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Occupational and environmental medicine
Research
A cross-sectional study of shift work, sleep quality and cardiometabolic risk in female hospital employees
  1. P Lajoie1,
  2. K J Aronson1,2,
  3. A Day1,3,
  4. J Tranmer1,3,4
  1. 1Department of Public Health Sciences, Queen's University, Kingston, Canada
  2. 2Division of Cancer Care and Epidemiology, Cancer Research Institute, Queen's University, Kingston, Canada
  3. 3Clinical Research Centre, Kingston General Hospital, Kingston, Canada
  4. 4Faculty of Health Sciences, School of Nursing, Queen's University, Kingston, Canada
  1. Correspondence to Dr Joan Tranmer;tranmerj{at}kgh.kari.net

Abstract

Objectives Investigating the potential pathways linking shift work and cardiovascular diseases (CVD), this study aimed to identify whether sleep disturbances mediate the relationship between shift work and the metabolic syndrome, a cluster of CVD risk factors.

Design Cross-sectional study.

Setting A tertiary-level, acute care teaching hospital in Southeastern Ontario, Canada.

Participants Female hospital employees working a shift schedule of two 12 h days, two 12 h nights, followed by 5 days off (n=121) were compared with female day-only workers (n=150).

Primary and secondary outcome measures Each of the seven components of the Pittsburgh Sleep Quality Index (PSQI) was measured. Of these, PSQI global score, sleep latency and sleep efficiency were examined as potential mediators in the relationship between shift work and the metabolic syndrome.

Results Shift work status was associated with poor (>5) PSQI global score (OR=2.10, 95% CI 1.20 to 3.65), poor (≥2) sleep latency (OR=2.18, 95% CI 1.23 to 3.87) and poor (≥2) sleep efficiency (OR=2.11, 95% CI 1.16 to 3.84). Although shift work was associated with the metabolic syndrome (OR=2.29, 95% CI 1.12 to 4.70), the measured components of sleep quality did not mediate the relationship between shift work and the metabolic syndrome.

Conclusions Women working in a rapid forward rotating shift pattern have poorer sleep quality according to self-reported indicators of the validated PSQI and they have a higher prevalence of the metabolic syndrome compared with women who work during the day only. However, sleep quality did not mediate the relationship between shift work and the metabolic syndrome, suggesting that there are other psychophysiological pathways linking shift work to increased risk for CVD.

  • OCCUPATIONAL & INDUSTRIAL MEDICINE
  • SLEEP MEDICINE
  • EPIDEMIOLOGY

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

http://dx.doi.org/10.1136/bmjopen-2014-007327

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    Strengths and limitations of this study

    • This study is strengthened by its use of a thoroughly validated sleep questionnaire which has been widely applied in the scientific literature (Pittsburgh Sleep Quality Index Questionnaire).

    • Its strength also lies in the statistical analysis that was performed using a well-known mediation analysis methodology.

    • The cross-sectional nature of this study limits the assessment of causality.

    Introduction

    In industrialised countries, approximately 20% of the working population engages in some type of shift work schedule.1 According to the Canadian General Social Survey (2009), 4.1 million employed Canadians are shift workers, representing roughly 27% of the workforce.2 In the healthcare sector, the proportion of shift workers is estimated to be even higher at 45%.2 Furthermore, for all health occupations combined, 84% of Canadian hospital employees are female.3 This study aimed to further examine the potential pathways in which shift work as a highly prevalent exposure may lead to risk for poor health among female hospital workers.

    Shift work has been associated with many adverse health outcomes including gastrointestinal disturbances, the metabolic syndrome (MetS), diabetes mellitus, reproductive difficulties and breast and prostate cancer.1 ,4–7 In this study, we are focusing on the relationship between shift work and atherosclerotic-related cardiovascular disease (CVD), which is inconsistently supported in the literature.8–11 A review in 2012 of shift work and vascular morbidity, vascular mortality or all-cause mortality identified that, in 34 studies including 2 011 935 participants, shift work was associated with myocardial infarction with a relative risk (RR) of 1.23 (95% CI 1.15 to 1.31) and ischaemic stroke with an RR of 1.05 (95% CI 1.01 to 1.09).8 Working night shifts was associated with the highest increase in risk for coronary events with an RR of 1.41 (95% CI 1.13 to 1.76).8

    In the healthcare setting specifically, women of the Nurses’ Health Study cohort were compared prospectively with women who had never been shift workers and the multivariate age-adjusted RR for developing coronary heart disease was 1.51 (95% CI 1.12 to 2.03) among those with six or more years of rotating shift work experience (≥3 nights/month with days and evenings).12 Another analysis of this cohort revealed a risk for ischaemic stroke, where every 5 years of rotating shift work was associated with 4% increased risk (HR=1.04, 95% CI 1.01 to 1.07).13

