Circadian misalignment increases mood vulnerability in simulated shift work

The aim of this study was to investigate the effects of 4 consecutive simulated night shifts on glucose homeostasis, mitochondrial function and central and peripheral rhythmicities compared with a simulated day shift schedule. Seventeen healthy adults (8M:9F) matched for sleep, physical activity and dietary/fat intake participated in this study (night shift work n=9; day shift work n=8). Glucose tolerance and insulin sensitivity before and after 4 nights of shift work were measured by an intravenous glucose tolerance test and a hyperinsulinaemic euglycaemic clamp respectively. Muscles biopsies were obtained to determine insulin signalling and mitochondrial function. Central and peripheral rhythmicities were assessed by measuring salivary melatonin and expression of circadian genes from hair samples respectively. Fasting plasma glucose increased (4.4±0.1 vs. 4.6±0.1mmolL-1 ; P=.001) and insulin sensitivity decreased (25±7%, P<.05) following the night shift, with no changes following the day shift. Night shift work had no effect on skeletal muscle protein expression (PGC1α, UCP3, TFAM and mitochondria Complex II-V) or insulin-stimulated pAkt Ser473, pTBC1D4Ser318 and pTBC1D4Thr642. Importantly, the metabolic changes after simulated night shifts occurred despite no changes in the timing of melatonin rhythmicity or hair follicle cell clock gene expression across the wake period (Per3, Per1, Nr1d1 and Nr1d2). Only 4 days of simulated night shift work in healthy adults is sufficient to reduce insulin sensitivity which would be expected to increase the risk of T2D.

In Australia, approximately 20% of motor vehicle collisions result from fatigue or sleepiness-related driving, making it one of the most common causes of preventable motor vehicle crashes (MVC). The shift working population is found to be overrepresented in sleepiness-related vehicle crashes due to the effect of circadian misalignment and sleep loss, resulting in excessive sleepiness and neurobehavioural performance decline during waking hours. It is therefore essential that effective countermeasures to the deleterious effects of shift work are developed. A significant barrier to the development of effective countermeasures is the lack of real-time and practical measures of alertness. A number of methods have been developed to objectively assess sleepiness or alertness levels while driving, including infrared oculography. This method utilises eye blink characteristics to quantify physiological sleepiness, as eye blinks associated with the onset of sleep display unique properties that reflect sleep- and wake-related CNS changes. Oculometrics have also shown potential in assessing sleepiness that is associated with attentional performance impairment. The dissertation examined, i) the utility of oculometrics as objective indicators of sleepiness in relation to validated measures of performance, vigilance, and subjective sleepiness, in healthy male volunteers under a highly controlled laboratory environment; ii) the response of ocular measures of sleepiness and attentional performance in night shift workers who were exposed to a simulated laboratory night shift during their circadian day, compared to those tested in their circadian night; and iii) the association between oculometrics and unsafe driving events during commutes to and from night shift work. The first study demonstrated the influence of homeostatic and circadian variation on oculometrics with sleep deprivation. The temporal dynamics of oculometrics were strongly phase-locked with validated measures of performance, vigilance, and subjective sleepiness, and established their potential to detect sleepiness-related attentional lapses. The second study in this dissertation showed the utility of oculometrics to measure sleepiness that is associated with circadian misalignment in night shift workers. The study found that shift workers who did not biologically adapt to the night shift displayed higher levels of sleepiness as measured by oculometrics, as well as increases in objective vigilance (EEG delta power frequency band), subjective sleepiness, and neurobehavioural performance, compared to those who showed biological adaptation. The study is the first to demonstrate the sleepiness-related ocular responses to circadian misalignment in shift work. Lastly, the final study in the dissertation demonstrated the potential of oculometrics to detect sleepiness-related driving performance impairment following night shift work. The study found that ocular measures of sleepiness were associated with increased risks of adverse (hazardous, inattentive, and sleep-related) driving events in shift workers commuting to and from night shift work. With the demand for a 24 hour society comes the likely increase in adverse occupational health and safety outcomes. This dissertation has demonstrated the accuracy and potential utility of oculometrics (specifically JDS, PosAVR, BTD, %TEC) to assess sleepiness in healthy participants, and the shift working population. It has further demonstrated the application of oculometrics in identifying performance impairment as a result of sleepiness and circadian misalignment. The dissertation presents the scientific basis for the future utilisation of oculometrics in field in the prevention of sleepiness-related MVCs, and as a measure in intervention trials, particularly in the high-risk shift working population.

