Abstract
This study investigated the association between work stress and sleep disturbance among Korean workers, focusing on the mediating effects of somatic and cognitive pre-sleep arousal symptoms. Data were derived from the “Korean Work, Sleep, and Health Study (KWSHS)”, involving 4,393 participants. Work stress was assessed using the Korean Occupational Stress Scale, and sleep disturbances were measured using the Insomnia Severity Index and Pittsburgh Sleep Quality Index. The Pre-Sleep Arousal Scale was utilized for assessing pre-sleep arousal status. For statistical analyses, the chi-square test, logistic regression analysis, and mediation analysis were used. Mediation analysis revealed that somatic pre-sleep arousal predominantly mediated the relationship between hazardous physical environments and insomnia symptoms (52.5%), while cognitive pre-sleep arousal was the primary mediator for high job demands (48.0%), organizational injustice (48.6%), and job insecurity (46.6%). These findings suggest that somatic and cognitive pre-sleep arousal serve distinct mediating roles in the relationship between specific types of work stress and sleep disturbances.
Keywords: Sleep initiation and maintenance disorders, Sleep quality, Occupational stress, Arousal, Pre-sleep arousal, Mediation analysis
Introduction
Sleep is a critical determinant of adult health, and work stress is a well-known risk factor for sleep disturbance1). Previous studies have demonstrated that work stress is associated with insomnia, poor sleep quality, and other sleep disorders, all of which can have detrimental effects on both physical and mental well-being2). Poor sleep quality increases the risk of cardiovascular diseases and metabolic disorders, including obesity and diabetes, and exacerbates depression and anxiety.
There is a significant negative association between work stress and sleep health1, 3). Various subtypes of work stress, such as job demands, organizational injustice, and low job control, have been identified to influence sleep health1, 4). Work stress causes sleep problems primarily through two mechanisms: cognitive and somatic arousal5, 6). Studies have shown that work-related stress elevates arousal levels, which can interfere with sleep3). Hyperarousal, which includes both cognitive and somatic arousal, mediates the relationship between stress and sleep quality6, 7). Physiologically, this involves increased activity of the sympathetic nervous system and activation of the hypothalamic-pituitary-adrenal (HPA) axis6). Somatic arousal involves physical symptoms, such as muscle tension, increased heart rate, and other symptoms associated with activated sympathetic nervous system3). Cognitive arousal refers to mental activities that keep the brain awake, such as worry, rumination, and repetitive thought6, 8). Additionally, EEG spectral analysis revealed a relationship between pre-sleep cognitive arousal and cortical arousal during sleep in patients with insomnia disorder9).
Although numerous studies have investigated the association between work stress and sleep quality, research on the mechanisms underlying this relationship remains limited, particularly regarding the mediating role of pre-sleep arousal symptoms5). Most studies have been conducted in Western populations, resulting in a limited understanding of these dynamics in different cultural contexts, such as among Korean workers. A previous study comparing sleep duration and perceptions between Japanese and Canadian university students revealed that Japanese students had shorter sleep durations and lower sleep efficiency compared with Canadian students, but reported feeling less fatigue, having better health conditions, and believing that the ideal sleep duration was shorter than Canadian students thought. This suggests that objective sleep indicators, subjective health levels, and sleep satisfaction can vary depending on cultural background10). Research focusing on the association between work stress and sleep disturbance using validated questionnaires in the general Korean working population remains limited.
This study aimed to address this gap by exploring the association between work-related stress and sleep quality among Korean workers. Specifically, we investigated whether pre-sleep arousal (both cognitive and somatic) mediated this association to examine the underlying pathway. Hence, this study sought to answer two research questions: (1) What is the relationship between work stress and sleep disturbance? (2) Does pre-sleep arousal mediate the relationship between work stress and sleep disturbances?
Materials and Methods
Study population
This study used baseline data from the ‘Korean Work Sleep and Health Study (KWSHS)’, a comprehensive investigation of working environment, sleep, and health among Korean workers11). Although the KWSHS is designed as a longitudinal study, the current analysis focuses solely on cross-sectional data from the baseline survey. The KWSHS commenced in August 2022 and was conducted online, targeting the general working population of South Korea. It enrolled all working-age individuals of both genders and included white-, pink-, and blue-collar workers. Participation and enrollment were facilitated through an online platform. The survey included questionnaires on comprehensive working conditions and health status. Participants with missing or illogical values in variables for work stress and sleep disturbance were excluded from the analysis, and a total of 4,393 participants were analyzed (Fig. 1).
Fig. 1.
Study flow chart.
Work stress
Perceived work stress was estimated using KOSS®19 (Korean Occupational Stress Scale), which consisted of 19 questions and eight subcomponents as follows: physical work environment (2 questions), job demand (3 questions), job control (2 questions), social support (2 questions), job insecurity (2 questions), organizational justice (4 questions), inappropriate reward (2 questions), and work-life balance (2 questions)12). The scores for each question ranges from one to four. Hence, the score ranges of work stress were as follows: physical work environment (2–8), job demand (3–12), job control (2–8), social support (2–8), job insecurity (2–8), organizational justice (4–16), inappropriate reward (2–8), and work-life balance (2–8). Higher scores indicated more stressful conditions13). Cut-off points differed between the sexes, and this study used the cut-off points provided by the KOSHA (Korea Occupational Safety and Health Agency) guidelines. The following are the cut-off points for occupational stress: for a hazardous physical environment (7 for men and 6 for women); for high job demands (8 for men and 10 for women); for low job control (5 for male and 7 for female); for low social support (5 for male and 7 for female); for job insecurity (6 for male and 5 for female); for organizational injustice (10 for male and 11 for female); for inappropriate reward (6 for male and 5 for female); for work-life imbalance (6 for both genders). This study considered that the cut-off point or higher scores as the work-related stress group.
