health Health 1949-4998 1949-5005 Scientific Research Publishing 10.4236/health.2025.173017 health-141606 Articles Biomedical Life Sciences, Medicine Healthcare Comparison of Sleep Quality and Fatigue among Shift Work Nurses across Different Age Groups in Japan Mio Hosona aGraduate School of Nursing, Osaka Metropolitan University, Osaka, Japan 10 03 2025 17 03 233 245 28, February 2025 24, February 2025 24, March 2025 © Copyright 2014 by authors and Scientific Research Publishing Inc. 2014 This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Purpose: To clarify the differences in sleep quality and fatigue among shift-working nurses based on age. Design: A descriptive correlation design using self-administered surveys. Methods: Questionnaires on fatigue, sleep satisfaction, and sleep quality (the Pittsburgh Sleep Quality Index; PSQI-J) among shift work nurses were distributed to 1190 nurses in Japan from July 2023 to August 2023. Results: Sleep satisfaction daily (p < 0.001) and pre-night shift sleep duration (p < 0.001) were significantly higher in the younger group, who also experienced a longer time to fall asleep (p = 0.014) and longer daytime naps before (p = 0.024) and after the night shift (p = 0.007). In addition, the older group experienced higher fatigue levels both daily (p = 0.038) and night shifts (p = 0.006). More morning-type nurses were observed in the older than in the younger age group (p = 0.001). No significant differences were noted in PSQI between the two groups. Conclusions: The older age group experienced higher levels of both regular fatigue and night shift fatigue compared to the younger group, suggesting they may not be getting sufficient rest after work. Although their sleep duration was shorter than that of the younger group, sleep quality was low in both groups, with 60% reporting poor sleep quality. Shift Work Nurse Age Fatigue Sleep Quality 1. Introduction

Shift workers have been shown to be at a higher risk of developing various diseases, including obesity, hypertension, diabetes, ischemic heart disease, cancer, and depression [1] - [7] . In 2007, the International Agency for Research on Cancer (IARC) classified “shift work” as a “probable human carcinogen” (Group 2A), suggesting a potential association with carcinogenicity [8] . Nurses who have engaged in shift work for more than 20 years have a 1.79 times higher risk of developing breast cancer compared to nurses with non-shift work schedules [9] . Melatonin is secreted in a dark environment at night, promoting sleep onset and regulating the sleep-wake cycle. Additionally, melatonin is involved in the autonomic nervous system and immune system, contributing to improvements in quality of life, the prevention of osteoporosis, cancer suppression, and anti-aging effects [10] . However, exposure to light at night and reduced daytime light exposure can suppress melatonin secretion [11] [12] . Nurses who work night shifts are exposed to light at night, and experience reduced light exposure during the day due to daytime naps. Therefore, it may lead to suppressed melatonin secretion, disruption of biological rhythms, and an increased risk of various diseases in nurses.

In Japan, nurses primarily work under a two-shift system, with day shifts lasting 8 hours (8:00 - 16:00) and night shifts typically extending to 16 hours (16:00 - 8:00). Although night shifts include rest breaks and naps, the extended 16-hour shift places a significant physical and mental burden on nurses, leading to high levels of fatigue. More errors occur when nurses work longer than 12 hours [13] . When high stress is combined with irregular hours in nursing, results include fatigue and lower performance [14] . For nurses working in a shift system, improving sleep quality and facilitating fatigue recovery are essential for managing the disruption of biological rhythms caused by long night shifts and sustaining their ability to continue working.

Human sleep patterns change with age, with total sleep duration decreasing, nighttime awakenings increasing, and sleep efficiency declining. As a result, aging is associated with a decrease in sleep quality [15] . Sleep quality is likely to vary depending on age, which may also affect the degree of fatigue and recovery among shift-working nurses. Sleep patterns and sleep quality change with aging. In the early 20s, individuals tend to go to bed late at night and wake up late in the morning. However, after the age of 25, they gradually shift toward an earlier bedtime and wake-up time [16] [17] . Additionally, the actual amount of sleep obtained at night gradually decreases with age. It is said that around the age of 15, individuals sleep for approximately 8 hours, while at 25, this decreases to about 7 hours. By the age of 45, nighttime sleep duration is around 6.5 hours, and by 65, it further declines to approximately 6 hours [18] . Nurses work long night shifts and are responsible for patients’ lives, leading to high physical and mental fatigue, making regular sleep extremely important. In shift work, sleep schedules become irregular, disrupting the body’s biological rhythm. Additionally, since sleep characteristics vary with age, sleep quality among nurses may differ depending on age, potentially affecting fatigue recovery.

