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Out of the Lab and into the Bathroom: Evening Short-Term Exposure to Conventional Light Suppresses Melatonin and Increases Alertness Perception


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Life in 24-h society relies on the use of artificial light at night that might disrupt synchronization of the endogenous circadian timing system to the solar day. This could have a negative impact on sleep-wake patterns and psychiatric symptoms. The aim of the study was to investigate the influence of evening light emitted by domestic and work place lamps in a naturalistic setting on melatonin levels and alertness in humans. Healthy subjects (6 male, 3 female, 22-33 years) were exposed to constant dim light (<10 lx) for six evenings from 7:00 p.m. to midnight. On evenings 2 through 6, 1 h before habitual bedtime, they were also exposed to light emitted by 5 different conventional lamps for 30 min. Exposure to yellow light did not alter the increase of melatonin in saliva compared to dim light baseline during (38 ± 27 pg/mL vs. 39 ± 23 pg/mL) and after light exposure (39 ± 22 pg/mL vs. 44 ± 26 pg/mL). In contrast, lighting conditions including blue components reduced melatonin increase significantly both during (office daylight white: 25 ± 16 pg/mL, bathroom daylight white: 24 ± 10 pg/mL, Planon warm white: 26 ± 14 pg/mL, hall daylight white: 22 ± 14 pg/mL) and after light exposure (office daylight white: 25 ± 15 pg/mL, bathroom daylight white: 23 ± 9 pg/mL, Planon warm white: 24 ± 13 pg/mL, hall daylight white: 22 ± 26 pg/mL). Subjective alertness was significantly increased after exposure to three of the lighting conditions which included blue spectral components in their spectra. Evening exposure to conventional lamps in an everyday setting influences melatonin excretion and alertness perception within 30 min.
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Int. J. Mol. Sci. 2013, 14, 2573-2589; doi:10.3390/ijms14022573
International Journal of
Molecular Sciences
ISSN 1422-0067
Out of the Lab and into the Bathroom: Evening Short-Term
Exposure to Conventional Light Suppresses Melatonin and
Increases Alertness Perception
Amely Wahnschaffe 1,*, Sven Haedel 1, Andrea Rodenbeck 1, Claudia Stoll 1, Horst Rudolph 2,
Ruslan Kozakov 3, Heinz Schoepp 3 and Dieter Kunz 1,4
1 Institute of Physiology, Charité–Universitätsmedizin Berlin (CBF), 10115 Berlin, Germany;
E-Mails: (S.H.); (A.R.); (C.S.); (D.K.)
2 Trilux GmbH & Co.KG, 59759 Arnsberg, Germany; E-Mail:
3 Leibniz Institute for Plasma Science and Technology (INP), 17489 Greifswald, Germany;
E-Mails: (R.K.); (H.S.)
4 German Heart Institute, 13353 Berlin, Germany
* Author to whom correspondence should be addressed; E-Mail:;
Tel.: +49-30-2311-2901; Fax: +49-30-2311-2903.
Received: 23 November 2012; in revised form: 23 December 2012 / Accepted: 16 January 2013 /
Published: 28 January 2013
Abstract: Life in 24-h society relies on the use of artificial light at night that might disrupt
synchronization of the endogenous circadian timing system to the solar day. This could
have a negative impact on sleep–wake patterns and psychiatric symptoms. The aim of the
study was to investigate the influence of evening light emitted by domestic and work place
lamps in a naturalistic setting on melatonin levels and alertness in humans. Healthy
subjects (6 male, 3 female, 22–33 years) were exposed to constant dim light (<10 lx) for
six evenings from 7:00 p.m. to midnight. On evenings 2 through 6, 1 h before habitual
bedtime, they were also exposed to light emitted by 5 different conventional lamps for
30 min. Exposure to yellow light did not alter the increase of melatonin in saliva compared
to dim light baseline during (38 ± 27 pg/mL vs. 39 ± 23 pg/mL) and after light exposure
(39 ± 22 pg/mL vs. 44 ± 26 pg/mL). In contrast, lighting conditions including blue
components reduced melatonin increase significantly both during (office daylight white:
25 ± 16 pg/mL, bathroom daylight white: 24 ± 10 pg/mL, Planon warm white:
26 ± 14 pg/mL, hall daylight white: 22 ± 14 pg/mL) and after light exposure (office
daylight white: 25 ± 15 pg/mL, bathroom daylight white: 23 ± 9 pg/mL, Planon warm
Int. J. Mol. Sci. 2013, 14 2574
white: 24 ± 13 pg/mL, hall daylight white: 22 ± 26 pg/mL). Subjective alertness was
significantly increased after exposure to three of the lighting conditions which included
blue spectral components in their spectra. Evening exposure to conventional lamps in an
everyday setting influences melatonin excretion and alertness perception within 30 min.
Keywords: melatonin; circadian rhythm; light; sleep disturbances; alertness
1. Introduction
Both nonorganic disturbances of the sleep–wake schedule (F51.2) and nonorganic insomnia (F51.0)
are discrete psychiatric diagnoses according to ICD-10 chapter V, as well as common symptoms of
various psychiatric disorders. Whereas the high incidence of the key feature—nonrestorative sleep—is
a widely accepted fact [1], it was not until recently that the enormous socioeconomic costs related to
sleep disorders were reported [2]. Recently approved melatonergic agents have proven efficient in
patients suffering from major depression, as well as nonorganic insomnia, and thereby introduced the
potential role of melatonin for psychiatric disorders into scientific discourse [3]. The hormone
melatonin is central for the linkage between environmental and internal rhythms, because its secretion
pattern depends on environmental light conditions, and an increase of its serum levels signals
“night-mode” to numerous body functions. The question arises whether light exposure at the wrong
time—e.g., artificial evening light—via suppression of melatonin may contribute to sleep-related
psychiatric disturbances by suppressing melatonin secretion.
The earth’s rotation causes the most reliably recurrent event in nature: the daily light–dark cycle.
