Batchelor et al., J Sleep Disor: Treat Care 2014, 3:1
http://dx.doi.org/10.4172/2325-9639.1000128
Journal of Sleep Disorders:
Treatment & Care
Research Article
Subjective and Objective Sleep
Measures in Older People with a
History of Falls
Frances A Batchelor1*, Susan B Williams1, Briony Dow1,2,
Xiaoping Lin1, Vanessa Wilkinson3, Karen Borschmann1,
Melissa A Russell2, Kate E Crowley3, Keith D Hill1,4 and David J
Berlowitz2,3
Abstract
Study background: Falls are common in older people, with
approximately 40% of those aged 80 and over falling each year.
Sleep difficulties in older people have been recognized as a risk
factor for falls. Most clinical and research information on sleep in
older people, particularly in older fallers has been self-reported.
Therefore, the objectives of this study were to describe the level
and type of sleep problems in community-dwelling older people who
have a history of falls, and to investigate whether sleep difficulties
are associated with falls and falls risk.
Methods: We undertook a cross-sectional observational study of
objective and subjective sleep falls risk and falls history. Thirty-five
community-dwelling Veterans or war widow/ers who had fallen
at least once in the previous year were recruited. Objective inlaboratory polysomnography and in-home assessment of subjective
sleep and falls risk profile were assessed.
Results: A high level of specific sleep disorders was found. This was
despite participants reporting minimal sleep issues. Daytime state
sleepiness was significantly higher in multiple fallers compared to
single fallers and those with high falls risk had significantly higher
state and trait sleepiness.
Conclusions: Sleep apnea, periodic leg movements and prolonged
periods of wakefulness after sleep onset were common. Falls risk
was more strongly associated with measures of state and trait
sleepiness than sleep apnea severity.
Keywords
Ageing; Accidental Falls; Polysomnography; Sleep Disorders
Abbreviations
AHI: Apnea-Hypopnea Index; AQoL: Assessment of Quality of Life
scale; BNSQ: Basic Nordic Sleep Questionnaire; ESS: Epworth
Sleepiness Scale; FROP-Com: Falls Risk for Older People in
the Community; KSS: Karolinska Sleep Scale; OSA: Obstructive
Sleep Apnea; PLM: Periodic Leg Movement Index; PSG:
Polysomnography
a SciTechnol journal
people aged 80 and over falling each year [3]. Falls can have serious
consequences including injury, fear of falling, physical and functional
decline, residential care admission and depression. There are many
well established risk factors for falls including balance impairment,
decreased strength, polypharmacy, and visual problems [4]. Recently,
several studies have found an association between sleep and falls
in older people [5-8]. For example, people experiencing daytime
sleepiness and poor sleep efficiency (less than 70% of time in bed spent
sleeping) were found to have significantly increased odds of falling
compared to those without these difficulties [6,7]. Additionally, it
has been found that daytime napping is independently associated
with falls risk in older women (after adjustment for age and other
co-variates) [7]. Potential mechanisms for the association between
sleep disorders and falls include decreased reaction time [9], and
the effect of sleep deprivation or fragmentation on postural control
[10], cognitive function and motor performance [11]. Despite the
associations between falls and sleep difficulties, most research has
focused on subjective sleep [12]. Although some studies have utilized
actigraphy to quantify activity during sleep [6], no published studies
examining the associations between sleep and falls have reported
objective sleep measures obtained using polysomnography. In
order to better understand the relationship between falls and sleep,
evaluation of sleep using polysomnography in addition to subjective
sleep assessment is required. The objectives of this exploratory study
were to include both objective laboratory-based polysomnography
and subjective information in the assessment of a group of active
older fallers to describe sleep problems, and to evaluate the association
between falls risk and specific sleep difficulties.
Materials and Methods
Study design and participants
This study was a cross-sectional observational study. Thirty-five
World War II Veterans, war widow/ers or members of the Veteran
community (mean age 83 years), who were community dwelling
and who had fallen at least once in the previous year were recruited.
Other eligibility criteria included being able to walk independently
with or without an aid. People were excluded if they had cognitive
impairment (defined by an Abbreviated Mental Test Score [13] <7),
were unable to follow simple instructions or communicate in English,
or if they lived more than 100 kilometers from the sleep laboratory.
