Association of wood use in bedrooms with comfort and sleep among workers in Japan: a cross-sectional analysis of the SLeep Epidemiology Project at the University of Tsukuba (SLEPT) study

Abstract

Several priority characteristics of wood that have beneficial effects on human beings have been reported. However, the advantages of wood use in bedroom interiors for sleep have not been fully evaluated. The aim of this cross-sectional epidemiological study was to evaluate the association of wood use in housing and bedrooms with comfort in the bedroom and sleep among workers in Japan. The study methods included sleep measurements using actigraphy and a self-administered questionnaire survey. In total, 671 workers (298 men and 373 women; mean age ± standard deviation: 43.3 ± 11.2 years) were included in the analysis. The amount of wood used in bedrooms was significantly associated with comfort in bedrooms, inversely associated with suspicion of insomnia, partly inversely associated with self-rated poor sleep quality, but not associated with low sleep efficiency. On logistic regression analysis, the adjusted odds ratio (aOR) of the “large amount of wood” group relative to the “no wood” group was 3.25 [95% confidence interval (CI) 1.63–6.47] for comfort. The aOR of the “no wood” group relative to the “large amount of wood” group was 2.15 (95% CI 1.11–4.16) for suspicion of insomnia. Wood structure of housing, as well as wood use on either the floor, wall, or ceiling, were not significantly associated with comfort and sleep conditions. Our study suggested that the use of a large amount of wood used in the bedroom interior could be beneficial for comfort, sleep, and therefore, health of workers. Further studies are required to obtain generalizable results.

Full text

Moritaetal. J Wood Sci (2020) 66:10
https://doi.org/10.1186/s10086-020-1852-y
ORIGINAL ARTICLE
Association ofwood use inbedrooms
withcomfort andsleep amongworkers
inJapan: across-sectional analysis oftheSLeep
Epidemiology Project attheUniversity
ofTsukuba (SLEPT) study
Emi Morita1,2* , Masashi Yanagisawa2, Asuka Ishihara2,3, Sumire Matsumoto2,3, Chihiro Suzuki2,4, Yu Ikeda5,
Mami Ishitsuka6, Daisuke Hori7, Shotaro Doki7, Yuichi Oi7, Shinichiro Sasahara7, Ichiyo Matsuzaki2,7
and Makoto Satoh2
Abstract
Several priority characteristics of wood that have beneficial effects on human beings have been reported. However,
the advantages of wood use in bedroom interiors for sleep have not been fully evaluated. The aim of this cross-sec-
tional epidemiological study was to evaluate the association of wood use in housing and bedrooms with comfort in
the bedroom and sleep among workers in Japan. The study methods included sleep measurements using actigraphy
and a self-administered questionnaire survey. In total, 671 workers (298 men and 373 women; mean age ± standard
deviation: 43.3 ± 11.2 years) were included in the analysis. The amount of wood used in bedrooms was significantly
associated with comfort in bedrooms, inversely associated with suspicion of insomnia, partly inversely associated with
self-rated poor sleep quality, but not associated with low sleep efficiency. On logistic regression analysis, the adjusted
odds ratio (aOR) of the “large amount of wood” group relative to the “no wood” group was 3.25 [95% confidence
interval (CI) 1.63–6.47] for comfort. The aOR of the “no wood” group relative to the “large amount of wood” group was
2.15 (95% CI 1.11–4.16) for suspicion of insomnia. Wood structure of housing, as well as wood use on either the floor,
wall, or ceiling, were not significantly associated with comfort and sleep conditions. Our study suggested that the use
of a large amount of wood used in the bedroom interior could be beneficial for comfort, sleep, and therefore, health
of workers. Further studies are required to obtain generalizable results.
Keywords: Sleep, Comfort, Bedroom, Wood, Cross-sectional study, Workers, Pittsburgh Sleep Quality Index (PSQI),
Athens Insomnia Scale (AIS), Actigraphy, Workers
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Introduction
e priority characteristics of wood that have beneficial
effects on human beings have been reported in a review
article on a dozen studies evaluating physiological indices
such as pulse rate, blood pressure, autonomic nervous
activity, and brain activity in case of viewing, touching,
or smelling of wood [1]. It has been shown that touch-
ing hinoki cypress (Chamaecyparis obtusa) wood with
the palm calms prefrontal cortex activity and increases
Open Access
Journal of Wood Scienc
e
*Correspondence: morita.emi.ga@u.tsukuba.ac.jp
1 Forestry and Forest Products Research Institute, Forest Research
and Management Organization, 1 Matsunosato, Tsukuba, Ibaraki
305-8687, Japan
Full list of author information is available at the end of the article

Page 2 of 9
Moritaetal. J Wood Sci (2020) 66:10
parasympathetic nervous activity, resulting in superior
physiological relaxation as compared with that when
touching marble [2].
