Predictors of the initiation of shift work disorder among Chinese intern nurses: a prospective study

Journal Pre-proof Predictors of the Initiation of Shift Work Disorder among Chinese Intern Nurses: A Prospective Study Dingxuan Chen, Min Jiang, Xuliang Shi, Fulei Geng, Haiying Qi, Yuechu Zhang, Yuan Lai, Fang Fan PII:

S1389-9457(19)31650-8

DOI:

https://doi.org/10.1016/j.sleep.2019.11.1263

Reference:

SLEEP 4257

To appear in:

Sleep Medicine

Received Date: 9 August 2019 Revised Date:

20 November 2019

Accepted Date: 27 November 2019

Please cite this article as: Chen D, Jiang M, Shi X, Geng F, Qi H, Zhang Y, Lai Y, Fan F, Predictors of the Initiation of Shift Work Disorder among Chinese Intern Nurses: A Prospective Study, Sleep Medicine, https://doi.org/10.1016/j.sleep.2019.11.1263. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Elsevier B.V. All rights reserved.

Predictors of the Initiation of Shift Work Disorder among Chinese Intern Nurses: A Prospective Study

Dingxuan Chen, a Min Jiang, a Xuliang Shi, b,a Fulei Geng, a Haiying Qi, a Yuechu Zhang, a Yuan Lai, a and Fang Fan a*

a

Center for Studies of Psychological Application and School of Psychology, South China

Normal University, Guangzhou, China b

College of Education, Hebei University, Baoding, China

*Corresponding author: Fang Fan, PhD, Professor at the Center for Studies of Psychological Application, South China Normal University, 55 West of Zhongshan Avenue, Tianhe District, Guangzhou, 510631, P. R. China. ([email protected]).

Declarations of interest: None. The authors declare no conflicts of interest regarding data and materials presented in this paper.

Ethical approval was obtained from the Human Research Ethics Committee of South China Normal University, Guangzhou, China.

1

ABSTRACT Aim: Individual vulnerability to shift work disorder (SWD) varies. The aim of the present study was to verify the individual characteristics that predicted SWD onset by following Chinese intern nurses who at baseline had not worked rotating or night shifts. Methods: A total of 706 Chinese first-year intern female nurses aged 16-24 years were recruited. At baseline (T0), they reported demographic characteristics, insomnia symptoms and excessive sleepiness, trait neuroticism, sleep reactivity, morningness, and circadian flexibility and languidity. At the 3-month (T1) and 6-month (T2) follow-up, the SWD status was determined based on significant sleep disturbance and/or excessive sleepiness in the context of working a rotating shift schedule. Results and Conclusions: The prevalence rates of SWD were 35.2% at T1 and 37.7% at T2. Two bivariate logistics regressions revealed that morningness (OR = 1.31, 95% CI = 1.09-1.58, T1; OR = 1.36, 95% CI = 1.12-1.65, T2), languidity (OR = 1.56, 95% CI = 1.28-1.90, T1), and sleep reactivity (OR = 1.29, 95% CI = 1.07-1.57, T1; OR = 1.31, 95% CI = 1.07-1.61, T2) predicted the onset of SWD, while flexibility (OR = 0.75, 95% CI = 0.62-0.90, T1) decreased the odds of SWD onset. By comparing nurses with SWD and nurses without SWD across all six months, morningness (OR = 1.58, 95% CI = 1.20-2.07), sleep reactivity (OR = 1.54, 95% CI = 1.16-2.04), languidity (OR = 1.70, 95% CI = 1.30-2.22), and flexibility (OR = 0.70, 95% CI = 0.54-0.90) showed significant effects on persistent SWD.

Keywords: shift work; Shift Work Disorder; circadian rhythm; sleep reactivity

Highlights This is the first study to examine predictors of the onset of shift work disorder by following nurses before they started working rotating or night shifts. Sleep reactivity and variables related to circadian rhythms, including circadian flexibility and languidity and morningness, play predisposing roles in SWD onset. Sociodemographic variables were involved systematically, and multiple appropriate selfreport instruments were implemented. There were three waves of data collection with a high sample size and response rate. 2

