High job stress evaluated using the Brief Job Stress Questionnaire as an independent factor for nonrestorative sleep among Japanese workers

Abstract

Nonrestorative sleep (NRS) is clearly more associated with objective indices than primary insomnia symptoms. Stress is a comorbid factor for NRS. In 2015, the Stress Check Program was launched in Japan as a new occupational health policy. This study aimed to clarify whether the presence or absence of high job stress (HJS), as determined by Brief Job Stress Questionnaire (BJSQ), is related to the comorbidity of NRS. The subjects were 23,813 Japanese office workers who were 20 to 59 years old. The results of the BJSQ and medical examinations from a single year were examined. Presence or absence of HJS was assessed using the BJSQ and investigated in a medical interview using a personal computer. Additionally, HJS and NRS comorbidity were analyzed to determine if there were relationships between them. The subjects had a mean age of 43.2 ± 10.7 years. The proportions of subjects with NRS and HJS were 27% and 10%, respectively. HJS was associated with a risk of NRS (odds ratio, 3.68; 95% confidence interval, 3.35–4.03; P < 0.001), after adjusting for age, gender, body mass index, life-related diseases comorbidity and cardiovascular disease comorbidity, sleep time, and lifestyle habits. HJS as measured using the BJSQ was the strongest significant comorbid factor for NRS.

Introduction

The symptoms of insomnia are defined as difficulty falling asleep, difficulty staying asleep, and early awakening [1]. Although nonrestorative sleep (NRS) is also one of the symptoms of sleep disorder, it is clearly more associated with objective indices, such as sleep stage transitions, sleep stability, sleep efficiency, total sleep duration measured with polysomnography independent of other objective sleep parameters [2–4], and inflammatory responses [5], than primary insomnia symptoms. This unrefreshing sleep is considered to reflect the symptomatic physiological lack of rest following sleep.

It is known that there is an association between a stressful life and NRS [6, 7]. In a report by Ohayon, the higher the current level of stress was, the higher the prevalence of NRS was and the more people there were who had experienced stressful events in the past [6]. Matsumoto et al. also reported that the more frequently people felt stress, the more frequently they were aware of NRS [7]. Furthermore, Doi, Minowa, and Tango reported that the most strongly associated factor underlying poor sleep quality was perceived stress among white-collar employees, followed by job dissatisfaction [8]. However, there have been no studies that have analyzed the relationship between job stress, which can cause health problems in working people, and NRS. One of the reasons for this might be that psychological stresses such as job stress are difficult to quantify and difficult for medical professionals to evaluate. Therefore, implementation of the Stress Check Program by employers has been mandated by the Government of Japan in all workplaces with at least 50 employees since December 1, 2015 [9]. According to the Ministry of Health, Labour and Welfare, the primary purpose of this program is to prevent mental health problems in workers. Employees are not obligated to participate in the program; however, employers must offer screening for mental health problems and must offer a physician's interview [9]. Psychological occupational stress can be divided into three models: the job demands–control model [10], the effort–reward imbalance model, and organizational justice. When the job demands are high, but the worker is not given any discretion or freedom in work, this is called job strain (job demands–control model; JDC model) [10]. The model that adds social support to this JDC model is the job demand–control–support model (JDCS model) [11]. The BJSQ has many questions derived from the JDCS model. High-stress individuals identified by the BJSQ have high job demands, little discretion or freedom at work, and little support from superiors or colleagues. This is high job strain, and those with high job strain are at the highest risk of developing illness [12].

This study aimed to clarify if the presence or absence of high job stress (HJS), as measured by Brief Job Stress Questionnaire (BJSQ) [9], is related to NRS comorbidity and investigated how high the degree of NRS risk is for HJS after adjusted other NRS comorbid factors in the present-day office workers. It was a retrospective and cross-sectional study in nature and was performed among workers of a single company.

