Association between Sleep Duration and the Prevalence of Depression, Anxiety, and Comorbid Symptoms among PIVAS Staff in China: Cross-Sectional Study

Association between Sleep Duration and the Prevalence of Depression, Anxiety, and Comorbid Symptoms among PIVAS Staff in China: Cross-Sectional Study | 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 Association between Sleep Duration and the Prevalence of Depression, Anxiety, and Comorbid Symptoms among PIVAS Staff in China: Cross-Sectional Study Zhicheng Pan, Minglin Zheng, Mengran Guo, Yunfu Lan, Hao Yang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8607092/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Insufficient sleep is a serious risk factor of mental disorders. However, the research evidence remains quite limited among the personnel working at Pharmacy Intravenous Admixture Services (PIVAS). It is therefore the purpose of this research to explore the relationship between the length of sleep and symptoms of depression, anxiety, and co-morbidity among PIVAS personnel in China. Methods The cross-sectional study was conducted among 3,525 PIVAS employee members between May and October 2025. The research utilized the Patient Health Questionnaire 9 (PHQ-9) to identify depression and Generalized Anxiety Disorder 7 (GAD-7) to identify symptoms of anxiety. Sleep duration was measured and grouped into three to represent the main exposure of interest (8–10 h, 6–7 h, and 3–5 h). The adjusted odds ratio and 95% confidence interval were measured. The study protocol was registered with the Chinese Clinical Trial Registry (ChiCTR2500114132). Results Prevalences of depression, anxiety, and comorbid symptoms among PIVAS personnel were 14.6%, 6.7%, and 5.9%, respectively. After adjusting for demographics, occupation, and lifestyle variables, a significantly increased risk for depression (OR = 5.4, 95% CI: 3.4–8.5), anxiety (OR = 4.4, 95% CI: 2.3–8.4), and co-symptoms (OR = 5.0, 95% CI: 2.5–9.9) was found for short sleep (3–5 h) compared to the reference group (8–10 h) ( P < 0.001). There was a significant dose response trend (trend P < 0.001). These findings reveal a significantly high prevalence of mental illnesses among male employees working with PIVAS, as well as among persons < 25 years old. Conclusions Based on the results of the research, the major risk factor for the development of depression, anxiety and comorbid symptoms with PIVAS is sleeping for a shorter period of time. The group of people at a high risk of developing mental health issues is males and those under 25 age. PIVAS Sleep duration Depression Anxiety Comorbid symptoms Cross-sectional study Figures Figure 1 Figure 2 Background Appropriate sleep is one of the basic requisites for health. However, due to the rising pace of modern life, as well as rising levels of occupational stress, sleep disorders are becoming an entrenched public health problem. Worldwide, about 12.4% of the adult population suffers from sleep disorders, with a rising incidence of 19.2% in China [ 1 , 2 ]. Sleep duration, an essential component of sleep quality, has been found to have a strong association with diverse health outcomes, primarily because it has a great influence on mental health. Various studies have identified a strong relationship between sleep duration and depression, anxiety, and co-occurrence of these symptoms. For instance, with regard to the established sleep need of 7–9 hours, reduced sleep of less than 7 hours has been found to significantly increase the incidence of depression by a steep 69% [ 3 ]. Interestingly, both short sleep duration as well as long sleep duration are found to have an increased rate of depression incidence [ 4 ]. Short sleep duration of less than 7 hours has been found to substantially increase the incidence of anxiety in commercial pilots in particular [ 5 ]. A Chinese multi-ethnic cohort (CMEC) study has identified a direct relationship between reduced sleep duration and increased incidence of co-occurring symptoms [ 6 ]. These facts re-emphasize the need for adequate sleep of an optimal duration in the prevention of psychiatric disorders. Depression and anxiety disorders together account for a large proportion of the global burden of diseases [ 7 ]. Both disorders have been seen to occur contemporaneously with lifestyle factors and co-existence with physical comorbid conditions, with a commonality of 80.3% of people with depression suffering from co-existing physical diseases like Hypertension (45.9%) and Hyperlipidaemia (24.0%) [ 8 , 9 ]. With the progression of depressive symptoms, they promote anxiety and manic episodes, leading to an increased suicide rate among patients [ 10 ]. Notably, there is a risk for the transmission of intergenerational generations of depression and anxiety disorders from parent to offspring [ 11 ]. This emphasizes how crucial early intervention is. The co-occurrence of both disorders is referred to as comorbid depression and anxiety symptoms (CDAS). Research shows a variation in the relative order of onset of symptoms of the disorder from individual to individual. In this context, it has been explained that 68% of people experience the onset of anxiety disorder symptoms first, followed by 13.5% for the symptoms of depression; Concurrent symptoms of both occur in 18.5% of the general populations [ 12 ]. The disorder has a higher risk of symptoms and relapse when co-existing with other mental conditions. In this context, the relative risk of suicide stands at 4.2 times more than the risk of suffering from depression alone [ 13 ]. While the association between the disorder of sleep duration and the mental conditions of depression and anxiety has been explored in the past, the epidemiological association with the specified mental disorder in healthcare professionals is still lacking. Hence, the implications of this association for the specified mental disorder in healthcare professionals for the purpose of developing a specific preventive strategy for the disorder in this group of professionals warrants exploration. The Pharmacy Intravenous Admixture Service (PIVAS) is an integral service within the hospitals. The staff of PIVAS face heavy occupational stresses such as excessive work, heavy workloads, and possible risk exposures [ 14 , 15 ]. These work attributes are likely to affect the regulation of the sleep-wake cycle as well as reduce the total sleeping hours [ 16 ]. Poor sleeping quality is among the major causes of developing mental health disorders. Previous studies that assessed the impacts of sleeping on mental health disorders were mainly conducted on groups comprising nurses and medical physicians [ 17 , 18 ]. However, the different working patterns of staff in PIVAS warrant distinct studies. Presently, there exists an apparent shortage of large-scale epidemiological studies among the PIVAS staff. In light of this, the current study adopted a cross-sectional multicenter design in order to investigate the relationship between sleep duration and depression, anxiety, and co-occurring disorders in PIVAS staff members. The purpose of this study is not only to shed light on improving strategies for mental health care but also to provide advice regarding human resource management in hospitals. 1 Methods 1.1 Study Design and Population Cross-sectional studies were performed in multiple centers between May and October 2025. Recruitment announcements were spread via two professional platforms: the PIVAS Professional Committee of the National Health Commission Hospital Management Institute and the PIVAS Management Professional Committee of Chinese Pharmaceutical Association. Recruitment of the participants entailed both online questionnaires in professional WeChat groups and direct personal invitations in order to cover the target group comprehensively. The inclusion criteria for participants in the study were: (1) full-time employment in the PIVAS department at the participating hospital, (2) voluntary participation in the study, (3) the absence of cognitive or language impairments, with the ability to complete assessments of their sleep and mental health questionnaires. The only exclusion criterion was employment in the PIVAS staff for less than two years. After excluding 555 participants based on the criteria for selection, the final sample of participants was 3,525 staff members (Fig. 1 ). 1.2 Assessment of Exposure Variable Sleep duration is considered the primary exposure variable for which the value is measured through a standardized questionnaire. The mean daily sleep duration is computed by taking a weighted average, which is determined by the following formula: (5 × average sleep time on weekdays + 2 × average sleep time during weekends) / 7 [ 19 ]. 1.3 Assessment of Outcome Variables The severity of depressive symptoms was assessed using the Patient Health Questionnaire 9 (PHQ-9) scale [ 20 ]. There were nine questions on which the respondents answered using a 4-point scale ranging from 0 ("Never") to 3 ("Nearly every day"). Scoring was from 0 to 27, with higher scores reflecting more severe symptoms. In accordance with criteria for diagnosis, a score of 10 or above was taken to reveal the presence of depressive symptoms [ 21 ]. For assessing the symptoms of anxiety, the Generalized Anxiety Disorder 7-item Scale (GAD-7 scale) was utilized [ 22 ]. There were seven questions on which the respondents answered using a 4-point scale from 0 ("Never") to 3 ("Nearly every day"). Scoring was from 0 to 21, with a score above 10 reflecting the symptoms of anxiety [ 23 ]. In the present study, persons who scored 10 or above on both scales were identified as having co-existing symptoms of depression and anxiety [ 24 ]. 1.4 Covariates Covariates were determined based on previous research regarding the factors of hospital personnel and occupational health psychology literature [ 15 , 25 – 27 ], which included sociodemographic factors, job information, and lifestyle factors. The sociodemographic factors included age, sex, marital status (never married, married/cohabiting, widowed/divorced/separated), education (junior college or less, Bachelor's degree, Master's degree or higher), and professional title (junior, intermediate, senior). Job characteristics included PIVAS years of service, daily work hours on the Laminar Airflow workbench, daily admixture workload ( 200 bags), frequency of handling sessions for hazardous drugs (never, occasionally, often, frequently), one-way commuting time ( 90 minutes), and history of dispensing errors (none, 1–3, 4–6, 7–12, > 12). The factors of lifestyle and behavior included daily short video viewing duration (low, moderate, high, very high), daily gaming duration (non-player, 3 hours), smoking status (non-smoker, light, moderate, heavy, very heavy), alcohol consumption (non-drinker, light, moderate, heavy), physical activity frequency (inactive, light, moderate, high, very high), and coffee consumption (never, occasionally, light, regular, heavy). 