Participants were recruited through Veteran community newsletters,
National Ageing Research Institute newsletters and presentations by
project staff at Veteran clubs and groups.
Introduction
Data collection
Falls are a common problem for older people. Each year
approximately 30% of those aged 65 years and older sustain a fall
[1,2]. This increases with age, with 40% of community-dwelling
The project was approved by the relevant Ethics Committee.
Informed consent was obtained for all participants. Data were
collected in two assessments: the first was conducted in the
participant’s home and the second, in-laboratory polysomnography
(PSG, CompumedicsTM E-Series, Abbotsford, Australia), occurred
approximately two weeks later. All polysomnography studies were
sleep staged, arousal and respiratory scored by a trained sleep scientist
according to standard criteria [14-16]. The home-based assessment
consisted of subjective questionnaires and objective measurements
designed to measure sleep complaints, falls risk, function and quality
*Corresponding author: Frances A Batchelor, National Ageing Research
Institute, PO Box 2127, The Royal Melbourne Hospital, Parkville, Victoria 3050,
Australia, Tel: +61 3 8387 2383; Fax + 61 3 8387 2153; E-mail: f.batchelor@nari.
unimelb.edu.au
Received: October 31, 2013 Accepted: December 05, 2013 Published:
December 09, 2013
International Publisher of Science,
Technology and Medicine
All articles published in Journal of Sleep Disorders : Treatment & Care are the property of SciTechnol, and is protected by
copyright laws. Copyright © 2013, SciTechnol, All Rights Reserved.
Citation: Batchelor FA, Williams SB, Dow B, Lin X, Wilkinson V, et al. (2014) Subjective and Objective Sleep Measures in Older People with a History of Falls.
J Sleep Disor: Treat Care 3:1.
doi:http://dx.doi.org/10.4172/2325-9639.1000128
of life. This included: information to describe the demographics and
health of the sample [age, health conditions, living arrangements,
falls history, medications (including sedative use)], body mass index,
cognitive status (Abbreviated Mental Test Score [13]), depression
(Geriatric Depression Scale–Short Form [17]), physical activity
level (Human Activity Profile [18], mobility (Timed Up and Go)
[19], reaction time [20], and falls risk (Falls Risk for Older People
in the Community–FROP-Com [21]). The FROP-Com is a tool
which assesses multiple falls risk factors and classifies falls risk. Apart
from assessing a range of physical and functional falls risk factors,
it specifically incorporates the use of sedating medications into
calculation of falls risk. Generic quality of life was measured using
the Assessment of Quality of Life Instrument (AQoL version 1) [22].
Subjective sleep was evaluated using the Epworth Sleepiness Scale
(ESS) [23], Karolinska Sleep Scale (KSS) [24], and the Basic Nordic
Sleep Questionnaire (BNSQ) [25].
Data analysis
Subjective and objective sleep: Responses from the subjective
sleep questionnaires and the AQoL were grouped according to the
following categories: overall sleep rating (BNSQ6, AQoL13), nighttime sleep difficulties (BNSQ1, 2, 3, 4, 5) daytime sleepiness (BNSQ9,
10, 11, KSS, ESS), daytime napping (BNSQ15) and snoring (BNSQ16,
17, 18, 19). Subjective hours of actual and ideal sleep were obtained
from the BNSQ12 and 20. From the PSG data, five summary statistics
were generated: Apnea-Hypopnea Index (AHI), Periodic Leg
Movement Index (PLM), sleep efficiency (proportion of time spent
asleep of the total time available for sleep after lights out), number
of awakenings after sleep onset, and sleep latency (time taken to fall
asleep after lights out).
Comparisons according to falls and falls risk: Comparisons of
subjective and objective sleep were made between single (one fall) and
multiple fallers (2 or more falls) based on self-report for the preceding
12 months, and falls risk based on the FROP-Com. The separation
between single and multiple fallers was based on previous findings
that multiple fallers differ in their falls risk profile and physiologically
[26]. Low to moderate falls risk was defined as a FROP-Com score ≤
18 and high falls risk as a FROP-Com score of ≥ 19 [21].