Insomnia symptoms, sleep quality, and pre-sleep arousal symptoms
Using validated questionnaires, insomnia symptoms, sleep quality, and pre-sleep arousal symptoms were assessed for evaluating sleep disturbance. The ISI (Insomnia Severity Index) was used for estimating insomnia symptoms, and sleep quality was assessed using (Pittsburgh Sleep Quality Index)14, 15). PSAS (Pre-Sleep Arousal Scale) was used for estimating the pre-sleep arousal scale16, 17). The pre-sleep arousal scale consists of cognitive and somatic components. The cut-off points for the ISI, PSQI, PSAS-cognitive, and PSAS-somatic were 14, 8, 19, and 13, respectively. This study identified a cut-off score of 8 for the PSQI-K, differing from the frequently reported cut-off score of 6 in other language versions of the Pittsburgh Sleep Quality Index (PSQI)18). Higher scores than the cut-off points were regarded as insomnia symptoms, low-quality sleep, cognitive pre-sleep arousal symptoms, and somatic pre-sleep arousal symptoms.
Other variables
Occupations were classified as managers, professionals, office workers, service and sales workers, or manual workers. Age, sex, educational level, occupation, employment status, full-time job/part-time job, income, working hours, and shift work were included as covariates. Age was divided into five groups: 20–29, 30–39, 40–49, 50–59, and >60 yr. Educational level was categorized into three distinct groups: ‘middle school or less’, ‘high school’, and ‘college or more’. Monthly income was classified into four groups (Quartile: lowest, low middle, high middle, highest). Employment status was divided into standard, subcontracted, and self-employed. Weekly working hours were divided into five groups (1–34 h, 35–40 h, 41–52 h, 53–60 h, and more than 60 h per week), and 35–40 h per week was considered the standard working hours. Shift work was defined as working outside of standard daytime hours, including night shifts and rotating schedules. Smoking status, alcohol, and coffee beverage consumption were asked of respondents. Smoking is classified into non-smokers, ex-smokers, or current smokers. Drinking two times more time per week or drinking more than six units at once were considered as risk alcohol drinking. More than 2 cups of coffee consumption were regarded as excessive coffee consumption. Hypertension, diabetes, obstructive sleep apnea (OSA), and mental illness, all of which were diagnosed by physicians, were assessed by self-report.
Statistical analysis
Prevalence of insomnia symptoms and quality of sleep were compared according to the characteristics of the study participants. The prevalence of insomnia symptoms and low-quality sleep was estimated based on the presence of various work stressors, and a χ2 test was performed for statistical analysis. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using logistic regression analysis to determine the relationship between work stress and sleep disturbance.
The mediation analysis of this study is grounded in the conceptual diagram (Fig. 2). Mediation analysis was performed using the newly introduced “mediate” command in Stata Ver. 18. A single-mediator model was employed to assess the mediating role of pre-sleep arousal (cognitive and somatic) in the relationship between work stress (predictor) and sleep disturbances (outcomes: insomnia symptoms and low sleep quality). The total effect is divided into the direct effect and the indirect effect. The initial pathway is a direct effect; occupational stress correlates with sleep disturbances, independent of pre-sleep arousal symptoms. The second pathway is the indirect effect, wherein pre-sleep arousal symptoms correlate with sleep disturbances, as occupational stress is linked to higher levels of pre-sleep arousal symptoms. The direct effect estimates the odds of sleep disturbance associated with the presence of work stress compared to its absence, while maintaining constant pre-sleep arousal levels. The natural indirect effect assesses the odds of sleep disturbance in the presence or absence of the pre-sleep arousal symptom at a consistent level of work stress. The effect size was presented as odds ratios (OR) and 95% confidence intervals (CI). Mediated proportion is the effect size of the indirect effect divided by the effect size of the total effect. Covariates included in the analysis were sex, age, education level, income, employment status, job type (full-/part-time), occupation, weekly working hours, shift work, and health-related variables (e.g., hypertension, diabetes, mental illness, obstructive sleep apnea, smoking, alcohol consumption, and coffee intake). For each type of work stress (e.g., high job demand, job insecurity, hazardous physical environment), separate models were run to evaluate the mediating effects of cognitive and somatic pre-sleep arousal independently. This resulted in a total of 16 mediation models (8 types of work stress × 2 mediators).
Fig. 2.
Conceptual diagram.
All analyses were cross-sectional, utilizing data collected at baseline. To address the potential inflation of Type 1 errors due to multiple comparisons, we applied Bonferroni corrections where appropriate in the mediation and logistic regression analyses. Specifically, for the mediation analyses involving multiple predictors (work stress subtypes), mediators (cognitive and somatic pre-sleep arousal), and outcomes (insomnia symptoms and low sleep quality), the significance threshold was adjusted by dividing the standard alpha level (0.05) by the number of comparisons conducted within each analysis set.
Results
Table 1 presents participant characteristics and sleep disturbance. Females and participants in their thirties showed a slightly higher prevalence of sleep disturbance. Regarding socioeconomic status, subcontractors, part-time workers, service/sales workers were related to insomnia and low-quality sleep. Long working hours and shift work are linked to sleep disturbance. Hypertension, diabetes, Mental illness, and OSA increased insomnia symptoms and low-quality sleep. Smoking, risky alcohol drinking, and excessive coffee consumption were associated with sleep disturbance.