1.5 Statistical Analyses The data analysis used the R software package version 3.5.2. Categorical data is expressed in the form of frequency (n) and percent (%), whereas the continuous data is expressed in the form of mean ± standard deviation (SD). To compare the means among two groups, the t test and rank sum test were used. Chi-square tests were applied for comparing categorical data. To examine the link between sleep duration and mental health outcomes, we carried out multivariate logistic regression analyses. Three hierarchical models were set to reduce the risk of confounding. These were Model 1, the unadjusted model; Model 2, adjusted for sociodemographic factors; and Model 3, adjusted for occupational factors, lifestyle variables, and the variables in the previous model. The results are presented as odds ratios with 95% confidence intervals. The cut-off point for statistical significance was established at P < 0.05 for the two-tailed test. 2 Results 2.1 Baseline Characteristics of Participants This survey included a total of 3,525 PIVAS staff members. The mean age was 35.5 ± 7.0 years. Male staff members numbered 621 (17.62%), while female staff members numbered 2,904 (82.38%). Sleep duration divided participants into three groups that included sleep duration of 8–10 hours (reference group), with a total of 430 participants ; sleep duration of 6–7 hours, with a total of 2,575 participants ; and sleep duration of 3–5 hours with a total of 520 participants (Table 1 ). Demographic results showed that sleep duration had significant correlations with age ( P = 0.016), gender ( P < 0.001), and marital status ( P < 0.001). However, there were non-significant correlations with educational status ( P = 0.076). In regard to work-related aspects, work duration on laminar flow workbenches ( P = 0.049), commuting time ( P = 0.01), Professional title ( P = 0.024), and frequency of dispensing errors ( P < 0.001)had significant correlations with sleep duration. Concerning aspects of lifestyles related to sleep duration, duration of short video viewing, gaming time, smoking status, alcohol consumption, coffee consumption, and physical activity frequency had significant correlations with sleep duration ( P < 0.001). Table 1 Baseline characteristics of PIVAS staff stratified by sleep duration. Characteristics Total Sleep Duration P -value n = 3525 8–10 h (n = 430) 6–7 h (n = 2575) 3–5 h (n = 520) Age (years), mean ± SD 35.5 ± 7.0 34.8 ± 6.1 35.5 ± 7.0 36.1 ± 7.8 0.016 Length of Service (years), mean ± SD 7.7 ± 4.5 7.6 ± 4.3 7.7 ± 4.4 7.9 ± 4.8 0.454 Time Spent Working in the Laminar Airflow Workbench (h), mean ± SD 3.4 ± 1.5 3.2 ± 1.5 3.4 ± 1.5 3.4 ± 1.5 0.049 Sex, n (%) < 0.001 Male 621 (17.6%) 52 (12.1%) 449 (17.4%) 120 (23.1%) Female 2904 (82.4%) 378 (87.9%) 2126 (82.6%) 400 (76.9%) Marital Status, n (%) < 0.001 Never Married 721 (20.4%) 76 (17.7%) 523 (20.3%) 122 (23.5%) Married/Cohabiting 2594 (73.6%) 335 (77.9%) 1909 (74.1%) 350 (67.3%) Widowed/Divorced/Separated 210 (6.0%) 19 (4.4%) 143 (5.6%) 48 (9.2%) Education Level, n (%) 0.076 Junior college or below 461 (13.1%) 64 (14.9%) 324 (12.6%) 73 (14.0%) Bachelor's Degree 2796 (79.3%) 340 (79.1%) 2037 (79.1%) 419 (80.6%) Master's Degree or above 268 (7.6%) 26 (6.0%) 214 (8.3%) 28 (5.4%) Professional Title, n (%) 0.024 Junior 1661 (47.1%) 218 (50.7%) 1184 (46.0%) 259 (49.8%) Intermediate 1577 (44.7%) 192 (44.6%) 1167 (45.3%) 218 (41.9%) Senior 287 (8.1%) 20 (4.6%) 224 (8.7%) 43 (8.3%) Daily Admixture Workload, n (%) 0.622 200 bags 1107 (31.4%) 127 (29.5%) 804 (31.2%) 176 (33.8%) Hazardous Drug Preparation Frequency, n (%) 0.109 Never 408 (11.6%) 61 (14.2%) 295 (11.5%) 52 (10.0%) Occasionally 2349 (66.6%) 276 (64.2%) 1731 (67.2%) 342 (65.8%) Often 512 (14.5%) 71 (16.5%) 359 (13.9%) 82 (15.8%) Frequently 256 (7.3%) 22 (5.1%) 190 (7.4%) 44 (8.5%) One-way Commuting Time, n (%) 0.01 90 min 44 (1.2%) 7 (1.6%) 29 (1.1%) 8 (1.5%) History of dispensing errors, n (%) < 0.001 None 1809 (51.3%) 276 (64.2%) 1307 (50.8%) 226 (43.5%) 1–3 times 1554 (44.1%) 143 (33.3%) 1159 (45.0%) 252 (48.5%) 4–6 times 118 (3.4%) 11 (2.6%) 81 (3.2%) 26 (5.0%) 7–12 times 23 (0.6%) 0 (0.0%) 17 (0.7%) 6 (1.2%) > 12 times 21 (0.6%) 0 (0.0%) 11 (0.4%) 10 (1.9%) Short-Video Viewing Duration, n (%) < 0.001 Light 805 (22.8%) 150 (34.9%) 545 (21.2%) 110 (21.2%) Moderate 1549 (43.9%) 190 (44.2%) 1155 (44.8%) 204 (39.2%) Frequent 965 (27.4%) 73 (17.0%) 734 (28.5%) 158 (30.4%) High - frequency 206 (5.8%) 17 (4.0%) 141 (5.5%) 48 (9.2%) Daily Gaming Duration, n (%) < 0.001 Non-player 2611 (74.1%) 321 (74.6%) 1958 (76.0%) 332 (63.8%) 3 h 51 (1.4%) 8 (1.9%) 25 (1.0%) 18 (3.5%) Smoking Status, n (%) < 0.001 Non - smoker 3279 (93.0%) 414 (96.3%) 2414 (93.8%) 451 (86.7%) Light 73 (2.1%) 6 (1.4%) 50 (1.9%) 17 (3.3%) Moderate 57 (1.6%) 2 (0.5%) 38 (1.5%) 17 (3.3%) Heavy 59 (1.7%) 7 (1.6%) 36 (1.4%) 16 (3.1%) Very heavy 57 (1.6%) 1 (0.2%) 37 (1.4%) 19 (3.6%) Alcohol consumption, n (%) < 0.001 Non - drinker 2697 (76.5%) 368 (85.6%) 1975 (76.7%) 354 (68.1%) Light 705 (20.0%) 54 (12.6%) 524 (20.4%) 127 (24.4%) Moderate 113 (3.2%) 8 (1.9%) 71 (2.8%) 34 (6.5%) Heavy 10 (0.3%) 0 (0.0%) 5 (0.2%) 5 (1.0%) Physical activity frequency, n (%) < 0.001 Inactive 445 (12.6%) 38 (8.8%) 296 (11.5%) 111 (21.4%) Light 2225 (63.1%) 270 (62.8%) 1645 (63.9%) 310 (59.6%) Moderate 580 (16.4%) 90 (20.9%) 423 (16.4%) 67 (12.9%) High 226 (6.4%) 25 (5.8%) 177 (6.9%) 24 (4.6%) Very High 49 (1.4%) 7 (1.6%) 34 (1.3%) 8 (1.5%) Coffee consumption frequency, n (%) < 0.001 Never 1344 (38.1%) 195 (45.4%) 958 (37.2%) 191 (36.7%) Occasionally 1264 (35.9%) 150 (34.9%) 952 (37.0%) 162 (31.2%) Lightly 416 (11.8%) 37 (8.6%) 323 (12.5%) 56 (10.8%) Regularly 457 (13.0%) 43 (10.0%) 316 (12.3%) 98 (18.8%) Heavily 44 (1.2%) 5 (1.2%) 26 (1.0%) 13 (2.5%) Data are presented as mean ± standard deviation (SD) for continuous variables and frequency (percentage) for categorical variables. P -values were calculated using one-way ANOVA or Kruskal-Wallis test for continuous variables, and Chi-square test or Fisher's exact test for categorical variables. Abbreviation: PIVAS, Pharmacy Intravenous Admixture Service. The data shown in Table 2 suggested that the groups who slept for 3–5 hours had a significantly high total depression and anxiety scale scores, as well as a proportion of persons with mental illness, compared to other groups ( P < 0.001). Table 1 . Baseline characteristics of PIVAS staff stratified by sleep duration. Table 2 Association of sleep duration with depression, anxiety, and comorbid symptoms Characteristics Total Sleep Duration P -value n = 3525 8–10 h (n = 430) 6–7 h (n = 2575) 3–5 h (n = 520) Total Depression Score, mean ± SD 5.2 ± 4.9 3.1 ± 4.2 4.9 ± 4.4 8.3 ± 5.9 < 0.001 Total Anxiety Score, mean ± SD 3.3 ± 4.1 1.7 ± 3.3 3.1 ± 3.8 5.5 ± 5.3 < 0.001 Depression, n (%) < 0.001 No 3009 (85.4%) 404 (94.0%) 2256 (87.6%) 349 (67.1%) Yes 516 (14.6%) 26 (6.0%) 319 (12.4%) 171 (32.9%) Anxiety, n (%) < 0.001 No 3289 (93.3%) 418 (97.2%) 2434 (94.5%) 437 (84.0%) Yes 236 (6.7%) 12 (2.8%) 141 (5.5%) 83 (16.0%) Comorbid Symptoms, n (%) 10; Anxiety was defined as GAD-7 score > 10; Comorbid symptoms was defined as concurrent presence of both conditions. 2.2 Prevalence of Depression, Anxiety, and Comorbid Symptoms Stratified by Gender, Age, and Sleep Duration Depression, anxiety, and comorbidity symptoms were compared across PIVAS staff members based on a questionnaire response in Fig. 2 and Table 3 . The findings of this study bring to notice that depression had a relatively higher prevalence of 14.6%, which was substantially higher than that of anxiety and comorbidity symptoms. Also, a gender-related study revealed that a relatively higher prevalence of all mental illness occurred in males than in females (depression: 17.1% vs. 14.1%; anxiety: 9.5% vs. 6.1%; comorbidity symptoms: 8.4% vs. 5.4%). Also, a prevalence study related to mental illness demonstrated that a relatively higher prevalence of all mental illness occurred in staff members aged under 25 years (depression: 20.6%; anxiety: 8.3%; comorbidity symptoms: 7.4%). Furthermore, a relatively shorter sleep duration had a substantially higher prevalence of mental illness (depression 32.9%, anxiety 16.0%, comorbidity symptoms 15.4%) than other groups in this study. Moreover, in all categories of this study, a relatively higher prevalence of depression was measured than that of anxiety and comorbidity symptoms combined. Table 3 Prevalence of depression, anxiety, and comorbid symptoms stratified by demographic and sleep characteristics. Variables Depression Anxiety Depression & Anxiety No Yes No Yes No Yes Gender, n (%) Male 515 (82.9%) 106 (17.1%) 562 (90.5%) 59 (9.5%) 569 (91.6%) 52 (8.4%) Female 2494 (85.9%) 410 (14.1%) 2727 (93.9%) 177 (6.1%) 2747 (94.6%) 157 (5.4%) Age, n (%) ≤ 25 154 (79.4%) 40 (20.6%) 178 (91.8%) 16 (8.2%) 179 (92.3%) 15 (7.7%) > 25, ≤ 35 1440 (83.9%) 277 (16.1%) 1588 (92.5%) 129 (7.5%) 1600 (93.2%) 117 (6.8%) > 35, ≤ 45 1113 (87.2%) 164 (12.8%) 1205 (94.4%) 72 (5.6%) 1217 (95.3%) 60 (4.7%) > 45 302 (89.6%) 35 (10.4%) 318 (94.4%) 19 (5.6%) 320 (95.0%) 17 (5.0%) Sleep Duration, n (%) 8-10h 404 (94.0%) 26 (6.0%) 418 (97.2%) 12 (2.8%) 420 (97.7%) 10 (2.3%) 6-7h 2256 (87.6%) 319 (12.4%) 2434 (94.5%) 141 (5.5%) 2456 (95.4%) 119 (4.6%) 3-5h 349 (67.1%) 171 (32.9%) 437 (84.0%) 83 (16.0%) 440 (84.6%) 80 (15.4%) Data are presented as n (%). Depression was defined as PHQ-9 score > 10; Anxiety was defined as GAD-7 score > 10; Comorbid symptoms was defined as concurrent presence of both conditions. 2.3 Multivariable Logistic Regression Analysis of the Association between Sleep Duration and Mental Health Outcome We constructed three logistic regression models to assess the interrelationship between sleep duration and mental health risk in a multivariate model (Table 4 ). In Model 1, when not adjusting for any confounding variables, short sleep duration was significantly linked to an increase in depression (OR = 7.61, 95% CI.: 4.92–11.78), anxiety (OR = 6.62, 95% CI.: 3.56–12.30), and comorbid symptoms (OR = 7.64, 95% CI.: 3.90-14.94) compared to the reference category of sleep duration (8–10 hours). After stepwise adjustment for demographic factors (Model 2) and for occupation and lifestyle factors (Model 3), none of these associations lost significance. In Model 3, when fully adjusting for confounding variables, short sleep duration was still significantly linked to an increase in depression symptoms (OR = 5.41, 95% CI.: 3.43–8.54), anxiety symptoms (OR = 4.38, 95% CI.: 2.30–8.35), as well as comorbid symptoms (OR = 4.95, 95% CI.: 2.47–9.93). A dose-response effect was also found to exist with significance at P < 0.001 for all models. Table 4 Multivariable logistic regression analysis of the association between sleep duration and mental health outcomes. Exposure variables Model I Model II Model III OR (95%CI) OR (95%CI) OR (95%CI) Depression 8-10h Ref. Ref. Ref. 6-7h 2.2 (1.4, 3.3) 2.2 (1.4, 3.3) 1.9 (1.2, 2.9) 3-5h 7.6 (4.9, 11.8) 7.6 (4.9, 11.8) 5.4 (3.4, 8.5) Trend Test P < 0.001 P < 0.001 P < 0.001 Anxiety 8-10h Ref. Ref. Ref. 6-7h 2.0 (1.1, 3.7) 1.9 (1.1, 3.5) 1.7 (0.9, 3.1) 3-5h 6.6 (3.6, 12.3) 6.2 (3.3, 11.5) 4.4 (2.3, 8.4) Trend Test P < 0.001 P < 0.001 P < 0.001 Comorbid Symptoms 8-10h Ref. Ref. Ref. 6-7h 2.0 (1.1, 3.9) 2.0 (1.0, 3.8) 1.7 (0.9, 3.3) 3-5h 7.6 (3.9, 14.9) 7.2 (3.6, 14.1) 5.0 (2.5, 9.9) Trend Test P < 0.001 P < 0.001 P < 0.001 Model 1: Unadjusted model. Model 2: Adjusted for gender, age, education level, marital status, professional title, and working years. Model 3: Adjusted for variables in Model 2 plus daily admixture workload, handling of hazardous drugs, commuting time, history of dispensing errors, short-video duration, gaming duration, smoking status, alcohol consumption, physical activity, and coffee consumption. P < 0.001 was considered statistically significant. Abbreviations: OR, odds ratio; CI, confidence interval; Ref., reference group. 