Further, another review article on wood use for built
indoor environments reported that autonomic stress
responses reduced with the use of wood for interiors
compared with the absence of or use of less wood for
interiors of rooms [3]. An experimental study with 15
participants evaluated comfort relative to the amount
of wood used for interiors and found that the interiors
that had 45% wood had the highest score for a subjective
comfortable feeling compared with those with 0% and
90% wood in the designated room [4]. In an interview
survey with 200 participants, a photograph of a room
with no wood materials prompted reactions such as “I
do not want to sleep” [5]. A study with 20 participants
reported that wooden rooms resulted in less tension and
fatigue and were more beneficial to the autonomic nerv-
ous system, respiratory system, and visual system than
were non-wooden rooms [6].
Sleep is an essential factor for health promotion along
with nutrition and exercise. It has been reported that
poor sleep is a risk factor for metabolic syndrome, can-
cers, and mortality [7–9]. Although good sleep is nec-
essary to maintain health and high performance, many
workers experience sleep problems. A survey target-
ing Japanese workers reported that 71.0% of partici-
pants were aware of insomnia symptoms within the
previous 1 year [10]. Another survey reported that the
self-reported prevalence of insomnia among Japanese
workers was 23.6% [11].
Sleep may be affected by personal factors including
age and lifestyle, social factors such as working hours,
and external factors such as environmental factors. Since
wood use in the built environment has beneficial effects
on human beings, it might provide a superior environ-
ment in bedrooms and lead to good sleep. However, the
association of wood use in housing and bedrooms with
comfort in bedrooms and daily sleep condition is still
unclear.
It is necessary to evaluate the daily comfort and sleep
of people in their residential environments to clarify this
association. Epidemiological studies with a large num-
ber of participants should be conducted for this purpose.
Observational studies, which are a kind of epidemiologi-
cal studies, cannot standardize various factors related to
comfort, sleep, or participants’ characteristics. erefore,
the study design requires a large number of participants
to adjust various factors during statistical analyses.
e aim of this epidemiological study, therefore, was
to evaluate the association of wood use in housing and
bedrooms with comfort in bedrooms and sleep among
workers.
Methods
Data collection
is study was a cross-sectional study, which is a type
of observational epidemiological study. e study pro-
tocol was approved by the ethics committee of the Uni-
versity of Tsukuba School of Medicine (approval No.
1065). Written informed consent was obtained from all
participants.
Data collection for the SLEPT Study (SLeep Epi-
demiology Project at the University of Tsukuba) was
conducted between August 2016 and November 2017
at 4 workplaces—a national university, a national insti-
tute, an institute of a company at the Ibaraki Prefec-
ture located near Tokyo, and a health care company
in Tokyo—as well as from some workers introduced
by the staff or study participants. Participants were
enrolled only through open recruitment using flyers,
posters, workplace group e-mails, and online workplace
bulletin boards. ere was no individual solicitation
in principle, and we did not ask the participants about
sleep status prior to enrollment.
Participants
In this study, 785 individuals were recruited. Among
them, 4 participants withdrew their consent, and 110
participants were excluded as they did not fulfill the
study criteria [e.g., lack of data on sleep measurements,
Pittsburgh Sleep Quality Index (PSQI), or questionnaire
responses related to housing or bedroom] or selected
“others” for “type of housing” (n = 13). In total, 671 par-
ticipants (298 men and 373 women; mean age ± stand-
ard deviation: 43.3 ± 11.2years, range 22–68years) who
completed the sleep measurements, responded to all rel-
evant questions in the questionnaire, and did not with-
draw consent were included in the analysis.
Questionnaire
e participants were requested to complete a self-
administrated questionnaire including questions about
type of housing (apartment, detached house, or others);
style of bedroom (western/Japanese); use of wood, for
example, structure of housing (reinforced concrete, steel‐
frame, or wood), amount of wood used for interiors, fur-
niture, and door(s) in the bedroom (“How much wood is
used in your bedroom, including interiors, furniture, and
door(s)?”: 1: large, 2: rather, 3: rare, 4: not at all), use of
wood on floor (yes/no), walls (yes/no), and ceiling (yes/
no) of the bedroom; uncomfortableness of noises includ-
ing snoring in the bedroom (noisy/quiet); health-related
parameters such as height, weight, and lifestyle factors
such as smoking status, nightcap (defined as drinking

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Moritaetal. J Wood Sci (2020) 66:10
within 2 h before sleeping once a week or more), and
habitual exercise.
e questionnaire also included items regarding com-
fort in the bedroom (“Do you feel mental comfort or
serenity in the bedroom?”; 1: very, 2: rather, 3: neutral,
4: rather not, 5: not at all) and PSQI, which is one of the
most frequently used indices for evaluating self-rated
sleep quality in sleep medicine [12, 13]. PSQI, which can
assess sleep quality and disturbances over 1month, con-
sists of the following seven components: subjective sleep
quality, sleep latency, sleep duration, habitual sleep effi-
ciency, sleep disturbance, use of sleeping medication, and
daytime dysfunction [12]. e Athens Insomnia Scale
(AIS) was developed based on ICD-10 (10th revision of
the International Statistical Classification of Diseases and
Related Health Problems) by the World Health Organi-
zation [14–16]. AIS consists of eight items; for example,
one of the eight items is awakenings during the night,
which can be graded as 0: no problem, 1: minor problem,
2: considerable problem, or 3: serious problem or did not
sleep at all [14]. AIS was added to the questionnaire of
the national university from June 2017. e available data
for AIS were obtained from 530 participants.
