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Psychiatry Investig > Volume 22(9); 2025 > Article
Cai, Lai, Huang, Xiao, Liu, Zhao, and Luo: Association Between Weekend Catch-Up Sleep and Depression: Evidence From the 2017-2018 National Health and Nutrition Examination Survey

Abstract

Objective

Weekend catch-up sleep (CUS) has been associated with certain health benefits; however, there is a paucity of research regarding the correlation between CUS and depression in adults. This study aimed to investigate the association between weekend CUS and depressive symptoms in a nationally representative adult population.

Methods

We analyzed data from the 2017-2018 National Health and Nutrition Examination Survey. Depression was assessed using the Patient Health Questionnaire-9, with a score ≥10 indicating clinically significant depressive symptoms. CUS duration was categorized into four groups: CUS≤0 h, 0 h<CUS≤1 h, 1 h<CUS≤2 h, and CUS>2 h. Multivariable logistic regression models adjusted for sociodemographic factors, health behaviors, and comorbidities were employed to examine associations.

Results

Out of 4,450 eligible participants, 2,169 (48.7%), 943 (21.2%), 641 (14.4%), and 697 (15.7%) had weekend CUS durations of ≤0, 0 to 1, 1 to 2, and >2 h, respectively. The prevalence of depression was found to be 9.59%, 7.74%, 7.18%, and 8.75%, respectively, in these groups. Adjusted for multiple variables, the odds ratios (ORs) for depression were 0.89 (95% confidence interval [CI] 0.54-1.48), 0.71 (95% CI 0.37-1.37), and 0.97 (95% CI 0.57-1.65) for individuals with 0 h<CUS≤1 h, 1 h<CUS≤2 h, and CUS>2 h, respectively, in comparison to those with CUS≤0 h. However, subgroup analyses suggested a potential protective effect of CUS (>2 h) against depression in individuals with weekday sleep duration <6 h (OR=0.47, 95% CI 0.27-0.83).

Conclusion

Weekend CUS was not associated with depression risk in the general adult population. The observed protective effect in sleep-restricted individuals warrants further investigation through prospective studies to evaluate potential causal relationships.

INTRODUCTION

Sleep plays a crucial role in human physiology, encompassing about one-third of our daily life. Despite common misconceptions, sleep is not a passive state but rather an active process that triggers significant physiological changes throughout the body [1]. Hence, ensuring adequate sleep duration and quality is crucial for optimal physical and mental well-being. Unfortunately, sleep disturbances are widespread in contemporary society [2], with sleep deprivation emerging as a prevalent concern [3]. Notably, both inadequate and excessive sleep duration have been linked to elevated risk of various metabolic and cardiovascular conditions, including diabetes [4], hypertension [5], metabolic syndrome [6], cardiovascular disease (CVD) [7], obesity, 8 and psychiatric disorders such as depression [9]. Currently chronic sleep deficiency and sleep disorders are regarded as pressing public health challenges [10].
Depression, a highly prevalent and debilitating disorder, affects approximately 7% of the global population [11]. Individuals with depression often experience impaired functional capacity and significant health-related disability, as evidenced by poor self-rated health status [12]. In 2015, depression ranked as the third leading cause of disability worldwide, due to its substantial prevalence and association with disabilities [13]. Furthermore, depression frequently co-occurs with chronic illnesses may precipitate suicidal behavior [14].
In contemporary society, the duration of sleep is often compromised by social commitments or work schedules, resulting in a population-wide decline in average sleep duration. This sleep curtailment adversely affects both mental well-being and metabolic health. This reduced sleep pattern is linked to a heightened risk of developing depression [15,16]. To compensate for weekday sleep debt, some individuals extend their sleep on weekends, a phenomenon termed weekend catch-up sleep (CUS). This compensatory strategy aims to counteract insufficient weekday sleep through prolonged sleep on free days. Notably, CUS may confer metabolic benefits, including improved insulin sensitivity, lower body mass index (BMI), reduced blood pressure, and a decreased risk of dyslipidemia [17-19]. Among Korean adults, data from the 2016 Korean National Health and Nutrition Examination Survey (NHANES) indicated that those with insufficient sleep who did not practice weekend CUS faced a significantly higher risk of depression compared to those who compensated with weekend CUS [20]. Similarly, a study of Korean high school students suggested that ≥2-hour CUS combined with frequent private tutoring was associated with a lower likelihood of depression [21]. Additionally, research involving a nationally representative Korean sample found that 1-2 hours of weekend CUS was associated with a lower depression risk relative to ≤0 hours of CUS [22]. However, existing evidence on the CUS-depression relationship remains limited and inconsistent. To address this gap, we analyzed data from the 2017-2018 NHANES to assess this association, with subgroup analyses to explore potential variations.