1. Introduction 1.1 Shift work and Shift Work Disorder The nonstandard work/rest schedule of shift work causes a misalignment of circadian and homeostatic sleep-regulatory processes, thereby imposing adverse impacts on physical and mental health [1]. Among the detrimental effects, shift work disorder (SWD) has a prevalence of approximately 24.4% to 32.4% [2-4]. According to the International Classification of Sleep Disorders: Diagnostic and Coding Manual (ICSD-3), shift work disorder is marked with consistent symptoms of insomnia and/or excessive sleepiness temporally associated with work schedules, resulting in a reduction in total sleep time, unsatisfactory sleep or impaired alertness over the course of at least three months [5]. 1.2 Individual characteristics and shift work Individual vulnerability to shift work varies when facing circadian disruption caused by rotational shift work. Cross-sectional studies have revealed the relationships between individual characteristics and shift work tolerance. Neuroticism has a negative effect on coping with the stress of shift work [6-8]. Circadian factors such as morningness, the preference for activities and alertness in the daytime [9], cause greater difficulty in adapting to night shifts than eveningness [10-12]. Circadian flexibility and circadian languidity show opposite relationships with shift work sleep disturbance[13, 14]. Sleep reactivity, the sensitivity to stress of the sleep system with genetic and environmental influences, is related to insomnia symptoms and circadian disorder [15, 16]. Personality factors and circadian factors seem to play predisposing roles in incident SWD among shift workers, but there is a shortage of longitudinal studies investigating the predictors of SWD, especially with a prospective design with baseline assessments [17]. In Norway, several longitudinal studies have examined the predictors of shift work tolerance or SWD [18-22]. Combined with their population-based studies, circadian flexibility, circadian languidity, morningness, and neuroticism seem to be predictive characteristics of SWD [2, 4, 23]. However, their results varied due to different assessment time points, different sample sizes or different adjusted variables. Moreover, the reliability of these results could be doubted because of the 3

considerable sample loss and the lack of baseline assessments. Only one study focusing on sleep reactivity traced community nurses before entering shift work, but the response rate was low, and the sample size was rather small [24]. To our knowledge, the predictors of the initiation of SWD have not been studied systematically with baseline data. The causal relationships between individual characteristics and SWD need to be verified. 1.3 Research on Chinese shift workers Studying Chinese healthcare shift workers and making sure they perform their duty well are of high research priority. In China, the population of shift workers is approximately 80 million, but there are only 2.74 nurses available per 1000 population, which is far less than the average [25]. With the busy work schedule and the increasingly tense work environment, Chinese healthcare shift workers are facing tremendous pressure and risks both physically and mentally. A recent Chinese shift work epidemiological study found that 1,673 of 3,871 Chinese shift workers had abdominal obesity, and only 36.8% of them had good sleep quality [26]. Another cross-sectional study of 2180 Chinese workers found that rotating shift workers were at higher risk of sleep disturbance than fixed day-shift workers [27]. So far, population-based studies on Chinese shift workers are limited. Therefore, longitudinal designs with baseline data are of great research value. In this study, we planned to conduct prospective research with baseline assessments by following up intern nurses for their first six months of shift work. We aimed to spotlight the causal relationships between individual characteristics and the the initiation of SWD. We hypothesized that trait neuroticism, sleep reactivity and circadian-related factors, including circadian type and morningness-eveningness, would play predisposing roles in initiating SWD.

2. Measure 2.1 Procedure and participants We enrolled 725 female first-year intern nurses from a nursing school in Guangzhou in July 2017, one week before they transferred into their first-time shift work. The investigation was conducted on an online Internet questionnaire platform designed and maintained by the research team. The participants were allowed to complete the questionnaire by their cellphone or computer with the assistance and supervision of the nursing school staff. 4

There were three waves of data collection. At baseline, T0, demographic variables, insomnia symptoms, excessive sleepiness and individual characteristics were collected. Follow-up surveys were distributed at 3 and 6 months after the transition to shift work. After three months of shift work, T1, the nurses’ shift work schedules and their SWD status were collected. We deleted the data of 19 subjects who worked only day shifts, and data from 672 of 706 eligible nurses were collected, with a response rate of 95.2%. After six months of shift work, T2, their SWD status was determined, and data from 634 eligible nurses were collected, with a response rate of 89.8%. Finally, a total of 706 nurses were included in this prospective cohort. 2.2 Instruments 2.2.1 Sociodemographics At baseline, participants completed a comprehensive battery of questions concerning age, height, weight, family location, whether they had siblings, parents’ education, parents’ marital quality, and family monthly income. Specifically, their self-reported height and weight were used to calculate their body mass index (BMI). Participants also answered questions about their lifestyle, including weekly exercise, weekly tea or coffee consumption, and monthly alcohol consumption. The descriptive information is presented in Table 1. 2.2.2 Insomnia symptoms The assessment of insomnia symptoms was based on DSM-V criteria, deriving three items rated on a 4-point scale [28]. Participants indicated how often in the past three months they a) had difficulties falling asleep, b) had difficulties maintaining sleep, and c) woke up early and could not fall asleep again. Potential responses included ‘not during the past three months’, ‘less than once a week’, ‘once or twice a week’, and ‘more than three times a week’. If any of these items were rated as ‘more than three times a week’, the participants were classified as having insomnia symptoms. Cronbach’s alpha coefficients of these three items were 0.80 at T0, 0.82 at T1, and 0.82 at T2. 2.2.3 Epworth Sleepiness Scale (ESS) We used the Chinese version of the Epworth sleepiness Scale to determine excessive sleepiness in each survey [29]. The ESS consists of eight items rated on a 4-point scale, with each item scored from 0 (no probability) to 3 (high probability). Participants indicated a 5

