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1 Department of Respiratory Medicine, Austin and Repatriation Medical Centre, Heidelberg, Victoria 3084; and 2 School of Behavioural Science, The University of Melbourne, Parkville, Victoria 3052, Australia
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ABSTRACT |
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 TOP
 ABSTRACT
 INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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In normal young men, there
is an abrupt fall in ventilation
(
E), a rise in upper
airway resistance (UAR), and falls in the activities of the diaphragm
(Di), intercostals (IC), genioglossus (GG), and tensor palatini (TP) at
sleep onset. On waking, there is an abrupt increase in
E and fall in UAR and an increase in the activities of Di, IC, GG, and TP. The aim of this study was to
determine whether these changes are age dependent. Nine men aged 20 to
25 yr were compared with nine men aged 42 to 67 yr. Airflow, UAR, Di,
and IC surface electromyograms (EMGs) and the intramuscular EMGs of GG
and TP were recorded. It was found that the falls in IC,
GG, and TP at the transition from 
to 
electroencephalogram (EEG)
activity were significantly greater in the older than in the younger
men (P < 0.05) and that the fall in Di was also greater, although this was only marginally significant (P = 0.15). The rise in GG at -to- transitions was also greater in the
older than in the younger men, and there was a trend for TP to be higher.
diaphragm; intercostals; genioglossus; tensor palatini; upper airway resistance
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INTRODUCTION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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IN NORMAL YOUNG MEN, there is an abrupt fall in
ventilation (E; Refs. 8, 32) and rise in
upper airway resistance (UAR; Refs. 14, 15) at the transition from to electroencephalogram (EEG) activity, that is, a transition from
wakefulness to sleep. As sleep progresses,
E remains depressed at a stable level, but UAR continues to rise until a stable level is reached in slow-wave sleep (16). When there is an awakening during sleep onset,
characterized by a change in EEG activity from back to , there
is an abrupt increase in E and fall in
UAR (14, 15).
The changes in E and UAR during sleep
onset are accompanied by changes in the electromyogram (EMG) activities
of respiratory muscles. The diaphragm (Di) and intercostal (IC)
activities fall abruptly at -to- transitions and increase
abruptly at -to- transitions. The activities of the upper airway
muscles, genioglossus (GG) and tensor palatini (TP), also fall abruptly
at -to- transitions and increase at -to- transitions. Two
to three breaths after the initial fall at -to- transitions,
there is recruitment of GG and its activity increases again. TP
activity continues to fall after the transition, and it is likely that
there is no recruitment so long as sleep is maintained (30, 31, 33, 34,
37). Although the Di shows some recruitment in the first 20 breaths, it
is likely that there is further recruitment as sleep becomes established given that other studies have shown that Di activity in
stable sleep is similar to or greater than that in quiet stable wakefulness (11, 29, 31). These findings indicate that the lower
E during sleep onset is at least in part
due to an initial reduction in central drive to the respiratory pump
muscles, that is, a withdrawal of the wakefulness stimulus. The
wakefulness stimulus is the component of ventilatory drive that is only
present during wakefulness. As sleep becomes established,
E remains lower than during wakefulness
because of inadequate recruitment of pump muscles to overcome the
greater resistance in the upper airway that occurs during sleep. The
increased UAR in sleep is probably due to the loss of tone of some
upper airway muscles such as TP during sleep, although its rise is
limited by the recruitment of other upper airway muscles such as GG.
These studies have implications for understanding the pathogenesis of
obstructive sleep apnea (OSA). It has been shown that there are falls
in the activities of GG and TP in the first two breaths of activity
after an -to- transition in subjects with OSA and that these
falls are greater than in normal subjects (20). Thus the repetitive
apneas and hypopneas in OSA may be due to an exaggeration of the
decrements in upper airway muscle activity during sleep onset,
particularly if there is also an anatomically narrow or excessively
compliant upper airway. Greater decrements in OSA patients could relate
to an elevated wakeful baseline muscle activity, as has been
demonstrated by Mezzanotte et al. (20), or to a lower sleep level of
activity in OSA compared with normal. Reduced muscle EMG activity in
these circumstances would be a reflection of reduced neural drive (22),
although reduced mechanical output of the muscles for any degree of
activation remains a further possibility in the pathogenesis of OSA.