METHODS

Study population and survey

This study conducted a cross-sectional analysis of data from the NHANES (https://www.cdc.gov/nchs/nhanes/?CDC_AAref_Val=https://www.cdc.gov/nchs/nhanes/index.htm). The research involving human participants underwent review and approval by the National Center for Health Statistics (NCHS). The NHANES survey protocol was approved by the Research Ethics Review Committee. The NCHS Research Ethics Review Board granted approval for the study (Protocol #2018-01), and informed consent was obtained from all participants (https://www.cdc.gov/nchs/nhanes/about/erb.html?CDC_AAref_Val=https://www.cdc.gov/nchs/nhanes/irba98.htm).

Assessments of sleep duration and weekend CUS

In the NHANES 2017-2018 survey, participants’ weekday and weekend sleep durations were determined based on their responses to separate questions regarding the number of hours slept on weekdays or workdays and weekends or non-workdays. The average sleep duration was computed as a weighted mean: (5×weekday sleep duration+2×weekend sleep duration)/7 [23]. The calculation of CUS duration involved subtracting the average sleep duration on weekdays from that on weekends. CUS duration greater than 0 hours was considered as experiencing CUS. Furthermore, CUS duration was categorized into four groups: CUS≤0 h, 0 h<CUS≤1 h, 1 h<CUS≤2 h, and CUS>2 h.

Depression

To assess the severity of depression, we utilized the Patient Health Questionnaire-9 (PHQ-9), which was developed in alignment with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for major depression. The PHQ-9 evaluates the following symptoms: 1) loss of interest or pleasure in activities; 2) feelings of sadness, hopelessness, or depression; 3) disturbances in sleep patterns; 4) fatigue or decreased energy levels; 5) changes in appetite; 6) negative self-perception; 7) difficulty concentrating; 8) changes in motor activity; and 9) thoughts of self-harm. Responses were rated on a 4-point scale from 0 to 3, reflecting experiences over the past two weeks. The total score of the PHQ-9 was calculated by summing the scores of the nine items, depression was defined as PHQ-9 score ≥10, with higher scores indicating more pronounced depression [24].

Covariates

Previous research has indicated a correlation between the average weekly sleep duration (hours, per night) and the risk of depression. Therefore, it was included as a covariate in the analysis of the association between CUS and depression [25,26]. We assessed sleep duration for all participants based on the following two questions: “On an average, at what time do you go to sleep and at what time do you wake up on weekdays?” and “On an average, at what time do you go to sleep and at what time do you wake up on weekends?” We used the following formula to assess the average number of hours of sleep per week: ([weekday sleep×5]+[weekend sleep×2])/7. Demographic factors such as age and sex, along with social factors including work status, alcohol intake, education, physical activity, and smoking, have been identified as key correlates of depression [27-30]. Data on age, sex, BMI, smoking status, educational attainment, living situation, alcohol consumption, physical activity level, family income-to-poverty ratio (PIR), and PHQ-9 scores were collected from each participant in the NHANES. Several variables were categorized for comparative analysis: living situation (living with a partner vs. living alone), education (college graduate or above vs. high school graduate/GED or less than a 9th-grade education), and smoking status (current vs. never or former). Physical activity levels were classified using scores from the Global Physical Activity Questionnaire (GPAQ) [31].