The evolutionary result is a network of internal clocks governed by a master clock located in the
hypothalamic suprachiasmatic nucleus (SCN), which drives the predictable part of daily physiological
variations in a precise manner [4]. This circadian timing system (CTS) has been shown to be involved
in the daily variation of almost every physiological and psychological system evaluated thus far
(e.g., hormones, neurotransmitters, receptor densities and affinities, gene expression, mood, motor
activity, pharmacokinetics, pharmacodynamics, responses to pharmacological treatment) [5–10].
Maintaining synchronized circadian rhythms is important to health and well-being. A growing body
of evidence suggests that desynchronization of circadian rhythms may play a role in various tumoral
diseases, diabetes, obesity, depression, and Alzheimer’s disease [11–14]. Shift workers, who serve as a
model for internal desynchronization, are subject to increased morbidity and mortality from a number
of diseases, including cardiovascular disorders and cancer [15–17].
The daily light–dark cycle synchronizes the CTS with the natural 24-h day [18]. In 2000,
melanopsin was identified in a subgroup of retinal ganglion cells, which were originally only known to
integrate the information from rods and cones and transform it into neuronal activation [19]. This
allowed for a non-image-forming system to be characterized in accretive detail: light and darkness are
predominantly perceived by specialized intrinsic photosensitive retinal ganglion cells expressing
melanopsin. On the one hand, they react directly to light input; on the other hand, they gather light
information from rods and cones. This integrated measurement provides the internal clock with
information on the time and length of day [20]. The blue portion of the visible spectrum appears to
Int. J. Mol. Sci. 2013, 14 2575
play the dominant role in the intrinsic photosensitivity of these cells, as well as for the integrated
non-image-forming response to light stimuli [21]. Two groups independently reported an action
spectrum for light-induced melatonin suppression by monochromatic light at night [22,23].
Additionally, monochromatic blue light has been shown to induce pupillary constriction, increase heart
rate, influence thermoregulation, enhance alertness, change the frequency of the electroencephalogram
and influence sleep architecture [24–26]. In contrast to green light, blue light was even shown to
increase human PER2 gene expression after 2 h of evening light exposure [27]. Enezi et al. recently
suggested a “melanopic” spectral efficiency function as an alternative to lux and photon density for
describing the impact of polychromatic light of different spectral distributions on melanopsin
expression and the proximate pupillomotor and circadian responses [28]. This melanopic function was
successfully applied to rod- and coneless mice, but not yet to wild-type mice or even humans. Effects
of long-term polychromatic light on human melatonin levels have already been shown: a study using
artificial room light demonstrated that light exposure <200 lux for 8 h until bedtime delayed
the melatonin onset without shifting melatonin offset [29]. Shanti et al. [30] reported a
wavelength-dependent influence of 4 h of evening light exposure on melatonin suppression, subjective
sleepiness, and sleep onset latency. However, data on short-term evening polychromatic light exposure
are still missing.
Many practical clinical trials have shown the effects of light as a therapeutic agent on depression,
age-related sleep problems and agitation in dementia (see, for example, [31–34]). Thus, evening light
exposure was successfully applied to increase alertness in older adults with evening sleepiness [35].
Nevertheless, most of the studies in the context of light influences on circadian rhythms were
performed using long-term, high intensity bright white, polychromatic or blue light in artificial settings
in a way that seldom occurs even in our world of artificial lighting [22,23,36]. Even when the design
for these studies was modeled on average exposition under natural conditions for the periods they
examined [30] they did not consider the impact of very short periods of light exposure on circadian
parameters. Yet the evening setting can include relevant changes in lighting conditions such as a
transition from a brightly lit gym to a moderately lit home, or from a dimly-lit reading corner or
television light in the living room to the neon-lit bathroom, where you get ready for bed. Their findings
are therefore difficult to generalize to such conditions. Other studies addressed the therapeutic
potential of strengthening circadian rhythms with light. The question could be raised if simple behavior
recommendations regarding “light hygiene” could already work as a therapeutic agent on circadian
rhythm associated disturbances.
The hypotheses of the present study are that (1) light emitted by conventional home and work place
lamps in a naturalistic evening setting can suppress melatonin excretion in healthy human subjects
after very short periods of time; and (2) the strength of this influence is wavelength and
intensity-dependent and can be minimized by blue depletion and intensity reduction. In a second step,
we conduct an exploratory investigation of different lamps on subjective calmness, contentedness
and alertness.
Int. J. Mol. Sci. 2013, 14 2576
2. Results and Discussion
2.1. Raw Data and Descriptive Statistics
Graphical analysis of melatonin raw data in most of the nine single subjects and in group means
shows differences between baseline (dim light) and yellow bathroom lamp, on the one hand, and
between baseline and the four lamps with blue components of the visible spectrum, on the other hand
(e.g., Figure 1, subject 13).
Figure 1. Raw data of melatonin levels in saliva in subject number 13 (subjects in the
present study were numbered 7–15 following a pilot study with subjects 1–6). Lines
represent the different lighting conditions.
Mean group changes of melatonin levels relative to “lights on” are given in Figure 2. While
melatonin concentrations continuously rise during the time of light exposure under baseline and yellow
bathroom lamp conditions, the increase of melatonin concentrations stops or is even reversed during
exposure to any of the four lamps, including blue portions, starting already as early as 20 min after
“lights on”. After termination of light exposure, melatonin concentrations start rising again, but not to
the level reached within 30 min after baseline or yellow bathroom lamp concentrations, which are
within 30 min after lights exposure. Nearly the same changes between lighting regimes are reached by
using the mean between the melatonin concentrations 10 min before “lights on” and “lights on” as zero
point (see means and standard deviations in Table 1). This applies both to the analysis of all subjects
and to the analysis including the six subjects with complete data for all lighting conditions. The mean
difference of melatonin concentration between 10 min before “lights on” and “lights on” was
0.68 ± 0.47 pg/mL (range: 0.12 to 1.34 pg/mL per subject).
