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. 2020 Jan 9;15(1):e0227190. doi: 10.1371/journal.pone.0227190

Gender differences influence over insomnia in Korean population: A cross-sectional study

Yun Kyung La 1, Yun Ho Choi 2, Min Kyung Chu 3, Jung Mo Nam 4, Young-Chul Choi 1, Won-Joo Kim 1,*
Editor: Masaki Mogi5
PMCID: PMC6952093  PMID: 31917784

Abstract

Study objectives

Insomnia is the most common sleep disorder with significant psychiatric/physical comorbidities in the general population. The aim of this study is to investigate whether socioeconomic and demographic factors are associated with gender differences in insomnia and subtypes in Korean population.

Method

The present study used data from the nationwide, cross-sectional study on sleep among all Koreans aged 19 to 69 years. The Insomnia Severity Index (ISI) was used to classify insomnia symptoms and their subtypes (cutoff value: 9.5). The Pittsburgh Sleep Quality Index (PSQI), Goldberg Anxiety Scale (GAS) and Patient Health Questionnaire-9 (PHQ-9) were used to measure sleep quality, anxiety and depression.

Results

A total of 2695 participants completed the survey. The overall prevalence of insomnia symptoms was 10.7%, including difficulty in initiating sleep (DIS) (6.8%), difficulty in maintaining sleep (DMS) (6.5%) and early morning awakening (EMA) (6.5%), and these symptoms were more prevalent in women than in men. Multivariate analysis showed that female gender, shorter sleep time and psychiatric complications were found to be independent predictors for insomnia symptoms and subtypes. After adjusting for covariates among these factors, female gender remained a significant risk factor for insomnia symptoms and their subtypes. As for men, low income was related to insomnia.

Conclusion

Approximately one-tenth of the sample from the Korean general population had insomnia symptoms. The prevalence of insomnia symptom and the subtypes were more prevalent in women than men. Gender is an independent factor for insomnia symptoms.

Introduction

Insomnia is the most common sleep disorder in the general population. It is associated with impaired social performance, cultural difference and daytime functioning, along with other psychological/physical conditions [1–3]. Insomnia affects 6–18% of the general population [4–7]. Therefore, insomnia imposes a significant personal and social burden [8]. Insomnia prevalence varies according to the definition of insomnia or insomnia symptom [9].

Different insomnia symptoms have been defined as subtypes of insomnia. These subtypes include difficulty in initiating sleep (DIS), difficulty in maintaining sleep (DMS) and early morning awakening (EMA) [9]. There are differences in the prevalence, association with excessive daytime sleepiness and psychiatric comorbidities among these subtypes [10].

Gender, age, socioeconomic status and psychiatric comorbidities are known to be significant factors for insomnia prevalence [9]. The elderly population has an increased insomnia prevalence compared to the young or middle age population in almost all epidemiological studies [11–13]. Insomnia prevalence is stable from 15 to 44 years of age and increases over 45 years [9]. Insomnia prevalence is typically higher among individuals with lower incomes and lower education levels [14]. However, some studies have reported contradictory results [15, 16]. The association between insomnia and psychiatric disorders has been repeatedly demonstrated. Approximately 90% and 80% of individuals with anxiety and depression had insomnia symptoms in cross-sectional studies, respectively [17, 18]. Longitudinal studies confirmed the close association of anxiety and depression with insomnia [16, 19].

Short sleep time and poor sleep quality are significant factors for insomnia. A survey in six European countries showed that a significant proportion of individuals with insomnia had short sleep times either voluntarily or non-voluntarily [20]. The authors classified sleep deprivation as a subtype of insomnia. Poor sleep quality is also common among individuals with insomnia [21].

Female gender has been recognized as a significant factor for insomnia. Epidemiological studies have consistently shown a higher prevalence of insomnia symptoms among women compared to men [22–24]. The difference in insomnia prevalence between women and men increases with age [9]. In addition to insomnia or insomnia symptoms, women report more frequent dissatisfaction with sleep and the daytime consequences of insomnia [4, 22, 24].

Nevertheless, information regarding gender differences in insomnia subtypes is currently limited. In addition, gender differences in insomnia symptoms adjusting for significant covariates have rarely been reported. The purpose of this study is to investigate gender differences in insomnia symptoms and their subtypes regarding covariates using population data in South Korea.

Methods

Study population and survey process

The present study population was collected from cross-sectional surveys. In brief, it was a nationwide, cross-sectional study on sleep among Koreans aged 19 to 69 years. We used a two-stage clustered random sampling method proportional to the population and socioeconomic distribution for all Korean territories. The study protocol was approved by the institutional review board/ethics committee of Hallym University Sacred Heart Hospital in Korea(Approval No. 2011-I077), conducted according to the principles expressed in the Declaration of Helsinki.; Participants provided their written informed consent to participate in this study. Trained interviewers conducted structured interviews using a questionnaire to assess sleep time, sleepiness, anxiety and depression using a face-to-face interview. The interview included questions on sleep status. To minimize potential interest bias, we informed candidates that the topic of the survey was social health issues rather than sleep issues. All interviewers were employed by Gallup Korea and had previous social survey interviewing experience.

Assessment for sleep time

We asked all participants to report their usual sleep time in terms of hours and minutes, separately for workdays and free days, during the past month. The average sleep time was a weighted mean of the sleep time on workdays and free days, calculated as ([workday sleep time x 5] + [free day sleep time x 2))/7. Short sleep time was defined as an average sleep time of <6 h [25].

Assessment for insomnia symptom and poor sleep quality

The Insomnia Severity Index (ISI) was used to classify insomnia symptoms. The ISI is a self-reporting, brief screening measure of insomnia that contains questions corresponding in part to the diagnostic criteria of insomnia [26]. The ISI comprises seven items concerning the severity of sleep-onset difficulty, sleep-maintaining difficulty, early awakening and satisfaction with sleep patterns. Each item was rated on a 0–4 scale [27]. The ISI was previously validated with good sensitivity and specificity and showed a 9.5 cut-off score for discriminating patients with “insomnia symptoms” in the population-based sample [28]. Among those who satisfy this definition (ISI score ≥ 10), we further classified the subtypes of insomnia symptoms as difficulty in initiating sleep (DIS), difficulty in maintaining sleep (DMS) and early morning awakening (EMA) if a participant responded with ≥ 2 on the scale (intermediate or higher) for those items [20]. The Pittsburgh Sleep Quality Index (PSQI) was used to measure sleep quality. If a participant’s PSQI score was 6 or higher, she/he was classified as having poor sleep quality [29].