Therefore, this study aims to clarify the differences in sleep quality and fatigue among shift-working nurses based on age.

 2. Methods 2.1. Study Design

A cross-sectional design using self-administered surveys was used to study shift work nurses in Japan.

 2.2. Participants and Setting

The study targeted shift-working nurses with at least two years of experience employed at 120 randomly selected hospitals with over 200 beds in the Kansai region of Japan using a random number table. At each facility, up to 50 nurses were included, or fewer if desired, while ensuring no extreme bias in years of experience. Among the 6000 nurses from 120 facilities, it was assumed that 60% would receive cooperation from nursing managers for the study, and 30% would respond via a mail survey. Based on these assumptions, the sample size was determined. A total of 1190 nurses from 27 hospitals were included in the study. Nurses who were not regularly engaged in shift work, those working exclusively night shifts or day shifts, and part-time workers were excluded.

 2.3. Procedure

This study was approved by the Institutional Review Board, Graduate School of Nursing, Osaka Metropolitan University (approval number: 2022-36). Following the declaration of Helsinki, the study was conducted. From July 2023 to August 2023, a research request letter was sent to the nursing administrators of the selected facilities. For facilities that agreed to participate, request letters and questionnaires were distributed by mail to the target nurses. Participation in the survey was voluntary. During the one-month study period, participants were requested to place the completed questionnaire in an envelope and return it. Consent for study participation was obtained by having participants indicate their agreement within the survey form.

 2.4. Independent Variables

The survey covered participants’ characteristics about age, gender, years of experience, ward characteristics, marital status, and presence of children. It also included the Morningness-Eveningness Questionnaire, sleep quality assessments using the Pittsburgh Sleep Quality Index (PSQI), and sleep satisfaction measured with a visual analog scale (VAS). Additionally, the survey examined physical and mental health, including subjective health status (VAS) and fatigue levels during daily life and work (VAS). The estimated time required to complete the questionnaire was approximately 25 minutes. The Pittsburgh Sleep Quality Index (PSQI) was developed by the University of Pittsburgh to assess sleep habits and sleep quality over the past month. In this study, we used the Japanese version developed by Doi et al. [19] . The questionnaire consists of 18 items, which can be categorized into seven components: “sleep quality,” “sleep duration,” “sleep onset latency,” “sleep efficiency,” “sleep disturbances,” “use of sleep medication,” and “daytime dysfunction.” A higher total score indicates greater sleep impairment, with a cutoff score of 5.5 points [20] . Reliability for the PSQI-J is established with a reported range of 0.64 - 0.87 [21] . The Morning-Evening Questionnaire (MEQ) is a 19-item questionnaire used to determine whether an individual has a morning or evening chronotype based on their sleep and eating habits. It was originally developed in English by Horne et al. (1976) and later adapted into Japanese by Ishihara et al. (1986) [22] [23] . Both the PSQI and MEQ scales can be used without permission from the developers. In addition, I investigated smartphone viewing habits that may affect sleep quality. The visual analog scale (VAS) is a widely used tool that quantifies subjective experiences by measuring the distance from the left end of a 10 cm straight line to the marked point, representing the perceived intensity of a given variable [24] .

 2.5. Statistical Analysis

The findings were analyzed using IBM Statistics SPSS 25.0. Descriptive statistics were used to summarize the sleep and fatigue levels of shift-working nurses, presented as means and standard deviations. Participants were divided into two groups: those above the median age (the older group) and those below the median age (the younger group). The Levene test was used to examine the homogeneity of variance. Independent t-tests, chi-square tests, and Fisher’s exact test were conducted to compare the two groups. A significance level of p < 0.05 was considered statistically significant.

 3. Results

Out of 1190 participants, 614 participants replied to the questionnaire, demonstrating a 51.6% response rate.

