Klokwerk + study protocol: An observational study to the effects of night-shift work on body weight and infection susceptibility and the mechanisms underlying these health effects

Sleep quality, sleep duration, and sleep disturbances among hospital night workers: a prospective cohort study

PURPOSE

This study aimed to assess among hospital night workers (i) to what extent sleep quality, sleep duration and sleep disturbances overlap, and (ii) associations between sociodemographic factors, lifestyle factors and work characteristics and sleep components.

METHODS

Data were used from 467 hospital night workers participating in the Klokwerk + study, a prospective cohort study with two measurements. Sleep quality was measured by the Pittsburgh Sleep Quality Index, sleep duration and sleep disturbances were measured by the Medical Outcomes Study Sleep Scale. The overlap between the three sleep measures was visualized with a Venn diagram and the proportions of overlap was calculated. Associations between independent variables (sociodemographic factors, lifestyle factors and work characteristics) and the three sleep outcomes were estimated using between-within Poisson regression models.

RESULTS

About 50% of the hospital night workers had at least one poor sleep outcome. Overlap in poor sleep outcomes was apparent for 36.8% of these workers, while the majority had a poor outcome in one of the sleep components only (63.1%). Former smoking had a significant association with poor sleep quality. For most independent variables no associations with poor sleep outcomes were observed.

CONCLUSION

Our findings suggest that sleep quality, sleep duration and sleep disturbances are separate entities and should be studied separately. Lifestyle factors and work characteristics were generally not associated with poor sleep. Since these factors can have an acute effect on sleep, future research should consider ecological momentary assessment to examine how exposure and outcomes (co)vary within-persons, over time, and across contexts. Trial registration Netherlands Trial Register trial number NL56022.041.16.

The Effects of the Exogenous Melatonin on Shift Work Sleep Disorder in Health Personnel: A Systematic Review

(1) Background: To know the medical documentation related to exogenous melatonin in sleep disorders caused by shift work in health personnel; (2) Methods: Systematic and critical review. Data were obtained by looking up the bibliographic data base: MEDLINE (via Pubmed), Embase, Cochrane Library, Scopus, Web of Science, Latin American and Caribbean literature in Health Sciences (LILACS) and Medicine in Spanish (MEDES). The used terms, as descriptors and text in the title and abstract record fields, were "Health Personnel", "Melatonin" and "Sleep Disorders", Circadian Rhythm, by using the following filters: "Humans", "Adult: 19+ years" and "Clinical Trial". The search update was in December 2021. The documentary quality of the articles was assessed using the CONSORT questionnaire. (3) Results: Having applied the inclusion and exclusion criteria, 10 clinical essays were selected out of 98 retrieved references. CONSORT scores ranged from a minimum of 6.0 to a maximum of 13. 7 with a median of 10.2. According to the SIGN criteria, this review presented "1-"evidence with a grade of recommendation B. The intervention dose via administration of exogenous melatonin ranged between 1 and 10 mg. It was not mentioned whether the route of administration was by fast or slow absorption. The outcomes showed decreased daytime sleepiness, lessened sleep onset latency, diminished night-time awakenings, increased total sleep period and improved daytime attention in the melatonin-treated group; (4) Conclusions: Exogenously administered melatonin is effective in shift worker health personnel that are suffering from sleep disorders, and given its low adverse effects and tolerability, it might be recommended. A great disparity was evidenced in terms of dose, follow-up periods and type of melatonin, small participant population, same age ranges and young age. Therefore, new trials would be needed to amend these observations in order to have full evidence that is able to ensure the efficacy of exogenous melatonin in the studied population.

The Sleep Quality of the Frontline Healthcare Workers and the Improving Effect of Tai Chi

BACKGROUND

A number of studies have documented that coronavirus disease 2019 (COVID-19) brought more negative impact on the physical and psychological functioning of frontline healthcare workers. Especially, sleep quality was focused. This study aimed to investigate the sleep quality of frontline healthcare workers, risk factors for sleep quality, and the effect of Tai Chi training.