tendency to sleep or doze off in eight different conditions. The sum of ESS total scores ranges from 0 to 24, and the clinical cut-off point of excessive daytime sleepiness is 11[30]. In the present study, the participants whose total score was over 10 were categorized as having excessive sleepiness. Cronbach’s alpha coefficients were 0.75 at T0, 0.80 at T1, and 0.86 at T2. 2.2.4 SWD measurements Based on the ICSD-3 criteria, we used three items derived from the DSM-V to determine insomnia symptoms, and we used the ESS total score (≥11) to determine the symptom of excessive sleepiness. In addition, the question ‘Have you had this sleep or sleepiness problem relate to the work schedule for at least three months? (yes/no)’ was added to fulfill the requirements to determine SWD [5]. 2.2.5 Composite Scale of Morningness (CMS) We used the Chinese version checklist of CMS to assess diurnal preference at baseline [31]. CMS is a 13-item self-reported questionnaire with three items rated on a 5-point Likert scale and ten items rated on a 4-point Likert scale. The sum of CMS total scores ranges from 13 (extreme eveningness) to 55 (extreme morningness), with higher scores meaning greater morningness. A total score of 22 or lower was defined as evening type, while a total score of 44 or higher was defined as morning type. In the present study, only two subjects were categorized as morning type, and five subjects were categorized as evening type. The scores ranged from 16 to 44, and Cronbach’s alpha coefficient was 0.50. 2.2.6 Circadian Type Inventory (CTI) We used the Chinese version checklist of the CTI to assess circadian flexibility and languidity at baseline [32]. Five items rated on a 5-point Likert scale evaluate circadian flexibility, while six items rated on a 5-point Likert scale evaluate circadian languidity. Higher total scores of the flexibility subscale mean more adaptivity to the nonstandard work-rest schedule, while higher total scores of the languidity subscale mean more difficulty in overcoming drowsiness. In the present study, Cronbach’s alpha coefficients were 0.81 for flexibility and 0.73 for languidity. 2.2.7 Ford Insomnia Response to Stress Test (FIRST)

6

We used the Chinese version checklist of the FIRST to assess sleep reactivity at baseline [33]. The FIRST is a 4-point Likert scale evaluating one’s possibility (1 = not likely; 2 = somewhat likely; 3 = moderately likely; 4 = very likely) of having insomnia under nine stress conditions. Participants were asked to rate the items even if they had not experienced the listed situations. In the present study, Cronbach’s alpha coefficient was 0.87. 2.2.8 Neuroticism subscale of IPIP-MINI We used the Neuroticism subscale of the Chinese version of the revised IPIP-MINI to assess neuroticism at baseline[34]. IPIP-MINI contains 5 subscales to assess the Big Five personality traits, Neuroticism, Extraversion, Agreeableness, Conscientiousness and Openness, and each subscale contains 8 items rated on a 6-point Likert scale. Higher total scores of the Neuroticism subscale mean a higher level of neuroticism. In the present study, Cronbach’s alpha coefficient was 0.86. 2.3 Ethics The study was approved by the Human Research Ethics Committee of South China Normal University, Guangzhou, China. All participants provided informed consent, and the nursing school staff signed informed consent before joining the research. 2.4 Statistics All data were analyzed by SPSS 23.0, with the significance level set to 0.05. Means and frequencies were calculated to describe demographic variables and individual characteristics as well as accessing missing data. Based on SWD status, subjects were categorized into four groups: (1) subjects with SWD at T1; (2) subjects with SWD at T2; (3) subjects with SWD at both T1 & T2 or persistent SWD; and (4) subjects without SWD at both T1 & T2. Independent-sample t-tests and χ2 tests were used to compare the differences between nurses with SWD and nurses without SWD. Bivariate logistic regression models were fit to examine the association between demographic variables, individual characteristics and SWD status. All demographic variables and individual characteristics were put into bivariate logistic regression models as the independent variables, while SWD after three months and SWD after six months were set as binary dependent variables. Moreover, to identify the variables that were predictors of the 7

persistence of SWD, we compared nurses with SWD and nurses without SWD at both T1 and T2 by using the same independent variables in logistic regression. In the case of the different score ranges of the research instruments, each total score of the implemented scales was standardized by Z score before being entered into the bivariate logistics regression model. All independent variables were first entered separately to conduct crude analyses and then they were all entered simultaneously to conduct an adjusted analysis. Selected entries were used for bivariate models.

3. Results 3.1 Descriptive statistics of Sample characteristics The descriptive information is presented in Table 1. All subjects recruited in this investigation were female, with a mean age of 17.80 (range 16 to 24, SD = 1.52). Most subjects (94.1%) had siblings. The majority (70%) of subjects were living in a town or village. The education level of their parents was basically below middle school (71.2% of their fathers and 81.4% of their mothers). Of their parents, 73.5% had good marital quality. Regarding family income, 59.8% of their families earned under ¥5000 per month, 30.9% of their families’ monthly incomes ranged from ¥5000 to ¥10000, and 9.2% of their families’ monthly income was over ¥10000. For the subjects’ lifestyle perspective, 65.7% of them exercised weekly. The majority

(71.7%) did not consume tea or coffee, and most subjects (97.5%) did not consume any alcohol. After they transferred into shift work, 20.5% of the participants were assigned to a rotating dayevening shift (2 shifts) work schedule, 59.9% were assigned to a rotating day-evening-night shift (3 shifts) work schedule, and 18.5% were assigned to random shifts. At baseline, there were 117 (16.6%) subjects reporting insomnia symptoms and 112 (15.9%) reporting excessive sleepiness.