3.1. Characteristics of Participants

The average age was (35.8 ± 10.5) years, with 12.3% males (n = 75) and 87.7% (n = 534) females. Nurses were categorized into older (the average age: (45.7 ± 6.4) years) and younger groups (the average age: (26.8 ± 3.2) years) based on the median age (34.0 years). 88.1% were female, 58.7% were married, 74.9% lived with their family, and 59.5% had children in the older group. On the other side, 87.1% were female, 17.8% were married, 41.9% lived alone, and 91.1% did not have children in the younger group. The nurses worked on various wards, including post-surgical (9.2%), internal/medical 26.1%), a combination of post-surgical and internal/medical (14.5%), (6.9%), and other (10.3%) in the older group. The nurses worked on various wards, including post-surgical (9.2%), internal/medical 26.1%), a combination of post-surgical and internal/medical (14.5%), Intensive Care Unit/High Care Unit/Cardiac Care Unit (6.9%), emergency ward (1.7%) and other (41.3%). In the younger group, nurses worked on post-surgical (19.5%), internal/medical (23.8%), combination of post-surgical and internal/medical (21.1%), Intensive Care Unit/High Care Unit/Cardiac Care Unit (7.9%), emergency ward (2.3%) and other (24.4%). In the older age group, 77.8% graduated from a nursing vocational school, while 10.5% had a university degree. In contrast, in the younger age group, 51.3% graduated from a vocational school, and 41.1% had a university degree. Table 1 lists other sample characteristics.

<xref ref-type="bibr" rid="scirp.141606-"></xref>Table 1. Characteristics among participants.

Older Age GroupN = 302

Younger Age GroupN = 303

χ2

P value

Sex

Male

36 (11.9)

39 (12.9)

0.126

0.723

Female

266 (88.1)

264 (87.1)

Ward

Surgical department

28 (9.2)

59 (19.5)

29.678

<0.001

Internal/medical department

79 (26.1)

72 (23.8)

Medical and surgical mixed

department

44 (14.5)

64 (21.1)

ICU, HCU, CCU

21 (6.9)

24 (7.9)

Emergency department

5 (1.7)

7 (2.3)

Others

125 (41.3)

74 (24.4)

Surgery mixed department

1 (0.3)

3 (1.0)

Nursing Experience (Year)

1 - 4

11 (3.8)

165 (57.9)

384.920

<0.001

5 - 9

21 (7.3)

97 (34.0)

10 - 19

116 (40.4)

23 (8.1)

20 - 29

106 (36.9)

0 (0.0)

30-

33 (11.5)

0 (0.0)

Highest Level of Education

Vocational School (registered nurse)

238 (77.8)

156 (51.3)

81.266

<0.001

Junior College

22 (7.2)

8 (2.6)

Four-Year University

32 (10.5)

125 (41.1)

Master’s Degree Program

4 (1.3)

1 (0.3)

High School Health and Nursing Department

5 (1.6)

8 (2.6)

Others

5 (1.6)

6 (2.0)

Midwifery Qualifications

Have

11 (3.6)

18 (5.9)

1.823

0.177

Not have

295 (96.4)

286 (94.1)

Public Health Nurse Qualification

Have

19 (6.2)

44 (14.5)

11.247

0.001

Not have

287 (93.8)

260 (85.5)

Marriage

Be married

179 (58.7)

54 (17.8)

107.95

<0.001

Be not married

126 (41.3)

250 (82.2)

Children

Have children

182 (59.5)

27 (8.9)

173.32

<0.001

Do not have children

124 (40.5)

277 (91.1)

Live together Someone

Living alone

72 (23.8)

127 (41.9)

36.476

<0.001

Living with family

227 (74.9)

158 (52.1)

Others

4 (1.3)

18 (5.9)

Qui-square test (n (%)).

 3.2. Comparison of Sleep Quality and Fatigue Level with the Older Group and the Younger Group

Table 2 shows a comparison of sleep quality and fatigue levels between the older group and the younger group.

Sleep satisfaction daily (p < 0.001) and pre-night shift sleep duration (p < 0.001) were significantly higher in the younger group, who also experienced a longer time to fall asleep (p = 0.014) and longer daytime naps before (p = 0.024) and after the night shift (p = 0.007). In addition, the older group experienced higher fatigue levels both daily (p = 0.038) and night shifts (p = 0.006).