Statistical analyses

All statistical analyses were conducted using R version 4.3.1 (NHANESR package; PBC formerly RStudio, https://posit.co/). A significance level of 0.05 was set for the analyses. Data for categorical variables is presented as weighted proportions, and data for continuous variables is presented as weighted means. Categorical variables were analyzed using weighted chi-square tests, while continuous variables were analyzed using weighted one-way analysis of variance. Categorical variables are represented by numbers and percentages, and continuous variables are represented by mean±standard deviation. To explore the relationship between weekend CUS and depression, multivariable logistic regression analysis was performed, including CUS and depression, with adjustments for age, sex, education, physical activity, smoking, drinking, living with a partner, PIR, average sleep duration, living status, BMI, race, diabetes, cholesterol, hypertension, and CVD. Model 1 was adjusted for age and sex, while Model 2 included adjustments for education, physical activity, smoking, drinking, PIR, and living status. Model 3 was adjusted for age, sex, and average sleep duration, and Model 4 included adjustments for multiple factors, such as age, sex, education, physical activity, smoking, drinking, PIR, living status, average sleep duration, BMI, race, diabetes, cholesterol, hypertension, and CVD. Additionally, multivariable linear regression analysis was carried out to assess the association between CUS duration and continuous depression severity scores (PHQ-9), after controlling for covariates.

RESULTS

Participants

The participant flow is presented in Figure 1. A total of 9,254 participants were sourced from the NHANES database. Among them, 4,804 participants were excluded, comprising 1,150 non-adults, 2,000 individuals with incomplete sleep duration data, 1,064 participants lacking PHQ-9 scores, and 590 participants reporting less than -1 hour of weekend sleep. Consequently, the final sample size for statistical analysis consisted of 4,450 eligible participants.

Sleep duration on weekdays and weekend, and weekly average sleep duration

Mean sleep duration on weekdays and weekends were 7.5± 1.6 h and 8.4±1.6 h, respectively. Mean weekly average sleep was 7.7±1.5 h (Table 1).

Baseline population characteristics and CUS duration ≤0, >0 to 1, >1 to 2, and >2 h

We categorized participants into four groups based on weekend CUS duration: CUS≤0 h, 0 h<CUS≤1 h, 1 h<CUS≤2 h, and CUS>2 h. There were no statistically significant differences observed in sex, BMI, alcohol consumption, PHQ-9 scores, or number of depressions across the groups. In the CUS≤0 h group, which comprised 2,169 participants, the number of participants was notably higher than in the other groups. Additionally, smoking rates, living status, and PIR indicators were significantly elevated compared to the other groups. Moreover, the prevalence of diabetes, high cholesterol, hypertension, and CVD was higher in this group. Conversely, the CUS>2 h group exhibited a higher PIR, increased physical activity levels, and significantly lower incidence rates of diabetes, high cholesterol, hypertension, and CVD (Table 1).

Depression, CUS, and sleep duration

Differences in the amount of sleep hours between weekdays and weekends, as well as the average weekly sleep duration, varied among the four groups. However, no significant disparities were observed in the number of depressive episodes, PHQ-9 scores, or PHQ-9 scores ≥10 (Table 1).

Multivariable logistic regression analyses association between weekend CUS and risk of depression

In Model 1, adjusted for age and sex, the multivariable adjusted odds ratios (ORs) for depression were 0.78 (95% confidence interval [CI] 0.59-1.04), 0.72 (95% CI 0.51-1.02), and 0.91 (95% CI 0.67-1.24) for individuals with different durations of weekend-CUS: >0 to 1 hour, >1 to 2 hours, and >2 hours, respectively, compared to those with ≤0 hours (Table 2). When further adjusting for education, physical activity, smoking, drinking, PIR, and living status in Model 2 in addition to Model 1, the multivariable adjusted ORs were 0.87 (95% CI 0.63-1.20), 0.80 (95% CI 0.59-1.19), and 0.96 (95% CI 0.67-1.36) for individuals with different CUS durations, as detailed in Table 2. Similarly, in Model 3 (adjusted for average sleep duration in addition to Model 1), the multivariable adjusted ORs of experiencing depression were 0.77 (95% CI 0.59-1.02), 0.71 (95% CI 0.51-0.99), and 0.87 (95% CI 0.65-1.18) for individuals with varying CUS durations compared to those with ≤0 hours. Lastly, in Model 4 (adjusted for BMI, race, diabetes, cholesterol, hypertension, and other CVD factors in addition to Models 2 and 3), the multivariable adjusted ORs for depression were 0.89 (95% CI 0.54-1.48), 0.71 (95% CI 0.37-1.37), and 0.97 (95% CI 0.57-1.65) for different CUS duration groups compared to the reference group with ≤0 hours (Table 2).