Introduction: Shift work is associated with increased incidence of obesity and other features of the metabolic syndrome. Health problems in shift workers are caused by several factors, one of these factors is the stress hormone cortisol. Aim of the work: to assess the association between night shift work and the changes in body mass index (BMI), fasting blood glucose, lipid (total cholesterol, HDL, and triglycerides) levels, cortisol hormone secretion, uric acid blood level and salivary cortisol level. Materials & Methods: this study was conducted on 160 male security personnel, their age ranging from 35 to 40 years in Cairo . Regarding the work schedule 80 subjects worked daytime for 8 hours, whereas 80 individuals worked only night shift for 12 hour with one day off, for at least continuous 5 years. Results: the results showed no significant difference between night shift and day workers as regard age and working years. As regard body mass index (BMI) there was highly significant difference (<0.001) between night and day workers. There was no significant difference between night and day shift workers as regard total cholesterol level, triglycerides, and fasting blood glucose (P< 0.05) where as there is a significant difference between night and day shift workers as regard HDL –cholesterol (P<0.05) and a highly significant difference between night and day shift workers as regard uric acid blood level (P<0.001).A significant difference was detected in salivary cortisol levels among night shift workers where the salivary cortisol level is higher in the evening than in the morning, also there is a significant difference in salivary cortisol level among day shift workers where the salivary cortisol level is higher in the morning than in the evening (P<0.05). Conclusion: Our results suggest an association between long-term shift work and increased body mass index, elevation cortisol level, HDL–cholesterol, fasting blood glucose and uric acid level. Further studies are needed to understand the biological mechanisms involved and the complex behavioral and social adaptations experienced by night-shift workers. Regular screening health programs should be done to maintain the health of shift workers.

Millions of people worldwide work during the night, resulting in disturbed circadian rhythms and sleep loss. This may cause deficits in cognitive functions, impaired alertness and increased risk of errors and accidents. Disturbed circadian rhythmicity resulting from night shift work could impair brain function and cognition through disrupted synthesis of proteins involved in synaptic plasticity and neuronal function. Recently, the circadian transcription factor brain-and-muscle arnt-like protein 1 (BMAL1) has been identified as a promoter of mRNA translation initiation, the most highly regulated step in protein synthesis, through binding to the mRNA “cap”. In this study we investigated the effects of simulated shift work on protein synthesis markers. Male rats (n = 40) were exposed to forced activity, either in their rest phase (simulated night shift work) or in their active phase (simulated day shift work) for 3 days. Following the third work shift, experimental animals and time-matched undisturbed controls were euthanized (rest work at ZT12; active work at ZT0). Tissue lysates from two brain regions (prefrontal cortex, PFC and hippocampus) implicated in cognition and sleep loss, were analyzed with m7GTP (cap) pull-down to examine time-of-day variation and effects of simulated shift work on cap-bound protein translation. The results show time-of-day variation of protein synthesis markers in PFC, with increased protein synthesis at ZT12. In the hippocampus there was little difference between ZT0 and ZT12. Active phase work did not induce statistically significant changes in protein synthesis markers at ZT0 compared to time-matched undisturbed controls. Rest work, however, resulted in distinct brain-region specific changes of protein synthesis markers compared to time-matched controls at ZT12. While no changes were observed in the hippocampus, phosphorylation of cap-bound BMAL1 and its regulator S6 kinase beta-1 (S6K1) was significantly reduced in the PFC, together with significant reduction in the synaptic plasticity associated protein activity-regulatedcytoskeleton-associated protein (Arc). Our results indicate considerable time-of-day and brain-region specific variation in cap-dependent translation initiation. We concludethat simulated night shift work in rats disrupts the pathways regulating the circadian component of the translation of mRNA in the PFC, and that this may partly explain impaired waking function during night shift work.

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&lt;.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&lt;.05). On night shifts, a longer DEW was associated with lower alcohol intake (r=-.45, p&lt;.05). Amongst non-shift workers, later FEO was associated with lower fibre intake on workdays (r=-.58, p&lt;.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&lt;.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.

