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ORIGINAL RESEARCH
The impact of sleepwear fiber type on sleep
quality under warm ambient conditions
This article was published in the following Dove Press journal:
Nature and Science of Sleep
Chin Moi Chow
1,2
Mirim Shin
2
Tr e v o r J M a h a r
3
Mark Halaki
1,2
Angus Ireland
3
1
Charles Perkins Centre, University of
Sydney, Sydney, NSW, Australia;
2
Exercise, Heath & Performance
Research Group, Faculty of Health
Sciences, University of Sydney, Sydney,
NSW, Australia;
3
Australian Wool
Innovation Limited, The Woolmark
Company, Sydney, NSW, Australia
Background: Sleep disturbance in adults with no health concerns is often linked to the thermal
environment. This study assesses the impact on sleep quality of sleepwear made from fibers with
differentthermal insulation and hygral properties. This randomized cross-over study investigated
the effects on sleep quality of sleepwear made from cotton, polyester and Merino wool in adults
aged 50–70 years, at an ambient temperature of 30 °C and a relative humidity of 50%.
Methods: Thirty-six healthy participants completed four nights of sleep study with poly-
somnography. Participants were categorized by body mass index as <25 kg·m
−2
or ≥25 kg·m
−2
,
age as <65 years or ≥65 years, and by Pittsburgh Sleep Quality Index (PSQI) as poor sleepers
(PSQI≥5) or good sleepers (PSQI<5).
Results: Small, but statistically significant sleep benefits were observed for wool over cotton
and polyester sleepwear for multiple sleep parameters, while neither cotton nor polyester was
responsible for any statistically significant sleep benefit over the 11 sleep parameters
examined. The key findings were: 1) A significant sleepwear effect was observed for sleep
onset latency (SOL), p=0.04. 2) For older participants, sleeping in wool significantly reduced
SOL (12.4 mins) compared with cotton (26.7 mins, p=0.001) or polyester (21.6 mins,
p=0.001). 3) A statistically significant effect was found for sleep fragmentation index
(p=0.01) in which wool sleepwear (12.1 no·h
−1
) was lower than polyester (13.7 no·h
−1
)
(p=0.005), but not different to cotton (13.3 no·h
−1
). 4) Poor sleepers had less wakefulness
when sleeping in wool compared to cotton (p=0.047). 5) And Poor sleepers had higher rapid
eye movement sleep latency in polyester than in cotton (p=0.037) or in wool (p=0.036).
Conclusion: Statistically significant benefits for wool sleepwear were observed on average for
all participants and, in particular, for the older and poorer sleepers. There were no significant
differences in any sleep variables between sleepwear types for the BMI sub-group.
Keywords: cotton, polyester, wool, polysomnography, thermal comfort
Introduction
In general, the quality of sleep decreases with aging. The sleep of older adults,
compared to younger adults, is more fragmented and lighter with increased duration
of sleep stages 1 and 2, and reduced duration of deep sleep (sleep stage N3), delta
activity and rapid eye movement (REM) sleep.
1,2
Reduced sleep efficiency (SE) and
total sleep time (TST) with frequent shifts in sleep stages have also been reported
1,2
in polysomnography (PSG) studies.
In older adults with no health concerns, sleep disturbances are often linked to the
thermal environment that is vital for sleep maintenance.
3
Sleeping outside the optimum
range of temperature for thermal comfort can negatively impact sleep. Older adults suffer
this impact more than younger adults, as they are more vulnerable to heat stress.
4,5
The
Correspondence: Chin Moi Chow
Discipline of Exercise and Sport Science,
The University of Sydney, 75 East street,
Lidcombe, NSW 2141, Australia
Tel +61 2 9351 9332
Email chin-moi.chow@sydney.edu.au
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http://doi.org/10.2147/NSS.S209116
reduced thermoregulatory ability in older adults under hot
conditions is due to a combined decreased sweat rate, reduced
skin blood flow and overall decrease in physical fitness and
increases in body adiposity that may accompany aging.
4,6
In
addition, reduced hydration levels
7
and diminished sweating
capacity
8
increase the risk of developing hyperthermia and
heat stroke
6
in older adults. Where bedcovers and clothing
were used, older adults have experienced more disturbed sleep
in warmer than in cooler conditions.
9
Increased wakefulness
and decreased REM sleep and SE were observed when sleep-
ingat32°Ccomparedto26°C
10
andwhensleepingin
summercomparedtoautumnorwinter.
9
Higher average summer temperatures and the frequency
and intensity of hot days are now observed in Australia
11
and
globally.
12
The night-time bedroom temperature in Australia
can exceed 30 °C with a maximum of 38.2 °C without air
conditioning.
11
A review reported a positive relationship
between heat/heat waves and increasing mortality among the
elderly and its relationship appeared consistent globally.
13
The
use of air-conditioning to control temperature is both con-
sumptive of energy and is associated with both direct and
indirect negative effects on human health including
Legionnaires’disease and sick building syndrome, with symp-
toms such as chronic headaches and fatigue.
14
It is therefore of
interest to investigate alternative healthy and environmentally-
friendly strategies for older adults to cope with sleeping under
warm ambient conditions.
Sleepwear influences thermal comfort in several crucial
ways. Fabrics allow varying rates of heat and moisture
transfer.
