Pattern of shiftwork and health status among nurses in a university hospital in northeastern Thailand

The purpose of this study was to examine the circadian temperature rhythm in clockwise (CW) and counter-clockwise (CCW) rapidly rotating shift schedules. Arguments against the CCW rotation of shifts are that they result in shortened sleep and promote greater disruption of circadian rhythms. The 3-week study included a week of day shifts (0800-1600) and 2 weeks of shiftwork. The CW 2-2-1 schedule rotated from two early mornings (0600-1400) to two evenings (1400-2200) to one midnight shift (2200-0600) allowing 24 hours off at each shift rotation and a 48-hour weekend. The CCW schedule rotated from two evenings to two early mornings to one midnight shifts allowing only 8 hours off at each shift rotation and an 80-hour weekend. Analysis of the 72-hr periods at the end of each workweek, including the midnight shifts and recovery periods during weeks 2 and 3 were compared to the same 72-hour period at the end of week 1 (baseline). A cosine function that fit the temperature curves by minimizing the sums of squares produced parameters that underwent analysis of covariance procedures. Significant differences were found between rotation conditions for amplitude and acrophase. An attenuation of amplitude and a delay in the acrophase was the found for the counter-clockwise condition. Features inherent in this schedule might explain these effects, particularly, the increased opportunity for "sleeping in" at the beginning of the week and an expanded (2-shift) workday at the end of the week.

We investigated the difference in sleep inertia between shift workers (SWs) and non-shift workers (NSWs) and the effects of depressive symptoms, sleepiness, insomnia, and chronotype on sleep inertia in SWs and NSWs. Altogether, 4,561 SWs (2,142 men and 2,419 women, aged 36.99±9.84 years) and 2,093 NSWs (999 men and 1,094 women, aged 37.80±9.73 years) participated in the current study. All participants completed the Sleep Inertia Questionnaire (SIQ), Epidemiological Studies Depression Scale (CESD), Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), and Morningness-Eveningness Questionnaire (MEQ) through an online survey. SWs reported higher SIQ scores than NSWs after controlling for CESD, ESS, ISI, or MEQ. The CESD, ESS, ISI, and MEQ predicted SIQ in both SWs and NSWs. The effects of CESD and MEQ on SIQ were stronger in SWs and NSWs, respectively. The indirect effects of CESD and MEQ on SIQ via ESS were significantly moderated by work schedules. SWs showed higher sleep inertia than NSWs. The effect of chronotypes on sleep inertia was more prominent in NSWs than in SWs. However, the effect of depressive symptoms on sleep inertia was more prominent in SWs than in NSWs. Moreover, the effect of depressive symptoms or chronotypes on sleep inertia was mediated by sleepiness, and such indirect effects were significantly different among the participants stratified by work schedules.

Insomnia is a commonly occurring sleep problem in shift workers. So far, no studies have investigated how insomnia symptoms present differently in shift workers and non-shift workers. The purpose of this study was to compare the network structures and centrality indices of shift and non-shift workers using network analysis and network comparison test. Participants included 1339 hospital employees, where 542 were shift workers and 797 were non-shift workers. Overall, a significant difference between network structures were observed. In particular, daytime dysfunction emerged as a strongly connected symptom in shift workers, as evidenced by strength centrality. Increased use of sleeping medication and decreased habitual sleep efficiency were more strongly associated with increased daytime dysfunction in shift workers. Sleep latency and sleep quality were also more strongly linked in shift workers. These results are in part attributable to differing causes of insomnia in shift and non-shift workers. Furthermore, the results indicate that shift workers are more vulnerable and susceptible to changes in sleep-related indices, such as sleep efficiency and latency. The findings suggest that certain insomnia symptoms are more consequential in shift workers, emphasizing the need for a differentiated approach in treating insomnia according to shift work.

