Existing physiological databases have not been sufficiently detailed to provide relevant and important information for characterizing the pathophysiology of obstructive sleep apnea. Critical collapsing pressure (PcRit) is a standard method for determining upper airway patency during sleep, however is labor intensive and prohibits large-scale studies. Based on previously published data indicating R US does not significantly vary between groups, our aim was to develop an approach to estimate the P CRIT from airflow at atmospheric pressure (V atm). In a dataset of 126 subjects, where Pcrit and R US were measured using standard techniques. We then determined the minimum sample size required to estimate the R US mean and variance by utilizing a bootstrap procedure (30 times for n3 to 126). We first estimated the minimum number of subjects needed for obtaining a group for a two-tailed (z1.96) standard error for R US in the population. Then in 75 individuals, quantitative estimates of airflow were obtained at atmospheric pressure. Using the estimated R US and atmospheric, we determined an estimated P CRIT (Pcrit). Bland-Altman plots were generated to determine the agreement between the measured P CRIT and Pcrit. For the entire population the meanSEM R US was 231cmH 2O/L/s (95% CI: 21, 25). 40 subjects represent the minimum sample required to estimate the population variance within 2 SEM. In the subsample with atmospheric flow measurements, a linear regression model (Pcrit [cmH 2O]V @PN [L/s]x23[cmH 2O/L/s]), Pcrit ranged from 0 to 9.6cmH 2O. In the Bland-Altman analysis there was no mean difference between the measured Pcrit and Pcrit (0.01cmH 2O; p0.8) with upper and lower limits of agreement at 2.3cmH 2O. The variance of upstream resistance approaches a constant value in groups with approximately 40 subjects. Utilizing a fixed up-stream resistance to estimate Pcrit from the airflow at atmospheric pressure agrees with the measured values. These data suggest that measurements of quantitative airflow during standard polysomnography can be used to determine upper airway properties in large cohorts.