15,16
As each fiber type has its inherent thermal insula-
tion and hygral properties, fabrics made from different fiber
types can yield differential effects on thermal insulation.
16
These effects could potentially alter sleep quality.
Natural fibers, such as cotton and wool, are hygro-
scopic with the ability to absorb and transfer large quan-
tities of moisture. Wool has the highest moisture regain of
the common textile fibers, with polyester having the low-
est regain and cotton having an intermediate regain level.
17
Dry wool fiber absorbs moisture up to about 35% of its dry
weight in saturated air, whereas cotton can absorb around
24% and polyester below 1%.
17
A previous study investi-
gated the influence of sleepwear (cotton vs wool) and
bedding type (polyester vs wool) on the sleep quality of
healthy young participants.
18
Although no effect on sleep
of bedding type was observed, sleep onset latency (SOL)
was significantly shortened when sleeping in wool sleep-
wear with less stage 3 sleep observed for wool than for
cotton. However, the effects of fiber type on the sleep of
older adults have not been studied.
The aims of this study were:
(i) to determine if sleepwear fiber type (cotton, polye-
ster or Merino wool) influences sleep quality for
adults aged 50–70 years, at an ambient temperature
of 30 ºC and a relative humidity (RH) of 50%; and,
(ii) to determine if there is an interaction effect on
sleep quality between sleepwear fiber type and
BMI (>25 vs ≤25 kg·m
−2
), age (>65 vs
≤65 years) and sleep self-ratings (PSQI >5 (poor
sleepers) vs ≤5 (good sleepers)).
Materials and methods
Participants
Thirty-six healthy participants aged between 50 and 70 years
with a mean and standard deviation (SD) of 60.0±6.2 years, a
body mass index (BMI) of 25.6±4.1 kg·m
−2
and mean
Pittsburgh Sleep Quality Index (PSQI)
19
of 4.4±2.6 completed
four nights of study. The female participants (n=18) had a
mean age of 59.8±6.7 years and BMI of 25.3±5.4 kg·m
−2
,
while similar values for the male participants were (n=18) 60.2
±5.9 years and a BMI of 25.8±2.3 kg·m
−2
. Participants with
certain pre-existing medical conditions were excluded. These
conditions were sleep disorders (insomnia, sleep apnea, peri-
odic limb movement disorders, restless legs syndrome and
bruxism), cardio-respiratory conditions (severe hypertension,
cardiovascular diseases, respiratory infections and chronic
obstructive pulmonary diseases), metabolic conditions
(uncontrolled diabetes and metabolic syndrome), and psychia-
tric or neurological disorders (depression, dementia and
Parkinson disease). Female participants with regular men-
struation were tested on the follicular phase (between men-
struation and ovulation) to minimize hormonal and
temperature effects on sleep. Females who were on hormone
replacement therapy were included. Individuals on nightshifts
or medications/drugs (eg, anti-depressants, hypnotics, stimu-
lants which interfere with sleep), or who smoked or had
travelled across trans-meridian borders in the last 2 weeks
were also excluded. Participants abstained from alcohol on
the study days and from caffeinated beverages and vigorous
exercise eight hours prior to their averaged bedtimes. Ethics
approval for this study was granted by the University of
Sydney Human Research Ethics Committee (Project no.
2012/562). Written informed consent was obtained from all
participants prior to study commencement.
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Procedure
Participants wore an Actiwatch 2 (Phillips-Respironics,
Murryville, PA) on the non-dominant arm for a week, prior
to study commencement, to assess their average bedtimes
and wake times. Subjective sleep quality was assessed using
PSQI. Eligible participants attended the sleep laboratory for
PSG testing on four occasions: an adaptation night where
participants were confirmed free of sleeping disorders, and
three testing nights. Their height and body mass were
recorded. On testing nights, participants slept in either cotton,
polyester or wool sleepwear in a random order. Participants
were blind to the type of sleepwear. Participants ate a stan-
dardized mixed macronutrient meal 4 hrs before their aver-
age bedtime. They changed into their sleepwear 2 hrs prior to
bedtime, during which they had PSG electrodes attached in
the sleep monitoring room, which recorded a temperature of
~25 °C and an RH of ~40%. The participants went to bed and
woke up according to their averaged times, collected during
5–7 nights prior to the study by Actiwatch 2. Participants in
their sleepwear were weighed at bedtime and on waking, and
overnight urine was collected and measured (to the nearest
0.01 kg). These measurements were used in the estimation of
whole body sweat evaporation loss and rate of loss (see Data
and Statistical analysis).
Sleepwear and bedding
Cotton, polyester and Merino wool sleepwear knitted from
singles yarn in single jersey structure, were finished clean,
plain colored and visibly similar. Both the fabric mass per
unit area (g·m
−2
) and thickness (mm) were taken into con-
sideration in matching the fabrics.
20,21
The lightest fabric,
cotton, was also the thickest, while the heaviest fabric, polye-
ster, was the thinnest, as shown in Tabl e 1. Fabric thickness
was prioritised as the characteristic to be most closely
matched, with the largest difference, 0.08 mm, being between
the cotton and polyester fabrics. This small difference was
considered acceptable for the purposes of this study. All sleep-
wear was custom-tailored to be loose-fitting using the same
pattern in long sleeves and long pants in four sizes (small,
medium, large, and extra-large). Participants were allocated a
size that was similar to that of their usual sizing in sleepwear.