Table 1 8

Descriptive sample characteristics Age BMI, kg/m2 Only child No Yes Location City Town Village Father’s education Below middle school Above high school Mother’s education Below middle school Above high school Parents’ marital quality Bad Moderate Good Physical exercise weekly No Yes Tea or coffee No 1-3 times per week Over 4 times per week Alcohol No 1-3 times per month Monthly income Under ¥5000rmb Over ¥5000rmb Over ¥10000rmb Insomnia symptoms at baseline No Yes Excessive sleepiness at baseline No Yes Shift schedule 2 shifts 3 shifts Random shifts Neuroticism total score Flexibility total score Languid total score FIRST total score CMS total score SWD T1 SWD T2 SWD T1 & T2

N 706 704

Mean/percentage 17.8 19.3

664 42

94.1% 5.9%

219 167 327

30.0% 23.7% 46.3%

503 202

71.2% 28.6%

575 131

81.4% 18.6%

39 147 519

5.5% 20.8% 73.5%

464 242

65.7% 34.3%

506 176 24

71.7% 24.9% 3.4%

688 18

97.5% 2.5%

422 218 65

59.8% 30.9% 9.2%

589 117

83.4% 16.6%

649 112

84.1% 15.9%

145 402 124 706 705 672 706 672 671 637 706

20.5% 59.9% 18.5% 16.2 14.4 18.5 17.3 32.1 35.2% (236) 37.7% (240) 18.3% (129)

9

SD 1.5 2.2

3.8 3.6 4.2 5.6 4.1

Notes: SD = standard deviation; BMI = body mass index. CMS = Composite Scale of Morningness. FIRST = Ford Insomnia Response to Stress Test

3.2 SWD status At baseline, none of the subjects were categorized as having SWD. At T1, after the first three months of shift work, 236 subjects (35.2%) were categorized as having SWD. At T2, after the first six months of shift work, 240 (37.7%) subjects were categorized as having SWD. The number of subjects who were categorized as having SWD at both T1 and T2 was 129 (18.3%). 3.3 Comparison of sample characteristics The comparisons of the differences between nurses with SWD and nurses without SWD across different assessments are presented in Table 2. Of the sociodemographic variables, the effects of parental marital quality were found to be significant in all three conditions, which means that the parental marital quality of healthy nurses was higher than that of SWD nurses. At T1, the percentage of healthy nurses who exercised weekly was higher than that of nurses with SWD. At T2, the percentage of healthy nurses who consumed alcohol was higher than that of nurses with SWD. The comparisons of rest of the sociodemographic variables showed no statistically significant or marginal differences in any of the three conditions and they were not presented at Table 2. As for baseline insomnia symptoms and baseline excessive sleepiness, the percentages of healthy nurses were significantly higher than those of SWD nurses in all three χ2 tests (p < 0.001).

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Table 2 Comparing nurses with SWD and nurses without SWD by independent-sample t-tests and χ2 test. T1 (n =671) T2 (n =637) T1 & T2 (n = 430)§ No SWD SWD t/χ2 No SWD SWD t/χ2 No SWD SWD t/χ2 *** *** Neuroticism total score 15.65 16.92 t = -4.25 15.47 16.91 t = -4.76 15.31 17.33 t = -5.20*** FIRST total score 16.39 18.88 16.35 18.59 15.98 19.36 t = -5.64*** t = -5.14*** t = -6.07*** *** *** CMS total score 31.38 32.96 31.10 33.43 31.49 33.06 t = -4.81 t = -4.72 t = -5.70*** *** *** Flexibility total score 14.78 13.45 14.71 13.78 14.78 13.12 t = 4.64 t = 3.21 t = 4.35*** *** *** Languidity total score 17.95 19.31 17.58 20.27 17.71 19.97 t = -6.93 t = -3.90 t = -6.28*** 2 ** 2 * χ = 10.41 χ = 7.11 χ2 = 16.04*** Parents’ marital quality Bad 24 (5.5%) 13 (5.5%) 16 (4.0%) 15 (6.3%) 13 (4.3%) 5 (3.9%) Moderate 73 (16.8%) 64 (27.2%) 71 (17.9%) 60 (25.1%) 49 (16.3) 43 (33.6%) Good 338 (77.7%) 158 (67.2%) 164 (68.6%) 310 (78.1%) 239 (79.4) 80 (62.5%) 165 (37.9%) 65 (27.5%) Physical exercise χ2 = 7.33** 142 (35.8%) 78 (32.5%) χ2 = 0.71 115 (38.2%) 38 (29.5%) χ2 = 3.02† 2 2 * weekly Alcohol consumption 7 (1.6%) 7 (3.0%) χ = 1.38 5 (1.3%) 10 (4.2%) χ = 5.50 4 (1.3%) 5 (3.9%) χ2 = 2.86† 2 *** 2 *** χ = 17.02 χ = 19.22 53 (12.2%) 58 (24.6%) 45 (11.3%) 59 (24.6%) 25 (8.3%) 34 (26.4%) χ2 = 24.85*** Insomnia symptoms T0 2 *** 2 *** χ = 23.15 χ = 35.08 Excessive sleepiness T0 46 (10.6%) 58 (24.7%) 33 (8.3%) 61 (25.5%) 19 (6.3%) 38 (29.7%) χ2 = 42.59*** Abbreviations: FIRST = Ford Insomnia Response to Stress Test; CMS = Composite Scale of Morningness. Note: *, p < 0.05; **, p < 0.01; ***, p < 0.001; † p < 0.10. § , To compare the differences between nurses with persistent SWD and all-time healthy nurses, nurses with SWD in only one of the two assessments were excluded.

