Optimal Sleep Durations for Depression Prevention: Evidence from the China Family Panel Studies

Optimal Sleep Durations for Depression Prevention: Evidence from the China Family Panel Studies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimal Sleep Durations for Depression Prevention: Evidence from the China Family Panel Studies Yanliqing Song, Lin Chen, Haoqiang Liu, Yue Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5460471/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To explore the relationship between nap time, nighttime sleep, and depression among Chinese residents, and to determine recommended sleep durations to provide scientific and reasonable evidence for the prevention and control of depression among residents. Methods Based on the 2020 China Family Panel Studies (CFPS), demographic data, health, and lifestyle information of the study subjects were obtained. A total of 6795 valid samples were included. Logistic regression, restricted cubic splines, and subgroup analysis were used to explore the relationship between sleep and depression. Results Compared to participants with nighttime sleep < 7 hours, those with nighttime sleep ≥ 7 hours were found to have a protective factor against the likelihood of depression. Compared to participants without a napping habit, those with nap times of 30–90 minutes were found to have a protective factor against the likelihood of depression. There was a U-shaped dose-response relationship between nighttime sleep and depressive symptoms (P-nonlinear < 0.001), with the likelihood of depression decreasing from 7.5 hours of sleep to about 8.5 hours, and the lowest likelihood of depression occurring around 8.5 hours of sleep. There was no nonlinear relationship between nap time and depression (P-nonlinear = 0.889). This study revealed a U-shaped dose-response relationship between nighttime sleep and depressive symptoms. Specifically, the probability of depressive symptoms significantly decreased when nighttime sleep increased from 7.5 hours to 8.5 hours. Subgroup analysis further showed that in all subgroups, individuals with self-rated general health or chronic diseases had a protective effect against the likelihood of depression if their sleep duration was 7–9 hours. The effect of nap time of 30–90 minutes on depression did not differ between baseline or demographic factors. Conclusion There is a U-shaped relationship between nighttime sleep and depressive symptoms among Chinese residents. Nighttime sleep of 7–9 hours is only associated with the likelihood of depression in certain subgroups, while appropriate nap time has a general preventive effect on depression for all participants. Considering the importance of both nighttime sleep and nap time in preventing depressive symptoms, it is essential to reasonably arrange sleep durations. COVID-19 Pandemic Depression Nap Time Nighttime Sleep Health promotion Figures Figure 1 Introduction Depression is a widespread mental health disorder, affecting an estimated 280 million people globally[ 1 ]. It is one of the leading causes of disability, making the prevention and intervention strategies for depression a pressing focus in the field of global public health. Notably, the prevalence of depression is not limited to middle-aged and elderly populations; its incidence among young adults is also significant[ 2 ]. A survey conducted in the United States revealed that the prevalence of depressive symptoms among college students is as high as 85%, highlighting the severity and urgency of this issue, which requires more attention and research[ 3 ]. During the COVID-19 pandemic, the global burden of depression has significantly increased. According to the latest data, the number of severe depression cases worldwide has risen by 52.3 million, an increase of 27.6%[ 4 ]. In the 204 countries and regions involved, the incidence of severe depression has risen to 3152.9 cases per 100,000 people[ 5 ]. Stress factors during the pandemic, including unemployment, the death of loved ones, social isolation, and the compound effects of multiple stressors, have had a severe negative impact on global mental health[ 6 ]. In the United States, the prevalence of depressive symptoms during COVID-19 has tripled compared to pre-pandemic levels[ 7 ]. With the daily addition of hundreds of thousands of new COVID-19 cases, the pandemic has had a profound impact on human diet, daily outdoor activities, and overall lifestyle habits[ 8 ]. To control the pandemic, the public has been advised to avoid crowded public places such as playgrounds, basketball courts, and football fields, inevitably leading to reduced opportunities for physical exercise. Existing research has clearly indicated a close link between the frequency of physical exercise and the incidence of anxiety and depressive symptoms[ 9 ]. As the number of new COVID-19 cases continues to rise, measures such as lockdowns and restrictions on population movement have become necessary to control the spread of the pandemic. However, these measures restricting personal freedom may exacerbate mental stress[ 10 ]. Studies have pointed out that an individual’s geographical proximity to disaster events and the degree of personal impact experienced during natural disasters or epidemics may affect post-event mental health recovery. The impact of economic and social changes on mental health may be delayed[ 11 ]. Although direct exposure to the COVID-19 virus does not have a significant direct impact on mental health symptoms, the increase in COVID-19-related occupational and social barriers may, over time, lead to significant changes in mental health, particularly in terms of social, work-related barriers, and economic difficulties[ 12 ]. Therefore, from a public health perspective, understanding and identifying modifiable risk factors for depression is crucial for developing effective prevention and intervention strategies. Depression, as a complex mental disorder, is believed to be determined by the interaction of genetic and environmental factors, as well as the interplay between genes and the environment[ 13 ]. Additionally, lifestyle significantly impacts its occurrence[ 14 ]. Sleep, as an important dimension of health, has increasingly gained prominence in recent academic research. Studies have indicated that sleep duration is significantly correlated with overall mortality, cardiovascular diseases, and the incidence of chronic conditions such as metabolic syndrome[ 15 – 16 ]. Insufficient sleep duration and quality are considered key influencing factors for mental health disorders. The association between sleep, as a modifiable lifestyle factor, and depression has been examined in numerous studies[ 17 – 18 ]. Researchers have extensively explored the role of sleep duration in the development of depression. A prospective study found that both short and long sleep durations are significantly associated with an increased risk of depression in adults[ 19 ]. Further research supports this view, suggesting that insufficient or excessive sleep may increase the incidence of depression[ 20 ]. However, it should be noted that the data collection for these studies was completed before the outbreak of the COVID-19 pandemic. Therefore, in this study, we analyzed the latest CFPS data obtained during the COVID-19 pandemic. We chose this dataset because it best represents the characteristics of depression among Chinese residents at this stage. The aim is to explore the relationship between nap time, nighttime sleep, and depression among residents, and to determine recommended sleep durations. This provides scientific and reasonable evidence for the prevention and treatment of depression among residents. Methods Study population The China Family Panel Studies (CFPS) is a nationwide comprehensive project aimed at collecting individual, family, and community data through biennial follow-up surveys to reflect changes in China’s socioeconomic, demographic, educational, and health fields. The data for this study were derived from the 2020 CFPS project. The project employed computer-assisted survey techniques to meet diverse design needs, improve survey efficiency, and ensure data quality. Samples with missing demographic variables and missing Center for Epidemiologic Studies Depression Scale scores were excluded. Ultimately, 6795 samples were included in this study. Outcome Nighttime sleep was assessed based on the following question: “Excluding nap time, how many hours do you usually sleep each day on average, representing a typical workday and rest day?” Previous studies on sleep duration have revealed the benefits of 7–9 hours of sleep [ 21 ]. Participants were categorized into three types of sleep duration: short nighttime sleep ( 9 h). Nap time was assessed based on the following question: “How many minutes do you usually nap?” Participants were categorized into four groups: no nap (0 min), short nap ( 90 min). These cut-points were selected with reference to epidemiological literature on daytime napping[ 22 ]. Explanatory variable Depression: The Center for Epidemiologic Studies Depression Scale (CESD) was used to measure depression. This scale, developed by Radloff at the National Institute of Mental Health, has been widely used to assess depression levels[ 23 ]. The CFPS2020 used the 8-item version of the CESD, which includes the following items: “I felt depressed, I found it hard to do anything, my sleep was poor, I felt happy, I felt lonely, I enjoyed life, I felt sad, I felt that life was not worth living.” Responses were scored as “0 = rarely or never, 1 = not often, 2 = sometimes or half the time, 3 = most of the time” (reverse-scored items were transposed). The scores of the 8 items were summed, with a range of 5–24. Higher total scores indicate a higher risk of depression, with scores ≥ 9 indicating clinically significant depressive symptoms[ 24 ]. The CESD-8 is an effective and reliable tool for assessing depressive symptoms in adults[ 25 ]. We examined the reliability coefficient of the CESD-8 scale, and the results showed that Cronbach’s alpha was greater than 0.7, indicating good internal consistency of the scale. Other covariates The analysis included a set of potential confounding variables. For sociodemographic data, we selected variables including age, gender (female or male), education level (illiterate, primary school, middle school, or high school and above), region (urban, rural), and marital status (married, single). Lifestyle factors included smoking (yes or no), drinking (yes or no), and frequency of physical activity (0 times a week, 1–2 times a week, 3–4 times a week, 5–6 times a week, or every day). Health status included health self-assessment (bad, fair, or good) and chronic disease (no, yes). 