Conforming to cultural conventions, female participants wore
cotton knickers, while male participants wore only sleepwear
without underwear. Participants slept on a sheet but without a
cover to avoid confounding effects arising from participants
inadvertently kicking off the cover to achieve comfort. The
bed comprised a king size innerspring mattress covered by a
cotton underlay and cotton bedsheet.
Ambient conditions
The temperatures and RH levels in the sleep monitoring
room and the two bedrooms (both identically equipped and
of similar size) were monitored continuously by means of
iButtons (type DS1923; Maxim/Dallas Semiconductor
Corporation) in each room. In the bedrooms, the tempera-
tures were controlled by a wall mounted air conditioner
(Email Air, Australia) and RH by a stand-alone humidi-
fier/dehumidifier (Munters, Sweden) with a steam vaporizer
(Vicks, USA). The ambient conditions of the bedrooms
were independently verified using an Indoor Climate
Analyzer - Type1213 (Brüel&Kjær, Denmark), which
showed temperature and RH readings were consistent with
the iButton readings. The air speed recorded (Brüel&Kjær,
Denmark) over a two-hour period in the bedroom was low
(below 0.04 m·s
−1
). Temporal changes in air speed would be
expected to be minimal, given the constant readings
obtained over the two hours in bedrooms that had no win-
dows and had their doors shut throughout the study period.
The radiant wall temperature was, as expected, similar to
the set ambient room temperature. The ambient conditions
in both bedrooms were 30.1±0.5 °C and 50.2±2.9% RH.
Measurements
PSG
Sleep parameters were measured using the Compumedics E-
series or Grael Sleep system (Compumedics Australia Pty
Ltd., Australia). Electroenceophalogram (EEG) electrode pla-
cement (C3/A2, O2/A1 and F3/A2) was conducted in accor-
dance with the International 10–20 system. Electrooculogram,
chin electromyogram (EMG) and electrocardiogram were
Table 1 Fabric characteristics of washed sleepwear
Mass per unit area (g·m
−2
) Thickness (mm) Thermal Resistance (m
2
·K·W
−1
)
Cotton 140.0±0.0 0.57±0.03 0.030
Polyester 150.5±0.7 0.49±0.04 0.025
Wool 143.5±2.1 0.52±0.01 0.030
Note: Data presented as mean ± SD.
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continuously recorded. All electrode sites were referenced to
the vertex (Cz), and a ground electrode was attached to the
forehead (Fpz). The impedance of EEG recording electrodes
was checked prior to data collection, and the threshold was
<5 kΩ. On the adaptation night, left and right leg EMG,
oxygen saturation, thoracic and abdominal breathing move-
ments and airflow were also recorded to determine sleep
disorders. PSG data were scored blind by two experienced
scorers according to the American Academy of Sleep
Medicine (AASM) guidelines.
22
The sleep variables included
SOL, TST, SE, wake after sleep onset (WASO), and the
proportion of each sleep stage including non-rapid eye move-
ment (NREM) sleep: stages 1 (N1), 2 (N2) and 3(N3), and
REM sleep.
EEG arousal index (AI, number of arousals per hour
(no. h
−1
)) was defined as an abrupt shift in EEG frequency
that lasts between 0.5 and a maximum of 14.9 seconds.
22
An EEG arousal that is longer than 15 seconds would be
considered an awake epoch. A minimum of 10 seconds of
intervening sleep between arousals was required. The scor-
ing process for the AI was relatively time consuming and
has been associated with high inter-scorer variability. The
sleep fragmentation index (SFI) was also assessed in this
study as in clinical practice. The SFI has previously been
reported to be significantly correlated with the AI with a
test-retest reproducibility of r=0.77. It was calculated as
the sum of any sleep stage shift and the total number of
awakenings, divided by TST (hours). A shift in sleep stage
refers to a change from a higher to a lower stage. The
number of sleep stage shifts was computed for the whole
night sleep recording after manual sleep scoring. In REM
sleep, a stage shift was defined as a shift to sleep stage 1.
Actigraphy
Actiwatch 2 (Phillips-Respironics, Murryville, PA) was
placed on the non-dominant wrist. Actigraphic data were
scored using Respironics Actiware v6.09 (Phillips-
Respironics). Data were collected in 30 s epochs with the
sensitivity set to the medium level. Rest intervals were
manually set based on the timing of lights-out and lights-
on in accordance with a previous study,
23
and sleep vari-
ables were estimated by the Actiware software.
Sweat evaporation rate
Whole body sweat evaporation loss during the sleep period
was calculated in the established manner
24
from the loss of
body mass during sleep according to the parameters of
whole body mass while clothed in sleepwear and overnight
urine volume, assuming a specific gravity of urine to be
approximately 1.0. No corrections were made for respira-
tory ‘insensible’water loss, or weight changes due to
metabolism.
