A Quantitative General Population Job Exposure Matrix for Occupational Daytime Light Exposure

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  • Anne Vested
  • Vivi Schlünssen
  • Alex Burdorf, Erasmus Medical Centre, Rotterdam
  • ,
  • Johan H Andersen
  • Jens Christoffersen, VELUX A/S, VELUX Group, Knowledge centre for Daylight, Energy & Indoor Climate, Ådalsvej DK, Hørsholm, Denmark.
  • ,
  • Stine Daugaard
  • ,
  • Esben M Flachs, Department of Occupational and Environmental Medicine, Bispebjerg University Hospital, Bispebjerg Bakke 23, 2400 Copenhagen, NW, Denmark. Electronic address: puksc@me.com.
  • ,
  • Anne Helene Garde, Københavns Universitet
  • ,
  • Åse Marie Hansen, National Research Centre for the Working Environment, Lersø Parkallé 105, 2100 Copenhagen Ø, Denmark. hbn@nrcwe.dk., Københavns Universitet
  • ,
  • Jakob Markvart, Department of Energy Performance, Indoor Environment and Sustainability, Danish Building Research Institute, Aalborg University, A.C. Meyers Vænge, Copenhagen SV, Denmark.
  • ,
  • Susan Peters, Department of Neurology, University Medical Centre Utrecht, Heidelberglaan, CX Utrecht, the Netherlands.
  • ,
  • Zara Stokholm
  • Jesper M Vestergaard
  • Helene T Vistisen
  • Henrik Albert Kolstad

High daytime light levels may reduce the risk of affective disorders. Outdoor workers are during daytime exposed to much higher light intensities than indoor workers. A way to study daytime light exposure and disease on a large scale is by use of a general population job exposure matrix (JEM) combined with national employment and health data. The objective of this study was to develop a JEM applicable for epidemiological studies of exposure response between daytime light exposure, affective disorders, and other health effects by combining expert scores and light measurements. We measured light intensity during daytime work hours 06:00-17:59 for 1-7 days with Philips Actiwatch Spectrum® light recorders (Actiwatch) among 695 workers representing 71 different jobs. Jobs were coded into DISCO-88, the Danish version of the International Standard Classification of Occupations 1988. Daytime light measurements were collected all year round in Denmark (55-56°N). Arithmetic mean white light intensity (lux) was calculated for each hour of observation (n = 15,272), natural log-transformed, and used as the dependent variable in mixed effects linear regression models. Three experts rated probability and duration of outdoor work for all 372 jobs within DISCO-88. Their ratings were used to construct an expert score that was included together with month of the year and hour of the day as fixed effects in the model. Job, industry nested within job, and worker were included as random effects. The model estimated daytime light intensity levels specific for hour of the day and month of the year for all jobs with a DISCO-88 code in Denmark. The fixed effects explained 37% of the total variance: 83% of the between-jobs variance, 57% of the between industries nested in jobs variance, 43% of the between-workers variance, and 15% of the within-worker variance. Modeled daytime light intensity showed a monotonic increase with increasing expert score and a 30-fold ratio between the highest and lowest exposed jobs. Building construction laborers were based on the JEM estimates among the highest and medical equipment operators among the lowest exposed. This is the first quantitative JEM of daytime light exposure and will be used in epidemiological studies of affective disorders and other health effects potentially associated with light exposure.

TidsskriftAnnals of Work Exposures and Health
Sider (fra-til)666-678
Antal sider13
StatusUdgivet - jul. 2019

Bibliografisk note

© The Author(s) 2019. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

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