2.5 Statistical Methods Statistical analyses were performed using R 4.2 software. Qualitative data were expressed as frequencies and percentages (%), and comparisons between groups were made using the χ2 test or Fisher’s exact test. Quantitative data conforming to a normal distribution were expressed as mean ± standard deviation (x ± s), and comparisons between groups were made using the t-test. Logistic regression models were constructed with nap time and nighttime sleep as reference groups. The variance inflation factor (VIF) was used to measure multicollinearity among the independent variables, and the Box-Tidwell method was used to test the linear relationship between continuous independent variables and the logit of depression. Model 1 included participants’ nighttime and nap times, Model 2 controlled for demographic variables, and Model 3 included all covariates. Restricted cubic spline plots were drawn to explore the dose-response relationship between participants’ sleep duration and depression. Stratified logistic regression analysis and interaction effect analysis were used to determine whether the association between sleep duration and depression depended on baseline or demographic factors. P-values were used for two-sided tests, and P < 0.05 was considered statistically significant. Results Participant characteristics The valid sample consisted of 6795 participants, of which 3411 were female (50.20%). The average age was 31.80 ± 8.67 years, and 5834 participants (85.8%) exhibited depressive symptoms. Differences in nap sleep time, nighttime sleep, region, level of education, health self-assessment, chronic disease, and frequency of physical activity were statistically significant (P < 0.05). Specific basic characteristics are shown in Table 1 . Table 1 Basic characteristics of study participants(n = 5834) Variables Total (n = 6795) Normal (n = 961) Depression (n = 5834) Statistic P Age, Mean ± SD 31.80 ± 8.67 31.75 ± 9.62 31.81 ± 8.51 t=-0.19 0.852 Nap Duration, M (Q₁, Q₃) 20.00 (0.00, 60.00) 30.00 (0.00, 60.00) 20.00 (0.00, 60.00) Z=-2.62 0.009 Nighttime sleep, Mean ± SD 7.59 ± 1.22 7.73 ± 1.12 7.56 ± 1.23 t = 4.27 < .001 Depression, Mean ± SD 13.53 ± 4.01 8.13 ± 2.46 14.42 ± 3.48 t=-68.68 < .001 Gender, n(%) χ²=3.64 0.056 female 3411 (50.20) 455 (47.35) 2956 (50.67) male 3384 (49.80) 506 (52.65) 2878 (49.33) Region, n(%) - < .001 countryside 5425 (79.84) 704 (73.26) 4721 (80.92) city 1370 (20.16) 257 (26.74) 1113 (19.08) Level of education n(%) χ²=15.83 0.001 illiterate 423 (6.23) 42 (4.37) 381 (6.53) elementary school 888 (13.07) 112 (11.65) 776 (13.30) Junior high school 2893 (42.58) 393 (40.89) 2500 (42.85) high school and above 2591 (38.13) 414 (43.08) 2177 (37.32) Marital status, n(%) χ²=0.09 0.760 single 2001 (29.45) 287 (29.86) 1714 (29.38) married 4794 (70.55) 674 (70.14) 4120 (70.62) Health self-assessment, n(%) χ²=102.73 < .001 bad 2834 (41.71) 530 (55.15) 2304 (39.49) fair 3097 (45.58) 377 (39.23) 2720 (46.62) good 864 (12.72) 54 (5.62) 810 (13.88) Chronic disease, n(%) χ²=14.18 < .001 No 6405 (94.26) 931 (96.88) 5474 (93.83) yes 390 (5.74) 30 (3.12) 360 (6.17) Frequency of physical activity, n(%) χ²=14.62 0.006 0 times a week 5058 (74.44) 673 (70.03) 4385 (75.16) 1 ~ 2 times a week 689 (10.14) 116 (12.07) 573 (9.82) 3 ~ 4 times a week 376 (5.53) 53 (5.52) 323 (5.54) 5 ~ 6 times a week 52 (0.77) 11 (1.14) 41 (0.70) every day 620 (9.12) 108 (11.24) 512 (8.78) Smoking, n(%) χ²=0.18 0.672 no 4911 (72.27) 700 (72.84) 4211 (72.18) yes 1884 (27.73) 261 (27.16) 1623 (27.82) Drink, n(%) χ²=0.65 0.420 no 6061 (89.20) 850 (88.45) 5211 (89.32) yes 734 (10.80) 111 (11.55) 623 (10.68) Nighttime sleep, n(%) χ²=18.40 < .001 9 h 1015 (14.94) 159 (16.55) 856 (14.67) Nap sleep time, n(%) χ²=8.49 0.037 0 min 3230 (47.53) 430 (44.75) 2800 (47.99) 90 min 551 (8.11) 89 (9.26) 462 (7.92) Note: t: t-test, Z: Mann-Whitney test, χ²: Chi-square test. M: Median, Q₁: 1st Quartile, Q₃: 3st Quartile. SD: standard deviat. Logistic regression of the relationship between sleep duration and depression For the diagnosis of multicollinearity, we eliminated variables with VIF values greater than 10 to avoid multicollinearity. The Box-Tidwell test results showed that the continuous independent variables (nighttime sleep, nap sleep time) had a linear relationship with the dependent variable (depression) (P >0.05). The results of the logistic regression model analysis showed that, after controlling for all covariates in Model 3, participants with nighttime sleep ≥7 hours were found to have a protective factor against the likelihood of depression compared to those with nighttime sleep <7 hours. Compared to participants without a napping habit, those with nap times of 30-90 minutes were found to have a protective factor against the likelihood of depression (Table 2). Dose–response relationship between nighttime sleep and depression The dose-response relationship analysis between nighttime sleep and depression indicated a U-shaped relationship (P-nonlinear <0.001), with the likelihood of depression decreasing from 7.5 hours of sleep to about 8.5 hours (Figure 1). The lowest likelihood of depression was observed when participants had around 8.5 hours of sleep. The dose-response relationship analysis between nap sleep time and depression indicated no nonlinear relationship (P-nonlinear = 0.889) (Figure 1). 2.4 Subgroup Analysis of the Impact of Sleep Duration on Depression Stratified logistic regression analysis and interaction effect analysis were used to determine whether the association between sleep duration and depression depended on baseline or demographic factors. The association between nighttime sleep of 7–9 hours and depression showed an interaction with health self-assessment and chronic disease (interaction P-values < 0.05). This indicates that for individuals with general health self-assessment or chronic diseases, a sleep duration of 7–9 hours may have a protective effect against the likelihood of depression. Nighttime sleep of 7–9 hours was only associated with the likelihood of depression in certain subgroups. The association between nap time of 30–90 minutes and depression showed no interaction with region, level of education, health self-assessment, chronic disease, and frequency of physical activity (interaction P-values > 0.05). The impact of nap time of 30–90 minutes on depression did not differ between baseline or demographic factors. This indicates that the association between appropriate nap time and the risk of depression is consistent across all stratified subgroups (all interaction P-values > 0.05). Table 3 Subgroup Analysis of the Impact of Nighttime Sleep on Depression Variables n (%) Normal Depression OR (95%CI) P P for interaction All patients 6795 (100.00) 1839/2108 3995/4687 0.84 (0.73 ~ 0.98) 0.028 Region 0.351 countryside 5425 (79.84) 1476/1677 3245/3748 0.88 (0.74 ~ 1.05) 0.146 city 1370 (20.16) 363/431 750/939 0.74 (0.55 ~ 1.01) 0.056 Level of education 0.585 illiterate 423 (6.23) 148/167 233/256 1.30 (0.68 ~ 2.47) 0.422 elementary school 888 (13.07) 279/317 497/571 0.91 (0.60 ~ 1.39) 0.676 Junior high school 2893 (42.58) 784/894 1716/1999 0.85 (0.67 ~ 1.08) 0.179 high school and above 2591 (38.13) 628/730 1549/1861 0.81 (0.63 ~ 1.03) 0.081 Health self-assessment 0.015 bad 2834 (41.71) 693/854 1611/1980 1.01 (0.83 ~ 1.25) 0.892 fair 3097 (45.58) 838/923 1882/2174 0.65 (0.51 ~ 0.84) 0.001 good 864 (12.72) 308/331 502/533 1.21 (0.69 ~ 2.11) 0.504 Chronic disease 0.040 No 6405 (94.26) 1698/1962 3776/4443 0.88 (0.75 ~ 1.03) 0.103 yes 390 (5.74) 141/146 219/244 0.31 (0.12 ~ 0.83) 0.020 Frequency of physical activity 0.628 0 times a week 5058 (74.44) 1415/1605 2970/3453 0.83 (0.69 ~ 0.99) 0.036 1 ~ 2 times a week 689 (10.14) 172/201 401/488 0.78 (0.49 ~ 1.23) 0.279 3 ~ 4 times a week 376 (5.53) 88/99 235/277 0.70 (0.34 ~ 1.42) 0.322 5 ~ 6 times a week 52 (0.77) 11/14 30/38 1.02 (0.23 ~ 4.57) 0.977 every day 620 (9.12) 153/189 359/431 1.17 (0.75 ~ 1.83) 0.479 OR: Odds Ratio, CI: Confidence Interval Table 4 Subgroup Analysis of the Impact of Nap Time on Depression Variables n (%) Normal Depression OR (95%CI) P P for interaction All patients 6795 (100.00) 4162/4814 1672/1981 0.85 (0.73 ~ 0.98) 0.027 Region 0.810 countryside 5425 (79.84) 3362/3840 1359/1585 0.85 (0.72 ~ 1.01) 0.071 city 1370 (20.16) 800/974 313/396 0.82 (0.61 ~ 1.10) 0.184 Level of education 0.271 illiterate 423 (6.23) 296/328 85/95 0.92 (0.43 ~ 1.95) 0.825 elementary school 888 (13.07) 577/647 199/241 0.57 (0.38 ~ 0.87) 0.009 Junior high school 2893 (42.58) 1761/2029 739/864 0.90 (0.72 ~ 1.13) 0.366 high school and above 2591 (38.13) 1528/1810 649/781 0.91 (0.72 ~ 1.14) 0.400 Health self-assessment 0.384 bad 2834 (41.71) 1649/2006 655/828 0.82 (0.67 ~ 1.00) 0.055 fair 3097 (45.58) 1920/2181 800/916 0.94 (0.74 ~ 1.18) 0.588 good 864 (12.72) 593/627 217/237 0.62 (0.35 ~ 1.10) 0.105 Chronic disease 0.623 No 6405 (94.26) 3935/4568 1539/1837 0.83 (0.72 ~ 0.96) 0.015 yes 390 (5.74) 227/246 133/144 1.01 (0.47 ~ 2.19) 0.976 Frequency of physical activity 0.381 0 times a week 5058 (74.44) 3218/3685 1167/1373 0.82 (0.69 ~ 0.98) 0.030 1 ~ 2 times a week 689 (10.14) 396/471 177/218 0.82 (0.54 ~ 1.24) 0.347 3 ~ 4 times a week 376 (5.53) 208/239 115/137 0.78 (0.43 ~ 1.41) 0.408 5 ~ 6 times a week 52 (0.77) 26/32 15/20 0.69 (0.18 ~ 2.66) 0.592 every day 620 (9.12) 314/387 198/233 1.32 (0.85 ~ 2.04) 0.223 OR: Odds Ratio, CI: Confidence Interval Discussion This study revealed a U-shaped dose-response relationship between nighttime sleep and depressive symptoms. Specifically, the probability of depressive symptoms significantly decreased when nighttime sleep increased from 7.5 hours to 8.5 hours. A cross-sectional study involving 1,788 American adults (aged 19–89 years) showed a U-shaped association between sleep duration and depressive symptoms[ 26 ]. Compared to those with nighttime sleep less than 6 hours, individuals with sufficient nighttime sleep (not less than 6 hours) had a lower risk of depression. A study conducted in southwestern China involving 44,900 Han adults aged 30–79 years explored the relationship between nighttime sleep, insomnia symptoms, and depressive symptoms. After adjusting for multiple variables, the study found that participants with nighttime sleep less than 7 hours had a higher odds ratio for depression (OR: 1.47, 95% CI: 1.31–1.65) compared to those with nighttime sleep in the range of 7–8 hours. However, no significant association was found between nighttime sleep exceeding 9 hours and depressive symptoms in the overall population analysis or subgroup analysis[ 27 ]. Other studies also support that there is no clear association between long sleep duration and depression[ 28 ]. A meta-analysis of seven prospective studies showed a significant association between short sleep duration and the risk of depression, with a risk ratio of 1.31 compared to normal sleep duration[ 29 ]. Additionally, some cross-sectional studies have found that both short sleep duration (≤ 6 hours) and long sleep duration (≥ 9 hours) are associated with an increased risk of depressive symptoms[ 30 ]. The inconsistency in the relationship between nighttime sleep and depressive symptoms may be attributed to several potential reasons: (1) Different methods were used in various studies to adjust for potential confounding factors, which may lead to biased results. (2) The definition of sleep duration varied across studies, which may affect the comparability of results. (3) The age distribution of study subjects differed, which may influence the observation of the relationship between sleep duration and depressive symptoms. (4) The proportion of participants with long sleep duration was relatively low (14.94%), which may result in insufficient statistical power to accurately assess the relationship between long sleep duration and depressive symptoms. (5) There is a potential bidirectional relationship between depression and sleep, which may cause differences in results between prospective cohort studies and cross-sectional studies. (6) Urban-rural differences and socioeconomic status (SES) disparities may significantly impact the pathogenesis of depression. Since both sleep and depression are associated with specific health behaviors and SES, these factors may confound the association between sleep and depression. For example, previous studies have shown that long sleep duration is associated with lower socioeconomic status, lower levels of physical activity, and obesity, all of which are risk factors for depression[ 31 ]. Therefore, when interpreting the relationship between sleep duration and depressive symptoms, these potential confounding variables must be considered. This study also found that participants with nap times of 30 to 90 minutes exhibited a lower likelihood of depression, supporting the potential role of napping in mood regulation. Previous studies have similarly indicated that short daytime naps are not significantly associated with depressive symptoms; however, excessively long nap times have been identified as an independent risk factor for depression[ 32 ]. Specifically, compared to moderate nappers, long nappers had a significantly higher incidence of depressive symptoms (OR = 1.32, 95% CI: 1.19–1.45) [ 33 ]. This finding underscores the importance of nap duration in mental health and suggests that appropriate nap times may have a protective effect on emotional health. There are several possible explanatory mechanisms for the link between sleep status and depressive symptoms. First, insufficient sleep may lead to daytime fatigue, which in turn causes excessive daytime sleepiness and disruption of circadian rhythms, factors that may increase the risk of depressive symptoms. Individuals with