Heliyon 10 (2024) e28228

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Research article

Insomnia symptoms and related factors in a community-based
population: The Yamagata Cohort study
Miho Suzuki a, b, *, Natsuko Suzuki a, Kaori Sakurada c, Norihiko Tsuchiya d,
Yoshiyuki Ueno e, Tsuneo Konta aaDepartment of Public Health and Hygiene, Yamagata University Graduate School of Medical Science, Yamagata, Japan
Department of Health and Nutrition, Yamagata Prefectural Yonezawa University of Nutrition Sciences, Yonezawa, Japanc
Department of Fundamental Nursing, Yamagata University Graduate School of Nursing, Yamagata, Japand
Department of Urology, Yamagata University Faculty of Medicine, Yamagata, Japane
Department of Gastroenterology, Yamagata University Faculty of Medicine,Yamagata,Japanb

A R T I C L E I N F O

A B S T R A C T

Keywords:
Insomnia
Community residents
Cohort study

Objective/background: Insomnia is prevalent and is a risk factor for the development of lifestylerelated diseases and early death. To improve insomnia, it is necessary to identify the factorsthat affect it. This study investigated the associations between insomnia symptoms and mental,
physical, and environmental factors in the general Japanese population.
Patients/methods: The study participants were 7,873 individuals who responded to the Health andLifestyle Survey questionnaire that included sleep-related items between December 2021 andMarch 2022. Insomnia symptoms were defined as a score of 6 or higher on the Athens Insomnia
Scale (AIS). A multivariate logistic regression analysis was performed to identify factors inde­
pendently associated with insomnia symptoms.
Results: Of all subjects, 23.4% had insomnia symptoms. Factors associated with insomnia symp­
toms were older age, female sex, very difficult living conditions on current income, pain/
discomfort, anxiety, lack of happiness, frequent nocturia, long duration from bathing time to
bedtime, bedroom lighting, and short walking duration. The subgroup analysis showed stronger
associations between walking time in men, higher body mass index in women, time from bathingtime to bedtime, and daily walking duration in older adults.
Conclusions: Insomnia symptoms were common in community-based populations and wereindependently associated with three different factor groups including physical, psychological, andenvironmental factors. Improvements in insomnia symptoms require appropriate practical sup­port tailored to an individual’s situation.

1. Introduction
Insomnia, in terms of less duration or deterioration in sleep, is associated with an increased risk of lifestyle-related diseases, such as
cardiovascular disease [1], hypertension [2], type II diabetes [3], and premature death [4]. In 2014, the Guidelines for Sleep for Health
Promotion proposed lifestyle and environmental goals for good sleep [5]. However, the 2021 Health Survey by the Japanese Ministry* Corresponding author. 6-15-1 Torimachi, Yonezawa, Yamagata, 992-0025, Japan.
E-mail address: m-suzuki@yone.ac.jp (M. Suzuki).
https://doi.org/10.1016/j.heliyon.2024.e28228
Received 27 September 2023; Received in revised form 9 March 2024; Accepted 13 March 2024
Available online 15 March 2024
2405-8440/© 2024 The Authors.
Published by Elsevier Ltd.
This is an open access article under the CC BY license(http://creativecommons.org/licenses/by/4.0/).

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M. Suzuki et al.