Night shift schedule alters endogenous regulation of circulating cytokines

Introduction Circadian misalignment is commonly cited as a culprit of daytime sleep disturbances in night shift workers; however, the specific impact and magnitude that circadian misalignment has on daytime sleep has not been well-characterized in larger samples of night shift workers. Methods Participants included fixed-night shift workers (n=52, ages 18–50) who completed an 8-hour daytime polysomnography (PSG) in the lab following a night shift. Measures of sleep disturbances included: difficulty falling asleep (sleep onset latency [SOL], latency to persistent sleep [LPS]), difficulty staying asleep (sleep efficiency [SE], wake after sleep onset [WASO]), and sleep duration (total sleep time [TST]). Melatonin samples were collected hourly for 24 hours under dim light (&amp;lt;10 lux) and used to determine dim light melatonin offset (DLMOff). Circadian misalignment (CM) was calculated as the time difference between bedtime and DLMOff (higher values represented sleeping after DLMOff), and correlated with PSG sleep variables. Results CM was significantly associated with difficulty staying asleep (WASO: r=0.48, p&amp;lt;0.001; SE: r=-0.45, p&amp;lt;0.001), and sleep duration (TST: r=-0.38, p&amp;lt;0.01). Specifically, every 3 hours of CM on average added 19.2 minutes of WASO and reduced TST by 15 minutes. In contrast, CM was not significantly correlated with sleep onset difficulties (SOL: r=-0.27; LPS: r=-0.02). Conclusion These data suggest that circadian misalignment in shift workers may be a better predictor of difficulties staying asleep and sleep duration during the day relative to difficulties falling asleep. Because longer work hours (10–12 hours) are common in night shift worker, it may be that sleep initiation difficulties associated with circadian misalignment is masked by elevated fatigue or an increased homeostatic drive from prolonged wakefulness. These results may help guide decisions about the magnitude of phase shifts required (e.g., with light therapy) for the desired improvement in daytime sleep. Support Support for this study was provided to PC by the NHLBI (K23HL138166)

<h3>Objective</h3> Alternating around-the-clock work schedules disrupt the natural circadian rhythms, resulting in circadian misalignment that increases risks for metabolic and cardiovascular diseases. How night shift work affects glycemic profiles in real-world settings remains to be settled. We hypothesized that working during the night impairs glucose levels among female hospital employees compared to shift work during the day. <h3>Material and Methods</h3> The study employs an observational design in which a subgroup of the 1001 nights-cohort in Denmark of 57 female hospital employees without known diabetes were found eligible to register working hours, sleep, and food intake in diaries while wearing a Continuous Glucose Monitor (CGM, Dexcom) for seven days. A night shift was defined as working 8 hours from 23:00 to 07:00, and a day shift as working 8 hours from 07:00 to 15:00. A ‘night off’ and a ‘day off’ were defined as not working during these intervals. The study included 39 participants, each having (1) at least one night shift and off night and/or (2) at least one day shift and off day. Thirty-five participants had both. Daily mean and standard error of glucose levels at night and day shifts and at off nights and days were calculated. <h3>Results</h3> Participants completed a total of 76 night shifts and 276 nights off, along with 72 day shifts and 246 days off. The mean glucose levels were 116.0 (SEM 1.9) mg/dL during night shifts, 113.2 (SEM 0.9) mg/dL during nights off, 111.7 (SEM 1.6) mg/dL during day shifts, and 111.7 (SEM 1.0) mg/dL during days off. <h3>Conclusion</h3> Shift work may modestly increase mean glucose levels at night but not at daytime. Results of other CGM-derived outcome variables and ongoing statistical variance component modeling using the within-person design will be presented at the conference. <h3>Funding</h3> The Danish Working Environment Research Fund (26202009; 19202209), The Health Foundation (22B0452), the European Union’s Horizon (# 874703), NFA, and The Danish Cardiovascular Academy.

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.