The prevalence of OSA is greater in middle-aged and older men compared with young men (1, 3-7, 12, 25, 27, 38). This is in part related to an increase in body fat in older men (2, 5-7, 26, 36). Older subjects have also been shown to have increased pharyngeal resistance during wakefulness that was not due to differences in weight (35) and to have greater fluctuations in UAR than younger subjects during both wakefulness and non-rapid eye movement sleep (13). The ventilatory responses and the responses in the pressure generated in the first 0.1 s after airway closure during inspiration (P0.1; used as an indicator of central respiratory drive) to hypoxia and hypercapnia are reduced in the elderly. Given that these differences between older and younger subjects cannot be explained by differences in lung mechanics or Di strength (18, 24), they may occur because of reduced neural input to respiratory muscles. Naifeh et al. (21) found the ventilatory response to CO2 to be the same in older subjects compared with younger subjects, although their younger subjects were older than those in the other studies.
This study was undertaken to directly assess the effects of age on the
changes in E, UAR, and the EMG activities
of Di, IC, GG, and TP. Obesity can have a confounding effect on upper airway muscle activity; it has been shown that obese subjects without
OSA have greater GG EMG activity during non-rapid eye movement sleep
than during wakefulness, whereas subjects who are not obese have the
same GG activity in stable sleep and wakefulness (28). To avoid this
confounding effect, we studied only subjects who had a normal body mass
index (BMI).
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METHODS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Subjects. Eleven young men aged between 18 and 25 yr and twelve older men aged between 42 and 67 yr were studied. The younger subjects were university students, and the older subjects were departmental staff and veteran athletes. All were healthy, regular night-time sleepers and nonsmokers. Data from the younger men have been reported previously (37). The data from two of the younger subjects were discarded because one subject was found to consistently have flow limitation during sleep as well as hypopneas and apneas, and the computer file of the other subject was corrupted; the data from three of the older subjects could not be used because one subject was also found to consistently have flow limitation during sleep as well as hypopneas and apneas, and two subjects were unable to sleep adequately in the laboratory with the measurement constraints required by this study. The BMIs of the younger subjects ranged between 20 and 25 kg/m2, and those of the older subjects ranged from 23 to 26 kg/m2. There was no significant difference in BMI between the two groups. Each subject was studied for two nights separated by at least 1 wk. They were not specifically asked to sleep deprive themselves. The University of Melbourne Human Ethics Committee approved the study, and each subject gave written, informed consent before commencing.
Laboratory procedure.
The laboratory procedure, EMG recordings, measurement of ventilation,
and measurement of UAR were conducted as previously described (37).
Subjects were asked not to consume alcohol or caffeine on the day of
each study. They arrived in the sleep laboratory at 9:00 PM and, after
having the monitoring equipment attached, went to bed at around 11:00
PM in a dark, quiet room. They maintained a supine posture throughout
data collection. Initially, they were asked to remain awake for ~10
min before falling asleep so that some baseline EEG activity could
be collected. To obtain multiple sleep onsets, they were woken once
stable stage 2 sleep had been observed and were then allowed to fall
asleep again. This procedure was repeated until ~4 h of data had been collected.
or , as previously described
(14). Briefly, for each subject, 10 min of and 10 min of were
visually identified. This included 100-150 breaths during and
100-150 breaths during . For each breath in these two periods, the
frequencies of all negative peak-to-peak intervals in the EEG in the
0.3- to 50-Hz range were determined, and these intervals were divided
into those >8 Hz, that is, 0.125 s, and those <8 Hz. For each
breath, a ratio of the number of EEG intervals >8 Hz to the total
number of intervals was calculated. The distributions of EEG ratios for
the breaths in the selected 10 min of and for the breaths in the 10 min of were then plotted. The point of intersection between these
two distributions was identified, and the ratio corresponding to this
point of intersection became the criterion ratio for that subject. Thus
any breath that had a ratio below the criterion ratio was classified as
occurring during EEG activity, and any breath with a ratio above
the criterion ratio was classified as occurring during EEG
activity. This criterion ratio was then used to classify all breaths
for that subject as occurring either during or EEG activity.