Multivariate logistic regression analyses assessing the relationship between weekend CUS and depression under subgroups of weekday sleep duration

Notwithstanding the absence of significant association between weekend CUS and depression in the primary analysis, the potential confounding effects of multiple variables warrant consideration. Specifically, whether weekday sleep duration modulates the potential antidepressant effects of CUS remains indeterminate. To elucidate this interaction, stratified analyses were conducted across prespecified subgroups based on weekday sleep duration patterns. When comparing those with no CUS, those with over 2 hours of CUS had an adjusted OR of 0.58 (95% CI 0.36-0.94), and those with CUS exceeding 2 hours had an OR of 0.47 (95% CI 0.27-0.83), in individuals with weekday sleep duration of 6 hours or less (Table 3). The risk reduction for depression through weekend CUS was notably higher in individuals who slept 6 hours or less on weekdays and had more than 2 hours of CUS on weekends. Weekend CUS resulted in a more significant decline in the risk of depression among those with less than 6 hours of weekday sleep and over 2 hours of CUS on weekends. No statistically significant variances were detected in the association between weekend CUS and the risk of depression in other subgroups.

Association between CUS duration and severity of depression (PHQ-9 score) among individuals with CUS≤0 h, 0 h<CUS≤1 h, 1 h<CUS≤2 h, and CUS>2 h

We conducted multivariate linear regression analyses to examine the association between the duration of chronic unpredictable stress and the severity of depression as measured by the PHQ-9 score, utilizing four models (Table 4). In Model 1, adjusted for age and sex, a significant negative linear correlation was observed between CUS duration and PHQ-9 scores among individuals with CUS durations of 0 to 1 hour and 1 to 2 hours. Conversely, no significant linear relationship was found between individuals with CUS durations ≤0 hours and those with CUS durations >2 hours. This pattern persisted in Model 3. However, in both Model 2 and Model 4, the groups categorized by CUS durations (CUS≤0 h, 0 h<CUS≤1 h, 1 h<CUS≤2 h, and CUS>2 h) did not display a significant linear association with PHQ-9 scores.

