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Does Illumination From Computer Screen Disrupts Sleep and Biological Rhythms?

2016-11-08 09:23:21 | BioPortfolio

Summary

Light exposure is on the rise in recent years. In large part because of unintentional illumination from screens that emit light directly into the eyes. Millions of computers, tablets, TVs, and smart-phones are sold worldwide every month and the usage time of these devices is increasing constantly. Today, people are exposed to ongoing light exposure from these device screens, emitting short wave length (SWL) during day and night hours, whether as active or passive users. In sum, artificial light at night (ALAN) seem to affect human circadian rhythmicity (melatonin and thermoregulation) and sleep, with two major factors. First, wavelength of light, with SWL being most detrimental to sleep and rhythms, when compared to LWL (Brianard et al., 2001). Second, a dose-response relationship exists between increasing light intensity and poorer sleep/circadian rhythms (Brianard et al., 1988; West et al., 2011).

Based on existing knowledge, we hypothesize that when compared to long wavelength LWL illumination, short wavelength SWL illumination from computer screen will have a more damaging effect on MLT production and secretion, interfering body temperature regulation and affecting sleep quality, efficiency and sleep architecture. In addition, we hypothesized that intensity of the screen illumination will play another important factor on these outcomes, we assume that high intensity compared to low intensity will have more damaging effect on: melatonin, thermoregulation and sleep.

Description

Methods:

Participants Participants were between the ages of 20 and 45 years, with BMI 18-25, regular sleep habits in Pittsburgh Sleep Quality Index (PSQI) questionnaire index<5 (Buysse et al., 1989, Shochat et al., 2007), and a normative sleep-wake cycle type (Horne-Ostberg morningness-eveningness questionnaire (Horne & Ostberg, 1976, Lavie & Segal, 1990) measured Sleep quality and continuity were measured for one week using actigraphy with compatible decoding software (Respironics Model II, Philips, Inc). Only participants with 6-8 hours of sleep, normative sleep patterns, and no sleep/wake schedule problems proceeded to the experimental phase of the study stage. Participants were healthy with no history of medical, neurological, sleep disorders (confirmed by polysomnography) or psychiatric conditions and no medication intake (excluding contraceptives for female participants). Participants with ocular damage, such as to their field of vision, color blindness, or impaired functioning of the pupil in reaction to light were excluded, however use of eyeglasses or contact lenses to correct vision was allowed. Participants signed informed consent prior to participation in the study. The study was approved by the Helsinki Committee of Assuta Medical Center and Maccabi Health Services.

Measurements

Three physiological measures were collected in the study:

Polysomnography: The sleep testing room was a standard test room at the Sleep Medicine Research Center at Assuta Medical Center. Standard in-lab polysomnography was conducted using the Somnoscreen-PSG type sleeping test instrument (Somnomedics, Germany). Sleep channels included: electroencephalography (EEG), electro-oculography (EOG), leg and chin electromyography (EMG), nasal breathing, chest breathing, diaphragm breath, snoring, electro-cardio-graphy (EKG), heart rate, blood oxygen saturation, and body position. Sleep data processing was performed by skilled and trained sleep technicians in accordance with of the Rechtschaffen and Kales criteria (1968). Sleep continuity parameters: latency to stage 1 (SL1) and stage 2 (SL2), percent wake after sleep onset (%WASO), index of awakenings, total sleep time (TST), time in bed (TIB), and sleep efficiency (SE). Sleep architecture parameters: percent stage 1 (%S1), stage 2 (%S2), REM (%REM), and SWS (%SWS), index of sleep stage changes and REM onset latency (ROL).

Melatonin: Urine samples were collected for analyzing melatonin levels by measuring 6-sulfahydroxymelatonin (6-SMT) concentration, the major metabolite of the hormone in urine (de Almeida et al., 2011). The quantitative determination of 6-SMT in urine was completed by a solid phase enzyme-linked immunosorbent assay (ELISA # RE54031; IBL, Hamburg; Germany) as described previously (Zubidat & Haim, 2007). 6-SMT concentrations (ng/mL) were spectrophotometrically determined by ELISA microplate reader at 450 nm with reference wavelength 650 nm (PowerWave HT, Biotek, Winooski; USA) and analyzed by Gen5TM Data Analysis Software (Version 2, Biotek, Winooski; USA).