<xref ref-type="bibr" rid="scirp.141606-"></xref>Table 2. Comparison of sleep patterns and fatigue among nurses on age.

Older Age GroupN = 302

Younger Age GroupN = 303

T/χ2

P value

Usual times on sleep in the past month (hour)†

6.2 ± 1.1

6.5 ± 1.2

3.319

0.001

Times it takes to get to sleep (minute)†

26.4 ± 22.1

31.2 ± 24.2

2.454

0.014

Falling asleep during sleep††

Good

145 (47.5)

114 (37.7)

9.539

0.008

Bad

65 (21.3)

58 (19.2)

Usually

95 (31.1)

130 (43.0)

Usual nighttime sleep satisfaction (VAS)†

44.6 ± 22.9

52.9 ± 22.8

4.430

<0.001

Current levels of health (VAS)†

55.9 ± 20.9

57.5 ± 20.0

0.974

0.331

Current levels of stress (VAS)†

67.0 ± 20.6

61.3 ± 20.4

−3.390

0.001

Current levels of fatigue (VAS)†

68.3 ± 20.6

64.8 ± 20.0

−2.075

0.038

Levels of fatigue on a night shift work (VAS)†

80.6 ± 16.0

77.0 ± 15.7

−2.740

0.006

Times on sleep before a night shift work (minute)†

491.0 ± 112.7

585.8 ± 124.2

9.471

<0.001

Nap time before a night shift work (minute)†

128.6 ± 78.8

147.5 ± 98.6

2.268

0.024

Nap time after a night shift work (minute)†

230.6 ± 89.1

255.2 ± 92.1

2.720

0.007

†: Independent-samples T test (mean ± SD); ††: Qui-square test (n (%)); VAS: visual analog scale (mm).

 3.3. Smartphone Use at Night and Daily among Participants

Table 3 shows smartphone use at nighttime and daily among nurses. The daily smartphone screen time was significantly longer in the younger age group than in the older group. Additionally, more than 90% of individuals in both age groups used their smartphones within two hours before bedtime. In the younger group, 97% used their smartphones, which was higher than 92.5% in the older age group. Regarding when they stopped using their smartphones, around 80% of individuals in both groups reported using them until 30 minutes before bedtime or right before sleeping, with 78% in the older group and 81% in the younger group.

<xref ref-type="bibr" rid="scirp.141606-"></xref>Table 3. Smartphone use among nurses on a daily basis and before going to bed.

Older Age GroupN = 302

Younger Age GroupN = 303

χ2

P value

Using a smartphone within

2 hours of going to bed††

Use

282 (92.5)

294 (97.0)

6.368

0.012

Not used

23 (7.5)

9 (3.0)

Daily smartphone viewing time (hour)†

2.6 ± 2.1

4.5 ± 2.4

9.376

<0.001

When to stop using your smartphone

before going to bed††

Until 2 hours before bedtime

10 (3.3)

2 (0.7)

5.668

0.129

2 to 1 hour before bedtime

11 (3.6)

11 (3.7)

1 hour to 30 minutes before bedtime

46 (15.1)

42 (14.0)

30 minutes to just before bedtime

237 (78.0)

246 (81.7)

†: Independent-samples T test (mean ± SD); ††: Qui-square test (n (%)).

 3.4. PSQI Scores and MEQ Score

Table 4 shows the results of the MEQ and PSQI among nurses. In the older age group, approximately 35% were classified as morning types, which was higher than in the younger group. On the other hand, about 12% of the younger group were classified as evening types, compared to 4% in the older group (p = 0.001). The PSQI score averaged (6.7 ± 2.9) points in the older group and (6.5 ± 2.8) points in the younger group, with both groups scoring above the Japanese version of the PSQI cutoff score of 5.5 points. Additionally, 60.2% of the older group and 62.8% of the younger age group were classified as having a sleep disorder. In addition, the effect of MEQ on PSQI in both the older and younger age groups is presented in Table 5 . No significant differences were observed in the younger age group; however, in the older age group, a higher proportion of morning-type individuals exhibited better sleep quality (p = 0.032).

