Shift work and cardiovascular disease - pathways from circadian stress to morbidity.

Centre of Expertise on Human Factors at Work, Finnish Institute of Occupational Health, FI-00250 Helsinki, Finland.
Scandinavian Journal of Work, Environment & Health (Impact Factor: 3.1). 03/2010; 36(2):96-108. DOI: 10.2307/40967836
Source: PubMed

ABSTRACT In order to establish a causal relation between shift work and cardiovascular disease (CVD), we need to verify the pathways from the former to the latter. This paper aims to review the current knowledge of the mechanisms between shift work and CVD. Shift work can increase the risk of CVD by several interrelated psychosocial, behavioral, and physiological mechanisms. The psychosocial mechanisms relate to difficulties in controlling working hours, decreased work-life balance, and poor recovery following work. The most probable behavioral changes are weight gain and smoking. The plausible physiological and biological mechanisms are related to the activation of the autonomic nervous system, inflammation, changed lipid and glucose metabolism, and related changes in the risk for atherosclerosis, metabolic syndrome, and type II diabetes. The data provide evidence for possible disease mechanisms between shift work and CVD, but compelling evidence on any specific mechanism is missing.

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    ABSTRACT: Objectives Epidemiological studies suggest that long working hours and shift work may increase the risk of chronic diseases, but the “toxic” elements remain unclear due to crude assessment of working time patterns based on self-reports. In this methodological paper, we present and evaluate objective register-based algorithms for assessment of working time patterns and validate a method to retrieve standard payroll data on working hours from the employer electronic records. Methods Detailed working hour records from employers’ registers were obtained for 12 391 nurses and physicians, a total 14.5 million separate work shifts from 2008–2013. We examined the quality and validity of the obtained register data and designed 29 algorithms characterizing four potentially health-relevant working time patterns: (i) length of the working hours; (ii) time of the day; (iii) shift intensity; and (iv) social aspects of the working hours. Results The collection of the company-based register data was feasible and the retrieved data matched with the originally published shift plans. The transferred working time records included <0.01% missing data. Two percent were duplicates that could be easily removed. The 29 variables of working time patterns, generated for each year, were stable across the follow-up (year-to-year correlation coefficients from r=0.7–0.9 for 23 variables), their distributions were as expected, and correlations of the variables within the four main dimensions of working hours were plausible. Conclusion The developed method and algorithms allow a detailed characterization of four main dimensions of working time patterns potentially relevant for health. We recommend this method for future large-scale epidemiological studies.
    Scandinavian Journal of Work, Environment & Health 03/2015; DOI:10.5271/sjweh.3492 · 3.10 Impact Factor
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    ABSTRACT: Our current 24-h society requires an increasing number of employees to work nightshifts with millions of people worldwide working during the evening or night. Clear associations have been found between shiftwork and the risk to develop metabolic health problems, such as obesity. An increasing number of studies suggest that the underlying mechanism includes disruption of the rhythmically organized body physiology. Normally, daily 24-h rhythms in physiological processes are controlled by the central clock in the brain in close collaboration with peripheral clocks present throughout the body. Working schedules of shiftworkers greatly interfere with these normal daily rhythms by exposing the individual to contrasting inputs, i.e., at the one hand (dim)light exposure at night, nightly activity and eating and at the other hand daytime sleep and reduced light exposure. Several different animal models are being used to mimic shiftwork and study the mechanism responsible for the observed correlation between shiftwork and metabolic diseases. In this review we aim to provide an overview of the available animal studies with a focus on the four most relevant models that are being used to mimic human shiftwork: altered timing of (1) food intake, (2) activity, (3) sleep, or (4) light exposure. For all studies we scored whether and how relevant metabolic parameters, such as bodyweight, adiposity and plasma glucose were affected by the manipulation. In the discussion, we focus on differences between shiftwork models and animal species (i.e., rat and mouse). In addition, we comment on the complexity of shiftwork as an exposure and the subsequent difficulties when using animal models to investigate this condition. In view of the added value of animal models over human cohorts to study the effects and mechanisms of shiftwork, we conclude with recommendations to improve future research protocols to study the causality between shiftwork and metabolic health problems using animal models.
    Frontiers in Pharmacology 03/2015; 1(6). DOI:10.3389/fphar.2015.00050


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May 26, 2014