of Health, Labor and Welfare showed that sleep problems were prevalent, such as waking up during sleep (44.6%), feeling sleepy
during the daytime (37.2%), and dissatisfaction with the overall quality of sleep (34.7%), indicating that ensuring an adequate
quantity and quality of sleep is an urgent issue in Japan [6].
Sleep is influenced by various factors, including pain, anxiety, nocturia [7], well-being [8], bedtime, and food intake [9]. Factors
associated with sleep may vary by region and culture. In Japan, the previous studies reported the association between sleep status andvarious factors, including physical factors (diet quality [10], older age, lack of exercise [11]), psychological factors (psychologicalstress, perceived health [11], anxiety/depression [12], mental health problems [13], subjective happiness [14], health-related qualityof life [15]), and environmental factors (unemployment [11,13], less years of schooling for women [13], household expenditure [14]).
However, these reports mostly examined associations with one or two of the three different factor groups (physical, psychological, andenvironmental) or small numbers of factors. Since all three factor groups are related to sleep status, it is necessary to include thesebroad factor groups simultaneously to clarify the factors associated with sleep. In addition, although sleep status varies by age andgender, the analysis for these subgroups has not been adequately examined.
In this study, we examined the independent associations between sleep and a wide range of factors consisting of three different
factor groups, both in the overall population and in subgroups by gender and age using data from the Yamagata Cohort Study, whichcontained information on sleep status and various background factors.
2. Methods
2.1. Study participants and survey procedures
The Yamagata Cohort Study is a prospective study supported by the 21st Century COE Program and the Global COE Program andwas conducted in seven cities in Yamagata Prefecture (Yamagata, Sakata, Kaminoyama, Sagae, Higashine, Tendo, and Yonezawa). The
study participants were a community-based population covered by the National Health Insurance system and comprising workers in
the agriculture, forestry, and fishery industries who were self-employed, part-time employed, retired, and unemployed. There were
20,969 study participants at baseline (2009–2015) in this study. After excluding 3,442 subjects who had died or moved away by
December 2021, Health and lifestyle questionnaires were mailed to the remaining 17,527 participants from December 2021 to March
2022. The completed questionnaires were returned by 12,216 participants (69.7% response rate). After excluding 4,343 participants
with missing information on sleep status and background factors, we analyzed the questionnaires of 7,873 participants (3,304 men,
4,569 women) with valid sleep status responses.
2.2. Study items
A wide range of information was collected on personal characteristics, including physical factors (age, sex, body mass index [BMI],
pain/discomfort, and nocturnal urination frequency), psychological factors (anxiety and happiness), and living conditions (daily
walking time, time between bathing time and bedtime, bedroom lighting, time spent using smartphones and other devices, and living
status on their current income) that may be related to sleep.
There are two questions to assess physical factors. Q1 ″Do you have pain/discomfort?" with answers to the five options (no pain/
discomfort, some, moderate, considerable, extreme). Considering the bias in the number of responses, the answer "no pain/discomfort"
was classified as "No" and the rest as "Yes". Q2 ″ How many times during the night did you get up to urinate?" with the answers to thefour options (0 times, 1 time, 2 times, 3 times).
There are two questions to assess psychological factors. Q3 ″Do you feel anxious?" with the answers to the five options (not anxious,
a little, moderately, considerably, extreme). Q4 ″How happy do you feel?" with the answers to five options (very happy, fairly happy,
neutral, not very happy, not happy). Considering the bias in the number of responses, the answers "not anxious" to Q3 were classified as"No" and the rest as "Yes. For Q4, "very happy," and "fairly happy," were classified as “Yes”, and the rest as “No”.
There are five questions to assess environmental factors. Q5 “How many minutes do you walk in a day?” We categorized thewalking time into four groups (<30 min, <1 hour, <2 hours, ≥2 hours). Q6 “How is life with your current income?” with the answers
to the five options (very comfortable, somewhat comfortable, neutral, somewhat difficult, very difficult). Q7 “How long is the timefrom bathing and bedtime (min)?” with the answers to the five options (<60 min, 60–89 min, 90–119 min, 120–149 min, ≥150 min).
Considering the bias in the number of responses, we categorized the obtained five-level responses into three groups (<60 min, 60–119
min, ≥120 min). Q8 “How is the bedroom lit while you sleep?” with the answers to the four options (no lighting, slightly lighting,lighting, others [free comments]). Q9 “How many hours per day do you spend on your smartphone, computers, and tablets combined?”with the answers to the five options (no use, <1 hour, 1–2 hours, 3–4 hours, ≥4 hours).
To examine the presence of insomnia symptoms among community residents, we used the Athens Insomnia Scale (AIS), a widelyused self-report measure on the International Classification of Diseases, Tenth Edition (ICD-10). The AIS questions included eightitems: time to fall asleep, mid-afternoon awakenings, early morning awakenings, sleep duration, sleep quality, daytime mood, physicaland mental activities during the day, and daytime sleepiness [16]. Scores range from 0 to 24, and a score of 6 or higher is consideredinsomnia [17]. A recent reliability generalizability meta-analysis, including studies in Japanese subjects, have shown that the AIS has
excellent internal consistency and retest reliability [18]. The Japanese version of the AIS has also been reported to have adequate
validity and diagnostic utility [19]. In a study examining the validity of the Japanese version of the AIS for pathological insomnia inJapanese, the cutoff value was 5.5 points [19]. Based on this report, a score of 6 or higher was considered as having insomnia
symptoms in the present study.
2