Sleep measurements
Participants were required to wear an actigraphy device
on the waist (MTI-210, ACOS Co., Ltd., Nagano, Japan)
for 24h a day, except during bath time, for a week to esti-
mate actual sleep time and sleep efficiency and to record
their sleeping and waking timesin a sleep diary [17, 18].
e actigraphy data were analyzed using Sleep Sign Act
software (Kissei Comtec Company Inc., Matsumoto City,
Japan) [18]. We included only the longest sleep time dur-
ing 24h (from noon to noon on the next day) but not
naps, because it seemed to be highly probable that only
the longest sleep time would be spent in the bedroom.
Statistical analysis
e four categories for the amount of wood used in the
bedroom interior were modified into three categories in
this study by combining the two lower categories (“rare”
and “not at all”) into one category, “not used”, because the
number of participants who responded “not at all” was
only 16. Comfort was defined by the two higher catego-
ries, “very” and “rather”. Poor sleep quality was defined as
PSQI ≥ 6 [12, 13]. Suspicion of insomnia was defined as
AIS ≥ 6 [15]. As no appropriate actigraphy-based cut-off
point of sleep efficiency is known at present, we defined
low sleep efficiency as sleep efficiency of < 70% based on
the available actigraphy data.
Overweight was defined as body mass index
(BMI) ≥ 25.0 kg/m2. BMI was calculated based on self-
assessed height and weight. Exercise habit was defined
as exercise activities performed for 30min or more per
session, twice a week or more, and continued for at least
1year, as same as that defined by National Health and
Nutrition Survey by conducted by Ministry of Health,
Labour and Welfare, Japan [19].
e percentage difference between the groups was
calculated using the Chi-square test. e associations
between the ordinal variables were analyzed using the
Mantel–Haenszel test for trend.
Since the participants had several different back-
grounds and circumstances, multivariate analysis was
conducted to adjust for various factors. Two multivari-
ate analyses are commonly used in epidemiology. One is
multiple regression analysis, which is performed when
the dependent variable is a continuous variable. e
other is logistic regression analysis, which is performed
when the dependent variable is a binary one, such as
presence or absence of a disease. is study adopted
several binary variables as outcomes, e.g., presence or
absence of the suspicion of insomnia. erefore, logistic
regression analysis was extensively used.
We used two models in the logistic regression analy-
sis. e results of logistic regression analysis might dif-
fer according to the set independent variables; therefore,
more than one analysis model, which have different inde-
pendent variables, are often used. Model 1 was adjusted
by considering possible confounders without wood-
related factors. Model 2 was adjusted by considering
possible confounders with the structure of housing for
targeting only the wood use in the bedroom.
To assess the relevant factors related to comfort in the
bedroom, in Model 1 the dependent variable was com-
fort in the bedroom (yes/no), whereas the independent
variables were sex, age (5 categories: 20, 30, 40, 50, and
60s), type of housing (apartment/detached house), age
of the building (4 categories: < 10 years, 10–19 years,
20–29years, and ≥ 30years), style of the bedroom, area
of the bedroom (3 categories: < 6Jo, 6–8Jo, and ≥ 8.5Jo),
noise in bedroom (noisy/quiet), and each one of the
wood-related factors in housing or bedrooms (5 factors):
structure of housing, wood floor, wood wall, wood ceil-
ing, and amount of wood used in the bedroom interior
(3 categories). “Jo” indicates the unit of Tatami (approxi-
mately 1800mm × 900mm). In Model 2, the independ-
ent variable, structure of housing (3 categories), was
added to the independent variables in Model 1, for all
calculations.
To evaluate the relevant factors of sleep condi-
tions, characteristics of participants were additionally
adjusted in logistic regression analysis. e dependent
variable was each one of the three sleep-related fac-
tors such as poor sleep quality (PSQI ≥ 6), suspicion
of insomnia (AIS ≥ 6), and low sleep efficiency (< 70%),

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Moritaetal. J Wood Sci (2020) 66:10
whereas the independent variables were sex, age(5 cat-
egories), BMI, habitual exercise (yes/no), smoking (cur-
rent smokers/other responses), nightcap (yes/no), shift
worker (current shift worker/other responses), type of
housing, age of building, style of the bedroom, area of
the bedroom, structure of housing, noise in the bed-
room, and each one of the four wood-related factors
in bedrooms; wood floor, wood wall, wood ceiling, and
amount of wood used in the bedroom interior.
e data set used was version 20191028. e signifi-
cance level was set at 5%. IBM SPSS Statistics version
23 for Windows (IBM, Armonk, NY, USA) was used for
the statistical analysis.
Results
Demographics ofparticipants andcharacteristics
ofhousing andbedroom amongtheparticipants
Characteristics of the participants are shown in Table1.