Table 1. Characteristics of study participants and prevalence of sleep disturbance (insomnia symptoms and low-quality sleep).
| Total N (%)* |
Insomnia symptoms |
Low quality sleep |
||||
|---|---|---|---|---|---|---|
| No n (%)** |
Yes n (%)** |
No n (%)** |
Yes n (%)** |
|||
| Sex | Male | 2,393 (54.5) | 1,879 (78.5) | 514 (21.5) | 1,439 (60.1) | 954 (39.9) |
| Female | 2,000 (45.5) | 1,547 (77.4) | 453 (22.6) | 1,054 (52.7) | 946 (47.3) | |
| Age group | 15–29 | 864 (19.7) | 655 (75.8) | 209 (24.2) | 515 (59.6) | 349 (40.4) |
| 30–39 | 873 (19.9) | 653 (74.8) | 220 (25.2) | 471 (53.9) | 402 (46.1) | |
| 40–49 | 1,069 (24.3) | 825 (77.2) | 244 (22.8) | 575 (53.8) | 494 (46.2) | |
| 50–59 | 1,095 (24.9) | 864 (78.9) | 231 (21.1) | 613 (56.0) | 482 (44.0) | |
| ≥60 | 492 (11.2) | 429 (87.2) | 63 (12.8) | 319 (64.8) | 173 (35.2) | |
| Education | Middle school or less | 21 (0.5) | 13 (61.9) | 8 (38.1) | 7 (33.3) | 14 (66.7) |
| High school | 748 (17.0) | 576 (77.0) | 172 (23.0) | 414 (55.4) | 334 (44.6) | |
| College or more | 3,624 (82.5) | 2,837 (78.3) | 787 (21.7) | 2,072 (57.2) | 1,552 (42.8) | |
| Income | Lowest | 1,192 (27.1) | 930 (78.0) | 262 (22.0) | 620 (52.0) | 572 (48.0) |
| Low middle | 1,095 (24.9) | 856 (78.2) | 239 (21.8) | 628 (57.4) | 467 (42.6) | |
| High middle | 1,036 (23.6) | 794 (76.6) | 242 (23.4) | 604 (58.3) | 432 (41.7) | |
| Highest | 1,070 (24.4) | 846 (79.1) | 224 (20.9) | 641 (59.9) | 429 (40.1) | |
| Employment status | Regular | 4,135 (94.1) | 3,228 (78.1) | 907 (21.9) | 2,364 (57.2) | 1,771 (42.8) |
| Subcontractor | 192 (4.4) | 146 (76.0) | 46 (24.0) | 95 (49.5) | 97 (50.5) | |
| Self-employed | 66 (1.5) | 52 (78.8) | 14 (21.2) | 34 (51.5) | 32 (48.5) | |
| Full/Part time | Full time | 4,147 (94.4) | 3,237 (78.1) | 910 (21.9) | 2,355 (56.8) | 1,792 (43.2) |
| Part time | 246 (5.6) | 189 (76.8) | 57 (23.2) | 138 (56.1) | 108 (43.9) | |
| Occupation | Professional and managerial | 482 (11.0) | 386 (80.1) | 96 (19.9) | 285 (59.1) | 197 (40.9) |
| Clerical (office work) | 2,598 (59.1) | 2,041 (78.6) | 557 (21.4) | 1,479 (56.9) | 1,119 (43.1) | |
| Sales and service | 439 (10.0) | 332 (75.6) | 107 (24.4) | 222 (50.6) | 217 (49.4) | |
| Manual | 874 (19.9) | 667 (76.3) | 207 (23.7) | 507 (58.0) | 367 (42.0) | |
| Weekly working hours | 1–34 | 719 (16.4) | 536 (74.6) | 183 (25.4) | 391 (54.4) | 328 (45.6) |
| 35–40 | 2,138 (48.6) | 1,732 (81.0) | 406 (19.0) | 1,254 (58.6) | 884 (41.4) | |
| 41–52 | 1,296 (29.5) | 978 (75.5) | 318 (24.5) | 727 (56.1) | 569 (43.9) | |
| 53–60 | 206 (4.7) | 162 (78.6) | 44 (21.4) | 109 (52.9) | 97 (47.1) | |
| >60 | 34 (0.8) | 18 (52.9) | 16 (47.1) | 12 (35.3) | 22 (64.7) | |
| Shift work | No | 3,991 (90.9) | 3,121 (78.2) | 870 (21.8) | 2,282 (57.2) | 1,709 (42.8) |
| Yes | 402 (9.1) | 305 (75.9) | 97 (24.1) | 211 (52.5) | 191 (47.5) | |
| Hypertension | No | 3,736 (86.4) | 2,924 (78.3) | 812 (21.7) | 2,160 (57.8) | 1,576 (42.2) |
| Yes | 586 (13.6) | 451 (77.0) | 135 (23.0) | 297 (50.7) | 289 (49.3) | |
| Diabetes | No | 4,160 (95.0) | 3,255 (78.3) | 905 (21.8) | 2,366 (56.9) | 1,794 (43.1) |
| Yes | 217 (5.0) | 159 (73.3) | 58 (26.7) | 118 (54.4) | 99 (45.6) | |
| Mental illness | No | 4,199 (95.6) | 3,334 (79.4) | 865 (20.6) | 2,446 (58.2) | 1,753 (41.8) |
| Yes | 194 (4.4) | 92 (47.4) | 102 (52.6) | 47 (24.2) | 147 (75.8) | |
| Obstructive sleep apnea (OSA) | No | 4,337 (98.7) | 3,390 (78.2) | 947 (21.8) | 2,474 (57.0) | 1,863 (43.0) |
| Yes | 56 (1.3) | 36 (64.3) | 20 (35.7) | 19 (33.9) | 37 (66.1) | |
| Smoking | Non- smoker | 2,382 (54.2) | 1,909 (80.1) | 473 (19.9) | 1,414 (59.4) | 968 (40.6) |
| Ex-smoker | 976 (22.2) | 767 (78.6) | 209 (21.4) | 552 (56.6) | 424 (43.4) | |
| Current-smoker | 1,035 (23.6) | 750 (72.5) | 285 (27.5) | 527 (50.9) | 508 (49.1) | |
| Alcohol | Non-risky drinking | 2,521 (57.4) | 2,017 (80.0) | 504 (20.0) | 1,459 (57.9) | 1,062 (42.1) |
| Risky drinking | 1,872 (42.6) | 1,409 (75.3) | 463 (24.7) | 1,034 (55.2) | 838 (44.8) | |
| Coffee | No excessive consumption | 3,684 (83.9) | 2,901 (78.8) | 783 (21.2) | 2,151 (58.4) | 1,533 (41.6) |
| Excessive consumption | 709 (16.1) | 525 (74.1) | 184 (25.9) | 342 (48.2) | 367 (51.8) | |
*: column percent, **: row percent.