Anxiety and depression assessment

We used the Goldberg Anxiety Scale (GAS) to diagnose anxiety among participants. The GAS questionnaire was composed of nine items: four screening items and five supplementary items. Anxiety was diagnosed when there were positive answers to two or more screening items and five or more of all scale items [30]. The Korean version of the scale has a sensitivity of 82.0% and specificity of 94.4% for diagnosing anxiety [31].

The Patient Health Questionnaire-9 (PHQ-9) was used to diagnose depression [32]. It is composed of nine items each scored 0 to 3. Participants who scored 10 or higher on this measure were considered to have depression. The Korean PHQ-9 has a sensitivity of 81.8% and specificity of 89.9% [33].

Statistical analysis

The Kolmogorov–Smirnov test was used to confirm the normality of the distribution. The Student’s t-test was used to compare continuous variables after the normality of the sample was confirmed. Post hoc analyses were performed using Tukey’s method. Categorical variables were compared using the Chi-square test. The significance level was set at p < 0.05 for all analyses.

We calculated the odds ratios (ORs) with 95% confidence intervals (CIs) for the occurrence of insomnia symptoms and their subtypes through univariable and multivariable logistic regression analyses. In univariable analyses, we modelled the ORs for insomnia symptoms without adjusting for covariates. In multivariable analyses, we used four models. In Model 1, adjustment was conducted for sociodemographic variables (age, gender, size of residential area and educational level) and short sleep time. Model 2 incorporated anxiety (GAS score) with Model 1. Model 3 included depression (PHQ-9 score ≥ 10) with Model 1. The final model, Model 4, incorporated poor sleep quality (PSQI score ≥ 6), anxiety and depression with Model 1. Statistical analyses were performed using the Statistical Package for Social Sciences 23.0 (IBM, Armonk, NY, USA).

Results

Survey

The interviewers approached 7,430 individuals and 3114 of them agreed to take the survey. After 352 individuals suspended the interview, 2695 participants completed the survey (cooperation rate of 36.2%; Fig 1). The distributions of age, gender, size of residential area and educational level were not significantly different from those of the general population of Korea. (Table 1).

Fig 1. Flow chart depicting the participation of subjects in the Korean headache-sleep study.

Fig 1

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Table 1. Sociodemographic characteristics of survey participants; the total Korean population; and cases identified as having insomnia.

Survey participants N (%) Total population N (%) P Poor sleep quality N, % (95% CI) p Insomnia N, % (95% CI) p Short sleep time p Average sleep time (hours + SD) P
Sex
Men 1,345 (49.3) 17,584,365 (50.6) 0.854a 334, 24.8 (22.5–27.1) 0.046 117, 8.7 (7.2–10.2) 0.001 141, 10.5 (8.8–12.1) 0.727 7.3 + 1.2 0.109
Women 1,350 (50.7) 17,198,350 (49.4) 381, 28.2 (25.8–30.6) 173, 12.8 (11.0–14.6) 136, 10.1 (8.5–11.7) 7.3 + 1.2
Age
19–29 542 (20.5) 7,717,947 (22.2) 0.917a 153, 28.3 (24.4–32.0) 0.028 59, 10.9 (9.2–12.6) 0.426 45, 8.3 (6.0–10.6) 0.002 7.6 + 1.3 <0.001
30–39 604 (21.9) 8,349,487 (24.0) 136, 22.5 (19.2–25.9) 53, 8.8 (7.3–10.3) 42, 7.0 (4.9–9.0) 7.5 + 1.1
40–49 611 (23.1) 8,613,110 (24.8) 167, 27.3 (23.8–30.1) 66, 10.8 (9.1–12.5) 73, 11.9 (9.4–14.5) 7.1 + 1.2
50–59 529 (18.9) 6,167,505 (17.7) 160, 30.2 (26.3–34.2) 63, 11.9 (10.2–13.6) 70, 13.2 (10.3–16.1) 7.1 + 1.3
60–69 409 (15.6) 3,934,666 (11.3) 99, 24.2 (20.0–28.4) 49, 12.0 (10.2–13.7) 47, 11.5 (8.4–14.6) 7.1 + 1.2
Size of residential area
Large city 1,248 (46.3) 16,776,771 (48.2) 0.921a 338, 27.1 (24.6–30.0) 0.541 136, 10.9 (9.2–12.6) 0.945 131, 10.5 (8.8–12.2) 0.670 7.3 + 1.2 0.471
Medium-to-small city 1186 (44.0) 15,164,345 (43.6) 303, 25.5 (23.1–28.0) 125, 10.5 (8.9–12.2) 116, 9.8 (8.1–11.5) 7.3 + 1.2
Rural area 261 (9.7) 2,841,599 (8.2) 74, 28.4 (22.8–33.9) 29, 11.1 (9.4–12.8) 30, 11.5 (7.6–15.4) 7.3 + 1.3
Education
Middle school or Less 393 (14.9) 6,608,716 (19.0) 0.752a 110, 28.0 (23.5–32.4) 0.917 62, 15.8 (13.8–17.7) 0.006 47, 12.0 (8.7–15.2) 0.514 7.2 + 1.4 0.012
High school 1,208 (44.5) 15,234,829 (43.8) 317, 26.2 (24.0–28.7) 116, 9.6 (8.0–11.2) 127, 10.5 (8.8–12.3) 7.2 + 1.3
College or more 1,068 (39.6) 12,939,170 (37.2) 281, 26.3 (23.7–29.0) 109, 10.2 (8.6–11.8) 100, 9.4 (7.6–11.1) 7.4 + 1.3
Not responded 26 (9.6) 7, 26.9 (8.7–45.2) 3, 1.0 (0.9–1.3) 3, 11.5 (0.0–24.7) 7.4 +1.2
Total 2695 (100.0) 34,782,715 (100.0) 715, 26.5 (24.8–28.2) 290, 10.7 (9.1–12.4) 277, 10.3 (9.1–11.4) 7.4 + 1.3
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aComparison of gender, age group, size of residential area, and educational level distributions between the sample in the present study and the total population of Korea

Abbreviations: CI = confidence interval

Prevalence of insomnia and poor sleep quality

Of the 2695 participants, 290 (10.7%) were classified as having insomnia symptoms according to the ISI score. Seven-hundred and fifteen (26.5%) participants who reported PSQI scores higher than 5 were classified as having poor sleep quality. 182 (6.8% of all participants) were accompanied by DIS, 175 (6.5%) with DMS and 176 (6.5%) with EMA (Fig 2).