About 17.7% (n = 119) of the participants were over-
weight (BMI ≥ 25 kg/m2), and being overweight is one of
the risk factors of sleep apnea syndrome, which is a dis-
order in which breathing is interrupted during sleeping,
resulting in poor sleep conditions. e percentage of par-
ticipants with nightcap which may lead to sleep-worthy
conditions was 24.4% (n = 164).
Characteristics of housing and bedroom among the
participants are shown in Table2. Wooden structures
occupied 44.0% (n = 295) for structure of housing. Per-
centage of “large” amount of wood used in bedroom inte-
rior was 28.9% (n = 194). Structure of housing between
apartments and detached houses revealed a statistically
significant difference (p < 0.001); reinforced concrete
occupied 73.8% of apartments, while wood occupied
78.4% of detached houses.
Age of the building was significantly associated with
individuals feeling hot during summer (< 10years, 24.7%
vs. ≥ 30years, 64.7%: Trend, p < 0.001) and feeling cold
during winter (< 10 years, 27.2% vs. ≥ 30 years, 68.6%:
Trend, p < 0.001) in bedrooms; higher percentages of hot
and cold feelings were observed for individuals living in
older buildings than in those that were recently built.
Table 1 Characteristics ofparticipants (n = 671)
SD standard deviation, BMI body mass index
Sex: men, n (%) 298 (44.4%)
Age (mean ± SD), years 43.3 ± 11.2
Nightcap, n (%) 164 (24.4%)
Current smokers, n (%) 59 (8.8%)
Exercise habit, n (%) 129 (19.2%)
BMI ≥ 25.0, n (%) 119 (17.7%)
Shift worker, n (%) 60 (8.9%)
Table 2 Characteristics ofhousing andbedroom amongtheparticipants
a Jo: unit of Tatami (approximately 1800mm × 900mm)
Structure of housing Reinforced concrete Steel‐frame construction Wood
266 (39.6%) 110 (16.4%) 295 (44.0%)
Type of housing Apartment Detached house
328 (48.9%) 343 (51.1%)
Age of building < 10years 10–19years 20–29years ≥ 30years
235 (35.0%) 194 (28.9%) 140 (20.9%) 102 (15.2%)
Style of bedroom Japanese Western
194 (28.9%) 477 (71.1%)
Area of bedroom < 6 Joa6–8 Jo ≥ 8.5 Jo
46 (6.9%) 498 (74.2%) 127 (18.9%)
Amount of wood in bedroom Large Rather None
194 (28.9%) 364 (54.2%) 113 (16.8%)
Wood use in bedroom Yes No
Floor 439 (65.4%) 232 (34.6%)
Wall 189 (28.2%) 482 (71.8%)
Ceiling 233 (34.7%) 438 (65.3%)
Comfortable temperature in bedroom Yes No
Feeling hot in summer 257 (38.3%) 414 (61.7%)
Feeling cold in winter 282 (42.0%) 389 (58.0%)
Noise in bedroom Yes No
130 (19.4%) 541 (80.6%)

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Moritaetal. J Wood Sci (2020) 66:10
Amount of wood used in the bedroom interior signifi-
cantly differed (p = 0.046) between Japanese style (“large”
amount: 37.1%) and western style (“large” amount:
25.6%) bedrooms.
Association ofcomfort inbedrooms withfactors related
tohousing andbedroom
e proportion of participants who responded to the
question regarding comfort in bedrooms was 81.5%. Per-
centage of comfort according to the structure of housing
and the amount of wood in bedroom interior is shown
in Fig.1a, b. Association between comfort and amount
of wood in bedrooms was statistically significant (Trend,
p = 0.001); larger the amount of wood in the bedroom
higher the percentage of comfort (Fig.1b).
Percentage of comfort in the bedroom with wood floor
(83.8%) or western style (83.4%) was significantly higher
than that with a non-wood floor (77.2%, p = 0.03) or
Japanese style (76.8%, p = 0.04). Comfort in the bedroom
between age of housing (< 10years 86.4%, 10–19 years
82.5%, 20–29years 80.0%, and ≥ 30years 70.6%; Trend,
p = 0.001), feeling hot in summer (yes 74.3%, no 86.0%;
p < 0.001), feeling cold in winter (yes 75.9%, no 85.6%;
p = 0.001), and noise in the bedroom (yes 64.6%, no
85.6%; p < 0.001) was also significantly different.
No significant difference was observed for comfort
in the bedroom with wood walls (yes 79.9%, no 82.2%;
p = 0.50), wood ceilings (yes 81.5%, no 81.5%; p = 0.99),
the structure of housing (p = 0.34, Fig. 1a), and type of
housing (p = 0.38). Although the area of the bedroom
was not significant (p = 0.09), the percentage of comfort
for small bedrooms (< 6Jo: 69.6%) was lower than that for
large bedrooms (6–8 Jo: 82.7%, ≥ 8.5 Jo: 81.1%).