Table 2 shows work stress and its association with the prevalence of insomnia symptoms and low sleep quality. Except for low job control, all other kinds of work stress were associated with the increased prevalence of insomnia symptoms and low-quality sleep. Workers under hazardous physical environments were the most highly likely to experience insomnia symptoms and low-quality sleep (insomnia symptoms: 45.3.0%, (p<0.001); low-quality sleep: 72.4%, (p<0.001)). Then, high job demand and work-life imbalance followed higher prevalence of insomnia symptoms and low-quality sleep.
Table 2. Prevalence of sleep disturbance according to work stress.
| Total N (%) |
Insomnia symptoms |
Low- quality sleep |
||||||
|---|---|---|---|---|---|---|---|---|
| No n (%) |
Yes n (%) |
p | No n (%) |
Yes n (%) |
p | |||
| Hazardous physical environment | <0.001 | <0.001 | ||||||
| No | 4,223 (96.1%) | 3,333 (78.9%) | 890 (21.1%) | 2,446 (57.9%) | 1,777 (42.1%) | |||
| Yes | 170 (3.9%) | 93 (54.7%) | 77 (45.3%) | 47 (27.7%) | 123 (72.4%) | |||
| High job demand | <0.001 | <0.001 | ||||||
| No | 3,562 (81.1%) | 2,897 (81.3%) | 665 (18.7%) | 2,153 (60.4%) | 1,409 (39.6%) | |||
| Yes | 831 (18.9%) | 529 (63.7%) | 302 (36.3%) | 340 (40.9%) | 491 (59.1%) | |||
| Low job control | 0.854 | 0.989 | ||||||
| No | 2,960 (67.4%) | 2,309 (78.0%) | 651 (22.0%) | 1,680 (56.8%) | 1,280 (43.2%) | |||
| Yes | 1,433 (32.6%) | 1,117 (77.9%) | 316 (21.9%) | 813 (56.7%) | 620 (43.3%) | |||
| Low social support | <0.001 | <0.001 | ||||||
| No | 2,992 (68.1%) | 2,379 (79.5%) | 613 (20.5%) | 1,752 (58.6%) | 1,240 (41.4%) | |||
| Yes | 1,401 (31.9%) | 1,047 (74.7%) | 354 (25.3%) | 741 (52.9%) | 660 (47.1%) | |||
| Job insecurity | <0.001 | <0.001 | ||||||
| No | 2,947 (67.1%) | 2,445 (83.0%) | 502 (17.0%) | 1,874 (63.6%) | 1,073 (36.4%) | |||
| Yes | 1,446 (32.9%) | 981 (67.8%) | 465 (32.2%) | 619 (42.8%) | 827 (57.2%) | |||
| Organizational injustice | <0.001 | <0.001 | ||||||
| No | 2,206 (50.2%) | 1,774 (80.4%) | 432 (19.6%) | 1,332 (60.4%) | 874 (39.6%) | |||
| Yes | 2,187 (49.8%) | 1.652 (75.5%) | 535 (24.5%) | 1,161 (53.1%) | 1,026 (46.9%) | |||
| Inappropriate reward | <0.001 | <0.001 | ||||||
| No | 1,938 (44.1%) | 1,581 (81.6%) | 357 (18.4%) | 1,227 (63.3%) | 711 (36.7%) | |||
| Yes | 2,455 (55.9%) | 1,845 (75.1%) | 610 (24.9%) | 1,266 (51.6%) | 1,189 (48.4%) | |||
| Work-life imbalance | <0.001 | <0.001 | ||||||
| No | 2,977 (67.8%) | 2,435 (81.8%) | 542 (18.2%) | 1,856 (62.3%) | 1,121 (37.7%) | |||
| Yes | 1,416 (32.2%) | 991 (70.0%) | 425 (30.0%) | 637 (45.0%) | 779 (55.0%) | |||
p-value is calculated by χ2 test.
Table 3 shows work stress and its association with insomnia symptoms and low-quality sleep via logistic regression. Similar to Table 2, hazardous physical environment, high job demand, low social support, job insecurity, organizational injustice, inappropriate reward, and work-life imbalance were linked with increased risks of insomnia symptoms and low-quality sleep. Hazardous physical environment showed the highest OR.