Int. J. Mol. Sci. 2013, 14 2577
Table 1. Group means and standard deviations of saliva melatonin concentrations. Data are given relative to the zero point representing the
mean of melatonin concentrations in saliva 10 min before and at “lights on”. The first part of the table gives values for the entire sample, and
the second part only for the six subjects with complete data sets.
Pre 60 Pre 30 Mean 10 to 0 min before lights on 10 20 30 Post +10 Post +30
Part 1
Baseline (n = 9) (4.21) ± 1.89 (2.26) ± 1.67 0 0.94 ± 2.47 1.08 ± 2.20 1.525 ± 1.69 3.48 ± 2.34 3.41 ± 1.78
bathroom yellow (n = 9) (4.40) ± 2.68 (2.37) ± 2.04 0 0.93 ± 1.56 1.95 ± 0.64 2.08 ± 1.15 2.075 ± 2.96 4.085 ± 4.26
office daylight white (n = 8) (3.33) ± 2.23 (1.29) ± 1.88 0 1.97 ± 2.90 0.56 ± 1.55 0.56 ± 2.48 0.94 ± 1.57 1.54 ± 2.23
bathroom daylight white (n = 8) (4.05) ± 1.99 (2.03) ± 1.44 0 0.97 ± 1.15 (0.12) ± 1.00 (0.13) ± 1.72 0.62 ± 2.96 2.03 ± 4.28
Planon warm white (n = 9) (3.68) ± 2.94 (1.77) ± 1.98 0 0.41 ± 2.12 (0.43) ± 1.72 (0.91) ± 1.64 (0.83) ± 2.07 0.09 ± 2.83
hall daylight white (n = 8) (2.66) ± 1.12 (1.15) ± 0.76 0 (0.30) ± 1.30 (1.475) ± 1.42 (2.50) ± 2.11 (3.23) ± 4.675 (0.98) ± 6.09
Part 2
n = 6
Baseline (3.40) ± 1.54 (1.88) ± 1.06 0 1.58 ± 1.87 1.42 ± 1.44 1.66 ± 1.92 3.84 ± 2.48 2.67 ± 1.58
bathroom yellow (5.18) ± 2.91 (2.76) ± 2.33 0 0.55 ± 1.80 2.02 ± 0.74 2.29 ± 1.39 1.18 ± 3.30 2.38 ± 3.72
office daylight white (2.96) ± 2.39 (0.97) ± 2.11 0 2.45 ± 3.24 0.37 ± 1.78 0.61 ± 2.94 0.885 ± 1.85 1.24 ± 2.14
bathroom daylight white (4.295) ± 2.07 (2.16) ± 1.65 0 0.58 ± 0.85 (0.11) ± 1.01 (0.505) ± 1.86 (0.535) ± 1.79 0.22 ± 2.47
Planon warm white (2.95) ± 1.43 (0.97) ± 1.31 0 0.98 ± 0.93 0.02 ± 0.69 (0.89) ± 1.45 (0.68) ± 1.17 0.27 ± 1.39
hall daylight white (2.31) ± 1.06 (1.02) ± 0.83 0 (0.26) ± 1.53 (1.29) ± 1.58 (2.09) ± 2.09 (1.69) ± 2.05 1.04 ± 3.60
Int. J. Mol. Sci. 2013, 14 2578
Figure 2. Group means of saliva melatonin concentrations; lines represent the different
lighting conditions. Data are given relative to the zero point that represents melatonin
concentrations at “lights on”. Values on X-axis represent mean differences of melatonin
concentrations to “lights on”.
2.2. Data Analysis
2.2.1. Melatonin Levels in Different Lighting Regimes
Friedman ANOVA was only applied to six of the nine subjects, because the melatonin in saliva data
sets of three subjects were incomplete due to an insufficient amount of saliva in the assays. In the six
subjects with complete melatonin data sets, Friedman ANOVA revealed significant group differences
in melatonin levels during (χ
= 15.5238, p < 0.009) and after (χ
= 18.09524, p < 0.003) light
exposure. In contrast, groups did not differ prior to light exposure with respect to the different lighting
regimes (χ
= 9.04719, p < 0.11), indicating comparable baselines each evening (see Figure 3). Thus,
an order effect induced by the experiment can be ruled out. Two out of three Friedman ANOVAs
showed significant differences between lighting conditions, thereby indicating a high overall
significance (p = 0.0072) of the comparisons.
Regarding the time during light exposure, post-hoc comparisons indicate significant decreases of
melatonin levels during lighting with three of the four lamps including blue components (daylight
white hall, daylight white bathroom, and warm white Planon) as compared to baseline (p < 0.03 each).
The decrease during exposure to daylight white office failed to reach significance (p = 0.07), while the
yellow bathroom showed no effect on melatonin levels. Post–hoc analysis of the time after “lights off”
showed significant (p < 0.03 each) lower melatonin levels for daylight white hall, daylight white
bathroom, and warm white Planon as compared to baseline. Furthermore, AUC of melatonin levels
was diminished following daylight white office (p < 0.05), while no changes following yellow
bathroom could be detected (Figure 3).
Int. J. Mol. Sci. 2013, 14 2579
Figure 3. Melatonin levels before, during, and after light exposure. Areas under curve
(AUC) of melatonin saliva levels before (AUC pre, 30–0 min before lights on), during
(AUC light, 0–30 min after lights on), and after (AUC post, 0–30 min after lights off) the
light exposure. Data are expressed as means ± standard deviation; * p < 0.05 compared to
baseline, n = 6.
2.2.2. Subjective Alertness, Calmness and Contentedness in Different Lighting Regimes
The exploratory analysis of subjective calmness and contentedness did not yield any significant
results. The results regarding subjective alertness are given in Figure 4. There were no significant
differences between the baseline condition and the yellow bathroom condition, nor between baseline
and daylight white office. In contrast, subjective alertness after light exposure was significantly
increased compared to the baseline condition in three of the four lighting conditions that included a
blue portion of the visible spectrum.