e adjusted odds ratio (aOR) and 95% confidence
interval (CI) of wood-related factors for comfort in
bedrooms on logistic regression analysis are shown in
Table3. ere was a significant association between the
86.6%
82.1%
70.8%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Large used Rather used No us ed
Trend p = 0.001
80.1%
86.4%
81.0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Reinforced concrete Steel-frame
construcon
Wooden
p = 0.34
(n = 266) (n = 110) (n = 295) (n = 194) (n = 364) (n = 113)
(a) (b)
Fig. 1 Proportion of comfort in bedrooms. a According to the structure of housing, b according to the amount of wood used in bedroom interior
Table 3 Adjusted odds ratios of wood-related factors
forcomfort inbedrooms
Model 1: adjusted by sex, age, type of housing, age of building, style of
bedroom, area of bedroom, and noise in bedroom
Model 2: adjusted by sex, age, type of housing, age of building, style of
bedroom, area of bedroom, noise in bedroom, and structure of housing
aOR adjusted odds ratio, CI condence interval
Model 1 Model 2
aOR (95% CI) aOR (95% CI)
Structure of housing
Reinforced concrete 1 Ref. –
Steel‐frame construc-
tion 1.28 (0.64–2.57) –
Wood 0.90 (0.45–1.80) –
Wood in bedroom
Floor (yes/no) 1.05 (0.54–2.05) 1.09 (0.56–2.14)
Wall (yes/no) 1.00 (0.61–1.65) 1.03 (0.63–1.70)
Ceiling (yes/no) 1.08 (0.67–1.76) 1.12 (0.68–1.85)
Amount of wood in bedroom
Large 2.86 (1.47–5.56) 3.25 (1.63–6.47)
Rather 1.69 (0.99–2.89) 1.76 (1.02–3.03)
None 1 Ref. 1Ref.

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Moritaetal. J Wood Sci (2020) 66:10
amount of wood used in the bedroom interior and com-
fort. e aORs for the “large amount of wood” group
relative to the “no wood group” were 2.86 (95% CI 1.47–
5.56) in Model 1 and 3.25 (95% CI 1.63–6.47) in Model
2. Even after adjusting for possible relevant factors, the
amount of wood used in the bedroom interior was sig-
nificantly associated with comfort in the bedroom.
Similarly, there was a significant association between
comfort and quietness in the bedroom in both models
[quiet (reference: noisy); Model 1: aOR, 3.32 (95% CI
2.08–5.28); Model 2: aOR, 3.21 (95% CI 2.01–5.13)].
Association ofsleep conditions withhousing andbedroom
characteristics
Proportions of participants with poor sleep qual-
ity (PSQI ≥ 6), suspicion of insomnia (AIS ≥ 6), and
low sleep efficiency were 49.2% (n = 330), 33.8%
(n = 179/530), and 14.8% (n = 99), respectively.
Percentages of poor sleep quality, suspicion of insom-
nia, and low sleep efficiency according to the amount
of wood are shown in Figs.2a–c. Suspicion of insom-
nia (Trend, p = 0.013) was inversely associated with
the amount of wood in the bedroom, while nosignifi-
cant associations were observed between the amount
of wood in the bedroom and poor sleep quality (Trend,
p = 0.11) or low sleep efficiency (Trend, p = 0.62).
e aORs and 95% CIs on logistic regression analysis
of factors related to wood for poor sleep quality, suspi-
cion of insomnia, and low sleep efficiency are shown
in Table4. After adjusting for the possible relevant fac-
tors in logistic regression analysis, the amount of wood
was significantly associated with suspicion of insomnia
and showed a partly significant association with poor
sleep quality, but not with sleep efficiency. e aOR of
the “no wood” group relative to the “large amount of
wood” group was 2.15 (95% CI 1.11–4.16) for suspicion
44.3%
50.5%
53.1%
0%
10%
20%
30%
40%
50%
60%
Large used Rather used No used
Trend p = 0.11
25.3%
36.3%
39.8%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Large used Rather used No used
Trend p = 0.013
14.9% 15.4%
12.4%
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
Large used Rather used No used
Trend p= 0.62
(n = 194) (n = 364) (n= 113) (n = 150) (n = 292) (n = 88) (n = 194) (n = 364) (n= 113)
(a) (b) (c)
Fig. 2 Proportion of poor sleep conditions according to the amount of wood in bedrooms. a Proportion of participants with poor sleep quality
(PSQI ≥ 6) according to the amount of wood in the bedroom. b Proportion of participants with suspicion of insomnia (AIS ≥ 6) according to the
amount of wood in the bedroom. c Proportion of participants with low sleep efficiency (< 70% by actigraphy) according to the amount of wood in
the bedroom
Table 4 Adjusted odds ratios ofwood use inbedrooms forsleep conditions
Adjusted by sex, age, body mass index, habitual exercise, smoking, nightcap, shift worker, type of housing, age of building, style of bedroom, area of bedroom,
structure of housing, and noise in bedroom
aOR adjusted odds ratio, CI condence interval, PSQI Pittsburgh Sleep Quality Index, AIS Athens Insomnia Scale
Poor sleep quality (PSQI ≥ 6) Suspicion ofinsomnia (AIS ≥ 6) Low sleep eciency
aOR (95% CI) aOR (95% CI) aOR (95% CI)
Wood in bedroom
Floor (no/yes) 1.57 (0.93–2.66) 1.63 (0.82–3.24) 1.00 (0.51–1.97)
Wall 1.34 (0.91–1.98) 1.17 (0.72–1.90) 1.36 (0.77–2.42)
Ceiling 1.05 (0.72–1.53) 1.14 (0.72–1.81) 0.88 (0.51–1.51)
Amount of wood in bedroom
Large 1 Ref. 1Ref. 1Ref.