Fig 2. Prevalence of insomnia symptoms in men and women with different age groups.

Fig 2

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p was calculated by χ2 test. Abbreviations: IS = Insomnia Symptoms, DIS = Difficulty in Initiating Sleep; DMS = Difficulty in Maintaining Sleep; EMA = Early Morning Awakening.

Demographic characteristics, psychiatric comorbidities and short sleep time according to the presence of insomnia symptom

The mean age of participants with insomnia symptoms did not significantly differ from participants without insomnia symptoms (43.8 ± 14.2 vs. 42.9 ± 13.7, p = 0.823). The proportion of women was higher among participants with insomnia symptoms than those without insomnia symptoms (59.6% vs. 49.1%, p < 0.001). The prevalence of anxiety and depression was significantly higher among participants with insomnia symptoms than in those without (40.3% vs. 6.3%, p < 0.001 for anxiety and 25.9% vs. 1.7%, p < 0.001 for depression). The average sleep time of all participants was 7.4 ± 1.3 h.

Two-hundred and seventy-seven (10.3%) participants were classified as having short sleep time. The average sleep time of participants with insomnia symptoms was significantly shorter than that of participants without insomnia symptoms (6.7 ± 1.5 h vs. 7.4 ± 1.2 h, p < 0.001). The prevalence of short sleep time (< 6 hours of average sleep time) was higher among participants with insomnia symptoms (35.5% vs. 15.2%, p < 0.001; Table 2).

Table 2. Distribution of demographic, social and lifestyle factors according to the presence of insomnia symptoms.

Subjects with IS N = 290 Subjects without IS N = 2405 P-value
Demographics
 Mean age ± SD (years) 43.76±14.20 42.88±13.70 0.366
 Women, N (%) 173 (59.6) 1182 (49.1) 0.001
Education level
 Middle school or less 62 331 0.006
 High school 116 1092
 College or more 109 959
 Not responded 3 23
Residential area
 Large city 136 1112 0.943
 Medium-to-small city 125 1061
 Rural area 29 232
Smoking, N (%) 78 (26.9) 666 (27.7) 0.486
Alcohol, N (%) 185 (63.8) 1597 (66.4) 0.313
ISI score, ± SD 14.37±4.39 2.47±2.50
Anxiety, N (%) 117 (40.3) 151 (6.3) <0.001
Depression, N (%) 75 (25.9) 41 (1.7) <0.001
BMI, ± SD (kg/cm^2) 23.09± 3.30 22.94± 2.97 0.031
Average sleep duration, ± SD, N (short sleep duration) 6.68± 1.54 (103) 7.36± 1.17 (366) <0.001
Poor sleep quality, N (%) 221 (76) 494 (20.5) <0.001
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p was calculated by χ2 test or student’s t test.

Abbreviations: IS–Insomnia symptoms

Prevalence of insomnia symptoms in women and men

A higher percentage of women reported insomnia symptoms compared to men (12.8% vs. 8.7%, p = 0.001). The mean ISI score was significantly higher in women compared to men (4.2 ± 4.9 vs. 3.3 ± 4.2, p < 0.001). All subtypes of insomnia symptoms including DIS (8.3% vs. 5.1%, p < 0.001), DMS (8.5% vs. 4.4%, p < 0.001) and EMA (8.0% vs. 5.0%, p = 0.001) were more prevalent in women than men (Fig 2).

Insomnia severity of women and men among participants with insomnia

Among 290 participants with insomnia symptoms, the total ISI score was not significantly different between women and men (14.6 ± 4.4 vs. 14.0 ± 4.3, p = 0.199). The prevalence of DIS (37.6% vs. 33.3%, p = 0.460), DMS (40.5% vs. 32.5%, p = 0.168) and EMA (36.4% vs. 29.9%, p = 0.251) did not significantly differ between women and men.

Factors associated with insomnia symptoms in women and men

When comparing participants with insomnia symptoms to participants without insomnia symptoms, age, size of residential area and education level did not significantly affect the prevalence of insomnia. In contrast, female gender (OR = 1.3, 95% CI = 1.0–1.78), short sleep time (OR = 2.6, 95% CI = 1.9–3.5), anxiety (OR = 6.0, 95% CI = 4.3–8.3) and depression (OR = 9.6, 95% CI = 6.0–15.3) were found to be independent predictors of insomnia symptoms in multiple regression analysis (Table 3).

Table 3. Univariable and multivariable regression analysis for insomnia symptoms.

Univariable ORs Multivariable analysis ORs
Model 1 Model 2 Model 3 Model4
OR (95%Ci) p-value OR (95%Ci) p-value OR (95%Ci) p-value OR (95%Ci) p-value OR (95%Ci) p-value
Sex (Women) 1.543 (1.204–1.977) 0.001 1.513 (1.172–1.953) 0.001 1.401 (1.068–1.839) 0.015 1.388 (1.057–1.824) 0.018 1.327 (1.000–1.760) 0.05
Age (40 years or older) 1.199 (0.934–1.539) 0.155 0.928 (0.702–1.226) 0.599 0.938 (0.698–1.261) 0.673 1.028 (0.762–1.387) 0.856 0.999 (0.734–1.361) 0.997
Size of residential area (Large city) 1.027 (0.804–1.311) 0.831 1.037 (0.807–1.332) 0.779 1.004 (0.768–1.312) 0.977 1.010 (0.771–1.321) 0.944 0.990 (0.749–1.308) 0.943
Education (Middle school or less) 1.707 (1.260–2.314) 0.001 1.552 (1.105–2.180) 0.011 1.427 (0.993–2.051) 0.055 1.556 (1.083–2.235) 0.017 1.473 (1.009–2.150) 0.045
Sleep duration (6 hours or shorter) 3.069 (2.354–4.000) <0.001 3.081 (2.348–4.042) <0.001 2.738 (2.039–3.675) <0.001 2.780 (2.069–3.736) <0.001 2.604 (1.913–3.544) <0.001
Anxiety 10.095 (7.579–13.447) <0.001 9.284 (6.910–12.473) <0.001 6.014 (4.344–8.325) <0.001
Depression 20.113 (13.409–30.170) <0.001 18.626 (12.243–28.336) <0.001 9.588 (6.026–15.257) <0.001
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In Model 1, adjustment was conducted for sociodemographic variables (age, sex, size of residential area and educational level) and short sleep time. Model 2 incorporated anxiety (GAS score) with Model 1. Model 3 included depression (PHQ-9 score ≥ 10) with Model 1. The final model, Model 4, incorporated poor sleep quality (PSQI score ≥ 6), anxiety and depression with Model 1. Subject with missing data was excluded from the analysis.

p was calculated by the univariable / multiple logistic regression analysis.