Urine samples were collected on all four days of the experiment at three time points: 21:00, 23:00 and at wake time. All urine samples were frozen (-20OC) immediately after collection. Melatonin was then analyses and secretion parameters were estimated. As the first morning sample concentration of 6-SMT has been extensively used as an estimate of overnight melatonin secretion (McMullan et al., 2013), we used this sample to represent the maximum (100%) MLT secretion per participant. The night samples (at 21:00 and 23:00) were transformed using the formula value at 21:00 or 23:00 /value in wake time *100 to reflect the percentage change in MLT secretion per participant.

Temperature: Oral temperature was measured using an electronic oral thermometer (Domotherem, UEBE Medical GMBH, Germany).

Procedure:

Recruitment ads were placed in social network websites stating basic inclusion criteria and study details. Interested persons were initially interviewed via phone to rule out major exclusion criteria (e.g. age, general health, and sleep patterns). Persons who were eligible and interested in participating were invited to the sleep laboratory at Assuta Medical Center (Tel Aviva, Israel) for in-lab screening. At the screening visit, all participants signed informed of consent and filled out intake questionnaires, including demographic and health questionnaires, PSQI, and the Horne-Ostberg questionnaire). Participants then received an actigraph for one week to assess the quality and quantity of their sleep and sleep wake patterns and schedules.

Following the home screening, participants were scheduled for four in-lab testing nights across two consecutive weeks. Participants were always scheduled on Sunday and Wednesday nights for each week. For the duration of the 2-week experimental period, all participants were requested to sleep in accordance with their normal sleep schedule, both at home and at the laboratory.

A repeated measures design was used, with two independent variables: screen luminance (or light intensity emitted from the screen) and light wavelength. The first, luminance at two levels: low - 80 lux (35mw/cm2) and high - 350 lux (160mw/cm2). The second, wavelength at two levels: short (SWL)-485 nm (13500k) and long (LWL)-620 nm (4250k). Luminance and wavelength levels were measured and adjusted using a light metering device (AvaSpec-2048-FT-SDU; Avantes, Inc., Eerbeek, Netherlands). There were three dependent measures that were analyzed separately, sleep, melatonin secretion, and oral temperature. Each participant underwent all four experimental conditions in counterbalanced order.

Participants arrived at sleep laboratory at 21:00h on all experimental nights. The experiment room was about 12 m2 in size and included a desk with a 22-inch computer LED (Light Emitting Diode) screen (Model 226V4L, Philips, USA) and a bed. The screen was placed at a distance of about 60 cm from the participant and at eye level.

The room was dark and the room temperature was set to 22OC. Participants sat in front of the computer screen for two hours and performed onscreen tasks between 21:00h and 23:00h. Tasks were reading texts and answering related questions, writing exercises and solving verbal and arithmetic problems. Participants were not informed of the differing light conditions and were told that the purpose of the study is to examine the effect of the content of the tasks on sleep.

During exposure, the subjects were allowed to eat light food and drink (non-caffeinated beverages only). Participants were requested to go to the bathroom before testing and were not allowed leave the room for the duration of the testing. Following the light exposure, participants were connected to the sleep testing system by a skilled technician and requested to go to sleep. Bedtimes and wake times were based on the average sleep/wake time as indicated in the individual actigraphy reports. Oral temperature was taken at six time points, three on the testing night: 21:00h, 23:00h, and immediately prior to bedtime and at three the following morning, at 0, 60, and 120 minutes after awakening. Urine samples were collected at three time points: 21:00h, 23:00h, and immediately following morning awakening. This protocol was repeated for each of the four testing nights. Upon completion of the study protocol participants were given monetary compensation for their participation in the study.

Statistical analysis:

Two-way (wavelength X intensity) repeated measures (RM) ANOVAs were performed to evaluate mean value differences for all sleep parameters. Three-way (wavelength x intensity X time) RM ANOVAs were performed to evaluate mean value differences in melatonin and temperature indices. Post-hoc Tukey tests were performed for significant ANOVAs. Two-tailed p-values below 0.05 were considered significant. Statistical analyses were preformed using SPSS, version 20 (SPSS Inc., Chicago, IL, USA).

Study Design

Allocation: Randomized, Intervention Model: Factorial Assignment, Masking: Single Blind (Subject), Primary Purpose: Basic Science

Conditions

Sleep Disorder

Intervention

Wavelength, Intensity

Status

Completed

Source

Assuta Medical Center

Results (where available)

View Results

Links

Published on BioPortfolio: 2016-11-08T09:23:21-0500

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