3 Discussion This study was conducted based on the sleep duration of the PIVAS staff as the exposure factor, and the results showed the relationship between the sleep duration of the PIVAS staff and the prevalence of depression, anxiety, and comorbid symptoms even after adjusting the potential confounders of demographics, work, and lifestyle factors. In the 8–10 hour control group, the risks of having mental health problems were significantly higher for 3–5 hours of sleep duration, showing OR of 5.4 (95%CI: 3.4–8.5) for depression, 4.4 (95%CI: 2.3–8.4) for anxiety, and 5.0 (95%CI: 2.5–9.9) for comorbid symptoms. There was a significant dose-response trend among them ( P < 0.001), showing that the risk of mental impairment increases cumulatively as the duration of sleep shortens. In addition, the risks of mental health impairment were higher in the subgroup analysis of demographics, including men and those aged less than 25 years. These results are in line with multiple other prospective and cross-sectional studies associating sleep duration with depression, anxiety, and comorbid symptoms risks. For example, the study on the elderly population of China found short sleep duration may contribute to increased vulnerability to depression [ 28 ]. Similarly, for anxiety risk. Among Chinese civil aviation pilots, it was found that short sleep duration may cause elevated anxiety risk [ 5 ]. The comorbidity of depression and anxiety is also relatively common in the general population. The China Multi-Ethnic Cohort (CMEC) study demonstrates individuals with less than 7 hours of sleep at night are more likely to suffer from comorbid symptoms [ 6 ]. PIVAS workers work under a special working condition. They need to concentrate for long periods and repeatedly carry out similar work tasks. These special occupational stresses may predispose them to adverse consequences of sleep loss, causing a variety of mental disorders [ 15 ]. Importantly, we found male PIVAS workers are more susceptible to mental health problems compared to female workers. This contrasts with some previous findings. For example,in studies involving Parkinson's disease patients, the prevalence rate of depressive symptoms in female (66.6%) patients is higher than in males (55.1%) [ 29 ]. In a study investigating psychological impact of the Coronavirus Disease 2019 (COVID-19), women were found to be at higher risk for mental distress [ 30 ]. In the CMEC study, comorbidity was found among women and middle-aged groups but not in men [ 6 ]. The gender discrepancy may be related to certain features specific to the PIVAS setting. Among PIVAS workers, it was found that men are especially prone to depressive disorder because of low job control owing to repetitiveness of the task,which shows a clear discrepancy with female workers [ 31 ]. When employees experience high job pressure but low job rewards, this could erode men's social identities as family breadwinners, contributing to psychological distress [ 32 ]. Furthermore, shame associated with seeking help often prevents men from asking for assistance, leading to their psychological symptoms worsening in silence [ 33 ]. Nevertheless,these hypotheses need to be tested in future research. Analysis by age demonstrates young workers have a greater risk of developing mental problems. Consistent with the pattern seen in young populations. Young people tend to be more susceptible to external environmental factors, thereby exhibiting greater psychological vulnerability [ 31 ]. 3.1 Potential Mechanisms The neurobiological processes involved also have an important role to play in relating short sleep to mental illness event,which is likely to have more implications within the PIVAS workplace setting. First, the hypothalamic-pituitary-adrenal (HPA) axis is set off by chronic sleep deprivation, which causes an increase in cortisol production [ 32 ]. This persistent dysregulation of cortisol secretion prevents the body from regulating stress and emotions, leading to an increased risk of mental illness [ 33 ]. Therefore, hyperactivation of the HPA axis is clinically recognized as one of the criteria for diagnosing mental disorders [ 34 ]. For professionals working under challenging conditions with PIVAS' zero tolerance to errors, there would be heightened levels of overacting to stress with short sleep hours to result in stress mental conditions. The work environment of PIVAS could also have adverse effects on disturbances of the circadian rhythms. The employees work long hours in a sealed clean room, mainly under artificial lighting,with minimal access to direct sunlight, thus contributing to the disturbance of melatonin secretion, leading to sleep structure disorder and impaired cognitive function [ 35 ]. Additionally, melatonin regulation of sleep has been associated with modifications in the structure of neurotransmitter systems, including changes in serotonin, dopamine, and norepinephrine receptor sensitivity [ 36 ]. The work setting in the PIVAS operates at a high level of intensity,involves repetition of tasks,mental concentration, and excessive work efforts. The main implication of human errors arising from insomnia could be the development of mental disorders. In particular,the relationship between the work characteristics associated with PIVAS, sleep disturbance, and impaired brain function can embody a central pathophysiologic process underlying the increased risk for psychiatric illness present in such workers. 3.2 Strengths of This Study The research shows a number of important strengths. Primarily, there is the selection of the research subjects-the PIVAS staff-that is a greatly neglected category of workers with a uniquely high level of occupation-related stress. The second strength is that it is a large-scale study with a representative sample of 3,525 participants coming from across China. Lastly, the inclusion of the occupation-related factors of PIVAS staff workers in the list of confounding variables improves the accuracy of the correlation tests. 3.3 Limitations of This Study The limitations of the present study include the following. Firstly, the current cross-sectional type of study cannot show a direct causal link between sleeping duration and mental health outcomes. Longitudinal research needs to be applied in order to replicate the temporal linkages found in the present work. Secondly, the present mental disorder assessment had depended on the researchers' questionnaire with a certain potential for recall bias in comparison with clinical diagnoses. Additionally, the presence of the healthy worker effect could distantly affect results in the surveyed working population. Specifically, the presence of serious sleeping disorders or mental health issues could make some people have left the workforce of the PIVAS organization or work in a different context. 4 Conclusions This paper has shown that brief sleep in PIVAS staff is a risk factor for depression, anxiety, and co-occurrence of both. For PIVAS workers not to develop psychiatric conditions, it is crucial to examine the mechanisms and occupational settings related to the development of these conditions among the staff. Abbreviations PIVAS: Pharmacy Intravenous Admixture Services, PHQ-9: Patient Health Questionnaire-9 GAD-7: Generalized Anxiety Disorder-7 OR: Odds Ratio CI: Confidence Interval SD: Standard Deviation HPA: Hypothalamic-Pituitary-Adrenal CDAS: Comorbid Depression and Anxiety Symptoms CMEC: China Multi-Ethnic Cohort COVID-19: Coronavirus Disease 2019 Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of West China Hospital, Sichuan University (Approval No. 20252053) and registered with the Chinese Clinical Trial Registry (Registration Number: ChiCTR2500114132; Registration Date: December 8, 2025). All procedures were conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment. Consent for publication Informed consent was obtained from all participants involved in the study. Competing interests The authors declare that they have no competing interests. Funding This study was funded by the Research Project on the High-Quality Development of Hospital Pharmacy, National Institute of Hospital Administration, NHC, China (NIHAYS2402) and the Youth Project of the Sichuan Pharmaceutical Society (scsyxh202506). Additional support was provided by the National Clinical Key Specialty Construction Project. Author Contribution ZP developed the study methodology and wrote the original draft. MZ conducted data curation, formal analysis, and investigation. YL, HY, ZX, and HN carried out the investigation and data collection. MG, AW, and LW reviewed and edited the manuscript. ZJ conceptualized the study, acquired funding, provided resources, and supervised the project. All authors reviewed the manuscript. Acknowledgements We show greatest gratitude to all the participants. Data Availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. 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J Affect Disord. 2023;333:535–42. https://doi.org/10.1016/j.jad.2023.04.065 . Punia K, Levitt E, Taisir R, Bird BM, Rush B, Remers S, et al. Psychometric validation of the Generalized Anxiety Disorder Scale (GAD-7) and Patient Health Questionnaire (PHQ-9) in an inpatient substance use disorder treatment program. Psychol Addict Behav. 2025. 10.1037/adb0001098 . Sun S, Liu M, Liu H, Li R, Liang Q, Quan W. Association of weekend catch-up sleep ratio with depressive risk: insights from NHANES 2021–2023. BMC Psychiatry. 2025;25:641. https://doi.org/10.1186/s12888-025-07083-w . Li M, Yu X, Zhang W, Yin J, Zhang L, Luo G, et al. The association between weight-adjusted-waist index and depression: results from NHANES 2005–2018. J Affect Disord. 2024;347:299–305. https://doi.org/10.1016/j.jad.2023.11.073 . Wang X, Zhong Y, Wang R, Zhang D, Li Y, Pan Y, et al. Association between sleep duration and anxiety in US adults: a nationally representative cross-sectional study. 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Ann Work Expo Health. 2018;62(4):416–25. https://doi.org/10.1093/annweh/wxy014 . Cui S, Jing FF, Ma H, Zhu M, Yan Y, Wang S. A longitudinal dyadic analysis of financial strain and mental distress among different-sex couples: the role of gender division of labor in income and housework. BMC Public Health. 2025;25:871. https://doi.org/10.1186/s12889-025-22059-x . Staiger T, Stiawa M, Mueller-Stierlin AS, Kilian R, Beschoner P, Gündel H, et al. Masculinity and help-seeking among men with depression: a qualitative study. Front Psychiatry. 2020;11:599039. https://doi.org/10.3389/fpsyt.2020.599039 . Wang X, Lei J, Li W, Liu X, Chen Z, Li Y, et al. Association of physical activity and sleep duration with depression in adolescents: a cohort study in Southwest China. J Affect Disord. 