25
Whole body sweat evaporation rate
(WBSER) was calculated by dividing evaporation loss by
total time in bed (in hours):
WBSER ¼bodyweight before sleep bodyweightð½
after sleep þurine volumeÞ=Total time in bed
Subjective ratings on tactile sensations
On each test night, participants rated the tactile sensation
of their sleepwear immediately after changing into the
sleepwear (approximately 2.5 hrs before bedtime), at bed-
time and on waking. Tactile sensations including the sur-
face texture (“very soft”to “very rough”), prickliness,
clamminess and clinginess of the sleepwear (“not at all”
to “extremely”) were assessed on a five-point Likert scale.
Data and statistical analysis
Participants were categorized into one of two groups for
each subgroup as follows:
BMI (as BMI<25 kg·m
−2
(but ≥18.5 kg·m
−2
), and
BMI≥25 kg·m
−2
); Age (Middle-age and Old age); and,
PSQI (Good and Poor sleepers). The BMI cut-off of 25
was applied based on World Health Organization defini-
tion of overweight (World Health Organization, 1999).
Age was grouped as Middle-age (50–64 years) and Old
age (≥65 years).
26,27
A PSQI global score of <5 was
considered as good quality of sleep and a score ≥5 was
classified as poor quality of sleep.
19,24,25
A linear mixed model (SPSS v21; IBM Corporation,
Armonk, NY, USA) was applied to compare the effects
of sleepwear fiber types on WBSER and the following
sleep variables: SOL; TST; percentage of TST of sleep
stages N1, N2, N3, and REM; SE; WASO; AI; and SFI.
In the linear mixed model the following fixed factors
were used: sleepwear fiber type (categorical: cotton,
wool and polyester), BMI (categorical), Age (categori-
cal) and PSQI (categorical) to test main and interaction
effects on sleep variables. Further post-hoc analysis on
interaction results was performed using Fisher’s least
significant difference for pairwise comparisons.
Subjective ratings were analysed by means of the
Kruskal-Wallis test, with the Mann-Whiney U test for
post-hoc analysis (SPSS).
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Results
Of the 36 participants, 13 had BMI<25 while 23 had
BMI≥25 kg·m
−2
; 23 participants were Middle-age (50–
64 years) while 13 were Old-age (65 years and above);
and 20 participants were Good sleepers (PSQI <5) while
16 were Poor sleepers (PSQI ≥5, range 5–11).
Main effects on sleep of sleepwear type,
BMI, age and PSQI
Sleepwear type
Table 2 shows mean ± SD values for all sleep variables for
each type of sleepwear. Statistically significant sleepwear
effects were observed for only SOL (p=0.044) and SFI
(p=0.006). While on average cotton sleepwear had the
highest and wool the lowest SOL, a post-hoc test with
pairwise comparisons did not reveal any significant differ-
ences in SOL among the sleepwear types. SFI was sig-
nificantly lower when sleeping in wool than in polyester
(p=0.005) with no statistically significant difference
between wool and cotton or between cotton and polyester
(p>0.05) in the post-hoc pairwise comparisons.
Subgroups of BMI, age and PSQI
Table 3 shows the effect on sleep parameters of sleep-
wear fiber type for the subgroups BMI, Age and PSQI.
Participants with a BMI≥25 kg·m
−2
had a statistically
significantly higher AI, more N1% and less N3% than
those with BMI<25 kg·m
−2
. The main effects for Age
showed that the Old age group took significantly longer
to fall asleep but had higher N3% than the Middle-age
group. Significant PSQI main effects showed Poor
sleepers had significantly higher N2% and SFI than
Good sleepers.
Interaction effects on sleep between
sleepwear and BMI, age or PSQI
A significant interaction between sleepwear fiber type and
Age group was observed for SOL (p=0.001), as shown in
Figure 1A. Further post-hoc testing with pairwise compar-
isons revealed that within the Old age group, SOL was
significantly reduced when sleeping in wool compared to
sleeping in cotton (p=0.011) or polyester (p=0.011). In
addition, when both Age groups slept in cotton sleepwear,
Middle-aged fell asleep significantly quicker than Old age
(p=0.008), as shown in Figure 1A.
Significant interactions between sleepwear and
PSQI group were found for WASO (p=0.049) and
REM sleep latency (p=0.038) as shown in Figure 1B
and C. In the comparison of sleepwear types, Poor
sleepers had significantly reduced WASO in wool
than in cotton (p=0.047). In the comparison between
Good and Poor sleepers, Poor sleepers had significantly
more wake time during the sleep period (WASO) than
Goodsleeperswhensleepingincotton(p=0.010), as
shown in Figure 1B. Additionally, REM sleep latency
was significantly longer when Poor sleepers slept in
polyester than either in cotton (p=0.037) or in wool
(p=0.036). When participants slept in polyester, Poor
sleepers had significantly higher REM sleep latency
than Good sleepers (p=0.010), as shown in Figure 1C.