Table 3. Association between work stress and sleep disturbance via logistic regression analysis.
| Type of work stress | Insomnia symptoms |
Low sleep quality |
||||
|---|---|---|---|---|---|---|
| Unadjusted OR (95% CI) |
Model 1a OR (95% CI) |
Model 2b OR (95% CI) |
Unadjusted OR (95% CI) |
Model 1a OR (95% CI) |
Model 2b OR (95% CI) |
|
| Hazardous physical environment | 3.10 (2.27–4.23) | 2.80 (2.02–3.86) | 2.65 (1.90–3.71) | 3.60 (2.56–5.07) | 3.19 (2.25–4.43) | 3.04 (2.12–4.36) |
| High job demand | 2.49 (2.10–2.93) | 2.65 (2.21–3.18) | 2.50 (2.07–3.01) | 2.21 (1.89–2.57) | 2.67 (2.26–3.15) | 2.51 (2.11−2.99) |
| Low job control | 1.00 (0.86–1.17) | 0.96 (0.81–1.15) | 0.97 (0.81–1.17) | 1.00 (0.88–1.14) | 1.13 (0.98–1.31) | 1.18 (1.01–1.38) |
| Low social support | 1.31 (1.13–1.52) | 1.40 (1.19–1.65) | 1.37 (1.15–1.62) | 1.26 (1.11–1.43) | 1.50 (1.31–1.73) | 1.48 (1.28–1.72) |
| Job insecurity | 2.31 (1.99–2.67) | 2.38 (2.05–2.78) | 2.25 (1.92–2.64) | 2.33 (2.05–2.65) | 2.18 (1.91–2.49) | 2.06 (1.80–2.36) |
| Organizational injustice | 1.33 (1.15–1.53) | 1.29 (1.11–1.49) | 1.30 (1.12–1.52) | 1.35 (1.19–1.52) | 1.36 (1.20–1.54) | 1.39 (1.22–1.58) |
| Inappropriate reward | 1.46 (1.26–1.70) | 1.49 (1.27–1.74) | 1.49 (1.27–1.75) | 1.62 (1.44–1.83) | 1.48 (1.30–1.69) | 1.51 (1.32–1.72) |
| Work-life imbalance | 1.93 (1.66–2.23) | 1.84 (1.58–2.14) | 1.79 (1.53–2.10) | 2.02 (1.78–2.30) | 2.00 (1.75–2.29) | 1.97 (1.72–2.26) |
aModel 1: Adjusted for sex, age, education, income, employment status, full/part-time job, occupation, weekly working hours and shift work.
bModel 2: Adjusted for sex, age, education, income, employment status, full/part-time job, occupation, weekly working hours and shift work, hypertension, diabetes, mental illness, OSA, smoking, alcohol, and coffee consumption. OR: odds ratio; OSA: obstructive sleep apnea.
Table 4 shows the findings of the mediation analysis, including the percentages mediated by pre-sleep arousal symptoms between work stress and insomnia symptoms. The relationship between work stress and insomnia symptoms is mediated by both cognitive and somatic components, except for low job control. Concerning OR for the indirect effect, the OR of cognitive PSA in the relationship between hazardous physical environment (OR: 1.51) and insomnia symptoms was the highest, followed by the high job demand (OR: 1.42). OR of Somatic PSA was the highest in relation to the hazardous physical environment (OR: 1.49) and insomnia symptoms, followed by the high job demand (OR: 1.45). The highest proportion of cognitive and somatic PAS mediated the relationship between organizational injustice (55.3%) and insomnia symptoms.
Table 4. Mediation of pre-sleep arousal symptoms between work stress and insomnia symptoms by mediation analysis.
| Type of work stress | Total effect OR (95% CI) |
Direct effect OR (95% CI) |
Indirect effect OR (95% CI) |
Mediated proportion of PSA cognitive percent (95% CI) |
Mediated proportion of PSA somatic percent (95% CI) |
|---|---|---|---|---|---|
| Hazardous physical environment | 2.96 (2.10−4.18) | 1.96 (1.38–2.78) | 1.51 (1.24–1.83) | 36.4% (16.7–56.2) | |
| High job demand | 2.47 (2.06–2.95) | 1.74 (1.45–2.08) | 1.42 (1.30–1.55) | 43.6% (32.5–54.8) | |
| Low job control | 0.98 (0.83–1.17) | 0.96 (0.82–1.13) | 1.02 (0.96–1.09) | Not calculateda | |
| Low social support | 1.34 (1.14–1.58) | 1.18 (1.01–1.38) | 1.14 (1.07–1.20) | 45.0% (19.9–70.2) | |
| Job insecurity | 2.21 (1.90–2.56) | 1.64 (1.42–1.90) | 1.34 (1.26–1.44) | 42.3% (32.8–51.7) | |
| Organizational injustice | 1.30 (1.13–1.51) | 1.16 (1.01–1.33) | 1.12 (1.07–1.18) | 46.2% (21.9–70.5) | |
| Inappropriate reward | 1.51 (1.29–1.77) | 1.29 (1.12–1.49) | 1.17 (1.11–1.24) | 40.9% (25.2–56.5) | |
| Work-life imbalance | 1.84 (1.58–2.13) | 1.52 (1.31–1.76) | 1.21 (1.14–1.28) | 34.5% (24.0–45.0) | |
| Hazardous physical environment | 2.64 (1.91–3.64) | 1.77 (1.27–2.46) | 1.49 (1.23–1.82) | 45.8% (23.9–67.8) | |
| High job demand | 2.51 (2.10–2.99) | 1.73 (1.50–2.07) | 1.45 (1.32–1.58) | 45.1% (33.9–56.4) | |
| Low job control | 0.98 (0.82–1.17) | 0.92 (0.78–1.08) | 1.07 (1.02–1.13) | Not calculateda | |
| Low social support | 1.35 (1.15–1.60) | 1.17 (1.01–1.38) | 1.15 (1.09–1.21) | 48.4% (22.9–73.9) | |
| Job insecurity | 2.20 (1.89–2.56) | 1.62 (1.40–1.88) | 1.36 (1.27–1.45) | 43.6% (33.6–53.6) | |
| Organizational injustice | 1.31 (1.13–1.51) | 1.14 (0.99–1.31) | 1.14 (1.10–1.20) | 55.3% (26.5–80.0) | |
| Inappropriate reward | 1.48 (1.27–1.73) | 1.34 (1.16–1.55) | 1.10 (1.05–1.16) | 26.9% (14.0–39.9) | |
| Work-life imbalance | 1.78 (1.54 − 2.07) | 1.51 (1.31–1.75) | 1.17 (1.12–1.24) | 31.6% (21.4–41.9) | |
Adjusted for sex, age, education, income, employment status, full/part-time job, occupation, weekly working hours and shift work, hypertension, diabetes, mental illness, OSA, smoking, alcohol, and coffee consumption.