Rather 1.48 (1.00–2.19) 1.90 (1.17–3.10) 0.91 (0.52–1.59)
None 1.66 (0.97–2.83) 2.15 (1.11–4.16) 0.54 (0.24–1.18)

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Moritaetal. J Wood Sci (2020) 66:10
of insomnia. e aOR of the “rather amount of wood”
group (n = 364) relative to the “large amount of wood”
group was 1.48 (95% CI 1.00–2.19; p = 0.049) for poor
sleep quality, but the aOR of the “no wood” group rela-
tive to the “large amount of wood” group (n = 194) did
not reach statistical significance [1.66 (95% CI 0.97–2.83;
p = 0.062)]. Regarding wood use in housing and the bed-
room, the structure of housing, wood floor, wood wall,
and wood ceiling were not significantly associated with
poor sleep quality, suspicion of insomnia, and low sleep
efficiency.
e results on these logistic regression analyses, except
for the above-mentioned wood-related factors, were as
follows: poor sleep quality was significantly associated
with noise in the bedroom (aOR: 1.68; 95% CI 1.12–2.53);
suspicion of insomnia was associated with noise in the
bedroom (aOR: 1.67; 95% CI 1.05–2.66), nightcap, and
age group; and low sleep efficiency was found to be asso-
ciated with sex and BMI.
Discussion
e study revealed that among the wood-related factors
assessed, the amount of wood used in the bedroom inte-
rior is the most relevant factor associated with comfort
in the bedroom. e amount of wood used and quietness
in the bedroom were also relevant factors associated with
self-rated sleep conditions such as lesssuspected insom-
nia. is study suggested that the use of a large amount
of wood in the bedroom interior is beneficial for comfort
and sleep, although the choice of material for the interior
depends on the preference of individuals.
Our study suggested that a higher percentage of wood
use was associated with higher levels of comfort and less
suspected insomnia. However, it has been reported that
the highest scores for a comfortable and restful state were
obtained with 45% wood use for the interior in the exper-
imental room compared with 0% and 90% wood use in
the room [4]. ese conflicting results may be due to the
inconsistency between the study methods. For example,
the evaluation in the previous study was conducted on
the room designated for the study. One of the reasons for
the inconsistent results in this study could be the use of
dark-colored wood for the room interior in the previous
study, which may impart a heavy feel. If a light-colored
interior had been used, the results might have been dif-
ferent. Furthermore, our study was evaluated using a
self-administered questionnaire. “Large amount of wood”
was not evaluated by percentage. Our study included not
only interior finish, but also furniture in the actual bed-
room of the participants, and therefore, we assumed that
it would be difficult for the participants to determine
the percentage of the amount of wood. In addition, the
volume of furniture and size of the bedroom would be
different between the participants. In contrast, the previ-
ous study mainly evaluated the interior finish and a few
items of furniture (limited to a sofa and a low table) in an
experimental room instead of the actual bedroom of the
participants.
e study evaluated both objective and subjective sleep
conditions. Self-rated sleep conditions were mostly asso-
ciated with the amount of wood used in the bedroom
interior, while sleep efficiency, which is an objective
sleep condition, was not associated with it. us, disa-
greements between objective and subjective results can
occur, because each item is used for a different assess-
ment. For example, the International Classification of
Sleep Disorders, ird Edition (ICSD-3) diagnostic crite-
ria for insomnia do not include sleep duration [20].
is study had some limitations. First, since this
research was an epidemiological study in which cer-
tain biases are common, the evaluation was limited. For
example, the evaluation was conducted only once, and
therefore, seasonal differences in sleep could not be eval-
uated. Moreover, the risk factors for poor sleep were not
fully assessed in this study (e.g., genetic factors, measure-
ment of temperature in the bedroom, etc.). Furthermore,
we could not conclude clearly what factors (e.g., vision)
related to a large amount of wood used in the bedroom
interior were relevant for comfort or sleep. Second, the
study was a cross-sectional study which could not iden-
tify a causal relationship. Cohort studies will be required
to evaluate the causal relationship between the use of
a large amount of wood in the bedroom interior and
good sleep by identifying the incidence of poor sleep in
follow-up participants who do not have complaints of
poor sleep at baseline survey, although the limitations of
an epidemiological study design will still remain. ird,
if the number of participants had been larger, a detailed
stratified analysis could have been conducted, e.g., based
on sex or age groups. Fourth, this study was not specific
to wood use, so there might have been a lack of informa-
tion on the wood used. However, because the study was
not specific to wood use, there might have been less bias
in favor of favorable responses for association between
wood use and sleep.
e strength of this epidemiological study was that
evaluation of the association between wood use in bed-
room interior and sleep was conducted on a relatively
large number of participants based on the actual daily sit-
uations and not in an artificial setup of an experimental
room. A review article described that one of the limita-
tions of previous studies was that the number of partici-
pants was generally small and a high proportion of these
studies only recruited men and women in their 20s, and
therefore, studies with large numbers of participants
including a greater range of ages are essential to obtain

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Moritaetal. J Wood Sci (2020) 66:10
generalizable results [1]. In addition, most of the sleep
epidemiological studies in Japan had been conducted
using only questionnaires. However, we conducted sleep
measurement using actigraphy in more than 600 work-
ers. us, our study highlighted a new aspect of research
in this field.