Therewerenosignificant differences in any sleep
Table 2 Effect on sleep parameters of sleepwear fiber type
Cotton Polyester Wool p-value
SOL (min) 18.5±23.5 18.2±15.5 16.0±15.5 0.04
REM sleep latency (min) 82.5±34.2 88.9±46.7 82.6±49.0 0.33
N1 (%) 5.3±4.0 4.6±2.5 4.6±2.7 0.57
N2 (%) 58.6±9.0 57.5±8.6 57.8±8.0 0.70
N3 (%) 15.9±5.4 16.1±6.8 16.5±5.7 0.91
REM sleep (%) 20.2±5.7 21.5±6.3 21.1±6.1 0.58
TST (min) 363.4±56.0 364.2±62.6 373.1±60.4 0.30
SE (%) 76.2±11.0 76.4±12.4 78.4±12.6 0.32
WASO (min) 97.0±52.3 95.8±56.6 89.1±57.0 0.76
AI (no.h
−1
) 10.3±7.1 9.6±6.0 10.5±6.4 0.36
SFI (no. h
−1
) 13.3±5.8 13.7±4.4* 12.1±4.2* 0.01
Notes: Data presented as mean ± SD, N=36. *p<0.05 for difference between polyester and wool.
Bold values indicate significant sleepwear effect on SOL but there was no significant difference among sleepwear types in the post-hoc pairwise comparisons.
Abbreviations: SOL, sleep onset latency; REM, rapid eye movement; TST, total sleep time; N1(%), sleep stage 1 as a percentage of TST; N2(%), sleep stage 2 as a
percentage of TST; N3(%), sleep stage 3 as a percentage of TST; SE, sleep efficiency; WASO, wake after sleep onset; AI, arousal index; SFI, sleep fragmentation index.
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variables between sleepwear types for the BMI sub-
group.
Whole body sweat evaporation rate
(WBSER)
WBSER was 48.0±17.7 g·h
−1
when sleeping in cotton
compared to wool (44.7±17.6 g·h
−1
) and polyester (44.5
±18.4 g·h
−1
), p=0.068 (Figure 2). There were no statisti-
cally significantly different differences among the three
fiber types in WBSER.
Subjective ratings
Participants reported average ratings between 1 (“Not at all”)
and 2 (“Slightly”) for perceived prickliness, clamminess and
clinginess for all fabrics at each evaluation point in the study.
The average ratings for surface texture were between 1
(“Very soft”)and2(“Soft”) for the polyester fabric and
between 2 and 3 (“Neutral”) for the cotton and wool fabrics,
indicating that the polyester fabric was slightly smoother
than the cotton and wool fabrics. Though small, there were
statistically significantly different tactile ratings between
sleepwear fiber types as shown in Tabl e 4 . The post-hoc
test with Mann-Whitney U showed that wool was perceived
to be slightly (0.4 units), but statistically significantly, prick-
lier than the other two fabrics (p=0.004) at all three time
points of measurement. Participants rated cotton sleepwear
immediately after donning as less clingy (0.25 units) than
polyester (p=0.021) and wool (p=0.021). They rated wool
significantly rougher (0.47 units) than polyester (p=0.037) at
bedtime, and both cotton and wool were rated significantly
rougher (0.42 units in each case) than polyester on waking
(p=0.031, p=0.032 respectively) (refer to Table 4). No sig-
nificantly different average ratings were observed for
“clamminess.”
Discussion
The study compared the effect on sleep quality of sleep-
wear fiber type (cotton, polyester and wool) in warm
conditions (30 ºC and 50% RH) for healthy participants
aged 50–70 years old.
Main effects on sleep of sleepwear type,
BMI, age and PSQI
Statistically significant differences among sleepwear type
were observed in two of the 11 sleep quality parameters,
SOL and SFI, as illustrated in Table 2.
Table 3 Effect on sleep parameters of sleepwear fiber type for subgroup BMI, Age and PSQI
BMI<25 (n=13) BMI≥25 (n=23) p-value Middle-age (n=23) Old age (n=13) p-value PSQI<5 (n=20) PSQI≥5 (n=16) p-value
SOL (min) 17.8±26.1 17.5±12.4 0.14 16.1±12.9 20.2±25.4 0.03 11.0±7.0 25.8±24.2 0.17
REM sleep latency (min) 83.3±36.9 85.4±47.0 0.84 86.4±46.5 81.6±38.0 0.92 71.1±33.7 101.6±48.5 0.07
N1 (%) 3.3±1.8 5.7±3.4 0.03 4.5±3.0 5.5±3.2 0.42 4.9±2.9 4.8±3.4 0.84
N2 (%) 57.8±8.1 58.1±8.7 0.35 59.1±8.1 56.0±8.8 0.05 56.0±8.2 60.5±8.2 0.01
N3 (%) 18.2±7.0 15.0±5.0 0.02 15.8±5.9 16.8±6.0 0.03 16.3±6.1 16.0±5.8 0.12
REM sleep (%) 20.7±4.8 21.1±6.6 0.87 20.6±6.2 21.4±5.7 0.87 22.7±5.4 18.8±6.1 0.05
TST (min) 381.7±62.6 358.6±56.1 0.31 364.4±63.6 371.3±51.4 0.71 379.4±46.1 351.4±70.0 0.56
SE (%) 78.2±10.4 76.3±12.7 0.88 77.2±13.5 76.6±8.7 0.15 81.0±9.7 71.9±12.6 0.23
WASO (min) 88.1±43.9 97.3±60.4 0.89 95.3±63.3 91.6±36.4 0.42 79.3±46.3 112.3±59.6 0.37
AI (no./h) 6.8±2.9 12.1±7.1 0.04 9.3±7.1 11.6±5.0 0.32 9.2±4.9 11.3±7.9 0.55
SFI (no./h) 11.2±2.8 14.1±5.5 0.09 12.2±5.0 14.6±4.2 0.32 11.4±3.8 15.1±5.2 0.01
Notes: Data presented as mean ± SD.