shorter sleep durations may experience insufficient rest and increased perceived stress, which has been identified as a risk factor for depressive symptoms [ 34 ]. Second, inflammation is a key correlate of depression. Studies have shown that short sleep duration and insomnia symptoms are associated with elevated levels of inflammatory cytokines such as C-reactive protein (CRP) and interleukin-6 (IL-6) [ 35 ]. Increasing evidence indicates that both short and long sleep durations are associated with elevated levels of inflammation, a phenomenon particularly evident in individuals with depression[ 36 ]. Chronic low-grade inflammation may be an important biological pathway linking sleep and depressive symptoms. It is noteworthy that inflammation is not only associated with depression and stress disorders but also plays a crucial role in their pathophysiology[ 37 ]. Increased inflammation may promote the activation of the kynurenine pathway, reducing serotonin levels, which is closely related to the pathophysiological mechanisms of depression[ 38 ]. Additionally, sleep quality and duration may influence the composition of the gut microbiota[ 39 ]. The microbiota-gut-brain axis is an interactive system that may affect various neurological diseases[ 40 ]. Studies have shown that sleep disorders may alter the levels of brain-derived neurotrophic factor (BDNF), which plays a key role in the pathophysiology of stress-related mood disorders[ 41 ]. The hypothalamic-pituitary-adrenal (HPA) axis is an important pathway for understanding the neurobiology of stress responses[ 42 ]. Corticotropin-releasing hormone (CRH) released by the hypothalamus stimulates the anterior pituitary to secrete adrenocorticotropic hormone (ACTH), which in turn promotes the adrenal cortex to release cortisol into the bloodstream, activating the HPA axis[ 43 ]. Conversely, sleep has a regulatory effect on the HPA axis. Therefore, a decline in sleep quality may enhance the stress reactivity of the HPA axis. Furthermore, adequate sleep helps to elevate melatonin levels, a molecule with multifaceted regulatory functions that can alleviate depressive symptoms. Finally, research on sleep and the immune system suggests that sleep can optimize immune defense, and immune cell signaling may induce sleep. Immune activation and cytokines may play a role in the occurrence of depressive symptoms in certain individuals. These findings underscore the important role of sleep in maintaining mental health and preventing depressive symptoms. In this study, we conducted a subgroup analysis of the relationship between sleep duration and depression to explore whether this association is influenced by baseline or demographic factors. Stratified logistic regression analysis and interaction effect analysis revealed a significant interaction between nighttime sleep of 7–9 hours and depression, particularly related to health self-assessment and chronic disease status. Specifically, for individuals with general health self-assessment or chronic diseases, maintaining 7–9 hours of nighttime sleep may have a protective effect, reducing the risk of depression. Previous studies using quantile regression, including 55,954 adults aged 18 to 80 from the National Health and Nutrition Examination Survey (N = 34,156) and the Korea National Health and Nutrition Examination Survey (N = 21,798), found that the association between short sleep duration and depression was stronger in individuals with chronic diseases[ 44 ]. The association between short sleep duration and depression is modified by chronic diseases. Sleep problems, chronic diseases, and depression are interrelated, with each increasing the risk of occurrence and worsening of the others. A review indicated that alterations in mesolimbic dopaminergic function are neurobiological factors associated with sleep problems, chronic diseases, and depression[ 45 ]. However, the exact nature of these associations remains to be elucidated. Further research is needed to clarify the underlying physiological mechanisms between sleep, depression, and chronic diseases. This finding suggests that the role of sleep duration in preventing depression may vary depending on an individual’s health status, emphasizing the importance of considering individual differences in clinical practice. Notably, the association between nighttime sleep of 7–9 hours and the likelihood of depression was significant only in certain subgroups, indicating that the impact of sleep on mental health is not universally applicable but is influenced by specific demographic characteristics. Therefore, future research and intervention strategies should consider the particularities of these subgroups to more effectively prevent and treat depression. On the other hand, this study also found that the association between nap time of 30–90 minutes and the risk of depression showed no interaction across subgroups of different regions, education levels, health self-assessment, chronic disease status, and frequency of physical activity. This means that the beneficial effect of appropriate nap time on reducing the risk of depression is consistent across different demographic characteristics and is not influenced by these factors. This finding supports the notion of napping as a universally beneficial health behavior and provides a theoretical basis for future sleep interventions. These findings offer new directions for future research, suggesting that sleep interventions should consider individual differences in health status and sleep habits. Additionally, public health strategies should promote appropriate sleep habits to reduce the incidence of depression. Despite providing valuable insights, this study has some limitations. First, due to the cross-sectional nature of the study design, we cannot determine the causal relationship between sleep duration and depressive symptoms. Future research should adopt longitudinal designs to explore the temporal relationship between sleep and depressive symptoms. Second, our study relies on self-reported sleep data, which may be subject to subjective bias. Future research could consider incorporating objective sleep monitoring techniques, such as polysomnography or wearable devices, to improve data accuracy. Additionally, this study did not account for individual differences, such as genetic factors, life events, and personality traits, which may influence the relationship between sleep and depressive symptoms. Future research should explore these potential mediating or moderating variables. Conclusion In summary, this study revealed the complex relationship between nighttime sleep and nap time and depressive symptoms, providing new evidence for the role of sleep in mental health. There is a U-shaped relationship between nighttime sleep and depressive symptoms among Chinese residents. Nighttime sleep of 7–9 hours is only associated with the likelihood of depression in certain subgroups, while appropriate nap time has a general preventive effect on depression for all participants. Considering the importance of both nighttime sleep and nap time in preventing depressive symptoms, it is essential to reasonably arrange sleep durations. Declarations Acknowledgments: The authors would like to thank China Social Science Survey Center (ISSS) at Peking University for providing the CFPS data Funding: This project is supported by the Foundation project（Supported by research project of Shanghai University of Sport(2023STD015), Ministry of Education Project of Humanities and Social Sciences for young scholars (22YJC890027). Authors' contributions: SYLQ conceived the study, participated in its design and coordination, and critically revised the manuscript. SYLQ had full access to all the data collection, analysis, and interpretation, and drafted the manuscript. CL and LHQ contributed to the process of data collection and data analyses as study investigators. All authors approved the final manuscript.LY are the guarantors. All authors had full access to all the data in the study, and the corresponding authors had final responsibility for the decision to submit for publication. The corresponding author (LY) attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: no support from any organization for the submitted work; no financial relationships with any organization that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. Ethics approval The CFPS project was approved by the Biomedical Ethics Committee of Peking University, approval number: IRB00001052-14010. Additionally, before the survey began, researchers first obtained informed consent from the subjects in written form. Therefore, at the start of this study, all data were completely anonymous. Data sharing: The acquisition of the data is a public database, and the link is: https://www.isss.pku.edu.cn/cfps/sjzx/gksj/index.htm Disclosure statement: No potential conflict of interest was reported by the authors. Provenance and peer review: Not commissioned; externally peer reviewed. References World Health Organization. 2023. Depressive disorder (depression). https://www.who.int/news-room/fact-sheets/detail/depression (Accessed 5 January 2024). Bayram N, Bilgel N. The prevalence and socio-demographic correlations of depression, anxiety and stress among a group of university students. 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Sleep Med. 2018;52:221–9. Epub 2018 Mar 31. PMID: 29861378. Chaput JP, Dutil C, Sampasa-Kanyinga H. Sleeping hours: what is the ideal number and how does age impact this? Nat Sci Sleep. 2018;10:421–30. 10.2147/NSS.S163071 . PMID: 30568521; PMCID: PMC6267703. Li J, Cacchione PZ, Hodgson N, Riegel B, Keenan BT, Scharf MT, et al. Afternoon Napping and Cognition in Chinese Older Adults: Findings from the China Health and Retirement Longitudinal Study Baseline Assessment. J Am Geriatr Soc. 2017;65(2):373–80. 10.1111/jgs.14368 . Radloff LS, Scale A. Self-Report Depression Scale for Research in the General. Population[J] Appl Psychol Meas. 1977;1(3):385–401. 10.1177/014662167700100306 . Wu Y, Su B, Chen C, Zhao Y, Zhong P, Zheng X. Urban-rural disparities in the prevalence and trends of depressive symptoms among Chinese elderly and their associated factors. J Affect Disord. 2023;340:258–68. Epub 2023 Aug 2. PMID: 37536424. Briggs R, Carey D, O'Halloran AM, Kenny RA, Kennelly SP. Validation of the 8-item Centre for Epidemiological Studies Depression Scale in a cohort of community-dwelling older people: data from The Irish Longitudinal Study on Ageing (TILDA). Eur Geriatr Med. 2018;9(1):121–126. 10.1007/s41999-017-0016-0 . Epub 2018 Jan 3. PMID: 34654281. Watson NF, Harden KP, Buchwald D, Vitiello MV, Pack AI, Strachan E, Goldberg J. Sleep duration and depressive symptoms: a gene-environment interaction. Sleep. 2014;37(2):351–8. 10.5665/sleep.3412 . PMID: 24497663; PMCID: PMC3900629. Gao Y, Tang W, Mao D, Chen L, Ding X. Association between Nocturnal Sleep Duration and Insomnia symptoms with depressive symptoms among 44,900 Chinese Han adults aged 30–79 in Southwest China. BMC Psychiatry. 2023;23(1):127. 10.1186/s12888-023-04601-6 . PMID: 36849922; PMCID: PMC9972728. Paudel M, Taylor BC, Ancoli-Israel S, Blackwell T, Maglione JE, Stone K, Redline S, Ensrud KE. Sleep Disturbances and Risk of Depression in Older Men. Sleep. 2013;36(7):1033–40. 10.5665/sleep.2804 . PMID: 23814340; PMCID: PMC3669078. Zhai L, Zhang H, Zhang D, SLEEP DURATION AND DEPRESSION AMONG ADULTS:. A META-ANALYSIS OF PROSPECTIVE STUDIES. Depress Anxiety. 2015;32(9):664 – 70. 10.1002/da.22386 . Epub 2015 Jun 5. PMID: 26047492. Sun X, Zheng B, Lv J, Guo Y, Bian Z, Yang L, Chen Y, Fu Z, Guo H, Liang P, Chen Z, Chen J, Li L, Yu C. China Kadoorie Biobank (CKB) Collaborative Group. Sleep behavior and depression: Findings from the China Kadoorie Biobank of 0.5 million Chinese adults. J Affect Disord. 2018;229:120–4. Epub 2017 Dec 28. PMID: 29306691; PMCID: PMC6675597. Whinnery J, Jackson N, Rattanaumpawan P, Grandner MA. Short and long sleep duration associated with race/ethnicity, sociodemographics, and socioeconomic position. Sleep. 2014;37(3):601–11. 10.5665/sleep.3508 . PMID: 24587584; PMCID: PMC3920327. Zhang X, Li G, Shi C, Sun Y. Associations of sleep duration, daytime napping, and snoring with depression in rural China: a cross-sectional study. BMC Public Health. 