The characteristics of participants were described using means
and Confidence Intervals (CI) for normally distributed variables,
medians and Interquartile Ranges (IQR) for non-normally distributed
variables, and percentages for categorical variables. For the normally
distributed variables independent t-tests were used to investigate
group differences and for those not normally distributed, the Mann–
Whitney U test was used.
Because this study was exploratory in nature, and insufficient data
was available on which to base an estimate, no sample size calculation
was made.
Subjective sleep
Overall sleep quality: The majority of participants reported that
they sleep well or rather well (n=19, 54.3%), five participants (14.3%)
felt that they sleep neither well nor badly and 11 (31.4%) participants
reported sleeping rather badly or badly (BNSQ6). When overall sleep
quality was assessed using the AQoL13, 12 (34.3%) people reporting
sleeping without difficulty most of the time, six people (17.1%)
reporting interruptions to sleep some of the time but able to go back
to sleep without difficulty, and for eight people (22.9%), although
their sleep was interrupted most nights, they could also go back to
sleep without difficulty. Nine people (25.7%) reported being awake
most of the night.
Subjective Sleep duration: The mean estimated actual and ideal
hours of sleep per night were 6.5 (95%CI: 5.8-7.1), ranging from 2 to
9 hours and 7.5 hours (95% CI: 7.0-7.9), ranging from 3 to 11 hours
respectively.
Night-time sleep difficulties: Difficulty falling asleep on a daily
or almost daily based was reported by six (17.1%) of participants.
Table 1: Characteristics of study participants, n=35.
Characteristic
Age, years; mean (95%CI)
82.8 (81.5 – 84.1)
Gender, female; N (%)
21 (60.0)
BMI, kg/m2; mean (95%CI)
27.7 (26.0 – 29.5)
Living arrangements; N (%)
Lives alone
27 (77.1)
Home with spouse
7 20.0)
Home with children
1 (2.9)
Most common health conditions; N (%)
Arthritis
25 (71.4)
Dizziness
12 (34.3)
Cardiac condition
11 (31.4)
Back pain
11 (31.4)
Respiratory condition
10 (28.6)
Lower limb joint replacement
10 (28.6)
Diabetes
6 (17.1)
Osteoporosis
3 (8.6)
Sedatives using sleeping pills less
than once per month or never; N (%)
27 (77.1)
Falls History
Number of falls in the past 12 months
– median (IQR)
2 (2)
Single faller/Multiple fallers; N (%)
13(37.1)/22(62.9)
Falls Risk (FROP-Com)
15.2 (13.3 – 17.1)
Raw Score – mean (95% CI)
24 (68.6%)/11(31.4%)
Low-Moderate Risk (≤18) / High Risk
– N (%)
HAP-AAS mean (95% CI)
56.9 (52.8-61.1)
Timed Up and Go (seconds) – mean
(95% CI)
11.7 (10.5-12.9)
Results
Reaction Time (seconds) – median
(IQR)
0.28 (0.06)
Participants
AMTS, median (IQR)
10 (1)
AQoL score, mean (95% CI)
Thirty-five people (21 women, 14 men) with a mean age of 82.8
(95% CI: 81.5–84.1) were recruited for the study (Table 1). Participants
had a median number of two falls (IQR 2) in the preceding year, with
the majority reporting multiple falls (n=22, 62.9%). The mean FROPCom score was 15.2 (95% CI: 13.3-17.1), with over half having lowmoderate falls risk (n=24, 68.6%) (Table 1).
Volume 3 • Issue 1 • 1000129
Raw score
27.11 (25.42-28.81)
Utility score
0.62 (0.54-0.69)
GDS score - median (IQR)
1 (4)
CI, confidence interval; BMI, body mass index; FROP-Com Falls Risk for Older
People in the Community assessment tool; HAP-AAS, Human Activity Profile
Adjusted Activity Score; AMTS Abbreviated Mental Test Score; IQR interquartile
range; AQoL Australian Quality of Life; GDS Geriatric Depression Scale
• Page 2 of 5 •
Citation: Batchelor FA, Williams SB, Dow B, Lin X, Wilkinson V, et al. (2014) Subjective and Objective Sleep Measures in Older People with a History of Falls.