METHODS

A total of 98 frontline healthcare workers were recruited, coming from the infection department, fever clinic, laboratory, and medical imaging department in a COVID-19-designated hospital in Shanghai. Of them, 50 participated in a 2-week intervention and were randomized to receive a Tai Chi training or relaxation training. Participants were assessed at baseline, 7 and 14 days after participation. Demographic information, sleep quality, and anxiety were measured by using the demographic questionnaire, Pittsburgh Sleep Quality Index (PSQI) and Beck Anxiety Inventory (BAI).

RESULTS

13.3% participants were above the cut-off score (>10) for the PSQI. Regression analysis showed gender, age, working years, and job category had effect on sleep quality. Compared to the control group, participants in the Tai Chi training group had lower scores on both PSQI (p < 0.05) and BAI (p < 0.01) after the 2-week intervention.

CONCLUSION

It was demonstrated that poor sleep quality existed in the frontline healthcare workers, which was related to gender, age, working years, and job category. Tai Chi training can dramatically improve their sleep quality and reduce anxiety symptoms.

The association between mental health and shift work: Findings from the Atlantic PATH study

We evaluated the relationship between mental health and shift work in the Atlantic Partnership for Tomorrow's Health (PATH) cohort study. In a matched study with 12,413 participants, including 4155 shift workers and 8258 non-shift workers, we utilized general linear models and logistic regression models to assess the differences in depression, anxiety, and self-rated health. Shift workers reported higher levels of each of the mental health-related domains compared to non-shift workers. There was a significant increased risk of depression (OR = 1.13, 95% CI, 1.00-1.27) and poor self-rated health (OR = 1.13, 95% CI, 1.14-1.55) among shift workers compared to non-shift workers. Shift workers were more likely to have increased rates of depression and poor self-rated health, as well as depressive and anxiety symptom scores compared to non-shift workers. As a result, shift workers may be at increased risk of comorbidity, poor quality of life, missed work, and early retirement.

Sleep quality and COVID-19 outcomes: the evidence-based lessons in the framework of predictive, preventive and personalised (3P) medicine

Sleep quality and duration play a pivotal role in maintaining physical and mental health. In turn, sleep shortage, deprivation and disorders are per evidence the risk factors and facilitators of a broad spectrum of disorders, amongst others including depression, stroke, chronic inflammation, cancers, immune defence insufficiency and individual predisposition to infection diseases with poor outcomes, for example, related to the COVID-19 pandemic. Keeping in mind that COVID-19-related global infection distribution is neither the first nor the last pandemic severely affecting societies around the globe to the costs of human lives accompanied with enormous economic burden, lessons by predictive, preventive and personalised (3P) medical approach are essential to learn and to follow being better prepared to defend against global pandemics. To this end, under extreme conditions such as the current COVID-19 pandemic, the reciprocal interrelationship between the sleep quality and individual outcomes becomes evident, namely, at the levels of disease predisposition, severe versus mild disease progression, development of disease complications, poor outcomes and related mortality for both - population and healthcare givers. The latter is the prominent example clearly demonstrating the causality of severe outcomes, when the long-lasting work overload and shift work rhythm evidently lead to the sleep shortage and/or deprivation that in turn causes immune response insufficiency and strong predisposition to the acute infection with complications. This article highlights and provides an in-depth analysis of the concerted risk factors related to the sleep disturbances under the COVID-19 pandemic followed by the evidence-based recommendations in the framework of predictive, preventive and personalised medical approach.