DISCUSSION

In this cross-sectional study, we found no evidence that weekend CUS increases depression risk compared to no weekend CUS. However, among participants averaging ≤6 hours of weekday sleep, weekend CUS was associated with reduced depression risk—particularly when exceeding 2 hours.
Prior research has established a strong link between sleep disorders and depression [9]. Conditions such as insomnia, restless legs syndrome, and obstructive sleep apnea elevate depression risk. A recent meta-analysis further indicates that both insufficient and excessive sleep duration increase depression susceptibility [15]. Our findings align with this evidence: participants consistently averaging <6 hours of sleep weekly showed higher depression rates than those maintaining 6-8 hours (Supplementary Table 1). Given epidemiological evidence that weekend CUS prevalence declines with age (particularly ≥60 years), we conducted age-stratified analyses. In the minimally adjusted model (Model 1: sex-adjusted), weekend CUS showed a nominally protective association with depression. However, this association attenuated to non-significance in fully adjusted models (Models 2-4), suggesting residual confounding rather than age-specific effects. The role of age in modifying CUS-depression relationships remains inconclusive, necessitating further investigation via prospective cohorts with longitudinal sleep monitoring (Supplementary Table 2).
The negative health impacts of inadequate sleep duration are well-established, with weekend CUS frequently employed as a compensatory strategy. Among Korean adolescents, one study identified CUS as significantly associated with both suicide attempts and self-injury risk, independent of depression [32]. However, this study did not adjust for sleep duration in its analyses, potentially overlooking that weekend CUS may primarily reflect chronic sleep deprivation. A separate Korean study found that >2 hours of weekend CUS significantly reduced depression risk compared to <0 hours of weekend CUS. This research further examined interactions among chronotype, sleep duration, CUS, sleep environment, sleep deprivation, and school-related factors in a multi-district sample of high school students [21]. Notably, both studies focused exclusively on adolescents, leaving the CUS-depression relationship in adults understudied. Adolescents display distinct sleep patterns from adults, including age-related reductions in total sleep time [33] and delayed circadian rhythm phases that progressively shift during maturation [34]. Consistent with these developmental differences, delayed sleep phase disorder is markedly more prevalent in adolescents than adults [35].
A Korean study was the first to investigate the association between weekend CUS and depression in adults [22]. The research, which analyzed a nationally representative sample of Korean adults, found that individuals with 1-2 hours of CUS had a significantly lower depression risk compared to those with no CUS. In contrast, no significant risk differences were observed among those with either no CUS, 0-1 hour of CUS, or >2 hours of CUS. Additionally, the study identified a linear trend between longer CUS (>2 hours) and higher PHQ-9 scores, while no such trend existed for no CUS, 0-1 hour, or 1-2 hour groups. These findings suggest a non-linear relationship between CUS duration and depression risk. The authors hypothesized that specifically 1-2 hours of weekend CUS might serve as a behavioral adaptation that could mitigate depression risk.
Key findings from this cross-sectional study suggest that weekend CUS is not associated with an increased risk of depression compared to non-practitioners. However, individuals who typically sleep fewer than 6 hours on weekdays may experience reduced depression risk through CUS, particularly when exceeding 2 hours. However, there are several limitations to this study. Firstly, the study did not exclude individuals with ≤-1 hour of CUS on weekends. The disrupted rhythm of individuals with greater CUS on weekends compared to weekday sleep duration may significantly impact the accuracy of the results. Secondly, the study did not conduct subgroup analyses based on average weekday sleep duration to determine potential differences in the risk of depression across different sleep duration groups. Our study excluded individuals with ≤-1 hour of CUS on weekends and also did not perform subgroup analyses on weekday sleep duration. While our findings did not reveal a significant association between CUS and depression, we observed that CUS on weekends was linked to a reduced risk of depression among those with less than 6 hours of average weekday sleep, with a more pronounced reduction in depression risk observed in individuals with over 2 hours of CUS. Multivariate linear regression analyses were conducted using four models to explore the association between the duration of CUS and the severity of depression, as evaluated by the PHQ-9 score (Table 4). In Model 1, upon adjusting for age and sex, a significant negative linear relationship between CUS duration and PHQ-9 scores was observed in individuals with 0 h<CUS≤1 h and 1 h<CUS≤2 h, while there was no significant linear relationship in those with CUS≤ 0 h and CUS>2 h. A similar pattern was seen in Model 3. However, in both Model 2 and Model 4, the four defined groups based on CUS duration did not exhibit a significant linear relationship with PHQ-9 scores.
There are several possible explanations for the non-linear relationship between CUS and depression. First, CUS may compensate for weekday sleep deprivation, though this effect likely varies across populations. For individuals with severe weekday sleep deprivation, weekend CUS may mitigate its negative impacts [36]. However, the threshold for this protective effect remains unclear and warrants confirmation in future cohort studies. Second, while CUS may offset sleep debt, prolonged exposure could lead to adverse outcomes, including circadian rhythm disruption and social jet lag. These conditions are associated with metabolic dysfunction [37], elevated BMI, atherosclerosis [38], and depression [39]. Other factors may also contribute, but limited data prevented a deeper analysis of circadian and social jet lag effects.
The relationship between CUS duration and depression may be influenced by chronotype—a behaviorally expressed circadian preference that regulates sleep-wake timing and daily activity patterns [40]. A meta-analysis of 36 cross-sectional studies found that later sleep timing (e.g., delayed bedtimes) was significantly associated with more severe depressive symptoms [41]. Additionally, longitudinal evidence supports an association between CUS duration and depressive outcomes [42]. Chronotype may further mediate this relationship, as individuals with later chronotypes are more prone to sleep deprivation and thus more likely to engage in weekend CUS. A large-scale, population-based study in South Korea [17] demonstrated that late chronotypes were overrepresented among individuals who practiced CUS compared to those who did not. Unfortunately, our study was unable to further investigate the impact of chronotype on the relationship between CUS and depression due to a lack of available data on chronotype.
There are several limitations to this study. First, the data were obtained from the NHANES database, which evaluated sleep duration using self-reported questionnaires (weekday/weekend) rather than objective measures like polysomnography or actigraphy. While large-scale objective sleep monitoring remains logistically challenging, most epidemiological studies rely on self-reports, which have demonstrated reasonable agreement with actigraphy-derived sleep duration [43]. Second, as a cross-sectional study, this analysis cannot establish causality between CUS and depression. Additionally, depression was assessed via the PHQ-9 questionnaire instead of clinical interviews aligned with DSM-5 criteria, potentially introducing misclassification bias. However, the PHQ-9 is a validated screening tool with high sensitivity and moderate specificity for depression in population-based studies [44]. Finally, key confounders—such as chronotype, circadian disruption, and social jet lag—could not be adjusted for due to data limitations, restricting further exploration of their role in the CUS-depression relationship.
This study has several notable strengths. First, the data were sourced from NHANES, a nationally representative, cross-sectional database that combines interview-based questionnaires with physical examinations, enhancing its reliability and accessibility.
Second, unlike previous studies, we excluded individuals with CUS durations of ≤-1 hour and conducted subgroup analyses for weekday sleep duration, enabling a more precise assessment of CUS’s effects. Although this study did not establish a direct causal link between CUS and depression risk, a key finding emerged: among participants with <6 hours of weekday sleep, CUS was associated with a significantly reduced depression risk. Given inconsistencies in existing literature, future research should prioritize high-quality cohort studies or randomized controlled trials to validate causality.