    A major issue among shift workers is disturbed sleep and this has been shown to be independent of levels of physical activity, smoking and drinking habits.14 ,15 Common problems include insufficient sleep (duration), difficulty getting to sleep (sleep latency) and the feeling of not being refreshed after sleep.15 ,16 Two recent reviews suggest that dysfunctional sleep patterns could contribute to the increased CVD risk in shift workers as several characteristics of sleep disturbances are associated with cardiometabolic consequences.9 ,10 For instance, evidence supports the relationship of poor sleep quality and short duration of sleep with the activation of the sympathetic nervous system,17 and increased levels of vascular inflammation.18 ,19 Using the Pittsburgh Sleep Quality Index (PSQI) Questionnaire, a cross-sectional study found that women with poor sleep latency (frequent episodes of >30 min to fall asleep) and poor overall sleep quality had higher levels of inflammatory biomarkers (C reactive protein and interleukin 6).20 Moreover, sleep has a regulatory effect on glucose metabolism and hormones regulating appetite, and therefore disturbances in sleep may promote weight gain among shift workers.11 In the population-based Wisconsin Sleep Cohort Study, those with 5 h of sleep compared with those with 8 h or more had lower levels of the appetite suppressing hormone leptin, and higher levels of the appetite stimulating hormone ghrelin, suggesting that a lack of sleep could encourage food consumption and therefore weight gain.21 Meanwhile, another study aiming to examine the effects of sleep from a metabolic perspective found that glucose clearance and acute insulin response were reduced up to 40% following nights of curtailed sleep in healthy individuals (≤4 h).22 Similar results were observed in a case-crossover study of men and women exposed to experimentally fragmented sleep.23 These findings suggest that it is biologically plausible that recurrent, long-term exposure to short duration and poor sleep quality among female shift workers increases the risk of MetS and CVD.

    Direct evidence of the association between shift patterns and biomarkers of CVD is needed.24 It is suggested that research needs to characterise shift work with regard to clearly defined patterns of shift schedules and identify contributors in the pathways between shift work and CVD.24 To this end, a mediation analysis is appropriate as it can provide further evidence in making a causal interpretation.25 Conceptually, a mediator is a variable that accounts for the relationship between an exposure and outcome; as such, it can represent the mechanism.26 The objective of this study was to determine the association between work patterns and the MetS among female hospital employees. The next step was to test whether sleep quality lies on the pathway between shift work and an increased risk of CVD as represented by the MetS. MetS is a cluster of risk factors for CVD that present together.27 This is the outcome of interest for three reasons: first, studies have demonstrated that MetS leads to an increased risk of developing CVD; for instance, a meta-analysis identified that the risks of myocardial infarction, stroke and CVD mortality among those with MetS were 1.99 (95% CI:1.61 to 2.46), 2.27 (95% CI 1.80 to 2.85) and 2.40 (95% CI 1.87 to 3.08), respectively.28 Second, the association between poor sleep quality and MetS has been demonstrated in cross-sectional studies.29 ,30 Lastly, rotating shift work has been associated with MetS in cross-sectional31 and prospective studies.32 ,33

    Methods

    Study design

    In a tertiary-level acute care teaching hospital in Southeastern Ontario, Canada, we conducted a cross-sectional study in 2012–2013 with recruitment through posters in the hospital and email advertising. Women were eligible if they had been working for a minimum of 2 years and were not pregnant. To qualify as shift workers, they had to be working a pattern of two 12 h days, two 12 h nights with 5 days off. The comparison group consisted of women working only during the day. During an in-person interview, participants received information about the study protocol, and after they provided consent anthropometric measurements were taken. Each participant provided detailed information in a written questionnaire and they completed the PSQI. This study was approved by the Queen's University Health Sciences Research Ethics Board.

    The MetS was defined according to the 2009 Joint Interim Studies consensus statement.27 A participant was considered as positive for the MetS if she met three or more of the following criteria: high waist circumference (≥80 cm); elevated triglycerides (≥1.7 mmol/L); reduced high-density lipoprotein (<1.3 mmol/L); elevated blood pressure (systolic ≥130 and/or diastolic ≥85 mm Hg); elevated fasting blood glucose (≥100 mg/dL). Women currently taking medication to treat their levels of cholesterol or high blood pressure were also identified as positive. The mean of three consecutive readings of blood pressure was taken using the BpTRU blood pressure monitor (VSM MedTech Ltd, Coquitlam, Canada).