In general, the results of different targeted populations
in epidemiological studies are often inconsistent. ere-
fore, further studies should be conducted across different
populations. Finally, it would also be beneficial to con-
duct a meta-analysis to assess the results of a large num-
ber of well-designed studies.
Conclusions
In conclusion, the use of a large amount of wood in the
bedroom interior was associated with comfort in the
bedroom, inversely associated with suspicion of insom-
nia, and partly inversely associated with self-rated poor
sleep quality in this study on more than 600 workers in
Japan. Noise, including that of snoring in the bedroom,
was also a relevant external factor for self-rated poor
quality and suspicion of insomnia. However, the amount
of wood was not associated with low sleep efficiency
measured by actigraphy. Our study suggested that the use
of a large amount of wood in the bedroom interior could
be beneficial for comfort, sleep, and therefore, health of
workers. Further epidemiological studies are required to
obtain robust results.
Abbreviations
aOR: adjusted odds ratio; CI: confidence interval; PSQI: Pittsburgh Sleep Quality
Index; AIS: Athens Insomnia Scale; BMI: body mass index.
Acknowledgements
The authors thank individuals who participated in the study. The authors also
thank Ms. Yuhmi Ito and Mr. Hayahiro Takikawa of MEDIROM Inc.; Dr. Hirokazu
Tachikawa and the staff of Tsukuba University Health Center; Ms. Noriko Naka-
mura, Ms. Emi Sakurai, and Ms. Noriko Fujiwara of the International Institute for
Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba; Mr. Hiroyuki Koda
and the staff of the Health and Safety Office, High Energy Accelerator Research
Organization (KEK); Ms. Miyoko Kobayashi and the staff of Tsukuba Research
Center, KURA RAY Co., Ltd., for collecting the data; and Mr. Naruki Teradaira, Mr.
Takumi Fukuda, and Mr. Kohei Kawahara at the University of Tsukuba for data
management assistance. The authors also thank all volunteers who donated
through crowdfunding, and Mr. Tetsuro Hiei, Ms. Yukari Hamaguchi, and Ms.
Sara Kobayashi of the Alliance and Communication Team of IIIS, University of
Tsukuba, for their support in conducting the crowdfunding.
Authors’ contributions
EM, MY, YO, SS, IM, and MS designed the study protocol. All authors, except YI
and CS, contributed to data collection. EM and YI conducted data manage-
ment. EM, YI, and CS contributed to the data set generation. EM was the main
contributor in writing the manuscript. All authors read and approved the final
manuscript.
Funding
This study was supported by JSPS KAKENHI Grant (No. 16H03245) from the
Ministry of Education, Culture, Sports, Science, and Technology, Japan, and
crowdfunding by volunteers.
Availability of data and materials
The datasets generated and analyzed during the current study are not publicly
available. Dataset use by third parties is not approved by the ethics committee
of the University of Tsukuba due to research on humans, but will be available
from the corresponding author on request after the approval of the ethics
committees in both institutions to provide and to receive such datasets.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Forestry and Forest Products Research Institute, Forest Research and Man-
agement Organization, 1 Matsunosato, Tsukuba, Ibaraki 305-8687, Japan.
2 International Institute for Integrative Sleep Medicine (WPI-IIIS), University
of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan. 3 Ph.D. Program
in Human Biology, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki
305-8577, Japan. 4 Master’s Program in Medical Sciences, University of Tsukuba,
1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan. 5 Graduate School of Com-
prehensive Human Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba,
Ibaraki 305-8577, Japan. 6 Faculty of Medical Technology, Teikyo University,
2-11-1 Kaga, Itabashi City, Tokyo 173-8605, Japan. 7 Faculty of Medicine, Uni-
versity of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan.