2025;375:202–10. https://doi.org/10.1016/j.jad.2025.120354 . Schipholt IJL, Coppieters MW, Diepens M, Hoekstra T, Ostelo RWJG, Barbe MF, et al. Systemic inflammation, sleep, and psychological factors determine recovery trajectories for people with neck pain: an exploratory study. J Pain. 2024;25(8):104495. https://doi.org/10.1016/j.jpain.2024.02.010 . Nollet M, Wisden W, Franks NP. Sleep deprivation and stress: a reciprocal relationship. Interface Focus. 2020;10(3):20190092. https://doi.org/10.1098/rsfs.2019.0092 . Additional Declarations No competing interests reported. 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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-8607092","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":593365023,"identity":"ab995acf-4064-41c0-a269-098f73dccf25","order_by":0,"name":"Zhicheng Pan","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Zhicheng","middleName":"","lastName":"Pan","suffix":""},{"id":593365025,"identity":"74b752b1-fe30-4e93-b035-524526c3cb12","order_by":1,"name":"Minglin Zheng","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Minglin","middleName":"","lastName":"Zheng","suffix":""},{"id":593365028,"identity":"3347b3fc-173c-4f48-906c-5d10746447d1","order_by":2,"name":"Mengran Guo","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Mengran","middleName":"","lastName":"Guo","suffix":""},{"id":593365031,"identity":"f57507d2-ba0c-4615-b14f-312da6bb7ded","order_by":3,"name":"Yunfu Lan","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Yunfu","middleName":"","lastName":"Lan","suffix":""},{"id":593365034,"identity":"c652bf4b-bd51-4012-b89f-2d42c5233b40","order_by":4,"name":"Hao Yang","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Yang","suffix":""},{"id":593365038,"identity":"4da6422a-48a0-452b-9d4c-62d9545b25a9","order_by":5,"name":"Zhengtan Xu","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Zhengtan","middleName":"","lastName":"Xu","suffix":""},{"id":593365039,"identity":"8f16b61d-7404-4236-b9ed-bcbf7b13430a","order_by":6,"name":"Hengfan Ni","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Hengfan","middleName":"","lastName":"Ni","suffix":""},{"id":593365041,"identity":"30082056-df7a-46a6-8032-977a63a9f618","order_by":7,"name":"Ao Wang","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Ao","middleName":"","lastName":"Wang","suffix":""},{"id":593365046,"identity":"47b820f3-51f3-45f6-bfd7-279476376fb9","order_by":8,"name":"Zhaohui Jin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYBACxmYGBmYgncDAzHyAgbEBIipBpBa2BOK0gABECwOPAXFamNt5D38uqLHJMzjO803i5446eYMDzAdv8zDY5eF2GF+C8YxjacUGh3m3SfaeOWy44QBbsjUPQ3Ixbi08Bsk8bIcTNwC13GZsO5BgcIDHTJqH4UBiAx4th3n+gbTwPANqqQNq4f9GSIthM28bWAsbUAszyBY2QlqMmXn70hJnHmYz/9nbdtgQyDC2nGOQjFOLYf8Z488832wS+84ffmzws61Onu9488MbbyrscGvBlABFE4MBDvVAII9bahSMglEwCkYBFAAAEFpVYjQgNsYAAAAASUVORK5CYII=","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"Zhaohui","middleName":"","lastName":"Jin","suffix":""},{"id":593365047,"identity":"a7d35991-68b5-4930-a2d9-6cb40675cdaa","order_by":9,"name":"Ling Wang","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-01-15 05:23:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8607092/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8607092/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102993116,"identity":"b721663d-c7db-48c2-ad26-dcd264046889","added_by":"auto","created_at":"2026-02-19 11:45:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88553,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of participant enrollment and exclusion.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8607092/v1/9ee85744f36c2715a2b83174.png"},{"id":102993114,"identity":"88250b8d-56a3-4c5f-9200-d0848e76e488","added_by":"auto","created_at":"2026-02-19 11:45:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":62847,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of depression, anxiety, and comorbid symptoms among PIVAS staff stratified by key variables\u003cstrong\u003e.\u003c/strong\u003e (A) Prevalence by gender; (B) Prevalence by age group; (C) Prevalence by sleep duration categories. Abbreviation: PIVAS, Pharmacy Intravenous Admixture Service.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8607092/v1/a6a9e28f2355271249fc0e54.png"},{"id":102993174,"identity":"91681ef1-f069-4a38-948a-8aa89e1bed18","added_by":"auto","created_at":"2026-02-19 11:45:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1401958,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8607092/v1/3e54da6e-99b6-4519-90b9-9daaaa777d26.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between Sleep Duration and the Prevalence of Depression, Anxiety, and Comorbid Symptoms among PIVAS Staff in China: Cross-Sectional Study","fulltext":[{"header":"Background","content":"\u003cp\u003eAppropriate sleep is one of the basic requisites for health. However, due to the rising pace of modern life, as well as rising levels of occupational stress, sleep disorders are becoming an entrenched public health problem. Worldwide, about 12.4% of the adult population suffers from sleep disorders, with a rising incidence of 19.2% in China [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Sleep duration, an essential component of sleep quality, has been found to have a strong association with diverse health outcomes, primarily because it has a great influence on mental health. Various studies have identified a strong relationship between sleep duration and depression, anxiety, and co-occurrence of these symptoms. For instance, with regard to the established sleep need of 7\u0026ndash;9 hours, reduced sleep of less than 7 hours has been found to significantly increase the incidence of depression by a steep 69% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Interestingly, both short sleep duration as well as long sleep duration are found to have an increased rate of depression incidence [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Short sleep duration of less than 7 hours has been found to substantially increase the incidence of anxiety in commercial pilots in particular [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. A Chinese multi-ethnic cohort (CMEC) study has identified a direct relationship between reduced sleep duration and increased incidence of co-occurring symptoms [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These facts re-emphasize the need for adequate sleep of an optimal duration in the prevention of psychiatric disorders.\u003c/p\u003e \u003cp\u003eDepression and anxiety disorders together account for a large proportion of the global burden of diseases [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Both disorders have been seen to occur contemporaneously with lifestyle factors and co-existence with physical comorbid conditions, with a commonality of 80.3% of people with depression suffering from co-existing physical diseases like Hypertension (45.9%) and Hyperlipidaemia (24.0%) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. With the progression of depressive symptoms, they promote anxiety and manic episodes, leading to an increased suicide rate among patients [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Notably, there is a risk for the transmission of intergenerational generations of depression and anxiety disorders from parent to offspring [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This emphasizes how crucial early intervention is. The co-occurrence of both disorders is referred to as comorbid depression and anxiety symptoms (CDAS). Research shows a variation in the relative order of onset of symptoms of the disorder from individual to individual. In this context, it has been explained that 68% of people experience the onset of anxiety disorder symptoms first, followed by 13.5% for the symptoms of depression; Concurrent symptoms of both occur in 18.5% of the general populations [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The disorder has a higher risk of symptoms and relapse when co-existing with other mental conditions. In this context, the relative risk of suicide stands at 4.2 times more than the risk of suffering from depression alone [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. While the association between the disorder of sleep duration and the mental conditions of depression and anxiety has been explored in the past, the epidemiological association with the specified mental disorder in healthcare professionals is still lacking. Hence, the implications of this association for the specified mental disorder in healthcare professionals for the purpose of developing a specific preventive strategy for the disorder in this group of professionals warrants exploration.\u003c/p\u003e \u003cp\u003eThe Pharmacy Intravenous Admixture Service (PIVAS) is an integral service within the hospitals. The staff of PIVAS face heavy occupational stresses such as excessive work, heavy workloads, and possible risk exposures [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These work attributes are likely to affect the regulation of the sleep-wake cycle as well as reduce the total sleeping hours [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Poor sleeping quality is among the major causes of developing mental health disorders. Previous studies that assessed the impacts of sleeping on mental health disorders were mainly conducted on groups comprising nurses and medical physicians [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, the different working patterns of staff in PIVAS warrant distinct studies. Presently, there exists an apparent shortage of large-scale epidemiological studies among the PIVAS staff.\u003c/p\u003e \u003cp\u003eIn light of this, the current study adopted a cross-sectional multicenter design in order to investigate the relationship between sleep duration and depression, anxiety, and co-occurring disorders in PIVAS staff members. The purpose of this study is not only to shed light on improving strategies for mental health care but also to provide advice regarding human resource management in hospitals.\u003c/p\u003e"},{"header":"1 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Study Design and Population\u003c/h2\u003e \u003cp\u003eCross-sectional studies were performed in multiple centers between May and October 2025. Recruitment announcements were spread via two professional platforms: the PIVAS Professional Committee of the National Health Commission Hospital Management Institute and the PIVAS Management Professional Committee of Chinese Pharmaceutical Association. Recruitment of the participants entailed both online questionnaires in professional WeChat groups and direct personal invitations in order to cover the target group comprehensively.