<xref ref-type="bibr" rid="scirp.141606-"></xref>Table 4. PSQI score and MEQ among nurses on age.

Older Age Group

Younger Age Group

χ2/T

P value

MEQ judgment††

Clearly morning type

5 (2.3)

2 (0.9)

19.73

0.001

Mostly morning type

71 (33.3)

39 (18.3)

Intermediate type

128 (60.1)

147 (69.0)

Mostly evening type

9 (4.2)

24 (11.3)

Clearly evening type

0 (0.0)

1 (0.5)

PSQI score†

6.7 ± 2.9

6.5 ± 2.8

−0.376

0.707

Sleep disorders††

Have

62 (60.2)

54 (62.8)

0.133

0.715

Not have

41 (39.8)

32 (37.2)

†: Independent-samples T test (mean ± SD); ††: Qui-square test (n (%)); MEQ: Morningness-Eveningness Questionnaire; PSQI: Pittsburgh Sleep Quality Index.

<xref ref-type="bibr" rid="scirp.141606-"></xref>Table 5. PSQI score and MEQ among nurses on age.

Good Sleep QualityPSQI Score < 5.5

Bad Sleep QualityPSQI Score > 5.5

χ2

P value

Older Age Group

Morning type

15 (45.5)

7 (17.9)

6.906

0.032

MEQ Judgment

Intermediate type

18 (54.5)

31 (79.5)

Evening type

0 (0.0)

1 (2.6)

Younger Age Group

Morning type

6 (24.0)

4 (11.4)

1.957

0.376

MEQ Judgment

Intermediate type

17 (68.0)

26 (74.3)

Evening type

2 (4.2)

5 (14.3)

Qui-square test (n (%)); MEQ: Morningness-Eveningness Questionnaire; PSQI: Pittsburgh Sleep Quality Index.

 4. Discussion

This study focused on nurses engaged in shift work, including night shifts, and compared sleep quality and fatigue between older and younger age groups.

The sleep satisfaction score of the VAS was higher in the younger age group than in the older age group. However, even in the younger group, the average satisfaction level was around 50%, indicating that overall nighttime sleep satisfaction was low. Before a night shift, the younger age group slept an average of more than 9 hours, whereas the older age group slept approximately 8 hours on average. In the older age group, a higher proportion of individuals were married or had children, requiring time for household chores and childcare, which may contribute to shorter sleep duration compared to younger individuals. Additionally, fatigue levels during night shifts were higher than usual, with the older age group experiencing greater fatigue. The current levels of fatigue and stress remained at around 60% in both groups, with the older age group experiencing higher levels. Low sleep satisfaction and shorter sleep duration before night shifts suggest that sleep quality may not be sufficient for adequate fatigue recovery. Additionally, this may have an impact on stress levels. Regarding usual sleep onset time, the younger age group took longer to fall asleep. Additionally, in the PSQI assessment, 60% of individuals in both groups were classified as having a sleep disorder. The fact that more than half of the nurses have sleep disorders suggests that they may be working without fully recovering from fatigue. This poses a risk of medical errors and other incidents, which is particularly concerning given their responsibility for patients’ lives. In menopausal women, insomnia symptoms related to estrogen deficiency have been noted. This study did not directly assess the impact of menopausal symptoms; however, this is an important factor that should be considered in future research. While the influence of menopause-specific symptoms cannot be ruled out in this study, the high prevalence of sleep disorders, even in the younger age group, suggests that other factors may also be contributing.

Shift work, including night shifts, disrupts the body’s biological rhythm, exposing workers to light during hours when they should be sleeping at night. Health issues associated with shift work have long been recognized, including obesity, heart disease, depression, hypertension, cancer, and stroke [1] - [9] . Melatonin, a hormone associated with the body’s biological rhythm, is secreted at night and plays a role in regulating circadian rhythms and promoting sleep, thereby influencing sleep quality. Exposure to light at night suppresses melatonin secretion, while exposure to light during the day is said to increase its production. Nurses working night shifts are exposed to light at night and may experience reduced light exposure during the day due to daytime naps, which can suppress melatonin secretion. This may lead to disruptions in circadian rhythm regulation and a decline in sleep quality. Shift-working nurses, influenced by hormonal imbalances, are forced to continue their demanding duties while facing significant physical and mental health risks.