Misalignment of the daily sleep-wake and fasting-feeding cycles with the endogenous circadian timing system is an inevitable consequence of night shift work and is associated with adverse metabolic health effects. However, a detailed characterisation of the effects of night shifts on 24-h rhythms in the metabolome is missing. We performed targeted metabolomic profiling on plasma samples collected every 2 h from healthy human subjects during two 24-h measurement periods at baseline and on the fourth day of a simulated night shift protocol, in which the habitual sleep-wake cycle was delayed by 10 h. Thirty-two out of the 130 detected metabolites showed a 24-h rhythm both at baseline and during the night shift condition. Among these, 75% were driven by sleep-wake and fasting-feeding cycles rather than by the endogenous circadian clock, showing an average phase delay of 8.8 h during the night shift condition. Hence, the majority of rhythmic metabolites were misaligned relative to the endogenous circadian system during the night shift condition. This could be a key mechanism involved in the increased prevalence of adverse metabolic health effects observed in shift workers. On the individual level, the response to the night shift protocol was highly diverse, with phase shifts of rhythmic metabolite profiles ranging from a 0.2-h advance in one subject to a 12-h delay in another subject, revealing an individual metabolomic signature of circadian misalignment. Our findings provide insight into the overall and individual responses of the metabolome to circadian misalignment associated with night schedules and may thereby contribute to the development of individually tailored strategies to minimise the metabolic impacts of shift work.

We compared bright-light durations of 6, 3 and 0 hours (i.e. dim light) during simulated night shifts for phase shifting the circadian rectal temperature rhythm to align with a 12-hour shift of the sleep schedule. After 10 baseline days there were 8 consecutive night-work, day-sleep days, with 8-hour sleep (dark) periods. The bright light (about 5,000 lux, around the baseline temperature minimum) was used during all 8 night shifts, and dim light was < 500 lux. This was a field study in which subjects (n = 46) went outside after the night shifts and slept at home. Substantial circadian adaptation (i.e. a large cumulative temperature rhythm phase shift) was produced in many subjects in the bright light groups, but not in the dim light group. Six and 3 hours of bright light were each significantly better than dim light for phase shifting the temperature rhythm, but there was no significant difference between 6 and 3 hours. Thus, durations > 3 hours are probably not necessary in similar shift-work situations. Larger temperature rhythm phase shifts were associated with better subjective daytime sleep, less subjective fatigue and better overall mood.

Background: The number of shift workers has progressively increased with increasing social needs. Shift work (especially night shift) is known to negatively affect workers’ health and well-being. We aimed to compare shift and non-shift workers in terms of depressive symptoms and related factors. Methods: Data were obtained from the 6th Korea National Health and Nutrition Examination Survey conducted in 2013. Of the 994 participants, 357 were women (all standard workers aged ≥19 years). Based on the information provided by a self-administered questionnaire, subjects were categorized according to work schedule (shift/non-shift). Differences in general characteristics (sociodemographic/health/work factors) between shift and non-shift workers were assessed using the t-test, chi-square test, linear-by-linear association, and Fisher exact test. To evaluate the factors that affect depression, a logistic regression analysis was performed for the general characteristic parameters. Results: Shift workers (9.5%) had higher incidence of depressive symptoms over 2 weeks than the non-shift workers (4.6%; P=0.024). The factors that affected depression were sex (female: odds ratio [OR], 2.94; P=0.001), stress perception (yes: OR, 3.43; P<0.001), suicidal ideation (yes: OR, 15.25; P<0.001), sleep duration (<7 hours/day: OR, 2.16; P=0.021), and occupation class (manual: OR, 2.20; P=0.048) in all subjects. Conclusion: Shift work had a negative effect on workers in terms of depressive symptoms. Shift workers faced harsher conditions than the non-shift workers. Female-sex, stress, suicide ideation, lack of sleep, and manual work were associated with higher depressive symptoms among the workers. Therefore, the working environment should be improved to prevent these depression triggers.