Figure 4. Subjective alertness after light exposure. Subjective alertness was measured by
visual analog scales [37]. Data are expressed as means ± standard deviation; * p < 0.05
compared to baseline (Wilcoxon signed ranks-Test), n = 9.
Int. J. Mol. Sci. 2013, 14 2580
2.3. Discussion
The results of the present study show that short-term polychromatic light emitted by conventional
lamps in the evening in a naturalistic setting can suppress melatonin secretion and increase subjective
alertness. It is noteworthy, however, that subjects in our study were exposed to only 30 min of light in
addition to dim light from 7:00 p.m. until midnight. On a descriptive level, these differences begin to
appear after only 20 min of light exposure (see Figure 2).
The explanatory power of the presented data is limited by the small sample size, the non-systematic
selection of lamps, and the merely subjective measurement of behavioral variables. To draw
substantiated conclusions on adverse effects of light regarding health conditions, more lamps with a
systematic variation of light intensity and spectral distribution reflecting the whole range of naturalistic
evening light conditions should be tested on a bigger sample and with additional outcome variables
such as validated vigilance tasks, polysomnographic sleep parameters, or cortisol levels. In our present
sample, the influence of a lamp with no blue component and low light intensity (130 lx) on melatonin
concentrations and on subjective alertness was close to zero (see yellow bathroom lamp in Table 2 and
Figure 5), while melatonin secretion was suppressed by light with equal low intensity but a high blue
component (white bathroom, 130 lx, 6000 K). In addition, all lamps with high (500 lx) light intensities
had a detectable influence on melatonin concentrations after light exposure. Even the lamp with the
lowest blue proportion (warm white Planon, 2000 K) of the high-intensity (500 lx) lights had strong
effects on both melatonin secretion and subjective alertness. The rather low blue component of the
warm white Planon—at this intensity (see Table 3 and Figure 5) and the relatively close distance of
subjects’ eyes to the lamp (1 meter)—seems to be sufficient to cause this effect. The lamp with high
blue component and high intensity (hall daylight white) produces, as expected, even more pronounced
effects. In spite of the high light intensity and high blue component of the daylight white office lamp, it
only reduced melatonin concentrations significantly after, but not during light exposure, and the
increase of subjective alertness was not significant. The values of irradiance or melanopic lux (see
Table 3), a measure that integrates light intensity and spectral distribution in one unit on an empirical
basis [28], would imply a different ranking of the lamps than the amount of their effects in our sample.
Thus, the expected combined influence of light intensity and spectral distribution [37] is not reflected
in detail by our sample. This is probably due to the small sample size, combined with the pronounced
individual differences [30].
Still, in none of the conditions exposing subjects to light containing a high proportion of blue or
bright light was the rise in melatonin levels as large as they were in conditions exposing only to dim or
yellow light.
Nevertheless, subjects varied substantially in the magnitude of melatonin suppression induced by
any one lighting condition. Because all subjects were studied during the same week and exposed to
their assigned lighting condition each evening during the experimental period, light history would only
differ slightly between subjects according to their daytime activities [38]. Chemical agents or
age-related changes in the lens of the eye can be ruled out [39,40]. It might therefore be argued that the
observed differential responses to light have predominantly been due to individual variations in light
sensitivity [41,42]. Experimental data in extreme chronotypes have shown that circadian rhythms
differ in their response to chemical and environmental phase-shifting agents at the cellular level [43].
Int. J. Mol. Sci. 2013, 14 2581
Though only suppression of melatonin as a circadian signal was investigated and not phase shifts of
melatonin, it would be interesting to validate the diagnostic properties of the setting and paradigm used
in the present study. This might help detect circadian rhythm sleep disorders by determining patients’
sensitivity to melatonin suppression by light. Regarding future research, it also seems worthwhile to
think about potential long-term consequences. Though still not generally accepted, several studies
suggest that melatonin in humans plays a similarly pivotal role to that already demonstrated in
animals [44,45]. Low melatonin is associated with numerous diseases [46], such as cancer [17],
and melatonin concentrations are reduced in the elderly [47], in patients with chronic primary
insomnia [48–50], and even more so in patients suffering from Alzheimer’s dementia [51,52]. Even the
neuroprotective properties of melatonin receive increasing evidence [53]. It is also well established
that the increase in melatonin levels that occurs in the evening facilitates sleep induction [54–56].
Thus, it is tempting to speculate that melatonin suppression by artificial light during the evening plays
a role in the sleep-related problems from which millions of individuals currently suffer. Nevertheless,
the general causal relations of light, melatonin-levels, and the health conditions mentioned above still
need to be determined.
The current study demonstrates that light affects not only melatonin levels, but also subjective
alertness. However, this is thought to rely on a different pathway than the retinal–pineal pathway. As
an fMRI study suggests, light directly activates cortical networks that underlie alertness [57]. This
relationship requires further investigation with objective measurements.
Diurnal species such as humans are obliged to use their eyes to find their way about the world.
Unlike nocturnal species like rats or bats, humans are at the mercy of their enemies when moving
about during the nighttime hours. It is most likely for this reason that the CTS promotes motor
inactivity and sleep during this period [4]. Although artificial light at night is clearly of great benefit to
society, its inappropriate timing might alter human physiology. In December 2007, the World Health
Organization added overnight shift work to its list of probable carcinogens [58]. One possible, but yet
to be proven, cause of cancer in overnight shift workers is the reduction of nighttime melatonin
resulting from exposure to artificial light. The results of the present study raise a question that should
be addressed in detail by future research: do we all suffer from these effects to some degree due to
nighttime exposure to blue and/or bright light?
3. Experimental Section
The study was performed in the sleep laboratory of the Institute of Physiology at the Charité in the
Sankt Hedwig Hospital, Berlin, in February of 2007. The protocol was approved by the local ethics
committee. Experimental procedures were conducted in accordance with the Declaration of Helsinki,
and all participants gave their written, informed consent.