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2.3. Statistical analysis
Student’s t-test and chi-square test were used to examine the differences in continuous and categorical variables between those withand without insomnia symptoms. Simple and multiple logistic regression analyses were performed to identify factors independently
associated with insomnia symptoms. The software JMP Pro16 for Windows were used for these analyses. The fitness of the multivariate
regression analysis was checked using the Hosmer-Lemeshow goodness of fit test by R-based free software EZR version 2.8.0 (Jichi
Medical School, Saitama, Japan) [20]. Statistical significance was set at p < 0.05.
3. Results
3.1. Characteristics of study subjects
The characteristics of the study participants are listed in Table 1. There were 7,873 participants (3,304 men [42.0%] and 4569
women [58.0%]) with an average age of 71.7 years. The prevalence of insomnia symptoms was 23.4% in the overall population (21.9%
in men and 24.5% in women). Compared to those without insomnia symptoms, the participants with insomnia symptoms showed ahigher proportion of women; those experiencing difficult conditions on current income, pain/discomfort, anxiety, and frequent
nocturia; those with longer time from bathing time to bedtime; and, those with bedroom lighting, and a lower prevalence of the feelingof happiness, lower BMI, and lower daily walking time. No significant differences were found in age or time spent using smartphones orother devices.

Table 1Comparison of basic attributes and factors related to insomnia symptoms.
Variables
Number (%)
Sex
Age

BMI(kg/m2)

Living situation on current income

Pain/discomfort
Anxiety
Feeling happiness
Nocturnal urination frequency

Time from bathing to bedtime (min)Bedroom lighting

Time spent using smartphones, computers, and tablets

Hours walked in a day

Male
Female
40–59
60–69
70–79
80–89
<18.5
18.5–24.9
25–29.9≥30
Very comfortable
Somewhat comfortable
NeutralSomewhat difficult
Very difficult
Yes
No
Yes
No
Yes
No
0 times
1 time2 times
3 times<60
60–119≥120
No lighting
Slightly Lighting
Lighting
OthersNo use
<1 h
1–2 h
3–4 h
≥4 h
<30 min
<1 h
<2 h
≥2 h

3

Total

AIS < 6 points

AIS ≥6 points

7873 (100%)
3304 (42.0%)4569 (58.0%)756 (9.6%)
1739 (22.1%)
4159 (52.8%)
1222 (15.5%)517 (6.6%)
5466 (69.4%)
1702 (21.6%)
188 (2.4%)
108 (1.4%)
754 (9.6%)4647 (59.0%)
1905 (24.2%)
459 (5.8%)
4631 (58.8%)3242 (41.2%)
2296 (29.2%)
5577 (70.8%)6771 (86.0%)1102 (14.0%)1640 (20.8%)3276 (41.6%)2061 (26.2%)
896 (11.4%)2253 (28.6%)3495 (44.4%)2125 (27.0%)4696 (59.7%)2511 (31.9%)288 (3.7%)
378 (4.8%)
1932 (24.6%)
3608 (45.8%)1530 (19.4%)
534 (6.8%)
269 (3.4%)
1997 (25.4%)2858 (36.3%)
2054 (26.1%)
964 (12.2%)6029 (76.6%)
2580 (42.8%)3449 (57.2%)
568 (9.4%)1330 (22.1%)
3194 (53.0%)
937 (15.5%)371 (6.2%)
4181 (69.3%)
1332 (22.1%)
145 (2.4%)
91 (1.5%)609 (10.1%)
3713 (61.6%)
1339 (22.2%)
277 (4.6%)
3223 (53.5%)2806 (46.5%)
1284 (21.3%)4745 (78.7%)5435 (90.2%)594 (9.8%)1402 (23.3%)2605 (43.2%)
1465 (24.3%)
557 (9.2%)
1825 (30.3%)2649 (43.9%)1555 (25.8%)3645 (60.4%)
1902 (31.6%)
198 (3.3%)
284 (4.7%)
1452 (24.1%)
2803 (46.5%)
1164 (19.4%)
402 (6.6%)
208 (3.4%)
550 (29.8%)686 (37.2%)
417 (22.6%)
191 (10.4%)

1844 (23.4%)
724 (39.3%)1120 (60.7%)
188 (10.2%)
409 (22.2%)
962 (52.1%)
285 (15.5%)
146 (7.9%)1285 (69.7%)
370 (20.1%)
43 (2.3%)
17 (0.9%)145 (7.9%)
934 (50.7%)566 (30.7%)
182 (9.9%)1408 (76.4%)
436 (23.6%)
1012 (54.9%)
832 (45.1%)
1336 (72.4%)508 (27.6%)
238 (12.9%)
671 (36.4%)
596 (32.3%)
339 (18.4%)
428 (23.2%)
846 (45.9%)
570 (30.9%)1051 (57.0%)
609 (33.0%)
90 (4.9%)
94 (5.1%)
480 (26.0%)805 (43.7%)
366 (19.8%)
132 (7.2%)
61 (3.3%)
1447 (24.0%)2172 (36.0%)
1637 (27.2%)
773 (12.8%)