J Sleep Disor: Treat Care 3:1.
doi:http://dx.doi.org/10.4172/2325-9639.1000128
Five participants (14.3%) reported difficulty falling asleep on 3-5 days
per week, four (11.4%) on 1-2 days per week, and six (17.1%) less
than once per month. Fourteen people (40.0%) reported they did not
difficulty falling asleep or less than once per month (Table 2). The
median time taken to fall asleep on work-days was reported as 25
minutes (IQR 50, range 0-360 minutes). During free time, median
time to sleep was 11.3 minutes (IQR 36, range 0–120 minutes).
The majority of participants (n=23, 65.7%) reported very frequent
(daily/almost daily) night-time waking. There was a spread of
responses across the BNSQ5 categories (early waking without going
back to sleep) (Table 2).
Daytime sleepiness: Participants reported low levels of daytime
sleepiness. Seventy-one percent (n=25) reported that they did not
experience excessive daytime sleepiness or less than once/month or
week (BNSQ9). Similar low levels were seen for the tendency to fall
asleep during the day, either while undertaking activity (BNSQ10) or
during free time (BNSQ11) (Table 2).
The median KSS score (day-time sleepiness) was 3 (IQR 2) and
the ESS score (likelihood of dozing off in different situations) was 5
(IQR 6), reflecting low levels of sleepiness.
Daytime napping: Thirteen (37.1%) participants reported that
they never or rarely had a daytime nap and six (17.1%) had a daytime
nap less than once/week. Nine (25.7%) napped on 1-2 days/week, 2
(5.7%) on 3-5 days/week, and five (14.3%) reported napping daily/
almost daily. The median reported nap time (n=21) was 45 minutes
(IQR 42.5), ranging from 0–210 minutes.
Snoring/Obstructive sleep apnea: The majority of participants
(n=16, 45.7%) reported that they did not snore while asleep or snored
less than once/month. Three (8.6%) people reported snoring less than
once/week, and three (8.6%) on 1-2 days/week. Nine people (25.7%)
reported very frequent snoring (daily/almost daily). The frequency of
snoring was unknown for four participants (11.4%). The majority of
people (23, 65.7%) reported no breathing pauses during sleep (or less
than once/month) (Table 2).
Objective sleep: The mean AHI was 32.9 (95%CI: 25.8–40.1) and
the median PLM index was 17.3 (IQR 4). The average sleep efficiency
(proportion of time spent asleep relative to total time spent in bed)
was 64% (95%CI: 58.5–69.2) and the median time taken to fall asleep
(sleep latency) was 24.5 minutes (IQR 38). The median number of
awakenings after sleep onset for the whole sample was 23 (IQR 7).
Relationships between sleep variables, falls history and falls risk
Falls history: Participants with a history of multiple falls had
significantly higher state sleepiness (median 3.0, IQR 1.5) as measured
by the KSS than those with a history of single falls (median 1.0, IQR
2.0) (p=0.02). There was no significant difference in trait sleepiness
as measured by the ESS in those with multiple falls (median 6.0,
IQR 7.1) compared to those with single falls (median 4.0, IQR 4.0)
(p=0.10) (Table 3).
Similarly, there was no difference in AHI and sleep efficiency
between participants who had two or more falls in the past 12 months
compared with participants who had only one fall (Table 3).
Falls risk: Participants with high falls risk (FROP-Com score ≥
19) had significantly higher scores on the ESS, KSS, BNQ9, and PLM
index, indicating higher trait and state sleepiness, more daytime
sleepiness and more lower limb movements while asleep. There were
no differences in sleep apnea and efficiency in those with high versus
low to moderate falls risk (Table 3).
Table 2: Subjective sleep.
