Abstract
Background
We aimed to investigate associations between weekday-to-weekend sleep differences and mental health and examine whether the association varies by weekday sleep duration among young adults in South Korea.
Methods
We used the Survey of Korean Youths’ Lives, a nationally representative data for young adults aged 19–34 years in South Korea. Weekday-to-weekend sleep differences were calculated by the difference between sleep durations on weekends (or free days) and those on weekdays (or working days). Indicators of mental health included unhappiness, life dissatisfaction, burnout, depression, and suicide ideation. A logistic regression analysis was conducted to investigate associations between weekday-to-weekend sleep differences and mental health. We stratified respondents by weekday sleep duration (i.e., < 7 hours and ≥ 7 hours) and examined the difference in associations of weekday-to-weekend sleep differences with mental health.
Results
Among the 14,931 respondents, 49.4% and 17.1% reported having 1–2 hours and more than 2 hours more sleep during weekends compared to their weekday sleep, respectively. Moreover, 38.5% of respondents had less than the recommended hours (≥ 7 hours) of sleep on weekdays and they were more likely to have additional hours of sleep on weekends. Larger weekday-to-weekend sleep differences were associated with poor mental health. Specifically, young adults who slept more than two additional hours on weekends were more likely to experience poor mental health conditions, including unhappiness, life dissatisfaction, burnout, depression, and suicide ideation. Furthermore, the associations between weekday-to-weekend sleep differences and poor mental health were more pronounced among those who slept less than the recommended hours on weekdays.
Conclusion
This study suggests that large differences in sleep duration between weekdays and weekends could be a useful indicator for detecting poor mental health status. However, further research is needed to better understand the mechanisms underlying factors contributing to weekday-to-weekend sleep differences among young adults.
Keywords: Weekday-To-Weekend Sleep Differences, Mental Health, Young Adulthood, Korea
Graphical Abstract
INTRODUCTION
Young adulthood (aged 19–34 years) has been characterised as an age group facing the challenges of entering adulthood within a society.1 During this developmental phase, they experience social and ecological changes as it coincides with a transition to university or work, involving increased responsibility, new roles, and changes in life circumstances due to socialisation, such as interpersonal relationships and career development.2,3 These changes could be highly challenging and stressful to manage, potentially leading to lifestyle and behaviour changes,4 with insufficient sleep being a common issue during this transition period.4,5 Previous studies from the US showed that the level of insufficient sleep was higher among young adults compared to other age groups6,7 and insufficient sleep duration may negatively influence well-being and mental health.8 Given that a significant proportion of young adults is perceived as sleep-deprived, this could be an important public health concern for this population.
Numerous young adults, including university students and those beginning their careers, may experience shorter than recommended sleep durations,8 particularly on weekdays when wake-up times are influenced by attending university or work. On weekends, in contrast, wake-up times might be delayed due to reduced social pressure to go to university or work, allowing them to catch up on the sleep lost during weekdays. However, associations between weekday-to-weekend sleep differences and mental health outcomes among young adults received relatively little attention compared to those in childhood and adolescence4,9 and other adult age groups, such as middle-aged10,11 and older adults.11,12 Previous studies indicated that weekday-to-weekend sleep differences were associated with poor well-being and mental health among adolescents9,13,14,15,16 whereas these differences had beneficial effects on mental health among middle-aged adults.10,11 This suggests that it is necessary to investigate whether the patterns for young adults are similar to those observed in adolescents or middle- and older-aged adults.
Associations between weekday-to-weekend sleep differences and mental health may vary between groups with sufficient and insufficient weekday sleep durations. However, few studies investigated these associations among young people, but they showed mixed findings.9,17 One study showed that adolescents having more than 2 hours of additional sleep during weekends compared to weekdays reported lower subjective well-being, particularly among those with insufficient sleep.9 In contrast, another study found that adolescents who had similar sleep durations between weekdays and weekends, but shorter sleep durations on weekdays, were more likely to have depressive symptoms and suicide ideation.17 Thus, it remains unclear whether and how weekday-to-weekend sleep differences and weekday sleep duration interact to influence well-being and mental health among young adults.
South Korea, with 51 million population in East Asia, is one of the countries with the shortest average sleep duration among high-income countries. Meanwhile, sleep duration recently decreased18 and associated mental health concerns have been recently prevalent among young adults compared to other age groups.19 Psychological distress and poor mental health have also become more prevalent among young adults due to an unstable social environment and increasing pressure.20,21 These suggest that more research is needed to better understand the associations between sleep and mental health among young adults in South Korea.
Therefore, we aimed to 1) investigate associations between weekday-to-weekend sleep differences and a range of mental health outcomes among young adults aged 19–34 years in South Korea and 2) examine whether these associations differ by weekday sleep duration in a nationally representative sample.
METHODS
Data and study participants
We used data from the Survey of Korean Youths’ Lives, which included a nationally representative sample of young adults aged 19–34 years in South Korea. This cross-sectional study was conducted in 2022 by the Office for Government Policy Coordination Prime Minister’s Secretariat and the Korea Institute for Health and Social Affairs to better understand the life conditions of young adults to enhance their quality of life.22 The study included various information on the life conditions of young adults in South Korea, including socioeconomic status such as housing conditions, education, working conditions, economic conditions, and health-related status such as mental and physical health status and health behaviour.22 The sample was drawn using a stratified two-stage probability proportionate sampling design.22 Of a total of 14,966 individuals who participated in the interview, we excluded those with incomplete information (n = 35), and the final study sample included 14,931 respondents.
Measures
We used variables of average sleep durations on weekdays (or working days) and weekends (or free days), which were assessed using a self-reported question: ‘On average, how many hours do you sleep on weekdays (or working days) and weekends (or free days), respectively?’ Then, individual weekday-to-weekend sleep differences were calculated as the difference between sleep durations on weekends and those on weekdays15,23 and classified into three groups: < 1 hour, 1 hour, 2 hours, and > 2 hours, similar to previous studies.24 Additionally, respondents reporting less than 7 hours of average weekday sleep duration were classified as an insufficient sleep group based on a recommendation from the National Sleep Foundation25 and previous studies.26,27,28
For mental health indicators, the present study included three aspects of mental health: positive mental health, psychopathology, and suicidality. Positive mental health was measured by happiness and life satisfaction. Happiness was assessed using a single question: ‘How happy were you yesterday?’ and life satisfaction was evaluated with a single question: ‘How satisfied are you with your personal life?’. Those indicators were rated on a 10-point Likert scale, and respondents with more than 7 points (the median point) were classified as those experiencing happiness and life satisfaction, respectively. Regarding psychopathology indicators, we used measures of burnout and depression. Burnout was measured by a single question: ‘Have you experienced burnout in the past year?’. Respondents who answered “Yes” to this question were classified as having experienced burnout. Depression symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9) scale. Respondents were asked to assess their experience of specific depressive symptoms over the past two weeks using a 4-point Likert scale for each of the 9 items.29 Each item was scored on a Likert scale ranging from 0 to 3, where 0 indicates ‘none’ and 3 indicates ‘almost every day.’ These scores were summed up to calculate the total PHQ-9 score, which spans from 0 to 27. Respondents with a total PHQ-9 score greater than 5 were classified as experiencing depressive symptoms.10,30 For suicidality, suicide ideation was assessed using a single question: ‘Have you thought seriously about dying by suicide over the past year?.’ Respondents who answered “Yes” to this question were categorised as those having experienced suicide ideation.