A total of 9 healthy subjects (3 women, 6 men, aged 22–33 years, mean = 26.3, SD = 4.2)
participated in the study. Subjects were recruited by word-of-mouth recommendation and received
pecuniary compensation. Medical, psychiatric, and sleep assessments were performed, including
evaluations of sleep quality (Pittsburgh Sleep Quality Index, or PSQI [59]), of chronotype (Horne and
Östberg [60]), and of seasonality (Seasonal Pattern Assessment Questionnaire, or SPAQ [61]). The
inclusion criterion was a habitual bedtime between 10:00 p.m. and 1:00 a.m. (PSQI: Item 1—“When
Int. J. Mol. Sci. 2013, 14 2582
did you habitually go to sleep during the last four weeks?”). Exclusion criteria were age <18 or >35;
current pregnancy; current or recent shift work (during the last year); poor sleep hygiene (sleep log or
actigraphic proof of a more than 1-h deviation from habitual bedtime during a 7-day entrainment
period); definite morning or evening types; seasonality score greater than 5; transmeridian travel
(during, or within 1 month of, the study); any psychiatric, medical, or sleep disorder, including drug or
alcohol abuse; and the intake of any medication, including over-the-counter medication, over the
past month.
During a 7-day entrainment period, subjects were asked to keep a regular sleep–wake schedule with
a tolerance range of ± 60 min of their self-estimated habitual bedtime. Compliance was monitored
using a sleep log and actimetry (Actiwatch, Cambridge Neurotechnology).
During the 6-day experimental phase, we tried to create conditions that were as natural as possible:
subjects followed their habitual daytime schedules, only attending the laboratory in the evening hours
from 7 p.m. until midnight (monitored by sleep log and actimetry). Subjects were allowed to eat until
7 p.m. and to drink caffeinated beverages until 3 p.m. Alcoholic beverages were forbidden during lab
days. Drinking water was accepted until 10 min prior to saliva collection. Subjects spent their time in
the laboratory pursuing self-chosen activities (e.g., playing games, talking, watching videos on a
dim-light screen) in a dimly lit room (<10 lx) by ordinary dimmable halogen lamps. Because circadian
phase is associated with habitual bedtime, light exposure was timed individually to occur 1 h before
habitual bedtime [62].
Table 2. Study design.
Group Day 1 Day 2 Day 3 Day 4 Day 5 Day 6
I Baseline: hall lighting office lighting bathroom bathroom Planon
II office lighting bathroom bathroom Planon hall lighting
II bathroom bathroom Planon hall lighting office lighting
daylight white warm white yellow
During evening 1, subjects were exposed only to dim light (baseline condition). During evenings 2
through 6, everyday lamps of different types (office, bathroom, industry), with two different intensities
(130 vs. 500 lx at the cornea) and spectral distributions (4 with various and 1 without blue portions)
were used to expose subjects, in randomly assigned groups of 3, to each lighting condition for a total
of 30 min (for study design, see Table 2; for a detailed description of the lamps, see Table 3 and for
their spectral distributions, see Figure 5). Three of the lamps were selected by their original application
as examples to reflect naturalistic lighting conditions as occurring in bathrooms (bathroom daylight
white), office work places (office daylight white) and industrial work places or gyms (hall daylight
white). Two of the lamps were custom-made to produce: (1) a zero blue component bathroom light
situation (bathroom yellow); and (2) a low blue component but high light intensity work place light
situation (Planon warm white).
Int. J. Mol. Sci. 2013, 14 2583
Table 3. Lighting conditions.
No. lamp name
Type Model
Eye (cm)
0 baseline
(dim light) <10 normal
pointing to
ceiling 150 cm
1 bathroom
yellow 130 2000 0.319 118 fluorescent Custom-
made zero wall over
mirror 100 cm Narva
130 6000 0.385 581 fluorescent 6641
L18/W high wall over
mirror 100 cm Narva
500 6000 1.437 2069 fluorescent
(3 pieces)
54W/860 high ceiling 150 cm
4 hall daylight
white 500 5000 1.391 1724 metal
halogenid NCT 70W high ceiling 150 cm
5 Planon warm
500 2800 1.432 1826 dielectric
made low wall 100 cm Osram
The unit melanopic lux (lx
) was recently suggested by al Enezi et al. to predict the sensitivity of melanopsin
photoreceptors to polychromatic light [28]. It was derived from action spectra of monochromatic lights in several species;
Due to reflection, the whole visual field was exposed with a maximum in the center;
The Planon is an advanced
prototype dielectric inhibited light source. It is being developed by Osram, Munich. So far, more than 150 lamps have
been built. It is currently being used as a rugged light source in CNC Machines.
Figure 5. Spectral distributions. Numbers represent the lamps as follows: 1. bathroom
yellow; 2. bathroom daylight white; 3. office daylight white; 4. hall daylight white;
5. Planon warm white.
Int. J. Mol. Sci. 2013, 14 2584
During light exposure, subjects were sitting at an assigned spot and were instructed to keep their
gaze straight (at approximately 90°) over the 30-min light exposure. No other activity was permitted
except talking. Subjects were informed that bright light may suppress melatonin; no information was
given regarding the effects of light spectrum. Lighting conditions were characterized using a luxmeter
(LMT Berlin), a spectrometer (StellarNet EPP-2000), and a luminance camera (LMK Mobile
Advanced, Ilmenau). Light intensity and spectral distribution were determined for each lamp at the site
of the experiment from the position of subjects’ eyes, i.e., in the direction and angle of the gaze
(performed by INP, Greifswald, Germany).