Night time sleep difficulties
Never/less than
once/month
Less than once per
week
On 1 – 2 days per
week
On 3-5 days per
week
Daily or almost daily
BSNQ 1 Difficulty falling asleep
14 (40.0)
6 (17.1)
4 (11.4)
5 (14.3)
6 (17.1)
BNSQ 3 Waking during the night
2 (5.7)
2 (5.7)
5 (14.3)
3 (8.6)
23 (65.7)
BNSQ 5 Early waking without going back to sleep
10 (28.6)
6 (17.1)
7 (20.0)
7 (20.0)
5 (14.3)
Never/less than
once/month
Less than once per
week
On 1 – 2 days per
week
On 3-5 days per
week
Daily or almost daily
BNSQ 9 Excessive daytime sleepiness
15 (42.9)
10 (28.6)
4 (11.4)
1 (2.9)
5 (14.3)
BNSQ 10 Tendency to fall asleep while at work
(therapy/treatment)
29 (82.9)
5 (14.3)
0 (0)
0 (0)
1 (2.9)
BNSQ 11 Tendency to fall asleep during free time
21 (60.0)
7 (20.0)
3 (8.6)
1 (2.9)
3 (8.6)
Median
IQR
Range
KSS momentary sleepiness (1-9)*
3.0
2.0
1-9
ESS likelihood of dozing off (0-24)*
5.0
6.0
0-19
Never/less than
once/month
Less than once per
week
On 1 – 2 days per
week
On 3-5 days per
week
Daily or almost daily
13 (37.1)
6 (17.1)
9 (25.7)
2 (5.7)
5 (14.3)
Never/less than
once/month
Less than once per
week
On 1 – 2 days per
week
On 3-5 days per
week
Daily or almost daily
BNSQ 16 Frequency of snoring while sleeping (no
response from 4)
16 (45.7)
3 (8.6)
3 (8.6)
-
9 (25.7)
BNSQ18 Frequency of breathing pauses during
sleep
23 (65.7)
3 (8.6)
2 (5.7)
1 (2.9)
Daytime sleepiness
Daytime napping
BNSQ 15a Frequency of daytime naps
Snoring/Obstructive sleep apnea
*higher score indicates more sleepiness ESS Epworth Sleep Scale; KSS Karolinska Sleep Scale; BNSQ Basic Nordic Sleep Questionnaire.
Volume 3 • Issue 1 • 1000129
• Page 3 of 5 •
Citation: Batchelor FA, Williams SB, Dow B, Lin X, Wilkinson V, et al. (2014) Subjective and Objective Sleep Measures in Older People with a History of Falls.
J Sleep Disor: Treat Care 3:1.
doi:http://dx.doi.org/10.4172/2325-9639.1000128
Table 3: Sleep difficulties by history of falls and falls risk.
Sleep variable
Single faller (n=13) Multiple faller (n=22) P-value Low-Moderate Falls risk (≤18)# (n=24) High falls risk (n=11)
P-value
ESS
4.0 (4.0)
6.0 (7.1)
0.10
4.5 (4.0)
9.0 (10.0)
KSS
1.0 (2.0)
3.0 (1.5)
0.02*
2.0 (2.0)
3.0 (1.0)
0.04*
0.01*
BNSQ9
1.0 (1.0)
2.0 (2.3)
0.08
1.0 (1.0)
2.0 (3.0)
0.03*
PLM index (events per
hour)
23.9 (57.2)
17.3 (63.8)
0.89
13.2 (35.9)
39.0 (30.4)
0.03*
Number of awakenings
after sleep onset
17.0 (17.5)
24.5 (17.0)
0.32
21.5 (16.0)
25.0 (18.0)
0.25
Sleep latency
23.5 (40.8)
24.8 (38.8)
0.93
25.8 (39.4)
21.0 (60.0)
0.66
AHI, mean (SD)
30.6 (17.0)
34.4 (23.1)
0.60
29.1 (17.6)
41.4 (15.6)
0.1
Sleep efficiency, mean
(SD)
62.5 (14.7)
64.8 (15.8)
0.70
64.2 (1.47)
63.6 (17.1)
0.9
Values are median (IQR) unless otherwise stated; *significant at P < 0.05; ESS Epworth Sleep Scale; KSS Karolinska Sleep Scale; BNSQ Basic Nordic Sleep
Questionnaire; PLM periodic limb movements; AHI apnea hypopnea index; #Falls Risk for Older People in the Community Score (FROP-Com score);
Discussion
This exploratory study is one of the first studies to use
polysomnography for objective sleep assessment in a population of
older fallers. We found a concerning level of sleep problems in this
sample, with a high frequency of objective sleep difficulties. Although
there are little normative values for this age group, 60% of participants
could be classified as having severe Obstructive Sleep Apnea (OSA)
[16]. Participants had a high number of awakenings after sleep onset
and sleep efficiency was poor across the whole sample (average of
64%). Of note was that no participant was assessed as having “normal”
sleep on PSG. Despite this, less than one third of participants felt that
they slept badly or very badly, and only two participants reported
waking at least five times per night even though the median number
of awakenings was found to be 23 when measured using PSG.