Materials and methods

Subjects

From April 1, 2022, to March 31, 2023, the BJSQ and medical checkups were administered to 33,147 company staff members of FUJITSU Limited. The subjects were employees aged 20 to 59 years who worked under the same company regulations, had the same salary structure, and underwent a health examination that included the survey items of this study in addition to the regular health examination required by Article 44 of Japan's Industrial Safety and Health Regulations. The subjects of this analysis included the 20- to 59-year-old Japanese men and women (19,169 men and 4,644 women, respectively) who were not missing study data and not on maintenance hemodialysis (Fig. 1). All of these subjects were non-shift office workers.

Fig. 1.

Flowchart for the inclusion criteria

The Brief Job Stress Questionnaire

The Stress Check Program requires questionnaires that include occupational stressors (dimension 1), stress reactions (dimension 2), and social support for workers (dimension 3) as dimensions for the assessment of mental health problems. The BJSQ, which has 57 items used to assess job stressors, stress reactions, and modulating factors such as social support, is recommended in the program’s manual. Furthermore, a stress survey using the BJSQ is recommended in the manual provided by the Government of Japan to identify high-job-stress workers [9]. Two methods for classifying individuals with high stress are recommended in the manual: the sum and score converted methods. The sum method simply sums the scores for each scale, whereas the score converted method uses converted scores based on the conversion table for each scale. In this study, the sum method was used to define high-job-stress individuals. To calculate the stress reaction and job stressor scores in the analysis, the simple approach of summing the scores for items scored on a Likert scale (four-point scale from 1 to 4, with 1 indicating low stress and 4 indicating high stress) was adopted. The stress reaction scores ranged from 29 to 116; the job stressor scores ranged from 26 to 104. The HJS cut-off point was either a stress reaction score (dimension 2 criteria) of 77 or a job stressor score (dimension 1 + 3 criteria) of 76 and a stress reaction score (dimension 2 criteria) of 63 [9]. In this study, all subjects responded to the BJSQ in November 2022.

Medical checkups

Subject characteristics were collected during the annual medical checkups, which were conducted throughout the year. This included age, gender, height, weight, body mass index (BMI), and use of diabetes drugs (including insulin), antihypertensive agents, or lipid metabolism disorder drugs. Blood samples were collected after a fast of ≥ 10 h and used for subsequent blood tests. High-performance liquid chromatography was used to measure glycosylated hemoglobin (HbA1c). An enzymatic method (hexokinase-UV method) was used to measure plasma glucose. Enzymatic methods were also used to measure total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels. The Friedewald equation was used to calculate LDL-Cd; when TG ≥ 400 mg/dL, a direct LDL-C method was used.

In conformity with the National Glycohemoglobin Standardization Program, fasting glucose ≥ 126 mg/dL or HbA1c ≥ 6.5% was defined as indicating diabetes mellitus; in addition, current use of diabetes drugs was also defined as indicating diabetes mellitus. Systolic blood pressure (BP) ≥ 140 mmHg, diastolic BP ≥ 90 mmHg, and/or current use of antihypertensive medications were defined as indicating hypertension. Subjects with dyslipidemia were defined as those with LDL-C ≥ 140 mg/dL, HDL-C < 40 mg/dL, TG ≥ 150 mg/dL, or non-HDL-C (TC—HDL-C) ≥ 170 mg/dL; in addition, subjects who were receiving treatment for a lipid metabolism disorder were also defined as having dyslipidemia. Subjects with arrhythmias, coronary heart disease, cerebrovascular disorder or non-cardiogenic cerebrovascular disorder, peripheral artery disease, or a history of hospitalization for heart failure were defined as having a medical history of cerebrocardiovascular disease (CVD).

Blood pressure measurement

BP was measured between 9 and 11 AM. Subjects were asked to sit for a few minutes in a backed chair in a waiting area that was supervised by clinic staff and asked not to cross their legs. Each subject subsequently used an automatic electronic sphygmomanometer to measure their BP via the brachial artery. The electronic sphygmomanometers used during the medical checkups were medical devices that conformed to the Japanese Industrial Standards (JIS). When measuring BP, the height of the measurement table was first adjusted to ensure that the tourniquet cuff was at heart level. After initiating measurement, the cuff automatically tightened around the upper arm (width, 13 cm). BP was only measured once unless the resulting measurement for BP ≥ 140/90 mmHg, in which case it was measured a second time. The second measurement was used in the analysis here if BP was measured two times.

