Currently, in developed countries, nights are excessively illuminated (light at night), whereas daytime is mainly spent indoors, and thus people are exposed to much lower light intensities than under natural conditions. In spite of the positive impact of artificial light, we pay a price for the easy access to light during the night: disorganization of our circadian system or chronodisruption (CD), including perturbations in melatonin rhythm. Epidemiological studies show that CD is associated with an increased incidence of diabetes, obesity, heart disease, cognitive and affective impairment, premature aging and some types of cancer. Knowledge of retinal photoreceptors and the discovery of melanopsin in some ganglion cells demonstrate that light intensity, timing and spectrum must be considered to keep the biological clock properly entrained. Importantly, not all wavelengths of light are equally chronodisrupting. Blue light, which is particularly beneficial during the daytime, seems to be more disruptive at night, and induces the strongest melatonin inhibition. Nocturnal blue light exposure is currently increasing, due to the proliferation of energy-efficient lighting (LEDs) and electronic devices. Thus, the development of lighting systems that preserve the melatonin rhythm could reduce the health risks induced by chronodisruption. This review addresses the state of the art regarding the crosstalk between light and the circadian system.

The disruption of the circadian system in humans has been associated with the development of chronic illnesses and the worsening of pre-existing pathologies. Therefore, the assessment of human circadian system function under free living conditions using non-invasive techniques needs further research. Traditionally, overt rhythms such as activity and body temperature have been analyzed separately; however, a comprehensive index could reduce individual recording artifacts. Thus, a new variable (TAP), based on the integrated analysis of three simultaneous recordings: skin wrist temperature (T), motor activity (A) and body position (P) has been developed. Furthermore, we also tested the reliability of a single numerical index, the Circadian Function Index (CFI), to determine the circadian robustness. An actimeter and a temperature sensor were placed on the arm and wrist of the non-dominant hand, respectively, of 49 healthy young volunteers for a period of one week. T, A and P values were normalized for each subject. A non-parametric analysis was applied to both TAP and the separate variables to calculate their interdaily stability, intradaily variability and relative amplitude, and these values were then used for the CFI calculation. Modeling analyses were performed in order to determine TAP and CFI reliability. Each variable (T, A, P or TAP) was independently correlated with rest-activity logs kept by the volunteers. The highest correlation (r = −0.993, p<0.0001), along with highest specificity (0.870), sensitivity (0.740) and accuracy (0.904), were obtained when rest-activity records were compared to TAP. Furthermore, the CFI proved to be very sensitive to changes in circadian robustness. Our results demonstrate that the integrated TAP variable and the CFI calculation are powerful methods to assess circadian system status, improving sensitivity, specificity and accuracy in differentiating activity from rest over the analysis of wrist temperature, body position or activity alone. Faced with environmental cycles and daily alternation between light and darkness, organisms have evolved a time measuring mechanism, the biological clocks. Besides following circadian rhythms, all physiological variables must be coordinated with one another, like an orchestra led by a conductor; if the appropriate rhythm is not kept, noise rather than music is produced. In an organism, when this temporal order is disrupted due to aging or shift work, health is compromised. Afflictions include metabolic syndrome, diabetes and cardiovascular diseases, among others, or even worse prognosis of preexisting illnesses like cancer. Since the circadian pacemaker (suprachiasmatic nuclei) is located deep within the brain in humans, the only way to evaluate its function is by assessing the output signals, observing marker rhythms such as the sleep-wake cycle, body temperature or activity. The problem is that isolated variable measurement is not error free. However, we can increase reliability by combining the information from several circadian marker rhythms in an integrated variable that we have called TAP (Temperature, Activity and Position), a methodological approach that has not been used before, that in conjunction with a new index called Circadian Function Index, provides a useful tool for standardizing the status of the circadian system.

Objective The main objective of this study was to determine the relationship between the characteristics of nurses' work environments in hospitals in the Spanish National Health System (SNHS) with nurse reported quality of care, and how care was provided by using different shifts schemes. The study also examined the relationship between job satisfaction, burnout, sleep quality and daytime drowsiness of nurses and shift work. Methods This was a multicentre, observational, descriptive, cross-sectional study, centred on a self-administered questionnaire. The study was conducted in seven SNHS hospitals of different sizes. We recruited 635 registered nurses who worked on day, night and rotational shifts on surgical, medical and critical care units. Their average age was 41.1 years, their average work experience was 16.4 years and 90% worked full time. A descriptive and bivariate analysis was carried out to study the relationship between work environment, quality and safety care, and sleep quality of nurses working different shift patterns. Results 65.4% (410) of nurses worked on a rotating shift. The Practice Environment Scale of the Nursing Work Index classification ranked 20% (95) as favourable, showing differences in nurse manager ability, leadership and support between shifts (p=0.003). 46.6% (286) were sure that patients could manage their self-care after discharge, but there were differences between shifts (p=0.035). 33.1% (201) agreed with information being lost in the shift change, showing differences between shifts (p=0.002). The Pittsburgh Sleep Quality Index reflected an average of 6.8 (SD 3.39), with differences between shifts (p=0.017). Conclusions Nursing requires shift work, and the results showed that the rotating shift was the most common. Rotating shift nurses reported worse perception in organisational and work environmental factors. Rotating and night shift nurses were less confident about patients' competence of self-care after discharge. The most common nursing care omissions reported were related to nursing care plans. For the Global Sleep Quality score, difference were found between day and night shift workers.

The increased prevalence of circadian disruptions due to abnormal coupling between internal and external time makes the detection of circadian phase in humans by ambulatory recordings a compelling need. Here, we propose an accurate practical procedure to estimate circadian phase with the least possible burden for the subject, that is, without the restraints of a constant routine protocol or laboratory techniques such as melatonin quantification, both of which are standard procedures. In this validation study, subjects (N = 13) wore ambulatory monitoring devices, kept daily sleep diaries and went about their daily routine for 10 days. The devices measured skin temperature at wrist level (WT), motor activity and body position on the arm, and light exposure by means of a sensor placed on the chest. Dim light melatonin onset (DLMO) was used to compare and evaluate the accuracy of the ambulatory variables in assessing circadian phase. An evening increase in WT: WTOnset (WTOn) and "WT increase onset" (WTiO) was found to anticipate the evening increase in melatonin, while decreases in motor activity (Activity Offset or AcOff), body position (Position Offset (POff)), integrative TAP (a combination of WT, activity and body position) (TAPOffset or TAPOff) and an increase in declared sleep propensity were phase delayed with respect to DLMO. The phase markers obtained from subjective sleep (R = 0.811), WT (R = 0.756) and the composite variable TAP (R = 0.720) were highly and significantly correlated with DLMO. The findings strongly support a new method to calculate circadian phase based on WT (WTiO) that accurately predicts and shows a temporal association with DLMO. WTiO is especially recommended due to its simplicity and applicability to clinical use under conditions where knowing endogenous circadian phase is important, such as in cancer chronotherapy and light therapy.