Abbreviations: OR = odds ratio, CI = confidence interval.

For DIS, female gender (OR = 1.4, 95% CI = 1.0–2.0), short sleep time (OR = 3.1, 95% CI = 2.1–4.4), anxiety (OR = 5.0, 95% CI = 3.4–7.3) and depression (OR = 9.6, 95% CI = 6.0–15.5) were found to be independent predictors (S1 Table).

In univariable analysis, age was a significant predictor of DIS (1.5, 95% CI = 1.1–2.1) and DMS (OR = 1.5, 95% CI = 1.1–2.0). However, age lost significance for DIS (p = 0.235) and DMS (p = 0.219) in multiple regression analysis. Female gender (OR = 1.8, 95% CI = 1.2–2.6), short sleep time (OR = 2.5, 95% CI = 1.7–3.7), anxiety (OR = 5.2, 95% CI = 3.6–7.7) and depression (OR = 8.6, 95% CI = 5.3–13.9) were significant predictors of DMS in multiple regression analysis (S2 Table).

In multiple regression analysis for EMA, female gender (OR = 1.4, 95% CI = 1.0–2.0), age (OR = 1.8, 95% CI = 1.2–2.6), educational level (OR = 1.6, 95% CI = 1.1–2.5), short sleep time (OR = 3.7, 95% CI = 2.6–5.3), anxiety (OR = 5.1, 95% CI = 3.4–7.6) and depression (OR = 5.7, 95% CI = 3.4–9.4) were independent predictors (S3 Table).

Women showed similar result aspects. In multiple regression analysis for insomnia symptoms, short sleep time (OR = 2.2, 95% CI = 1.4–3.3), anxiety (OR = 6.1, 95% CI = 4.0–9.3), and depression (OR = 6.9, 95% CI = 3.8–12.3) were significant predictors. Those factors also had significance for insomnia symptoms, DIS, DMS and EMA in multiple regression analysis for both genders. Additionally, relatively low monthly income was a significant risk factor for men in insomnia symptoms and their subtypes (Table 4), while no socio-economic risk factor was related to female insomnia. (S4 Table).

Table 4. Univariable and multivariable regression analysis for insomnia symptoms and insomnia subtypes in men.

Multivariable analysis ORs
IS DIS DMS EMA
OR (95%Ci) p-value OR (95%Ci) p-value OR (95%Ci) p-value OR (95%Ci) p-value
Age (40 years or older) 0.772 (0.479–1.244) 0.287 1.204 (0.653–2.222) 0.552 1.220 (0.630–2.362) 0.555 1.469 (0.767–2.816) 0.246
Size of residential area (Large city) 1.433 (0.919–2.235) 0.113 1.420 (0.809–2.493) 0.222 1.104 (0.607–2.010) 0.745 0.932 (0.523–1.659) 0.810
Education (Middle school or less) 0.869 (0.411–1.836) 0.713 0.598 (0.236–1.517) 0.279 0.865 (0.362–2.071) 0.745 0.810 (0.345–1.900) 0.628
Sleep duration (6 hours or shorter) 3.489 (2.177–5.591) <0.001 3.664 (2.055–6.533) <0.001 3.247 (1.756–6.006) <0.001 4.855 (2.724–8.654) <0.001
Anxiety 6.031 (3.517–10.341) <0.001 6.059 (3.215–11.419) <0.001 9.307 (4.113–21.061) <0.001 6.849 (3.630–12.922) <0.001
Depression 18.158 (8.267–39.882) <0.001 12.766 (5.677–28.711) <0.001 5.578 (2.855–10.900) <0.001 7.614 (3.306–17.536) <0.001
Monthly income (<,2000 dollar) 2.030 (1.130–3.645) 0.018 2.006 (0.988–4.074) 0.054 2.776 (1.363–5.653) 0.005 2.477 (1.231–4.984) 0.011
Occupation (unemployed) 1.174 (0.644–2.141) 0.600 1.487 (0.708–3.123) 0.295 0.798 (0.338–1.881) 0.606 0.834 (0.360–1.928) 0.671
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Subject with missing data was excluded from the analysis.

p was calculated by the univariable / multiple logistic regression analysis.

Abbreviations: OR = odds ratio, CI = confidence interval, IS = Insomnia Symptoms, DIS = Difficulty in Initiating Sleep, DMS = Difficulty in Maintaining Sleep, EMA = Early Morning Awakening

Discussion

The main findings of the present study were as follows: 1) The prevalence of insomnia symptoms in a Korean general population-based sample was 10.7% and 2) The prevalence of insomnia symptoms was significantly higher in women than men. Among the subtypes of insomnia symptoms, there was a higher prevalence of DIS, DMA and EMA in women than in men and 3) Female gender was a significant factor for insomnia symptoms even after adjusting for covariates including sociodemographic variables, short sleep time, anxiety and depression.

General insomnia prevalence was similar with that reported in previous study [34]. Gender differences in insomnia disorder or insomnia symptoms have also been demonstrated in epidemiological studies. A meta-analysis combining data from 29 studies reported that women were at a 41% greater risk for having insomnia than men in adult populations [22]. Our results are in agreement with the previous findings that women had more insomnia symptoms than men.

What are possible mechanisms for higher insomnia prevalence in women? One possible explanation is roles of sex steroids. The major gonadal sex steroids are estrogen and progesterone in women and testosterone in men [35]. Sleep complaints typically co-occur in women with the fluctuation of ovarian steroids such as puberty, pregnancy, the menstrual cycle and the menopausal period [36–38]. Estrogen replacement therapy improves sleep disturbances in menopausal women [37]. In men, androgen deprivation therapy worsens insomnia in prostate cancer patients [38, 39]. On the contrary, high-dose testosterone replacement was associated with a reduction of sleep efficacy and total sleep time [40]. In summary, low or fluctuating levels of estrogen was consistently associated with increase occurrence of sleep disturbances including insomnia in women. Nevertheless, role of testosterone level on sleep in men is currently uncertain owing to inconsistent results.