Objective:Higher BMI, lower quality of diet and a higher percentage of breakfast-skippers have been reported among rotating shift (RS) workers compared with day shift (DS) workers. As such, this study examined the association between breakfast skipping, habitual food consumption and BMI in RS workers.Design:Japanese nurses were studied using a self-administered questionnaire that assessed the height, weight, breakfast consumption habits, dietary consumption, physical activity, sleep habits, chronotype and demographic characteristics of the participants.Setting:A cross-sectional study was conducted in a population of nurses in Japan. Dietary and health-related questionnaires were mailed to 5536 nurses aged 20–59 years, working at 346 institutions.Participants:A total of 3646 nurses at 274 institutions responded to the questionnaire. After removing those who met the exclusion criteria, 2450 participants were included in the statistical analysis.Results:The RS breakfast-skippers had lower total energy intake, diet quality and higher BMI than DS workers, whereas the RS breakfast-consumers had a higher total energy intake and BMI than the DS workers. In the RS workers, breakfast skipping on the days of DS and the end days of evening/night shift was associated with a poorer diet quality. Additionally, breakfast skipping on the days of DS was positively associated with BMI, independent of the total energy intake and diet quality.Conclusions:Breakfast skipping on workdays may contribute to a difference in dietary intake and BMI between RS workers and DS workers and may increase BMI in RS workers, independent of dietary intake.

Objectives Shift work may alter workers' leisure-time and occupational physical activity (PA) levels, which might be one of the potential underlying mechanisms of the negative health effects of shift work. Therefore, we compared objectively measured PA levels between hospital shift and non-shift workers. Methods Data were used from Klokwerk+, a cohort study examining the health effects of shift work among healthcare workers employed in hospitals. In total, 401 shift workers and 78 non-shift workers were included, all of whom wore Actigraph GT3X accelerometers for up to seven days. Time spent sedentary, standing, walking, running, stairclimbing, and cycling during leisure time and at work was estimated using Acti4 software. Linear regression was used to compare proportions of time spent in these activities between hospital shift and non-shift workers. Results Average accelerometer wear-time was 105.9 [standard deviation (SD) 14.0] waking hours over an average of 6.9 (SD 0.6) days. No differences between hospital shift and non-shift workers were found in leisure-time PA (P>0.05). At work, shift workers were less sedentary [B=-10.6% (95% CI -14.3- -6.8)] and spent larger proportions of time standing [B=9.5% (95% CI 6.4-12.6)] and walking [B=1.2% (95% CI 0.1-2.2)] than non-shift workers. However, these differences in occupational PA became smaller when the number of night shifts during accelerometer wear-time increased. Conclusions Leisure-time PA levels of hospital shift workers were similar to those of non-shift workers, but shift workers were less sedentary and more physically active (ie, standing/walking) at work. Future research to the role of occupational activities in the health effects of shift work is recommended.

Physical activity and sedentary behaviour in shift and non-shift workers: A systematic review and meta-analysis

IntroductionShift work is known to reduce productivity and safety at work. Previous studies have suggested that a variety of interrelated factors, such as mood, cognition, and sleep, can affect the performance of shift workers. This study aimed to identify potential pathways from depression, sleep, and cognition to work performance in shift and non-shift workers.Material and methodsOnline survey including the Center for Epidemiologic Studies Depression Scale (CES-D), Cognitive Failure Questionnaire (CFQ), and Pittsburgh Sleep Quality Index (PSQI), as well as two items representing work mistakes were administered to 4,561 shift workers and 2,093 non-shift workers. A multi-group structural equation model (SEM) was used to explore differences in the paths to work mistakes between shift and non-shift workers.ResultsShift workers had higher PSQI, CES-D, and CFQ scores, and made more mistakes at work than non-shift workers. The SEM revealed that PSQI, CES-D, and CFQ scores were significantly related to mistakes at work, with the CFQ being a mediating variable. There were significant differences in the path coefficients of the PSQI and CES-D between shift and non-shift workers. The direct effects of sleep disturbances on mistakes at work were greater in shift workers, while direct effects of depressive symptoms were found only in non-shift workers.DiscussionThe present study found that shift workers made more mistakes at work than non-shift workers, probably because of depressed mood, poor sleep quality, and cognitive inefficiency. Sleep influences work performance in shift workers more directly compared to non-shift workers.

