Citation for published version (APA): Lammers-van der Holst, H. M. (2016). Individual differences in shift work tolerance

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1 UvA-DARE (Digital Academic Repository) Individual differences in shift work tolerance Lammers-van der Holst, H.M. Link to publication Citation for published version (APA): Lammers-van der Holst, H. M. (2016). Individual differences in shift work tolerance General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam ( Download date: 04 Jan 2018

2 Sleep is the best meditation Dalai Lama

3 Chapter 2 Shift work tolerance and the importance of sleep quality: a study of police officers Abstract The aim of this study was to examine how subjective shift work tolerance was related to general health variables, with the expectation of inter-individual differences in the nature of this relation. A total of 740 employees of the Dutch police force completed a questionnaire, covering seven health-related domains: sleep quality, sleep duration, need for recovery, fatigue, physical health, mental health, and work life balance. Based on subjective reports of shift work tolerance, participants were classified as intolerant, medium-tolerant, or tolerant workers. Analysis involved group comparisons, regression, and cluster analysis. Eighteen percent of the shift workers were classified as intolerant. The intolerant and medium-tolerant workers expressed more severe complaints than the tolerant workers, for all seven health-related domains. Shift work tolerance was primarily related to sleep quality and subsequently to need for recovery, fatigue and work life balance. No indications were found for systematic inter-individual differences in the nature of this relationship. For all participants equally, the degree of shift work tolerance was related to the severity of healthrelated complaints. This study highlights the central role of sleep for tolerance to shift work and underlines the need for occupational medicine to take explicit account of sleep. This chapter is based on: Lammers-van der Holst HM, Kerkhof GA (2015). Shift work tolerance and the importance of sleep quality: a study of police officers. Biological Rhythm Research, 2:

4 Chapter 2 Introduction Shift work usually requires the shift worker to sleep at an inappropriate phase of the circadian pacemaker, especially during night and early morning shifts (Rajaratnam et al., 2013; Sallinen & Kecklund, 2010). This circadian misalignment causes sleep wake disturbances and a variety of health-related problems (Åkerstedt, 2003; Knutsson, 2003). These adverse consequences of shift work are well documented and involve insomnia, excessive sleepiness [both referred to as shift work sleep disorder (SWSD)], fatigue, the metabolic syndrome, gastrointestinal and cardiovascular diseases, mental health problems and disturbed social life (De Bacquer et al., 2009; Drake et al., 2004; Tucker & Folkard, 2012; Vogel et al., 2012). Notably, there is considerable inter-individual variability in the degree of shift work tolerance, as defined by various subjective and objective measures of sleep, health and well-being (Härmä, 1993; Lammers-van der Holst et al., 2006; Saksvik et al., 2011; Van Dongen, 2006). The present questionnaire study set out to analyze subjective reports of shift work tolerance in relation to variables in the domains of sleep, health and work life balance. This analysis was motivated by the hypothesis that individuals may differ in the nature of the determinants of their shift work tolerance. For example, some shift workers may attribute their intolerance to repeatedly occurring conflicts at home, whereas others may primarily refer to health-related problems underlying their intolerance. Methods Participants Questionnaires were sent to 2244 employees of the Dutch police force in Amsterdam. A total of 954 questionnaires were returned (response rate of 43%). From these, 46 were discarded because of incomplete information about working hours. Also, regular day workers, including those who reported to work evening shifts, were left out of the analyses (N = 148). Twenty participants did not respond to the question about their shift work tolerance, leaving a total N of 740. On the basis of their subjective tolerance score (see below), the subjects were classified as tolerant, intolerant or medium-tolerant. Table 1 shows the characteristics of the subgroups and the total group. 22

5 Shift work tolerance and the importance of sleep quality Table 1. Demographics and shift characteristics for the subgroups and total group. Measures Intolerant (N = 133) Medium tolerant (N = 130) Tolerant (N = 477) Total (N = 740) Post hoc comparisons M SD M D M SD M SD Directions d Age I>T, I>M BMI SWE I>T, I>M Work hours a I<T, M<T Females (%) I>T part-timers b NA Morning shifts c Evening shifts c I<T Night shifts c Day shifts c Note: a weekly work hours in decimals, b less than 30 working hours a week. c percentage worked shift type per month. d Post hoc comparisons were evaluated at p < BMI: Body mass index, SWE: years of shift work experience at the police force. I: intolerant, M: medium tolerant, T: tolerant, NA: not applicable. Work schedules The police officers worked a rotating schedule. Their actual work hours (mean ± SD) were as follows: morning shift: 06:42 15:56 h, duration: 9 h, 14 min ± 28 min; evening shift: 14:01 23:19 h, duration: 9 h, 19 min ± 23 min; night shift: 22:25 06:52 h, duration: 8 h, 28 min ± 25 min; and day shift: 08:12 17:24 h, duration: 9 h, 13 min ± 29 min. Shift durations did not differ between subgroups (p > 0.05). Shift work tolerance To indicate their tolerance, participants responded to the verbatim question: Do you consider yourself as someone who has difficulty doing shift work?. On the basis of their answers, subjects were categorized into three subgroups: intolerant (N = 133), mediumtolerant (N = 130) and tolerant (N = 476). 23