A range of covariates included sex, age group (19–24, 25–29, and 30–34 years), household size (1 person, 2–3 persons, and +4 persons), marital status (single and married), education level (high school graduation and below, in college or university, and college graduation or higher), working status (working and not working), income level (low and high income), current smoking (yes and no), alcohol consumption (yes and no), and subjective health status (very good, good, and moderate and poor and very poor).
Statistical analysis
First, we used a χ2 test to describe the characteristics of the study samples and compare the level of mental health. Second, univariate and multivariate logistic regression analyses were used to examine the association between weekday-to-weekend sleep differences and mental health indicators, estimating the odds ratio (OR) and 95% confidence intervals (CIs), with adjustments for covariates in three steps. Model 1 was adjusted for sex and age, and Model 2 was adjusted for sex, age, household size, marital status, education level, working status, and income level. The final model (Model 3) was adjusted for sex, age, household size, marital status, education level, working status, income level, current smoking, high-risk alcohol consumption, weekly sleep durations, and subjective health status. Furthermore, we examined trends in the associations by specifying the variable of weekday-to-weekend sleep differences as a continuous variable.31,32 We assessed sex differences in the associations of weekday-to-weekend sleep differences with mental health by including an interaction term (i.e., weekday-to-weekend sleep differences × sex) in the final model (Model 3). Last, we stratified weekday sleep duration (i.e., < 7 hours and ≥ 7 hours) and investigated the difference in associations of weekday-to-weekend sleep differences with mental health in the final model. Additionally, we conducted interaction tests by including interaction terms (i.e., weekday-to-weekend sleep differences × weekday sleep duration) in the same model. All analyses were conducted using SAS 9.4 (SAS Institute Inc., Cary, NC, USA), and statistical evidence was considered when P values were less than 0.05.
Ethics statement
This study was approved by the Institutional Review Board of Korea University and the requirement for informed consent was waived (approval number: KUIRB-2024-0182-01).
RESULTS
Table 1 presents the sample characteristics. Among the 14,931 respondents, 7,156 (47.9%) and 7,775 (52.1%) were men and women, respectively. Regarding weekday-to-weekend sleep differences, 3,137 (21.0%) and 4,244 (28.4%) reported having 1 and 2 hours more sleep during the weekend compared to their weekday sleep, while 2,555 (17.1%) reported having more than 2 hours of additional sleep during the weekend. The proportion of respondents having insufficient sleep (i.e., less than 7 hours of sleep) during weekdays was 38.5%. Respondents with less than the recommended weekday sleep duration were more likely to have additional hours of sleep on weekends than those who had more than the recommended hours on weekdays (P < 0.001) (Fig. 1). For mental health indicators, the prevalence of unhappiness, life dissatisfaction, burnout, depression, and suicide ideation were 37.7%, 38.3%, 32.5%, 20.8%, and 2.4%, respectively (Table 1).
Table 1. General characteristics of the study samples.
| Variables | Values | |
|---|---|---|
| Weekday-to-weekend sleep differences, hr | ||
| < 1 | 4,995 (33.5) | |
| 1 | 3,137 (21.0) | |
| 2 | 4,244 (28.4) | |
| > 2 | 2,555 (17.1) | |
| Weekly sleep duration, hr | ||
| ≥ 7 | 9,190 (61.6) | |
| < 7 | 5,741 (38.5) | |
| Unhappiness | ||
| Yes | 5,623 (37.7) | |
| No | 9,308 (62.3) | |
| Life dissatisfaction | ||
| Yes | 5,714 (38.3) | |
| No | 9,217 (61.7) | |
| Burnout | ||
| Yes | 4,852 (32.5) | |
| No | 10,079 (67.5) | |
| Depressive symptom | ||
| Yes | 3,104 (20.8) | |
| No | 11,827 (79.2) | |
| Suicide ideation | ||
| Yes | 351 (2.4) | |
| No | 14,580 (97.7) | |
| Sex | ||
| Male | 7,156 (47.9) | |
| Female | 7,775 (52.1) | |
| Age group, yr | ||
| 19–24 | 7,171 (48.0) | |
| 25–29 | 4,543 (30.4) | |
| 30–34 | 3,217 (21.6) | |
| Household size, person | ||
| 1 | 5,343 (35.8) | |
| 2–3 | 6,211 (41.6) | |
| 4+ | 3,377 (22.6) | |
| Marital status | ||
| Single | 13,356 (89.5) | |
| Married | 1,575 (10.6) | |
| Education level | ||
| High school graduation and below | 2,076 (13.9) | |
| In college or university | 4,719 (31.6) | |
| College graduation or higher | 8,136 (54.5) | |
| Working status | ||
| Not working | 5,478 (36.7) | |
| Working | 9,453 (63.3) | |
| Income level | ||
| Low | 7,464 (50.0) | |
| High | 7,467 (50.0) | |
| Current smoking | ||
| Yes | 2,864 (19.2) | |
| No | 12,067 (80.8) | |
| Alcohol consumption | ||
| Yes | 11,867 (79.5) | |
| No | 3,064 (20.5) | |
| Subjective health status | ||
| Poor | 1,004 (6.7) | |
| Moderate or good | 13,927 (93.3) | |
| Total | 14,931 (100.0) | |
Values are presented as number (%).
Fig. 1. Distribution of weekday sleep duration by weekday-to-weekend sleep differences. P for group differences represents the P value from the χ2 test.
Table 2 shows the bivariate association between weekday-to-weekend sleep differences and mental health. The prevalence of poor mental health increased with larger weekday-to-weekend sleep differences, particularly for psychopathology and suicidality indicators. For example, the prevalence of depression symptom was 17.7% for respondents with less than 1 hour of weekday-to-weekend sleep differences and 28.9% for those with more than 2 hours.