This process was repeated for each subject. It is illustrated in
Fig. 1.
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, that being defined as at least three out of five consecutive breaths having predominantly activity. Phase 2 was defined
as the period from the first appearance of to the first sleep
spindle or K complex. Phase 3 was defined as the period from
the first sleep spindle or K complex to the attainment of stable stage
2 sleep. The development of sleep was described in terms of these phases rather than as stages of sleep because the changes between phases can be identified more precisely in time than changes between stages, which are arbitrarily defined in terms of epochs extending over
a period such as 30 s. Each breath could then be identified as
occurring during phase 1, 2, or 3 and breaths
within phases 2 and 3 could be identified as occurring
during or EEG activity.
EMG recordings. Diaphragmatic EMG was recorded with gold-plated, cup-shaped surface electrodes placed over the subcostal margin anteriorly, and external intercostal EMG was recorded with surface electrodes placed over the sixth intercostal space laterally. Fine wire intramuscular electrodes were used to record GG and TP EMGs. The wire was stainless steel, 3/1,000 in. thick, with a 1/1,000-in. Teflon coating. The Teflon was stripped from the end of the wire for 1.5 mm, and a 1-mm hook was fashioned in the end of the wire. The wires were inserted into the muscles perorally with hypodermic needles. The sites of insertion were anesthetized with a small amount of 2% lidocaine gel. While the electrodes were being inserted, the visual and auditory EMG signals were monitored to ensure that the electrodes were placed in muscle. To confirm that the electrodes were in the correct muscle, a series of maneuvers that have previously been shown to elicit responses from GG and TP was performed (19, 30). Jaw opening, jaw protrusion, blowing, sucking, swallowing, nasal breathing, and increased tidal volume produced increases in the EMG activity of TP. Tongue protrusion, the Muller maneuver, swallowing, and increased tidal volume produced increased EMG activity in GG.
Sections of the recording containing movement and other artifacts were removed before analysis. Furthermore, 100- to 160-ms sections of the Di and IC surface EMGs containing QRS complexes were removed and replaced by the data points in the 50- to 80-ms periods before and after the QRS complex using computer software. The raw EMG signals for all muscles were then integrated by using a 100-ms moving time average (MTA). For each muscle, several values were calculated on a breath-by-breath basis: 1) For each breath, the preceding expiration was divided into 10 equal time periods, and the mean EMG amplitude from the period with the lowest mean amplitude was used as the tonic activity for that breath. 2) Phasic activity was defined as the area under the inspiratory MTA curve above the tonic activity level identified in the previous expiratory phase. 3) Total inspiratory activity was calculated as the total area under the inspiratory MTA curve. It should be noted that because tonic activity was defined as the lowest level of activity during expiration, statistically all muscles were identified as having phasic activity.Measurement of ventilation. An oronasal mask with an air-filled cushion was strapped to the head tightly enough to eliminate any leaks. A heated pneumotachograph (Morgan) was attached to the mask. The dead space of the mask and pneumotachograph was 120 ml. The pneumotachograph was connected to a differential pressure transducer (Validyne model DP45-14) and to a carrier demodulator (Validyne CD75) that converted the output to a voltage signal. Airflow was calibrated with a flowmeter (Shorate 1355). The airflow signal was analyzed off-line to calculate extrapolated minute ventilation for each breath.
Measurement of UAR. Simultaneous recordings of mask pressure, epiglottic pressure, and airflow were used to calculate UAR. Mask pressure was recorded via a pressure transducer (Validyne DP45-28) and carrier demodulator (Validyne CD15). The other side of the pressure transducer was connected to an equal length of tubing left open to the atmosphere. Epiglottic pressure was measured with a transducer-tipped catheter (Millar model MPC-500) inserted through the nose and advanced until the tip was 1 cm below the base of the tongue visualized through the mouth without the tongue protruded. The nostril was premedicated with 0.05% oxymetazoline hydrochloride spray and 2% lidocaine gel. Computer software was used to calculate the pressure gradient across the upper airway from epiglottis to mask and to zero this pressure differential at the end of inspiration and the end of expiration, the points of zero flow. The phasing and time constants of the epiglottic pressure catheter and mask pressure measurements were adjusted to coincide. Although a number of resistance measures were generated by the software, the UAR reported was the resistance at peak airflow.
