In a randomly selected probability sample of community-dwelling persons 65 yr and older, the prevalence rate of sleep-disordered breathing was 24% for AI ≥ 5 and 62% for RDI ≥ 10.
Overall, the severity of sleep-disordered breathing in this sample was somewhat mild. Of the 427 volunteers studied, 10% had AI ≥ 10, 4% had AI ≥ 20 [which some authorities regard as an indication for prompt intervention (28
)] and 1% had AI ≥ 40. However, the group had a very high number of hypopneas with 44% having RDI ≥ 20. In a previous study in an elderly nursing home population, it was shown that RDI ≥ 50 was predictive of increased mortality. Most of the nursing home patients were also severely ill with multiple illnesses (29
). Nevertheless, in the current sample, 18% had RDI ≥ 50.
It seems quite certain that the prevalence of sleep-disordered breathing is greater among the elderly than among younger adults (30
). There were no significant correlations between age and apnea indices in this sample, which started at age 65 and covered a narrow age range. It appears that most of the increase in apnea indices associated with aging occurs before age 65 is reached. One cannot ignore the possibility that people with the more severe sleep-disordered breathing died before reaching age 65, as there are now several reports linking severe sleep apnea with increased mortality (28
). We are continuing to study these questions with further research.
In sleep clinic samples, sleep apnea has appeared predominantly to be a disease of men (30
). The rate of sleep-disordered breathing was significantly higher among men in this study also, and male gender was a predictor of RDI ≥ 10. The rate of AI ≥ 5 in these postmenopausal women, however, was substantially higher than that reported in premenopausal women (21
Given the high prevalence of sleep-disordered breathing, it is important to inquire whether clinicians can reliably recognize sleep-disordered breathing by history alone. In our experience they cannot. Our logistic regression models indicate that there are only a few significant independent predictors of AI ≥ 5 and RDI ≥ 10. Despite statistical significance, all of the associations between interview variables and respiratory disturbance indices were small. No combination of demographic variables and symptoms allowed reliable prediction of the apnea index. Neither model was both sensitive and specific. New factors that are clear-cut indicators of the conditions, or of their absence, are needed before a useful predictive model can be developed.
Our results are consistent with the hypothesis that sleep-disordered breathing causes symptoms of excessive daytime sleepiness and disturbed sleep at night in the elderly (34
). Histories of waking up confused or wandering at night, lack of a bed partner, use of dentures, reported stoppage of breathing at night and reported leg kicks were associated with higher apnea in univariate analyses ( and ), but these associations were not independently significant in the multivariable analyses. In general, BMI was the strongest predictor. Only 65% of subjects could report whether or not they snored. Among those who could report, snoring was as strong a correlate of OI as BMI; however, snoring did not contribute to the discriminative prediction of RDI. Reported total sleep time had little correlation with apnea indices. Elsewhere, we examined this association and showed that higher apnea indices are found both among subjects with under 7 hr reported sleep and among those reporting over 8 hr sleep (i.e. a U-shaped association) (35
At the time this study was begun, it did not seem practical to calibrate the Respitrace. More recently, we have examined the issue of calibration by blindly scoring calibrated and uncalibrated Respitrace records. Correlations for total apneas (rs
= 0.84), total hypopneas (rs
= 0.95), total events (rs
= 0.88) and type of apnea (obstructive, rs
= 0.87; central, rs
= 0.71; mixed, rs
= 0.68) were all medium to high and were all significant (21
). In the uncalibrated records, apneas tended to be underscored while hypopneas were over-scored. Therefore, the uncalibrated recordings used in this study may actually give too conservative an estimate of apneas.
The current study was only successful in obtaining full data on 23% of the random sample identified. It is unlikely that any study that requires objective sleep recording can obtain high compliance from a random population sample. Paying the volunteers a minimal amount had no effect on cooperation. Larger monetary rewards or other inducements powerful enough to produce high compliance could bias the sample in other ways. To reduce this problem, the study was prospectively designed to identify those randomly selected volunteers that refused to be recorded and to assess the extent to which compliance would bias our conclusions by selecting for particular types of subjects. Thus, demographic features of persons identified by telephone interview and home interview (without recording) were obtained for comparison with volunteers completing the study. Although we did demonstrate that there were some sampling biases in this volunteer sample, we also tried to demonstrate that no sampling bias distorted the results to a serious extent. None of the variables in which significant biases were demonstrated were retained by the final logistic models. In addition, the low correlations of these factors with measured apnea indicated that these sampling biases could not have seriously affected prevalence estimates.
To determine point prevalence, the single-night recordings that we utilized seemed adequate, but the question arises whether a single overnight recording is a reliable predictor of sleep apnea over an extended period of time. In three studies, using our technology, we have found that the night-to-night correlations for apnea indices range from rs
= 0.76 to rs
= 0.94 (p < 0.01). Others have reported similar findings (36
). We have also been able to rerecord 30 of the initial volunteers for this study after an average lapse of 4.6 yr. The correlation of apnea indices over these 4.6 yr was rs
= 0.50 (p < 0.01). The correlation for RDI was rs
= 0.69 (p < 0.001) (37
). These results demonstrate substantial night-to-night variability in apnea indices with even greater variability over several years. A substantial proportion of the variance between questionnaire-predicted and observed apnea indices may be related to such night-to-night variability in sleep apnea. This variability must likewise affect the reliability of sleep clinic polysomnograms. In other words, we would probably have obtained higher correlations of apnea indices and symptoms if we could have recorded more nights for each subject.
At the time this study was planned, very little was known about the prevalence of sleep-disordered breathing in any age group. This study showed that mild sleep-disordered breathing is exceptionally prevalent among elderly Americans. These disturbances are significant, but weakly associated with various symptoms. The clinician could not reliably screen for these sleep disturbances on the basis of demographic factors, signs and symptoms. In this final report, we now see that in the elderly mild sleep-disordered breathing is usually occult. It is now necessary to go beyond the question of prevalence with longitudinal designs. Repeated recordings are needed to better assess the impact of sleep-disordered breathing on morbidity and mortality in the elderly.