Table 2. Bivariate association of weekday-to-weekend sleep differences with poor mental health.
| Variables | Unhappiness | Life dissatisfaction | Burnout | Depressive symptom | Suicide ideation | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Yes | No | P value | Yes | No | P value | Yes | No | P value | Yes | No | P value | Yes | No | P value | ||
| Weekday-to-weekend sleep difference, hr | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | |||||||||||
| < 1 | 1,830 (36.6) | 3,165 (63.4) | 1,856 (37.2) | 3,139 (62.8) | 1,450 (29.0) | 3,545 (71.0) | 884 (17.7) | 4,111 (82.3) | 107 (2.1) | 4,888 (97.9) | ||||||
| 1 | 1,125 (35.9) | 2,012 (64.1) | 1,161 (37.0) | 1,976 (63.0) | 939 (29.9) | 2,198 (70.1) | 613 (19.5) | 2,524 (80.5) | 60 (1.9) | 3,077 (98.1) | ||||||
| 2 | 1,620 (38.2) | 2,624 (61.8) | 1,611 (38.0) | 2,633 (62.0) | 1,380 (32.5) | 2,864 (67.5) | 870 (20.5) | 3,374 (79.5) | 83 (2.0) | 4,161 (98.0) | ||||||
| > 2 | 1,048 (41.0) | 1,507 (59.0) | 1,086 (42.5) | 1,469 (57.5) | 1,083 (42.4) | 1,472 (57.6) | 737 (28.9) | 1,818 (71.2) | 101 (4.0) | 2,454 (96.1) | ||||||
| Weekly sleep duration, hr | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.034 | |||||||||||
| < 7 | 2,315 (40.3) | 3,426 (59.7) | 2,338 (40.7) | 3,403 (59.3) | 2,192 (38.2) | 3,549 (61.8) | 1,450 (25.3) | 4,291 (74.7) | 154 (2.7) | 5,587 (97.3) | ||||||
| ≥ 7 | 3,308 (36.0) | 5,882 (64.0) | 3,376 (36.7) | 5,814 (63.3) | 2,660 (28.9) | 6,530 (71.1) | 1,654 (18.0) | 7,536 (82.0) | 197 (2.1) | 8,993 (97.9) | ||||||
| Sex | 0.004 | 0.210 | < 0.001 | < 0.001 | < 0.001 | |||||||||||
| Male | 2,780 (38.9) | 4,376 (61.2) | 2,775 (38.8) | 4,381 (61.2) | 2,000 (28.0) | 5,156 (72.1) | 1,241 (17.3) | 5,915 (82.7) | 122 (1.7) | 7,034 (98.3) | ||||||
| Female | 2,843 (36.6) | 4,932 (63.4) | 2,939 (37.8) | 4,836 (62.2) | 2,852 (36.7) | 4,923 (63.3) | 1,863 (24) | 5,912 (76) | 229 (3.0) | 7,546 (97.1) | ||||||
| Age group, yr | 0.039 | < 0.001 | < 0.001 | < 0.001 | 0.570 | |||||||||||
| 19–24 | 2,672 (37.3) | 4,499 (62.7) | 2,639 (36.8) | 4,532 (63.2) | 2,200 (30.7) | 4,971 (69.3) | 1,299 (18.1) | 5,872 (81.9) | 159 (2.2) | 7,012 (97.8) | ||||||
| 25–29 | 1,777 (39.1) | 2,766 (60.9) | 1,840 (40.5) | 2,703 (59.5) | 1,626 (35.8) | 2,917 (64.2) | 1,034 (22.8) | 3,509 (77.2) | 111 (2.4) | 4,432 (97.6) | ||||||
| 30–34 | 1,174 (36.5) | 2,043 (63.5) | 1,235 (38.4) | 1,982 (61.6) | 1,026 (31.9) | 2,191 (68.1) | 771 (24) | 2,446 (76) | 81 (2.5) | 3,136 (97.5) | ||||||
| Household size, person | 0.007 | 0.081 | < 0.001 | 0.013 | 0.170 | |||||||||||
| 1 | 2,082 (39.0) | 3,261 (61.0) | 2,046 (38.3) | 3,297 (61.7) | 1,793 (33.6) | 3,550 (66.4) | 1,142 (21.4) | 4,201 (78.6) | 142 (2.7) | 5,201 (97.3) | ||||||
| 2–3 | 2,337 (37.6) | 3,874 (62.4) | 2,427 (39.1) | 3,784 (60.9) | 1,877 (30.2) | 4,334 (69.8) | 1,221 (19.7) | 4,990 (80.3) | 133 (2.1) | 6,078 (97.9) | ||||||
| 4+ | 1,204 (35.7) | 2,173 (64.4) | 1,241 (36.8) | 2,136 (63.3) | 1,182 (35.0) | 2,195 (65.0) | 741 (21.9) | 2,636 (78.1) | 76 (2.3) | 3,301 (97.8) | ||||||
| Marital status | < 0.001 | < 0.001 | 0.003 | 0.005 | 0.210 | |||||||||||
| Single | 5,204 (39.0) | 8,152 (61.0) | 5,249 (39.3) | 8,107 (60.7) | 4,391 (32.9) | 8,965 (67.1) | 2,734 (20.5) | 10,622 (79.5) | 321 (2.4) | 13,035 (97.6) | ||||||
| Married | 419 (26.6) | 1,156 (73.4) | 465 (29.5) | 1,110 (70.5) | 461 (29.3) | 1,114 (70.7) | 370 (23.5) | 1,205 (76.5) | 30 (1.9) | 1,545 (98.1) | ||||||
| Education level | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.004 | |||||||||||
| High school graduation and below | 1,025 (49.4) | 1,051 (50.6) | 1,048 (50.5) | 1,028 (49.5) | 608 (29.3) | 1,468 (70.7) | 482 (23.2) | 1,594 (76.8) | 69 (3.3) | 2,007 (96.7) | ||||||
| In college or university | 1,568 (33.2) | 3,151 (66.8) | 1,531 (32.4) | 3,188 (67.6) | 1,361 (28.8) | 3,358 (71.2) | 753 (16.0) | 3,966 (84.0) | 96 (2.0) | 4,623 (98.0) | ||||||
| College graduation or higher | 3,030 (37.2) | 5,106 (62.8) | 3,135 (38.5) | 5,001 (61.5) | 2,883 (35.4) | 5,253 (64.6) | 1,869 (23.0) | 6,267 (77.0) | 186 (2.3) | 7,950 (97.7) | ||||||
| Working status | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.440 | |||||||||||
| Not working | 2,153 (39.3) | 3,325 (60.7) | 2,194 (40.1) | 3,284 (60.0) | 1,668 (30.5) | 3,810 (69.6) | 988 (18.0) | 4,490 (82.0) | 122 (2.2) | 5,356 (97.8) | ||||||
| Working | 3,470 (36.7) | 5,983 (63.3) | 3,520 (37.2) | 5,933 (62.8) | 3,184 (33.7) | 6,269 (66.3) | 2,116 (22.4) | 7,337 (77.6) | 229 (2.4) | 9,224 (97.6) | ||||||
| Income level | < 0.001 | 0.004 | 0.096 | < 0.001 | 0.110 | |||||||||||
| Low | 2,931 (39.3) | 4,533 (60.7) | 2,940 (39.4) | 4,524 (60.6) | 2,378 (31.9) | 5,086 (68.1) | 1,403 (18.8) | 6,061 (81.2) | 190 (2.6) | 7,274 (97.5) | ||||||