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Table 3 Logistic regression analyses predicting SWD at T1 and SWD at T2 among Chinese intern nurses. In the crude analyses, each independent variable was analyzed one by one against SWD. In the adjusted analysis, all independent variables were simultaneously entered into the regression. OR Independent variable Age BMI, kg/m2 Only child (yes=1) Location Town Village Father’s education (≥high school = 1) Mother’s education (≥high school=1) Marital quality Moderate Good Monthly income Over ¥5000 Over ¥10000 Physical exercise weekly (yes=1) Tea or coffee 1-3 times per week Over 3 times per week Alcohol (1-3 times per month=1) Insomnia symptoms T0 (yes=1) Excessive sleepiness_T0 (yes=1)

No City

≤ middle school ≤ middle school

95% CI

SWD T1 OR

95% CI

OR

95% CI

SWD T2 OR 95% CI

Crude (N = 669 to 671)

Adjusted (N = 667)

Crude (N = 604 to 637)

Adjusted (N = 601)

1.01 0.98 0.75

0.91-1.12 0.91-1.06 0.38-1.50

1.00 0.95 0.66

0.89-1.13 0.88-1.04 0.31-1.44

1.00 1.00 0.96

0.98-1.11 0.93-1.08 0.49-1.90

0.98 0.96 0.79

0.87-1.11 0.89-1.05 0.36-1.7

1.00 0.99 0.93 1.05

0.64-1.55 0.68-1.43 0.65-1.33 0.70-1.58

1.07 1.07 0.74 1.38

0.65-1.76 0.69-1.68 0.46-1.17 0.79-2.41

0.90 0.74 0.93 0.85

0.28-1.39 0.51-1.08 0.64-1.33 0.55-1.30

0.90 0.66† 0.84 0.81

0.55-1.5 0.42-1.06 0.53-1.34 0.46-1.45

1.62 0.86

0.76-3.44 0.43-1.74

1.46 1.11

0.62-3.42 0.5-2.46

0.90 0.56

0.41-1.97 0.27-1.17

0.74 0.64

0.3-1.82 0.28-1.47

1.11 1.09 0.62**

0.78-1.57 0.62-1.91 0.44-0.88

1.02 0.90 0.82

0.69-1.52 0.47-1.74 0.55-1.21

1.05 1.02 0.87

0.74-1.50 0.58-1.78 0.62-1.21

1.12 0.79 1.17

0.74-1.69 0.4-1.57 0.78-1.74

1.02 0.54 1.87 2.35*** 2.77***

0.71-1.48 0.19-1.48 0.65-5.39 1.55-3.55 1.81-4.24

0.97 0.42 1.97 1.72* 1.58†

0.64-1.47 0.14-1.25 0.56-6.99 1.06-2.77 0.97-2.58

1.05 1.71 3.41* 2.55*** 3.78***

0.72-1.52 0.72-4.02 1.15-10.10 1.66-3.91 2.39-5.99

1.02 1.15 2.18 2.17* * 2.20*

0.66-1.56 0.43-3.09 0.58-8.19 1.31-3.62 1.29-3.74

Bad

Below ¥5000

No No

No No No

*

12

Shift schedule 3 shifts Random shifts Neuroticism total score FIRST total score CMS total score Flexibility total score Languidity total score

2 shifts 1.08 1.28 1.41*** 1.57*** 1.49*** 0.68*** 1.78***

0.72-1.61 0.77-2.11 1.20-1.67 1.33-1.85 1.26-1.76 0.58-0.81 1.50-2.13

1.16 1.38 1.12 1.29** 1.31** 0.75** 1.56***

0.74-1.82 0.78-2.43 0.92-1.36 1.07-1.57 1.09-1.58 0.62-0.90 1.28-1.90

1.47† 1.38 1.48*** 1.54*** 1.51*** 0.77** 1.39***

0.97-2.24 0.81-2.35 1.26-1.75 1.30-1.82 1.26-1.80 0.65-0.91 1.17-1.65

1.58† 1.31 1.19 1.31* * * 1.36 * † 0.85 1.18†

0.99-2.52 0.72-2.37 0.97-1.45 1.07-1.61 1.12-1.65 0.7-1.03 0.97-1.43

Abbreviations: OR, odds ratio; CI, confidence interval; BMI = body mass index; FIRST = Ford Insomnia Response to Stress Test; CMS = Composite Scale of Morningness. Note: *, p < 0.05; **, p < 0.01; ***, p < 0.001; † p < 0.10

