JEMs and incompatible occupational coding systems: effect of manual and automatic recoding of job codes on exposure assignment.
BACKGROUND
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.


METHODS
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.


RESULTS
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.


CONCLUSIONS
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.
Institute for Risk Assessment Sciences, Environmental Epidemiology Division, Utrecht University, Jenalaan 18D, 3584 CK Utrecht, The Netherlands. t.koeman@uu.nl
Tom
T
Koeman
Nadine S M
NS
Offermans
Yvette
Y
Christopher-de Vries
Pauline
P
Slottje
Piet A
PA
Van Den Brandt
R Alexandra
RA
Goldbohm
Hans
H
Kromhout
Roel
R
Vermeulen
D000368:Aged; D001194:Asbestos / Q000009:adverse effects / Q000032:analysis; D002857:Chromium / Q000009:adverse effects / Q000032:analysis; D059019:Clinical Coding / Q000379:methods* / Q000706:statistics & numerical data; D015331:Cohort Studies; D001330:Electronic Data Processing / Q000379:methods* / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D060526:Magnetic Fields / Q000009:adverse effects; D008297:Male; D008875:Middle Aged; D009426:Netherlands / Q000453:epidemiology; D016273:Occupational Exposure / Q000706:statistics & numerical data*; D010575:Pesticides / Q000009:adverse effects / Q000032:analysis; D012189:Retrospective Studies; D012822:Silicon Dioxide / Q000009:adverse effects / Q000032:analysis; D012997:Solvents / Q000009:adverse effects / Q000032:analysis
D010575:Pesticides; D012997:Solvents; D002857:Chromium; D001194:Asbestos; D012822:Silicon Dioxide