Received: 10 June 2019 Accepted: 16 January 2020
References
1. Ikei H, Song C, Miyazaki Y (2017) Physiological effects of wood on
humans: a review. J Wood Sci 63:1–23. https ://doi.org/10.1007/s1008
6-016-1597-9
2. Ikei H, Song C, Miyazaki Y (2018) Physiological effects of touching hinoki
cypress (Chamaecyparis obtusa). J Wood Sci 64:226–236. https ://doi.
org/10.1007/s1008 6-017-1691-7
3. Burnard MD, Kutnar A (2015) Wood and human stress in the built indoor
environment: a review. Wood Sci Technol 49:969–986. https ://doi.
org/10.1007/s0022 6-015-0747-3
4. Tsunetsugu Y, Miyazaki Y, Sato H (2007) Physiological effects in humans
induced by the visual stimulation of room interiors with different
wood quantities. J Wood Sci 53:11–16. https ://doi.org/10.1007/s1008
6-006-0812-5
5. Sakuragawa S (2006) Change in the impression of rooms with interior
wood finishes arranged differently: questionnaire survey with the use
of photographs for the analysis of impressions of rooms concerning
living activities. J Wood Sci 52:290–294. https ://doi.org/10.1007/s1008
6-005-0764-1
6. Zhang X, Lian Z, Wu Y (2017) Human physiological responses to wooden
indoor environment. Physiol Behav 174:27–34. https ://doi.org/10.1016/j.
physb eh.2017.02.043
7. Matsumoto T, Murase K, Tabara Y, Gozal D, Smith D, Minami T, Tachikawa
R, Tanizawa K, Oga T, Nagashima S, Wakamura T, Komenami N, Setoh K,
Kawaguchi T, Tsutsumi T, Takahashi Y, Nakayama T, Hirai T, M atsuda F, Chin
K (2018) Impact of sleep characteristics and obesity on diabetes and
hypertension across genders and menopausal status: the Nagahama
study. Sleep. https ://doi.org/10.1093/sleep /zsy07 1
8. Cao J, Eshak ES, Liu K, Muraki I, Cui R, Iso H, Tamakoshi A, JACC Study
Group (2019) Sleep duration and risk of breast cancer: the JACC study.
Breast Cancer Res Treat 174:219–225. https ://doi.org/10.1007/s1054
9-018-4995-4
9. Tamakoshi A, Ohno Y, JACC Study Group (2004) Self-reported sleep
duration as a predictor of all-cause mortality: results from the JACC study,
Japan. Sleep 27:51–54
10. Toyoshima A, Moriyama M, Asano K, Mitsuhashi K, Rahman MM (2018)
Workers’ sleep condition and related disorders in Japan: an analysis based
on health insurance claim data and questionnaire. Int J Occup Saf Ergon
24:614–623. https ://doi.org/10.1080/10803 548.2017.13394 40
11. Nakata A, Haratani T, Takahashi M, Kawakami N, Arito H, Kobayashi F, Araki
S (2004) Job stress, social support, and prevalence of insomnia in a popu-
lation of Japanese daytime workers. Soc Sci Med 59:1719–1730. https ://
doi.org/10.1016/j.socsc imed.2004.02.002

Page 9 of 9
Moritaetal. J Wood Sci (2020) 66:10
12. Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ (1989) The
Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice
and research. Psychiatry Res 28:193–213. https ://doi.org/10.1016/0165-
1781(89)90047 -4
13. Doi Y, Minowa M, Uchiyama M, Okawa M, Kim K, Shibui K, Kamei Y (2000)
Psychometric assessment of subjective sleep quality using the Japanese
version of the Pittsburgh Sleep Quality Index (PSQI-J) in psychiatric
disordered and control subjects. Psychiatry Res 97:165–172. https ://doi.
org/10.1016/s0165 -1781(00)00232 -8
14. Soldatos CR, Dikeos DG, Paparrigopoulos TJ (2000) Athens Insomnia
Scale: validation of an instrument based on ICD-10 criteria. J Psychosom
Res 48:555–560. https ://doi.org/10.1016/S0022 -3999(00)00095 -7
15. Soldatos CR, Dikeos DG, Paparrigopoulos TJ (2003) The diagnostic validity
of the Athens Insomnia Scale. J Psychosom Res 55:263–267. https ://doi.
org/10.1016/S0022 -3999(02)00604 -9
16. Okajima I, Nakajima S, Kobayashi M, Inoue Y (2013) Development and
validation of the Japanese version of the Athens Insomnia Scale. Psychia-
try Clin Neurosci 67:420–425. https ://doi.org/10.1111/pcn.12073
17. Nakazaki K, Kitamura S, Motomura Y, Hida A, Kamei Y, Miura N,
Mishima K (2014) Validity of an algorithm for determining sleep/wake
states using a new actigraph. J Physiol Anthropol 33:31. https ://doi.
org/10.1186/1880-6805-33-31
18. Matsuo M, Masuda F, Sumi Y, Takahashi M, Yamada N, Ohira MH, Fujiwara
K, Kanemura T, Kadotani H (2016) Comparisons of portable sleep moni-
tors of different modalities: potential as naturalistic sleep recorders. Front
Neurol 7:110. https ://doi.org/10.3389/fneur .2016.00110
19. National Institute of Health and Nutrition (2012) Outline of the National
Health and Nutrition Survey (NHNS) Japan, 2012. In: Section of the
National Health and Nutrition Survey. National Institute of Health and
Nutrition. http://www.nibio hn.go.jp/eiken /engli sh/resea rch/proje
ct_nhns.html. Accessed 13 Feb 2019
20. American Academy of Sleep Medicine (2014) International classification
of sleep disorders, 3rd edn. American Academy of Sleep Medicine, Darien
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