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3.4 SWD predictors 3.4.1 T1 SWD predictors As Table 3 shows, baseline insomnia symptoms and baseline excessive sleepiness significantly increased the risk of having SWD at T1 in crude analyses (p < 0.001), but the effect of baseline excessive sleepiness was weakened into marginal significance in adjusted analysis. As for the individual characteristics, higher levels of sleep reactivity, morningness and circadian languidity increased the risk of having SWD at T1 in both crude analyses and adjusted analysis. Meanwhile, higher levels of circadian flexibility decreased the risk of having SWD at T1 in both crude analyses and adjusted analysis. For demographic variables, weekly physical exercise was shown to be a protective factor against SWD at T1 in crude analyses. 3.4.2 T2 SWD predictors As Table 3 shows, baseline insomnia symptoms and baseline excessive sleepiness significantly increased the risk of having SWD at T2 in crude analyses, but the OR value of baseline excessive sleepiness was reduced by 1.58 in adjusted analysis. As for the individual characteristics, trait neuroticism, higher levels of morningness, sleep reactivity and circadian languidity increased the risk of having SWD at T2, while circadian flexibility decreased the risk of having SWD at T2 in crude analyses. In the adjusted analysis, trait neuroticism was no significantly related to SWD at T2, while circadian languidity and flexibility had marginal effects on SWD at T2. For demographic variables, drinking alcohol one to three times per month increased the risk of having SWD at T2 in crude analyses. 3.4.3 Persistent SWD predictors As Table 4 shows, by comparing the nurses with SWD at both T1 & T2 and the nurses without SWD at both T1 & T2, baseline insomnia symptoms and baseline excessive sleepiness significantly increased the risk of having persistent SWD in crude analyses (p < 0.001), but the OR values of baseline insomnia symptoms and baseline excessive sleepiness were much reduced in adjusted analysis. As for the individual characteristics, higher levels of sleep reactivity, morningness, circadian languidity significantly increased the risk of having persistent SWD in both crude analyses and adjusted analysis. By contrast, higher levels of circadian flexibility

14

decreased the risk of having persistent SWD in both crude analyses and adjusted analysis. The effect of trait neuroticism was weakened into marginal in adjusted analysis. Table 4 Logistic regression analyses predicting the persistence of shift work disorder (SWD) at follow-up among Chinese nurses with SWD compared with healthy nurses. In the crude analyses, each independent variable was analyzed one by one against SWD. In the adjusted analysis, all independent variables were simultaneously entered into the regression.

Independent variable Age 2 BMI, kg/m Only child (yes=1) Location Town Village Father’s education (above high school=1) Mother’s education (above high school=1) Marital quality Moderate Good Monthly income Over ¥5000 Over ¥10000 Physical exercise weekly (yes=1) Tea or coffee 1-3 times per week Over 3 times per week Alcohol (1-3 times per month=1)

Persistent 6-month OR 95% CI OR 95% CI Crude (N = 428 to 430) § Adjusted (N = 427) § 1.01 0.88-1.16 0.92 0.77-1.09 0.99 0.89-1.09 0.91 0.80-1.03 0.57 0.21-1.54 0.49 0.14-1.71

No City

Below middle school Below middle school Bad

0.98 0.80

0.56-1.70 0.49-1.30

1.11 0.85

0.55-2.24 0.44-1.63

0.95

0.60-1.52

0.76

0.40-1.46

0.87

0.49-1.54

0.93

0.40-2.2

2.28 0.87

0.75-6.29 0.30-2.52

1.80 1.03

0.43-7.59 0.26-4.08

1.16 1.20

0.74-1.84 0.60-2.41

1.15 0.72

0.68†

0.43-1.05

1.20

0.65-2.05 0.29-1.79 0.69-2.11

1.24 0.99

0.78-1.96 0.30-3.24

1.00 0.60

2.99 3.95*** 6.27***

0.79-11.34 2.24-6.96 3.44-11.42

5.42† 2.14* 2.77**

Below ¥5000

No No

0.56-1.78 0.15-2.40 0.90-32.57

Insomnia symptoms_T0 (yes=1) No 1.04-4.39 Excessive sleepiness_T0 (yes=1) No 1.30-5.91 Shift schedule 2 shifts 3 shifts 1.28 0.77-2.14 1.31 0.69-2.47 Random shifts 1.37 0.70-2.65 1.22 0.54-2.79 *** † Neuroticism total score 1.74 1.39-2.17 1.30 0.99-1.71 FIRST total score 1.89*** 1.52-2.36 1.54** 1.16-2.04 CMS total score 1.90*** 1.50-2.40 1.58*** 1.20-2.07 *** Flexibility total score 0.64 0.52-0.79 0.70** 0.54-0.90 Languidity total score 1.98*** 1.57-2.49 1.70*** 1.30-2.22 Abbreviations: FIRST = Ford Insomnia Response to Stress Test; CMS = Composite Scale of Morningness. Note: *, p < 0.05; **, p < 0.01; ***, p < 0.001; † p < 0.10 15

§

, To compare the differences between nurses with persistent SWD and all-time healthy nurses, nurses with SWD in only one of the two assessments were excluded.