    Mediation measures: sleep quality

    The PSQI is a validated and widely used tool to identify elements of sleep over the past 30 days and reflects the cohort's perception of sleep on shift and non-shift days.34 This questionnaire identifies seven “components” of sleep routinely assessed clinically: sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep medication, daytime dysfunction and subjective sleep quality. The sum of scores of the aforementioned seven component scores gives a global PSQI score that ranges from 0 to 21 points; a score >5 is associated with poor sleep quality, and was therefore dichotomised as such in our analysis. The PSQI scores have been shown to have good test–retest reliability, with a correlation coefficient of 0.85 for the global score, and correlation coefficients ranging from 0.65 (medication use) to 0.84 (sleep latency) for the component scores.34

    Statistical analyses

    The PSQI component scores range from 0 (best) to 3 (worst) and were dichotomised as good (0,1) and poor (2,3) in logistic regression models. The adjusted OR relating shift workers to day workers for the global PSQI score (>5) and each of its seven components were computed separately. For multivariable models, age was always retained. To assess other variables as potential confounders, a backward deletion approach was taken, with a change in estimate of 10% or more as the criterion to keep a variable in the model.35

    Global PSQI, sleep latency and sleep efficiency scores were all significantly associated with shift work and therefore tested as mediating variables using multivariate logistic regression in separate models using the classic method of Baron and Kenny26 investigating the significance of individual relationships in the mediation pathway. According to the Baron and Kenny criteria, mediation occurs if: (1) the independent variable shift work affects the dependent variable MetS (path c); (2) the independent variable shift work significantly affects the mediators (path a); and, (3) the mediators affect the dependent variable MetS while controlling for shift work (path b).26 Mediation occurs if, when paths a and b are controlled, the significant relationship between the predictor and outcome of interest is attenuated (path c’).26 These conditions are depicted in figure 1 and summarised by the following regression equations:Embedded Image 1Embedded Image 2Embedded Image 3

    Figure 1
    Figure 1

    Conceptual framework for a mediation analysis of the relationship between shift work and the metabolic syndrome (PSQI, Pittsburgh Sleep Quality Index).

    In terms of assessing for confounders, we considered that many behavioural factors potentially altering sleep quality could feasibly be a result of shift work, such as smoking and stress.36 Behavioural changes are suggested as components of the multifactorial relationship existing between shift work and CVD risk,10 and many studies investigating this relationship erroneously consider these factors as confounders, when they in fact lie on the causal path.24 This analysis included only those variables that are not known to be on the causal pathway between shift work and sleep disturbances or the MetS: age, income and menopausal status. All data analyses were performed using SAS V.9.3 (SAS Institute Inc., Cary, North Carolina, 2012).

    Results

    Table 1 shows that, on average, shift workers were younger than day workers; a larger proportion were single or never married without children, had achieved a university degree and had higher household income. Groups were comparable in regard to CVD risk factors including family history of heart disease, body mass index and smoking. The majority of shift workers were in nursing positions and the rest of the group was comprised of women in other regulated health professions and administrative and support services. The majority (>75%) of the day working group included women in nursing and management positions. A greater proportion of current shift workers (39%) had worked more than 15 years of shift work, although about 25% of day workers had also worked more than 15 years of shift work in the past.

    View this table:
    Table 1

    Characteristics of the study population

    Table 2 shows that a greater proportion of shift workers were positive for all but one of the risk factors of the MetS. Almost twice as many shift workers presented with the MetS than day workers with frequencies of 22% and 13%, respectively (p=0.05).

    View this table:
    Table 2

    The metabolic syndrome and its risk factors

    Mean scores of the PSQI global score and its seven components are presented in table 3 along with the proportion of shift and day workers with a component score ≥2 (a ‘poor’ score). Poor sleep latency score was significantly more frequent in shift workers (42%) compared with day workers (27%), and mean scores differed significantly (p<0.01). Significant differences were also apparent for sleep efficiency, a measure that reflects factors such as fragmented sleep and ability to stay asleep. The sleep efficiency score was 1.2 (±1.1) in shift workers, corresponding to a mean sleep efficiency of ≥65% to <85% as compared with a mean score of 0.6 (±0.9) in day workers, corresponding to a mean sleep efficiency of >75% to 100%. Similarly, significant differences in the mean PSQI global score were observed with 47.9% of shift workers having a PSQI score >5 and only 32.7% in our day working group (p<0.01). These differences persisted in multivariate logistic regression, adjusting for age, household income and menopausal status.

    View this table:
    Table 3

    Mean PSQI global and component scores; proportion of women with scores >2 (components) or >5 (global); and adjusted ORs comparing shift and day workers for seven components and PSQI global score

    Results of the mediation analysis are seen in table 4. Shift work is strongly associated with the MetS with an OR of 2.29 (95% CI 1.12 to 4.70; path c), while controlling for age, menopausal status and income. When regressing all three indicators of sleep quality on the independent variable shift work, each relationship was statistically significant with ORs ranging from 2.10 to 2.18 (path a). In the analysis of the relationship of sleep quality with the MetS, no relationship was statistically significant (path b). Furthermore, the relationship between shift work and the MetS did not change when taking into account all three suspected mediators (path c’), and therefore no mediation is apparent.

