and 62 patients with obstructive sleep apnea (average age, 47 years; average BMI, 32; average ± SD AHI, 48 ± 35/h. We determined the AHI from overnight polysomnography and the number of oxygen desaturations (≥ 2%) per hour of sleep. We used lateral facial cephalometric radiographs to measure 41 anatomic landmarks and 55 dimensions in the upper airway.
Setting: A university hospital and a sleep-disorders clinic.
Data analysis: We used stepwise regression analysis to determine the independent contributions of measured variables to SDB.
Measurements and results: In the entire study population (n = 204), variations in BMI and six measures of craniofacial morphology accounted equally for one half of the total variance in AHI, and their interactive effects accounted for an additional 15%. Membership in the clinical or nonclinical group per se had no significant influence on these relationships. The single most important cephalometric variable in predicting AHI severity was the horizontal dimension of the maxilla (ie, porion vertical to supradentale [PV-A] distance). When the PV-A distance was relatively narrow (< 97 mm) the probability of having mild (AHI, 15 to 30/h) to severe (AHI > 30/h) SDB increased fivefold to sevenfold in nonobese subjects and threefold in obese subjects. Thus, in nonobese subjects (average BMI, 25 ± 2) and in subjects with narrow upper airway dimensions, four cephalometric dimensions were the dominant predictors of AHI, accounting for 50% of the variance. However, in subjects with a large anteroposterior facial dimension, BMI was the major predictor of AHI and a BMI > 28 increased the probability of moderate-to-severe sleep apnea by approximately fivefold. Finally, the combination of cephalometric dimensions and BMI accounted for an increasing amount of the variance in AHI as the severity of AHI increased.
Conclusions: Across the population spectrum of SDB, four cephalometric dimensions of the upper airway in combination with BMI accounted independently for up to two thirds of the variation in AHI; and the relative contribution of these two sets of determinants of AHI varied depending on airway size, obesity, and the amount of SDB.