Questionnaires about sleep and lifestyle

Focusing on those that were significantly associated with NRS, lifestyle habits in the most recent 2-to-3 months were investigated using a personal computer at a medical interview before the medical checkup. Lifestyle habits, sleep duration, and duration of overtime work in the most recent 2–3 months were collected through a computer-assisted medical interview before the medical checkup. We investigated presence or absence of NRS, sleep time, smoking, overdrinking, exercise, and eating before bedtime. Subjects who responded with "No" to the following question were defined as having NRS in this study: "Have you been feeling sufficiently rested after sleeping in the most recent two to three months?" Those who responded with "Yes" were defined as not having NRS.

Sleep duration was calculated to the closest hour by asking subjects to enter their replies, in integers, to the following questions on a personal computer, without specifying a specific day of the week: "What time do you go to bed?" and "What time do you wake up?" Smoking habit, drinking habit, overdrinking, exercise habit, and short dinner-to-bed interval were defined based on the following criteria: The criterion for a smoking habit was currently smoking on a regular basis (including heated cigarettes). That for a drinking habit was alcohol consumption at least once a week. We also calculated their average alcohol consumption per day (g). The criterion for overdrinking was an average alcohol consumption of at least 20 g of alcohol daily. That for an exercise habit was 30 min or more of exercise at least twice a week on a regular basis. Finally, the criterion for short dinner-to-bed interval was defined as having the habit of eating within 2 h before bed three or more days a week.

Statistical analyses

The odds ratio (OR) for the comorbidity of NRS with HJS after adjusting other NRS risks was the primary endpoint in this study. The subjects were assigned to groups according to the presence or absence of NRS. The following items were extracted as associated with NRS and the subjects’ lifestyle habits: age [7]; rate of males [6]; BMI; rates of diabetes mellitus [13], hypertension [13], dyslipidemia, and CVD [14]; sleep time [7, 15]; and rates of smoking habit, overdrinking, exercise habit [16], and short dinner-to-bed interval [16]. These items and HJS were compared between two groups. The Kolmogorov–Smirnov–Lilliefors test was used to evaluate the goodness of fit of age, BMI, and sleep time data to a normal distribution. Testing with P = 0.010, their distributions were not normal. Data are shown as the mean ± standard deviation. Univariate and multiple logistic regression analyses were performed to determine the extent to which HJS is a comorbid factor for NRS, unadjusted and adjusted for age; rate of males; BMI; rates of diabetes mellitus, hypertension, dyslipidemia, and CVD; sleep time; and rates of smoking habit, overdrinking, exercise habit, and short dinner-to-bed interval. Variance inflation factors (VIF) were calculated to assess multicollinearity, with VIF > 10 indicating severe collinearity. The JMP software for Windows (version 10.0; SAS Institute, Cary, NC, USA) and the Easy R (EZR) software (version 1.63, Saitama Medical Center, Jichi Medical University, Japan) were used to perform the statistical analyses. A P value for the hazard ratio of < 0.05 was defined as indicating significance.

Ethics

The conduct of this research conformed to the principles of the Helsinki Declaration. Any information that could identify individuals was anonymized during the research. Furthermore, we referred to the “Guidelines for Proper Handling of Personal Information by Medical Care/Nursing Care Service Providers” and “Things to Keep in Mind for Proper Handling of Personal Health Information on Employment Management” of the Ministry of Health, Labour and Welfare of Japan and conducted the study under strict control. The questionnaire for each patient clearly stated that health information would be used in a manner that prevented individuals from being identified, and the Fujitsu Limited internal website regarding health checks and stress checks, which can be viewed by all test takers, included notices explaining that we would answer questions about how health information was managed and that subjects were allowed to opt out. The FUJITSU LIMITED Ethics Committee reviewed this study, and we obtained the approval of the Committee before conducting the study (Ethical Committee Approval No. 24–001).