| High | 2,692 (36.1) | 4,775 (64.0) | 2,774 (37.2) | 4,693 (62.9) | 2,474 (33.1) | 4,993 (66.9) | 1,701 (22.8) | 5,766 (77.2) | 161 (2.2) | 7,306 (97.8) | ||||||
| Current smoking | < 0.001 | < 0.001 | 0.078 | 0.220 | < 0.001 | |||||||||||
| Yes | 1,231 (43.0) | 1,633 (57.0) | 1,232 (43.0) | 1,632 (57.0) | 891 (31.1) | 1,973 (68.9) | 619 (21.6) | 2,245 (78.4) | 102 (3.6) | 2,762 (96.4) | ||||||
| No | 4,392 (36.4) | 7,675 (63.6) | 4,482 (37.1) | 7,585 (62.9) | 3,961 (32.8) | 8,106 (67.2) | 2,485 (20.6) | 9,582 (79.4) | 249 (2.1) | 11,818 (97.9) | ||||||
| Alcohol consumption | 0.010 | 0.100 | < 0.001 | < 0.001 | 0.100 | |||||||||||
| Yes | 4,408 (37.2) | 7,459 (62.9) | 4,502 (37.9) | 7,365 (62.1) | 4,069 (34.3) | 7,798 (65.7) | 2,553 (21.5) | 9,314 (78.5) | 291 (2.5) | 11,576 (97.6) | ||||||
| No | 1,215 (39.7) | 1,849 (60.4) | 1,212 (39.6) | 1,852 (60.4) | 783 (25.6) | 2,281 (74.5) | 551 (18.0) | 2,513 (82.0) | 60 (2.0) | 3,004 (98.0) | ||||||
| Subjective health status | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | |||||||||||
| Poor | 632 (63.0) | 372 (37.1) | 678 (67.5) | 326 (32.5) | 685 (68.2) | 319 (31.8) | 644 (64.1) | 360 (35.9) | 136 (13.6) | 868 (86.5) | ||||||
| Moderate or good | 4,991 (35.8) | 8,936 (64.2) | 5,036 (36.2) | 8,891 (63.8) | 4,167 (29.9) | 9,760 (70.1) | 2,460 (17.7) | 11,467 (82.3) | 215 (1.5) | 13,712 (98.5) | ||||||
Values are presented as number (%).
Table 3 shows multivariate associations between weekday-to-weekend sleep differences and mental health. After accounting for covariates, young adults with larger weekday-to-weekend sleep differences were more likely to report poor mental health. Additionally, linear trends in the associations were observed across all mental health indicators. However, there was no statistical evidence that an association between weekday-to-weekend sleep differences and most poor mental health indicators among individuals with one or two hours of sleep differences after full adjustments (Model 3). The strength of the associations appeared to be greater in psychopathology and suicidality indicators than in positive mental health indicators. For example, the adjusted OR of having suicide ideation among individuals with more than two hours of weekday-to-weekend sleep differences was 1.58 (95% CI, 1.16–2.15) while the corresponding OR for unhappiness was 1.12 (95% CI, 1.01–1.25). There was no statistical evidence of sex differences in associations of weekday-to-weekend sleep differences with mental health (Supplementary Table 1). Regarding weekday sleep duration, individuals with less than the recommended weekday sleep duration were more likely to have poor mental health except for suicide ideation (Supplementary Table 2).
Table 3. Multivariate association of weekday-to-weekend sleep differences with poor mental health.
| Variables | Unhappiness | Life dissatisfaction | Burnout | Depressive symptom | Suicide ideation | |
|---|---|---|---|---|---|---|
| Model 1a | ||||||
| < 1 hr | Reference | Reference | Reference | Reference | Reference | |
| 1 hr | 0.97 (0.88–1.06) | 0.99 (0.90–1.09) | 1.03 (0.93–1.14) | 1.11 (0.99–1.24) | 0.88 (0.64–1.21) | |
| 2 hr | 1.07 (0.98–1.16) | 1.03 (0.95–1.12) | 1.17 (1.07–1.28) | 1.19 (1.07–1.32) | 0.90 (0.68–1.21) | |
| > 2 hr | 1.21 (1.09–1.33) | 1.25 (1.14–1.38) | 1.77 (1.6–1.95) | 1.88 (1.68–2.10) | 1.84 (1.40–2.43) | |
| P for trend | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.001 | |
| Model 2b | ||||||
| < 1 hr | Reference | Reference | Reference | Reference | Reference | |
| 1 hr | 0.99 (0.90–1.09) | 1.02 (0.92–1.12) | 1.03 (0.93–1.14) | 1.11 (0.99–1.24) | 0.90 (0.66–1.25) | |
| 2 hr | 1.09 (1.00–1.19) | 1.07 (0.98–1.16) | 1.17 (1.07–1.28) | 1.19 (1.07–1.32) | 0.93 (0.69–1.24) | |
| > 2 hr | 1.24 (1.12–1.37) | 1.31 (1.18–1.44) | 1.76 (1.59–1.95) | 1.86 (1.66–2.09) | 1.89 (1.43–2.50) | |
| P for trend | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | |
| Model 3c | ||||||
| < 1 hr | Reference | Reference | Reference | Reference | Reference | |
| 1 hr | 1.00 (0.91–1.10) | 1.03 (0.93–1.13) | 1.03 (0.93–1.14) | 1.14 (1.01–1.29) | 0.98 (0.71–1.36) | |
| 2 hr | 1.06 (0.97–1.16) | 1.04 (0.95–1.14) | 1.08 (0.98–1.19) | 1.13 (1.01–1.26) | 0.95 (0.70–1.30) | |
| > 2 hr | 1.12 (1.01–1.25) | 1.18 (1.07–1.32) | 1.47 (1.32–1.63) | 1.56 (1.37–1.76) | 1.58 (1.16–2.15) | |
| P for trend | 0.021 | 0.005 | < 0.001 | < 0.001 | 0.018 | |
Values are presented as odds ratio (95% confidence interval).
aModel 1: adjusted for sex and age group.
bModel 2: adjusted for sex, age group, household size, marital status, education level, working status, income level.
cModel 3: adjusted for sex, age group, household size, marital status, education level, working status, income level, current smoking, high-risk drinking, weekly sleep duration, and subjective health status.