amediated percentages were not calculated because low job control did not significantly increase the Ors. OR: odds ratio; PSA: pre-sleep arousal; OSA: obstructive sleep apnea.
The mediation of pre-sleep arousal symptoms between work stress and low-quality sleep is shown in Table 5. Cognitive and somatic pre-sleep arousal symptoms, similar to insomnia symptoms, significantly mediated the relationship between work stress and low-quality sleep. The hazardous physical environment had the highest OR for the indirect effect, and the high job demand had the second highest OR in cognitive and somatic PSA. The Cognitive and somatic PAS mediated the highest percentage relationship between high job demand and low-quality sleep.
Table 5. Mediation of pre-sleep arousal symptoms between work stress and low-quality sleep by mediation analysis.
| Type of work stress | Total effect OR (95% CI) |
Direct effect OR (95% CI) |
Indirect effect OR (95% CI) |
Mediated percent of PSA−Cognitive percent (95% CI) |
Mediated percent of PSA−Cognitive percent (95% CI) |
|---|---|---|---|---|---|
| Hazardous physical environment | 2.96 (2.10–4.17) | 1.95 (1.37–2.77) | 1.52 (1.25–1.85) | 36.8 (16.9–56.8) | |
| High job demand | 2.45 (2.09–2.88) | 1.75 (1.49–2.07) | 1.40 (1.29–1.52) | 37.3 (26.7–47.8) | |
| Low job control | 1.18 (1.02–1.36) | 1.16 (1.02–1.33) | 1.01 (0.97–1.07) | 9.0 (−19.5–37.6) | |
| Low social support | 1.46 (1.28–1.68) | 1.33 (1.17–1.52) | 1.10 (1.05–1.15) | 24.8 (12.2–37.4) | |
| Job insecurity | 2.03 (1.78–2.31) | 1.60 (1.41–1.83) | 1.26 (1.20–1.34) | 33.6 (24.8–42.5) | |
| Organizational injustice | 1.39 (1.24–1.57) | 1.27 (1.14–1.43) | 1.09 (1.05–1.14) | 27.2 (14.7–39.7) | |
| Inappropriate reward | 1.51 (1.33–1.71) | 1.34 (1.19–1.51) | 1.12 (1.08–1.17) | 29.3 (17.8–40.7) | |
| Work-life imbalance | 1.93 (1.69–2.19) | 1.72 (1.51–1.95) | 1.12 (1.08–1.17) | 18.1 (11.7–24.5) | |
| Hazardous physical environment | 2.96 (2.10–4.17) | 2.02 (1.41–2.89) | 1.47 (1.21–1.78) | 33.7 (13.8–53.6) | |
| High job demand | 2.45 (2.09–2.87) | 1.73 (1.46–2.03) | 1.42 (1.31–1.55) | 38.9 (28.1–49.8) | |
| Low job control | 1.17 (1.02–1.35) | 1.11 (0.97–1.27) | 1.06 (1.02–1.11) | 36.5 (0.01–71.9) | |
| Low social support | 1.46 (1.27–1.67) | 1.30 (1.14–1.48) | 1.12 (1.07–1.17) | 30.8 (16.9–44.8) | |
| Job insecurity | 2.03 (1.78–2.32) | 1.56 (1.37–1.78) | 1.30 (1.23–1.38) | 38.0 (28.3–47.7) | |
| Organizational injustice | 1.39 (1.23–1.57) | 1.24 (1.10–1.39) | 1.12 (1.08–1.17) | 35.8 (21.2–50.3) | |
| Inappropriate reward | 1.51 (1.33–1.71) | 1.38 (1.23–1.56) | 1.09 (1.05–1.13) | 21.5 (11.5–31.4) | |
| Work-life imbalance | 1.93 (1.70–2.20) | 1.70 (1.49–1.92) | 1.14 (1.09–1.19) | 20.0 (13.2–26.8) | |
Adjusted for sex, age, education, income, employment status, full/part-time job, occupation, weekly working hours and shift work, hypertension, diabetes, mental illness, OSA, smoking, alcohol, and coffee consumption. OR: odds ratio; PSA: pre-sleep arousal; OSA: obstructive sleep apnea.
Appendix Tables 1 and 2 summarize the association between work stress and sleep disturbances, including insomnia symptoms and low-quality sleep disturbances. As the number of work stressors increases, the prevalence of insomnia and low-quality sleep also increases. A similar trend was observed in logistic regression model, using workers not exposed to any work stressors as the reference group (Appendix Table 2). An exposure-response relationship was observed.
Discussion
The findings of this study indicated a significant association between work stress and sleep disturbance among the Korean working population, as measured by insomnia symptoms and subjective sleep quality. Increased job stress is associated with poor sleep quality and a higher prevalence of insomnia symptoms. All work stress subtypes, except low job control, were significantly associated with insomnia symptoms and poor sleep quality. Notably, hazardous physical environments, high job demands, and job insecurity were most strongly correlated with sleep problems among the various work stressors. Furthermore, both cognitive and somatic pre-sleep arousals significantly mediate this relationship. These results are consistent with previous research suggesting that work stress adversely influences sleep by increasing arousal levels before bedtime6, 17).