Results

Subjects’ background characteristics

The mean age of the 23,813 subjects was 43.2 ± 10.7 years, and 81% (n = 19,169) of them were male. The mean BMI was 23.5 ± 4.1 kg/m². Subjects with HJS comprised 10% of the subjects; those with NRS comprised 27% of the subjects (Table 1). Age; gender; BMI; presence of HJS; diabetes, hypertension, and CVD comorbidity; sleep time; and the rates of smoking habit, overdrinking, exercise habit, and short dinner-to-bed interval showed significant differences between subjects with the presence and absence of NRS (Table 1). Women with NRS were more prevalent than men with NRS in all age groups. The prevalence of women with HJS was highest for those in their 30 s when comparing the prevalence of HJS among men, among women, or overall according to age (Table 2).

Table 1.

Backgrounds of the subjects according to absence or presence of nonrestorative sleep

	All subjects	NRS −	NRS +	P value
Subjects, no	23,813	17,367	6,446	/
Age, years	43.2 ± 10.7	42.9 ± 10.7	44.0 ± 10.5	< 0.001a
Male, no. (%)	19,169 (81)	14,165 (82)	5,004 (78)	< 0.001b
BMI, kg/m2	23.5 ± 4.1	23.4 ± 4.0	23.6 ± 4.2	0.003a
HJS, no. (%)	2,438 (10)	1,078 (6)	1,360 (21)	< 0.001b
Comorbidity, no. (%)
Diabetes mellitus	1,738 (7)	1,229 (7)	509 (8)	0.031b
Hypertension	3,781 (16)	2,708 (16)	1,073 (17)	0.048b
Dyslipidemia	11,006 (46)	7,965 (46)	3,041 (47)	0.071b
Cerebrocardiovascular disease	590 (2)	395 (2)	195 (3)	0.001b
Lifestyle, no. (%)
Sleep time (h)	6.2 ± 0.9	6.3 ± 0.9	5.7 ± 0.9	< 0.001a
Smoking habit	3,705 (16)	2,824 (16)	881 (14)	< 0.001b
Overdrinking	5,068 (21)	3,771 (22)	1,297 (20)	0.008b
Exercise habit	8,831 (37)	6,839 (39)	1,992 (31)	< 0.001b
Short dinner-to-bed interval	7,312 (31)	4,880 (28)	2,432 (38)	< 0.001b

Values are mean ± SD values or percentages

^aKruskal-Wallis test

^bPearson’s χ²

NRS nonrestorative sleep, NRS absent, -, NRS present, + , BMI body mass index, HJS high job stress

Table 2.

Prevalence of NRS and HJS according to gender and age

	Overall		Male		Female
Subjects, %	NRS +	HJS +	NRS +	HJS +	NRS +	HJS +
Overall (n = 23,813)	27	10	26	10	31	11
20–29 years old (n = 3,797)	23	11	23	10	25	12
30–39 years old (n = 5,096)	27	12	26	11	28	13
40–49 years old (n = 6,237)	26	10	25	10	32	10
50–59 years old (n = 8,683)	30	9	29	9	39	10

Present, + 

Associations between nonrestorative sleep and high job stress

Logistic regression analyses were performed using NRS as an objective variable. The results of univariate analyses indicated significant relationships between the occurrence of NRS and presence of HJS (OR, 4.04; 95% CI, 3.1–4.40; P < 0.001). The multivariate analysis demonstrated that HJS (OR, 3.68; 95% CI, 3.35–4.03; P < 0.001) was an independent determinant of NRS after adjusting for age; rate of males; BMI; rates of diabetes mellitus, hypertension, dyslipidemia, and CVD; sleep time; and rates of smoking habit, overdrinking, exercise habit, and short dinner-to-bed interval. Furthermore, all explanatory variables were independent and without multicollinearity (Table 3).

Table 3.