2023;23(1):1530. 10.1186/s12889-023-16479-w . PMID: 37568108; PMCID: PMC10416418. Li Y, Wu Y, Zhai L, Wang T, Sun Y, Zhang D. Longitudinal Association of Sleep Duration with Depressive Symptoms among Middle-aged and Older Chinese. Sci Rep. 2017;7(1):11794. 10.1038/s41598-017-12182-0 . PMID: 28924238; PMCID: PMC5603546. Racic M, Todorovic R, Ivkovic N, Masic S, Joksimovic B, Kulic M. Self- Perceived Stress in Relation to Anxiety, Depression and Health-related Quality of Life among Health Professions Students: A Cross-sectional Study from Bosnia and Herzegovina. Zdr Varst. 2017;56(4):251–9. 10.1515/sjph-2017-0034 . PMID: 29062400; PMCID: PMC5639815. Kim S, Yoon H, Volunteering SS, Quality, Inflammation C. A 5-Year Follow-Up of the National Social Life, Health, and Aging Project. Res Aging 2020 Oct-Dec;42(9–10):291–9. doi: 10.1177/0164027520922624. Epub 2020 May 8. PMID: 32383394. Prather AA, Vogelzangs N, Penninx BW. Sleep duration, insomnia, and markers of systemic inflammation: results from the Netherlands Study of Depression and Anxiety (NESDA). J Psychiatr Res. 2015;60:95–102. 10.1016/j.jpsychires.2014.09.018 . Epub 2014 Sep 26. PMID: 25307717; PMCID: PMC4250403. Osimo EF, Baxter LJ, Lewis G, Jones PB, Khandaker GM. Prevalence of low-grade inflammation in depression: a systematic review and meta-analysis of CRP levels. Psychol Med. 2019;49(12):1958–70. Epub 2019 Jul 1. PMID: 31258105; PMCID: PMC6712955. Haroon E, Welle JR, Woolwine BJ, Goldsmith DR, Baer W, Patel T, Felger JC, Miller AH. Associations among peripheral and central kynurenine pathway metabolites and inflammation in depression. Neuropsychopharmacology. 2020;45(6):998–1007. 10.1038/s41386-020-0607-1 . Epub 2020 Jan 15. PMID: 31940661; PMCID: PMC7162907. Matenchuk BA, Mandhane PJ, Kozyrskyj AL. Sleep, circadian rhythm, and gut microbiota. Sleep Med Rev. 2020;53:101340. 10.1016/j.smrv.2020.101340 . Epub 2020 May 13. PMID: 32668369. Kelly JR, Keane VO, Cryan JF, Clarke G, Dinan TG. Mood and Microbes: Gut to Brain Communication in Depression. Gastroenterol Clin North Am. 2019;48(3):389–405. 10.1016/j.gtc.2019.04.006 . Epub 2019 Jun 12. PMID: 31383278. Rahmani M, Rahmani F, Rezaei N. The Brain-Derived Neurotrophic Factor: Missing Link Between Sleep Deprivation, Insomnia, and Depression. Neurochem Res. 2020;45(2):221–31. 10.1007/s11064-019-02914-1 . Epub 2019 Nov 28. PMID: 31782101. Sapolsky RM, Romero LM, Munck AU. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocr Rev. 2000;21(1):55–89. 10.1210/edrv.21.1.0389 . PMID: 10696570. van Dalfsen JH, Markus CR. The influence of sleep on human hypothalamic-pituitary-adrenal (HPA) axis reactivity: A systematic review. Sleep Med Rev. 2018;39:187–94. 10.1016/j.smrv.2017.10.002 . Epub 2017 Oct 18. PMID: 29126903. Pan L, Huang C, Liu Y, Peng J, Lin R, Yu Y, Qin G. Quantile regression to explore association of sleep duration with depression among adults in NHANES and KNHANES. J Affect Disord. 2024;345:244–51. 10.1016/j.jad.2023.10.126 . Epub 2023 Oct 21. PMID: 37871729. Finan PH, Smith MT. The comorbidity of insomnia, chronic pain, and depression: dopamine as a putative mechanism. Sleep Med Rev. 2013;17(3):173–83. 10.1016/j.smrv.2012.03.003 . Epub 2012 Jun 29. PMID: 22748562; PMCID: PMC3519938. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5460471","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":378576069,"identity":"cd1b125b-7313-41d2-87cf-f2ac3f3b25b8","order_by":0,"name":"Yanliqing Song","email":"","orcid":"","institution":"Nanjing Tech University","correspondingAuthor":false,"prefix":"","firstName":"Yanliqing","middleName":"","lastName":"Song","suffix":""},{"id":378576070,"identity":"2c696a74-f67d-4d35-ac46-403674befd5e","order_by":1,"name":"Lin Chen","email":"","orcid":"","institution":"Nanjing Tech University","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Chen","suffix":""},{"id":378576071,"identity":"820a9166-c2e8-4ef1-8613-1c7f8db1edd9","order_by":2,"name":"Haoqiang Liu","email":"","orcid":"","institution":"Nanjing Tech University","correspondingAuthor":false,"prefix":"","firstName":"Haoqiang","middleName":"","lastName":"Liu","suffix":""},{"id":378576072,"identity":"fec0e175-91f9-47e7-9ef4-ea641f3c8c8a","order_by":3,"name":"Yue Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqElEQVRIiWNgGAWjYBACPghlw8PP30CkFjYIlSYjOeMAaVoO2xg0JBCrRSLH8MGPivM8BgwHGD98zCFOi7Fhz5nbPObMDcySM7cRp8VMmrHtNo9lwwE2Zl4itZj/Zvx3jsfgQALxWsyYGRsOkKKF51mxZM+xZB7JGQebifMLP3vyxg8/auzs+fmbD374SIwWBoEEGIuxgRj1IGsOEKlwFIyCUTAKRi4AAJpGMErmvEFmAAAAAElFTkSuQmCC","orcid":"","institution":"Shanghai University of Sport","correspondingAuthor":true,"prefix":"","firstName":"Yue","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-11-15 12:23:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5460471/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5460471/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69251361,"identity":"7115f353-04ab-4bd7-9d37-7afaeed65fec","added_by":"auto","created_at":"2024-11-18 11:47:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51866,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Dose-response relationship between nighttime sleep and depression in older adults, (b) Dose-response relationship between nap time and depression in older adults. The x-axis represents sleep duration. The y-axis represents the OR values calculated by the model. The shaded area represents the 95% confidence interval (Overall trend test: P \u0026lt; 0.001; Nonlinear trend test: P \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5460471/v1/7efd641d27c871bc6499bbce.png"},{"id":79276984,"identity":"917312f9-8aca-428b-9446-48165289a13c","added_by":"auto","created_at":"2025-03-26 12:31:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1130405,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5460471/v1/fbd37705-4885-403a-aed3-466943b05642.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimal Sleep Durations for Depression Prevention: Evidence from the China Family Panel Studies","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDepression is a widespread mental health disorder, affecting an estimated 280\u0026nbsp;million people globally[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is one of the leading causes of disability, making the prevention and intervention strategies for depression a pressing focus in the field of global public health. Notably, the prevalence of depression is not limited to middle-aged and elderly populations; its incidence among young adults is also significant[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A survey conducted in the United States revealed that the prevalence of depressive symptoms among college students is as high as 85%, highlighting the severity and urgency of this issue, which requires more attention and research[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDuring the COVID-19 pandemic, the global burden of depression has significantly increased. According to the latest data, the number of severe depression cases worldwide has risen by 52.3\u0026nbsp;million, an increase of 27.6%[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In the 204 countries and regions involved, the incidence of severe depression has risen to 3152.9 cases per 100,000 people[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Stress factors during the pandemic, including unemployment, the death of loved ones, social isolation, and the compound effects of multiple stressors, have had a severe negative impact on global mental health[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In the United States, the prevalence of depressive symptoms during COVID-19 has tripled compared to pre-pandemic levels[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWith the daily addition of hundreds of thousands of new COVID-19 cases, the pandemic has had a profound impact on human diet, daily outdoor activities, and overall lifestyle habits[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. To control the pandemic, the public has been advised to avoid crowded public places such as playgrounds, basketball courts, and football fields, inevitably leading to reduced opportunities for physical exercise. Existing research has clearly indicated a close link between the frequency of physical exercise and the incidence of anxiety and depressive symptoms[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAs the number of new COVID-19 cases continues to rise, measures such as lockdowns and restrictions on population movement have become necessary to control the spread of the pandemic. However, these measures restricting personal freedom may exacerbate mental stress[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Studies have pointed out that an individual\u0026rsquo;s geographical proximity to disaster events and the degree of personal impact experienced during natural disasters or epidemics may affect post-event mental health recovery. The impact of economic and social changes on mental health may be delayed[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlthough direct exposure to the COVID-19 virus does not have a significant direct impact on mental health symptoms, the increase in COVID-19-related occupational and social barriers may, over time, lead to significant changes in mental health, particularly in terms of social, work-related barriers, and economic difficulties[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Therefore, from a public health perspective, understanding and identifying modifiable risk factors for depression is crucial for developing effective prevention and intervention strategies.\u003c/p\u003e\u003cp\u003eDepression, as a complex mental disorder, is believed to be determined by the interaction of genetic and environmental factors, as well as the interplay between genes and the environment[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Additionally, lifestyle significantly impacts its occurrence[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Sleep, as an important dimension of health, has increasingly gained prominence in recent academic research. Studies have indicated that sleep duration is significantly correlated with overall mortality, cardiovascular diseases, and the incidence of chronic conditions such as metabolic syndrome[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Insufficient sleep duration and quality are considered key influencing factors for mental health disorders. The association between sleep, as a modifiable lifestyle factor, and depression has been examined in numerous studies[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eResearchers have extensively explored the role of sleep duration in the development of depression. A prospective study found that both short and long sleep durations are significantly associated with an increased risk of depression in adults[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Further research supports this view, suggesting that insufficient or excessive sleep may increase the incidence of depression[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, it should be noted that the data collection for these studies was completed before the outbreak of the COVID-19 pandemic.\u003c/p\u003e\u003cp\u003eTherefore, in this study, we analyzed the latest CFPS data obtained during the COVID-19 pandemic. We chose this dataset because it best represents the characteristics of depression among Chinese residents at this stage. The aim is to explore the relationship between nap time, nighttime sleep, and depression among residents, and to determine recommended sleep durations. This provides scientific and reasonable evidence for the prevention and treatment of depression among residents.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy population\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe China Family Panel Studies (CFPS) is a nationwide comprehensive project aimed at collecting individual, family, and community data through biennial follow-up surveys to reflect changes in China\u0026rsquo;s socioeconomic, demographic, educational, and health fields. The data for this study were derived from the 2020 CFPS project. The project employed computer-assisted survey techniques to meet diverse design needs, improve survey efficiency, and ensure data quality. Samples with missing demographic variables and missing Center for Epidemiologic Studies Depression Scale scores were excluded. Ultimately, 6795 samples were included in this study.