Making efforts to improve sleep quality in daily life contributes to maintaining nurses’ physical and mental health. This, in turn, helps sustain the quality of medical care and enhances safety by preventing medical errors.

Blue light from smartphone screens is said to affect sleep quality. Smartphones have become an essential part of daily life, serving not only as a communication tool but also as a platform for information sharing, accessing the latest news, and entertainment. With various applications for gaming, watching videos and images, and listening to music, smartphones can be considered a multifunctional tool that fulfills various personal needs. However, prolonged smartphone use and screen time before bedtime can negatively affect sleep, not only due to blue light exposure but also by stimulating brain activity, making it harder to fall asleep [25] . In this study, an analysis of smartphone screen time revealed that the older age group had an average daily usage of 2.6 hours, while the younger age group averaged 4 hours.

For nurses working day shifts, spending several hours on their smartphones before bedtime, despite responsibilities such as household chores and childcare after returning home, takes up a significant portion of their non-working hours. Reducing exposure to blue light from smartphones before bedtime may facilitate faster sleep onset and enhance overall sleep quality. The study found that over 90% of nurses in both age groups used their smartphones within two hours before bedtime, and about 80% in both groups stopped using them just before sleep. Regarding sleep onset, the younger age group took longer to fall asleep than the older group, with an average of 31 minutes. Karas et al. also demonstrated a link between smartphone addiction, depressive symptoms, anxiety, and poor sleep quality in older adults [26] . After returning home from work, reducing smartphone screen time may help the brain relax, leading to better sleep onset and improved sleep quality. Given the irregular lifestyle associated with night shifts, adjusting environmental factors—such as using night mode on smartphone and computer screens and dimming room lighting—could be beneficial in promoting better sleep.

The older age group experienced higher fatigue levels and insufficient recovery compared to the younger group. As individuals age, changes in sleep patterns are observed, including a reduction in total sleep duration, an increase in nighttime awakenings, and a decline in sleep efficiency. Consequently, aging is linked to a deterioration in sleep quality [15] . Lin et al. demonstrated that heightened fatigue is linked to poor sleep quality and a decline in health status among shift work nurses [27] . In addition, nighttime sleep duration gradually decreases with age, dropping to approximately 6.5 hours by the age of 45 and further declining to around 6 hours by the age of 65 [18] . Caruso showed that long hours among shift workers might be associated with lower performance, injuries, chronic diseases, and fatigue-related errors [28] . On the other hand, it is essential to review their environment and lifestyle to improve sleep quality and enhance fatigue recovery. The older age group has limited time to rest after work due to household chores and childcare responsibilities, compared to younger individuals. However, it is important to establish habits that promote both physical and mental relaxation in alignment with nighttime sleep. A good starting point may be reassessing smartphone usage before bedtime. Furthermore, improving the sleep environment before and after night shifts is essential to maintaining nurses’ health. Specifically, reducing blue light exposure, reviewing shifts, and managing rest to promote fatigue recovery are important measures.

 5. Limitations

This study obtained subjective data through a self-administered questionnaire; however, it did not include objective verification. Therefore, future research should incorporate objective data alongside subjective indicators for a more comprehensive evaluation. As this study relied on self-reported data, future research should incorporate objective measures, such as actigraphy, to more accurately assess sleep quality. Additionally, the high number of missing values in the PSQI may have introduced bias in the results, highlighting the need for continued verification. Furthermore, to examine the impact of age on sleep and fatigue, potential confounding variables such as work schedules, workload, family responsibilities, and health status should be adjusted for and further investigated.

 6. Conclusion

The older age group experienced higher levels of both regular fatigue and night shift fatigue compared to the younger group, suggesting they may not be getting sufficient rest after work. Although their sleep duration was shorter than that of the younger group, sleep quality was low in both groups, with 60% reporting poor sleep quality. Many individuals continued using their smartphones until just before bedtime, suggesting a potential impact on sleep onset and sleep quality. The older age group, in addition to their work responsibilities, also had household and childcare duties. Therefore, it is crucial for them to create a sleep-friendly environment and adopt relaxation habits suited to their individual needs to support fatigue recovery.