6 Chapter 2 Health-related domains Participants responded to 59 questions concerning the following seven domains, using 5- point rating scales (or otherwise specified). (1) Sleep quality (seven items). Two questions on sleep quality in general (e.g. shift work has a negative effect on my sleep ), four questions about the quality of sleep during the different shift types and one question about the days off. (2) Sleep duration (five items). For each shift type separately and for days off, participants indicated their habitual sleep duration (h:min). (3) Need for recovery (three items). For instance: in general, I only start to feel relaxed on the second non-working day. Items were derived from the need for recovery scale of the VBBA (Veldhoven & Meijman, 1994), a sum score was calculated (range 3 15). (4) Fatigue (20 items). The Checklist Individual Strength questionnaire, with a 7-point rating scale, was used (Beurskens et al., 2000). A sum score was obtained by adding the scores on the four subscales; severity of tiredness, concentration, motivation and physical activity (range ). (5) Physical health (eight items). Three questions covered gastrointestinal problems, three questions about cardiovascular complaints and two questions on flu like symptoms. (6) Mental health (10 items). The Rasch-derived short form of the Center for Epidemiologic Studies-Depression scale was used, with a 4-point rating scale (Cole et al., 2004). Scores were summed up to create a total score (range 10 40). (7) Work life balance (six items). For example: my working hours are balanced with my private life. A sum score was computed (range 6 30). If needed, the scores were transformed in such a way that higher scores indicate more severity of complaints (with the exception for sleep duration). Statistical analysis ANOVA s and Chi-square analyses were used to compare demographic and work schedule data between groups. For the seven domains, analysis of covariance (ANCOVA) was used to compare data between groups with age, gender and shift work experience as covariates. When main effects were statistically significant, Bonferroni post hoc tests were performed. A binary logistic regression analysis was performed to understand how health-related variables were associated with shift work tolerance. The dependent factor was dichotomized as tolerance vs. intolerance, with the seven domains as predictors. The results yielded odds ratios (OR s) with 95% confidence intervals (CI). 24

7 Shift work tolerance and the importance of sleep quality To investigate inter-individual differences in shift work tolerance, a cluster analysis (twostep cluster, based on the predictors) was performed over the total group (N = 740). All analyses were performed using the statistical package SPSS 21 for Windows (SPSS, Chicago, IL, USA). Results As presented in Table 1, the intolerant group showed a larger proportion of females, a higher average age, more shift work experience, less weekly work hours and less evening shifts per month than the tolerant group (p < 0.05). The average age and duration of shift work experience of the intolerant workers were also significantly higher compared to the medium-tolerant workers (p < 0.05). The medium-tolerant group showed less weekly work hours compared to the tolerant group (p < 0.01). No group differences were found in the distributions of morning, night and day shifts per month. When controlled for gender, age and shift work experience, the most consistent result was that for all domains, both the intolerant and the medium-tolerant workers expressed more severe health-related complaints than the tolerant workers and that for five out of the seven domains, the intolerant workers differed from the medium-tolerant workers, as detailed in Table 2. Results of the binary logistic regression analysis, with tolerance vs. intolerance as the dependent variable and the seven domains as predictors, are shown in Table 3. The amount of explained variance was 43% (p < 0.01). Significant predictors were sleep quality, need for recovery, fatigue and work life balance (p < 0.01). By far, the strongest predictor was sleep quality (OR: 3.32, 95% CI: ). Cluster analysis with the seven domains as cluster variables identified two clusters with a fair silhouette measure of cohesion and separation (0.4), as detailed in Table 4. The first cluster (N = 417) was characterized by only moderate complaints for all domains, whereas the second cluster (N = 283) showed more serious complaints. Seventy-four percent of the tolerant workers were represented in the first cluster, whereas the second cluster represented 82% of the intolerant workers (p < 0.01). The medium tolerant workers were equally divided between both clusters (51% vs 49%) (p > 0.05). 25

8 Chapter 2 Table 2. Results of the ANCOVA s for the 7 health-related domains. Intolerant Medium tolerant Tolerant Model Post hoc comparisons M SE M SE M SE R² F-value Directions c Sleep quality a *** I>M, I>T, M>T Sleep duration a, b 7:18 0:05 7:18 0:05 7:36 0: *** I<T, M<T Need for recovery *** I>M, I>T, M>T Fatigue a *** I>M, I>T, M>T Physical health *** I>T, M>T Mental health *** I>M, I>T, M>T Work-life balance *** I>M, I>T, M>T *** p < a age was significant as covariate (p < 0.05), b (h:min). c Post hoc comparisons were evaluated at p Higher scores indicate more complaints, with the exception for sleep duration. M: adjusted means; SE: standard error. 26