Bold values indicate significant BMI, Age and PSQI effect on sleep variables.
Abbreviations: BMI, body mass index; PSQI, Pittsburgh Sleep Quality Index; SOL, sleep onset latency; REM, rapid eye movement; TST, total sleep time; N1(%), sleep stage 1 as a percentage of TST; N2(%), sleep stage 2 as a percentage
of TST; N3(%), sleep stage 3 as a percentage of TST; SE, sleep efficiency; WASO, wake after sleep onset; AI, arousal index; SFI, sleep fragmentation index.
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Sleepwear type
Sleep onset latency
The shortest sleep onset duration was observed for wool
sleepwear (16.0 mins) followed in order by polyester
(18.2 mins) and cotton (18.5 mins), although post-hoc
analysis showed that the differences between each pair of
fiber types were statistically non-significant due to the high
values of SD compared to the mean values (Table 2).
It is known that sleep onset initiation is associated with
a fall in core body temperature,
28
and heat dissipation via
peripheral vasodilation reflected in a rise in the distal skin
temperature.
29
Thus, it would be expected that participants
who dissipate heat at a faster rate should fall asleep more
quickly. Two factors may explain the ease of sleep onset
when sleeping in wool and cotton compared to polyester
sleepwear: the physical transition from the sleep monitor-
ing room to the bedroom, and the fiber properties of the
sleepwear. In this study, the participants stayed in the
monitoring room (at 25 °C and 40% RH) before entering
the warm bedroom (30 °C and 50% RH). This process,
although unusual in a “real life”situation, permitted an
abrupt transition from a warm to hot condition. There may
have been marginally more cool air from the monitoring
room trapped within the wool and cotton fabrics compared
to polyester fabrics due to the crimped nature, three-
dimensional waviness providing bulkiness (loft), and
rough scaly surface of wool fibers
17
and the uneven
twisted structure of cotton fibers
17
compared to the smooth
0
200
180
160
140
120
100
80
60
40
20
REM sleep latency (min)
0
150
100
50
0
Wake after sleep onset (min)
Middle-age Old age
Cotton
Polyeste
r
Wool
Good sleeper Poor sleeper
Good sleeper
Group
Poor sleeper
10
Sleep onset latency (min)
20
30
40
50
60
70 A
B
C
α
α
α
ᆱ
α*
α*
†
† *
*
±
†
Figure 1 Interaction effects between sleepwear and Age/PSQI on sleep variables.
Notes: (A) Sleep onset latency, between sleepwear and Age; (B) Wake after sleep onset, between sleepwear and PSQI; (C) REM sleep latency, between sleepwear and PSQI. Error
bars with standard deviations aredisplayed. Comparison between sleepwearconditionsindicated by*p<0.05 between cotton and wool; †p<0.05 between polyester and wool; ±p<0.05
between cotton and polyester; α,p<0.05 between groups.
Abbreviations: PSQI, Pittsburgh Sleep Quality Index; REM, rapid eye movement.
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DovePress 173
surface of both polyester fibers and fabrics.
17
Also, a
recently published study related to the breathability of
fabrics has highlighted the differing dynamic moisture
buffering potential of cotton, polyester and wool fabrics.
30
Values of the dynamic moisture buffering potential quoted
for matched lightweight single jersey fabrics very similar
to those used in this study were 0.6 KJ·m
−2
, 6.9 KJ·m
−2
,
and 9.9 KJ·m
−2
for polyester, cotton and wool fabrics
respectively. These results show the relatively poor moist-
ure buffering of polyester fibers compared to the more
hygroscopic natural fibers, cotton and wool, and also
quantify the approximately 30% higher value for wool
compared to cotton. Thus, during this short transition
from bedtime to sleep onset (average 18 mins, Table 2),
it is possible that the participants in the wool or cotton
sleepwear were relatively well buffered from the higher
temperature and RH in the sleeping room compared to
when they were in the polyester sleepwear.
Sleep Fragmentation Index, SFI
The lowest value of SFI was observed for wool followed
by cotton and polyester, with a significant difference
observed between wool and polyester sleepwear in the
pairwise comparisons. Again, wool sleepwear was asso-
ciated with the higher sleep quality with an SFI of 12.1 h
−1
compared with 13.3 h
−1
and 13.7 h
−1
for the cotton and
polyester sleepwear, respectively. SFI reflected stage shifts
plus awakenings. The higher rates of SFI suggested a
greater thermal stress when sleeping in cotton or polyester
sleepwear than in wool sleepwear, consistent with reports
of increased thermal stress when sleeping under hot humid
conditions.
24
Thus, the lower SFI when sleeping in wool
would suggest lower thermal stress that may be linked to
the beneficial moisture transfer and wicking properties of
wool.
31
In this study, WBSER was not statistically signifi-
cantly different among the sleepwear. Thus no explanation
is supported about the link between WBSER and thermal
stress experienced by the participants (Figure 2). We were
also unable to confirm respiratory “insensible”loss or
changes in metabolic rates, since any measurements during
the sleep period may interfere with sleep per se or would
40
Cotton Polyester Wool
Sleepwear fiber type
50
Estimated WBSER (g.h-1)
60
70
Figure 2 Estimated whole body sweat evaporation rate (WBSER) (g·h
−1
).