When and what you eat can be linked to circadian preference (i.e., chronotype) and occupation (e.g., shift worker). Evening chronotypes, with a later circadian preference, tend to have meals later, distribute energy intake toward the end of the day(1), and more unhealthy eating habits than morning chronotypes(2); whereas night shift work is associated with later mealtimes and poor diet quality as a result of circadian disruption due to their work(3). What is unclear is whether chronotype influences the occupation-induced dietary patterns observed in shift workers. This study aimed to investigate associations between chronotype, temporal patterns of eating and diet composition in shift and non-shift workers. Adults from shift (SW) and non-shift (N-SW) populations were recruited. A Chrononutrition Questionnaire captured chronotype, duration of eating window (DEW), time of first eating occasion (FEO) and last eating occasion (LEO) while diet composition (energy, protein, total fat, saturated fat, carbohydrate, fibre, alcohol) was extracted from 7-day food diaries. Associations between chronotype and DEW/FEO/LEO, and between DEW/FEO/LEO and diet composition were determined by Spearman Rank Coefficients. 95 participants were enrolled (N-SW: n = 39; SW: n = 56); predominantly female (71%), morning chronotype (37%), on average 40.46 ± 15.08 years with BMI of 27.04 ± 5.77kg/m2. 84 returned food diaries. Later chronotype was positively associated with later times of FEO (N-SW: r = ,50, SW: r = ,69) and LEO (N-SW: r = ,63, SW: r = ,54) on free (non-work) days (p≤.002), and longer DEW (r = ,42) and later LEO (r = ,60) on workdays for non-shift workers (p<.01). However, there were no significant differences in diet composition by day/shift type between chronotypes across the study population. On afternoon shifts, longer DEW was associated with greater energy (r = ,60) and total fat intake (r = ,60) and later LEO with greater alcohol intake (r = ,59) (p<.05). On night shifts, a longer DEW was associated with lower alcohol intake (r=-.45, p<.05). Amongst non-shift workers, later FEO was associated with lower fibre intake on workdays (r=-.58, p<.001). Additionally, non-shift workers who were later chronotypes had later LEO, which on workdays associated with lower fibre (r=-.45) and alcohol intake (r=-.43); and on work-free days, associated with lower alcohol intake (r=-.45) (p<.05). Not surprisingly, evening chronotypes across the study population had longer and/or later eating windows on work-free days (i.e., free of constraints), as did non-shift workers on workdays, while the influence of chronotype on DEW, FEO, and LEO across shifts were less clear. Hence, for shift workers, occupation appeared to be a greater driver of temporal eating patterns than chronotype. Additionally, later eating times of evening chronotypes was not associated with negative diet composition. The exception was lower fibre intake amongst non-shift workers; but regardless of chronotype, shift workers may benefit from having a shorter and earlier DEW on afternoon shifts to minimise energy, fat, and alcohol intake.

Effects of sleep and impulsivity on suicidality in shift and non-shift workers

BackgroundShift work is known to cause changes in the circadian rhythm of the human body and adversely affect not only physical health but also mental health. Some studies have demonstrated the correlation between shift work and thyroid stimulating hormone (TSH), a hormone that changes according to the diurnal rhythm, but few studies have reported the different TSH levels according to the shift work type. This study aimed to investigate changes in TSH according to the shift work type.MethodsThis study included 1,318 female workers who had a medical checkup at a university hospital in Changwon from 2015 to 2019. Shift work types were classified as non-shift work, regular 2 shifts, and irregular three shifts, and a TSH ≥ 4.2 mIU/L was defined as abnormal. A general linear model (GLM) was used to compare the TSH levels and the risk of subclinical hypothyroidism in each year, and a binary logistic analysis was performed using a generalized estimation equation (GEE) to compare the risk of subclinical hypothyroidism over the 5-year period.ResultsOf the 1,318 participants included in this study, 363, 711, and 244 were non-shift, two-shift, and irregular three-shift workers, respectively. In the GEE analysis, after adjusting for age, body mass index, smoking, and alcohol consumption, the odds ratios (ORs) were 1.81 (95% confidence interval [CI]: 1.15–2.86; p = 0.011) in 2 shifts and 2.02 (95% CI: 1.23–3.32; p = 0.006) in irregular three shifts, compared to non-shift.ConclusionsOur results showed that shift work had a higher risk of subclinical hypothyroidism than non-shift work and that there was a significant difference in the risk of subclinical hypothyroidism according to the shift work type. These findings suggest that the shift work type can be considered in future thyroid function tests and evaluations.