In the stratified analysis by weekday sleep duration (i.e., less than recommended weekday sleep duration (< 7 hours) and recommended weekday sleep duration (≥ 7 hours), stronger associations of weekday-to-weekend sleep differences with poor mental health among individuals with less than the recommended weekday sleep duration (Table 4, Fig. 2). There was also statistical evidence of group differences in associations of weekday-to-weekend sleep differences with mental health. For example, the adjusted OR of having depression symptom among individuals with more than two hours of weekday-to-weekend sleep differences and less than recommended weekday sleep duration was 1.90 (95% CI, 1.56–2.31) while the corresponding OR among those with more than two hours of weekday-to-weekend sleep differences and sufficient weekday sleep was 1.27 (95% CI, 1.06–1.52).
Table 4. Multivariate association of weekday-to-weekend sleep differences with poor mental health stratified by weekly sleep duration.
| Variables | Unhappiness | Life dissatisfaction | Burnout | Depressive symptom | Suicide ideation | |
|---|---|---|---|---|---|---|
| Less than recommended sleep during weekdays (< 7 hr)a | ||||||
| < 1 hr | Reference | Reference | Reference | Reference | Reference | |
| 1 hr | 1.13 (0.94–1.36) | 1.12 (0.94–1.35) | 1.25 (1.03–1.52) | 1.32 (1.06–1.65) | 0.84 (0.45–1.55) | |
| 2 hr | 1.08 (0.93–1.27) | 1.00 (0.86–1.17) | 1.31 (1.11–1.54) | 1.19 (0.98–1.44) | 0.83 (0.50–1.38) | |
| > 2 hr | 1.33 (1.13–1.57) | 1.40 (1.19–1.66) | 1.87 (1.57–2.22) | 1.90 (1.56–2.31) | 1.45 (0.89–2.35) | |
| P for trend | 0.002 | < 0.001 | < 0.001 | < 0.001 | 0.010 | |
| More than recommended sleep during weekdays (≥ 7 hr)a | ||||||
| < 1 hr | Reference | Reference | Reference | Reference | Reference | |
| 1 hr | 0.95 (0.85–1.07) | 0.99 (0.89–1.11) | 0.96 (0.85–1.09) | 1.09 (0.94-1.26) | 1.08 (0.73–1.6) | |
| 2 hr | 1.10 (0.98–1.24) | 1.13 (1.01–1.26) | 1.01 (0.9–1.14) | 1.15 (1.00–1.33) | 1.06 (0.71–1.57) | |
| > 2 hr | 0.95 (0.82–1.1) | 0.98 (0.84–1.14) | 1.25 (1.07–1.46) | 1.27 (1.06–1.52) | 1.60 (1.04–2.47) | |
| P for trend | 0.670 | 0.350 | 0.031 | 0.004 | 0.095 | |
| Group differenceb | 0.013 | 0.019 | < 0.001 | 0.001 | 0.480 | |
Values are presented as odds ratio (95% confidence interval).
aAdjusted for sex, age group, household size, marital status, education level, working status, income level, current smoking, high-risk drinking, and subjective health status.
bAn interaction term between weekday-to-weekend sleep differences and weekday sleep duration was included.
Fig. 2. Interaction effect of weekday-to-weekend sleep differences and weekday sleep duration on poor mental health. (A) Unhappiness, (B) life dissatisfaction, (C) burnout, (D) depressive symptom, (E) suicide ideation. All odd ratios were adjusted odd ratios for sex, age group, household size, marital status, education level, working status, income level, current smoking, high-risk drinking, weekly sleep duration, and subjective health status. Vertical solid red lines or dashed dark blue lines represent 95% confidence interval ranges. Gray dashed lines (odds ratio, 1) represent the reference group of individuals with less than 1 hour of weekday-to-weekend sleep differences.
DISCUSSION
This study investigated the associations between weekday-to-weekend sleep differences and a range of mental health outcomes and examined whether these associations vary by weekday sleep duration in a nationally representative sample of young adults aged 19–34 years in South Korea. Our findings showed that larger weekday-to-weekend sleep differences were associated with a range of poor mental health outcomes among young adults. In particular, those who slept more than two additional hours during weekends compared to weekdays were more likely to have poor mental health conditions, including unhappiness, life dissatisfaction, burnout, depression, and suicide ideation. We also found that the associations between weekday-to-weekend sleep differences and poor mental health were stronger among individuals with fewer than recommended hours of sleep during weekdays.
In this study, approximately 40% of respondents had fewer than the recommended hours (≥ 7 hours) of sleep on weekdays and they were more likely to have additional hours of sleep on weekends than those who had the recommended hours on weekdays. Young adults may have socially prescribed early wake-up times for their study and work, but their sleep onset time is not socially limited because they often have additional work or study, which may result in insufficient sleep during weekdays. Consequently, they were more likely to catch up on sleep during weekends, suggesting that the weekday-to-weekend sleep difference may partially represent the accumulation of sleep debt.11,15
This study found that a greater weekday-to-weekend sleep difference was independently associated with poor mental health after adjusting for confounding factors, consistent with previous studies among adolescents.9,14,15 In a stratified analysis, the association between weekday-to-weekend sleep differences and poor mental health, except for suicide ideation, was stronger among those who slept fewer than the recommended hours during weekdays, consistent with a previous study.9 Previous research, including a systematic review, showed a bidirectional association between sleep disturbance and poor mental health conditions, such as depression and anxiety in both youth and adult populations.33,34,35 This suggests that larger weekday-to-weekend sleep differences may affect, or be affected by, poor mental health conditions. Therefore, our findings on the association between weekday-to-weekend sleep differences and poor mental health could be interpreted in both directions.