The objective data indicates that this group experienced substantial
sleep disturbances and it is possible that poor sleep may have played
a role in their falls history. Previous research has shown that poor
sleep efficiency (where less than 70% of time in bed is spent sleeping)
increased the odds of falling 1.36-fold [7]. Decreased reaction time
[9], decreased mood, cognitive function and motor performance [11]
due to inadequate and interrupted sleep may be possible mechanisms
for an association between sleep and falls. Further research comparing
the results of polysomnography of a group of older fallers and a group
of age/gender-matched healthy older non-fallers would be useful.
We confirmed an association between falls history and daytime
sleepiness [27], and importantly found those at high risk of falling
to have both more daytime sleepiness (higher ESS, KSS and BNQ9
scores), and a significantly higher rate of periodic leg movements
(PLM index) than those with low-moderate falls risk (Table 3).
Although the ESS was significantly higher in the high falls risk group,
the median score of nine in this sample is lower than the cut-off of
around ten considered indicative of normality [28]. Similar data
have previously been observed in sleep apnea in older people, where
both the average ESS and the proportion of people with an ESS>10
(excessive daytime sleepiness) was significantly lower in older people
than in middle-aged or young people with the same degree of sleep
apnea [29]. These results suggest that with older people perhaps an
equivalent physiological sleep insult does not result in equivalent
subjective sleepiness.
There appeared to be more differentiation in sleep-related
variables when participants were grouped according to falls risk
rather than falls history. This probably reflects the multi-dimensional
Volume 3 • Issue 1 • 1000129
nature of the falls risk assessment undertaken encompassing aspects
of physical activity, mobility and balance.
The interpretation of our findings is limited by the paucity of
normative data for this age group. Further research is required to better
establish normal values for OSA severity, PLM index, sleep efficiency
and latency as well as for the number of awakenings after sleep onset,
particularly given the low scores on scales of daytime sleepiness. The
relationship between falls risk and sleep difficulties offers potential
possibilities for testing interventions aimed at improving sleep and
potentially reducing falls. In addition, further research with a larger
sample is required to determine the associations between subjective
and objective measures.
Despite the small sample size, the study results have important
clinical implications. Health professionals should consider asking
older people who have reported falls in the previous 12 months about
their sleep. Subjective reporting will likely underestimate objective
abnormalities (as shown in this study), and health professionals
should consider implementing sleep hygiene recommendations
in fallers even if they subjectively report sleep is of little concern to
them. This could be done in conjunction with addressing identified
falls risk factors using evidence-based interventions. Where other
risk factors for sleep problems are present, referral for comprehensive
polysomnography may be appropriate. Additionally, clinicians
assessing the sleep of older people should consider referral for
comprehensive falls risk assessment particularly for those who report
ESS scores close to nine or above.
In conclusion, this research highlights that older people who
have recently fallen experience high levels of sleep difficulties. This
preliminary study supports the need for clinicians and researchers to
consider objective assessment of sleep in those falling and not to rely
solely on subjective information.
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Citation: Batchelor FA, Williams SB, Dow B, Lin X, Wilkinson V, et al. (2014) Subjective and Objective Sleep Measures in Older People with a History of Falls.
J Sleep Disor: Treat Care 3:1.
doi:http://dx.doi.org/10.4172/2325-9639.1000128
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Author Affiliations
Top
National Ageing Research Institute, Parkville, Victoria, Australia
University of Melbourne, Parkville, Victoria, Australia
Institute for Breathing and Sleep, Heidelberg, Victoria, Australia
4
Curtin University, Perth, Western Australia
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