9 Shift work tolerance and the importance of sleep quality Table 3. Results of the binary logistic regression analysis with Tolerance vs. Intolerance as dependent variable and the 7 health-related domains as predictors. OR 95% CI Wald P-value Sleep quality Sleep duration Need for recovery Fatigue Physical health Mental health Work-life balance (R² = 0.43 Nagelkerke, p < 0.01). Table 4. Centroids for 2 clusters as a result from the two-step cluster analysis. Cluster variables Cluster 1 (N = 417) Cluster 2 (N = 283) M SD M SD Sleep quality Sleep duration a 7:42 1:00 7:06 0:54 Need for recovery Fatigue Physical health Mental health Work-life balance a (h: min). Higher scores indicate more complaints, with the exception for sleep duration. 27

10 Chapter 2 Discussion This questionnaire-based study of 740 police officers investigated their tolerance for shift work in relation to their reports on seven health-related domains. The results clarified that shift work tolerance was primarily associated with sleep quality and also subsequently with need for recovery, fatigue and work life balance. Contrary to our expectation, no indications were found for systematic inter-individual differences in the nature of this relationship. So, for all participants equally, the degree of shift work tolerance was related to the severity of complaints, irrespective of a particular domain. Eighteen percent of the responders were classified as intolerant, a percentage that is similar to previous reports (Härmä, 2006; Waage et al., 2009). The demographic data of the present study suggest possible explanations for the reported intolerance. The intolerant group included a larger proportion of females (44%) compared to the tolerant group (30%). Previous research has shown that shift working women experience more specific healthrelated disturbances, in terms of menstrual cycle irregularities, problems with reproductive health and increased risk of breast cancer (Shechter et al., 2008). The intolerant workers also reported less working hours and fewer evening shifts, which could be a direct result of the women s double burden of responsibilities at home and at work. Consistent with previous research (Costa & Di Milia, 2008), a higher average age and more years of shift work experience were found for the intolerant group, contradicting the healthy workers effect in the present data (Knutsson & Åkerstedt, 1992). The central role of sleep quality for shift work tolerance is documented by many studies (Åkerstedt, 2003; Axelsson et al., 2004; Lammers-van der Holst et al., 2006; Rajaratnam et al., 2013; Van Dongen, 2006). The extreme difficulty to maintain an adequate sleep wake function while working in shifts, due to circadian misalignment, is diagnosed as SWSD (Drake et al., 2004). Recent studies show that SWSD can be a chronic condition, as evidenced by measurements in retired shift workers (Monk et al., 2013; Rotenberg et al., 2011). The present results may be interpreted within the view that disturbed sleep is a factor in the causative pathway from shift work to deteriorating health (Puttonen et al., 2010; Rajaratnam et al., 2013). Short sleep and poor sleep quality have convincingly been shown to have adverse health effects (Cappuccio et al., 2011; Hoevenaar-Blom et al., 2011; Jennings et al., 2007). Sleep deprivation and poor sleep quality in shift workers might 28

11 Shift work tolerance and the importance of sleep quality contribute to the development of the metabolic syndrome and other health problems (Drake & Wright, 2011; Härmä, 2006; Karlsson et al., 2001; Waage et al., 2009). In addition to sleep quality, need for recovery, fatigue and work life balance were significantly related to shift work tolerance, as consistent with previous reports (Bohle & Tilley, 1998; Jansen et al., 2003; Takahashi et al., 2005; Winwood et al., 2006). These results are in line with a longitudinal study where high levels of poor sleep quality, need for recovery, fatigue and work life conflict were associated with an increased risk of leaving shift work (Van Amelsvoort & Kant, 2004). A similar subjective approach to shift work tolerance (as in the present study) has been described by Axelsson et al. (2004), relating sleep wake measurements with satisfaction to work hours. They reported increased sleep wake problems for dissatisfied shift workers and suggested this to be related to increased sensitivity to curtailed and displaced sleep. The dominant role of sleep quality with regard to shift work tolerance suggests that inter-individual differences in vulnerability for sleep loss might be the most important factor to determine the inter-individual variability in shift work tolerance (Van Dongen, 2006). This study holds some limitations. Unfortunately, it was not feasible to strengthen the results with objective measurements, such as actigraphy. An overall response rate of 43% was reasonable for a survey in the working population, yet a potential bias for selective participation cannot be ruled out. In addition, the cross-sectional design of this study makes it difficult to decide on causality. Future research should focus on longitudinal designs to investigate predictability of inter-individual differences in shift work tolerance, using subjective as well as objective measurements. In conclusion, distinct evidence was found for the workers quality of sleep to be the strongest determinant for subjective tolerance for shift work. The severity of complaints in all the domains of sleep, health and work life balance appeared to be related to the degree of shift work tolerance, equally for all subjects. This study emphasizes the importance for occupational medicine to detect early signs of sleep wake disturbances, not only to help shift workers cope with their work schedules, through proper countermeasure management (sleep hygiene, napping), but also to prevent further associated health problems and the risk of sleepiness related accidents. 29

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