 Funding

This manuscript was subsidized by JSPS KAKENHI (Grant Number: 20K10631).

 Acknowledgements

The author thanks the participants in this study.

 References Sun, M., Feng, W., Wang, F., Li, P., Li, Z., Li, M., et al. (2017) Meta‐Analysis on Shift Work and Risks of Specific Obesity Types. Obesity Reviews, 19, 28-40. >https://doi.org/10.1111/obr.12621 Guo, Y.J., Liu, Y.W., Huang, X.J., Rong, Y., He, M.A., Wang, Y., et al. (2013) The Effects of Shift Work on Sleeping Quality, Hypertension and Diabetes in Retired Workers. PLOS ONE, 8, e71107. >https://doi.org/10.1371/journal.pone.0071107 Oishi, M., Suwazono, Y., Sakata, K., Okubo, Y., Harada, H., Kobayashi, E., et al. (2005) A Longitudinal Study on the Relationship between Shift Work and the Progression of Hypertension in Male Japanese Workers. Journal of Hypertension, 23, 2173-2178. >https://doi.org/10.1097/01.hjh.0000189870.55914.b3 Karlsson, B., Knutsson, A. and Lindahl, B. (2001) Is There an Association between Shift Work and Having a Metabolic Syndrome? Results from a Population Based Study of 27 485 People. Occupational and Environmental Medicine, 58, 747-752. >https://doi.org/10.1136/oem.58.11.747 Pan, A., Schernhammer, E.S., Sun, Q. and Hu, F.B. (2011) Rotating Night Shift Work and Risk of Type 2 Diabetes: Two Prospective Cohort Studies in Women. PLOS Medicine, 8, e1001141. >https://doi.org/10.1371/journal.pmed.1001141 Skipper, J.K., Jung, F.D. and Coffey, L.C. (1990) Nurses and Shiftwork: Effects on Physical Health and Mental Depression. Journal of Advanced Nursing, 15, 835-842. >https://doi.org/10.1111/j.1365-2648.1990.tb01915.x Hansen, J. (2001) Light at Night, Shiftwork, and Breast Cancer Risk. JNCI Journal of the National Cancer Institute, 93, 1513-1515. >https://doi.org/10.1093/jnci/93.20.1513 Ward, E.M., Germolec, D., Kogevinas, M., McCormick, D., Vermeulen, R., Anisimov, V.N., et al. (2019) Carcinogenicity of Night Shift Work. The Lancet Oncology, 20, 1058-1059. >https://doi.org/10.1016/s1470-2045(19)30455-3 Schernhammer, E.S., Kroenke, C.H., Laden, F. and Hankinson, S.E. (2006) Night Work and Risk of Breast Cancer. Epidemiology, 17, 108-111. >https://doi.org/10.1097/01.ede.0000190539.03500.c1 Brzezinski, A. (1997) Melatonin in Humans. New England Journal of Medicine, 336, 186-195. >https://doi.org/10.1056/nejm199701163360306 Zeitzer, J.M., Dijk, D., Kronauer, R.E., Brown, E.N. and Czeisler, C.A. (2000) Sensitivity of the Human Circadian Pacemaker to Nocturnal Light: Melatonin Phase Resetting and Suppression. The Journal of Physiology, 526, 695-702. >https://doi.org/10.1111/j.1469-7793.2000.00695.x Mishima, K. (2001) Diminished Melatonin Secretion in the Elderly Caused by Insufficient Environmental Illumination. Journal of Clinical Endocrinology&Metabolism, 86, 129-134. >https://doi.org/10.1210/jc.86.1.129 Rogers, A.E., Hwang, W., Scott, L.D., Aiken, L.H. and Dinges, D.F. (2004) The Working Hours of Hospital Staff Nurses and Patient Safety. Health Affairs, 23, 202-212. >https://doi.org/10.1377/hlthaff.23.4.202 Scott, L.D., Hwang, W. and Rogers, A.E. (2006) The Impact of Multiple Care Giving Roles on Fatigue, Stress, and Work Performance among Hospital Staff Nurses. JONA: The Journal of Nursing Administration, 36, 86-95. >https://doi.org/10.1097/00005110-200602000-00007 