Variance inflation factor results in the multiple logistic regression analyses performed to determine the factors related to NRS

Variables	VIF value
HJS (0 = no; 1 = yes)	1.01
Age (1 yrs)	1.30
Male gender (0 = no; 1 = yes)	1.13
BMI (kg/m2)	1.40
Diabetes mellitus (0 = no; 1 = yes)	1.16
Hypertension (0 = no; 1 = yes)	1.27
Dyslipidemia (0 = no; 1 = yes)	1.24
Cerebrocardiovascular disease (0 = no; 1 = yes)	1.02
Sleep time (1 h)	1.08
Smoking habit (0 = no; 1 = yes)	1.06
Overdrinking (0 = no; 1 = yes)	1.08
Exercise habit (0 = no; 1 = yes)	1.01
Short dinner-to-bed interval (0 = no; 1 = yes)	1.05

VIF variance inflation factor

Associations between nonrestorative sleep and high job stress according to gender and age

In men, the OR for having NRS was highest among men in their 20 s, followed by those in their 50 s. In women, the OR for having NRS was highest in women in their 50 s, followed by those in their 20 s. The OR was bimodal in both men and women in their 20 s and 50 s (Table 4).

Table 4.

Odds ratio of having NRS by multivariate logistic analysis of HJS according to gender and age

Male	Overall		20–29 years old		30–39 years old		40–49 years old		50–59 years old
	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value
Presence of HJS (0 = no; 1 = yes)	3.65 (3.29–4.05)	< 0.001	4.15 (3.13–5.52)	< 0.001	3.72 (3.00–4.63)	< 0.001	3.51 (2.90–4.26)	< 0.001	4.01 (3.39–4.74)	< 0.001

Female	Overall		20–29 years old		30–39 years old		40–49 years old		50–59 years old
	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value
Presence of HJS (0 = no; 1 = yes)	3.85 (3.14–4.74)	< 0.001	3.94 (2.71–5.72)	< 0.001	3.91 (2.64–5.83)	< 0.001	2.28 (3.14–4.74)	< 0.001	5.48 (3.51–8.76)	< 0.001

OR odds ratio, CI confidence interval

Adjusted for BMI, diabetes mellitus, hypertension, dyslipidemia, cerebrocardiovascular disease, sleep time, smoking habit, overdrinking, exercise habit, and short dinner-to-bed interval

Discussion

This study is the first cross-sectional study to examine whether HJS as measured using the BJSQ is a comorbid factor for NRS comorbidity in office workers. The findings of this study of 20- to 59-year-old office workers can be summarized as follows: HJS was a comorbid factor for NRS with a high OR of 3.68 even after adjusting for sleep duration, age, gender, the presence or absence of lifestyle-related diseases, and lifestyle habits.

The strengths of this paper are that HJS was assessed using the BJSQ [17], which is voluntarily completed by many workers in Japan; the performance of the BJSQ and the medical checkups under the same conditions, as they were conducted at a single company; and the large number of subjects. It was suggested that HJS has a malicious effect not only on sleep but also on daytime functions and health conditions. Overall, the study suggests that investigating the relationships between NRS and HJS in an occupational population has significant implications for disease prevention.

Nonrestorative sleep

Restorative sleep is considered to be a subjective index that reflects an individual's level of health. However, the definition of subjects with NRS has yet to be standardized, making it difficult to draw comparisons between studies [15]. The definition of NRS varies depending on the study, with some studies evaluating it based on only the presence or absence of NRS [7], like this study; NRS frequency [5, 15]; severity of feeling that sleep is restless [2]; and the NRS scale [18]. In this study, the subjects were only asked about the presence or absence of NRS in the most recent 2–3 months with a single item. A single question regarding the presence of NRS is appealing, as it minimizes the administrative burden in such a large observational study. In studies using a yes–no questionnaire to determine the presence of NRS, the prevalence of NRS was relatively higher compared with studies using the other methods. The prevalence of NRS was reported to be 19.2% to 31.0% in men and 26.3% to 42.1% in women [7, 19, 20]. The frequency of NRS in this study was similar. However, the subjects of the above-mentioned studies were community residents in their 30 s to early 70 s [7, 19, 20]. Therefore, when examining NRS, it was necessary to pay attention to the methodology used for the assessment of NRS and the background of the subjects. Differences in the background of the subjects and differences in the definition of NRS in each paper might be the reasons for the difference in the frequency of subjects having NRS [2, 5, 7].