Sickness absenteeism, work performance, and healthcare use due to respiratory infections for shift and non-shift workers

This study aimed to compare sickness absenteeism, work performance, and healthcare use due to respiratory infections, as well as general sickness absenteeism and work performance between shift and non-shift workers. In this study, 589 shift and non-shift workers employed in hospitals were included. For 6 months, participants kept a daily record of their influenza-like illness/acute respiratory infection (ILI/ARI) symptoms using a diary application. After an episode of ILI/ARI symptoms ended, participants (n = 531) were questioned about their sickness absenteeism (occurrence and duration in hours), work performance (on a 10 point scale), and healthcare use during the ILI/ARI episode. At the end of the 6 months follow-up, participants (n = 498) were also asked about general sickness absenteeism and work performance in the past 4 weeks. Mixed-model and regression analyses were used to compare absenteeism, work performance, and healthcare use between shift and non-shift workers. No differences were found in sickness absenteeism [Odds Ratio (OR) = 1.00 (95%‒Confidence Interval (CI): 0.61‒1.64)] and work performance [Regression coefficient (B) = -0.19 (95%‒CI: -0.65‒0.26)] due to ILI/ARI between shift and non-shift workers. In addition, healthcare use due to ILI/ARI was similar between shift and non-shift workers. Furthermore, similar general sickness absenteeism rates and work performance levels were found between shift and non-shift workers. As this is the first study that examined the associations with shift work due to ILI/ARI, further studies are needed to confirm our findings.

In-depth immune cellular profiling reveals sex-specific associations with frailty

Background

With advancing age, the composition of leukocyte subpopulations in peripheral blood is known to change, but how this change differs between men and women and how it relates to frailty is poorly understood. Our aim in this exploratory study was to investigate whether frailty is associated with changes in immune cell subpopulations and whether this differs between men and women. Therefore, we performed in-depth immune cellular profiling by enumerating a total of 37 subpopulations of T cells, B cells, NK cells, monocytes, and neutrophils in peripheral blood of 289 elderly people between 60-87 years of age. Associations between frailty and each immune cell subpopulation were tested separately in men and women and were adjusted for age and CMV serostatus. In addition, a random forest algorithm was used to predict a participant’s frailty score based on enumeration of immune cell subpopulations.

Results

In the association study, frailty was found to be associated with increased numbers of neutrophils in both men and in women. Frailer women, but not men, showed higher numbers of total and CD16^- monocytes, and lower numbers of both CD56⁺ T cells and late differentiated CD4⁺ TemRA cells. The random forest algorithm confirmed all the findings of the association studies in men and women. In men, the predictive accuracy of the algorithm was too low (5.5%) to warrant additional conclusions on top of the ones derived from the association study. In women however, the predictive accuracy was higher (23.1%), additionally revealing that total T cell numbers and total lymphocyte numbers also contribute in predicting frailty.

Conclusions

In-depth immune cellular profiling revealed consistent associations of frailty with elevated numbers of myeloid cell subpopulations in both men and women. Furthermore, additional associations were found between frailty and lower numbers of some T cell subpopulations, in women only. Thus, our study indicates sex-specific associations of immune subpopulations with frailty. We hope that our study will prompt further investigation into the sex-specific immune mechanisms associated with the development of frailty.

The mediating role of sleep, physical activity, and diet in the association between shift work and respiratory infections

Objectives:

Shift work may be associated with an increased incidence of respiratory infections. However, underlying mechanisms are unclear. Therefore, our aim was to examine the mediating role of sleep, physical activity, and diet in the association between shift work and respiratory infections.

Methods:

This prospective cohort study included 396 shift and non-shift workers employed in hospitals. At baseline, sleep duration and physical activity were measured using actigraphy and sleep/activity diaries, sleep quality was reported, and frequency of meal and snack consumption was measured using food diaries. In the following six months, participants used a smartphone application to report their influenza-like illness/acute respiratory infection (ILI/ARI) symptoms daily. Mediation analysis of sleep, physical activity, and diet as potential mediators of the effect of shift work on ILI/ARI incidence rate was performed using structural equation modeling with negative binomial and logistic regression.