Conclusions

Weekend CUS was not associated with depression risk in the general adult population. The observed protective effect in sleep-restricted individuals warrants further investigation through prospective studies to evaluate potential causal relationships.

Supplementary Materials

The Supplement is available with this article at https://doi.org/10.30773/pi.2024.0252.
Supplementary Table 1.
Distribution of weekend catch-up sleep and depression in individuals with weekly average sleep time <6 h, 6-8 h, and >8 h per night
pi-2024-0252-Supplementary-Table-1.pdf
Supplementary Table 2.
Age-stratified multivariable-adjusted ORs with 95% CIs for the association between CUS and depression
pi-2024-0252-Supplementary-Table-2.pdf

Notes

Availability of Data and Material

Data from the National Health and Nutrition Survey (2017-2018) is publicly available: [http://cwres.ncu.edu.cn/s/gov/cdc/wwwn/G.https/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2017]. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Wenting Cai. Data curation: Wenting Cai. Formal analysis: Zhonghong Lai. Investigation: Wenting Cai. Methodology: Wenting Cai. Project administration: Ye Luo. Resources: Ye Luo. Software: Wenting Cai, Shan Huang. Supervision: Ye Luo. Validation: Feng Xiao. Visualization: Xueqin Liu. Writing—original draft: Wenting Cai. Writing—review & editing: Ye Luo, Yuxu Zhao.

Funding Statement

None

Acknowledgments

The authors would like to thank the Centers for Disease Control and Prevention (CDC) for conducting NHANES, as well as the participants of the 2017-2018 NHANES cycle for making this research possible.