One possible explanation is that larger weekday-to-weekend sleep differences may cause poor mental health, as extending sleep duration on weekends could lead to social jetlag and circadian misalignment.24 During weekdays (or working days), individuals often experience a temporary and persistent mismatch between their required sleep schedule and their internal circadian rhythm, commonly referred to as circadian misalignment and social jetlag.36,37 Previous studies showed that the differences in sleep duration between weekdays and weekends were associated with social jetlag among adult populations.24,38 Particularly, a previous study among adult populations in South Korea suggested that individuals with large differences in sleep duration between weekdays and weekends had a higher tendency for a late chronotype (eveningness) compared to those without these differences.39 Several previous review studies reported that social jetlag and late chronotype were associated with poor mental health.36,40,41 Although sleep debt may be compensated with longer sleep on free days, sleep duration on the night before work may be sharply reduced due to a late bedtime from the weekend phase and an early wake-up imposed by social constraints.36 Moreover, weekday-to-weekend sleep differences might be associated with social withdrawal, which is strongly linked to poor mental health.13,42 Previous studies suggested that social withdrawal or isolation could be attributable to insufficient sleep duration.43,44,45 Consequently, the cycle of sleep debt may be perpetuated,36,46 potentially affecting mental health. However, this study did not include late chronotype due to limited data. Further investigation is needed to consider more sleep-related factors. Thus, insufficient sleep and large weekday-to-weekend sleep differences could be modifiable and sufficient sleep during the weekdays and less weekday-to-weekend sleep differences may promote mental health.
Another possible explanation is that larger weekday-to-weekend sleep differences may be attributed to poor mental health, which could be closely related to social constraints such as academic or work-related stress or pressure during weekdays among young adults. This is similar to patterns observed in young people.13 In a report from the Organization for Economic Co-operation and Development (OECD), the average annual working hours in South Korea in 2021 were 1,910 hours, the fifth-highest hours among OECD countries following Colombia, Mexico, Costa Rica, and Chile.47 Moreover, low work-life balance was pronounced among the working population in South Korea48 driven by the after-work social culture.49 Given these socio-environmental circumstances, young adults may be particularly susceptible to the observed societal pressure, leading them to allocate more time to study and work. This increased focus on academic and job demands could potentially cause psychological distress, even though their efforts to maintain a better work-life balance.50 The psychological distress and poor mental health may lead to irregular sleep patterns or sleep disturbance.16,35 Thus, young adults who have psychological distress due to social pressure during weekdays may tend to have higher weekday-to-weekend sleep differences. However, further investigation is needed to understand the underlying mechanisms, such as social and environmental demands, of increased differences in sleep duration between weekdays and weekends among young adults.
In this study, we used nationally representative data from a large sample size of young adults aged 19–34 years in South Korea, which allows more detailed analyses of the association between weekday-to-weekend sleep and mental health. Additionally, we included a range of mental health indicators across various domains, including positive mental health, psychopathology, and suicidality. We also investigated stratified associations between weekday-to-weekend sleep differences and poor mental health by weekday sleep duration. However, several limitations in this study should be interpreted cautiously. First, our findings regarding the associations between weekday-to-weekend sleep differences and poor mental health were observed in a cross-sectional study, which may not necessarily imply causality. Second, we used only weekday-to-weekend sleep differences and weekday sleep duration and did not include other sleep-related indicators, such as sleep pattern, sleep quality, and social jetlag, due to limited data. Third, most mental health indicators, except for depression symptom, were assessed by a single self-report question. Although these single self-report questions were widely used in previous studies, the reliability of such questions, including happiness, life satisfaction, burnout, and suicide ideation, might be limited.
In most societies, such as South Korea, poor mental health becomes prevalent among young adults20,51 and it could have more severe and long-lasting consequences for this age group compared to others.3,52 Our findings show that larger weekday-to-weekend sleep differences were associated with poor mental health, particularly among individuals with insufficient sleep during weekdays. This suggests that sufficient sleep duration with less weekday-to-weekend sleep differences might play an important role in promoting better mental health among young adults. Furthermore, insufficient sleep or irregular sleep, including large weekday-to-weekend sleep differences, could be considered useful indicators of population mental health.16 Further research is needed to better understand the mechanisms underlying factors contributing to weekday-to-weekend sleep differences.
Footnotes
Funding: Yo Han Lee was supported by grants from Korea University. Minjae Choi was supported by grants from the National Research Foundation (NRF) of Korea funded by the Ministry of Education (grant number: NRF-2022R1A6A3A01086222).
Disclosure: The authors have no potential conflicts of interest to disclose.
Data Availability Statement: The datasets used and/or analysed during the current study are available from MicroData Integrated Service (https://mdis.kostat.go.kr/index.do) provided by Statistics Korea.
- Conceptualization: Choi M, Lee YH.
- Data curation: Choi M.
- Formal analysis: Choi M.
- Funding acquisition: Choi M, Lee YH.
- Investigation: Choi M, Lee YH.
- Methodology: Choi M, Lee YH.
- Project administration: Choi M, Lee YH.
- Resources: Choi M, Sempungu JK.
- Software: Choi M, Sempungu JK.
- Supervision: Lee YH.
- Validation: Sempungu JK.
- Visualization: Sempungu JK, Kim MH, Han JH.
- Writing - original draft: Choi M, Sempungu JK, Lee YH.
- Writing - review & editing: Sempungu JK, Kim MH, Han JH.