    View this table:
    Table 4

    Mediation analysis of the relationship between shift work and the metabolic syndrome by sleep disturbances in female hospital employees

    Discussion

    Shift work is strongly associated with MetS, a proxy measure for CVD risk, among this group of female workers. Our result is of similar magnitude to results in one study of men working a rapidly rotating three-shift system (OR=2.38, 95% CI 1.13 to 4.98).31 The large population-based Swedish Västerbotten intervention programme identified that the RR relating a group of females working various shift schedules compared with day workers in association with the MetS was 1.7 (p<0.0001).37 The relationship has also been demonstrated in prospective studies,32 ,33 one of which included male and female nurses working night shifts or rotating shifts with ≥4 nights/month: after 4 years, the RR for developing the MetS was 5.0 (95% CI 2.1 to 14.6).32

    Having observed a significant relationship between shift work and MetS, we explored this in relation to indicators of sleep quality using the extensively administered and validated PSQI to facilitate the comparison with other studies.34 ,38 We observed that shift work is strongly associated with poor sleep latency (difficulty falling asleep), as have other studies among those working early morning shifts14 ,16 and other shift-working groups.39 ,40 It has been suggested that adaptation to night shifts occurs rarely, since usual daytime activity and night-time sleep are resumed on days off.41 In our study, shift work was also associated with poor sleep efficiency with its components of prolonged sleep latency, waking during the night and early awakenings.42 Since shift workers and day workers reported similar answers to the question about trouble sleeping because of “waking up in the middle of the night or early morning”, this suggests that sleep latency was the most important contributor to poor sleep efficiency. Our study also demonstrated that shift work was associated with poor overall sleep as measured by the PSQI global score, corresponding to results of other studies of shift workers.43–45 Similar to our findings, a study of female nurses in Taiwan found that working a rotational shift schedule was associated with poor overall sleep quality (OR=2.26; 95% CI 1.57 to 3.28 for a global PSQI score >5 compared with day workers).

    We systematically investigated whether three indicators of sleep quality acted as mediators in the relationship between shift work and the MetS, and we found no such evidence. From a methodological perspective, the measures of sleep used in our study could have lacked the precision needed to observe mediation if it exists. Our measurements did not allow us to identify when in the shift cycle a participant had difficulty falling asleep or inefficient sleep, and whether this persisted on days off. A Norwegian study of 1586 nurses provides insight into when sleep latency may be problematic during a shift cycle: among those working a three-shift system, difficulty initiating sleep was a problem for 28% after nights shifts, 12% after day shifts and 8% on days off.42 Similarly, our questionnaire may not have effectively captured short sleep length, a component that has been demonstrated as a risk factor for the development of CVD in the Nurses’ Health Study and in a meta-analysis.46 ,47 One study looking at sleep among nurses over three consecutive 12 h night shifts observed that short sleep (<6 h) occurred between night shifts, while longer sleep periods occurred before the first night shift, with some sleeping as long as 15 h.48 Since the PSQI questionnaire represents general sleep duration in the past month, it limits our ability to identify the variability of sleep length within a shift cycle. To address this, future studies utilising tools such as actigraphy devices will allow us to isolate the effect of poor sleep quality at various moments within one shift cycle.

    Alternatively, assuming that shift work is causally associated with the MetS, the lack of mediation observed suggests that there may be other factors contributing to this relationship such as stress (sociotemporal disruption, poor work–life balance), unhealthy lifestyle factors (poor dietary habits, increased smoking and alcohol consumption and lack of physical activity) and other markers of circadian disruption (ie, phase shifting of melatonin).9 In addition, the exact timing of sleep relative to the body's internal circadian rhythm may be an important contributing factor to increased risk of CVD observed in shift-working populations. Some experimental studies support that circadian misalignment, which can be described as inappropriate timing of physiological and behavioural processes,49 can be detrimental to cardiovascular health. Metabolic effects have been described in animal models50 and in humans51 ,52; for instance, one experimental study demonstrated that circadian misalignment of sleep and food consumption decreased leptin, increased mean arterial blood pressure and led to glucose responses that were typical of a prediabetic state in adults.51

    In terms of potential limitations of this study, selection bias is unlikely because we did not advertise ‘sleep quality’ in the recruitment process. There is potential for residual confounding as medications that affect sleep, such as benzodiazepines, antidepressants and antipsychotics, were not considered in this study.53 The cross-sectional nature of this study limits the assessment of temporality and therefore causality. Nonetheless, a temporal relationship is plausible, as it was longitudinally demonstrated by Åkerstedt et al54 that entering shift work (2-shift or 3-shift system) was associated with an increased risk of difficulties in falling asleep, and leaving shift work was associated with an increased probability of these difficulties being reduced. Finally, it is a strength that this study focuses on women since there are known sex differences in sleep disturbances.55

    An important strength of this study is the use of a mediation analysis. To the best of our knowledge, no study has explicitly tested the mediating effect of sleep quality in the relationship between shift work and cardiometabolic risk. Our findings further contribute to the body of knowledge about a forward and rapidly rotating shift schedule among working women. This may be a more optimal shift schedule in terms of health, as some research has found that changing from a backward and slowly rotating shift to a forward and rapidly rotating shift is beneficial for sleep length and sleep quality,56–60 improvements in levels of triglycerides, cholesterol, glucose and blood pressure.37 ,60