Data analysis.
Once each breath had been classified as occurring during or EEG
activity, computer software was used to identify sets of consecutive
or breaths occurring at either side of -to- transitions
and of -to- transitions. Thus for each transition four to ten
breaths were identified, two to five consecutive breaths and two to
five consecutive breaths. Each of these breaths then had an
identifiable position within a transition from 
5 to +5. For each
subject, the parameters of interest were averaged for each breath
position. These parameters were E, UAR
at peak flow, and the EMG activities of Di, IC, GG, and TP expressed as arbitrary units. The changes in these parameters between wake and sleep
were determined by the changes in EEG activity between and without reference to changes in the respiratory parameters. Each
subject had to have data from at least five breaths at a particular
breath position for those data to be included, so that an aberrant
breath from one subject would not unduly bias the group data. Changes
beyond five posttransition breaths were also studied, but data from
phases 2 and 3 needed to be combined, and for this
latter analysis there was no minimum requirement for the number of data
points at a particular breath position.
5 to 2 for each of
the four types of transition, i.e., to in phase 2, to in phase 3, to in phase 2, and to
in phase 3. Four pretransition breaths were chosen as the
baseline to overcome the inherent variability seen in any physiological parameter. Using the 5 to 2 breaths as a comparison for
the posttransition breaths better reflects any changes at transitions than comparing each of the posttransition breaths with a single pretransition breath. Breath position 1 was not used in the
determination of the baseline because a breath in the +1 or 1
position may have the change in EEG activity occurring during it and so
may not be purely or activity. It should be noted that the lack of precision in the classification of breaths at transitions results in
some smoothing of the data over the transition and can create the
impression that changes in the parameters at transitions have commenced
before the -to- transition.
Statistics.
To determine whether there were significant changes at -to- and
-to- transitions, single sample t-tests were performed comparing the mean data from all of the subjects at each of the first
five posttransition breath positions with a reference value of 100 for
E, UAR, and the EMG activities of the
four muscles for phase 2 and for phase 3. A 2 × 2 × 5 ANOVA with repeated measures on phase and
breath position was used to assess the effect of age, phase, and breath
position on E, UAR, and the EMG
activities of the four muscles. The breath position data for each
parameter were the values at each of the first five posttransition breaths at -to- transitions; there was a separate 2 × 2 × 5 ANOVA for the five posttransition breaths at -to-
transitions. To assess the effect of age and breath position in the 20 posttransition breaths at -to- transitions, a 2 × 20 ANOVA was performed.
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RESULTS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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An example of the raw data from an individual older subject is shown in
Fig. 2. It illustrates the dramatic fall in
activities of the four muscles at an -to- transition and the
precision with which the changes are associated with the state changes.
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The group data for all subjects are shown in Tables
1 and 2. The
group data for the younger and older subjects are illustrated in Figs.
3 and 4. At
-to- transitions, E in each of the
five breaths immediately after the transition was significantly
lower than the average of the five preceding breaths in both
phases 2 and 3, whereas UAR was significantly higher in each
breath. The EMG activity of Di was significantly lower across each
of the five breaths than the preceding five breaths in
phases 2 and 3. IC activity was significantly lower in
each of the first two breaths in phase 2 and significantly
lower in four of the five breaths in phase 3. GG activity
was significantly lower in each of the first three breaths in
phase 2 and significantly lower in all the five breaths in
phase 3. TP activity was significantly lower in all the five
breaths in both phases 2 and 3.