Each evening during the study period, self-assessment of alertness, calmness and contentedness was
performed every 30 min using a paper and pencil version of visual analogue scales [63]. The VAS
assessment at the start of light exposure was brought forward by 5 min to avoid disturbing the
exposure procedure. In addition, saliva was collected with salivettes every 30 min during dim-light
exposure, as well as 10 min before, every 10 min during, and 10 min after light exposure. Saliva
collection never took more than one minute. Melatonin concentration in saliva was determined by a
commercial radioimmunoassay (Bühlmann Laboratories, Allschwill, Switzerland) with an analytical
least detectable dose of 0.15 pg/mL, intraassay precision: 6.7% (range: 4.9%–8.8%), interassay
precision: 10.4% (range: 8.5%–13.9%).
As a consequence of the design, subjects’ bedtimes were slightly delayed during the experiment, as
they still needed to get home after midnight. We tried to rule out possible order effects by using a
crossover design and by also controlling for differences between lighting conditions and light
exposition (see results section for details).
Statistical Analysis
In order to calculate descriptive group differences, the reference point for differential melatonin
levels was set to zero for each individual: (1) at time of “lights on” (see Figure 2); and (2) at the mean
of 10 min before “lights on” and “lights on” (see Table 1). For statistical analysis, melatonin
concentrations were calculated as areas under the curve (AUC) before, during, and after light exposure.
AUC before light exposure (AUC pre) included 30 to 0 min before “lights on,” based on
20- and 10-min intervals. AUC during lighting (AUC light) included 10 to 30 min after “lights on,”
based on 10-min intervals. AUC after light exposure (AUC post) included 0 to 30 min after “lights
off,” based on 10- and 20-min intervals. Friedman ANOVAs were calculated for each AUC (pre, light,
and post), followed by post–hoc Wilcoxon-tests. Friedman ANOVAs were alpha-adjusted using the
method of Cross and Chaffin [64]. Three subjects had to be excluded from statistical analysis of
melatonin levels due to single missing data caused by incorrect saliva collection.
For explorative purposes, subjective alertness was compared between baseline and the various
lighting conditions using Wilcoxon signed-rank test.
4. Conclusions
Low-intensity light emitted by everyday lamps in a naturalistic setting can influence melatonin
levels and alertness perception in healthy human subjects after only 30 min. The suppressive effect of
this light exposure on melatonin can be minimized by using a yellow lamp without blue component.
Int. J. Mol. Sci. 2013, 14 2585
The order of the other lamps in the degree of influence on alertness and melatonin concentrations in
our sample is not completely as expected, which could be due to the small sample size. It should be
replicated with bigger sample sizes, also including further outcome variables such as sleep parameters
and objective measures of behavioral variables. This could highlight the impact of evening light on
adverse health outcomes in more depth. Still, even with this small sample size, the melatonin
suppressing and alertness enhancing power of short exposition to ordinary lamps in contrast to dim
light or yellow light without blue component could be shown in this study. We suggest that potentially
adverse biological effects of untimely light exposure could be reduced or avoided by appropriate
tuning of the spectral content and intensity of lighting devices, similar to the way lamps with specially
designed spectral distributions can be used therapeutically in order to relieve various conditions. To
put it—albeit tentatively—in a nutshell: filter out blue or dim the light when you go brush your
teeth at night!
This study was funded by BMBF (German Ministry for Education and Research) FKZ: 13N8973.
We thank the BMBF for their support.
Conflict of Interest
The authors declare no conflict of interest.
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... Occupants' action over lighting systems and shading devices was used as a predictor in those studies grouped under the category "Lighting and blinds control" [43,80,82,86,88,105]. The category "Lighting type" embodies different types of predictors, from studies examining natural vs. artificial light to dynamic vs. static lighting [37,63,65,70,71,95]. "Window features" is a broad category, which includes studies dealing with the window view, type of shadings and glazing, window area and windowed vs. windowless rooms [30,32,43,45,51,58,62,72,[92][93][94][99][100][101]104]. ...
... Twenty-four studies reported the use of questionnaires and scales for assessing alertness/sleepiness -mainly through the Karolinska and Epworth Sleepiness Scales- [33,34,38,40,46,53,57,62,69,70], for reporting mental effort and work load [51,57,70], mental health and stress [45,74,103], subjective wellbeing and quality of life [30,45,57,62,74,77,102], and some symptoms, such as muscular ache, headache, eyestrain and fatigue [46,50,51,55,65,70,74,87,90,96]. In 17 studies, the emotional state was assessed through affective tests [31,37,47,52,87,98,102], self-reported mood assessments and mood rating inventory [31,34,38,40,[46][47][48][55][56][57]73,75,94]. ...
... In 17 studies, the emotional state was assessed through affective tests [31,37,47,52,87,98,102], self-reported mood assessments and mood rating inventory [31,34,38,40,[46][47][48][55][56][57]73,75,94]. Effects of lighting were analyzed through melatonin and cortisol by measuring hormones secretion or concentration using salivary or urinary samples [40,44,46,54,57,65,73,75,95,102] or other physiological responses as heart rate [44,51], brain activity [44,87], pupil size and eye fatigue [56,97], and body temperature [100,101]; while monitoring devices were used to track circadian entrainment and motion, mainly during sleep [37,62,67]. ...
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... There are several health concerns that have been associated with digital technology and media use influence and affect. First, technology and media use has been shown to negatively affect sleep by delaying bedtime as well as through exposure to light from screens disrupting melatonin levels [4][5][6]. Second, decreased physical activity has been associated with the sedentary nature of most media use [5,7,8]. Third, PIU is defined as "Internet use that is risky, excessive or impulsive in nature leading to adverse life consequences, specifically physical, emotional, social or functional impairment" [37]. ...