The Brief Job Stress Questionnaire

A previous study reported that high-stress workers as defined by the sum method could have a diagnosis of potential psychological distress, with a score of 13 points or more on the Kessler Psychological Distress Scale (K6) [21], and that the BJSQ had the following screening performance characteristics: sensitivity, 60.5%; specificity, 88.9%; positive likelihood ratio, 6.0; and negative likelihood ratio, 0.4 [22]. Furthermore, the number of workers with psychological distress as assessed by the K6 was less than half that of workers with HJS as measured by the BJSQ [22]. However, in a cross-sectional survey, HJS as assessed by the BJSQ was associated with increasing economic losses due to presenteeism and treatment costs [23], and items on the BJSQ were associated with salivary cortisol levels, a stress marker [24]. Additionally, longitudinal surveys have shown that the BJSQ is useful for predicting the onset of depression [25] and employee long-term sickness absence [26]. In other words, the BJSQ can evaluate stress at a certain level.

Nonrestorative sleep and job stress

In our study, HJS had the highest OR among NRS comorbid factors. Stressful events and psychosocial stressors could impact sleep by increasing the activity of the hypothalamic–pituitary–adrenal axis and release of cortisol while decreasing the production of melatonin [27], which is reflected by increased sleep latency and awakenings and reduced slow-wave sleep and sleep efficiency [28]. Individuals who suffer from stress may have difficulty falling asleep and more awakenings after sleep onset, which can then increase the risk of poor sleep and NRS [7]. The results of our study also might reveal that stress during daytime work causes NRS. There was a significantly strong relationship between HJS as evaluated by the BJSQ and NRS. Since the BJSQ shows a model close to the JDCS model, this study might be therefore the first to investigate the relationship between the JDCS and the NRS.

High job stress and nonrestorative sleep

This study was unable to distinguish between cause and effect. However, the relationship between HJS and NRS should be considered. Even in the absence of improvements in objective data, individuals with negative cognitions tend to report sleep more negatively [29]. Therefore, it is speculated that workers with negative cognitions due to HJS tend to report NRS [7, 27]. On the other hand, individuals with NRS show decreased daytime physical, cognitive, and emotional function [15]. This may lead to a deterioration in mental health, reduced work productivity, increased daytime sleepiness, and increased work-related stress. A previous report [30] analyzed the relationship between perceived stress and work stressors, such as work demand, decision authority, and workplace social support, and difficulties initiating sleep, difficulties maintaining sleep, and NRS. According to that report, only NRS was associated with all job stress in a bidirectional manner. In other words, regardless of the type of job stress, NRS and HJS showed a very close bidirectional relationship. It is known that NRS is a risk factor for poor sleep quality and mental and physical illness [6, 7]. The presence or absence of NRS can stratify the risk of health problems among workers with HJS. Since workers with HJS who complain of NRS are at high risk of health problems, early intervention by occupational health staff may be able to prevent health problems.

Associations between nonrestorative sleep and high job stress according to age and gender

Individuals with NRS tend to be younger and are more likely to be female than individuals with primary symptoms of insomnia [5]. Young people have a larger sleep debt and are more dissatisfied with their sleep than older people after retirement, which is thought to be one of the reasons why young people have a higher rate of NRS [6]. In our workers with HJS, the ORs of NRS comorbidity factors were high in both men and women in their 20 s, and it is possible that these workers were unable to cope with job-related stress, which led to daytime functional impairment [5] and caused NRS. On the other hand, it is possible that those in their 50 s had physical problems, such as obstructive sleep apnea (OSA), respiratory disease, cancer, and thyroid disease [5], that are closely related to NRS and were not detected in this survey. NRS was not necessarily more prevalent among younger workers in this study, as the workers in the 20–59-year-old age group had the same working conditions and salary system, and this may have led to the relationship between NRS and age being unclear. As shown in the results in Table 2, the proportion of women with NRS was higher than that of men in all age groups. There are physical and psychosocial factors that make women more likely to complain of insomnia. Physically, they include menopausal symptoms, restless legs syndrome, and OSA [31], while psychosocially, they include insomnia caused by the psychosocial role of being a caregiver in the family. These factors may have influenced the tendency for women to have a higher prevalence of NRS in this study.