The dominant mediating effect between sleep disturbance and work stress subtypes varies depending on whether pre-sleep arousal is cognitive or somatic. Specifically, in the relationship between the hazardous physical environment and insomnia symptoms, somatic arousal (52.5%) revealed a stronger mediating effect than cognitive arousal (42.8%). Although somatic and cognitive arousal represent distinct types of arousal states, they are interrelated and bi-directionally associated with hyperarousal5). Somatic arousal, characterized by symptoms such as palpitations, shortness of breath, and dry mouth or throat, reflects activation of the autonomic nervous system17). Cognitive arousal, manifested as rumination and worry about daytime consequences, represents cortical activity during the sleep phase17). These two forms of arousal exhibit a bidirectional relationship: cognitive hyperarousal can induce somatic hyperarousal, while somatic hyperarousal can exacerbate cognitive hyperarousal5).
Extreme physical activity is often associated with insomnia symptoms18). According to the previous cross-sectional study for the sleep difficulty by occupation, both service and sales workers and agricultural-fishery industry workers had more sleep difficulty than other jobs group19, 20). While emotional suppression may explain the sleep discomfort experienced by service workers, the sleep discomfort of those in agriculture, forestry, and fisheries occupation has been reported at higher levels in job categories involving more physical labor. This can be explained by somatic hyperarousal due to autonomic nervous system activation6, 7). In this study, hazardous physical environments were also associated with insomnia symptoms, as shown in Table 3. Additionally, the proportion of the mediating effect was higher for somatic hyperarousal (52.5%) than cognitive hyperarousal (42.8%). The somatic component of pre-sleep arousal should be interpreted carefully. The impact of pre-sleep arousal on sleep quality differs depending on the source of stress, whether it originates from a hazardous physical environment (such as maintaining an uncomfortable posture or extended working hours) or from physical eustress due to leisure activities21, 22).
It can be inferred that the hazardous physical environments to which manual workers are exposed, mainly in factories and production facilities, contribute to the worsening of sleep quality and the development of insomnia symptoms. This can be attributed to prolonged repetitive work in awkward postures, heavy loading, and insufficient rest time, potentially increasing musculoskeletal pain14, 23). The musculoskeletal pain and sustained inflammation due to occupational physical activity can trigger heightened physiological arousal, subsequently interfering with sleep quality14, 23).
Previous studies have shown that cognitive hyperarousal induces sleep disturbances through maladaptive cognitive-emotional reactivity to stress6). Repetitive thinking and rumination about stressors often lead to persistent thoughts about stressful events24, 25). When individuals engage in rumination and become fixated on stressors, negative metacognitions of stress are activated, resulting in poor sleep quality and subjective sleep disturbance5, 17). These findings are consistent with previous research indicating that the risk of sleep disturbances increases when individuals fail to psychologically detach from work-related thoughts during leisure time26, 27).
On the other hand, as shown in Table 3, only low job control did not show significant associations with either insomnia symptoms or poor sleep quality. Previous studies have reported that low job control is associated with sleep problems28, 29). Although the precise interpretation remains unclear, this discrepancy might be attributed to the internal reliability of the low job control subscale of KOSS, which was the lowest compared to other subscales. This suggests that the correlation between items within this subscale is relatively low30). These factors may explain why the association between low job control and both insomnia symptoms and poor sleep quality was not significant in our study
Negative metacognition or emotional responses to stress can be exacerbated by organizational injustice and unfairness in the workplace31, 32). Moreover, when people lose control over their jobs, poor sleep quality and depressive symptoms are often observed32, 33). When people have high demands and low job control, they often experience cognitive overload, increased stress, and anxiety levels34). Additionally, the lack of autonomy can lead to feelings of helplessness and frustration, exacerbating depressive symptoms35). For these reasons, both individual assistance and solutions at the organizational level are warranted31). Organizations can help reduce work stress and improve sleep by managing the workload to provide employees with sufficient recovery time. Additionally, it is beneficial for individuals to regain control over their work and achieve a healthy work-life balance.
This study had several limitations. First, it has a cross-sectional design, which precluded causal inferences. Although this study analyzed the mediating effect of pre-sleep arousal between occupational stress and sleep quality, it could not definitively identify the causal direction of these associations. Due to the cross-sectional study design, the timing of the measurements of occupational stress and sleep quality could not be considered. Short-term occupational stress may lead to short-term sleep disturbances, whereas long-term occupational stress may contribute to persistent sleep problems. This study design did not allow for an examination of these temporal dynamics. Due to these limitations, the results of this study should be interpreted with caution; as seen in the previous research, there could be substantial differences between longitudinal and cross-sectional mediation analysis36). Another limitation of this study was the convenience sampling method utilized for recruiting participants, which does not guarantee the generalizability of the findings to the general population. Large-scale, nationally representative studies conducted by government agencies could provide more generalizable insights into the relationship between occupational stress and sleep quality in South Korea. Also, this study did not consider restless leg syndrome (RLS) and circadian rhythm sleep-wake disorders (CRSWD). This one drawback of this study. Despite these limitations, this study contributes to the evaluation of mechanisms underlying job stress and sleep problems caused by pre-sleep arousal. As this study is part of an ongoing longitudinal research project, future waves of data collection will allow longitudinal analyses to be conducted, addressing some of the current limitations.