Results:

Shift workers had a 23% [incidence rate ratio (IRR) 1.23, 95% CI 1.01–1.49] higher incidence rate of ILI/ARI than non-shift workers. After adding the potential mediators to the model, this reduced to 15% (IRR 1.15, 95% CI 0.94–1.40). The largest mediating (ie, indirect) effect was found for poor sleep quality, with shift workers having 29% more ILI/ARI episodes via the pathway of poorer sleep quality (IRR 1.29, 95% CI 1.02–1.95).

Conclusions:

Compared to non-shift workers, shift workers had a higher incidence rate of ILI/ARI that was partly mediated by poorer sleep quality. Therefore, it may be relevant for future research to focus on perceived sleep quality as an underlying mechanism in the relation between shift work and increased infection susceptibility.

Immunological effects of shift work in healthcare workers

The immune system potentially plays an important mechanistic role in the relation between shift work and adverse health effects. To better understand the immunological effects of shift work, we compared numbers and functionality of immune cells between night-shift and non-shift workers. Blood samples were collected from 254 night-shift and 57 non-shift workers employed in hospitals. Absolute numbers of monocytes, granulocytes, lymphocytes, and T cell subsets were assessed. As read out of immune function, monocyte cytokine production and proliferative capacity of CD4 and CD8 T cells in response to various stimuli were analysed. The mean number of monocytes was 1.15 (95%-CI = 1.05–1.26) times higher in night-shift than in non-shift workers. Furthermore, night-shift workers who worked night shifts in the past three days had a higher mean number of lymphocytes (B = 1.12 (95%-CI = 1.01–1.26)), T cells (B = 1.16 (95%-CI = 1.03–1.31)), and CD8 T cells (B = 1.23 (95%-CI = 1.05–1.45)) compared to non-shift workers. No differences in functional parameters of monocytes and lymphocytes were observed. The differences in numbers of monocytes and T cells suggest that chronic exposure to night-shift work as well as recent night-shift work may influence the immune status of healthcare workers. This knowledge could be relevant for preventive initiatives in night-shift workers, such as timing of vaccination.

Mobilizing Breast Cancer Prevention Research Through Smartphone Apps: A Systematic Review of the Literature

Background: Breast cancer rates have been increasing worldwide, particularly among young women, suggesting important interactions between genes and health behaviors. At the same time, mobile technology, including smartphones applications (apps), has emerged as a new tool for delivering healthcare and health-related services. As of 2018, there were nearly 600 publicly available breast cancer apps designed to provide disease and treatment information, to manage disease, and to raise overall awareness. However, the extent to which apps are incorporated into breast cancer prevention research is unknown. Therefore, the objective of this review was to determine how mobile applications are being used for breast cancer prevention among women across the cancer control continuum. Methods: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched PubMed and Web of Science Core Collection databases using the keywords breast cancer, smartphone, mobile application, and phone app. Full-length journal articles available in English that addressed the research question were included. We categorized articles by prevention type (primary, secondary, and tertiary) and phase of research (protocol, development, feasibility, pilot, measurement, and effectiveness), and identified common themes and gaps. Results: Our search yielded 82 studies (69 unique) that used apps in breast cancer prevention research across 20 countries. Approximately half of the named apps were publicly available. The majority (73%) of studies targeted tertiary prevention; 15% targeted secondary and 13% targeted primary prevention. Apps were used across all phases of research with the predominant phase being feasibility in tertiary prevention (34%), effectiveness in secondary prevention (63%), and development (30%) and effectiveness (30%) in primary prevention. Common uses included assessing outcomes relevant to clinical care coordination, quality of life, increasing self-efficacy and screening behaviors, and tracking and managing health behaviors. Conclusions: We identified the following gaps: few effectiveness studies in tertiary prevention, minimal use of apps for breast cancer etiology or early detection, and few interventions in those at average risk of breast cancer. These findings suggest that while mobile apps can inform breast cancer prevention across the continuum, more work is needed to incorporate apps into primary prevention.