P-Value
0.008
0.784

0.024

<0.001<0.001<0.001<0.001<0.001<0.001

0.003

0.243

<0.001

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3.2. Factors associated with insomnia symptoms
Logistic regression analysis was performed to identify the factors associated with insomnia symptoms. In the simple analysis, thefactors associated with insomnia symptoms were female sex, BMI <18.5, experiencing difficulty in living on current income, pain/
discomfort, anxiety, lack of happiness, frequent nocturia, long time from bathing to bedtime, and short walking time (Table 2). The
multivariate logistic regression analysis showed that the factors independently associated with insomnia symptoms were age in the 80s(odds ratio [OR] 0.75, 95% confidence interval [Cl] 0.58–0.97, vs. 40–59 years), belonging to the female sex (OR 1.32, 95%Cl
1.16–1.50, vs. males), experiencing difficulty in living on current income (OR 1.63, 95%Cl 1.30–2.05, vs. neutral), having pain/
discomfort (OR 1.90, 95%Cl 1.66–2.16) and anxiety (OR 3.21, 95%Cl 2.84–3.62), not feeling happiness (OR 2.03, 95%Cl 1.74–2.36),
three times nocturia (OR 4.71, 95%Cl 3.73–5.94, vs. none), ≥120 min from bathing time to bedtime (OR 1.62, 95%Cl 1.39–1.90, vs.
60 min or less), bedroom lighting (OR 1.36, 95%Cl 1.02–1.81, vs. no lighting), ≥2 h daily walking (OR 0.70, 95% Cl 0.57–0.86, vs. <30 min) (Table 2). The Hosmer-Lemeshow goodness of fit test showed that the fitness of this model was acceptable (P = 0.09 > 0.05).
Subgroup analyses were conducted according to patient sex and age. By sex, factors associated only in women were BMI 25–29.9(OR 0.79, 95%CI 0.64–0.96), BMI ≥30 (OR 0.51, 95%CI 0.31–0.84) (vs. BMI 18.5–24.9), bedroom lighting (OR 1.81, 95%CI
1.25–2.63, vs. no lighting), and 1–2 h use of smartphone/computer/tablet (OR 1.34, 95%CI 1.05–1.71, vs. no use). The factor asso­
ciated with insomnia symptoms only in men was ≥2 h of daily walking (OR 0.63, 95% Cl 0.45–0.88, <30 min) (Supplementary file 1).
By age, factors associated only in those aged 65 years and older were 1–2 h from bathing to bedtime (OR 1.42, 95%CI 1.21–1.65, vs.
<60 min); 1–2 h of daily walking time (OR 0.81, 95%CI 0.68–0.97); and, ≥2 h (OR 0.65, 95%CI 0.51–0.82, vs. <30 min). No associatedfactors were found in the patients aged <65 years (Supplementary file 2).

Table 2
Factors associated with insomnia symptoms.
Variables

Univariate analysis
Odd radio (95%CI)

Age

Sex
BMI(kg/m2)

Living situation on current income

Pain/discomfort
Anxiety
Feeling happiness
Nocturnal urination frequency

Time from bathing to bedtime (min)Bedroom lighting

Time spent using smartphones, computers, and tablets

Hours walked in a day

40–59
60–69
70–79
80–89
Male
Female<18.5
18.5–24.9
25–29.9≥30
Very comfortable
Somewhat comfortable
NeutralSomewhat difficult
Very difficult
Yes
No
Yes
No
Yes
No
0 times
1 time2 times
3 times<60
60–119≧120
No lighting
Slightly Lighting
Lighting
OthersNo use
<1 h
1–2 h
3–4 h
≥4 h
<30 min
<1 h
<2 h
≥2 h