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutcome\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNighttime sleep was assessed based on the following question: \u0026ldquo;Excluding nap time, how many hours do you usually sleep each day on average, representing a typical workday and rest day?\u0026rdquo; Previous studies on sleep duration have revealed the benefits of 7\u0026ndash;9 hours of sleep [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Participants were categorized into three types of sleep duration: short nighttime sleep (\u0026lt;\u0026thinsp;7 h), moderate nighttime sleep (7\u0026ndash;9 h; reference group), and long nighttime sleep (\u0026gt;\u0026thinsp;9 h).\u003c/p\u003e\u003cp\u003eNap time was assessed based on the following question: \u0026ldquo;How many minutes do you usually nap?\u0026rdquo; Participants were categorized into four groups: no nap (0 min), short nap (\u0026lt;\u0026thinsp;30 min), moderate nap (30\u0026ndash;90 min), and long nap (\u0026gt;\u0026thinsp;90 min). These cut-points were selected with reference to epidemiological literature on daytime napping[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eExplanatory variable\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDepression: The Center for Epidemiologic Studies Depression Scale (CESD) was used to measure depression. This scale, developed by Radloff at the National Institute of Mental Health, has been widely used to assess depression levels[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The CFPS2020 used the 8-item version of the CESD, which includes the following items: \u0026ldquo;I felt depressed, I found it hard to do anything, my sleep was poor, I felt happy, I felt lonely, I enjoyed life, I felt sad, I felt that life was not worth living.\u0026rdquo; Responses were scored as \u0026ldquo;0\u0026thinsp;=\u0026thinsp;rarely or never, 1\u0026thinsp;=\u0026thinsp;not often, 2\u0026thinsp;=\u0026thinsp;sometimes or half the time, 3\u0026thinsp;=\u0026thinsp;most of the time\u0026rdquo; (reverse-scored items were transposed). The scores of the 8 items were summed, with a range of 5\u0026ndash;24. Higher total scores indicate a higher risk of depression, with scores\u0026thinsp;\u0026ge;\u0026thinsp;9 indicating clinically significant depressive symptoms[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The CESD-8 is an effective and reliable tool for assessing depressive symptoms in adults[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. We examined the reliability coefficient of the CESD-8 scale, and the results showed that Cronbach\u0026rsquo;s alpha was greater than 0.7, indicating good internal consistency of the scale.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOther covariates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe analysis included a set of potential confounding variables. For sociodemographic data, we selected variables including age, gender (female or male), education level (illiterate, primary school, middle school, or high school and above), region (urban, rural), and marital status (married, single).\u003c/p\u003e\u003cp\u003eLifestyle factors included smoking (yes or no), drinking (yes or no), and frequency of physical activity (0 times a week, 1\u0026ndash;2 times a week, 3\u0026ndash;4 times a week, 5\u0026ndash;6 times a week, or every day).\u003c/p\u003e\u003cp\u003eHealth status included health self-assessment (bad, fair, or good) and chronic disease (no, yes).\u003c/p\u003e\u003cp\u003e\u003cb\u003e2.5 Statistical Methods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eStatistical analyses were performed using R 4.2 software. Qualitative data were expressed as frequencies and percentages (%), and comparisons between groups were made using the χ2 test or Fisher\u0026rsquo;s exact test. Quantitative data conforming to a normal distribution were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (x\u0026thinsp;\u0026plusmn;\u0026thinsp;s), and comparisons between groups were made using the t-test. Logistic regression models were constructed with nap time and nighttime sleep as reference groups. The variance inflation factor (VIF) was used to measure multicollinearity among the independent variables, and the Box-Tidwell method was used to test the linear relationship between continuous independent variables and the logit of depression. Model 1 included participants\u0026rsquo; nighttime and nap times, Model 2 controlled for demographic variables, and Model 3 included all covariates. Restricted cubic spline plots were drawn to explore the dose-response relationship between participants\u0026rsquo; sleep duration and depression. Stratified logistic regression analysis and interaction effect analysis were used to determine whether the association between sleep duration and depression depended on baseline or demographic factors. P-values were used for two-sided tests, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipant characteristics\u003c/h2\u003e\n \u003cp\u003eThe valid sample consisted of 6795 participants, of which 3411 were female (50.20%). The average age was 31.80\u0026thinsp;\u0026plusmn;\u0026thinsp;8.67 years, and 5834 participants (85.8%) exhibited depressive symptoms. Differences in nap sleep time, nighttime sleep, region, level of education, health self-assessment, chronic disease, and frequency of physical activity were statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Specific basic characteristics are shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBasic characteristics of study participants(n\u0026thinsp;=\u0026thinsp;5834)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;6795)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNormal (n\u0026thinsp;=\u0026thinsp;961)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDepression (n\u0026thinsp;=\u0026thinsp;5834)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.80\u0026thinsp;\u0026plusmn;\u0026thinsp;8.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.75\u0026thinsp;\u0026plusmn;\u0026thinsp;9.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.81\u0026thinsp;\u0026plusmn;\u0026thinsp;8.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003et=-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNap Duration, M (Q₁, Q₃)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.00 (0.00, 60.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.00 (0.00, 60.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.00 (0.00, 60.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZ=-2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNighttime sleep, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003et\u0026thinsp;=\u0026thinsp;4.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDepression, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.53\u0026thinsp;\u0026plusmn;\u0026thinsp;4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.13\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.42\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003et=-68.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=3.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3411 (50.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e455 (47.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2956 (50.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3384 (49.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e506 (52.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2878 (49.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegion, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecountryside\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5425 (79.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e704 (73.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4721 (80.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1370 (20.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e257 (26.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1113 (19.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLevel of education n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=15.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eilliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e423 (6.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (4.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e381 (6.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eelementary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e888 (13.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112 (11.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e776 (13.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2893 (42.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e393 (40.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500 (42.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh school and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2591 (38.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e414 (43.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2177 (37.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarital status, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.760\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2001 (29.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e287 (29.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1714 (29.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4794 (70.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e674 (70.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4120 (70.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth self-assessment, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=102.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2834 (41.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e530 (55.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2304 (39.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003efair\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3097 (45.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e377 (39.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2720 (46.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e864 (12.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54 (5.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e810 (13.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic disease, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=14.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6405 (94.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e931 (96.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5474 (93.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e390 (5.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (3.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e360 (6.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFrequency of physical activity, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=14.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5058 (74.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e673 (70.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4385 (75.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;~\u0026thinsp;2 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e689 (10.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116 (12.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e573 (9.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;~\u0026thinsp;4 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e376 (5.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53 (5.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e323 (5.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;~\u0026thinsp;6 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eevery day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e620 (9.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108 (11.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e512 (8.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4911 (72.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e700 (72.