The factors influencing the eating behaviour of shiftworkers: what, when, where and why

Shiftwork leads to altered eating patterns, with workers often eating foods at all times across the 24 h period. Strategies to reduce the burden of shiftwork on the workers should be prioritised and altering these eating patterns is an important area for change. This narrative review examines the current evidence on the individual and environmental factors influencing the eating behaviours of shiftworkers. A systematic search was conducted and yielded 62 articles. These were split into four themes that influence eating patterns; When shiftworkers eat, What type of foods shiftworkers eat, Where the food is sourced from, and Why shiftworkers choose to eat on shift. Irregular working hours was the biggest influence on when workers ate on shift, shift-type was the biggest influence on what workers ate, the majority of food was sourced from canteens and cafeterias, and socialising with colleagues was the biggest reason why workers chose to eat. While more research is needed to explore multiple industries and shift-types, and to investigate the ideal size, type and timing of food on shift, this review has highlighted that future research into shiftworker eating needs to adopt an integrative approach and consider the different individual and social contexts that influence eating patterns.

The relationship between anthropometric measures and cardiometabolic health in shift work: findings from the Atlantic PATH Cohort Study

PURPOSE

To evaluate the relationship between anthropometric measures and cardiometabolic health in shift workers compared to non-shift workers.

METHODS

A population health study was conducted with 4155 shift workers and 8258 non-shift workers from the Atlantic Partnership for Tomorrow's Health (PATH) cohort. Linear and logistic regression models were used to assess the differences in anthropometric measures (body adiposity) and self-reported cardiometabolic disease outcomes (obesity, diabetes, and cardiovascular disease) between shift workers and non-shift workers.

RESULTS

There was a significant increased risk of cardiovascular disease, obesity, and diabetes among shift workers compared to matched controls despite higher levels of physical activity and lower levels of sedentary behaviour. Shift workers were 17% more likely to be obese (95% CI 7-27) and 27% more likely to have diabetes (95% CI 8-51). The strength of this association was demonstrated by also controlling for body mass index and fat mass index.

CONCLUSIONS

Shift work is associated with obesity, cardiovascular disease, and diabetes despite higher levels of physical activity and lower levels of sedentary behaviour. The association between shift work and cardiometabolic health was independent of body mass index for cardiovascular disease and diabetes, and independent of fat mass index for diabetes.

Shift Work and Respiratory Infections in Health-Care Workers

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.

The association between exposure to different aspects of shift work and metabolic risk factors in health care workers, and the role of chronotype

Objective

Shift work has been linked to cardio-metabolic diseases, but insight into different shift work-related aspects and chronotype of shift workers and their relation with metabolic risk factors is limited. This study examined the association between current shift work status, frequency and duration of night shift work, chronotype, and metabolic risk factors in a population of health care workers.

Methods

Anthropometrics, questionnaires, and blood samples were collected from 503 shift working and 93 non-shift working health care workers employed in hospitals. Body mass index, waist circumference, cholesterol (total, HDL, LDL), triglycerides, and high-sensitivity C-reactive protein were measured. Associations of current shift work, frequency (non-night shift worker, 1–2, 3–4, ≥5 night shifts/month) and duration of night shift work (non-night shift workers, <10, 10–19, ≥20 years), and shift workers’ chronotype, with metabolic risk factors were studied using linear regression analysis.

Results

Compared to non-shift workers, shift workers’ total cholesterol level was 0.38 mmol/L lower (95%-CI = -0.73 –-0.04) and LDL cholesterol was 0.34 mmol/L lower (95%-CI = -0.60 –-0.08). For all other metabolic risk factors, no differences were found. The association between shift work and LDL cholesterol was especially found among shift workers working night shifts for ≥20 years (B = -0.49 (95%-CI = -0.78 –-0.19)). No differences were found for night shift frequency and chronotype.

Conclusion

In this population of health care workers employed in hospitals, no evidence for differences in metabolic risk factors was observed that could underlie a link between shift work and cardio-metabolic diseases. Further research using different aspects of shift work to study the association with metabolic risk factors is recommended.