4. Discussion To our knowledge, this is the pioneer prospective study with baseline assessments tracking Chinese shift nurses and their experiences with first-time shift work. The current study sought to examine the causal relationship between predisposing individual characteristics and the initiation of SWD status among female nurses exposed to their first six months of shift work. Individual characteristics, including morningness, circadian languidity and sleep reactivity, were proven to be predictors of the initiation of SWD. The features of our research include a prospective design with baseline assessments; a considerable sample size and high response rates; highly homogeneous participants and the absence of the influence of many uncontrollable confounding factors; assessments of SWD by psychometric instruments; and the 3-month frequency of our research. The prevalence of SWD at T1 and SWD T2 was somewhat high for intern nurses without exposure to night shift work. Compared with other longitudinal studies in hospital settings, Waage, Pallesen [20] found a significant reduction in the prevalence of SWD over two years, from 35.7% to 28.6%, and the prevalence of persistent SWD was 18.9%; Kalmbach, Pillai [24] revealed a prevalence rate of 18.8% after one year of first-time rotating shift work. The stable high incidence rates of SWD might be due to the short periods between each evaluation time, so that most of the participants were in a stressed state caused by shift work. The other reason for the stability might be the small portion of the sample lost, because leaving shift work dramatically decreased the odds of having SWD [20]. Most likely, the prevalence rate of SWD would decline if the shift work continued because some nurses with SWD might find ways to adjust to the nonstandard schedule or leave shift work. As for the persistence of SWD during all 6 months of shift work (18.3%), the prevalence was consistent with previous studies [20, 24], which implied that around 18% of nurses would develop persistent SWD and they need major consideration and interventions. Baseline insomnia symptoms and baseline excessive sleepiness predicted the occurrence of SWD at T1 and T2 and predicted the persistent SWD from T1 to T2. These results implied that subjects with primary sleep disturbances were vulnerable to secondary sleep disturbances, especially in the first-time shift-work setting. A significant proportion of the nurses with baseline 16

sleep disturbance were prone to having chronic sleep problems [20] as well as excessive sleepiness [21]. The tendency of morningness was found to be a risk predictor of SWD in all three bivariate logistic models, which could help determine the controversial relationship between morningness and SWD in previous studies. Individuals with higher morningness scores seem to have difficulty staying awake in the evening or during a night shift and in restoring energy from daytime sleep, ultimately leading to first-time SWD. The present study met inconsistencies with the studies of the Norway shift nurses cohort. Storemark, Fossum [18] found that morningness was positively related to day-shift tolerance and was not related to evening shift tolerance. Morningness was negatively predictive of insomnia at the 6-month follow-up [22]. Vedaa, Krossbakken [21] documented a positive relationship between morningness and fewer symptoms of work-related insomnia over a three-year prospective study. However, we should point out that the participants in our research were quite different from those in the Norwegian nurse cohort in terms of age and shift work exposure. Vedaa, Bjorvatn [35] observed a significant change in the diurnal type of shift nurses over a 24-month follow-up; therefore, the results of these longitudinal studies could all be convincing under different circumstances. In this case, morningness, with cautious speculation, could be a risk factor for the onset of SWD in young female first-time nurses. As for circadian types, languidity increased the risk of having SWD at T1 and the risk of persistent SWD, while flexibility decreased the risk of SWD onset at T1 and the risk of persistent SWD, which was in line with the results of studies of a Norwegian nurse cohort [2, 18, 23]. In the present study, we found that the effects of languidity were larger than those of flexibility. In terms of SWD at T2, both languidity and flexibility showed a marginally significance. Languidity concerns the tendency to become tired or sleepy when cutting down on sleep, while flexibility denotes the ability to both work and sleep at odd times of the day. We speculated that the adaptability of working and sleeping at odd times of the day and the resilience of drowsiness could be nurtured after the nurses get used to the shift work schedule, so that the effects of flexibility and languidity were attenuated after 6 months of follow-up. However, for nurses with persistent SWD, the ability to overcome excessive sleepiness and tiredness when cutting down sleep was rather difficult for them to develop (the biggest OR value), which might imply that 17