SUPPLEMENTARY MATERIALS
Sex differences in multivariate association of weekday-to-weekend sleep differences with poor mental health
Multivariate association of weekday sleep durations with poor mental health
References
- 1.Pegado A, Alvarez MJ, Roberto MS. The role of behaviour-change theory in sleep interventions with emerging adults (aged 18-29 years): a systematic review and meta-analysis. J Sleep Res. 2023;32(5):e13877. doi: 10.1111/jsr.13877. [DOI] [PubMed] [Google Scholar]
- 2.Conley CS, Shapiro JB, Huguenel BM, Kirsch AC. Navigating the college years: Developmental trajectories and gender differences in psychological functioning, cognitive-affective strategies, and social well-being. Emerg Adulthood. 2020;8(2):103–117. [Google Scholar]
- 3.Newman DL, Moffitt TE, Caspi A, Magdol L, Silva PA, Stanton WR. Psychiatric disorder in a birth cohort of young adults: prevalence, comorbidity, clinical significance, and new case incidence from ages 11 to 21. J Consult Clin Psychol. 1996;64(3):552–562. [PubMed] [Google Scholar]
- 4.Vela-Bueno A, Fernandez-Mendoza J, Olavarrieta-Bernardino S. Sleep patterns in the transition from adolescence to young adulthood. Sleep Med Clin. 2009;4(1):77–85. [Google Scholar]
- 5.Bruce ES, Lunt L, McDonagh JE. Sleep in adolescents and young adults. Clin Med (Lond) 2017;17(5):424–428. doi: 10.7861/clinmedicine.17-5-424. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Grandner MA, Jackson NJ, Izci-Balserak B, Gallagher RA, Murray-Bachmann R, Williams NJ, et al. Social and behavioral determinants of perceived insufficient sleep. Front Neurol. 2015;6:112. doi: 10.3389/fneur.2015.00112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Grandner MA, Martin JL, Patel NP, Jackson NJ, Gehrman PR, Pien G, et al. Age and sleep disturbances among American men and women: data from the U.S. Behavioral risk factor surveillance system. Sleep (Basel) 2012;35(3):395–406. doi: 10.5665/sleep.1704. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Morita Y, Sasai-Sakuma T, Asaoka S, Inoue Y. Prevalence and correlates of insufficient sleep syndrome in Japanese young adults: a web-based cross-sectional study. J Clin Sleep Med. 2015;11(10):1163–1169. doi: 10.5664/jcsm.5092. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Tonetti L, Andreose A, Bacaro V, Grimaldi M, Natale V, Crocetti E. Different effects of social jetlag and weekend catch-up sleep on well-being of adolescents according to the actual sleep duration. Int J Environ Res Public Health. 2022;20(1):574. doi: 10.3390/ijerph20010574. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Park JH, Moon JH, Kim HJ, Kong MH, Oh B, Kim S, et al. Association between weekend catch-up sleep and the risk of depression among Korean middle-aged adults. Sleep Biol Rhythms. 2023;21(1):51–58. doi: 10.1007/s41105-022-00415-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Adachi H, Yamamoto R, Fujino R, Kanayama D, Sakagami Y, Akamine S, et al. Association of weekday-to-weekend sleep differences and stress response among a Japanese working population: a cross-sectional study. Sleep Med. 2021;82:159–164. doi: 10.1016/j.sleep.2021.04.006. [DOI] [PubMed] [Google Scholar]
- 12.Suh S, Yang HC, Kim N, Yu JH, Choi S, Yun CH, et al. Chronotype differences in health behaviors and health-related quality of life: a population-based study among aged and older adults. Behav Sleep Med. 2017;15(5):361–376. doi: 10.1080/15402002.2016.1141768. [DOI] [PubMed] [Google Scholar]
- 13.Kim J, Noh JW, Kim A, Kwon YD. The impact of weekday-to-weekend sleep differences on health outcomes among adolescent students. Children (Basel) 2022;9(1):52. doi: 10.3390/children9010052. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Sun W, Ling J, Zhu X, Lee TMC, Li SX. Associations of weekday-to-weekend sleep differences with academic performance and health-related outcomes in school-age children and youths. Sleep Med Rev. 2019;46:27–53. doi: 10.1016/j.smrv.2019.04.003. [DOI] [PubMed] [Google Scholar]
- 15.Kang SG, Lee YJ, Kim SJ, Lim W, Lee HJ, Park YM, et al. Weekend catch-up sleep is independently associated with suicide attempts and self-injury in Korean adolescents. Compr Psychiatry. 2014;55(2):319–325. doi: 10.1016/j.comppsych.2013.08.023. [DOI] [PubMed] [Google Scholar]
- 16.Zhang J, Paksarian D, Lamers F, Hickie IB, He J, Merikangas KR. Sleep patterns and mental health correlates in US adolescents. J Pediatr. 2017;182:137–143. doi: 10.1016/j.jpeds.2016.11.007. [DOI] [PubMed] [Google Scholar]
- 17.Lee H, Kim YJ, Jeon YH, Kim SH, Park EC. Association of weekend catch-up sleep ratio and subjective sleep quality with depressive symptoms and suicidal ideation among Korean adolescents. Sci Rep. 2022;12(1):10235. doi: 10.1038/s41598-022-14352-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Shin D, Hur J, Cho KH, Cho EH. Trends of self-reported sleep duration in Korean adults: results from the Korea National Health and Nutrition Examination Survey 2007-2015. Sleep Med. 2018;52:103–106. doi: 10.1016/j.sleep.2018.08.008. [DOI] [PubMed] [Google Scholar]
- 19.Kim HJ, Oh SY, Joo JH, Choi DW, Park EC. The relationship between sleep duration and perceived stress: findings from the 2017 community health survey in Korea. Int J Environ Res Public Health. 2019;16(17):3208. doi: 10.3390/ijerph16173208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Lee EJ, Kim SJ. Prevalence and related factors of depression before and during the COVID-19 pandemic: findings from the Korea National Health and Nutrition Examination Survey. J Korean Med Sci. 2023;38(10):e74. doi: 10.3346/jkms.2023.38.e74. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Park CR, Han CK. The effect of social trust on depression among young adults: focusing on gender differences. Health Soc Welf Rev. 2023;43(1):141–156. [Google Scholar]
- 22.Cheong S, Ryoo J, Kang YE, Kim S, Ham S, Kim D, et al. 2022 Survey of Korean Youths’ Lives. Sejong, Korea: Korea Institute for Health and Social Affairs; 2022. [Google Scholar]
- 23.Kim SJ, Lee YJ, Cho SJ, Cho IH, Lim W, Lim W. Relationship between weekend catch-up sleep and poor performance on attention tasks in Korean adolescents. Arch Pediatr Adolesc Med. 2011;165(9):806–812. doi: 10.1001/archpediatrics.2011.128. [DOI] [PubMed] [Google Scholar]
- 24.Kim KM, Han SM, Min IK, Heo K, Kim WJ, Chu MK. Weekend catch-up sleep and depression: results from a nationally representative sample in Korea. Sleep Med. 2021;87:62–68. doi: 10.1016/j.sleep.2021.02.058. [DOI] [PubMed] [Google Scholar]