Notes: Error bars with standard deviations are displayed. The equation used for
the calculation of WBSER can be found in the section Data and Statistical Analysis.
Table 4 Subjective ratings on tactile sensation for each sleepwear
Cotton Polyester Wool p-value
Surface texture After donning 2.08±0.73 1.75±0.73 2.22±0.96 0.065
At bedtime 2.19±0.62 1.81±0.75 2.28±0.94†0.037
On waking 2.36±0.80 1.94±0.79†‡ 2.36±0.87 0.045
Prickliness After donning 1.17±0.45 1.17±0.45 1.64±0.90*†0.002
At bedtime 1.28±0.57 1.28±0.62 1.64±0.83*†0.024
On waking 1.33±0.76 1.36±0.68 1.72±0.85*†0.022
Clamminess After donning 1.13±0.48 1.19±0.62 1.16±0.56 0.912
At bedtime 1.28±0.66 1.44±0.84 1.22±0.54 0.454
On waking 1.42±0.77 1.64±0.83 1.53±0.81 0.339
Clinginess After donning 1.11±0.40‡* 1.36±0.64 1.36±0.59 0.043
At bedtime 1.19±0.47 1.42±0.84 1.44±0.65 0.182
On waking 1.42±0.73 1.67±0.96 1.61±0.96 0.456
Notes: Data presented as mean ± SD, N=36. Tactile sensations included surface texture (1=“very soft”to 5=“very rough”), prickliness, clamminess and clinginess of the
sleepwear (1=“not at all”to 5=“extremely”) and were assessed on a five-point Likert scale. Bold values indicate significant sleepwear effect on subjective ratings.*p<0.05 for
difference between cotton and wool; †p<0.05 for difference between polyester and wool;
‡
p<0.05 for difference between cotton and polyester.
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require specialized equipment which was unavailable. In
addition, individual WBSER response to sleeping under
warm conditions differed between subjects; Sagot and
colleagues reported that not all subjects sweated under
sleeping conditions of 30 °C where participants were not
covered.
32
The observation in this study differed from
earlier findings where greater sweat loss and higher micro-
climate relative humidity were observed for sleeping in
polyester compared to wool
31
or cotton.
33
A further study
showed an initial rapid increase in sweating for both wool
and polyester, although the subsequent rate decreased for
wool due to the higher moisture absorption rate of wool
31
compared to the slower moisture transfer capacity of
polyester.
34,35
Other indicators of sleep fragmentation are the AI and
WASO. Non-significant changes were observed for the AI
between fiber types. This observation may be linked to the
greater variability observed for AI compared to that for
SFI (Table 2). Haba-Rubio et al reported that the scoring
process for AI was associated with high inter-scorer varia-
bility, whereas the SFI had a good test-retest reproducibil-
ity and that SFI was significantly correlated with AI.
BMI, age and PSQI
The findings in this study, with respect to the BMI, Age
and PSQI factors generally conform to published litera-
ture. Participants with BMI≥25 kg·m
−2
had poorer sleep
than those with BMI<25 kg·m
−2
as shown by a higher N1,
lower N3 and a higher AI. A previous study has shown
that a low amount of slow wave sleep (N3) was associated
with high BMI in insomniacs.
36
The Old age subgroup
took longer to fall asleep as indicated by a longer SOL
than the Middle-age subgroup. This result was consistent
with data found in a meta-analysis.
2
However, unexpect-
edly this subgroup recorded more N3 than the Middle-age
subgroup, indicating better sleep quality using this para-
meter. Poor sleepers had higher SFI and less REM sleep
than Good sleepers indicating that the Poor sleepers had
lower sleep quality than the Good sleepers in this trial.
This finding is consistent with previous studies that
reported less REM sleep time was associated with a higher
rectal temperature in poor sleepers.
37,38
Interaction effects on sleep quality
between sleepwear and BMI, age or PSQI
Several statistically significant differences were observed
in the interactions between sleepwear fiber type and two of
the three subgroups, Age and PSQI, as shown in Figure 1.
When examined according to the Age factor, the Old age
subgroup showed significantly lower SOL in wool than in
polyester or cotton (Figure 1A). Thus the older partici-
pants (≥65 years) in this cohort fell asleep within 12 mins
on average in wool compared to 22 mins or 27 mins for
polyester or cotton, respectively. As noted in the earlier
discussion of the SOL results, the different thermal insula-
tion and moisture management properties of the three fiber
types may have contributed to the ease of falling asleep in
wool compared with the other fiber types. The SOL find-
ings for sleepwear between the Old age and Middle-age
group may have significant, practical implications, since
this Old age group, who generally took longer to fall
asleep than the Middle-age group, may have preferentially
benefitted from wearing wool sleepwear.