Another possible explanation is role of biological gender. Androgen and estrogen affect differently on sleep between women and men. Gonadectomized female and male rats showed no significant difference in NREM and REM sleep amount. However, estradiol replacement significantly reduces NREM and REM sleep time in dark phase in female rats. In contrast, NREM and REM sleep architecture did not change by estradiol treatment in male rats [41]. Therefore, gender difference may be owing to biological gender rather than sex steroids.

The higher prevalence of mood symptoms in women could be a reason for gender difference. Both anxiety and depression are closely associated with sleep disturbances, including insomnia. Epidemiological studies have consistently reported a close association of insomnia with anxiety and depression. A meta-analysis including 21 longitudinal epidemiological studies showed an odds ratio for insomnia to predict depression of 2.60 (confidence interval: 1.98–3.42) [42]. Women preponderance of anxiety and depression has been persistently noted [43, 44]. Therefore, a higher prevalence of anxiety and depression in women may account for the higher prevalence of insomnia in women than men. Nevertheless, insomnia prevalence was significantly higher in women than men even after adjusting for anxiety and depression in the present study (Table 3). Therefore, the higher prevalence of insomnia in women could not be solely explained by the higher prevalence of anxiety and depression in women.

Differences in pain and somatic perception can also explain gender differences in insomnia symptoms. Pain and somatic symptoms are generally more prevalent in women [22, 45]. In particular, pain, insomnia, and somatic symptoms showed significant differences in adults rather than in adolescents before puberty. [46] These differences might speculate the relationship between sex and insomnia symptoms.

The present study showed that all subtypes of insomnia symptoms including DIS, DMS and EMA were more common in women than men. The significant differences in prevalence between women and men persisted even after adjusting for covariates including sociodemographic variables, short sleep time, anxiety and depression. Gender differences in the subtypes of insomnia have been demonstrated in epidemiological studies. Janson et al. reported that female gender was positively related to DMS in a European study [47]. An interview-based study showed a clear correlation between female gender and insomnia symptoms as well as the DMS-IV inclusion criteria [23]. Another study showed that 11.9% (14.0% of women vs. 9.3% of men) of the Hong Kong Chinese adult population complained of insomnia in the preceding month. Insomnia symptoms including DIS, DMS and EMA, more prominently appeared in women than in men. Gender (as women) was a specific risk factor despite common risk factors for insomnia in both genders [24].

The prevalence of EMA only showed significance in older individuals after including anxiety and depression in the adjustment (S3 Table). Still, we found a tendency that prevalence of insomnia symptoms increased with age. In this study, inclusion criteria for participants maximally limited to 69 years, and the size of the sample was small. These are possible explanations for the absence of statistical significance. (Table 1). Gender differences in insomnia prevalence were apparent in the elderly in epidemiological studies. In elderly populations, the risk of insomnia in women was almost doubled compared to that of men. Elderly (>65 years) women had a 73% greater risk of insomnia compared to elderly men [22]. In contrast, the predisposition for insomnia in women did not appear before puberty. These findings suggest a possible role of hormonal changes in the differences in insomnia between women and men [48, 49]. Also, we failed to report lower education levels as independent risk factor for insomnia and all subtypes. The statistical significance of low monthly income in men alone offered weak explanatory power, due to disputes in recent studies [9].

Despite of the low response rate (36.3%), we can speculate the general status of the Korean population through our data: 1) there were no significant differences in the distribution of age, gender, size of residential area, and educational level between survey participants and the Korean general population. 2) The prevalence of insomnia symptoms, anxiety, depression, and short sleep duration in this sample were similar to that of previous studies [4].

The present study has some limitations. First, this study did not use any objective measurement of sleep or sleep disorders such as polysomnography or actigraphy. Nevertheless, we evaluated insomnia symptoms, sleep habits and sleep quality using validated questionnaires via face-to-face interviews. Second, we did not evaluate the use of antidepressants, anxiolytics, hypnotics or caffeine. Antidepressants, anxiolytics or hypnotics may have a positive effect on sleep time and caffeine may negatively affect sleep time. Also, we could not measure sleep-relevant-treatments such as sleep-education, relaxation training or cognitive behavioral therapy for insomnia (CBTI). Third, although the present study was a large population-based study, some subgroup analyses might not have statistical significance due to the limited sample size and low response rate. In other words, the lack of significant findings in subgroup analyses could be due to the small subgroup sample size.

The present study has several strengths. First, the present study included a large sample size across the Korean general population. The distribution of age, gender, size of residential area and educational level of our sample was similar to the Korean population. Second, the present study assessed potential covariates of insomnia symptoms such as sociodemographic variables, poor sleep quality, short sleep time, anxiety and depression, which are related to insomnia symptoms. Third, we investigated gender differences in the subtypes of insomnia symptoms including DIS, DMS and EMA in addition to overall insomnia symptoms. Further, we analyzed the factors affecting insomnia subtypes.

Conclusions

Approximately one-tenth of the Korean general population sample had insomnia symptoms. The prevalence of insomnia symptoms was higher in women than men. Among the subtypes of insomnia symptoms, DIS, DMS and EMA were more prevalent in women than in men. The predisposition of insomnia symptoms in women was prominent even after adjusting for covariates including anxiety and depression.

Supporting information

S1 Table. Univariable and multivariable regression analysis for difficulty initiating sleep (DIS).

In Model 1, adjustment was conducted for sociodemographic variables (age, sex, size of residential area and educational level) and short sleep time. Model 2 incorporated anxiety (GAS score) with Model 1. Model 3 included depression (PHQ-9 score ≥ 10) with Model 1. The final model, Model 4, incorporated poor sleep quality (PSQI score ≥ 6), anxiety and depression with Model 1. Subject with missing data was excluded from the analysis. p was calculated by the univariable / multiple logistic regression analysis. Abbreviations: OR = odds ratio, CI = confidence interval.

(DOCX)

Click here for additional data file. (32.7KB, docx)
S2 Table. Univariable and multivariable regression analysis for difficulty maintaining sleep (DMS).

In Model 1, adjustment was conducted for sociodemographic variables (age, sex, size of residential area and educational level) and short sleep time. Model 2 incorporated anxiety (GAS score) with Model 1. Model 3 included depression (PHQ-9 score ≥ 10) with Model 1. The final model, Model 4, incorporated poor sleep quality (PSQI score ≥ 6), anxiety and depression with Model 1. Subject with missing data was excluded from the analysis. p was calculated by the univariable / multiple logistic regression analysis. Abbreviations: OR = odds ratio, CI = confidence interval.