4

1.00
0.93 (0.76–1.13)
0.91 (0.76–1.09)
0.92 (0.74–1.14)
1.00
1.16 (1.04–1.29)
1.28 (1.05–1.57)
1.00
0.90 (0.79–1.03)
0.96 (0.68–1.36)
0.74 (0.44–1.25)
0.95 (0.78–1.15)
1.00
1.68 (1.49–1.90)
2.61 (2.14–3.19)
1.00
2.81 (2.50–3.17)
1.00
4.49 (4.02–5.02)
1.00
3.35 (3.05–3.97)
1.00
1.52 (1.29–1.78)
2.40 (2.03–2.83)
3.59 (2.96–4.35)
1.00
1.36 (1.19–1.55)
1.56 (1.36–1.80)
1.00
1.11 (0.99–1.24)
1.57 (1.22–2.04)
1.15 (0.90–1.46)
1.00
0.87 (0.76–0.99)
0.95 (0.81–1.11)
0.99 (0.80–1.24)
0.89 (0.65–1.20)
1.00
0.83 (0.73–0.95)
0.67 (0.58–0.78)
0.65 (0.54–0.78)

Multivariate Analysis
P-Value
0.468
0.304
0.434
0.007
0.016
0.130
0.840
0.265
0.580
<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001
0.072<0.001
0.266
0.033
0.530
0.953
0.439
0.005
<0.001<0.002

Odd radio (95%CI)
1.00
1.05 (0.84–1.31)
0.97 (0.78–1.21)
0.75 (0.58–0.97)
1.00
1.32 (1.16–1.50)
1.15 (0.92–1.43)
1.00
0.84 (0.73–0.98)
0.69 (0.47–1.00)
1.02 (0.59–1.77)
1.04 (0.84–1.28)
1.00
1.29 (1.12–1.48)
1.63 (1.30–2.05)
1.00
1.90 (1.66–2.16)
1.00
3.21 (2.84–3.62)
1.00
2.03 (1.74–2.36)
1.00
1.69 (1.41–2.02)
2.84 (2.33–3.45)
4.71 (3.73–5.94)
1.00
1.39 (1.20–1.60)
1.62 (1.39–1.90)
1.00
1.01 (0.89–1.15)
1.36 (1.02–1.81)
0.99 (0.76–1.29)
1.00
0.97 (0.84–1.12)
1.12 (0.93–1.34)
1.11 (0.86–1.43)
0.94 (0.66–1.33)
1.00
0.96 (0.83–1.11)
0.82 (0.70–0.96)
0.70 (0.57–0.86)

P-Value
0.696
0.800
0.031
<0.001
0.230
0.026
0.052
0.947
0.725
<0.000<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001
0.861
0.035
0.928
0.674
0.221
0.437
0.716
0.616
0.015
0.001