- 25.Hirshkowitz M, Whiton K, Albert SM, Alessi C, Bruni O, DonCarlos L, et al. National Sleep Foundation’s updated sleep duration recommendations. Sleep Health. 2015;1(4):233–243. doi: 10.1016/j.sleh.2015.10.004. [DOI] [PubMed] [Google Scholar]
- 26.Steptoe A, Peacey V, Wardle J. Sleep duration and health in young adults. Arch Intern Med. 2006;166(16):1689–1692. doi: 10.1001/archinte.166.16.1689. [DOI] [PubMed] [Google Scholar]
- 27.Watson NF, Badr MS, Belenky G, Bliwise DL, Buxton OM, Buysse D, et al. Recommended amount of sleep for a healthy adult: a joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. J Clin Sleep Med. 2015;11(6):591–592. doi: 10.5664/jcsm.4758. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Grandner MA. Epidemiology of insufficient sleep and poor sleep quality. Sleep Health. 2019:11–20. [Google Scholar]
- 29.Löwe B, Kroenke K, Herzog W, Gräfe K. Measuring depression outcome with a brief self-report instrument: sensitivity to change of the Patient Health Questionnaire (PHQ-9) J Affect Disord. 2004;81(1):61–66. doi: 10.1016/S0165-0327(03)00198-8. [DOI] [PubMed] [Google Scholar]
- 30.Park SJ, Choi HR, Choi JH, Kim KW, Hong JP. Reliability and validity of the Korean version of the Patient Health Questionnaire-9 (PHQ-9) Anxiety Mood. 2010;6(2):119–124. [Google Scholar]
- 31.Jung EJ, Cho SS, Lee HE, Min J, Jang TW, Kang MY. Association between social jetlag and self-rated health: Evidence from Korean representative working population. Sleep Med. 2024;114:86–91. doi: 10.1016/j.sleep.2023.12.019. [DOI] [PubMed] [Google Scholar]
- 32.Min J, Jang TW, Lee HE, Cho SS, Kang MY. Social jetlag and risk of depression: results from the Korea National Health and Nutrition Examination Survey. J Affect Disord. 2023;323:562–569. doi: 10.1016/j.jad.2022.12.010. [DOI] [PubMed] [Google Scholar]
- 33.Alvaro PK, Roberts RM, Harris JK. A systematic review assessing bidirectionality between sleep disturbances, anxiety, and depression. Sleep (Basel) 2013;36(7):1059–1068. doi: 10.5665/sleep.2810. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Jansson-Fröjmark M, Lindblom K. A bidirectional relationship between anxiety and depression, and insomnia? A prospective study in the general population. J Psychosom Res. 2008;64(4):443–449. doi: 10.1016/j.jpsychores.2007.10.016. [DOI] [PubMed] [Google Scholar]
- 35.Kaneita Y, Yokoyama E, Harano S, Tamaki T, Suzuki H, Munezawa T, et al. Associations between sleep disturbance and mental health status: a longitudinal study of Japanese junior high school students. Sleep Med. 2009;10(7):780–786. doi: 10.1016/j.sleep.2008.06.014. [DOI] [PubMed] [Google Scholar]
- 36.Taillard J, Sagaspe P, Philip P, Bioulac S. Sleep timing, chronotype and social jetlag: impact on cognitive abilities and psychiatric disorders. Biochem Pharmacol. 2021;191:114438. doi: 10.1016/j.bcp.2021.114438. [DOI] [PubMed] [Google Scholar]
- 37.Wittmann M, Dinich J, Merrow M, Roenneberg T. Social jetlag: misalignment of biological and social time. Chronobiol Int. 2006;23(1-2):497–509. doi: 10.1080/07420520500545979. [DOI] [PubMed] [Google Scholar]
- 38.Lee HJ, Cho S, Lee SH, Kim SJ, Kim KM, Chu MK. Catch-up sleep on free days and body mass index: results from the seventh Korea National Health and Nutrition Examination Survey, 2016. J Clin Sleep Med. 2024;20(1):39–47. doi: 10.5664/jcsm.10790. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Im HJ, Baek SH, Chu MK, Yang KI, Kim WJ, Park SH, et al. Association between weekend catch-up sleep and lower body mass: population-based study. Sleep (Basel) 2017;40(7):zsx089. doi: 10.1093/sleep/zsx089. [DOI] [PubMed] [Google Scholar]
- 40.Au J, Reece J. The relationship between chronotype and depressive symptoms: a meta-analysis. J Affect Disord. 2017;218:93–104. doi: 10.1016/j.jad.2017.04.021. [DOI] [PubMed] [Google Scholar]
- 41.Henderson SEM, Brady EM, Robertson N. Associations between social jetlag and mental health in young people: a systematic review. Chronobiol Int. 2019;36(10):1316–1333. doi: 10.1080/07420528.2019.1636813. [DOI] [PubMed] [Google Scholar]
- 42.Zhu S, Lee PH, Wong PWC. Investigating prolonged social withdrawal behaviour as a risk factor for self-harm and suicidal behaviours. BJPsych Open. 2021;7(3):e90. doi: 10.1192/bjo.2021.47. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Ben Simon E, Walker MP. Sleep loss causes social withdrawal and loneliness. Nat Commun. 2018;9(1):3146. doi: 10.1038/s41467-018-05377-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Schoger LI. Coping with work-related stressors: does education reduce work-related stress? J Public Health (Oxf) 2025;33:1123–1134. [Google Scholar]
- 45.Vézina M, Derriennic F, Monfort C. The impact of job strain on social isolation: a longitudinal analysis of French workers. Soc Sci Med. 2004;59(1):29–38. doi: 10.1016/j.socscimed.2003.09.033. [DOI] [PubMed] [Google Scholar]
- 46.Skeldon AC, Phillips AJ, Dijk DJ. The effects of self-selected light-dark cycles and social constraints on human sleep and circadian timing: a modeling approach. Sci Rep. 2017;7(1):45158. doi: 10.1038/srep45158. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Organisation for Economic Co-operation and Development. Hours worked. [Updated 2025]. [Accessed April 30, 2024]. https://data.oecd.org/emp/hours-worked.htm .
- 48.Noh HJ. A categorization of time guarantee in work-life balance. Health Soc Wel Rev. 2023;43(2):192–214. [Google Scholar]
- 49.Organisation for Economic Co-operation and Development. Rejuvenating Korea: Policies for a Changing Society. Paris, France: OECD Publishing; 2019. [Google Scholar]
- 50.Park MS, Kim MY, Kim KA, Chun J. Factors of the happiness of youth generations by work-life balance: a cross-national comparison utilizing the better life index and world value survey. J Fam Resour Manag Policy Rev. 2019;23(2):79–97. [Google Scholar]
- 51.Patel V, Flisher AJ, Hetrick S, McGorry P. Mental health of young people: a global public-health challenge. Lancet. 2007;369(9569):1302–1313. doi: 10.1016/S0140-6736(07)60368-7. [DOI] [PubMed] [Google Scholar]
- 52.Vanheusden K, van der Ende J, Mulder CL, van Lenthe FJ, Verhulst FC, Mackenbach JP. Beliefs about mental health problems and help-seeking behavior in Dutch young adults. Soc Psychiatry Psychiatr Epidemiol. 2009;44(3):239–246. doi: 10.1007/s00127-008-0428-8. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Sex differences in multivariate association of weekday-to-weekend sleep differences with poor mental health
Multivariate association of weekday sleep durations with poor mental health