(DOCX)

Click here for additional data file. (24.2KB, docx)
S3 Table. Univariable and multivariable regression analysis for early morning awakening (EMA).

In Model 1, adjustment was conducted for sociodemographic variables (age, sex, size of residential area and educational level) and short sleep time. Model 2 incorporated anxiety (GAS score) with Model 1. Model 3 included depression (PHQ-9 score ≥ 10) with Model 1. The final model, Model 4, incorporated poor sleep quality (PSQI score ≥ 6), anxiety and depression with Model 1. Subject with missing data was excluded from the analysis. p was calculated by the univariable / multiple logistic regression analysis. Abbreviations: OR = odds ratio, CI = confidence interval.

(DOCX)

Click here for additional data file. (24.2KB, docx)
S4 Table. Univariable and multivariable regression analysis for insomnia symptoms and insomnia subtypes in women.

Subject with missing data was excluded from the analysis. p was calculated by the univariable / multiple logistic regression analysis. Abbreviations: OR = odds ratio, CI = confidence interval, IS = Insomnia Symptoms, DIS = Difficulty in Initiating Sleep, DMS = Difficulty in Maintaining Sleep, EMA = Early Morning Awakening.

(DOCX)

Click here for additional data file. (24.9KB, docx)

Acknowledgments

The authors would like to thank Gallup Korea for providing technical support.

Abbreviations

CBTI

Cognitive Behavioral Therapy for Insomnia

DIS

difficulty in initiating sleep

DMS

difficulty in maintaining sleep

EMA

early morning awakening

GAS

Goldberg Anxiety Scale

IS

insomnia symptoms

ISI

The insomnia severity index

PHQ-9

Patient Health Questionnaire-9

PSQI

Pittsburgh Sleep Quality Index

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

This study was supported by a 2011 grant from Korean Academy of Medical Sciences and Korean Neurological Association (grant # KNA-10-MI-03). Funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Masaki Mogi

30 Sep 2019

PONE-D-19-17898

Gender differences influence over insomnia in Korean population: A cross-sectional study

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Choi Yun Ho has no conflicts of interest to declare.

Min Kyung Chu was involved as a site investigator for a multicenter trial sponsored by Otsuka Korea, Novartis International AG and Eli Lilly and company. Min Kyung Chu worked an advisory member for Teva and received lecture honoraria from Allergan Korea and Yuyu Pharmaceutical Company in the past 24 months.    

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Reviewer #1: This is a cross-sectional study aiming at the gender differences of insomnia symptoms. The findings and conclusions are not new while the methodology sounds satisfactory. The findings in the current study confirmed gender differences in insomnia and its subtype in Korean population. The strengths of the study include a reasonable measurement tool and good sampling framework, despite a lack of details. I have some suggestions for the authors.

1. What is the validity for each questionnaire in Korean version? Especially for ISI and PSQI.

2. The two-stage clustered random sampling method proportional to the population and socioeconomic distribution for all Korean territories should be presented in more details. Residents from which area were randomly selected?

3. When was the study conducted?

4. The response rate was poor, which should be considered a significant limitation.

5. Gender steroids should be rephrased as “sex steroids”. In general, gender is a more sociology concept while sex is a more biology concept.

6. Another explanation for the gender difference of insomnia is the gender difference in somatic perception.

Reviewer #2: Thank you for this chance to review this interesting manuscript, titled “Gender differences influence over insomnia in Korean population: A cross-sectional study”. This manuscript reported on the prevalence and associated factors of insomnia/symptoms in a sample of 2,695 Korean Adults. It was found that insomnia symptoms were present in 10.7% of survey respondents, and were positively associated with female gender, shorter total sleep duration, and psychiatric co-morbidities/symptoms. This is an interesting study which replicates data of previous studies in the general population of Korea. Its major strengths are the large sample size and reporting of results in the Korean population. My main concern is the limited amount of novel data/findings presented in this manuscript. As this is such a potentially rich dataset and study, I’ve tried to give some general comments/questions to investigate some more novel data.

Major:

·       Non-restorative sleep is no longer included among insomnia disorder criteria (or subtype). Consider removing and focusing only on DIS, DMS, and EMA subtypes/criteria for insomnia disorder.

·       What item of the ISI was used to determine NRS? Unless an additional item was included, I don’t think any of the items assess NRS (Dis/satisfaction, Noticeable to others, worry, and daytime functioning interference).

·       Abstract: Method section, page 6 description of the ISI, etc. The ISI should not be used in isolation to ‘diagnose’ insomnia. Consider re-wording to ‘classify’ insomnia rather than ‘diagnose insomnia’ in these sections.

·       Consider selection/response bias (of the 7,430 individuals approached, is it anticipated that more/less respondents with insomnia symptoms self-selected to complete the survey?

·       Table 3. Multivariate regression analysis, examining effect of gender, while controlling for gender as co-variate? The different models/co-variates may require review from a statistical reviewer. I may have mis-read something here.

·       The last 3 items of the ISI may be confounded with measures of depression/anxiety. I wonder whether the association between the ISI and psychiatric symptoms could be driven by the overlap in symptoms assessed by these items? It may be interesting to examine a ‘night time insomnia symptom’ group, using a composite score on the first 3 or 4 ISI items only, and re-examining relationships with anxiety/depression. This could be reported in a sensitivity analysis confined to the supplement.

·       Consider a sensitivity analysis removing the “difficulties falling asleep, staying asleep, etc” question from the PHQ-9 and investigating whether the relationship between the PHQ and ISI is reduced. Shared symptoms may increase relationship here without truly reflecting a positive association between insomnia and depression.

·       Same for the ‘sleep’ items of the Goldberg Anxiety Scale.

Minor:

·       Minor grammatical changes throughout (‘symptom’ vs ‘symptoms’, etc.).

·       Consider clearly differentiating “Insomnia disorder” (chronic and frequent night-time symptoms, plus daytime functional impairments), and “Insomnia symptoms” (night time complaints only) early in the manuscript.

·       Page 9, “Prevalence of insomnia and poor sleep quality’ section – There is a potential for some wording confusion in the second and third sentence. Please consider modifying the final sentence (“182 (6.8%) were accompanied by DIS…”) to specify that the denominator was the total 2,695 participants, not the 715 participants with PSQI of 5+.

·       Consider collapsing the multiple sub-headings in the Results section into a single sub-heading (e.g. several sections report gender differences for different outcomes/definitions).