\u003c/p\u003e \u003cp\u003eThe inclusion criteria for participants in the study were: (1) full-time employment in the PIVAS department at the participating hospital, (2) voluntary participation in the study, (3) the absence of cognitive or language impairments, with the ability to complete assessments of their sleep and mental health questionnaires. The only exclusion criterion was employment in the PIVAS staff for less than two years. After excluding 555 participants based on the criteria for selection, the final sample of participants was 3,525 staff members (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Assessment of Exposure Variable\u003c/h2\u003e \u003cp\u003eSleep duration is considered the primary exposure variable for which the value is measured through a standardized questionnaire. The mean daily sleep duration is computed by taking a weighted average, which is determined by the following formula: (5 \u0026times; average sleep time on weekdays\u0026thinsp;+\u0026thinsp;2 \u0026times; average sleep time during weekends) / 7 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.3 Assessment of Outcome Variables\u003c/h2\u003e \u003cp\u003eThe severity of depressive symptoms was assessed using the Patient Health Questionnaire 9 (PHQ-9) scale [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. There were nine questions on which the respondents answered using a 4-point scale ranging from 0 (\"Never\") to 3 (\"Nearly every day\"). Scoring was from 0 to 27, with higher scores reflecting more severe symptoms. In accordance with criteria for diagnosis, a score of 10 or above was taken to reveal the presence of depressive symptoms [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For assessing the symptoms of anxiety, the Generalized Anxiety Disorder 7-item Scale (GAD-7 scale) was utilized [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. There were seven questions on which the respondents answered using a 4-point scale from 0 (\"Never\") to 3 (\"Nearly every day\"). Scoring was from 0 to 21, with a score above 10 reflecting the symptoms of anxiety [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In the present study, persons who scored 10 or above on both scales were identified as having co-existing symptoms of depression and anxiety [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e1.4 Covariates\u003c/h2\u003e \u003cp\u003eCovariates were determined based on previous research regarding the factors of hospital personnel and occupational health psychology literature [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], which included sociodemographic factors, job information, and lifestyle factors. The sociodemographic factors included age, sex, marital status (never married, married/cohabiting, widowed/divorced/separated), education (junior college or less, Bachelor's degree, Master's degree or higher), and professional title (junior, intermediate, senior). Job characteristics included PIVAS years of service, daily work hours on the Laminar Airflow workbench, daily admixture workload (\u0026lt;\u0026thinsp;50, 50\u0026ndash;100, 100\u0026ndash;200, \u0026gt;\u0026thinsp;200 bags), frequency of handling sessions for hazardous drugs (never, occasionally, often, frequently), one-way commuting time (\u0026lt;\u0026thinsp;30, 30\u0026ndash;60, 60\u0026ndash;90, \u0026gt;\u0026thinsp;90 minutes), and history of dispensing errors (none, 1\u0026ndash;3, 4\u0026ndash;6, 7\u0026ndash;12, \u0026gt;\u0026thinsp;12). The factors of lifestyle and behavior included daily short video viewing duration (low, moderate, high, very high), daily gaming duration (non-player, \u0026lt;\u0026thinsp;30 minutes, 30\u0026ndash;60 minutes, 1\u0026ndash;3 hours, \u0026gt;\u0026thinsp;3 hours), smoking status (non-smoker, light, moderate, heavy, very heavy), alcohol consumption (non-drinker, light, moderate, heavy), physical activity frequency (inactive, light, moderate, high, very high), and coffee consumption (never, occasionally, light, regular, heavy).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e1.5 Statistical Analyses\u003c/h2\u003e \u003cp\u003eThe data analysis used the R software package version 3.5.2. Categorical data is expressed in the form of frequency (n) and percent (%), whereas the continuous data is expressed in the form of mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). To compare the means among two groups, the t test and rank sum test were used. Chi-square tests were applied for comparing categorical data.\u003c/p\u003e \u003cp\u003eTo examine the link between sleep duration and mental health outcomes, we carried out multivariate logistic regression analyses. Three hierarchical models were set to reduce the risk of confounding. These were Model 1, the unadjusted model; Model 2, adjusted for sociodemographic factors; and Model 3, adjusted for occupational factors, lifestyle variables, and the variables in the previous model. The results are presented as odds ratios with 95% confidence intervals. The cut-off point for statistical significance was established at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for the two-tailed test.\u003c/p\u003e \u003c/div\u003e"},{"header":"2 Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Baseline Characteristics of Participants\u003c/h2\u003e \u003cp\u003eThis survey included a total of 3,525 PIVAS staff members. The mean age was 35.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0 years. Male staff members numbered 621 (17.62%), while female staff members numbered 2,904 (82.38%). Sleep duration divided participants into three groups that included sleep duration of 8\u0026ndash;10 hours (reference group), with a total of 430 participants ; sleep duration of 6\u0026ndash;7 hours, with a total of 2,575 participants ; and sleep duration of 3\u0026ndash;5 hours with a total of 520 participants (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Demographic results showed that sleep duration had significant correlations with age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016), gender (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and marital status (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, there were non-significant correlations with educational status (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.076). In regard to work-related aspects, work duration on laminar flow workbenches (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049), commuting time (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01), Professional title (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024), and frequency of dispensing errors (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001)had significant correlations with sleep duration. Concerning aspects of lifestyles related to sleep duration, duration of short video viewing, gaming time, smoking status, alcohol consumption, coffee consumption, and physical activity frequency had significant correlations with sleep duration (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of PIVAS staff stratified by sleep duration.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eSleep Duration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;3525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u0026ndash;10 h (n\u0026thinsp;=\u0026thinsp;430)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u0026ndash;7 h (n\u0026thinsp;=\u0026thinsp;2575)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u0026ndash;5 h (n\u0026thinsp;=\u0026thinsp;520)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.1\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of Service (years), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime Spent Working in the Laminar Airflow Workbench (h), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e621 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e449 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120 (23.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2904 (82.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e378 (87.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2126 (82.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e400 (76.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever Married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e721 (20.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (17.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e523 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e122 (23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried/Cohabiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2594 (73.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e335 (77.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1909 (74.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e350 (67.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed/Divorced/Separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e210 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e143 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (9.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation Level, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior college or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e461 (13.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (14.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e324 (12.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73 (14.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2796 (79.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e340 (79.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2037 (79.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e419 (80.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster's Degree or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e268 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e214 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfessional Title, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1661 (47.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e218 (50.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1184 (46.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e259 (49.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1577 (44.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192 (44.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1167 (45.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e218 (41.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e287 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e224 (8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily Admixture Workload, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50 bags\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e339 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e245 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;100 bags\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e619 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e458 (17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u0026ndash;200 bags\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1460 (41.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180 (41.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1068 (41.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e212 (40.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;200 bags\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1107 (31.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127 (29.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e804 (31.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e176 (33.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHazardous Drug Preparation Frequency, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e408 (11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (14.