Fatigue and somatization in shift-workers: Effects of depression and sleep

The aim of this study was to compare chronotype- and age-dependent sleep disturbances and social jetlag between rotating shift workers and non-shift workers, and between different types of shifts. In the Klokwerk+ cohort study, we included 120 rotating shift workers and 74 non-shift workers who were recruited from six Dutch hospitals. Participants wore Actigraph GT3X accelerometers for 24 hr for 7 days. From the Actigraph data, we predicted the sleep duration and social jetlag (measure of circadian misalignment). Mixed models and generalized estimation equations were used to compare the sleep parameters between shift and non-shift workers. Within shift workers, sleep on different shifts was compared with sleep on work-free days. Differences by chronotype and age were investigated using interaction terms. On workdays, shift workers had 3.5 times (95% confidence interval: 2.2-5.4) more often a short (< 7 hr per day) and 4.1 times (95% confidence interval: 2.5-6.8) more often a long (≥ 9 hr per day) sleep duration compared with non-shift workers. This increased odds ratio was present in morning chronotypes, but not in evening chronotypes (interaction p-value < .05). Older shift workers (≥ 50 years) had 7.3 times (95% confidence interval: 2.5-21.8) more often shorter sleep duration between night shifts compared with work-free days, while this was not the case in younger shift workers (< 50 years). Social jetlag due to night shifts increased with increasing age (interaction p-value < .05), but did not differ by chronotype (interaction p-value ≥ .05). In conclusion, shift workers, in particular older workers and morning chronotypes, experienced more sleep disturbances than non-shift workers. Future research should elucidate whether these sleep disturbances contribute to shift work-related health problems.

Introduction Both shift work and restless leg syndrome (RLS) are common and can disrupt sleep and mood. However, the effects of shift work on RLS remain unclear. The current study aims to explore the prevalence, severity, and related sleep and mood symptoms of RLS in shift workers (SWs) compared to non-shift workers (NSWs). Methods This study recruited 4,562 SWs (age 36.98±9.84, 2,150 males and 2,422 females) and 2,093 NSWs (age 37.79±9.73, 999 males and 1,094 females). All participants completed online self-report questionnaires regarding RLS, sleep, and depression. The presence of RLS was screened using a single standard question for rapid screening of RLS. The severity of RLS was assessed using the International Restless Legs Syndrome Rating Scale (iRLS). Additionally, the Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), and short-term Center for Epidemiologic Studies Depression Scale (CES-D) were used to assess daytime sleepiness, insomnia, and depressive symptoms, respectively. Results Of participants, 1,255 (27.45%) of SWs and 548 (26.18%) of NSWs were screened as having RLS, with no significant differences in the prevalence of RLS between the groups. However, among those with RLS, SWs with RLS showed higher iRLS scores compared to NSWs with RLS after controlling for age and sex (SWs: 9.55±7.26, NSWs: 6.75±6.05, F=64.15, p&amp;lt; 0.01). In addition, SWs with RLS exhibited higher ISI scores (SWs: 11.81±6.27, NSWs: 9.54±5.95, F=46.09, p&amp;lt; 0.01), higher ESS scores (SWs: 8.77±4.06, NSWs: 8.22±3.94, F=4.80, p=0.03), and higher CES-D scores (SWs: 10.43±6.54, NSWs: 8.38±6.15, F=33.50, p&amp;lt; 0.01) than NSWs with RLS. Conclusion Although there was no significant difference in RLS prevalence between SWs and NSWs, SWs with RLS exhibited more severe RLS symptoms and RLS-related symptoms, such as insomnia, sleepiness, and depression, compared to NSWs with RLS. The current study suggests that shift work may exacerbate RLS severity and RLS-related sleep and mood symptoms, although it may not be associated with the onset of RLS. Support (if any) This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)(RS-2024-00457381) and Culture, Sports and Tourism R&amp;D Program through the Korea Creative Content Agency grant funded by the Ministry of Culture, Sports and Tourism (RS-2024-00344893)