sufficient sleep duration is required for the nurses to restore enough vigor to deal with rotational shift work. Sleep reactivity revealed increasing odds of initiation of SWD and persistent SWD. The OR values increased by each regression model, and sleep reactivity increased the risk of persistent SWD by 54%. Interestingly, neuroticism showed only marginal effects on predicting persistent SWD, but the scores of neuroticism among SWD nurses were significantly higher than those among health nurses. As proposed by the model of Harvey, Gehrman [36], trait neuroticism, combined with predisposing genetics, may increase the stress-reactivity and negative emotions that lead to sleep disturbance. Sleep reactivity is the trait-like degree to which stress exposure leads to sleep disturbance, and high sleep reactivity is pathologically and clinically pertinent and linked to the risk of SWD [37]. Therefore, parts of the effect of neuroticism might be explained by sleep reactivity. As sleep reactivity appears to be a stable trait that reacts to stress sensitively and perpetuates sleep problems, it is advisable to apply the FIRST as a reference tool in career exploration. Among the sociodemographic variables, alcohol consumption, physical exercise, and parents’ marital quality should be concerned, although none of them were found significant in logistics regressions. As a recent study revealed, alcohol and night-shift can impose detrimental effects on shift workers productivity [38], so it would be best for shift workers to stop drinking. Physical exercise was shown to be protective at T1, and more healthy nurses did exercise than SWD nurses. Exercise is proven to entrain circadian rhythm and significant circadian phaseshifting effects, so doing exercise is highly recommended for coping circadian misalignment [39, 40]. From the comparison of parents’ marital quality in three conditions, we all found that the marital quality of healthy shift workers’ parents was significantly better than that of the parents of those with SWD. Studies have documented that parental marital hostility was associated with a child’s sleep disturbance [41]. A cohesive family relationship may provide a sense of stability and security for subjects to fall asleep [42]. There are several methodological weaknesses of our research; therefore, the results should be interpreted cautiously. First, all measurements were based on self-reported data, which potentially threatens the validity of the results. The better way to determine SWD status is to implement clinical diagnostic interviews. Moreover, the ICSD-3 recommends using sleep logs 18

and actigraphy-based assessments as collateral measurements to inform SWD diagnoses whenever possible [5]. More objective biomarkers of circadian patterns and sleep should be applied to ensure the validity of these results. Second, Cronbach’s alpha coefficient of the composite scale of morningness was rather low, which might create bias in reflecting the preference of morningness and undermine the validity of the relationship between morningness and SWD. Third, the highly homogeneous sample (female, nurses, young age) also implies the lack of representatives. It is still uncertain whether the SWD predictors could also be generalized to male healthcare shift workers, shift workers in other occupational settings or shift workers of a wider range of ages. Finally, the changes in SWD over a longer period of time are unknown, as well as the relationship between these individual characteristics and SWD status. Future research can build on the merits of this research and conduct more objective methods in studying shift work tolerance, such as sleep logs and actigraphy-based assessments. Furthermore, cutting-edge genetic and neuroimaging methods could also be applied to illustrate the mechanisms of these predictors of SWD. People with a high tendency for SWD should carefully consider taking on the shift work schedule, because the sleep disturbance caused by shift work and its comorbidity tend to go hand in hand [43]. Moreover, employees with primary sleep disturbance should accept treatments to avoid incident SWD. Bright light exposure, napping, psychoeducation for sleep hygiene, and cognitive-behavioral measures are common nonpharmacological recommendations to help circadian systems better adjust to shift work schedules. For workers with high neuroticism or sleep reactivity, enough rest and less stress are recommended to reduce the odds of having SWD.

5. Conclusions From this prospective investigation tracking first-time intern nurses, it has been revealed that sleep reactivity and variables related to circadian rhythms, including circadian flexibility and languidity and morningness, proved to be the predictors of SWD status in the first 6 months of shift work for new intern female nurses. Specifically, circadian flexibility contributed as a protective factor against SWD, while circadian languidity, morningness and sleep reactivity contributed as risk factors for SWD.

6. Acknowledgements 19

The present study was funded by National Natural Science Foundation of China (grant numbers: 31871129, 31671165); Humanities and Social Science Fund of Ministry of Education of China (grant number: 16JJD190001); Guangdong Province Higher Vocational Colleges and Schools Pearl River Scholar Funded Scheme, GDUPS (2016).

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22

Authors Contribution Sections Dingxuan Chen: Writing-Original draft preparation, Writing – review & editing, Methodology, Formal analysis Min

Jiang: Software, Formal analysis, Visualization, Data curation

Xuliang Shi: Conceptualization, Data curation, Investigation. Writing- Reviewing and Editing, Validation Fulei Geng: Methodology, Writing- Reviewing and Editing Haiying Qi: Investigation. Yuechu Zhang: Investigation Yuan Lai: Investigation Fang Fan: Supervision. Resources, Project administration, Funding acquisition, Writing- Reviewing and Editing

Highlights This is the first study to examine predictors of the onset of shift work disorder by following nurses before they started working rotating or night shifts. Sleep reactivity and variables related to circadian rhythms, including circadian flexibility and languidity and morningness, play predisposing roles in SWD onset. Sociodemographic variables were involved systematically, and multiple appropriate self-report instruments were implemented. There were three waves of data collection with a high sample size and response rate.