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e295 (11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2349 (66.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e276 (64.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1731 (67.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e342 (65.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOften\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e512 (14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (16.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e359 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82 (15.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequently\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e256 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne-way Commuting Time, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2570 (72.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e325 (75.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1902 (73.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e343 (66.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;60 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e798 (22.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e566 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e146 (28.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;90 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;90 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of dispensing errors, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1809 (51.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e276 (64.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1307 (50.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e226 (43.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;3 times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1554 (44.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1159 (45.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e252 (48.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026ndash;6 times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u0026ndash;12 times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12 times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShort-Video Viewing Duration, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e805 (22.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150 (34.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e545 (21.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110 (21.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1549 (43.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e190 (44.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1155 (44.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e204 (39.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e965 (27.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e734 (28.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e158 (30.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh - frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e206 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e141 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (9.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily Gaming Duration, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-player\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2611 (74.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e321 (74.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1958 (76.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e332 (63.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e382 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e259 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74 (14.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;60 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e295 (8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e203 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54 (10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;3 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e186 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e130 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking Status, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon - smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3279 (93.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e414 (96.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2414 (93.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e451 (86.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery heavy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol consumption, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon - drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2697 (76.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e368 (85.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1975 (76.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e354 (68.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e705 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (12.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e524 (20.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e127 (24.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical activity frequency, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e445 (12.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e296 (11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e111 (21.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2225 (63.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e270 (62.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1645 (63.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e310 (59.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e580 (16.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 (20.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e423 (16.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226 (6.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e177 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery High\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee consumption frequency, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1344 (38.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e195 (45.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e958 (37.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e191 (36.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1264 (35.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150 (34.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e952 (37.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e162 (31.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLightly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e416 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e323 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegularly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e457 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e316 (12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) for continuous variables and frequency (percentage) for categorical variables. \u003cem\u003eP\u003c/em\u003e-values were calculated using one-way ANOVA or Kruskal-Wallis test for continuous variables, and Chi-square test or Fisher's exact test for categorical variables. Abbreviation: PIVAS, Pharmacy Intravenous Admixture Service.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe data shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e suggested that the groups who slept for 3\u0026ndash;5 hours had a significantly high total depression and anxiety scale scores, as well as a proportion of persons with mental illness, compared to other groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Baseline characteristics of PIVAS staff stratified by sleep duration.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of sleep duration with depression, anxiety, and comorbid symptoms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eSleep Duration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;3525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u0026ndash;10 h (n\u0026thinsp;=\u0026thinsp;430)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u0026ndash;7 h (n\u0026thinsp;=\u0026thinsp;2575)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u0026ndash;5 h (n\u0026thinsp;=\u0026thinsp;520)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Depression Score, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Anxiety Score, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3009 (85.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e404 (94.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2256 (87.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e349 (67.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e516 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e319 (12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e171 (32.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3289 (93.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e418 (97.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2434 (94.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e437 (84.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e236 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e141 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbid Symptoms, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3316 (94.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e420 (97.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2456 (95.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e440 (84.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e119 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData are presented as n (%). Depression was defined as PHQ-9 score\u0026thinsp;\u0026gt;\u0026thinsp;10; Anxiety was defined as GAD-7 score\u0026thinsp;\u0026gt;\u0026thinsp;10; Comorbid symptoms was defined as concurrent presence of both conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Prevalence of Depression, Anxiety, and Comorbid Symptoms Stratified by Gender, Age, and Sleep Duration\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDepression, anxiety, and comorbidity symptoms were compared across PIVAS staff members based on a questionnaire response in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The findings of this study bring to notice that depression had a relatively higher prevalence of 14.6%, which was substantially higher than that of anxiety and comorbidity symptoms. Also, a gender-related study revealed that a relatively higher prevalence of all mental illness occurred in males than in females (depression: 17.1% vs. 14.1%; anxiety: 9.5% vs. 6.1%; comorbidity symptoms: 8.4% vs. 5.4%). Also, a prevalence study related to mental illness demonstrated that a relatively higher prevalence of all mental illness occurred in staff members aged under 25 years (depression: 20.6%; anxiety: 8.3%; comorbidity symptoms: 7.4%). Furthermore, a relatively shorter sleep duration had a substantially higher prevalence of mental illness (depression 32.9%, anxiety 16.0%, comorbidity symptoms 15.4%) than other groups in this study. Moreover, in all categories of this study, a relatively higher prevalence of depression was measured than that of anxiety and comorbidity symptoms combined.