A Quantitative General Population Job Exposure Matrix for Occupational Daytime Light Exposure
A Quantitative General Population Job Exposure Matrix for Occupational Daytime Light Exposure
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DOI：
10.1093/annweh/wxz031
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发表时间：
2019-07-01
影响因子：
2.6
通讯作者：
Kolstad, Henrik Albert
中科院分区：
文献类型：
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作者：
Vested, Anne;Schlunssen, Vivi;Kolstad, Henrik Albert
白天的高光照水平可能会降低患情感障碍的风险。室外工作人员在白天接触的光照强度比室内工作人员高得多。大规模研究日间光暴露和疾病的一种方法是使用一般人群工作暴露矩阵 (JEM) 与国家就业和健康数据相结合。本研究的目的是通过结合专家评分和光测量，开发适用于日光暴露、情感障碍和其他健康影响之间的暴露反应的流行病学研究的 JEM。我们使用飞利浦 Actiwatch Spectrum (R) 光记录仪 (Actiwatch) 对代表 71 种不同工作的 695 名工人测量了白天工作时间 06:00-17:59 的光强度，持续 1-7 天。工作被编码到 DISCO-88，即 1988 年国际标准职业分类的丹麦版本。丹麦全年收集日间光测量值（北纬 55-56 度）。计算每个观察小时（n = 15,272）的算术平均白光强度（勒克斯），进行自然对数转换，并用作混合效应线性回归模型中的因变量。三位专家对 DISCO-88 中所有 372 种工作的户外工作概率和持续时间进行了评估。他们的评分用于构建专家评分，该评分与一年中的月份和一天中的小时一起作为固定效应包含在模型中。工作、工作中嵌套的行业以及工人都被作为随机效应包括在内。该模型针对丹麦使用 DISCO-88 代码的所有工作，估算了一天中特定时间和一年中特定月份的白天光强度水平。固定效应解释了总方差的 37%：83% 的工作间方差、57% 的嵌套在工作中的行业间方差、43% 的工人间方差和 15% 的工人内部方差。模拟的白天光强度显示出随着专家评分的增加而单调增加，最高和最低暴露工作之间的比率为 30 倍。根据正义与平等运动的估计，建筑工人的暴露程度最高，而医疗设备操作人员的暴露程度最低。这是第一个对日间光照射进行定量的 JEM，将用于情感障碍和其他可能与光照射相关的健康影响的流行病学研究。
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 (R) 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 degrees 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.