    If poor sleep quality is indeed a routine occurrence beyond the 30-day period examined in this study, this could have important adverse health effects on shift workers in the long term. The American Academy of Sleep Medicine has guidelines for the clinical management of shift-working patients presenting with sleep disturbances or those who have been diagnosed with shift work disorder.61 Medical surveillance of shift workers in the workplace can help detect early signs of severe sleep disturbances and, in turn, help diminish work accidents and absenteeism, which are both related to sleep disturbances in shift-working women.62–64

    A future direction is to perform this mediation analysis using measures of actigraphy to discriminate between those who have poor sleep quality precisely after a night shift. Finally, since the relationship between shift work and CVD is certainly multifactorial, other path analyses considering work stress, lifestyle behaviours, measures of circadian disruption and misalignment should be pursued. More investigations of the adverse sleep quality in well-defined shift systems will allow us to develop healthy shift scheduling policies.

    Acknowledgments

    The authors acknowledge Dr Ian Janssen, Dr L. McGillis Hall and Dr Christine Collier as co-investigators for the original study from which this project derives. They would also like to acknowledge C. Kelly and R. Corbin as research coordinators.

    References

    1. ↵
      1. Straif K,
      2. Baan R,
      3. Grosse Y, et al
      . Carcinogenicity of shift-work, painting, and fire-fighting. Lancet Oncol 2007;8:1065–6. doi:10.1016/S1470-2045(07)70373-X
      OpenUrlCrossRefPubMedWeb of Science
    2. ↵
      1. Williams C
      . Work-life balance of shift workers. Vol. 9. Statistics Canada, 2008.
    3. ↵
      Statistics Canada. 2006 Census of Population. Statistics Canada catalogue no. 97–564-XCB2006005. Date modified 2010-01-07. Date accessed: August 17 2013.
    4. ↵
      1. Wang X,
      2. Armstrong MEG,
      3. Cairns BJ, et al
      . Shift work and chronic disease: the epidemiological evidence. Occup Med (Lond) 2011;61:78–89. doi:10.1093/occmed/kqr001
      OpenUrlAbstract/FREE Full Text
    5. ↵
      1. Zhu JL,
      2. Hjollund NH,
      3. Andersen AN, et al
      . Shift work, job stress, and late fetal loss: The National Birth Cohort in Denmark. J Occup Environ Med 2004;46:1144–9. doi:10.1097/01.jom.0000145168.21614.21
      OpenUrlCrossRefPubMedWeb of Science
    6. ↵
      1. Nurminen T
      . Shift work and reproductive health. Scand J Work Environ Health 1998;24(Suppl 3):28–34.
      OpenUrlPubMedWeb of Science
    7. ↵
      1. Knutson K,
      2. Spiegel K,
      3. Penev P, et al
      . The metabolic consequences of sleep deprivation. Sleep Med Rev 2007;11:163–78. doi:10.1016/j.smrv.2007.01.002
      OpenUrlCrossRefPubMedWeb of Science
    8. ↵
      1. Vyas MV,
      2. Hackam DG,
      3. Garg AX, et al
      . Shift work and vascular events: systematic review and meta-analysis. BMJ 2012;345:e4800. doi:10.1136/bmj.e4800
      OpenUrlAbstract/FREE Full Text
    9. ↵
      1. Knutsson A,
      2. Boggild H
      . Shiftwork and cardiovascular disease: review of disease mechanisms. Rev Environ Health 2000;15:359–72. doi:10.1515/REVEH.2000.15.4.359
      OpenUrlPubMed
    10. ↵
      1. Puttonen S,
      2. Härmä M,
      3. Hublin C
      . Shift work and cardiovascular disease—pathways from circadian stress to morbidity. Scand J Work Environ Health 2010;36:96–108. doi:10.5271/sjweh.2894
      OpenUrlCrossRefPubMedWeb of Science
    11. ↵
      1. Morselli LL,
      2. Guyon A,
      3. Spiegel K
      . Sleep and metabolic function. Pflugers Arch 2012;463:139–60. doi:10.1007/s00424-011-1053-z
      OpenUrlCrossRefPubMed
    12. ↵
      1. Kawachi I,
      2. Colditz GA,
      3. Stampfer MJ, et al
      . Prospective study of shift work and risk of coronary heart disease in women. Circulation 1995;92:3178–82. doi:10.1161/01.CIR.92.11.3178
      OpenUrlAbstract/FREE Full Text
    13. ↵
      1. Brown DL,
      2. Feskanich D,
      3. Sánchez BN, et al
      . Rotating night shift work and the risk of ischemic stroke. Am J Epidemiol 2009;169:1370–7. doi:10.1093/aje/kwp056
      OpenUrlAbstract/FREE Full Text
