Jakob Markvart

Comparison and Correction of the Light Sensor Output from 48 Wearable Light Exposure Devices by Using a Side-by-Side Field Calibration Method

ABSTRACT Measurement of personal light exposures and activity has gained popularity in studies of the circadian rhythm and its effects on human health. Calibration of a batch of measuring devices may be needed, especially before initiating interventional studies, but manufactory calibration of devices before every initiated study is costly for the researcher and therefore often left out. Still, knowledge of inter-equipment variability is essential and seldom provided by the manufactory. The aim of the present study was to develop and test a method for field calibration of Actiwatch Spectrum devices. We tested 48 Actiwatch devices side by side under various light sources and present the red, green, blue, and white light response variability among the Actiwatches. The influence of different spatial and spectral light environments on the white light response when compared with the output from a calibrated photometer is discussed. In agreement with previous studies by Price and others [2012] and Figueiro and others [2013], we confirm the devices’ white light responses to be highly dependent on both the spatial and the spectral composition of the light. The white light response represents photopic illuminance only to a minor degree and light source-specific calibration may therefore be needed in some cases. Moreover, light responses were found to vary between devices by up to 60%. Implications are that the results of light effects on health issues in studies using Actiwatches are blurred by the equipment variability. To compensate for inter-equipment variability we stress the need for a field calibration procedure. When light exposure devices of lower grade quality are used in spectrally and spatially changing light environments, daylight from a diffused overcast sky is suggested to be used for side-by-side calibration of Actiwatches and similar personal light exposure devices. We suggest that the calibration methods presented can be used for calibration of other practical field devices, with respect to the various sensors already on the market and devices that will be introduced in the future.

Can sleep quality and wellbeing be improved by changing the indoor lighting in the homes of healthy, elderly citizens?

The study investigated the effect of bright blue-enriched versus blue-suppressed indoor light on sleep and wellbeing of healthy participants over 65 years. Twenty-nine participants in 20 private houses in a uniform settlement in Copenhagen were exposed to two light epochs of 3 weeks with blue-enriched (280 lux) and 3 weeks blue-suppressed (240 lux) indoor light or vice versa from 8 to 13 pm in a randomized cross-over design. The first light epoch was in October, the second in November and the two light epochs were separated by one week. Participants were examined at baseline and at the end of each light epoch. The experimental indoor light was well tolerated by the majority of the participants. Sleep duration was 7.44 (95% CI 7.14–7.74) hours during blue-enriched conditions and 7.31 (95% CI 7.01–7.62) hours during blue-suppressed conditions (p = 0.289). Neither rest hours, chromatic pupillometry, nor saliva melatonin profile showed significant changes between blue-enriched and blue-suppressed epochs. Baseline Pittsburgh Sleep Quality Index (PSQI) was significantly worse in females; 7.62 (95% CI 5.13–10.0) versus 4.06 (95% CI 2.64–5.49) in males, p = 0.009. For females, PSQI improved significantly during blue-enriched light exposure (p = 0.007); no significant changes were found for males. The subjective grading of indoor light quality doubled from participants habitual indoor light to the bright experimental light, while it was stable between light epochs, although there were clear differences between blue-enriched and blue-suppressed electrical light conditions imposed. Even though the study was carried out in the late autumn at northern latitude, the only significant difference in Actiwatch-measured total blue light exposure was from 8 to 9 am, because contributions from blue-enriched, bright indoor light were superseded by contributions from daylight.

Night work, light exposure and melatonin on work days and days off

ABSTRACT We aimed to examine the effects of night work on salivary melatonin concentration during and subsequent to night work and the mediating role of light. We included 254 day workers and 87 night workers who were followed during 322 work days and 301 days off work. Each day was defined as the 24 hour period starting from the beginning of a night shift or from waking in the mornings with day work and days off. Light levels were recorded and synchronized with diary information (start and end of sleep and work). On average, participants provided four saliva samples per day, and these were analyzed for melatonin concentration by liquid chromatography tandem mass spectrometry (LC-MS/MS). Differences between day and night workers on work days and days off were assessed with multilevel regression models with melatonin concentration as the primary outcome. All models were stratified or adjusted by time of day. For light exposure, we estimated the total, direct and indirect effects of night work on melatonin concentrations obtaining 95% confidence intervals through bootstrapping. On work days, night workers showed 15% lower salivary melatonin concentrations compared with day workers (−15.0%; 95% CI: −31.4%; 5.2%). During the night, light exposure mediated a melatonin suppression of approximately 6% (−5.9%, 95% CI: −10.2%; −1.5%). No mediating effect of light was seen during the day time. On days off, we observed no difference in melatonin concentrations between day and night workers. These findings are in accordance with a transient and partly light-mediated effect of night work on melatonin production.

Erratum to: Can dynamic light improve melatonin production and quality of sleep?

Unfortunately, the original version of this article [1] contained an error. The author’s names and affiliations have not been included correctly. The correct names and affiliations are: HI Jensen1,2*, TD Thomsen1, JW Larsen1 and J Markvart3 * Corresponding author: Hanne Irene Jensen, Hanne.Irene.Jensen@rsyd.dk 1 Kolding Hospital, part of Lillebaelt Hospital, Kolding, Denmark 2 Institute of Regional Health Research, University of Southern Denmark 3 Danish Building Research Institute/Aalborg University, Copenhagen, Denmark