·       Supplement Tables 1, 2, correct to ‘difficulty initiating/maintaining/etc sleep’

·       Other studies have reported a greater incidence of EMA, but lower incidence of DIS in older adults. It may be interesting to make comparisons in the discussion section.

·       What is the state of treatment services for insomnia in Korea? If 10% of the population suffer from insomnia symptoms, will more resources be required to treat them? May be worth commenting on these aspects in the discussion.

Additional Considerations and other Analyses

·       Separate cohort into different age brackets and examine prevalence of different insomnia complaints (e.g. <30, 31-40, 41-50, etc.).

·       It would be interesting to present a figure of changes in the three insomnia subtypes by age.

·       Did you collect any measure of employment (either job area, work hours/week, sick leave, etc.)? This may make an interesting comparison between insomnia/no-insomnia symptoms groups.

·       Any additional measure of other medical/psychiatric co-morbidities?

·       It may be interesting to also include a different ISI cut-off to define “Moderate” or “severe” insomnia (in addition to insomnia symptoms ISI >9.5). I wonder whether your gender and age effects will persist with different definitions of insomnia.

·       Consider examining TST between weekends and weekdays in both insomnia and no-insomnia participants. Is it possible that there is a greater discrepancy between weekends/weekdays for insomnia sufferers but not for those without insomnia symptoms. It would be interesting to examine the effect of age here too.

**********

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PLoS One. 2020 Jan 9;15(1):e0227190. doi: 10.1371/journal.pone.0227190.r002

Author response to Decision Letter 0

13 Nov 2019

Response to Reviewers

Reviewer #1:

1. What is the validity for each questionnaire in Korean version? Especially for ISI and PSQI.

Insomnia severity index : ISI≥ 10 which showed validity across population-based sample and The correlation between the ISI-K total score and PSQI-K was 0.84. A cutoff score of 15.5 on the ISI-K was optimal for discriminating patients with insomnia. (Cho YW, Song ML, Morin CM. Validation of a Korean version of the insomnia severity index. J Clin Neurol. 2014 Jul;10(3):210-5.)

Pittsburgh Sleep Quality Index : Cronbach's α coefficient for internal consistency of the total score of the PSQI-K was 0.84 which shows high reliability. Sensitivity and specificity for distinguishing poor and good sleepers were 0.943 and 0.844 using the best cutoff point of 8.5. The total and component scores of the PSQI-K for insomnia and narcolepsy were significantly higher than those for controls (p < 0.05). ( Sohn SI1, Kim DH, Lee MY, Cho YW. The reliability and validity of the Korean version of the Pittsburgh Sleep Quality Index. Sleep Breath. 2012 Sep;16(3):803-12.) which is higher than the score of 5 in the original paper (Buysse DJ, Reynolds CF 3rd, Monk TH et al. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res 28(2):193-213). This difference may be due to the high severity of symptoms in the insomnia and narcolepsy group and there is a limitation that this study was conducted on one sleep center in Korea. Consider that we conducted THE study in general population with various ages and The PSQI-K has been validated as a screening tool for sleep quality, we classified participants as “poor” sleeper if participant’s PSQI score was 6 or higher.

2. The two-stage clustered random sampling method proportional to the population and socioeconomic distribution for all Korean territories should be presented in more details. Residents from which area were randomly selected?

: Residents were randomly selected from all Korean territories except Jeju-do. 15 administrative divisions were designated as the primary sampling units. In each of the 15 administrative divisions, 4 representative basic units were randomly selected as secondary sampling units. The survey was applied in 60 representative basic units where appropriate assessments of residential status, population structure, household income, and occupational structure were available. In each sampling unit, the target sample number was determined based on the distributions of sociodemographic parameters such as age, gender, educational level, and monthly household income. And we sampled individuals in proportion to the population distribution and stratified as age, gender, and occupation.

3. When was the study conducted?

: This survey was collected from November 2011 to January 2012. Analyzing this data, drafting and revising of this manuscript was conducted from November 2016 to July 2017.

4. The response rate was poor, which should be considered a significant limitation.

: We agree with your comment and we described poor response rate as a limitation in the manuscript.

5. Gender steroids should be rephrased as “sex steroids”. In general, gender is a more sociology concept while sex is a more biology concept.

Referring to your opinion, we corrected the context.

6. Another explanation for the gender difference of insomnia is the gender difference in somatic perception.

We revised the manuscript based on your opinion.

Reviewer #2:

Major:

Non-restorative sleep is no longer included among insomnia disorder criteria (or subtype). Consider removing and focusing only on DIS, DMS, and EMA subtypes/criteria for insomnia disorder.

-> Thank you for your opinion and we revised the manuscript removing NRS as subtypes for insomnia disorder.

What item of the ISI was used to determine NRS? Unless an additional item was included, I don’t think any of the items assess NRS (Dis/satisfaction, Noticeable to others, worry, and daytime functioning interference).

-> We add a question asking participants to score whether they are having none restorative sleep within the past 2 weeks from 0 (never) to 4 (severe, at least three times per week).

Abstract: Method section, page 6 description of the ISI, etc. The ISI should not be used in isolation to ‘diagnose’ insomnia. Consider re-wording to ‘classify’ insomnia rather than ‘diagnose insomnia’ in these sections.

-> referring to your opinion, we corrected the context.

Consider selection/response bias (of the 7,430 individuals approached, is it anticipated that more/less respondents with insomnia symptoms self-selected to complete the survey?

-> To reduce sampling error, this survey was commissioned from Gallup Korea and they conducted the two-stage clustered random sampling gaining a large sample size.

Table 3. Multivariate regression analysis, examining effect of gender, while controlling for gender as co-variate? The different models/co-variates may require review from a statistical reviewer. I may have mis-read something here.

-> Yes, as we know, it has statistical power while using gender as co-variate to examining the statistical significance of gender in multivariate regression analysis. We also asked an opinion about statistical designs of this study from Professor Jung Mo Nam, Department of Preventive Medicine.

The last 3 items of the ISI may be confounded with measures of depression/anxiety. I wonder whether the association between the ISI and psychiatric symptoms could be driven by the overlap in symptoms assessed by these items? It may be interesting to examine a ‘night time insomnia symptom’ group, using a composite score on the first 3 or 4 ISI items only, and re-examining relationships with anxiety/depression. This could be reported in a sensitivity analysis confined to the supplement.

