Koeman Tom, Offermans Nadine S M, Christopher-de Vries Yvette, Slottje Pauline, Van Den Brandt Piet A, Goldbohm R Alexandra, Kromhout Hans, Vermeulen Roel
Institute for Risk Assessment Sciences, Environmental Epidemiology Division, Utrecht University, Jenalaan 18D, 3584 CK Utrecht, The Netherlands.
Ann Occup Hyg. 2013 Jan;57(1):107-14. doi: 10.1093/annhyg/mes046. Epub 2012 Jul 17.
In epidemiological studies, occupational exposure estimates are often assigned through linkage of job histories to job-exposure matrices (JEMs). However, available JEMs may have a coding system incompatible with the coding system used to code the job histories, necessitating a translation of the originally assigned job codes. Since manual recoding is usually not feasible in large studies, this is often done by use of automated crosswalks translating job codes from one system to another. We set out to investigate whether automatically translating job codes led to different exposure estimates compared with those resulting from manual recoding using the original job descriptions.
One hundred job histories were randomly drawn from the Netherlands Cohort Study on diet and cancer (NLCS), using a sampling strategy designed to oversample potentially exposed jobs. This resulted in 220 job codes that were automatically translated from the original Dutch coding system to the International Standard Classification of Occupations (ISCO)-68 and ISCO-88 as well as manually recoded from the job descriptions in the original questionnaire by two coders. Exposure to several agents (i.e. chromium, asbestos, silica, pesticides, aromatic solvents, and extremely low-frequency magnetic fields) was assigned by JEMs based on job codes resulting from automatic and manual recodings.
The agreement between occupational exposure estimates based on the crosswalk versus those based on manual recoding reached a Cohen's Kappa (κ) of 0.66 or higher and were similar to the agreements between the two coders.
Results of this study indicate that using automated crosswalks to recode job codes from one occupational classification system to another results only in a limited loss in agreement in assigned occupational exposure estimates compared with direct manual recoding. Therefore, in this case, crosswalks provide an efficient alternative to the costly and time-consuming direct manual recoding from job history descriptions from questionnaires.
在流行病学研究中，职业暴露估计值通常通过将工作经历与工作暴露矩阵（JEM）相联系来确定。然而，现有的JEM可能具有与用于编码工作经历的编码系统不兼容的编码系统，因此需要对最初分配的工作代码进行转换。由于在大型研究中手动重新编码通常不可行，这通常通过使用自动编码对照表将工作代码从一个系统转换到另一个系统来完成。我们着手研究与使用原始工作描述进行手动重新编码相比，自动转换工作代码是否会导致不同的暴露估计值。
从荷兰饮食与癌症队列研究（NLCS）中随机抽取100份工作经历，采用旨在对潜在暴露工作进行过度抽样的抽样策略。这产生了220个工作代码，这些代码从原始荷兰编码系统自动转换为国际标准职业分类（ISCO）-68和ISCO-88，同时由两名编码人员根据原始问卷中的工作描述进行手动重新编码。基于自动和手动重新编码产生的工作代码，JEM分配了对几种物质（即铬、石棉、二氧化硅、农药、芳香族溶剂和极低频磁场）的暴露情况。
基于编码对照表的职业暴露估计值与基于手动重新编码的估计值之间的一致性达到科恩kappa（κ）系数为0.66或更高，并且与两名编码人员之间的一致性相似。
本研究结果表明，与直接手动重新编码相比，使用自动编码对照表将工作代码从一个职业分类系统重新编码到另一个系统只会导致在分配的职业暴露估计值方面的一致性有有限损失。因此，在这种情况下，编码对照表为从问卷中的工作经历描述进行昂贵且耗时的直接手动重新编码提供了一种有效的替代方法。