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At -to- transitions for all subjects,
E was significantly higher and UAR was
significantly lower in each of the five breaths than the preceding
five breaths in both phases 2 and 3. There was a
trend for Di activity to be higher in each of the first four breaths in phase 2, and Di activity was significantly higher in
the first three breaths in phase 3. IC activity did not
differ significantly between the and breaths. GG activity was
significantly higher in the first posttransition breath in phase
2, and in the first two posttransition breaths in phase 3.
TP activity was significantly higher in each of the posttransition breaths in phase 3.
With respect to the age effects, there were significant group effects
showing greater changes at -to- transitions in the older subjects
for UAR, IC, GG, and TP, and a trend for
E (P = 0.09) and Di (P = 0.15), and significant phase effects showing that phase 3 changed more than phase 2 for E,
UAR, Di, and IC but not GG and TP. There was no difference in IC EMG
activity between and in the younger subjects, yet its activity
was lower in than in the older subjects.
The 2 × 20 ANOVA on the 20 posttransition breath data at
-to- transitions showed that there was a significant age group effect showing lower activity in the posttransition breaths in the
older subjects for IC and UAR, but not for
E, Di, GG, or TP.
With respect to the -to- transition data, there was a significant
age group effect for UAR and GG and a trend for
E (P = 0.08) and TP (P = 0.08), but not for Di or IC, and a significant phase effect for
E, UAR, and Di and trends for
GG (P = 0.09) and TP (P = 0.10), but not
for IC.
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DISCUSSION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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This study has shown that during sleep onset the decreases in IC, GG,
and TP activities and the increases in UAR are greater in older than
younger normal men, and there were trends for
E and Di activity to be lower. On waking
from sleep, the increase in GG and fall in UAR was greater in older
than younger men, and there were trends for
E and TP activity to be higher. The falls in E and EMG activity and rise in UAR at
-to- transitions and rises and falls at -to- transitions
were greater in phase 3 than in phase 2, although not
all of these differences were statistically significant. These phase
differences were not different between the older and younger groups.
The demonstrated greater fall in the activities of respiratory muscles
at -to- transitions in older men compared with younger men could
occur by two mechanisms. One possibility is that older men have greater
muscle activity during wakefulness yet fall to the same level as the
younger men during sleep. Alternatively, the muscle activities may be
similar during wakefulness, but the older men have a lower level during
sleep. As the EMG is recorded in arbitrary units, it is possible to
directly compare only the relative changes in EMG activities between
the two groups and not the absolute activities of the muscles in either
sleep or wakefulness. Thus our data cannot distinguish between the two explanations. Also, it is not possible to relate EMG activity directly
to UAR because UAR is dependent not only on neural activity and upper
airway muscle activity but also on the mechanical output of individual
muscles, the interactions between the upper airway muscles, the anatomy
of the upper airway, and the driving force during inspiration. Thus
examining the UAR of the two groups does not help in determining why
there is a difference in the changes at sleep onset between older and
younger men.
Nevertheless, irrespective of the relative activities in wakefulness,
it is possible that the greater fall in upper airway muscle activity
during sleep onset in older men may contribute to the greater
prevalence of OSA in older men. The older men in our study had normal
BMIs and did not have sleep apnea, but if they were predisposed to
having sleep apnea because of truncal obesity or some other cause of a
narrow or more compliant upper airway, the greater fall in upper airway
muscle activity might have been critical and led to sleep apnea,
whereas in a younger man with the same degree of upper airway
functional narrowness, but a lesser fall in upper airway muscle
activity during sleep onset, sleep apnea might not have resulted. Our
data also support the hypothesis that the higher prevalence of periodic
breathing in the elderly may be explained by respiratory instability
associated with changes in state (23). As older men have greater
changes in the activity of their respiratory muscles associated
with state changes, fluctuations in state during the sleep
onset period would produce greater fluctuations in
E, predisposing to periodic breathing.
The difference between the fall in Di, GG, and TP activities in older
and younger men would appear to be a transient phenomenon because it
was confined to the first five breaths of , but no difference was
found when the first 20 breaths were assessed. This finding is
consistent with other studies (28) showing no difference in GG activity
in stable sleep between young and older thin men given that their study
did not specifically examine the first few breaths after transition.