&lt;div&gt;Abstract&lt;p&gt;&lt;b&gt;Background:&lt;/b&gt; Night shift work has been associated with an increased risk for breast and prostate cancer. The effect of circadian disruption on sex steroid production is a possible underlying mechanism, underinvestigated in humans. We have assessed daily rhythms of sex hormones and melatonin in night and day shift workers of both sexes.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Methods:&lt;/b&gt; We recruited 75 night and 42 day workers, ages 22 to 64 years, in different working settings. Participants collected urine samples from all voids over 24 hours on a working day. Urinary concentrations of 16 sex steroid hormones and metabolites (estrogens, progestagens, and androgens) and 6-sulfatoxymelatonin were measured in all samples. Mean levels and peak time of total and individual metabolite production were compared between night and day workers.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Results:&lt;/b&gt; Night workers had higher levels of total progestagens [geometric mean ratio (GMR) 1.65; 95% confidence intervals (CI), 1.17–2.32] and androgens (GMR: 1.44; 95% CI, 1.03–2.00), compared with day workers, after adjusting for potential confounders. The increased sex hormone levels among night shift workers were not related to the observed suppression of 6-sulfatoxymelatonin. Peak time of androgens was significantly later among night workers, compared with day workers (testosterone: 12:14 hours; 10:06-14:48 vs. 08:35 hours; 06:52-10:46).&lt;/p&gt;&lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; We found increased levels of progestagens and androgens as well as delayed peak androgen production in night shift workers compared with day workers.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Impact:&lt;/b&gt; The increase and mistiming of sex hormone production may explain part of the increased risk for hormone-related cancers observed in night shift workers. &lt;i&gt;Cancer Epidemiol Biomarkers Prev; 24(5); 854–63. ©2015 AACR&lt;/i&gt;.&lt;/p&gt;&lt;/div&gt;

Some night-shift workers are more impacted by circadian misalignment than others, resulting in differential impairments to cognitive performance. One explanation may be a polymorphism in the period 3 gene, as 4- and 5-repeat alleles have been shown to predict differences in cognitive performance and alertness after sleep loss. However, the role of Per3 polymorphism in shift workers has not been examined, and may have implications for circadian interventions. This study examined if Per3 genotypes differed in the cognitive consequences of circadian misalignment in night-shift workers. Thirty fixed night-shift workers (22 female) were enrolled in a large observational study examining the health and performance consequences of circadian misalignment. Participants were genotyped as having the 5-repeat allele (Per35/-; n=20) or not (Per34/4; n=10). Circadian phase was assessed hourly via salivary melatonin for 24 hours (dim light melatonin onset). Nocturnal sleepiness was assessed using Multiple Sleep Latency Tests (every two hours from 11pm to 5am). Cognitive flexibility was measured using a computerized task-switching paradigm (tested at 5:30am), which indexed switch-cost (efficiency in switching to a new task) and set-inhibition (efficiency in suppressing previous task rules). As expected, individuals with a delayed circadian phase exhibited less sleepiness (r = -.50, p < .01), though this relationship did not differ by Per3 genotypes. Individuals with delayed circadian phase also showed greater cognitive flexibility (r = .40, p < .05). However, this relationship differed by Per3 genotypes (β = .72, p = .05); delayed circadian phase was associated with greater cognitive flexibility in Per34/4 individuals (β = .86, p < .01) but not in Per35/- individuals (β = .14, p > .05). Results suggest that Per35/- shift workers may experience cognitive deficits resulting from factors beyond circadian misalignment. As prior studies have demonstrated increased susceptibility to sleep disruption in Per35/- individuals, future studies may explore the role of variable sleep timing in cognitive performance, particularly because night shift workers commonly switch to nighttime sleep on nights-off. The work was supported by Teva Pharmaceuticals.

Recently, there has been interest in whether shift work may enhance susceptibility to infection. Our aim was to determine whether shift workers in the health-care field have a higher incidence, duration, and/or severity of influenza-like illness (ILI) and acute respiratory infection (ARI) than non–shift workers. From September 2016 to June 2017, 501 rotating and/or night-shift workers and 88 non–shift workers from the Klokwerk+ Study (the Netherlands, 2016–2017) registered the occurrence of ILI/ARI symptoms daily using a smartphone application. The incidence rate of ILI/ARI (defined as ≥2 symptoms on the same day/≥1 symptom on 2 consecutive days), the mean duration of each episode, and the incidence rate of severe episodes were compared between shift workers and non–shift workers using negative binomial regression and linear mixed-model analysis. In total, participants completed 110,347 diaries. Shift workers’ incidence rate of ILI/ARI was 1.20 (95% confidence interval (CI): 1.01, 1.43) times higher than that of non–shift workers, and for severe ILI/ARI episodes, shift workers’ incidence rate was 1.22 (95% CI: 1.01, 1.49) times higher. The mean duration of an ILI/ARI episode did not differ (ratio between means = 1.02, 95% CI: 0.87, 1.19). In conclusion, shift workers in health care had more ILI/ARI episodes and more severe ILI/ARI episodes than non–shift workers, but with a similar duration. Insight into underlying mechanisms connecting shift work and infection susceptibility will contribute to the design of preventive initiatives.