    14. ↵
      1. Akerstedt T
      . Shift work and disturbed sleep/wakefulness. Sleep Med Rev 1998;2:117–28. doi:10.1016/S1087-0792(98)90004-1
      OpenUrlCrossRefPubMed
    15. ↵
      1. Härmä M,
      2. Tenkanen L,
      3. Sjöblom T, et al
      . Combined effects of shift work and life-style on the prevalence of insomnia, sleep deprivation and daytime sleepiness. Scand J Work Environ Health 1998;24:300–7. doi:10.5271/sjweh.324
      OpenUrlPubMedWeb of Science
    16. ↵
      1. Akerstedt T
      . Shift work and disturbed sleep/wakefulness. Occup Med (Lond) 2003;53:89–94. doi:10.1093/occmed/kqg046
      OpenUrlAbstract
    17. ↵
      1. Dettoni JL,
      2. Consolim-Colombo FM,
      3. Drager LF, et al
      . Cardiovascular effects of partial sleep deprivation in healthy volunteers. J Appl Physiol 2012;113:232–6. doi:10.1152/japplphysiol.01604.2011
      OpenUrlAbstract/FREE Full Text
    18. ↵
      1. Faraut B,
      2. Zouaoui Boudjeltia K,
      3. Vanhamme L, et al
      . Immune, inflammatory and cardiovascular consequences of sleep restriction and recovery. Sleep Med Rev 2012;16:137–49. doi:10.1016/j.smrv.2011.05.001
      OpenUrlCrossRefPubMedWeb of Science
    19. ↵
      1. Motivala SJ
      . Sleep and inflammation: psychoneuroimmunology in the context of cardiovascular disease. Ann Behav Med 2011;42:141–52. doi:10.1007/s12160-011-9280-2
      OpenUrlCrossRefPubMed
    20. ↵
      1. Suarez EC
      . Self-reported symptoms of sleep disturbance and inflammation, coagulation, insulin resistance and psychosocial distress: evidence for gender disparity. Brain Behav Immun 2008;22:960–8. doi:10.1016/j.bbi.2008.01.011
      OpenUrlCrossRefPubMedWeb of Science
    21. ↵
      1. Taheri S,
      2. Lin L,
      3. Austin D, et al
      . Short sleep duration is associated with reduced leptin, elevated ghrelin, and increased body mass index. PLoS Med 2004;1:e62–217. doi:10.1371/journal.pmed.0010062
      OpenUrlCrossRefPubMed
    22. ↵
      1. Spiegel K,
      2. Leproult R,
      3. Van Cauter E
      . Impact of sleep debt on metabolic and endocrine function. Lancet 1999;354:1435–9. doi:10.1016/S0140-6736(99)01376-8
      OpenUrlCrossRefPubMedWeb of Science
    23. ↵
      1. Stamatakis K
      . Effects of sleep fragmentation on glucose metabolism in normal subjects. Chest 2010;137:95–101. doi:10.1378/chest.09-0791
      OpenUrlCrossRefPubMedWeb of Science
    24. ↵
      1. Bøggild H
      . Settling the question—the next review on shift work and heart disease in 2019. Scand J Work Environ Health 2009;35:157–61. doi:10.5271/sjweh.1330
      OpenUrlPubMedWeb of Science
    25. ↵
      1. Hafeman DM,
      2. Schwartz S
      . Opening the Black Box: a motivation for the assessment of mediation. Int J Epidemiol 2009;38:838–45. doi:10.1093/ije/dyn372
      OpenUrlAbstract/FREE Full Text
    26. ↵
      1. Baron RM,
      2. Kenny DA
      . The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986;51:1173–82. doi:10.1037/0022-3514.51.6.1173
      OpenUrlCrossRefPubMedWeb of Science
    27. ↵
      1. Alberti KG,
      2. Eckel RH,
      3. Grundy SM, et al
      . Harmonizing the Metabolic Syndrome: A Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosis society; and International Association for the Study of Obesity. Circulation 2009;120:1640–5. doi:10.1161/CIRCULATIONAHA.109.192644
      OpenUrlAbstract/FREE Full Text
    28. ↵
      1. Mottillo S,
      2. Filion KB,
      3. Genest J, et al
      . The metabolic syndrome and cardiovascular risk. J Am Coll Cardiol 2010;56:1113–32. doi:10.1016/j.jacc.2010.05.034
      OpenUrlCrossRefPubMedWeb of Science
    29. ↵
      1. Jennings JR,
      2. Muldoon MF,
      3. Hall M, et al
      . Self-reported sleep quality is associated with the metabolic syndrome. Sleep 2007;30:219.
      OpenUrlPubMedWeb of Science
    30. ↵
      1. Hung H,
      2. Yang Y,
      3. Ou H, et al
      . The association between self-reported sleep quality and metabolic syndrome. PLoS ONE 2013;8:e54304. doi:10.1371/journal.pone.0054304
      OpenUrl
    31. ↵
      1. Esquirol Y,
      2. Bongard V,
      3. Mabile L, et al
      . Shift work and metabolic syndrome: respective impacts of job strain, physical activity, and dietary rhythms. Chronobiol Int 2009;26:544–49. doi:10.1080/07420520902821176