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Media use among early adolescents is nearly ubiquitous and has been associated with important health outcomes such as physical activity, sleep and problematic internet use (PIU). Parent involvement has been recommended as a prevention strategy; it remains unclear how it is associated with media use and health outcomes. The purpose of this study was to develop profiles of media use, parent involvement and health outcomes among adolescents. Early adolescents were recruited to a cross-sectional online survey using the Qualtrics platform and panels. Media use measures included ownership and bedroom use of devices, social media platforms and video games. Parent media involvement assessed media rules and role-modeling. Health measures included physical activity, sleep and PIU. We used latent class analysis (LCA) to identify distinct profile groups across these three areas. The 1155 participants had a mean age of 13.6 years (SD = 1.1), of whom 49.7% were female, 73.7% were White and 61.1% had parent education with a college degree. We found that most participants owned personal media devices, including smartphones (81.4%), computers (64.6%) and video game systems (58.9%). The LCA identified three distinct profile groups: (1) Active Autonomous Media Users, (2) Young Low-Tech Sleepers and (3) Risky Regulated Media Users. Findings support that media use patterns vary across adolescents, suggesting different education and prevention approaches may be needed. Targeting educational messages to different media profiles may be an effective strategy to optimize productive media use and health.
The article is devoted to the description of experimental studies on the assessment of the hygienic efficiency of lighting conditions with light emitting diodes (LEDs) of the first and second generations when performing industrial work. In the course of the research work, an experimental lighting installation (ELI) was developed and installed, able to implement lighting options with LEDs and fluorescent lamps (FL). The state of the accommodative-muscular apparatus, the retina and the central link of the organ of vision was assessed; integral indicators of visual performance were studied. It was found that the illumination with LEDs does not have a negative effect on the organ of vision, the human body as a whole or indicators of visual performance. Changes in the functional indicators of the organ of vision occurring during the performance of visual work are within the corresponding boundaries of physiological fluctuations and are reversible. It was revealed that second generation LEDs create a more favourable light environment for performing visual work of a production nature. The practical significance of the results obtained was shown.
Digital media, including social media, has fundamentally changed how the human species communicates with, relates to, and influences one another. Adolescents use digital media extensively. Researchers, scholars, teachers, parents, and teens themselves have many questions about the effects of digital media on young people's psychological development. This handbook offers a comprehensive synthesis of scientific studies that explain what we know so far about digital media and its effects on youth mental health. With chapters from internationally renowned experts in the fields of psychology, psychiatry, media, and communications, the book offers a broad overview of the positive and negative implications of youths' engagement with digital media for brain development, relationships, identity exploration, daily behaviors, and psychological symptoms. Chapters include a discussion of the current state of knowledge, directions for future research, and practical suggestions for parents, educators, and teens themselves. This title is also available as Open Access on Cambridge Core.
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This paper reviews 49 studies that addressed how window view, daylighting, and lighting in buildings affect occupants’ behavior and well-being. The systematic literature search was performed in November 2021 and focused on office and educational buildings. We quantified the number of papers per study type, study aim, and lighting condition. Predictor categories and methods for data collection were also considered. We analyzed the results according to a structure of records, defined by the number of predictors and type of outcomes from a study. We obtained 106 records. A gap in the number of studies under different lighting conditions and building types was identified. Studies under natural light and studies conducted in learning environments were fewer than studies dealing with artificial lighting in offices. A wide variety of methods for data collection was found. Artificial lighting features and correlated color temperature were the most used predictors. Based on the analysis of records, we found that 61.3% of the associations between predictors and outcomes were statistically significant. The type of effect was not reported in 3.8% of the records-meaning that approximately 35% of the records found no significant associations between predictors and outcomes.
A substantial portion of critical adolescent development is occurring within digital environments. However, certain individual differences may lead adolescents to use digital media in diverse ways. In this chapter we suggest that the way teens use digital media influences how digital media affects their mental health. Further, we propose a model in which these influences, in the context of ongoing development, may have feedback effects on how digital media is subsequently used, thus resulting in a self-perpetuating cycle. Our model suggests that certain developmental risk/protective factors and maladaptive/adaptive digital media behaviors likely perpetuate each other in a cyclical manner each serving to maintain and/or escalate the other. We discuss existing evidence of these processes in psychosocial, identity, incentive processing, and physical health development. Future research focusing on individual differences and self-reinforcing digital media behaviors that manifest these feedback loops may portray a more complete picture of cascading digital media influences across adolescent development.
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Biologically, effectively regulated light with a wavelength of about 485 nm can support physiological processes in the body and has a positive impact on the human sleep–wake rhythm. However, the application of common light therapy devices is not always practicable and sometimes difficult to integrate into everyday life. Here, miniaturization of therapy devices, for example, in the form of contact lenses, can reduce the handling disadvantages. Especially, contact lenses modified with phosphorescence materials offer this benefit. Herein, a method to prepare phosphorescent Eu2+, Dy3+‐doped strontium aluminate nanoparticles (NPs) by laser vaporization of macroscopic Eu2+, Dy3+‐doped Sr4Al14O25 particle powder and their integration into polymer‐based contact lenses is provided. NPs with a diameter of about 34 nm emit light in the desired therapeutic wavelength region. These novel NPs are biocompatible and do not show any negative effects during the testing of eye irritation safety in a 3D in vitro cornea model. Phosphorescent lanthanide‐doped strontium aluminate nanoparticles (NPs) are prepared by laser vaporization of a macroscopic powder and integrated into contact lenses to apply for the light therapy of winter depression or sleep disorders. Novel NPs are biocompatible and do not show any negative effects during the testing of eye irritation safety in a 3D in vitro cornea model.