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of depression, anxiety, and comorbid symptoms stratified by demographic and sleep characteristics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eDepression \u0026amp; Anxiety\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e515 (82.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (17.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e562 (90.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e569 (91.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52 (8.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2494 (85.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e410 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2727 (93.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e177 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2747 (94.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e157 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154 (79.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (20.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e178 (91.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e179 (92.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;25, \u0026le;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1440 (83.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e277 (16.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1588 (92.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e129 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1600 (93.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e117 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;35, \u0026le;\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1113 (87.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164 (12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1205 (94.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1217 (95.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e302 (89.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e318 (94.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e320 (95.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep Duration, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8-10h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e404 (94.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e418 (97.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e420 (97.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-7h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2256 (87.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e319 (12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2434 (94.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e141 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2456 (95.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e119 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-5h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e349 (67.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171 (32.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e437 (84.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e440 (84.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData are presented as n (%). Depression was defined as PHQ-9 score\u0026thinsp;\u0026gt;\u0026thinsp;10; Anxiety was defined as GAD-7 score\u0026thinsp;\u0026gt;\u0026thinsp;10; Comorbid symptoms was defined as concurrent presence of both conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Multivariable Logistic Regression Analysis of the Association between Sleep Duration and Mental Health Outcome\u003c/h2\u003e \u003cp\u003eWe constructed three logistic regression models to assess the interrelationship between sleep duration and mental health risk in a multivariate model (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In Model 1, when not adjusting for any confounding variables, short sleep duration was significantly linked to an increase in depression (OR\u0026thinsp;=\u0026thinsp;7.61, 95% CI.: 4.92\u0026ndash;11.78), anxiety (OR\u0026thinsp;=\u0026thinsp;6.62, 95% CI.: 3.56\u0026ndash;12.30), and comorbid symptoms (OR\u0026thinsp;=\u0026thinsp;7.64, 95% CI.: 3.90-14.94) compared to the reference category of sleep duration (8\u0026ndash;10 hours). After stepwise adjustment for demographic factors (Model 2) and for occupation and lifestyle factors (Model 3), none of these associations lost significance. In Model 3, when fully adjusting for confounding variables, short sleep duration was still significantly linked to an increase in depression symptoms (OR\u0026thinsp;=\u0026thinsp;5.41, 95% CI.: 3.43\u0026ndash;8.54), anxiety symptoms (OR\u0026thinsp;=\u0026thinsp;4.38, 95% CI.: 2.30\u0026ndash;8.35), as well as comorbid symptoms (OR\u0026thinsp;=\u0026thinsp;4.95, 95% CI.: 2.47\u0026ndash;9.93). A dose-response effect was also found to exist with significance at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all models.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable logistic regression analysis of the association between sleep duration and mental health outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel II\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel III\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8-10h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-7h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2 (1.4, 3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2 (1.4, 3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9 (1.2, 2.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-5h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.6 (4.9, 11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.6 (4.9, 11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.4 (3.4, 8.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrend Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8-10h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-7h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0 (1.1, 3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9 (1.1, 3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7 (0.9, 3.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-5h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.6 (3.6, 12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.2 (3.3, 11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4 (2.3, 8.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrend Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbid Symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8-10h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-7h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0 (1.1, 3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0 (1.0, 3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7 (0.9, 3.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-5h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.6 (3.9, 14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2 (3.6, 14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.0 (2.5, 9.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrend Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eModel 1: Unadjusted model. Model 2: Adjusted for gender, age, education level, marital status, professional title, and working years. Model 3: Adjusted for variables in Model 2 plus daily admixture workload, handling of hazardous drugs, commuting time, history of dispensing errors, short-video duration, gaming duration, smoking status, alcohol consumption, physical activity, and coffee consumption. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 was considered statistically significant. Abbreviations: OR, odds ratio; CI, confidence interval; Ref., reference group.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Discussion","content":"\u003cp\u003eThis study was conducted based on the sleep duration of the PIVAS staff as the exposure factor, and the results showed the relationship between the sleep duration of the PIVAS staff and the prevalence of depression, anxiety, and comorbid symptoms even after adjusting the potential confounders of demographics, work, and lifestyle factors. In the 8\u0026ndash;10 hour control group, the risks of having mental health problems were significantly higher for 3\u0026ndash;5 hours of sleep duration, showing OR of 5.4 (95%CI: 3.4\u0026ndash;8.5) for depression, 4.4 (95%CI: 2.3\u0026ndash;8.4) for anxiety, and 5.0 (95%CI: 2.5\u0026ndash;9.9) for comorbid symptoms. There was a significant dose-response trend among them (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), showing that the risk of mental impairment increases cumulatively as the duration of sleep shortens. In addition, the risks of mental health impairment were higher in the subgroup analysis of demographics, including men and those aged less than 25 years.\u003c/p\u003e \u003cp\u003eThese results are in line with multiple other prospective and cross-sectional studies associating sleep duration with depression, anxiety, and comorbid symptoms risks. For example, the study on the elderly population of China found short sleep duration may contribute to increased vulnerability to depression [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Similarly, for anxiety risk. Among Chinese civil aviation pilots, it was found that short sleep duration may cause elevated anxiety risk [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The comorbidity of depression and anxiety is also relatively common in the general population. The China Multi-Ethnic Cohort (CMEC) study demonstrates individuals with less than 7 hours of sleep at night are more likely to suffer from comorbid symptoms [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. PIVAS workers work under a special working condition. They need to concentrate for long periods and repeatedly carry out similar work tasks. These special occupational stresses may predispose them to adverse consequences of sleep loss, causing a variety of mental disorders [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Importantly, we found male PIVAS workers are more susceptible to mental health problems compared to female workers. This contrasts with some previous findings. For example,in studies involving Parkinson's disease patients, the prevalence rate of depressive symptoms in female (66.6%) patients is higher than in males (55.1%) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In a study investigating psychological impact of the Coronavirus Disease 2019 (COVID-19), women were found to be at higher risk for mental distress [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In the CMEC study, comorbidity was found among women and middle-aged groups but not in men [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The gender discrepancy may be related to certain features specific to the PIVAS setting. Among PIVAS workers, it was found that men are especially prone to depressive disorder because of low job control owing to repetitiveness of the task,which shows a clear discrepancy with female workers [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. When employees experience high job pressure but low job rewards, this could erode men's social