Objectives Professional judgment is necessary to assess occupational exposure in population-based case–control studies; however, the assessments lack transparency and are time-consuming to perform. To improve transparency and efficiency, we systematically applied decision rules to questionnaire responses to assess diesel exhaust exposure in the population-based case–control New England Bladder Cancer Study.
Methods 2631 participants reported 14 983 jobs; 2749 jobs were administered questionnaires (‘modules’) with diesel-relevant questions. We applied decision rules to assign exposure metrics based either on the occupational history (OH) responses (OH estimates) or on the module responses (module estimates); we then combined the separate OH and module estimates (OH/module estimates). Each job was also reviewed individually to assign exposure (one-by-one review estimates). We evaluated the agreement between the OH, OH/module and one-by-one review estimates.
Results The proportion of exposed jobs was 20–25% for all jobs, depending on approach, and 54–60% for jobs with diesel-relevant modules. The OH/module and one-by-one review estimates had moderately high agreement for all jobs (κw=0.68–0.81) and for jobs with diesel-relevant modules (κw=0.62–0.78) for the probability, intensity and frequency metrics. For exposed subjects, the Spearman correlation statistic was 0.72 between the cumulative OH/module and one-by-one review estimates.
Conclusions The agreement seen here may represent an upper level of agreement because the algorithm and one-by-one review estimates were not fully independent. This study shows that applying decision-based rules can reproduce a one-by-one review, increase transparency and efficiency, and provide a mechanism to replicate exposure decisions in other studies.
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