SLEEP 2011 Abstract Supplement

B. Clinical Sleep Science XIV. Instrumentation and Methodology
0942
THE IMPACT OF BLUE LIGHT ON ACUTE MELATONIN
SUPPRESSION: IRRADIANCE AND DURATION
RELATIONSHIP
Rea MS, Figueiro M
Lighting Research Center, Rensselaer Polytechnic Institute, Troy, NY,
USA
Introduction: The spectral sensitivity of melatonin suppression peaks
close to 450 nm. A model of human circadian phototransduction was developed
based on the neuroanatomy and neurophysiology of the human
retina. This model has been used to successfully predict acute melatonin
suppression of polychromatic light sources. The present study is aimed
at providing a further, a priori test of the model using a previously described
personal light delivery device. In addition, a more accurate estimate
of threshold for human circadian phototransduction is provided.
Methods: Each of 11 healthy adults (age 50 or older) experienced seven
lighting conditions (dark, 0.7, 2, 7, 11, 20 and 65 microwatts/cm2) of
470-nm light. Blood and saliva samples were collected for 110 minutes.
The first two samples were collected 10 minutes apart while subjects
remained in the dark, after which the 470-nm light goggles were energized.
During the first 30 minutes after lights were turned on, blood
samples were collected every 10 minutes and saliva sample collection
was interleafed five minutes after each blood sample collection.
Results: Melatonin concentrations from both fluids were normalized
and a 2 x 2 ANOVA (7 lighting conditions x 14 sample times) were
performed. Results were consistent with model predictions. Threshold
for melatonin suppression was between 0.7 and 2 microwatts/cm2 and
significant suppression was observed only after 15 minutes of exposure
to the highest irradiance.
Conclusion: A priori predictions of acute melatonin suppression can
be made using the model of human circadian phototransduction. Much
lower levels of 470-nm light can suppress nocturnal melatonin. Implications
for clinical applications include more confortable, less bright, and
flexible light treatment delivery device.
Support (If Any): NSF-EEC-0812056 and NYSTAR-C090145
0943
NEW TOOLS TO MEASURE LIGHT EXPOSURE, ACTIVITY
AND CIRCADIAN DISRUPTION IN OLDER ADULTS
Figueiro M, Rea MS
Lighting Research Center, Rensselaer Polytechnic Institute, Troy, NY,
USA
Introduction: Sleep disturbances in older adults may result from lack
of entrainment to the 24-hr day-night cycle due to low circadian light
stimulus experienced by older adults. Clinicians will not embrace light
treatment, such as blue light, until the relationships between sleep disturbances,
circadian disruption and light exposures are established in the
field. Several practical measurement problems exist for obtaining human
circadian light-exposure data as they might relate to quantifying
circadian disruption in older adults.
Methods: Each of 18 healthy older adults (age 65 or older) wore a Daysimeter,
three Dime-simeters and a commercially available wrist actigraph
for seven consecutive days; all devices measured activity as well
as light. Saliva samples were collected every 4 hrs. The Daysimeter is a
head-worn device that places a calibrated red-green-blue (RGB) sensor
package near the plane of the person’s cornea. The Dime-simeter also
contains a calibrated RGB sensor package, but is dime-sized and can be
worn as a pin, a pendant, attached to glasses, and on the wrist.
Results: Phasor analysis was applied to the light and activity data from
each device to quantify circadian entrainment. Like healthy young
adults, but in contrast to persons with Alzheimer’s disease, healthy
older adults have high phasor magnitudes, suggesting a good circadian
entrainment. The phasors obtained with the different devices were cor-
related despite the significant differences in the absolute levels of light
recorded by the different devices.
Conclusion: The Daysimeter and Dime-simeter are tools that can be
used to accurately measure light exposures as they affect the circadian
system and can quantify circadian entrainment in older adults. The next
step will be to deploy these devices among people with and without
sleep disorders to determine if measured circadian disruption is related
to sleep disturbances in older adults.
Support (If Any): U01DA023822 and R01AG034157
0944
COMPARISON OF AN AMBULATORY SLEEP-STAGE
RECORDER WITH OUTPATIENT ACTIGRAPHY AND SLEEP
LOGS ACROSS A WIDE RANGE OF SLEEP PHENOTYPES
Curtis BJ, Walker KA, Jones CR
Neurology Department and Sleep-Wake Center, University of Utah,
Salt Lake City, UT, USA
Introduction: Wrist actigraphy (ACT) and sleep logs (SL) are validated
techniques for estimating habitual sleep timing outside the laboratory.
In 2009, Fabregas et al demonstrated reasonable agreement between a
commercially available wireless sleep-stage recorder (“Zeo”) and both
inpatient polysomnography and inpatient ACT in 10 healthy participants.
Here we report the results of a 10-day outpatient protocol using
this wireless system (WS), ACT, and SL in participants with a wide
range of sleep phenotypes.
Methods: Seventeen participants (11 female; ages 25-75; mean=51)
completed the protocol. Sleep phenotypes were determined by CRJ using
questionnaires and structured telephone interviews: Delayed Sleep
Phase Syndrome (n=1); Sighted Non-24-Hour Sleep-Wake Syndrome
(n=1); Narcolepsy (n=1); Advanced Sleep Phase Syndrome (n=2); Conventional
Sleepers (n=5); Short Sleeper Syndrome (n=7). ACT data
were collected using the Phillips Respironics Actiwatch-L (n=10) and
Ambulatory Monitoring Inc. MicroMini-Motionlogger. Total sleep time
(TST), initial sleep onset (ISON) and final sleep offset (FSOFF) were
scored automatically using Actiware-Sleep 3.4 and Action-W 2.0 software.
TST, ISON and FSOFF were scored automatically by the WS using
an artificial neural network. Participants estimated daily ISON and
FSOFF by SL. Correlation coefficients (r) between the WS and both
ACT and SL for TST, ISON, and FSOFF were calculated across all 134
participant-nights.
Results: There was a wide range of average TST, ISON, and FSOFF
across all six sleep phenotypes by conventional, well-validated ACT:
TST=287-484 min; ISON=15:26-03:58; FSOFF=04:32-18:44. The WS
correlated well with ACT and SL: WS/ACT TST r=0.75; WS/SL TST
r=0.74; WS/ACT ISON r=0.99; WS/SL ISON r=0.92; WS/ACT FSOFF
r=1.00; WS/SL FSOFF r=0.93. Over all 134 participant-nights, WS estimated
a lower TST relative to both ACT and SL: WS average TST=369
min; ACT average TST=396 min; SL average TST=425 min.
Conclusion: Ambulatory WS TST was moderately correlated with TST
from conventional, well-validated ACT and SL measures across both
genders and a wide range of ages and sleep phenotypes. Further research
is needed to determine whether the lower WS TST relative to ACT and
SL is a measure of its ability to detect wakefulness during sleep.
Support (If Any): NIH R01HL059596: Principle Investigator Louis
J. Ptacek; Co-Investigator Ying-Hui Fu, University of California, San
Francisco, CA, USA. NIH R01HL080978: Jeanne F. Duffy, Harvard
Medical School, Division of Sleep Medicine, Boston, MA, USA
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SLEEP, Volume 34, Abstract Supplement, 2011