TY - JOUR

T1 - A Quantitative General Population Job Exposure Matrix for Occupational Daytime Light Exposure

AU - Vedsted, Anne

AU - Schlünssen, Vivi

AU - Burdorf, Alex

AU - Andersen, Johan H

AU - Christoffersen, Jens

AU - Daugaard, Stine

AU - Flachs, Esben M.

AU - Garde, Anne Helene

AU - Hansen, Åse Marie

AU - Markvart, Jakob

AU - Peters, Susan

AU - Stokholm, Zara

AU - Vestergaard, Jesper M

AU - Vistisen, Helene T

AU - Kolstad, Henrik Albert

N1 - © The Author(s) 2019. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

U2 - 10.1093/annweh/wxz031

DO - 10.1093/annweh/wxz031

M3 - Journal article

C2 - 31050711

VL - 63

SP - 666

EP - 678

JO - Annals of Occupational Hygiene

JF - Annals of Occupational Hygiene

SN - 2398-7308

IS - 6

ER -