The shift work and health research agenda: Considering changes in gut microbiota as a pathway linking shift work, sleep loss and circadian misalignment, and metabolic disease

2017 ◽  
Vol 34 ◽  
pp. 3-9 ◽  
Author(s):  
Amy C. Reynolds ◽  
Jessica L. Paterson ◽  
Sally A. Ferguson ◽  
Dragana Stanley ◽  
Kenneth P. Wright ◽  
...  
2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
S Gamboa Madeira ◽  
C Reis ◽  
T Paiva ◽  
T Roenneberg

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Fundação para a Ciência e Tecnologia (FCT) and Fundo Social Europeu (FSE) Introduction Atypical work schedules encompass more than 20% of the European workforce. The link between shift work and cardiovascular disease (CVD) has been extensively studied being lifestyle behaviours, sleep disruption and circadian misalignment the key mechanisms involved. Social Jetlag (SJL) has been proposed as a proxy for circadian misalignment in epidemiological studies, once it takes into account  individual’s chronotype and working schedules. Therefore we hypothesize that, among  workers under fixed atypical work schedules, those with a greater SJL have a higher CVD risk. Methods A cross-sectional observational study was conducted among blue-collar workers of one retail company. Fixed working schedules were early morning, late evening, and night work. Sociodemographic, occupational, lifestyle and sleep data were collected through questionnaire. SJL was quantified by the difference for mid-sleep points on work- and free-days. Even though SJL is a continuous variable, 3 categories have been used (≤2h; 2-4h; ≥4h). Blood pressure (BP) and the total cholesterol (TC) were assessed. The CVD risk was estimated according to the relative risk SCORE chart. A relative risk≥3 was considered "high CVD risk". Descriptive statistics and bivariate analysis according to the CVD risk (high vs other) was performed. The relationship between SJL and high CVD risk was analysed through logistic binary regression using generalized linear models adjusted for age, sex, education, Body Mass Index, consumptions, sleep duration and quality plus work schedule and seniority. Results Of the 301 workers, 56.1% were male with a mean age of 33.0 ± 9.4years. Average SJL was 1:57 ± 1:38hours with the majority of workers experiencing ≤2h (59.4%) and 8% (n = 24) more than 4h. Less than a half had hypercholesterolemia (48.8%), overweight (37.9%)or hypertensive values (10.6%), however 50.5% were currently smokers. We found a significant trend for hypertension (p = 0.006) and smoking prevalence (p = 0.043) among ordinal SJL categories. A relative "high CVD risk" was found in 20.3% of the sample (n = 61). These workers were significantly older (p < 0.001), less educated (p = 0.003) and slept less hours on workdays (p = 0.021). In the multiple regression analysis, SJL was an independent risk factor for a "high CVD risk" (p = 0.029).The odds of having a "high CVD risk" increased almost thirty per cent  per each additional hour of SJL (OR = 1.29; 95% CI:1.03-1.63), even after adjusting for sociodemographic, lifestyle, sleep and working features. Conclusions We found compelling evidence that a greater SJL was associated with a bigger chance of high CVD risk. From this innovative perspective, the focus is not just on the working schedule itself but also on the worker’s chronotype. These findings suggest that interventions aimed to reduce Social Jetlag, especially in extreme chronotypes and working schedules, poses a great opportunity to minimize the cardiovascular health impact of shift work.


SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A56-A56
Author(s):  
Mark McCauley ◽  
Peter McCauley ◽  
Hans Van Dongen

Abstract Introduction In commercial aviation and other operational settings where biomathematical models of fatigue are used for fatigue risk management, accurate prediction of recovery during rest periods following duty periods with sleep loss and/or circadian misalignment is critical. The recuperative potential of recovery sleep is influenced by a variety of factors, including long-term, allostatic effects of prior sleep/wake history. For example, recovery tends to be slower after sustained sleep restriction versus acute total sleep deprivation. Capturing such dynamics has proven to be challenging. Methods Here we focus on the dynamic biomathematical model of McCauley et al. (2013). In addition to a circadian process, this model features differential equations for sleep/wake regulation including a short-term sleep homeostatic process capturing change in the order of hours/days and a long-term allostatic process capturing change in the order of days/weeks. The allostatic process modulates the dynamics of the homeostatic process by shifting its equilibrium setpoint, which addresses recently observed phenomena such as reduced vulnerability to sleep loss after banking sleep. It also differentiates the build-up and recovery rates of fatigue under conditions of chronic sleep restriction versus acute total sleep deprivation; nonetheless, it does not accurately predict the disproportionately rapid recovery seen after total sleep deprivation. To improve the model, we hypothesized that the homeostatic process may also modulate the allostatic process, with the magnitude of this effect scaling as a function of time awake. Results To test our hypothesis, we added a parameter to the model to capture modulation by the homeostatic process of the allostatic process build-up during wakefulness and dissipation during sleep. Parameter estimation using previously published laboratory datasets of fatigue showed this parameter as significantly different from zero (p<0.05) and yielding a 10%–20% improvement in goodness-of-fit for recovery without adversely affecting goodness-of-fit for pre-recovery days. Conclusion Inclusion of a modulation effect of the allostatic process by the homeostatic process improved prediction accuracy in a variety of sleep loss and circadian misalignment scenarios. In addition to operational relevance for duty/rest scheduling, this finding has implications for understanding mechanisms underlying the homeostatic and allostatic processes of sleep/wake regulation. Support (if any) Federal Express Corporation


2000 ◽  
Vol 27 (4) ◽  
pp. 1057-1078 ◽  
Author(s):  
Allene J. Scott
Keyword(s):  

2021 ◽  
Vol 69 (37) ◽  
pp. 10907-10919
Author(s):  
Hao Suo ◽  
Mohammad Rezaul Islam Shishir ◽  
Jianbo Xiao ◽  
Mingfu Wang ◽  
Feng Chen ◽  
...  

2017 ◽  
Vol 38 (2) ◽  
pp. 86 ◽  
Author(s):  
Myung-Ji Bae ◽  
Yun-Mi Song ◽  
Jin-Young Shin ◽  
Bo-Young Choi ◽  
Jung-Hyun Keum ◽  
...  

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