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4211 (72.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1884 (27.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e261 (27.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1623 (27.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDrink, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6061 (89.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e850 (88.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5211 (89.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e734 (10.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111 (11.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e623 (10.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNighttime sleep, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=18.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; 7h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1093 (16.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 (11.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e983 (16.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u0026ndash;9 h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4687 (68.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e692 (72.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3995 (68.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;9 h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1015 (14.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e159 (16.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e856 (14.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNap sleep time, n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;=8.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3230 (47.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e430 (44.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2800 (47.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;30 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1033 (15.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e133 (13.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e900 (15.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026ndash;90 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1981 (29.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e309 (32.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1672 (28.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;90 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e551 (8.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89 (9.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e462 (7.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eNote: t: t-test, Z: Mann-Whitney test, \u0026chi;\u0026sup2;: Chi-square test. M: Median, Q₁: 1st Quartile, Q₃: 3st Quartile. SD: standard deviat.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eLogistic regression of the relationship between sleep duration and depression\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFor the diagnosis of multicollinearity, we eliminated variables with VIF values greater than 10 to avoid multicollinearity. The Box-Tidwell test results showed that the continuous independent variables (nighttime sleep, nap sleep time) had a linear relationship with the dependent variable (depression) (P \u0026gt;0.05). The results of the logistic regression model analysis showed that, after controlling for all covariates in Model 3, participants with nighttime sleep \u0026ge;7 hours were found to have a protective factor against the likelihood of depression compared to those with nighttime sleep \u0026lt;7 hours. Compared to participants without a napping habit, those with nap times of 30-90 minutes were found to have a protective factor against the likelihood of depression (Table 2).\u003c/p\u003e\n \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/58894_9946feeafa4c1df7/58894_custom_files/img1731906283.png\" width=\"667\" height=\"309\"\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDose\u0026ndash;response relationship between nighttime sleep and depression\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe dose-response relationship analysis between nighttime sleep and depression indicated a U-shaped relationship (P-nonlinear \u0026lt;0.001), with the likelihood of depression decreasing from 7.5 hours of sleep to about 8.5 hours (Figure 1). The lowest likelihood of depression was observed when participants had around 8.5 hours of sleep. The dose-response relationship analysis between nap sleep time and depression indicated no nonlinear relationship (P-nonlinear = 0.889) (Figure 1).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Subgroup Analysis of the Impact of Sleep Duration on Depression\u003c/h2\u003e\n \u003cp\u003eStratified logistic regression analysis and interaction effect analysis were used to determine whether the association between sleep duration and depression depended on baseline or demographic factors. The association between nighttime sleep of 7\u0026ndash;9 hours and depression showed an interaction with health self-assessment and chronic disease (interaction P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This indicates that for individuals with general health self-assessment or chronic diseases, a sleep duration of 7\u0026ndash;9 hours may have a protective effect against the likelihood of depression. Nighttime sleep of 7\u0026ndash;9 hours was only associated with the likelihood of depression in certain subgroups.\u003c/p\u003e\n \u003cp\u003eThe association between nap time of 30\u0026ndash;90 minutes and depression showed no interaction with region, level of education, health self-assessment, chronic disease, and frequency of physical activity (interaction P-values\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The impact of nap time of 30\u0026ndash;90 minutes on depression did not differ between baseline or demographic factors. This indicates that the association between appropriate nap time and the risk of depression is consistent across all stratified subgroups (all interaction P-values\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSubgroup Analysis of the Impact of Nighttime Sleep on Depression\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP for interaction\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6795 (100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1839/2108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3995/4687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.84 (0.73\u0026thinsp;~\u0026thinsp;0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecountryside\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5425 (79.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1476/1677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3245/3748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88 (0.74\u0026thinsp;~\u0026thinsp;1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1370 (20.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e363/431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e750/939\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.74 (0.55\u0026thinsp;~\u0026thinsp;1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLevel of education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.585\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eilliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e423 (6.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e148/167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e233/256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.30 (0.68\u0026thinsp;~\u0026thinsp;2.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.422\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eelementary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e888 (13.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e279/317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e497/571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91 (0.60\u0026thinsp;~\u0026thinsp;1.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2893 (42.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e784/894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1716/1999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85 (0.67\u0026thinsp;~\u0026thinsp;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh school and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2591 (38.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e628/730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1549/1861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81 (0.63\u0026thinsp;~\u0026thinsp;1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth self-assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2834 (41.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e693/854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1611/1980\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01 (0.83\u0026thinsp;~\u0026thinsp;1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003efair\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3097 (45.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e838/923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1882/2174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65 (0.51\u0026thinsp;~\u0026thinsp;0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e864 (12.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e308/331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e502/533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21 (0.69\u0026thinsp;~\u0026thinsp;2.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.040\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6405 (94.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1698/1962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3776/4443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88 (0.75\u0026thinsp;~\u0026thinsp;1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e390 (5.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e141/146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e219/244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.31 (0.12\u0026thinsp;~\u0026thinsp;0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFrequency of physical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.628\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5058 (74.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1415/1605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2970/3453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83 (0.69\u0026thinsp;~\u0026thinsp;0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;~\u0026thinsp;2 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e689 (10.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e172/201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e401/488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78 (0.49\u0026thinsp;~\u0026thinsp;1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;~\u0026thinsp;4 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e376 (5.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88/99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e235/277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.70 (0.34\u0026thinsp;~\u0026thinsp;1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;~\u0026thinsp;6 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11/14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30/38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02 (0.23\u0026thinsp;~\u0026thinsp;4.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eevery day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e620 (9.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e153/189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e359/431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17 (0.75\u0026thinsp;~\u0026thinsp;1.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eOR: Odds Ratio, CI: Confidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSubgroup Analysis of the Impact of Nap Time on Depression\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP for interaction\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6795 (100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4162/4814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1672/1981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85 (0.73\u0026thinsp;~\u0026thinsp;0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.027\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecountryside\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5425 (79.