      OpenUrlCrossRefPubMedWeb of Science
    32. ↵
      1. Pietroiusti A,
      2. Neri A,
      3. Somma G, et al
      . Incidence of metabolic syndrome among night-shift healthcare workers. Occup Environ Med 2010;67:54–7. doi:10.1136/oem.2009.046797
      OpenUrlAbstract/FREE Full Text
    33. ↵
      1. De Bacquer D,
      2. Van Risseghem M,
      3. Clays E, et al
      . Rotating shift work and the metabolic syndrome: a prospective study. Int J Epidemiol 2009;38:848–0. doi:10.1093/ije/dyn360
      OpenUrlAbstract/FREE Full Text
    34. ↵
      1. Buysse DJ,
      2. Reynolds III CF,
      3. Monk TH, et al
      . The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res 1989;28:193–213. doi:10.1016/0165-1781(89)90047-4
      OpenUrlCrossRefPubMedWeb of Science
    35. ↵
      1. Rothman KJ,
      2. Greenland S,
      3. Lash TL
      . Modern epidemiology. 3rd edn. Philadelphia: Lippincott Williams & Wilkins, 2008.
    36. ↵
      1. Van Amelsvoort L,
      2. Jansen N,
      3. Kant I
      . Smoking among shift workers: more than a confounding factor. Chronobiol Int 2006;23:1105–13. doi:10.1080/07420520601089539
      OpenUrlCrossRefPubMedWeb of Science
    37. ↵
      1. Bøggild H,
      2. Jeppesen HJ
      . Intervention in shift scheduling and changes in biomarkers of heart disease in hospital wards. Scand J Work Environ Health 2001;27:87–96. doi:10.5271/sjweh.594
      OpenUrlPubMedWeb of Science
    38. ↵
      1. Carpenter JS,
      2. Andrykowski MA
      . Psychometric evaluation of the Pittsburgh Sleep Quality Index. J Psychosom Res 1997;45:5–13. doi:10.1016/S0022-3999(97)00298-5
      OpenUrlCrossRef
    39. ↵
      1. Admi H,
      2. Tzischinsky O,
      3. Epstein R, et al
      . Shift work in nursing: is it really a risk factor for nurses’ health and patients’ safety? Nurs Econ 2008;26:250.
      OpenUrlPubMed
    40. ↵
      1. Marquié JC,
      2. Foret J
      . Sleep, age, and shiftwork experience. J Sleep Res 1999;8:297–304. doi:10.1046/j.1365-2869.1999.00170.x
      OpenUrlCrossRefPubMedWeb of Science
    41. ↵
      American Academy of Sleep Medicine. The international classification of sleep disorders, revised: diagnostic and coding manual. Rochester, MN: American Sleep Disorders Association, 2001.
    42. ↵
      1. Flo E,
      2. Pallesen S,
      3. Åkerstedt T, et al
      . Shift-related sleep problems vary according to work schedule. Occup Environ Med 2013;70:238. doi:10.1136/oemed-2012-101091
      OpenUrlAbstract/FREE Full Text
    43. ↵
      1. De Martino MM,
      2. Abreu AC,
      3. Barbosa MF, et al
      . The relationship between shift work and sleep patterns in nurses. Cien Saude Colet 2013;18:763. doi:10.1590/S1413-81232013000300022
      OpenUrl
    44. ↵
      1. Lin P,
      2. Chen C,
      3. Pan S, et al
      . Atypical work schedules are associated with poor sleep quality and mental health in Taiwan female nurses. Int Arch Occup Environ Health 2012;85:877–84. doi:10.1007/s00420-011-0730-8
      OpenUrlPubMed
    45. ↵
      1. Shao M,
      2. Chou Y,
      3. Yeh M, et al
      . Sleep quality and quality of life in female shift-working nurses. J Adv Nurs 2010;66:1565–72. doi:10.1111/j.1365-2648.2010.05300.x
      OpenUrlCrossRefPubMed
    46. ↵
      1. Cappuccio FP,
      2. Cooper D,
      3. D'Elia L, et al
      . Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies. Eur Heart J 2011;32:1484–92. doi:10.1093/eurheartj/ehr007
      OpenUrlAbstract/FREE Full Text
    47. ↵
      1. Ayas NT,
      2. White DP,
      3. Manson JE, et al
      . A prospective study of sleep duration and coronary heart disease in women. Arch Intern Med 2003;163:205–9. doi:10.1001/archinte.163.2.205
      OpenUrlCrossRefPubMedWeb of Science
    48. ↵
      1. Geiger-Brown J,
      2. Trinkoff A,
      3. Rogers VE
      . The impact of work schedules, home, and work demands on self-reported sleep in registered nurses. J Occup Environ Med 2011;53:303. doi:10.1097/JOM.0b013e31820c3f87
      OpenUrlCrossRefPubMed
    49. ↵
      1. Markwald RR,
      2. Wright KP Jr.
      . Circadian misalignment and sleep disruption in shift work: implications for fatigue and risk of weight gain and obesity. In: Shiromani PJ, Horvath T, Redline S, et al. eds. Sleep Loss and Obesity. Intersecting epidemics 2012:101–18.