Li, L., Nakamura, T., Hayano, J. and Yamamoto, Y. (2021) Age and Gender Differences in Objective Sleep Properties Using Large-Scale Body Acceleration Data in a Japanese Population. Scientific Reports, 11, Article No. 9970. >https://doi.org/10.1038/s41598-021-89341-x Czeisler, C.A., Dumont, M., Duffy, J.F., Steinberg, J.D., Richardson, G.S., Brown, E.N., et al. (1992) Association of Sleep-Wake Habits in Older People with Changes in Output of Circadian Pacemaker. The Lancet, 340, 933-936. >https://doi.org/10.1016/0140-6736(92)92817-y Foster, R.G. and Roenneberg, T. (2008) Human Responses to the Geophysical Daily, Annual and Lunar Cycles. Current Biology, 18, R784-R794. >https://doi.org/10.1016/j.cub.2008.07.003 Ohayon, M.M., Carskadon, M.A., Guilleminault, C. and Vitiello, M.V. (2004) Meta-Analysis of Quantitative Sleep Parameters from Childhood to Old Age in Healthy Individuals: Developing Normative Sleep Values across the Human Lifespan. Sleep, 27, 1255-1273. >https://doi.org/10.1093/sleep/27.7.1255 Buysse, D.J., Reynolds, C.F., Monk, T.H., Berman, S.R. and Kupfer, D.J. (1989) The Pittsburgh Sleep Quality Index: A New Instrument for Psychiatric Practice and Research. Psychiatry Research, 28, 193-213. >https://doi.org/10.1016/0165-1781(89)90047-4 Doi, Y., Minowa, M., Uchiyama, M. and Okawa, M. (1998) Development of the Pittsburgh Sleep Quality Index Japanese Version. Japanese Journal of Psychiatry Treatment, 13, 755-763. Doi, Y., Minowa, M., Uchiyama, M., Okawa, M., Kim, K., Shibui, K., et al. (2000) Psychometric Assessment of Subjective Sleep Quality Using the Japanese Version of the Pittsburgh Sleep Quality Index (PSQI-J) in Psychiatric Disordered and Control Subjects. Psychiatry Research, 97, 165-172. >https://doi.org/10.1016/s0165-1781(00)00232-8 Horne, J.A. and Ostberg, O. (1976) A Self-Assessment Questionnaire Eveningness to Determine Morningness in Human Circadian Rhythms. International Journal of Chronobiology, 4, 97-110. Ishihara, K., Miyashita, A., Inugami, M., Fukuda, K., Yamazaki, K. and Miyata, Y. (1986) Survey Results Using the Japanese Morningness-Eveningness Questionnaire. The Japanese Journal of Psychology, 57, 87-91. >https://doi.org/10.4992/jjpsy.57.87 Wewers, M.E. and Lowe, N.K. (1990) A Critical Review of Visual Analogue Scales in the Measurement of Clinical Phenomena. Research in Nursing&Health, 13, 227-236. >https://doi.org/10.1002/nur.4770130405 Ishizawa, M., Uchiumi, T., Takahata, M., Yamaki, M. and Sato, T. (2021) Effects of Pre-Bedtime Blue-Light Exposure on Ratio of Deep Sleep in Healthy Young Men. Sleep Medicine, 84, 303-307. >https://doi.org/10.1016/j.sleep.2021.05.046 Mireku, M.O., Barker, M.M., Mutz, J., Dumontheil, I., Thomas, M.S.C., Röösli, M., et al. (2019) Nighttime Screen-Based Media Device Use and Adolescents’ Sleep and Health-Related Quality of Life. Environment International, 124, 66-78. >https://doi.org/10.1016/j.envint.2018.11.069 Lin, S.-H., Liao, W.-C., Chen, M.-Y. and Fan, J.-Y. (2012) The Impact of Shift Work on Nurses’ Job Stress, Sleep Quality and Self-Perceived Health Status. Journal of Nursing Management, 22, 604-612. >https://doi.org/10.1111/jonm.12020 Caruso, C.C. (2014) Negative Impacts of Shiftwork and Long Work Hours. Rehabilitation Nursing, 39, 16-25. >https://doi.org/10.1002/rnj.107