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3362/3840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1359/1585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85 (0.72\u0026thinsp;~\u0026thinsp;1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1370 (20.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e800/974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e313/396\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82 (0.61\u0026thinsp;~\u0026thinsp;1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLevel of education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eilliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e423 (6.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e296/328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85/95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92 (0.43\u0026thinsp;~\u0026thinsp;1.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eelementary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e888 (13.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e577/647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e199/241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57 (0.38\u0026thinsp;~\u0026thinsp;0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2893 (42.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1761/2029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e739/864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90 (0.72\u0026thinsp;~\u0026thinsp;1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh school and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2591 (38.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1528/1810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e649/781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91 (0.72\u0026thinsp;~\u0026thinsp;1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth self-assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.384\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2834 (41.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1649/2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e655/828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82 (0.67\u0026thinsp;~\u0026thinsp;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003efair\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3097 (45.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1920/2181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e800/916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94 (0.74\u0026thinsp;~\u0026thinsp;1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e864 (12.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e593/627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e217/237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.62 (0.35\u0026thinsp;~\u0026thinsp;1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.623\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6405 (94.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3935/4568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1539/1837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83 (0.72\u0026thinsp;~\u0026thinsp;0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e390 (5.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227/246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e133/144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01 (0.47\u0026thinsp;~\u0026thinsp;2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFrequency of physical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5058 (74.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3218/3685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1167/1373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82 (0.69\u0026thinsp;~\u0026thinsp;0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.030\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;~\u0026thinsp;2 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e689 (10.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e396/471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e177/218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82 (0.54\u0026thinsp;~\u0026thinsp;1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;~\u0026thinsp;4 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e376 (5.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e208/239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e115/137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78 (0.43\u0026thinsp;~\u0026thinsp;1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;~\u0026thinsp;6 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26/32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15/20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.69 (0.18\u0026thinsp;~\u0026thinsp;2.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eevery day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e620 (9.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e314/387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e198/233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.32 (0.85\u0026thinsp;~\u0026thinsp;2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eOR: Odds Ratio, CI: Confidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study revealed a U-shaped dose-response relationship between nighttime sleep and depressive symptoms. Specifically, the probability of depressive symptoms significantly decreased when nighttime sleep increased from 7.5 hours to 8.5 hours. A cross-sectional study involving 1,788 American adults (aged 19\u0026ndash;89 years) showed a U-shaped association between sleep duration and depressive symptoms[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Compared to those with nighttime sleep less than 6 hours, individuals with sufficient nighttime sleep (not less than 6 hours) had a lower risk of depression. A study conducted in southwestern China involving 44,900 Han adults aged 30\u0026ndash;79 years explored the relationship between nighttime sleep, insomnia symptoms, and depressive symptoms. After adjusting for multiple variables, the study found that participants with nighttime sleep less than 7 hours had a higher odds ratio for depression (OR: 1.47, 95% CI: 1.31\u0026ndash;1.65) compared to those with nighttime sleep in the range of 7\u0026ndash;8 hours. However, no significant association was found between nighttime sleep exceeding 9 hours and depressive symptoms in the overall population analysis or subgroup analysis[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Other studies also support that there is no clear association between long sleep duration and depression[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. A meta-analysis of seven prospective studies showed a significant association between short sleep duration and the risk of depression, with a risk ratio of 1.31 compared to normal sleep duration[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Additionally, some cross-sectional studies have found that both short sleep duration (\u0026le;\u0026thinsp;6 hours) and long sleep duration (\u0026ge;\u0026thinsp;9 hours) are associated with an increased risk of depressive symptoms[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe inconsistency in the relationship between nighttime sleep and depressive symptoms may be attributed to several potential reasons: (1) Different methods were used in various studies to adjust for potential confounding factors, which may lead to biased results. (2) The definition of sleep duration varied across studies, which may affect the comparability of results. (3) The age distribution of study subjects differed, which may influence the observation of the relationship between sleep duration and depressive symptoms. (4) The proportion of participants with long sleep duration was relatively low (14.94%), which may result in insufficient statistical power to accurately assess the relationship between long sleep duration and depressive symptoms. (5) There is a potential bidirectional relationship between depression and sleep, which may cause differences in results between prospective cohort studies and cross-sectional studies. (6) Urban-rural differences and socioeconomic status (SES) disparities may significantly impact the pathogenesis of depression. Since both sleep and depression are associated with specific health behaviors and SES, these factors may confound the association between sleep and depression. For example, previous studies have shown that long sleep duration is associated with lower socioeconomic status, lower levels of physical activity, and obesity, all of which are risk factors for depression[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Therefore, when interpreting the relationship between sleep duration and depressive symptoms, these potential confounding variables must be considered.\u003c/p\u003e \u003cp\u003eThis study also found that participants with nap times of 30 to 90 minutes exhibited a lower likelihood of depression, supporting the potential role of napping in mood regulation. Previous studies have similarly indicated that short daytime naps are not significantly associated with depressive symptoms; however, excessively long nap times have been identified as an independent risk factor for depression[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Specifically, compared to moderate nappers, long nappers had a significantly higher incidence of depressive symptoms (OR\u0026thinsp;=\u0026thinsp;1.32, 95% CI: 1.19\u0026ndash;1.45) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This finding underscores the importance of nap duration in mental health and suggests that appropriate nap times may have a protective effect on emotional health.\u003c/p\u003e \u003cp\u003eThere are several possible explanatory mechanisms for the link between sleep status and depressive symptoms. First, insufficient sleep may lead to daytime fatigue, which in turn causes excessive daytime sleepiness and disruption of circadian rhythms, factors that may increase the risk of depressive symptoms. Individuals with shorter sleep durations may experience insufficient rest and increased perceived stress, which has been identified as a risk factor for depressive symptoms [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Second, inflammation is a key correlate of depression. Studies have shown that short sleep duration and insomnia symptoms are associated with elevated levels of inflammatory cytokines such as C-reactive protein (CRP) and interleukin-6 (IL-6) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Increasing evidence indicates that both short and long sleep durations are associated with elevated levels of inflammation, a phenomenon particularly evident in individuals with depression[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Chronic low-grade inflammation may be an important biological pathway linking sleep and depressive symptoms. It is noteworthy that inflammation is not only associated with depression and stress disorders but also plays a crucial role in their pathophysiology[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Increased inflammation may promote the activation of the kynurenine pathway, reducing serotonin levels, which is closely related to the pathophysiological mechanisms of depression[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditionally, sleep quality and duration may influence the composition of the gut microbiota[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The microbiota-gut-brain axis is an interactive system that may affect various neurological diseases[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Studies have shown that sleep disorders may alter the levels of brain-derived neurotrophic factor (BDNF), which plays a key role in the pathophysiology of stress-related mood disorders[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The hypothalamic-pituitary-adrenal (HPA) axis is an important pathway for understanding the neurobiology of stress responses[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Corticotropin-releasing hormone (CRH) released by the hypothalamus stimulates the anterior pituitary to secrete adrenocorticotropic hormone (ACTH), which in turn promotes the adrenal cortex to release cortisol into the bloodstream, activating the HPA axis[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Conversely, sleep has a regulatory effect on the HPA axis. Therefore, a decline in sleep quality may enhance the stress reactivity of the HPA axis.