Figure 1.
Flowchart of the screening of participants for the 2017-2018 NHANES database in the United States. NHANE, National Health and Nutrition Examination Survey; CUS, weekend catch-up sleep; PHQ-9, Patient Health Questionnaire-9.
pi-2024-0252f1.jpg
Table 1.
Baseline characteristics of individuals with CUS duration ≤0 h, 0 h<CUS≤1 h, 1 h<CUS≤2 h, and >2 h
All (N=4,450) CUS≤0 h (N=2,169) 0 h<CUS≤1 h (N=943) 1 h<CUS≤2 h (N=641) CUS>2 h (N=697) p
Age (yr) 50.14±18.38 56.13±18.35 46.34±17.46 43.98±16.05 42.33±15.27 <0.001
 <60 years old 2,807 (63.1) 1,044 (48.1) 673 (71.4) 504 (78.6) 586 (84.1) <0.001
 ≥60 years old 1,643 (36.9) 1,125 (51.9) 270 (28.6) 137 (21.4) 111 (15.9) <0.001
Sex, women 2,283 (51.3) 1,078 (49.7) 509 (54.0) 344 (53.7) 352 (50.5) 0.088
BMI (kg/m2) 29.74±7.42 29.48±7.17 29.80±7.58 29.92±7.54 30.32±7.79 0.088
Smoking <0.001
 Current smoker 751 (16.9) 384 (17.7) 143 (15.2) 98 (15.3) 126 (18.1)
 Former smoker 1,040 (23.4) 598 (27.6) 211 (22.4) 108 (16.8) 123 (17.6)
 Never smoker 2,659 (59.8) 1,187 (54.7) 589 (62.5) 435 (67.9) 448 (64.3)
Education <0.001
 College graduate or above 1,088 (25.7) 524 (24.9) 287 (32.4) 175 (29.4) 102 (15.6)
 High school grad/GED 990 (23.3) 497 (23.6) 182 (20.5) 133 (22.3) 178 (27.2)
 Less than 9th grade 335 (7.9) 163 (7.8) 55 (6.2) 46 (7.7) 71 (10.8)
Drinking 497 (11.2) 250 (11.5) 110 (11.7) 65 (10.1) 72 (10.3) 0.631
Diabetes 876 (35.0) 523 (46.4) 144 (27.5) 100 (26.2) 109 (23.1) <0.001
High cholesterol 2,017 (79.2) 1,168 (85.5) 378 (75.3) 235 (73.2) 236 (65.7) <0.001
Hypertension 2,413 (70.2) 1,352 (78.7) 453 (64.8) 295 (60.5) 313 (58.7) <0.001
CVD 499 (11.7) 347 (16.5) 63 (7.1) 37 (6.2) 52 (7.9) <0.001
Physical activity <0.001
 Moderate 1,383 (31.1) 752 (34.7) 257 (27.3) 184 (28.7) 190 (27.3) <0.001
 Other 1,221 (27.4) 668 (30.8) 235 (24.9) 155 (24.2) 163 (23.4) <0.001
 Vigorous 1,846 (41.5) 749 (34.5) 451 (47.8) 302 (47.1) 344 (49.4) <0.001
Living with partner 380 (9.0) 160 (7.6) 78 (8.8) 64 (10.7) 78 (11.9) <0.001
PIR <0.001
 Low 1,086 (27.8) 561 (29.3) 204 (24.1) 129 (23.3) 192 (32.2)
 Moderate 1,588 (40.6) 802 (41.9) 311 (36.8) 219 (39.5) 256 (43.0)
 High 1,233 (31.6) 549 (28.7) 330 (39.1) 206 (37.2) 148 (24.8)
Weekday sleep duration, per day (hour) 7.5±1.6 7.9±1.6 7.6±1.4 7.2±1.3 6.3±1.5 <0.001
Weekend sleep duration, per day (hour) 8.4±1.6 7.8±1.6 8.4±1.4 9.0±1.3 10.0±1.6 <0.001
Weekly average sleep duration, per day (hour) 7.7±1.5 7.8±1.6 7.8±1.4 7.7±1.3 7.4±1.4 <0.001
Depressive 388 (8.7) 208 (9.6) 73 (7.8) 46 (7.2) 61 (8.8) 0.163
PHQ-9 score 3.18±4.21 3.33±4.37 2.94±3.96 2.91±3.98 3.26±4.22 0.178
PHQ-9 score ≥10 388 (8.7) 208 (9.6) 73 (7.7) 46 (7.2) 61 (8.8) 0.163

Values are presented as mean±standard error or number (%). CUS, weekend catch-up sleep; BMI, body mass index; CVD, adults with cardiovascular disease; PIR, ratio of family income to poverty; PHQ-9, Patient Health Questionnaire-9.

Table 2.
Multivariable adjusted OR (95% CI) for the association between CUS with depression
CUS≤0 h (N=2,169) 0 h<CUS≤1 h (N=943) 1 h<CUS≤2 h (N=641) CUS>2 h (N=697)
Model 1 1 0.78 (0.59 to 1.04) 0.72 (0.51 to 1.02) 0.91 (0.67 to 1.24)
Model 2 1 0.87 (0.63 to 1.20) 0.80 (0.54 to 1.19) 0.96 (0.67 to 1.36)
Model 3 1 0.77 (0.59 to 1.02) 0.71 (0.51 to 0.99) 0.87 (0.65 to 1.18)
Model 4 1 0.89 (0.54 to 1.48) 0.71 (0.37 to 1.37) 0.97 (0.57 to 1.65)

Model 1 adjusted for age and sex; Model 2 adjusted for: age and sex, education, physical activity, smoking, drinking, PIR, living status; Model 3 adjusted for: age and sex, average sleep duration; Model 4 adjust for: age, sex, education, physical activity, smoking, drinking, PIR, living status, average sleep duration, BMI, race, diabets, cholesterol, hypertension, CVD. OR, odds ratio; 95% CI, 95% confidence interval; CUS, weekend catch-up sleep; PIR, ratio of family income to poverty; CVD, cardiovascular disease; BMI, body mass index.