There was also an indication that Poor sleepers bene-
fitted from wool sleepwear over the other fiber types. The
lowest WASO in Poor sleepers was observed for wool
(90 mins) with a statistically significant difference
between wool and cotton (116 mins), but no significant
difference between wool and polyester (99 mins) as shown
in Figure 1B. These differences in sleep quality may be
related to the superior moisture management of the wool
sleepwear compared to the cotton and polyester sleepwear,
which would assist heat dissipation. Even though cotton
and wool are both natural fibers they differ greatly in their
hygroscopicity. Dry wool fibers absorb moisture up to
about 35% of its dry weight in saturated air, whereas
cotton can absorb around 24%.
17
Polyester, an oil-based
synthetic fiber, has a relatively low ability to absorb and
release water vapour quickly with a fiber hygroscopicity
39
of 8–9%.
40
A previous study has shown that Poor sleepers
had more wake time when they had a higher core body
temperature.
41
Poor sleepers also had significantly shorter latency to
REM sleep when sleeping in wool (88 mins) and cotton
(92 mins) than sleeping in polyester (111 mins). Given that
REM sleep latency was increased at high ambient
temperatures,
42
the shortened latency in Poor sleepers
would suggest that sleeping in wool favored an early
appearance of the first REM sleep episode that may be
related to fiber properties of wool mentioned earlier.
Whilst the relationship of this result to sleep quality is
unclear, a reduction in the time to the first REM sleep
episode may also be linked to increased REM sleep
pressure.
43
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Perception of tactile sensations
The average ratings for perceived prickliness, clamminess
and clinginess for all sleepwear at each evaluation point in
the study were between “Not at all”and “Slightly”, indi-
cating that all fabrics were suitable for sleepwear.
Participants rated the average surface texture of the polye-
ster sleepwear as between “Very Soft”and “Soft”while
the cotton and wool sleepwear was rated on average to be
between “Soft”and “Neutral”.
Participants perceived the wool sleepwear to be
slightly pricklier than the cotton and polyester sleepwear.
The prickle sensation in textiles has been shown to be
related to the incidence of stiff fibers on the product’s
surface rather than to fiber type.
44
For wool fabrics the
occurrence of coarse surface fibers has been shown to be
related to the mean and variation in diameter of the wool
fibers within the fabric.
45,46
Moreover, participants
reported wool felt pricklier and rougher than the other
sleepwear at bedtime and on waking on exposure to a
warm condition. This observation is supported by previous
literature that the sensations of prickliness and roughness
were increased with warmth.
47,48
It appears that there is a dissociation between perceived
tactile sensations (prickliness, roughness or clinginess)
during the waking period and objectively measured sleep.
Sleeping in wool promoted sleep onset with the least sleep
fragmentation compared to cotton or polyester sleepwear.
The cotton sleepwear was perceived to be slightly less
clingy than the other sleepwear after the participants chan-
ged into their sleepwear. The subjective feeling of clingi-
ness may be caused by a build-up of static electricity
between the skin surface and the fiber.
49
There was no
difference in the clinginess between polyester and wool
even though electrical resistance has been shown to be
highest for polyester, followed by wool, then cotton at a
constant RH of 35%.
49,50
The study was designed to blind the sleepwear fiber
type. Nonetheless, participants may detect differences in
sleepwear fiber type (cotton, polyester or wool) by the
sense of touch, which could consciously or subconsciously
affect their attitude and potentially their sleep quality.
However, participants did not provide any feedback
about their prediction of fiber types.
Summary and conclusion
This study compared the effect on sleep quality of sleep-
wear fiber type (cotton, polyester and wool) in warm
conditions (30 ºC and 50% RH) for healthy participants
aged 50–70 years old. As would be expected from the
literature
2,36
higher BMI, older and poorer sleepers were
found to have poorer sleep quality in hot, moist conditions
than lower BMI, younger and better sleepers in this study.
Sleeping in wool compared to sleeping in polyester
resulted in less fragmented sleep for all participants.
Sleeping in wool compared to polyester and cotton pro-
moted a quicker sleep onset (SOL) in participants
≥65 years. Poor sleepers had less wake time during the
sleep period (WASO) in wool than in cotton sleepwear and
had a more delayed REM sleep latency in polyester than in
cotton or wool sleepwear. Non-significant differences
between cotton and polyester were observed for all sleep
variables apart from that observed in Poor sleepers. It is
suggested that the superior moisture buffering and moist-
ure management properties of wool compared to cotton
and polyester may be responsible for the different sleep
outcomes observed in this study.
In conclusion, wool sleepwear was shown to promote
better sleep in warm ambient conditions, particularly for
adults aged 65 years and older and for poor sleepers. Thus,
subgroups known to experience poorer sleep quality may
enjoy an extra benefit from using wool sleepwear.
Judicious selection of sleepwear fiber type may therefore
offer an alternative, healthy and natural strategy for older
adults sleeping under warm ambient conditions.
51–54
Future studies could investigate the effects on sleep
quality of sleepwear fiber type in, for example, menopau-
sal women who often experience hot flashes and disturbed
sleep,
51,52
shift workers who have disrupted circadian
timing,
53
in patients with hypothyroidism who have low
metabolic rates or in nursing home residents who often
experience inefficient heating and cooling systems.
54
Disclosure
This study was supported by Australian Wool Innovation Ltd
(AWI) which is funded by Australian woolgrowers and by
the Australian Government. CMC received funding from
AWI and MS was employed under that funding. TM and
AI are employees of AWI. The authors report no other con-
flicts of interest in this work.
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