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4. Discussion
This study showed that insomnia symptoms was common (23.4%) in a Japanese community-based population, and three different
factor groups, including physical (age, sex, BMI, pain/discomfort, frequent nocturia), psychological (anxiety, feeling happy), andenvironmental (living situation on current income, time from bathing time to bedtime, bedroom lighting, daily walking time) factors,
were independently associated with insomnia symptoms. Furthermore, factors associated with insomnia symptoms varied according tosex and age.
4.1. Physical factors
The prevalence of insomnia symptoms was 10.0%–40.0% in previous studies [13,17,21], and it was higher, particularly in older
people [22,23], women [24], obese subjects (BMI ≥30.0) [25], and those with pain and nocturia [7]. In the present study, theprevalence of insomnia symptoms was similar (23.4%) to that in other populations. Belonging to the female sex and having pain/­discomfort and frequent nocturia were insomnia symptoms -related factors, which is in line with previous findings. Even a single
nocturia episode was significantly associated with insomnia symptoms, and the more frequent the nocturia episodes, the higher therisk of insomnia symptoms. However, in contrast to previous findings, insomnia symptoms were less prevalent in the older populationand in those with a high BMI, especially in women in the present study. Although the reason for this difference is unclear, insomnia
symptoms may be associated with emaciation rather than obesity in this population.
4.2. Psychological factors
A previous study by Dragioti et al. showed that anxiety is strongly associated with insomnia symptoms in older adults [23]. Zhao
et al. found that a decreased sense of well-being in older adults and women was associated with insomnia symptoms [8], and Otsuka
et al. noted that subjective well-being in adolescence was strongly associated with the prevalence of sleep disorders [26]. Similarly, inthe present study, 54.9% of patients with insomnia symptoms had anxiety, which was independently associated with insomnia
symptoms, regardless of sex or age. Additionally, this study showed that happiness was independently associated with a decrease in
insomnia symptoms. These results suggest that both positive and negative psychological factors are independently associated withinsomnia symptoms.
Previous studies have reported that the majority of depressed subjects have insomnia and that depression and anxiety often co-exist[27–29]. Although this study could not assess depression due to the lack of questions on depression, depression is likely to co-occur
with anxiety and may be related to sleep status.
4.3. Environmental factors
Regarding the association between income and insomnia symptoms, Lallukka et al. noted that a low socioeconomic status andhousehold income were associated with insomnia [30]. The current study revealed that a difficult living condition in relation to current
income was independently associated with insomnia symptoms. However, the group with comfortable living condition on current
income did not show a significant decrease in the odds ratio for insomnia symptoms, suggesting that a worse living situation isassociated with insomnia symptoms but an economically comfortable situation may not reduce insomnia symptoms.
Interestingly, the current study showed that the odds ratio of insomnia symptoms increased in subjects with a long time gap frombathing time to bedtime, especially in older people. Kalmbach et al. noted that exposure to stress interferes with sleep [31] and Harvey
et al. noted that those with insomnia were more likely to worry about various things before bedtime [32], indicating that sleep isinfluenced by psychological factors [33]. Based on these findings, it may be recommended to avoid a long gap from bathing time to bed
time to avoid factors that interfere with falling asleep easily.
Furthermore, the current study showed that the risk of insomnia symptoms was higher among those who slept in well-lit bedrooms
than among those who slept in bedrooms with none or small night lights. Matsumoto et al. reported that lighting, rather than tem­
perature or humidity, is the most relevant factor for insomnia [34] and Zeitzer et al. reported that melatonin production could be
suppressed by normal room light [35]. It is reported that disruption of the sleep–wake rhythm can lead to insomnia [36]. Taken
together, lighting conditions appear to be an important factor in the prevention of insomnia symptoms. Concerning the exercise, Chenet al. reported that walking improved sleep efficiency in older women with mild sleep disorders [37]. The current study also showedthat insomnia symptoms were infrequent in the group that walked ≥2 h daily.
The subgroup analyses revealed that the factors associated with insomnia symptoms varied according to sex and age: BMI, bedroom
lighting, smartphone use time for women, walking time for men, time between bathing and bedtime, and walking time for older
people. This finding suggests that the advice for good sleep should be tailored to individual conditions rather than uniformity.
Combining previous reports and the results of the present study, it seems that not only drugs but also cognitive-behavioral therapy(CBT) from psychological and social environments may be effective intervention methods since these factors are related to sleep.
Recently, CBT with telemedicine has been reported to be as effective as face-to-face intervention [38] and is expected to be an effective
intervention method in the future.
5

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4.4. Strengths and limitations of this study
The strength of this study is the robustness of the results owing to the large sample size that enables a more detailed analysis that
includes various types of factors simultaneously and sub-grouped by age and gender. Consequently, this study simultaneously
examined a wide range of insomnia symptoms-related factors individually reported in the literature. However, this study had several
limitations. First, the study subjects were community-based health examination participants. In addition, the moderate response rate
(69.7%) and the exclusion of those with missing data may have led to a possible selection bias, as relatively healthy individuals were
included in the analysis. Secondly, sleep status is subjective and may differ from objective measurements. Third, because this was across-sectional study, it was not possible to determine the causal relationship. Fourth, the present study lacked information on thehistory of sleep-related illnesses and use of sleep-inducing medications.
5. Conclusions
This questionnaire-based study showed that insomnia symptoms is common in the Japanese community-based population, andthree different factor groups are independently associated with insomnia symptoms. These results suggest that factors associated withinsomnia symptoms may vary depending on each person’s characteristics and situation and that measures tailored to the individual’s
condition might be required to improve insomnia symptoms.
Ethics statement
The questionnaire package contained an overview of the study, including information on the voluntary nature of participation andprotection of personal information. Written informed consent was obtained from all the participants. This study was conducted inaccordance with the Declaration of Helsinki and approved by the Ethics Committee of Yamagata University School of Medicine (20091222, 2022-263).
Funding
The Yamagata Cohort Study is supported by the 21st Century COE Program and Global COE Program.
Data availability
The dataset of the current study was not publicly available for ethical reasons. However, it can be accessed by contacting thecorresponding author upon reasonable request.
Prior presentations
None.
CRediT authorship contribution statement
Miho Suzuki: Writing – original draft. Natsuko Suzuki: Writing – review & editing. Kaori Sakurada: Writing – review & editing.
Norihiko Tsuchiya: Writing – review & editing. Yoshiyuki Ueno: Writing – review & editing. Tsuneo Konta: Writing – review &editing.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared toinfluence the work reported in this paper.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.heliyon.2024.e28228.

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