Table 3.
Adjusted multivariate logistic regression analyses assessing the relationship between weekend CUS and depression under subgroups of weekday sleep duration
Weekend catch-up sleep Depressive (aOR [95% CI]) p
Complete sample
 CUS≤0 h Reference
 CUS>0 h 0.87 (0.59 to 1.29) 0.4905
 0 h<CUS≤1 h 0.79 (0.60 to 1.04) 0.0989
 1 h<CUS≤2 h 0.73 (0.52 to 1.02) 0.0621
 CUS>2 h 0.90 (0.67 to 1.22) 0.5095
Weekday sleep≤6 h
 CUS≤0 h Reference
 CUS>0 h 0.58 (0.36 to 0.94) 0.0254
 0 h<CUS≤1 h 0.85 (0.44 to 1.63) 0.6292
 1 h<CUS≤2 h 0.60 (0.30 to 1.20) 0.1477
 CUS>2 h (N=697) 0.47 (0.27 to 0.83) 0.0093
6 h<Weekday sleep≤7 h
 CUS≤0 h Reference
 CUS>0 h 0.89 (0.54 to 1.46) 0.6462
 0 h<CUS≤1 h 0.91 (0.50 to 1.66) 0.7531
 1 h<CUS≤2 h 0.78 (0.38 to 1.63) 0.5153
 CUS>2 h 0.97 (0.50 to 1.90) 0.9278
7 h<Weekday sleep≤8 h
 CUS≤0 h Reference
 CUS>0 h 1.13 (0.68 to 1.85) 0.6441
 0 h<CUS≤1 h 1.09 (0.59 to 2.00) 0.7848
 1 h<CUS≤2 h 1.11 (0.56 to 2.18) 0.7638
 CUS>2 h 1.25 (0.55 to 2.81) 0.5949
Weekday sleep>8 h
 CUS≤0 h Reference
 CUS>0 h 0.90 (0.57 to 1.43) 0.6614
 0 h<CUS≤1 h 0.72 (0.40 to 1.29) 0.2677
 1 h<CUS≤2 h 0.95 (0.41 to 2.21) 0.9130
 CUS>2 h 1.74 (0.75 to 4.02) 0.1942

Adjust for: age, sex, education, physical activity, smoking, drinking, PIR, living status, average sleep duration, BMI, race, diabets, cholesterol, hypertension, CVD. CUS, catch-up sleep; aOR, adjusted odd ratio; CI, confidence interval; PIR, ratio of family income to poverty; BMI, body mass index; CVD, adults with cardiovascular disease.

Table 4.
Association between CUS duration and severity of depression (PHQ-9 score) among individuals with CUS≤0 h, 0 h<CUS≤1 h, 1 h<CUS ≤2 h, and CUS>2 h
CUS≤0 h
0 h<CUS≤1 h
1 h<CUS≤2 h
CUS>2 h
β 95% CI p β 95% CI p β 95% CI p β 95% CI p
Model 1 -0.10 -0.21 to 0.02 0.103 -0.48 -0.81 to -0.16 0.004 -0.52 -0.90 to -0.14 0.007 -0.15 -0.52 to 0.22 0.427
Model 2 -0.08 -0.20 to 0.04 0.198 -0.26 -0.61 to 0.08 0.131 -0.38 -0.79 to 0.02 0.062 -0.14 -0.54 to 0.25 0.062
Model 3 -0.10 -0.21 to 0.02 0.103 -0.44 -0.76 to -0.12 0.007 -0.49 -0.86 to -0.02 0.009 -0.15 -0.51 to 0.21 0.420
Model 4 -0.08 -0.20 to 0.04 0.198 -0.29 -0.76 to 0.18 0.223 -0.45 -0.99 to 0.1 0.107 -0.18 -0.69 to 0.33 0.484

Model 1 adjusted for age and sex; Model 2 adjusted for: age and sex, education, physical activity, smoking, drinking, PIR, living status; Model 3 adjusted for: age and sex, average sleep duration; Model 4 adjust for: age, sex, education, physical activity, smoking, drinking, PIR, living status, average sleep duration, BMI, race, diabets, cholesterol, hypertension, CVD. CUS, catch-up sleep; PHQ-9, Patient Health Questionnaire-9; CI, confidence interval; PIR, ratio of family income to poverty; BMI, body mass index; CVD, adults with cardiovascular disease.

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