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The pineal gland participates in the internal temporal organization of the vertebrate organism by the rhythmic synthesis of its hormone melatonin. This hormone is considered the darkness hormone because of its unique feature of being synthesized exclusively at night, regardless of the organism activity pattern. The presence and absence of this indolamine help to mark, respectively, dark and light time, i.e., night and day, to the organism. Moreover, the daily duration of the secretory episode of melatonin, synchronized to the duration of the night in the environment, times the several physiological regulatory processes in order to adapt the organism to the annual seasonal environmental variation. The mechanisms of melatonin production are different among the several classes of vertebrates. In fishes, amphibians, some reptiles and birds, the pineal gland is photosensitive, whereas in mammals the photosensitivity is absent. In this case, the light periodical information is conveyed to the gland through a neural pathway that originates in the retina, projects to the hypothalamic suprachiasmatic region, including the suprachiasmatic nuclei (the circadian biological clock in vertebrates) and, then, indirectly to the pineal gland. The signal that stimulates melatonin synthesis during the dark period of the daily light/dark cycle, in mammals, is the neurotransmitter noradrenaline, which is released from the sympathetic terminals of neurons whose cell body are located in the superior cervical ganglia. This transmitter interacts with adrenoreceptors in the pinealocytes membrane, resulting in cAMP and calcium elevation that induces melatonin synthesis. The signaling cascade that involves cAMP triggers and/or increases the arylalkylamine N-acetyltransferase transcription and translation, as well as its activation by phosphorylation and association with 14-3-3 protein. This enzyme converts serotonin into N-acetylserotonin that is then transformed by hydroxyindole-O-methyltransferase into melatonin. These two steps occur only at night. Melatonin, immediately after being synthesized, is released to the systemic circulation and it influences almost every physiological function in the organisms. It regulates the circadian clock, rest-activity and wake-sleep cycles, immunological system, energy metabolism and many other functions. Melatonin also influences the seasonal rhythms through the variation observed in its plasmatic profile duration according to the length of night. Among the seasonal physiological functions modulated by melatonin are reproduction, immune response, and metabolic adaptations and weight. Melatonin is an ancestral molecule as it appears soon in the evolutionary chain and it is ubiquitous in the living organisms. It seems that early in evolution melatonin could have had an anti-oxidative role, protecting the primitive life from the possible oxidation process mainly dependent on light and aerobiosis. This property is still conserved by its intracellular direct interaction with other molecules involved in oxidation. Besides, melatonin has its proper receptors, known as MT1, MT2 and MT3 which are found in the central nervous system and peripheral organs. Thus, melatonin is part of a photo-neuroendocrine temporal system, which adapts the organisms to the external environmental cyclic fluctuations, like day and night and the seasons, regulating most of the physiological regulatory processes, including insulin synthesis and action, playing a putative role in the pathophysiology of diabetes mellitus.
The interaction of homeostatic and circadian processes in the regulation of waking neurobehavioral functions and sleep was studied in six healthy young subjects. Subjects were scheduled to 15–24 repetitions of a 20-h rest/activity cycle, resulting in desynchrony between the sleep-wake cycle and the circadian rhythms of body temperature and melatonin. The circadian components of cognitive throughput, short-term memory, alertness, psychomotor vigilance, and sleep disruption were at peak levels near the temperature maximum, shortly before melatonin secretion onset. These measures exhibited their circadian nadir at or shortly after the temperature minimum, which in turn was shortly after the melatonin maximum. Neurobehavioral measures showed impairment toward the end of the 13-h 20-min scheduled wake episodes. This wake-dependent deterioration of neurobehavioral functions can be offset by the circadian drive for wakefulness, which peaks in the latter half of the habitual waking day during entrainment. The data demonstrate the exquisite sensitivity of many neurobehavioral functions to circadian phase and the accumulation of homeostatic drive for sleep.
Conference Paper
Data on the circadian melatonin secretion in sleep disordered patients and effects of sleep medication on melatonin are still missing. We studied plasma melatonin concentration, sleep, and effects of some hypnotics in 15 patients and 10 controls. Nocturnal melatonin levels were significantly decreased in patients with a more than five years history of sleep complaints compared to controls or patients with a shorter duration of illness. Independent of their sleep promoting properties drugs increased or decreased nocturnal melatonin in controls and patients. Patients with chronic sleep-wake rhythm disorders showed altered relations between their circadian melatonin secretion pattern and sleep. We conclude that nocturnal melatonin secretion is primarly independent of sleep regulation but represents a neuroendocrine feature of chronically disturbed sleep.
Background: Although the epidemiology of insomnia in the general population has received considerable attention in the past 20 years, few studies have investigated the prevalence of insomnia using operational definitions such as those set forth in the ICSD and DSM-IV, specifying what proportion of respondents satisfied the criteria to reach a diagnosis of insomnia disorder. Methods: This is a cross-sectional study involving 25,579 individuals aged 15 years and over representative of the general population of France, the United Kingdom, Germany, Italy, Portugal, Spain and Finland. The participants were interviewed on sleep habits and disorders managed by the Sleep-EVAL expert system using DSM-IV and ICSD classifications. Results: At the complaint level, too short sleep (20.2%), light sleep (16.6%), and global sleep dissatisfaction (8.2%) were reported by 37% of the subjects. At the symptom level (difficulty initiating or maintaining sleep and non-restorative sleep at least 3 nights per week), 34.5% of the sample reported at least one of them. At the criterion level, (symptoms + daytime consequences), 9.8% of the total sample reported having them. At the diagnostic level, 6.6% satisfied the DSM-IV requirement for positive and differential diagnosis. However, many respondents failed to meet diagnostic criteria for duration, frequency and severity in the two classifications, suggesting that multidimensional measures are needed. Conclusions: A significant proportion of the population with sleep complaints do not fit into DSM-IV and ICSD classifications. Further efforts are needed to identify diagnostic criteria and dimensional measures that will lead to insomnia diagnoses and thus provide a more reliable, valid and clinically relevant classification.
Often in the social and behavioral sciences, several individual tests of significance are used to determine whether some common or overall hypothesis should be rejected. Thus, it becomes necessary to interpret r significant results out of n tests. Many authors contend that one or more significant results should be interpreted as an overall significant result for the set of tests. The authors of this work suggest that a more appropriate approach would be to use the binomial theorem to compute the probability that r or more Type I errors would occur when all n of the null hypotheses are true, and use this result as the level of overall significance a*. It is shown that in the independent test situation, it is possible to set an action limit r for rejection of the overall hypothesis based on some required overall level of significance a*. In addition, an upper limit is obtained for a* when r significant test results are used to reject a set of n hypotheses when the tests are dependent to an unknown extent.