    50. ↵
      1. Laposky AD,
      2. Turek FW
      . Physiologic and health consequences of circadian disruption (in animal models). Sleep Medicine Clinics 2009;2:127–42. doi:10.1016/j.jsmc.2009.02.004
      OpenUrl
    51. ↵
      1. Scheer FA,
      2. Hilton MF,
      3. Mantzoros CS, et al
      . Adverse metabolic and cardiovascular consequences of circadian misalignment. Proc Natl Acad Sci USA 2009;106:4453–8. doi:10.1073/pnas.0808180106
      OpenUrlAbstract/FREE Full Text
    52. ↵
      1. Leproux R,
      2. Holmback U,
      3. Van Cauter E
      . Circadian misalignment augments markers of insulin resistance and inflammation, independently of sleep loss. Diabetes 2014;63:1860–9. doi:10.2337/db13-1546
      OpenUrlAbstract/FREE Full Text
    53. ↵
      1. Roux FJ,
      2. Kryger MH
      . Medication effects on sleep. Clin Chest Med 2010;31:397–405. doi:10.1016/j.ccm.2010.02.008
      OpenUrlCrossRefPubMedWeb of Science
    54. ↵
      1. Åkerstedt T,
      2. Nordin M,
      3. Alfredsson L, et al
      . Sleep and sleepiness: impact of entering or leaving shiftwork—a prospective study. Chronobiol Int 2010;27:987–96. doi:10.3109/07420528.2010.489423
      OpenUrlPubMed
    55. ↵
      1. Krishnan V,
      2. Collop NA
      . Gender differences in sleep disorders. Curr Opin Pulm Med 2006;12:383–9. doi:10.1097/01.mcp.0000245705.69440.6a
      OpenUrlPubMed
    56. ↵
      1. Härmä M,
      2. Tarja H,
      3. Irja K, et al
      . A controlled intervention study on the effects of a very rapidly forward rotating shift system on sleep–wakefulness and well-being among young and elderly shift workers. Int J of Psychophysiol 2006;59:70–9. doi:10.1016/j.ijpsycho.2005.08.005
      OpenUrlCrossRefPubMedWeb of Science
    57. ↵
      1. Hakola T,
      2. Härmä M
      . Evaluation of a fast forward rotating shift schedule in the steel industry with a special focus on ageing and sleep. J Hum Ergol 2001;30:315.
      OpenUrl
    58. ↵
      1. Hakola T,
      2. Paukkonen M,
      3. Pohjenen T
      . Less quick returns—greater well-being. Ind Health 2010;48:390–4. doi:10.2486/indhealth.MSSW-02
      OpenUrlCrossRefPubMedWeb of Science
    59. ↵
      1. Sallinen M,
      2. Kecklund G
      . Shift work, sleep, and sleepiness—differences between shift schedules and systems. Scand J Work Environ Health 2010;36:121–33. doi:10.5271/sjweh.2900
      OpenUrlCrossRefPubMedWeb of Science
    60. ↵
      1. Orth-Gomér K
      . Intervention on coronary risk factors by adapting a shift work schedule to biologic rhythmicity. Psychosom Med 1983;45:407. doi:10.1097/00006842-198310000-00004
      OpenUrlAbstract/FREE Full Text
    61. ↵
      1. Roth T
      . Appropriate therapeutic selection for patients with shift work disorder. Sleep Med 2012;13:335. doi:10.1016/j.sleep.2011.11.006
      OpenUrlPubMed
    62. ↵
      1. Wong IS,
      2. McLeod CB,
      3. Demers PA
      . Shift work trends and risk of work injury among Canadian workers. Scand J Work Environ Health 2011;37:54. doi:10.5271/sjweh.3124
      OpenUrlCrossRefPubMedWeb of Science
    63. ↵
      1. Costa G
      . Guidelines for the medical surveillance of shift workers. Scand J Work Environ Health 1998;24(Suppl 3):151.
      OpenUrlPubMed
    64. ↵
      1. Drake CL,
      2. Roehrs T,
      3. Richardson G, et al
      . Shift work sleep disorder: prevalence and consequences beyond that of symptomatic day workers. Sleep 2004;27:1453.
      OpenUrlPubMedWeb of Science

    Footnotes

    • Contributors All of the authors have agreed to the content of this manuscript. The conceptual design of this project including all statistical analyses and manuscript writing was completed by PL with the feedback and critical revisions of JT and KJA and with important feedback from AD, specifically in terms of statistical analyses.

    • Funding The Canadian Institutes of Health Research and the Workplace Safety and Insurance Board (Ontario) are thanked for funding.

    • Competing interests None.

    • Ethics approval Queen’s University Health Sciences Research Ethics Board.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement No additional data are available.