BackgroundPrevious studies assessing shift workers’ behaviours have mainly used self-report recall questionnaires, however these measures don’t always account for variations in work schedules. Alternative methods that allow for real-time assessments tailored to capture variations in work patterns might provide more accurate measures of physical activity (PA) and sedentary behaviour (SB). Therefore, the aim of this study was to evaluate the feasibility of Ecological Momentary Assessment (EMA), which provides real-time evaluations of PA and SB in shift workers. A secondary aim was to compare shift workers and non-shift worker responses.MethodsParticipants (n = 120; 58% female, mean Mage=36.0), included 69 shift workers and 51 non-shift workers. After downloading the EMA app, shift workers received either interval-contingent tailored (SW-T) or standardized EMA prompts (SW-S) over 7–10 days, while non-shift workers received standardized prompts (NSW-S) for seven days. Prompts were scheduled five times daily, every three hours. The EMA survey asked participants to report their current activity, including type, duration, and location of physical activity and sitting. Feasibility was assessed by analysing recruitment, retention, and compliance rates (EMA surveys completed) across SW-T, SW-S, and NSW-S groups.ResultsApproximately 78% of invited workers enrolled, and all enrolled workers completed at least one prompt on 4 out 7 days in the NSW-S and 7 out of 10 days in the SW group. Workers who chose not to participate reported unwillingness to travel for meetings (n = 14), while others did not respond (n = 20). Participants completed an average of 24 surveys per day, each one taking less than 30 s to complete. Overall, 64% of EMA surveys were started and completed. SW-S completed the least prompts (57%), while SW-T and NSW-S completed 64% and 68%, respectively (p = 0.90). On average, workers missed 36% EMA surveys which was similar for SW and NSW (p = 0.05).ConclusionOur study represents one of the few studies that has used EMA in the shift work population with adaptation to shift schedules. The findings showed a modest compliance to EMA. Strategies are needed to enhance compliance rates. However, EMA shows promise for capturing real-time behaviours in shift workers’ natural work environments.

BackgroundShift work has been related to adverse health outcomes that can partially be attributed to physical inactivity. However, our knowledge of the influence of shift work on physical activity and sedentary behavior is inconclusive. Therefore, this study aimed to assess physical activity levels among shift and non-shift workers among a sample of Iranian adults.MethodsBaseline data of the Ravansar Non-Communicable Disease (RaNCD) cohort study were used. All participants of RaNCD except those excluded due to unemployment or considerable disability were included in the study. We evaluated participants’ physical activity levels using the PERSIAN cohort questionnaire and examined its associations with being a shift worker.ResultsA total of 4695 participants with a mean age of 46.1 (SD = 7.74) were included in the study. In total, 1108 (23.6%) participants were shift workers, 1420 (30.2%) had insufficient physical activity levels, and 4283 (91.2%) were male. The prevalence of physical inactivity was significantly lower among shift workers compared to non-shift workers (21% vs. 33.1%, p < 0.001). Multiple backward stepwise binary logistic regression tests indicated that being a shift worker was significantly associated with a lower chance of having insufficient physical activity levels (OR = 0.77, 95% CI = 0.65–0.92, p = 0.003).ConclusionsThe prevalence of insufficient physical activity was higher among non-shift workers than shift workers in our study. By providing the factors associated with insufficient physical activity among the workers in a region of Iran, the current study findings might help policymakers target groups at higher risk of physical activity in Iran and design interventions to improve physical activity, especially among non-shift workers.