The lack of a difference in E is also
consistent with the finding (27) that the difference in
E between quiet wakefulness and
established stable sleep was the same in young men as older men,
although E was more variable in both
sleep and wakefulness in the older men. It would thus appear that the
direct sleep influence on both respiratory pump and upper airway
muscles leading to an immediate fall in their activities is greater in
older than younger men. These differences then disappear in a time
frame consistent with the effects of reflexes to chemical and
mechanical factors beginning to influence the respiratory muscles so
that difference in activity of the muscles between the age groups is no
longer apparent.
We deliberately chose to compare a group of middle-aged men with a young group rather than study an elderly group because other studies have indicated that sleep-related influences on respiratory variables change as young men become middle-aged, with little further change as they become elderly (17, 25). There was no relationship between age and sleep-disordered breathing in males over the age of 60 yr in two studies addressing this issue (9, 17).
The tendency for the changes of both respiratory pump and upper airway
muscle activities at -to- and -to- transitions to be
greater in phase 3 than phase 2 is consistent with
previous work (15, 37). This may be due to a greater difference in central neural activity between and in phase 3 than in
phase 2 so that changes in state during phase 3 will
produce greater changes in muscle activity than during phase 2.
It has been shown that the difference in response to chemoreceptor
drive between and is greater in phase 3 than in
phase 2 (10), and this would explain the greater muscle changes
in phase 3 than in phase 2. Another possibility is that
there is an arousal complex producing greater muscle activity with
shifts from to and that this arousal response has a greater
influence in phase 3. Finally, there is also a methodological
explanation. The periods of between periods of tended to be
longer in phase 2 than in phase 3, in which a period of
may only last for 2 or 3 breaths, and the periods of were
generally briefer in phase 2 than in phase 3. This
means that the five breaths preceding an -to- transition in
phase 2 represented more stable , whereas the breaths
before an -to- transition in phase 3 may have been the
same or arousal breaths that form part of the -to-
transition. Thus the pretransition activity was higher in phase
3 than in phase 2, at least in part explaining the greater
falls in muscle activity at -to- transitions in phase 3 than in phase 2.
In Figs. 2 and 3, there is an impression that a change has occurred in
some variables before the actual transition point in the EEG. We
believe that this is due to the -to- change occurring during a
breath and not at the end of one breath and start of another. Thus at
-to- transitions some of the 1 breaths will contain
some activity and some of the +1 breaths will contain some activity. This is the reason that the baseline chosen was 5 to
2 breaths rather than 5 to 1 breaths.
The posttransition data were compared with the data from several
pretransition breaths because there was some breath-to-breath variability during stable activity and stable activity. This can be regarded as physiological noise. If the posttransition breath
data were compared with various individual pretransition breath data,
the effect of a change in state on the relevant parameter could be
over- or underestimated. To avoid this problem, it was decided to
determine whether there was a significant change in the posttransition
breaths relative to the pretransition baseline defined above.
In summary, at transitions from EEG activity to activity, there
are significant falls in E and the EMG
activities for Di, IC, GG, and TP and a rise in UAR. The changes in
E and UAR and the activities of all the
muscles were greater in normal older men than in normal younger men. At
transitions from -to- activity, there was an increase in
E, a fall in UAR, and increases in the
activities of Di, GG, and TP in phase 3. The changes in
E, UAR, GG, and TP were greater in the
older than in the younger men. These differences may help explain the
greater prevalence of sleep-disordered breathing with increasing age.
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ACKNOWLEDGEMENTS |
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This work was supported by a grant from the Department of Veterans' Affairs, Australia. C. J. Worsnop is a National Health and Medical Research Council of Australia Postgraduate Medical Scholar.
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FOOTNOTES |
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The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. §1734 solely to indicate this fact.
Address for reprint requests and other correspondence: C. J. Worsnop, Dept. of Respiratory Medicine, Bowen Centre, Austin Campus, Austin and Repatriation Medical Centre, Heidelberg, Victoria 3084, Australia (E-mail: christopher.worsnop{at}armc.org.au).
Received 20 January 1999; accepted in final form 17 December 1999.
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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