identities as family breadwinners, contributing to psychological distress [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Furthermore, shame associated with seeking help often prevents men from asking for assistance, leading to their psychological symptoms worsening in silence [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Nevertheless,these hypotheses need to be tested in future research. Analysis by age demonstrates young workers have a greater risk of developing mental problems. Consistent with the pattern seen in young populations. Young people tend to be more susceptible to external environmental factors, thereby exhibiting greater psychological vulnerability [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Potential Mechanisms\u003c/h2\u003e \u003cp\u003eThe neurobiological processes involved also have an important role to play in relating short sleep to mental illness event,which is likely to have more implications within the PIVAS workplace setting. First, the hypothalamic-pituitary-adrenal (HPA) axis is set off by chronic sleep deprivation, which causes an increase in cortisol production [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This persistent dysregulation of cortisol secretion prevents the body from regulating stress and emotions, leading to an increased risk of mental illness [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Therefore, hyperactivation of the HPA axis is clinically recognized as one of the criteria for diagnosing mental disorders [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. For professionals working under challenging conditions with PIVAS' zero tolerance to errors, there would be heightened levels of overacting to stress with short sleep hours to result in stress mental conditions. The work environment of PIVAS could also have adverse effects on disturbances of the circadian rhythms. The employees work long hours in a sealed clean room, mainly under artificial lighting,with minimal access to direct sunlight, thus contributing to the disturbance of melatonin secretion, leading to sleep structure disorder and impaired cognitive function [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Additionally, melatonin regulation of sleep has been associated with modifications in the structure of neurotransmitter systems, including changes in serotonin, dopamine, and norepinephrine receptor sensitivity [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The work setting in the PIVAS operates at a high level of intensity,involves repetition of tasks,mental concentration, and excessive work efforts. The main implication of human errors arising from insomnia could be the development of mental disorders. In particular,the relationship between the work characteristics associated with PIVAS, sleep disturbance, and impaired brain function can embody a central pathophysiologic process underlying the increased risk for psychiatric illness present in such workers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Strengths of This Study\u003c/h2\u003e \u003cp\u003eThe research shows a number of important strengths. Primarily, there is the selection of the research subjects-the PIVAS staff-that is a greatly neglected category of workers with a uniquely high level of occupation-related stress. The second strength is that it is a large-scale study with a representative sample of 3,525 participants coming from across China. Lastly, the inclusion of the occupation-related factors of PIVAS staff workers in the list of confounding variables improves the accuracy of the correlation tests.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Limitations of This Study\u003c/h2\u003e \u003cp\u003eThe limitations of the present study include the following. Firstly, the current cross-sectional type of study cannot show a direct causal link between sleeping duration and mental health outcomes. Longitudinal research needs to be applied in order to replicate the temporal linkages found in the present work. Secondly, the present mental disorder assessment had depended on the researchers' questionnaire with a certain potential for recall bias in comparison with clinical diagnoses. Additionally, the presence of the healthy worker effect could distantly affect results in the surveyed working population. Specifically, the presence of serious sleeping disorders or mental health issues could make some people have left the workforce of the PIVAS organization or work in a different context.\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Conclusions","content":"\u003cp\u003eThis paper has shown that brief sleep in PIVAS staff is a risk factor for depression, anxiety, and co-occurrence of both. For PIVAS workers not to develop psychiatric conditions, it is crucial to examine the mechanisms and occupational settings related to the development of these conditions among the staff.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePIVAS: Pharmacy Intravenous Admixture Services, PHQ-9: Patient Health Questionnaire-9\u003c/p\u003e\n\u003cp\u003eGAD-7: Generalized Anxiety Disorder-7\u003c/p\u003e\n\u003cp\u003eOR: Odds Ratio CI: Confidence Interval\u003c/p\u003e\n\u003cp\u003eSD: Standard Deviation\u003c/p\u003e\n\u003cp\u003eHPA: Hypothalamic-Pituitary-Adrenal\u003c/p\u003e\n\u003cp\u003eCDAS: Comorbid Depression and Anxiety Symptoms\u003c/p\u003e\n\u003cp\u003eCMEC: China Multi-Ethnic Cohort\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCOVID-19: Coronavirus Disease 2019\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of West China Hospital, Sichuan University (Approval No. 20252053) and registered with the Chinese Clinical Trial Registry (Registration Number: ChiCTR2500114132; Registration Date: December 8, 2025). All procedures were conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eInformed consent was obtained from all participants involved in the study.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was funded by the Research Project on the High-Quality Development of Hospital Pharmacy, National Institute of Hospital Administration, NHC, China (NIHAYS2402) and the Youth Project of the Sichuan Pharmaceutical Society (scsyxh202506). Additional support was provided by the National Clinical Key Specialty Construction Project.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eZP developed the study methodology and wrote the original draft. MZ conducted data curation, formal analysis, and investigation. YL, HY, ZX, and HN carried out the investigation and data collection. MG, AW, and LW reviewed and edited the manuscript. ZJ conceptualized the study, acquired funding, provided resources, and supervised the project. All authors reviewed the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe show greatest gratitude to all the participants.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003evan Straten A, Weinreich KJ, F\u0026aacute;bi\u0026aacute;n B, Reesen J, Grigori S, Luik AI, et al. The prevalence of insomnia disorder in the general population: a meta-analysis. 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Interface Focus. 2020;10(3):20190092. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rsfs.2019.0092\u003c/span\u003e\u003cspan address=\"10.1098/rsfs.2019.0092\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"PIVAS, Sleep duration, Depression, Anxiety, Comorbid symptoms, Cross-sectional study","lastPublishedDoi":"10.21203/rs.3.rs-8607092/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8607092/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eInsufficient sleep is a serious risk factor of mental disorders. However, the research evidence remains quite limited among the personnel working at Pharmacy Intravenous Admixture Services (PIVAS). It is therefore the purpose of this research to explore the relationship between the length of sleep and symptoms of depression, anxiety, and co-morbidity among PIVAS personnel in China.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe cross-sectional study was conducted among 3,525 PIVAS employee members between May and October 2025. The research utilized the Patient Health Questionnaire 9 (PHQ-9) to identify depression and Generalized Anxiety Disorder 7 (GAD-7) to identify symptoms of anxiety. Sleep duration was measured and grouped into three to represent the main exposure of interest (8\u0026ndash;10 h, 6\u0026ndash;7 h, and 3\u0026ndash;5 h). The adjusted odds ratio and 95% confidence interval were measured. The study protocol was registered with the Chinese Clinical Trial Registry (ChiCTR2500114132).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003ePrevalences of depression, anxiety, and comorbid symptoms among PIVAS personnel were 14.6%, 6.7%, and 5.9%, respectively. After adjusting for demographics, occupation, and lifestyle variables, a significantly increased risk for depression (OR\u0026thinsp;=\u0026thinsp;5.4, 95% CI: 3.4\u0026ndash;8.5), anxiety (OR\u0026thinsp;=\u0026thinsp;4.4, 95% CI: 2.3\u0026ndash;8.4), and co-symptoms (OR\u0026thinsp;=\u0026thinsp;5.0, 95% CI: 2.5\u0026ndash;9.9) was found for short sleep (3\u0026ndash;5 h) compared to the reference group (8\u0026ndash;10 h) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There was a significant dose response trend (trend \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These findings reveal a significantly high prevalence of mental illnesses among male employees working with PIVAS, as well as among persons\u0026thinsp;\u0026lt;\u0026thinsp;25 years old.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eBased on the results of the research, the major risk factor for the development of depression, anxiety and comorbid symptoms with PIVAS is sleeping for a shorter period of time. The group of people at a high risk of developing mental health issues is males and those under 25 age.\u003c/p\u003e","manuscriptTitle":"Association between Sleep Duration and the Prevalence of Depression, Anxiety, and Comorbid Symptoms among PIVAS Staff in China: Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-19 11:45:32","doi":"10.21203/rs.3.rs-8607092/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-01T09:55:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"268226907036712601994627643143758256606","date":"2026-03-01T06:44:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-23T08:24:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"139818338851395975142575161944948059270","date":"2026-02-23T05:58:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-16T12:47:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-20T05:39:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-17T11:24:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-17T11:23:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-01-15T05:16:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"598ad2ba-3c88-49b4-865a-d82c71ba5f1e","owner":[],"postedDate":"February 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-19T11:45:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-19 11:45:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8607092","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8607092","identity":"rs-8607092","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}