\u003c/p\u003e \u003cp\u003eFurthermore, adequate sleep helps to elevate melatonin levels, a molecule with multifaceted regulatory functions that can alleviate depressive symptoms. Finally, research on sleep and the immune system suggests that sleep can optimize immune defense, and immune cell signaling may induce sleep. Immune activation and cytokines may play a role in the occurrence of depressive symptoms in certain individuals. These findings underscore the important role of sleep in maintaining mental health and preventing depressive symptoms.\u003c/p\u003e \u003cp\u003eIn this study, we conducted a subgroup analysis of the relationship between sleep duration and depression to explore whether this association is influenced by baseline or demographic factors. Stratified logistic regression analysis and interaction effect analysis revealed a significant interaction between nighttime sleep of 7\u0026ndash;9 hours and depression, particularly related to health self-assessment and chronic disease status. Specifically, for individuals with general health self-assessment or chronic diseases, maintaining 7\u0026ndash;9 hours of nighttime sleep may have a protective effect, reducing the risk of depression. Previous studies using quantile regression, including 55,954 adults aged 18 to 80 from the National Health and Nutrition Examination Survey (N\u0026thinsp;=\u0026thinsp;34,156) and the Korea National Health and Nutrition Examination Survey (N\u0026thinsp;=\u0026thinsp;21,798), found that the association between short sleep duration and depression was stronger in individuals with chronic diseases[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The association between short sleep duration and depression is modified by chronic diseases. Sleep problems, chronic diseases, and depression are interrelated, with each increasing the risk of occurrence and worsening of the others. A review indicated that alterations in mesolimbic dopaminergic function are neurobiological factors associated with sleep problems, chronic diseases, and depression[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. However, the exact nature of these associations remains to be elucidated. Further research is needed to clarify the underlying physiological mechanisms between sleep, depression, and chronic diseases. This finding suggests that the role of sleep duration in preventing depression may vary depending on an individual\u0026rsquo;s health status, emphasizing the importance of considering individual differences in clinical practice. Notably, the association between nighttime sleep of 7\u0026ndash;9 hours and the likelihood of depression was significant only in certain subgroups, indicating that the impact of sleep on mental health is not universally applicable but is influenced by specific demographic characteristics. Therefore, future research and intervention strategies should consider the particularities of these subgroups to more effectively prevent and treat depression.\u003c/p\u003e \u003cp\u003eOn the other hand, this study also found that the association between nap time of 30\u0026ndash;90 minutes and the risk of depression showed no interaction across subgroups of different regions, education levels, health self-assessment, chronic disease status, and frequency of physical activity. This means that the beneficial effect of appropriate nap time on reducing the risk of depression is consistent across different demographic characteristics and is not influenced by these factors. This finding supports the notion of napping as a universally beneficial health behavior and provides a theoretical basis for future sleep interventions. These findings offer new directions for future research, suggesting that sleep interventions should consider individual differences in health status and sleep habits. Additionally, public health strategies should promote appropriate sleep habits to reduce the incidence of depression.\u003c/p\u003e \u003cp\u003eDespite providing valuable insights, this study has some limitations. First, due to the cross-sectional nature of the study design, we cannot determine the causal relationship between sleep duration and depressive symptoms. Future research should adopt longitudinal designs to explore the temporal relationship between sleep and depressive symptoms. Second, our study relies on self-reported sleep data, which may be subject to subjective bias. Future research could consider incorporating objective sleep monitoring techniques, such as polysomnography or wearable devices, to improve data accuracy. Additionally, this study did not account for individual differences, such as genetic factors, life events, and personality traits, which may influence the relationship between sleep and depressive symptoms. Future research should explore these potential mediating or moderating variables.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, this study revealed the complex relationship between nighttime sleep and nap time and depressive symptoms, providing new evidence for the role of sleep in mental health. There is a U-shaped relationship between nighttime sleep and depressive symptoms among Chinese residents. Nighttime sleep of 7\u0026ndash;9 hours is only associated with the likelihood of depression in certain subgroups, while appropriate nap time has a general preventive effect on depression for all participants. Considering the importance of both nighttime sleep and nap time in preventing depressive symptoms, it is essential to reasonably arrange sleep durations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgments:\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank China Social Science Survey Center (ISSS)\u0026nbsp;at\u0026nbsp;Peking University for providing the\u0026nbsp;CFPS\u0026nbsp;data\u003c/p\u003e\n\u003cp\u003eFunding:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis project is supported by the Foundation project（Supported by research project of Shanghai University of Sport(2023STD015), Ministry of Education Project of Humanities and Social Sciences for young scholars (22YJC890027).\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions:\u003c/p\u003e\n\u003cp\u003eSYLQ conceived the study, participated in its design and coordination, and critically revised the manuscript. SYLQ had full access to all the data collection, analysis, and interpretation, and drafted the manuscript. CL and LHQ contributed to the process of data collection and data analyses as study investigators. All authors approved the final manuscript.LY are the guarantors. All authors had full access to all the data in the study, and the corresponding authors had final responsibility for the decision to submit for publication. The corresponding author (LY) attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.\u003c/p\u003e\n\u003cp\u003eCompeting interests:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: no support from any organization for the submitted work; no financial relationships with any organization that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.\u003c/p\u003e\n\u003cp\u003eEthics approval\u003c/p\u003e\n\u003cp\u003eThe CFPS project was approved by the Biomedical Ethics Committee of Peking University, approval number: IRB00001052-14010. Additionally, before the survey began, researchers first obtained informed consent from the subjects in written form. Therefore, at the start of this study, all data were completely anonymous.\u003c/p\u003e\n\u003cp\u003eData sharing:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe acquisition of the data is a public database, and the link is: https://www.isss.pku.edu.cn/cfps/sjzx/gksj/index.htm\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDisclosure statement:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the authors.\u003c/p\u003e\n\u003cp\u003eProvenance and peer review:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot commissioned; externally peer reviewed.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. 2023. 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PMID: 22748562; PMCID: PMC3519938.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COVID-19 Pandemic, Depression, Nap Time, Nighttime Sleep, Health promotion","lastPublishedDoi":"10.21203/rs.3.rs-5460471/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5460471/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo explore the relationship between nap time, nighttime sleep, and depression among Chinese residents, and to determine recommended sleep durations to provide scientific and reasonable evidence for the prevention and control of depression among residents.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eBased on the 2020 China Family Panel Studies (CFPS), demographic data, health, and lifestyle information of the study subjects were obtained. A total of 6795 valid samples were included. Logistic regression, restricted cubic splines, and subgroup analysis were used to explore the relationship between sleep and depression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCompared to participants with nighttime sleep\u0026thinsp;\u0026lt;\u0026thinsp;7 hours, those with nighttime sleep\u0026thinsp;\u0026ge;\u0026thinsp;7 hours were found to have a protective factor against the likelihood of depression. Compared to participants without a napping habit, those with nap times of 30\u0026ndash;90 minutes were found to have a protective factor against the likelihood of depression. There was a U-shaped dose-response relationship between nighttime sleep and depressive symptoms (P-nonlinear\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with the likelihood of depression decreasing from 7.5 hours of sleep to about 8.5 hours, and the lowest likelihood of depression occurring around 8.5 hours of sleep. There was no nonlinear relationship between nap time and depression (P-nonlinear\u0026thinsp;=\u0026thinsp;0.889). This study revealed a U-shaped dose-response relationship between nighttime sleep and depressive symptoms. Specifically, the probability of depressive symptoms significantly decreased when nighttime sleep increased from 7.5 hours to 8.5 hours. Subgroup analysis further showed that in all subgroups, individuals with self-rated general health or chronic diseases had a protective effect against the likelihood of depression if their sleep duration was 7\u0026ndash;9 hours. The effect of nap time of 30\u0026ndash;90 minutes on depression did not differ between baseline or demographic factors.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThere is a U-shaped relationship between nighttime sleep and depressive symptoms among Chinese residents. Nighttime sleep of 7\u0026ndash;9 hours is only associated with the likelihood of depression in certain subgroups, while appropriate nap time has a general preventive effect on depression for all participants. Considering the importance of both nighttime sleep and nap time in preventing depressive symptoms, it is essential to reasonably arrange sleep durations.\u003c/p\u003e","manuscriptTitle":"Optimal Sleep Durations for Depression Prevention: Evidence from the China Family Panel Studies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-18 11:46:59","doi":"10.21203/rs.3.rs-5460471/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9b135a7d-dbe6-4d43-8dd5-2af625724209","owner":[],"postedDate":"November 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-26T12:23:50+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-18 11:46:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5460471","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5460471","identity":"rs-5460471","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}