Comorbid factors of nonrestorative sleep other than job stress

Among the significant comorbid factors for NRS other than HJS, the ones with the next highest ORs were short sleep time and short dinner-to-bed interval (data not shown). It is known that short sleep time causes NRS [7]. It has been reported that the restorative value of sleep is a simple and direct function of sleep quantity. Short dinner-to-bed interval is also known to be a strong comorbid factor for NRS [16]. One of the reasons why a short dinner-to-bed interval is a comorbid factor for NRS is that a meal eaten before bed is not digested, leading to bile reflux and NRS. Another reason is that subjects who eat a late dinner inevitably sleep less, which is thought to lead to NRS.

Subjects with NRS have a high risk of developing mental illness and lifestyle-related diseases [5, 15]. This study did not evaluate the relationship between sleep disorders and NRS. The prevalence of sleep disorders such as depression and OSA among active workers is not low. Depression is strongly associated with NRS due to its association with mental state, poor sleep quality, and increased peripheral inflammatory markers [5]. As a sleep disorder, OSA has also been shown to be associated with NRS [32]. We could not deny the possibility that the comorbidity of depression or OSA in workers may have affected the results, indicating that HJS is an independent comorbid factor of NRS in this study.

Conclusion

For 20- to 59-year-old office workers, HJS as measured using the BJSQ was the highest comorbid factor for NRS comorbidity even after adjusting for sleep time and some factors.

Limitations

This study targeted white-collar workers employed by a single company. Whether or not the results of the present study can be applied to general workers is unclear. Furthermore, the details of job stress were not examined in this study. Job stress occurs in a variety of occupations and industries, and there are various considerations for work-related stress, such as effort–reward imbalance, shift work, and job insecurity. In addition, in this study, we were unable to obtain data on stress scores and each dimension obtained from the BJSQ, and therefore, we were unable to conduct an analysis by job strain category (job strain quadrants) and kinds of job stress (job demand-control-support). In addition to this, NRS symptoms often overlap the main symptoms of insomnia of difficulties in initiating and maintaining sleep and early morning awakening [31]; however, we were unable to compare these symptoms with NRS in this study. It is well known that HJS is one of the causes of depression. OSA and HJS are also closely related [33]. Subjective symptoms of OSA, such as daytime sleepiness and poor subjective sleep quality, increase job stress [33]. However, the relationship between HJS and sleep disorders such as depression and OSA could not be evaluated in this study. Finally, it is known that the results of health checkups show seasonal variations both for individuals and for a target group [34]. Job stress, including emotional exhaustion and workload, varies greatly from season to season depending on the job [35]. Because NRS and HJS fluctuate in workers throughout the year, the relationship between NRS and HJS could not be assessed with any seasonal precision.

Author contributions

H.S. conceived of the presented idea. H.K. collected the data for this study. H.S. verified the analytical methods. T.I. and S.N. encouraged H.S. to investigate and supervised the interpretation of findings for the whole work. All authors discussed the results and contributed to the final manuscript.

Funding

None declared.

Declarations

Conflict of interest

The authors declare no conflicts of interest.

Ethical approval

All authors have no conflicts of interest to declare. This article does not contain any studies with animal subjects performed by any of the authors. The conduct of this research conformed to the principles of the Helsinki Declaration. Any information that could identify individuals was anonymized during the research. Furthermore, we referred to the “Guidelines for Proper Handling of Personal Information by Medical Care/Nursing Care Service Providers” and “Things to Keep in Mind for Proper Handling of Personal Health Information on Employment Management” of the Ministry of Health, Labour and Welfare of Japan and conducted the study under strict control. The questionnaire for each patient clearly stated that health information would be used in a manner that prevented individuals from being identified, and the Fujitsu Limited internal website regarding health checks and stress checks, which can be viewed by all test takers, included notices explaining that we would answer questions about how health information was managed and that subjects were allowed to opt out. The FUJITSU LIMITED Ethics Committee reviewed this study, and we obtained the approval of the Committee before conducting the study (Ethical Committee Approval No. 24–001).