Conclusion
The results of this study suggest that work stress significantly contributes to the sleep disturbance among workers and that pre-sleep arousal partially mediates this relationship. These insights emphasize the necessity for preventive interventions to mitigate the effects of work stress on sleep. Organizations should focus on managing workloads, improving work environments, and fostering a supportive workplace culture to help employees achieve better sleep. Individual strategies to reduce cognitive arousal, such as stress management techniques and relaxation exercises, may also be beneficial. To provide deeper insights into these dynamics and help develop targeted strategies to improve workers’ health and well-being, future research should consider longitudinal designs to establish causal relationships.
Ethics Statement
All participants signed a consent form and anonymity and confidentiality were ensured.
This study was approved by the Institutional Review Board (IRB) of the Dong-A University of Korea (IRB number: 2-1040709-AB-N-01-202202-HR-017-06).
Author Contributions
CRediT: Conceptualization: SS Cho. Data curation: SS Cho and MY Kang. Formal analysis: H Ryu and SS Cho. Methodology: SS Cho and MY Kang. Project administration: SS Cho. Writing–original draft: SS Cho and J Min, Writing–review & editing: MY Kang.
Conflict of Interest
None.
Acknowledgments
This research is supported by the National Research Foundation of Korea (grant number: NRF-2021R1C1C1007796).
Appendix
Appendix Table 1. Prevalence of sleep disturbance by number of work stress
| Number of work stress | Total N (%) |
Insomnia symptoms |
Low sleep quality |
||||
|---|---|---|---|---|---|---|---|
| (−) n (%) |
(+) n (%) |
p | (−) n (%) |
(+) n (%) |
p | ||
| <0.001 | <0.001 | ||||||
| 0 | 612 (13.9) | 550 (89.9) | 62 (10.1) | 465 (76) | 147 (24) | ||
| 1 | 823 (18.7) | 685 (83.2) | 138 (16.8) | 517 (62.8) | 306 (37.2) | ||
| 2 | 854 (19.4) | 674 (78.9) | 180 (21.1) | 498 (58.3) | 356 (41.7) | ||
| 3 | 730 (16.6) | 564 (77.3) | 166 (22.7) | 387 (53) | 343 (47) | ||
| 4 | 611 (13.9) | 440 (72.0) | 171 (28.0) | 296 (48.5) | 315 (51.6) | ||
| 5 | 480 (10.9) | 345 (71.9) | 135 (28.1) | 236 (49.2) | 244 (50.8) | ||
| 6 | 214 (4.9) | 134 (62.6) | 80 (37.4) | 74 (34.6) | 140 (65.4) | ||
| 7 | 62 (1.4) | 31 (50.0) | 31 (50.0) | 18 (29) | 44 (71) | ||
| 8 | 7 (0.2) | 3 (42.9) | 4 (57.1) | 2 (28.6) | 5 (71.4) | ||
Appendix Table 2. Association between the number of work stress and sleep disturbance via logistic regression analysis
| Number of work stress | Insomnia symptoms |
Poor sleep quality |
||||
|---|---|---|---|---|---|---|
| Unadjusted OR (95% CI) |
Model 1a OR (95% CI) |
Model 2b OR (95% CI) |
Unadjusted OR (95% CI) |
Model 1a OR (95% CI) |
Model 2b OR (95% CI) |
|
| 0 | 1 (Reference) | 1 (Reference) | 1 (Reference) | 1 (Reference) | 1 (Reference) | 1 (Reference) |
| 1 | 1.78 (1.30–2.46) | 1.70 (1.23–2.35) | 1.67 (1.21–2.32) | 1.87 (1.48–2.36) | 1.75 (1.38–2.22) | 1.78 (1.40–2.27) |
| 2 | 2.37 (1.74–3.23) | 2.23 (1.64–3.06) | 2.11 (1.53–2.32) | 2.26 (1.80–2.85) | 2.10 (1.66–2.65) | 2.07 (1.63–2.63) |
| 3 | 2.61 (1.91–3.58) | 2.50 (1.82–3.44) | 2.31 (1.67–3.20) | 2.80 (2.22–3.55) | 2.65 (2.09–3.37) | 2.58 (2.02–3.30) |
| 4 | 3.45 (2.51–4.73) | 3.32 (2.41–4.58) | 3.09 (2.23–4.29) | 3.37 (2.64–4.30) | 3.29 (2.56–4.22) | 3.23 (2.50–4.17) |
| 5 | 3.47 (2.50–4.84) | 3.45 (2.46–4.83) | 3.28 (2.33–4.63) | 3.27 (2.53–4.23) | 3.47 (2.66–4.53) | 3.45 (2.62–4.54) |
| 6 | 5.30 (3.62–7.76) | 5.45 (3.66–8.07) | 5.14 (3.43–7.70) | 5.98 (4.27–8.38) | 6.62 (4.67–9.38) | 6.49 (4.53–9.29) |
| 7 | 8.87 (5.05–15.57) | 8.66 (4.87–15.38) | 7.50 (4.14–13.58) | 7.73 (4.33–13.8) | 8.88 (4.93–15.99) | 8.27 (4.52–15.15) |
| 8 | 11.83 (2.59–54.07) | 12.19 (2.59–57.40) | 20.32 (3.51–117.72) | 7.91 (1.52–41.19) | 8.60 (1.62–45.57) | 15.63 (1.78–137.47) |
aModel 1: Adjusted for sex, age, education, income, employment status, full/part-time, occupation, weekly working hours and shift work.
bModel 2: Adjusted for sex, age, education, income, employment status, full/part-time, occupation, weekly working hours, shift work, smoking alcohol, coffee, hypertension, diabetes, mental illness, and obstructive sleep apnea (OSA). OR: odds ratio.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.