Consider a sensitivity analysis removing the “difficulties falling asleep, staying asleep, etc” question from the PHQ-9 and investigating whether the relationship between the PHQ and ISI is reduced. Shared symptoms may increase relationship here without truly reflecting a positive association between insomnia and depression.

Same for the ‘sleep’ items of the Goldberg Anxiety Scale.

->

We doubt that the last three items of the ISI solely measuring anxiety or depression that can be removed. We think that ISI, PHQ-9 and Goldberg Anxiety Scale has its validity as a screening tool for each disorder/symptom as a whole questionnaire. But we agree that it might be intriguing to analysis removing “sleep section” from each questionnaire and see a correlation with insomnia symptom but since this study is focused on to see the effect of gender as a covariate in insomnia and take it into the next paper. Thank you for your opinion.

Minor:

Minor grammatical changes throughout (‘symptom’ vs ‘symptoms’, etc.).

Consider clearly differentiating “Insomnia disorder” (chronic and frequent night-time symptoms, plus daytime functional impairments), and “Insomnia symptoms” (night time complaints only) early in the manuscript.

Page 9, “Prevalence of insomnia and poor sleep quality’ section – There is a potential for some wording confusion in the second and third sentence. Please consider modifying the final sentence (“182 (6.8%) were accompanied by DIS…”) to specify that the denominator was the total 2,695 participants, not the 715 participants with PSQI of 5+.

Consider collapsing the multiple sub-headings in the Results section into a single sub-heading (e.g. several sections report gender differences for different outcomes/definitions).

Supplement Tables 1, 2, correct to ‘difficulty initiating/maintaining/etc sleep’

-> We revised the manuscript based on your opinion.

What is the state of treatment services for insomnia in Korea? If 10% of the population suffer from insomnia symptoms, will more resources be required to treat them? May be worth commenting on these aspects in the discussion.

-> We mentioned these aspects as limitations in discussion; we could not measure state of treatment services in this study.

Additional Considerations and other Analyses

It would be interesting to present a figure of changes in the three insomnia subtypes by age.

-> We revised the manuscript based on your opinion.

Did you collect any measure of employment (either job area, work hours/week, sick leave, etc.)? This may make an interesting comparison between insomnia/no-insomnia symptoms groups. Any additional measure of other medical/psychiatric co-morbidities?

-> No, we collected only their current state of job by criteria. We gathered information on other specific medical comorbidities (hypertension, diabetes, coronary artery disease, cerebrovascular diseases, dyslipidemia, etc) and age of onset, but we ruled out these comorbidities as a covariate due to a small number of sample and low statistical power compare to others.

Separate cohort into different age brackets and examine prevalence of different insomnia complaints (e.g. <30, 31-40, 41-50, etc.).

Other studies have reported a greater incidence of EMA, but lower incidence of DIS in older adults. It may be interesting to make comparisons in the discussion section.

It may be interesting to also include a different ISI cut-off to define “Moderate” or “severe” insomnia (in addition to insomnia symptoms ISI >9.5). I wonder whether your gender and age effects will persist with different definitions of insomnia.

Consider examining TST between weekends and weekdays in both insomnia and no-insomnia participants. Is it possible that there is a greater discrepancy between weekends/weekdays for insomnia sufferers but not for those without insomnia symptoms. It would be interesting to examine the effect of age here too.

-> We did separated participants into different age groups but the results were not significantly different. The current state of employment was also irrelevant. We appreciate your great feedback and will analyze in detail and take it seriously into the next paper.

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Decision Letter 1

Masaki Mogi

16 Dec 2019

Gender differences influence over insomnia in Korean population: A cross-sectional study

PONE-D-19-17898R1

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Acceptance letter

Masaki Mogi

23 Dec 2019

PONE-D-19-17898R1

Gender differences influence over insomnia in Korean population: A cross-sectional study

Dear Dr. Kim:

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If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Univariable and multivariable regression analysis for difficulty initiating sleep (DIS).

    In Model 1, adjustment was conducted for sociodemographic variables (age, sex, size of residential area and educational level) and short sleep time. Model 2 incorporated anxiety (GAS score) with Model 1. Model 3 included depression (PHQ-9 score ≥ 10) with Model 1. The final model, Model 4, incorporated poor sleep quality (PSQI score ≥ 6), anxiety and depression with Model 1. Subject with missing data was excluded from the analysis. p was calculated by the univariable / multiple logistic regression analysis. Abbreviations: OR = odds ratio, CI = confidence interval.

    (DOCX)

    Click here for additional data file. (32.7KB, docx)
    S2 Table. Univariable and multivariable regression analysis for difficulty maintaining sleep (DMS).

    In Model 1, adjustment was conducted for sociodemographic variables (age, sex, size of residential area and educational level) and short sleep time. Model 2 incorporated anxiety (GAS score) with Model 1. Model 3 included depression (PHQ-9 score ≥ 10) with Model 1. The final model, Model 4, incorporated poor sleep quality (PSQI score ≥ 6), anxiety and depression with Model 1. Subject with missing data was excluded from the analysis. p was calculated by the univariable / multiple logistic regression analysis. Abbreviations: OR = odds ratio, CI = confidence interval.

    (DOCX)

    Click here for additional data file. (24.2KB, docx)
    S3 Table. Univariable and multivariable regression analysis for early morning awakening (EMA).

    In Model 1, adjustment was conducted for sociodemographic variables (age, sex, size of residential area and educational level) and short sleep time. Model 2 incorporated anxiety (GAS score) with Model 1. Model 3 included depression (PHQ-9 score ≥ 10) with Model 1. The final model, Model 4, incorporated poor sleep quality (PSQI score ≥ 6), anxiety and depression with Model 1. Subject with missing data was excluded from the analysis. p was calculated by the univariable / multiple logistic regression analysis. Abbreviations: OR = odds ratio, CI = confidence interval.

    (DOCX)

    Click here for additional data file. (24.2KB, docx)
    S4 Table. Univariable and multivariable regression analysis for insomnia symptoms and insomnia subtypes in women.

    Subject with missing data was excluded from the analysis. p was calculated by the univariable / multiple logistic regression analysis. Abbreviations: OR = odds ratio, CI = confidence interval, IS = Insomnia Symptoms, DIS = Difficulty in Initiating Sleep, DMS = Difficulty in Maintaining Sleep, EMA = Early Morning Awakening.

    (DOCX)

    Click here for additional data file. (24.9KB, docx)
    Attachment

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    Data Availability Statement

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